{
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   "cell_type": "markdown",
   "id": "7457ec4c",
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   "source": [
    ">> ON THE MUTATION-MAX MYSTERIOUS RELATION\n",
    ">>>>\n",
    ">>> José Rodríguez\n",
    ">>>>\n",
    ">>> jose@ejristos.com\n",
    ">>>>\n",
    ">>> 28 February 2026.\n",
    ">>>>\n",
    ">>> Bogotá, Colombia.\n",
    "\n",
    "**Abstract.**\n",
    "\n",
    "Our problem is to match the binary string 111...1. To that aim, we use a Genetic Algorithm (an abstraction of Evolution), which is composed of mutation, MAX (which an abstraction of the selection of the fittest), and cloning of the fittest to create the next generation. Random mutation can touch a site and posit a one or a zero with equal probability.  The mutation rate is not a deterministic parameter but a probability. That is why the actual number of posited ones is not equal in all chromosomes. A fluctuation is any deviation from its expected value. The best or the fittest is picked up by MAX and cloned. Is in that way the Evolution gathers small improvement generation after generation. Our aim for this contribution is to convert this intuitive discourse into a mathematical formulation that must fit the results of our simulations. We failed in the previous work, but we give us here a new try.  Our plan is to be more natural and rigorous with the application of MAX. If we succeed, we can decide whether the considered form of Evolution solves the MAX-Rocket challenge, which consists in skyrocketing the capabilities of MAX to battle complexity. "
   ]
  },
  {
   "cell_type": "markdown",
   "id": "68490b73",
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   "source": [
    "\n",
    "# INTRODUCTION\n",
    "\n",
    "We are studying the capabilities of the MUTATION + MAX-DUO to battle complexity, which is incarnated in our works as the Shakespeare Challenge, which consists in partially match a binary string.\n",
    "\n",
    "We already know that our duo works, and that, when compared to randomness, the duo is a rocket and randomness an ameba. \n",
    "\n",
    "Nevertheless, the battle against complexity is fierce. Think of a rocket for intergalactic missions. In fact, we gave up with perfection in our simulations to get conformed with 80\\% of the posed task. We called this scheme truncated Evolution.\n",
    "\n",
    "\n",
    "The power of the Mutation-MAX duo resides in its fuel, which consists of fluctuations caused by mutation and profited by MAX. A fluctuation is a departure from the expected or average value.  This is our credo, and our purpose for this contribution is to test it. \n",
    "\n",
    "We need mathematical models to predict the behavior of our simulations. If we succeed, we can make trustable extrapolations that must answer whether our Duo solves the MAX-rocket challenge. This consists in tailoring a machinery that includes MAX to skyrocket its capabilities to battle complexity.\n",
    "\n",
    "Let us review an important point.\n",
    "\n",
    "# THE WAR OF THE MUTATION-MAX DUO\n",
    "\n",
    "How do we put our duo and complexity in the same ring that they could fight one against the other?\n",
    "\n",
    "The Shakespeare Challenge is our version of complexity, which consists in matching a binary string, say, up to 80\\%. We truncate the target fitness, which is the number of required matched sites, but not the string. The Duo must try to solve this challenge, first for easy or short strings, next for more complex and so on until we declare that our time is expired. Let us see a nice detail in this regard.\n",
    "\n",
    "## The duo is super-magic\n",
    "\n",
    "Our duo is composed of mutation, to create variability, and MAX, to choose the best that is next cloned to create the next generation. Let us compare the performance of the duo with that of magic mutation. This is a special type of mutation that solves every touched site. The task for both actors is to match the binary string 111...1. \n",
    " \n",
    "According to our [previous work](https://drive.google.com/file/d/1j33fwHMIW6eLN34Q1cLekOpL2DtWc1HS/view?usp=sharing), magic mutation is described by the difference equation\n",
    "\n",
    "\n",
    "$\\Delta M_t = M_{t+1} - M_t = \\mu ( H -M_t)$ \n",
    "\n",
    "or\n",
    "\n",
    "$M_{t+1}  =  M_t +  \\mu ( H -M_t)$ \n",
    "\n",
    "\n",
    "where $M_t$ is the number of matched sites at generation $t$. This equation says that if a task is incomplete, the degree of incompleteness is the fuel to pursue perfection. The duo is implemented as a simulation. In it, the variable $M_t$ is called `best_fitness`. The code to compare the best fitness with the value of $M_t$ predicted by the magic mutation is the following. "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "a98d0aef",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Lab: Simple Genetic Algorithm\n",
      "Purpose: solve an instance of the Shakespeare challenge\n",
      "Date of Experiment  = 2026-02-25 14:12:19.384240\n",
      "alphabet =  01\n",
      "target_sequence = 11111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111\n",
      "length_of_target_sequence = 800\n",
      "population_size = 200\n",
      "include_clone_populationf1 = True\n",
      "include_mutate_allf1 = True\n",
      "include_crossover_allf1 = False\n",
      "mutation_rate = 0.01\n",
      "print_best_fitness = False\n",
      "\n",
      "Target sequence matched in generation 390\n",
      "Final chromosome: 11111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111\n",
      "Total cost = population size * number of generations: 78000\n"
     ]
    },
    {
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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "## Program DuoMutationMax_VS_Magic_Mutation.py\n",
    "## Magic mutation solves every touched site.\n",
    "## It is like king Midas, who turned everything he touched into gold.\n",
    "## This program compares observed best fitness in the simulation \n",
    "# with the predicted number of solved sites \n",
    "# according to the Magic Mutation model, \n",
    "# M_t = M_{t-1} + mutation_rate * (length_of_target_sequence - M_{t-1})\n",
    "# Magic mutation model is a simple mathematical model that \n",
    "# predicts the number of solved sites (M_t) \n",
    "# in a genetic algorithm over generations, \n",
    "# based on the mutation rate and the length of the target sequence.\n",
    "# The program runs a simple genetic algorithm to evolve a population of binary strings towards a target binary string of 800 bits, all set to 1.\n",
    "# The program also plots the best fitness and M_t over generations.\n",
    "# In this program, the target sequence is a binary string of 800 bits, all set to 1.\n",
    "\n",
    "import datetime\n",
    "import random\n",
    "import matplotlib.pyplot as plt # Import matplotlib for plotting\n",
    "# target_sequence = 'Methinks it is like a weasel.'\n",
    "# alphabet = 'abcdefghijklmnopqrstuvwxyzABCDEFGHIJKLMNOPQRSTUVWXYZ .,'\n",
    "alphabet = '01' # Binary alphabet, binary strings\n",
    "length_of_target_sequence = 800\n",
    "target_sequence = '1'*length_of_target_sequence  #1111...1 (800 ones)\n",
    "population_size = 200\n",
    "include_clone_populationf1 = True\n",
    "include_mutate_allf1 = True\n",
    "include_crossover_allf1 = False\n",
    "# Default parameter for the genetic algorithm.\n",
    "# mutation_rate = 0.01 # Mutation rate of 1% means that \n",
    "# each site has a 1% chance of being mutated in each generation.\n",
    "mutation_rate = 0.01\n",
    "recombination_rate = 0\n",
    "# alphabet = 'abcdefghijklmnopqrstuvwxyzABCDEFGHIJKLMNOPQRSTUVWXYZ .,'\n",
    "# Boolean flag to print the generation, best chromosome and fitness.\n",
    "# This is the ancestral line of the solution.\n",
    "print_best_fitness = False\n",
    "show_graph = True\n",
    "\n",
    "\n",
    "def print_parametersf1():\n",
    "    print(f\"Lab: Simple Genetic Algorithm\")\n",
    "    print(f\"Purpose: solve an instance of the Shakespeare challenge\")\n",
    "    print(f\"Date of Experiment  = {datetime.datetime.now()}\")\n",
    "    print(f\"alphabet =  {alphabet}\")\n",
    "    print(f\"target_sequence = {target_sequence}\")\n",
    "    print(f\"length_of_target_sequence = {length_of_target_sequence}\")\n",
    "    print(f\"population_size = {population_size}\")\n",
    "    print(f\"include_clone_populationf1 = {include_clone_populationf1}\")\n",
    "    print(f\"include_mutate_allf1 = {include_mutate_allf1}\")\n",
    "    print(f\"include_crossover_allf1 = {include_crossover_allf1}\")\n",
    "    if include_mutate_allf1:\n",
    "        print(f\"mutation_rate = {mutation_rate}\")\n",
    "    if include_crossover_allf1:\n",
    "        print(f\"recombination_rate = {recombination_rate}\")\n",
    "    if include_clone_populationf1:\n",
    "        print(f\"print_best_fitness = {print_best_fitness}\")\n",
    "\n",
    "\n",
    "def create_populationf1(population_size, target_sequence, alphabet):\n",
    "    \"\"\"Creates a new population with random chromosomes.\"\"\"\n",
    "    # print(\"create_population8(population_size, target_sequence, alphabet)\")\n",
    "    population = []\n",
    "    for _ in range(population_size):\n",
    "        random_string = ''.join(random.choice(alphabet) for _ in range(len(target_sequence)))\n",
    "        population.append(random_string)\n",
    "    # print(\"initial population\")\n",
    "    # print(population)\n",
    "    return population\n",
    "\n",
    "def calculate_fitnessf1(chromosome, target_sequence):\n",
    "    \"\"\"Calculates the fitness of a chromosome based on its similarity to the target sequence.\"\"\"\n",
    "    #  print(\"\\n *calculate_fitness8(chromosome, target_sequence)\")\n",
    "    fitness = 0\n",
    "    for i in range(len(chromosome)):\n",
    "        if chromosome[i] == target_sequence[i]:\n",
    "            fitness += 1\n",
    "    # print(chromosome, \"  fitness: \", fitness)\n",
    "    return fitness\n",
    "\n",
    "def calculate_all_fitnessf1(population, target_sequence):\n",
    "    # print(\"\\n*calculate_all_fitness8(population, target_sequence)\")\n",
    "    \"\"\"Calculates the fitness of all chromosomes in the population.\"\"\"\n",
    "    fitness_scores = [calculate_fitnessf1(chromosome, target_sequence) for chromosome in population]\n",
    "    # print(\"fitness_scores: \", fitness_scores)\n",
    "    return fitness_scores\n",
    "\n",
    "def select_the_bestf1(population, target_sequence):\n",
    "    \"\"\"Selects the best chromosome for reproduction.\"\"\"\n",
    "    fitness_scores = calculate_all_fitnessf1(population, target_sequence)\n",
    "    best_fitness = max(fitness_scores)\n",
    "    best_chromosome_index = fitness_scores.index(best_fitness)\n",
    "    best_chromosome = population[best_chromosome_index]\n",
    "    # print(\"\\n*select_the_bestf1(population)\")\n",
    "    # print(\"best_fitness = \", best_fitness)\n",
    "    # print(\"The chro = \", best_chromosome )\n",
    "    return best_fitness, best_chromosome\n",
    "\n",
    "def clone_populationf1(best_chromosome, population_size):\n",
    "    \"\"\"Creates a new population by cloning the best chromosome.\"\"\"\n",
    "    return [best_chromosome] * population_size\n",
    "\n",
    "\n",
    "def mutatef1(chromosome, mutation_rate, alphabet):\n",
    "    \"\"\"Mutates a chromosome.\"\"\"\n",
    "    mutated_chromosome_list = list(chromosome)\n",
    "    for i in range(len(mutated_chromosome_list)):\n",
    "        if random.random() < mutation_rate:\n",
    "                mutated_chromosome_list[i] = random.choice(alphabet)\n",
    "    return \"\".join(mutated_chromosome_list)\n",
    "\n",
    "def mutate_allf1(population, mutation_rate, alphabet):\n",
    "    \"\"\"Mutates all chromosomes in the population.\"\"\"\n",
    "    mutated_population = []\n",
    "    for chromosome in population:\n",
    "        mutated_chromosome = mutatef1(chromosome, mutation_rate, alphabet)\n",
    "        mutated_population.append(mutated_chromosome)\n",
    "    return mutated_population\n",
    "\n",
    "def crossoverf1(parent1, parent2, target_sequence, recombination_rate):\n",
    "    \"\"\"Performs crossover between two parent chromosomes.\"\"\"\n",
    "    if random.random() < recombination_rate:\n",
    "        crossover_point = random.randint(0, len(target_sequence))\n",
    "        return parent1[:crossover_point] + parent2[crossover_point:]\n",
    "    else:\n",
    "        return parent1\n",
    "\n",
    "def crossover_allf1(population, target_sequence, recombination_rate):\n",
    "    \"\"\"Performs crossover on all chromosomes in the population.\"\"\"\n",
    "    recombinant_population = []\n",
    "    for i in range(len(population)):\n",
    "        parent1 =  population[i]\n",
    "        parent2 = random.choice(population)\n",
    "        child = crossoverf1(parent1, parent2, target_sequence, recombination_rate)\n",
    "        recombinant_population.append(child)\n",
    "    return recombinant_population\n",
    "\n",
    "\n",
    "\n",
    "def run_one_generationf1(population, target_sequence, mutation_rate, recombination_rate, alphabet):\n",
    "    \"\"\"Runs one generation of the genetic algorithm.\"\"\"\n",
    "    # Calculate fitness scores for the current population\n",
    "    best_fitness, best_chromosome  = select_the_bestf1(population, target_sequence)\n",
    "    # print(f\" best_chromosome {best_chromosome}, best_fitness {best_fitness}\")\n",
    "    # Clone the best to build the new population\n",
    "    new_population = []\n",
    "    if include_clone_populationf1:\n",
    "        new_population = clone_populationf1(best_chromosome, population_size)\n",
    "    if include_mutate_allf1:\n",
    "        new_population = mutate_allf1(new_population, mutation_rate, alphabet)\n",
    "    if include_crossover_allf1:\n",
    "        new_population = crossover_allf1(new_population, target_sequence, recombination_rate)\n",
    "    return best_fitness, best_chromosome, new_population\n",
    "\n",
    "\n",
    "\n",
    "def plot_Best_Fitnessf1(best_fitness_history, M_t_history):\n",
    "    # Plot the fitness history\n",
    "    plt.plot(best_fitness_history, label='Best Fitness in simulation', color='blue')\n",
    "    plt.plot(M_t_history, label='M_t (Magic Mutation)', color='orange')\n",
    "    plt.axhline(y=length_of_target_sequence, color='red', linestyle='--', linewidth=2)\n",
    "    plt.xlabel('Generation')\n",
    "    plt.ylabel('Best Fitness')  \n",
    "    plt.title('Genetic Algorithm - Fitness over Generations')\n",
    "    plt.grid(True)\n",
    "    plt.legend()\n",
    "    plt.show()\n",
    "\n",
    "\n",
    "def mainf1( target_sequence, mutation_rate, recombination_rate, alphabet):\n",
    "    print_parametersf1()\n",
    "    population = create_populationf1(population_size, target_sequence, alphabet)\n",
    "    # print(population)\n",
    "    best_fitness, best_chromosome = select_the_bestf1(population, target_sequence)\n",
    "    generation = 0\n",
    "    best_fitness_history = [] # List to store best fitness of each generation\n",
    "    M_t = best_fitness # Initial number of solved sites according to simulation results, M_t starts at the best fitness of the initial population\n",
    "    M_t_history = [] \n",
    "    best_fitness_history.append(best_fitness)\n",
    "    M_t_history.append(M_t)# List to store M_t of each generation\n",
    "    if print_best_fitness:\n",
    "        print(\"Generation, best_chromosome and best_fitness, M_t\")\n",
    "    while best_fitness < len(target_sequence):\n",
    "        generation += 1\n",
    "        best_fitness, best_chromosome, population = run_one_generationf1(population, target_sequence, mutation_rate, recombination_rate, alphabet)\n",
    "        M_t = M_t + mutation_rate * (len(target_sequence) - M_t)\n",
    "        \n",
    "        if print_best_fitness:\n",
    "            print(f\" {generation}  {best_chromosome} {best_fitness} {M_t}\")\n",
    "        best_fitness_history.append(best_fitness)\n",
    "        M_t_history.append(M_t)\n",
    "    print(f\"\\nTarget sequence matched in generation {generation}\")\n",
    "    print(f\"Final chromosome: {best_chromosome}\")\n",
    "    totalCost = population_size * generation\n",
    "    print(f\"Total cost = population size * number of generations: {totalCost}\")\n",
    "    if show_graph:\n",
    "        plot_Best_Fitnessf1(best_fitness_history, M_t_history)\n",
    "\n",
    "if __name__ == \"__main__\":    mainf1( target_sequence, mutation_rate, recombination_rate, alphabet)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "cb2ec3b5",
   "metadata": {},
   "source": [
    "\n",
    "**Exercise.** Run the previous program and explain why the result is mysterious. Would you explain that mystery?\n",
    ">\n",
    "> *Answer.* The graphic shows that the Mutation-Max_Duo is more efficient than magic mutation. This is a mystery because magic mutation is the top of what mutation can do, and hence it is also an upper bound for the performance of the duo. \n",
    "> \n",
    "> The solution to the mystery is the following: magic mutation is calculated for an isolated chromosome. But the simulation studies a population from which the max for each generation is taken and cloned to form the next generation. Thus, it is clear that there must be an ensemble property that makes the whole population stronger than a single individual. According to the MAX theory that we are developing, the ensemble property is created by the fluctuations due to the mutation, which are deviations off the expected or mean value, from which MAX picks up the maximal value.\n",
    "\n",
    "\n",
    "\n",
    "**Example.** The next code, a slight modification of a previous work, shows how the duo solves the Shakespeare challenge for string of length $n$. We vary $n$ across a set with instances of increasing complexity. \n",
    "\n",
    "\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "56feb34f",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Lab: Cost of truncated Evolution\n",
      "Purpose: estimation of the cost to solve the Truncated Shakespeare challenge\n",
      "Date of Experiment  = 2026-02-13 08:26:40.814599\n",
      "number_of_points = 3\n",
      "step_size = 500\n",
      "alphabet =  01\n",
      "percentageOfTask = 0.8\n",
      "population_size = 200\n",
      "include_clone_populationf2 = True\n",
      "include_mutate_allf2 = True\n",
      "include_crossover_allf2 = False\n",
      "mutation_rate = 0.01\n",
      "print_best_fitness = False\n",
      "Total cost = population size * number of generations\n",
      "Length of target sequence, Total cost, employed time\n",
      "500    7600 0:00:00.621285\n",
      "1000    12400 0:00:02.327342\n",
      "1500    18400 0:00:04.447922\n",
      "[500, 1000, 1500]\n",
      "[7600, 12400, 18400]\n"
     ]
    },
    {
     "data": {
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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1000x600 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1000x600 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Linear Regression Equation (Cost vs Length): y = 10.80x + 2000.00\n",
      "Linear Regression Equation (Log(Cost) vs Length): log(y) = 0.0009x + 8.5096\n"
     ]
    }
   ],
   "source": [
    "# Program  CostOfTruncatedEvolution.py\n",
    "# This program estimates the cost of Evolution\n",
    "# to solve\n",
    "# the Evolutionary Truncated Shakespeare Challenge,\n",
    "# which consists in matching a percentage of a given string.\n",
    "# The cost is given as a function on\n",
    "# the length of the target sequence.\n",
    "\n",
    "from datetime import datetime, timedelta\n",
    "import time\n",
    "import random\n",
    "import math\n",
    "import numpy as np\n",
    "import matplotlib.pyplot as plt # Import matplotlib for plotting\n",
    "import datetime\n",
    "import time\n",
    "\n",
    "start_time = time.time() # Record the start time\n",
    "\n",
    "# Number of points in the graph\n",
    "#number_of_points = 3\n",
    "#startPoint = 1\n",
    "# step size for length of target sequence\n",
    "#step_size = 50\n",
    "#percentageOfTask = 0.95\n",
    "\n",
    "## Redefinition of parameters for easier testing and debugging\n",
    "# \n",
    "# Redefinition1 : n = 1..200\n",
    "# number_of_points = 200\n",
    "# startPoint = 1\n",
    "# step_size = 1\n",
    "# percentageOfTask = 0.80\n",
    "\n",
    "# Redefinition2 : n = 200..500\n",
    "#number_of_points = 25\n",
    "#startPoint = 4\n",
    "#step_size = 20\n",
    "#percentageOfTask = 0.80\n",
    "\n",
    "# Redefinition3: n = 500..5000  \n",
    "number_of_points = 3\n",
    "startPoint = 1\n",
    "step_size = 500\n",
    "percentageOfTask = 0.80\n",
    "\n",
    "alphabet = '01'\n",
    "population_size = 200\n",
    "# Include cloning of the fittest\n",
    "include_clone_populationf2 = True\n",
    "# Include mutation\n",
    "include_mutate_allf2 = True\n",
    "# Include recombination\n",
    "include_crossover_allf2 = False\n",
    "mutation_rate = 0.01\n",
    "recombination_rate = 0.01\n",
    "# Boolean flag to print the generation, best chromosome and fitness.\n",
    "# This is the ancestral line of the solution.\n",
    "print_best_fitness = False\n",
    "print_parameters = True\n",
    "show_graph = True\n",
    "\n",
    "\n",
    "\n",
    "\n",
    "    \n",
    "\n",
    "def print_parametersf2():\n",
    "    print(f\"Lab: Cost of truncated Evolution\")\n",
    "    print(f\"Purpose: estimation of the cost to solve the Truncated Shakespeare challenge\")\n",
    "    print(f\"Date of Experiment  = {datetime.datetime.now()}\")\n",
    "    print(f\"number_of_points = {number_of_points}\")\n",
    "    print(f\"step_size = {step_size}\")\n",
    "    print(f\"alphabet =  {alphabet}\")\n",
    "    # print(f\"target_sequence = {target_sequence}\")\n",
    "    # print(f\"length_of_target_sequence = {length_of_target_sequence}\")\n",
    "    print(f\"percentageOfTask = {percentageOfTask}\")\n",
    "    print(f\"population_size = {population_size}\")\n",
    "    print(f\"include_clone_populationf2 = {include_clone_populationf2}\")\n",
    "    print(f\"include_mutate_allf2 = {include_mutate_allf2}\")\n",
    "    print(f\"include_crossover_allf2 = {include_crossover_allf2}\")\n",
    "    if include_mutate_allf2:\n",
    "        print(f\"mutation_rate = {mutation_rate}\")\n",
    "    if include_crossover_allf2:\n",
    "        print(f\"recombination_rate = {recombination_rate}\")\n",
    "    if include_clone_populationf2:\n",
    "        print(f\"print_best_fitness = {print_best_fitness}\")\n",
    "\n",
    "\n",
    "def create_populationf2(population_size, target_sequence, alphabet):\n",
    "    \"\"\"Creates a new population with random chromosomes.\"\"\"\n",
    "    # print(\"create_populationf2(population_size, target_sequence, alphabet)\")\n",
    "    population = []\n",
    "    for _ in range(population_size):\n",
    "        random_string = ''.join(random.choice(alphabet) for _ in range(len(target_sequence)))\n",
    "        population.append(random_string)\n",
    "    # print(\"initial population\")\n",
    "    # print(population)\n",
    "    return population\n",
    "\n",
    "def calculate_fitnessf2(chromosome, target_sequence):\n",
    "    \"\"\"Calculates the fitness of a chromosome based on its similarity to the target sequence.\"\"\"\n",
    "    #  print(\"\\n *calculate_fitnessf2(chromosome, target_sequence)\")\n",
    "    fitness = 0\n",
    "    for i in range(len(chromosome)):\n",
    "        if chromosome[i] == target_sequence[i]:\n",
    "            fitness += 1\n",
    "    # print(chromosome, \"  fitness: \", fitness)\n",
    "    return fitness\n",
    "\n",
    "def calculate_all_fitnessf2(population, target_sequence):\n",
    "    # print(\"\\n*calculate_all_fitnessf2(population, target_sequence)\")\n",
    "    \"\"\"Calculates the fitness of all chromosomes in the population.\"\"\"\n",
    "    fitness_scores = [calculate_fitnessf2(chromosome, target_sequence) for chromosome in population]\n",
    "    # print(\"fitness_scores: \", fitness_scores)\n",
    "    return fitness_scores\n",
    "\n",
    "def select_the_bestf2(population, target_sequence):\n",
    "    \"\"\"Selects the best chromosome for reproduction.\"\"\"\n",
    "    fitness_scores = calculate_all_fitnessf2(population, target_sequence)\n",
    "    best_fitness = max(fitness_scores)\n",
    "    best_chromosome_index = fitness_scores.index(best_fitness)\n",
    "    best_chromosome = population[best_chromosome_index]\n",
    "    # print(\"\\n*select_the_bestf2(population)\")\n",
    "    # print(\"best_fitness = \", best_fitness)\n",
    "    # print(\"The chro = \", best_chromosome )\n",
    "    return best_fitness, best_chromosome\n",
    "\n",
    "def clone_populationf2(best_chromosome, population_size):\n",
    "    \"\"\"Creates a new population by cloning the best chromosome.\"\"\"\n",
    "    return [best_chromosome] * population_size\n",
    "\n",
    "\n",
    "def mutatef2(chromosome, mutation_rate, alphabet):\n",
    "    \"\"\"Mutates a chromosome.\"\"\"\n",
    "    mutated_chromosome_list = list(chromosome)\n",
    "    for i in range(len(mutated_chromosome_list)):\n",
    "        if random.random() < mutation_rate:\n",
    "                mutated_chromosome_list[i] = random.choice(alphabet)\n",
    "    return \"\".join(mutated_chromosome_list)\n",
    "\n",
    "def mutate_allf2(population, mutation_rate, alphabet):\n",
    "    \"\"\"Mutates all chromosomes in the population.\"\"\"\n",
    "    mutated_population = []\n",
    "    for chromosome in population:\n",
    "        mutated_chromosome = mutatef2(chromosome, mutation_rate, alphabet)\n",
    "        mutated_population.append(mutated_chromosome)\n",
    "    return mutated_population\n",
    "\n",
    "def crossoverf2(parent1, parent2, target_sequence, recombination_rate):\n",
    "    \"\"\"Performs crossover between two parent chromosomes.\"\"\"\n",
    "    if random.random() < recombination_rate:\n",
    "        crossover_point = random.randint(0, len(target_sequence))\n",
    "        return parent1[:crossover_point] + parent2[crossover_point:]\n",
    "    else:\n",
    "        return parent1\n",
    "\n",
    "def crossover_allf2(population, target_sequence, recombination_rate):\n",
    "    \"\"\"Performs crossover on all chromosomes in the population.\"\"\"\n",
    "    recombinant_population = []\n",
    "    for i in range(len(population)):\n",
    "        parent1 =  population[i]\n",
    "        parent2 = random.choice(population)\n",
    "        child = crossoverf2(parent1, parent2, target_sequence, recombination_rate)\n",
    "        recombinant_population.append(child)\n",
    "    return recombinant_population\n",
    "\n",
    "\n",
    "\n",
    "def run_one_generationf2(population, target_sequence, mutation_rate, recombination_rate, alphabet):\n",
    "    \"\"\"Runs one generation of the genetic algorithm.\"\"\"\n",
    "    # Calculate fitness scores for the current population\n",
    "    best_fitness, best_chromosome  = select_the_bestf2(population, target_sequence)\n",
    "    # print(f\" best_chromosome {best_chromosome}, best_fitness {best_fitness}\")\n",
    "    # Clone the best to build the new population\n",
    "    new_population = []\n",
    "    if include_clone_populationf2:\n",
    "        new_population = clone_populationf2(best_chromosome, population_size)\n",
    "    if include_mutate_allf2:\n",
    "        new_population = mutate_allf2(new_population, mutation_rate, alphabet)\n",
    "    if include_crossover_allf2:\n",
    "        new_population = crossover_allf2(new_population, target_sequence, recombination_rate)\n",
    "    return best_fitness, best_chromosome, new_population\n",
    "\n",
    "\n",
    "\n",
    "def plot_functionf2(best_fitness_history, xlabel, ylabel, title):\n",
    "    # Plot the fitness history\n",
    "    plt.plot(best_fitness_history)\n",
    "    plt.xlabel(xlabel)\n",
    "    plt.ylabel(ylabel)\n",
    "    plt.title(title)\n",
    "    plt.grid(True)\n",
    "    plt.show()\n",
    "\n",
    "\n",
    "def truncated_taskf2( target_sequence, mutation_rate, recombination_rate, alphabet, percentageOfTask):\n",
    "    \n",
    "    population = create_populationf2(population_size, target_sequence, alphabet)\n",
    "    # print(population)\n",
    "    generation = 0\n",
    "    best_chromosome = ''\n",
    "    best_fitness = 0\n",
    "    start_time = time.time()\n",
    "    best_fitness_history = [] # List to store best fitness of each generation\n",
    "    if print_best_fitness:\n",
    "        print(\"Generation, best_chromosome and best_fitness\")\n",
    "    while best_fitness < percentageOfTask * len(target_sequence):\n",
    "        generation += 1\n",
    "        best_fitness, best_chromosome, population = run_one_generationf2(population, target_sequence, mutation_rate, recombination_rate, alphabet)\n",
    "        if print_best_fitness:\n",
    "            print(f\" {generation}  {best_chromosome} {best_fitness}\")\n",
    "        best_fitness_history.append(best_fitness)\n",
    "    # print(f\"\\nTarget sequence matched in generation {generation}\")\n",
    "    # print(f\"Final chromosome: {best_chromosome}\")\n",
    "    totalCost = population_size * generation\n",
    "    \n",
    "    end_time = time.time()\n",
    "    # Calculate the difference in seconds\n",
    "    elapsed_seconds = end_time - start_time\n",
    "    start_time = end_time # Reset start time for the next run\n",
    "    # Create a timedelta object\n",
    "    # The default output includes days if applicable, and microseconds\n",
    "    elapsed_time = timedelta(seconds=elapsed_seconds)\n",
    "    print(f\"{len(target_sequence)}    {totalCost} {elapsed_time}\")\n",
    "    \n",
    "    \n",
    "    return len(target_sequence), totalCost\n",
    "\n",
    "def main():\n",
    "    print_parametersf2()\n",
    "    print_parameters = False\n",
    "    xArray = []\n",
    "    yArray = []\n",
    "    print(\"Total cost = population size * number of generations\")\n",
    "    print(f\"Length of target sequence, Total cost, employed time\")\n",
    "    for i in range(startPoint, number_of_points + 1):\n",
    "        target_sequence = '1'*step_size * i\n",
    "        x, y = truncated_taskf2(target_sequence, mutation_rate, recombination_rate, alphabet, percentageOfTask)\n",
    "        xArray.append(x)\n",
    "        yArray.append(y)\n",
    "    print(xArray)\n",
    "    print(yArray)\n",
    "\n",
    "\n",
    "    fig, ax = plt.subplots()\n",
    "    truncation = 0.8\n",
    "    t = str(truncation)\n",
    "    ax.plot(xArray, yArray, linewidth=2, label=r\"Truncation percentage = \" + t)\n",
    "    ax.set( xlabel=\"Length of target sequence\")\n",
    "    ax.legend(fontsize=14)\n",
    "    ax.set_ylabel('Cost')\n",
    "    ax.set_title('Cost of Truncated Evolution vs Length of target sequence')\n",
    "    plt.show()\n",
    "\n",
    "\n",
    "    # Perform linear regression\n",
    "    # Fit a polynomial of degree 1 (linear)\n",
    "    slope, intercept = np.polyfit(xArray, yArray, 1)\n",
    "\n",
    "    # Create the regression line\n",
    "    regression_line = slope * np.array(xArray) + intercept\n",
    "\n",
    "    # Plot the original data and the regression line\n",
    "    plt.figure(figsize=(10, 6))\n",
    "    plt.scatter(xArray, yArray, label='Observed Data')\n",
    "    plt.plot(xArray, regression_line, color='red', label=f'Linear Regression: y = {slope:.2f}x + {intercept:.2f}')\n",
    "    plt.xlabel('Length of Target Sequence')\n",
    "    plt.ylabel('Total Cost (Number of Chromosomes)')\n",
    "    plt.title('Linear Regression of Truncated Evolution Cost vs. Target Sequence Length')\n",
    "    plt.legend()\n",
    "    plt.grid(True)\n",
    "    plt.show()\n",
    "\n",
    "    # Also perform linear regression on the log of yArray\n",
    "    log_y_array = np.log(yArray)\n",
    "    log_slope, log_intercept = np.polyfit(xArray, log_y_array, 1)\n",
    "    log_regression_line = log_slope * np.array(xArray) + log_intercept\n",
    "\n",
    "    # Plot the original log data and the log regression line\n",
    "    plt.figure(figsize=(10, 6))\n",
    "    plt.scatter(xArray, log_y_array, label='Observed Log Data')\n",
    "    plt.plot(xArray, log_regression_line, color='red', label=f'Linear Regression on Log: log(y) = {log_slope:.4f}x + {log_intercept:.4f}')\n",
    "    plt.xlabel('Length of Target Sequence')\n",
    "    plt.ylabel('Log of Total Cost (Log of Number of Chromosomes)')\n",
    "    plt.title('Linear Regression of Log of Truncated Evolution Cost vs. Target Sequence Length')\n",
    "    plt.legend()\n",
    "    plt.grid(True)\n",
    "    plt.show()\n",
    "\n",
    "    print(f\"Linear Regression Equation (Cost vs Length): y = {slope:.2f}x + {intercept:.2f}\")\n",
    "    print(f\"Linear Regression Equation (Log(Cost) vs Length): log(y) = {log_slope:.4f}x + {log_intercept:.4f}\")\n",
    "\n",
    "if __name__ == \"__main__\":    main()\n",
    "\n"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "a640947b",
   "metadata": {},
   "source": [
    "**Exercise.** Run the code to get a first impression. Next, play with the code to discover different regimes, i.e., different intervals of $n$, which can be fitted by different patterns.\n",
    ">\n",
    "> **Answer.** There are different regimes for $n$, i.e., different regions where different fits can be proposed.\n",
    ">\n",
    "- 0-20:  for this region,  200 chromosomes are more than enough to match the task. Much the same as 10 coins are more than enough to get one head. \n",
    "- 20-200: linear, the cost grows as a linear function of the length of the input string.\n",
    "- 200-500: linear, but with a slope that is less than the former. \n",
    "- 500-3500: parabolic\n",
    "- 3500-?: unknown?\n",
    "\n",
    "**A long experiment that was run by Colab**\n",
    "\n",
    "Lab: Cost of truncated Evolution  \n",
    "Purpose: estimation of the cost to solve the Truncated Shakespeare  challenge  \n",
    "Date of Experiment  = 2026-02-12 13:05:34.289132  \n",
    "number_of_points = 14  \n",
    "step_size = 500  \n",
    "alphabet =  01  \n",
    "percentageOfTask = 0.8  \n",
    "population_size = 200  \n",
    "include_clone_population17 = True  \n",
    "include_mutate_all17 = True  \n",
    "include_crossover_all17 = False  \n",
    "mutation_rate = 0.01  \n",
    "print_best_fitness = False  \n",
    "Total cost = population size * number of generations  \n",
    "Length of target sequence, Total cost, employed time  \n",
    "500    7600 0:00:00.677019  \n",
    "1000    14400 0:00:03.153980  \n",
    "1500    17400 0:00:05.037411  \n",
    "2000    23600 0:00:09.574838  \n",
    "2500    33000 0:00:15.981888  \n",
    "3000    41200 0:00:24.489939  \n",
    "3500    59600 0:00:41.185164  \n",
    "4000    1135200 0:15:04.310150  \n",
    "\n",
    "Twelve hours of work by Colab were not sufficient to reach a length of the target string of 4500.\n",
    "\n",
    "**Exercise.** We are data hungry. So, run the previous program at home to try to surpass the barrier of the 4500.  \n",
    ">\n",
    "> *Answer.* Working at home, we found that 4000 was solved with a cost of 3.4 million chromosomes. But, two days were not enough to solve the barrier of the 4500. So, we planed an experiment for various days. The output was the following:\n",
    ">\n",
    "Lab: Cost of truncated Evolution  \n",
    "Purpose: estimation of the cost to solve the Truncated Shakespeare challenge  \n",
    "Date of Experiment  = 2026-02-13 07:03:43.791441  \n",
    "number_of_points = 50  \n",
    "step_size = 100  \n",
    "alphabet =  01  \n",
    "percentageOfTask = 0.8  \n",
    "population_size = 200  \n",
    "include_clone_population17 = True  \n",
    "include_mutate_all17 = True  \n",
    "include_crossover_all17 = False  \n",
    "mutation_rate = 0.01  \n",
    "print_best_fitness = False  \n",
    "Total cost = population size * number of generations  \n",
    "Length of target sequence, Total cost, employed time  \n",
    "100    2200 0:00:00.061027  \n",
    "200    3800 0:00:00.117134  \n",
    "300    5000 0:00:00.338891  \n",
    "400    7200 0:00:00.523325  \n",
    "500    8200 0:00:00.678946  \n",
    "600    9200 0:00:00.932542  \n",
    "700    10600 0:00:01.292804  \n",
    "800    11800 0:00:01.588590  \n",
    "900    12400 0:00:02.003650  \n",
    "1000    13200 0:00:02.307484  \n",
    "1100    13400 0:00:02.556647  \n",
    "1200    14200 0:00:03.138259  \n",
    "1300    16600 0:00:03.799097  \n",
    "1400    18400 0:00:04.470924  \n",
    "1500    20200 0:00:05.096861  \n",
    "1600    19000 0:00:05.258689  \n",
    "1700    20600 0:00:06.166497  \n",
    "1800    21200 0:00:06.572901  \n",
    "1900    22600 0:00:07.384061  \n",
    "2000    25000 0:00:08.674209  \n",
    "2100    27200 0:00:09.823615  \n",
    "2200    26600 0:00:10.076484  \n",
    "2300    28800 0:00:11.416397  \n",
    "2400    31800 0:00:12.897955  \n",
    "2500    32800 0:00:13.712395  \n",
    "2600    34800 0:00:15.313911  \n",
    "2700    36400 0:00:17.078005  \n",
    "2800    39400 0:00:18.698050  \n",
    "2900    39800 0:00:19.574990  \n",
    "3000    45000 0:17:23.146962    \n",
    "3100    49200 0:00:29.731594  \n",
    "3200    45800 0:00:24.160093  \n",
    "3300    57000 0:00:31.381588  \n",
    "3400    60200 0:00:32.293667  \n",
    "3500    64800 0:00:28.811930  \n",
    "3600    79000 0:00:36.104549  \n",
    "3700    86200 0:00:40.665940  \n",
    "3800    246000 2:14:21.950245  \n",
    "3900    145200 0:01:13.390478  \n",
    "4000    2016000 3:13.39.581563   \n",
    "4100    26225800 5 and a half hours   \n",
    "4200    Twelve hours of work by Free Colab were not enough.\n",
    "\n",
    "\n",
    "The graph of this output is made by the following program\n",
    "\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "85c25c40",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1000x600 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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IJGpf3BT3z+tLEACxf/9+tXVnzZolTExMNPr+999/FwDE7t27hRBCzJ8/XwAQz549y/cYP/jgA1G9evUC+yH3F6mnT58KKysr0bp1a7X1bt++LSwsLETXrl2Vy3r16iUAiN9++01t3datWws/P78C9xsXFycAqH1wCCHEqVOnBADx9ddfK5dpk/xou252drbw8PAQVatWVfvi+/z5c+Hq6irq16+vXFa7dm3h6ekp0tPT1dYrXbr0axMlXfpRm9dbXvJLlPJ6Xgmhe6KU+7GZO3euACASExOFEELcuHFDmJqa5vklMz8FvYbnzZun8aVeCHmfmZmZiaFDh6otf/78uXB3dxcfffSREEL12NaoUUP5XiOEEDdv3hRSqVTrRAlAnn/9+vVTrvfdd98JAOLKlSvKZUlJScLCwkKMGjVKuez9998Xrq6u4vnz58plWVlZokqVKqJcuXLKOAubKAkhxKNHj/J9bI31+p49e7byxw1tjBs3TgAQp06dUls+aNAgIZFIlP08ZMgQ4ejoWOC2tmzZotGXBfnyyy+FlZWV2ntpbGysACCWLl0qhBDi8ePHAoBYvHixVtvUxevesxSvmUOHDgkA4sKFC8o2xWO0atUqtfv89ddfeSaqs2bN0niuaPv5dubMGa2/xAshT+I7dOigfP2YmpqK4OBgMWHCBLXE9cWLF8LJyUm0bdtW7f7Z2dmiWrVqok6dOspldevWFR4eHuLVq1fKZSkpKcLJyanQiZK2x694jeZ+7fz2228CgDhx4oQQQv6+ZG9vLxo2bKj2PpSbv7+/CA4OVv6oovDBBx+IMmXKqH0+5eV1iZLiR4WtW7eqLVc8jsuXL1cu8/LyEpaWluLWrVvKZa9evRJOTk5i4MCBymVdunQRNjY2as/V7OxsERgYqPHe/d577+X5/qVtP75rOPXuHdOuXTu120FBQUhLS8PDhw8BAH/++SckEgm6d++OrKws5Z+7uzuqVaumNt3m4cOH+Pzzz+Hp6QkzMzNIpVJ4eXkBgMZUEQD48MMPdYr1448/hlQqVQ71p6Sk4K+//lKeTJ6Wlob9+/ejY8eOsLa2Vou3devWSEtLw8mTJwEAhw4dQpUqVTROpv/000/z3HepUqXQrFkztWV//vknqlSpgurVq6vtKzw8XG0qkmIaxEcffYTffvsN9+7d09h+nTp1cOHCBQwePBh79+7VqsrQiRMn8OrVK43pX56enmjWrJnGVAiJRIK2bduqLQsKCsKtW7cK3M/BgwcBQGM/derUQUBAQJ5TLvThypUruH//Pnr06AETE9Vbk62tLT788EOcPHkSL1++xIsXL3D27Fl06NAB5ubmauvlPt686NqP+pTX86ow8nodA1A+thEREcjOzsYXX3xR4HZ0fQ3ntnfvXmRlZaFnz55qrwlLS0s0adJE+ZpQPLZdu3ZVm4bj5eWF+vXra33cFStWxJkzZzT+Jk2apFynW7dusLCwUJvas3HjRqSnp6NPnz4AgBcvXuDUqVPo3Lmz2vQjU1NT9OjRA3fv3i3yqSZF9frW1YEDBxAYGKhxjl7v3r0hhFAWLKlTpw6ePXuGTz/9FH/88Ydeqlv27dsXr169wubNm5XLVq9eDQsLC3Tt2hUA4OTkhIoVK2LevHlYuHAhzp8/b5CKfQo3btxA165d4e7uDlNTU0ilUjRp0gSAdp97hw4dAiD/fMgp92eRLp9vurKwsMD27dsRGxuLRYsW4ZNPPsGjR48wc+ZMBAQEKJ/7x48fR1JSEnr16qW2f5lMhpYtW+LMmTN48eIFXrx4gTNnzqBTp06wtLRU7sfOzk6r9+S8FOb4X/e+ePz4caSkpGDw4MH5TtG+du0a/v33X3Tr1g0ANPabmJj4xu8Nf/75JxwdHdG2bVu17VevXh3u7u4aVTKrV6+O8uXLK29bWlqicuXKaq/1Q4cOoVmzZmrn0pmYmGg8z7Txun581zBReseULl1a7baiWpTixN3//vsPQgi4ublBKpWq/Z08eVL54SeTyRAWFoZt27ZhzJgx2L9/P06fPq1848rrRGBdqzvNmTMHZ86cwaFDhzBhwgT8999/6NChg3IO/pMnT5CVlYWlS5dqxNq6dWsAUMb75MkTuLm5aewjr2X5xfrff//h4sWLGvuys7ODEEK5r8aNG2PHjh3KL5DlypVDlSpVsHHjRuW2xo8fj/nz5+PkyZNo1aoVSpcujebNmxdY/vzJkyf5xubh4aFsV7C2tlb70ALkj3daWlq++yjMfvTldfuVyWR4+vQpnj59qnyO5pbf46nLfgx1fPntszBe9zpWzHMvV65cvtsozGs4N8X5grVr19Z4XWzevFnt9QcA7u7uGtvIa1l+LC0tUatWLY0/RXIHyL84t2vXDr/88guys7MByM+PqVOnDt577z0AUD6H8nsO5Iy5qBTV61vxhSshIUHruLTppx49emDVqlW4desWPvzwQ7i6uqJu3bqIiIjQaj95ee+991C7dm2sXr0aAJCdnY1169ahffv2cHJyAgDleUzh4eGYO3cuatSoARcXFwwbNgzPnz8v9L7zkpqaikaNGuHUqVOYMWMGoqKicObMGWzbtg2A5mvG2tpao3rckydPYGZmpoxfIfd7ly6fb4UVEBCAESNGYN26dbh9+zYWLlyIJ0+eKH94ULy+O3furBHDnDlzIIRAUlISnj59CplM9sav75wKc/z6eF9UHPPo0aM19jt48OA896ur//77D8+ePYO5ubnGPh48ePDa41IcW87nm67fcQryun5817DqHalxdnaGRCLBkSNH8iy5q1h26dIlXLhwAWvWrEGvXr2U7deuXct329qeZK/g4+OjLODQuHFjWFlZYeLEiVi6dClGjx6NUqVKKX8Bzu+X8woVKgCQv/BzF4EA5Cc2axurs7MzrKys8jyJUtGu0L59e7Rv3x7p6ek4efIkZs2aha5du8Lb2xv16tWDmZkZvvzyS3z55Zd49uwZIiMj8fXXXyM8PBx37tzJszKS4s0rMTFRo+3+/ft6qcqUez+5P1D0uZ+C9pvb/fv3YWJiglKlSkEIAYlEotPjqct+DHV8QP6vAQsLizxPwi/sl3VFEYG7d+/C09Mzz3UK8xrOTdFXv//+u1qykpuiz/N6fLR5zHTVp08fbNmyBREREShfvjzOnDmDFStWKNtLlSoFExOTfJ8DAAp8HlhaWmoUwQHe7AtUUT0vmzZtCqlUih07duDzzz/XKi5t+6lPnz7o06cPXrx4gcOHD2PKlCn44IMPEB8fX+DzoyB9+vTB4MGDERcXhxs3biAxMVE5Mqjg5eWlLOARHx+P3377DVOnTkVGRgZWrlxZqP3m5cCBA7h//z6ioqKUo0gA8r2+WF6v99KlSyMrKwtJSUlqyVLu14Eun2/6IJFIMHLkSHzzzTfKaqaKx3bp0qX5Vpt0c3NDZmYmJBKJVq9vRXKf+/0u93udIY4/5/tifhTHPH78eHTq1CnPdfz8/HTab177KF26tLKqYm55XYLidXT9jkPa44gSqfnggw8ghMC9e/fy/OW2atWqAFQfALmTqR9++MFgsY0ZMwa+vr6YPXs2nj9/DmtrazRt2hTnz59HUFBQnvEqvnw0adIEly5dQmxsrNo2N23apPX+P/jgA1y/fh2lS5fOc195XRfEwsICTZo0wZw5cwAgz0pgjo6O6Ny5M7744gskJSXlezHGevXqwcrKCuvWrVNbfvfuXRw4cEBZUelNKaaG5d7PmTNnEBcXp7f95Obn54eyZctiw4YNauVpX7x4ga1btyor4dnY2KBWrVrYsWMHMjIylOulpqbizz//fO1+iqofdeHt7a2s4KVw4MABpKamFmp7YWFhMDU1VUsOctPlNZzfL4rh4eEwMzPD9evX83xNKH7o8PPzQ5kyZbBx40a1x/bWrVs4fvx4oY6xIGFhYShbtixWr16N1atXw9LSUm1qk42NDerWrYtt27apHZNMJsO6detQrlw5VK5cOd/te3t7Iz4+Xu3L3pMnTzSORZdfYovqeenu7o7PPvsMe/fuzbfq4PXr15XPx+bNmyM2NhbR0dFq6/zyyy+QSCRo2rSpxv1tbGzQqlUrTJgwARkZGcoy+4X5ZfrTTz+FpaUl1qxZgzVr1qBs2bIICwvLd/3KlStj4sSJqFq1qkbMb0ofn3uKBCvndEJA87NIl883Xfs1r8QXkCe/KSkpytHCBg0awNHREbGxsfm+vs3NzWFjY4M6depg27ZtaiOaz58/x65du9T24ebmBktLS433uz/++KPQx6+t+vXrw8HBAStXrsy3BLqfnx8qVaqECxcu5HvMhUlkcvrggw/w5MkTZGdn57n9wiRiTZo0wYEDB9R+rJHJZNiyZYvGurlHo6hgHFF6Sx04cCDPL9SKIenCatCgAQYMGIA+ffrg7NmzaNy4MWxsbJCYmIijR4+iatWqGDRoEPz9/VGxYkWMGzcOQgg4OTlh165dbzTN4nWkUim+/fZbfPTRR1iyZAkmTpyIJUuWoGHDhmjUqBEGDRoEb29vPH/+HNeuXcOuXbuU8+dHjBiBVatWoVWrVvjmm2/g5uaGDRs24N9//wUAtXNi8jNixAhs3boVjRs3xsiRIxEUFASZTIbbt29j3759GDVqFOrWrYvJkyfj7t27aN68OcqVK4dnz55hyZIlanPZ27ZtiypVqqBWrVpwcXHBrVu3sHjxYnh5eeV7MV1HR0dMmjQJX3/9NXr27IlPP/0UT548wbRp02BpaYkpU6bopZ/9/PwwYMAALF26FCYmJmjVqhVu3ryJSZMmwdPTEyNHjnyj7e/atSvPD5rOnTtj7ty56NatGz744AMMHDgQ6enpmDdvHp49e4bZs2cr1/3mm2/Qpk0bhIeHY/jw4cjOzsa8efNga2uLpKSkAvdfVP2oix49emDSpEmYPHkymjRpgtjYWCxbtkztIpe68Pb2xtdff43p06fj1atXyksCxMbG4vHjx5g2bZpOr2HFDyRLlixBr169IJVK4efnB29vb3zzzTeYMGECbty4gZYtW6JUqVL477//cPr0adjY2GDatGkwMTHB9OnT8dlnn6Fjx47o378/nj17hqlTp+o0NefVq1f5npeR8xdvU1NT9OzZEwsXLoS9vT06deqk0ZezZs1CaGgomjZtitGjR8Pc3BzLly/HpUuXsHHjxgJHwHv06IEffvgB3bt3R//+/fHkyRPMnTtXY5qVnZ0dvLy88Mcff6B58+ZwcnKCs7Nznj+qFOXzcuHChbhx4wZ69+6NvXv3omPHjnBzc8Pjx48RERGB1atXY9OmTQgKCsLIkSPxyy+/oE2bNvjmm2/g5eWFv/76C8uXL8egQYOUCWX//v1hZWWFBg0aoEyZMnjw4AFmzZoFBwcH5XmbVapUAQD873//g52dHSwtLVGhQoUCv/A6OjqiY8eOWLNmDZ49e4bRo0ervV9fvHgRQ4YMQZcuXVCpUiWYm5vjwIEDuHjxIsaNG6dcr1+/fli7di2uX79e6NGt+vXro1SpUvj8888xZcoUSKVSrF+/HhcuXNB6Gy1btkSDBg0watQopKSkoGbNmjhx4oQyac15bNp+vlWsWBFWVlZYv349AgICYGtrCw8PD2XCk9uAAQPw7NkzfPjhh6hSpQpMTU3x77//YtGiRTAxMcHYsWMByM/7XLp0KXr16oWkpCR07twZrq6uePToES5cuIBHjx4pf4yZPn06WrZsidDQUIwaNQrZ2dmYM2cObGxs1N6TFedAr1q1ChUrVkS1atVw+vRpbNiwQSNObY9fW7a2tliwYAE+++wztGjRAv3794ebmxuuXbuGCxcuYNmyZQDkiW+rVq0QHh6O3r17o2zZskhKSkJcXByio6PzTD5yu379On7//XeN5YGBgfjkk0+wfv16tG7dGsOHD0edOnUglUpx9+5dHDx4EO3bt0fHjh11OrYJEyZg165daN68OSZMmAArKyusXLlSWbY+5/OqatWq2LRpEzZv3gwfHx9YWloq3+MpD0YpIUGFpqiUlN9fQkJCgVXvclfvyatErRBCrFq1StStW1fY2NgIKysrUbFiRdGzZ09x9uxZ5TqxsbEiNDRU2NnZiVKlSokuXbqI27dva1Su0aUymhD5lwdXqFu3rihVqpSyElJCQoLo27evKFu2rJBKpcLFxUXUr19fzJgxQ+1+ly5dEi1atBCWlpbCyclJ9OvXT6xdu1ajWpGiDHFeUlNTxcSJE4Wfn58wNzdXli4dOXKksnT6n3/+KVq1aiXKli0rzM3Nhaurq2jdurVaeesFCxaI+vXrC2dnZ2Fubi7Kly8v+vXrJ27evKlcJ7/H5qeffhJBQUHK/bdv316jml9eVdeEUD0Wr5OdnS3mzJkjKleuLKRSqXB2dhbdu3fXKDlbmKp3+f0p7NixQ9StW1dYWloKGxsb0bx5c3Hs2DGN7W3fvl1UrVpV2X+zZ88Ww4YNE6VKlXptLEJo14/6rnqX3/MqPT1djBkzRnh6egorKyvRpEkTERMTk2/Vu9zx5FWZTQghfvnlF1G7dm1haWkpbG1tRXBwsNr7gravYSGEGD9+vPDw8BAmJiYa+9qxY4do2rSpsLe3FxYWFsLLy0t07txZrXywEPI+r1SpkjA3NxeVK1cWq1at0qgUl5+Cqt4B0KhQFR8fr2yLiIjIc5tHjhwRzZo1U77Pvf/++2LXrl1a9e3atWtFQECAsLS0FIGBgWLz5s15HktkZKQIDg4WFhYWAoDy8TTm61sIeYW/tWvXimbNmgknJydhZmYmXFxcRKtWrcSGDRvUKnvdunVLdO3aVZQuXVpIpVLh5+cn5s2bp7bO2rVrRdOmTYWbm5swNzcXHh4e4qOPPhIXL15U2+/ixYtFhQoVhKmpqdaV2vbt26d8LHOWSRdCiP/++0/07t1b+Pv7CxsbG2FrayuCgoLEokWL1MoZK6rQ5e7vguT1/nb8+HFRr149YW1tLVxcXMRnn30moqOjNY4lv8dICHkVxj59+ghHR0dhbW0tQkNDxcmTJwUAsWTJErV1tf1827hxo/D39xdSqTTfSosKe/fuFX379hWBgYHCwcFBmJmZiTJlyohOnTrlWdns0KFDok2bNsLJyUlIpVJRtmxZ0aZNG43P6J07dyqfu4r35Lyek8nJyeKzzz4Tbm5uwsbGRrRt21bcvHkzz7i1Of78vjPkV2Fv9+7dokmTJsLGxkZYW1uLwMBAMWfOHLV1Lly4oLykgFQqFe7u7qJZs2Zi5cqV+farQkHvU4rjy8zMFPPnzxfVqlVTvj/7+/uLgQMHiqtXryq35eXlJdq0aaOxj7wqbx45ckTUrVtXWFhYCHd3d/HVV1+JOXPmCOSqwnvz5k0RFhYm7OzsBADle5au/fiukAjBSzDTu2vAgAHYuHEjnjx5olZBjd4+mZmZqF69OsqWLYt9+/YZOxwiIq1t2LAB3bp1w7Fjx3SqBFncTZ06FdOmTct3qhsZVlhYGG7evIn4+Hhjh/LW4tQ7emd888038PDwgI+Pj/J8lp9++gkTJ05kkvQW6tevH0JDQ5XTfFauXIm4uDgsWbLE2KEREeVr48aNuHfvHqpWrQoTExOcPHkS8+bNQ+PGjUtUkkRF68svv0RwcDA8PT2RlJSE9evXIyIiQlnohAqHiRK9M6RSKebNm4e7d+8iKysLlSpVwsKFCzF8+HBjh0aF8Pz5c4wePRqPHj2CVCpFjRo1sHv3brRo0cLYoRER5cvOzg6bNm3CjBkz8OLFC5QpUwa9e/fGjBkzjB0avcWys7MxefJkPHjwABKJBIGBgfj111/RvXt3Y4f2VuPUOyIiIiIiolxYHpyIiIiIiCgXJkpERERERES5MFEiIiIiIiLKpcQXc5DJZLh//z7s7OwKvIAgERERERGVbEIIPH/+HB4eHmoX481LiU+U7t+/D09PT2OHQURERERExcSdO3dQrly5Atcp8YmSnZ0dAHln2NvbF3o7mZmZ2LdvH8LCwiCVSvUVHv0/9q9hsX8Ni/1rWOxfw2L/Ghb717DYv4ZVEvs3JSUFnp6eyhyhICU+UVJMt7O3t3/jRMna2hr29vYl5olSnLB/DYv9a1jsX8Ni/xoW+9ew2L+Gxf41rJLcv9qcksNiDkRERERERLkwUSIiIiIiIsqFiRIREREREVEuJf4cJW0IIZCVlYXs7Ox818nMzISZmRnS0tIKXI8Kh/1rWOxfw2L/Gta70L9SqRSmpqbGDoOIiHJ45xOljIwMJCYm4uXLlwWuJ4SAu7s77ty5w+sxGQD717DYv4bF/jWsd6F/JRIJypUrB1tbW2OHQkRE/++dTpRkMhkSEhJgamoKDw8PmJub5/shLJPJkJqaCltb29denIp0x/41LPavYbF/Dauk968QAo8ePcLdu3dRqVIljiwRERUT73SilJGRAZlMBk9PT1hbWxe4rkwmQ0ZGBiwtLUvkB7WxsX8Ni/1rWOxfw3oX+tfFxQU3b95EZmYmEyUiomKiZH7i6KikfvASEdHboaROKSQiepsxQyAiIiIiIsqFiRIREREREVEuTJRKOG9vbyxevNjYYehNSTseIiIiIiqemCi9pe7cuYN+/fopq/V5eXlh+PDhePLkibFDM6qpU6eievXqRbrPqKgoSCQSSCQSmJiYwMHBAcHBwRgzZgwSExN13p5EIsGOHTv0HygRERERaY2Jkh5kywROXH+CP2Lu4cT1J8iWCYPu78aNG6hVqxbi4+OxceNGXLt2DStXrsT+/ftRr149JCUlGXT/BcnOzoZMJjPa/o3pypUruH//Ps6cOYOxY8ciMjISVapUwT///GPs0IiIiIhIR0yU3tCeS4loOOcAPv3xJIZvisGnP55EwzkHsOeS7iMJ2vriiy9gbm6Offv2oUmTJihfvjxatWqFyMhI3Lt3DxMmTFBb//nz5+jatStsbW3h4eGBpUuXqrVPnToV5cuXh4WFBTw8PDBs2DBlW0ZGBsaMGYOyZcvCxsYGdevWRVRUlLJ9zZo1cHR0xJ9//onAwEBYWFjgxx9/hKWlJZ49e6a2n2HDhqFJkybK28ePH0fjxo1hZWUFLy8vjB07Fi9evFC2P3z4EG3btoWVlRUqVKiA9evXv3Hf/fPPP2jWrBmsrKxQunRpDBgwAKmpqcr2rKwsDBs2DI6OjihdujTGjh2LXr16oUOHDq/dtqurK9zd3VG5cmV88sknOHbsGFxcXDBo0CDlOmfOnEFoaCicnZ3h4OCAJk2aIDo6Wtnu7e0NAOjYsSMkEony9vXr19G+fXu4ubnB1tYWtWvXRmRk5Bv3BxEREZEhFfWAgj4xUXoDey4lYtC6aCQmp6ktf5CchkHrog2SLCUlJWHv3r0YPHgwrKys1Nrc3d3RrVs3bN68GUKonoTz5s1DUFAQoqOjMX78eIwcORIREREAgN9//x2LFi3CDz/8gKtXr2LHjh2oWrWq8r59+vTBsWPHsGnTJly8eBFdunRBy5YtcfXqVeU6L1++xKxZs/DTTz/h8uXL6N69OxwdHbF161blOtnZ2fjtt9/QrVs3APKEJTw8HJ06dcLFixexceNGnDx5EkOHDlXep3fv3rh58yYOHDiA33//HcuXL8fDhw8L3XcvX75Ey5YtUapUKZw5cwZbtmxBZGQkhgwZolxnzpw5WL9+PVavXo1jx44hJSWl0NPgrKys8Pnnn+PYsWPKuJ8/f45evXrhyJEjOHnyJCpVqoTWrVvj+fPnAOSJFACsXr0aiYmJytupqalo3bo1IiMjcf78eYSHh6Nt27a4fft2ofuDiIiIyJCMMaCgT+/0BWffRLZMYNquWOSVEwsAEgDTdsUiNNAdpib6uz7G1atXIYRAQEBAnu0BAQF4+vQpHj16BFdXVwBAgwYNMG7cOABA5cqVcezYMSxatAihoaG4ffs23N3d0aJFC0ilUpQvXx516tQBIB/F2LhxI+7evQsPDw8AwOjRo7Fnzx6sXr0a3377LQAgMzMTy5cvR7Vq1ZRxfPzxx9iwYQP69esHANi/fz+ePn2KLl26AJAnb127dsWIESMAABUrVsTs2bPxwQcfYOXKlbh9+zb+/vtvnDx5EnXr1gUA/Pzzz/ketzbWr1+PV69e4ZdffoGNjQ0AYNmyZWjbti3mzJkDNzc3LF26FOPHj0fHjh2V7bt37y70Pv39/QEAN2/ehKurK5o1a6bW/sMPP6BUqVI4dOgQPvjgA7i4uAAAHB0d4e7urlyvWrVqav07Y8YMbN++HTt37lRL9IiIiIiKA8WAQu7vyooBhRXda6BllTJGiU1bHFEqpNMJSRojSTkJAInJaTidULTnCylGknJevLBevXpq69SrVw9xcXEAgC5duuDVq1fw8fFB//79sX37dmRlZQEAoqOjIYRA5cqVYWtrq/w7dOgQrl+/rtyeubk5goKC1PbRrVs3REVF4f79+wDkSUrr1q1RqlQpAMC5c+ewZs0a5Tbt7e3RuXNnyGQyJCQkIC4uDmZmZqhVq5Zym/7+/nB0dCx038TFxaFatWrKJAmQJ5EymQxXrlxBcnIy/vvvP2WiCACmpqaoWbNmofeZ+/F4+PAhPv/8c1SuXBkODg5wcHBAamrqa0eGXrx4gTFjxiAwMBCOjo6wtbXFv//+yxElIiIiKnZeN6AAyAcUivs0PI4oFdLD5/knSYVZT1u+vr6QSCSIjY3N87yZf//9F6VKlYKzs3OB21F8cff09MSVK1cQERGByMhIDB48GPPmzcOhQ4cgk8lgamqKc+fOwdTUVO3+tra2yv+trKw0ripfp04dVKxYEZs2bcKgQYOwfft2rF69Wtkuk8kwcOBA5flQMpkMqampsLW1hbe3N65cuaIWpz4IIfLdXs7ludfJOY1RV4qEVHGuUe/evfHo0SMsXrwYXl5esLCwQL169ZCRkVHgdr766ivs3bsX8+fPh6+vL6ysrNC5c+fX3o+IiIioqOkyoFCvYumiC0xHTJQKydXOUq/raat06dIIDQ3F8uXLMXLkSLXzlB48eID169ejZ8+eal/2T548qbaNkydPKqeEAfJEp127dmjXrh2++OIL+Pv7459//kFwcDCys7Px8OFDNGrUSOdYu3btivXr16NcuXIwMTFBmzZtlG01atTA5cuX4evrC0CeKKWkpMDe3h4mJiYICAhAVlYWzp49qxzhuXLlikaBCF0EBgZi7dq1ePHihXJU6dixYzAxMVGO8Li5ueH06dPK483Ozsb58+cLVXL81atX+N///ofGjRsrp9QdOXIEy5cvR+vWrQHIy7w/fvxY7X5SqRTZ2dlqy44cOYLevXsrpwSmpqbi5s2bOsdEREREZGjGGlDQN069K6Q6FZxQxsES+Y13SACUcbBEnQpOet/3smXLkJ6ejvDwcBw+fBh37tzBnj17EBoairJly2LmzJlq6x87dgxz585FfHw8vv/+e2zZsgXDhw8HIK9a9/PPP+PSpUu4ceMGfv31V2UVusqVK6Nbt27o2bMntm3bhoSEBJw5cwZz5szR6rydbt26ITo6GjNnzkTnzp1haalKGseOHYsTJ07giy++QExMDK5evYrdu3crR5j8/PzQsmVL9O/fH6dOncK5c+fw2WefaRSwyMurV68QExOj9nft2jV069YNlpaW6NWrFy5duoSDBw9i6NCh6NGjB9zc3AAAQ4cOxaxZs/DHH3/gypUrGD58OJ4+farVyNbDhw/x4MEDXL16FZs2bUKDBg3w+PFjrFixQrmOr68vfv31V8TFxeHUqVPo1q2bxjF5e3tj//79ePDgAZ4+faq837Zt2xATE4MLFy6ga9eu72wZdiIiIirejDWgoG9MlArJ1ESCKW0DAUAjWVLcntI2UK+FHBQqVaqEs2fPomLFivj4449RsWJFDBgwAE2bNsWJEyfg5KSenI0aNQrnzp1DcHAwpk+fjgULFiA8PByAvGjAjz/+iAYNGiAoKAj79+/Hrl27ULq0fBh09erV6NmzJ0aNGgU/Pz+0a9cOp06dgqenp1Zx1q5dGxcvXlRWu1MICgrCoUOHcPXqVTRq1Ag1a9bEt99+izJlVCf1rV69Gp6enmjSpAk6deqEAQMGKAtUFCQ+Ph7BwcFqf5999hmsra2xd+9eJCUloXbt2ujcuTOaN2+OZcuWKe87duxYfPrpp+jZsyfq1asHW1tbhIeHqyV5+fHz84OHhwdq1qyJ2bNno0WLFrh06RICAwOV66xatQpPnz5FcHAwevTogWHDhmkc04IFCxAREQFPT08EBwcDABYtWoRSpUqhfv36aNu2LcLDw1GjRo3XxkRERERU1Iw5oKBPEvEmJ2C8BVJSUuDg4IDk5GTY29urtaWlpSEhIQEVKlR47Rfh3FPDFPZcSsS0XbFq8zDLOFhiStvAYl/JozjJr3+NTSaTISAgAB999BGmT59u7HAKrbj2b0nB/jWsd6F/dfk80rfMzEzs3r0brVu3hlQqLdJ9vwvYv4bF/jWsN+lfRdU7AGpFHRTJk7Gq3hWUG+TGc5TeUMsqZRAa6I7TCUl4+DwNrnby7NgQI0lkeLdu3VJeyDc9PR3Lli1DQkICunbtauzQiIiIiN4aLauUwYruNTQGFNzfogEFJkp6YGoiKdYVO0h7JiYmWLNmDUaPHg0hBKpUqYLIyMg3un4TERER0bvobR9QYKJElIOnpyeOHTtm7DCIiIiISoS3eUChZE72JiIiIiIiegNMlIiIiIiIiHJhokRERERERJQLEyUiIiIiIqJcmCgRERERERHlwkSJiIiIiIgoFyZKJZBEIsGOHTuMHcY7Z82aNXB0dDR2GG81Q/bhzz//jLCwMK3X//PPPxEcHAyZTGaQeIiIiKh4Y6L0Furduzc6dOiQb3tiYiJatWpVdAHpSCKRKP9sbW1RrVo1rFmzxthhvbGPP/4Y8fHxxg6jUG7evAmJRIKYmBhjh2IQ6enpmDx5MiZNmqT1fT744ANIJBJs2LDBgJHJHTp0CDVr1oSlpSV8fHywcuXK197n9u3baNu2LWxsbODs7Ixhw4YhIyNDbZ1//vkHTZo0gZWVFcqWLYtvvvkGQghle2JiIrp27Qo/Pz+YmJhgxIgRGvu5fPkyPvzwQ3h7e0MikWDx4sVverh68eDBA/To0QPu7u6wsbFBjRo18Pvvv7/2fsuXL0eFChVgaWmJmjVr4siRI2rtqampGDJkCMqVKwcrKysEBARgxYoVGts5ceIEmjVrBhsbGzg6OiIkJASvXr0CAERFRam9z+X8O3PmjH46gIiIDI6JUgnk7u4OCwsLo8YghEBWVla+7atXr0ZiYiIuXLiAjz/+GP369cP+/fsNGlPuL5H6ZmVlBVdXV4Pugwpn69atsLW1RaNGjXS6X58+fbB06VIDRSWXkJCA1q1bo1GjRjh//jy+/vprDBs2DFu3bs33PtnZ2WjTpg1evHiBo0ePYtOmTdi6dStGjRqlXCclJQWhoaHw8PDAmTNnsHTpUsyfPx8LFy5UrpOeng4XFxdMmDAB1apVy3NfL1++hI+PD2bPng13d3f9HXgOikRdFz169MCVK1ewc+dO/PPPP+jUqRM+/vhjnD9/Pt/7bN68GSNGjMCECRNw/vx5NGrUCK1atcLt27eV64wcORJ79uzBunXrEBcXh5EjR2Lo0KH4448/lOucOHECLVu2RFhYGE6fPo0zZ85gyJAhMDGRf6TWr18fiYmJan+fffYZvL29UatWLR17h4iIjEaUcMnJyQKASE5O1mh79eqViI2NFa9evVItlMmESE3V+MtOSRFP794V2Skpeba/8Z9MpvUx9erVS7Rv3z7fdgBi+/btQgghEhISBACxdetWERISIqysrERQUJA4fvy42n2OHTsmGjVqJCwtLUW5cuXE0KFDRWpqqrL9119/FTVr1hS2trbCzc1NfPrpp+K///5Tth88eFAAEHv27BE1a9YUUqlUHDhw4LXxKTg5OYkvvvhCZGdnCyGEePbsmejfv79wcXERdnZ2omnTpiImJkbtPtOnTxcuLi7C1tZW9OvXT4wdO1ZUq1ZNo5++/fZbUaZMGeHl5SWEEOLu3bvio48+Eo6OjsLJyUm0a9dOJCQkqB1L7dq1hbW1tXBwcBD169cXN2/eFEIIERMTI0JCQoStra2ws7MTNWrUEGfOnBFCCLF69Wrh4OCgFuPy5cuFj4+PkEqlonLlyuKXX37R6Isff/xRdOjQQVhZWQlfX1/xxx9/5NlvCklJSaJHjx7C0dFRWFlZiZYtW4r4+HhluyKOPXv2CH9/f2FjYyPCwsJEXFycsn9zUzxPzp8/n2d7WlqaGDp0qHBxcREWFhaiQYMG4vTp02rr/PHHH8LX11dYWlqKkJAQsWbNGgFAPH36tMDjyakwfRgXFycaNGggLCwsREBAgIiIiNB4jrVt21aMHj1aefvQoUPCzMxMJCYmqm3ryy+/FI0aNVLevnnzpgAgrl+/XmDc2dnZ4unTp/n2b0HGjBkj/P391ZYNHDhQvP/++/neZ/fu3cLExETcu3dPuWzjxo3CwsJC+V63fPly4eDgINLS0pTrzJo1S3h4eAhZHu83TZo0EcOHDy8wVi8vL7Fo0SK1ZQ8fPhRubm5i5syZymUnT54UUqlU7N27t8DtKSief/nJq39tbGw0ngtOTk7ip59+ync7derUEZ9//rnaMn9/fzFu3Djl7ffee0988803auvUqFFDTJw4UXm7bt26ardfJyMjQ7i6umpsN6c8P4+KSEZGhtixY4fIyMgo8n2/C9i/hsX+NayS2L8F5Qa5cUQpt5cvAVtbjT8Te3s4lisHE3v7PNvf+O/lS4Me1oQJEzB69GjExMSgcuXK+PTTT5UjPv/88w/Cw8PRqVMnXLx4EZs3b8bRo0cxZMgQ5f0zMjIwffp0XLhwATt27EBCQgJ69+6tsZ8xY8Zg1qxZiIuLQ1BQ0Gvjys7Oxm+//YakpCSYmZkBkI9GtWnTBg8ePMDu3btx7tw51KhRA82bN0dSUhIAYP369Zg5cybmzJmDc+fOoXz58nlOj9m/fz/i4uIQERGBP//8Ey9fvkTTpk1ha2uLw4cP4+jRo7C1tUXLli2RkZGBrKwsdOjQAU2aNMHFixdx4sQJDBgwQPlrd7du3VCuXDmcOXMG586dw7hx4yCVSvM8tu3bt2P48OEYNWoULl26hIEDB6JPnz44ePCg2nrTpk3DRx99hIsXL6J169bo1q2b8jjz0rt3b5w9exY7d+7EiRMnIIRA69atkZmZqVzn5cuXmD9/Pn799VccPnwYd+7c0WnaWW5jxozB1q1bsXbtWkRHR8PX1xfh4eHKOG/evInOnTujQ4cOiImJwcCBAzFhwgSN7UgkEp2mWb6uD2UyGTp06ABra2ucOnUK//vf//Lc75EjR9R+yW/cuDF8fHzw66+/KpdlZWVh3bp16NOnj3KZl5cXXF1dNaZn5bR+/XrY29ujXLlysLe3h62trcbf+vXr873/iRMnNM6dCg8Px9mzZ9Ue09z3qVKlCjw8PNTuk56ejnPnzinXadKkidrocnh4OO7fv4+bN2/mG4+uXFxcsGrVKkydOhVnz55FamoqunfvjsGDB+t0TpiuGjZsiM2bNyMpKQkymQybNm1Ceno6QkJC8lw/IyMD586d04gpLCwMx48fV9vuzp07ce/ePQghcPDgQcTHxyM8PBwA8PDhQ5w6dQqurq6oX78+3Nzc0KRJExw9ejTfWHfu3InHjx/n+Z5JRETFmKGzNmPTeUQpNVUIoOj/cozevE5hRpRy/sp6+fJlAUDExcUJIYTo0aOHGDBggNo2jhw5IkxMTPL9dfP06dMCgHj+/LkQQjWitGPHjtfGD0BYWloKGxsbYWpqKgAIJycnce7cOZGdnS32798v7O3t1X4JF0KIihUrih9++EEIIf9F94svvlBrb9CggcaIkpubm0hPT1cu+/nnn4Wfn5/aL+rp6enCyspK7N27Vzx58kQAEFFRUXnGbmdnJ9asWZNnW+7RkPr164v+/furrdOlSxfRunVrtb7I+ct0amqqkEgk4u+//85zH/Hx8QKAOHbsmHLZ48ePhZWVlfjtt9+UcQAQ165dU66zbNky4erqWqgRpdTUVCGVSsX69euVyzIyMoSHh4eYO3euEEKIsWPHiipVqqjdb8KECRojSn5+fmLbtm15xqCIXZc+/PvvvzVGhnKPKD19+lQAEIcPH1bbzpw5c0RAQIDy9o4dO4Stra3aSKoQQgQHB4upU6fmG3NKSoq4cuWKOHfunLhy5Yq4evWqxl9KSkq+969UqZLaaIwQ8hFeAOL+/ft53qd///4iNDRUY7m5ubnYsGGDEEKI0NBQjb67d++eAKAxoixE4UeUFAYPHiwqV64sunXrJqpUqaLTyEhhRpSePXsmwsPDBQBhZmYm7O3txb59+/LdhuLYc752hBBi5syZonLlysrb6enpomfPnsrtmpubq41cnThxQvmetWrVKhEdHS1GjBghzM3N1UZ2c2rVqpVo1apVgX3AEaWSi/1rWOxfwyqJ/csRpTdhbQ2kpmr8yVJS8OzuXchSUvJsf+M/a2uDHlbO0Z0yZcoAkP8yCgDnzp3DmjVr1H4BDw8Ph0wmQ0JCAgDg/PnzaN++Pby8vGBnZ6f81Tbn3H4AWs+/X7RoEWJiYhAREYHq1atjwYIF8PHxUcaTmpqK0qVLq8WUkJCA69evAwCuXLmCOnXqqG0z920AqFq1KszNzZW3z507h2vXrsHOzk65XScnJ6SlpeH69etwcnJC7969ER4ejrZt22LJkiVITExU3v/LL7/EZ599hhYtWmD27NnKePISFxeHBg0aqC1r0KAB4uLi1JblfGxsbGxgZ2enfGzy2qaZmRnq1q2rXFa6dGn4+fmpbdfa2hoVK1ZU3nZ3d8ejR4/yjbUg169fR2ZmptqxSKVS1KlTR7nPK1euoHbt2mr3y+vx+Pfff9GxY0et9/26Prxy5Qo8PT3Vzp3JvV/FCfaWlpZqy3v37o1r167h5MmTAIBVq1bho48+go2Njdp6VlZWeFnAiK+dnR18fX3h4+MDX1/fPP/s7OwKPM7c5+eI/y+4UNB5O3m1CSHUlhdmu4U1f/58ZGVl4bfffsP69es1+ju39957T/kafO+99wBA7fWuWJafiRMn4unTp4iMjMTZs2fx5ZdfokuXLvjnn38KvF9efZJz2XfffYeTJ09i586dOHfuHBYsWIDBgwcjMjISAJRVEBWjm8HBwVi0aBH8/PywatUqjf3dvXsXe/fuRb9+/QqMi4iIih8zYwdQ7EgkQK4vSgAAmQzIzpa3mbx9+WXO6WGKLwWKD3yZTIaBAwdi2LBhGvcrX748Xrx4gbCwMISFhWHdunVwcXHB7du3ER4erlEgIfeXzPy4u7srv0Ru2bIFwcHB8Pf3R506dSCTyVCmTBlERUVp3C9n6ej8vgQWFI9MJkPNmjXznArl4uICQF5oYtiwYdizZw82b96MiRMnIiIiAu+//z6mTp2Krl274q+//sLff/+NKVOmYNOmTfl++X/dlzIAGlP3JBJJviWp8zrGvLab1zbzu+/r5PflOuc+8zquwu4vN133m1vp0qUhkUjw9OlTteWurq5o27YtVq9eDR8fH+zevTvP51xSUpLyuZGX9evXY+DAgQXG8MMPP6Bbt255trm7u+PBgwdqyx4+fAgzMzOULl063/ucOnVKbdnTp0+RmZkJNze3ArcLQLmOPt24cQP379+HTCbDrVu3Xjv1dvfu3cqphffu3UNISIha1cX8prQC8uR92bJluHTpkjKhqlatGo4cOYLvv/8+z6qBzs7OMDU1zbNPFP3x6tUrfP3119i+fTvatGkDQP5DRkxMDObPn48WLVoof2gKDAxU205AQIDGD0eA/P2kdOnSaNeuXYH9QURExc/b942f9K5GjRq4fPlynr+Em5ub499//8Xjx48xe/ZsNGrUCP7+/vmOeBSGr68vOnXqhG+++UYZz4MHD2BmZqYRj7OzMwDAz88Pp0+fVtvO2bNntTrWq1evwtXVVWPbDg4OyvWCg4Mxfvx4HD9+HFWqVFErEV25cmWMHDkS+/btQ6dOnbB69eo89xUQEKBx3sLx48cREBCgXcfkITAwEFlZWWpfkp88eYL4+Pg32m5BFM+DnMeSmZmJs2fPKvfp7++vUfZYm8fjdV7Xh/7+/rh9+zb+++8/ZXvuOMzNzREYGIjY2FiN7X/22WfYtGkTfvjhB1SsWFFj9Eox0hgcHJxvjO3atUN0dDQOHz6M6OhoxMTEaPwV9CW5Xr16iIiIUFu2b98+1KpVK99koV69erh06ZLaaOe+fftgYWGBmjVrKtc5fPiw2o8Z+/btg4eHB7y9vfONpzAyMjLQrVs3fPzxx5gxYwb69eun9pjkxcvLS/na8/LyAgC116NiWV4UI3wmuX60MjU1zfdHBnNzc9SsWVOjryMiIlC/fn0A8ud1ZmZmgdv19vaGh4cHrly5orZOfHy8RsxCCKxevRo9e/YsMPEjIqJiygBT/4oVnc9RysebVLXSt169eomQkBBx/vx5tb9bt24JIfI+RynnuSeKczYOHjwohBDiwoULwsrKSgwePFicP39exMfHiz/++EMMGTJECCGvamVubi6++uorcf36dfHHH3+IypUrq21XcY6SNhXOcsanEBMTIyQSiTh16pSQyWSiYcOGolq1amLPnj0iISFBHDt2TEyYMEFZYW7dunXCyspKrFmzRsTHx4vp06cLe3t7Ub16dbV+yn0u14sXL0SlSpVESEiIOHz4sLhx44aIiooSw4YNE3fu3BE3btwQ48aNE8ePHxc3b94Ue/fuFU5OTmL58uXi5cuX4osvvhAHDx4UN2/eFEePHhUVK1YUY8aMEUJonl+zfft2IZVKxYoVK0R8fLxYsGCBMDU1VfZ7fn3h4OAgVq9enW//tW/fXgQGBoojR46ImJgY0bJlS+Hr66ucP5xX5bitW7cKAK89R2nTpk0az6v09HQxfPhw4eHhIf7++29x+fJl0atXL1GqVCmRlJQkhBDixo0bQiqVijFjxogrV66IzZs3i3LlygkA4tmzZ8r96HqO0uv6MCsrS/j5+Ynw8HBx4cIFcfToUVG3bl2N8+W+/PJL8eGHH2rsLzs7W3h6egpzc3Mxe/ZsjfaDBw8KW1tb8eLFi3xjVmynsO8PN27cENbW1mLkyJEiNjZW/Pzzz0IqlYrff/9duc62bduEn5+f8nZWVpaoUqWKaN68uYiOjhaRkZGiXLlyytesEPJzeBQVKv/55x+xbds2YW9vL+bPn6+2f8XjXLNmTdG1a1dx/vx5cfnyZWV7enq6cp0yZcqI0aNHi/Pnz4urV68q1xk9erTw9vYWycnJIjs7WzRu3Fi0adNG6z7Q9RyljIwM4evrKxo1aiROnTolrl27JubPny8kEon466+/lPdr1qyZWLp0qfL2pk2bhFQqFT///LOIjY0VI0aMEDY2NsqqlkLIz9V67733xMGDB8WNGzfE6tWrhaWlpVi+fLlynUWLFgl7e3uxZcsWcfXqVTFx4kRhaWmpdl6gEEJERkYKACI2Nva1fcBzlEou9q9hsX8NqyT2ry7nKDFReksTJQAaf7169RJC6J4oCSEvzhAaGipsbW2FjY2NCAoKUjvBfMOGDcLb21tYWFiIevXqiZ07d+o1UcrOzhZNmzYVLVu2FELIT5AfOnSo8PDwEFKpVHh6eopu3bqJ27dvK+/zzTffCGdnZ2Frayv69u0rhg0bplZSOb+iF4mJiaJnz57C2dlZWFhYCB8fH9G/f3+RnJwsHjx4IDp06CDKlCkjzM3NhZeXl5g8ebLIzs4W6enp4pNPPlF+sfbw8BBDhgxRPn8KWx5c10RJUR7cwcFBWFlZifDw8DzLg+ekbaKU119CQoJ49eqVGDp0qLLPCioPbmFhIUJCQsSKFSsEALXXF4ACj+1NyoObm5sLf39/sWvXLmWp+pzrWFlZqSVtCpMmTRKmpqZ5Fk4YMGCAGDhwYL7xKrzp+0NUVJQIDg4W5ubmwtvbW6xYsUKtXVGgI6dbt26JNm3aCCsrK+Hk5CSGDBmiUQDl4sWLolGjRsLCwkK4u7uLqVOnapQGz+sxV5TSFyL/50aTJk2EEPLXvpmZmThy5IhabA4ODmrJRUEKU8whPj5edOrUSbi6ugpra2sRFBSk8dzw8vISU6ZMUVv2/fffCy8vL2Fubi5q1KghDh06pNaemJgoevfuLTw8PISlpaXw8/MTCxYs0Oi3WbNmiXLlyglra2tRr149teNX+PTTT0X9+vW16gMmSiUX+9ew2L+GVRL7V5dESSKEnk4kKKZSUlLg4OCA5ORk2Nvbq7WlpaUhISFBeZX2gshkMqSkpMDe3l5jWga9OX30b2hoKNzd3dVKPpOcMZ6/M2fOxMqVK3Hnzp0i2Z/CsWPH0LBhQ1y7dk2toMVHH32knFKZU//+/fHff/9h586dassfPXoEf39/nD17FhUqVChwn3x/MKx3oX91+TzSt8zMTOzevRutW7fmFEEDYP8aFvvXsEpi/xaUG+TGYg70Vnr58iVWrlyJ8PBwmJqaYuPGjYiMjNQ4/4CKzvLly1G7dm2ULl0ax44dw7x589SuxWUo27dvh62tLSpVqoRr165h+PDhaNCggVqSBADz5s1TS4aSk5Nx5swZrF+/Hn/88YfGdhMSErB8+fLXJklERERUMjFRoreSRCLB7t27MWPGDKSnp8PPzw9bt25FixYtjB3aO+vq1auYMWMGkpKSUL58eYwaNUpj9MYQnj9/jjFjxuDOnTtwdnZGixYtsGDBAo31vLy8MHToUOXt9u3b4/Tp0xg4cCBCQ0M11q9Tp06eJc6JiIjo3cBEid5KVlZWyuuaUPGwaNEiLFq0qMj327NnT/Ts2VPn++VVCpyIiIhIoWRO9iYiIiIiInoDTJSgvwtjEhERFQY/h4iIip93OlFSVO9QXLyQiIjIGBQXBjY1NTVyJEREpPBOn6NkamoKR0dHPHz4EABgbW0NiUSS57oymQwZGRlIS0srseVpjYn9a1jsX8Ni/xpWSe9fmUyGR48ewdraGmZm7/THMhFRsfLOvyO7u7sDgDJZyo8QAq9evYKVlVW+yRQVHvvXsNi/hsX+Nax3oX9NTExQvnz5Ent8RERvo3c+UZJIJChTpgxcXV2RmZmZ73qZmZk4fPgwGjduXGIuuFWcsH8Ni/1rWOxfw3oX+tfc3LxEjpYREb3N3vlEScHU1LTAueGmpqbIysqCpaVlif2gNib2r2Gxfw2L/WtY7F8iIjIGnROlmzdv4siRI7h58yZevnwJFxcXBAcHo169erC0tDREjEREREREREVK60Rpw4YN+O6773D69Gm4urqibNmysLKyQlJSEq5fvw5LS0t069YNY8eOhZeXlyFjJiIiIiIiMiitEqUaNWrAxMQEvXv3xm+//Yby5curtaenp+PEiRPYtGkTatWqheXLl6NLly4GCZiIiIiIiMjQtEqUpk+fjjZt2uTbbmFhgZCQEISEhGDGjBlISEjQW4BERERERERFTatEqaAkKTdnZ2c4OzsXOiAiIiIiIiJj07kWaXR0NP755x/l7T/++AMdOnTA119/rbyyOBERERER0dtM50Rp4MCBiI+PBwDcuHEDn3zyCaytrbFlyxaMGTNG7wESEREREREVNZ0Tpfj4eFSvXh0AsGXLFjRu3BgbNmzAmjVrsHXrVn3HR0REREREVOR0TpSEEJDJZACAyMhItG7dGgDg6emJx48f6zc6IiIiIiIiI9A5UapVqxZmzJiBX3/9FYcOHVIWekhISICbm5tO2zp8+DDatm0LDw8PSCQS7NixQ2OduLg4tGvXDg4ODrCzs8P777+P27dv6xo2ERERERGR1nROlBYvXozo6GgMGTIEEyZMgK+vLwDg999/R/369XXa1osXL1CtWjUsW7Ysz/br16+jYcOG8Pf3R1RUFC5cuIBJkybB0tJS17CJiIiIiIi0plV58JyCgoLUqt4pzJs3D6ampjptq1WrVmjVqlW+7RMmTEDr1q0xd+5c5TIfHx+d9kFERERERKQrnRMlAHj27Bl+//13XL9+HV999RWcnJwQGxsLNzc3lC1bVi+ByWQy/PXXXxgzZgzCw8Nx/vx5VKhQAePHj0eHDh3yvV96ejrS09OVt1NSUgAAmZmZyMzMLHQ8ivu+yTYof+xfw2L/Ghb717DYv4bF/jUs9q9hsX8NqyT2ry7HIhFCCF02fvHiRTRv3hyOjo64efMmrly5Ah8fH0yaNAm3bt3CL7/8onPAACCRSLB9+3ZlEvTgwQOUKVMG1tbWmDFjBpo2bYo9e/bg66+/xsGDB9GkSZM8tzN16lRMmzZNY/mGDRtgbW1dqNiIiIiIiOjt9/LlS3Tt2hXJycmwt7cvcF2dE6UWLVqgRo0amDt3Luzs7HDhwgX4+Pjg+PHj6Nq1K27evFmooHMnSvfv30fZsmXx6aefYsOGDcr12rVrBxsbG2zcuDHP7eQ1oqSoyPe6zihIZmYmIiIiEBoaCqlUWujtUN7Yv4bF/jUs9q9hsX8Ni/1rWOxfw2L/GlZJ7N+UlBQ4OztrlSjpPPXuzJkz+OGHHzSWly1bFg8ePNB1c/lydnaGmZkZAgMD1ZYHBATg6NGj+d7PwsICFhYWGsulUqleHmB9bYfyxv41LPavYbF/DYv9a1jsX8Ni/xoW+9ewSlL/6nIcOle9s7S0VJ73k9OVK1fg4uKi6+byZW5ujtq1a+PKlStqy+Pj4+Hl5aW3/RAREREREeWm84hS+/bt8c033+C3334DIJ8yd/v2bYwbNw4ffvihTttKTU3FtWvXlLcTEhIQExMDJycnlC9fHl999RU+/vhjNG7cWHmO0q5duxAVFaVr2ERERERERFrTeURp/vz5ePToEVxdXfHq1Ss0adIEvr6+sLOzw8yZM3Xa1tmzZxEcHIzg4GAAwJdffong4GBMnjwZANCxY0esXLkSc+fORdWqVfHTTz9h69ataNiwoa5hExERERERaU3nESV7e3scPXoUBw4cQHR0NGQyGWrUqIEWLVrovPOQkBC8rpZE37590bdvX523TUREREREVFiFuo4SADRr1gzNmjXTZyxERERERETFQqESpdOnTyMqKgoPHz6ETCZTa1u4cKFeAiMiIiIiIjIWnROlb7/9FhMnToSfnx/c3NwgkUiUbTn/JyIiIiIielvpnCgtWbIEq1atQu/evQ0QDhERERERkfHpXPXOxMQEDRo0MEQsRERERERExYLOidLIkSPx/fffGyIWIiIiIiKiYkHnqXejR49GmzZtULFiRQQGBkIqlaq1b9u2TW/BERERERERGYPOidLQoUNx8OBBNG3aFKVLl2YBByIiIiIiKnF0TpR++eUXbN26FW3atDFEPEREREREREan8zlKTk5OqFixoiFiISIiIiIiKhZ0TpSmTp2KKVOm4OXLl4aIh4iIiIiIyOh0nnr33Xff4fr163Bzc4O3t7dGMYfo6Gi9BUdERERERGQMOidKHTp0MEAYRERERERExYfOidKUKVMMEQcREREREVGxoXOipHDu3DnExcVBIpEgMDAQwcHB+oyLiIiIiIjIaHROlB4+fIhPPvkEUVFRcHR0hBACycnJaNq0KTZt2gQXFxdDxElERERERFRkdK56N3ToUKSkpODy5ctISkrC06dPcenSJaSkpGDYsGGGiJGIiIiIiKhI6TyitGfPHkRGRiIgIEC5LDAwEN9//z3CwsL0GhwREREREZEx6DyiJJPJNEqCA4BUKoVMJtNLUERERERERMakc6LUrFkzDB8+HPfv31cuu3fvHkaOHInmzZvrNTgiIiIiIiJj0DlRWrZsGZ4/fw5vb29UrFgRvr6+qFChAp4/f46lS5caIkYiIiIiIqIipfM5Sp6enoiOjkZERAT+/fdfCCEQGBiIFi1aGCI+IiIiIiKiIlfo6yiFhoYiNDQUAPDs2TN9xUNERERERGR0Ok+9mzNnDjZv3qy8/dFHH6F06dIoW7YsLly4oNfgiIiIiIiIjEHnROmHH36Ap6cnACAiIgIRERH4+++/0apVK3z11Vd6D5CIiIiIiKio6Tz1LjExUZko/fnnn/joo48QFhYGb29v1K1bV+8BEhERERERFTWdR5RKlSqFO3fuAJBffFZRxEEIgezsbP1GR0REREREZAQ6jyh16tQJXbt2RaVKlfDkyRO0atUKABATEwNfX1+9B0hERERERFTUdE6UFi1aBG9vb9y5cwdz586Fra0tAPmUvMGDB+s9QCIiIiIioqKmc6IklUoxevRojeUjRozQRzxERERERERGV6jrKF2/fh2LFy9GXFwcJBIJAgICMGLECPj4+Og7PiIiIiIioiKnczGHvXv3IjAwEKdPn0ZQUBCqVKmCU6dOITAwEBEREYaIkYiIiIiIqEjpPKI0btw4jBw5ErNnz9ZYPnbsWISGhuotOCIiIiIiImPQeUQpLi4O/fr101jet29fxMbG6iUoIiIiIiIiY9I5UXJxcUFMTIzG8piYGLi6uuojJiIiIiIiIqPSeepd//79MWDAANy4cQP169eHRCLB0aNHMWfOHIwaNcoQMRIRERERERUpnROlSZMmwc7ODgsWLMD48eMBAB4eHpg6dSqGDRum9wCJiIiIiIiKms6JkkQiwciRIzFy5Eg8f/4cAGBnZ6f3wIiIiIiIiIylUNdRUmCCREREREREJZHOidKTJ08wefJkHDx4EA8fPoRMJlNrT0pK0ltwRERERERExqBzotS9e3dcv34d/fr1g5ubGyQSiSHiIiIiIiIiMhqdE6WjR4/i6NGjqFatmiHiISIiIiIiMjqdr6Pk7++PV69eGSIWIiIiIiKiYkHnRGn58uWYMGECDh06hCdPniAlJUXtj4iIiIiI6G2n89Q7R0dHJCcno1mzZmrLhRCQSCTIzs7WW3BERERERETGoHOi1K1bN5ibm2PDhg0s5kBERERERCWSzonSpUuXcP78efj5+RkiHiIiIiIiIqPT+RylWrVq4c6dO4aIhYiIiIiIqFjQeURp6NChGD58OL766itUrVoVUqlUrT0oKEhvwRERERERERmDzonSxx9/DADo27evcplEImExByIiIiIiKjF0TpQSEhIMEQcREREREVGxoXOi5OXlZYg4iIiIiIiIig2dEyUAuH79OhYvXoy4uDhIJBIEBARg+PDhqFixor7jIyIiIiIiKnI6V73bu3cvAgMDcfr0aQQFBaFKlSo4deoU3nvvPURERBgiRiIiIiIioiKl84jSuHHjMHLkSMyePVtj+dixYxEaGqq34IiIiIiIiIxB5xGluLg49OvXT2N53759ERsbq5egiIiIiIjIeLJlAqcTkgAApxOSkC0TRo6o6OmcKLm4uCAmJkZjeUxMDFxdXfURExERERERGcmeS4loOOcA+q49AwDou/YMGs45gD2XEo0cWdHSeepd//79MWDAANy4cQP169eHRCLB0aNHMWfOHIwaNcoQMRIRERERURHYcykRg9ZFQwCwMFUtf5CchkHrorGiew20rFLGaPEVJZ0TpUmTJsHOzg4LFizA+PHjAQAeHh6YOnUqhg0bpvcAiYiIiIjI8LJlAtN2xSKvSXYCgATAtF2xCA10h6mJpIijK3o6JUpZWVlYv349Pv30U4wcORLPnz8HANjZ2RkkOCIiIiIiKhqnE5KQmJyWb7sAkJichtMJSahXsXTRBWYkOp2jZGZmhkGDBiE9PR2APEFikkRERERE9PZ7+Dz/JKkw673tdC7mULduXZw/f94QsRARERERkZG42lnqdb23nc7nKA0ePBijRo3C3bt3UbNmTdjY2Ki1BwUF6S04IiIiIiIqGnUqOKGMgyUeJKfleZ6SBIC7gyXqVHAq6tCMQudE6eOPPwYAtcINEokEQghIJBJkZ2frLzoiIiIiIioSpiYSTGkbiEHropG7VIPi9pS2ge9EIQegEIlSQkKCIeIgIiIiIiIja1mlDFZ0r4Fpu2KRlPpKudzdwRJT2ga+M6XBgUIkSl5eXoaIg4iIiIiIioGWVcogNNAdJ689xOO4k1jVqzbe93V9Z0aSFHROlAAgPj4eUVFRePjwIWQymVrb5MmT9RIYEREREREZh6mJBHUqOGF3nPzcpXctSQIKkSj9+OOPGDRoEJydneHu7g6JRNVpEomEiRIREREREb31dE6UZsyYgZkzZ2Ls2LGGiIeIiIiIiMjodL6O0tOnT9GlSxdDxEJERERERFQs6JwodenSBfv27TNELERERERERMWCVlPvvvvuO+X/vr6+mDRpEk6ePImqVatCKpWqrZvz+kpERERERERvI60SpUWLFqndtrW1xaFDh3Do0CG15RKJhIkSERERERG99bRKlHiRWSIiIiIiepfodI5SSkqKxnWTAEAmkyElJUVvQRERERERERmT1onS9u3bUatWLaSlpWm0paWloXbt2ti1a5degyMiIiIiIjIGrROlFStWYMyYMbC2ttZos7a2xtixY7Fs2TK9BkdERERERGQMWidKly5dQkhISL7tjRs3xj///KOPmIiIiIiIiIxK60Tp6dOnyMrKyrc9MzMTT58+1UtQRERERERExqR1ouTt7Y2zZ8/m23727Fl4eXnptPPDhw+jbdu28PDwgEQiwY4dO/Jdd+DAgZBIJFi8eLFO+yAiIiIiItKV1olSp06dMGHCBPz3338abQ8ePMDEiRPx4Ycf6rTzFy9eoFq1aq89t2nHjh04deoUPDw8dNo+ERERERFRYWh1HSUAGDduHP744w9UqlQJ3bt3h5+fHyQSCeLi4rB+/Xp4enpi3LhxOu28VatWaNWqVYHr3Lt3D0OGDMHevXvRpk0bnbZPRERERERUGFonSnZ2djh27BjGjx+PzZs3K89HKlWqFLp3745vv/0WdnZ2eg1OJpOhR48e+Oqrr/Dee+9pdZ/09HSkp6crbyuu75SZmYnMzMxCx6K475tsg/LH/jUs9q9hsX8Ni/1rWOxfw2L/Ghb717BKYv/qciwSIYTQdQdCCDx+/BhCCLi4uEAikei6Cc1AJBJs374dHTp0UC6bNWsWDh48iL1790IikcDb2xsjRozAiBEj8t3O1KlTMW3aNI3lGzZsyLO0ORERERERvRtevnyJrl27Ijk5Gfb29gWuq/WIUk4SiQQuLi6FCk5b586dw5IlSxAdHa1TIjZ+/Hh8+eWXytspKSnw9PREWFjYazujIJmZmYiIiEBoaCikUmmht0N5Y/8aFvvXsNi/hsX+NSz2r2Gxfw2L/WtYJbF/FbPNtFGoRKkoHDlyBA8fPkT58uWVy7KzszFq1CgsXrwYN2/ezPN+FhYWsLCw0FgulUr18gDrazuUN/avYbF/DYv9a1jsX8Ni/xoW+9ew2L+GVZL6V5fjKLaJUo8ePdCiRQu1ZeHh4ejRowf69OljpKiIiIiIiOhdYNREKTU1FdeuXVPeTkhIQExMDJycnFC+fHmULl1abX2pVAp3d3f4+fkVdahERERERPQO0eo6Sk5OTnj8+DEAoG/fvnj+/Lledn727FkEBwcjODgYAPDll18iODgYkydP1sv2iYiIiIiICkOrEaWMjAykpKTA2dkZa9euxZw5c/RSCjwkJAS6FN3L77wkIiIiIiIifdIqUapXrx46dOiAmjVrQgiBYcOGwcrKKs91V61apdcAiYiIiIiIippWidK6deuwaNEiXL9+HRKJBMnJyUhLSzN0bEREREREREahVaLk5uaG2bNnAwAqVKiAX3/9VaPQAhERERERUUmhc9W7hIQEQ8RBRERERERUbGhV9S63Q4cOoW3btvD19UWlSpXQrl07HDlyRN+xERERERERGYXOidK6devQokULWFtbY9iwYRgyZAisrKzQvHlzbNiwwRAxEhERERERFSmdp97NnDkTc+fOxciRI5XLhg8fjoULF2L69Ono2rWrXgMkIiIiIiIqajqPKN24cQNt27bVWN6uXTuev0RERERERCWCzomSp6cn9u/fr7F8//798PT01EtQRERERERExqTz1LtRo0Zh2LBhiImJQf369SGRSHD06FGsWbMGS5YsMUSMRERERERERUrnRGnQoEFwd3fHggUL8NtvvwEAAgICsHnzZrRv317vARIRERERERU1nRMlAOjYsSM6duyo71iIiIiIiIiKhUJdR4mIiIiIiKgkY6JERERERESUCxMlIiIiIiKiXJgoERERERER5aJTopSZmQkfHx/ExsYaKh4iIiIiIiKj0ylRkkqlSE9Ph0QiMVQ8RERERERERqfz1LuhQ4dizpw5yMrKMkQ8RERERERERqfzdZROnTqF/fv3Y9++fahatSpsbGzU2rdt26a34IiIiIiIiIxB50TJ0dERH374oSFiISIiIiIiKhZ0TpRWr15tiDiIiIiIiIiKjUKVB8/KykJkZCR++OEHPH/+HABw//59pKam6jU4IiIiIiIiY9B5ROnWrVto2bIlbt++jfT0dISGhsLOzg5z585FWloaVq5caYg4iYiIiIiIiozOI0rDhw9HrVq18PTpU1hZWSmXd+zYEfv379drcERERERERMag84jS0aNHcezYMZibm6st9/Lywr179/QWGBERERERkbHoPKIkk8mQnZ2tsfzu3buws7PTS1BERERERETGpHOiFBoaisWLFytvSyQSpKamYsqUKWjdurU+YyMiIiIiIjIKnafeLVq0CE2bNkVgYCDS0tLQtWtXXL16Fc7Ozti4caMhYiQiIiIiIipSOidKHh4eiImJwcaNGxEdHQ2ZTIZ+/fqhW7duasUdiIiIiIiI3lY6J0oAYGVlhb59+6Jv3776joeIiIiIiMjoCpUoXblyBUuXLkVcXBwkEgn8/f0xZMgQ+Pv76zs+IiIiIiKiIqdzMYfff/8dVapUwblz51CtWjUEBQUhOjoaVatWxZYtWwwRIxERERERUZHSeURpzJgxGD9+PL755hu15VOmTMHYsWPRpUsXvQVHRERERERkDDqPKD148AA9e/bUWN69e3c8ePBAL0EREREREREZk86JUkhICI4cOaKx/OjRo2jUqJFegiIiIiIiIjImrabe7dy5U/l/u3btMHbsWJw7dw7vv/8+AODkyZPYsmULpk2bZpgoiYiIiIiIipBWiVKHDh00li1fvhzLly9XW/bFF1/g888/10tgRERERERExqJVoiSTyQwdBxERERERUbGh8zlKREREREREJV2hLjh7+vRpREVF4eHDhxqjTQsXLtRLYERERERERMaic6L07bffYuLEifDz84ObmxskEomyLef/REREREREbyudE6UlS5Zg1apV6N27twHCISIiIiIiMj6dz1EyMTFBgwYNDBELERERERFRsaBzojRy5Eh8//33hoiFiIiIiIioWNB56t3o0aPRpk0bVKxYEYGBgZBKpWrt27Zt01twRERERERExqBzojR06FAcPHgQTZs2RenSpVnAgYiIiIiIShydE6VffvkFW7duRZs2bQwRDxERERERkdHpfI6Sk5MTKlasaIhYiIiIiIiIigWdE6WpU6diypQpePnypSHiISIiIiIiMjqdp9599913uH79Otzc3ODt7a1RzCE6OlpvwRERERERERmDzolShw4dDBAGERERERFR8aFzojRlyhRDxEFERERERFRs6HyOEhERERERUUmn84iSiYlJgddOys7OfqOAiIiIiIiIjE3nRGn79u1qtzMzM3H+/HmsXbsW06ZN01tgRERERERExqJzotS+fXuNZZ07d8Z7772HzZs3o1+/fnoJjIiIiIiIyFj0do5S3bp1ERkZqa/NERERERHR2ywjA4iKAr7+Gvj2W2NHozOdR5Ty8urVKyxduhTlypXTx+aIiIiIiOhtIwRw9Sqwdy+wbx9w8CDw4oW8rVw5YPx4oIBaB8WNzolSqVKl1Io5CCHw/PlzWFtbY926dXoNjoiIiIjoXZEtEzidkISHz9PgameJOhWcYGpSzBOLZ8+A/fvlidHevcCtW+rtrq5AWJj8TyYDTE2NEmZh6JwoLV68WO22iYkJXFxcULduXZQqVUpfcRERERERvTP2XErEtF2xSExOUy4r42CJKW0D0bJKGSNGlktWFnDmjCoxOnVKngApmJsDDRsC4eHy5CgoCDB5O69IpHOi1KtXL0PEQURERET0TtpzKRGD1kVD5Fr+IDkNg9ZFY0X3GsZNlm7dkk+j27tXPnr07Jl6u7+/KjFq0gSwsTFKmPqmdaJ0+/ZtrdYrX758oYMhIiIiInqXZMsEpu2K1UiSAEAAkACYtisWoYHuRTcNLzUVOHQIJn//jebbt0N6/756e6lSQIsWqil1JfT7v9aJkre3d54XmhVCKJdLJBJkZWXpLzoiIiIiohLsdEKS2nS73ASAxOQ0nE5IQr2KpQ0ThEwGxMSoptMdOwZkZsIUgC0AYWoKyfvvy5Oi8HCgVq236lyjwtI6UTp//nyey4UQ2LRpE7777jvY2trqLTAiIiIiopLu4fP8k6TCrKe1xEQgIkKeGEVEAI8eqbd7eyM7NBTnnJwQPGoUpC4u+t3/W0DrRKlatWoayyIjIzFu3DjEx8djzJgxGD16tF6DIyIiIiIqyVztLPW6Xr7S0oCjR1Wluy9eVG+3tQWaNVNNp/P1hSwrC4m7dyPY0fHN9v2WKtR1lM6dO4dx48bhyJEj+Oyzz7B79264urrqOzYiIiIiohKtTgUnlHGwxIPktDzPU5IAcHeQlwrXiRBAbKxqOt2hQ/JkSblhCVCzpmo63fvvyyvWkZJOidK1a9cwYcIEbN26FR999BFiY2Ph4+NjqNiIiIiIiEo0UxMJprQNxKB10ZAAasmSojrAlLaB2hVyePIEiIxUjRrdu6fe7uGhSoxatACcnfV0FCWT1onS4MGD8fPPP6Np06Y4e/YsqlevbsCwiIiIiIjeDS2rlMGK7jU0rqPk/rrrKGVmAidPqhKjs2flI0kKlpbyct2K6XTvvScfSSKtaJ0orVy5EpaWlnj48CH69u2b73rR0dF6CYyIiIiI6F3RskoZhAa643RCEh4+T4OrnXy6ncZI0rVrqul0Bw8Cz5+rt1etqkqMGjUCrKyK7iBKGK0TpSlTphgyDiIiIiKid5qpiUSzBHhysupir/v2ATduqLc7OwOhofLpdKGh8ul1pBdMlIiIiIiIiovsbODcOVVidOKEfJmCVAo0aKA616h6dcDExGjhlmSFqnpHRERERER6cueOPCnat09ejCEpSb29cmVVYtSkCWBnZ5w43zFMlIiIiIiIitKLF8Dhw6pRo7g49XYHB3lVOsW5Rt7eRgnzXcdEiYiIiIjIkISQX+BVkRgdOQJkZKjaTUyAunVVo0a1awNm/JpubHwEiIiIiIj07b//gIgI1ZS6//5Tby9fXp4UhYcDzZoBpUoZJ07Kl1aJkpOTE+Lj4+Hs7Iy+fftiyZIlsOPcSCIiIiIiufR04Ngx1ahRTIx6u40N0LSpajpd5cq8plExp1WilJGRgZSUFDg7O2Pt2rWYM2cOEyUiIiIiencJAVy5okqMoqKAly/V16lRQzWdrl49wMLCKKFS4WiVKNWrVw8dOnRAzZo1IYTAsGHDYJXPxatWrVql9c4PHz6MefPm4dy5c0hMTMT27dvRoUMHAEBmZiYmTpyI3bt348aNG3BwcECLFi0we/ZseLA+PBEREREVtaQkYP9+1QVf79xRb3d3VyVGLVoArq7GiZP0QqtEad26dVi0aBGuX78OiUSC5ORkpKWlvfHOX7x4gWrVqqFPnz748MMP1dpevnyJ6OhoTJo0CdWqVcPTp08xYsQItGvXDmfPnn3jfRMRERERFSgrCzh1SjVqdOYMIJOp2i0sgMaNVdPpqlbldLoSRKtEyc3NDbNnzwYAVKhQAb/++itKly79mnu9XqtWrdCqVas82xwcHBAREaG2bOnSpahTpw5u376N8uXLv/H+iYiIiIjUJCSoEqP9+4GUFPX2995TjRo1agRYWxsnTjI4naveJSQkGCIOrSQnJ0MikcDR0THfddLT05Genq68nfL/T+7MzExkZmYWet+K+77JNih/7F/DYv8aFvvXsNi/hsX+NSz2r2HppX+fP4ckKgqSyEiYRERAcu2aWrNwcoJo3hyysDCI5s2BcuVyB1H4fRdzJfH5q8uxSIQQQtcdHDp0CPPnz0dcXBwkEgkCAgLw1VdfoVGjRrpuShWIRKJ2jlJuaWlpaNiwIfz9/bFu3bp8tzN16lRMmzZNY/mGDRtgzYyfiIiI6N0mk8Hxxg24nj8Pl5gYOP37L0yys1XNpqZI8vPDo+BgPKxeHc98fABTUyMGTPr08uVLdO3aFcnJybC3ty9wXZ0TpXXr1qFPnz7o1KkTGjRoACEEjh8/ju3bt2PNmjXo2rVroYIuKFHKzMxEly5dcPv2bURFRRV4UHmNKHl6euLx48ev7YyCZGZmIiIiAqGhoZBKpYXeDuWN/WtY7F/DYv8aFvvXsNi/hsX+NSyt+/fePdWI0f79kDx5otYsfH0ha94cIjQUIiQEeIPvjMYWGfcfZv/9Lx6kqOoJuNtbYlwrf7QIcNNpWyXx+auo5K1NoqTz1LuZM2di7ty5GDlypHLZ8OHDsXDhQkyfPr3QiVJ+MjMz8dFHHyEhIQEHDhx47QFZWFjAIo/Si1KpVC8PsL62Q3lj/xoW+9ew2L+Gxf41LPavYbF/DUujf1+9Ag4fVlWnu3xZ/Q52dkDz5vLzjMLCIPHxQUkYM9pzKRGDN1yAfBREVVTi9tN0DN5wASu610DLKmV03m5Jev7qchw6J0o3btxA27ZtNZa3a9cOX3/9ta6bK5AiSbp69SoOHjyolwISRERERFTCCAH884+qCMPhw/ILwCpIJEDt2srECHXrAiXki79Ctkxg2q5Y5DVVTECeNk3bFYvQQHeYmrAynzZ0TpQ8PT2xf/9++Pr6qi3fv38/PD09ddpWamoqruU4YS4hIQExMTFwcnKCh4cHOnfujOjoaPz555/Izs7GgwcPAABOTk4wNzfXNXQiIiIiKikePYLk778RvGYNzAYNAhIT1dvLlZMnRuHh8tEjJyfjxFlETickITE5/8v3CACJyWk4nZCEehU5+KANnROlUaNGYdiwYYiJiUH9+vUhkUhw9OhRrFmzBkuWLNFpW2fPnkXTpk2Vt7/88ksAQK9evTB16lTs3LkTAFC9enW1+x08eBAhISG6hk5EREREb6uMDOD4cdV0uuhomAFQXjDGygoICVGNGvn7v1PXNHr4XLtrnGq7HhUiURo0aBDc3d2xYMEC/PbbbwCAgIAAbN68Ge3bt9dpWyEhISiolkQhCvIRERERUUkgBHD1qioxOngQePFCfZWgIFzz8UGFzz+HWUiI/AKw7yhXO0u9rkeFSJQAoGPHjujYsaO+YyEiIiKid9mzZ8CBA6pzjW7eVG93dZWPFoWFAaGhyCpdGrG7d8O7WbMSd86RrupUcEIZB0s8SE7L8zwlCQB3B0vUqVCypyDqU6ESJSIiIiKiN5aVBZw5oxo1OnUKkMlU7ebmQMOG8sQoPBwICgJMTFTtJehCqG/K1ESCKW0DMWhdNCSAWrKkmIA4pW0gCznogIkSERERERWdW7dUidH+/fJRpJz8/VWJUZMmgI2NUcJ8G7WsUgYrutfAtF2xaoUd3B0sMaVtYKFKg7/LmCgRERERkeGkpgJRUarkKD5evd3REWjRQp4YhYYCXl7GiLLEaFmlDEID3XE6IQkPn6fB1U4+3Y4jSbpjokRERERE+iOTATExqsTo2DH1KXKmpvLrGClGjWrXli8jvTE1kbAEuB4wUSIiIiKiN5OYKE+M9u0DIiKAR4/U2729VWW7mzWTjyIRFXM6J0qKax3lJpFIYGlpCV9fX7Rv3x5OJfyiXkRERETvrLQ04MgR1ajRP/+ot9vYyBMixaiRr+87dU0jKhl0TpTOnz+P6OhoZGdnw8/PD0IIXL16FaampvD398fy5csxatQoHD16FIGBgYaImYiIiIiKkhBAbKwqMTp0SJ4s5VSzpioxqldPXrGO6C2mc6KkGC1avXo17O3tAQApKSno168fGjZsiP79+6Nr164YOXIk9u7dq/eAiYiIiKgIPHkCREaqrml07556e5kyqul0LVoALi7GiZPIQHROlObNm4eIiAhlkgQA9vb2mDp1KsLCwjB8+HBMnjwZYWFheg2UiIiIiAwoMxM4eVKVGJ09Kx9JUrC0BBo3Vl3wtUoVTqejEk3nRCk5ORkPHz7UmFb36NEjpKSkAAAcHR2RkZGhnwiJiIiIyDCuX1clRgcOAM+fq7dXqaIaNWrUCLCyMk6cREZQqKl3ffv2xYIFC1C7dm1IJBKcPn0ao0ePRocOHQAAp0+fRuXKlfUdKxERERG9iZQUeUKkONfoxg31dmdn+bWMFKNGHh7GiZOoGNA5Ufrhhx8wcuRIfPLJJ8jKypJvxMwMvXr1wqJFiwAA/v7++Omnn/QbKRERERHpJjsbOHdOVbr7xAng/7+/AQDMzIAGDVRFGIKDARMT48VLVIzonCjZ2trixx9/xKJFi3Djxg0IIVCxYkXY2toq16levbo+YyQiIiIibd29qxoxiowEkpLU2ytVUiVGISGAnZ1RwiQq7gp9wVlbW1s4OTlBIpGoJUlEREREVIRevpSX61YkR3Fx6u0ODkDz5qrpdBUqGCdOoreMzomSTCbDjBkzsGDBAqSmpgIA7OzsMGrUKEyYMAEmHK4lIiIiMhwhgIsXVYnRkSNAziJaJiZAnTqqUaM6deRT7IhIJzq/aiZMmICff/4Zs2fPRoMGDSCEwLFjxzB16lSkpaVh5syZhoiTiIiI6N318CEQESFPjCIigAcP1Ns9PeVJUXg40KwZ4ORknDiJShCdE6W1a9fip59+Qrt27ZTLqlWrhrJly2Lw4MFMlIiIiIjeVHo6cPy4qnT3+fPq7dbWQNOmqlGjypV5TSMjypYJnE5IwsPnaXC1s0SdCk4wNeHj8bbTOVFKSkqCv7+/xnJ/f38k5T5ZkIiIiIheTwjgyhVVdbqDB+XnHuUUHKxKjOrXBywsjBMrqdlzKRHTdsUiMTlNuayMgyWmtA1EyypljBgZvSmdE6Vq1aph2bJl+O6779SWL1u2DNWqVdNbYEREREQl2tOnwP79qlGj27fV293cVIlRixby21Ss7LmUiEHroiFyLX+QnIZB66KxonsNJktvMZ0Tpblz56JNmzaIjIxEvXr1IJFIcPz4cdy5cwe7d+82RIxEREREb7+sLODUKdWo0enTgEymajc3Bxo3VlWnCwridLoiUNhpc9kygWm7YjWSJAAQACQApu2KRWigO6fhvaV0TpSaNGmC+Ph4fP/99/j3338hhECnTp0wePBgePDqzUREREQqN2/Ca+9emK5eLZ9Ol5Ki3h4YqBo1atxYfu4RFZk3mTZ3OiFJ7X65CQCJyWk4nZCEehVL6ytkKkKFqhXp4eGhUbThzp076Nu3L1atWqWXwIiIiIjeOs+fA1FRyul00qtXUT1nu5OTfBpdeDgQGiqvVkdG8abT5h4+zz9JKsx6VPzorah+UlIS1q5dy0SJiIiI3h0ymbwineI8o+PHgcxMZbMwM0NSpUpw/PhjmLZqBdSsCZiaGjFgAvQzbc7VzlKrfWm7HhU/vPoYERERkS7u31edZxQRATx+rN5esaJyOl1Ww4Y4evQoWrduDVOp1DjxkgZ9TJurU8EJZRws8SA5Lc+ESwLA3UF+zhO9nZgoERERERXk1SvgyBHVqNGlS+rtdnbyi7yGh8sTpIoVVW05Rpeo+NDHtDlTEwmmtA3EoHXRkABqyZJiDGpK20AWcniLMVEiIiIiykkI4PJlVWJ0+DCQluMLs0QC1KqlSozefx/gaNFbRV/T5lpWKYMV3WtoFIRw53WUSgStE6VOnToV2P7s2bM3jYWIiIjIOB49AiIjVclRYqJ6e9my8sQoPBxo3hwozSpmbzN9TptrWaUMQgPdC1VinIo3rRMlBweH17b37NnzjQMiIiIiMriMDODECVViFB0tH0lSsLICmjRRjRoFBPCaRiWIvqfNmZpIWAK8BNI6UVq9erUh4yAiIiIyHCGAa9dUidHBg0Bqqvo6QUGqxKhhQ8CS1cqKM8WFYgF5cYb3fV11GsXhtDl6HZ6jRERERCXTs2fAgQPyxGjvXuDmTfV2FxfVxV5btADK8Ivx20Jxodik1FeYWwfou/YMnGytdE5wOG2OCqJVovT5559jwoQJ8NTiomibN29GVlYWunXr9sbBEREREWktOxs4c0aVGJ06JV+mIJXKR4oUo0bVqgEmJsaLlwol54ViLXJckkrbC8XmxmlzlB+tEiUXFxdUqVIF9evXR7t27VCrVi14eHjA0tIST58+RWxsLI4ePYpNmzahbNmy+N///mfouImIiIiA27dV0+kiI+WjSDn5+akSo5AQwMbGGFGSnujjQrFE2tIqUZo+fTqGDh2Kn3/+GStXrsSlXNcPsLOzQ4sWLfDTTz8hLCzMIIESERER4cULICpKNWp05Yp6u6OjfBpdWJj8z8vLGFHSayjOL9J1ups+LhRLpC2tz1FydXXF+PHjMX78eDx79gy3bt3Cq1ev4OzsjIoVK0LCSjBERESkbzIZcOGCKjE6elT9Iq6mpkDduqpRo9q15cuo2FKcX5Qz4SmjZQEFfVwolkhbhSrm4OjoCEdHRz2HQkRERATgwQN5YrRvHxARATx8qN7u7a1KjJo1k48iUZEo7EiQQs7zi3LS9vwifV0olkgbrHpHRERExpWWJh8pUowaXbyo3m5rCzRtqkqOfH15TSMjeJORIEA/5xfp80KxRK/DRImIiIiKlhBAXJwqMTp0CHj1StUukQA1aqgSo3r1AHNz48VLbzwSBOjn/KLcF4rNqTAXiiUqCBMlIiIiMrwnT+RV6RRT6u7eVW/38FAVYGjRQn6NIyoW9FVpTl/nF+W8UGxSqirB5oViSd+YKBEREZH+ZWYCJ0+qRo3OnpWPJClYWgKNG6su+Pree5xOV0zpq9KcPs8vUlwo9uS1h3gcdxKretXG+76uHEkivdI5UWrWrBm2bdumUcwhJSUFHTp0wIEDB/QVGxEREb1Nrl9XJUYHDgDPn6u3V6miSowaNQKsrIwTJ+lEXyNB+j6/yNREgjoVnLA7DjoXlSDShs6JUlRUFDIyMjSWp6Wl4ciRI3oJioiIiN4CKSnAwYOqC75ev67eXro0EBoqT4xCQ4GyZY0TJ70RfY0E5T6/KGeyxPOLqDjSOlG6mKMCTWxsLB48eKC8nZ2djT179qAs3wCJiIhKruxsIDpalRidOAFkZanazcyA+vVVRRhq1ABMTIwXbwnxpiW535Q+R4Jynl+Uczofzy+i4kjrRKl69eqQSCSQSCRo1qyZRruVlRWWLl2q1+CIiIjIyO7eVb+mUVKSeruvryoxatoUsLMzTpwl1JuW5NYHfY8EKc4vMmbyR6QNrROlhIQECCHg4+OD06dPwyVHNRpzc3O4urrClFfCJiIieru9fAkcPqw61yg2Vr3d3h5o3lxVoc7HxzhxvgP0UZJbX/Q9EmRqIimw8ANRcaB1ouTl5QUAkMlkBguGiIiIipgQsL95EyYLF8rLdx85AqSnq9pNTIDatVWjRnXryqfYkUHpqyR3zu296QgOR4LoXaPzO93atWvh7OyMNm3aAADGjBmD//3vfwgMDMTGjRuVCRUREREVUw8fypOivXthtm8fmuY47xgA4OmpSoyaNwectKtCRuoUyQkgL7GtS/lqfZXkBvQ7fY8jQfQu0fkMy2+//RZW/1/O88SJE1i2bBnmzp0LZ2dnjBw5Uu8BEhER0RvKyJBXpxs/Xl5gwc0N6NYN+OUXSB48QJaFBWStWgGLFwNxccCtW8CPPwJdujBJKqQ9lxLRcM4B9F17BgDQd+0ZNJxzAHsuJWp1f32V5FZM38uddCmm72kbD9G7SOcRpTt37sDX1xcAsGPHDnTu3BkDBgxAgwYNEBISou/4iIiISFdCAPHxqvOMoqKAFy/U16leHQgLQ1bz5vg7JQUt27eHiVRqjGhLnJznFlnkOH1bl3OL9FGSW9/T94jeNTonSra2tnjy5AnKly+Pffv2KUeRLC0t8erVK70HSERERFp4+lR+kVdF6e5bt9Tb3dxUBRhCQ+W3AYjMTMh27zZCwCWTvpITfZTk1uf0PaJ3kc6JUmhoKD777DMEBwcjPj5eea7S5cuX4e3tre/4iIiIKC9ZWcCZM6rE6NQpIGfBJXNzoFEjeWIUHg5UrcprGhUBfSUn+ijJra/pe0TvKp0Tpe+//x4TJ07EnTt3sHXrVpQuLX+Rnzt3Dp9++qneAyQiIqL/d/Omajrd/v1AcrJ6e0CAqghDkyaAtbVRwnzbvUmFOH0mJ29aklsf0/eI3mU6J0qOjo5YtmyZxvJp06bpJSAiIiL6f6mp8vOLFKNG8fHq7aVKyafRKabUeXoaJczi5E3LYL9phTh9JydvUpJbH9P3iN5lhboQwrNnz/Dzzz8jLi4OEokEAQEB6NevHxwcHPQdHxER0btDJgPOn5cnRfv2AceOAZmZqnZTU6BePdV0upo15csIwJsnOfq4wKshkpPCluTWx/Q9oneZzpOVz549i4oVK2LRokVISkrC48ePsWjRIlSsWBHR0dGGiJGIiKjkun8fWLsW6NpVXmChVi3g66/lI0mZmUCFCsDnnwPbtwNPnsgvCDtpElCnDpOkHN60DPbrijAA8iIM2bK81lBRJCeAKhlRMEZyopi+5+6gPoLl7mCpVeJH9C7TeURp5MiRaNeuHX788UeY/f+VubOysvDZZ59hxIgROHz4sN6DJCIiKjFevQKOHlVNp/vnH/V2OzugWTPVdLr/vyRHSfcmU+b0UWlOnxXicp5blJSqqgis7blF+vYm0/eI3mU6J0pnz55VS5IAwMzMDGPGjEGtWrX0GhwREdFbTwggNlaVGB06BKTl+EIukchHkRTT6d5/H3jHrmf0plPm9JHk6LtCnCI5OXntIR7HncSqXrXxvq+r0ZKTwk7fI3qX6Zwo2dvb4/bt2/D391dbfufOHdjZ2ektMCIiorfW48dAZKTqXKN799Tby5ZVJUbNmwPOzsaJU0/eZDRIH+cF6SPJMUSFOFMTCepUcMLuOHAEh+gtpHOi9PHHH6Nfv36YP38+6tevD4lEgqNHj+Krr75ieXAiIno3ZWQAJ0+qRo3OnZOPJClYWsrLdYeHy/8CAuQjSSXAm4wG6evirPpIclghjohy0zlRmj9/PiQSCXr27ImsrCwAgFQqxaBBgzB79my9B0hERFTsCAFcv65KjA4ckJfyzikoSHWeUaNG8mSphHnT0SB9nRekjySHFeKIKDedEyVzc3MsWbIEs2bNwvXr1yGEgK+vL6x5UTsiIirJkpPlCZHigq8JCertzs6qxCgsDChT/KuJKabMAfKkRZdzaPQxGqSv84L0leS86QVeiahk0TpRys7OxuXLl1GpUiVYWVnB2toaVatWBQC8evUKFy9eRJUqVWBionPFcSIiouInOxs4e1aVGJ08KV+mIJUCDRrIp9KFhQHVqwNF9Bn4phdVBVRT5pJSX2FuHaDv2jNwsrUq0gIK+jwvSF9JDivEEZGC1onSr7/+imXLluHUqVMabebm5ujbty9GjBiB7t276zVAIiKiInPnjmo6XWQk8PSperufn2rEKCQEsLUt8hDftEKcYhuKKXMWOS7FVNQFFPR9XpC+khxWiCMiQIdE6eeff8bo0aNhmsfF7UxNTTFmzBgsW7aMiRIREb09XryQl+tWjBr9+696u4MD0KKFfNQoNBTw9jZKmAr6qBBXnAooGOK8ICY5RKQvWidKV65cwfvvv59ve+3atREXF6eXoIiIiAxCJgMuXlSNGh09Kq9Yp2BiIr+OkWLUqHZtwEzn03kNQl8JTnEqoADwvCAiKr60fvd/8eIFUlJS8m1//vw5Xr58qZegiIiI9ObBAyAiQp4YRUQA//2n3u7lpSrb3awZ4OholDBfR18JTnEroADwvCAiKp60TpQqVaqE48ePIygoKM/2o0ePolKlSnoLjIiIqFDS0oBjx1TT6S5cUG+3sQGaNlUVYahUqUivaVTYQgz6SnCKYwEFgFPmiKj40TpR6tq1KyZOnIj69etrJEsXLlzA5MmTMWbMGL0HSEREVCAh5OcWKabTRUUBr16pr1Ojhioxql8fMDc3SqhvUohBXwlOcS2gQERU3GidKI0cORJ///03atasiRYtWsDf3x8SiQRxcXGIjIxEgwYNMHLkSEPGSkREJPfkCbB/vzwx2rdPXq0upzJl5ElReDjQogWySzurvsjfeW6UL/JvWohBXwlO7ilzubcBsIACERGgQ6IklUqxb98+LFq0CBs2bMDhw4chhEDlypUxc+ZMjBgxAlKp1JCxEhHRO0qSlQXJsWOq5OjMGflIkoKFBdC4sWrUqEoV5XS6PZcSMe2nA29UTht4s2sX6aMQg77PCVJMmUtKVY2+sYACEZGKTqV8pFIpxowZwyl2RERkeDduAHv3wnTPHrSKjIRZ7oJBVaqoRo0aNQKsrDQ2oY9y2ortvMm1i/RViEGf5wQppsydvPYQj+NOYlWv2njf15VT5oiI/l/xqHlKRESUkgIcPKgqwnD9OgDA5P//ROnSkISGqq5pVLZsgZvTVzltfSRb+irEAOj3nCBTEwnqVHDC7jjwvCIiolyYKBERkXFkZwPR0aoiDCdOAFlZqnYzM4j69XG7ZgPcLFsaZm264v3KBSc1OeljFKc4XZw1J54TRERkeEyUiIio6Ny9qyrAEBkpL8qQk6+v8jyjCLcATD5wG0mprzDXNxtjfj0HJ1srraeY6WMUp7hdnJWIiIoOEyUiIjKcly+Bw4dV0+liY9Xb7e2B5s3l5xqFhQE+PgDUp7tZmKpW12W6mz5GcYrjxVmJiKhoMFEiIiL9EQL45x9VYnTkCJCermo3MQFq11ZVp6tbFzBT/yjS13Q3fYziFNeLsxIRkeFplSh9+eWXWm9w4cKFhQ6GiIjeQg8fAhERqil1Dx6oNaeXKQtp65YwCQ+Xjx45FTy9TF/T3fQxisOLsxIRvbu0SpTOnz+v1cYkEr7RExGVeBkZwLFjqlGjXJ8RWVZWOFW+KiLLVcNh7xq4XrocyjhaYUpAIFq+JkkC9F8h7k1GcQwxZY6FGIiI3g5aJUoHDx40dBxERFRcCQHEx6sSo6go4MUL9XWqVwfCwnC6ci30iJMi3Uz9AuRFfW5RTm86isMpc0RE7yajnqN0+PBhzJs3D+fOnUNiYiK2b9+ODh06KNuFEJg2bRr+97//4enTp6hbty6+//57vPfee8YLmoiohMuWCZyLuQHsj4TXuWNwPXkYklu31FdydVVd7LVFC8DdHdkygeFzDiDdTHOkp6jPLcrtTUdxOGWOiOjdU6hE6cyZM9iyZQtu376NjIwMtbZt27ZpvZ0XL16gWrVq6NOnDz788EON9rlz52LhwoVYs2YNKleujBkzZiA0NBRXrlyBnZ1dYUInIqK8ZGUBp0/j2rqtePXn36h59wpMhUzZLJOaw6RRQ1URhqAgeWGGHAx1blFOxqwQxylzRETvFp0TpU2bNqFnz54ICwtDREQEwsLCcPXqVTx48AAdO3bUaVutWrVCq1at8mwTQmDx4sWYMGECOnXqBABYu3Yt3NzcsGHDBgwcOFDX0ImISrRsmdBtxOPmTdV0uv37geRk+OZovuZUDocr1MCRCsE45VkVC/vWL3CamaHOLUpKfaVczuluRERUVHROlL799lssWrQIX3zxBezs7LBkyRJUqFABAwcORJky+vvgSkhIwIMHDxAWFqZcZmFhgSZNmuD48eP5Jkrp6elIz1GKNiUlBQCQmZmJzMzMQsejuO+bbIPyx/41LPav4WTLBM7ceAQAOHntIWr7uBhlOlZk3H+Y/fe/eJCS4xwae0uMa+WPFgFu8gWpqZAcOgRJRARMIiIguXpVbRspVnY45hWEoz7BOFYhGIkOrso2CYBZf11GSKXS+R6fs7UZLEzzmiynuZ42z8Xmfs4IqdQIZ248QlL8WfzUPVjZv3wu6w/fHwyL/WtY7F/DKon9q8uxSIQQr/9Uy8HGxgaXL1+Gt7c3nJ2dcfDgQVStWhVxcXFo1qwZEhMTdQ4YkFfMy3mO0vHjx9GgQQPcu3cPHh4eyvUGDBiAW7duYe/evf/X3r3HRV3l/wN/zQz3a6Ig4A3EC3LxhjfEu4KmGWYPs2wL87u1ZW1kpq2WipWbVmq2bdqapmWtWV5+W5mKhCCiolxSAu+Y5g6iooAh1zm/P2ZnhhluM/AZZsDX8/HgkXzOZz5z5u15GG/OOe9T53Pi4uKwfPnyWte//vprODk5NalvREStkkoF97w8eGVlwTMzE+3PnIG8qkrXLJfjdu/eKOjfHzcGDMDtgABAoWjggURERK1baWkpZs2ahaKiIri5uTV4r8kzSh4eHigpKQEAdOrUCdnZ2QgNDcWdO3dQWlratB43wLDkuBCiwTLkixYt0jv3qbi4GF26dEFUVFSjwWhIZWUl4uPjERkZCVtb28ZfQCZhfM2L8ZXewdzrmPdNFgQAe7nA24NUWHJSjgqV+t+ntTP762ZyGlGtEkj/7TZu3i1HBxd7hHVrZ/SsVLVKYOKHydqZJM+7hRiel4WRlzIwPC8L7UuL9O4X/v5QRUZCTJgAMXYs3Nzd4Qbg3GklFu481ej7vfdoX0wOrX/1gCYuQN2ltE2JiwbHr3kxvubF+JoX42tebTG+mtVmxjA5URo5ciTi4+MRGhqKxx57DLGxsfj5558RHx+P8ePHm/q4enl7ewMA8vPz9Zb0FRQUoGPH+v8na29vD3t7+1rXbW1tJfkLluo5VDfG17wYX2lUqwTe+vEsyqr1k5lylQzl1TLIALz141lEhXRqNOHZl62sVXbax4R9OOk519Al4xhmXc7EqLwM9LlxWa/9rp0jjnbti4Anp6P7n6ZDFhAARR2/bPJyd0Z5dePJmZe7c4Nj6MG+nSGTK5r1merD8WtejK95Mb7mxfiaV1uKrymfw+RE6eOPP0ZZmfp/fosWLYKtrS1SUlIwffp0LFmyxNTH1cvf3x/e3t6Ij4/HgAEDAAAVFRVISkrCqlWrJHsfIro/mVz4oAapqrvty1bihW0ZtUpgN3jmkBBATo62CMPgQ4ewrca+TBVkyPYOQLL/QCT7D0Smb29UKmyxblp/dO/Rqd6+SFmSm6W0iYioLWjS0jsNuVyOhQsXYuHChU1687t37+LChQva7/Py8pCVlQUPDw907doVr7zyCv7+97+jZ8+e6NmzJ/7+97/DyckJs2bNatL7EREBzZ/FkaK6W7VKYPn3OXUmJbXOHLpdCBw8qK5Od+AAcO2a9l4FgHwXDxz2G4hk/wFI8euP207utZ7Z2OGshiW561o2Z0pJbpbSJiKi1s7kREmhUECpVMLLy0vv+q1bt+Dl5YXq6mqjn3Xy5EmMHTtW+71mb1FMTAy2bNmChQsX4t69e5g7d672wNkDBw7wDCUiarImzeIYaCzpMOa+hmalbKqrMPC/ZzAyORP3/v0aXLJ/Uc8kaTg4AKNHA1FRqI6MwiPf5yO/uFySmSBNSe6afWNJbiIiuh+ZnCjVVySvvLwcdnZ2Jj1rzJgx9T4PUBdyiIuLQ1xcnEnPJSKqi0mzOA3MnEixTM1wtqnb7f9iZF4mRudlYNiVU3CtuKf/gtBQ9UGvEycCI0YAjo4A1DNKy2TtJZsJ4rI5IiIiNaMTpY8++giAOnn57LPP4OLiom2rrq5GcnIyAgMDpe8hEZGBpu4vkmpvkeEytZqMTU58UIGoc0cxKi8DIy9notudfL32W45uOOw/ACGzZ6DHk48ANY5JMCT1TBCXzREREZmQKK1duxaAekZpw4YNUNQ4a8POzg5+fn7YsGGD9D0kIqqhOfuLpNhbpFEzOSm8q5v9qTc5qa4G0tO1+4wGHz2KITWWKlfIbZDRKRDJ/gOR5D8QuR27o+MDTkiZPw4wIgnkTBAREZG0jE6U8vLyAABjx47Frl270K5dO7N1ioioLs3dXyTF3qKaNMnJsQsFuJl7DJtjBmNYDy9dcnL1qrr4woED6mIMhYXa18oA/OHXHd+2D8ZhvwE42jUUpXaO2jbAtCVzAGeCiIiIpGTyHqXExETtnzX7ixo6AJaISApS7C+SsgS2hkIuwxB/D+zNBYZ42UOxf5+uOl1urv7N7u7AhAnqvUZRUXD284N3thI53+eglMUTiIiIrIrJiRIAfPHFF3j//fdx/vx5AECvXr2wYMECPPXUU5J2johIQ4r9RVKXwIYQwKlTkO/di+Hbt8PmzBmgokLXLpcDQ4fqijAMHgzY6P+zyyVzRERE1snkRGnNmjVYsmQJXnrpJUREREAIgSNHjuD555/HzZs3MW/ePHP0k4juc1LtL2p24YPr14H4ePWsUXw8cP06FAA8Ne1du6qTookTgXHjACOWKXPJHBERkfUxOVH6xz/+gfXr1+Ppp5/WXouOjkZwcDDi4uKYKBGRWUi5v8ikWZzycuDIEd1yuqws/XZnZ6hGj8avvr4IjI2FbXAwwOXIRERErZ7JiZJSqcTw4cNrXR8+fDiUSqUknSKitqmpZb0B6fcX1TuLIwRw5oyuCMOhQ0Bpqf49AwfqltOFh6NaLselvXsR2Ls3kyQiIqI2wuREqUePHtixYwcWL16sd/2bb75Bz549JesYEbUtzSnrDZhhf1FNhYVAQoJu1ujqVf12b29dYjRhAuDlpd9eWWn6exIREZFVMzpRGjduHHbt2oXly5dj5syZSE5ORkREBGQyGVJSUpCQkIAdO3aYs69E1Eo1t6y3hmQHq1ZVAceP6xKjEycAlUrXbm8PjBypToyiooDQUM4UERER3WeMTpQOHTqEiooKPProozh+/DjWrl2LPXv2QAiBoKAgpKWlYcCAAebsKxFZSHOWzElR1rumJleJy8vTJUYJCUBxsX57UJAuMRo1CnByMurzERERUdvUpPLgYWFh2LZtm9R9ISIz0CQ5gLrEtt6BqEZo7pI5Kcp6GzKqSlxJCZCYqEuOLlzQb/fwACIj1clRZCTQubNR701ERET3B5MSpZKSEjg4NFxRys3NrVkdIiLpaJKcwrv38N4QYM7WE/BwcTQ6yZFiyZxUZb0bpVIBGRm6xCg1Vb3ETsPGBggP180aDRwIKBTNe08iIiJqs0xKlHr16lVvmxACMpkM1dXVze4UETVvuRugn+TY18gHjE1ypFoyJ2VZ71quXdNVp4uPB27d0m/v0UNXhGHMGIC/yCEiIiIjmZQofffdd/DwMK70LhE1XXOXu0mR5Ei1ZE7Sst737gHJyerEaP9+4Ndf9dvd3NSHvGpmjbp3b/yZRERERHUwKVGKiIiAl2FZXCKSlBTL3aRIcqRaMtesst5CANnZusQoOVl9AKyGXA4MGqROjCZOBIYMAWxtjeo3ERERUUOaVMyBiBrW1GVzUi13kyLJkXLJnEllvW/cUC+j0yypMzzIunNnXWI0fry6KAMRERGRxIxOlLp16wYFNz4TNao5y+akWu4mRZIj6ZI5NFDWu6oSOHRIN2uUkaH/QkdH9f4izXK6wECeaURERERmZ3SilJeXZ85+ELUJzV02J9VyNymSnGYtmWvgmeHdPYDz54GfdqsTo8RE4I8/9G/s10+XGEVEAI1U2yQiIiKSGpfeEUlEimVzUi13M0xyajIlyTFpyVxD7txRH/KqmTX67TeDD+SlToqiotRnGnl7G/dcIiIiIjNhokRUQ3NKckuxbE7K5W41k5zCu/e0101NcupdMtdQXKqqgBMndInR8ePqc4407OzUM0WaWaN+/dSFGYiIiIisBBMlov9pbkluKZbNSb3cTZPkHLtQgJu5x7A5ZjCG9fAyabmcpl8N7YkCoJ4l0iRGCQnqWaSaAgN1ZxqNHg04O5vUByIiIqKWZNSvcD08PHDz5k0AwJw5c1BSUmLWThG1NM3eIsMZIc3eon3ZynpeqSPVsjnNTJC3u/593u4ORpUGN6SQy7QzUKYeWtugu3eBH34AXn4Z6N0b8PMDnnsO2LlTnSS1awfMmAFs3Ahcvgzk5gLr1gGTJzNJIiIiIqtn1IxSRUUFiouL0aFDB2zduhWrVq2Cq6uruftG1CKkKskt9bI5k5e7mZtKBWRl6WaNjhwBKit17QoFMGyYbtZo0CD1NSIiIqJWyKhEKTw8HNOmTUNYWBiEEHj55Zfh6OhY572bN2+WtINE5iZVSW6pl80ZtdzN3JRK9ZlG+/er/3vjhn67v79un9HYscADD1ikm0RERERSMypR2rZtG9auXYuLFy9CJpOhqKgIZWXG7ccgsnZSleQGJKwSZyllZcDhw7pZo9On9dtdXIBx43QV6nr04JlGRERE1CYZlSh17NgRK1euBAD4+/vjyy+/RPv2Fv5NN5FEpNpbpGGVy+bqIwSQk6NLjJKS1MmShkwGhIXpltMNG6auWEdERETUxplc9Y4Hz5I1ak5Zbyn3FmlYxbK5+ty8CRw8qE6ODhwArl3Tb/f11SVG48cDnp6W6ScRERGRBTWpPHhSUhI++OAD5ObmQiaToU+fPliwYAFGjhwpdf+IGtXcst5S7y2yOpWVkB0+jMCvvoLi7beBjAz1TJKGgwMwapRur1FwMJfTERER0X3P5BMet23bhgkTJsDJyQkvv/wyXnrpJTg6OmL8+PH4+uuvzdFHonpJUdYbkL4kt8VduAB88gkQHQ14eMBm/Hj0/vZbyNPT1UlSSAgwf756uV1hofq/r76qvs4kiYiIiMj0GaUVK1bgvffew7x587TXYmNjsWbNGrz99tuYNWuWpB0kqo9UZb01WtXeIkNFRUBiojrhOXAAuHRJr1l06IBrffrAOyYGNg8+qF5eR0RERET1MjlRunTpEqZOnVrr+sMPP4zFixdL0ikiY0hV1rsmq95bVFN1NZCerkuMjh5VX9OwsQEiIrR7japCQpC+bx8mT54M2Npart9ERERErYTJiVKXLl2QkJCAHj166F1PSEhAly5dJOsY3T80hRgAdfIzrIeXUbM4Upb1bhWuXtUVYDh4UL1krqaePXX7jMaMAWoeCl3zYFgiIiIiapTJidL8+fPx8ssvIysrC8OHD4dMJkNKSgq2bNmCdevWmaOP1IZpCjEU3r2H94YAc7aegIeLo1GFGKQu6211SkvV5bo1pbtzc/Xb3d3VVek0Zxr5+1umn0RERERtkMmJ0gsvvABvb2+sXr0aO3bsAAD06dMH33zzDaKjoyXvILVdmkIMAoC9QnddU4ihsSIK5ijrbVFCAKdO6RKjw4eBigpdu1wODBmiK909ZIh6iR0RERERSa5JP2U98sgjeOSRR6TuC91HpCjE0CbKehcUAPHx6sQoPh7Iz9dv79JFnRRNnAiMGwd4tJKkj4iIiKiV46+jySKkKsSgKetteI6StwnnKLWo8nLgyBHdXqPMTP12Jydg7FjdrFGvXizXTURERGQBTJTIIqQsxGDVZb2FAM6e1S2nO3RIvfeopgEDdInR8OGAvb1FukpEREREOkyUqMk01eqakpxIXYjBqsp6374NJCToSndfuaLf3rGjLjGaMEH9PRERERFZFSZK1CSaanU1l7v5mLDcrU0VYqiqAo4f1y2nS0sDVCpdu50dMGqUrjpd375cTkdERERk5ZgokclqVqurydhqdUDtQgw1tYpCDHl5uuV0CQlAcbF+e1CQbtZo1Cj13iMiIiIiajVMTpReffXVOq/LZDI4ODigR48eiI6Ohgerc7VJUlSr06hZiKHw7j3tdassxFBSot5fpFlOd/68fruHBxAZqU6OIiPV1eqIiIiIqNUyOVHKzMxERkYGqqur0bt3bwghcP78eSgUCgQGBuKTTz7B/PnzkZKSgqCgIHP0mSxIqmp1GppCDMcuFOBm7jFsjhmMYT28LD+TpFKpK9JpEqPUVKCyUtduYwOEh+tmjQYOBBSK+p9HRERERK2KyYmSZrbo888/h5ubGwCguLgY//d//4cRI0bg2WefxaxZszBv3jzs379f8g6TZUlZrU5DIZdhiL8H9ubCstXqrl1Tn2V04ID6vzdv6rcHBOgSo7Fjgf+NfyIiIiJqe0xOlN5//33Ex8drkyQAcHNzQ1xcHKKiohAbG4ulS5ciKipK0o6SdZC6Wp1F3bsHHD6smzXKztZvd3VVH/I6caI6QQoIsEw/iYiIiKjFmZwoFRUVoaCgoNayuhs3bqD4fxvaH3jgAVRUVEjTQ7IqrbpanRDqZEhTnS45GSirMfMlkwGDBukSo2HDAFtby/WXiIiIiCymSUvv5syZg9WrV2Pw4MGQyWRIS0vDa6+9hmnTpgEA0tLS0KtXL6n7SlbAsFpdzWTJKqvV3bgBHDyomzVSKvXbO3VSJ0YTJwLjxwPtreQsJiIiIiKyKJMTpU8//RTz5s3D448/jqqqKvVDbGwQExODtWvXAgACAwPx2WefSdtTsho1q9XVLOxgFdXqKiqAo0d1iVFGhnomScPRERg9Wjdr1KcPzzQiIiIiolpMTpRcXFywceNGrF27FpcuXYIQAgEBAXBxcdHe079/fyn7SFZIU60uLa8QBSVl8HJ1sEwhBiGACxd0iVFiInD3rv49/frpijBERAAOrWD/FBERERFZVJMPnHVxcYGHhwdkMplekkT3D4VcZlQJcMnduQP8/LPuwNfLl/XbPT11idGECYCPFZ3HREREREStgsmJkkqlwjvvvIPVq1fj7v9+c+/q6or58+fjjTfegFwul7yTdJ+rqgJOntTNGh0/DlRX69ptbYERI3TL6fr1AzgOiYiIiKgZTE6U3njjDWzatAkrV65EREQEhBA4cuQI4uLiUFZWhhUrVpijn3S/uXJFlxgdPKieRaopMFA3azR6NODsbJFuEhEREVHbZHKitHXrVnz22Wd4+OGHtdf69euHTp06Ye7cuUyUqGnu3kXHkychj49XJ0Znz+q3P/CAehndxIlAZCTQrZtFuklERERE9weTE6XCwkIEBgbWuh4YGIjCwkJJOkX3AZUK+OUX7ayRTUoKhlVW6toVCmDoUN1yusGD1deIiIiIiFqAyYlSv3798PHHH+Ojjz7Su/7xxx+jX79+knWMzKdaJSxTrS4/X3fYa3w8UFCgbZIB+MPLCw7R0VA8+CAwdqx6FomIiIiIyAJMTpTee+89TJkyBQcPHkR4eDhkMhlSU1Nx9epV7N271xx9JAnty1bWOv/Ix1znH5WVASkpuup0p07pt7u4qBOiiRNROXYsDp47h8lTpkBhayttP4iIiIiITGRyojR69GicO3cO//znP3HmzBkIITB9+nTMnTsXvr6+5ugjSWRfthIvbMuAMLieX1SGF7ZlYP2fBjYvWRICyM3VJUZJScC9e7p2mQwIC9MVYRg2DLCzU7dVVgLnzzf9vYmIiIiIJNSkc5R8fX1rFW24evUq5syZg82bN0vSMZJWtUpg+fc5tZIkABBQL31b/n0OIoO8TVuGd+uWuviCZknd77/rt/v66hKj8ePVZxwREREREVm5Jh84a6iwsBBbt25lomSl0vIK9ZbbGRIAlEVlSMsrbPgQ2cpK4Ngx3azRyZPqmSQNBwdg1ChdEYbgYPVMEhERERFRKyJZokTWraCk/iSp0fsuXtQlRj//DJSU6LeHhOgSo5EjAUdHCXpMRERERGQ5TJTuE16uDsbfV1wMJCbqDny9eFH/pg4d1GcZRUWpv7g3jYiIiIjaGCZK94kh/h7wcXdAflFZrX1KclU1Qq9fxOT/nsKw1FXA0aNAVZXuBhsbICJCN2s0YAAgl7do/4mIiIiIWpLRidL06dMbbL9z505z+0JmpJDLsGxqEF7YlgEZgI7FNzHycgZG5WVixOUstCszWE7Xs6cuMRozBnB1tUS3iYiIiIgswuhEyd3dvdH2p59+utkdIjMpLcWk339B4rX/B9WBA+he8Jtec6WrG2wjJ+iW0/n7W6ijRERERESWZ3Si9Pnnn5uzHyQ1IYDTp3X7jA4fBsrL4adplstxO7g//hg9Dr4zp8F22FD1EjsiIiIiIuIepTaloACIj1cnR/HxQH6+fnuXLurldBMnQjZuHDw8POBhmZ4SEREREVk1JkqtTLVKIC2vEAUlZehoJ8Ng5Rko4v932Gtmpv7NTk7q/UWavUa9e/NMIyIiIiIiIzBRakX2nf4vtmzej8DTxzDycib6XjkFRWW5/k0DBuj2GUVEAPb2luksEREREVErxkTJ2t2+DSQk4Or23QiNj8f24ht6zTecH8BhvwEIeHI6+s2ZAXTsaKGOEhERERG1HUyUrE1VFXD8uHop3YEDQFoaoFKhy/+ayxU2ONE5GIf9ByDZfyDOePoBMjm84YAUTy8oLNl3IiIiIqI2gomSNcjLUydF+/cDCQlAcbFec2lAL/y7XR8c9huAY11DUGbrUOsRyqIypOUVIjygfUv1moiIiIiozWKiZAklJcChQ7rS3efP67e3awdERmr3GsXfkuPt7VmNPragpMws3SUiIiIiut8wUWopQgCrVgE//QSkpqqX2GkoFEB4uDoxmjgRCAtTX/sfr4pbRr2Fl2vtmSYiIiIiIjIdE6WWIpMB334LZGSov/f3155phLFjAXf3el86xN8DPu4OyC8qg6jr0QC83R0wxJ+nIhERERERSYGJUkuaN0+9/ygqCujRw+iXKeQyLJsahBe2ZUAG6CVLmlORlk0NgkLOM5KIiIiIiKTARKkl/elPTX7ppBAfrP/TQCz/PgfKIt1eJG93ByybGoRJIT5S9JCIiIiIiMBEqVWZFOKDyCBvpOUVoqCkDF6u6uV2nEkiIiIiIpIWE6VWRiGXsQQ4EREREZGZyS3dgYZUVVXhzTffhL+/PxwdHdG9e3e89dZbUKlUlu4aERERERG1YVY9o7Rq1Sps2LABW7duRXBwME6ePIlnnnkG7u7uiI2NtXT3iIiIiIiojbLqROno0aOIjo7GlClTAAB+fn7497//jZMnT1q4Z0RERERE1JZZdaI0YsQIbNiwAefOnUOvXr3wyy+/ICUlBR9++GG9rykvL0d5ebn2++LiYgBAZWUlKisrm9wXzWub8wyqH+NrXoyveTG+5sX4mhfja16Mr3kxvubVFuNrymeRCSHqOsPUKgghsHjxYqxatQoKhQLV1dVYsWIFFi1aVO9r4uLisHz58lrXv/76azg5OZmzu0REREREZMVKS0sxa9YsFBUVwc3NrcF7rTpR2r59OxYsWID3338fwcHByMrKwiuvvII1a9YgJiamztfUNaPUpUsX3Lx5s9FgNKSyshLx8fGIjIyEra1tk59DdWN8zYvxNS/G17wYX/NifM2L8TUvxte82mJ8i4uL0aFDB6MSJateerdgwQL87W9/w+OPPw4ACA0NxW+//YZ333233kTJ3t4e9vb2ta7b2tpK8hcs1XOoboyveTG+5sX4mhfja16Mr3kxvubF+JpXW4qvKZ/DqsuDl5aWQi7X76JCoWB5cCIiIiIiMiurnlGaOnUqVqxYga5duyI4OBiZmZlYs2YN5syZY+muERERERFRG2bVidI//vEPLFmyBHPnzkVBQQF8fX3xl7/8BUuXLrV014iIiIiIqA2z6kTJ1dUVH374YYPlwImIiIiIiKRm1XuUiIiIiIiILIGJEhERERERkQGrXnrXllSrBNLyClFQUgYvVwcM8feAQi6zdLeIiIiIiKgOTJRawL5sJZZ/nwNlUZn2mo+7A5ZNDcKkEB8L9oyIiIiIiOrCpXdmti9biRe2ZeglSQCQX1SGF7ZlYF+20kI9IyIiIiKi+jBRMqNqlcDy73Mg6mjTXFv+fQ6qVXXdQURERERElsJEyYzS8gprzSTVJAAoi8qQllfYcp0iIiIiIqJGMVEyo4KS+pOkptxHREREREQtg4mSGXm5Okh6HxERERERtQwmSmY0xN8DPu4OqK8IuAzq6ndD/D1asltERERERNQIJkpmpJDLsGxqEADUSpY03y+bGsTzlIiIiIiIrAwTJTObFOKD9X8aCG93/eV13u4OWP+ngTxHiYiIiIjICvHA2RYwKcQHkUHeSMsrREFJGbxc1cvtOJNERERERGSdmCi1EIVchvCA9pbuBhERERERGYFL74iIiIiIiAwwUSIiIiIiIjLARImIiIiIiMgAEyUiIiIiIiIDTJSIiIiIiIgMMFEiIiIiIiIywESJiIiIiIjIABMlIiIiIiIiA0yUiIiIiIiIDDBRIiIiIiIiMsBEiYiIiIiIyAATJSIiIiIiIgNMlIiIiIiIiAzYWLoD5iaEAAAUFxc36zmVlZUoLS1FcXExbG1tpega1cD4mhfja16Mr3kxvubF+JoX42tejK95tcX4anICTY7QkDafKJWUlAAAunTpYuGeEBERERGRNSgpKYG7u3uD98iEMelUK6ZSqfDf//4Xrq6ukMlkTX5OcXExunTpgqtXr8LNzU3CHhLA+Job42tejK95Mb7mxfiaF+NrXoyvebXF+AohUFJSAl9fX8jlDe9CavMzSnK5HJ07d5bseW5ubm1moFgjxte8GF/zYnzNi/E1L8bXvBhf82J8zautxbexmSQNFnMgIiIiIiIywESJiIiIiIjIABMlI9nb22PZsmWwt7e3dFfaJMbXvBhf82J8zYvxNS/G17wYX/NifM3rfo9vmy/mQEREREREZCrOKBERERERERlgokRERERERGSAiRIREREREZEBJkpEREREREQGmCgZ4ZNPPoG/vz8cHBwQFhaGw4cPW7pLVi8uLg4ymUzvy9vbW9suhEBcXBx8fX3h6OiIMWPG4Ndff9V7Rnl5Of7617+iQ4cOcHZ2xsMPP4zff/+9pT+K1UhOTsbUqVPh6+sLmUyGPXv26LVLFdPbt2/jqaeegru7O9zd3fHUU0/hzp07Zv50ltdYfGfPnl1rTA8bNkzvHsa3bu+++y4GDx4MV1dXeHl5Ydq0aTh79qzePRy/TWdMfDl+m279+vXo27ev9sDN8PBw/PTTT9p2jt3maSy+HLvSevfddyGTyfDKK69or3EMN0BQg7Zv3y5sbW3Fxo0bRU5OjoiNjRXOzs7it99+s3TXrNqyZctEcHCwUCqV2q+CggJt+8qVK4Wrq6vYuXOnOH36tJg5c6bw8fERxcXF2nuef/550alTJxEfHy8yMjLE2LFjRb9+/URVVZUlPpLF7d27V7zxxhti586dAoDYvXu3XrtUMZ00aZIICQkRqampIjU1VYSEhIiHHnqopT6mxTQW35iYGDFp0iS9MX3r1i29exjfuk2cOFF8/vnnIjs7W2RlZYkpU6aIrl27irt372rv4fhtOmPiy/HbdP/5z3/Ejz/+KM6ePSvOnj0rFi9eLGxtbUV2drYQgmO3uRqLL8eudNLS0oSfn5/o27eviI2N1V7nGK4fE6VGDBkyRDz//PN61wIDA8Xf/vY3C/WodVi2bJno169fnW0qlUp4e3uLlStXaq+VlZUJd3d3sWHDBiGEEHfu3BG2trZi+/bt2nuuXbsm5HK52Ldvn1n73hoY/iAvVUxzcnIEAHHs2DHtPUePHhUAxJkzZ8z8qaxHfYlSdHR0va9hfI1XUFAgAIikpCQhBMev1AzjKwTHr9TatWsnPvvsM45dM9HEVwiOXamUlJSInj17ivj4eDF69GhtosQx3DAuvWtARUUF0tPTERUVpXc9KioKqampFupV63H+/Hn4+vrC398fjz/+OC5dugQAyMvLQ35+vl5c7e3tMXr0aG1c09PTUVlZqXePr68vQkJCGPs6SBXTo0ePwt3dHUOHDtXeM2zYMLi7uzPuAA4dOgQvLy/06tULzz77LAoKCrRtjK/xioqKAAAeHh4AOH6lZhhfDY7f5quursb27dvxxx9/IDw8nGNXYobx1eDYbb4XX3wRU6ZMwYQJE/Sucww3zMbSHbBmN2/eRHV1NTp27Kh3vWPHjsjPz7dQr1qHoUOH4osvvkCvXr1w/fp1vPPOOxg+fDh+/fVXbezqiutvv/0GAMjPz4ednR3atWtX6x7GvjapYpqfnw8vL69az/fy8rrv4/7ggw9ixowZ6NatG/Ly8rBkyRKMGzcO6enpsLe3Z3yNJITAq6++ihEjRiAkJAQAx6+U6oovwPHbXKdPn0Z4eDjKysrg4uKC3bt3IygoSPsDIMdu89QXX4BjVwrbt29HRkYGTpw4UauN//42jImSEWQymd73Qoha10jfgw8+qP1zaGgowsPDERAQgK1bt2o3YTYlrox9w6SIaV33M+7AzJkztX8OCQnBoEGD0K1bN/z444+YPn16va9jfPW99NJLOHXqFFJSUmq1cfw2X33x5fhtnt69eyMrKwt37tzBzp07ERMTg6SkJG07x27z1BffoKAgjt1munr1KmJjY3HgwAE4ODjUex/HcN249K4BHTp0gEKhqJUJFxQU1Mq8qWHOzs4IDQ3F+fPntdXvGoqrt7c3KioqcPv27XrvIR2pYurt7Y3r16/Xev6NGzcYdwM+Pj7o1q0bzp8/D4DxNcZf//pX/Oc//0FiYiI6d+6svc7xK4364lsXjl/T2NnZoUePHhg0aBDeffdd9OvXD+vWrePYlUh98a0Lx65p0tPTUVBQgLCwMNjY2MDGxgZJSUn46KOPYGNjo/38HMN1Y6LUADs7O4SFhSE+Pl7venx8PIYPH26hXrVO5eXlyM3NhY+PD/z9/eHt7a0X14qKCiQlJWnjGhYWBltbW717lEolsrOzGfs6SBXT8PBwFBUVIS0tTXvP8ePHUVRUxLgbuHXrFq5evQofHx8AjG9DhBB46aWXsGvXLvz888/w9/fXa+f4bZ7G4lsXjt/mEUKgvLycY9dMNPGtC8euacaPH4/Tp08jKytL+zVo0CA8+eSTyMrKQvfu3TmGG9JCRSNaLU158E2bNomcnBzxyiuvCGdnZ3H58mVLd82qzZ8/Xxw6dEhcunRJHDt2TDz00EPC1dVVG7eVK1cKd3d3sWvXLnH69GnxxBNP1FmKsnPnzuLgwYMiIyNDjBs37r4uD15SUiIyMzNFZmamACDWrFkjMjMztaXqpYrppEmTRN++fcXRo0fF0aNHRWhoaKsv72mMhuJbUlIi5s+fL1JTU0VeXp5ITEwU4eHholOnToyvEV544QXh7u4uDh06pFfit7S0VHsPx2/TNRZfjt/mWbRokUhOThZ5eXni1KlTYvHixUIul4sDBw4IITh2m6uh+HLsmkfNqndCcAw3hImSEf75z3+Kbt26CTs7OzFw4EC9kqtUN00NfltbW+Hr6yumT58ufv31V227SqUSy5YtE97e3sLe3l6MGjVKnD59Wu8Z9+7dEy+99JLw8PAQjo6O4qGHHhJXrlxp6Y9iNRITEwWAWl8xMTFCCOlieuvWLfHkk08KV1dX4erqKp588klx+/btFvqUltNQfEtLS0VUVJTw9PQUtra2omvXriImJqZW7BjfutUVVwDi888/197D8dt0jcWX47d55syZo/0ZwNPTU4wfP16bJAnBsdtcDcWXY9c8DBMljuH6yYQQouXmr4iIiIiIiKwf9ygREREREREZYKJERERERERkgIkSERERERGRASZKREREREREBpgoERERERERGWCiREREREREZICJEhERERERkQEmSkRERERERAaYKBERUS2zZ8/GtGnTJH9ufn4+IiMj4ezsjAceeEDy5xMREUmFiRIRkYWYKxkxxeXLlyGTyZCVldUi77d27VoolUpkZWXh3Llztdr9/Pwgk8nq/RozZkyL9LMuY8aMwSuvvNLofZcuXcITTzwBX19fODg4oHPnzoiOjq7z8xIRkfWysXQHiIjo/nHx4kWEhYWhZ8+edbafOHEC1dXVAIDU1FQ8+uijOHv2LNzc3AAAdnZ2Jr1fRUWFya9pjoqKCkRGRiIwMBC7du2Cj48Pfv/9d+zduxdFRUUt1g8iImo+zigREVmpnJwcTJ48GS4uLujYsSOeeuop3Lx5U9s+ZswYvPzyy1i4cCE8PDzg7e2NuLg4vWecOXMGI0aMgIODA4KCgnDw4EHIZDLs2bMHAODv7w8AGDBgQJ0zNh988AF8fHzQvn17vPjii6isrGywz+vXr0dAQADs7OzQu3dvfPnll9o2Pz8/7Ny5E1988QVkMhlmz55d6/Wenp7w9vaGt7c3PDw8AABeXl7w9vaGp6cnFixYAH9/fzg6OqJ3795Yt26d3us1s3TvvvsufH190atXLwDqpKt///5wcHDAoEGDsGfPnlozaQ3Fe/bs2UhKSsK6deu0s1uXL1+u1f+cnBxcunQJn3zyCYYNG4Zu3bohIiICK1aswODBg7X3Xbt2DTNnzkS7du3Qvn17REdH6z2vuroar776Kh544AG0b98eCxcuRExMjN4MpJ+fHz788EO99+/fv7/eGCgqKsJzzz0HLy8vuLm5Ydy4cfjll1+07XFxcejfvz++/PJL+Pn5wd3dHY8//jhKSkq096hUKqxatQo9evSAvb09unbtihUrVhj9WYiIWismSkREVkipVGL06NHo378/Tp48iX379uH69et47LHH9O7bunUrnJ2dcfz4cbz33nt46623EB8fD0D9A+60adPg5OSE48eP41//+hfeeOMNvdenpaUBAA4ePAilUoldu3Zp2xITE3Hx4kUkJiZi69at2LJlC7Zs2VJvn3fv3o3Y2FjMnz8f2dnZ+Mtf/oJnnnkGiYmJANSzRZMmTcJjjz0GpVJZK8lpjEqlQufOnbFjxw7k5ORg6dKlWLx4MXbs2KF3X0JCAnJzcxEfH48ffvgBJSUlmDp1KkJDQ5GRkYG3334br7/+uknxXrduHcLDw/Hss89CqVRCqVSiS5cutfro6ekJuVyO7777TjszZqi0tBRjx46Fi4sLkpOTkZKSAhcXF0yaNAkVFRUAgNWrV2Pz5s3YtGkTUlJSUFhYiN27d5sULyEEpkyZgvz8fOzduxfp6ekYOHAgxo8fj8LCQu19Fy9exJ49e/DDDz/ghx9+QFJSElauXKltX7RoEVatWoUlS5YgJycHX3/9NTp27Gj0ZyEiarUEERFZRExMjIiOjq6zbcmSJSIqKkrv2tWrVwUAcfbsWSGEEKNHjxYjRozQu2fw4MHi9ddfF0II8dNPPwkbGxuhVCq17fHx8QKA2L17txBCiLy8PAFAZGZm1upbt27dRFVVlfbajBkzxMyZM+v9PMOHDxfPPvus3rUZM2aIyZMna7+Pjo4WMTEx9T6jpsTERAFA3L59u9575s6dKx599FG9fnfs2FGUl5drr61fv160b99e3Lt3T3tt48aNep/b2HjHxsY22u+PP/5YODk5CVdXVzF27Fjx1ltviYsXL2rbN23aJHr37i1UKpX2Wnl5uXB0dBT79+8XQgjh4+MjVq5cqW2vrKwUnTt31hsv3bp1E2vXrtV77379+olly5YJIYRISEgQbm5uoqysTO+egIAA8emnnwohhFi2bJlwcnISxcXF2vYFCxaIoUOHCiGEKC4uFvb29mLjxo11flZjPgsRUWvFGSUiIiuUnp6OxMREuLi4aL8CAwMBqGcANPr27av3Oh8fHxQUFAAAzp49iy5dusDb21vbPmTIEKP7EBwcDIVCUeez65Kbm4uIiAi9axEREcjNzTX6PRuzYcMGDBo0CJ6ennBxccHGjRtx5coVvXtCQ0P19iWdPXsWffv2hYODg/aaYRyMjbcxXnzxReTn52Pbtm0IDw/Ht99+i+DgYO1MX3p6Oi5cuABXV1fte3l4eKCsrAwXL15EUVERlEolwsPDtc+0sbHBoEGDTOpHeno67t69i/bt2+t9rry8PL3P5OfnB1dXV+33Nf+ec3NzUV5ejvHjx9f7Hg19FiKi1ozFHIiIrJBKpcLUqVOxatWqWm0+Pj7aP9va2uq1yWQyqFQqAOqlVzKZrMl9aOjZ9TF8v+b2oaYdO3Zg3rx5WL16NcLDw+Hq6or3338fx48f17vP2dm50T4IIfS+NzbexnJ1dcXDDz+Mhx9+GO+88w4mTpyId955B5GRkVCpVAgLC8NXX31V63Wenp5Gv4dcLq/1OWruIVOpVPDx8cGhQ4dqvbZmafaG/p4dHR0b7INUn4WIyBoxUSIiskIDBw7Ezp074efnBxubpv1THRgYiCtXruD69evaPSUnTpzQu0cz81LffhpT9OnTBykpKXj66ae111JTU9GnT59mPxsADh8+jOHDh2Pu3Lnaa8bMWgQGBuKrr75CeXk57O3tAQAnT57Uu8eYeNvZ2TUpTjKZDIGBgUhNTdW+1zfffKMtsFAXHx8fHDt2DKNGjQIAVFVVafcYaXh6ekKpVGq/Ly4uRl5ent5nys/Ph42NDfz8/EzuNwD07NkTjo6OSEhIwJ///Oda7cZ8FiKi1opL74iILKioqAhZWVl6X1euXMGLL76IwsJCPPHEE0hLS8OlS5dw4MABzJkzx+gf1iMjIxEQEICYmBicOnUKR44c0RZz0MyweHl5wdHRUVu8oDklrBcsWIAtW7Zgw4YNOH/+PNasWYNdu3bhtddea/Iza+rRowdOnjyJ/fv349y5c1iyZEmtxK8us2bNgkqlwnPPPYfc3Fzs378fH3zwAQBdHIyJt5+fH44fP47Lly/j5s2bdc6uZWVlITo6Gt999x1ycnJw4cIFbNq0CZs3b0Z0dDQA4Mknn0SHDh0QHR2Nw4cPIy8vD0lJSYiNjcXvv/8OAIiNjcXKlSuxe/dunDlzBnPnzsWdO3f03mvcuHH48ssvcfjwYWRnZyMmJkZvqeSECRMQHh6OadOmYf/+/bh8+TJSU1Px5ptv1koU6+Pg4IDXX38dCxcuxBdffIGLFy/i2LFj2LRpk9GfhYiotWKiRERkQYcOHcKAAQP0vpYuXQpfX18cOXIE1dXVmDhxIkJCQhAbGwt3d3fI5cb9061QKLBnzx7cvXsXgwcPxp///Ge8+eabAKDdr2NjY4OPPvoIn376KXx9fbU/zDfFtGnTsG7dOrz//vsIDg7Gp59+is8//1yyQ2Kff/55TJ8+HTNnzsTQoUNx69Ytvdml+ri5ueH7779HVlYW+vfvjzfeeANLly4FoIuDMfF+7bXXoFAoEBQUBE9Pz1p7owCgc+fO8PPzw/LlyzF06FAMHDgQ69atw/Lly7VJqpOTE5KTk9G1a1dMnz4dffr0wZw5c3Dv3j3trMz8+fPx9NNPY/bs2dplho888ojeey1atAijRo3CQw89hMmTJ2PatGkICAjQtstkMuzduxejRo3CnDlz0KtXLzz++OO4fPmydobRGEuWLMH8+fOxdOlS9OnTBzNnztTuYTLmsxARtVYyYbjAmYiI2qwjR45gxIgRuHDhgt4P1febr776Cs888wyKiooa3YdjLWbPno07d+5oz8AiIiLz4h4lIqI2bPfu3XBxcUHPnj1x4cIFxMbGIiIi4r5Lkr744gt0794dnTp1wi+//ILXX38djz32WKtJkoiIqOUxUSIiasNKSkqwcOFCXL16FR06dMCECROwevVqS3erxeXn52Pp0qXIz8+Hj48PZsyYgRUrVli6W0REZMW49I6IiIiIiMgAizkQEREREREZYKJERERERERkgIkSERERERGRASZKREREREREBpgoERERERERGWCiREREREREZICJEhERERERkQEmSkRERERERAb+PyhMduaDSrttAAAAAElFTkSuQmCC",
      "text/plain": [
       "<Figure size 1000x600 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Linear Regression Equation (Cost vs Length): y = 1001.92x + -1379823.41\n",
      "Linear Regression Equation (Log(Cost) vs Length): log(y) = 0.0011x + 8.0867\n"
     ]
    }
   ],
   "source": [
    "# Program graph_regression.py\n",
    "# This program performs linear regression\n",
    "# on the data obtained from\n",
    "# CostOfTruncatedEvolution.py\n",
    "\n",
    "import numpy as np\n",
    "import matplotlib.pyplot as plt\n",
    "\n",
    "# Assuming xArray and yArray are defined from the previous cell's output\n",
    "# Example data (replace with your actual xArray and yArray)\n",
    "xArray = np.array([100, \n",
    "200,\n",
    "300,\n",
    "400,\n",
    "500,\n",
    "600,\n",
    "700,\n",
    "800,\n",
    "900,\n",
    "1000,\n",
    "1100,\n",
    "1200,\n",
    "1300,\n",
    "1400,\n",
    "1500,\n",
    "1600,\n",
    "1700,\n",
    "1800,\n",
    "1900,\n",
    "2000,\n",
    "2100,\n",
    "2200,\n",
    "2300,\n",
    "2400,\n",
    "2500,\n",
    "2600,\n",
    "2700,\n",
    "2800,\n",
    "2900,\n",
    "3000,\n",
    "3100,\n",
    "3200,\n",
    "3300,\n",
    "3400,\n",
    "3500,\n",
    "3600,\n",
    "3700,\n",
    "3800,\n",
    "3900,\n",
    "4000,\n",
    "4100\n",
    "])\n",
    "yArray = np.array([ 2200,\n",
    "3800,\n",
    "5000,\n",
    "7200,\n",
    "8200,\n",
    "9200,\n",
    "10600,\n",
    "11800,\n",
    "12400,\n",
    "13200,\n",
    "13400,\n",
    "14200,\n",
    "16600,\n",
    "18400,\n",
    "20200,\n",
    "19000,\n",
    "20600,\n",
    "21200,\n",
    "22600,\n",
    "25000,\n",
    "27200,\n",
    "26600,\n",
    "28800,\n",
    "31800,\n",
    "32800,\n",
    "34800,\n",
    "36400,\n",
    "39400,\n",
    "39800,\n",
    "45000,\n",
    "49200,\n",
    "45800,\n",
    "57000,\n",
    "60200,\n",
    "64800,\n",
    "79000,\n",
    "86200,\n",
    "246000,\n",
    "145200,\n",
    "2016000,\n",
    "26225800\n",
    "])\n",
    "\n",
    "# Perform linear regression\n",
    "# Fit a polynomial of degree 1 (linear)\n",
    "slope, intercept = np.polyfit(xArray, yArray, 1)\n",
    "\n",
    "# Create the regression line\n",
    "regression_line = slope * np.array(xArray) + intercept\n",
    "\n",
    "# Plot the original data and the regression line\n",
    "plt.figure(figsize=(10, 6))\n",
    "plt.scatter(xArray, yArray, label='Observed Data')\n",
    "plt.plot(xArray, regression_line, color='red', label=f'Linear Regression: y = {slope:.2f}x + {intercept:.2f}')\n",
    "plt.xlabel('Length of Target Sequence')\n",
    "plt.ylabel('Total Cost (Number of Chromosomes)')\n",
    "plt.title('Linear Regression of Truncated Evolution Cost vs. Target Sequence Length')\n",
    "plt.legend()\n",
    "plt.grid(True)\n",
    "plt.show()\n",
    "\n",
    "# Also perform linear regression on the log of yArray\n",
    "log_y_array = np.log(yArray)\n",
    "log_slope, log_intercept = np.polyfit(xArray, log_y_array, 1)\n",
    "log_regression_line = log_slope * np.array(xArray) + log_intercept\n",
    "\n",
    "# Plot the original log data and the log regression line\n",
    "plt.figure(figsize=(10, 6))\n",
    "plt.scatter(xArray, log_y_array, label='Observed Log Data')\n",
    "plt.plot(xArray, log_regression_line, color='red', label=f'Linear Regression on Log: log(y) = {log_slope:.4f}x + {log_intercept:.4f}')\n",
    "plt.xlabel('Length of Target Sequence')\n",
    "plt.ylabel('Log of Total Cost (Log of Number of Chromosomes)')\n",
    "plt.title('Linear Regression of Log of Truncated Evolution Cost vs. Target Sequence Length')\n",
    "plt.legend()\n",
    "plt.grid(True)\n",
    "plt.show()\n",
    "\n",
    "print(f\"Linear Regression Equation (Cost vs Length): y = {slope:.2f}x + {intercept:.2f}\")\n",
    "print(f\"Linear Regression Equation (Log(Cost) vs Length): log(y) = {log_slope:.4f}x + {log_intercept:.4f}\")"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "5f4cf333",
   "metadata": {},
   "source": [
    "*Comment.* We see that the graph is described by a complex function that near 4000 disproportionally increases with the length of the input. \n",
    "\n"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "387f426c",
   "metadata": {},
   "source": [
    "## The Mutation-MAX Duo is full scientific\n",
    "\n",
    "We have seen that the needed time for our simulations disproportionately grows in the length of the target string. Employed time is paralleled by the cost, given in the number of needed chromosomes, to achieve a partial task. In our words: the quantity of waste that is produced by the Duo to achieve a humble task is enormous. In Genomics and Evolution, waste means a defective product.  From this we have a simple, robust, mandatory prediction: if the Mutation-MAX-Duo is responsible for our existence, the fossil record and our own anatomy and physiology must be filled in every kind of defects and malfunction.  \n",
    "\n",
    "**Challenge.** By looking at yourself, decide whether you are here because of the Mutation-MAX DUO.\n",
    "\n",
    "## MORE MEASUREMENTS\n",
    "\n",
    "We know that the Mutation-MAX Duo works. Our aim is to understand why. Some of our previous conclusions are: \n",
    "\n",
    "- Recursive mutation produces the sea of nonsense where mediocrity is the law. \n",
    "- Magic mutation in an isolated chromosome works and produces perfection.\n",
    "- The Duo is better than magic mutation. The Duo is composed of random mutation and MAX, followed by cloning of the fittest. This profits on ensemble properties. What are these ensemble properties? It is the variability created by mutation that allows MAX to pick up the best of the group, which is better than the majority of chromosomes. This variability corresponds to fluctuations of the number of matched sites that are higher than the average. \n",
    "\n",
    "Keeping in mind these results, the following hypothesis summarizes what we believe until this moment about the functioning of Evolution: \n",
    "\n",
    "Mutation is a force that battles for the establishment of mediocrity, but it also creates variability among chromosomes, whose fluctuations in the number of matched sites guarantees values above mediocrity.  MAX picks up the best, which is reproduced to create the next generation. The expected value of the magnitude of the fluctuations, the fuel of MAX, is proportional to a convex function of the population size. This means that to get more improvement, one must increase the population size more than proportionally. Or to wait during more generations. We studied in our previous work a model in which the role of fluctuations was to produce more good points, which were added to those present. Comparison with simulations rendered this model false. Its predictions of the cost are orders of magnitude off the values found in simulations, and the cost function is not defined past some barrier. \n",
    "\n",
    "What is the best way to continue?\n",
    "\n",
    "We need more data of the appropriate observables. One that was ignored in the previous work is the role of the fluctuations in the number of sites that are touched by mutation. In fact, we have assumed that this number is constant and equal to the expected value $\\mu H$, where $\\mu$ is the mutation rate. $H$ is the length of the target string that is equal to the length of all chromosomes. Since $\\mu$ is a probability and not a classical parameter, there must be a variability in the number of sites that are touched by mutation. Let us evaluate it.\n",
    "\n",
    "**Exercise.** Develop a program to exhibit the variability in the number of sites that are touched by mutation along an evolutionary process. Report the MAX.\n",
    ">\n",
    "> *Answer.* The following program exhibits the variability in the number of touched by mutation sites along an evolutionary process.  The MAX of each generation is reported.\n",
    ">\n",
    ">"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "39590b5c",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Lab: Simple Genetic Algorithm\n",
      "Purpose: solve an instance of the Shakespeare challenge\n",
      "Date of Experiment  = 2026-02-25 14:40:22.129114\n",
      "alphabet =  01\n",
      "target_sequence = 11111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111\n",
      "length_of_target_sequence = 800\n",
      "population_size = 200\n",
      "include_clone_populationf3 = True\n",
      "include_mutate_allf3 = True\n",
      "include_crossover_allf3 = False\n",
      "mutation_rate = 0.01\n",
      "print_best_fitness = False\n",
      "\n",
      "Target sequence matched in generation 450\n",
      "Final chromosome: 11111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111\n",
      "Total cost = population size * number of generations: 90000\n"
     ]
    },
    {
     "data": {
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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "All touched numbers for each generation:\n",
      "Genrtn 1: mean = 7.825  stddev = 2.786462811522881  max = 16 [3, 13, 6, 10, 6, 10, 8, 4, 7, 9, 6, 3, 8, 7, 8, 11, 5, 3, 8, 16, 7, 9, 10, 8, 8, 16, 8, 6, 10, 8, 11, 8, 7, 11, 12, 6, 5, 8, 6, 9, 5, 9, 8, 8, 3, 9, 3, 6, 5, 2, 14, 3, 6, 11, 7, 9, 6, 7, 9, 9, 12, 7, 5, 7, 9, 6, 13, 6, 4, 4, 9, 10, 5, 4, 8, 8, 9, 6, 4, 5, 7, 6, 7, 5, 7, 6, 12, 10, 5, 6, 13, 7, 9, 7, 10, 8, 12, 6, 5, 8, 5, 8, 4, 10, 6, 10, 7, 6, 9, 6, 12, 14, 6, 9, 9, 13, 8, 7, 5, 4, 3, 7, 9, 10, 9, 12, 7, 8, 10, 6, 13, 11, 7, 6, 12, 9, 3, 8, 12, 11, 6, 7, 14, 16, 9, 8, 11, 7, 2, 7, 11, 6, 11, 8, 11, 6, 6, 10, 9, 8, 13, 4, 11, 3, 5, 9, 8, 11, 6, 7, 11, 8, 8, 6, 6, 6, 9, 5, 6, 11, 7, 7, 11, 8, 7, 5, 8, 8, 9, 9, 6, 2, 8, 6, 7, 7, 9, 5, 8, 11]\n",
      "Genrtn 2: mean = 8.295  stddev = 2.622589369306602  max = 17 [6, 10, 5, 10, 11, 9, 9, 12, 11, 8, 8, 12, 7, 8, 8, 8, 6, 7, 4, 8, 6, 12, 12, 14, 12, 11, 7, 11, 5, 8, 12, 13, 4, 10, 4, 11, 10, 13, 11, 10, 10, 8, 5, 7, 11, 8, 10, 6, 10, 11, 11, 11, 2, 2, 8, 7, 11, 9, 6, 5, 7, 7, 9, 8, 11, 6, 7, 4, 7, 3, 10, 11, 5, 8, 8, 8, 4, 2, 5, 4, 10, 9, 6, 11, 5, 8, 10, 8, 8, 11, 9, 10, 7, 10, 9, 6, 11, 11, 13, 10, 8, 11, 8, 5, 7, 17, 4, 9, 8, 8, 6, 8, 11, 5, 4, 10, 11, 9, 12, 13, 7, 7, 8, 7, 7, 9, 10, 4, 11, 9, 10, 8, 10, 11, 10, 9, 6, 9, 7, 4, 13, 3, 8, 6, 8, 6, 6, 10, 6, 9, 8, 9, 7, 9, 9, 5, 8, 9, 10, 9, 8, 8, 13, 8, 8, 6, 7, 4, 8, 5, 11, 6, 4, 11, 8, 8, 11, 11, 12, 2, 8, 7, 11, 11, 9, 11, 8, 6, 10, 5, 9, 4, 8, 9, 6, 8, 9, 8, 8, 13]\n",
      "Genrtn 3: mean = 7.56  stddev = 3.0027320892813596  max = 20 [11, 6, 12, 6, 5, 9, 9, 8, 4, 6, 10, 7, 5, 9, 4, 12, 2, 8, 12, 6, 8, 11, 11, 3, 6, 8, 7, 6, 15, 9, 5, 6, 11, 6, 10, 4, 5, 5, 10, 7, 8, 12, 3, 10, 12, 9, 8, 7, 3, 11, 7, 8, 7, 7, 5, 5, 5, 9, 3, 2, 8, 9, 10, 9, 7, 4, 10, 8, 9, 8, 8, 20, 10, 10, 8, 3, 12, 6, 11, 10, 8, 5, 9, 8, 3, 5, 14, 5, 8, 2, 4, 5, 5, 14, 4, 11, 6, 3, 5, 7, 7, 7, 2, 10, 9, 7, 6, 7, 3, 6, 9, 7, 10, 10, 6, 5, 9, 13, 5, 10, 4, 8, 4, 9, 9, 14, 5, 4, 7, 7, 4, 6, 7, 5, 3, 7, 6, 12, 9, 5, 7, 6, 6, 6, 4, 9, 9, 10, 9, 8, 4, 12, 4, 6, 6, 5, 13, 7, 8, 9, 8, 12, 4, 10, 13, 5, 6, 10, 12, 7, 4, 12, 15, 5, 8, 7, 7, 7, 5, 9, 5, 8, 8, 8, 11, 9, 11, 10, 17, 5, 9, 8, 6, 6, 6, 4, 4, 8, 9, 7]\n",
      "Genrtn 4: mean = 7.905  stddev = 2.5992258462857745  max = 15 [7, 7, 10, 8, 9, 12, 10, 5, 5, 6, 6, 5, 9, 14, 8, 6, 6, 10, 7, 8, 14, 4, 8, 5, 11, 10, 10, 5, 6, 7, 3, 5, 9, 6, 9, 7, 9, 8, 11, 8, 11, 11, 8, 8, 9, 9, 4, 5, 13, 8, 6, 11, 3, 8, 9, 6, 6, 9, 4, 7, 4, 5, 8, 10, 5, 5, 12, 7, 7, 8, 8, 4, 8, 10, 10, 9, 13, 6, 9, 9, 9, 5, 12, 11, 14, 4, 6, 8, 6, 9, 8, 5, 6, 7, 3, 4, 6, 5, 8, 10, 5, 8, 4, 14, 6, 8, 6, 15, 8, 9, 7, 7, 9, 6, 5, 9, 7, 9, 4, 9, 7, 12, 5, 12, 7, 5, 9, 4, 7, 8, 10, 8, 4, 9, 10, 7, 13, 7, 8, 9, 11, 3, 12, 10, 11, 11, 7, 9, 7, 6, 8, 10, 7, 3, 11, 9, 9, 7, 4, 5, 10, 5, 10, 4, 9, 10, 6, 9, 13, 8, 6, 8, 8, 6, 10, 4, 7, 10, 13, 8, 2, 9, 8, 9, 13, 9, 7, 7, 9, 7, 7, 5, 8, 12, 11, 7, 11, 9, 11, 9]\n",
      "Genrtn 5: mean = 8.38  stddev = 2.804567702873297  max = 18 [10, 4, 12, 13, 9, 12, 6, 7, 2, 9, 5, 6, 9, 6, 4, 4, 13, 4, 11, 7, 7, 3, 11, 9, 8, 11, 9, 8, 14, 12, 11, 9, 5, 6, 9, 7, 12, 10, 10, 9, 11, 12, 14, 9, 9, 3, 9, 8, 4, 12, 5, 6, 12, 9, 11, 9, 10, 7, 18, 10, 7, 9, 8, 10, 8, 5, 11, 6, 7, 9, 8, 8, 7, 8, 8, 6, 10, 6, 11, 9, 11, 11, 11, 10, 9, 13, 11, 8, 6, 13, 7, 6, 6, 5, 3, 8, 9, 7, 7, 5, 6, 7, 9, 5, 4, 7, 8, 11, 9, 6, 4, 3, 7, 6, 8, 7, 16, 7, 9, 8, 15, 10, 8, 7, 11, 9, 10, 10, 6, 11, 10, 11, 13, 7, 6, 9, 9, 10, 11, 12, 5, 6, 4, 5, 5, 3, 10, 12, 12, 8, 11, 10, 2, 8, 6, 6, 8, 11, 6, 8, 6, 9, 6, 12, 10, 10, 15, 11, 8, 7, 8, 7, 5, 13, 9, 9, 7, 7, 7, 12, 8, 4, 6, 6, 13, 11, 8, 6, 8, 5, 8, 7, 10, 7, 11, 10, 5, 12, 9, 8]\n",
      "Genrtn 6: mean = 7.85  stddev = 2.658477007611689  max = 19 [10, 6, 9, 15, 6, 11, 4, 12, 5, 10, 10, 8, 8, 4, 10, 5, 7, 6, 9, 11, 10, 7, 9, 7, 10, 4, 8, 4, 10, 9, 4, 13, 6, 12, 8, 5, 11, 5, 7, 7, 5, 8, 10, 10, 4, 2, 5, 5, 9, 9, 8, 10, 7, 11, 3, 5, 5, 14, 5, 6, 7, 9, 8, 11, 4, 10, 8, 7, 7, 8, 8, 5, 7, 5, 6, 9, 8, 12, 8, 19, 9, 4, 9, 11, 8, 6, 7, 7, 6, 13, 16, 7, 12, 14, 10, 4, 9, 5, 10, 6, 8, 9, 6, 8, 5, 11, 10, 5, 5, 8, 8, 9, 8, 8, 7, 9, 4, 5, 8, 10, 6, 4, 9, 7, 3, 7, 8, 9, 5, 9, 6, 11, 9, 7, 9, 7, 5, 6, 11, 13, 8, 9, 8, 6, 8, 8, 7, 6, 12, 7, 7, 5, 8, 6, 5, 9, 8, 10, 7, 6, 10, 9, 9, 10, 7, 10, 3, 9, 11, 10, 8, 4, 6, 7, 3, 8, 5, 8, 8, 8, 10, 9, 14, 2, 9, 7, 10, 9, 7, 5, 10, 7, 8, 11, 6, 9, 6, 6, 12, 6]\n",
      "Genrtn 7: mean = 8.265  stddev = 3.1264636572332005  max = 17 [7, 7, 10, 11, 3, 6, 6, 7, 2, 8, 6, 9, 4, 8, 9, 8, 8, 5, 8, 2, 14, 5, 2, 11, 4, 8, 14, 9, 7, 8, 5, 7, 16, 10, 11, 10, 4, 8, 6, 11, 12, 12, 13, 6, 3, 10, 11, 5, 9, 6, 9, 8, 6, 11, 10, 7, 8, 8, 7, 15, 7, 8, 8, 11, 12, 8, 12, 7, 15, 4, 3, 6, 13, 12, 5, 7, 6, 10, 4, 12, 7, 9, 8, 7, 10, 7, 11, 4, 9, 6, 11, 5, 4, 8, 9, 6, 12, 10, 8, 1, 6, 6, 11, 7, 7, 13, 6, 8, 10, 8, 7, 10, 5, 6, 5, 5, 17, 11, 7, 13, 12, 11, 8, 10, 7, 6, 10, 5, 12, 14, 10, 11, 11, 6, 7, 6, 12, 14, 3, 9, 9, 10, 3, 6, 9, 7, 4, 9, 8, 9, 6, 3, 9, 11, 6, 11, 8, 8, 11, 12, 9, 15, 8, 12, 8, 10, 11, 9, 6, 8, 6, 9, 7, 4, 10, 3, 10, 12, 12, 4, 12, 9, 4, 3, 8, 6, 14, 8, 6, 10, 8, 13, 3, 8, 8, 5, 14, 15, 4, 9]\n",
      "Genrtn 8: mean = 7.875  stddev = 2.6980316899547345  max = 17 [13, 5, 7, 9, 7, 7, 11, 7, 13, 7, 9, 7, 17, 7, 7, 8, 11, 8, 14, 10, 9, 6, 8, 9, 7, 5, 15, 8, 4, 7, 9, 9, 5, 4, 7, 5, 11, 7, 4, 6, 4, 8, 9, 8, 7, 7, 8, 9, 4, 9, 3, 12, 2, 5, 8, 5, 12, 13, 11, 12, 10, 5, 8, 6, 5, 6, 8, 13, 14, 4, 4, 9, 9, 7, 10, 9, 6, 3, 8, 8, 11, 6, 4, 10, 4, 6, 4, 5, 7, 6, 8, 8, 10, 6, 8, 9, 6, 6, 8, 12, 7, 7, 8, 10, 12, 6, 11, 10, 9, 9, 10, 4, 9, 10, 7, 6, 11, 9, 6, 8, 6, 8, 12, 5, 9, 8, 6, 11, 4, 6, 9, 3, 6, 6, 6, 9, 7, 7, 13, 5, 8, 6, 12, 8, 11, 5, 6, 8, 8, 6, 7, 9, 5, 10, 12, 8, 7, 8, 7, 8, 12, 8, 8, 6, 9, 11, 7, 6, 2, 8, 13, 4, 6, 8, 12, 4, 3, 4, 4, 11, 12, 4, 8, 10, 11, 9, 11, 12, 5, 9, 9, 8, 11, 9, 9, 5, 6, 10, 7, 9]\n",
      "Genrtn 9: mean = 7.67  stddev = 2.983471132757949  max = 18 [10, 7, 7, 9, 7, 8, 6, 8, 8, 11, 9, 5, 10, 7, 8, 15, 17, 14, 11, 6, 7, 8, 8, 3, 8, 8, 7, 6, 8, 13, 5, 3, 10, 6, 5, 12, 6, 9, 7, 9, 10, 13, 5, 7, 6, 8, 8, 5, 12, 7, 5, 7, 7, 8, 7, 5, 5, 9, 5, 4, 11, 10, 11, 4, 4, 8, 6, 12, 6, 11, 7, 16, 11, 8, 3, 4, 5, 7, 11, 5, 4, 6, 8, 6, 6, 5, 7, 12, 8, 8, 3, 9, 6, 8, 9, 7, 4, 3, 3, 8, 14, 9, 9, 7, 10, 4, 7, 5, 11, 16, 10, 9, 7, 3, 8, 5, 6, 9, 10, 4, 10, 6, 4, 9, 8, 13, 7, 9, 9, 8, 7, 8, 13, 8, 8, 3, 8, 6, 13, 6, 7, 6, 10, 5, 1, 8, 18, 6, 8, 6, 6, 8, 3, 8, 11, 17, 11, 8, 10, 6, 1, 8, 7, 4, 2, 9, 11, 5, 8, 6, 7, 5, 9, 12, 6, 8, 8, 5, 9, 10, 8, 9, 6, 3, 12, 8, 4, 9, 4, 7, 7, 6, 5, 6, 8, 6, 10, 7, 5, 11]\n",
      "Genrtn 10: mean = 7.745  stddev = 2.603838512657803  max = 19 [8, 7, 6, 6, 10, 11, 9, 5, 8, 7, 13, 7, 6, 8, 10, 4, 9, 4, 7, 6, 8, 9, 9, 6, 10, 8, 8, 8, 2, 11, 9, 4, 12, 6, 5, 6, 6, 6, 6, 7, 5, 5, 13, 7, 5, 6, 4, 8, 12, 3, 11, 8, 9, 5, 6, 5, 6, 7, 7, 8, 5, 6, 9, 8, 11, 10, 8, 5, 7, 10, 9, 10, 10, 6, 13, 14, 5, 8, 7, 11, 10, 8, 8, 9, 6, 7, 10, 7, 6, 7, 11, 5, 7, 10, 5, 8, 9, 7, 11, 8, 5, 9, 7, 5, 12, 15, 8, 5, 19, 11, 5, 9, 6, 6, 9, 9, 7, 7, 5, 9, 11, 6, 8, 12, 6, 6, 8, 9, 8, 10, 8, 10, 9, 8, 7, 5, 4, 9, 9, 11, 6, 3, 8, 6, 13, 8, 11, 9, 8, 10, 7, 8, 9, 8, 7, 7, 6, 7, 8, 9, 1, 8, 12, 14, 9, 8, 8, 11, 3, 5, 5, 7, 6, 5, 7, 6, 13, 5, 4, 5, 4, 9, 4, 9, 4, 10, 6, 7, 6, 9, 5, 10, 6, 7, 14, 7, 10, 10, 8, 4]\n",
      "Genrtn 11: mean = 7.68  stddev = 2.9081953166869656  max = 16 [7, 5, 5, 8, 3, 4, 10, 3, 6, 15, 7, 5, 9, 9, 10, 7, 10, 1, 8, 4, 6, 10, 5, 4, 7, 8, 5, 9, 8, 4, 12, 12, 9, 8, 7, 8, 5, 3, 8, 9, 9, 8, 13, 8, 14, 10, 11, 10, 10, 5, 12, 10, 3, 10, 6, 4, 12, 10, 8, 9, 6, 8, 6, 10, 10, 7, 7, 4, 7, 6, 4, 10, 7, 8, 13, 7, 11, 8, 6, 8, 13, 12, 14, 12, 4, 6, 13, 8, 8, 9, 4, 5, 8, 6, 13, 6, 5, 5, 6, 3, 3, 9, 6, 6, 5, 7, 4, 10, 4, 7, 9, 3, 6, 9, 9, 8, 4, 7, 7, 8, 7, 6, 7, 6, 3, 11, 7, 5, 3, 10, 12, 13, 15, 12, 10, 7, 6, 13, 7, 6, 16, 11, 8, 7, 6, 9, 8, 8, 4, 4, 4, 8, 12, 8, 5, 6, 10, 7, 5, 10, 9, 5, 5, 11, 6, 3, 11, 10, 7, 5, 9, 5, 10, 9, 11, 8, 12, 6, 8, 3, 9, 6, 6, 8, 12, 8, 10, 3, 5, 9, 11, 6, 6, 4, 9, 2, 9, 11, 8, 10]\n",
      "Genrtn 12: mean = 7.745  stddev = 2.7257980482787056  max = 17 [10, 8, 10, 8, 9, 9, 5, 13, 4, 9, 4, 9, 5, 11, 10, 10, 7, 6, 7, 4, 7, 12, 8, 9, 10, 7, 6, 9, 4, 14, 8, 8, 6, 5, 6, 3, 8, 7, 11, 7, 4, 12, 6, 7, 12, 7, 5, 5, 5, 11, 5, 7, 8, 8, 11, 9, 6, 8, 7, 7, 7, 16, 8, 5, 10, 8, 6, 10, 6, 13, 4, 9, 7, 9, 7, 9, 8, 8, 10, 6, 10, 11, 7, 2, 8, 13, 11, 5, 9, 13, 6, 7, 6, 11, 11, 8, 7, 8, 4, 7, 10, 8, 5, 8, 7, 8, 7, 6, 10, 8, 7, 10, 2, 7, 10, 11, 7, 11, 5, 11, 10, 8, 7, 5, 7, 7, 5, 11, 9, 5, 8, 3, 12, 4, 7, 5, 4, 10, 4, 12, 6, 9, 10, 2, 7, 11, 9, 8, 9, 4, 3, 6, 3, 6, 8, 9, 4, 8, 8, 7, 6, 6, 8, 10, 5, 2, 8, 12, 9, 5, 9, 5, 10, 8, 7, 2, 4, 6, 17, 10, 4, 13, 10, 5, 12, 11, 6, 7, 12, 8, 5, 3, 7, 9, 10, 10, 10, 7, 11, 9]\n",
      "Genrtn 13: mean = 7.875  stddev = 2.754882030142126  max = 14 [1, 8, 7, 7, 6, 4, 6, 5, 8, 10, 10, 7, 10, 3, 8, 4, 12, 9, 7, 9, 14, 7, 9, 6, 10, 4, 9, 14, 5, 7, 8, 8, 8, 7, 7, 6, 4, 11, 8, 10, 11, 13, 5, 9, 14, 5, 4, 8, 3, 10, 2, 10, 8, 8, 6, 8, 7, 8, 2, 10, 7, 6, 8, 6, 4, 11, 12, 6, 12, 8, 6, 10, 6, 6, 12, 6, 8, 7, 6, 6, 8, 6, 9, 3, 8, 3, 4, 10, 6, 12, 10, 5, 7, 3, 12, 4, 11, 5, 7, 8, 11, 9, 6, 8, 10, 14, 6, 7, 8, 3, 7, 9, 9, 8, 7, 6, 11, 7, 10, 9, 3, 11, 6, 6, 8, 5, 7, 12, 1, 6, 8, 9, 7, 9, 6, 10, 6, 9, 14, 10, 5, 7, 12, 10, 7, 10, 8, 9, 5, 12, 6, 6, 8, 8, 9, 9, 14, 9, 6, 10, 5, 11, 10, 12, 6, 11, 7, 11, 6, 12, 10, 10, 5, 10, 4, 10, 14, 7, 8, 7, 8, 5, 9, 13, 11, 2, 9, 11, 11, 5, 11, 8, 7, 7, 5, 9, 9, 9, 9, 5]\n",
      "Genrtn 14: mean = 7.67  stddev = 2.661033633759634  max = 16 [8, 7, 8, 7, 16, 4, 6, 10, 7, 10, 5, 5, 7, 13, 6, 6, 10, 11, 12, 5, 2, 5, 14, 7, 14, 8, 8, 5, 11, 12, 10, 6, 9, 6, 7, 11, 7, 11, 5, 7, 9, 7, 4, 0, 11, 10, 10, 11, 6, 3, 9, 4, 6, 5, 10, 6, 7, 8, 8, 4, 7, 9, 6, 2, 7, 10, 3, 10, 6, 5, 9, 10, 6, 6, 8, 6, 7, 10, 9, 7, 8, 8, 4, 7, 7, 7, 15, 11, 10, 5, 6, 11, 3, 5, 6, 6, 8, 4, 6, 7, 6, 9, 9, 11, 13, 8, 10, 9, 6, 12, 4, 8, 5, 7, 6, 6, 8, 9, 10, 4, 6, 6, 5, 7, 8, 10, 7, 6, 8, 14, 7, 8, 8, 13, 9, 7, 7, 7, 13, 9, 9, 10, 8, 8, 12, 9, 8, 6, 2, 5, 9, 7, 4, 7, 8, 9, 8, 4, 2, 5, 8, 7, 8, 7, 5, 8, 8, 5, 13, 7, 5, 6, 9, 7, 12, 11, 4, 5, 10, 8, 5, 7, 7, 10, 10, 6, 8, 7, 7, 4, 8, 6, 10, 9, 9, 11, 9, 12, 10, 8]\n",
      "Genrtn 15: mean = 7.75  stddev = 2.649056435789921  max = 15 [7, 7, 12, 7, 5, 7, 8, 9, 8, 5, 11, 10, 7, 6, 6, 5, 5, 7, 7, 6, 9, 6, 10, 6, 8, 7, 11, 9, 7, 5, 8, 5, 9, 9, 7, 8, 9, 9, 7, 8, 9, 9, 9, 9, 8, 13, 9, 8, 10, 4, 9, 9, 4, 7, 12, 9, 11, 7, 12, 10, 7, 12, 4, 8, 10, 6, 8, 8, 8, 6, 9, 10, 5, 3, 7, 11, 9, 10, 5, 7, 8, 9, 10, 9, 4, 10, 11, 4, 3, 15, 5, 6, 11, 8, 9, 12, 6, 9, 5, 7, 14, 8, 5, 12, 4, 8, 8, 8, 3, 9, 9, 11, 7, 8, 5, 7, 9, 9, 13, 6, 8, 7, 9, 7, 13, 9, 6, 3, 9, 7, 4, 2, 8, 7, 9, 11, 8, 9, 9, 8, 8, 12, 9, 4, 12, 11, 8, 8, 6, 5, 6, 7, 6, 6, 7, 4, 10, 8, 5, 5, 9, 8, 5, 10, 12, 12, 9, 7, 15, 8, 6, 5, 9, 8, 8, 4, 9, 1, 4, 15, 3, 5, 7, 5, 11, 4, 9, 6, 2, 3, 6, 8, 4, 10, 4, 10, 11, 11, 8, 2]\n",
      "Genrtn 16: mean = 7.86  stddev = 2.674023186137323  max = 16 [6, 9, 9, 7, 12, 10, 7, 14, 7, 12, 8, 6, 10, 4, 6, 12, 9, 9, 5, 7, 10, 11, 6, 7, 4, 8, 10, 4, 9, 4, 11, 8, 9, 12, 5, 8, 6, 9, 8, 10, 7, 9, 4, 6, 11, 7, 6, 7, 9, 10, 11, 11, 7, 11, 12, 11, 6, 7, 10, 8, 7, 4, 4, 3, 3, 8, 9, 11, 7, 10, 5, 5, 4, 9, 6, 10, 9, 5, 9, 10, 10, 11, 8, 5, 8, 8, 8, 5, 10, 8, 3, 6, 8, 5, 14, 7, 12, 8, 9, 8, 8, 6, 8, 5, 9, 7, 9, 11, 9, 5, 9, 12, 5, 5, 7, 3, 4, 11, 12, 7, 9, 6, 5, 7, 16, 6, 7, 4, 10, 14, 10, 2, 5, 8, 8, 5, 10, 5, 6, 10, 10, 6, 5, 12, 11, 6, 5, 13, 5, 6, 5, 10, 10, 8, 7, 2, 13, 9, 8, 5, 9, 6, 7, 12, 10, 10, 8, 9, 5, 6, 6, 9, 7, 14, 8, 6, 8, 9, 1, 9, 7, 6, 9, 10, 4, 7, 12, 7, 5, 6, 4, 11, 10, 10, 5, 9, 10, 5, 9, 9]\n",
      "Genrtn 17: mean = 7.95  stddev = 2.906458325866724  max = 17 [8, 5, 5, 5, 13, 8, 5, 7, 6, 5, 6, 5, 10, 6, 15, 12, 4, 10, 10, 9, 7, 6, 2, 10, 8, 4, 10, 11, 8, 11, 5, 6, 7, 7, 3, 7, 11, 2, 12, 10, 5, 11, 9, 11, 7, 8, 8, 11, 9, 6, 9, 5, 7, 7, 9, 4, 8, 6, 9, 12, 9, 5, 8, 7, 8, 8, 3, 7, 7, 4, 7, 11, 6, 8, 8, 7, 5, 9, 12, 8, 9, 8, 9, 9, 10, 14, 10, 4, 10, 9, 11, 12, 10, 14, 6, 11, 5, 5, 7, 7, 7, 7, 8, 11, 9, 9, 8, 8, 5, 15, 6, 7, 6, 6, 12, 5, 9, 13, 2, 6, 7, 12, 11, 8, 12, 8, 15, 9, 9, 13, 8, 2, 8, 8, 4, 8, 8, 5, 13, 6, 8, 9, 6, 17, 5, 7, 2, 13, 6, 5, 6, 8, 13, 11, 5, 7, 7, 3, 9, 13, 14, 8, 12, 9, 11, 9, 4, 11, 6, 4, 6, 7, 1, 4, 9, 7, 6, 8, 3, 8, 4, 8, 8, 7, 10, 11, 8, 12, 5, 7, 12, 8, 10, 6, 7, 8, 10, 9, 6, 5]\n",
      "Genrtn 18: mean = 8.28  stddev = 2.4822570374560327  max = 14 [6, 7, 8, 8, 5, 5, 8, 4, 12, 6, 7, 8, 7, 9, 6, 10, 6, 8, 8, 10, 9, 8, 11, 8, 7, 7, 7, 7, 6, 13, 7, 6, 8, 6, 7, 9, 7, 13, 9, 10, 9, 13, 6, 7, 7, 8, 11, 7, 9, 10, 9, 8, 4, 9, 7, 7, 8, 9, 8, 10, 12, 8, 7, 9, 7, 9, 7, 8, 6, 6, 7, 7, 10, 5, 12, 4, 9, 10, 8, 8, 8, 9, 4, 9, 5, 4, 8, 6, 10, 12, 6, 7, 14, 10, 13, 7, 10, 6, 11, 8, 9, 6, 10, 10, 10, 8, 11, 7, 6, 4, 6, 11, 7, 4, 8, 7, 9, 14, 14, 7, 7, 5, 9, 9, 7, 4, 5, 8, 7, 5, 10, 5, 9, 6, 13, 13, 14, 8, 12, 8, 7, 3, 7, 8, 9, 9, 2, 6, 7, 8, 11, 8, 9, 6, 13, 7, 11, 14, 7, 11, 11, 11, 10, 10, 10, 10, 5, 7, 9, 12, 12, 8, 10, 8, 9, 9, 10, 9, 8, 10, 5, 4, 9, 6, 4, 10, 14, 12, 8, 7, 8, 12, 7, 10, 5, 13, 7, 4, 12, 11]\n",
      "Genrtn 19: mean = 8.0  stddev = 2.6627053911388696  max = 18 [9, 5, 5, 5, 11, 7, 13, 8, 6, 8, 6, 14, 12, 7, 12, 13, 6, 5, 9, 8, 6, 5, 9, 10, 8, 3, 12, 7, 13, 8, 11, 8, 6, 10, 10, 11, 10, 10, 3, 8, 7, 9, 8, 5, 8, 8, 7, 8, 8, 6, 6, 7, 4, 8, 10, 10, 6, 4, 3, 8, 5, 4, 5, 12, 6, 11, 8, 6, 7, 9, 9, 10, 9, 13, 6, 4, 11, 10, 8, 14, 9, 9, 6, 9, 10, 9, 8, 7, 8, 8, 4, 9, 7, 8, 7, 11, 8, 8, 3, 7, 10, 12, 10, 5, 7, 10, 6, 6, 7, 9, 10, 7, 7, 11, 13, 5, 3, 10, 6, 11, 12, 8, 4, 9, 8, 11, 3, 10, 8, 6, 7, 8, 5, 8, 8, 6, 8, 9, 7, 5, 7, 5, 9, 5, 9, 9, 12, 7, 6, 13, 8, 18, 3, 9, 11, 11, 5, 4, 5, 6, 11, 8, 8, 6, 4, 9, 10, 7, 9, 7, 11, 13, 3, 7, 10, 12, 9, 7, 8, 7, 8, 7, 12, 9, 4, 8, 4, 10, 7, 7, 13, 7, 6, 10, 6, 14, 6, 10, 5, 5]\n",
      "Genrtn 20: mean = 8.355  stddev = 2.772900106386813  max = 15 [7, 11, 11, 8, 9, 5, 4, 4, 9, 14, 7, 7, 7, 6, 8, 10, 12, 8, 6, 9, 10, 8, 13, 8, 15, 11, 7, 2, 13, 12, 6, 5, 6, 9, 8, 6, 4, 3, 12, 11, 4, 8, 8, 11, 9, 6, 10, 11, 8, 6, 10, 8, 10, 10, 6, 13, 6, 6, 14, 11, 13, 13, 12, 10, 9, 5, 15, 9, 10, 12, 9, 8, 6, 9, 11, 8, 7, 12, 6, 2, 9, 11, 6, 8, 5, 3, 6, 5, 5, 7, 6, 5, 9, 7, 10, 5, 9, 7, 14, 9, 10, 8, 6, 11, 8, 9, 5, 7, 8, 4, 10, 13, 10, 7, 7, 15, 7, 8, 11, 8, 10, 6, 9, 9, 6, 9, 6, 12, 8, 11, 4, 4, 11, 9, 8, 8, 11, 5, 11, 11, 7, 9, 11, 7, 13, 6, 9, 10, 7, 8, 7, 7, 10, 12, 10, 7, 6, 5, 11, 7, 12, 6, 11, 9, 8, 10, 8, 4, 12, 15, 6, 5, 3, 7, 11, 5, 3, 8, 9, 6, 5, 11, 7, 7, 5, 11, 9, 11, 9, 9, 5, 8, 6, 14, 11, 6, 6, 10, 8, 8]\n",
      "Genrtn 21: mean = 7.92  stddev = 2.839647865493185  max = 18 [9, 7, 8, 12, 9, 5, 12, 4, 8, 8, 10, 10, 7, 6, 6, 10, 6, 5, 8, 7, 10, 10, 3, 4, 6, 7, 7, 10, 7, 9, 8, 12, 6, 12, 7, 6, 2, 8, 11, 15, 10, 9, 7, 9, 10, 13, 7, 14, 11, 6, 10, 8, 6, 10, 10, 7, 13, 6, 9, 4, 6, 5, 6, 9, 9, 7, 14, 7, 10, 9, 13, 4, 5, 7, 7, 7, 9, 5, 9, 12, 7, 3, 5, 12, 8, 6, 9, 6, 7, 3, 7, 5, 9, 6, 12, 9, 8, 6, 3, 8, 10, 4, 7, 4, 5, 9, 4, 6, 10, 9, 5, 9, 11, 11, 10, 9, 7, 1, 10, 6, 7, 8, 8, 10, 6, 17, 6, 9, 7, 5, 4, 7, 11, 11, 4, 4, 5, 4, 9, 12, 7, 11, 7, 12, 11, 10, 6, 6, 18, 8, 7, 8, 10, 5, 10, 11, 9, 11, 5, 6, 11, 6, 4, 6, 8, 5, 5, 7, 6, 8, 7, 9, 9, 9, 8, 5, 9, 4, 8, 5, 11, 5, 8, 10, 6, 6, 10, 3, 5, 15, 11, 10, 11, 7, 13, 7, 5, 8, 14, 6]\n",
      "Genrtn 22: mean = 7.925  stddev = 2.7293543192484186  max = 16 [6, 6, 3, 6, 7, 11, 6, 7, 7, 10, 4, 8, 6, 8, 6, 14, 9, 2, 7, 4, 14, 11, 8, 8, 6, 9, 7, 6, 9, 11, 7, 8, 8, 7, 7, 6, 7, 8, 6, 8, 13, 5, 5, 7, 3, 12, 5, 6, 10, 4, 8, 2, 12, 7, 8, 8, 9, 13, 6, 6, 6, 7, 12, 4, 6, 7, 4, 3, 6, 6, 10, 8, 4, 14, 6, 10, 11, 16, 15, 12, 9, 3, 11, 11, 6, 10, 4, 9, 8, 12, 5, 9, 3, 13, 8, 5, 9, 9, 9, 16, 9, 6, 7, 7, 8, 7, 6, 8, 5, 6, 4, 7, 5, 11, 7, 9, 16, 5, 7, 4, 10, 4, 8, 9, 7, 6, 7, 11, 8, 9, 8, 10, 8, 8, 10, 6, 9, 11, 12, 13, 13, 11, 6, 8, 8, 9, 14, 8, 7, 10, 10, 7, 7, 11, 8, 7, 7, 7, 10, 6, 8, 6, 6, 6, 6, 7, 10, 9, 6, 10, 10, 10, 5, 8, 9, 7, 9, 7, 13, 11, 6, 5, 10, 8, 7, 9, 7, 9, 8, 11, 5, 8, 6, 3, 5, 7, 9, 7, 8, 9]\n",
      "Genrtn 23: mean = 8.01  stddev = 2.915458797513695  max = 16 [8, 3, 10, 10, 5, 10, 9, 4, 4, 9, 10, 7, 6, 8, 4, 8, 7, 6, 9, 8, 11, 11, 2, 3, 12, 7, 6, 7, 3, 6, 13, 6, 5, 4, 15, 11, 8, 9, 7, 9, 7, 2, 5, 9, 9, 8, 9, 4, 9, 8, 6, 2, 4, 3, 10, 11, 10, 9, 5, 4, 8, 4, 8, 11, 9, 6, 8, 12, 8, 11, 11, 5, 11, 7, 10, 6, 5, 8, 8, 4, 11, 11, 11, 12, 11, 5, 11, 5, 12, 4, 6, 7, 8, 9, 10, 6, 8, 10, 6, 10, 8, 8, 13, 12, 5, 12, 6, 4, 11, 4, 8, 9, 11, 3, 4, 6, 10, 7, 7, 10, 5, 16, 9, 10, 5, 9, 11, 8, 14, 10, 13, 6, 10, 6, 7, 6, 7, 7, 12, 8, 7, 7, 8, 9, 15, 9, 9, 5, 4, 6, 10, 8, 15, 16, 6, 11, 10, 12, 8, 7, 8, 6, 6, 8, 7, 9, 8, 6, 10, 6, 8, 7, 6, 3, 7, 4, 9, 7, 9, 8, 1, 10, 7, 6, 7, 8, 7, 10, 16, 11, 5, 7, 5, 14, 10, 11, 10, 10, 11, 8]\n",
      "Genrtn 24: mean = 8.215  stddev = 2.7800674452250256  max = 16 [11, 3, 11, 15, 6, 3, 9, 9, 6, 8, 10, 11, 8, 6, 11, 5, 5, 11, 3, 6, 6, 9, 4, 10, 7, 9, 6, 5, 14, 6, 11, 10, 7, 9, 13, 9, 10, 7, 7, 6, 15, 11, 10, 8, 5, 6, 6, 9, 1, 7, 6, 7, 10, 5, 12, 8, 10, 4, 11, 7, 12, 7, 7, 7, 5, 10, 9, 8, 12, 10, 7, 10, 11, 8, 8, 8, 4, 6, 7, 8, 8, 12, 9, 8, 4, 10, 8, 5, 8, 8, 9, 3, 11, 9, 9, 6, 7, 2, 11, 5, 11, 6, 8, 7, 6, 9, 12, 11, 10, 10, 6, 9, 12, 5, 9, 9, 12, 8, 3, 14, 11, 8, 4, 11, 12, 10, 4, 9, 9, 8, 6, 9, 11, 6, 11, 10, 9, 16, 8, 10, 5, 16, 11, 7, 12, 10, 4, 12, 8, 8, 6, 10, 9, 10, 9, 7, 7, 9, 13, 6, 7, 8, 13, 8, 6, 6, 7, 5, 8, 11, 7, 8, 10, 7, 12, 12, 9, 7, 6, 7, 3, 3, 7, 7, 10, 9, 4, 11, 8, 10, 4, 9, 12, 4, 9, 5, 10, 3, 10, 7]\n",
      "Genrtn 25: mean = 7.915  stddev = 2.7382065298293337  max = 15 [5, 7, 9, 9, 7, 8, 13, 11, 7, 7, 7, 7, 11, 7, 7, 10, 4, 10, 5, 6, 11, 12, 9, 7, 4, 8, 4, 9, 10, 7, 9, 5, 4, 6, 8, 6, 12, 4, 5, 10, 12, 10, 10, 5, 7, 15, 6, 4, 8, 4, 9, 8, 8, 7, 10, 6, 12, 5, 9, 13, 5, 8, 9, 10, 8, 13, 13, 8, 8, 9, 6, 9, 5, 11, 3, 8, 8, 9, 2, 15, 7, 10, 4, 6, 7, 14, 15, 12, 5, 8, 5, 10, 7, 12, 4, 8, 7, 11, 9, 9, 7, 8, 14, 6, 9, 6, 7, 12, 7, 11, 4, 5, 15, 9, 5, 7, 5, 9, 6, 11, 5, 10, 9, 10, 6, 7, 6, 7, 10, 8, 8, 9, 12, 6, 7, 7, 6, 6, 7, 7, 9, 5, 8, 11, 7, 7, 7, 5, 2, 5, 4, 12, 5, 7, 5, 12, 3, 13, 4, 8, 8, 8, 9, 4, 5, 7, 4, 11, 8, 9, 8, 5, 10, 4, 12, 12, 7, 9, 5, 7, 10, 13, 8, 7, 8, 6, 6, 8, 5, 11, 6, 13, 7, 9, 10, 6, 8, 10, 6, 7]\n",
      "Genrtn 26: mean = 8.14  stddev = 2.889705867385122  max = 16 [6, 11, 4, 13, 10, 14, 11, 4, 10, 7, 10, 10, 3, 10, 8, 11, 9, 12, 16, 8, 5, 8, 8, 8, 7, 10, 5, 7, 8, 11, 9, 8, 6, 11, 8, 5, 13, 7, 8, 4, 8, 5, 7, 10, 5, 4, 10, 7, 6, 8, 12, 12, 7, 8, 10, 4, 13, 7, 9, 9, 8, 10, 15, 6, 7, 10, 9, 6, 11, 10, 9, 11, 7, 5, 11, 12, 9, 10, 7, 9, 9, 3, 7, 7, 7, 8, 10, 11, 4, 6, 4, 7, 8, 7, 5, 8, 7, 6, 9, 5, 5, 5, 7, 2, 7, 9, 12, 12, 8, 8, 5, 8, 4, 8, 5, 10, 12, 9, 10, 7, 7, 6, 9, 9, 4, 12, 9, 3, 5, 10, 8, 9, 10, 8, 2, 7, 16, 11, 10, 3, 8, 10, 8, 6, 4, 8, 10, 12, 10, 9, 6, 13, 10, 9, 5, 12, 6, 6, 12, 9, 6, 2, 1, 11, 8, 6, 11, 8, 13, 8, 12, 8, 7, 14, 11, 13, 6, 11, 7, 7, 9, 9, 6, 6, 9, 14, 7, 8, 14, 10, 5, 7, 6, 13, 3, 4, 4, 5, 8, 3]\n",
      "Genrtn 27: mean = 7.835  stddev = 2.68845215691111  max = 15 [6, 11, 6, 5, 7, 8, 7, 3, 6, 5, 4, 7, 9, 9, 7, 8, 6, 6, 6, 9, 7, 12, 5, 11, 13, 5, 9, 10, 10, 6, 9, 6, 7, 5, 7, 8, 4, 12, 10, 4, 9, 7, 9, 10, 8, 7, 5, 5, 8, 10, 7, 10, 10, 13, 8, 7, 9, 7, 12, 8, 14, 5, 7, 8, 9, 9, 4, 11, 4, 8, 4, 13, 8, 6, 7, 10, 10, 12, 5, 7, 9, 11, 7, 8, 7, 10, 8, 8, 7, 10, 12, 9, 8, 6, 13, 10, 5, 7, 11, 10, 5, 6, 7, 6, 9, 5, 5, 7, 8, 10, 6, 11, 13, 4, 12, 4, 4, 10, 9, 10, 5, 7, 13, 6, 9, 5, 6, 9, 6, 5, 11, 7, 6, 6, 10, 7, 5, 9, 4, 3, 4, 6, 12, 10, 4, 9, 8, 4, 8, 5, 7, 15, 5, 3, 5, 13, 11, 5, 8, 9, 7, 6, 4, 10, 10, 12, 10, 10, 7, 9, 6, 4, 6, 14, 7, 4, 5, 11, 5, 12, 13, 12, 11, 6, 9, 3, 10, 7, 10, 7, 9, 3, 10, 8, 2, 9, 9, 11, 9, 8]\n",
      "Genrtn 28: mean = 8.16  stddev = 2.9990665214362955  max = 16 [10, 11, 7, 9, 3, 11, 4, 4, 3, 8, 9, 10, 8, 10, 12, 10, 9, 7, 9, 6, 8, 5, 4, 8, 10, 8, 10, 11, 8, 6, 7, 8, 5, 8, 15, 8, 5, 7, 10, 5, 14, 7, 8, 12, 7, 11, 6, 6, 6, 7, 7, 13, 5, 13, 12, 4, 10, 12, 6, 12, 9, 5, 11, 9, 4, 8, 9, 15, 10, 10, 10, 1, 7, 7, 2, 8, 11, 3, 12, 7, 8, 3, 14, 6, 14, 5, 7, 9, 10, 10, 5, 8, 6, 7, 5, 8, 7, 11, 7, 10, 8, 13, 11, 7, 8, 6, 10, 9, 7, 12, 1, 8, 10, 12, 8, 2, 12, 3, 12, 3, 3, 5, 6, 8, 10, 6, 6, 7, 9, 6, 12, 14, 10, 6, 8, 8, 5, 6, 8, 11, 10, 13, 4, 9, 7, 8, 6, 11, 5, 9, 5, 8, 8, 13, 3, 10, 11, 12, 6, 4, 4, 11, 8, 6, 10, 6, 4, 10, 10, 10, 15, 8, 5, 7, 10, 4, 6, 8, 10, 7, 7, 10, 8, 14, 7, 8, 7, 6, 9, 11, 11, 9, 9, 11, 4, 14, 6, 16, 11, 5]\n",
      "Genrtn 29: mean = 8.0  stddev = 2.7802877548915688  max = 16 [4, 8, 6, 7, 3, 5, 8, 12, 7, 14, 6, 7, 12, 7, 9, 6, 6, 12, 9, 8, 6, 8, 9, 10, 10, 6, 12, 9, 8, 7, 7, 9, 8, 7, 4, 8, 6, 9, 4, 9, 6, 8, 5, 4, 6, 10, 9, 9, 8, 11, 6, 10, 10, 9, 11, 10, 11, 7, 13, 9, 7, 10, 4, 6, 5, 6, 11, 10, 9, 2, 8, 10, 9, 10, 16, 5, 8, 8, 2, 4, 9, 10, 7, 12, 6, 3, 6, 4, 3, 11, 12, 8, 13, 14, 10, 8, 8, 7, 9, 4, 8, 8, 8, 4, 8, 10, 9, 12, 3, 5, 12, 8, 9, 11, 15, 7, 7, 8, 7, 12, 11, 5, 9, 7, 10, 13, 7, 11, 7, 8, 6, 8, 6, 7, 9, 8, 11, 11, 10, 10, 13, 7, 2, 9, 5, 10, 8, 11, 8, 9, 12, 10, 6, 10, 6, 7, 8, 9, 5, 11, 8, 4, 12, 5, 7, 4, 2, 8, 4, 13, 8, 3, 2, 11, 7, 4, 3, 8, 10, 5, 8, 11, 5, 8, 6, 5, 8, 12, 5, 12, 7, 11, 7, 6, 5, 8, 7, 11, 11, 10]\n",
      "Genrtn 30: mean = 8.305  stddev = 2.6687028684362746  max = 17 [8, 9, 7, 10, 7, 7, 10, 13, 6, 8, 12, 9, 7, 7, 9, 9, 12, 9, 12, 15, 5, 7, 13, 9, 7, 4, 8, 7, 7, 6, 10, 10, 13, 9, 12, 8, 8, 4, 7, 7, 7, 7, 10, 10, 10, 8, 8, 7, 9, 8, 12, 10, 13, 12, 6, 8, 10, 7, 5, 4, 5, 11, 8, 6, 10, 9, 12, 4, 5, 8, 2, 6, 3, 9, 2, 3, 5, 8, 9, 8, 6, 7, 8, 5, 9, 6, 5, 5, 9, 8, 10, 12, 7, 14, 7, 6, 9, 14, 9, 13, 9, 11, 9, 6, 6, 6, 12, 17, 9, 6, 8, 12, 6, 7, 11, 9, 10, 11, 8, 15, 10, 8, 5, 12, 6, 8, 11, 10, 7, 5, 12, 3, 6, 7, 5, 6, 13, 8, 7, 5, 9, 7, 8, 11, 7, 6, 6, 14, 6, 8, 7, 10, 9, 12, 12, 10, 7, 9, 7, 8, 12, 9, 11, 13, 11, 6, 8, 6, 5, 6, 6, 8, 11, 8, 12, 6, 8, 8, 8, 10, 6, 6, 10, 6, 5, 10, 10, 6, 7, 8, 5, 9, 8, 11, 8, 2, 10, 10, 8, 9]\n",
      "Genrtn 31: mean = 7.785  stddev = 2.951063367669356  max = 17 [4, 9, 10, 8, 9, 12, 9, 10, 5, 8, 4, 14, 3, 5, 12, 5, 6, 9, 10, 12, 10, 9, 8, 8, 5, 7, 4, 5, 11, 9, 4, 8, 12, 4, 5, 5, 10, 7, 9, 9, 12, 9, 11, 6, 11, 8, 5, 9, 5, 5, 8, 6, 9, 7, 7, 9, 12, 11, 10, 8, 8, 7, 9, 3, 11, 9, 11, 12, 8, 12, 14, 4, 14, 6, 12, 5, 12, 9, 5, 8, 9, 4, 0, 7, 5, 9, 5, 7, 7, 7, 9, 11, 12, 9, 5, 17, 12, 15, 5, 5, 7, 10, 6, 7, 11, 10, 16, 5, 11, 11, 7, 13, 2, 7, 8, 4, 8, 5, 10, 7, 15, 9, 2, 6, 9, 5, 6, 7, 7, 10, 8, 6, 4, 11, 10, 2, 11, 10, 6, 9, 6, 12, 4, 6, 8, 3, 10, 8, 8, 12, 2, 9, 7, 9, 6, 7, 5, 6, 6, 3, 6, 6, 8, 9, 10, 5, 7, 6, 9, 7, 7, 9, 9, 8, 11, 7, 10, 6, 6, 2, 9, 8, 5, 5, 2, 5, 4, 9, 8, 8, 4, 4, 7, 11, 7, 11, 6, 5, 8, 8]\n",
      "Genrtn 32: mean = 7.85  stddev = 2.7271780286589284  max = 15 [10, 7, 5, 6, 8, 7, 12, 10, 11, 6, 9, 7, 9, 9, 11, 6, 4, 9, 12, 6, 15, 7, 8, 4, 3, 11, 8, 11, 6, 5, 3, 8, 6, 3, 5, 11, 8, 10, 10, 11, 10, 6, 11, 7, 14, 11, 6, 8, 8, 7, 7, 10, 5, 8, 13, 12, 10, 8, 8, 3, 8, 11, 7, 10, 10, 6, 11, 8, 6, 7, 8, 9, 6, 11, 7, 5, 10, 4, 11, 7, 8, 10, 4, 5, 6, 9, 9, 10, 2, 6, 9, 11, 6, 6, 6, 5, 5, 6, 8, 2, 8, 11, 6, 8, 8, 11, 9, 5, 7, 7, 7, 7, 4, 9, 13, 6, 4, 7, 9, 10, 8, 8, 4, 5, 10, 11, 6, 10, 12, 10, 10, 6, 5, 11, 14, 12, 8, 9, 13, 8, 6, 7, 7, 7, 5, 12, 8, 2, 13, 8, 9, 5, 4, 7, 9, 6, 4, 6, 5, 11, 7, 5, 14, 6, 14, 7, 4, 10, 9, 5, 9, 6, 6, 6, 8, 5, 9, 6, 8, 4, 3, 4, 12, 7, 10, 7, 7, 9, 9, 13, 7, 4, 7, 7, 14, 12, 7, 10, 5, 7]\n",
      "Genrtn 33: mean = 8.19  stddev = 2.538483799436191  max = 16 [6, 9, 6, 5, 9, 13, 5, 7, 4, 9, 7, 4, 6, 7, 6, 10, 9, 8, 6, 8, 14, 12, 9, 8, 5, 9, 10, 8, 7, 8, 8, 8, 10, 14, 12, 8, 7, 6, 8, 8, 6, 8, 5, 12, 7, 4, 7, 8, 5, 9, 5, 8, 9, 9, 11, 6, 8, 8, 8, 3, 10, 12, 9, 8, 9, 3, 9, 7, 4, 9, 8, 7, 8, 5, 12, 7, 8, 4, 9, 9, 7, 8, 10, 8, 9, 7, 11, 6, 6, 8, 9, 9, 3, 8, 12, 10, 9, 5, 11, 10, 5, 9, 9, 8, 9, 5, 12, 6, 8, 12, 9, 4, 7, 7, 9, 9, 8, 7, 8, 6, 2, 15, 11, 11, 9, 10, 10, 10, 7, 2, 10, 10, 7, 4, 6, 9, 8, 6, 8, 12, 7, 7, 11, 8, 7, 6, 11, 9, 12, 8, 8, 8, 6, 13, 8, 9, 12, 8, 7, 5, 8, 5, 5, 15, 10, 16, 10, 5, 6, 6, 11, 10, 12, 9, 11, 12, 6, 9, 11, 7, 5, 11, 8, 7, 5, 12, 8, 10, 8, 6, 10, 12, 6, 13, 5, 11, 10, 10, 6, 5]\n",
      "Genrtn 34: mean = 7.84  stddev = 2.7989998213647675  max = 15 [6, 5, 8, 9, 8, 8, 6, 13, 12, 6, 6, 4, 7, 6, 8, 12, 7, 2, 10, 7, 9, 5, 7, 7, 12, 7, 10, 6, 9, 8, 5, 10, 2, 10, 7, 3, 8, 6, 9, 5, 3, 10, 7, 8, 13, 8, 3, 4, 9, 11, 8, 11, 8, 12, 7, 8, 7, 9, 7, 14, 10, 11, 9, 4, 14, 11, 9, 6, 6, 11, 11, 8, 7, 8, 8, 13, 8, 8, 7, 7, 11, 6, 11, 9, 6, 5, 11, 7, 7, 8, 6, 8, 6, 13, 12, 10, 11, 10, 7, 12, 8, 4, 11, 7, 7, 5, 6, 9, 5, 10, 11, 9, 3, 2, 8, 8, 7, 13, 5, 4, 9, 5, 6, 9, 8, 8, 13, 8, 7, 6, 8, 4, 8, 8, 11, 7, 8, 3, 11, 5, 5, 8, 9, 9, 9, 3, 9, 3, 6, 9, 3, 8, 5, 9, 9, 4, 3, 6, 11, 7, 15, 5, 8, 7, 10, 6, 4, 9, 8, 11, 5, 4, 6, 9, 8, 13, 3, 2, 11, 6, 5, 6, 13, 9, 7, 12, 11, 11, 11, 5, 10, 12, 8, 5, 9, 6, 13, 3, 12, 7]\n",
      "Genrtn 35: mean = 7.925  stddev = 2.986532270041628  max = 18 [8, 6, 7, 10, 6, 7, 3, 4, 13, 2, 5, 7, 5, 11, 5, 3, 4, 9, 10, 3, 6, 8, 3, 13, 6, 5, 9, 6, 5, 5, 8, 9, 7, 6, 8, 5, 9, 5, 6, 5, 9, 13, 10, 5, 4, 6, 6, 8, 6, 8, 13, 12, 12, 8, 9, 6, 9, 9, 3, 6, 7, 11, 7, 7, 8, 8, 9, 9, 7, 11, 6, 7, 12, 10, 10, 6, 11, 2, 7, 4, 9, 11, 10, 12, 9, 13, 10, 14, 6, 4, 9, 9, 10, 11, 6, 12, 5, 7, 7, 7, 14, 9, 4, 10, 5, 5, 7, 2, 13, 11, 11, 6, 7, 8, 2, 6, 6, 9, 4, 11, 8, 15, 8, 6, 13, 8, 12, 12, 6, 8, 1, 7, 4, 9, 11, 11, 9, 8, 12, 11, 8, 6, 8, 8, 6, 8, 6, 6, 7, 12, 6, 7, 12, 11, 7, 9, 6, 13, 13, 9, 6, 12, 5, 6, 11, 7, 5, 8, 8, 4, 11, 10, 5, 8, 8, 10, 5, 8, 12, 5, 5, 4, 11, 7, 4, 12, 8, 15, 6, 8, 8, 3, 18, 9, 6, 5, 10, 8, 11, 12]\n",
      "Genrtn 36: mean = 7.93  stddev = 2.6749018673588756  max = 17 [10, 14, 8, 6, 9, 11, 3, 5, 13, 12, 3, 10, 9, 8, 2, 9, 13, 7, 11, 10, 9, 4, 16, 10, 4, 3, 10, 10, 5, 5, 7, 8, 9, 7, 3, 8, 5, 7, 4, 8, 8, 7, 8, 10, 7, 11, 10, 8, 6, 11, 9, 8, 9, 10, 10, 8, 11, 5, 7, 5, 12, 5, 10, 9, 11, 7, 10, 8, 7, 6, 6, 8, 5, 8, 8, 3, 6, 6, 12, 6, 9, 10, 14, 5, 6, 1, 10, 9, 7, 7, 5, 5, 10, 7, 10, 6, 9, 12, 11, 7, 9, 10, 5, 8, 3, 8, 6, 17, 8, 11, 5, 7, 6, 8, 6, 10, 6, 8, 6, 6, 9, 10, 5, 5, 8, 4, 7, 11, 9, 8, 5, 10, 9, 9, 3, 3, 10, 11, 5, 14, 12, 8, 10, 4, 10, 7, 6, 9, 8, 8, 5, 11, 8, 6, 9, 7, 9, 9, 9, 9, 6, 10, 6, 10, 11, 9, 5, 4, 9, 7, 5, 4, 6, 11, 11, 7, 7, 7, 3, 8, 10, 5, 5, 9, 6, 9, 10, 9, 10, 9, 9, 9, 14, 6, 11, 10, 9, 8, 7, 7]\n",
      "Genrtn 37: mean = 7.615  stddev = 2.794060665053642  max = 20 [7, 15, 6, 5, 8, 6, 8, 7, 6, 6, 5, 6, 8, 7, 6, 2, 6, 9, 1, 3, 3, 5, 11, 8, 6, 10, 5, 13, 11, 8, 6, 3, 9, 8, 7, 9, 4, 9, 8, 8, 13, 8, 6, 10, 9, 7, 6, 8, 12, 4, 6, 12, 8, 9, 9, 9, 5, 7, 5, 3, 4, 6, 8, 6, 8, 7, 8, 6, 8, 7, 9, 10, 9, 6, 10, 6, 7, 6, 6, 12, 9, 12, 7, 8, 8, 8, 12, 6, 4, 5, 9, 12, 9, 5, 7, 7, 9, 7, 9, 10, 10, 6, 5, 7, 2, 3, 10, 4, 8, 12, 13, 8, 14, 4, 10, 9, 5, 9, 6, 8, 11, 15, 4, 4, 20, 7, 7, 9, 7, 6, 4, 8, 9, 10, 8, 10, 7, 6, 4, 8, 8, 14, 4, 7, 11, 9, 6, 3, 7, 12, 8, 8, 6, 8, 11, 7, 13, 9, 4, 3, 11, 4, 5, 7, 5, 9, 11, 12, 9, 4, 5, 4, 7, 6, 3, 9, 11, 8, 7, 8, 10, 8, 7, 4, 6, 8, 4, 9, 8, 7, 10, 6, 11, 10, 10, 10, 10, 5, 7, 7]\n",
      "Genrtn 38: mean = 7.65  stddev = 2.6433879775772606  max = 15 [6, 10, 11, 2, 9, 6, 4, 6, 3, 12, 14, 7, 9, 8, 7, 5, 10, 11, 7, 7, 8, 8, 9, 7, 4, 10, 6, 4, 5, 10, 7, 7, 9, 8, 10, 6, 11, 7, 8, 3, 5, 15, 10, 12, 7, 7, 6, 11, 5, 6, 6, 9, 4, 11, 4, 9, 8, 4, 6, 8, 11, 4, 10, 4, 9, 4, 10, 6, 6, 3, 6, 6, 1, 9, 8, 7, 11, 8, 5, 8, 9, 5, 11, 11, 7, 9, 10, 7, 13, 7, 9, 9, 8, 8, 13, 7, 10, 7, 4, 9, 9, 9, 8, 6, 11, 5, 12, 3, 6, 6, 4, 4, 10, 8, 6, 11, 8, 11, 10, 9, 7, 7, 2, 11, 8, 6, 6, 11, 6, 10, 13, 9, 6, 4, 7, 7, 7, 14, 6, 2, 10, 5, 8, 8, 10, 8, 11, 9, 6, 6, 10, 6, 8, 10, 9, 8, 4, 7, 10, 11, 5, 5, 4, 6, 9, 9, 10, 10, 8, 9, 9, 8, 2, 5, 9, 7, 6, 5, 4, 9, 11, 6, 8, 10, 9, 6, 7, 10, 1, 9, 6, 5, 7, 9, 14, 6, 7, 8, 10, 10]\n",
      "Genrtn 39: mean = 8.165  stddev = 2.9304905732658484  max = 18 [5, 8, 6, 6, 6, 8, 11, 10, 8, 9, 10, 6, 8, 11, 8, 14, 14, 7, 9, 6, 11, 6, 5, 14, 10, 8, 4, 5, 18, 6, 13, 14, 10, 7, 6, 6, 6, 9, 9, 7, 9, 7, 14, 4, 9, 13, 10, 8, 5, 5, 8, 10, 8, 12, 9, 10, 13, 5, 12, 10, 8, 5, 6, 5, 9, 9, 8, 7, 11, 10, 2, 11, 11, 6, 12, 5, 6, 7, 14, 10, 5, 9, 11, 17, 9, 8, 9, 4, 10, 12, 9, 13, 8, 9, 5, 9, 7, 5, 11, 8, 6, 5, 10, 4, 12, 7, 9, 7, 5, 8, 7, 10, 5, 5, 5, 10, 10, 12, 6, 7, 9, 12, 8, 10, 5, 9, 5, 15, 8, 5, 7, 5, 12, 5, 11, 9, 10, 6, 8, 5, 9, 10, 8, 4, 6, 9, 7, 2, 4, 5, 10, 9, 10, 12, 6, 7, 7, 6, 5, 8, 6, 8, 11, 4, 6, 13, 9, 8, 7, 5, 4, 9, 3, 12, 8, 8, 6, 4, 4, 4, 7, 4, 7, 6, 11, 8, 7, 12, 7, 10, 14, 14, 9, 12, 11, 8, 3, 5, 7, 9]\n",
      "Genrtn 40: mean = 7.795  stddev = 2.8675730156353474  max = 18 [9, 5, 12, 14, 9, 8, 3, 5, 9, 9, 12, 4, 8, 12, 8, 9, 10, 13, 8, 11, 7, 4, 5, 6, 9, 7, 9, 10, 8, 10, 10, 8, 8, 9, 7, 3, 10, 2, 11, 5, 7, 5, 9, 6, 16, 6, 6, 6, 5, 6, 11, 8, 8, 6, 9, 8, 6, 9, 2, 7, 4, 10, 11, 9, 5, 11, 8, 10, 11, 10, 5, 9, 5, 18, 9, 8, 10, 8, 4, 8, 7, 15, 6, 12, 10, 11, 3, 10, 5, 9, 10, 10, 3, 10, 7, 6, 12, 10, 5, 7, 1, 4, 4, 7, 4, 5, 7, 5, 13, 5, 5, 9, 6, 9, 7, 6, 6, 9, 13, 5, 17, 10, 7, 10, 7, 9, 11, 7, 5, 3, 4, 6, 8, 8, 9, 4, 7, 7, 11, 12, 6, 7, 3, 7, 6, 10, 6, 9, 11, 10, 6, 12, 4, 9, 11, 4, 11, 6, 10, 9, 10, 8, 6, 8, 10, 8, 10, 4, 8, 5, 9, 10, 11, 6, 8, 2, 7, 3, 4, 6, 6, 8, 8, 11, 9, 9, 4, 7, 6, 8, 7, 9, 8, 11, 6, 3, 9, 6, 8, 11]\n",
      "Genrtn 41: mean = 8.06  stddev = 2.6431799030712986  max = 15 [3, 10, 8, 12, 12, 6, 5, 9, 11, 3, 5, 5, 7, 8, 10, 4, 10, 5, 11, 5, 7, 6, 9, 9, 7, 10, 10, 9, 7, 8, 5, 6, 8, 11, 12, 4, 4, 11, 7, 7, 10, 13, 8, 13, 8, 12, 11, 11, 6, 10, 6, 6, 8, 5, 11, 6, 8, 7, 6, 9, 9, 9, 7, 7, 10, 10, 8, 5, 9, 10, 6, 8, 8, 6, 12, 15, 7, 8, 12, 5, 8, 6, 7, 8, 5, 5, 6, 6, 9, 8, 7, 8, 5, 8, 5, 11, 10, 8, 3, 3, 9, 9, 9, 14, 10, 10, 7, 11, 5, 6, 7, 5, 9, 15, 7, 7, 7, 10, 7, 10, 4, 6, 10, 11, 9, 10, 7, 9, 4, 7, 6, 4, 7, 10, 10, 5, 7, 9, 8, 4, 8, 6, 9, 7, 7, 11, 5, 9, 10, 8, 8, 13, 9, 7, 4, 8, 6, 7, 9, 13, 6, 9, 4, 10, 12, 8, 9, 7, 10, 9, 14, 12, 12, 8, 9, 4, 11, 5, 14, 7, 12, 15, 8, 8, 10, 6, 5, 14, 6, 3, 4, 7, 9, 11, 5, 6, 10, 9, 7, 5]\n",
      "Genrtn 42: mean = 8.165  stddev = 2.950893932353381  max = 17 [10, 8, 10, 9, 7, 7, 10, 9, 10, 11, 5, 17, 12, 9, 6, 11, 9, 7, 10, 9, 7, 12, 3, 6, 4, 9, 5, 7, 8, 10, 10, 9, 6, 9, 16, 7, 6, 6, 7, 6, 4, 7, 14, 4, 7, 7, 5, 12, 4, 11, 10, 10, 6, 8, 7, 10, 7, 10, 10, 11, 10, 8, 4, 10, 5, 10, 6, 5, 6, 7, 8, 5, 8, 5, 13, 9, 6, 8, 7, 7, 11, 9, 10, 10, 8, 12, 12, 9, 6, 5, 2, 7, 5, 3, 7, 4, 16, 3, 14, 8, 11, 8, 7, 12, 8, 8, 6, 8, 7, 6, 6, 8, 8, 9, 11, 10, 8, 9, 6, 14, 12, 10, 11, 6, 8, 5, 8, 15, 10, 6, 8, 13, 6, 8, 5, 9, 10, 8, 9, 9, 8, 15, 9, 10, 5, 11, 4, 7, 7, 6, 8, 8, 3, 8, 3, 11, 7, 6, 8, 5, 9, 12, 10, 8, 5, 3, 11, 9, 6, 12, 8, 11, 9, 8, 5, 5, 12, 5, 6, 7, 3, 16, 5, 5, 10, 15, 13, 11, 8, 2, 13, 14, 9, 8, 7, 8, 3, 5, 5, 6]\n",
      "Genrtn 43: mean = 8.11  stddev = 2.8174279050225937  max = 18 [9, 9, 7, 5, 8, 5, 8, 3, 7, 9, 18, 7, 9, 7, 5, 7, 8, 5, 7, 11, 10, 6, 10, 11, 12, 3, 8, 6, 4, 7, 4, 6, 6, 12, 5, 3, 8, 7, 9, 9, 7, 7, 5, 8, 13, 10, 11, 12, 10, 11, 8, 8, 8, 10, 5, 8, 9, 10, 6, 5, 4, 9, 11, 10, 9, 9, 3, 5, 13, 9, 8, 7, 9, 7, 5, 8, 6, 12, 11, 10, 10, 9, 8, 10, 8, 5, 1, 12, 6, 14, 8, 6, 6, 14, 5, 9, 11, 9, 9, 11, 6, 12, 9, 3, 5, 8, 7, 4, 6, 6, 4, 3, 8, 6, 10, 11, 7, 11, 8, 9, 7, 6, 9, 15, 6, 7, 12, 9, 10, 10, 13, 10, 6, 14, 10, 12, 5, 6, 13, 5, 10, 4, 12, 11, 4, 16, 7, 9, 9, 8, 7, 4, 8, 8, 5, 3, 13, 9, 5, 9, 6, 5, 12, 8, 8, 10, 5, 13, 4, 10, 7, 7, 5, 8, 8, 7, 9, 5, 7, 9, 8, 9, 6, 8, 10, 12, 6, 13, 9, 6, 13, 10, 6, 10, 7, 10, 5, 8, 9, 8]\n",
      "Genrtn 44: mean = 7.57  stddev = 2.8627085076898764  max = 16 [10, 13, 5, 8, 8, 4, 7, 11, 7, 7, 7, 4, 4, 5, 7, 4, 8, 9, 11, 7, 5, 6, 7, 10, 5, 4, 4, 5, 6, 9, 5, 3, 6, 3, 12, 10, 11, 12, 8, 6, 8, 7, 7, 6, 7, 11, 7, 6, 7, 7, 5, 6, 6, 9, 13, 9, 7, 10, 8, 7, 7, 7, 8, 10, 6, 5, 8, 13, 13, 6, 9, 10, 6, 1, 0, 6, 11, 9, 10, 11, 6, 7, 9, 4, 4, 7, 4, 6, 6, 8, 3, 6, 9, 9, 7, 5, 14, 4, 7, 8, 8, 10, 4, 6, 8, 14, 7, 5, 3, 9, 6, 8, 13, 11, 13, 6, 11, 12, 8, 6, 6, 8, 7, 6, 7, 6, 11, 7, 7, 6, 10, 5, 6, 10, 4, 5, 5, 7, 4, 7, 10, 6, 5, 8, 4, 9, 8, 7, 6, 5, 8, 6, 13, 10, 8, 4, 6, 11, 4, 8, 7, 10, 13, 7, 5, 11, 15, 13, 16, 9, 14, 7, 10, 4, 8, 4, 8, 12, 7, 10, 5, 9, 7, 7, 8, 1, 6, 13, 6, 10, 10, 4, 13, 6, 3, 6, 8, 13, 8, 8]\n",
      "Genrtn 45: mean = 8.03  stddev = 2.6924152725759076  max = 14 [5, 6, 4, 7, 8, 6, 5, 4, 10, 7, 7, 11, 10, 6, 6, 9, 12, 11, 6, 11, 10, 4, 5, 4, 8, 11, 10, 9, 9, 10, 9, 7, 7, 4, 5, 13, 7, 7, 5, 10, 10, 8, 6, 4, 7, 12, 3, 5, 10, 9, 14, 7, 12, 7, 7, 9, 7, 8, 9, 7, 4, 7, 8, 9, 4, 12, 8, 10, 4, 6, 10, 8, 10, 8, 10, 11, 6, 10, 6, 7, 5, 7, 8, 12, 10, 9, 11, 12, 7, 6, 14, 6, 5, 4, 4, 4, 8, 11, 6, 12, 6, 6, 11, 7, 7, 5, 7, 5, 4, 9, 10, 7, 5, 8, 7, 9, 9, 4, 12, 5, 5, 8, 10, 4, 8, 8, 9, 11, 7, 7, 6, 12, 14, 9, 10, 10, 11, 11, 8, 8, 6, 13, 5, 13, 11, 10, 5, 9, 7, 12, 6, 11, 7, 10, 10, 7, 5, 10, 7, 8, 10, 3, 8, 5, 10, 8, 8, 4, 10, 9, 10, 10, 5, 14, 7, 10, 7, 13, 9, 7, 9, 11, 5, 4, 6, 7, 6, 6, 7, 14, 4, 7, 2, 8, 8, 13, 11, 14, 8, 13]\n",
      "Genrtn 46: mean = 7.765  stddev = 2.9016848553900543  max = 16 [9, 5, 6, 9, 7, 9, 6, 10, 8, 6, 5, 12, 15, 10, 9, 6, 2, 11, 13, 8, 9, 8, 10, 9, 6, 4, 6, 10, 12, 6, 6, 6, 13, 7, 9, 7, 8, 4, 10, 8, 5, 8, 3, 11, 4, 4, 7, 8, 7, 5, 7, 11, 4, 7, 7, 10, 11, 8, 3, 13, 8, 5, 4, 8, 9, 7, 14, 4, 8, 12, 10, 12, 15, 10, 6, 8, 6, 5, 9, 7, 5, 8, 8, 12, 9, 6, 6, 5, 8, 2, 7, 7, 7, 7, 9, 7, 7, 3, 4, 9, 5, 11, 10, 4, 8, 8, 6, 9, 3, 12, 6, 9, 6, 8, 7, 10, 7, 10, 7, 6, 7, 10, 6, 7, 6, 4, 10, 16, 13, 8, 9, 2, 5, 12, 11, 8, 11, 9, 9, 11, 9, 10, 14, 3, 11, 9, 8, 3, 4, 11, 14, 3, 8, 6, 9, 7, 2, 1, 9, 9, 7, 7, 7, 10, 5, 4, 6, 7, 11, 7, 11, 2, 12, 10, 12, 10, 0, 4, 6, 9, 6, 6, 9, 8, 4, 10, 8, 7, 7, 8, 7, 9, 12, 10, 4, 9, 11, 8, 11, 6]\n",
      "Genrtn 47: mean = 7.945  stddev = 2.853414621116251  max = 16 [9, 7, 10, 12, 9, 10, 11, 11, 9, 9, 5, 9, 15, 5, 7, 6, 4, 12, 8, 4, 11, 8, 12, 9, 8, 2, 7, 7, 12, 4, 9, 14, 4, 13, 4, 8, 13, 9, 8, 7, 6, 6, 10, 10, 7, 7, 11, 15, 4, 6, 7, 9, 9, 7, 11, 7, 6, 10, 9, 12, 13, 12, 7, 12, 8, 5, 8, 5, 4, 7, 13, 7, 6, 7, 2, 7, 8, 9, 9, 5, 4, 9, 2, 9, 7, 7, 3, 7, 10, 11, 12, 4, 3, 11, 7, 6, 4, 8, 11, 6, 10, 5, 4, 7, 7, 10, 8, 6, 10, 8, 13, 9, 11, 4, 7, 8, 12, 4, 10, 7, 11, 8, 8, 4, 10, 7, 7, 9, 11, 9, 8, 9, 8, 10, 10, 9, 8, 9, 6, 4, 10, 6, 6, 6, 7, 10, 7, 5, 3, 9, 3, 11, 13, 5, 5, 11, 5, 6, 7, 13, 10, 5, 5, 4, 12, 2, 6, 9, 16, 3, 10, 10, 8, 4, 10, 5, 7, 10, 10, 8, 8, 7, 5, 11, 8, 13, 11, 4, 3, 9, 5, 6, 9, 9, 7, 8, 11, 8, 9, 6]\n",
      "Genrtn 48: mean = 7.85  stddev = 2.8226760352544886  max = 15 [11, 7, 4, 7, 6, 9, 11, 5, 7, 10, 8, 4, 12, 4, 6, 11, 9, 11, 5, 8, 9, 7, 6, 7, 14, 7, 8, 12, 10, 12, 6, 9, 7, 5, 11, 5, 11, 10, 4, 10, 14, 3, 6, 8, 9, 9, 14, 10, 11, 8, 12, 8, 8, 8, 8, 7, 9, 4, 11, 7, 8, 7, 6, 5, 8, 5, 7, 7, 13, 7, 9, 10, 8, 4, 8, 5, 7, 7, 9, 6, 5, 15, 7, 13, 1, 8, 10, 6, 7, 7, 12, 6, 10, 8, 8, 4, 10, 11, 5, 6, 7, 8, 10, 10, 6, 7, 8, 6, 8, 7, 4, 6, 7, 5, 8, 6, 5, 9, 8, 9, 14, 11, 9, 5, 8, 11, 5, 9, 8, 4, 5, 9, 7, 2, 11, 13, 9, 7, 8, 6, 10, 5, 8, 11, 10, 4, 10, 12, 4, 13, 9, 11, 6, 4, 7, 11, 13, 4, 2, 3, 7, 11, 4, 12, 8, 13, 3, 8, 5, 7, 9, 11, 6, 5, 8, 5, 11, 15, 7, 5, 4, 8, 4, 5, 11, 9, 5, 5, 9, 4, 10, 5, 5, 11, 4, 10, 9, 11, 11, 4]\n",
      "Genrtn 49: mean = 8.11  stddev = 2.754614310570538  max = 16 [9, 10, 10, 9, 7, 7, 6, 5, 7, 8, 6, 7, 5, 13, 7, 6, 5, 11, 8, 4, 6, 10, 16, 10, 6, 4, 12, 5, 8, 7, 10, 7, 8, 6, 15, 10, 8, 7, 6, 6, 11, 7, 9, 6, 9, 12, 6, 13, 13, 7, 8, 12, 10, 6, 10, 10, 12, 10, 11, 4, 12, 6, 7, 4, 12, 8, 4, 6, 8, 8, 6, 11, 10, 10, 6, 7, 6, 15, 7, 8, 8, 2, 6, 9, 12, 10, 7, 9, 6, 8, 7, 5, 8, 10, 9, 8, 10, 6, 8, 8, 5, 11, 11, 9, 11, 7, 9, 9, 11, 5, 15, 6, 13, 6, 10, 6, 10, 7, 9, 9, 11, 8, 5, 10, 6, 6, 4, 1, 12, 5, 12, 3, 6, 6, 15, 7, 8, 6, 6, 14, 11, 11, 8, 3, 7, 6, 4, 5, 6, 10, 10, 7, 6, 8, 5, 5, 8, 6, 5, 8, 4, 10, 6, 5, 9, 12, 8, 3, 5, 8, 11, 7, 11, 7, 6, 6, 4, 7, 8, 11, 14, 8, 7, 11, 12, 10, 7, 10, 9, 9, 11, 12, 9, 11, 11, 4, 9, 7, 6, 8]\n",
      "Genrtn 50: mean = 8.01  stddev = 2.5961317377976028  max = 16 [10, 8, 7, 10, 7, 4, 10, 9, 13, 9, 5, 11, 7, 4, 6, 10, 11, 6, 4, 3, 6, 9, 4, 10, 6, 11, 7, 8, 4, 7, 5, 8, 9, 7, 10, 4, 8, 9, 4, 6, 6, 6, 7, 5, 7, 7, 8, 6, 8, 7, 9, 11, 7, 5, 7, 9, 5, 9, 8, 11, 4, 10, 5, 5, 14, 10, 12, 11, 5, 4, 5, 7, 11, 3, 8, 8, 8, 9, 6, 4, 6, 7, 9, 10, 6, 8, 16, 5, 8, 8, 3, 2, 6, 6, 7, 7, 11, 5, 11, 10, 6, 7, 12, 7, 9, 8, 11, 6, 8, 8, 9, 9, 10, 7, 6, 6, 6, 4, 10, 10, 9, 9, 10, 6, 9, 11, 12, 10, 6, 7, 8, 7, 13, 11, 10, 7, 11, 9, 10, 5, 10, 5, 13, 12, 5, 9, 13, 10, 7, 7, 9, 8, 8, 6, 9, 7, 11, 7, 12, 12, 4, 6, 9, 6, 10, 13, 6, 7, 10, 8, 6, 4, 11, 10, 7, 9, 3, 9, 16, 7, 6, 5, 10, 10, 9, 6, 13, 11, 8, 9, 12, 11, 8, 8, 6, 10, 8, 12, 10, 6]\n",
      "Genrtn 51: mean = 7.915  stddev = 2.8509252883932263  max = 15 [8, 9, 9, 5, 7, 8, 4, 9, 5, 10, 9, 7, 8, 10, 7, 10, 6, 13, 8, 12, 3, 12, 11, 7, 11, 10, 14, 8, 2, 8, 4, 12, 5, 12, 4, 10, 12, 4, 15, 7, 9, 8, 10, 7, 7, 6, 6, 8, 10, 5, 11, 10, 10, 9, 12, 5, 5, 4, 6, 6, 7, 12, 6, 10, 2, 9, 3, 6, 5, 6, 4, 8, 9, 10, 7, 8, 15, 13, 4, 7, 11, 9, 10, 6, 6, 7, 7, 10, 7, 7, 8, 12, 6, 9, 8, 10, 8, 14, 7, 11, 4, 6, 9, 10, 8, 12, 6, 12, 10, 6, 6, 10, 9, 7, 4, 14, 13, 3, 8, 8, 10, 7, 11, 5, 10, 8, 6, 10, 4, 6, 9, 3, 8, 11, 6, 8, 9, 6, 7, 4, 7, 7, 3, 7, 10, 8, 8, 6, 6, 11, 5, 5, 9, 14, 8, 6, 7, 10, 7, 7, 9, 12, 3, 8, 11, 9, 3, 7, 8, 11, 4, 6, 2, 6, 10, 14, 9, 3, 12, 4, 6, 13, 9, 13, 7, 6, 6, 7, 5, 8, 9, 11, 9, 3, 3, 9, 7, 11, 8, 5]\n",
      "Genrtn 52: mean = 8.0  stddev = 2.8600699292150185  max = 16 [8, 10, 6, 14, 8, 8, 6, 4, 7, 14, 11, 3, 11, 8, 8, 9, 6, 10, 11, 8, 8, 6, 8, 13, 9, 13, 8, 8, 12, 5, 6, 8, 6, 10, 6, 11, 6, 4, 12, 2, 6, 13, 11, 13, 9, 9, 7, 2, 9, 3, 8, 10, 6, 11, 6, 14, 4, 9, 12, 6, 13, 10, 9, 2, 15, 9, 6, 8, 10, 6, 8, 8, 5, 7, 16, 8, 8, 12, 7, 7, 8, 5, 6, 14, 7, 8, 8, 11, 7, 6, 8, 5, 9, 8, 12, 8, 10, 7, 5, 9, 4, 13, 8, 3, 7, 4, 8, 6, 9, 4, 7, 10, 7, 5, 9, 8, 10, 2, 6, 4, 8, 5, 4, 12, 6, 7, 7, 10, 9, 11, 6, 11, 15, 15, 6, 8, 7, 12, 9, 9, 10, 11, 11, 7, 11, 5, 9, 4, 10, 10, 12, 8, 8, 7, 5, 6, 7, 6, 8, 13, 3, 6, 9, 7, 9, 5, 7, 4, 7, 7, 8, 5, 3, 6, 6, 3, 10, 7, 7, 7, 10, 9, 7, 3, 10, 8, 12, 8, 11, 6, 13, 6, 6, 7, 6, 8, 9, 10, 6, 6]\n",
      "Genrtn 53: mean = 8.02  stddev = 2.7856058586957344  max = 18 [9, 7, 9, 10, 11, 8, 8, 5, 8, 5, 5, 10, 5, 12, 15, 12, 5, 5, 8, 7, 5, 6, 8, 6, 5, 7, 10, 9, 5, 9, 4, 6, 5, 4, 10, 8, 13, 6, 7, 7, 10, 8, 8, 5, 9, 10, 8, 13, 9, 11, 7, 8, 6, 6, 9, 6, 13, 7, 7, 7, 5, 4, 5, 6, 8, 10, 5, 2, 11, 9, 6, 11, 12, 9, 14, 10, 11, 7, 10, 4, 7, 8, 10, 7, 7, 3, 10, 13, 5, 8, 12, 9, 5, 9, 9, 9, 10, 5, 6, 10, 10, 9, 10, 9, 7, 8, 6, 9, 10, 8, 11, 13, 12, 4, 4, 11, 13, 14, 10, 8, 7, 9, 9, 7, 7, 6, 11, 2, 8, 8, 7, 8, 12, 7, 5, 6, 10, 3, 10, 6, 5, 9, 7, 18, 9, 12, 4, 8, 5, 7, 12, 12, 6, 8, 10, 7, 2, 6, 4, 6, 11, 8, 8, 5, 10, 7, 3, 5, 3, 6, 6, 7, 14, 8, 9, 6, 5, 7, 11, 14, 10, 10, 6, 7, 9, 9, 7, 12, 4, 5, 9, 14, 9, 6, 11, 10, 7, 10, 7, 6]\n",
      "Genrtn 54: mean = 8.09  stddev = 2.738959656511939  max = 16 [14, 7, 7, 10, 7, 9, 13, 6, 10, 8, 8, 12, 10, 9, 6, 8, 6, 4, 5, 9, 5, 6, 3, 13, 11, 12, 7, 2, 7, 7, 12, 16, 11, 10, 7, 11, 13, 8, 14, 7, 7, 5, 9, 5, 10, 6, 13, 6, 8, 10, 7, 13, 8, 7, 5, 7, 4, 6, 10, 5, 9, 7, 7, 12, 4, 7, 4, 7, 6, 15, 10, 7, 8, 9, 9, 10, 5, 6, 12, 9, 6, 10, 8, 8, 10, 9, 7, 12, 8, 6, 7, 14, 8, 8, 10, 5, 7, 13, 4, 10, 12, 7, 6, 8, 5, 5, 5, 7, 5, 5, 10, 6, 5, 10, 8, 4, 8, 9, 7, 7, 7, 9, 8, 7, 9, 7, 12, 5, 6, 10, 5, 11, 6, 4, 9, 6, 8, 8, 7, 10, 9, 5, 7, 9, 7, 11, 5, 8, 8, 10, 8, 6, 8, 12, 9, 8, 6, 7, 13, 4, 12, 13, 6, 10, 6, 7, 14, 4, 6, 6, 8, 8, 7, 16, 8, 4, 12, 8, 8, 4, 8, 7, 5, 11, 8, 11, 8, 10, 11, 5, 7, 7, 6, 5, 4, 14, 7, 7, 10, 13]\n",
      "Genrtn 55: mean = 8.325  stddev = 2.8669452384027148  max = 18 [7, 14, 4, 14, 9, 7, 6, 15, 9, 5, 4, 11, 9, 7, 10, 8, 7, 4, 11, 6, 9, 14, 12, 6, 5, 6, 6, 4, 5, 8, 15, 8, 8, 11, 8, 6, 5, 8, 12, 5, 8, 14, 14, 5, 18, 8, 6, 10, 9, 8, 9, 7, 4, 7, 10, 11, 12, 10, 8, 8, 3, 16, 2, 9, 11, 7, 11, 10, 6, 13, 3, 9, 9, 8, 8, 6, 6, 9, 12, 6, 7, 6, 7, 8, 4, 5, 9, 11, 7, 9, 10, 11, 5, 8, 9, 9, 11, 11, 15, 9, 8, 6, 7, 6, 10, 11, 12, 10, 7, 12, 7, 9, 12, 8, 12, 8, 7, 13, 3, 9, 6, 6, 9, 3, 6, 7, 10, 3, 6, 7, 9, 6, 7, 4, 9, 10, 6, 4, 10, 6, 8, 9, 9, 11, 8, 6, 5, 7, 10, 11, 10, 9, 10, 4, 12, 6, 10, 13, 8, 6, 6, 14, 4, 10, 6, 8, 6, 8, 7, 10, 5, 9, 8, 11, 7, 9, 9, 8, 8, 7, 8, 10, 5, 5, 6, 11, 3, 11, 13, 7, 9, 12, 11, 12, 8, 7, 12, 9, 8, 6]\n",
      "Genrtn 56: mean = 7.97  stddev = 2.903291235821856  max = 18 [5, 8, 12, 10, 8, 4, 8, 5, 11, 8, 7, 12, 11, 10, 10, 9, 6, 11, 8, 18, 7, 5, 6, 7, 7, 8, 3, 7, 5, 8, 7, 10, 9, 11, 3, 4, 8, 11, 4, 7, 5, 10, 8, 5, 17, 7, 12, 9, 5, 9, 10, 9, 11, 12, 11, 11, 8, 10, 9, 8, 6, 10, 6, 8, 11, 7, 8, 8, 2, 6, 10, 6, 6, 8, 10, 9, 3, 9, 15, 7, 7, 10, 5, 8, 10, 6, 7, 13, 8, 10, 8, 12, 6, 8, 10, 3, 5, 7, 11, 12, 2, 10, 4, 7, 8, 5, 7, 11, 11, 6, 4, 11, 7, 6, 9, 3, 6, 7, 8, 3, 3, 7, 5, 3, 10, 4, 9, 3, 5, 8, 6, 7, 13, 6, 8, 9, 9, 13, 10, 10, 12, 9, 5, 6, 5, 14, 11, 4, 10, 8, 8, 2, 7, 9, 6, 7, 8, 7, 11, 10, 6, 7, 16, 11, 6, 4, 11, 7, 4, 11, 10, 10, 9, 8, 4, 9, 6, 6, 11, 11, 8, 7, 11, 9, 6, 6, 9, 14, 4, 13, 4, 11, 9, 8, 7, 8, 5, 11, 4, 6]\n",
      "Genrtn 57: mean = 7.95  stddev = 2.5529394822439486  max = 15 [6, 11, 11, 4, 8, 10, 5, 4, 11, 15, 10, 7, 5, 8, 10, 10, 8, 10, 8, 9, 7, 3, 5, 10, 9, 6, 6, 2, 10, 5, 13, 12, 5, 9, 11, 8, 10, 9, 11, 5, 10, 12, 8, 5, 9, 6, 9, 8, 8, 2, 10, 10, 10, 8, 12, 6, 5, 4, 8, 2, 11, 8, 9, 9, 6, 13, 5, 6, 9, 9, 8, 12, 8, 12, 3, 6, 5, 7, 10, 6, 8, 7, 12, 10, 10, 9, 7, 12, 7, 5, 4, 6, 8, 9, 8, 5, 9, 3, 8, 10, 8, 9, 7, 5, 11, 8, 8, 6, 4, 7, 10, 6, 8, 10, 9, 7, 6, 6, 10, 10, 7, 9, 10, 7, 4, 7, 7, 11, 4, 11, 6, 8, 12, 6, 7, 9, 10, 6, 8, 2, 7, 8, 5, 5, 12, 6, 8, 10, 6, 8, 12, 12, 8, 9, 12, 5, 9, 9, 8, 6, 6, 7, 8, 10, 11, 3, 9, 8, 8, 4, 7, 6, 11, 12, 8, 7, 7, 9, 9, 4, 7, 12, 9, 8, 6, 7, 3, 7, 7, 12, 11, 14, 6, 9, 11, 7, 11, 7, 6, 8]\n",
      "Genrtn 58: mean = 8.275  stddev = 2.964688010567048  max = 18 [13, 8, 8, 8, 7, 8, 8, 8, 10, 9, 11, 5, 5, 10, 9, 7, 6, 7, 12, 9, 8, 10, 14, 9, 8, 12, 8, 11, 5, 5, 5, 9, 11, 8, 8, 6, 12, 3, 4, 15, 7, 5, 7, 7, 7, 8, 17, 7, 10, 8, 5, 8, 5, 9, 6, 6, 10, 6, 10, 10, 11, 11, 18, 8, 11, 10, 7, 8, 7, 5, 6, 12, 6, 18, 9, 13, 4, 8, 4, 10, 2, 8, 11, 9, 4, 13, 8, 6, 10, 8, 12, 10, 7, 9, 6, 7, 6, 8, 8, 7, 5, 9, 10, 7, 8, 9, 8, 11, 9, 4, 12, 11, 8, 8, 10, 11, 6, 7, 8, 11, 7, 5, 7, 7, 5, 11, 6, 7, 15, 8, 9, 14, 8, 11, 5, 11, 14, 9, 2, 7, 9, 9, 6, 4, 13, 7, 5, 10, 9, 8, 10, 11, 11, 4, 3, 10, 6, 8, 7, 12, 8, 8, 8, 5, 5, 8, 15, 8, 9, 9, 10, 3, 10, 5, 4, 14, 5, 7, 10, 5, 12, 13, 10, 2, 7, 5, 8, 9, 7, 9, 1, 11, 9, 9, 9, 4, 5, 10, 3, 12]\n",
      "Genrtn 59: mean = 7.58  stddev = 3.010581339210087  max = 15 [13, 10, 2, 11, 5, 4, 6, 5, 11, 9, 4, 7, 12, 10, 11, 11, 6, 1, 5, 8, 3, 8, 8, 6, 2, 6, 6, 7, 4, 2, 8, 3, 4, 10, 13, 11, 3, 10, 5, 8, 9, 15, 14, 8, 13, 6, 4, 12, 7, 11, 3, 9, 13, 6, 6, 8, 9, 5, 8, 8, 6, 8, 9, 8, 14, 11, 2, 7, 11, 7, 10, 7, 5, 6, 14, 4, 7, 11, 12, 10, 7, 14, 8, 5, 9, 3, 9, 11, 4, 10, 5, 10, 4, 11, 8, 5, 11, 7, 8, 10, 6, 9, 8, 11, 5, 8, 9, 3, 7, 11, 7, 7, 12, 10, 7, 5, 7, 9, 6, 2, 4, 9, 5, 8, 9, 12, 5, 5, 9, 6, 7, 7, 8, 5, 3, 4, 11, 14, 10, 5, 15, 11, 4, 7, 6, 7, 8, 6, 11, 4, 9, 8, 9, 5, 7, 6, 5, 8, 8, 9, 8, 4, 8, 8, 15, 9, 8, 4, 7, 11, 9, 6, 7, 4, 11, 7, 15, 7, 8, 8, 8, 7, 4, 3, 10, 4, 2, 6, 4, 9, 9, 7, 7, 5, 8, 3, 7, 8, 6, 7]\n",
      "Genrtn 60: mean = 7.86  stddev = 2.5397637685422634  max = 15 [7, 7, 9, 7, 5, 9, 11, 3, 9, 8, 9, 7, 7, 6, 4, 4, 11, 8, 4, 5, 9, 11, 6, 7, 6, 10, 8, 5, 12, 5, 3, 11, 6, 9, 7, 5, 13, 8, 8, 12, 12, 9, 8, 6, 5, 8, 10, 6, 8, 5, 10, 2, 13, 11, 12, 4, 7, 10, 4, 5, 8, 4, 9, 12, 9, 7, 10, 14, 11, 13, 7, 12, 6, 9, 9, 4, 8, 10, 8, 10, 9, 8, 6, 4, 5, 6, 4, 8, 9, 8, 4, 10, 3, 5, 10, 5, 10, 7, 8, 7, 9, 7, 8, 7, 6, 8, 15, 6, 8, 8, 10, 9, 6, 10, 7, 11, 1, 9, 9, 11, 10, 9, 6, 11, 10, 7, 8, 8, 3, 8, 6, 8, 6, 11, 7, 7, 5, 6, 11, 9, 11, 4, 8, 9, 9, 8, 8, 10, 11, 4, 9, 6, 7, 8, 7, 7, 10, 10, 9, 13, 8, 5, 8, 8, 9, 5, 5, 6, 8, 8, 6, 8, 10, 6, 9, 5, 8, 8, 13, 7, 8, 2, 6, 7, 10, 11, 9, 12, 8, 8, 4, 6, 10, 13, 4, 10, 7, 8, 11, 7]\n",
      "Genrtn 61: mean = 7.61  stddev = 2.954301948007346  max = 15 [8, 15, 6, 10, 7, 6, 10, 4, 12, 8, 4, 13, 6, 11, 9, 4, 2, 6, 4, 11, 6, 9, 7, 5, 10, 6, 4, 6, 7, 4, 6, 8, 8, 9, 5, 11, 5, 13, 6, 3, 3, 7, 12, 4, 7, 3, 8, 4, 14, 5, 10, 5, 7, 8, 7, 8, 6, 7, 8, 11, 6, 9, 9, 9, 4, 9, 5, 13, 7, 5, 8, 6, 9, 12, 10, 6, 6, 9, 12, 2, 8, 11, 11, 11, 3, 8, 5, 6, 2, 6, 7, 9, 10, 8, 9, 3, 5, 5, 12, 9, 6, 6, 7, 7, 8, 8, 9, 5, 10, 10, 3, 8, 11, 4, 5, 4, 14, 5, 6, 6, 5, 6, 5, 8, 12, 8, 7, 9, 6, 6, 9, 10, 6, 6, 4, 11, 10, 8, 7, 12, 12, 5, 9, 4, 12, 9, 4, 5, 8, 9, 7, 8, 12, 7, 6, 12, 10, 15, 3, 7, 9, 9, 13, 8, 14, 10, 9, 8, 3, 1, 12, 11, 8, 12, 6, 10, 4, 7, 8, 5, 5, 8, 8, 8, 11, 8, 5, 4, 12, 4, 5, 8, 4, 9, 9, 13, 14, 1, 9, 7]\n",
      "Genrtn 62: mean = 8.105  stddev = 2.581467605839748  max = 15 [7, 7, 8, 10, 5, 4, 6, 11, 11, 6, 8, 7, 7, 9, 11, 5, 6, 9, 11, 7, 8, 8, 7, 7, 5, 11, 6, 7, 3, 14, 5, 8, 13, 3, 10, 3, 9, 11, 9, 12, 6, 10, 4, 9, 8, 8, 5, 9, 7, 8, 4, 8, 8, 9, 8, 9, 13, 13, 4, 8, 7, 5, 9, 10, 9, 8, 8, 10, 5, 10, 6, 12, 13, 6, 6, 5, 10, 7, 3, 7, 6, 5, 13, 9, 7, 3, 11, 10, 10, 6, 9, 5, 3, 4, 14, 14, 5, 5, 11, 7, 5, 10, 10, 9, 6, 8, 11, 8, 10, 9, 11, 12, 7, 7, 5, 8, 11, 6, 5, 9, 7, 6, 12, 5, 10, 9, 7, 11, 8, 14, 12, 9, 7, 12, 7, 12, 8, 8, 7, 11, 8, 5, 8, 11, 13, 8, 6, 8, 7, 10, 6, 7, 7, 15, 7, 11, 10, 10, 10, 13, 11, 7, 9, 5, 7, 9, 8, 9, 6, 10, 3, 6, 6, 4, 9, 8, 9, 6, 10, 8, 10, 12, 5, 8, 7, 7, 9, 6, 6, 8, 11, 6, 6, 9, 7, 5, 10, 10, 7, 8]\n",
      "Genrtn 63: mean = 8.1  stddev = 2.7964262908219126  max = 16 [7, 8, 8, 8, 7, 6, 7, 8, 6, 7, 5, 7, 10, 8, 11, 7, 4, 2, 10, 6, 4, 7, 3, 6, 2, 6, 7, 8, 7, 5, 7, 6, 11, 6, 7, 14, 4, 6, 9, 4, 8, 15, 5, 9, 5, 6, 7, 7, 5, 9, 11, 7, 5, 8, 11, 13, 10, 4, 12, 15, 8, 6, 10, 8, 9, 8, 6, 6, 2, 6, 16, 8, 4, 8, 11, 6, 7, 8, 7, 7, 10, 9, 12, 8, 8, 8, 9, 6, 13, 8, 8, 9, 10, 11, 5, 9, 8, 10, 12, 12, 8, 8, 8, 7, 8, 11, 8, 7, 6, 9, 7, 5, 13, 10, 8, 11, 13, 15, 6, 10, 8, 8, 12, 9, 6, 5, 13, 10, 8, 4, 6, 5, 6, 15, 4, 8, 12, 14, 7, 6, 6, 13, 9, 8, 5, 2, 4, 9, 15, 11, 7, 14, 6, 9, 8, 10, 8, 14, 9, 6, 5, 9, 9, 9, 10, 7, 6, 9, 8, 7, 5, 11, 8, 6, 13, 6, 7, 5, 8, 8, 15, 10, 6, 7, 8, 9, 9, 6, 8, 4, 9, 8, 6, 7, 9, 12, 8, 11, 9, 7]\n",
      "Genrtn 64: mean = 7.83  stddev = 2.7606339851563084  max = 15 [5, 8, 6, 4, 9, 11, 8, 6, 7, 11, 7, 7, 10, 5, 4, 13, 10, 10, 9, 11, 12, 4, 7, 8, 7, 7, 8, 10, 6, 10, 8, 9, 8, 5, 13, 8, 8, 8, 7, 13, 5, 5, 7, 9, 6, 10, 6, 2, 8, 11, 6, 13, 10, 5, 5, 12, 9, 7, 6, 5, 11, 10, 4, 7, 9, 6, 11, 10, 6, 5, 9, 8, 12, 11, 5, 9, 5, 8, 7, 9, 6, 9, 8, 7, 9, 7, 5, 13, 4, 5, 6, 6, 10, 6, 10, 5, 5, 10, 14, 6, 8, 8, 7, 4, 12, 5, 3, 10, 7, 8, 7, 10, 10, 13, 7, 3, 7, 8, 5, 6, 15, 8, 10, 11, 11, 14, 5, 4, 11, 9, 6, 9, 9, 11, 2, 9, 4, 8, 9, 8, 8, 8, 14, 8, 8, 9, 7, 8, 8, 3, 6, 3, 9, 7, 10, 9, 4, 9, 11, 4, 7, 8, 10, 9, 10, 12, 4, 3, 8, 13, 7, 7, 7, 7, 3, 5, 10, 14, 4, 4, 14, 6, 4, 10, 10, 1, 5, 7, 7, 6, 4, 9, 10, 9, 8, 5, 11, 9, 7, 11]\n",
      "Genrtn 65: mean = 8.125  stddev = 2.7963145388171196  max = 16 [6, 5, 3, 6, 8, 8, 9, 8, 13, 5, 3, 12, 6, 9, 15, 9, 4, 16, 12, 4, 6, 11, 10, 5, 6, 9, 8, 9, 5, 10, 10, 6, 4, 7, 5, 9, 10, 10, 10, 14, 10, 9, 6, 10, 8, 8, 10, 11, 4, 10, 7, 5, 9, 6, 8, 11, 9, 8, 7, 10, 3, 10, 11, 9, 6, 12, 6, 5, 9, 8, 4, 9, 10, 7, 14, 6, 6, 5, 6, 10, 11, 13, 7, 10, 11, 9, 7, 8, 8, 11, 5, 2, 7, 9, 3, 3, 13, 7, 7, 13, 10, 5, 6, 8, 9, 11, 11, 7, 4, 7, 8, 8, 7, 7, 11, 9, 7, 12, 5, 9, 4, 9, 7, 8, 6, 8, 6, 9, 7, 14, 6, 11, 6, 10, 8, 8, 8, 12, 4, 5, 13, 10, 6, 6, 9, 4, 10, 13, 9, 6, 7, 5, 9, 2, 8, 8, 10, 13, 8, 10, 15, 6, 10, 8, 5, 8, 10, 12, 13, 8, 6, 5, 11, 6, 5, 5, 9, 4, 8, 6, 10, 9, 10, 8, 6, 11, 8, 10, 14, 2, 10, 7, 6, 8, 6, 13, 9, 6, 11, 7]\n",
      "Genrtn 66: mean = 7.77  stddev = 2.7289375221869774  max = 15 [11, 9, 8, 8, 7, 10, 10, 6, 4, 9, 10, 7, 4, 3, 8, 15, 8, 7, 5, 5, 5, 8, 10, 5, 10, 7, 14, 8, 10, 10, 5, 5, 11, 2, 6, 10, 6, 4, 9, 11, 9, 7, 9, 8, 6, 8, 6, 5, 9, 9, 8, 5, 10, 10, 4, 12, 12, 11, 7, 10, 7, 6, 7, 8, 3, 9, 5, 6, 5, 5, 8, 7, 8, 12, 9, 7, 8, 12, 8, 3, 5, 9, 10, 8, 8, 11, 6, 8, 8, 10, 8, 4, 5, 9, 11, 15, 4, 4, 5, 8, 4, 14, 10, 11, 10, 5, 11, 6, 8, 7, 8, 5, 5, 5, 8, 7, 11, 5, 5, 5, 7, 5, 4, 8, 9, 4, 6, 8, 8, 6, 7, 4, 13, 15, 4, 9, 12, 10, 12, 5, 6, 9, 12, 5, 10, 11, 6, 8, 8, 8, 8, 6, 7, 2, 7, 6, 4, 8, 2, 12, 8, 4, 5, 10, 5, 9, 6, 12, 5, 13, 4, 13, 6, 13, 10, 7, 5, 9, 12, 11, 11, 6, 12, 8, 7, 7, 8, 7, 7, 8, 5, 9, 10, 6, 9, 8, 10, 11, 6, 7]\n",
      "Genrtn 67: mean = 8.05  stddev = 2.7726341266023544  max = 17 [9, 10, 14, 9, 7, 14, 6, 5, 13, 6, 12, 6, 6, 11, 7, 11, 6, 8, 7, 4, 9, 5, 4, 9, 5, 7, 7, 3, 10, 12, 14, 6, 6, 10, 8, 9, 6, 5, 9, 9, 7, 7, 4, 10, 11, 3, 8, 4, 4, 10, 8, 8, 7, 9, 10, 12, 15, 10, 7, 7, 11, 10, 4, 13, 15, 2, 1, 8, 7, 12, 9, 7, 6, 11, 6, 10, 8, 7, 7, 8, 9, 7, 8, 9, 10, 9, 4, 6, 6, 8, 12, 11, 12, 10, 8, 6, 9, 8, 9, 5, 7, 7, 7, 7, 6, 4, 11, 9, 8, 9, 12, 3, 5, 5, 8, 8, 11, 5, 9, 8, 3, 6, 5, 7, 12, 7, 9, 7, 6, 8, 9, 8, 8, 11, 5, 7, 8, 10, 5, 17, 5, 8, 9, 12, 10, 4, 7, 6, 8, 4, 7, 11, 11, 6, 3, 8, 3, 6, 7, 8, 10, 12, 7, 7, 10, 9, 4, 8, 10, 7, 1, 8, 5, 6, 8, 11, 11, 8, 8, 10, 10, 6, 11, 9, 13, 8, 9, 13, 7, 6, 10, 7, 8, 9, 11, 7, 9, 8, 15, 11]\n",
      "Genrtn 68: mean = 7.865  stddev = 2.6696020302659345  max = 16 [14, 10, 7, 7, 11, 9, 6, 6, 5, 9, 10, 8, 6, 6, 13, 12, 5, 8, 9, 10, 10, 9, 9, 11, 11, 5, 7, 7, 7, 2, 9, 9, 7, 6, 6, 8, 4, 11, 11, 7, 6, 7, 7, 14, 5, 12, 13, 7, 9, 9, 11, 4, 5, 8, 5, 12, 3, 5, 2, 9, 7, 14, 6, 10, 8, 12, 8, 12, 9, 12, 9, 6, 10, 10, 1, 11, 6, 6, 7, 6, 5, 4, 7, 7, 7, 8, 5, 6, 6, 12, 8, 9, 9, 7, 16, 9, 6, 4, 8, 8, 7, 8, 7, 8, 9, 6, 8, 5, 7, 8, 14, 7, 13, 6, 7, 8, 5, 9, 8, 7, 8, 10, 8, 7, 8, 6, 9, 3, 6, 10, 13, 9, 9, 8, 9, 6, 7, 5, 8, 6, 15, 6, 6, 5, 13, 6, 13, 6, 6, 6, 10, 10, 10, 7, 11, 8, 5, 12, 6, 7, 7, 3, 7, 7, 8, 12, 7, 6, 5, 11, 2, 7, 8, 6, 5, 6, 6, 5, 10, 6, 8, 10, 4, 11, 6, 10, 7, 9, 8, 7, 7, 13, 6, 8, 12, 7, 6, 4, 6, 9]\n",
      "Genrtn 69: mean = 7.98  stddev = 2.8999310336626976  max = 17 [15, 13, 13, 7, 5, 6, 11, 6, 8, 10, 9, 8, 11, 8, 7, 11, 6, 7, 6, 11, 5, 7, 5, 5, 14, 5, 11, 9, 7, 11, 10, 8, 10, 7, 7, 8, 8, 4, 2, 8, 11, 5, 10, 9, 11, 8, 5, 5, 6, 9, 12, 9, 5, 8, 7, 3, 8, 9, 10, 6, 10, 4, 9, 7, 9, 7, 7, 6, 6, 8, 12, 8, 7, 11, 7, 6, 3, 10, 9, 16, 9, 7, 5, 8, 6, 11, 7, 8, 8, 9, 6, 10, 4, 7, 6, 1, 7, 9, 5, 10, 8, 8, 5, 5, 8, 7, 7, 3, 6, 6, 7, 4, 3, 8, 6, 7, 11, 9, 6, 10, 7, 12, 4, 6, 3, 7, 9, 7, 8, 11, 5, 11, 5, 13, 7, 8, 13, 10, 15, 8, 8, 13, 6, 9, 5, 9, 12, 6, 6, 5, 5, 5, 6, 6, 12, 1, 10, 6, 9, 12, 13, 4, 8, 8, 4, 9, 7, 6, 6, 8, 14, 9, 9, 10, 9, 15, 14, 11, 8, 8, 10, 6, 6, 11, 8, 13, 5, 3, 6, 4, 17, 15, 7, 11, 10, 6, 8, 9, 8, 9]\n",
      "Genrtn 70: mean = 7.725  stddev = 2.7927361135631847  max = 17 [8, 8, 3, 7, 9, 13, 10, 9, 8, 4, 7, 12, 12, 16, 6, 9, 5, 7, 6, 7, 10, 12, 9, 4, 7, 9, 9, 10, 7, 6, 7, 6, 7, 8, 10, 14, 10, 11, 9, 8, 8, 13, 5, 11, 8, 4, 9, 6, 10, 9, 4, 10, 10, 7, 5, 9, 6, 6, 6, 6, 11, 11, 8, 4, 8, 7, 4, 10, 6, 8, 8, 3, 11, 10, 6, 7, 5, 4, 11, 6, 8, 6, 9, 10, 11, 9, 5, 9, 8, 17, 4, 8, 10, 10, 9, 7, 9, 5, 6, 10, 1, 6, 8, 8, 3, 6, 6, 7, 9, 3, 5, 6, 5, 5, 12, 7, 4, 11, 3, 5, 7, 6, 9, 12, 6, 6, 3, 12, 6, 7, 4, 5, 6, 4, 9, 10, 9, 9, 16, 14, 8, 6, 7, 10, 5, 12, 5, 5, 9, 8, 7, 6, 4, 13, 6, 8, 8, 9, 3, 6, 4, 9, 6, 8, 7, 12, 10, 6, 9, 10, 15, 8, 8, 5, 6, 10, 10, 7, 8, 6, 7, 9, 8, 10, 3, 7, 11, 5, 9, 8, 10, 9, 2, 1, 10, 8, 7, 6, 10, 7]\n",
      "Genrtn 71: mean = 8.27  stddev = 2.972726021684474  max = 18 [8, 11, 11, 6, 5, 15, 9, 5, 12, 8, 14, 9, 3, 7, 11, 13, 7, 10, 4, 6, 5, 7, 8, 10, 10, 6, 9, 10, 4, 10, 12, 9, 9, 11, 8, 7, 7, 9, 11, 6, 5, 7, 4, 11, 7, 9, 11, 7, 3, 6, 8, 8, 8, 8, 6, 11, 10, 11, 12, 8, 5, 12, 14, 8, 18, 8, 10, 10, 5, 4, 6, 8, 7, 15, 6, 12, 5, 13, 6, 5, 12, 10, 4, 9, 13, 10, 4, 8, 9, 8, 12, 3, 13, 8, 11, 11, 7, 7, 5, 5, 8, 8, 6, 8, 9, 13, 10, 10, 7, 8, 6, 16, 11, 13, 7, 6, 8, 13, 8, 10, 7, 6, 11, 14, 6, 9, 6, 5, 8, 5, 3, 8, 5, 9, 9, 8, 8, 11, 12, 9, 8, 5, 9, 10, 13, 8, 8, 2, 9, 11, 9, 10, 8, 5, 5, 7, 3, 6, 7, 4, 4, 12, 10, 4, 5, 7, 6, 6, 9, 9, 10, 6, 7, 13, 6, 13, 4, 10, 13, 11, 8, 4, 6, 8, 12, 5, 6, 13, 11, 5, 3, 3, 3, 9, 12, 9, 8, 9, 8, 8]\n",
      "Genrtn 72: mean = 7.915  stddev = 2.908225403919029  max = 15 [10, 4, 4, 11, 11, 6, 9, 12, 9, 7, 5, 8, 9, 10, 10, 7, 9, 9, 11, 6, 5, 11, 7, 10, 7, 12, 9, 8, 6, 8, 7, 5, 10, 13, 7, 9, 4, 5, 5, 5, 14, 5, 5, 4, 8, 9, 9, 3, 8, 9, 11, 8, 7, 9, 8, 5, 6, 10, 9, 12, 9, 12, 4, 3, 12, 5, 9, 9, 15, 11, 7, 7, 3, 4, 8, 8, 13, 10, 12, 6, 7, 11, 5, 7, 6, 4, 10, 8, 8, 9, 8, 9, 2, 10, 12, 8, 7, 5, 7, 14, 8, 9, 7, 14, 9, 2, 7, 15, 12, 6, 9, 13, 13, 5, 7, 7, 6, 6, 11, 9, 8, 8, 5, 6, 6, 5, 4, 13, 12, 4, 3, 8, 11, 9, 14, 7, 9, 6, 8, 4, 9, 8, 5, 9, 10, 7, 8, 9, 12, 4, 10, 6, 6, 5, 10, 11, 9, 4, 8, 7, 4, 5, 10, 4, 8, 10, 6, 10, 9, 11, 8, 4, 5, 8, 14, 4, 7, 10, 5, 11, 5, 7, 6, 4, 8, 6, 12, 5, 8, 9, 6, 14, 3, 6, 11, 1, 13, 11, 4, 6]\n",
      "Genrtn 73: mean = 7.465  stddev = 2.7108624089023774  max = 15 [9, 8, 11, 9, 13, 10, 4, 7, 4, 6, 6, 9, 8, 7, 15, 6, 8, 9, 4, 5, 5, 8, 7, 9, 4, 5, 6, 4, 9, 5, 3, 9, 8, 10, 6, 3, 8, 8, 4, 5, 4, 12, 5, 12, 7, 7, 8, 3, 11, 7, 3, 13, 3, 12, 10, 8, 3, 5, 9, 10, 8, 8, 4, 3, 8, 9, 9, 13, 3, 7, 12, 10, 3, 10, 8, 7, 13, 7, 7, 7, 9, 10, 8, 9, 14, 8, 3, 6, 6, 8, 6, 3, 8, 9, 7, 8, 7, 6, 7, 12, 6, 10, 13, 9, 9, 7, 6, 5, 7, 2, 6, 4, 6, 11, 8, 9, 4, 4, 11, 10, 5, 4, 9, 8, 7, 8, 11, 5, 7, 2, 8, 10, 6, 12, 7, 2, 9, 11, 8, 9, 6, 8, 11, 8, 10, 6, 11, 5, 7, 6, 11, 8, 8, 9, 12, 6, 6, 9, 9, 5, 9, 8, 11, 9, 4, 6, 10, 4, 8, 9, 8, 11, 4, 7, 7, 2, 8, 4, 7, 5, 10, 8, 9, 8, 6, 4, 11, 10, 4, 5, 9, 9, 5, 7, 11, 6, 2, 6, 9, 11]\n",
      "Genrtn 74: mean = 7.895  stddev = 2.724697230886397  max = 20 [7, 7, 6, 6, 4, 9, 11, 7, 9, 8, 10, 8, 12, 4, 6, 7, 8, 10, 8, 10, 8, 10, 7, 9, 7, 10, 5, 7, 11, 7, 15, 7, 7, 9, 7, 9, 6, 10, 13, 2, 4, 11, 9, 7, 4, 8, 4, 7, 7, 9, 8, 5, 8, 10, 7, 6, 10, 6, 11, 4, 7, 14, 5, 4, 3, 3, 8, 10, 20, 9, 6, 8, 8, 5, 8, 7, 13, 7, 10, 5, 7, 15, 11, 8, 10, 8, 10, 12, 9, 7, 4, 7, 12, 12, 6, 8, 4, 9, 8, 6, 7, 9, 9, 12, 13, 7, 4, 11, 13, 5, 7, 8, 13, 6, 5, 6, 4, 16, 8, 5, 5, 8, 9, 7, 13, 8, 12, 3, 12, 7, 7, 6, 7, 4, 7, 4, 3, 11, 7, 9, 6, 4, 8, 7, 8, 7, 6, 6, 9, 7, 10, 9, 9, 9, 9, 5, 11, 7, 5, 9, 9, 8, 10, 9, 11, 6, 4, 12, 6, 8, 10, 8, 7, 5, 5, 9, 9, 5, 7, 6, 7, 11, 6, 8, 7, 7, 8, 5, 13, 12, 6, 5, 9, 9, 6, 7, 7, 6, 8, 9]\n",
      "Genrtn 75: mean = 7.915  stddev = 2.8823211132696507  max = 17 [11, 9, 6, 10, 12, 10, 7, 3, 11, 7, 5, 6, 7, 9, 3, 5, 6, 8, 6, 11, 11, 5, 13, 11, 9, 9, 5, 11, 10, 13, 4, 6, 9, 3, 8, 9, 7, 14, 7, 7, 7, 2, 11, 2, 11, 17, 7, 6, 8, 2, 5, 7, 9, 3, 9, 9, 13, 11, 6, 12, 4, 4, 9, 6, 11, 8, 6, 9, 10, 6, 13, 7, 9, 5, 10, 10, 7, 9, 7, 8, 6, 7, 11, 6, 11, 10, 12, 8, 5, 5, 5, 6, 9, 4, 7, 11, 12, 5, 10, 7, 4, 10, 11, 5, 7, 5, 6, 9, 7, 7, 6, 4, 6, 6, 9, 7, 8, 6, 10, 6, 9, 6, 8, 4, 9, 6, 10, 6, 11, 10, 7, 7, 8, 4, 8, 5, 8, 8, 10, 11, 6, 9, 8, 7, 15, 13, 11, 7, 10, 6, 6, 8, 5, 7, 12, 6, 17, 13, 5, 4, 14, 7, 7, 14, 6, 13, 12, 9, 5, 6, 10, 7, 6, 8, 10, 10, 5, 7, 15, 6, 4, 9, 8, 5, 7, 4, 5, 9, 6, 10, 5, 4, 6, 9, 10, 13, 7, 6, 9, 6]\n",
      "Genrtn 76: mean = 8.095  stddev = 2.8418259974882347  max = 17 [16, 4, 12, 10, 8, 6, 6, 5, 8, 4, 9, 8, 6, 13, 6, 5, 8, 10, 10, 14, 9, 11, 8, 6, 10, 5, 7, 6, 7, 6, 4, 10, 8, 11, 4, 10, 9, 8, 10, 5, 2, 6, 3, 9, 12, 8, 4, 9, 6, 17, 6, 10, 7, 9, 3, 6, 11, 11, 4, 10, 10, 9, 9, 8, 15, 9, 6, 8, 7, 8, 7, 5, 9, 14, 9, 13, 9, 6, 12, 4, 7, 12, 8, 7, 9, 5, 12, 9, 7, 10, 7, 8, 14, 11, 8, 6, 11, 9, 10, 5, 4, 9, 6, 5, 10, 12, 8, 5, 8, 7, 7, 7, 7, 9, 6, 8, 9, 6, 10, 9, 7, 1, 11, 7, 9, 5, 11, 15, 6, 9, 11, 5, 3, 1, 4, 10, 6, 7, 11, 14, 4, 7, 5, 8, 8, 4, 8, 6, 12, 12, 8, 5, 9, 9, 5, 3, 8, 14, 12, 10, 6, 9, 7, 7, 8, 4, 7, 6, 7, 9, 5, 7, 10, 10, 2, 8, 11, 8, 9, 8, 9, 9, 9, 8, 13, 11, 7, 6, 9, 13, 10, 11, 8, 10, 7, 8, 8, 7, 8, 11]\n",
      "Genrtn 77: mean = 7.935  stddev = 2.6231231385506857  max = 16 [8, 7, 9, 8, 8, 4, 10, 2, 8, 11, 10, 8, 11, 4, 7, 12, 6, 10, 9, 10, 9, 6, 8, 6, 7, 9, 6, 7, 11, 8, 10, 13, 16, 9, 7, 7, 15, 10, 7, 7, 2, 10, 3, 11, 11, 11, 7, 2, 5, 10, 16, 6, 4, 10, 6, 9, 11, 12, 9, 7, 13, 9, 7, 6, 7, 7, 14, 11, 6, 11, 8, 7, 8, 8, 4, 11, 5, 5, 8, 9, 6, 4, 9, 13, 9, 8, 11, 8, 7, 10, 7, 5, 8, 5, 5, 7, 5, 7, 8, 9, 7, 8, 8, 4, 6, 9, 5, 11, 5, 10, 11, 8, 7, 10, 6, 4, 9, 11, 6, 9, 9, 7, 4, 6, 6, 10, 8, 9, 7, 3, 11, 9, 11, 6, 6, 9, 8, 9, 3, 7, 11, 9, 8, 7, 4, 8, 7, 7, 7, 6, 6, 13, 9, 5, 6, 9, 9, 6, 12, 8, 8, 8, 8, 2, 10, 8, 8, 14, 8, 4, 14, 8, 9, 6, 4, 8, 11, 4, 8, 7, 11, 5, 9, 8, 8, 8, 11, 8, 9, 5, 9, 3, 9, 7, 8, 4, 9, 8, 9, 6]\n",
      "Genrtn 78: mean = 8.035  stddev = 2.6951391429757385  max = 16 [12, 8, 8, 5, 13, 6, 12, 7, 6, 5, 8, 9, 7, 9, 7, 10, 11, 6, 6, 5, 9, 10, 5, 10, 9, 9, 3, 11, 9, 7, 11, 1, 8, 5, 7, 5, 8, 6, 10, 8, 7, 8, 9, 6, 6, 10, 6, 10, 6, 3, 9, 11, 9, 11, 6, 6, 11, 13, 8, 10, 11, 5, 13, 7, 9, 6, 10, 2, 3, 9, 5, 7, 14, 10, 9, 11, 14, 5, 3, 10, 11, 9, 6, 4, 9, 8, 5, 6, 6, 9, 7, 6, 7, 9, 5, 11, 7, 6, 11, 6, 3, 10, 6, 6, 7, 6, 11, 6, 5, 5, 11, 10, 4, 9, 8, 13, 6, 6, 6, 7, 4, 13, 7, 9, 11, 6, 6, 9, 7, 4, 11, 11, 9, 7, 6, 7, 9, 8, 7, 15, 10, 9, 8, 7, 10, 7, 11, 14, 5, 6, 10, 7, 5, 10, 5, 6, 10, 5, 6, 9, 7, 11, 8, 11, 8, 5, 8, 12, 6, 8, 11, 5, 4, 16, 8, 11, 8, 11, 11, 4, 11, 8, 7, 10, 5, 7, 10, 9, 8, 7, 11, 10, 8, 5, 16, 9, 6, 10, 8, 11]\n",
      "Genrtn 79: mean = 7.87  stddev = 2.676396831562913  max = 15 [6, 6, 11, 6, 8, 6, 8, 7, 8, 11, 5, 2, 9, 9, 9, 10, 6, 10, 6, 7, 5, 4, 8, 14, 8, 6, 10, 6, 3, 10, 6, 15, 12, 5, 12, 9, 7, 7, 3, 9, 3, 10, 6, 5, 5, 9, 2, 11, 6, 7, 9, 7, 10, 6, 11, 6, 5, 9, 7, 5, 7, 14, 11, 7, 11, 8, 7, 7, 10, 4, 10, 5, 6, 8, 6, 11, 10, 8, 9, 9, 9, 9, 11, 5, 11, 13, 6, 9, 7, 9, 13, 6, 8, 9, 5, 7, 13, 9, 7, 1, 7, 8, 6, 7, 13, 11, 11, 9, 9, 6, 5, 8, 8, 13, 8, 7, 6, 10, 7, 14, 8, 6, 9, 3, 10, 5, 9, 8, 8, 11, 10, 5, 5, 9, 5, 5, 6, 3, 4, 5, 6, 6, 15, 5, 10, 8, 12, 8, 11, 11, 10, 5, 7, 7, 9, 7, 7, 5, 6, 4, 10, 13, 9, 7, 4, 7, 8, 8, 8, 4, 10, 7, 4, 3, 10, 10, 5, 14, 8, 5, 8, 7, 6, 11, 9, 11, 5, 7, 10, 7, 9, 7, 10, 8, 10, 7, 9, 9, 12, 9]\n",
      "Genrtn 80: mean = 7.965  stddev = 2.644574634983857  max = 15 [7, 10, 7, 12, 10, 8, 7, 8, 8, 8, 5, 8, 10, 8, 5, 10, 9, 3, 9, 7, 7, 7, 9, 3, 5, 9, 9, 6, 11, 8, 8, 9, 11, 7, 6, 7, 14, 9, 6, 10, 12, 10, 6, 5, 8, 9, 8, 7, 4, 7, 7, 7, 11, 10, 10, 6, 13, 9, 7, 4, 9, 5, 10, 7, 9, 7, 10, 4, 9, 6, 5, 6, 10, 8, 11, 7, 9, 6, 6, 9, 14, 15, 12, 8, 8, 3, 8, 8, 8, 8, 10, 12, 12, 7, 1, 8, 8, 8, 10, 9, 10, 8, 10, 9, 8, 10, 11, 2, 8, 14, 5, 3, 2, 5, 9, 7, 6, 9, 9, 8, 7, 7, 6, 12, 9, 5, 13, 11, 7, 7, 8, 9, 6, 10, 6, 2, 9, 11, 6, 7, 8, 9, 5, 10, 8, 12, 14, 11, 12, 11, 11, 7, 8, 8, 7, 8, 6, 9, 9, 9, 7, 5, 4, 6, 5, 6, 9, 7, 13, 5, 9, 9, 8, 3, 10, 6, 4, 6, 4, 5, 6, 9, 3, 6, 5, 5, 15, 7, 7, 8, 6, 7, 3, 11, 12, 6, 13, 10, 9, 11]\n",
      "Genrtn 81: mean = 7.655  stddev = 2.721392106992302  max = 16 [5, 5, 14, 6, 12, 8, 6, 7, 7, 5, 9, 9, 12, 8, 12, 2, 8, 7, 14, 10, 8, 7, 7, 7, 8, 10, 11, 8, 3, 9, 5, 11, 5, 11, 8, 6, 5, 8, 9, 8, 9, 4, 4, 6, 4, 9, 9, 9, 7, 16, 6, 7, 12, 6, 4, 9, 3, 10, 3, 6, 11, 1, 9, 5, 8, 12, 5, 9, 9, 5, 4, 10, 6, 9, 6, 7, 9, 4, 9, 13, 6, 7, 12, 5, 11, 9, 9, 8, 7, 7, 6, 3, 5, 10, 4, 9, 6, 6, 6, 7, 10, 8, 9, 7, 7, 12, 3, 9, 9, 9, 9, 11, 11, 11, 6, 10, 7, 3, 8, 3, 7, 10, 4, 6, 9, 3, 5, 6, 7, 7, 5, 12, 5, 10, 14, 8, 13, 4, 8, 9, 12, 2, 10, 6, 10, 6, 8, 7, 5, 1, 6, 8, 9, 7, 7, 8, 9, 5, 8, 5, 8, 11, 4, 5, 8, 13, 14, 9, 8, 6, 6, 7, 8, 10, 8, 9, 9, 9, 4, 7, 8, 7, 9, 4, 6, 12, 9, 6, 8, 7, 4, 11, 6, 10, 8, 8, 8, 9, 12, 6]\n",
      "Genrtn 82: mean = 7.93  stddev = 2.815155413116654  max = 17 [10, 10, 7, 5, 7, 9, 7, 7, 11, 7, 4, 12, 6, 9, 9, 5, 6, 9, 10, 9, 8, 10, 9, 12, 11, 7, 8, 8, 10, 6, 8, 8, 12, 5, 11, 8, 7, 7, 8, 14, 8, 3, 12, 5, 4, 5, 9, 6, 14, 6, 8, 11, 7, 7, 7, 14, 10, 10, 7, 7, 6, 5, 4, 7, 7, 6, 10, 16, 4, 8, 6, 7, 5, 3, 11, 6, 4, 10, 7, 8, 7, 9, 7, 7, 5, 13, 12, 8, 5, 6, 8, 9, 10, 4, 13, 10, 9, 3, 7, 6, 8, 6, 14, 9, 8, 11, 8, 6, 3, 12, 12, 3, 6, 8, 11, 8, 7, 6, 6, 10, 9, 3, 16, 7, 8, 10, 6, 9, 11, 5, 5, 6, 10, 12, 11, 1, 6, 6, 12, 4, 9, 12, 4, 10, 9, 8, 17, 10, 5, 8, 11, 8, 8, 7, 12, 7, 6, 5, 10, 9, 8, 7, 3, 6, 14, 8, 7, 9, 4, 6, 10, 10, 6, 10, 10, 6, 5, 6, 5, 6, 14, 8, 5, 4, 6, 10, 4, 8, 11, 7, 6, 10, 7, 8, 12, 6, 5, 6, 9, 6]\n",
      "Genrtn 83: mean = 7.825  stddev = 2.715580048534751  max = 18 [6, 8, 10, 9, 10, 12, 7, 7, 11, 7, 4, 10, 7, 8, 5, 7, 9, 10, 8, 10, 9, 4, 11, 7, 9, 13, 6, 12, 11, 9, 7, 11, 9, 7, 9, 13, 8, 9, 11, 7, 4, 11, 6, 7, 5, 8, 9, 8, 7, 5, 3, 6, 9, 13, 6, 6, 12, 9, 7, 9, 7, 10, 11, 7, 6, 11, 7, 11, 11, 10, 6, 5, 6, 5, 9, 5, 10, 7, 8, 6, 9, 10, 10, 9, 8, 8, 10, 1, 9, 9, 10, 5, 4, 9, 6, 11, 8, 3, 5, 9, 7, 8, 12, 7, 5, 10, 10, 11, 18, 12, 4, 8, 8, 6, 7, 5, 6, 8, 3, 4, 10, 8, 3, 6, 9, 7, 4, 9, 11, 6, 9, 9, 6, 6, 12, 10, 3, 6, 15, 7, 3, 10, 3, 9, 3, 11, 9, 7, 6, 9, 8, 4, 10, 9, 5, 9, 5, 8, 5, 9, 9, 4, 5, 5, 9, 8, 5, 5, 7, 10, 15, 5, 7, 8, 5, 9, 9, 10, 5, 7, 9, 6, 11, 6, 5, 8, 10, 8, 7, 9, 12, 1, 7, 10, 8, 2, 5, 15, 7, 7]\n",
      "Genrtn 84: mean = 8.375  stddev = 2.7720705257983607  max = 18 [5, 9, 10, 8, 9, 10, 3, 13, 10, 4, 14, 7, 8, 11, 9, 12, 10, 7, 7, 18, 2, 7, 10, 5, 13, 13, 10, 10, 9, 5, 10, 11, 6, 8, 9, 12, 13, 10, 10, 8, 7, 7, 9, 7, 10, 11, 10, 16, 9, 8, 11, 8, 10, 5, 12, 4, 9, 9, 9, 14, 5, 10, 6, 6, 4, 1, 9, 6, 5, 9, 7, 5, 5, 7, 9, 11, 12, 9, 10, 10, 10, 9, 13, 9, 9, 9, 6, 8, 7, 12, 8, 11, 7, 9, 5, 4, 8, 10, 12, 12, 8, 9, 6, 8, 6, 9, 8, 6, 7, 10, 5, 5, 10, 8, 10, 14, 13, 9, 8, 8, 8, 11, 3, 11, 10, 12, 5, 8, 5, 6, 7, 9, 8, 8, 7, 7, 8, 4, 6, 13, 9, 12, 6, 9, 7, 7, 5, 6, 7, 7, 10, 11, 9, 5, 12, 4, 4, 11, 4, 8, 6, 12, 12, 10, 8, 6, 10, 3, 10, 8, 4, 5, 6, 8, 8, 9, 6, 9, 6, 6, 15, 10, 4, 5, 9, 6, 9, 11, 13, 8, 9, 11, 11, 6, 5, 9, 5, 10, 9, 8]\n",
      "Genrtn 85: mean = 8.03  stddev = 2.908453197147927  max = 16 [8, 11, 7, 7, 12, 12, 6, 9, 12, 4, 5, 10, 11, 7, 8, 13, 10, 5, 6, 6, 8, 6, 15, 3, 4, 11, 9, 10, 13, 13, 9, 10, 10, 7, 10, 12, 11, 9, 8, 7, 6, 12, 8, 7, 9, 3, 7, 6, 9, 11, 9, 4, 4, 8, 12, 11, 7, 11, 12, 8, 9, 8, 9, 6, 5, 9, 12, 6, 7, 2, 8, 14, 14, 9, 2, 12, 6, 7, 9, 4, 10, 3, 9, 5, 8, 11, 5, 5, 7, 9, 13, 14, 5, 8, 13, 2, 9, 5, 7, 5, 4, 9, 9, 9, 7, 6, 8, 11, 11, 9, 5, 4, 7, 6, 12, 6, 9, 8, 10, 3, 6, 13, 10, 13, 7, 4, 16, 7, 6, 9, 8, 4, 7, 8, 7, 9, 5, 10, 10, 9, 5, 7, 8, 7, 8, 6, 6, 7, 5, 14, 15, 4, 11, 9, 8, 6, 3, 11, 6, 9, 6, 11, 5, 4, 7, 5, 12, 6, 4, 10, 12, 9, 8, 11, 3, 9, 5, 6, 11, 12, 9, 7, 9, 5, 6, 8, 5, 7, 10, 7, 5, 7, 3, 11, 8, 6, 9, 8, 10, 5]\n",
      "Genrtn 86: mean = 7.97  stddev = 2.8894809222419173  max = 17 [8, 12, 5, 6, 11, 8, 15, 9, 5, 9, 11, 3, 7, 6, 6, 10, 11, 4, 7, 3, 3, 6, 5, 9, 9, 10, 9, 10, 5, 14, 7, 8, 6, 8, 6, 7, 9, 5, 6, 7, 9, 3, 9, 8, 8, 10, 12, 3, 8, 6, 6, 9, 7, 2, 6, 5, 7, 7, 8, 8, 6, 2, 9, 8, 8, 8, 8, 13, 5, 4, 8, 7, 12, 8, 14, 3, 6, 9, 8, 4, 7, 12, 9, 10, 7, 9, 7, 7, 17, 13, 5, 6, 5, 9, 5, 8, 4, 12, 11, 5, 5, 9, 10, 6, 8, 8, 11, 13, 9, 10, 9, 5, 11, 13, 7, 9, 2, 7, 13, 9, 9, 5, 5, 5, 6, 5, 6, 7, 11, 6, 11, 11, 6, 10, 2, 4, 9, 9, 4, 9, 10, 7, 8, 8, 13, 8, 6, 9, 12, 11, 8, 10, 9, 8, 6, 7, 3, 5, 6, 11, 12, 9, 9, 9, 12, 7, 8, 6, 3, 12, 7, 10, 13, 4, 13, 8, 9, 13, 10, 6, 9, 10, 6, 9, 8, 5, 8, 6, 10, 8, 16, 5, 6, 9, 14, 3, 13, 8, 9, 9]\n",
      "Genrtn 87: mean = 7.845  stddev = 2.6927634504352587  max = 14 [9, 5, 4, 13, 8, 8, 10, 4, 6, 11, 7, 9, 4, 3, 6, 12, 8, 6, 6, 12, 10, 6, 6, 4, 9, 7, 5, 11, 5, 11, 9, 14, 12, 10, 7, 8, 6, 12, 13, 13, 6, 11, 11, 10, 4, 13, 5, 10, 10, 4, 8, 11, 8, 7, 11, 12, 10, 8, 10, 13, 6, 14, 11, 4, 5, 10, 7, 7, 6, 9, 6, 10, 10, 5, 6, 8, 5, 11, 7, 4, 13, 5, 7, 7, 11, 10, 9, 9, 5, 5, 12, 8, 8, 6, 2, 11, 11, 10, 7, 8, 6, 14, 6, 8, 10, 10, 6, 8, 8, 4, 4, 10, 4, 5, 5, 4, 8, 7, 5, 9, 4, 9, 7, 5, 5, 5, 9, 6, 7, 8, 3, 5, 6, 14, 6, 9, 7, 7, 11, 8, 8, 10, 11, 3, 11, 5, 13, 6, 9, 9, 8, 5, 10, 9, 9, 4, 8, 7, 10, 5, 7, 7, 6, 4, 8, 8, 10, 10, 6, 5, 8, 8, 6, 9, 7, 10, 10, 5, 7, 11, 5, 4, 11, 9, 12, 6, 8, 6, 9, 10, 8, 9, 4, 8, 12, 6, 6, 5, 6, 5]\n",
      "Genrtn 88: mean = 8.17  stddev = 2.676023168808521  max = 18 [7, 5, 10, 7, 12, 5, 6, 14, 7, 6, 9, 7, 13, 7, 9, 12, 10, 8, 9, 7, 8, 10, 5, 9, 5, 3, 9, 5, 9, 10, 3, 4, 6, 12, 5, 8, 7, 10, 10, 6, 8, 14, 9, 11, 7, 9, 6, 12, 7, 10, 7, 10, 12, 8, 9, 13, 8, 6, 8, 9, 4, 5, 6, 12, 5, 7, 7, 9, 9, 6, 10, 5, 4, 6, 10, 11, 11, 3, 7, 6, 8, 5, 8, 9, 5, 5, 6, 8, 7, 9, 9, 14, 10, 11, 9, 12, 8, 18, 5, 8, 11, 7, 5, 13, 8, 7, 13, 8, 6, 11, 9, 13, 12, 7, 10, 4, 5, 8, 8, 9, 12, 8, 10, 9, 8, 13, 10, 13, 6, 7, 4, 4, 4, 13, 5, 9, 9, 9, 6, 10, 6, 9, 12, 13, 8, 9, 14, 8, 5, 7, 4, 7, 8, 10, 4, 9, 7, 5, 7, 10, 9, 6, 10, 8, 7, 9, 9, 7, 8, 6, 8, 8, 5, 11, 12, 5, 6, 3, 5, 7, 12, 7, 7, 9, 11, 6, 6, 6, 6, 5, 8, 9, 8, 10, 8, 10, 11, 8, 13, 6]\n",
      "Genrtn 89: mean = 7.995  stddev = 2.7303800101817326  max = 17 [8, 8, 4, 6, 7, 8, 6, 5, 9, 4, 8, 8, 12, 8, 7, 9, 15, 6, 8, 7, 10, 8, 9, 6, 11, 10, 7, 7, 4, 7, 5, 8, 6, 9, 13, 7, 6, 7, 11, 12, 5, 9, 14, 10, 14, 4, 4, 3, 4, 7, 7, 9, 10, 7, 11, 8, 9, 7, 1, 7, 3, 10, 9, 9, 9, 9, 3, 10, 5, 11, 4, 9, 7, 13, 6, 7, 6, 10, 4, 5, 11, 6, 3, 10, 7, 13, 10, 9, 9, 7, 7, 10, 12, 6, 5, 4, 7, 7, 9, 7, 9, 6, 10, 10, 9, 5, 11, 9, 7, 11, 5, 11, 11, 8, 9, 7, 10, 3, 9, 8, 9, 6, 9, 7, 7, 7, 5, 4, 8, 11, 17, 7, 4, 8, 10, 12, 10, 3, 10, 6, 7, 13, 9, 6, 5, 14, 11, 8, 8, 11, 6, 5, 4, 16, 7, 6, 10, 6, 8, 8, 9, 10, 8, 10, 9, 11, 9, 4, 9, 12, 12, 5, 6, 9, 9, 4, 8, 9, 8, 5, 8, 11, 9, 3, 13, 12, 8, 4, 8, 7, 7, 7, 11, 8, 11, 6, 5, 9, 7, 9]\n",
      "Genrtn 90: mean = 8.365  stddev = 2.7788081977711236  max = 17 [8, 10, 10, 11, 13, 11, 6, 9, 11, 7, 11, 10, 8, 7, 4, 17, 10, 13, 13, 7, 12, 7, 6, 6, 7, 7, 7, 10, 9, 9, 6, 9, 5, 10, 9, 7, 6, 9, 14, 12, 9, 7, 8, 10, 8, 10, 8, 16, 8, 7, 11, 3, 7, 9, 8, 12, 14, 7, 6, 6, 8, 14, 9, 10, 8, 10, 9, 8, 3, 12, 10, 6, 13, 8, 11, 7, 5, 2, 8, 12, 7, 3, 11, 8, 8, 10, 3, 7, 11, 9, 8, 6, 7, 7, 13, 7, 10, 10, 5, 13, 4, 14, 3, 6, 9, 7, 6, 4, 9, 14, 4, 6, 12, 9, 10, 12, 14, 7, 9, 8, 11, 7, 8, 11, 12, 8, 11, 6, 8, 7, 9, 11, 9, 6, 6, 5, 12, 6, 11, 8, 11, 8, 4, 8, 5, 9, 9, 13, 13, 7, 4, 7, 11, 5, 9, 7, 6, 4, 9, 9, 8, 10, 11, 8, 8, 9, 7, 4, 7, 7, 8, 10, 7, 7, 3, 6, 12, 6, 5, 6, 10, 11, 7, 10, 12, 6, 6, 6, 7, 10, 7, 5, 5, 12, 9, 3, 8, 4, 8, 8]\n",
      "Genrtn 91: mean = 7.935  stddev = 2.913893443487596  max = 16 [6, 4, 7, 8, 6, 9, 9, 6, 5, 9, 9, 7, 6, 9, 9, 8, 9, 5, 4, 4, 7, 5, 10, 1, 11, 7, 5, 8, 12, 9, 8, 10, 13, 8, 5, 16, 9, 8, 13, 10, 4, 8, 10, 8, 7, 6, 10, 6, 10, 11, 7, 7, 5, 5, 9, 8, 4, 10, 10, 7, 3, 7, 5, 11, 7, 3, 7, 11, 8, 4, 11, 9, 13, 4, 7, 5, 11, 12, 10, 11, 11, 3, 9, 5, 8, 8, 4, 9, 6, 7, 9, 5, 5, 8, 4, 8, 11, 7, 8, 3, 6, 12, 4, 6, 12, 10, 7, 7, 6, 10, 10, 4, 2, 4, 9, 11, 10, 12, 9, 8, 5, 9, 6, 13, 4, 6, 9, 8, 8, 10, 10, 11, 5, 13, 3, 14, 5, 10, 6, 6, 10, 4, 13, 10, 5, 4, 10, 10, 7, 8, 4, 6, 13, 6, 9, 10, 13, 5, 5, 8, 10, 16, 6, 6, 7, 8, 8, 13, 14, 7, 12, 10, 7, 8, 4, 10, 11, 11, 7, 12, 6, 7, 5, 6, 9, 11, 10, 12, 10, 11, 14, 8, 4, 3, 6, 8, 3, 11, 4, 9]\n",
      "Genrtn 92: mean = 8.13  stddev = 2.6482258211867054  max = 17 [6, 8, 6, 8, 8, 11, 8, 9, 4, 8, 7, 9, 10, 5, 9, 10, 9, 5, 11, 14, 7, 2, 6, 6, 11, 11, 5, 6, 6, 6, 11, 12, 6, 7, 11, 9, 4, 7, 5, 9, 7, 7, 10, 5, 9, 14, 6, 7, 7, 5, 8, 5, 11, 8, 9, 9, 7, 10, 10, 6, 8, 7, 12, 7, 5, 10, 9, 7, 9, 12, 9, 4, 4, 7, 8, 6, 7, 17, 10, 9, 12, 8, 9, 10, 6, 9, 9, 5, 6, 10, 6, 10, 9, 9, 11, 2, 7, 7, 9, 10, 7, 8, 12, 11, 9, 6, 9, 10, 10, 7, 10, 10, 8, 7, 16, 4, 8, 12, 5, 10, 11, 10, 10, 15, 7, 11, 6, 11, 11, 9, 6, 10, 8, 9, 4, 5, 14, 7, 8, 6, 3, 10, 3, 9, 9, 11, 4, 5, 6, 2, 11, 4, 8, 12, 5, 11, 12, 4, 12, 10, 6, 10, 8, 9, 7, 6, 7, 4, 5, 8, 9, 8, 12, 9, 5, 7, 6, 7, 9, 12, 8, 12, 10, 7, 7, 8, 9, 8, 9, 6, 9, 2, 11, 5, 10, 8, 6, 8, 11, 7]\n",
      "Genrtn 93: mean = 7.875  stddev = 2.7146592788046164  max = 15 [8, 8, 7, 7, 8, 6, 6, 9, 5, 7, 8, 11, 6, 7, 9, 6, 12, 5, 5, 7, 7, 5, 10, 4, 6, 6, 6, 9, 7, 12, 7, 7, 9, 9, 7, 10, 9, 9, 5, 7, 5, 9, 11, 10, 11, 8, 7, 6, 6, 11, 8, 4, 9, 8, 7, 9, 7, 8, 3, 7, 10, 2, 9, 9, 10, 6, 11, 11, 2, 9, 11, 12, 7, 5, 10, 6, 7, 14, 9, 4, 5, 9, 15, 9, 11, 12, 10, 7, 6, 9, 6, 7, 12, 7, 5, 8, 13, 7, 7, 5, 6, 6, 11, 7, 6, 7, 8, 6, 9, 9, 7, 7, 8, 4, 8, 8, 5, 9, 2, 7, 5, 7, 8, 10, 4, 5, 10, 4, 2, 7, 4, 10, 6, 10, 7, 6, 9, 6, 6, 15, 9, 6, 9, 10, 6, 10, 15, 9, 10, 12, 7, 4, 10, 8, 4, 8, 12, 4, 10, 4, 12, 6, 5, 10, 11, 14, 3, 14, 11, 10, 8, 13, 9, 8, 12, 10, 11, 8, 9, 3, 7, 13, 6, 11, 10, 11, 6, 3, 5, 9, 5, 5, 9, 9, 4, 6, 7, 7, 7, 14]\n",
      "Genrtn 94: mean = 7.865  stddev = 2.6013025583349583  max = 16 [7, 7, 5, 8, 13, 7, 11, 6, 12, 8, 8, 8, 11, 5, 8, 5, 7, 6, 8, 8, 8, 8, 13, 10, 11, 12, 5, 6, 10, 10, 6, 10, 6, 6, 5, 5, 5, 5, 9, 6, 8, 12, 6, 8, 8, 9, 7, 6, 11, 4, 4, 11, 4, 11, 6, 10, 7, 16, 9, 8, 7, 7, 10, 3, 8, 4, 8, 9, 7, 8, 8, 13, 9, 10, 7, 11, 6, 10, 7, 10, 9, 9, 9, 4, 11, 7, 9, 8, 10, 9, 6, 9, 4, 6, 8, 15, 14, 8, 9, 8, 9, 9, 7, 1, 6, 4, 4, 8, 9, 4, 7, 8, 6, 6, 5, 12, 7, 9, 8, 7, 10, 6, 10, 10, 7, 11, 4, 5, 5, 8, 11, 4, 9, 6, 9, 9, 7, 10, 7, 4, 5, 7, 12, 9, 10, 8, 5, 6, 9, 7, 11, 5, 7, 7, 5, 14, 3, 11, 11, 4, 5, 9, 11, 7, 13, 8, 8, 3, 13, 9, 8, 11, 7, 8, 8, 8, 8, 6, 9, 16, 4, 8, 7, 5, 5, 6, 8, 10, 6, 7, 8, 6, 8, 5, 4, 10, 8, 5, 11, 10]\n",
      "Genrtn 95: mean = 8.36  stddev = 2.8706096913373647  max = 17 [8, 14, 3, 7, 7, 10, 12, 8, 10, 6, 4, 4, 4, 9, 12, 7, 4, 6, 9, 5, 6, 7, 9, 7, 9, 17, 10, 11, 7, 7, 7, 9, 9, 6, 5, 10, 5, 8, 4, 10, 9, 8, 4, 7, 7, 5, 9, 7, 5, 5, 7, 5, 8, 8, 11, 7, 10, 10, 10, 6, 4, 7, 9, 11, 8, 6, 7, 9, 7, 6, 7, 4, 6, 6, 8, 11, 9, 11, 5, 10, 16, 13, 15, 8, 5, 7, 10, 9, 9, 7, 9, 8, 6, 9, 7, 7, 7, 6, 7, 13, 5, 6, 8, 7, 11, 8, 12, 10, 7, 15, 11, 10, 12, 11, 6, 6, 9, 7, 8, 7, 8, 11, 9, 17, 6, 14, 8, 11, 9, 13, 8, 12, 10, 4, 11, 5, 7, 5, 3, 12, 8, 8, 13, 12, 13, 9, 6, 11, 7, 13, 11, 8, 7, 9, 5, 9, 10, 9, 9, 12, 8, 9, 14, 7, 2, 5, 8, 15, 10, 11, 10, 14, 9, 8, 10, 2, 10, 3, 6, 13, 10, 7, 8, 8, 10, 8, 5, 11, 7, 10, 12, 6, 8, 6, 4, 7, 8, 9, 13, 4]\n",
      "Genrtn 96: mean = 8.28  stddev = 2.8899134935149875  max = 17 [8, 9, 7, 8, 12, 7, 7, 8, 5, 9, 4, 8, 8, 7, 7, 8, 11, 8, 12, 5, 9, 7, 5, 3, 7, 8, 8, 4, 9, 4, 8, 11, 10, 7, 7, 5, 2, 11, 13, 7, 9, 10, 8, 7, 5, 6, 8, 7, 7, 9, 10, 6, 10, 11, 15, 9, 9, 7, 4, 5, 8, 8, 8, 8, 8, 7, 8, 4, 13, 9, 5, 16, 10, 9, 12, 5, 11, 4, 11, 9, 5, 10, 8, 9, 7, 12, 8, 13, 9, 5, 6, 2, 5, 10, 10, 8, 10, 17, 9, 7, 9, 11, 7, 3, 11, 5, 13, 12, 6, 12, 11, 14, 6, 8, 11, 10, 8, 6, 8, 9, 9, 8, 8, 12, 6, 10, 3, 6, 11, 3, 8, 6, 7, 7, 5, 9, 4, 8, 7, 11, 13, 8, 13, 8, 14, 7, 8, 6, 12, 12, 17, 7, 11, 5, 7, 11, 9, 7, 10, 5, 9, 8, 6, 6, 13, 5, 9, 12, 6, 9, 12, 15, 4, 10, 7, 8, 9, 12, 9, 6, 6, 3, 6, 10, 11, 12, 7, 5, 9, 16, 5, 8, 4, 10, 4, 6, 9, 8, 10, 6]\n",
      "Genrtn 97: mean = 8.045  stddev = 2.888420848837648  max = 18 [9, 8, 8, 9, 11, 4, 13, 10, 9, 12, 6, 12, 12, 5, 8, 9, 11, 6, 12, 9, 11, 3, 6, 5, 5, 6, 5, 7, 9, 5, 8, 13, 7, 10, 11, 8, 8, 8, 12, 11, 7, 8, 7, 10, 9, 5, 7, 7, 10, 10, 6, 10, 5, 9, 5, 11, 9, 7, 7, 10, 11, 11, 5, 7, 8, 10, 6, 3, 5, 11, 5, 12, 13, 12, 4, 4, 10, 10, 7, 10, 7, 7, 11, 5, 7, 8, 10, 10, 7, 9, 9, 8, 6, 5, 6, 7, 11, 5, 4, 12, 5, 8, 13, 10, 8, 4, 12, 6, 5, 6, 3, 7, 13, 2, 11, 6, 13, 7, 9, 11, 8, 6, 6, 6, 7, 10, 5, 11, 8, 11, 3, 6, 6, 9, 10, 12, 11, 8, 6, 13, 10, 6, 8, 8, 12, 6, 7, 12, 7, 5, 10, 8, 3, 12, 3, 7, 5, 10, 7, 6, 2, 6, 5, 8, 5, 9, 3, 11, 12, 8, 5, 6, 10, 3, 6, 9, 5, 6, 8, 10, 10, 18, 17, 2, 7, 6, 3, 9, 6, 8, 13, 12, 7, 7, 8, 8, 7, 13, 8, 12]\n",
      "Genrtn 98: mean = 8.53  stddev = 2.8929396813621953  max = 18 [13, 8, 6, 9, 5, 10, 11, 5, 6, 7, 7, 11, 7, 9, 7, 10, 5, 9, 11, 0, 9, 9, 13, 10, 7, 8, 9, 11, 11, 14, 10, 7, 11, 10, 9, 10, 7, 8, 5, 12, 10, 11, 4, 9, 9, 13, 9, 5, 11, 11, 11, 9, 3, 11, 7, 7, 10, 5, 11, 11, 10, 7, 11, 7, 10, 13, 8, 5, 11, 5, 14, 16, 9, 6, 9, 6, 12, 10, 6, 6, 8, 7, 9, 9, 6, 8, 8, 8, 6, 11, 17, 9, 8, 10, 9, 13, 7, 10, 6, 10, 7, 6, 9, 13, 10, 9, 6, 7, 7, 9, 9, 7, 6, 7, 8, 7, 6, 6, 4, 11, 12, 13, 7, 11, 6, 8, 7, 7, 9, 14, 9, 13, 7, 6, 2, 18, 10, 8, 11, 9, 11, 6, 8, 17, 6, 2, 10, 6, 8, 6, 8, 6, 9, 11, 10, 14, 4, 7, 10, 8, 12, 5, 10, 7, 14, 11, 7, 7, 4, 12, 11, 7, 10, 5, 3, 8, 9, 8, 11, 4, 13, 5, 8, 7, 7, 2, 4, 6, 6, 10, 8, 9, 13, 7, 7, 7, 9, 4, 8, 10]\n",
      "Genrtn 99: mean = 7.52  stddev = 2.7367133572955717  max = 17 [5, 7, 6, 10, 7, 7, 8, 6, 8, 9, 6, 3, 7, 8, 7, 7, 8, 8, 10, 5, 5, 7, 7, 10, 6, 11, 12, 7, 9, 13, 13, 9, 9, 5, 9, 5, 7, 10, 5, 11, 3, 8, 5, 7, 7, 9, 6, 10, 7, 12, 5, 7, 5, 9, 9, 4, 9, 7, 10, 5, 7, 12, 5, 8, 10, 4, 9, 8, 10, 8, 5, 8, 6, 4, 5, 8, 4, 8, 4, 6, 4, 4, 11, 14, 5, 11, 7, 9, 11, 5, 7, 6, 4, 6, 9, 11, 6, 7, 14, 5, 6, 8, 7, 7, 9, 10, 7, 8, 6, 7, 9, 9, 7, 5, 9, 5, 9, 11, 8, 8, 5, 8, 8, 8, 7, 8, 7, 4, 9, 13, 7, 5, 9, 5, 9, 5, 4, 15, 5, 10, 6, 5, 2, 10, 6, 9, 8, 8, 10, 5, 9, 13, 6, 3, 11, 4, 2, 3, 5, 10, 8, 9, 4, 8, 5, 8, 8, 2, 9, 11, 2, 11, 4, 12, 10, 5, 4, 9, 15, 6, 4, 13, 9, 6, 3, 9, 9, 6, 8, 10, 4, 7, 13, 5, 7, 7, 17, 11, 6, 8]\n",
      "Genrtn 100: mean = 7.925  stddev = 2.801673606971376  max = 20 [12, 7, 9, 4, 4, 13, 10, 11, 8, 8, 13, 12, 13, 16, 4, 9, 7, 11, 16, 4, 6, 15, 6, 5, 10, 9, 7, 12, 11, 6, 7, 10, 6, 10, 10, 8, 3, 5, 12, 7, 8, 8, 12, 11, 4, 10, 9, 8, 8, 6, 5, 7, 8, 5, 6, 8, 5, 9, 5, 6, 7, 7, 9, 6, 6, 13, 5, 9, 8, 7, 3, 11, 11, 4, 7, 10, 10, 10, 4, 7, 6, 8, 7, 4, 4, 5, 8, 5, 8, 8, 4, 8, 12, 9, 4, 7, 7, 6, 9, 11, 5, 6, 8, 6, 9, 9, 10, 9, 6, 9, 3, 8, 13, 9, 11, 11, 11, 9, 6, 10, 9, 6, 6, 6, 3, 8, 4, 10, 10, 5, 7, 13, 6, 10, 6, 4, 10, 6, 8, 6, 7, 7, 9, 8, 2, 5, 9, 10, 10, 20, 14, 10, 7, 7, 8, 7, 6, 11, 6, 11, 14, 6, 7, 4, 9, 10, 11, 6, 6, 6, 9, 8, 12, 9, 7, 7, 6, 10, 10, 8, 5, 5, 9, 4, 9, 7, 7, 4, 8, 6, 9, 6, 5, 7, 10, 9, 6, 8, 6, 7]\n",
      "Genrtn 101: mean = 8.17  stddev = 2.6440688342023173  max = 15 [11, 9, 10, 6, 13, 8, 9, 11, 9, 12, 7, 13, 4, 11, 10, 14, 6, 2, 8, 13, 7, 10, 8, 8, 12, 5, 9, 14, 11, 2, 8, 8, 5, 6, 5, 3, 6, 9, 7, 7, 9, 6, 10, 7, 4, 8, 6, 9, 8, 12, 10, 5, 6, 7, 11, 11, 10, 10, 11, 5, 9, 7, 12, 8, 12, 9, 8, 9, 8, 7, 6, 6, 8, 7, 8, 11, 12, 6, 7, 8, 6, 10, 7, 8, 9, 10, 7, 8, 6, 15, 9, 10, 8, 6, 14, 7, 11, 10, 13, 7, 6, 12, 7, 12, 7, 7, 7, 8, 8, 7, 4, 14, 8, 7, 6, 5, 10, 11, 4, 7, 8, 5, 8, 9, 9, 6, 9, 11, 12, 7, 8, 11, 4, 5, 6, 8, 9, 4, 8, 9, 4, 10, 8, 11, 6, 9, 9, 4, 12, 5, 8, 3, 9, 2, 8, 6, 10, 9, 7, 5, 12, 10, 11, 6, 12, 8, 6, 10, 5, 10, 9, 9, 6, 5, 6, 7, 7, 14, 8, 9, 5, 8, 9, 4, 15, 8, 5, 7, 9, 6, 12, 9, 7, 9, 4, 9, 5, 9, 11, 5]\n",
      "Genrtn 102: mean = 7.645  stddev = 2.8158435680981997  max = 17 [9, 12, 11, 5, 5, 4, 2, 7, 13, 15, 5, 8, 10, 11, 9, 12, 11, 7, 10, 5, 6, 6, 6, 6, 6, 7, 4, 8, 13, 11, 11, 5, 9, 5, 4, 6, 7, 7, 8, 3, 9, 4, 4, 7, 7, 7, 4, 5, 5, 4, 5, 4, 13, 7, 6, 9, 9, 9, 5, 10, 5, 11, 11, 6, 5, 4, 7, 11, 7, 6, 9, 7, 12, 7, 8, 7, 3, 11, 7, 12, 5, 6, 8, 9, 8, 4, 4, 10, 4, 4, 7, 6, 6, 7, 9, 3, 11, 8, 8, 8, 10, 7, 8, 7, 11, 8, 5, 5, 8, 12, 8, 7, 7, 14, 6, 8, 10, 8, 9, 8, 6, 10, 5, 8, 7, 9, 9, 16, 17, 9, 7, 12, 7, 10, 13, 10, 10, 4, 6, 6, 8, 3, 9, 8, 6, 5, 4, 5, 9, 6, 7, 9, 4, 14, 8, 8, 13, 10, 5, 13, 9, 8, 14, 4, 8, 8, 8, 5, 8, 7, 8, 4, 5, 6, 11, 8, 13, 7, 7, 8, 5, 10, 9, 5, 3, 11, 6, 6, 8, 7, 10, 5, 9, 3, 10, 6, 4, 5, 11, 6]\n",
      "Genrtn 103: mean = 7.99  stddev = 2.9325586098149854  max = 18 [10, 8, 6, 12, 12, 8, 6, 10, 8, 10, 7, 5, 8, 6, 12, 7, 4, 4, 9, 8, 10, 9, 6, 13, 8, 5, 10, 7, 9, 9, 3, 8, 4, 6, 8, 10, 7, 4, 11, 9, 7, 9, 8, 7, 6, 8, 17, 10, 7, 10, 6, 6, 2, 13, 10, 6, 13, 7, 11, 13, 13, 8, 6, 5, 12, 3, 3, 5, 7, 10, 3, 8, 9, 6, 9, 4, 6, 5, 10, 10, 6, 5, 10, 8, 10, 10, 9, 9, 8, 12, 6, 5, 11, 8, 6, 9, 9, 5, 12, 10, 7, 4, 11, 9, 3, 6, 4, 8, 11, 11, 5, 8, 7, 6, 8, 12, 8, 6, 8, 10, 11, 7, 6, 11, 9, 9, 9, 9, 7, 4, 9, 5, 15, 7, 3, 8, 9, 8, 15, 4, 11, 4, 18, 7, 8, 15, 9, 8, 11, 9, 7, 7, 7, 9, 12, 11, 4, 7, 5, 4, 14, 8, 12, 3, 4, 7, 7, 7, 7, 7, 4, 5, 6, 11, 3, 4, 10, 8, 8, 6, 5, 7, 9, 8, 5, 7, 7, 13, 8, 10, 10, 18, 7, 8, 7, 7, 3, 11, 7, 8]\n",
      "Genrtn 104: mean = 8.0  stddev = 2.8635642126552705  max = 16 [9, 6, 5, 8, 5, 8, 5, 7, 10, 7, 10, 6, 12, 7, 9, 7, 6, 9, 9, 13, 7, 10, 11, 15, 12, 8, 9, 13, 13, 11, 5, 11, 4, 7, 5, 5, 5, 9, 9, 7, 7, 7, 15, 5, 7, 9, 7, 6, 8, 12, 8, 7, 6, 8, 14, 3, 2, 8, 8, 6, 3, 5, 10, 5, 2, 12, 5, 9, 7, 8, 5, 9, 5, 8, 8, 8, 9, 4, 6, 6, 13, 12, 13, 5, 5, 7, 10, 6, 11, 7, 10, 10, 8, 9, 4, 16, 6, 7, 11, 5, 4, 7, 8, 11, 13, 15, 8, 6, 13, 7, 4, 9, 8, 5, 12, 10, 6, 10, 10, 7, 10, 11, 9, 4, 6, 9, 12, 4, 12, 7, 4, 6, 7, 7, 4, 8, 9, 9, 11, 10, 11, 7, 8, 11, 8, 5, 6, 11, 8, 8, 11, 6, 4, 12, 6, 5, 6, 8, 6, 9, 7, 5, 10, 11, 12, 8, 10, 7, 5, 9, 11, 9, 7, 4, 7, 9, 6, 8, 8, 6, 4, 7, 10, 2, 12, 7, 16, 7, 8, 5, 5, 8, 5, 5, 7, 6, 5, 12, 12, 14]\n",
      "Genrtn 105: mean = 7.8  stddev = 2.630589287593181  max = 17 [9, 8, 8, 11, 7, 9, 11, 5, 7, 3, 10, 6, 9, 4, 6, 11, 12, 9, 9, 3, 12, 8, 9, 10, 7, 9, 9, 8, 10, 12, 12, 4, 9, 6, 5, 7, 11, 8, 5, 8, 5, 8, 7, 7, 6, 10, 9, 14, 6, 7, 14, 3, 10, 7, 5, 7, 7, 5, 9, 4, 5, 7, 11, 8, 6, 8, 6, 9, 9, 9, 5, 7, 7, 6, 8, 14, 9, 10, 12, 3, 7, 7, 9, 4, 7, 12, 11, 4, 4, 11, 9, 9, 3, 8, 4, 6, 6, 5, 10, 10, 4, 9, 13, 9, 6, 11, 10, 11, 9, 5, 12, 12, 7, 6, 5, 10, 7, 10, 11, 7, 4, 11, 6, 5, 9, 10, 7, 12, 7, 8, 5, 9, 5, 6, 5, 10, 11, 9, 9, 10, 7, 4, 8, 10, 8, 9, 3, 7, 17, 11, 3, 9, 2, 7, 5, 7, 10, 8, 6, 12, 13, 9, 6, 7, 5, 8, 7, 8, 7, 5, 8, 9, 9, 9, 4, 6, 7, 10, 6, 7, 11, 3, 8, 6, 10, 8, 3, 9, 6, 11, 7, 4, 8, 9, 6, 9, 7, 9, 4, 6]\n",
      "Genrtn 106: mean = 7.99  stddev = 2.7184370509540954  max = 18 [14, 7, 9, 11, 5, 12, 10, 6, 7, 9, 10, 9, 7, 9, 7, 6, 12, 11, 5, 9, 7, 4, 8, 11, 7, 9, 8, 11, 6, 6, 4, 6, 3, 11, 6, 11, 7, 8, 8, 2, 6, 9, 11, 10, 6, 8, 5, 8, 11, 1, 9, 7, 5, 8, 4, 9, 7, 11, 9, 5, 8, 5, 8, 11, 8, 6, 4, 9, 7, 7, 9, 8, 10, 11, 10, 8, 7, 11, 4, 9, 5, 6, 11, 15, 7, 5, 8, 8, 11, 7, 6, 4, 13, 8, 9, 6, 8, 9, 3, 6, 18, 6, 9, 5, 8, 9, 11, 10, 6, 11, 5, 10, 6, 9, 7, 5, 10, 6, 9, 5, 8, 8, 6, 12, 5, 7, 4, 7, 8, 6, 5, 8, 9, 9, 9, 5, 3, 10, 12, 5, 6, 16, 8, 3, 6, 8, 6, 10, 12, 11, 7, 7, 8, 8, 10, 7, 8, 9, 5, 7, 10, 4, 4, 10, 7, 17, 6, 4, 8, 6, 8, 14, 8, 7, 10, 10, 5, 11, 13, 7, 12, 11, 8, 9, 7, 10, 5, 11, 13, 6, 11, 5, 9, 9, 5, 9, 8, 9, 8, 9]\n",
      "Genrtn 107: mean = 7.865  stddev = 2.761661637492906  max = 17 [12, 5, 8, 9, 3, 7, 11, 6, 9, 10, 4, 9, 4, 9, 13, 6, 8, 5, 7, 9, 11, 9, 8, 11, 9, 13, 8, 2, 11, 8, 8, 7, 8, 4, 8, 10, 11, 7, 5, 4, 7, 6, 13, 7, 9, 9, 9, 12, 5, 8, 10, 7, 6, 13, 6, 8, 9, 8, 6, 8, 6, 10, 5, 3, 3, 5, 10, 3, 6, 6, 5, 7, 9, 5, 11, 9, 9, 12, 9, 7, 10, 8, 6, 7, 8, 9, 7, 16, 5, 10, 10, 7, 8, 3, 8, 4, 7, 4, 5, 8, 11, 8, 11, 13, 5, 5, 15, 3, 11, 10, 5, 6, 7, 8, 11, 5, 2, 11, 12, 4, 11, 15, 8, 11, 7, 5, 6, 9, 6, 7, 8, 11, 7, 7, 7, 6, 8, 11, 9, 17, 9, 6, 8, 8, 11, 10, 10, 10, 11, 8, 3, 9, 10, 10, 6, 2, 3, 12, 10, 9, 9, 6, 8, 8, 10, 9, 5, 7, 7, 8, 8, 4, 6, 4, 5, 12, 8, 10, 10, 10, 10, 2, 8, 9, 5, 5, 8, 5, 6, 5, 6, 12, 10, 6, 8, 8, 7, 9, 6, 8]\n",
      "Genrtn 108: mean = 7.94  stddev = 2.6203816515919964  max = 19 [7, 10, 8, 7, 6, 5, 8, 5, 8, 2, 10, 6, 16, 8, 7, 9, 8, 7, 3, 8, 7, 10, 5, 9, 4, 11, 4, 10, 9, 9, 8, 9, 4, 5, 9, 14, 6, 11, 3, 7, 6, 19, 10, 6, 6, 7, 9, 7, 9, 6, 5, 6, 10, 6, 9, 11, 7, 8, 13, 7, 14, 8, 9, 4, 6, 12, 7, 6, 9, 7, 7, 6, 6, 9, 9, 8, 10, 6, 2, 8, 12, 11, 11, 8, 8, 4, 8, 10, 7, 8, 10, 10, 8, 4, 6, 13, 13, 3, 7, 15, 12, 8, 10, 10, 6, 7, 8, 6, 9, 6, 9, 4, 7, 8, 7, 11, 10, 7, 8, 5, 6, 7, 7, 12, 9, 12, 7, 10, 10, 8, 5, 10, 7, 9, 6, 9, 5, 12, 10, 6, 5, 8, 7, 6, 8, 9, 8, 9, 7, 10, 10, 10, 9, 8, 7, 8, 6, 5, 5, 12, 11, 8, 4, 10, 9, 7, 8, 7, 8, 7, 9, 10, 10, 10, 7, 6, 8, 9, 7, 12, 5, 2, 13, 10, 6, 3, 5, 8, 10, 8, 12, 6, 2, 9, 6, 7, 7, 7, 8, 7]\n",
      "Genrtn 109: mean = 8.125  stddev = 2.894715011879408  max = 18 [11, 5, 6, 9, 6, 7, 13, 9, 7, 8, 11, 5, 5, 6, 8, 12, 6, 11, 5, 9, 8, 9, 5, 8, 15, 8, 4, 8, 8, 7, 13, 5, 8, 10, 9, 11, 6, 5, 13, 12, 9, 6, 9, 10, 7, 11, 7, 5, 4, 4, 12, 8, 8, 3, 2, 8, 9, 11, 9, 9, 12, 14, 2, 12, 9, 7, 10, 9, 3, 12, 5, 14, 8, 10, 9, 6, 12, 10, 9, 7, 6, 12, 6, 11, 11, 6, 18, 7, 7, 7, 7, 9, 5, 10, 8, 8, 10, 11, 2, 14, 11, 5, 10, 7, 9, 12, 12, 6, 11, 5, 4, 9, 6, 8, 10, 8, 9, 4, 6, 5, 9, 8, 10, 5, 6, 11, 10, 11, 9, 11, 5, 8, 11, 10, 9, 9, 8, 11, 10, 9, 10, 3, 13, 9, 2, 4, 9, 5, 8, 5, 2, 4, 5, 11, 8, 9, 7, 6, 10, 5, 6, 10, 4, 3, 12, 10, 4, 5, 6, 6, 7, 9, 11, 9, 5, 3, 14, 4, 11, 13, 7, 10, 7, 7, 11, 10, 10, 9, 8, 5, 9, 8, 6, 4, 9, 9, 8, 6, 12, 9]\n",
      "Genrtn 110: mean = 7.83  stddev = 2.5614644248944782  max = 14 [8, 10, 9, 11, 6, 9, 10, 8, 5, 10, 7, 10, 9, 13, 10, 12, 6, 14, 5, 9, 7, 6, 10, 6, 4, 9, 10, 6, 5, 13, 6, 13, 11, 9, 9, 5, 6, 6, 9, 5, 9, 11, 10, 10, 8, 10, 6, 11, 12, 8, 10, 7, 10, 11, 11, 9, 6, 8, 4, 6, 8, 0, 5, 8, 11, 11, 6, 7, 9, 8, 7, 8, 3, 4, 6, 10, 8, 12, 9, 7, 10, 8, 5, 11, 9, 14, 6, 7, 5, 5, 7, 6, 6, 7, 7, 9, 11, 12, 14, 14, 8, 8, 10, 8, 7, 7, 11, 7, 4, 11, 7, 7, 8, 7, 9, 5, 6, 5, 2, 3, 11, 7, 5, 7, 7, 10, 9, 6, 8, 10, 5, 8, 8, 6, 10, 9, 6, 6, 7, 4, 11, 9, 10, 4, 6, 10, 9, 3, 8, 10, 9, 5, 9, 6, 10, 9, 5, 11, 7, 6, 7, 5, 12, 1, 4, 7, 9, 6, 5, 5, 9, 8, 3, 8, 12, 7, 7, 10, 8, 4, 6, 3, 6, 9, 9, 9, 9, 9, 9, 7, 7, 7, 11, 7, 8, 4, 11, 5, 7, 7]\n",
      "Genrtn 111: mean = 7.955  stddev = 2.997161156828241  max = 18 [9, 6, 5, 5, 5, 7, 4, 7, 12, 12, 4, 10, 11, 12, 11, 6, 14, 11, 7, 11, 8, 12, 4, 8, 9, 2, 10, 11, 8, 9, 3, 8, 4, 8, 14, 9, 6, 5, 10, 5, 7, 12, 9, 11, 8, 5, 6, 6, 8, 6, 8, 12, 6, 13, 6, 5, 5, 14, 8, 6, 5, 5, 13, 5, 13, 9, 5, 10, 7, 6, 8, 4, 9, 12, 6, 8, 10, 8, 7, 8, 8, 6, 7, 6, 5, 5, 9, 4, 6, 9, 8, 6, 7, 7, 6, 9, 4, 12, 7, 9, 5, 12, 12, 8, 4, 10, 13, 4, 10, 8, 4, 10, 7, 7, 4, 11, 18, 12, 9, 9, 4, 2, 9, 9, 3, 12, 10, 6, 10, 8, 9, 3, 10, 6, 9, 8, 15, 10, 6, 9, 4, 10, 7, 6, 7, 9, 6, 7, 9, 6, 5, 13, 9, 5, 12, 8, 8, 2, 6, 6, 9, 8, 6, 6, 8, 10, 6, 13, 5, 11, 6, 8, 8, 11, 14, 4, 7, 14, 5, 5, 5, 5, 4, 4, 13, 14, 6, 6, 6, 9, 13, 4, 8, 9, 9, 13, 5, 11, 13, 9]\n",
      "Genrtn 112: mean = 8.115  stddev = 2.8092303216361594  max = 19 [5, 14, 12, 5, 8, 12, 5, 9, 8, 5, 6, 10, 11, 5, 10, 6, 7, 7, 10, 10, 10, 9, 12, 7, 10, 5, 10, 10, 9, 6, 6, 9, 13, 8, 6, 10, 13, 8, 9, 10, 8, 11, 5, 7, 8, 8, 8, 9, 9, 11, 10, 9, 7, 10, 4, 11, 8, 5, 6, 9, 10, 14, 5, 15, 10, 7, 7, 7, 12, 8, 6, 7, 2, 7, 12, 6, 8, 4, 9, 15, 9, 10, 10, 6, 7, 11, 13, 7, 6, 4, 5, 7, 6, 11, 7, 9, 4, 10, 10, 5, 6, 13, 6, 12, 9, 9, 4, 13, 7, 6, 8, 7, 9, 6, 11, 4, 13, 7, 11, 7, 4, 6, 4, 7, 8, 7, 8, 5, 6, 6, 11, 8, 11, 11, 7, 12, 2, 6, 6, 4, 9, 10, 10, 7, 11, 6, 9, 9, 9, 7, 8, 8, 5, 9, 6, 13, 8, 13, 10, 6, 6, 4, 7, 19, 11, 8, 9, 9, 11, 1, 2, 10, 10, 9, 7, 5, 11, 5, 6, 7, 7, 8, 7, 12, 4, 9, 4, 8, 5, 5, 5, 11, 12, 8, 3, 5, 8, 11, 10, 8]\n",
      "Genrtn 113: mean = 8.275  stddev = 3.01983029324497  max = 17 [5, 6, 4, 12, 15, 3, 5, 7, 5, 6, 6, 7, 11, 5, 5, 7, 10, 6, 3, 10, 7, 6, 8, 8, 8, 13, 7, 7, 5, 4, 11, 11, 5, 7, 8, 6, 8, 7, 4, 8, 7, 7, 5, 7, 7, 9, 7, 10, 10, 13, 6, 5, 6, 16, 7, 10, 6, 15, 4, 11, 12, 9, 9, 7, 6, 3, 3, 6, 10, 4, 13, 10, 9, 9, 10, 7, 7, 11, 5, 12, 9, 4, 7, 5, 8, 14, 5, 7, 10, 4, 7, 8, 7, 13, 11, 8, 3, 8, 6, 14, 13, 4, 10, 14, 10, 5, 7, 8, 9, 6, 7, 9, 8, 6, 17, 8, 9, 8, 9, 8, 8, 6, 6, 6, 8, 7, 16, 14, 10, 11, 1, 6, 3, 7, 8, 5, 7, 10, 9, 12, 6, 5, 13, 6, 7, 13, 11, 7, 13, 13, 9, 7, 10, 11, 9, 10, 10, 6, 5, 8, 7, 8, 5, 10, 4, 12, 12, 11, 6, 12, 8, 8, 5, 8, 6, 11, 11, 10, 13, 10, 7, 7, 8, 4, 8, 14, 12, 10, 11, 7, 7, 11, 9, 8, 13, 6, 10, 15, 12, 11]\n",
      "Genrtn 114: mean = 7.675  stddev = 2.7837699258379813  max = 17 [13, 7, 7, 10, 11, 10, 4, 9, 6, 8, 7, 6, 12, 8, 10, 5, 11, 7, 7, 8, 10, 6, 7, 6, 9, 5, 5, 2, 8, 6, 8, 13, 6, 8, 12, 6, 9, 4, 15, 5, 8, 6, 7, 11, 8, 5, 9, 7, 9, 13, 6, 9, 12, 13, 2, 11, 10, 4, 11, 8, 4, 11, 7, 7, 4, 6, 10, 7, 10, 8, 6, 12, 1, 5, 9, 7, 15, 8, 1, 5, 7, 11, 11, 5, 6, 8, 8, 7, 6, 9, 12, 10, 7, 6, 5, 9, 6, 7, 9, 4, 3, 10, 6, 6, 9, 7, 6, 10, 8, 5, 15, 7, 5, 12, 10, 4, 10, 7, 7, 10, 8, 8, 5, 4, 12, 10, 7, 8, 7, 12, 3, 6, 6, 9, 8, 8, 11, 7, 4, 9, 8, 6, 3, 12, 11, 17, 7, 8, 8, 4, 10, 6, 9, 9, 7, 6, 10, 5, 5, 9, 9, 6, 8, 8, 6, 11, 7, 8, 5, 9, 4, 8, 9, 9, 5, 6, 9, 7, 8, 9, 10, 5, 3, 3, 6, 6, 6, 11, 6, 5, 3, 7, 11, 6, 9, 4, 10, 5, 14, 4]\n",
      "Genrtn 115: mean = 7.9  stddev = 2.7331300737432898  max = 17 [7, 8, 6, 3, 6, 6, 11, 12, 2, 9, 7, 7, 7, 4, 7, 7, 11, 5, 8, 13, 11, 6, 7, 10, 9, 6, 9, 5, 11, 5, 13, 9, 4, 10, 8, 9, 8, 7, 4, 6, 10, 5, 9, 7, 6, 5, 5, 3, 7, 8, 8, 5, 7, 12, 8, 4, 16, 8, 8, 11, 10, 8, 11, 6, 4, 10, 10, 8, 10, 10, 6, 10, 4, 9, 7, 5, 9, 5, 12, 3, 5, 9, 11, 7, 7, 7, 7, 3, 6, 11, 10, 8, 10, 10, 6, 9, 12, 4, 12, 7, 7, 6, 6, 8, 3, 8, 8, 6, 6, 4, 7, 6, 8, 8, 7, 6, 6, 7, 6, 8, 8, 4, 6, 10, 4, 7, 13, 8, 8, 12, 12, 15, 11, 5, 10, 6, 9, 9, 8, 6, 13, 9, 7, 3, 9, 4, 7, 10, 7, 9, 6, 14, 9, 3, 6, 10, 8, 9, 12, 8, 8, 4, 5, 17, 10, 6, 10, 8, 7, 7, 6, 4, 8, 6, 12, 8, 7, 7, 8, 17, 11, 12, 8, 11, 15, 9, 8, 7, 9, 10, 7, 7, 6, 10, 6, 9, 8, 9, 7, 8]\n",
      "Genrtn 116: mean = 7.775  stddev = 2.907640796247019  max = 18 [6, 9, 11, 13, 13, 5, 6, 8, 9, 9, 5, 4, 6, 11, 8, 10, 7, 10, 7, 7, 8, 5, 6, 7, 6, 4, 9, 6, 6, 12, 5, 4, 6, 7, 11, 13, 9, 9, 12, 11, 6, 9, 10, 7, 10, 7, 6, 8, 6, 3, 6, 8, 3, 5, 5, 11, 5, 10, 7, 4, 11, 4, 11, 5, 12, 11, 6, 10, 8, 9, 6, 7, 7, 12, 7, 6, 3, 8, 9, 7, 17, 7, 8, 8, 5, 5, 9, 9, 9, 14, 4, 15, 8, 8, 13, 12, 7, 5, 5, 5, 9, 10, 10, 9, 5, 10, 11, 3, 7, 9, 4, 3, 7, 2, 8, 10, 7, 10, 11, 6, 10, 9, 10, 11, 7, 7, 10, 4, 7, 16, 11, 7, 9, 8, 11, 8, 6, 9, 5, 4, 7, 9, 8, 9, 18, 11, 6, 11, 8, 3, 11, 8, 3, 9, 6, 6, 4, 7, 9, 6, 4, 8, 8, 4, 7, 11, 5, 13, 10, 8, 5, 4, 3, 5, 7, 8, 4, 8, 12, 9, 5, 7, 9, 3, 3, 9, 3, 12, 10, 11, 7, 1, 7, 7, 8, 9, 11, 6, 8, 9]\n",
      "Genrtn 117: mean = 7.635  stddev = 2.753502315234182  max = 15 [10, 6, 8, 8, 3, 7, 13, 9, 8, 4, 11, 10, 8, 10, 5, 7, 6, 9, 2, 8, 9, 7, 8, 5, 4, 11, 5, 11, 8, 8, 9, 4, 4, 7, 7, 12, 2, 9, 13, 8, 9, 7, 6, 4, 5, 8, 7, 6, 8, 12, 12, 5, 5, 7, 10, 7, 8, 8, 6, 9, 5, 7, 7, 6, 4, 10, 7, 11, 7, 14, 8, 8, 3, 11, 7, 11, 7, 8, 7, 6, 7, 8, 5, 9, 3, 7, 7, 5, 9, 3, 6, 7, 9, 3, 8, 10, 7, 8, 9, 12, 9, 6, 12, 7, 10, 9, 6, 2, 12, 10, 5, 7, 8, 8, 10, 10, 14, 6, 6, 7, 4, 8, 8, 9, 7, 9, 13, 4, 6, 14, 13, 5, 5, 3, 5, 3, 5, 13, 6, 7, 10, 6, 6, 4, 8, 5, 13, 11, 7, 4, 6, 10, 7, 2, 10, 12, 5, 7, 8, 4, 7, 9, 4, 10, 9, 10, 8, 6, 6, 15, 15, 13, 8, 8, 6, 5, 7, 8, 4, 7, 10, 6, 11, 9, 8, 3, 5, 9, 6, 9, 6, 11, 6, 7, 10, 10, 13, 7, 6, 6]\n",
      "Genrtn 118: mean = 8.095  stddev = 2.7723591037237583  max = 19 [7, 9, 8, 13, 6, 4, 11, 11, 3, 6, 10, 8, 6, 9, 4, 12, 13, 9, 9, 3, 9, 5, 8, 5, 5, 5, 9, 11, 6, 6, 5, 7, 5, 8, 7, 3, 8, 13, 7, 8, 6, 5, 12, 7, 7, 4, 7, 7, 9, 15, 12, 12, 12, 7, 6, 8, 12, 9, 13, 6, 4, 5, 7, 8, 7, 8, 5, 5, 11, 8, 10, 6, 15, 9, 6, 5, 6, 8, 9, 7, 8, 10, 6, 7, 10, 7, 8, 12, 5, 8, 7, 7, 7, 12, 8, 7, 6, 8, 6, 12, 9, 7, 10, 6, 8, 7, 12, 9, 7, 6, 14, 7, 14, 4, 5, 9, 6, 6, 12, 6, 7, 12, 6, 4, 6, 3, 12, 10, 7, 4, 7, 7, 9, 10, 10, 10, 7, 12, 7, 8, 6, 7, 5, 2, 9, 7, 4, 8, 11, 11, 12, 6, 9, 9, 9, 13, 7, 6, 6, 6, 12, 10, 12, 7, 7, 9, 11, 11, 6, 11, 10, 9, 8, 8, 6, 8, 11, 6, 8, 9, 11, 3, 9, 7, 7, 6, 7, 13, 7, 13, 7, 7, 11, 6, 8, 8, 19, 5, 14, 10]\n",
      "Genrtn 119: mean = 7.79  stddev = 2.5701945451657937  max = 16 [9, 1, 8, 6, 6, 7, 11, 10, 3, 7, 10, 7, 5, 6, 10, 10, 3, 5, 4, 7, 5, 7, 7, 6, 7, 6, 3, 10, 9, 9, 6, 6, 12, 8, 7, 8, 9, 9, 8, 3, 8, 9, 5, 7, 10, 11, 10, 8, 7, 9, 12, 10, 8, 7, 5, 7, 11, 5, 10, 9, 4, 4, 4, 8, 10, 11, 8, 7, 9, 11, 5, 9, 4, 8, 10, 6, 10, 10, 6, 4, 6, 6, 7, 6, 12, 12, 11, 5, 2, 10, 3, 11, 8, 5, 7, 10, 9, 9, 7, 8, 10, 8, 7, 4, 11, 10, 7, 7, 6, 2, 5, 9, 5, 5, 7, 7, 7, 9, 8, 6, 11, 9, 10, 6, 6, 13, 9, 7, 14, 7, 6, 8, 8, 9, 11, 10, 8, 7, 6, 11, 7, 8, 6, 9, 11, 10, 10, 4, 5, 14, 5, 12, 4, 5, 14, 5, 16, 9, 4, 6, 10, 3, 8, 7, 8, 11, 8, 6, 9, 8, 9, 8, 7, 9, 6, 7, 10, 6, 14, 9, 6, 11, 7, 7, 13, 8, 8, 7, 7, 11, 8, 6, 7, 10, 11, 8, 4, 10, 8, 8]\n",
      "Genrtn 120: mean = 8.12  stddev = 2.9318253699700465  max = 21 [11, 5, 8, 5, 8, 12, 12, 7, 9, 6, 8, 8, 9, 7, 9, 7, 11, 10, 7, 11, 11, 7, 10, 7, 7, 9, 5, 11, 6, 10, 7, 4, 10, 9, 7, 10, 7, 8, 8, 8, 6, 6, 10, 11, 4, 5, 6, 6, 6, 13, 12, 7, 10, 9, 7, 12, 8, 3, 10, 8, 9, 11, 4, 10, 10, 8, 9, 5, 13, 2, 5, 4, 13, 8, 8, 9, 9, 8, 7, 7, 10, 3, 7, 15, 10, 2, 12, 9, 5, 6, 2, 8, 14, 5, 11, 10, 8, 11, 13, 9, 10, 14, 8, 7, 9, 11, 9, 4, 7, 6, 8, 7, 5, 13, 11, 9, 5, 6, 4, 7, 9, 9, 9, 7, 8, 6, 4, 8, 14, 5, 9, 7, 6, 13, 3, 5, 12, 15, 9, 6, 4, 6, 4, 5, 5, 8, 13, 8, 7, 7, 5, 9, 6, 6, 12, 11, 7, 9, 5, 11, 5, 8, 7, 4, 9, 2, 11, 7, 12, 9, 6, 9, 8, 12, 5, 10, 7, 6, 8, 9, 21, 9, 9, 8, 6, 15, 5, 7, 3, 5, 7, 7, 8, 14, 5, 11, 12, 9, 8, 10]\n",
      "Genrtn 121: mean = 7.94  stddev = 3.0473595127585456  max = 17 [7, 8, 14, 8, 6, 6, 9, 10, 7, 7, 5, 7, 7, 6, 14, 9, 12, 11, 10, 2, 11, 6, 12, 10, 8, 6, 8, 9, 11, 10, 11, 6, 6, 9, 3, 12, 6, 8, 15, 12, 12, 5, 6, 15, 11, 5, 14, 7, 7, 10, 10, 6, 8, 10, 5, 10, 5, 8, 14, 6, 7, 5, 10, 5, 7, 6, 11, 10, 6, 6, 3, 10, 11, 12, 6, 12, 4, 7, 6, 9, 3, 8, 4, 6, 9, 8, 2, 3, 6, 15, 8, 10, 6, 7, 5, 4, 5, 3, 8, 8, 7, 10, 4, 10, 7, 8, 6, 9, 8, 9, 9, 5, 4, 9, 8, 9, 8, 13, 8, 11, 15, 5, 3, 5, 8, 16, 10, 3, 8, 10, 8, 7, 6, 6, 7, 9, 4, 7, 11, 8, 8, 17, 7, 6, 5, 9, 8, 11, 11, 4, 5, 13, 7, 8, 5, 10, 2, 8, 10, 11, 11, 4, 7, 9, 10, 7, 7, 9, 9, 5, 3, 4, 11, 10, 2, 4, 8, 12, 7, 9, 3, 8, 16, 11, 8, 9, 12, 6, 7, 7, 12, 6, 9, 4, 7, 3, 8, 7, 11, 4]\n",
      "Genrtn 122: mean = 8.08  stddev = 2.6783577057592587  max = 15 [8, 10, 7, 12, 5, 14, 5, 8, 3, 7, 9, 10, 5, 4, 7, 9, 11, 12, 7, 4, 6, 14, 9, 7, 11, 4, 11, 10, 8, 6, 8, 4, 10, 10, 11, 3, 8, 8, 7, 8, 10, 7, 6, 10, 5, 10, 7, 11, 3, 11, 10, 7, 10, 7, 7, 5, 8, 10, 10, 11, 14, 8, 11, 10, 7, 10, 5, 13, 9, 14, 11, 10, 4, 10, 12, 7, 7, 11, 7, 5, 11, 12, 10, 7, 7, 8, 7, 7, 7, 11, 10, 7, 1, 8, 10, 11, 6, 5, 6, 3, 3, 13, 10, 12, 9, 3, 7, 13, 8, 8, 12, 6, 7, 7, 8, 6, 10, 5, 8, 9, 4, 13, 10, 7, 11, 9, 8, 10, 8, 7, 4, 5, 9, 7, 8, 6, 5, 6, 11, 4, 7, 9, 4, 6, 6, 10, 9, 8, 9, 9, 8, 13, 6, 8, 12, 3, 5, 11, 10, 6, 8, 12, 15, 7, 9, 6, 5, 5, 10, 6, 12, 8, 12, 4, 6, 4, 7, 8, 8, 10, 10, 8, 10, 9, 5, 10, 8, 9, 8, 7, 10, 9, 7, 5, 5, 6, 11, 6, 6, 6]\n",
      "Genrtn 123: mean = 8.05  stddev = 2.8631276604440816  max = 15 [3, 7, 9, 9, 9, 8, 9, 5, 5, 5, 6, 9, 9, 10, 6, 3, 9, 4, 3, 11, 11, 7, 10, 7, 7, 10, 7, 7, 6, 8, 7, 8, 11, 4, 10, 12, 7, 15, 12, 9, 9, 8, 4, 12, 9, 5, 6, 4, 7, 11, 10, 9, 8, 5, 13, 6, 15, 7, 11, 7, 5, 13, 8, 9, 8, 11, 8, 7, 8, 5, 11, 13, 10, 15, 8, 8, 8, 8, 7, 4, 5, 8, 7, 10, 6, 9, 6, 6, 8, 6, 11, 12, 5, 5, 8, 2, 7, 11, 7, 10, 7, 11, 5, 7, 5, 12, 4, 7, 7, 6, 10, 13, 12, 15, 4, 9, 8, 7, 5, 12, 8, 3, 13, 6, 12, 6, 6, 10, 7, 6, 8, 7, 9, 7, 8, 5, 12, 4, 8, 6, 7, 10, 3, 7, 8, 8, 10, 7, 5, 5, 5, 15, 7, 7, 9, 11, 9, 15, 6, 10, 5, 9, 7, 11, 10, 10, 15, 5, 6, 5, 8, 5, 9, 9, 9, 3, 4, 10, 11, 11, 7, 2, 7, 11, 5, 4, 7, 14, 5, 9, 13, 11, 9, 8, 10, 14, 6, 8, 7, 7]\n",
      "Genrtn 124: mean = 8.06  stddev = 2.9114257675578816  max = 18 [7, 13, 6, 9, 8, 2, 5, 6, 8, 7, 8, 10, 2, 11, 12, 6, 6, 8, 9, 7, 8, 6, 12, 10, 7, 6, 9, 5, 7, 5, 5, 9, 7, 10, 6, 6, 6, 13, 11, 6, 12, 9, 3, 8, 6, 6, 11, 7, 9, 7, 8, 8, 5, 9, 13, 6, 5, 12, 11, 14, 12, 7, 10, 8, 6, 7, 5, 9, 13, 10, 7, 6, 11, 7, 7, 8, 6, 6, 6, 4, 8, 9, 12, 9, 5, 6, 6, 5, 6, 8, 7, 10, 4, 6, 11, 7, 9, 7, 10, 11, 8, 11, 11, 12, 10, 4, 13, 7, 16, 4, 12, 11, 7, 9, 1, 5, 4, 10, 3, 6, 5, 4, 14, 4, 6, 4, 5, 5, 12, 6, 6, 7, 9, 16, 8, 8, 14, 13, 9, 6, 9, 10, 5, 8, 5, 8, 4, 10, 5, 9, 8, 6, 7, 6, 10, 8, 13, 11, 8, 10, 9, 10, 5, 9, 6, 9, 7, 9, 13, 9, 10, 9, 11, 18, 12, 10, 5, 12, 9, 13, 10, 4, 9, 7, 5, 7, 5, 8, 5, 11, 13, 4, 9, 5, 4, 11, 5, 9, 8, 9]\n",
      "Genrtn 125: mean = 8.17  stddev = 2.714976979644579  max = 17 [5, 11, 7, 9, 11, 12, 9, 8, 4, 2, 4, 8, 8, 8, 10, 8, 7, 7, 7, 7, 11, 6, 7, 8, 10, 8, 10, 10, 8, 6, 7, 9, 6, 7, 12, 10, 10, 6, 8, 8, 8, 7, 12, 5, 4, 5, 9, 8, 7, 10, 6, 6, 6, 11, 15, 9, 8, 8, 8, 11, 10, 9, 8, 6, 4, 17, 14, 9, 16, 10, 4, 7, 10, 7, 10, 9, 9, 8, 9, 10, 8, 14, 7, 5, 7, 10, 8, 6, 11, 7, 12, 14, 6, 5, 6, 4, 5, 11, 2, 12, 9, 11, 9, 7, 9, 9, 8, 8, 5, 14, 12, 7, 6, 7, 9, 7, 9, 6, 8, 9, 8, 8, 6, 5, 8, 10, 6, 8, 5, 13, 11, 2, 7, 9, 11, 10, 8, 7, 14, 8, 6, 9, 6, 8, 8, 5, 9, 6, 12, 6, 8, 6, 7, 6, 4, 11, 11, 10, 11, 10, 8, 3, 1, 8, 5, 6, 6, 9, 11, 12, 9, 5, 6, 4, 8, 11, 11, 10, 4, 13, 10, 4, 4, 10, 11, 8, 12, 5, 10, 7, 4, 9, 9, 9, 13, 8, 5, 9, 10, 7]\n",
      "Genrtn 126: mean = 7.915  stddev = 2.828033769246754  max = 17 [11, 6, 8, 6, 10, 11, 9, 9, 7, 9, 6, 3, 6, 8, 8, 9, 7, 8, 6, 10, 9, 9, 8, 7, 9, 10, 8, 4, 7, 4, 11, 17, 8, 8, 6, 12, 7, 14, 5, 5, 12, 9, 10, 4, 10, 7, 8, 7, 6, 6, 3, 6, 8, 11, 13, 6, 11, 8, 8, 5, 10, 9, 5, 6, 11, 13, 8, 7, 7, 11, 12, 6, 13, 13, 7, 5, 6, 8, 10, 9, 14, 9, 6, 3, 9, 8, 5, 8, 8, 12, 4, 5, 6, 14, 11, 5, 6, 5, 5, 6, 6, 7, 3, 6, 13, 4, 3, 9, 6, 6, 5, 15, 9, 5, 8, 6, 8, 2, 10, 7, 4, 10, 7, 9, 5, 6, 7, 10, 8, 12, 6, 8, 4, 9, 13, 14, 5, 12, 7, 5, 11, 7, 9, 9, 3, 10, 6, 5, 10, 5, 9, 8, 10, 6, 13, 9, 5, 6, 9, 7, 12, 9, 4, 4, 8, 10, 8, 8, 9, 9, 9, 5, 11, 9, 6, 5, 9, 8, 11, 5, 12, 5, 12, 7, 10, 11, 11, 10, 3, 6, 12, 12, 4, 5, 7, 3, 9, 11, 4, 6]\n",
      "Genrtn 127: mean = 7.87  stddev = 2.6595300336713628  max = 17 [12, 9, 12, 8, 9, 8, 10, 7, 5, 6, 11, 12, 10, 5, 9, 9, 6, 7, 8, 7, 10, 7, 11, 10, 4, 5, 10, 9, 11, 3, 9, 5, 4, 9, 9, 7, 5, 10, 10, 8, 10, 5, 10, 6, 6, 15, 10, 8, 9, 7, 8, 6, 14, 10, 8, 7, 11, 11, 6, 8, 6, 7, 4, 5, 10, 4, 7, 6, 5, 7, 9, 10, 4, 6, 6, 7, 7, 3, 3, 7, 9, 10, 11, 5, 7, 4, 7, 5, 13, 10, 8, 8, 11, 12, 9, 5, 6, 10, 10, 15, 10, 8, 10, 10, 9, 5, 10, 11, 10, 10, 7, 8, 5, 6, 7, 6, 9, 10, 12, 10, 11, 8, 10, 9, 9, 8, 11, 9, 2, 3, 7, 7, 3, 6, 5, 7, 11, 6, 10, 6, 4, 13, 6, 10, 6, 8, 14, 7, 4, 9, 7, 17, 7, 9, 6, 7, 10, 6, 3, 12, 8, 10, 8, 7, 5, 7, 3, 5, 11, 9, 9, 6, 5, 7, 8, 2, 7, 8, 7, 6, 7, 10, 6, 13, 8, 5, 4, 9, 7, 5, 8, 8, 6, 6, 6, 6, 14, 9, 6, 8]\n",
      "Genrtn 128: mean = 8.045  stddev = 2.7915900486998444  max = 15 [6, 8, 11, 9, 3, 14, 8, 9, 8, 15, 8, 6, 6, 5, 14, 10, 6, 8, 10, 6, 12, 9, 8, 5, 8, 7, 9, 10, 5, 7, 10, 11, 7, 4, 10, 7, 4, 7, 10, 4, 9, 10, 7, 4, 11, 11, 5, 5, 1, 8, 8, 11, 11, 9, 11, 7, 9, 7, 12, 14, 6, 7, 4, 5, 11, 5, 6, 11, 8, 6, 9, 4, 4, 6, 7, 7, 7, 8, 5, 10, 6, 6, 9, 5, 8, 6, 4, 9, 12, 6, 7, 8, 10, 14, 12, 8, 6, 8, 10, 6, 7, 12, 9, 8, 7, 8, 5, 7, 5, 12, 10, 5, 6, 7, 5, 10, 5, 10, 10, 8, 6, 8, 8, 4, 12, 8, 7, 8, 7, 8, 8, 7, 10, 13, 14, 6, 4, 8, 10, 3, 9, 9, 11, 10, 7, 6, 6, 5, 9, 10, 14, 15, 6, 2, 9, 8, 11, 8, 9, 11, 6, 7, 6, 8, 11, 13, 6, 7, 7, 3, 4, 11, 8, 11, 13, 3, 5, 9, 3, 9, 6, 13, 10, 8, 2, 5, 12, 7, 6, 8, 11, 8, 12, 10, 10, 7, 8, 11, 13, 12]\n",
      "Genrtn 129: mean = 8.12  stddev = 2.9437391188758557  max = 16 [6, 5, 8, 11, 2, 6, 3, 11, 10, 5, 4, 6, 8, 14, 6, 8, 7, 8, 8, 13, 11, 7, 7, 4, 6, 8, 4, 9, 3, 12, 10, 8, 9, 8, 9, 5, 9, 13, 6, 10, 5, 10, 13, 8, 6, 15, 10, 14, 8, 11, 7, 6, 10, 6, 5, 8, 11, 14, 6, 9, 8, 10, 7, 10, 4, 6, 13, 6, 9, 6, 4, 7, 6, 6, 2, 11, 7, 9, 8, 7, 5, 6, 9, 7, 8, 13, 8, 6, 6, 3, 10, 6, 6, 4, 4, 11, 9, 5, 3, 8, 9, 6, 9, 6, 16, 9, 12, 4, 6, 5, 11, 10, 5, 4, 8, 6, 11, 9, 6, 10, 7, 8, 4, 10, 15, 5, 7, 10, 7, 11, 8, 8, 11, 5, 13, 7, 6, 5, 8, 7, 5, 4, 11, 6, 7, 8, 10, 15, 14, 10, 11, 10, 12, 5, 11, 15, 6, 9, 5, 7, 4, 11, 8, 12, 11, 8, 6, 8, 11, 5, 12, 8, 7, 13, 6, 11, 5, 12, 6, 9, 4, 11, 5, 8, 11, 12, 6, 11, 10, 7, 7, 11, 8, 10, 10, 8, 13, 7, 3, 12]\n",
      "Genrtn 130: mean = 8.08  stddev = 2.9263629303283625  max = 19 [5, 15, 10, 9, 13, 13, 9, 7, 11, 13, 7, 10, 7, 2, 8, 10, 9, 4, 8, 10, 3, 8, 4, 8, 7, 6, 13, 9, 5, 15, 3, 5, 6, 8, 9, 8, 8, 7, 8, 8, 4, 4, 9, 9, 5, 10, 6, 9, 10, 12, 10, 6, 5, 5, 8, 11, 9, 6, 8, 9, 12, 5, 7, 12, 9, 8, 6, 5, 12, 15, 6, 5, 7, 3, 8, 6, 13, 5, 9, 8, 7, 4, 10, 5, 10, 19, 5, 7, 14, 10, 10, 7, 9, 7, 9, 8, 6, 10, 10, 2, 8, 6, 11, 5, 6, 9, 10, 14, 8, 3, 6, 4, 9, 8, 11, 8, 4, 5, 4, 7, 10, 16, 8, 5, 11, 8, 10, 9, 13, 9, 11, 11, 5, 7, 8, 7, 10, 13, 6, 8, 6, 6, 6, 8, 10, 7, 14, 11, 8, 10, 4, 7, 7, 5, 7, 9, 4, 6, 5, 7, 6, 9, 8, 12, 4, 8, 9, 7, 6, 7, 5, 11, 4, 12, 9, 8, 7, 5, 4, 7, 8, 8, 10, 8, 8, 9, 11, 5, 9, 16, 6, 9, 6, 5, 10, 10, 5, 13, 9, 12]\n",
      "Genrtn 131: mean = 8.23  stddev = 2.774364792164145  max = 16 [5, 6, 9, 8, 8, 6, 12, 11, 10, 9, 10, 6, 6, 8, 10, 4, 5, 5, 10, 5, 8, 5, 6, 9, 7, 9, 7, 9, 12, 10, 8, 3, 13, 13, 6, 9, 7, 9, 14, 8, 5, 5, 9, 7, 4, 9, 11, 5, 5, 9, 12, 4, 6, 7, 7, 9, 12, 11, 11, 14, 9, 8, 9, 7, 3, 14, 6, 7, 7, 9, 6, 7, 8, 11, 4, 8, 9, 12, 8, 10, 5, 3, 10, 10, 10, 7, 12, 9, 6, 10, 13, 4, 6, 10, 3, 3, 8, 9, 10, 5, 11, 10, 7, 6, 11, 12, 9, 3, 7, 6, 10, 11, 10, 11, 11, 5, 11, 8, 8, 13, 10, 15, 3, 13, 4, 10, 9, 7, 8, 5, 8, 9, 6, 6, 10, 6, 12, 7, 7, 6, 16, 8, 16, 10, 6, 10, 8, 8, 11, 9, 9, 4, 6, 7, 7, 9, 5, 5, 9, 12, 9, 4, 8, 11, 8, 12, 6, 3, 12, 8, 12, 8, 10, 7, 7, 5, 6, 8, 11, 11, 6, 8, 10, 7, 11, 10, 5, 11, 9, 4, 7, 11, 4, 7, 8, 8, 13, 5, 11, 7]\n",
      "Genrtn 132: mean = 8.08  stddev = 2.839647865493185  max = 18 [8, 6, 13, 11, 7, 11, 8, 7, 7, 12, 9, 7, 12, 3, 10, 9, 8, 6, 10, 11, 7, 8, 9, 8, 8, 9, 8, 6, 11, 9, 5, 11, 5, 6, 6, 11, 7, 6, 12, 11, 12, 3, 8, 9, 7, 8, 9, 8, 5, 10, 7, 6, 6, 6, 14, 7, 10, 13, 7, 3, 3, 6, 9, 6, 7, 4, 4, 6, 11, 5, 9, 6, 5, 9, 13, 4, 7, 11, 6, 8, 8, 6, 12, 11, 8, 9, 9, 6, 9, 12, 9, 7, 9, 5, 7, 8, 5, 8, 6, 12, 7, 8, 5, 10, 10, 17, 8, 11, 5, 4, 5, 8, 13, 6, 10, 5, 4, 9, 6, 10, 15, 5, 10, 18, 5, 5, 8, 5, 12, 5, 7, 6, 8, 16, 9, 5, 6, 8, 5, 16, 5, 4, 9, 10, 14, 5, 7, 10, 12, 6, 10, 14, 15, 9, 11, 6, 8, 7, 6, 8, 8, 9, 5, 6, 6, 8, 5, 5, 8, 10, 10, 4, 7, 9, 8, 10, 11, 5, 7, 5, 10, 11, 11, 10, 4, 7, 10, 11, 6, 6, 5, 6, 6, 7, 10, 8, 10, 7, 7, 6]\n",
      "Genrtn 133: mean = 8.08  stddev = 2.9620263334413486  max = 17 [7, 9, 7, 8, 3, 11, 12, 7, 9, 10, 8, 14, 11, 4, 7, 12, 6, 9, 7, 9, 7, 8, 6, 7, 13, 3, 8, 7, 10, 11, 6, 7, 15, 6, 6, 3, 11, 8, 6, 7, 10, 10, 8, 8, 8, 7, 10, 6, 6, 7, 10, 6, 9, 7, 6, 4, 11, 7, 8, 11, 5, 10, 5, 6, 5, 8, 9, 10, 4, 8, 9, 5, 5, 5, 3, 6, 6, 8, 8, 7, 8, 9, 12, 4, 11, 8, 4, 9, 15, 12, 12, 11, 10, 4, 11, 8, 3, 3, 10, 9, 5, 8, 7, 4, 6, 12, 3, 9, 9, 5, 4, 10, 7, 9, 5, 12, 10, 4, 4, 9, 15, 5, 6, 9, 10, 8, 10, 6, 8, 8, 16, 5, 7, 11, 8, 6, 5, 6, 11, 14, 6, 13, 4, 7, 4, 5, 7, 6, 8, 6, 7, 9, 14, 10, 8, 5, 9, 17, 11, 6, 7, 7, 5, 12, 6, 3, 6, 8, 5, 6, 13, 12, 10, 5, 4, 9, 15, 6, 13, 8, 8, 6, 13, 10, 6, 11, 11, 8, 12, 7, 15, 8, 12, 11, 5, 8, 9, 6, 12, 11]\n",
      "Genrtn 134: mean = 8.105  stddev = 3.0567916186747177  max = 21 [10, 5, 4, 4, 11, 5, 8, 9, 7, 9, 9, 6, 5, 7, 7, 7, 6, 12, 6, 7, 11, 11, 7, 10, 6, 10, 5, 6, 8, 8, 10, 5, 6, 12, 10, 8, 4, 10, 12, 6, 7, 5, 13, 12, 5, 8, 6, 7, 8, 9, 8, 11, 13, 4, 7, 6, 6, 6, 9, 6, 11, 3, 4, 13, 5, 3, 4, 8, 11, 5, 9, 14, 4, 12, 8, 8, 9, 8, 6, 7, 10, 4, 7, 6, 4, 9, 10, 4, 6, 6, 5, 6, 13, 8, 13, 12, 13, 12, 8, 15, 5, 9, 8, 13, 7, 6, 8, 21, 5, 8, 7, 12, 10, 7, 12, 5, 10, 8, 6, 11, 11, 3, 6, 8, 14, 8, 6, 9, 8, 5, 6, 6, 9, 12, 9, 3, 5, 5, 6, 8, 6, 9, 11, 9, 7, 11, 10, 8, 15, 7, 15, 5, 13, 8, 5, 12, 6, 9, 11, 7, 7, 4, 11, 4, 9, 10, 8, 8, 7, 12, 3, 10, 4, 13, 3, 5, 10, 6, 9, 8, 7, 6, 6, 7, 8, 8, 7, 10, 12, 8, 14, 6, 17, 12, 12, 3, 8, 8, 4, 10]\n",
      "Genrtn 135: mean = 8.085  stddev = 3.009613762594795  max = 19 [8, 11, 5, 10, 2, 4, 13, 5, 6, 15, 9, 5, 9, 8, 11, 8, 1, 8, 5, 11, 11, 9, 8, 6, 9, 15, 11, 19, 6, 8, 12, 7, 7, 7, 14, 10, 9, 11, 7, 11, 11, 5, 6, 8, 5, 13, 8, 9, 7, 8, 5, 9, 8, 7, 13, 8, 4, 11, 7, 5, 13, 10, 7, 6, 11, 5, 4, 11, 8, 6, 12, 6, 13, 6, 5, 5, 5, 8, 10, 8, 11, 4, 9, 6, 11, 3, 10, 10, 9, 7, 9, 7, 10, 5, 13, 14, 8, 8, 2, 10, 7, 8, 8, 8, 3, 6, 8, 6, 5, 8, 15, 7, 5, 6, 10, 8, 4, 10, 13, 5, 6, 5, 8, 7, 11, 9, 7, 3, 8, 4, 7, 6, 11, 6, 7, 6, 7, 5, 14, 7, 8, 9, 6, 11, 5, 14, 10, 5, 10, 9, 8, 7, 6, 5, 10, 9, 7, 8, 6, 13, 7, 9, 5, 7, 4, 9, 11, 12, 7, 6, 8, 4, 2, 8, 5, 10, 9, 13, 7, 9, 6, 9, 6, 5, 14, 14, 4, 12, 4, 9, 8, 4, 9, 13, 7, 7, 6, 13, 11, 11]\n",
      "Genrtn 136: mean = 8.065  stddev = 2.6834259818373973  max = 14 [14, 7, 11, 3, 6, 12, 8, 9, 8, 7, 9, 9, 8, 11, 7, 10, 9, 7, 6, 12, 5, 9, 7, 7, 8, 6, 8, 10, 4, 3, 7, 6, 8, 6, 6, 10, 5, 7, 6, 10, 5, 13, 8, 7, 11, 6, 5, 11, 9, 9, 11, 10, 8, 7, 7, 7, 12, 11, 8, 10, 7, 4, 12, 8, 8, 5, 7, 6, 9, 6, 5, 8, 10, 2, 12, 10, 7, 8, 11, 6, 3, 9, 10, 12, 7, 10, 7, 14, 7, 9, 14, 8, 5, 9, 11, 8, 8, 4, 9, 7, 6, 3, 2, 3, 13, 3, 5, 10, 7, 7, 6, 9, 5, 9, 5, 9, 7, 8, 10, 8, 9, 8, 8, 11, 6, 10, 6, 8, 9, 8, 8, 5, 7, 10, 7, 4, 9, 11, 12, 8, 10, 10, 11, 5, 8, 13, 4, 4, 5, 9, 3, 8, 8, 8, 14, 13, 6, 8, 3, 8, 12, 7, 10, 10, 12, 8, 14, 9, 10, 8, 6, 8, 12, 6, 11, 10, 6, 11, 4, 8, 9, 13, 7, 4, 8, 13, 12, 8, 11, 9, 5, 7, 10, 13, 6, 5, 5, 5, 11, 5]\n",
      "Genrtn 137: mean = 8.045  stddev = 2.87801580954657  max = 17 [11, 12, 8, 5, 10, 11, 11, 7, 3, 9, 6, 12, 16, 16, 8, 6, 8, 12, 10, 9, 12, 4, 10, 10, 6, 7, 9, 7, 4, 12, 11, 6, 6, 7, 12, 8, 11, 10, 11, 6, 9, 10, 4, 6, 6, 7, 6, 4, 6, 8, 10, 8, 11, 10, 5, 5, 8, 6, 6, 8, 4, 8, 4, 10, 7, 9, 3, 4, 8, 8, 9, 14, 4, 5, 7, 9, 10, 3, 6, 12, 12, 9, 8, 15, 9, 9, 5, 4, 6, 4, 8, 4, 10, 5, 6, 8, 8, 7, 8, 9, 9, 9, 5, 8, 5, 1, 9, 6, 7, 8, 8, 8, 12, 8, 7, 10, 7, 14, 11, 12, 14, 8, 12, 5, 5, 6, 11, 12, 2, 13, 3, 7, 12, 6, 6, 9, 11, 7, 11, 8, 5, 8, 9, 9, 6, 8, 9, 4, 10, 8, 6, 3, 8, 10, 6, 10, 12, 8, 11, 13, 11, 6, 9, 5, 9, 3, 5, 9, 13, 9, 7, 9, 10, 5, 6, 8, 7, 8, 6, 8, 4, 4, 7, 7, 6, 10, 9, 8, 6, 7, 5, 8, 17, 5, 9, 14, 10, 6, 11, 8]\n",
      "Genrtn 138: mean = 7.765  stddev = 2.6925406217919905  max = 16 [6, 4, 7, 8, 7, 12, 7, 6, 5, 12, 4, 9, 9, 9, 3, 8, 4, 6, 6, 8, 9, 6, 12, 2, 6, 5, 8, 2, 5, 6, 8, 9, 7, 7, 6, 9, 7, 16, 6, 5, 10, 3, 8, 9, 12, 8, 11, 11, 9, 9, 8, 4, 7, 7, 8, 6, 10, 8, 9, 3, 7, 7, 10, 8, 7, 8, 3, 6, 9, 8, 9, 8, 9, 7, 8, 8, 5, 13, 6, 13, 7, 7, 7, 5, 8, 12, 6, 15, 10, 9, 9, 5, 9, 12, 9, 11, 11, 9, 9, 10, 9, 7, 3, 12, 5, 10, 6, 3, 5, 10, 8, 9, 10, 5, 4, 10, 7, 6, 10, 10, 7, 7, 10, 8, 7, 8, 8, 10, 5, 9, 10, 10, 10, 9, 8, 8, 5, 7, 6, 7, 5, 12, 9, 9, 6, 13, 5, 15, 8, 3, 7, 4, 9, 9, 5, 12, 6, 4, 8, 5, 8, 7, 9, 9, 5, 11, 7, 7, 4, 5, 10, 7, 6, 3, 5, 5, 7, 10, 6, 7, 6, 10, 7, 9, 1, 13, 12, 8, 5, 14, 12, 5, 10, 14, 13, 7, 6, 8, 6, 7]\n",
      "Genrtn 139: mean = 8.055  stddev = 2.6799207077822285  max = 15 [8, 10, 12, 6, 11, 7, 8, 5, 10, 4, 5, 10, 10, 8, 6, 9, 10, 5, 11, 6, 10, 14, 11, 6, 10, 9, 8, 3, 5, 6, 9, 10, 8, 9, 6, 7, 8, 7, 4, 9, 9, 8, 12, 5, 13, 11, 3, 7, 5, 12, 14, 10, 4, 5, 6, 4, 9, 14, 7, 11, 9, 7, 8, 13, 9, 13, 10, 8, 8, 5, 7, 7, 8, 4, 11, 10, 8, 7, 13, 5, 11, 12, 10, 11, 4, 10, 9, 7, 11, 9, 5, 10, 14, 9, 10, 11, 9, 8, 7, 5, 6, 7, 9, 4, 5, 15, 8, 8, 4, 6, 8, 12, 12, 9, 10, 4, 8, 9, 9, 6, 7, 12, 6, 9, 7, 11, 10, 8, 5, 9, 6, 7, 2, 9, 10, 5, 7, 5, 11, 11, 11, 8, 12, 5, 8, 4, 8, 10, 10, 10, 4, 5, 11, 5, 7, 6, 8, 6, 6, 8, 6, 5, 9, 7, 10, 11, 8, 9, 10, 4, 6, 10, 13, 8, 4, 8, 6, 6, 8, 6, 4, 6, 4, 5, 13, 8, 6, 7, 9, 15, 6, 8, 8, 7, 7, 11, 4, 8, 7, 5]\n",
      "Genrtn 140: mean = 7.935  stddev = 2.733271848901971  max = 17 [8, 5, 8, 9, 10, 9, 8, 11, 11, 7, 4, 4, 3, 7, 7, 4, 5, 8, 10, 8, 12, 6, 3, 10, 4, 5, 7, 10, 11, 9, 12, 14, 5, 9, 10, 8, 13, 4, 11, 9, 8, 10, 8, 10, 6, 11, 9, 8, 6, 4, 8, 8, 9, 4, 6, 5, 8, 6, 4, 8, 5, 8, 10, 10, 4, 6, 12, 7, 5, 8, 12, 8, 4, 11, 7, 11, 10, 8, 11, 6, 8, 11, 8, 8, 8, 5, 9, 12, 11, 4, 7, 9, 6, 12, 17, 11, 10, 7, 6, 5, 14, 10, 4, 8, 5, 10, 10, 11, 6, 6, 8, 7, 7, 8, 6, 6, 6, 10, 4, 12, 6, 9, 5, 7, 8, 9, 6, 10, 8, 5, 6, 8, 7, 5, 2, 7, 7, 13, 11, 5, 6, 6, 9, 6, 6, 7, 7, 7, 10, 3, 7, 5, 8, 3, 9, 8, 3, 4, 10, 8, 12, 7, 6, 11, 5, 6, 12, 14, 9, 11, 7, 10, 11, 13, 7, 11, 6, 8, 8, 8, 6, 4, 9, 4, 6, 7, 8, 10, 8, 10, 9, 10, 8, 9, 15, 7, 3, 11, 11, 15]\n",
      "Genrtn 141: mean = 8.055  stddev = 2.674317669986122  max = 18 [9, 7, 7, 6, 4, 12, 8, 7, 6, 5, 3, 8, 12, 9, 8, 8, 5, 7, 8, 11, 6, 6, 3, 5, 6, 11, 5, 6, 7, 6, 6, 10, 7, 8, 11, 10, 9, 4, 8, 4, 9, 5, 11, 3, 6, 5, 9, 8, 7, 11, 4, 4, 5, 11, 10, 10, 10, 8, 10, 12, 4, 6, 10, 16, 6, 9, 9, 10, 11, 3, 9, 10, 8, 7, 8, 12, 10, 7, 7, 4, 5, 7, 5, 6, 8, 7, 11, 6, 10, 9, 8, 3, 11, 8, 9, 11, 10, 6, 6, 8, 9, 9, 8, 8, 7, 7, 13, 4, 9, 11, 9, 12, 8, 9, 8, 8, 7, 9, 14, 8, 11, 9, 12, 4, 9, 8, 7, 8, 10, 4, 5, 7, 9, 13, 6, 7, 9, 11, 8, 9, 6, 12, 8, 8, 9, 7, 15, 9, 7, 8, 10, 7, 8, 11, 9, 10, 17, 14, 11, 12, 6, 6, 9, 9, 10, 10, 3, 5, 6, 8, 6, 13, 10, 9, 5, 7, 8, 7, 6, 7, 10, 4, 18, 8, 8, 7, 11, 8, 6, 9, 5, 5, 7, 9, 5, 7, 11, 4, 6, 6]\n",
      "Genrtn 142: mean = 8.2  stddev = 2.9189039038652846  max = 18 [9, 10, 10, 8, 8, 9, 12, 7, 10, 12, 16, 5, 7, 11, 3, 15, 10, 8, 9, 7, 6, 7, 5, 10, 10, 8, 7, 7, 12, 9, 6, 3, 13, 11, 9, 6, 7, 8, 5, 8, 9, 10, 7, 6, 7, 12, 13, 8, 12, 7, 9, 6, 4, 12, 10, 9, 7, 9, 7, 6, 4, 8, 9, 11, 4, 13, 6, 8, 8, 2, 7, 5, 7, 4, 11, 6, 5, 11, 7, 12, 4, 7, 9, 7, 3, 10, 6, 8, 9, 6, 7, 12, 11, 12, 8, 8, 10, 15, 6, 8, 5, 5, 11, 9, 18, 8, 12, 6, 9, 8, 9, 6, 6, 11, 5, 5, 4, 9, 9, 8, 8, 8, 6, 6, 5, 10, 3, 8, 6, 9, 10, 9, 8, 5, 3, 7, 9, 9, 8, 4, 10, 9, 10, 6, 11, 11, 8, 8, 10, 10, 5, 10, 14, 10, 11, 6, 16, 8, 5, 6, 6, 4, 6, 6, 9, 8, 5, 5, 13, 12, 5, 7, 7, 4, 8, 15, 8, 8, 8, 8, 14, 6, 10, 11, 1, 6, 9, 9, 12, 11, 15, 10, 3, 11, 8, 10, 10, 2, 6, 9]\n",
      "Genrtn 143: mean = 7.765  stddev = 3.03805447614094  max = 17 [10, 2, 15, 8, 6, 6, 5, 13, 7, 6, 11, 13, 12, 6, 4, 9, 6, 10, 4, 3, 8, 4, 13, 6, 8, 8, 6, 6, 9, 10, 8, 11, 8, 9, 3, 6, 5, 7, 12, 5, 6, 5, 12, 11, 10, 4, 9, 8, 8, 5, 3, 8, 8, 6, 9, 8, 10, 9, 8, 5, 4, 7, 6, 14, 7, 9, 6, 6, 4, 6, 9, 7, 5, 7, 10, 6, 12, 2, 6, 7, 7, 5, 8, 6, 17, 13, 10, 6, 10, 10, 5, 7, 9, 4, 7, 12, 6, 12, 9, 3, 5, 10, 7, 12, 13, 7, 4, 8, 12, 11, 7, 9, 9, 4, 1, 5, 5, 12, 11, 5, 5, 7, 5, 8, 10, 12, 11, 9, 8, 8, 5, 12, 9, 5, 5, 5, 11, 10, 12, 10, 9, 10, 6, 8, 10, 11, 12, 16, 7, 7, 11, 9, 7, 5, 1, 5, 5, 7, 6, 8, 6, 9, 10, 4, 7, 8, 11, 10, 2, 8, 3, 11, 9, 4, 7, 8, 10, 8, 13, 2, 6, 5, 8, 7, 2, 10, 6, 4, 5, 6, 10, 6, 9, 6, 16, 5, 15, 8, 9, 10]\n",
      "Genrtn 144: mean = 7.76  stddev = 2.6310454196003534  max = 15 [11, 13, 8, 10, 9, 5, 7, 10, 7, 9, 7, 11, 7, 7, 5, 9, 11, 3, 9, 9, 4, 6, 12, 7, 4, 9, 12, 7, 8, 10, 5, 4, 8, 10, 6, 5, 9, 7, 9, 9, 7, 10, 2, 12, 8, 12, 9, 5, 8, 10, 8, 5, 12, 2, 9, 8, 9, 6, 7, 3, 13, 8, 6, 6, 10, 8, 3, 5, 9, 5, 8, 8, 6, 9, 8, 6, 11, 8, 12, 6, 8, 7, 8, 14, 13, 6, 8, 6, 14, 5, 10, 12, 12, 12, 9, 5, 9, 9, 7, 5, 6, 7, 7, 8, 5, 6, 7, 7, 7, 6, 12, 15, 8, 6, 9, 9, 9, 9, 6, 8, 3, 9, 5, 12, 8, 12, 11, 8, 7, 5, 11, 7, 8, 9, 5, 4, 5, 11, 7, 9, 9, 6, 9, 12, 6, 3, 9, 10, 11, 4, 7, 7, 11, 12, 8, 5, 7, 5, 3, 11, 10, 11, 8, 2, 7, 5, 6, 7, 10, 10, 5, 8, 5, 8, 3, 3, 4, 8, 5, 8, 5, 8, 8, 8, 8, 9, 8, 9, 7, 6, 2, 6, 8, 12, 10, 5, 8, 7, 4, 9]\n",
      "Genrtn 145: mean = 8.045  stddev = 2.740980663923042  max = 19 [8, 8, 12, 8, 6, 8, 2, 5, 4, 7, 14, 7, 6, 8, 6, 6, 8, 9, 10, 13, 11, 6, 8, 5, 5, 9, 9, 3, 7, 7, 7, 4, 5, 6, 10, 10, 6, 4, 4, 9, 7, 10, 6, 12, 10, 6, 10, 9, 8, 6, 8, 7, 7, 7, 5, 7, 5, 11, 13, 13, 8, 11, 12, 9, 6, 6, 9, 9, 12, 7, 7, 13, 10, 7, 19, 6, 4, 9, 10, 10, 10, 9, 7, 8, 11, 8, 5, 7, 6, 11, 17, 5, 8, 8, 6, 5, 9, 11, 11, 1, 6, 10, 7, 7, 11, 7, 8, 8, 8, 8, 8, 7, 11, 6, 9, 11, 6, 7, 11, 9, 6, 8, 10, 7, 7, 11, 5, 11, 10, 6, 7, 10, 8, 10, 7, 4, 14, 5, 10, 8, 8, 4, 11, 12, 8, 8, 3, 5, 8, 5, 10, 14, 5, 6, 10, 3, 6, 4, 7, 8, 5, 5, 9, 12, 11, 6, 7, 6, 5, 5, 8, 8, 10, 10, 6, 7, 6, 10, 12, 10, 5, 12, 9, 10, 9, 4, 9, 5, 14, 9, 5, 10, 10, 7, 8, 14, 6, 11, 7, 9]\n",
      "Genrtn 146: mean = 7.895  stddev = 2.670950205451236  max = 15 [9, 7, 9, 8, 10, 10, 6, 5, 8, 11, 8, 13, 7, 10, 7, 4, 7, 5, 5, 13, 7, 7, 10, 6, 8, 5, 9, 8, 10, 14, 14, 12, 4, 4, 7, 14, 8, 5, 8, 9, 11, 7, 5, 13, 10, 10, 6, 8, 8, 8, 4, 11, 8, 8, 12, 13, 8, 8, 8, 10, 11, 9, 9, 7, 8, 6, 9, 9, 5, 12, 8, 7, 6, 6, 5, 8, 10, 7, 12, 14, 9, 8, 6, 7, 8, 13, 7, 4, 13, 8, 8, 5, 5, 12, 8, 6, 6, 5, 7, 11, 11, 8, 9, 10, 8, 10, 9, 7, 7, 12, 6, 7, 6, 6, 8, 13, 4, 10, 7, 6, 8, 5, 10, 6, 8, 7, 7, 14, 7, 8, 12, 9, 2, 7, 7, 6, 5, 10, 4, 8, 8, 9, 8, 8, 4, 11, 8, 9, 6, 5, 6, 6, 6, 8, 7, 8, 6, 7, 2, 8, 5, 8, 5, 4, 7, 4, 7, 7, 3, 4, 4, 11, 6, 14, 12, 10, 5, 3, 11, 11, 7, 3, 5, 7, 9, 9, 4, 13, 6, 7, 6, 7, 6, 9, 15, 11, 7, 7, 5, 10]\n",
      "Genrtn 147: mean = 7.885  stddev = 2.94138997754463  max = 15 [7, 7, 9, 10, 5, 5, 10, 10, 7, 6, 7, 10, 6, 6, 0, 3, 7, 9, 10, 4, 4, 5, 11, 2, 7, 13, 7, 4, 7, 8, 5, 13, 5, 10, 4, 5, 12, 9, 7, 7, 9, 8, 14, 8, 9, 7, 7, 9, 10, 5, 8, 7, 8, 9, 10, 9, 8, 6, 6, 15, 5, 7, 9, 6, 8, 10, 8, 12, 5, 8, 11, 3, 9, 9, 6, 8, 7, 7, 5, 9, 8, 4, 9, 13, 2, 9, 6, 6, 12, 4, 7, 8, 12, 5, 4, 11, 11, 6, 5, 10, 8, 12, 4, 10, 10, 9, 4, 8, 7, 8, 4, 9, 14, 12, 5, 11, 8, 13, 11, 6, 7, 2, 4, 12, 9, 13, 9, 8, 8, 6, 7, 7, 3, 5, 5, 6, 6, 10, 9, 11, 5, 9, 12, 8, 7, 7, 15, 6, 7, 9, 5, 2, 3, 13, 9, 11, 6, 5, 12, 10, 6, 5, 11, 8, 6, 8, 13, 10, 6, 12, 10, 8, 11, 10, 5, 7, 8, 7, 7, 4, 8, 7, 4, 9, 7, 7, 13, 15, 13, 15, 9, 3, 10, 10, 2, 10, 11, 7, 10, 5]\n",
      "Genrtn 148: mean = 7.775  stddev = 2.850328928387038  max = 17 [7, 9, 7, 8, 3, 7, 5, 6, 10, 6, 4, 13, 8, 8, 7, 9, 7, 7, 9, 8, 8, 9, 7, 8, 6, 6, 12, 6, 10, 15, 7, 7, 7, 8, 6, 8, 5, 8, 7, 10, 5, 6, 11, 8, 8, 5, 11, 11, 9, 7, 7, 9, 7, 2, 6, 7, 14, 4, 6, 10, 5, 5, 10, 9, 11, 9, 8, 10, 8, 2, 4, 6, 11, 10, 13, 8, 10, 8, 6, 5, 7, 7, 17, 5, 8, 8, 4, 14, 7, 12, 4, 13, 8, 9, 7, 7, 5, 12, 9, 8, 11, 4, 6, 7, 3, 10, 7, 6, 12, 8, 17, 7, 6, 4, 7, 9, 8, 8, 6, 11, 11, 9, 8, 8, 4, 11, 5, 9, 10, 9, 9, 7, 9, 5, 9, 11, 8, 7, 15, 9, 7, 6, 10, 7, 8, 6, 3, 3, 7, 11, 15, 12, 9, 7, 2, 3, 13, 4, 11, 6, 13, 4, 5, 11, 3, 6, 8, 6, 7, 6, 7, 6, 8, 4, 8, 10, 5, 9, 13, 8, 4, 5, 3, 8, 6, 8, 3, 8, 7, 9, 9, 11, 5, 2, 9, 13, 7, 8, 6, 7]\n",
      "Genrtn 149: mean = 8.355  stddev = 2.7584370574656947  max = 15 [9, 15, 6, 4, 7, 7, 3, 4, 13, 6, 13, 5, 6, 8, 10, 11, 8, 4, 12, 5, 15, 6, 12, 4, 11, 8, 9, 7, 10, 4, 9, 5, 6, 12, 9, 9, 11, 7, 8, 11, 4, 7, 7, 11, 5, 9, 5, 12, 4, 10, 13, 12, 9, 7, 11, 11, 10, 9, 9, 9, 11, 7, 7, 14, 9, 6, 10, 5, 12, 7, 14, 10, 7, 5, 11, 6, 9, 8, 12, 11, 10, 9, 10, 2, 7, 6, 8, 5, 6, 11, 8, 7, 8, 5, 12, 10, 12, 8, 9, 4, 13, 7, 9, 9, 10, 11, 6, 8, 8, 9, 5, 7, 6, 8, 14, 12, 7, 3, 11, 9, 6, 10, 8, 4, 11, 10, 7, 5, 5, 6, 8, 8, 8, 6, 7, 14, 12, 14, 11, 4, 10, 7, 10, 7, 10, 10, 5, 9, 8, 9, 8, 6, 2, 9, 7, 9, 5, 12, 10, 5, 5, 12, 6, 9, 7, 5, 9, 13, 6, 8, 3, 6, 6, 9, 11, 10, 12, 9, 9, 7, 10, 8, 3, 13, 10, 8, 5, 12, 9, 9, 12, 9, 11, 8, 8, 7, 7, 10, 8, 7]\n",
      "Genrtn 150: mean = 7.585  stddev = 3.007120715900843  max = 20 [10, 4, 7, 6, 10, 6, 6, 9, 3, 7, 3, 5, 5, 5, 5, 3, 8, 9, 11, 7, 8, 11, 7, 10, 5, 10, 2, 16, 8, 5, 9, 3, 10, 10, 10, 12, 7, 17, 12, 6, 7, 7, 7, 6, 10, 6, 6, 10, 8, 5, 7, 12, 6, 7, 2, 8, 6, 9, 7, 4, 8, 4, 7, 7, 7, 5, 6, 8, 5, 6, 8, 8, 6, 2, 5, 9, 5, 6, 5, 5, 11, 8, 6, 8, 4, 5, 7, 20, 6, 5, 6, 3, 15, 8, 6, 10, 6, 6, 8, 7, 6, 9, 9, 9, 8, 7, 6, 2, 7, 6, 10, 10, 14, 9, 12, 5, 9, 8, 9, 6, 10, 12, 5, 15, 6, 13, 5, 8, 6, 9, 1, 5, 9, 7, 8, 7, 6, 10, 5, 8, 7, 10, 4, 13, 11, 7, 11, 11, 8, 12, 7, 11, 6, 9, 2, 8, 6, 7, 11, 6, 12, 3, 13, 8, 12, 10, 11, 6, 6, 4, 7, 6, 4, 3, 6, 12, 7, 14, 7, 7, 9, 9, 4, 9, 9, 5, 11, 6, 7, 5, 7, 3, 7, 9, 8, 4, 15, 10, 7, 8]\n",
      "Genrtn 151: mean = 8.015  stddev = 2.6804430603913225  max = 15 [8, 10, 5, 7, 14, 9, 10, 5, 5, 14, 8, 10, 5, 9, 8, 8, 12, 6, 6, 9, 9, 6, 9, 5, 7, 15, 13, 11, 10, 7, 9, 7, 5, 9, 7, 8, 6, 7, 8, 9, 9, 9, 9, 10, 4, 5, 9, 12, 9, 9, 7, 6, 7, 10, 12, 11, 4, 5, 7, 7, 4, 10, 7, 7, 7, 7, 6, 7, 12, 9, 7, 4, 10, 8, 9, 5, 11, 10, 9, 5, 12, 6, 8, 8, 4, 6, 8, 5, 5, 6, 3, 9, 15, 9, 9, 6, 9, 5, 12, 5, 13, 4, 12, 5, 12, 8, 6, 9, 11, 7, 4, 11, 8, 10, 3, 8, 4, 8, 7, 8, 12, 8, 4, 7, 9, 4, 11, 9, 6, 6, 4, 2, 6, 9, 10, 8, 11, 4, 9, 8, 9, 9, 9, 6, 9, 6, 5, 6, 4, 9, 5, 7, 6, 4, 8, 11, 5, 12, 9, 4, 7, 9, 10, 14, 6, 9, 9, 11, 13, 11, 9, 7, 12, 5, 3, 7, 9, 12, 4, 12, 7, 8, 6, 13, 5, 4, 11, 12, 12, 10, 13, 10, 8, 10, 7, 8, 8, 7, 8, 9]\n",
      "Genrtn 152: mean = 8.09  stddev = 2.740784559209279  max = 17 [3, 14, 9, 10, 5, 9, 11, 9, 12, 4, 12, 6, 11, 6, 9, 4, 6, 6, 9, 6, 8, 8, 12, 8, 9, 9, 7, 7, 8, 6, 10, 7, 9, 7, 10, 10, 4, 8, 2, 12, 6, 10, 14, 9, 14, 8, 6, 7, 7, 10, 9, 8, 10, 11, 5, 7, 5, 9, 17, 12, 11, 9, 9, 14, 7, 4, 8, 9, 9, 13, 4, 4, 6, 7, 6, 12, 6, 6, 15, 12, 9, 7, 8, 5, 8, 1, 5, 7, 6, 13, 10, 6, 13, 5, 5, 9, 8, 6, 12, 12, 5, 10, 8, 1, 7, 10, 8, 8, 6, 9, 8, 6, 5, 8, 12, 5, 7, 7, 7, 7, 6, 8, 7, 11, 9, 4, 7, 9, 8, 6, 11, 4, 9, 10, 4, 6, 8, 8, 9, 7, 13, 3, 7, 10, 12, 6, 7, 12, 4, 10, 11, 6, 9, 11, 5, 8, 4, 9, 9, 9, 12, 9, 11, 6, 6, 11, 6, 7, 6, 10, 8, 5, 9, 7, 10, 12, 6, 10, 12, 8, 9, 6, 8, 8, 8, 5, 6, 10, 8, 7, 6, 9, 8, 6, 3, 9, 9, 12, 5, 13]\n",
      "Genrtn 153: mean = 7.67  stddev = 2.927644104053633  max = 14 [2, 5, 9, 9, 9, 4, 6, 10, 4, 12, 6, 8, 9, 10, 5, 3, 6, 6, 7, 4, 4, 2, 10, 7, 4, 10, 6, 8, 8, 6, 9, 4, 9, 7, 6, 6, 5, 14, 10, 8, 6, 7, 7, 4, 6, 6, 13, 12, 7, 7, 11, 5, 6, 11, 10, 9, 7, 8, 11, 11, 13, 7, 12, 13, 6, 1, 7, 4, 5, 6, 10, 10, 12, 12, 9, 7, 6, 7, 8, 10, 7, 7, 13, 5, 12, 6, 8, 13, 9, 8, 7, 10, 11, 7, 8, 8, 11, 3, 10, 4, 7, 6, 13, 12, 12, 4, 9, 4, 8, 6, 6, 10, 7, 13, 5, 3, 11, 10, 5, 10, 7, 7, 3, 7, 14, 7, 10, 9, 3, 13, 8, 8, 6, 4, 3, 7, 12, 6, 7, 8, 10, 7, 9, 6, 10, 13, 6, 11, 13, 2, 8, 6, 3, 9, 6, 3, 7, 5, 7, 3, 7, 10, 9, 3, 3, 5, 8, 4, 10, 5, 9, 12, 11, 14, 6, 5, 7, 5, 7, 10, 7, 9, 2, 5, 10, 7, 8, 10, 11, 5, 12, 11, 12, 7, 7, 6, 4, 6, 7, 11]\n",
      "Genrtn 154: mean = 7.97  stddev = 2.8929396813621953  max = 19 [5, 5, 6, 6, 3, 7, 11, 4, 7, 3, 8, 9, 5, 5, 4, 8, 6, 6, 11, 2, 9, 7, 12, 8, 9, 5, 11, 6, 4, 8, 9, 6, 14, 4, 5, 10, 4, 12, 9, 8, 9, 4, 7, 8, 6, 4, 9, 10, 2, 7, 8, 10, 14, 5, 9, 10, 10, 9, 4, 8, 6, 9, 10, 7, 14, 8, 6, 10, 8, 12, 11, 9, 12, 7, 4, 9, 11, 7, 5, 8, 7, 2, 9, 3, 9, 13, 9, 5, 7, 6, 6, 5, 8, 8, 8, 6, 11, 6, 7, 11, 8, 7, 7, 6, 10, 10, 10, 6, 4, 14, 11, 9, 11, 7, 9, 11, 16, 5, 6, 8, 9, 5, 7, 12, 9, 12, 7, 8, 5, 11, 7, 7, 9, 15, 9, 5, 8, 7, 8, 9, 8, 12, 11, 8, 5, 9, 7, 4, 11, 11, 7, 4, 12, 11, 7, 8, 9, 7, 7, 11, 5, 8, 19, 8, 4, 8, 7, 7, 6, 7, 4, 9, 10, 6, 8, 7, 7, 6, 5, 10, 7, 11, 7, 7, 6, 7, 10, 13, 4, 11, 10, 15, 2, 17, 7, 7, 8, 12, 9, 7]\n",
      "Genrtn 155: mean = 7.92  stddev = 2.784528685433138  max = 18 [9, 6, 5, 11, 8, 8, 6, 5, 8, 5, 4, 13, 7, 8, 11, 7, 4, 13, 10, 6, 3, 7, 9, 9, 12, 7, 11, 12, 10, 8, 11, 10, 4, 18, 3, 6, 7, 12, 9, 9, 12, 13, 9, 9, 8, 5, 7, 10, 14, 5, 9, 8, 9, 13, 10, 10, 8, 7, 8, 8, 7, 5, 4, 13, 4, 6, 7, 11, 4, 6, 12, 6, 7, 5, 8, 7, 9, 7, 9, 4, 10, 6, 9, 10, 8, 9, 7, 10, 9, 7, 9, 6, 15, 9, 4, 9, 14, 10, 13, 13, 10, 5, 9, 11, 7, 6, 9, 11, 8, 6, 8, 4, 7, 13, 10, 3, 10, 8, 9, 8, 9, 6, 10, 6, 4, 6, 5, 9, 10, 8, 3, 2, 1, 9, 5, 7, 6, 8, 10, 8, 7, 8, 7, 7, 4, 4, 7, 5, 7, 5, 8, 9, 11, 7, 5, 7, 9, 6, 11, 6, 11, 6, 13, 9, 3, 9, 5, 11, 12, 5, 11, 6, 7, 4, 7, 6, 5, 4, 8, 9, 6, 4, 8, 9, 9, 9, 12, 7, 12, 6, 11, 9, 7, 13, 8, 5, 6, 6, 6, 5]\n",
      "Genrtn 156: mean = 7.71  stddev = 2.712176247960298  max = 15 [10, 7, 5, 11, 11, 7, 7, 10, 9, 11, 7, 6, 11, 7, 7, 7, 4, 7, 8, 9, 9, 8, 2, 12, 3, 6, 13, 9, 11, 8, 5, 3, 4, 8, 8, 9, 7, 11, 10, 10, 8, 4, 6, 8, 7, 8, 8, 6, 8, 4, 8, 11, 10, 4, 6, 10, 6, 6, 5, 8, 11, 8, 8, 7, 5, 10, 8, 14, 8, 6, 4, 11, 10, 2, 4, 5, 8, 8, 9, 3, 9, 8, 11, 8, 9, 9, 8, 10, 11, 8, 6, 13, 9, 8, 9, 9, 5, 6, 4, 8, 4, 7, 9, 9, 10, 7, 7, 8, 5, 6, 9, 15, 8, 7, 8, 2, 10, 6, 3, 6, 4, 6, 9, 12, 5, 7, 9, 8, 7, 14, 12, 6, 3, 8, 12, 2, 7, 7, 12, 4, 7, 8, 10, 6, 8, 11, 8, 7, 12, 6, 13, 9, 6, 1, 8, 5, 4, 8, 8, 6, 9, 11, 10, 12, 9, 11, 7, 6, 10, 4, 7, 5, 6, 8, 10, 9, 5, 5, 8, 6, 11, 4, 4, 7, 7, 7, 11, 14, 5, 4, 12, 6, 3, 7, 7, 15, 7, 7, 12, 8]\n",
      "Genrtn 157: mean = 7.81  stddev = 3.050229499562287  max = 17 [8, 4, 8, 17, 3, 9, 7, 8, 4, 6, 3, 13, 0, 7, 8, 9, 10, 6, 7, 8, 9, 10, 5, 10, 6, 8, 5, 8, 9, 4, 8, 8, 7, 5, 11, 9, 9, 9, 11, 2, 8, 9, 9, 7, 12, 8, 10, 8, 6, 6, 9, 3, 7, 8, 6, 10, 5, 7, 9, 10, 8, 9, 7, 8, 8, 9, 7, 7, 15, 4, 8, 8, 9, 7, 11, 7, 3, 7, 8, 14, 9, 8, 7, 8, 13, 6, 7, 7, 4, 8, 13, 7, 5, 3, 8, 8, 6, 6, 4, 6, 8, 8, 10, 6, 8, 9, 8, 9, 5, 10, 13, 11, 6, 11, 3, 12, 11, 8, 10, 7, 9, 13, 12, 4, 13, 9, 8, 6, 7, 13, 13, 7, 12, 11, 4, 10, 9, 10, 5, 8, 4, 4, 15, 6, 7, 6, 14, 5, 2, 10, 10, 8, 9, 5, 5, 15, 3, 6, 11, 6, 6, 5, 4, 17, 3, 9, 2, 4, 7, 4, 5, 5, 14, 4, 12, 9, 5, 8, 8, 7, 7, 5, 6, 7, 7, 12, 12, 6, 8, 9, 5, 7, 9, 3, 12, 2, 3, 12, 11, 12]\n",
      "Genrtn 158: mean = 7.985  stddev = 2.6617240653381034  max = 16 [5, 4, 8, 7, 9, 9, 2, 6, 6, 4, 8, 9, 11, 8, 9, 5, 7, 11, 7, 8, 9, 5, 10, 11, 12, 9, 6, 8, 11, 1, 8, 6, 12, 8, 7, 7, 9, 8, 10, 12, 8, 12, 9, 11, 10, 7, 8, 12, 6, 8, 12, 7, 5, 5, 13, 11, 5, 5, 4, 7, 8, 10, 10, 5, 6, 8, 7, 6, 7, 8, 11, 6, 10, 8, 10, 8, 4, 12, 7, 9, 9, 5, 3, 11, 9, 5, 11, 7, 7, 3, 9, 10, 7, 6, 9, 6, 11, 7, 7, 6, 7, 8, 8, 5, 8, 15, 5, 10, 9, 4, 9, 9, 7, 6, 6, 6, 5, 7, 12, 9, 5, 7, 5, 8, 6, 5, 5, 8, 13, 6, 10, 6, 7, 10, 6, 15, 7, 7, 8, 5, 8, 9, 7, 13, 6, 7, 11, 8, 6, 4, 5, 10, 5, 11, 6, 14, 9, 7, 9, 6, 3, 10, 12, 7, 13, 13, 9, 10, 7, 6, 5, 8, 8, 8, 13, 8, 10, 6, 7, 7, 8, 9, 8, 15, 10, 9, 11, 11, 7, 4, 4, 5, 8, 7, 12, 12, 8, 9, 4, 16]\n",
      "Genrtn 159: mean = 7.845  stddev = 2.7930225562998947  max = 17 [7, 3, 5, 9, 9, 6, 6, 4, 8, 13, 8, 8, 7, 4, 12, 6, 9, 10, 7, 6, 5, 10, 5, 13, 8, 11, 4, 6, 5, 6, 2, 6, 6, 8, 8, 9, 4, 8, 14, 5, 11, 6, 8, 11, 7, 12, 13, 9, 5, 3, 4, 6, 9, 6, 10, 12, 4, 7, 9, 11, 6, 9, 3, 7, 8, 5, 7, 7, 11, 10, 5, 9, 8, 11, 8, 17, 7, 4, 9, 7, 4, 11, 4, 10, 11, 5, 15, 8, 10, 5, 6, 13, 7, 6, 8, 7, 10, 10, 9, 5, 10, 13, 4, 4, 9, 8, 8, 7, 4, 11, 7, 13, 7, 11, 8, 13, 6, 4, 10, 10, 13, 5, 9, 10, 6, 7, 8, 11, 12, 8, 10, 8, 11, 7, 10, 7, 6, 6, 5, 10, 5, 12, 5, 14, 8, 8, 13, 9, 8, 8, 4, 4, 6, 10, 6, 10, 2, 12, 8, 7, 6, 6, 7, 11, 7, 11, 9, 8, 8, 10, 6, 11, 7, 7, 9, 6, 9, 6, 5, 11, 5, 9, 6, 5, 5, 12, 7, 5, 6, 11, 7, 6, 5, 6, 4, 8, 7, 14, 6, 5]\n",
      "Genrtn 160: mean = 7.885  stddev = 3.066231400269719  max = 18 [6, 10, 5, 4, 12, 4, 3, 6, 13, 12, 7, 8, 10, 7, 6, 5, 9, 13, 4, 10, 7, 5, 10, 6, 11, 7, 7, 4, 8, 13, 6, 10, 9, 9, 9, 8, 12, 8, 8, 9, 9, 17, 14, 4, 5, 18, 9, 6, 5, 4, 7, 10, 3, 9, 6, 11, 6, 10, 7, 12, 4, 4, 10, 7, 4, 7, 6, 8, 6, 10, 13, 8, 6, 7, 6, 8, 10, 11, 11, 7, 5, 7, 15, 10, 5, 9, 7, 14, 3, 7, 6, 6, 6, 3, 5, 6, 10, 12, 6, 11, 9, 5, 3, 17, 5, 8, 4, 6, 9, 8, 9, 7, 7, 6, 6, 3, 6, 15, 7, 7, 11, 7, 8, 8, 11, 10, 11, 8, 8, 10, 7, 5, 7, 7, 13, 3, 11, 16, 6, 4, 4, 9, 13, 11, 7, 6, 6, 7, 6, 10, 9, 9, 4, 8, 6, 7, 7, 12, 7, 8, 8, 7, 8, 14, 10, 7, 3, 8, 10, 7, 9, 9, 7, 3, 10, 3, 8, 5, 7, 8, 12, 8, 4, 9, 7, 2, 5, 6, 15, 9, 12, 12, 10, 9, 4, 4, 9, 4, 7, 6]\n",
      "Genrtn 161: mean = 7.91  stddev = 2.8865030746562526  max = 16 [10, 6, 8, 8, 5, 16, 9, 7, 9, 12, 9, 4, 8, 5, 12, 10, 9, 7, 10, 8, 9, 3, 8, 8, 10, 6, 10, 9, 5, 9, 10, 11, 8, 7, 4, 6, 8, 10, 9, 6, 4, 9, 7, 4, 7, 3, 6, 9, 3, 6, 9, 11, 12, 10, 10, 8, 12, 9, 15, 5, 9, 8, 12, 6, 6, 10, 6, 9, 10, 3, 7, 1, 4, 13, 12, 12, 12, 3, 8, 6, 5, 7, 3, 10, 9, 9, 10, 11, 6, 9, 15, 13, 16, 5, 6, 3, 5, 12, 10, 8, 3, 8, 6, 8, 10, 5, 10, 5, 6, 7, 6, 7, 11, 8, 10, 7, 7, 10, 7, 9, 16, 6, 4, 6, 12, 5, 1, 8, 2, 6, 5, 10, 9, 4, 9, 6, 4, 9, 9, 9, 5, 8, 10, 9, 8, 8, 6, 3, 10, 11, 13, 5, 8, 8, 5, 8, 9, 9, 7, 4, 9, 10, 10, 6, 7, 7, 7, 6, 9, 5, 10, 7, 8, 16, 7, 12, 7, 7, 4, 11, 7, 5, 8, 12, 12, 8, 10, 5, 12, 5, 7, 11, 6, 6, 9, 5, 7, 10, 5, 7]\n",
      "Genrtn 162: mean = 8.085  stddev = 2.690311320275035  max = 17 [12, 4, 5, 9, 7, 8, 8, 12, 8, 7, 4, 8, 5, 12, 6, 8, 5, 7, 7, 10, 7, 13, 12, 6, 12, 2, 12, 2, 8, 9, 11, 8, 9, 8, 7, 5, 9, 7, 5, 8, 5, 8, 5, 6, 6, 9, 9, 8, 14, 8, 11, 7, 10, 9, 5, 5, 5, 10, 8, 9, 7, 7, 8, 8, 10, 9, 10, 17, 11, 5, 8, 8, 12, 7, 9, 4, 10, 6, 7, 9, 3, 11, 6, 9, 7, 12, 6, 14, 12, 1, 9, 3, 9, 10, 8, 11, 10, 7, 3, 7, 9, 9, 6, 4, 9, 6, 6, 8, 5, 10, 10, 10, 9, 7, 11, 11, 7, 9, 7, 9, 6, 8, 8, 7, 5, 8, 7, 10, 9, 10, 7, 14, 9, 7, 13, 12, 5, 9, 6, 6, 8, 8, 4, 8, 10, 7, 8, 8, 7, 6, 4, 8, 13, 4, 12, 8, 5, 11, 7, 5, 7, 3, 11, 9, 10, 6, 11, 8, 8, 6, 3, 10, 5, 5, 10, 8, 11, 6, 15, 11, 7, 9, 15, 8, 10, 7, 11, 8, 9, 10, 5, 7, 10, 7, 4, 8, 8, 14, 8, 11]\n",
      "Genrtn 163: mean = 7.865  stddev = 2.704953788884387  max = 19 [6, 8, 2, 11, 11, 6, 8, 11, 10, 6, 7, 5, 9, 7, 12, 9, 13, 13, 19, 5, 11, 12, 9, 5, 8, 8, 11, 6, 3, 8, 5, 10, 9, 10, 9, 9, 6, 8, 6, 7, 11, 7, 8, 9, 6, 11, 6, 10, 13, 11, 7, 4, 7, 8, 12, 3, 3, 9, 10, 8, 7, 7, 6, 6, 8, 4, 11, 11, 12, 9, 10, 6, 4, 7, 6, 6, 7, 4, 7, 3, 10, 7, 7, 6, 4, 9, 8, 10, 10, 5, 13, 5, 4, 10, 8, 5, 9, 8, 9, 9, 9, 6, 3, 9, 7, 7, 6, 8, 6, 10, 11, 8, 9, 5, 6, 3, 11, 8, 3, 6, 11, 8, 7, 9, 9, 12, 15, 5, 13, 10, 9, 7, 10, 10, 11, 5, 7, 4, 11, 7, 8, 8, 10, 2, 4, 6, 3, 10, 7, 9, 5, 6, 4, 9, 12, 9, 7, 9, 7, 10, 10, 8, 4, 13, 13, 7, 7, 9, 5, 7, 7, 10, 9, 8, 6, 5, 5, 9, 9, 5, 7, 7, 11, 5, 10, 6, 8, 8, 3, 7, 8, 8, 6, 4, 10, 6, 12, 8, 8, 11]\n",
      "Genrtn 164: mean = 8.22  stddev = 2.735251359564601  max = 18 [8, 10, 6, 13, 4, 13, 12, 12, 12, 7, 4, 12, 6, 9, 4, 7, 10, 6, 9, 3, 12, 11, 7, 5, 9, 8, 6, 9, 8, 9, 11, 7, 12, 10, 13, 6, 6, 7, 5, 6, 8, 6, 7, 9, 11, 9, 6, 6, 6, 9, 10, 4, 7, 9, 8, 8, 9, 13, 8, 9, 9, 5, 12, 6, 8, 9, 10, 9, 4, 2, 5, 15, 10, 4, 6, 6, 3, 8, 9, 6, 10, 6, 5, 15, 12, 8, 18, 9, 7, 5, 11, 6, 7, 7, 9, 7, 11, 13, 9, 10, 8, 3, 7, 4, 7, 8, 7, 11, 6, 7, 9, 9, 6, 10, 10, 5, 8, 3, 11, 6, 5, 11, 10, 6, 12, 16, 8, 6, 3, 8, 10, 4, 6, 6, 9, 14, 10, 6, 7, 8, 9, 8, 7, 11, 8, 12, 6, 11, 8, 5, 13, 10, 7, 10, 6, 10, 10, 6, 9, 3, 5, 11, 8, 10, 12, 8, 8, 11, 7, 11, 7, 9, 8, 8, 9, 5, 9, 10, 5, 13, 7, 10, 9, 7, 10, 7, 7, 9, 9, 11, 7, 6, 12, 9, 7, 4, 8, 6, 12, 7]\n",
      "Genrtn 165: mean = 8.14  stddev = 2.7749594591633224  max = 17 [5, 11, 6, 6, 5, 14, 9, 6, 4, 14, 10, 12, 6, 6, 13, 6, 9, 9, 9, 8, 10, 11, 6, 11, 13, 8, 7, 5, 5, 11, 11, 8, 6, 8, 8, 11, 6, 6, 7, 2, 8, 6, 11, 6, 10, 9, 8, 8, 3, 7, 12, 9, 8, 8, 11, 5, 5, 7, 7, 9, 6, 10, 7, 6, 9, 8, 5, 11, 8, 7, 6, 8, 13, 4, 7, 5, 9, 9, 6, 17, 15, 10, 9, 7, 12, 7, 9, 8, 6, 3, 8, 8, 12, 10, 7, 8, 7, 14, 8, 6, 6, 4, 7, 7, 11, 4, 6, 6, 11, 4, 11, 4, 6, 10, 11, 9, 10, 9, 10, 2, 6, 9, 4, 10, 7, 7, 11, 7, 8, 11, 13, 10, 8, 8, 10, 7, 14, 8, 7, 4, 10, 10, 15, 8, 9, 4, 11, 11, 7, 7, 5, 8, 8, 11, 5, 8, 10, 5, 13, 11, 8, 11, 9, 8, 7, 7, 5, 4, 8, 9, 5, 7, 3, 7, 9, 7, 11, 7, 8, 12, 11, 8, 12, 6, 6, 9, 7, 4, 12, 8, 12, 6, 10, 2, 13, 7, 4, 12, 10, 4]\n",
      "Genrtn 166: mean = 8.265  stddev = 3.0716078851311734  max = 18 [7, 17, 9, 5, 13, 4, 8, 14, 8, 10, 7, 10, 12, 3, 11, 7, 5, 8, 12, 14, 8, 3, 10, 6, 10, 16, 7, 8, 9, 9, 9, 9, 8, 9, 7, 6, 8, 4, 7, 9, 9, 7, 5, 11, 5, 6, 6, 3, 11, 11, 4, 14, 9, 7, 11, 7, 9, 9, 5, 14, 4, 7, 9, 8, 4, 7, 7, 10, 7, 7, 7, 10, 10, 9, 7, 4, 12, 6, 8, 9, 7, 8, 9, 8, 10, 10, 8, 11, 10, 6, 9, 8, 11, 11, 2, 3, 5, 5, 6, 7, 7, 7, 9, 6, 7, 12, 13, 5, 12, 14, 7, 8, 11, 2, 7, 11, 12, 5, 9, 5, 6, 11, 9, 8, 6, 10, 11, 5, 2, 16, 9, 9, 7, 8, 7, 4, 17, 10, 12, 7, 12, 11, 10, 12, 5, 7, 16, 7, 3, 9, 10, 10, 7, 10, 11, 9, 12, 4, 9, 7, 9, 18, 12, 6, 8, 10, 6, 5, 10, 7, 8, 5, 6, 10, 11, 7, 8, 11, 7, 3, 6, 12, 6, 6, 5, 7, 11, 15, 8, 5, 4, 6, 8, 5, 9, 9, 1, 11, 6, 7]\n",
      "Genrtn 167: mean = 8.04  stddev = 2.7800000000000002  max = 15 [6, 8, 6, 4, 8, 11, 10, 6, 8, 8, 8, 10, 6, 11, 13, 6, 10, 12, 4, 6, 2, 14, 8, 11, 6, 10, 7, 11, 4, 11, 8, 10, 11, 7, 9, 3, 5, 5, 12, 9, 13, 7, 5, 5, 9, 4, 10, 8, 9, 5, 8, 3, 7, 3, 8, 10, 7, 11, 12, 5, 7, 13, 6, 12, 4, 5, 9, 8, 9, 11, 12, 7, 15, 12, 8, 8, 3, 10, 13, 6, 12, 11, 8, 5, 6, 11, 8, 8, 3, 12, 7, 6, 9, 5, 11, 11, 11, 8, 6, 10, 5, 5, 7, 8, 9, 6, 9, 11, 10, 8, 8, 7, 5, 7, 6, 5, 9, 4, 3, 10, 12, 11, 7, 5, 8, 7, 11, 7, 3, 6, 7, 7, 9, 6, 6, 10, 12, 4, 5, 10, 2, 10, 7, 9, 8, 7, 12, 10, 4, 8, 5, 13, 8, 11, 11, 10, 6, 6, 3, 10, 10, 9, 8, 6, 6, 12, 14, 14, 10, 5, 8, 11, 8, 8, 9, 13, 5, 5, 4, 8, 10, 8, 10, 5, 10, 6, 10, 6, 10, 9, 6, 10, 6, 6, 8, 5, 8, 5, 11, 12]\n",
      "Genrtn 168: mean = 7.66  stddev = 2.845065904333325  max = 15 [7, 14, 12, 10, 7, 7, 8, 7, 3, 6, 10, 6, 7, 9, 10, 8, 6, 10, 9, 5, 2, 10, 9, 9, 8, 4, 8, 10, 7, 2, 7, 8, 12, 9, 10, 10, 7, 4, 8, 11, 13, 4, 10, 6, 13, 7, 3, 5, 10, 11, 10, 7, 9, 3, 11, 9, 3, 8, 8, 7, 2, 9, 5, 13, 5, 6, 3, 4, 8, 6, 8, 2, 12, 10, 11, 7, 8, 8, 1, 11, 15, 5, 9, 8, 4, 5, 5, 3, 7, 8, 9, 10, 13, 7, 4, 11, 5, 9, 7, 4, 10, 8, 10, 7, 11, 7, 5, 7, 4, 10, 10, 8, 6, 3, 4, 10, 7, 11, 10, 14, 8, 5, 7, 6, 8, 7, 5, 5, 6, 9, 12, 8, 9, 9, 9, 4, 10, 10, 6, 13, 9, 11, 9, 8, 7, 8, 7, 7, 13, 11, 6, 4, 6, 10, 6, 6, 8, 5, 8, 3, 5, 6, 7, 4, 8, 14, 7, 3, 6, 5, 10, 13, 9, 10, 12, 9, 5, 10, 8, 5, 2, 5, 11, 8, 5, 4, 9, 8, 3, 5, 5, 13, 7, 9, 9, 6, 7, 10, 10, 10]\n",
      "Genrtn 169: mean = 8.215  stddev = 2.6886381310990886  max = 16 [12, 9, 5, 10, 5, 13, 9, 15, 8, 4, 8, 6, 9, 11, 12, 13, 4, 10, 12, 15, 5, 8, 7, 10, 16, 7, 13, 7, 13, 10, 11, 7, 6, 2, 6, 12, 8, 5, 5, 5, 11, 8, 12, 6, 8, 6, 7, 8, 6, 9, 4, 9, 5, 8, 5, 10, 8, 12, 7, 4, 8, 8, 8, 3, 8, 12, 10, 8, 13, 8, 11, 7, 9, 9, 11, 7, 8, 10, 6, 5, 3, 5, 5, 12, 15, 10, 8, 9, 9, 5, 2, 7, 12, 5, 6, 4, 10, 8, 9, 8, 10, 4, 13, 12, 14, 10, 5, 6, 9, 6, 9, 8, 9, 4, 6, 9, 6, 7, 10, 9, 10, 5, 8, 6, 8, 10, 6, 7, 9, 10, 7, 7, 9, 10, 6, 11, 4, 9, 8, 7, 12, 10, 10, 8, 7, 8, 7, 7, 7, 8, 8, 8, 11, 9, 11, 5, 9, 11, 7, 5, 12, 10, 10, 7, 6, 10, 7, 7, 2, 8, 7, 10, 4, 10, 8, 9, 6, 9, 8, 7, 8, 9, 10, 6, 6, 7, 11, 3, 4, 11, 7, 10, 10, 9, 12, 10, 8, 12, 9, 6]\n",
      "Genrtn 170: mean = 7.86  stddev = 2.7350319925002706  max = 15 [11, 4, 8, 7, 7, 6, 9, 7, 7, 10, 3, 9, 6, 7, 5, 4, 13, 5, 6, 7, 8, 13, 6, 4, 9, 10, 11, 4, 12, 13, 8, 6, 8, 7, 9, 8, 4, 5, 7, 9, 9, 6, 8, 7, 6, 4, 8, 8, 9, 6, 10, 7, 7, 11, 7, 7, 8, 8, 5, 6, 8, 3, 7, 6, 4, 11, 7, 9, 9, 4, 11, 6, 9, 5, 3, 8, 13, 14, 11, 6, 9, 11, 9, 4, 10, 6, 10, 9, 10, 5, 13, 5, 9, 8, 10, 8, 9, 7, 9, 4, 4, 10, 9, 15, 3, 10, 3, 6, 11, 7, 2, 7, 8, 8, 5, 9, 7, 8, 3, 11, 8, 7, 6, 9, 9, 5, 10, 10, 15, 8, 11, 8, 8, 11, 4, 8, 7, 4, 8, 8, 11, 13, 8, 6, 11, 9, 6, 9, 7, 5, 13, 12, 8, 8, 10, 11, 5, 6, 9, 11, 11, 7, 3, 11, 5, 5, 9, 3, 6, 6, 2, 4, 8, 6, 10, 7, 11, 8, 7, 8, 8, 8, 6, 8, 6, 8, 15, 8, 10, 14, 7, 13, 6, 10, 3, 8, 7, 12, 9, 13]\n",
      "Genrtn 171: mean = 7.9  stddev = 2.5573423705088842  max = 14 [8, 7, 10, 6, 8, 5, 10, 7, 8, 9, 7, 7, 12, 4, 12, 7, 14, 6, 6, 7, 12, 9, 10, 7, 5, 13, 3, 14, 4, 13, 14, 12, 8, 5, 10, 7, 11, 8, 7, 5, 9, 11, 5, 10, 7, 7, 4, 8, 13, 7, 9, 10, 7, 9, 8, 8, 6, 7, 7, 4, 7, 12, 8, 5, 8, 8, 8, 9, 11, 14, 8, 2, 3, 6, 9, 9, 11, 11, 8, 10, 8, 7, 4, 7, 9, 7, 10, 8, 3, 11, 7, 2, 9, 7, 7, 11, 11, 5, 8, 6, 8, 3, 11, 10, 4, 7, 6, 10, 11, 8, 12, 8, 5, 11, 10, 8, 5, 6, 7, 7, 9, 12, 4, 7, 7, 9, 5, 6, 8, 11, 9, 9, 8, 4, 10, 10, 3, 7, 7, 6, 5, 6, 5, 10, 8, 6, 3, 5, 11, 12, 8, 6, 10, 9, 8, 6, 7, 5, 8, 7, 11, 13, 7, 9, 8, 5, 5, 9, 13, 6, 10, 5, 8, 6, 9, 7, 10, 8, 6, 7, 6, 10, 6, 7, 8, 10, 7, 13, 6, 8, 11, 10, 10, 5, 6, 4, 7, 8, 7, 9]\n",
      "Genrtn 172: mean = 7.995  stddev = 2.6429103276501835  max = 18 [8, 6, 4, 10, 6, 9, 8, 10, 15, 7, 12, 11, 8, 7, 5, 5, 11, 11, 8, 7, 3, 9, 5, 8, 3, 8, 10, 9, 3, 7, 8, 11, 4, 7, 6, 7, 7, 5, 7, 8, 10, 2, 8, 15, 6, 9, 9, 4, 5, 9, 7, 9, 4, 9, 7, 9, 11, 11, 8, 18, 2, 13, 11, 9, 7, 6, 10, 5, 10, 6, 9, 8, 4, 8, 10, 5, 7, 10, 11, 8, 8, 8, 6, 7, 5, 10, 9, 10, 9, 3, 7, 6, 7, 9, 8, 6, 3, 5, 10, 8, 7, 8, 9, 10, 9, 5, 12, 8, 6, 5, 7, 7, 8, 8, 10, 6, 5, 7, 10, 8, 7, 7, 6, 5, 8, 12, 12, 11, 6, 7, 10, 4, 11, 12, 6, 15, 12, 9, 14, 12, 9, 7, 10, 9, 7, 9, 12, 9, 5, 5, 9, 8, 6, 7, 8, 9, 6, 11, 8, 7, 6, 8, 10, 13, 12, 11, 12, 9, 7, 8, 7, 8, 3, 8, 7, 12, 9, 7, 6, 7, 8, 10, 6, 9, 7, 10, 10, 5, 10, 11, 4, 5, 5, 7, 12, 3, 10, 7, 7, 5]\n",
      "Genrtn 173: mean = 7.82  stddev = 2.9287540012776767  max = 20 [7, 5, 10, 7, 10, 9, 8, 9, 14, 20, 14, 7, 10, 16, 9, 7, 8, 7, 4, 7, 6, 6, 9, 5, 7, 8, 11, 8, 6, 10, 8, 4, 10, 10, 9, 12, 9, 10, 5, 15, 9, 9, 9, 6, 7, 12, 6, 7, 10, 11, 11, 5, 9, 9, 6, 6, 14, 7, 7, 4, 9, 13, 8, 11, 6, 8, 5, 7, 11, 10, 5, 8, 10, 4, 9, 10, 5, 13, 10, 8, 9, 6, 3, 8, 3, 10, 9, 12, 4, 9, 6, 9, 4, 3, 6, 4, 6, 6, 9, 10, 6, 13, 9, 6, 7, 5, 5, 5, 6, 8, 12, 1, 9, 5, 3, 6, 5, 2, 9, 9, 6, 8, 5, 6, 10, 5, 14, 10, 5, 6, 6, 6, 6, 5, 13, 11, 14, 14, 7, 6, 7, 8, 4, 7, 5, 8, 6, 9, 7, 5, 7, 11, 7, 7, 7, 8, 11, 3, 4, 8, 6, 6, 10, 3, 6, 6, 12, 6, 10, 8, 8, 5, 5, 2, 10, 6, 8, 7, 12, 7, 12, 3, 4, 11, 7, 10, 11, 5, 6, 9, 10, 8, 7, 4, 9, 11, 7, 11, 7, 10]\n",
      "Genrtn 174: mean = 7.7  stddev = 2.7092434368288134  max = 16 [12, 7, 8, 10, 3, 8, 6, 12, 6, 2, 10, 4, 11, 7, 7, 11, 8, 9, 8, 9, 5, 8, 9, 10, 9, 8, 6, 6, 4, 6, 6, 4, 13, 11, 5, 16, 10, 5, 8, 10, 10, 7, 5, 6, 7, 10, 6, 7, 8, 10, 4, 16, 13, 8, 6, 7, 5, 10, 8, 6, 8, 8, 11, 4, 11, 9, 8, 13, 8, 5, 8, 11, 7, 8, 5, 7, 7, 9, 11, 4, 6, 5, 11, 13, 3, 9, 4, 7, 7, 2, 5, 6, 9, 9, 9, 8, 7, 12, 5, 10, 5, 9, 8, 9, 5, 9, 3, 8, 5, 2, 6, 6, 13, 10, 7, 8, 13, 6, 8, 4, 8, 9, 9, 8, 4, 8, 9, 1, 8, 8, 12, 10, 6, 8, 10, 10, 9, 6, 5, 7, 10, 9, 6, 12, 8, 5, 8, 9, 5, 6, 7, 5, 8, 9, 2, 9, 5, 11, 13, 8, 9, 6, 7, 11, 2, 5, 8, 9, 8, 4, 5, 7, 4, 8, 8, 8, 12, 7, 8, 10, 10, 13, 5, 5, 7, 7, 4, 5, 6, 9, 8, 14, 8, 7, 7, 11, 6, 4, 9, 10]\n",
      "Genrtn 175: mean = 8.29  stddev = 2.90790302451784  max = 18 [9, 11, 9, 5, 10, 9, 17, 11, 10, 12, 8, 11, 7, 7, 6, 10, 6, 10, 12, 4, 7, 3, 9, 7, 8, 4, 10, 8, 10, 11, 7, 12, 8, 9, 9, 7, 6, 10, 8, 9, 8, 10, 11, 15, 9, 10, 12, 7, 5, 13, 8, 12, 8, 9, 7, 8, 18, 8, 6, 8, 4, 14, 6, 9, 11, 10, 3, 11, 9, 11, 8, 11, 7, 10, 8, 9, 8, 8, 9, 7, 10, 14, 7, 9, 7, 14, 8, 15, 9, 5, 10, 9, 9, 11, 10, 8, 11, 7, 4, 5, 10, 9, 10, 4, 14, 9, 7, 10, 4, 6, 10, 8, 10, 9, 7, 13, 8, 8, 9, 5, 9, 9, 4, 8, 7, 4, 3, 11, 8, 5, 9, 5, 6, 5, 10, 6, 6, 14, 10, 7, 4, 7, 7, 9, 5, 9, 11, 6, 17, 7, 7, 6, 17, 17, 7, 8, 9, 5, 8, 9, 5, 6, 9, 7, 10, 12, 7, 6, 9, 5, 7, 9, 4, 12, 5, 6, 7, 6, 3, 8, 7, 8, 8, 6, 5, 10, 2, 5, 8, 7, 6, 5, 10, 3, 11, 7, 4, 6, 8, 5]\n",
      "Genrtn 176: mean = 7.795  stddev = 2.8745390934895982  max = 16 [8, 11, 9, 10, 10, 15, 14, 9, 6, 2, 4, 5, 8, 12, 4, 8, 10, 8, 7, 6, 10, 5, 7, 4, 8, 10, 9, 7, 9, 10, 7, 10, 4, 13, 7, 12, 4, 5, 11, 7, 5, 5, 6, 9, 7, 6, 7, 6, 5, 5, 4, 10, 14, 7, 8, 8, 7, 1, 8, 6, 12, 5, 11, 8, 5, 5, 8, 6, 4, 6, 13, 5, 7, 8, 10, 10, 6, 10, 13, 5, 9, 8, 12, 6, 10, 10, 10, 8, 5, 12, 9, 7, 5, 9, 7, 9, 1, 11, 9, 2, 10, 10, 5, 8, 8, 1, 7, 12, 5, 8, 6, 3, 9, 10, 6, 3, 6, 9, 3, 8, 9, 10, 7, 11, 5, 10, 11, 7, 8, 13, 5, 8, 3, 11, 5, 11, 9, 7, 7, 8, 8, 8, 12, 7, 5, 8, 9, 11, 9, 7, 9, 5, 7, 4, 4, 12, 16, 5, 7, 10, 4, 10, 3, 7, 7, 8, 4, 4, 7, 8, 13, 9, 9, 7, 5, 9, 7, 13, 8, 7, 15, 12, 10, 5, 7, 9, 7, 15, 10, 10, 7, 10, 6, 6, 6, 8, 11, 5, 7, 4]\n",
      "Genrtn 177: mean = 8.0  stddev = 2.5729360660537215  max = 18 [8, 6, 11, 10, 10, 9, 12, 7, 9, 9, 3, 4, 10, 6, 5, 12, 7, 5, 13, 10, 10, 8, 8, 8, 3, 14, 9, 6, 5, 7, 8, 5, 7, 9, 5, 7, 5, 8, 12, 5, 9, 6, 10, 11, 9, 5, 9, 5, 11, 7, 9, 5, 11, 11, 7, 6, 9, 5, 9, 10, 10, 8, 6, 9, 8, 8, 6, 8, 10, 12, 7, 5, 7, 10, 5, 9, 8, 9, 7, 10, 8, 11, 11, 4, 9, 9, 11, 8, 10, 9, 8, 5, 6, 8, 5, 10, 5, 7, 7, 6, 9, 7, 9, 9, 11, 4, 10, 5, 5, 4, 8, 8, 7, 9, 10, 7, 3, 7, 8, 9, 8, 5, 14, 10, 7, 9, 13, 9, 12, 11, 10, 4, 9, 3, 9, 7, 5, 9, 5, 6, 13, 7, 8, 5, 8, 11, 8, 7, 6, 9, 6, 6, 8, 7, 12, 10, 4, 3, 11, 9, 8, 10, 8, 10, 7, 4, 13, 10, 10, 7, 5, 10, 7, 9, 4, 7, 14, 6, 6, 16, 8, 12, 7, 3, 8, 7, 10, 8, 8, 9, 6, 9, 18, 9, 8, 5, 6, 6, 7, 5]\n",
      "Genrtn 178: mean = 8.055  stddev = 2.6176277428236427  max = 16 [9, 6, 11, 7, 5, 6, 6, 5, 6, 12, 5, 4, 6, 9, 7, 7, 9, 9, 8, 7, 9, 10, 10, 10, 8, 7, 7, 8, 8, 7, 7, 8, 8, 4, 10, 4, 11, 10, 7, 5, 12, 11, 7, 7, 12, 10, 6, 7, 10, 13, 6, 6, 5, 6, 9, 15, 8, 9, 10, 11, 16, 7, 5, 13, 6, 6, 4, 12, 11, 7, 6, 8, 8, 7, 11, 10, 3, 10, 8, 10, 8, 7, 6, 7, 8, 11, 9, 6, 6, 11, 9, 8, 10, 6, 8, 13, 8, 11, 7, 10, 7, 13, 11, 5, 7, 5, 9, 6, 10, 13, 11, 12, 8, 13, 10, 13, 6, 7, 7, 4, 3, 3, 7, 11, 9, 8, 8, 5, 10, 11, 6, 8, 7, 9, 12, 8, 7, 6, 5, 8, 4, 6, 5, 7, 9, 9, 4, 7, 8, 6, 11, 10, 8, 4, 8, 9, 6, 7, 7, 6, 2, 7, 9, 7, 11, 7, 4, 6, 6, 5, 6, 7, 14, 6, 13, 13, 5, 7, 13, 11, 6, 5, 7, 11, 7, 7, 9, 10, 13, 11, 11, 7, 6, 9, 8, 5, 13, 4, 8, 7]\n",
      "Genrtn 179: mean = 8.32  stddev = 2.870121948628664  max = 19 [8, 10, 6, 9, 4, 15, 6, 8, 5, 12, 5, 10, 4, 6, 8, 6, 9, 8, 11, 8, 3, 12, 8, 7, 12, 9, 8, 7, 7, 11, 9, 14, 9, 11, 8, 9, 9, 3, 12, 8, 8, 9, 6, 11, 12, 10, 5, 7, 11, 12, 9, 9, 11, 9, 8, 11, 3, 5, 9, 11, 9, 6, 12, 8, 9, 7, 12, 9, 10, 7, 6, 12, 5, 10, 4, 10, 6, 5, 7, 8, 3, 1, 7, 8, 8, 7, 10, 9, 5, 7, 7, 4, 6, 9, 6, 11, 11, 9, 8, 4, 8, 12, 5, 12, 5, 6, 10, 13, 10, 4, 4, 9, 13, 3, 13, 7, 7, 7, 8, 9, 5, 8, 8, 9, 7, 11, 12, 10, 9, 6, 2, 3, 6, 5, 13, 10, 7, 6, 9, 16, 5, 13, 8, 9, 9, 10, 6, 11, 12, 7, 12, 9, 7, 9, 8, 9, 11, 11, 6, 8, 3, 10, 6, 3, 9, 5, 9, 14, 7, 10, 6, 11, 3, 11, 7, 7, 13, 9, 9, 9, 8, 9, 8, 13, 10, 6, 11, 4, 10, 8, 6, 5, 10, 19, 9, 10, 11, 6, 13, 8]\n",
      "Genrtn 180: mean = 7.875  stddev = 2.681300990191142  max = 16 [6, 8, 14, 7, 7, 9, 7, 2, 11, 8, 7, 6, 5, 7, 11, 5, 8, 5, 6, 5, 6, 6, 5, 9, 9, 8, 12, 3, 10, 8, 7, 6, 12, 12, 8, 8, 7, 8, 11, 6, 9, 9, 9, 12, 11, 9, 8, 7, 10, 11, 6, 8, 9, 7, 10, 11, 8, 8, 6, 12, 7, 5, 8, 10, 12, 9, 8, 11, 15, 6, 3, 11, 6, 8, 9, 8, 2, 6, 9, 9, 11, 7, 11, 5, 6, 8, 6, 3, 6, 4, 9, 4, 11, 7, 9, 12, 3, 9, 9, 5, 7, 6, 10, 10, 9, 6, 6, 11, 8, 10, 10, 4, 3, 7, 8, 5, 12, 12, 7, 5, 10, 5, 5, 6, 6, 6, 13, 6, 7, 7, 8, 7, 5, 9, 7, 5, 9, 6, 16, 6, 11, 1, 8, 7, 7, 7, 5, 7, 6, 10, 7, 4, 7, 4, 8, 3, 8, 4, 5, 4, 5, 12, 10, 11, 5, 11, 9, 9, 11, 4, 11, 6, 6, 9, 6, 8, 11, 6, 8, 10, 7, 12, 10, 8, 10, 8, 8, 6, 5, 5, 11, 12, 14, 11, 6, 9, 13, 9, 11, 12]\n",
      "Genrtn 181: mean = 7.865  stddev = 2.4973535993126803  max = 18 [5, 11, 9, 8, 8, 9, 3, 6, 8, 12, 8, 5, 10, 5, 7, 9, 7, 7, 7, 9, 6, 7, 6, 8, 4, 6, 11, 8, 9, 7, 4, 6, 8, 7, 9, 8, 7, 8, 8, 8, 6, 10, 10, 5, 8, 4, 9, 9, 7, 5, 6, 14, 14, 7, 6, 4, 10, 8, 12, 9, 7, 7, 6, 10, 9, 6, 10, 6, 7, 10, 9, 3, 8, 6, 8, 7, 9, 8, 8, 7, 5, 4, 9, 9, 14, 9, 12, 15, 4, 10, 6, 6, 9, 7, 6, 5, 6, 8, 12, 7, 9, 11, 10, 5, 8, 7, 10, 10, 9, 9, 7, 10, 10, 5, 9, 6, 12, 9, 7, 6, 6, 7, 12, 12, 8, 9, 10, 11, 8, 10, 6, 7, 2, 18, 4, 9, 6, 12, 6, 8, 6, 8, 6, 9, 3, 11, 6, 12, 8, 8, 7, 4, 5, 7, 5, 7, 7, 6, 3, 6, 11, 8, 9, 12, 4, 8, 9, 7, 7, 7, 9, 5, 11, 7, 9, 8, 9, 14, 6, 11, 9, 4, 8, 8, 10, 4, 8, 8, 9, 8, 7, 9, 4, 4, 6, 12, 7, 10, 11, 7]\n",
      "Genrtn 182: mean = 7.83  stddev = 2.7333313008122526  max = 16 [12, 12, 9, 5, 8, 5, 5, 8, 9, 8, 6, 10, 3, 15, 7, 4, 9, 8, 11, 5, 5, 9, 7, 8, 7, 7, 7, 13, 8, 8, 7, 8, 11, 6, 8, 6, 10, 5, 7, 10, 8, 11, 9, 13, 8, 6, 9, 9, 8, 9, 3, 4, 9, 7, 3, 2, 4, 3, 9, 6, 7, 10, 5, 9, 8, 7, 8, 7, 7, 7, 7, 6, 16, 5, 6, 10, 7, 10, 5, 8, 12, 10, 15, 9, 8, 10, 6, 4, 5, 8, 9, 10, 6, 5, 8, 3, 4, 7, 10, 8, 8, 5, 13, 8, 7, 10, 5, 12, 12, 5, 11, 11, 4, 4, 9, 7, 4, 10, 7, 5, 10, 8, 9, 7, 7, 7, 3, 6, 8, 12, 8, 7, 8, 9, 6, 6, 7, 6, 7, 5, 6, 4, 9, 9, 10, 6, 13, 6, 9, 7, 5, 12, 8, 7, 13, 12, 12, 11, 4, 7, 10, 12, 4, 4, 10, 11, 2, 14, 7, 7, 7, 9, 6, 11, 8, 9, 8, 13, 3, 9, 10, 6, 10, 11, 9, 11, 8, 9, 4, 7, 6, 5, 10, 11, 5, 13, 3, 7, 10, 6]\n",
      "Genrtn 183: mean = 7.98  stddev = 2.7585503439306667  max = 16 [4, 9, 7, 6, 11, 11, 6, 4, 5, 5, 7, 8, 4, 9, 9, 10, 6, 5, 10, 8, 4, 9, 8, 8, 14, 9, 9, 5, 6, 10, 12, 8, 7, 7, 7, 8, 6, 6, 7, 6, 10, 9, 12, 6, 7, 10, 7, 3, 11, 10, 16, 11, 6, 11, 6, 7, 8, 12, 3, 8, 8, 6, 5, 9, 8, 5, 13, 5, 6, 7, 8, 9, 11, 5, 7, 8, 9, 8, 7, 12, 8, 10, 14, 4, 10, 5, 11, 7, 6, 10, 10, 5, 8, 7, 6, 7, 15, 5, 3, 13, 9, 9, 8, 9, 5, 12, 9, 4, 9, 6, 7, 6, 5, 5, 8, 8, 4, 10, 12, 11, 4, 9, 9, 8, 11, 11, 8, 10, 11, 10, 6, 3, 6, 9, 5, 11, 10, 7, 6, 5, 8, 13, 11, 13, 13, 4, 1, 5, 5, 8, 10, 6, 6, 8, 5, 6, 11, 12, 11, 9, 11, 3, 10, 3, 10, 8, 8, 12, 2, 9, 10, 11, 8, 9, 10, 6, 13, 7, 5, 10, 3, 7, 9, 7, 8, 8, 8, 4, 12, 9, 8, 12, 12, 7, 11, 8, 5, 4, 10, 6]\n",
      "Genrtn 184: mean = 8.205  stddev = 3.0826895724350836  max = 23 [8, 5, 8, 6, 11, 13, 7, 3, 8, 6, 8, 7, 14, 8, 7, 9, 7, 11, 11, 8, 10, 6, 11, 23, 6, 10, 7, 8, 8, 7, 3, 8, 6, 8, 10, 7, 9, 9, 10, 5, 10, 7, 7, 7, 9, 3, 5, 12, 7, 9, 5, 5, 7, 6, 10, 9, 10, 4, 12, 12, 7, 11, 6, 11, 12, 9, 6, 8, 6, 5, 7, 11, 15, 6, 3, 4, 6, 6, 5, 9, 8, 9, 3, 7, 7, 8, 7, 11, 9, 6, 9, 8, 10, 6, 7, 14, 6, 14, 9, 8, 7, 14, 7, 6, 5, 3, 5, 7, 8, 7, 13, 10, 10, 11, 10, 11, 6, 8, 9, 7, 16, 2, 7, 4, 9, 6, 10, 7, 4, 4, 8, 8, 10, 10, 14, 14, 9, 11, 7, 3, 9, 10, 9, 8, 12, 14, 5, 4, 6, 7, 11, 12, 8, 4, 6, 7, 9, 18, 10, 7, 4, 12, 9, 5, 4, 9, 10, 15, 6, 6, 6, 8, 7, 13, 12, 7, 9, 10, 9, 9, 13, 14, 6, 3, 8, 5, 5, 8, 10, 6, 8, 8, 11, 11, 12, 7, 4, 8, 6, 4]\n",
      "Genrtn 185: mean = 7.97  stddev = 2.8087541722265406  max = 17 [7, 9, 6, 10, 9, 7, 11, 12, 9, 16, 12, 6, 10, 12, 9, 9, 6, 9, 6, 7, 9, 7, 10, 5, 10, 7, 7, 9, 9, 9, 4, 17, 7, 3, 5, 5, 5, 12, 11, 9, 8, 9, 8, 8, 4, 5, 10, 10, 8, 13, 6, 4, 7, 4, 3, 10, 4, 10, 6, 4, 12, 9, 12, 7, 9, 8, 5, 7, 6, 6, 9, 7, 6, 2, 9, 7, 7, 8, 6, 8, 4, 5, 11, 5, 5, 8, 17, 6, 7, 2, 10, 9, 6, 12, 4, 11, 11, 6, 5, 9, 9, 5, 5, 10, 8, 6, 12, 9, 7, 8, 5, 7, 9, 9, 6, 10, 5, 7, 7, 3, 9, 15, 11, 11, 4, 7, 10, 11, 4, 12, 7, 7, 11, 9, 5, 6, 8, 7, 13, 15, 4, 6, 5, 7, 12, 8, 11, 7, 6, 6, 8, 8, 8, 15, 4, 10, 8, 5, 11, 10, 5, 6, 5, 5, 13, 8, 12, 5, 8, 13, 10, 4, 7, 9, 11, 11, 8, 10, 7, 9, 6, 8, 9, 11, 10, 5, 9, 9, 6, 8, 7, 7, 9, 10, 9, 6, 3, 7, 7, 8]\n",
      "Genrtn 186: mean = 7.915  stddev = 2.815630480016865  max = 16 [9, 7, 5, 6, 4, 13, 7, 6, 7, 8, 8, 10, 5, 4, 8, 7, 16, 7, 8, 11, 11, 10, 9, 6, 14, 9, 8, 12, 4, 10, 9, 10, 5, 14, 8, 11, 15, 9, 8, 9, 4, 7, 4, 11, 10, 2, 9, 5, 11, 8, 12, 4, 11, 8, 5, 8, 5, 6, 9, 6, 9, 5, 5, 9, 11, 10, 10, 8, 12, 9, 4, 8, 11, 12, 7, 8, 6, 4, 10, 11, 9, 7, 5, 5, 11, 13, 6, 4, 8, 7, 6, 9, 5, 5, 3, 3, 8, 11, 6, 6, 11, 6, 7, 6, 6, 4, 8, 4, 13, 6, 7, 7, 8, 11, 12, 4, 9, 5, 7, 6, 7, 6, 11, 5, 5, 4, 6, 6, 12, 10, 7, 15, 7, 5, 9, 8, 7, 11, 4, 2, 6, 5, 11, 8, 12, 9, 5, 11, 10, 9, 9, 10, 9, 5, 8, 10, 10, 7, 4, 6, 8, 14, 10, 11, 12, 6, 7, 13, 9, 9, 8, 7, 8, 5, 8, 9, 8, 9, 7, 8, 7, 14, 4, 5, 4, 7, 8, 10, 5, 3, 6, 10, 11, 7, 12, 7, 12, 6, 10, 3]\n",
      "Genrtn 187: mean = 7.72  stddev = 2.796712355606132  max = 17 [8, 11, 6, 6, 7, 9, 6, 12, 8, 11, 5, 9, 5, 5, 9, 10, 12, 4, 4, 6, 10, 14, 7, 9, 7, 9, 7, 6, 6, 6, 9, 11, 12, 2, 5, 10, 7, 3, 5, 13, 8, 4, 6, 3, 7, 12, 8, 12, 8, 4, 8, 5, 5, 5, 13, 10, 10, 8, 8, 11, 5, 10, 1, 5, 7, 7, 5, 8, 5, 12, 2, 5, 8, 8, 8, 8, 11, 9, 10, 7, 7, 7, 6, 8, 7, 9, 2, 3, 9, 7, 5, 7, 6, 9, 9, 8, 8, 10, 3, 10, 9, 16, 8, 8, 7, 9, 10, 5, 12, 6, 7, 8, 4, 5, 12, 8, 6, 7, 8, 7, 6, 7, 7, 5, 6, 7, 11, 6, 13, 6, 10, 6, 9, 12, 17, 9, 6, 7, 5, 5, 5, 6, 12, 7, 8, 10, 15, 8, 4, 13, 10, 8, 7, 10, 10, 11, 4, 4, 6, 11, 2, 8, 7, 9, 7, 6, 2, 9, 10, 6, 4, 10, 9, 16, 5, 7, 7, 7, 7, 5, 6, 12, 6, 8, 8, 7, 5, 6, 9, 11, 8, 10, 6, 7, 10, 6, 8, 9, 11, 10]\n",
      "Genrtn 188: mean = 7.77  stddev = 2.587875576607191  max = 15 [11, 11, 7, 9, 10, 5, 7, 13, 4, 8, 10, 7, 7, 6, 7, 9, 9, 4, 10, 6, 9, 6, 7, 13, 8, 8, 15, 7, 10, 11, 11, 3, 5, 6, 7, 8, 5, 8, 5, 9, 6, 9, 11, 13, 5, 3, 8, 7, 6, 5, 5, 7, 9, 3, 9, 9, 4, 7, 13, 6, 13, 7, 7, 7, 2, 8, 6, 13, 10, 11, 8, 3, 5, 9, 3, 6, 8, 6, 12, 5, 11, 7, 11, 9, 6, 6, 10, 7, 6, 8, 8, 8, 6, 5, 10, 8, 8, 3, 6, 7, 5, 10, 7, 4, 8, 10, 6, 10, 6, 8, 7, 11, 8, 8, 4, 10, 7, 6, 8, 10, 11, 5, 7, 7, 12, 7, 14, 6, 6, 9, 5, 6, 9, 9, 7, 11, 6, 9, 7, 5, 6, 9, 6, 3, 6, 8, 10, 5, 9, 14, 9, 9, 6, 7, 11, 8, 7, 12, 6, 7, 7, 11, 5, 5, 6, 7, 13, 10, 10, 11, 6, 14, 8, 6, 7, 10, 7, 10, 11, 7, 7, 6, 9, 5, 6, 14, 2, 8, 12, 4, 5, 6, 8, 9, 8, 6, 9, 10, 6, 9]\n",
      "Genrtn 189: mean = 7.985  stddev = 2.6785770476131536  max = 16 [7, 5, 9, 9, 5, 5, 4, 10, 9, 7, 7, 11, 6, 8, 10, 11, 3, 8, 9, 7, 5, 11, 10, 7, 6, 5, 4, 5, 4, 10, 8, 12, 5, 10, 4, 8, 7, 11, 8, 10, 10, 14, 9, 2, 7, 7, 7, 5, 6, 11, 9, 10, 8, 13, 7, 8, 14, 7, 6, 7, 7, 5, 6, 5, 6, 6, 6, 10, 14, 6, 5, 8, 6, 10, 6, 6, 6, 4, 6, 9, 8, 10, 7, 9, 9, 11, 5, 6, 14, 8, 6, 8, 7, 9, 9, 11, 5, 10, 7, 6, 2, 6, 6, 11, 9, 10, 12, 13, 13, 12, 6, 7, 13, 8, 12, 9, 8, 9, 8, 8, 4, 4, 13, 9, 5, 10, 9, 7, 3, 10, 8, 9, 7, 10, 7, 5, 8, 9, 7, 7, 5, 5, 5, 10, 5, 9, 11, 5, 12, 10, 10, 8, 10, 8, 4, 5, 13, 7, 8, 6, 6, 8, 6, 10, 8, 10, 10, 6, 10, 7, 7, 11, 11, 4, 5, 7, 10, 10, 11, 11, 11, 8, 7, 1, 10, 16, 9, 8, 7, 7, 8, 5, 11, 8, 3, 6, 10, 11, 11, 14]\n",
      "Genrtn 190: mean = 8.18  stddev = 2.8280028288528993  max = 18 [10, 10, 8, 5, 13, 9, 6, 5, 7, 8, 4, 12, 6, 10, 13, 4, 6, 9, 8, 12, 8, 9, 10, 9, 9, 11, 8, 13, 7, 3, 9, 11, 6, 11, 8, 4, 10, 11, 10, 7, 7, 14, 9, 13, 9, 15, 6, 6, 7, 8, 5, 14, 10, 8, 5, 5, 6, 6, 7, 7, 4, 13, 3, 8, 7, 6, 5, 8, 9, 13, 8, 9, 8, 6, 5, 9, 14, 7, 7, 4, 18, 13, 5, 6, 7, 8, 11, 7, 4, 8, 9, 6, 6, 12, 11, 5, 8, 9, 9, 9, 6, 7, 7, 7, 7, 12, 10, 12, 5, 5, 7, 12, 10, 6, 5, 7, 6, 9, 3, 9, 9, 5, 10, 7, 4, 9, 13, 4, 11, 5, 5, 6, 5, 11, 6, 10, 11, 8, 4, 10, 14, 15, 8, 5, 8, 4, 4, 9, 9, 10, 9, 10, 8, 10, 10, 10, 9, 6, 5, 11, 9, 8, 12, 7, 9, 8, 9, 8, 8, 9, 12, 8, 10, 7, 8, 6, 13, 6, 11, 4, 10, 2, 5, 8, 8, 8, 9, 10, 6, 8, 4, 9, 6, 7, 4, 7, 10, 6, 13, 15]\n",
      "Genrtn 191: mean = 8.125  stddev = 2.798102035308934  max = 17 [6, 6, 9, 7, 9, 8, 7, 8, 13, 5, 8, 8, 9, 8, 10, 10, 10, 15, 12, 11, 7, 12, 7, 10, 8, 6, 5, 8, 7, 17, 5, 4, 15, 4, 4, 12, 13, 8, 6, 8, 8, 5, 4, 7, 5, 2, 8, 8, 7, 14, 9, 7, 4, 6, 8, 10, 6, 14, 9, 7, 9, 8, 10, 9, 5, 11, 7, 7, 9, 3, 14, 10, 9, 6, 8, 8, 4, 5, 12, 10, 8, 11, 6, 8, 7, 14, 7, 11, 13, 7, 11, 7, 4, 12, 8, 3, 7, 9, 7, 10, 9, 8, 12, 12, 9, 7, 8, 8, 9, 5, 10, 6, 9, 9, 8, 9, 11, 5, 6, 2, 7, 7, 12, 8, 8, 10, 5, 6, 4, 9, 11, 7, 12, 6, 14, 12, 10, 11, 11, 8, 5, 7, 12, 8, 7, 8, 10, 8, 10, 8, 11, 8, 5, 6, 8, 6, 5, 2, 6, 3, 7, 10, 8, 8, 11, 9, 9, 12, 8, 5, 12, 8, 5, 12, 7, 6, 7, 5, 10, 7, 7, 13, 9, 6, 2, 2, 9, 4, 5, 8, 12, 8, 6, 12, 8, 8, 5, 10, 9, 6]\n",
      "Genrtn 192: mean = 7.6  stddev = 2.7  max = 19 [8, 15, 8, 8, 6, 9, 6, 4, 8, 5, 7, 7, 6, 9, 8, 8, 8, 9, 6, 9, 2, 6, 6, 8, 6, 4, 7, 8, 4, 8, 6, 10, 9, 11, 6, 8, 5, 3, 7, 9, 4, 9, 3, 7, 9, 8, 13, 11, 6, 7, 13, 14, 7, 7, 8, 9, 4, 7, 12, 7, 4, 5, 7, 6, 6, 9, 10, 10, 6, 9, 12, 14, 4, 12, 10, 12, 5, 5, 5, 9, 7, 8, 11, 7, 5, 9, 8, 6, 6, 10, 8, 9, 9, 7, 7, 9, 6, 6, 8, 10, 10, 5, 9, 8, 7, 3, 7, 10, 9, 8, 7, 3, 10, 6, 8, 3, 10, 8, 5, 5, 7, 11, 7, 10, 7, 11, 4, 8, 19, 3, 5, 9, 13, 6, 5, 8, 7, 5, 9, 11, 7, 8, 8, 12, 6, 4, 5, 10, 7, 3, 14, 4, 9, 5, 11, 10, 6, 8, 13, 4, 10, 6, 3, 6, 6, 12, 5, 9, 4, 3, 6, 5, 5, 8, 8, 11, 5, 8, 7, 4, 13, 9, 11, 9, 6, 7, 11, 10, 8, 8, 9, 6, 9, 7, 5, 8, 6, 9, 3, 7]\n",
      "Genrtn 193: mean = 7.7  stddev = 2.6627053911388696  max = 15 [4, 7, 14, 6, 5, 7, 11, 8, 4, 8, 8, 7, 12, 13, 12, 5, 6, 6, 9, 9, 7, 7, 6, 4, 6, 5, 6, 8, 4, 8, 7, 6, 9, 6, 7, 9, 11, 8, 8, 8, 4, 11, 7, 5, 3, 8, 4, 5, 11, 10, 7, 7, 8, 14, 6, 6, 9, 5, 4, 4, 7, 14, 12, 7, 5, 8, 4, 14, 10, 6, 10, 13, 9, 13, 9, 11, 9, 11, 8, 8, 11, 9, 4, 9, 14, 6, 8, 6, 5, 7, 6, 4, 3, 7, 7, 7, 4, 8, 13, 12, 7, 7, 9, 9, 8, 15, 10, 7, 5, 9, 10, 8, 5, 9, 5, 3, 7, 8, 8, 3, 5, 8, 9, 5, 10, 2, 10, 6, 7, 7, 8, 4, 10, 6, 9, 8, 8, 9, 10, 6, 7, 11, 9, 8, 9, 9, 12, 11, 5, 10, 8, 9, 9, 8, 7, 7, 7, 4, 8, 5, 7, 6, 8, 10, 3, 4, 4, 6, 9, 5, 4, 10, 10, 4, 3, 10, 8, 10, 7, 8, 7, 7, 7, 8, 6, 9, 12, 11, 12, 8, 8, 4, 12, 4, 7, 7, 12, 7, 12, 5]\n",
      "Genrtn 194: mean = 8.23  stddev = 2.9710435876977637  max = 18 [8, 7, 7, 4, 7, 10, 7, 3, 6, 11, 6, 3, 5, 10, 11, 9, 9, 5, 9, 9, 9, 4, 4, 9, 11, 11, 12, 9, 5, 7, 10, 7, 10, 15, 12, 8, 10, 9, 7, 3, 8, 8, 12, 5, 14, 4, 7, 11, 7, 12, 7, 12, 7, 11, 8, 7, 9, 6, 12, 7, 4, 9, 4, 7, 6, 9, 4, 12, 10, 8, 11, 10, 4, 9, 9, 12, 7, 4, 13, 10, 8, 7, 10, 7, 9, 8, 4, 9, 4, 7, 4, 5, 10, 4, 2, 8, 9, 9, 7, 11, 8, 9, 9, 12, 10, 7, 9, 9, 9, 5, 10, 11, 8, 5, 5, 4, 4, 12, 6, 4, 15, 8, 14, 10, 5, 16, 7, 5, 10, 10, 11, 15, 8, 2, 6, 9, 7, 11, 12, 8, 8, 11, 7, 6, 18, 3, 6, 6, 10, 8, 9, 7, 10, 10, 12, 6, 7, 9, 9, 10, 6, 14, 9, 5, 3, 11, 3, 10, 12, 6, 12, 9, 10, 7, 2, 15, 8, 8, 10, 8, 9, 6, 9, 10, 7, 12, 13, 4, 7, 6, 5, 6, 5, 7, 11, 8, 13, 7, 10, 10]\n",
      "Genrtn 195: mean = 7.885  stddev = 2.6873360415102536  max = 16 [6, 6, 10, 4, 1, 6, 6, 3, 6, 4, 9, 7, 9, 8, 7, 10, 5, 7, 8, 9, 8, 6, 10, 11, 8, 7, 6, 8, 5, 9, 8, 11, 9, 9, 9, 4, 8, 11, 8, 16, 6, 9, 10, 8, 11, 9, 9, 11, 7, 6, 11, 8, 11, 9, 5, 10, 5, 9, 10, 5, 10, 7, 8, 7, 9, 6, 9, 10, 10, 7, 6, 2, 4, 8, 5, 7, 9, 6, 4, 6, 8, 9, 7, 8, 10, 6, 7, 9, 6, 6, 7, 8, 11, 7, 7, 11, 7, 5, 8, 8, 13, 9, 5, 11, 12, 10, 4, 4, 5, 13, 9, 5, 7, 3, 11, 9, 7, 4, 12, 14, 3, 15, 7, 7, 5, 8, 15, 4, 12, 11, 10, 7, 5, 3, 7, 10, 5, 5, 11, 5, 6, 10, 9, 15, 8, 11, 10, 6, 7, 6, 7, 7, 7, 4, 7, 12, 5, 7, 5, 5, 5, 9, 6, 10, 7, 12, 8, 6, 12, 8, 9, 9, 11, 9, 13, 9, 10, 5, 11, 4, 11, 14, 5, 7, 10, 11, 6, 8, 11, 5, 10, 5, 10, 6, 5, 6, 7, 8, 6, 11]\n",
      "Genrtn 196: mean = 7.84  stddev = 2.9076450952618  max = 15 [12, 12, 10, 11, 8, 11, 6, 13, 11, 8, 8, 11, 5, 9, 15, 4, 7, 11, 13, 13, 8, 9, 10, 8, 11, 10, 7, 10, 7, 9, 3, 11, 7, 10, 8, 4, 6, 3, 2, 5, 8, 11, 12, 9, 8, 10, 9, 9, 7, 6, 4, 10, 9, 9, 4, 5, 5, 10, 8, 6, 7, 3, 6, 10, 10, 7, 4, 4, 8, 5, 6, 5, 11, 3, 5, 5, 10, 6, 5, 8, 7, 6, 10, 3, 6, 1, 10, 9, 9, 9, 7, 10, 10, 8, 9, 3, 11, 10, 7, 10, 6, 4, 3, 5, 7, 10, 3, 9, 7, 8, 4, 4, 12, 14, 5, 9, 7, 15, 6, 6, 5, 9, 10, 7, 10, 9, 10, 8, 5, 12, 10, 7, 6, 10, 9, 7, 6, 4, 9, 5, 10, 9, 8, 9, 5, 12, 5, 10, 11, 6, 11, 4, 9, 11, 11, 9, 8, 2, 10, 7, 13, 9, 12, 5, 5, 6, 4, 10, 7, 8, 5, 12, 6, 5, 9, 3, 12, 11, 8, 6, 6, 12, 4, 5, 2, 6, 11, 5, 14, 11, 14, 4, 8, 5, 7, 9, 8, 8, 12, 4]\n",
      "Genrtn 197: mean = 7.675  stddev = 2.6342693484152298  max = 17 [6, 4, 6, 8, 9, 7, 8, 9, 12, 7, 6, 8, 6, 9, 4, 6, 5, 6, 5, 10, 7, 4, 7, 8, 10, 11, 7, 5, 8, 9, 5, 11, 11, 5, 9, 6, 6, 3, 7, 14, 8, 8, 13, 9, 10, 3, 9, 5, 3, 6, 4, 7, 7, 5, 8, 9, 10, 9, 5, 6, 7, 5, 10, 6, 4, 10, 8, 7, 6, 8, 4, 4, 8, 12, 4, 6, 9, 10, 6, 8, 10, 7, 10, 5, 13, 9, 5, 10, 7, 2, 9, 7, 6, 3, 3, 7, 12, 7, 9, 6, 10, 6, 8, 14, 9, 8, 8, 6, 9, 9, 5, 7, 10, 7, 12, 15, 10, 11, 7, 7, 10, 2, 5, 8, 13, 7, 7, 10, 7, 13, 9, 8, 5, 11, 17, 8, 5, 11, 3, 7, 4, 4, 8, 11, 5, 8, 4, 8, 11, 10, 8, 6, 9, 7, 8, 9, 5, 7, 8, 10, 10, 5, 8, 6, 10, 7, 6, 5, 10, 7, 8, 6, 15, 4, 9, 7, 7, 9, 7, 9, 10, 9, 6, 11, 8, 8, 8, 10, 10, 5, 6, 10, 11, 3, 5, 5, 12, 7, 9, 6]\n",
      "Genrtn 198: mean = 7.915  stddev = 2.908225403919029  max = 17 [8, 13, 9, 5, 11, 6, 8, 7, 7, 3, 8, 9, 10, 6, 7, 9, 2, 5, 5, 9, 8, 6, 8, 5, 9, 12, 5, 7, 6, 5, 6, 13, 5, 6, 9, 10, 4, 14, 8, 5, 10, 4, 7, 2, 10, 4, 12, 8, 5, 10, 5, 6, 7, 6, 10, 9, 10, 4, 5, 7, 10, 6, 8, 13, 3, 15, 10, 7, 7, 13, 9, 9, 15, 8, 14, 8, 6, 8, 5, 7, 13, 7, 9, 7, 8, 12, 7, 8, 7, 7, 6, 15, 7, 7, 8, 12, 5, 4, 8, 11, 8, 8, 17, 6, 4, 7, 3, 9, 7, 6, 9, 14, 11, 10, 6, 6, 10, 1, 2, 7, 6, 9, 9, 9, 6, 5, 5, 8, 7, 9, 6, 8, 6, 13, 12, 7, 3, 6, 4, 9, 10, 11, 8, 9, 5, 3, 13, 9, 8, 7, 5, 6, 6, 5, 8, 8, 10, 10, 10, 7, 10, 9, 11, 9, 10, 11, 6, 6, 8, 7, 14, 6, 8, 8, 6, 9, 5, 11, 13, 7, 11, 7, 3, 4, 10, 9, 7, 13, 9, 6, 11, 15, 7, 4, 10, 5, 11, 10, 7, 6]\n",
      "Genrtn 199: mean = 8.12  stddev = 2.602998271224935  max = 17 [9, 4, 5, 9, 10, 10, 5, 12, 6, 4, 6, 10, 5, 7, 8, 6, 7, 9, 10, 10, 7, 8, 8, 6, 7, 9, 6, 10, 8, 8, 7, 8, 4, 12, 7, 4, 5, 5, 8, 9, 9, 4, 8, 8, 9, 8, 7, 6, 6, 9, 9, 5, 2, 7, 6, 6, 8, 8, 8, 9, 6, 4, 8, 8, 13, 6, 9, 4, 11, 8, 10, 8, 8, 10, 14, 10, 8, 6, 7, 10, 9, 11, 9, 8, 6, 7, 9, 3, 10, 14, 7, 9, 6, 7, 7, 8, 7, 7, 10, 6, 11, 9, 6, 8, 13, 9, 11, 9, 12, 5, 9, 7, 12, 6, 8, 6, 9, 10, 5, 12, 11, 13, 11, 6, 8, 13, 5, 13, 11, 7, 8, 9, 10, 8, 8, 17, 5, 5, 10, 7, 8, 7, 9, 13, 12, 4, 7, 3, 12, 11, 7, 6, 2, 12, 7, 7, 5, 5, 10, 10, 6, 10, 7, 5, 7, 3, 9, 14, 8, 8, 11, 7, 6, 12, 9, 6, 11, 7, 5, 10, 11, 8, 8, 10, 14, 3, 8, 11, 5, 11, 13, 9, 8, 5, 10, 9, 9, 5, 10, 9]\n",
      "Genrtn 200: mean = 7.815  stddev = 2.453726757403929  max = 15 [11, 5, 9, 7, 9, 7, 12, 10, 7, 5, 11, 9, 10, 9, 6, 4, 9, 13, 9, 10, 4, 9, 6, 4, 9, 10, 8, 4, 4, 12, 11, 6, 11, 10, 7, 5, 8, 7, 4, 5, 9, 3, 3, 13, 4, 6, 10, 7, 10, 11, 6, 8, 4, 9, 9, 9, 7, 8, 7, 9, 10, 11, 4, 8, 10, 9, 9, 8, 10, 10, 6, 6, 10, 6, 8, 10, 7, 8, 6, 6, 8, 5, 7, 10, 5, 6, 6, 9, 10, 5, 9, 11, 5, 10, 10, 6, 6, 6, 11, 8, 5, 7, 6, 10, 6, 8, 5, 13, 8, 8, 6, 6, 8, 12, 8, 13, 5, 10, 5, 7, 4, 6, 10, 12, 15, 10, 7, 10, 13, 7, 11, 7, 10, 10, 12, 5, 7, 9, 7, 7, 7, 5, 8, 5, 4, 7, 9, 6, 10, 12, 11, 6, 4, 5, 5, 8, 4, 6, 9, 12, 10, 8, 8, 8, 11, 8, 7, 9, 8, 6, 9, 9, 9, 8, 6, 5, 2, 8, 5, 9, 10, 3, 4, 7, 9, 9, 11, 6, 8, 10, 7, 6, 5, 8, 4, 6, 9, 7, 9, 11]\n",
      "Genrtn 201: mean = 7.965  stddev = 2.768352398088076  max = 16 [7, 8, 7, 9, 10, 8, 12, 9, 4, 6, 6, 6, 8, 6, 11, 8, 6, 10, 11, 8, 9, 11, 5, 7, 16, 4, 6, 9, 2, 8, 4, 3, 9, 6, 10, 9, 7, 10, 15, 9, 6, 8, 5, 6, 11, 8, 5, 10, 7, 8, 6, 9, 9, 7, 13, 12, 9, 8, 7, 8, 3, 9, 7, 7, 12, 8, 11, 2, 7, 7, 7, 6, 6, 6, 8, 4, 5, 7, 7, 11, 8, 11, 5, 9, 13, 8, 10, 8, 11, 10, 8, 10, 9, 7, 9, 5, 12, 5, 8, 9, 5, 12, 9, 5, 13, 9, 8, 14, 5, 8, 13, 8, 6, 8, 12, 4, 4, 6, 7, 9, 11, 7, 6, 6, 9, 12, 5, 8, 9, 5, 6, 5, 11, 12, 5, 4, 7, 4, 10, 10, 8, 5, 3, 7, 9, 12, 9, 5, 11, 7, 5, 7, 13, 7, 10, 6, 12, 5, 12, 5, 8, 14, 11, 6, 12, 11, 4, 4, 10, 7, 16, 11, 5, 8, 11, 7, 7, 5, 2, 7, 5, 12, 11, 8, 8, 10, 11, 6, 4, 6, 8, 11, 9, 9, 7, 8, 8, 8, 4, 3]\n",
      "Genrtn 202: mean = 8.08  stddev = 2.8237563634279783  max = 18 [9, 10, 9, 8, 6, 9, 8, 4, 8, 9, 13, 6, 4, 11, 7, 11, 6, 6, 3, 9, 6, 8, 4, 8, 7, 5, 9, 8, 9, 8, 7, 10, 18, 7, 5, 12, 11, 11, 9, 10, 8, 13, 10, 9, 11, 9, 9, 7, 7, 6, 5, 1, 12, 7, 8, 13, 8, 6, 10, 7, 6, 12, 8, 3, 5, 10, 10, 8, 5, 11, 7, 7, 10, 6, 2, 7, 8, 5, 10, 6, 11, 7, 15, 7, 6, 9, 5, 12, 7, 6, 8, 7, 12, 7, 15, 5, 5, 9, 14, 3, 7, 6, 5, 8, 5, 13, 5, 9, 8, 7, 5, 8, 11, 9, 10, 5, 7, 9, 8, 5, 14, 7, 9, 9, 10, 6, 7, 7, 8, 10, 16, 13, 10, 9, 7, 13, 9, 6, 8, 7, 4, 7, 8, 7, 8, 12, 9, 7, 5, 9, 10, 6, 11, 8, 14, 14, 11, 8, 2, 12, 6, 9, 5, 12, 10, 4, 5, 6, 10, 9, 5, 4, 8, 10, 4, 5, 7, 11, 4, 5, 11, 10, 2, 10, 7, 10, 9, 9, 5, 7, 7, 11, 7, 8, 7, 12, 5, 8, 8, 7]\n",
      "Genrtn 203: mean = 8.05  stddev = 3.024483426967323  max = 17 [7, 5, 7, 11, 11, 11, 9, 4, 11, 8, 9, 7, 6, 6, 9, 7, 13, 7, 10, 3, 6, 12, 5, 8, 9, 11, 5, 11, 8, 6, 8, 11, 5, 4, 6, 5, 7, 9, 3, 10, 7, 8, 6, 10, 6, 6, 4, 5, 8, 6, 12, 8, 12, 7, 5, 7, 11, 10, 5, 5, 12, 8, 10, 7, 5, 7, 7, 7, 9, 9, 6, 6, 11, 8, 8, 5, 11, 6, 16, 12, 13, 8, 6, 6, 6, 12, 6, 4, 6, 9, 12, 8, 7, 3, 9, 7, 9, 3, 10, 7, 12, 8, 5, 2, 12, 11, 7, 4, 5, 7, 6, 12, 8, 3, 9, 10, 5, 5, 10, 7, 15, 7, 15, 8, 16, 9, 16, 6, 10, 9, 14, 10, 6, 6, 4, 8, 7, 8, 11, 7, 10, 9, 10, 13, 6, 10, 9, 5, 9, 6, 9, 8, 5, 9, 7, 7, 6, 9, 8, 8, 2, 14, 4, 10, 6, 9, 4, 5, 7, 11, 11, 5, 8, 16, 13, 12, 6, 6, 10, 8, 9, 12, 7, 11, 5, 9, 7, 11, 1, 17, 13, 4, 7, 12, 2, 4, 6, 8, 9, 7]\n",
      "Genrtn 204: mean = 7.54  stddev = 2.9813419797131626  max = 18 [8, 4, 5, 6, 5, 4, 9, 7, 17, 10, 10, 7, 5, 3, 5, 4, 9, 2, 8, 10, 10, 6, 10, 11, 11, 3, 10, 5, 8, 8, 8, 4, 6, 9, 10, 6, 12, 9, 9, 6, 6, 7, 8, 8, 3, 13, 3, 13, 6, 11, 6, 11, 10, 3, 7, 4, 9, 7, 8, 11, 7, 4, 8, 11, 3, 5, 8, 10, 14, 12, 10, 10, 10, 7, 7, 6, 10, 5, 7, 11, 6, 7, 8, 7, 4, 7, 5, 9, 8, 12, 6, 11, 7, 6, 4, 8, 4, 5, 8, 8, 13, 6, 6, 8, 18, 12, 8, 9, 11, 6, 7, 8, 10, 10, 8, 6, 14, 4, 7, 3, 7, 7, 2, 14, 6, 3, 5, 4, 5, 6, 5, 4, 11, 5, 3, 6, 8, 3, 5, 7, 13, 10, 7, 10, 6, 9, 8, 10, 6, 6, 6, 15, 8, 8, 10, 7, 7, 9, 12, 6, 8, 5, 7, 3, 9, 7, 8, 11, 7, 11, 8, 6, 4, 15, 4, 9, 11, 6, 9, 4, 8, 7, 6, 8, 14, 6, 2, 5, 7, 3, 7, 6, 8, 10, 3, 4, 10, 9, 9, 3]\n",
      "Genrtn 205: mean = 8.005  stddev = 2.7486314776630207  max = 16 [7, 12, 6, 16, 5, 5, 6, 2, 8, 6, 8, 4, 7, 6, 9, 9, 6, 4, 8, 11, 4, 8, 10, 7, 10, 4, 7, 9, 8, 12, 10, 8, 11, 9, 10, 7, 9, 8, 5, 9, 4, 12, 6, 5, 15, 15, 7, 11, 7, 11, 8, 8, 9, 7, 10, 8, 10, 5, 12, 8, 9, 8, 12, 7, 4, 8, 11, 8, 7, 10, 7, 7, 11, 12, 3, 11, 7, 6, 11, 5, 8, 9, 6, 10, 8, 12, 7, 15, 9, 7, 11, 10, 8, 8, 6, 4, 7, 11, 6, 9, 9, 6, 9, 12, 11, 4, 6, 8, 4, 6, 4, 7, 16, 6, 6, 8, 10, 3, 7, 7, 7, 5, 13, 2, 7, 6, 9, 7, 7, 7, 7, 8, 6, 10, 12, 6, 11, 9, 6, 7, 7, 5, 7, 8, 16, 3, 12, 5, 8, 11, 7, 5, 7, 7, 8, 7, 11, 10, 11, 11, 12, 3, 10, 12, 12, 8, 6, 4, 11, 8, 11, 9, 8, 7, 9, 6, 8, 8, 7, 7, 4, 4, 10, 6, 8, 8, 9, 4, 9, 4, 7, 4, 14, 7, 9, 8, 10, 7, 9, 4]\n",
      "Genrtn 206: mean = 8.145  stddev = 2.7756035379715165  max = 16 [8, 13, 2, 3, 6, 7, 9, 9, 4, 9, 11, 13, 8, 7, 12, 7, 9, 8, 6, 7, 9, 10, 6, 9, 5, 3, 6, 11, 11, 12, 12, 5, 8, 10, 7, 2, 8, 5, 7, 15, 9, 6, 6, 6, 10, 12, 6, 12, 12, 15, 10, 6, 7, 8, 10, 7, 11, 6, 6, 3, 11, 12, 8, 3, 3, 12, 6, 9, 10, 12, 6, 7, 6, 12, 8, 7, 4, 5, 9, 5, 7, 14, 11, 6, 8, 9, 9, 9, 8, 6, 6, 7, 5, 9, 9, 9, 10, 8, 8, 7, 10, 4, 7, 9, 4, 7, 15, 7, 6, 7, 6, 10, 9, 8, 6, 9, 6, 11, 9, 12, 6, 10, 9, 11, 10, 6, 6, 8, 9, 3, 11, 8, 8, 5, 8, 12, 10, 8, 7, 7, 2, 5, 7, 4, 8, 16, 8, 8, 3, 10, 10, 5, 10, 8, 8, 6, 7, 8, 2, 9, 5, 6, 12, 9, 11, 10, 6, 6, 8, 8, 11, 10, 8, 11, 11, 6, 15, 9, 14, 11, 11, 13, 9, 5, 5, 9, 7, 8, 14, 6, 6, 7, 9, 10, 8, 9, 8, 6, 9, 8]\n",
      "Genrtn 207: mean = 7.93  stddev = 2.635355763459651  max = 19 [8, 9, 9, 12, 10, 3, 13, 10, 8, 8, 12, 5, 8, 7, 7, 9, 9, 8, 8, 12, 8, 6, 4, 9, 7, 9, 7, 8, 5, 8, 12, 3, 3, 7, 4, 7, 11, 7, 7, 7, 6, 6, 11, 10, 13, 7, 14, 9, 6, 5, 7, 9, 9, 5, 5, 8, 6, 11, 11, 10, 8, 8, 7, 10, 7, 6, 10, 10, 12, 2, 8, 8, 9, 7, 9, 9, 1, 9, 12, 8, 12, 9, 8, 9, 7, 8, 9, 9, 8, 11, 10, 9, 5, 8, 9, 9, 6, 7, 10, 10, 9, 9, 3, 8, 5, 8, 4, 8, 8, 8, 8, 10, 2, 14, 11, 5, 6, 12, 10, 9, 5, 7, 7, 7, 6, 19, 3, 9, 5, 13, 6, 9, 7, 4, 8, 8, 9, 8, 7, 5, 14, 8, 12, 6, 7, 9, 7, 9, 4, 11, 5, 3, 10, 11, 2, 9, 9, 11, 6, 5, 11, 7, 7, 7, 5, 8, 6, 8, 4, 12, 9, 12, 6, 10, 6, 7, 9, 7, 9, 3, 5, 5, 10, 7, 8, 7, 5, 9, 6, 6, 7, 7, 8, 9, 7, 8, 5, 11, 8, 13]\n",
      "Genrtn 208: mean = 7.955  stddev = 2.7245137180788794  max = 17 [12, 10, 12, 9, 7, 9, 4, 6, 11, 11, 8, 8, 6, 8, 10, 6, 7, 10, 4, 15, 10, 9, 7, 12, 9, 7, 3, 8, 9, 11, 13, 10, 7, 10, 10, 7, 12, 10, 8, 7, 9, 5, 5, 5, 15, 12, 8, 12, 15, 10, 8, 9, 6, 7, 9, 8, 2, 7, 9, 17, 6, 6, 5, 7, 4, 6, 6, 8, 9, 5, 8, 7, 10, 5, 8, 6, 9, 12, 11, 4, 10, 10, 11, 6, 5, 10, 10, 3, 7, 8, 7, 8, 10, 4, 3, 6, 6, 6, 10, 8, 11, 5, 10, 8, 4, 8, 8, 8, 9, 9, 5, 15, 8, 4, 6, 5, 5, 8, 6, 9, 6, 6, 7, 8, 6, 7, 8, 12, 6, 4, 4, 8, 12, 7, 7, 13, 7, 7, 9, 7, 8, 8, 5, 8, 10, 6, 5, 3, 8, 5, 10, 6, 7, 9, 12, 6, 8, 8, 6, 4, 5, 8, 12, 4, 10, 7, 11, 10, 8, 14, 9, 5, 9, 5, 7, 9, 10, 5, 13, 14, 9, 2, 7, 10, 8, 13, 8, 7, 7, 8, 7, 4, 9, 6, 6, 7, 10, 5, 7, 12]\n",
      "Genrtn 209: mean = 7.96  stddev = 2.622670394845681  max = 16 [6, 8, 8, 9, 10, 9, 11, 4, 11, 11, 5, 6, 9, 4, 7, 7, 12, 4, 5, 9, 4, 7, 4, 11, 8, 7, 8, 11, 10, 8, 10, 7, 8, 5, 7, 5, 9, 12, 7, 7, 5, 7, 8, 4, 11, 9, 6, 6, 10, 4, 8, 6, 10, 5, 6, 9, 8, 11, 6, 8, 10, 11, 8, 8, 4, 9, 10, 8, 5, 12, 7, 8, 4, 7, 5, 12, 4, 7, 10, 10, 7, 10, 8, 11, 8, 12, 12, 6, 6, 11, 7, 7, 14, 5, 8, 3, 6, 8, 5, 10, 7, 9, 10, 8, 6, 11, 8, 11, 6, 13, 6, 9, 13, 7, 8, 8, 7, 12, 6, 6, 10, 14, 13, 9, 8, 9, 8, 9, 9, 6, 8, 5, 10, 4, 7, 3, 9, 10, 5, 14, 9, 7, 5, 5, 9, 9, 9, 8, 5, 4, 6, 10, 7, 10, 7, 5, 5, 7, 11, 5, 8, 6, 10, 2, 8, 13, 5, 8, 7, 6, 4, 5, 6, 10, 10, 6, 9, 12, 9, 5, 5, 9, 10, 4, 8, 11, 4, 4, 10, 10, 8, 14, 16, 11, 8, 5, 12, 8, 11, 11]\n",
      "Genrtn 210: mean = 7.73  stddev = 2.452977782206761  max = 14 [6, 7, 8, 6, 8, 9, 10, 5, 9, 10, 7, 6, 6, 9, 7, 8, 7, 9, 3, 7, 9, 9, 5, 8, 5, 6, 10, 12, 8, 7, 7, 9, 9, 6, 9, 7, 4, 8, 11, 5, 5, 13, 10, 6, 7, 10, 10, 9, 7, 11, 9, 9, 5, 12, 10, 5, 8, 9, 8, 8, 8, 13, 4, 13, 10, 9, 11, 9, 7, 7, 12, 9, 11, 5, 5, 5, 5, 9, 7, 5, 5, 7, 7, 4, 13, 9, 5, 6, 12, 6, 7, 10, 5, 5, 9, 6, 10, 5, 5, 5, 9, 10, 10, 4, 4, 5, 11, 4, 7, 8, 8, 4, 9, 6, 8, 7, 2, 8, 5, 8, 7, 9, 4, 8, 7, 4, 9, 12, 7, 7, 5, 14, 12, 9, 5, 9, 7, 7, 10, 10, 11, 8, 13, 7, 10, 9, 10, 7, 3, 11, 8, 9, 2, 8, 12, 9, 7, 13, 8, 9, 11, 12, 9, 9, 7, 5, 6, 7, 7, 7, 1, 10, 10, 7, 6, 7, 6, 7, 5, 7, 10, 5, 9, 9, 9, 7, 5, 11, 8, 5, 6, 6, 11, 8, 6, 3, 8, 6, 8, 10]\n",
      "Genrtn 211: mean = 8.07  stddev = 2.7358910797032836  max = 16 [5, 7, 8, 13, 2, 9, 7, 6, 7, 10, 7, 7, 8, 8, 7, 6, 5, 10, 9, 9, 11, 4, 12, 9, 7, 5, 7, 7, 8, 13, 10, 9, 6, 11, 11, 9, 12, 8, 7, 6, 10, 9, 10, 12, 11, 8, 7, 8, 7, 8, 9, 7, 7, 7, 7, 5, 13, 5, 8, 6, 6, 6, 11, 9, 6, 10, 9, 9, 3, 7, 8, 4, 5, 4, 10, 7, 6, 16, 5, 6, 14, 9, 8, 10, 9, 4, 10, 8, 10, 8, 5, 6, 4, 9, 14, 13, 10, 12, 9, 7, 7, 12, 5, 12, 10, 5, 8, 9, 11, 3, 7, 13, 4, 11, 10, 5, 8, 10, 13, 8, 4, 7, 9, 9, 11, 11, 14, 5, 7, 3, 10, 10, 6, 9, 15, 5, 8, 5, 7, 11, 3, 11, 9, 7, 12, 11, 3, 8, 9, 9, 11, 8, 13, 5, 5, 8, 8, 8, 8, 6, 5, 9, 8, 10, 8, 4, 8, 6, 9, 8, 10, 3, 7, 9, 4, 12, 6, 9, 7, 8, 6, 7, 10, 7, 6, 9, 4, 16, 6, 5, 9, 5, 7, 4, 11, 6, 11, 12, 4, 8]\n",
      "Genrtn 212: mean = 8.09  stddev = 2.6080452450063056  max = 17 [5, 6, 12, 8, 9, 13, 4, 11, 7, 9, 9, 7, 12, 9, 7, 12, 10, 8, 7, 6, 3, 9, 5, 9, 11, 5, 6, 11, 12, 6, 6, 8, 12, 7, 5, 5, 7, 12, 4, 2, 3, 9, 7, 9, 8, 8, 9, 7, 7, 9, 4, 5, 11, 6, 10, 13, 12, 5, 8, 7, 6, 7, 9, 10, 8, 13, 4, 8, 10, 9, 10, 6, 6, 11, 9, 10, 13, 8, 6, 8, 11, 8, 8, 11, 10, 11, 13, 8, 13, 6, 8, 6, 12, 5, 10, 6, 4, 7, 9, 11, 6, 5, 13, 8, 5, 6, 7, 7, 9, 11, 10, 7, 5, 5, 9, 8, 6, 4, 8, 9, 13, 5, 3, 7, 9, 9, 9, 8, 4, 9, 12, 5, 11, 7, 6, 2, 7, 9, 7, 9, 7, 11, 12, 9, 6, 7, 13, 6, 8, 7, 17, 8, 7, 16, 9, 10, 9, 9, 10, 6, 3, 8, 9, 7, 6, 6, 9, 10, 10, 6, 6, 7, 9, 7, 7, 7, 10, 3, 7, 9, 10, 8, 12, 9, 10, 8, 4, 9, 7, 9, 7, 7, 6, 8, 8, 11, 10, 10, 7, 5]\n",
      "Genrtn 213: mean = 7.825  stddev = 2.6672785756272255  max = 14 [6, 6, 9, 8, 10, 7, 7, 6, 10, 8, 4, 10, 7, 12, 12, 4, 10, 11, 7, 8, 8, 8, 9, 8, 7, 12, 6, 5, 8, 9, 9, 7, 5, 11, 5, 7, 6, 7, 6, 4, 5, 10, 4, 3, 4, 12, 7, 11, 13, 7, 7, 7, 9, 8, 8, 8, 9, 10, 6, 7, 8, 10, 7, 3, 8, 3, 5, 6, 4, 13, 11, 4, 4, 7, 7, 7, 7, 9, 7, 12, 4, 3, 12, 7, 9, 6, 6, 11, 5, 5, 12, 8, 10, 5, 6, 4, 3, 6, 9, 9, 6, 5, 6, 6, 8, 8, 4, 2, 4, 5, 7, 8, 6, 10, 7, 14, 10, 7, 13, 10, 7, 12, 3, 8, 9, 5, 12, 10, 6, 12, 6, 6, 9, 8, 12, 6, 9, 13, 8, 11, 8, 9, 5, 7, 6, 4, 9, 8, 11, 5, 8, 7, 10, 9, 4, 11, 5, 8, 6, 13, 4, 11, 8, 5, 9, 9, 7, 5, 3, 9, 8, 9, 9, 9, 14, 14, 11, 7, 7, 8, 12, 6, 9, 10, 9, 10, 8, 10, 4, 12, 7, 10, 10, 7, 13, 11, 9, 6, 6, 13]\n",
      "Genrtn 214: mean = 7.825  stddev = 2.912795049432761  max = 17 [12, 6, 9, 11, 10, 6, 10, 11, 8, 12, 6, 5, 7, 5, 5, 7, 9, 7, 12, 11, 12, 11, 10, 11, 8, 9, 4, 4, 9, 8, 14, 6, 5, 5, 11, 8, 8, 5, 4, 10, 10, 4, 6, 10, 6, 8, 12, 7, 10, 7, 11, 2, 10, 4, 8, 7, 11, 8, 6, 6, 4, 7, 5, 8, 1, 8, 6, 2, 4, 5, 4, 5, 4, 9, 8, 12, 3, 14, 8, 5, 8, 10, 6, 4, 6, 10, 12, 10, 10, 6, 5, 11, 10, 8, 17, 4, 6, 6, 4, 11, 12, 8, 6, 8, 5, 14, 12, 5, 10, 3, 8, 12, 8, 16, 13, 10, 9, 5, 9, 10, 4, 10, 4, 10, 5, 3, 11, 9, 11, 6, 10, 7, 8, 7, 7, 8, 6, 9, 6, 9, 4, 6, 8, 5, 9, 12, 6, 4, 9, 8, 6, 6, 7, 8, 6, 11, 8, 12, 11, 7, 4, 6, 14, 8, 7, 9, 7, 9, 9, 2, 7, 8, 4, 8, 6, 4, 12, 10, 13, 11, 9, 6, 3, 4, 7, 9, 6, 13, 7, 10, 8, 9, 6, 9, 4, 9, 5, 8, 7, 12]\n",
      "Genrtn 215: mean = 8.215  stddev = 2.5804602302690114  max = 16 [8, 11, 12, 3, 12, 8, 9, 13, 4, 7, 2, 11, 4, 9, 4, 9, 11, 8, 11, 8, 5, 7, 5, 8, 11, 8, 12, 12, 9, 4, 11, 8, 8, 7, 9, 4, 8, 4, 5, 9, 11, 5, 10, 9, 6, 4, 12, 6, 15, 8, 10, 9, 7, 4, 6, 8, 12, 9, 11, 7, 7, 5, 8, 7, 9, 7, 13, 8, 14, 7, 7, 9, 11, 4, 10, 6, 6, 12, 6, 9, 11, 8, 5, 5, 10, 7, 8, 10, 9, 10, 7, 8, 8, 10, 5, 12, 13, 11, 7, 5, 9, 6, 11, 5, 9, 7, 8, 11, 8, 13, 11, 11, 7, 11, 4, 9, 11, 11, 6, 10, 6, 8, 9, 5, 11, 16, 7, 5, 10, 7, 6, 9, 7, 7, 7, 6, 8, 7, 5, 9, 5, 7, 7, 7, 7, 5, 9, 7, 9, 10, 11, 4, 7, 10, 8, 7, 7, 7, 8, 9, 7, 9, 9, 13, 12, 5, 8, 6, 9, 12, 7, 10, 10, 8, 9, 10, 9, 7, 6, 5, 4, 13, 13, 12, 13, 9, 8, 5, 9, 10, 9, 5, 10, 7, 8, 5, 7, 5, 5, 10]\n",
      "Genrtn 216: mean = 8.065  stddev = 2.740579318319395  max = 18 [11, 8, 3, 5, 7, 3, 8, 5, 9, 7, 9, 6, 7, 7, 11, 4, 8, 8, 11, 9, 9, 9, 8, 9, 10, 5, 7, 9, 14, 13, 5, 5, 6, 8, 7, 7, 6, 7, 4, 8, 5, 8, 9, 5, 12, 6, 7, 4, 16, 9, 6, 12, 7, 8, 18, 9, 11, 9, 7, 13, 7, 9, 7, 7, 4, 7, 9, 9, 5, 9, 10, 14, 9, 5, 7, 8, 9, 12, 10, 12, 6, 10, 13, 6, 8, 9, 5, 9, 12, 9, 10, 5, 10, 12, 11, 11, 5, 9, 6, 6, 9, 12, 7, 11, 10, 8, 10, 8, 6, 6, 6, 6, 9, 4, 13, 9, 9, 6, 4, 6, 11, 7, 12, 5, 13, 9, 9, 9, 6, 7, 7, 6, 5, 6, 8, 6, 9, 3, 7, 12, 10, 7, 8, 15, 4, 12, 4, 14, 8, 7, 6, 8, 11, 6, 11, 11, 6, 5, 6, 13, 5, 6, 6, 10, 2, 5, 11, 4, 9, 7, 14, 8, 4, 12, 11, 7, 8, 6, 9, 7, 7, 10, 9, 6, 6, 10, 10, 7, 9, 5, 8, 6, 9, 4, 9, 7, 9, 9, 4, 6]\n",
      "Genrtn 217: mean = 8.64  stddev = 2.8160965892525773  max = 17 [9, 10, 4, 6, 11, 11, 9, 7, 7, 12, 10, 8, 8, 7, 6, 12, 9, 11, 12, 8, 10, 10, 7, 8, 5, 6, 10, 8, 6, 3, 5, 8, 8, 9, 4, 9, 10, 11, 6, 12, 13, 6, 9, 10, 12, 8, 2, 11, 4, 12, 8, 7, 14, 9, 9, 10, 7, 6, 9, 11, 12, 10, 6, 9, 7, 8, 8, 10, 4, 9, 4, 4, 7, 9, 6, 8, 8, 11, 11, 9, 13, 17, 10, 8, 6, 8, 9, 8, 5, 4, 10, 12, 6, 10, 14, 5, 13, 13, 9, 9, 17, 9, 9, 7, 14, 11, 4, 7, 6, 12, 14, 8, 7, 5, 17, 7, 15, 7, 14, 12, 10, 7, 9, 10, 6, 9, 8, 9, 7, 7, 4, 7, 6, 8, 8, 5, 7, 9, 5, 5, 9, 9, 8, 8, 6, 13, 7, 12, 6, 8, 8, 9, 7, 12, 9, 4, 7, 9, 8, 13, 9, 5, 12, 8, 10, 11, 9, 4, 12, 7, 9, 8, 11, 8, 9, 5, 11, 9, 10, 10, 7, 9, 8, 14, 9, 7, 11, 5, 9, 4, 12, 8, 9, 12, 4, 12, 4, 14, 6, 9]\n",
      "Genrtn 218: mean = 8.02  stddev = 2.7675982367388516  max = 16 [5, 10, 8, 5, 5, 10, 10, 3, 6, 10, 7, 9, 2, 10, 9, 7, 7, 14, 8, 11, 3, 5, 5, 9, 10, 12, 15, 8, 9, 15, 11, 9, 4, 9, 10, 10, 11, 12, 6, 6, 10, 8, 9, 11, 7, 6, 5, 9, 5, 2, 7, 5, 8, 11, 8, 9, 9, 8, 6, 5, 4, 7, 16, 8, 6, 1, 7, 13, 15, 7, 7, 7, 8, 7, 4, 11, 7, 3, 13, 5, 12, 12, 8, 5, 7, 10, 11, 4, 9, 9, 7, 9, 10, 5, 5, 6, 8, 4, 5, 5, 8, 9, 13, 7, 12, 7, 8, 10, 8, 13, 10, 6, 9, 8, 5, 6, 10, 9, 6, 8, 8, 4, 10, 11, 5, 6, 13, 9, 7, 10, 5, 4, 6, 11, 4, 8, 10, 11, 7, 9, 11, 6, 10, 7, 10, 8, 6, 9, 12, 10, 4, 7, 11, 12, 11, 4, 8, 7, 10, 11, 5, 13, 4, 9, 9, 9, 10, 8, 12, 6, 4, 5, 8, 11, 10, 7, 10, 9, 8, 5, 7, 3, 12, 6, 9, 7, 8, 6, 8, 8, 8, 6, 4, 11, 6, 8, 6, 7, 10, 8]\n",
      "Genrtn 219: mean = 7.915  stddev = 3.0802232061978887  max = 21 [8, 7, 9, 3, 10, 5, 12, 6, 10, 9, 7, 4, 6, 2, 2, 5, 12, 5, 4, 8, 6, 9, 4, 6, 6, 5, 13, 11, 9, 8, 11, 10, 11, 3, 2, 4, 5, 6, 10, 14, 8, 10, 6, 16, 8, 8, 10, 10, 9, 6, 7, 9, 5, 11, 8, 9, 6, 6, 9, 5, 4, 7, 8, 10, 10, 10, 11, 8, 7, 5, 11, 11, 3, 8, 16, 9, 14, 8, 5, 6, 9, 9, 15, 6, 6, 7, 12, 7, 6, 10, 2, 9, 12, 16, 8, 7, 7, 3, 6, 10, 7, 12, 2, 9, 5, 6, 7, 5, 6, 9, 6, 8, 4, 9, 8, 5, 7, 4, 12, 14, 6, 7, 12, 7, 4, 6, 8, 10, 9, 11, 5, 7, 5, 8, 9, 6, 8, 8, 10, 11, 5, 10, 6, 5, 15, 9, 5, 7, 10, 5, 3, 9, 8, 5, 12, 5, 8, 6, 10, 10, 10, 13, 7, 4, 7, 4, 13, 4, 14, 7, 6, 10, 7, 6, 6, 21, 12, 6, 8, 8, 8, 7, 11, 6, 10, 10, 7, 9, 7, 11, 9, 9, 9, 8, 3, 7, 10, 12, 3, 8]\n",
      "Genrtn 220: mean = 8.205  stddev = 2.8324856575100252  max = 18 [11, 10, 11, 8, 8, 13, 13, 9, 11, 5, 8, 9, 9, 6, 5, 6, 7, 8, 8, 7, 11, 12, 11, 7, 9, 3, 15, 6, 5, 6, 15, 8, 6, 7, 8, 9, 10, 5, 4, 10, 9, 8, 18, 9, 7, 14, 8, 9, 3, 5, 6, 7, 11, 9, 7, 6, 12, 8, 11, 8, 9, 6, 9, 9, 11, 8, 6, 7, 9, 9, 10, 12, 5, 11, 8, 12, 9, 4, 7, 10, 4, 6, 5, 6, 2, 9, 9, 10, 5, 8, 10, 8, 6, 11, 6, 16, 7, 8, 8, 12, 6, 11, 6, 10, 4, 8, 13, 6, 8, 12, 16, 9, 8, 8, 5, 8, 5, 7, 10, 9, 11, 6, 9, 9, 7, 10, 9, 7, 4, 9, 7, 5, 6, 7, 8, 6, 3, 10, 5, 7, 7, 15, 7, 6, 11, 4, 7, 8, 9, 7, 5, 10, 11, 5, 3, 9, 10, 8, 12, 12, 7, 8, 8, 4, 4, 6, 9, 11, 10, 10, 5, 10, 6, 5, 11, 8, 6, 12, 5, 12, 4, 6, 11, 7, 5, 9, 7, 11, 10, 7, 5, 8, 12, 9, 1, 8, 15, 6, 12, 10]\n",
      "Genrtn 221: mean = 7.965  stddev = 2.9434291226391034  max = 22 [10, 6, 14, 6, 10, 11, 12, 8, 10, 7, 11, 7, 13, 11, 6, 10, 5, 10, 5, 7, 13, 5, 8, 10, 2, 9, 3, 6, 6, 1, 13, 22, 6, 6, 4, 9, 9, 6, 9, 7, 5, 5, 9, 8, 6, 14, 12, 2, 5, 4, 10, 7, 8, 6, 10, 8, 9, 7, 12, 8, 4, 6, 9, 9, 6, 6, 10, 6, 5, 12, 5, 7, 8, 6, 5, 7, 11, 13, 8, 7, 8, 9, 3, 13, 9, 5, 12, 6, 7, 6, 12, 12, 12, 9, 10, 7, 8, 5, 7, 6, 10, 9, 14, 11, 7, 6, 2, 8, 10, 7, 10, 8, 10, 6, 11, 9, 10, 7, 9, 9, 9, 7, 8, 5, 6, 2, 12, 6, 8, 9, 9, 10, 5, 13, 8, 6, 7, 8, 6, 7, 7, 8, 6, 7, 7, 5, 6, 9, 11, 9, 5, 3, 6, 12, 4, 4, 6, 4, 9, 8, 9, 6, 8, 9, 9, 10, 9, 10, 12, 8, 8, 2, 8, 6, 6, 6, 5, 10, 7, 13, 5, 10, 14, 6, 8, 10, 12, 12, 4, 3, 10, 3, 6, 11, 12, 9, 6, 13, 7, 7]\n",
      "Genrtn 222: mean = 8.305  stddev = 2.891707972807766  max = 19 [9, 13, 11, 9, 4, 7, 8, 8, 7, 5, 5, 9, 5, 4, 7, 7, 10, 10, 7, 1, 7, 4, 6, 8, 13, 7, 8, 9, 9, 4, 5, 9, 11, 6, 7, 7, 9, 11, 5, 14, 11, 9, 7, 12, 10, 6, 8, 11, 7, 8, 13, 9, 11, 6, 10, 6, 7, 12, 13, 6, 7, 4, 9, 12, 14, 10, 8, 8, 12, 7, 10, 4, 11, 9, 8, 9, 10, 12, 8, 8, 12, 6, 19, 9, 10, 9, 8, 5, 5, 10, 4, 9, 9, 8, 4, 4, 9, 10, 7, 7, 9, 10, 12, 12, 13, 11, 6, 8, 4, 12, 4, 14, 13, 11, 7, 8, 13, 9, 6, 6, 13, 4, 7, 7, 9, 11, 11, 10, 10, 11, 8, 9, 8, 11, 14, 10, 11, 14, 11, 6, 4, 8, 11, 3, 9, 6, 6, 8, 11, 6, 11, 5, 9, 7, 8, 12, 9, 9, 12, 11, 10, 6, 5, 8, 5, 5, 7, 3, 4, 8, 14, 9, 7, 11, 10, 5, 7, 8, 8, 5, 12, 10, 7, 6, 4, 3, 8, 11, 9, 5, 4, 6, 1, 7, 9, 4, 8, 5, 10, 8]\n",
      "Genrtn 223: mean = 8.31  stddev = 2.640814268364968  max = 16 [5, 13, 8, 11, 11, 8, 7, 6, 7, 5, 11, 12, 5, 6, 8, 3, 14, 7, 8, 11, 5, 16, 5, 8, 10, 14, 8, 12, 8, 11, 7, 11, 4, 3, 8, 8, 7, 5, 8, 7, 10, 10, 8, 4, 10, 7, 12, 6, 8, 11, 9, 10, 7, 4, 12, 4, 5, 9, 5, 9, 8, 9, 13, 6, 7, 7, 4, 10, 7, 9, 8, 7, 9, 7, 8, 7, 9, 9, 9, 8, 8, 8, 10, 5, 10, 10, 10, 10, 8, 8, 7, 10, 7, 6, 10, 6, 7, 8, 9, 12, 8, 8, 13, 4, 5, 10, 4, 11, 9, 10, 9, 10, 10, 6, 8, 7, 8, 7, 5, 7, 6, 8, 6, 11, 10, 9, 5, 11, 9, 11, 5, 11, 6, 8, 6, 5, 5, 9, 9, 8, 10, 9, 8, 11, 10, 5, 6, 13, 5, 7, 12, 15, 8, 6, 8, 11, 10, 9, 4, 16, 9, 9, 8, 7, 6, 14, 6, 15, 7, 12, 5, 12, 11, 9, 11, 5, 11, 5, 6, 10, 6, 2, 11, 7, 12, 6, 9, 11, 7, 11, 7, 10, 7, 5, 8, 8, 12, 6, 6, 12]\n",
      "Genrtn 224: mean = 7.8  stddev = 2.9563490998188966  max = 15 [7, 7, 9, 7, 10, 14, 7, 9, 6, 9, 13, 9, 9, 5, 4, 10, 5, 5, 10, 6, 9, 9, 6, 10, 2, 6, 5, 8, 1, 5, 8, 15, 4, 10, 8, 8, 10, 7, 3, 5, 6, 10, 9, 5, 9, 12, 4, 12, 9, 8, 14, 7, 14, 7, 5, 5, 14, 7, 5, 6, 5, 7, 3, 6, 4, 11, 14, 12, 7, 9, 7, 7, 10, 3, 6, 9, 4, 6, 7, 7, 5, 13, 4, 7, 7, 5, 9, 11, 5, 10, 3, 5, 6, 5, 3, 11, 9, 6, 3, 7, 13, 8, 12, 10, 6, 13, 9, 7, 13, 12, 7, 11, 4, 7, 8, 6, 7, 5, 9, 7, 7, 6, 6, 11, 10, 7, 4, 13, 2, 7, 12, 9, 8, 7, 4, 9, 9, 9, 7, 10, 10, 14, 4, 6, 8, 8, 7, 6, 5, 11, 9, 9, 8, 7, 15, 5, 8, 4, 12, 8, 11, 7, 5, 8, 4, 6, 8, 9, 8, 8, 8, 9, 4, 14, 3, 10, 9, 11, 9, 10, 11, 12, 1, 6, 9, 7, 14, 7, 8, 6, 8, 6, 9, 7, 4, 8, 6, 6, 15, 8]\n",
      "Genrtn 225: mean = 8.165  stddev = 2.8085182926233543  max = 16 [6, 7, 8, 7, 13, 10, 10, 11, 9, 8, 5, 9, 5, 8, 6, 9, 9, 5, 4, 6, 8, 5, 7, 6, 13, 9, 4, 5, 5, 5, 12, 8, 8, 8, 8, 5, 7, 12, 8, 13, 9, 6, 5, 9, 10, 10, 8, 8, 8, 6, 4, 12, 11, 10, 5, 7, 7, 3, 11, 4, 8, 14, 13, 11, 8, 9, 8, 9, 5, 12, 5, 8, 11, 5, 11, 9, 7, 9, 14, 7, 8, 5, 12, 8, 8, 10, 9, 10, 3, 14, 7, 14, 6, 5, 11, 9, 10, 7, 7, 7, 8, 7, 4, 7, 2, 7, 6, 4, 10, 6, 9, 3, 11, 6, 6, 6, 8, 13, 12, 4, 9, 8, 3, 8, 11, 7, 5, 5, 11, 8, 7, 5, 9, 8, 10, 11, 8, 6, 12, 5, 14, 5, 12, 8, 8, 3, 8, 12, 13, 13, 6, 4, 8, 11, 6, 6, 9, 9, 6, 7, 7, 10, 8, 6, 4, 15, 13, 10, 7, 5, 9, 10, 9, 9, 6, 10, 14, 6, 9, 2, 9, 7, 10, 7, 8, 8, 9, 4, 10, 9, 12, 9, 9, 11, 11, 13, 16, 8, 8, 6]\n",
      "Genrtn 226: mean = 7.99  stddev = 3.128881589322293  max = 16 [9, 13, 8, 9, 10, 13, 5, 6, 9, 3, 12, 6, 4, 6, 7, 14, 6, 9, 4, 9, 10, 5, 10, 4, 8, 5, 11, 6, 7, 7, 8, 13, 9, 7, 4, 13, 6, 11, 3, 10, 7, 10, 11, 14, 13, 12, 12, 3, 10, 3, 10, 5, 11, 15, 4, 3, 7, 10, 6, 5, 15, 6, 9, 7, 10, 6, 9, 14, 8, 5, 10, 8, 6, 10, 7, 10, 6, 5, 13, 7, 8, 6, 5, 9, 11, 4, 10, 6, 11, 11, 5, 11, 7, 5, 10, 12, 6, 8, 10, 8, 11, 13, 14, 7, 8, 5, 7, 9, 11, 8, 6, 7, 12, 4, 5, 7, 4, 11, 4, 5, 5, 12, 8, 11, 7, 8, 5, 7, 10, 13, 5, 7, 2, 6, 7, 2, 8, 5, 10, 7, 9, 10, 8, 5, 7, 9, 4, 13, 11, 8, 8, 3, 12, 3, 5, 13, 10, 7, 7, 7, 10, 12, 7, 7, 4, 8, 4, 6, 12, 10, 15, 6, 1, 10, 10, 8, 10, 6, 3, 9, 7, 16, 13, 3, 11, 10, 11, 10, 10, 9, 9, 4, 4, 7, 6, 7, 3, 2, 8, 4]\n",
      "Genrtn 227: mean = 8.08  stddev = 2.905787328763067  max = 16 [7, 8, 3, 10, 4, 8, 6, 12, 7, 8, 6, 10, 4, 9, 9, 8, 5, 5, 5, 11, 8, 7, 5, 4, 11, 13, 13, 7, 9, 8, 10, 7, 15, 8, 7, 9, 4, 7, 7, 8, 5, 9, 4, 12, 11, 5, 8, 5, 6, 11, 9, 12, 10, 9, 10, 5, 8, 10, 11, 4, 6, 9, 11, 9, 7, 8, 3, 8, 12, 6, 6, 3, 6, 7, 4, 13, 13, 6, 9, 8, 6, 4, 7, 7, 6, 6, 8, 11, 9, 3, 7, 10, 9, 5, 6, 11, 5, 8, 14, 5, 13, 4, 7, 10, 8, 9, 8, 6, 5, 14, 16, 8, 2, 6, 5, 6, 13, 6, 6, 4, 6, 7, 9, 6, 5, 9, 13, 3, 10, 6, 10, 8, 9, 7, 12, 12, 6, 11, 12, 9, 5, 6, 7, 11, 9, 9, 10, 10, 10, 16, 9, 13, 7, 6, 10, 12, 9, 10, 13, 11, 5, 5, 3, 11, 9, 2, 6, 8, 12, 12, 9, 5, 13, 5, 5, 9, 5, 8, 11, 8, 8, 6, 11, 11, 8, 6, 10, 10, 6, 3, 11, 11, 12, 7, 5, 12, 9, 4, 9, 10]\n",
      "Genrtn 228: mean = 8.03  stddev = 2.6998333281889826  max = 17 [9, 8, 5, 7, 10, 6, 14, 11, 9, 11, 6, 5, 6, 6, 7, 10, 9, 12, 5, 7, 7, 4, 5, 5, 9, 10, 8, 17, 7, 10, 4, 9, 7, 7, 8, 8, 7, 9, 10, 6, 7, 3, 9, 7, 10, 5, 6, 4, 8, 9, 8, 5, 8, 6, 7, 9, 9, 7, 8, 10, 7, 7, 13, 10, 7, 13, 8, 7, 8, 11, 5, 7, 7, 7, 13, 10, 9, 7, 13, 6, 9, 10, 14, 4, 4, 7, 8, 9, 9, 10, 7, 7, 10, 8, 8, 12, 5, 5, 7, 11, 6, 7, 6, 6, 7, 5, 2, 10, 11, 9, 11, 3, 6, 11, 11, 8, 4, 9, 8, 10, 9, 8, 9, 1, 13, 4, 12, 7, 9, 7, 12, 13, 12, 9, 10, 10, 7, 8, 4, 7, 6, 6, 6, 12, 9, 7, 5, 4, 6, 6, 7, 6, 5, 9, 6, 8, 8, 6, 9, 2, 5, 13, 12, 11, 7, 12, 6, 6, 8, 6, 9, 14, 7, 5, 8, 7, 13, 6, 8, 6, 4, 7, 5, 14, 12, 7, 8, 13, 6, 8, 5, 6, 10, 11, 8, 10, 10, 10, 12, 13]\n",
      "Genrtn 229: mean = 8.11  stddev = 2.957684905462379  max = 20 [6, 4, 1, 7, 5, 12, 10, 6, 9, 6, 9, 3, 7, 20, 5, 6, 6, 9, 13, 5, 9, 9, 10, 2, 4, 7, 3, 9, 8, 7, 8, 10, 6, 7, 8, 10, 11, 7, 11, 10, 8, 7, 5, 7, 11, 13, 11, 11, 7, 7, 8, 7, 5, 10, 8, 11, 9, 12, 4, 12, 7, 8, 13, 11, 11, 7, 10, 3, 6, 7, 6, 12, 10, 11, 8, 7, 5, 9, 10, 11, 5, 11, 10, 6, 5, 8, 15, 3, 6, 8, 11, 9, 4, 5, 15, 12, 7, 10, 6, 7, 7, 10, 9, 3, 6, 10, 9, 6, 10, 7, 10, 15, 14, 10, 3, 13, 5, 8, 8, 10, 8, 6, 11, 3, 12, 6, 10, 4, 5, 8, 6, 7, 9, 9, 6, 10, 5, 10, 9, 5, 6, 10, 8, 7, 5, 6, 9, 10, 4, 10, 12, 6, 10, 6, 6, 8, 11, 9, 8, 7, 9, 6, 12, 12, 17, 10, 5, 6, 6, 8, 9, 8, 6, 4, 3, 7, 7, 12, 7, 6, 14, 13, 9, 9, 6, 10, 7, 3, 9, 7, 8, 7, 3, 8, 14, 8, 6, 11, 8, 9]\n",
      "Genrtn 230: mean = 7.855  stddev = 2.8799262143325826  max = 17 [6, 11, 11, 8, 6, 11, 11, 8, 7, 4, 9, 7, 9, 5, 12, 11, 6, 3, 8, 8, 10, 13, 5, 6, 7, 9, 9, 5, 7, 16, 7, 7, 14, 5, 7, 6, 6, 7, 9, 5, 8, 9, 12, 7, 4, 11, 4, 8, 3, 7, 7, 9, 9, 10, 7, 12, 8, 5, 9, 8, 7, 9, 10, 6, 8, 15, 6, 14, 7, 5, 13, 8, 13, 7, 8, 12, 7, 10, 6, 12, 9, 4, 14, 8, 8, 5, 9, 2, 10, 7, 12, 7, 8, 4, 10, 9, 5, 7, 5, 6, 7, 5, 5, 7, 4, 7, 8, 5, 6, 17, 8, 8, 9, 6, 8, 8, 9, 5, 8, 10, 6, 4, 15, 9, 6, 9, 17, 7, 12, 6, 10, 5, 4, 10, 6, 7, 7, 3, 9, 5, 7, 1, 4, 8, 7, 12, 7, 7, 11, 4, 7, 7, 5, 4, 5, 8, 12, 10, 9, 10, 6, 7, 6, 9, 6, 8, 9, 8, 7, 7, 8, 14, 7, 8, 7, 9, 7, 8, 3, 9, 7, 9, 13, 8, 7, 6, 4, 16, 3, 7, 6, 8, 7, 6, 8, 8, 9, 7, 3, 14]\n",
      "Genrtn 231: mean = 7.865  stddev = 2.794060665053642  max = 16 [13, 4, 11, 7, 8, 6, 4, 6, 5, 4, 11, 8, 9, 10, 7, 9, 11, 15, 4, 11, 10, 8, 6, 7, 10, 5, 8, 10, 7, 6, 7, 12, 8, 2, 7, 9, 7, 13, 6, 8, 7, 16, 8, 8, 11, 15, 10, 10, 8, 11, 11, 10, 11, 9, 6, 4, 7, 6, 9, 5, 5, 11, 5, 4, 2, 7, 3, 5, 9, 6, 10, 5, 5, 6, 5, 5, 8, 4, 4, 7, 11, 6, 7, 12, 10, 3, 9, 8, 5, 5, 10, 5, 16, 11, 4, 11, 10, 9, 8, 8, 6, 6, 9, 8, 9, 10, 6, 10, 9, 5, 5, 8, 11, 12, 10, 12, 7, 7, 7, 7, 4, 12, 8, 6, 12, 9, 3, 4, 4, 9, 8, 4, 7, 13, 7, 11, 6, 7, 12, 7, 9, 5, 9, 7, 7, 8, 8, 15, 6, 11, 10, 9, 6, 4, 7, 9, 6, 6, 8, 7, 13, 11, 7, 4, 7, 4, 9, 9, 12, 8, 11, 9, 7, 9, 11, 7, 7, 4, 12, 6, 13, 11, 8, 4, 10, 8, 6, 7, 4, 9, 9, 6, 9, 4, 4, 6, 7, 6, 10, 6]\n",
      "Genrtn 232: mean = 7.935  stddev = 2.6212163207183035  max = 16 [7, 8, 10, 8, 7, 10, 10, 5, 10, 9, 11, 8, 7, 8, 7, 9, 12, 5, 9, 1, 7, 7, 6, 3, 10, 7, 8, 9, 8, 5, 8, 5, 9, 8, 7, 10, 6, 6, 9, 7, 14, 5, 8, 8, 5, 8, 6, 7, 5, 11, 9, 7, 8, 3, 4, 6, 8, 9, 9, 5, 11, 5, 5, 12, 5, 15, 10, 6, 8, 8, 7, 4, 4, 3, 10, 12, 7, 3, 10, 6, 8, 11, 10, 10, 9, 8, 9, 3, 10, 8, 7, 12, 6, 4, 7, 9, 9, 10, 9, 9, 7, 16, 5, 10, 7, 10, 8, 4, 6, 12, 8, 4, 5, 6, 3, 13, 5, 8, 9, 8, 8, 6, 11, 7, 4, 10, 7, 11, 9, 9, 8, 7, 10, 11, 7, 4, 9, 8, 5, 8, 12, 9, 9, 6, 3, 12, 9, 2, 10, 11, 9, 11, 8, 6, 10, 7, 3, 7, 5, 7, 9, 8, 8, 2, 11, 9, 7, 7, 6, 7, 8, 9, 5, 11, 9, 12, 10, 9, 5, 8, 11, 11, 11, 16, 4, 11, 11, 11, 6, 9, 9, 7, 12, 7, 9, 7, 9, 9, 11, 7]\n",
      "Genrtn 233: mean = 7.645  stddev = 2.9118679571711352  max = 19 [6, 9, 7, 7, 5, 5, 3, 7, 9, 14, 11, 8, 3, 5, 7, 7, 4, 15, 7, 7, 8, 5, 9, 8, 7, 10, 7, 6, 7, 6, 10, 19, 9, 9, 6, 12, 7, 6, 6, 2, 6, 6, 9, 7, 7, 8, 4, 6, 10, 6, 9, 11, 7, 5, 9, 10, 4, 7, 7, 5, 9, 10, 3, 7, 8, 9, 10, 7, 10, 14, 7, 8, 8, 9, 9, 9, 10, 8, 4, 3, 4, 5, 7, 10, 3, 9, 11, 9, 4, 9, 4, 7, 6, 2, 5, 9, 4, 8, 6, 6, 3, 9, 7, 9, 6, 7, 8, 13, 11, 6, 6, 10, 7, 11, 6, 9, 8, 7, 8, 9, 17, 8, 3, 8, 11, 4, 6, 6, 4, 7, 6, 9, 9, 4, 6, 11, 7, 4, 11, 5, 6, 15, 8, 5, 5, 5, 11, 8, 6, 11, 7, 14, 9, 6, 2, 11, 10, 10, 12, 5, 12, 5, 8, 10, 4, 4, 14, 9, 5, 13, 8, 11, 8, 9, 12, 8, 9, 7, 5, 13, 7, 8, 1, 2, 7, 10, 7, 5, 9, 9, 6, 13, 9, 9, 6, 6, 7, 12, 8, 4]\n",
      "Genrtn 234: mean = 8.01  stddev = 2.754977313881187  max = 18 [7, 9, 6, 8, 5, 14, 13, 11, 5, 8, 6, 8, 10, 7, 9, 3, 9, 5, 2, 7, 4, 5, 7, 9, 7, 12, 10, 7, 10, 5, 11, 6, 7, 8, 6, 10, 5, 14, 4, 9, 11, 10, 4, 10, 15, 3, 11, 9, 7, 6, 2, 7, 10, 11, 8, 10, 7, 6, 7, 9, 8, 8, 6, 7, 11, 8, 6, 6, 7, 7, 14, 10, 5, 9, 5, 8, 8, 3, 10, 7, 9, 8, 6, 5, 8, 13, 5, 5, 12, 9, 9, 12, 6, 6, 12, 11, 12, 4, 11, 9, 10, 13, 11, 8, 7, 9, 8, 5, 4, 10, 8, 10, 11, 5, 9, 5, 6, 7, 9, 7, 9, 11, 9, 8, 3, 12, 8, 10, 6, 9, 7, 8, 7, 12, 11, 8, 9, 12, 10, 6, 6, 5, 7, 8, 7, 5, 12, 7, 2, 5, 18, 9, 6, 12, 8, 9, 10, 2, 4, 10, 11, 10, 10, 4, 7, 7, 8, 9, 3, 13, 10, 7, 7, 7, 7, 8, 5, 13, 8, 7, 7, 6, 4, 9, 9, 11, 7, 6, 11, 7, 11, 8, 4, 7, 7, 4, 7, 11, 8, 12]\n",
      "Genrtn 235: mean = 8.12  stddev = 2.9249957264926048  max = 16 [14, 6, 4, 10, 9, 11, 9, 5, 8, 10, 9, 11, 2, 8, 5, 4, 8, 7, 7, 15, 4, 7, 6, 8, 9, 8, 3, 6, 8, 12, 8, 11, 16, 5, 13, 3, 4, 6, 12, 8, 8, 10, 8, 7, 6, 12, 6, 8, 13, 3, 5, 12, 7, 9, 6, 12, 7, 8, 6, 7, 10, 5, 10, 7, 11, 10, 7, 7, 8, 10, 9, 7, 1, 1, 14, 6, 10, 7, 2, 4, 11, 7, 11, 10, 7, 10, 11, 6, 9, 14, 6, 12, 11, 6, 13, 8, 10, 5, 10, 9, 7, 13, 9, 11, 13, 12, 7, 7, 5, 8, 12, 14, 4, 5, 8, 9, 3, 10, 12, 12, 10, 15, 9, 9, 9, 8, 3, 10, 12, 6, 6, 9, 13, 8, 6, 9, 6, 6, 9, 6, 6, 11, 9, 6, 5, 14, 5, 6, 6, 13, 8, 6, 8, 6, 5, 9, 11, 9, 7, 7, 5, 9, 4, 8, 11, 6, 7, 7, 9, 7, 11, 4, 8, 10, 12, 5, 7, 4, 9, 11, 11, 9, 11, 10, 6, 7, 10, 7, 4, 8, 9, 7, 5, 7, 3, 7, 11, 9, 7, 4]\n",
      "Genrtn 236: mean = 8.15  stddev = 2.9694275542602484  max = 17 [9, 9, 4, 8, 7, 11, 5, 9, 11, 8, 5, 3, 15, 7, 7, 7, 6, 7, 10, 4, 11, 7, 7, 12, 12, 7, 6, 14, 3, 15, 7, 5, 6, 10, 12, 6, 10, 3, 8, 16, 5, 7, 11, 7, 10, 7, 8, 9, 5, 6, 7, 6, 10, 7, 10, 4, 5, 13, 12, 8, 6, 10, 11, 6, 10, 4, 17, 5, 11, 4, 8, 3, 10, 9, 7, 3, 15, 14, 5, 9, 7, 3, 11, 8, 7, 8, 9, 4, 5, 6, 9, 6, 8, 8, 10, 7, 7, 9, 9, 8, 5, 10, 10, 11, 11, 8, 3, 8, 10, 6, 12, 5, 7, 12, 9, 5, 9, 9, 10, 10, 7, 7, 8, 9, 6, 5, 5, 4, 5, 7, 9, 7, 15, 11, 7, 5, 4, 5, 12, 6, 14, 6, 11, 11, 6, 4, 11, 13, 13, 7, 15, 12, 10, 3, 7, 7, 6, 9, 11, 7, 10, 13, 6, 10, 8, 8, 7, 6, 10, 12, 12, 6, 11, 5, 13, 9, 7, 9, 10, 5, 6, 10, 7, 4, 6, 5, 5, 10, 7, 9, 4, 9, 6, 11, 12, 10, 9, 12, 5, 7]\n",
      "Genrtn 237: mean = 8.315  stddev = 3.0733979566596967  max = 17 [7, 12, 7, 12, 5, 6, 8, 9, 12, 12, 10, 10, 8, 6, 12, 9, 11, 7, 16, 4, 4, 13, 10, 7, 9, 5, 1, 9, 12, 8, 11, 5, 8, 8, 5, 5, 8, 11, 12, 4, 6, 12, 11, 10, 10, 15, 12, 3, 12, 7, 7, 9, 6, 9, 14, 5, 12, 8, 8, 8, 2, 6, 8, 13, 8, 7, 7, 4, 6, 7, 7, 8, 10, 6, 10, 14, 3, 15, 14, 7, 8, 6, 4, 9, 11, 6, 2, 7, 4, 11, 8, 11, 11, 9, 7, 5, 6, 2, 8, 9, 6, 10, 9, 7, 10, 8, 5, 8, 13, 6, 4, 11, 9, 6, 7, 8, 5, 5, 2, 11, 5, 5, 4, 8, 8, 4, 10, 7, 10, 10, 8, 3, 5, 9, 10, 7, 8, 17, 13, 9, 11, 13, 5, 11, 6, 9, 7, 10, 5, 7, 5, 4, 8, 14, 6, 5, 10, 11, 7, 12, 6, 5, 10, 13, 6, 11, 11, 10, 15, 9, 10, 12, 7, 6, 9, 9, 5, 5, 10, 13, 9, 5, 8, 6, 6, 10, 8, 11, 14, 11, 11, 12, 6, 8, 7, 7, 4, 11, 13, 10]\n",
      "Genrtn 238: mean = 8.17  stddev = 2.976759983606337  max = 18 [8, 14, 8, 8, 9, 2, 9, 3, 10, 10, 6, 6, 14, 10, 5, 2, 7, 12, 3, 9, 10, 7, 8, 12, 15, 8, 6, 10, 8, 3, 6, 10, 3, 9, 12, 10, 3, 4, 12, 10, 10, 5, 8, 14, 7, 9, 11, 13, 9, 11, 10, 6, 9, 9, 4, 12, 8, 8, 6, 8, 4, 7, 7, 6, 10, 9, 7, 8, 13, 6, 5, 6, 7, 10, 15, 9, 9, 5, 5, 5, 6, 7, 11, 6, 5, 4, 9, 10, 3, 10, 10, 7, 12, 11, 2, 12, 6, 8, 8, 12, 8, 8, 5, 4, 7, 2, 5, 5, 10, 9, 7, 7, 4, 11, 18, 9, 10, 18, 12, 7, 5, 5, 13, 12, 9, 6, 8, 8, 12, 8, 10, 10, 8, 13, 9, 5, 13, 7, 13, 11, 6, 7, 11, 10, 12, 7, 4, 10, 10, 8, 10, 9, 7, 8, 10, 8, 8, 6, 8, 5, 3, 6, 8, 5, 7, 8, 10, 8, 7, 8, 10, 9, 7, 5, 15, 3, 10, 9, 8, 9, 7, 8, 7, 7, 8, 6, 3, 11, 8, 12, 10, 10, 11, 7, 7, 7, 3, 6, 8, 8]\n",
      "Genrtn 239: mean = 8.175  stddev = 2.8007811410390495  max = 17 [7, 10, 9, 7, 5, 5, 7, 11, 11, 9, 10, 8, 5, 8, 8, 10, 4, 11, 9, 6, 13, 10, 15, 8, 11, 13, 9, 6, 5, 8, 10, 6, 10, 10, 15, 10, 8, 8, 8, 4, 9, 14, 8, 8, 8, 6, 5, 5, 14, 7, 7, 8, 9, 4, 9, 12, 10, 8, 7, 4, 7, 5, 9, 5, 12, 6, 9, 14, 7, 10, 3, 7, 13, 13, 8, 12, 5, 9, 6, 10, 4, 8, 5, 5, 7, 8, 8, 2, 6, 10, 8, 6, 11, 7, 8, 8, 6, 7, 12, 7, 17, 6, 10, 16, 5, 9, 8, 11, 16, 6, 13, 11, 5, 5, 2, 7, 11, 8, 4, 8, 10, 10, 6, 6, 7, 7, 9, 11, 8, 6, 9, 9, 1, 9, 4, 4, 6, 7, 4, 11, 6, 5, 4, 9, 9, 10, 6, 11, 11, 16, 7, 8, 5, 8, 10, 9, 8, 7, 11, 10, 5, 12, 10, 7, 7, 11, 8, 12, 4, 8, 8, 7, 9, 8, 7, 13, 9, 9, 9, 6, 10, 11, 6, 7, 7, 7, 7, 10, 9, 8, 8, 7, 7, 5, 10, 6, 7, 7, 5, 8]\n",
      "Genrtn 240: mean = 8.03  stddev = 2.922173848353311  max = 16 [11, 8, 8, 8, 3, 8, 10, 7, 11, 11, 4, 6, 8, 6, 6, 10, 9, 10, 7, 8, 4, 13, 8, 4, 11, 5, 8, 8, 16, 7, 6, 5, 7, 5, 6, 9, 5, 8, 7, 11, 6, 9, 10, 6, 5, 9, 5, 7, 8, 9, 8, 9, 14, 4, 6, 9, 9, 6, 3, 13, 4, 10, 10, 9, 13, 8, 13, 8, 12, 11, 3, 7, 9, 12, 8, 8, 6, 11, 5, 15, 14, 6, 8, 12, 12, 5, 12, 11, 7, 13, 12, 15, 7, 7, 8, 13, 6, 5, 8, 7, 5, 10, 5, 4, 6, 9, 5, 7, 13, 13, 8, 12, 7, 9, 5, 7, 2, 10, 9, 13, 9, 8, 7, 8, 6, 9, 9, 7, 7, 4, 5, 4, 3, 8, 4, 8, 11, 13, 4, 9, 13, 7, 15, 7, 7, 8, 6, 7, 9, 7, 5, 6, 3, 10, 6, 10, 8, 4, 7, 11, 12, 4, 3, 7, 7, 8, 9, 10, 4, 9, 10, 3, 8, 8, 4, 6, 7, 10, 7, 6, 12, 12, 5, 9, 6, 6, 8, 8, 7, 2, 7, 11, 6, 13, 4, 12, 12, 10, 8, 11]\n",
      "Genrtn 241: mean = 8.21  stddev = 2.7469801601030905  max = 15 [6, 9, 6, 8, 8, 10, 4, 12, 10, 7, 5, 6, 12, 11, 5, 7, 9, 11, 9, 8, 6, 7, 6, 7, 4, 7, 9, 8, 2, 7, 7, 11, 12, 9, 7, 6, 3, 13, 7, 7, 11, 7, 15, 7, 12, 6, 10, 11, 10, 7, 7, 12, 4, 4, 9, 8, 8, 11, 11, 10, 7, 5, 8, 5, 10, 8, 10, 10, 12, 8, 12, 9, 11, 13, 5, 5, 9, 10, 2, 6, 10, 7, 12, 9, 9, 6, 8, 6, 11, 10, 11, 4, 5, 12, 5, 10, 6, 7, 6, 3, 4, 9, 12, 14, 10, 14, 13, 11, 10, 4, 5, 7, 10, 7, 7, 14, 10, 7, 8, 8, 7, 12, 5, 9, 9, 7, 5, 13, 8, 6, 12, 10, 11, 8, 10, 6, 12, 6, 9, 3, 11, 11, 8, 8, 3, 3, 15, 7, 11, 7, 14, 4, 5, 7, 9, 6, 5, 5, 6, 8, 9, 7, 8, 6, 10, 7, 4, 6, 8, 9, 11, 10, 8, 9, 11, 10, 7, 8, 3, 10, 8, 10, 10, 6, 7, 12, 6, 9, 8, 8, 8, 7, 5, 11, 8, 9, 14, 10, 5, 5]\n",
      "Genrtn 242: mean = 8.11  stddev = 2.906527137323854  max = 19 [8, 10, 5, 10, 9, 6, 9, 11, 10, 5, 10, 8, 5, 5, 11, 8, 4, 4, 7, 13, 5, 7, 7, 7, 10, 7, 10, 6, 10, 13, 11, 8, 5, 7, 2, 11, 7, 6, 8, 12, 4, 4, 4, 9, 9, 9, 9, 7, 6, 6, 7, 9, 12, 7, 8, 8, 6, 10, 19, 7, 5, 7, 11, 3, 10, 11, 11, 8, 10, 4, 6, 8, 7, 4, 7, 16, 10, 6, 7, 13, 8, 10, 3, 6, 6, 4, 8, 6, 6, 5, 6, 13, 13, 7, 9, 9, 9, 6, 6, 8, 12, 9, 11, 11, 11, 6, 7, 9, 7, 10, 4, 11, 6, 8, 7, 9, 5, 8, 8, 12, 6, 5, 10, 9, 12, 12, 5, 5, 10, 9, 7, 3, 3, 5, 7, 12, 5, 7, 10, 7, 5, 10, 5, 6, 12, 8, 13, 8, 6, 12, 8, 12, 10, 16, 8, 14, 8, 7, 6, 13, 6, 11, 7, 6, 9, 4, 6, 11, 5, 4, 3, 11, 12, 6, 8, 14, 14, 11, 6, 8, 6, 6, 6, 12, 9, 7, 5, 9, 7, 7, 9, 2, 12, 6, 11, 10, 7, 10, 12, 11]\n",
      "Genrtn 243: mean = 7.685  stddev = 2.9044405657544448  max = 17 [10, 8, 7, 9, 15, 10, 10, 4, 7, 6, 14, 8, 5, 10, 3, 9, 6, 7, 9, 7, 12, 17, 7, 9, 10, 11, 11, 7, 11, 7, 4, 11, 9, 7, 10, 9, 7, 3, 8, 11, 4, 9, 6, 8, 12, 8, 4, 9, 4, 12, 13, 3, 6, 3, 8, 7, 9, 6, 11, 9, 8, 11, 10, 10, 13, 9, 8, 11, 6, 17, 4, 8, 5, 9, 7, 12, 5, 7, 8, 13, 9, 9, 5, 10, 6, 10, 7, 5, 9, 13, 8, 8, 6, 5, 10, 8, 9, 9, 5, 3, 6, 1, 8, 6, 3, 6, 2, 5, 4, 7, 12, 7, 7, 11, 13, 7, 9, 8, 6, 6, 7, 5, 8, 4, 7, 7, 7, 5, 9, 5, 11, 9, 4, 8, 8, 4, 6, 5, 5, 9, 9, 6, 5, 10, 7, 9, 13, 3, 4, 5, 10, 3, 7, 8, 5, 5, 8, 11, 4, 7, 10, 3, 4, 10, 13, 8, 10, 6, 13, 5, 3, 9, 5, 11, 9, 10, 5, 11, 9, 6, 6, 8, 7, 7, 16, 5, 7, 5, 9, 8, 6, 5, 5, 3, 9, 7, 6, 7, 5, 9]\n",
      "Genrtn 244: mean = 8.38  stddev = 2.843518946657469  max = 18 [11, 9, 7, 11, 5, 12, 12, 6, 6, 4, 8, 7, 9, 8, 11, 12, 11, 11, 8, 4, 9, 5, 8, 13, 9, 6, 2, 12, 9, 10, 11, 7, 7, 7, 10, 9, 9, 4, 5, 7, 11, 4, 9, 9, 9, 10, 11, 9, 7, 12, 15, 8, 10, 4, 7, 9, 11, 6, 7, 7, 6, 7, 13, 11, 7, 9, 5, 10, 9, 12, 5, 10, 5, 6, 6, 5, 8, 13, 13, 6, 8, 10, 9, 5, 7, 10, 11, 9, 7, 13, 13, 12, 8, 4, 13, 9, 11, 12, 12, 8, 6, 9, 13, 13, 9, 4, 12, 4, 10, 8, 11, 5, 13, 8, 12, 9, 11, 4, 7, 5, 6, 7, 10, 8, 3, 7, 4, 10, 9, 6, 6, 7, 14, 12, 7, 18, 8, 12, 7, 5, 9, 7, 7, 4, 10, 7, 4, 10, 9, 12, 12, 12, 11, 12, 11, 7, 7, 8, 7, 7, 9, 5, 5, 8, 3, 7, 8, 7, 9, 11, 9, 10, 2, 15, 6, 3, 9, 11, 5, 10, 8, 7, 9, 7, 11, 7, 6, 7, 7, 10, 5, 11, 8, 5, 10, 4, 8, 8, 3, 8]\n",
      "Genrtn 245: mean = 8.015  stddev = 3.1312577345213857  max = 17 [6, 10, 4, 6, 7, 2, 6, 10, 11, 7, 10, 6, 13, 7, 4, 6, 4, 11, 8, 8, 10, 6, 4, 5, 10, 14, 8, 5, 13, 8, 12, 5, 14, 3, 4, 7, 11, 7, 12, 9, 8, 10, 9, 12, 5, 10, 5, 11, 7, 3, 8, 9, 11, 14, 6, 8, 11, 8, 4, 6, 5, 7, 11, 4, 10, 7, 2, 9, 9, 11, 8, 9, 5, 9, 12, 12, 8, 14, 13, 4, 5, 6, 7, 14, 12, 12, 6, 5, 5, 4, 9, 8, 12, 10, 5, 6, 5, 5, 6, 2, 6, 6, 6, 7, 14, 5, 4, 6, 4, 9, 7, 4, 9, 11, 8, 7, 9, 4, 13, 10, 7, 10, 15, 5, 13, 6, 6, 7, 10, 5, 8, 2, 7, 17, 7, 11, 10, 5, 12, 15, 10, 12, 9, 7, 5, 10, 10, 6, 11, 5, 9, 6, 11, 11, 8, 5, 6, 7, 5, 10, 8, 8, 12, 8, 8, 11, 5, 4, 4, 12, 6, 4, 2, 6, 3, 13, 8, 3, 4, 9, 4, 8, 8, 14, 10, 9, 9, 8, 6, 9, 12, 12, 9, 8, 10, 9, 9, 11, 5, 14]\n",
      "Genrtn 246: mean = 7.995  stddev = 2.8008882519657936  max = 18 [4, 4, 8, 7, 9, 8, 8, 6, 7, 8, 9, 9, 4, 7, 10, 4, 4, 9, 4, 10, 10, 7, 9, 7, 3, 6, 5, 9, 4, 13, 12, 12, 5, 10, 10, 4, 14, 2, 12, 12, 10, 9, 12, 6, 11, 10, 6, 8, 5, 6, 6, 8, 13, 5, 7, 8, 7, 10, 4, 6, 8, 11, 9, 13, 7, 7, 7, 6, 6, 6, 6, 13, 13, 10, 5, 9, 6, 8, 6, 3, 11, 8, 5, 4, 8, 8, 7, 7, 9, 12, 5, 7, 9, 10, 11, 11, 5, 10, 7, 9, 6, 9, 7, 9, 9, 6, 5, 5, 7, 6, 5, 9, 14, 5, 5, 7, 12, 9, 9, 7, 13, 5, 15, 7, 10, 10, 10, 14, 9, 16, 12, 7, 6, 4, 4, 11, 7, 8, 9, 8, 9, 5, 10, 9, 7, 6, 11, 8, 9, 8, 7, 8, 11, 6, 11, 18, 4, 12, 4, 5, 9, 8, 8, 7, 10, 8, 11, 11, 7, 6, 7, 6, 4, 9, 13, 8, 9, 9, 6, 3, 12, 5, 10, 8, 9, 6, 10, 11, 9, 10, 4, 5, 3, 6, 7, 7, 5, 6, 8, 11]\n",
      "Genrtn 247: mean = 8.035  stddev = 2.8885593294928182  max = 17 [8, 8, 10, 6, 12, 6, 12, 5, 14, 3, 6, 8, 10, 13, 4, 13, 9, 9, 4, 5, 6, 4, 9, 8, 5, 8, 7, 9, 9, 10, 7, 4, 4, 10, 5, 13, 8, 6, 4, 5, 10, 6, 5, 9, 3, 9, 5, 5, 2, 7, 10, 7, 12, 9, 12, 10, 6, 4, 5, 8, 9, 7, 9, 6, 11, 6, 7, 12, 6, 8, 8, 6, 9, 6, 11, 7, 9, 10, 11, 8, 5, 6, 10, 6, 9, 11, 11, 9, 7, 8, 9, 4, 4, 4, 13, 13, 10, 9, 15, 7, 6, 5, 12, 7, 9, 9, 15, 12, 9, 9, 5, 6, 6, 6, 11, 2, 5, 9, 9, 6, 9, 9, 6, 6, 10, 8, 4, 7, 11, 8, 11, 10, 5, 11, 6, 9, 11, 8, 5, 9, 6, 9, 11, 8, 10, 5, 5, 8, 3, 7, 12, 11, 9, 7, 7, 10, 12, 10, 14, 9, 17, 7, 6, 8, 6, 13, 4, 10, 13, 9, 11, 6, 6, 10, 10, 8, 7, 11, 5, 6, 12, 9, 3, 17, 9, 4, 7, 3, 5, 8, 4, 6, 8, 8, 5, 8, 7, 9, 14, 8]\n",
      "Genrtn 248: mean = 8.035  stddev = 2.7484131785450305  max = 17 [5, 9, 7, 9, 14, 8, 5, 9, 10, 9, 7, 9, 4, 8, 8, 8, 11, 5, 7, 9, 9, 8, 7, 8, 9, 4, 8, 6, 10, 15, 8, 6, 9, 14, 12, 8, 10, 10, 8, 7, 7, 9, 7, 9, 6, 9, 6, 9, 14, 5, 10, 8, 8, 9, 10, 5, 6, 5, 9, 3, 6, 1, 7, 6, 8, 5, 9, 11, 9, 10, 8, 8, 8, 5, 11, 4, 10, 12, 4, 7, 10, 4, 13, 5, 15, 5, 6, 11, 8, 10, 7, 5, 8, 17, 8, 14, 7, 10, 9, 4, 17, 12, 6, 4, 11, 4, 10, 7, 4, 4, 6, 9, 8, 14, 9, 14, 3, 6, 10, 6, 6, 9, 3, 8, 8, 11, 9, 4, 9, 15, 4, 9, 8, 8, 11, 6, 9, 7, 7, 8, 9, 10, 8, 7, 6, 6, 4, 11, 13, 5, 5, 9, 7, 7, 6, 7, 5, 5, 12, 5, 5, 8, 10, 9, 8, 3, 7, 6, 8, 7, 5, 10, 11, 7, 9, 6, 10, 8, 11, 10, 7, 9, 8, 6, 8, 8, 8, 11, 12, 10, 8, 9, 7, 11, 6, 6, 5, 7, 8, 9]\n",
      "Genrtn 249: mean = 8.36  stddev = 2.9069571720271354  max = 18 [6, 6, 5, 4, 5, 2, 7, 9, 5, 12, 6, 9, 11, 10, 3, 8, 8, 10, 9, 14, 9, 3, 8, 8, 8, 5, 11, 7, 3, 6, 4, 8, 10, 7, 12, 6, 5, 9, 14, 7, 8, 11, 6, 6, 11, 7, 9, 12, 12, 8, 9, 11, 13, 10, 10, 8, 11, 12, 9, 14, 10, 7, 15, 5, 8, 9, 6, 18, 8, 7, 4, 5, 10, 6, 6, 11, 6, 10, 10, 11, 11, 8, 13, 12, 5, 10, 10, 8, 8, 5, 11, 7, 10, 8, 5, 8, 10, 6, 9, 11, 7, 11, 7, 2, 8, 5, 10, 10, 8, 4, 7, 14, 9, 11, 2, 10, 12, 6, 7, 10, 7, 9, 14, 7, 7, 8, 8, 3, 17, 7, 8, 5, 10, 11, 6, 6, 5, 12, 5, 4, 5, 5, 6, 5, 13, 9, 10, 9, 13, 5, 4, 12, 8, 9, 12, 8, 7, 6, 8, 8, 8, 6, 4, 6, 10, 9, 6, 12, 9, 9, 11, 9, 8, 7, 9, 9, 10, 11, 8, 8, 14, 15, 6, 9, 10, 11, 11, 7, 12, 8, 7, 9, 8, 6, 6, 4, 14, 9, 5, 8]\n",
      "Genrtn 250: mean = 8.065  stddev = 2.9649241137000453  max = 17 [8, 8, 12, 5, 14, 5, 9, 9, 11, 10, 7, 5, 11, 11, 9, 10, 9, 8, 9, 9, 4, 9, 6, 7, 8, 16, 14, 6, 6, 13, 7, 11, 7, 4, 7, 9, 8, 6, 4, 9, 7, 8, 9, 6, 4, 9, 6, 2, 9, 8, 10, 8, 11, 9, 8, 10, 4, 13, 8, 9, 11, 4, 8, 4, 9, 8, 6, 9, 4, 7, 8, 13, 5, 11, 6, 3, 8, 7, 15, 5, 9, 7, 8, 10, 11, 12, 9, 11, 8, 10, 6, 8, 3, 8, 5, 7, 11, 7, 10, 7, 9, 6, 15, 4, 10, 3, 6, 7, 3, 6, 7, 7, 9, 8, 7, 13, 7, 9, 9, 5, 4, 7, 5, 8, 6, 12, 12, 9, 8, 10, 5, 12, 9, 7, 11, 6, 2, 10, 5, 6, 7, 12, 17, 3, 6, 9, 5, 6, 8, 12, 14, 9, 7, 6, 12, 10, 7, 9, 12, 7, 12, 7, 8, 4, 7, 9, 7, 6, 3, 8, 14, 9, 8, 4, 12, 5, 15, 12, 5, 10, 8, 1, 11, 8, 10, 14, 10, 6, 4, 2, 6, 13, 8, 4, 5, 8, 6, 7, 9, 10]\n",
      "Genrtn 251: mean = 7.885  stddev = 2.748049308145689  max = 18 [13, 7, 8, 7, 11, 6, 6, 7, 9, 6, 18, 13, 7, 9, 7, 9, 9, 3, 6, 8, 9, 7, 10, 11, 10, 11, 7, 10, 7, 2, 7, 5, 6, 8, 5, 12, 5, 7, 9, 6, 6, 7, 9, 9, 6, 5, 6, 4, 6, 8, 3, 10, 9, 12, 8, 9, 6, 11, 11, 9, 7, 10, 5, 9, 9, 7, 2, 6, 5, 9, 4, 8, 10, 8, 5, 4, 10, 8, 8, 9, 10, 7, 8, 5, 6, 7, 2, 12, 5, 10, 5, 9, 2, 7, 10, 6, 11, 7, 6, 12, 5, 7, 8, 10, 8, 10, 7, 9, 9, 6, 7, 9, 11, 5, 10, 11, 10, 11, 7, 11, 6, 6, 7, 4, 11, 10, 12, 7, 9, 10, 9, 6, 5, 8, 5, 7, 7, 6, 8, 11, 10, 7, 7, 15, 6, 8, 10, 4, 10, 7, 5, 3, 3, 4, 8, 17, 13, 8, 11, 9, 6, 7, 11, 9, 12, 8, 7, 6, 7, 11, 6, 6, 5, 9, 8, 8, 9, 5, 2, 11, 9, 4, 11, 8, 6, 9, 3, 12, 13, 10, 7, 3, 7, 13, 8, 9, 5, 10, 6, 14]\n",
      "Genrtn 252: mean = 8.07  stddev = 2.9622795276610883  max = 17 [2, 8, 5, 8, 9, 7, 13, 8, 4, 8, 6, 8, 1, 6, 3, 9, 8, 8, 6, 17, 8, 7, 10, 8, 6, 6, 10, 6, 10, 8, 6, 7, 7, 6, 11, 12, 6, 8, 6, 12, 9, 8, 9, 8, 7, 9, 12, 6, 6, 5, 5, 5, 10, 12, 15, 9, 13, 7, 6, 5, 9, 10, 11, 2, 7, 9, 9, 12, 12, 5, 14, 8, 11, 6, 8, 6, 4, 10, 10, 7, 9, 9, 8, 3, 6, 9, 7, 8, 8, 7, 12, 9, 10, 8, 5, 5, 8, 12, 7, 4, 12, 5, 4, 6, 6, 6, 7, 10, 9, 6, 7, 6, 9, 5, 11, 10, 6, 5, 7, 10, 9, 12, 6, 7, 14, 3, 10, 8, 6, 7, 7, 8, 11, 6, 7, 10, 6, 12, 9, 5, 8, 8, 11, 10, 11, 5, 5, 9, 12, 4, 10, 12, 13, 13, 14, 8, 8, 10, 5, 7, 8, 10, 5, 12, 5, 9, 10, 4, 12, 15, 10, 9, 15, 10, 7, 7, 1, 14, 8, 5, 7, 3, 4, 7, 4, 8, 6, 15, 15, 4, 10, 15, 9, 6, 6, 6, 7, 6, 7, 6]\n",
      "Genrtn 253: mean = 7.795  stddev = 2.687559301671314  max = 18 [7, 5, 10, 10, 10, 11, 10, 7, 6, 2, 4, 8, 8, 8, 9, 9, 9, 5, 6, 8, 8, 8, 6, 8, 11, 11, 7, 9, 6, 4, 14, 6, 11, 12, 14, 8, 8, 11, 9, 8, 7, 5, 6, 4, 5, 7, 11, 9, 5, 3, 9, 7, 12, 14, 7, 8, 8, 5, 8, 9, 8, 4, 3, 7, 10, 3, 4, 2, 12, 10, 13, 10, 7, 10, 9, 9, 7, 9, 6, 5, 4, 9, 7, 3, 8, 7, 4, 5, 5, 10, 7, 6, 9, 7, 8, 13, 6, 4, 10, 7, 11, 7, 10, 6, 7, 6, 14, 8, 7, 5, 6, 3, 10, 6, 9, 8, 6, 3, 2, 5, 7, 7, 8, 7, 8, 7, 7, 7, 8, 7, 10, 11, 6, 4, 10, 12, 8, 13, 6, 8, 6, 10, 8, 7, 9, 9, 9, 8, 11, 11, 8, 11, 8, 8, 5, 10, 8, 7, 5, 9, 12, 12, 6, 7, 6, 7, 5, 10, 9, 18, 4, 2, 3, 10, 10, 11, 11, 11, 3, 10, 6, 10, 12, 8, 5, 4, 6, 9, 10, 8, 9, 7, 8, 11, 6, 6, 8, 8, 8, 9]\n",
      "Genrtn 254: mean = 8.06  stddev = 2.7470711676256223  max = 17 [4, 5, 8, 4, 6, 7, 7, 11, 6, 15, 9, 8, 7, 7, 9, 12, 12, 8, 9, 9, 4, 6, 9, 4, 11, 5, 7, 9, 9, 12, 8, 7, 4, 8, 11, 7, 6, 9, 7, 10, 6, 5, 6, 9, 15, 10, 7, 4, 7, 9, 5, 6, 5, 9, 7, 10, 7, 6, 7, 9, 10, 13, 10, 5, 12, 9, 9, 4, 10, 6, 7, 8, 9, 6, 10, 6, 6, 9, 6, 8, 9, 5, 6, 9, 7, 9, 9, 8, 13, 9, 5, 9, 12, 9, 8, 2, 5, 10, 6, 9, 8, 10, 3, 9, 11, 10, 1, 12, 7, 14, 10, 7, 7, 5, 7, 7, 17, 13, 9, 11, 5, 6, 12, 11, 5, 7, 12, 11, 4, 7, 13, 7, 5, 10, 5, 11, 10, 11, 3, 10, 7, 8, 4, 8, 9, 10, 15, 7, 11, 11, 11, 8, 10, 9, 7, 12, 5, 7, 6, 7, 3, 8, 5, 5, 7, 7, 9, 5, 5, 8, 8, 11, 11, 10, 8, 6, 6, 8, 6, 12, 8, 6, 12, 9, 12, 15, 4, 6, 14, 7, 7, 6, 9, 6, 6, 6, 5, 6, 10, 8]\n",
      "Genrtn 255: mean = 7.975  stddev = 2.504870256121063  max = 17 [6, 9, 7, 6, 7, 6, 4, 7, 9, 6, 7, 5, 6, 11, 6, 8, 7, 11, 6, 8, 5, 9, 8, 4, 6, 10, 12, 9, 15, 9, 5, 9, 10, 9, 9, 8, 8, 8, 11, 10, 11, 8, 9, 11, 7, 8, 7, 10, 11, 8, 7, 12, 8, 4, 9, 5, 10, 5, 4, 5, 4, 6, 4, 9, 6, 10, 9, 7, 5, 8, 6, 8, 7, 4, 11, 7, 11, 7, 11, 8, 7, 9, 11, 8, 10, 9, 7, 4, 9, 10, 5, 9, 6, 8, 10, 9, 8, 12, 6, 7, 10, 2, 8, 8, 12, 11, 9, 7, 17, 10, 9, 6, 9, 10, 11, 5, 8, 8, 6, 7, 5, 14, 8, 6, 9, 6, 10, 8, 7, 10, 11, 14, 10, 7, 8, 6, 9, 9, 9, 8, 7, 6, 7, 8, 7, 17, 8, 7, 12, 10, 3, 9, 5, 7, 6, 4, 7, 7, 13, 4, 5, 11, 8, 13, 8, 10, 5, 7, 9, 9, 9, 5, 6, 5, 7, 6, 6, 3, 7, 3, 7, 6, 9, 9, 11, 8, 10, 9, 15, 8, 7, 7, 7, 7, 6, 9, 8, 5, 7, 10]\n",
      "Genrtn 256: mean = 8.01  stddev = 2.605743655849516  max = 17 [8, 8, 6, 5, 7, 6, 12, 8, 9, 2, 10, 7, 8, 13, 9, 8, 13, 11, 10, 4, 6, 6, 7, 9, 4, 9, 8, 4, 6, 12, 12, 8, 5, 3, 10, 7, 12, 7, 10, 10, 10, 10, 5, 7, 4, 7, 7, 13, 7, 7, 4, 7, 8, 8, 9, 10, 7, 14, 7, 4, 7, 7, 9, 8, 6, 5, 8, 11, 10, 11, 8, 7, 12, 10, 7, 8, 11, 9, 13, 8, 10, 8, 6, 7, 6, 8, 5, 8, 5, 12, 12, 8, 9, 6, 7, 6, 4, 5, 8, 6, 7, 6, 5, 9, 8, 9, 11, 10, 10, 11, 5, 5, 9, 4, 5, 6, 8, 6, 6, 13, 6, 8, 15, 7, 7, 6, 9, 15, 9, 11, 2, 11, 9, 13, 7, 6, 9, 9, 9, 4, 6, 8, 7, 7, 5, 5, 10, 7, 9, 11, 11, 8, 7, 10, 11, 8, 11, 7, 11, 7, 8, 7, 6, 9, 9, 11, 6, 12, 9, 11, 8, 5, 13, 10, 7, 9, 8, 6, 6, 2, 4, 10, 9, 7, 4, 8, 7, 11, 9, 5, 6, 9, 8, 9, 5, 5, 17, 7, 9, 5]\n",
      "Genrtn 257: mean = 7.985  stddev = 2.9299786688643317  max = 15 [9, 4, 6, 10, 15, 9, 6, 14, 12, 9, 10, 6, 5, 7, 15, 7, 10, 5, 6, 9, 12, 11, 4, 6, 9, 7, 13, 3, 8, 6, 9, 5, 6, 13, 13, 8, 4, 6, 12, 8, 12, 12, 9, 4, 5, 7, 14, 5, 10, 8, 8, 7, 6, 8, 11, 10, 8, 6, 8, 5, 6, 5, 8, 14, 13, 6, 10, 7, 7, 9, 10, 12, 11, 6, 6, 8, 5, 13, 10, 10, 3, 6, 5, 7, 6, 11, 5, 4, 10, 4, 6, 8, 9, 8, 13, 6, 10, 7, 8, 10, 9, 8, 5, 8, 7, 8, 7, 5, 11, 12, 10, 11, 14, 9, 7, 10, 9, 13, 6, 3, 8, 8, 11, 6, 3, 13, 5, 7, 9, 15, 10, 12, 7, 7, 5, 4, 4, 6, 5, 10, 8, 8, 7, 13, 5, 10, 4, 4, 5, 11, 3, 13, 9, 4, 4, 6, 12, 12, 3, 7, 9, 6, 12, 9, 4, 10, 4, 11, 7, 5, 11, 7, 7, 4, 6, 10, 5, 11, 8, 5, 9, 4, 4, 5, 6, 6, 11, 10, 10, 4, 10, 5, 10, 7, 7, 5, 7, 9, 11, 9]\n",
      "Genrtn 258: mean = 7.985  stddev = 2.9924530071498197  max = 17 [8, 11, 5, 3, 7, 8, 9, 13, 10, 17, 6, 8, 7, 5, 8, 7, 9, 3, 7, 17, 8, 10, 14, 9, 3, 9, 10, 5, 7, 8, 12, 13, 7, 7, 13, 9, 8, 7, 10, 9, 8, 7, 7, 10, 8, 7, 7, 6, 8, 11, 5, 7, 6, 9, 2, 8, 7, 5, 10, 11, 8, 5, 6, 5, 3, 7, 7, 9, 7, 12, 6, 7, 10, 12, 9, 3, 7, 4, 5, 9, 7, 4, 11, 9, 15, 9, 10, 12, 15, 8, 3, 6, 6, 8, 7, 11, 13, 4, 13, 4, 6, 3, 9, 4, 9, 9, 10, 6, 9, 4, 4, 6, 6, 5, 9, 10, 9, 15, 7, 2, 10, 5, 13, 6, 9, 9, 5, 7, 8, 10, 6, 7, 9, 5, 7, 13, 9, 17, 4, 7, 7, 9, 10, 7, 3, 8, 5, 8, 9, 9, 10, 3, 9, 8, 8, 5, 8, 8, 6, 7, 11, 8, 14, 13, 9, 8, 7, 8, 7, 11, 5, 10, 4, 10, 5, 8, 9, 15, 11, 9, 5, 6, 5, 6, 13, 9, 8, 8, 5, 4, 11, 13, 6, 9, 7, 10, 11, 2, 5, 6]\n",
      "Genrtn 259: mean = 8.215  stddev = 3.0197309482799954  max = 19 [7, 5, 8, 6, 8, 7, 10, 4, 7, 6, 9, 8, 3, 9, 9, 4, 19, 7, 8, 6, 11, 6, 8, 7, 10, 8, 7, 9, 5, 6, 9, 5, 7, 2, 7, 17, 5, 7, 9, 6, 10, 6, 11, 9, 10, 8, 9, 6, 11, 10, 10, 10, 13, 5, 11, 16, 11, 6, 9, 10, 13, 10, 8, 7, 8, 7, 7, 6, 16, 9, 4, 14, 5, 3, 11, 6, 7, 10, 10, 9, 11, 5, 13, 9, 6, 11, 10, 11, 4, 7, 4, 5, 16, 10, 10, 11, 7, 6, 9, 8, 9, 4, 8, 7, 9, 8, 9, 6, 9, 4, 8, 8, 8, 8, 8, 9, 6, 9, 6, 1, 12, 7, 9, 16, 10, 7, 11, 7, 8, 10, 8, 7, 14, 5, 8, 11, 11, 8, 9, 12, 7, 8, 4, 1, 14, 8, 9, 12, 6, 7, 11, 7, 12, 7, 8, 11, 9, 10, 8, 11, 9, 6, 2, 5, 11, 6, 7, 2, 12, 7, 7, 6, 8, 6, 9, 10, 6, 4, 6, 5, 5, 17, 9, 10, 7, 5, 6, 9, 5, 12, 6, 10, 4, 9, 9, 7, 7, 14, 14, 5]\n",
      "Genrtn 260: mean = 7.935  stddev = 2.946315495665731  max = 15 [11, 8, 10, 5, 8, 4, 10, 2, 2, 5, 5, 3, 8, 1, 8, 5, 7, 8, 6, 7, 9, 13, 12, 11, 12, 9, 11, 11, 10, 3, 8, 9, 6, 8, 9, 10, 8, 8, 10, 6, 7, 7, 6, 12, 10, 11, 12, 6, 11, 7, 12, 8, 5, 9, 3, 13, 8, 8, 6, 9, 4, 7, 11, 15, 11, 4, 6, 2, 4, 7, 10, 10, 5, 8, 9, 7, 4, 3, 8, 8, 7, 3, 5, 4, 5, 10, 11, 12, 8, 7, 8, 7, 3, 3, 10, 10, 7, 7, 8, 10, 13, 9, 4, 7, 7, 9, 4, 7, 8, 7, 10, 15, 10, 9, 9, 6, 9, 6, 8, 3, 7, 6, 7, 8, 13, 9, 15, 4, 4, 14, 10, 8, 11, 5, 11, 9, 10, 9, 6, 7, 11, 8, 10, 7, 8, 5, 7, 6, 7, 7, 8, 6, 4, 4, 7, 11, 13, 5, 7, 10, 11, 5, 12, 15, 9, 14, 14, 7, 5, 9, 9, 7, 11, 6, 5, 8, 7, 9, 10, 9, 10, 5, 6, 11, 5, 7, 2, 11, 7, 9, 6, 6, 9, 10, 4, 14, 12, 3, 12, 8]\n",
      "Genrtn 261: mean = 7.71  stddev = 2.768736173780377  max = 17 [13, 4, 8, 17, 10, 10, 12, 6, 6, 8, 11, 8, 10, 5, 8, 6, 4, 2, 7, 4, 11, 8, 10, 6, 8, 7, 8, 5, 5, 5, 6, 15, 8, 11, 9, 7, 8, 11, 9, 10, 5, 10, 8, 7, 11, 16, 7, 5, 7, 5, 9, 4, 7, 10, 9, 7, 8, 5, 8, 8, 7, 7, 2, 3, 4, 10, 9, 4, 5, 8, 8, 7, 8, 11, 7, 11, 4, 11, 8, 12, 6, 3, 7, 8, 6, 6, 6, 8, 6, 7, 6, 10, 6, 5, 4, 7, 5, 7, 8, 6, 7, 6, 8, 8, 5, 4, 3, 6, 5, 6, 7, 3, 9, 8, 8, 5, 7, 7, 8, 7, 13, 10, 7, 5, 10, 11, 11, 6, 7, 6, 8, 5, 8, 14, 14, 11, 5, 14, 9, 9, 10, 7, 7, 17, 6, 6, 16, 8, 10, 6, 13, 9, 9, 11, 9, 10, 6, 10, 9, 7, 10, 4, 5, 5, 5, 5, 8, 6, 7, 6, 9, 8, 7, 6, 9, 10, 6, 10, 9, 8, 8, 2, 9, 8, 10, 4, 4, 10, 9, 7, 7, 9, 8, 4, 5, 7, 6, 9, 8, 14]\n",
      "Genrtn 262: mean = 8.045  stddev = 2.6651407092309403  max = 18 [13, 10, 7, 4, 5, 7, 5, 7, 8, 8, 9, 5, 6, 7, 5, 7, 10, 8, 17, 5, 5, 7, 7, 6, 6, 13, 5, 7, 12, 6, 10, 10, 10, 7, 3, 8, 10, 9, 11, 7, 6, 4, 3, 9, 10, 9, 7, 9, 8, 10, 10, 7, 10, 8, 8, 9, 6, 3, 7, 8, 9, 6, 10, 8, 2, 7, 6, 7, 9, 5, 12, 9, 7, 8, 6, 5, 6, 10, 6, 7, 8, 6, 7, 12, 15, 9, 10, 8, 4, 10, 7, 2, 6, 8, 8, 13, 7, 8, 9, 15, 10, 8, 8, 14, 8, 11, 8, 9, 10, 6, 11, 9, 10, 12, 12, 6, 13, 9, 8, 5, 5, 11, 7, 3, 8, 6, 7, 6, 7, 6, 9, 14, 5, 11, 10, 4, 7, 10, 13, 8, 7, 7, 4, 18, 4, 12, 5, 10, 11, 7, 10, 12, 9, 13, 5, 8, 9, 8, 7, 8, 6, 8, 6, 7, 7, 11, 8, 3, 10, 8, 7, 9, 11, 7, 8, 8, 8, 7, 4, 10, 7, 8, 10, 9, 12, 8, 10, 5, 9, 7, 7, 5, 8, 8, 8, 3, 7, 10, 8, 9]\n",
      "Genrtn 263: mean = 7.75  stddev = 2.9012928152808017  max = 18 [11, 8, 10, 9, 5, 7, 4, 8, 7, 10, 11, 3, 3, 11, 10, 7, 14, 5, 6, 11, 12, 6, 10, 5, 7, 10, 13, 7, 8, 3, 10, 7, 7, 8, 6, 7, 8, 6, 7, 8, 4, 10, 6, 5, 6, 15, 7, 7, 4, 5, 9, 11, 11, 8, 10, 7, 12, 4, 10, 16, 5, 10, 7, 4, 12, 11, 14, 4, 12, 4, 3, 10, 7, 5, 9, 9, 9, 10, 9, 9, 4, 8, 14, 8, 3, 9, 8, 3, 5, 3, 5, 8, 7, 6, 18, 4, 7, 8, 5, 11, 5, 4, 9, 3, 4, 6, 6, 2, 7, 7, 8, 8, 12, 9, 12, 8, 10, 6, 5, 4, 7, 4, 7, 6, 13, 5, 9, 7, 11, 7, 12, 7, 9, 7, 8, 9, 10, 6, 4, 7, 8, 11, 2, 4, 8, 12, 5, 8, 13, 6, 8, 6, 8, 7, 11, 12, 9, 3, 6, 3, 8, 8, 10, 6, 8, 8, 5, 7, 15, 8, 8, 8, 9, 10, 7, 7, 7, 6, 6, 9, 10, 3, 11, 5, 6, 9, 8, 10, 5, 4, 8, 7, 11, 12, 8, 6, 10, 7, 11, 10]\n",
      "Genrtn 264: mean = 8.03  stddev = 2.6323183698025585  max = 16 [8, 5, 4, 5, 5, 13, 7, 9, 10, 7, 11, 12, 10, 8, 8, 5, 10, 12, 6, 8, 11, 9, 11, 8, 6, 7, 5, 7, 2, 6, 11, 5, 6, 9, 7, 10, 6, 11, 11, 8, 8, 8, 10, 6, 10, 5, 6, 6, 6, 6, 7, 11, 7, 7, 7, 6, 5, 10, 3, 9, 12, 10, 15, 10, 5, 2, 8, 6, 10, 3, 8, 12, 12, 12, 7, 9, 4, 14, 5, 7, 8, 7, 14, 9, 10, 3, 11, 8, 8, 6, 7, 7, 8, 10, 6, 6, 10, 7, 2, 5, 8, 12, 10, 7, 6, 7, 13, 7, 7, 9, 5, 7, 6, 9, 7, 8, 9, 8, 14, 10, 16, 9, 9, 7, 9, 5, 9, 7, 6, 4, 11, 4, 10, 9, 9, 6, 7, 3, 8, 5, 11, 9, 7, 5, 15, 7, 7, 9, 12, 8, 7, 9, 9, 9, 12, 10, 5, 11, 12, 8, 6, 9, 7, 8, 9, 9, 10, 9, 9, 6, 7, 8, 9, 7, 7, 9, 12, 10, 12, 5, 5, 5, 6, 9, 7, 3, 9, 7, 7, 10, 4, 12, 4, 11, 9, 6, 6, 10, 10, 9]\n",
      "Genrtn 265: mean = 7.99  stddev = 2.747708135883431  max = 17 [13, 6, 4, 6, 11, 2, 4, 4, 8, 8, 4, 11, 10, 7, 11, 7, 7, 7, 9, 6, 7, 7, 4, 8, 9, 7, 11, 5, 5, 6, 12, 5, 10, 12, 8, 9, 9, 11, 10, 6, 3, 3, 15, 11, 9, 7, 10, 8, 11, 11, 6, 12, 5, 9, 10, 6, 10, 7, 8, 7, 4, 15, 6, 5, 9, 8, 6, 6, 8, 7, 8, 8, 3, 8, 10, 7, 6, 7, 6, 3, 7, 7, 8, 7, 4, 10, 14, 8, 6, 7, 16, 10, 11, 6, 10, 17, 7, 4, 11, 6, 4, 4, 8, 9, 6, 14, 11, 14, 9, 5, 9, 5, 4, 10, 7, 5, 12, 6, 6, 11, 9, 10, 6, 13, 5, 7, 10, 9, 2, 5, 9, 7, 4, 10, 11, 11, 9, 11, 11, 8, 6, 5, 11, 9, 9, 7, 5, 6, 10, 7, 8, 7, 2, 10, 7, 9, 9, 10, 10, 4, 11, 5, 9, 9, 7, 11, 11, 5, 4, 8, 7, 11, 10, 6, 8, 9, 9, 6, 11, 7, 9, 10, 10, 9, 6, 6, 6, 5, 9, 7, 11, 9, 8, 9, 8, 10, 5, 11, 10, 9]\n",
      "Genrtn 266: mean = 8.0  stddev = 3.0675723300355937  max = 17 [9, 11, 10, 5, 7, 13, 5, 7, 4, 12, 6, 10, 11, 9, 7, 3, 6, 3, 7, 11, 6, 8, 8, 8, 9, 6, 4, 5, 8, 7, 8, 9, 9, 8, 12, 7, 3, 6, 11, 11, 5, 12, 9, 7, 10, 5, 6, 7, 7, 8, 11, 9, 7, 5, 9, 9, 9, 12, 11, 8, 9, 10, 11, 13, 5, 9, 8, 9, 4, 6, 5, 7, 8, 8, 3, 10, 4, 12, 4, 12, 6, 11, 8, 15, 3, 7, 10, 12, 10, 8, 9, 6, 10, 7, 13, 5, 5, 6, 4, 5, 6, 10, 9, 2, 7, 13, 11, 6, 8, 6, 9, 14, 6, 5, 7, 4, 2, 3, 9, 9, 9, 4, 12, 7, 12, 11, 9, 10, 6, 8, 7, 14, 15, 5, 9, 16, 8, 9, 9, 3, 13, 7, 9, 9, 10, 9, 4, 9, 6, 6, 9, 7, 8, 7, 11, 2, 8, 4, 6, 9, 8, 8, 4, 5, 10, 9, 7, 13, 13, 5, 17, 11, 9, 3, 11, 11, 10, 13, 12, 9, 7, 5, 7, 5, 1, 4, 8, 7, 7, 4, 10, 2, 7, 10, 16, 13, 7, 5, 3, 10]\n",
      "Genrtn 267: mean = 8.03  stddev = 2.8929396813621953  max = 18 [8, 4, 11, 2, 8, 9, 13, 10, 6, 12, 10, 3, 11, 7, 8, 6, 4, 10, 12, 17, 9, 11, 3, 12, 8, 10, 4, 5, 13, 8, 5, 9, 5, 11, 8, 6, 9, 3, 5, 5, 16, 7, 11, 8, 11, 6, 5, 7, 4, 8, 8, 10, 11, 5, 8, 12, 7, 8, 9, 7, 9, 9, 6, 4, 7, 8, 5, 9, 10, 7, 5, 6, 8, 10, 6, 9, 7, 17, 11, 9, 4, 6, 8, 9, 5, 10, 11, 9, 3, 8, 10, 5, 7, 5, 10, 10, 6, 5, 7, 9, 6, 10, 7, 4, 8, 9, 2, 9, 9, 8, 6, 10, 13, 7, 8, 6, 9, 9, 9, 6, 6, 3, 10, 13, 4, 8, 11, 9, 11, 7, 11, 12, 9, 9, 9, 6, 12, 6, 4, 12, 18, 11, 5, 3, 9, 6, 9, 10, 4, 6, 8, 11, 6, 12, 6, 9, 10, 7, 10, 5, 4, 11, 12, 4, 9, 4, 5, 11, 9, 9, 9, 10, 2, 7, 6, 3, 13, 9, 7, 9, 7, 7, 12, 10, 7, 11, 5, 7, 8, 10, 7, 11, 8, 8, 5, 9, 11, 4, 7, 10]\n",
      "Genrtn 268: mean = 7.715  stddev = 2.711784467836631  max = 16 [7, 5, 14, 4, 8, 8, 5, 7, 7, 11, 13, 6, 8, 8, 3, 4, 9, 13, 7, 8, 3, 7, 9, 12, 7, 6, 6, 4, 7, 7, 11, 7, 14, 6, 5, 2, 7, 9, 10, 7, 9, 11, 7, 5, 8, 10, 11, 9, 6, 7, 12, 4, 8, 9, 8, 8, 5, 6, 8, 11, 8, 10, 6, 5, 8, 10, 8, 8, 9, 6, 4, 9, 4, 9, 10, 7, 6, 4, 4, 6, 7, 8, 11, 5, 7, 7, 8, 6, 11, 10, 8, 9, 11, 10, 3, 7, 11, 9, 3, 5, 14, 6, 8, 14, 5, 8, 6, 12, 5, 9, 12, 4, 8, 5, 12, 7, 13, 6, 5, 10, 9, 10, 6, 6, 6, 9, 6, 8, 8, 12, 10, 4, 8, 9, 8, 6, 3, 8, 14, 7, 5, 7, 4, 7, 6, 8, 4, 3, 8, 6, 4, 4, 10, 4, 8, 13, 7, 8, 14, 7, 10, 7, 5, 7, 8, 6, 5, 10, 7, 9, 7, 11, 4, 10, 10, 6, 9, 9, 11, 5, 8, 16, 7, 6, 9, 4, 11, 6, 14, 11, 11, 4, 8, 8, 5, 10, 7, 7, 6, 6]\n",
      "Genrtn 269: mean = 8.28  stddev = 2.83400776286869  max = 15 [5, 8, 9, 7, 13, 9, 14, 7, 11, 11, 6, 7, 8, 8, 6, 4, 6, 5, 6, 12, 10, 13, 12, 10, 14, 13, 9, 8, 13, 10, 8, 6, 13, 14, 11, 10, 10, 9, 9, 8, 9, 7, 9, 5, 7, 8, 8, 5, 11, 8, 14, 9, 8, 8, 10, 6, 6, 10, 9, 8, 7, 7, 12, 4, 7, 8, 9, 5, 9, 9, 15, 9, 7, 8, 10, 8, 7, 10, 5, 12, 6, 5, 10, 9, 9, 10, 0, 7, 9, 7, 10, 7, 6, 10, 5, 8, 7, 8, 11, 1, 8, 8, 9, 15, 13, 4, 8, 6, 4, 7, 5, 5, 10, 15, 8, 10, 5, 7, 11, 6, 7, 8, 14, 9, 6, 10, 9, 6, 12, 11, 11, 9, 5, 14, 5, 14, 2, 6, 5, 7, 6, 7, 7, 10, 7, 8, 11, 6, 10, 5, 7, 14, 4, 6, 10, 3, 9, 5, 11, 6, 12, 11, 6, 9, 1, 7, 5, 9, 4, 9, 12, 6, 7, 9, 8, 12, 6, 10, 5, 6, 5, 6, 11, 10, 7, 11, 11, 6, 8, 12, 7, 12, 5, 4, 7, 9, 9, 9, 9, 8]\n",
      "Genrtn 270: mean = 7.78  stddev = 2.6156452358834903  max = 18 [10, 3, 9, 11, 11, 7, 3, 12, 5, 13, 6, 10, 8, 9, 6, 5, 11, 5, 8, 7, 10, 6, 5, 8, 6, 8, 4, 7, 9, 11, 11, 12, 5, 10, 12, 6, 11, 8, 7, 4, 12, 6, 5, 6, 10, 8, 12, 10, 4, 7, 18, 8, 6, 7, 12, 5, 8, 2, 10, 11, 6, 13, 10, 8, 10, 7, 5, 8, 7, 5, 7, 13, 10, 8, 6, 7, 8, 4, 7, 8, 5, 9, 8, 7, 8, 15, 12, 9, 8, 3, 11, 10, 10, 11, 8, 7, 6, 9, 9, 5, 9, 11, 5, 12, 5, 8, 10, 9, 4, 9, 4, 9, 6, 8, 8, 10, 3, 6, 6, 9, 4, 5, 6, 9, 8, 7, 10, 12, 6, 9, 10, 7, 14, 8, 5, 8, 6, 9, 10, 8, 7, 8, 6, 7, 11, 10, 4, 5, 5, 7, 7, 8, 11, 6, 8, 8, 7, 8, 5, 6, 3, 10, 8, 13, 9, 5, 9, 7, 9, 4, 8, 5, 10, 9, 5, 5, 10, 5, 7, 8, 8, 8, 4, 7, 9, 11, 7, 8, 8, 5, 6, 10, 7, 9, 3, 3, 7, 5, 9, 4]\n",
      "Genrtn 271: mean = 8.03  stddev = 2.7765266071118426  max = 15 [6, 8, 12, 14, 6, 8, 9, 6, 9, 15, 7, 6, 12, 7, 10, 9, 6, 10, 10, 8, 4, 10, 3, 10, 9, 3, 6, 8, 9, 10, 6, 8, 8, 6, 8, 3, 10, 7, 5, 3, 7, 7, 12, 11, 8, 10, 12, 14, 11, 5, 9, 9, 6, 5, 8, 6, 5, 12, 8, 8, 9, 5, 1, 4, 12, 9, 13, 8, 3, 7, 9, 8, 5, 10, 7, 7, 9, 11, 10, 2, 7, 7, 12, 8, 12, 5, 9, 7, 14, 9, 7, 4, 10, 10, 8, 8, 10, 6, 10, 13, 10, 6, 13, 3, 7, 3, 5, 3, 12, 4, 8, 8, 8, 4, 9, 6, 9, 9, 12, 7, 7, 5, 4, 6, 10, 7, 9, 8, 10, 11, 10, 8, 5, 6, 8, 13, 8, 12, 3, 8, 9, 11, 6, 4, 10, 9, 9, 4, 8, 8, 5, 10, 8, 9, 12, 5, 11, 9, 8, 9, 9, 9, 4, 8, 7, 8, 7, 4, 8, 7, 9, 7, 9, 8, 11, 11, 3, 13, 10, 8, 6, 12, 12, 7, 9, 11, 4, 9, 15, 9, 4, 8, 8, 5, 10, 7, 12, 5, 10, 3]\n",
      "Genrtn 272: mean = 8.355  stddev = 3.052699624922177  max = 18 [9, 2, 17, 6, 5, 7, 8, 3, 6, 8, 3, 8, 9, 12, 12, 9, 9, 5, 8, 9, 14, 7, 9, 4, 9, 6, 4, 12, 3, 11, 14, 8, 13, 4, 10, 7, 6, 11, 11, 8, 11, 3, 9, 12, 8, 10, 4, 11, 11, 10, 12, 6, 6, 8, 11, 8, 11, 15, 9, 8, 6, 10, 8, 8, 9, 13, 8, 12, 11, 6, 10, 15, 8, 5, 11, 5, 5, 10, 11, 6, 5, 11, 12, 8, 14, 7, 2, 10, 7, 8, 7, 5, 9, 3, 13, 4, 7, 7, 7, 8, 7, 4, 7, 4, 7, 5, 10, 10, 7, 7, 4, 5, 8, 8, 5, 9, 4, 9, 6, 8, 9, 5, 4, 8, 8, 8, 9, 6, 12, 10, 4, 11, 9, 6, 10, 7, 9, 13, 8, 7, 8, 10, 5, 12, 10, 10, 5, 7, 5, 16, 6, 14, 6, 5, 9, 7, 6, 6, 7, 13, 9, 10, 4, 15, 12, 10, 9, 17, 12, 7, 8, 5, 7, 7, 9, 12, 7, 8, 10, 9, 13, 6, 9, 9, 8, 18, 11, 8, 13, 10, 6, 9, 4, 9, 9, 8, 4, 12, 8, 6]\n",
      "Genrtn 273: mean = 7.705  stddev = 2.8632106104860675  max = 16 [9, 7, 7, 5, 5, 11, 9, 6, 13, 9, 5, 5, 9, 7, 10, 9, 5, 5, 8, 6, 7, 5, 12, 11, 16, 7, 5, 6, 8, 8, 15, 4, 3, 9, 6, 12, 9, 5, 10, 14, 13, 10, 8, 6, 6, 9, 8, 6, 9, 12, 12, 8, 10, 6, 8, 7, 9, 5, 6, 7, 9, 3, 10, 7, 7, 5, 9, 9, 4, 11, 12, 5, 11, 8, 9, 2, 4, 5, 11, 7, 9, 8, 5, 8, 11, 8, 13, 12, 8, 3, 2, 2, 7, 8, 7, 8, 10, 7, 9, 5, 10, 9, 8, 5, 16, 7, 6, 10, 9, 6, 6, 5, 7, 9, 13, 7, 11, 6, 8, 8, 8, 10, 11, 4, 4, 8, 8, 8, 8, 10, 7, 11, 8, 10, 12, 7, 12, 10, 3, 6, 5, 6, 5, 7, 10, 2, 10, 6, 10, 11, 6, 5, 2, 7, 8, 1, 8, 11, 5, 7, 7, 7, 4, 8, 4, 6, 12, 13, 6, 12, 11, 4, 6, 6, 4, 9, 7, 9, 7, 8, 7, 3, 10, 4, 8, 13, 11, 3, 3, 7, 6, 13, 7, 10, 7, 8, 4, 4, 8, 7]\n",
      "Genrtn 274: mean = 8.13  stddev = 2.7790465991055275  max = 16 [11, 3, 10, 5, 9, 12, 8, 9, 9, 5, 10, 6, 12, 6, 2, 9, 13, 11, 12, 4, 8, 8, 9, 4, 11, 5, 13, 6, 6, 8, 12, 6, 9, 7, 8, 5, 8, 10, 11, 13, 11, 1, 10, 7, 11, 6, 10, 8, 7, 11, 9, 7, 2, 9, 5, 8, 5, 6, 8, 12, 11, 6, 10, 10, 8, 7, 6, 8, 5, 4, 6, 9, 6, 9, 11, 5, 8, 6, 10, 8, 10, 9, 4, 9, 7, 7, 4, 6, 11, 8, 14, 7, 8, 5, 4, 7, 11, 11, 9, 8, 7, 8, 7, 11, 10, 4, 7, 10, 11, 8, 5, 16, 12, 15, 6, 6, 6, 5, 7, 7, 11, 8, 9, 7, 16, 6, 6, 9, 9, 9, 12, 11, 10, 7, 8, 11, 14, 9, 8, 7, 6, 12, 8, 8, 12, 3, 4, 8, 11, 5, 6, 6, 7, 11, 4, 12, 12, 11, 11, 11, 7, 3, 8, 1, 9, 6, 10, 8, 8, 6, 8, 2, 6, 10, 10, 7, 7, 9, 13, 8, 6, 5, 5, 7, 10, 9, 9, 5, 10, 10, 12, 6, 8, 8, 9, 7, 7, 12, 9, 5]\n",
      "Genrtn 275: mean = 7.985  stddev = 3.00579024550949  max = 20 [11, 5, 10, 2, 5, 6, 7, 11, 9, 5, 10, 6, 7, 10, 10, 3, 11, 9, 6, 4, 9, 9, 10, 6, 14, 9, 4, 12, 10, 4, 8, 17, 10, 14, 6, 8, 11, 13, 10, 11, 10, 5, 8, 8, 9, 10, 2, 8, 8, 7, 9, 7, 8, 3, 7, 7, 9, 14, 8, 10, 16, 11, 8, 11, 8, 9, 9, 7, 9, 8, 13, 8, 9, 5, 5, 7, 5, 8, 8, 8, 4, 12, 6, 10, 12, 4, 9, 6, 9, 8, 11, 3, 3, 9, 8, 13, 11, 6, 4, 8, 11, 6, 6, 6, 5, 6, 14, 12, 4, 5, 7, 5, 8, 7, 5, 4, 9, 9, 6, 4, 5, 4, 5, 3, 11, 14, 8, 7, 13, 6, 4, 8, 7, 9, 4, 11, 12, 7, 8, 20, 7, 8, 11, 12, 4, 10, 9, 10, 6, 6, 8, 8, 5, 9, 9, 8, 8, 5, 10, 6, 12, 3, 5, 7, 6, 8, 6, 12, 9, 8, 7, 6, 10, 8, 13, 4, 9, 7, 6, 7, 11, 9, 10, 6, 7, 9, 1, 7, 3, 9, 8, 7, 4, 8, 12, 5, 5, 7, 12, 13]\n",
      "Genrtn 276: mean = 8.04  stddev = 2.819290690936286  max = 16 [9, 15, 11, 9, 7, 9, 10, 12, 11, 10, 11, 2, 10, 6, 6, 10, 10, 7, 16, 8, 6, 8, 1, 4, 8, 9, 8, 11, 6, 4, 8, 9, 5, 6, 9, 2, 6, 15, 7, 8, 15, 4, 12, 7, 6, 4, 8, 10, 4, 9, 11, 7, 6, 6, 4, 4, 6, 7, 4, 8, 8, 7, 12, 6, 12, 6, 4, 9, 11, 5, 10, 9, 8, 8, 7, 12, 13, 9, 16, 9, 7, 6, 6, 7, 6, 7, 4, 10, 15, 7, 7, 7, 5, 5, 9, 7, 5, 8, 9, 4, 6, 9, 12, 9, 5, 7, 9, 7, 4, 7, 10, 7, 6, 11, 7, 4, 4, 5, 5, 11, 6, 9, 14, 7, 11, 6, 6, 9, 7, 11, 10, 10, 6, 8, 4, 10, 8, 8, 10, 7, 5, 8, 11, 10, 8, 7, 14, 7, 10, 10, 7, 9, 7, 5, 10, 10, 5, 7, 10, 7, 9, 11, 5, 5, 6, 9, 14, 8, 12, 10, 10, 7, 7, 6, 9, 5, 12, 11, 3, 5, 10, 8, 7, 14, 9, 8, 7, 6, 9, 10, 5, 12, 5, 13, 6, 11, 8, 9, 10, 5]\n",
      "Genrtn 277: mean = 8.26  stddev = 2.898689359003479  max = 16 [9, 4, 9, 6, 7, 8, 10, 10, 14, 7, 8, 5, 7, 8, 8, 8, 11, 3, 14, 8, 11, 10, 6, 8, 6, 8, 8, 8, 11, 6, 8, 9, 11, 5, 10, 9, 10, 8, 8, 7, 5, 8, 9, 6, 9, 9, 9, 6, 6, 6, 6, 4, 6, 6, 6, 12, 11, 7, 12, 4, 8, 5, 5, 6, 8, 12, 14, 9, 8, 8, 12, 6, 11, 8, 10, 6, 13, 7, 9, 8, 12, 9, 5, 6, 7, 8, 10, 6, 7, 12, 5, 11, 11, 9, 9, 5, 3, 11, 8, 3, 15, 12, 11, 6, 5, 11, 12, 12, 11, 4, 9, 10, 11, 8, 9, 6, 7, 10, 12, 6, 10, 6, 15, 5, 4, 10, 8, 7, 6, 14, 5, 11, 5, 11, 10, 3, 1, 6, 8, 9, 10, 5, 3, 14, 8, 15, 7, 9, 5, 9, 10, 13, 8, 7, 10, 6, 7, 8, 6, 3, 11, 9, 9, 6, 5, 6, 2, 9, 12, 5, 7, 6, 7, 12, 8, 10, 8, 8, 11, 8, 9, 6, 7, 8, 6, 5, 9, 14, 7, 13, 7, 16, 15, 11, 3, 7, 16, 6, 7, 9]\n",
      "Genrtn 278: mean = 7.915  stddev = 2.8439013695977575  max = 17 [10, 11, 8, 10, 12, 8, 5, 7, 13, 14, 4, 9, 2, 8, 10, 8, 12, 10, 9, 9, 5, 7, 8, 8, 14, 7, 2, 5, 12, 8, 6, 6, 11, 4, 7, 12, 11, 4, 6, 10, 6, 4, 7, 8, 6, 6, 4, 5, 9, 3, 17, 5, 6, 7, 4, 14, 7, 9, 8, 12, 10, 7, 8, 10, 9, 6, 8, 10, 7, 9, 8, 14, 8, 7, 5, 9, 16, 8, 3, 5, 3, 8, 6, 10, 3, 7, 9, 9, 6, 9, 9, 9, 10, 10, 7, 9, 11, 8, 11, 5, 9, 10, 6, 10, 11, 9, 8, 10, 10, 6, 10, 5, 8, 6, 9, 4, 6, 8, 7, 7, 5, 3, 3, 9, 13, 8, 9, 7, 8, 5, 9, 4, 10, 9, 9, 2, 9, 7, 5, 8, 8, 6, 7, 6, 9, 7, 9, 16, 9, 5, 6, 7, 6, 10, 8, 5, 6, 7, 8, 7, 11, 8, 10, 4, 9, 10, 7, 4, 12, 11, 9, 5, 7, 12, 10, 13, 5, 8, 10, 11, 10, 5, 9, 1, 7, 9, 16, 8, 5, 9, 10, 8, 3, 4, 6, 10, 6, 11, 4, 8]\n",
      "Genrtn 279: mean = 8.115  stddev = 2.807449910505974  max = 20 [1, 4, 12, 10, 5, 8, 7, 13, 12, 8, 8, 8, 12, 9, 8, 7, 4, 9, 9, 4, 7, 5, 8, 13, 4, 11, 6, 9, 8, 12, 10, 10, 11, 12, 3, 7, 5, 7, 9, 6, 10, 9, 9, 8, 4, 8, 6, 5, 11, 8, 6, 6, 7, 7, 14, 5, 10, 4, 3, 5, 11, 6, 9, 6, 10, 6, 9, 12, 8, 3, 8, 10, 8, 8, 3, 7, 7, 9, 10, 9, 7, 10, 7, 2, 9, 8, 9, 2, 7, 8, 7, 13, 7, 10, 10, 13, 4, 6, 5, 5, 12, 8, 8, 5, 4, 10, 9, 9, 6, 9, 5, 6, 6, 4, 6, 12, 4, 9, 8, 10, 6, 9, 7, 12, 10, 9, 11, 9, 6, 12, 9, 7, 7, 9, 10, 8, 5, 9, 8, 11, 12, 8, 11, 8, 11, 14, 3, 10, 8, 8, 6, 8, 7, 10, 10, 9, 7, 4, 13, 8, 6, 2, 9, 8, 9, 6, 6, 9, 9, 7, 7, 6, 7, 7, 11, 11, 13, 10, 7, 9, 7, 20, 13, 12, 8, 15, 11, 9, 7, 14, 7, 9, 8, 7, 9, 6, 11, 9, 4, 5]\n",
      "Genrtn 280: mean = 7.655  stddev = 2.9421038390920193  max = 15 [6, 9, 11, 11, 10, 0, 8, 13, 4, 11, 12, 6, 4, 9, 14, 5, 8, 6, 9, 7, 6, 8, 7, 3, 6, 6, 6, 8, 7, 9, 11, 8, 4, 4, 9, 7, 10, 13, 10, 8, 7, 14, 8, 8, 12, 7, 13, 4, 7, 10, 4, 10, 7, 5, 10, 8, 3, 5, 6, 8, 7, 6, 11, 6, 9, 6, 9, 9, 6, 7, 2, 9, 9, 4, 11, 4, 10, 15, 9, 8, 6, 9, 10, 3, 5, 7, 5, 4, 9, 4, 9, 8, 5, 7, 8, 3, 6, 8, 11, 5, 10, 6, 8, 5, 8, 6, 7, 8, 6, 3, 9, 7, 5, 10, 10, 6, 4, 4, 5, 9, 11, 10, 4, 2, 7, 8, 4, 3, 9, 9, 4, 15, 9, 9, 6, 8, 8, 7, 10, 15, 10, 9, 13, 6, 6, 8, 4, 4, 15, 15, 6, 6, 7, 7, 6, 6, 8, 5, 9, 5, 11, 8, 1, 4, 10, 9, 13, 6, 5, 8, 12, 9, 5, 8, 10, 13, 8, 7, 5, 15, 11, 10, 9, 8, 5, 7, 5, 6, 7, 12, 4, 6, 6, 9, 4, 10, 10, 10, 5, 13]\n",
      "Genrtn 281: mean = 8.215  stddev = 2.998128582966381  max = 17 [11, 5, 5, 11, 6, 9, 8, 8, 8, 6, 6, 6, 7, 9, 10, 5, 8, 2, 10, 13, 10, 8, 2, 6, 8, 9, 9, 8, 8, 9, 10, 9, 7, 8, 12, 9, 6, 6, 9, 10, 4, 5, 14, 10, 12, 6, 13, 6, 5, 7, 4, 11, 9, 9, 6, 7, 7, 8, 5, 8, 8, 9, 4, 8, 14, 16, 9, 6, 10, 9, 15, 9, 9, 3, 7, 7, 9, 14, 6, 16, 7, 11, 8, 9, 7, 11, 5, 9, 5, 5, 14, 6, 8, 6, 7, 10, 10, 7, 17, 6, 13, 8, 8, 6, 8, 12, 8, 10, 13, 8, 6, 10, 13, 6, 9, 5, 5, 11, 10, 11, 5, 8, 13, 12, 5, 7, 8, 6, 17, 1, 7, 6, 7, 4, 10, 5, 6, 10, 5, 9, 16, 7, 11, 11, 7, 13, 7, 10, 12, 9, 11, 7, 7, 4, 9, 8, 8, 8, 2, 10, 4, 7, 11, 6, 8, 6, 8, 8, 5, 5, 5, 13, 9, 8, 5, 12, 8, 10, 9, 5, 9, 14, 10, 2, 3, 9, 3, 9, 12, 9, 8, 6, 11, 4, 9, 5, 5, 11, 8, 8]\n",
      "Genrtn 282: mean = 7.91  stddev = 2.7480720514571666  max = 16 [5, 11, 7, 6, 6, 7, 3, 0, 6, 10, 7, 3, 11, 9, 11, 9, 8, 4, 9, 10, 8, 10, 11, 6, 8, 5, 3, 7, 6, 4, 11, 4, 11, 10, 9, 10, 8, 16, 11, 10, 7, 7, 8, 10, 6, 8, 6, 8, 14, 7, 9, 7, 9, 11, 8, 5, 10, 9, 10, 7, 8, 5, 13, 8, 8, 4, 16, 7, 5, 15, 6, 6, 15, 7, 3, 8, 8, 14, 4, 6, 7, 8, 6, 8, 8, 8, 11, 6, 7, 9, 7, 8, 9, 8, 7, 4, 6, 14, 8, 10, 5, 6, 10, 9, 5, 12, 6, 8, 8, 13, 9, 12, 6, 5, 8, 5, 8, 4, 7, 12, 10, 9, 7, 7, 6, 8, 9, 6, 10, 7, 7, 8, 3, 8, 6, 14, 10, 11, 6, 9, 4, 7, 9, 13, 7, 10, 8, 11, 10, 8, 5, 6, 8, 8, 2, 10, 6, 9, 6, 9, 8, 7, 3, 5, 4, 10, 11, 12, 9, 8, 7, 7, 8, 6, 9, 9, 9, 4, 10, 14, 9, 7, 5, 7, 6, 6, 7, 13, 8, 8, 5, 4, 10, 8, 4, 10, 7, 4, 6, 12]\n",
      "Genrtn 283: mean = 8.025  stddev = 2.8380230795396995  max = 18 [6, 3, 6, 11, 8, 9, 14, 6, 3, 11, 10, 9, 10, 13, 7, 9, 6, 11, 10, 4, 3, 4, 8, 7, 10, 7, 3, 13, 8, 9, 9, 9, 7, 4, 9, 6, 12, 4, 7, 5, 9, 5, 9, 10, 12, 10, 6, 10, 9, 9, 6, 6, 7, 7, 11, 9, 11, 12, 7, 8, 6, 9, 11, 11, 12, 6, 14, 10, 6, 8, 5, 11, 12, 7, 7, 7, 12, 5, 4, 10, 4, 7, 7, 11, 13, 9, 9, 12, 5, 8, 8, 5, 6, 5, 3, 9, 12, 11, 8, 10, 10, 10, 7, 11, 8, 8, 8, 5, 17, 11, 6, 5, 5, 8, 7, 4, 6, 8, 12, 7, 6, 8, 5, 7, 10, 8, 11, 10, 11, 9, 10, 6, 4, 8, 11, 10, 7, 4, 10, 12, 6, 11, 4, 7, 8, 4, 7, 10, 8, 9, 9, 11, 1, 5, 9, 10, 5, 9, 5, 9, 9, 10, 8, 13, 7, 18, 2, 6, 9, 12, 5, 8, 7, 4, 6, 11, 7, 4, 3, 9, 11, 9, 6, 6, 7, 7, 12, 7, 6, 8, 10, 5, 8, 5, 15, 6, 6, 7, 4, 7]\n",
      "Genrtn 284: mean = 7.845  stddev = 2.985125625497192  max = 17 [7, 8, 5, 10, 12, 7, 7, 9, 2, 14, 7, 7, 7, 10, 11, 6, 7, 11, 8, 9, 11, 8, 9, 14, 12, 3, 7, 4, 6, 7, 5, 3, 9, 3, 12, 2, 7, 8, 8, 6, 10, 9, 10, 8, 11, 13, 6, 11, 2, 8, 10, 7, 8, 5, 10, 6, 3, 5, 4, 10, 13, 6, 8, 13, 1, 5, 6, 11, 7, 6, 6, 16, 8, 4, 5, 8, 12, 12, 8, 13, 9, 9, 2, 7, 6, 11, 9, 5, 9, 7, 8, 8, 9, 5, 7, 11, 11, 10, 13, 9, 3, 6, 8, 8, 5, 4, 8, 7, 3, 10, 3, 8, 13, 4, 7, 9, 9, 11, 7, 4, 7, 6, 10, 15, 6, 4, 9, 9, 10, 6, 6, 17, 9, 11, 4, 9, 9, 7, 5, 5, 3, 8, 8, 10, 7, 7, 10, 6, 5, 8, 9, 5, 12, 8, 13, 8, 6, 7, 4, 7, 7, 9, 5, 10, 9, 6, 3, 8, 11, 11, 8, 5, 6, 9, 8, 3, 7, 15, 10, 12, 7, 9, 4, 10, 15, 7, 7, 7, 10, 13, 8, 8, 2, 9, 5, 6, 10, 6, 7, 8]\n",
      "Genrtn 285: mean = 7.88  stddev = 2.827649200307563  max = 19 [3, 6, 7, 11, 10, 3, 10, 6, 7, 5, 10, 10, 4, 4, 8, 8, 8, 11, 8, 4, 8, 8, 7, 8, 9, 9, 8, 10, 11, 14, 4, 7, 7, 10, 8, 7, 9, 10, 7, 8, 9, 12, 8, 10, 6, 6, 6, 4, 8, 7, 14, 7, 11, 11, 10, 10, 10, 3, 12, 11, 10, 5, 6, 9, 8, 5, 3, 9, 4, 8, 5, 5, 4, 7, 7, 11, 11, 11, 6, 6, 10, 5, 10, 5, 7, 10, 8, 2, 4, 9, 8, 3, 10, 8, 10, 8, 11, 10, 14, 5, 6, 13, 10, 7, 7, 9, 8, 11, 6, 14, 9, 9, 5, 12, 7, 7, 11, 8, 6, 4, 9, 10, 4, 4, 4, 5, 8, 2, 11, 5, 14, 7, 6, 6, 11, 5, 11, 11, 6, 9, 6, 7, 9, 8, 5, 9, 9, 5, 11, 4, 5, 8, 7, 7, 12, 6, 13, 12, 6, 6, 3, 8, 8, 9, 8, 10, 6, 4, 5, 7, 10, 8, 8, 10, 7, 7, 13, 3, 13, 7, 14, 4, 6, 10, 7, 9, 12, 11, 10, 5, 7, 4, 10, 6, 19, 8, 5, 7, 5, 7]\n",
      "Genrtn 286: mean = 8.25  stddev = 3.204293994002423  max = 19 [11, 11, 11, 4, 13, 5, 9, 14, 13, 11, 6, 6, 9, 11, 5, 15, 12, 9, 12, 15, 4, 9, 6, 9, 7, 10, 4, 7, 7, 4, 11, 7, 6, 6, 7, 11, 10, 6, 1, 11, 9, 7, 9, 13, 11, 7, 10, 10, 5, 11, 10, 10, 5, 7, 14, 13, 8, 10, 11, 11, 5, 9, 3, 7, 2, 3, 8, 11, 8, 5, 7, 8, 8, 6, 10, 7, 9, 8, 6, 5, 5, 8, 4, 9, 7, 7, 6, 10, 7, 5, 9, 3, 5, 8, 6, 6, 11, 8, 3, 14, 5, 4, 13, 5, 11, 19, 9, 8, 12, 1, 12, 14, 16, 11, 11, 2, 12, 7, 12, 7, 8, 7, 7, 8, 10, 7, 8, 5, 8, 9, 7, 10, 7, 4, 8, 3, 13, 6, 5, 12, 6, 5, 5, 5, 9, 9, 14, 6, 4, 5, 9, 8, 7, 10, 9, 9, 11, 6, 10, 4, 7, 3, 10, 7, 8, 8, 2, 10, 8, 9, 6, 12, 7, 18, 9, 12, 12, 13, 11, 11, 9, 8, 6, 12, 11, 6, 11, 4, 11, 9, 5, 7, 8, 12, 2, 6, 6, 9, 7, 12]\n",
      "Genrtn 287: mean = 7.995  stddev = 2.8080197648877046  max = 18 [6, 8, 10, 4, 10, 10, 10, 8, 6, 4, 5, 10, 8, 15, 6, 5, 10, 5, 15, 12, 8, 8, 7, 7, 10, 8, 10, 10, 4, 5, 6, 6, 2, 8, 10, 3, 9, 7, 5, 12, 11, 6, 8, 6, 10, 15, 12, 9, 7, 9, 7, 12, 9, 9, 7, 3, 7, 3, 5, 5, 10, 6, 10, 4, 8, 7, 8, 9, 10, 12, 11, 7, 7, 7, 6, 5, 9, 3, 8, 9, 4, 7, 9, 8, 8, 12, 8, 16, 11, 11, 8, 7, 5, 8, 9, 8, 8, 8, 8, 11, 8, 2, 6, 9, 8, 8, 18, 8, 8, 10, 3, 6, 7, 8, 9, 9, 9, 6, 4, 7, 5, 11, 9, 6, 9, 6, 6, 11, 6, 9, 8, 9, 8, 8, 7, 11, 4, 7, 6, 5, 13, 6, 14, 4, 9, 7, 5, 9, 5, 6, 9, 8, 11, 9, 12, 5, 10, 9, 7, 7, 7, 4, 4, 9, 13, 9, 12, 11, 10, 6, 4, 5, 10, 4, 5, 7, 8, 9, 6, 7, 12, 10, 9, 13, 4, 12, 10, 11, 12, 7, 6, 11, 3, 10, 3, 6, 10, 14, 9, 6]\n",
      "Genrtn 288: mean = 8.025  stddev = 2.6654033465875293  max = 15 [12, 10, 12, 4, 3, 7, 6, 8, 9, 4, 11, 8, 8, 9, 10, 8, 10, 8, 7, 6, 8, 11, 8, 6, 7, 6, 12, 12, 7, 3, 14, 11, 14, 5, 2, 8, 9, 7, 7, 5, 4, 10, 12, 9, 6, 5, 5, 6, 3, 7, 9, 7, 13, 13, 4, 6, 8, 12, 4, 10, 4, 6, 6, 8, 8, 8, 10, 10, 9, 7, 6, 4, 8, 7, 7, 8, 10, 12, 10, 12, 8, 12, 5, 4, 6, 5, 10, 6, 10, 9, 5, 8, 9, 8, 12, 14, 7, 8, 7, 8, 3, 7, 6, 8, 5, 11, 14, 12, 8, 9, 12, 7, 7, 6, 10, 6, 8, 13, 5, 5, 9, 8, 10, 8, 6, 8, 1, 8, 13, 8, 10, 8, 4, 12, 9, 10, 10, 7, 6, 14, 5, 9, 7, 8, 6, 10, 5, 6, 8, 7, 11, 7, 8, 8, 11, 9, 10, 10, 6, 9, 5, 9, 6, 7, 6, 8, 3, 7, 8, 14, 10, 4, 10, 8, 8, 9, 9, 7, 8, 6, 11, 10, 9, 7, 9, 7, 11, 15, 5, 7, 9, 9, 10, 5, 3, 10, 7, 5, 9, 8]\n",
      "Genrtn 289: mean = 8.22  stddev = 2.760724542579357  max = 16 [13, 9, 9, 5, 14, 5, 8, 10, 10, 8, 9, 10, 6, 5, 8, 6, 8, 7, 11, 6, 8, 7, 12, 4, 7, 11, 9, 7, 6, 5, 13, 8, 13, 6, 12, 11, 8, 10, 7, 13, 7, 5, 8, 5, 8, 6, 7, 4, 10, 10, 12, 6, 4, 12, 11, 13, 8, 7, 8, 4, 12, 6, 12, 15, 9, 11, 6, 6, 7, 6, 11, 7, 9, 9, 5, 6, 3, 9, 9, 9, 6, 5, 10, 13, 6, 7, 2, 10, 6, 7, 11, 7, 11, 11, 7, 3, 4, 8, 4, 13, 7, 12, 5, 4, 12, 3, 15, 8, 11, 4, 6, 8, 10, 8, 9, 7, 6, 7, 6, 10, 4, 11, 8, 7, 3, 11, 4, 13, 11, 6, 16, 5, 8, 10, 11, 6, 8, 7, 6, 4, 9, 4, 7, 10, 7, 8, 10, 12, 8, 8, 9, 7, 13, 8, 9, 7, 8, 14, 8, 7, 6, 9, 7, 11, 6, 10, 10, 6, 8, 6, 6, 8, 6, 11, 5, 8, 14, 8, 10, 13, 7, 6, 6, 9, 12, 11, 8, 8, 5, 11, 8, 10, 5, 11, 8, 8, 9, 7, 9, 11]\n",
      "Genrtn 290: mean = 7.94  stddev = 2.8242521133921454  max = 15 [5, 7, 7, 6, 6, 6, 10, 7, 9, 6, 7, 8, 9, 13, 8, 9, 9, 4, 6, 3, 8, 4, 9, 7, 7, 10, 7, 10, 7, 8, 11, 8, 12, 14, 3, 10, 9, 7, 7, 5, 9, 9, 8, 2, 7, 5, 9, 7, 15, 9, 4, 9, 10, 13, 6, 7, 6, 8, 4, 13, 11, 5, 10, 7, 6, 8, 10, 8, 11, 2, 6, 7, 6, 13, 10, 7, 9, 4, 5, 9, 4, 10, 6, 7, 9, 9, 9, 8, 13, 14, 9, 7, 9, 10, 8, 7, 13, 9, 10, 12, 10, 10, 6, 5, 9, 1, 5, 6, 11, 5, 8, 11, 5, 8, 4, 8, 10, 4, 12, 8, 11, 5, 4, 5, 15, 9, 8, 14, 7, 10, 8, 9, 10, 11, 4, 10, 7, 9, 10, 10, 5, 5, 4, 12, 8, 6, 10, 5, 9, 9, 13, 5, 12, 8, 7, 6, 9, 5, 6, 9, 6, 9, 6, 5, 8, 9, 5, 5, 5, 7, 6, 3, 12, 3, 10, 8, 9, 10, 7, 12, 2, 11, 2, 14, 7, 12, 7, 9, 12, 5, 13, 9, 10, 6, 12, 10, 6, 5, 7, 4]\n",
      "Genrtn 291: mean = 8.295  stddev = 2.8979259824916164  max = 16 [5, 8, 7, 10, 11, 5, 7, 5, 9, 5, 10, 12, 10, 6, 5, 6, 9, 9, 13, 5, 12, 11, 10, 7, 6, 6, 6, 6, 12, 6, 9, 6, 10, 9, 7, 11, 8, 7, 11, 12, 9, 12, 5, 15, 7, 14, 9, 9, 10, 6, 11, 10, 9, 14, 14, 10, 14, 8, 5, 10, 6, 6, 7, 6, 10, 6, 12, 9, 6, 11, 7, 6, 11, 6, 6, 5, 9, 7, 10, 9, 15, 16, 8, 12, 5, 5, 4, 9, 7, 8, 4, 5, 6, 13, 11, 10, 6, 11, 7, 11, 4, 11, 8, 11, 12, 15, 9, 4, 7, 1, 7, 8, 5, 9, 8, 12, 9, 9, 10, 10, 8, 8, 4, 8, 16, 9, 12, 7, 6, 5, 5, 6, 4, 5, 8, 10, 9, 10, 6, 11, 7, 6, 11, 6, 11, 4, 12, 9, 7, 4, 3, 7, 5, 12, 3, 4, 9, 10, 9, 11, 4, 10, 12, 5, 5, 10, 10, 8, 7, 5, 6, 4, 11, 9, 4, 12, 8, 11, 7, 9, 10, 3, 5, 13, 14, 7, 9, 11, 7, 11, 7, 12, 8, 8, 7, 7, 8, 8, 8, 5]\n",
      "Genrtn 292: mean = 8.12  stddev = 2.950525376945604  max = 18 [8, 9, 6, 5, 5, 7, 9, 5, 8, 8, 15, 11, 10, 9, 7, 10, 12, 11, 6, 5, 13, 7, 8, 3, 6, 11, 3, 10, 12, 8, 8, 6, 6, 8, 17, 11, 5, 7, 14, 9, 10, 5, 13, 4, 12, 18, 8, 7, 9, 9, 10, 3, 5, 6, 7, 6, 10, 5, 11, 6, 6, 7, 12, 2, 9, 5, 8, 5, 11, 9, 10, 11, 4, 7, 7, 15, 7, 9, 8, 7, 8, 8, 7, 8, 7, 10, 10, 7, 5, 9, 10, 6, 9, 11, 10, 14, 4, 7, 11, 5, 7, 13, 9, 11, 5, 8, 7, 6, 12, 7, 2, 14, 7, 12, 17, 10, 5, 11, 7, 4, 5, 15, 4, 7, 10, 5, 6, 7, 11, 5, 4, 9, 10, 6, 6, 10, 13, 8, 8, 7, 5, 11, 12, 6, 7, 9, 11, 9, 7, 4, 4, 5, 6, 5, 10, 9, 11, 9, 7, 7, 7, 6, 9, 9, 12, 11, 5, 5, 13, 8, 7, 10, 6, 10, 12, 11, 3, 6, 8, 9, 8, 3, 11, 11, 5, 9, 9, 9, 4, 6, 6, 9, 9, 7, 7, 7, 5, 4, 8, 9]\n",
      "Genrtn 293: mean = 8.295  stddev = 2.878884332514941  max = 19 [6, 8, 11, 7, 7, 9, 9, 9, 7, 15, 10, 6, 5, 10, 12, 7, 8, 14, 13, 15, 13, 7, 7, 6, 12, 9, 12, 9, 5, 11, 7, 7, 6, 9, 8, 6, 8, 15, 6, 9, 9, 4, 11, 7, 13, 4, 6, 3, 11, 9, 5, 12, 6, 4, 3, 7, 8, 4, 5, 9, 9, 9, 3, 10, 7, 9, 8, 10, 9, 6, 5, 6, 14, 5, 14, 5, 10, 8, 3, 12, 10, 13, 10, 11, 11, 9, 8, 12, 7, 11, 11, 6, 11, 6, 6, 8, 8, 7, 8, 6, 5, 9, 7, 11, 7, 10, 4, 8, 11, 8, 13, 7, 8, 8, 10, 11, 10, 10, 11, 7, 3, 4, 4, 9, 3, 9, 10, 8, 15, 7, 10, 8, 6, 11, 5, 8, 8, 12, 10, 6, 8, 6, 6, 10, 13, 8, 10, 7, 7, 5, 9, 11, 3, 12, 4, 5, 10, 5, 7, 9, 3, 6, 6, 19, 5, 8, 11, 11, 5, 9, 7, 10, 10, 8, 11, 4, 10, 6, 8, 14, 10, 6, 9, 6, 7, 8, 10, 10, 14, 9, 10, 6, 8, 9, 5, 8, 9, 5, 5, 7]\n",
      "Genrtn 294: mean = 7.935  stddev = 3.160818723052621  max = 17 [12, 14, 10, 10, 12, 8, 14, 5, 14, 11, 6, 9, 5, 7, 9, 3, 6, 10, 7, 3, 12, 11, 9, 5, 4, 8, 8, 8, 7, 7, 8, 13, 6, 7, 7, 13, 11, 8, 15, 4, 6, 8, 8, 6, 13, 11, 15, 6, 6, 11, 4, 6, 7, 4, 7, 6, 2, 7, 9, 4, 8, 7, 5, 9, 6, 16, 2, 7, 8, 5, 11, 11, 12, 7, 5, 6, 5, 16, 6, 7, 5, 5, 6, 13, 12, 6, 7, 12, 6, 8, 9, 4, 11, 7, 4, 6, 5, 4, 7, 1, 11, 10, 7, 9, 17, 10, 5, 10, 5, 5, 9, 4, 6, 6, 4, 6, 8, 9, 6, 9, 6, 8, 10, 4, 6, 7, 6, 9, 10, 5, 3, 6, 10, 10, 11, 11, 11, 8, 11, 10, 6, 5, 6, 6, 11, 6, 9, 5, 11, 5, 2, 8, 7, 11, 5, 13, 8, 5, 9, 7, 9, 10, 4, 13, 5, 10, 3, 10, 12, 11, 7, 2, 7, 9, 14, 7, 13, 11, 7, 6, 9, 4, 9, 5, 14, 4, 10, 13, 7, 10, 7, 10, 14, 6, 4, 11, 6, 12, 6, 4]\n",
      "Genrtn 295: mean = 8.205  stddev = 2.9466888196754  max = 19 [11, 6, 14, 7, 10, 7, 9, 5, 5, 8, 19, 9, 11, 9, 13, 8, 7, 5, 6, 5, 7, 7, 12, 12, 5, 9, 10, 3, 10, 7, 11, 6, 11, 8, 9, 6, 10, 12, 12, 9, 8, 10, 7, 9, 7, 8, 14, 16, 4, 9, 0, 3, 8, 13, 13, 7, 8, 3, 12, 8, 8, 11, 5, 6, 12, 8, 8, 11, 10, 10, 11, 6, 7, 7, 7, 7, 4, 10, 8, 12, 11, 7, 11, 6, 9, 10, 13, 5, 6, 11, 12, 10, 7, 8, 11, 11, 5, 5, 7, 7, 9, 6, 2, 5, 10, 4, 7, 12, 10, 6, 8, 13, 9, 8, 12, 8, 8, 5, 7, 6, 4, 6, 10, 11, 3, 12, 9, 7, 7, 7, 5, 7, 5, 10, 7, 12, 8, 10, 6, 10, 10, 4, 12, 13, 7, 10, 6, 5, 7, 9, 6, 9, 10, 5, 4, 3, 4, 12, 10, 4, 8, 8, 9, 9, 4, 9, 4, 10, 12, 3, 9, 12, 11, 14, 8, 5, 11, 8, 9, 7, 12, 7, 11, 9, 9, 6, 7, 10, 8, 10, 10, 10, 4, 3, 4, 4, 6, 12, 3, 8]\n",
      "Genrtn 296: mean = 7.985  stddev = 2.781146346383088  max = 16 [6, 9, 3, 4, 7, 8, 8, 11, 8, 7, 8, 5, 6, 8, 12, 8, 5, 12, 12, 10, 4, 8, 13, 8, 10, 8, 8, 6, 8, 7, 6, 5, 11, 10, 11, 12, 6, 15, 9, 3, 6, 9, 8, 1, 10, 10, 7, 4, 5, 5, 8, 10, 12, 8, 9, 8, 6, 6, 0, 6, 6, 4, 14, 9, 8, 8, 8, 6, 11, 15, 8, 6, 8, 6, 10, 7, 6, 11, 5, 13, 4, 5, 9, 10, 8, 12, 10, 6, 5, 5, 5, 9, 5, 6, 3, 7, 9, 5, 8, 12, 8, 9, 10, 6, 9, 7, 9, 6, 3, 12, 5, 10, 12, 9, 10, 9, 4, 7, 9, 7, 9, 6, 9, 9, 7, 10, 9, 12, 6, 7, 6, 4, 4, 8, 13, 10, 8, 7, 12, 9, 6, 9, 10, 9, 10, 7, 9, 7, 10, 6, 7, 11, 10, 7, 7, 7, 16, 4, 11, 7, 7, 4, 9, 9, 6, 12, 4, 15, 7, 15, 12, 5, 8, 10, 4, 6, 9, 9, 8, 5, 14, 6, 6, 9, 7, 5, 12, 12, 7, 7, 9, 9, 7, 10, 3, 6, 10, 8, 5, 10]\n",
      "Genrtn 297: mean = 8.235  stddev = 2.7495045008146466  max = 17 [4, 14, 10, 13, 6, 7, 10, 13, 8, 7, 5, 10, 7, 12, 7, 6, 9, 14, 9, 6, 8, 4, 6, 13, 8, 9, 8, 7, 9, 9, 1, 9, 13, 14, 13, 7, 7, 7, 9, 9, 8, 11, 2, 12, 4, 8, 10, 9, 6, 9, 10, 7, 7, 10, 9, 5, 11, 11, 10, 9, 7, 7, 11, 9, 14, 4, 9, 11, 7, 7, 10, 3, 6, 9, 14, 4, 12, 7, 8, 9, 11, 7, 8, 8, 6, 9, 17, 4, 10, 7, 9, 9, 5, 10, 10, 6, 6, 7, 6, 13, 8, 9, 7, 9, 4, 6, 8, 7, 9, 6, 6, 5, 14, 7, 3, 8, 8, 12, 7, 10, 8, 6, 14, 11, 8, 6, 7, 10, 8, 8, 9, 11, 5, 9, 8, 5, 4, 8, 7, 8, 11, 11, 9, 10, 8, 8, 6, 7, 8, 14, 9, 10, 3, 4, 7, 12, 6, 8, 5, 8, 17, 5, 11, 12, 6, 7, 3, 6, 11, 13, 4, 7, 8, 6, 6, 7, 5, 10, 8, 9, 7, 9, 10, 9, 5, 8, 9, 11, 9, 8, 10, 9, 9, 9, 4, 6, 6, 6, 7, 7]\n",
      "Genrtn 298: mean = 8.015  stddev = 2.6504292105242127  max = 15 [6, 10, 12, 6, 12, 10, 7, 8, 9, 6, 7, 8, 5, 10, 11, 5, 7, 6, 6, 7, 7, 8, 7, 9, 6, 3, 3, 9, 6, 7, 7, 10, 11, 8, 12, 7, 8, 6, 9, 6, 6, 7, 7, 9, 12, 5, 7, 9, 6, 6, 11, 14, 9, 6, 3, 9, 6, 9, 8, 8, 7, 8, 9, 5, 6, 8, 9, 7, 5, 5, 8, 9, 7, 4, 15, 6, 8, 10, 7, 9, 9, 11, 8, 4, 8, 12, 5, 6, 6, 6, 7, 8, 7, 4, 4, 8, 1, 5, 9, 8, 12, 12, 7, 8, 8, 5, 7, 11, 12, 8, 4, 8, 7, 7, 8, 8, 7, 10, 11, 8, 12, 2, 7, 8, 5, 5, 9, 7, 7, 7, 8, 12, 11, 7, 9, 7, 9, 5, 8, 4, 6, 8, 14, 5, 8, 12, 10, 11, 10, 6, 7, 11, 14, 8, 8, 7, 4, 6, 15, 5, 12, 5, 4, 10, 10, 11, 9, 11, 14, 6, 10, 10, 11, 8, 7, 4, 11, 6, 14, 10, 5, 5, 10, 9, 6, 14, 7, 11, 12, 12, 12, 7, 7, 8, 9, 6, 3, 11, 11, 11]\n",
      "Genrtn 299: mean = 7.66  stddev = 3.058496362593881  max = 15 [5, 12, 11, 11, 5, 7, 3, 8, 7, 15, 6, 6, 9, 4, 12, 5, 6, 10, 8, 3, 13, 12, 11, 6, 10, 9, 8, 7, 8, 12, 7, 5, 4, 5, 7, 10, 7, 10, 6, 10, 9, 3, 10, 11, 13, 8, 9, 5, 13, 5, 13, 4, 4, 7, 9, 7, 4, 3, 6, 11, 6, 8, 6, 2, 4, 14, 6, 10, 4, 6, 9, 6, 11, 7, 5, 7, 6, 10, 5, 7, 7, 8, 7, 9, 8, 10, 7, 4, 4, 6, 6, 5, 6, 3, 4, 7, 5, 10, 10, 4, 8, 8, 6, 5, 13, 9, 11, 7, 9, 6, 10, 9, 4, 11, 10, 0, 10, 11, 4, 10, 13, 4, 5, 13, 10, 8, 3, 9, 4, 3, 12, 3, 2, 3, 4, 12, 10, 13, 8, 10, 7, 12, 7, 11, 9, 6, 7, 13, 9, 5, 8, 15, 9, 3, 9, 3, 9, 5, 12, 6, 8, 11, 8, 13, 8, 6, 3, 7, 10, 12, 6, 10, 7, 6, 7, 9, 7, 11, 11, 8, 6, 5, 11, 3, 4, 12, 7, 8, 14, 6, 4, 11, 8, 11, 7, 9, 7, 6, 6, 1]\n",
      "Genrtn 300: mean = 8.465  stddev = 2.9238288253589677  max = 18 [9, 12, 8, 11, 10, 11, 9, 5, 4, 12, 13, 10, 7, 10, 8, 8, 7, 10, 12, 3, 10, 14, 9, 4, 7, 7, 8, 11, 8, 12, 7, 4, 8, 10, 8, 8, 10, 5, 14, 15, 8, 12, 4, 8, 4, 9, 7, 6, 9, 2, 8, 9, 4, 6, 7, 6, 5, 11, 8, 6, 11, 12, 5, 7, 3, 5, 7, 7, 8, 15, 9, 10, 11, 7, 6, 10, 8, 7, 5, 7, 7, 8, 13, 10, 12, 13, 10, 7, 9, 11, 10, 17, 13, 7, 6, 6, 10, 9, 9, 11, 6, 7, 9, 4, 6, 7, 7, 11, 7, 8, 8, 6, 4, 11, 6, 7, 4, 9, 14, 9, 14, 10, 10, 14, 6, 12, 13, 6, 14, 6, 7, 12, 7, 7, 12, 6, 8, 8, 6, 8, 5, 18, 13, 9, 6, 9, 7, 11, 9, 12, 9, 11, 11, 7, 6, 3, 13, 13, 9, 13, 8, 12, 9, 9, 8, 9, 8, 8, 9, 10, 10, 8, 7, 10, 10, 8, 4, 5, 12, 12, 6, 4, 10, 2, 5, 7, 10, 6, 7, 5, 8, 7, 5, 4, 4, 8, 10, 5, 11, 8]\n",
      "Genrtn 301: mean = 7.645  stddev = 2.7090542630224297  max = 16 [12, 9, 6, 11, 7, 7, 6, 6, 7, 7, 4, 5, 5, 15, 9, 6, 11, 9, 5, 8, 3, 5, 6, 4, 7, 6, 4, 8, 4, 7, 11, 12, 7, 10, 5, 6, 5, 4, 12, 11, 6, 7, 8, 5, 3, 9, 5, 11, 5, 4, 4, 8, 9, 8, 11, 6, 8, 10, 7, 7, 9, 5, 9, 8, 7, 5, 8, 10, 9, 6, 7, 13, 5, 10, 9, 8, 8, 12, 8, 9, 10, 13, 5, 8, 13, 4, 10, 10, 8, 10, 4, 6, 8, 13, 9, 6, 14, 8, 7, 15, 8, 9, 7, 6, 3, 6, 11, 5, 4, 5, 8, 8, 3, 6, 4, 9, 7, 10, 8, 2, 5, 12, 11, 9, 9, 9, 7, 11, 11, 6, 7, 5, 5, 9, 5, 11, 8, 12, 9, 7, 7, 12, 7, 7, 4, 10, 9, 12, 12, 4, 8, 7, 10, 6, 3, 11, 6, 6, 9, 8, 11, 4, 6, 5, 11, 3, 7, 7, 7, 5, 5, 7, 12, 7, 9, 4, 6, 11, 5, 9, 9, 4, 11, 16, 6, 5, 9, 6, 10, 9, 6, 3, 8, 6, 7, 8, 7, 9, 9, 6]\n",
      "Genrtn 302: mean = 7.905  stddev = 2.618391681929959  max = 17 [5, 11, 6, 7, 5, 12, 7, 9, 4, 8, 4, 5, 13, 11, 11, 11, 8, 8, 4, 6, 15, 5, 6, 10, 10, 11, 8, 8, 10, 10, 8, 6, 9, 9, 6, 8, 10, 5, 8, 5, 7, 10, 17, 7, 13, 8, 8, 10, 11, 7, 8, 8, 4, 10, 10, 2, 9, 5, 8, 5, 8, 9, 6, 7, 8, 7, 5, 5, 9, 2, 13, 9, 5, 11, 3, 8, 8, 8, 6, 11, 6, 10, 10, 7, 6, 6, 8, 7, 6, 17, 6, 9, 11, 5, 9, 7, 3, 10, 10, 9, 9, 9, 4, 7, 7, 8, 6, 7, 9, 17, 13, 9, 7, 6, 6, 4, 5, 4, 7, 8, 12, 8, 12, 7, 10, 11, 6, 8, 8, 6, 8, 9, 7, 12, 8, 7, 4, 8, 6, 8, 13, 11, 8, 4, 8, 6, 3, 6, 7, 9, 7, 6, 7, 5, 5, 11, 12, 9, 9, 9, 7, 9, 11, 8, 8, 11, 8, 9, 9, 5, 9, 8, 6, 7, 8, 11, 5, 8, 12, 6, 7, 7, 7, 7, 3, 8, 6, 6, 10, 7, 9, 11, 8, 3, 9, 8, 6, 6, 9, 8]\n",
      "Genrtn 303: mean = 8.19  stddev = 2.7025728482318474  max = 17 [6, 4, 8, 8, 8, 4, 11, 7, 6, 8, 5, 14, 8, 9, 9, 8, 9, 9, 5, 13, 11, 7, 14, 7, 6, 4, 7, 9, 11, 7, 6, 10, 8, 3, 7, 5, 9, 9, 13, 9, 7, 7, 4, 6, 11, 7, 8, 10, 8, 10, 11, 8, 8, 6, 5, 12, 8, 5, 10, 8, 7, 12, 7, 7, 6, 13, 9, 2, 9, 11, 11, 7, 11, 5, 8, 11, 8, 5, 6, 11, 6, 6, 6, 12, 11, 5, 7, 6, 7, 7, 8, 8, 15, 7, 10, 4, 9, 7, 7, 17, 5, 5, 11, 5, 8, 7, 9, 6, 14, 6, 9, 13, 5, 7, 5, 5, 4, 9, 3, 8, 9, 8, 14, 7, 9, 6, 6, 5, 8, 6, 14, 5, 8, 6, 4, 8, 9, 8, 6, 6, 8, 7, 9, 10, 6, 7, 9, 9, 11, 8, 13, 6, 11, 11, 5, 10, 4, 9, 12, 10, 8, 13, 12, 8, 9, 9, 5, 15, 4, 8, 7, 6, 10, 9, 9, 10, 10, 10, 11, 6, 5, 9, 8, 12, 8, 8, 12, 5, 13, 10, 10, 5, 9, 6, 7, 10, 8, 14, 7, 11]\n",
      "Genrtn 304: mean = 8.39  stddev = 2.840404900713981  max = 16 [7, 7, 14, 9, 11, 6, 7, 4, 4, 9, 12, 6, 10, 11, 9, 10, 9, 10, 2, 5, 10, 6, 9, 5, 10, 8, 5, 11, 7, 8, 10, 9, 10, 10, 7, 8, 6, 11, 12, 13, 8, 7, 14, 12, 6, 3, 12, 8, 8, 14, 4, 11, 11, 11, 4, 8, 6, 7, 8, 10, 8, 8, 5, 16, 11, 11, 10, 13, 4, 7, 3, 10, 9, 7, 9, 7, 7, 7, 10, 9, 9, 11, 4, 14, 7, 8, 9, 11, 12, 10, 8, 8, 7, 14, 5, 11, 13, 9, 7, 5, 7, 12, 9, 13, 5, 10, 7, 11, 5, 13, 11, 8, 12, 4, 8, 6, 3, 9, 8, 5, 14, 9, 6, 6, 6, 12, 10, 10, 8, 5, 10, 14, 11, 6, 4, 9, 12, 8, 5, 6, 7, 6, 5, 9, 8, 7, 15, 8, 14, 7, 9, 2, 8, 7, 14, 8, 6, 8, 7, 9, 9, 8, 5, 10, 3, 8, 5, 6, 7, 9, 9, 8, 6, 6, 9, 11, 9, 7, 12, 4, 8, 5, 12, 5, 7, 14, 10, 7, 12, 12, 9, 6, 8, 7, 7, 8, 10, 8, 6, 3]\n",
      "Genrtn 305: mean = 7.705  stddev = 2.727265113625736  max = 18 [6, 9, 6, 8, 7, 10, 8, 9, 3, 11, 5, 5, 2, 7, 10, 4, 6, 9, 13, 9, 13, 5, 15, 12, 8, 6, 6, 6, 6, 10, 8, 9, 4, 8, 8, 5, 6, 8, 8, 9, 7, 7, 5, 9, 8, 12, 12, 4, 6, 8, 5, 8, 5, 4, 6, 8, 9, 2, 8, 10, 8, 4, 11, 2, 5, 12, 9, 4, 9, 9, 6, 7, 5, 10, 8, 12, 7, 11, 6, 11, 8, 8, 5, 5, 10, 7, 6, 5, 7, 5, 4, 9, 8, 9, 11, 8, 2, 9, 9, 9, 8, 7, 6, 7, 7, 9, 7, 12, 4, 7, 6, 1, 5, 7, 4, 6, 8, 6, 8, 9, 6, 9, 5, 6, 5, 11, 2, 8, 6, 12, 8, 18, 10, 7, 8, 10, 12, 8, 11, 12, 8, 7, 4, 8, 6, 8, 11, 8, 7, 7, 8, 10, 11, 8, 8, 9, 3, 2, 12, 14, 7, 8, 7, 10, 9, 12, 7, 6, 5, 6, 5, 2, 7, 13, 9, 10, 6, 8, 8, 10, 10, 2, 8, 9, 10, 12, 8, 10, 8, 8, 13, 8, 6, 5, 11, 8, 9, 11, 7, 6]\n",
      "Genrtn 306: mean = 8.08  stddev = 2.8659378918601845  max = 19 [8, 10, 9, 10, 6, 8, 8, 12, 8, 7, 5, 6, 5, 6, 8, 12, 5, 14, 8, 12, 11, 10, 5, 2, 9, 12, 8, 6, 8, 5, 8, 8, 8, 6, 10, 7, 4, 8, 3, 6, 4, 4, 12, 11, 6, 5, 12, 8, 9, 9, 7, 10, 11, 6, 12, 19, 10, 7, 6, 6, 10, 12, 11, 7, 3, 5, 11, 7, 14, 7, 9, 7, 6, 7, 5, 7, 6, 10, 3, 13, 8, 8, 5, 10, 12, 11, 6, 9, 7, 7, 9, 3, 6, 11, 7, 10, 9, 7, 8, 6, 6, 4, 12, 11, 9, 4, 7, 9, 7, 5, 9, 4, 9, 12, 10, 9, 10, 15, 9, 9, 6, 3, 7, 9, 6, 8, 6, 13, 7, 11, 9, 7, 4, 16, 3, 11, 10, 9, 5, 6, 9, 6, 12, 11, 6, 8, 7, 6, 9, 5, 6, 13, 4, 4, 7, 6, 8, 10, 3, 7, 13, 6, 10, 9, 10, 8, 9, 5, 10, 7, 9, 13, 7, 8, 14, 5, 12, 10, 10, 7, 8, 9, 6, 8, 4, 4, 6, 4, 11, 12, 8, 8, 6, 8, 13, 14, 9, 6, 8, 5]\n",
      "Genrtn 307: mean = 8.075  stddev = 2.879127471995639  max = 19 [15, 10, 5, 10, 12, 4, 6, 9, 4, 7, 3, 12, 9, 6, 10, 9, 5, 11, 10, 8, 5, 7, 8, 11, 10, 3, 6, 8, 4, 13, 19, 8, 9, 8, 9, 4, 9, 5, 8, 11, 11, 10, 7, 15, 9, 8, 9, 9, 6, 6, 9, 9, 12, 4, 9, 8, 3, 10, 7, 8, 5, 10, 10, 8, 2, 5, 11, 10, 7, 8, 5, 4, 8, 19, 5, 4, 5, 4, 10, 4, 12, 4, 6, 7, 9, 9, 10, 9, 8, 10, 6, 11, 6, 6, 9, 4, 5, 8, 5, 7, 8, 7, 7, 7, 9, 6, 7, 7, 10, 8, 11, 10, 9, 9, 6, 7, 15, 5, 8, 8, 4, 4, 5, 9, 8, 9, 4, 9, 6, 8, 14, 10, 7, 8, 14, 13, 12, 8, 11, 9, 12, 11, 6, 6, 10, 10, 10, 8, 5, 9, 9, 11, 6, 8, 9, 10, 4, 6, 10, 7, 7, 8, 11, 8, 6, 8, 11, 12, 7, 7, 6, 9, 7, 5, 9, 7, 4, 10, 9, 10, 6, 7, 8, 2, 11, 8, 9, 6, 5, 6, 6, 9, 7, 9, 13, 6, 5, 8, 8, 18]\n",
      "Genrtn 308: mean = 8.175  stddev = 2.8851992998751403  max = 17 [5, 11, 11, 5, 6, 9, 6, 14, 8, 8, 10, 12, 5, 13, 7, 7, 14, 13, 8, 17, 8, 8, 7, 5, 6, 10, 11, 6, 7, 10, 6, 7, 11, 8, 6, 9, 5, 6, 7, 7, 6, 8, 7, 5, 8, 5, 13, 7, 5, 7, 8, 5, 5, 8, 7, 10, 5, 4, 7, 9, 8, 12, 10, 6, 8, 9, 9, 7, 7, 7, 7, 7, 8, 8, 9, 9, 9, 5, 8, 14, 3, 8, 10, 4, 13, 9, 8, 10, 5, 6, 2, 6, 10, 9, 11, 7, 11, 5, 11, 8, 11, 6, 7, 9, 8, 6, 11, 9, 16, 8, 13, 6, 11, 5, 7, 8, 6, 6, 10, 8, 13, 9, 10, 8, 8, 8, 5, 12, 5, 7, 4, 7, 9, 11, 3, 5, 8, 5, 9, 6, 9, 6, 7, 8, 8, 9, 5, 7, 9, 9, 10, 5, 8, 14, 10, 5, 9, 11, 10, 14, 13, 9, 7, 6, 6, 13, 6, 10, 6, 6, 12, 12, 6, 14, 4, 2, 9, 13, 5, 12, 5, 6, 14, 12, 11, 4, 1, 4, 10, 9, 6, 14, 9, 9, 6, 8, 5, 11, 7, 16]\n",
      "Genrtn 309: mean = 8.15  stddev = 2.67348087705897  max = 14 [5, 6, 10, 12, 9, 6, 9, 8, 11, 7, 8, 12, 11, 10, 6, 7, 10, 8, 11, 3, 8, 11, 10, 6, 8, 10, 12, 8, 10, 9, 11, 4, 10, 7, 7, 11, 7, 12, 5, 8, 6, 5, 7, 7, 8, 12, 5, 9, 9, 13, 8, 12, 4, 6, 12, 8, 5, 7, 10, 9, 5, 4, 11, 12, 6, 9, 4, 7, 7, 12, 14, 2, 5, 3, 5, 8, 10, 10, 6, 6, 11, 8, 7, 12, 11, 6, 10, 8, 3, 10, 7, 10, 4, 12, 8, 11, 8, 4, 9, 10, 8, 9, 3, 6, 5, 11, 4, 11, 4, 8, 6, 8, 8, 12, 10, 13, 12, 10, 10, 4, 8, 8, 6, 8, 5, 6, 7, 11, 11, 9, 9, 5, 6, 8, 8, 9, 5, 12, 13, 6, 9, 10, 9, 10, 12, 12, 9, 4, 8, 2, 11, 6, 9, 5, 9, 9, 7, 12, 7, 11, 5, 7, 9, 6, 12, 5, 5, 4, 13, 7, 11, 11, 9, 2, 6, 12, 9, 3, 8, 4, 8, 9, 8, 7, 8, 7, 7, 7, 13, 8, 9, 9, 11, 8, 6, 9, 8, 11, 11, 5]\n",
      "Genrtn 310: mean = 7.71  stddev = 2.7651220587887257  max = 16 [11, 12, 13, 9, 10, 7, 4, 2, 8, 5, 12, 9, 10, 6, 8, 11, 8, 12, 6, 9, 6, 10, 15, 11, 13, 8, 12, 8, 5, 6, 3, 9, 9, 8, 5, 6, 4, 10, 3, 10, 11, 10, 6, 7, 7, 3, 10, 3, 9, 4, 6, 6, 13, 8, 5, 5, 6, 8, 8, 7, 5, 7, 9, 11, 7, 11, 9, 5, 9, 11, 8, 6, 5, 6, 10, 4, 11, 8, 10, 7, 8, 10, 4, 6, 4, 6, 5, 8, 7, 11, 3, 6, 8, 9, 4, 12, 6, 3, 8, 8, 8, 6, 9, 7, 5, 6, 5, 5, 7, 6, 10, 8, 6, 8, 10, 6, 7, 8, 10, 5, 6, 6, 11, 8, 8, 8, 11, 12, 7, 6, 15, 5, 11, 3, 5, 5, 6, 9, 10, 8, 8, 12, 14, 6, 3, 11, 6, 6, 4, 10, 8, 8, 6, 9, 9, 8, 9, 6, 7, 7, 11, 4, 5, 16, 5, 8, 11, 3, 5, 7, 7, 7, 4, 12, 7, 9, 11, 10, 15, 4, 15, 9, 9, 7, 7, 8, 3, 10, 8, 6, 7, 11, 4, 5, 7, 7, 6, 7, 7, 9]\n",
      "Genrtn 311: mean = 8.175  stddev = 2.8713019694904958  max = 17 [8, 9, 11, 8, 10, 8, 10, 6, 11, 9, 12, 11, 7, 8, 8, 8, 10, 8, 11, 15, 12, 10, 4, 13, 7, 10, 6, 9, 5, 8, 4, 7, 4, 6, 9, 7, 7, 3, 9, 8, 8, 14, 5, 7, 7, 6, 9, 11, 6, 5, 13, 9, 9, 2, 7, 1, 11, 6, 5, 8, 12, 2, 5, 11, 6, 6, 8, 9, 5, 6, 4, 8, 4, 14, 9, 9, 8, 14, 10, 3, 6, 8, 7, 7, 7, 8, 5, 17, 5, 10, 9, 13, 14, 5, 6, 7, 13, 7, 7, 13, 7, 11, 11, 12, 4, 8, 5, 7, 10, 8, 6, 6, 7, 9, 12, 13, 8, 9, 7, 10, 12, 10, 5, 4, 7, 10, 8, 8, 8, 5, 5, 7, 13, 13, 7, 3, 7, 8, 9, 6, 5, 5, 4, 10, 9, 12, 9, 5, 7, 7, 13, 12, 11, 5, 7, 5, 8, 11, 8, 7, 4, 9, 10, 6, 5, 6, 8, 7, 8, 6, 8, 10, 8, 14, 12, 10, 10, 8, 6, 8, 7, 16, 12, 10, 7, 10, 5, 10, 11, 7, 9, 3, 7, 7, 7, 13, 11, 7, 6, 10]\n",
      "Genrtn 312: mean = 8.21  stddev = 2.7992677613976125  max = 17 [10, 9, 7, 8, 8, 6, 12, 9, 13, 11, 6, 7, 4, 5, 10, 11, 5, 8, 6, 7, 8, 6, 9, 9, 10, 7, 8, 6, 5, 7, 2, 5, 6, 7, 4, 6, 16, 4, 5, 10, 11, 8, 7, 6, 7, 3, 5, 4, 2, 7, 5, 5, 17, 6, 9, 9, 8, 11, 11, 10, 5, 6, 9, 4, 8, 11, 9, 12, 11, 4, 12, 8, 7, 12, 11, 9, 4, 7, 6, 13, 7, 8, 10, 11, 8, 5, 11, 7, 8, 7, 11, 13, 13, 6, 13, 9, 6, 9, 8, 14, 8, 5, 9, 6, 7, 15, 8, 8, 10, 6, 4, 4, 10, 11, 8, 8, 12, 7, 7, 8, 11, 11, 9, 5, 7, 6, 5, 10, 7, 9, 9, 7, 11, 7, 14, 11, 5, 10, 11, 8, 8, 7, 8, 5, 8, 7, 11, 7, 6, 4, 6, 2, 11, 6, 8, 4, 9, 10, 10, 10, 5, 11, 15, 7, 11, 8, 11, 6, 12, 8, 6, 8, 6, 5, 8, 10, 7, 7, 10, 7, 9, 8, 9, 9, 11, 8, 9, 5, 8, 13, 9, 13, 4, 8, 11, 17, 8, 10, 9, 10]\n",
      "Genrtn 313: mean = 7.89  stddev = 2.41824316395188  max = 14 [7, 13, 8, 14, 4, 12, 10, 11, 7, 6, 10, 12, 6, 8, 6, 5, 4, 7, 5, 6, 8, 8, 7, 14, 12, 7, 8, 7, 6, 10, 8, 6, 4, 8, 6, 7, 10, 10, 8, 9, 9, 9, 4, 7, 7, 7, 12, 5, 7, 8, 10, 9, 6, 12, 6, 11, 11, 4, 10, 8, 11, 13, 6, 6, 8, 8, 4, 8, 7, 5, 4, 8, 9, 6, 12, 7, 5, 7, 5, 8, 7, 9, 8, 4, 5, 10, 6, 9, 7, 7, 5, 11, 8, 7, 7, 8, 4, 7, 7, 9, 8, 7, 11, 8, 10, 7, 7, 10, 9, 14, 8, 11, 10, 9, 5, 5, 3, 5, 4, 9, 8, 7, 11, 9, 5, 7, 7, 7, 8, 10, 4, 8, 6, 8, 7, 11, 4, 12, 11, 6, 10, 5, 10, 4, 11, 13, 5, 9, 4, 8, 4, 7, 9, 8, 10, 7, 10, 6, 10, 11, 9, 11, 8, 7, 10, 9, 7, 11, 7, 8, 8, 6, 6, 8, 9, 10, 8, 11, 5, 9, 11, 3, 6, 9, 8, 11, 8, 12, 8, 8, 9, 4, 7, 6, 9, 13, 6, 3, 8, 7]\n",
      "Genrtn 314: mean = 7.925  stddev = 2.799888390632741  max = 16 [8, 6, 5, 3, 15, 4, 10, 9, 6, 11, 15, 6, 8, 12, 6, 3, 9, 11, 9, 8, 10, 6, 11, 10, 9, 9, 10, 5, 6, 10, 11, 14, 5, 5, 7, 2, 14, 9, 6, 2, 6, 11, 10, 7, 5, 10, 9, 8, 5, 6, 4, 5, 3, 9, 7, 9, 13, 9, 5, 8, 6, 6, 3, 5, 11, 5, 4, 7, 7, 12, 7, 5, 8, 6, 9, 12, 11, 6, 5, 12, 8, 6, 12, 9, 9, 6, 8, 13, 8, 9, 10, 5, 5, 11, 5, 9, 11, 8, 5, 8, 4, 10, 11, 13, 9, 7, 6, 9, 9, 8, 6, 8, 6, 6, 10, 10, 7, 8, 3, 6, 5, 10, 11, 5, 6, 9, 7, 5, 11, 9, 8, 6, 7, 6, 5, 9, 8, 6, 7, 6, 11, 9, 9, 16, 14, 9, 7, 7, 11, 7, 13, 7, 9, 10, 9, 7, 3, 4, 11, 13, 10, 5, 11, 11, 6, 14, 6, 8, 7, 6, 9, 4, 7, 2, 10, 6, 5, 9, 7, 9, 10, 14, 9, 8, 7, 10, 2, 8, 10, 8, 8, 8, 5, 8, 5, 10, 8, 7, 10, 4]\n",
      "Genrtn 315: mean = 8.445  stddev = 2.7869293137788764  max = 16 [8, 10, 14, 7, 7, 6, 10, 11, 5, 8, 7, 14, 10, 13, 7, 9, 8, 9, 5, 8, 6, 4, 5, 12, 6, 11, 8, 10, 10, 15, 15, 9, 10, 7, 8, 14, 6, 11, 9, 12, 11, 8, 10, 5, 5, 7, 7, 12, 6, 7, 10, 5, 8, 6, 6, 4, 7, 7, 10, 6, 10, 6, 3, 12, 7, 5, 9, 7, 5, 10, 10, 7, 10, 11, 5, 5, 8, 9, 8, 10, 9, 7, 6, 10, 7, 6, 3, 9, 9, 8, 8, 8, 9, 7, 5, 13, 14, 8, 9, 10, 8, 14, 8, 5, 7, 6, 11, 4, 10, 7, 6, 8, 13, 7, 13, 7, 13, 10, 11, 9, 6, 6, 9, 9, 5, 12, 8, 8, 7, 15, 5, 4, 9, 7, 7, 9, 6, 9, 8, 10, 6, 9, 6, 11, 1, 4, 7, 9, 10, 7, 13, 9, 8, 10, 6, 6, 5, 3, 6, 13, 7, 5, 7, 12, 10, 7, 9, 12, 6, 11, 8, 8, 4, 7, 11, 10, 11, 9, 11, 8, 11, 14, 5, 9, 14, 7, 5, 14, 12, 16, 13, 11, 8, 6, 6, 8, 8, 11, 10, 10]\n",
      "Genrtn 316: mean = 8.15  stddev = 2.692118125194361  max = 16 [3, 9, 5, 9, 13, 10, 12, 6, 15, 8, 6, 12, 11, 10, 5, 7, 9, 12, 6, 2, 8, 3, 9, 9, 3, 14, 9, 8, 9, 10, 7, 8, 9, 9, 9, 9, 11, 8, 9, 9, 5, 8, 6, 7, 13, 12, 4, 10, 7, 8, 8, 7, 10, 5, 10, 13, 9, 9, 10, 6, 6, 5, 14, 5, 10, 9, 10, 5, 9, 5, 6, 2, 7, 10, 7, 7, 11, 8, 4, 9, 10, 3, 10, 10, 7, 11, 5, 7, 7, 8, 8, 14, 12, 8, 6, 7, 11, 13, 8, 8, 8, 7, 7, 6, 11, 8, 8, 9, 12, 7, 9, 7, 5, 8, 7, 14, 9, 8, 7, 8, 8, 8, 2, 8, 10, 6, 9, 6, 8, 6, 12, 10, 6, 10, 10, 12, 7, 8, 7, 10, 7, 7, 6, 3, 4, 9, 5, 8, 3, 6, 4, 7, 12, 6, 8, 12, 8, 7, 12, 7, 5, 10, 11, 11, 5, 10, 5, 8, 9, 8, 3, 8, 4, 4, 6, 12, 7, 8, 5, 8, 16, 6, 6, 10, 12, 11, 5, 5, 8, 12, 9, 10, 7, 7, 10, 11, 12, 11, 7, 10]\n",
      "Genrtn 317: mean = 7.825  stddev = 2.7900492827188557  max = 18 [6, 8, 6, 2, 4, 8, 12, 12, 4, 8, 8, 7, 12, 12, 8, 8, 11, 5, 7, 6, 6, 6, 11, 10, 13, 8, 6, 10, 6, 4, 12, 7, 5, 7, 9, 10, 4, 8, 11, 6, 7, 12, 8, 13, 5, 5, 8, 8, 6, 9, 5, 4, 9, 9, 4, 7, 10, 9, 10, 5, 8, 7, 10, 7, 10, 10, 4, 10, 8, 15, 9, 16, 6, 13, 10, 15, 12, 6, 7, 7, 5, 6, 12, 11, 9, 4, 11, 10, 8, 7, 6, 10, 9, 6, 11, 13, 11, 6, 3, 9, 4, 10, 5, 9, 9, 6, 10, 8, 7, 7, 7, 5, 10, 4, 6, 11, 9, 9, 5, 7, 6, 11, 6, 11, 5, 12, 10, 4, 10, 7, 8, 9, 10, 9, 10, 10, 6, 10, 5, 2, 7, 9, 6, 6, 6, 8, 5, 6, 6, 3, 3, 6, 8, 6, 7, 8, 8, 5, 8, 8, 4, 9, 6, 11, 13, 3, 18, 9, 4, 4, 7, 6, 11, 13, 5, 7, 8, 6, 6, 7, 7, 8, 14, 5, 5, 5, 6, 6, 10, 4, 5, 9, 10, 8, 8, 9, 9, 8, 5, 6]\n",
      "Genrtn 318: mean = 7.88  stddev = 2.9825492451927764  max = 17 [7, 5, 8, 6, 8, 11, 17, 8, 11, 2, 8, 8, 7, 11, 7, 6, 6, 4, 5, 7, 3, 5, 7, 10, 9, 9, 7, 10, 5, 9, 7, 12, 10, 3, 9, 10, 3, 9, 3, 8, 4, 8, 12, 7, 12, 9, 10, 11, 11, 8, 7, 2, 5, 13, 10, 7, 11, 7, 3, 6, 6, 4, 3, 11, 10, 9, 6, 11, 10, 3, 3, 13, 3, 11, 8, 9, 9, 11, 8, 6, 8, 5, 4, 7, 9, 9, 4, 2, 6, 6, 6, 10, 9, 8, 6, 8, 3, 4, 8, 15, 11, 12, 7, 6, 10, 7, 7, 4, 8, 10, 8, 7, 9, 9, 9, 8, 12, 10, 8, 7, 9, 11, 8, 9, 7, 8, 7, 13, 8, 3, 9, 6, 9, 9, 12, 12, 9, 12, 12, 9, 8, 8, 11, 7, 8, 9, 4, 4, 9, 4, 6, 15, 11, 6, 9, 7, 2, 13, 15, 10, 13, 7, 6, 10, 8, 1, 13, 7, 10, 4, 9, 7, 9, 10, 9, 7, 6, 11, 15, 6, 9, 11, 8, 5, 6, 7, 7, 6, 1, 4, 7, 7, 8, 2, 9, 11, 5, 11, 10, 3]\n",
      "Genrtn 319: mean = 7.945  stddev = 2.6780543310396077  max = 17 [7, 15, 6, 6, 7, 5, 9, 10, 13, 10, 9, 8, 4, 8, 10, 6, 7, 15, 9, 9, 7, 6, 9, 4, 10, 8, 7, 11, 7, 4, 6, 6, 5, 8, 8, 4, 5, 7, 5, 8, 8, 10, 5, 1, 3, 6, 4, 11, 8, 13, 6, 10, 17, 6, 6, 15, 9, 14, 6, 9, 7, 9, 9, 7, 3, 8, 10, 6, 4, 9, 9, 10, 9, 6, 8, 6, 7, 7, 8, 9, 9, 12, 8, 9, 9, 13, 8, 4, 3, 6, 10, 10, 5, 4, 5, 13, 8, 8, 4, 12, 9, 4, 6, 8, 8, 8, 7, 5, 8, 9, 12, 6, 9, 5, 10, 8, 11, 10, 10, 9, 8, 10, 8, 11, 10, 5, 5, 10, 6, 8, 8, 7, 10, 4, 12, 8, 7, 5, 4, 3, 7, 8, 12, 9, 8, 9, 8, 6, 10, 8, 9, 9, 7, 12, 5, 6, 10, 9, 5, 7, 8, 10, 7, 11, 2, 7, 11, 7, 9, 7, 10, 8, 6, 6, 7, 11, 8, 11, 9, 7, 2, 13, 9, 8, 15, 9, 6, 10, 4, 5, 8, 11, 4, 8, 9, 9, 9, 10, 9, 8]\n",
      "Genrtn 320: mean = 7.935  stddev = 2.735100546597876  max = 16 [7, 6, 13, 8, 14, 10, 6, 9, 11, 4, 7, 6, 9, 8, 11, 3, 6, 12, 10, 10, 6, 6, 9, 9, 11, 5, 12, 6, 14, 9, 6, 8, 8, 3, 5, 10, 8, 8, 8, 4, 3, 10, 8, 9, 8, 8, 8, 7, 8, 7, 2, 10, 6, 9, 8, 14, 11, 9, 3, 8, 10, 9, 11, 11, 11, 2, 9, 4, 7, 10, 6, 7, 7, 10, 3, 6, 7, 10, 6, 7, 11, 10, 11, 4, 6, 10, 8, 4, 9, 10, 9, 9, 8, 6, 8, 6, 8, 5, 8, 8, 16, 8, 6, 5, 5, 10, 8, 8, 4, 10, 5, 8, 4, 7, 5, 9, 8, 6, 8, 10, 4, 10, 10, 7, 7, 1, 6, 12, 5, 13, 11, 8, 8, 8, 8, 16, 5, 13, 9, 9, 11, 7, 4, 8, 6, 8, 9, 10, 6, 10, 13, 12, 4, 7, 12, 7, 10, 7, 8, 7, 11, 8, 5, 7, 5, 10, 4, 9, 13, 13, 7, 7, 9, 4, 8, 10, 7, 9, 12, 2, 11, 5, 9, 5, 9, 7, 9, 8, 7, 7, 6, 11, 4, 7, 8, 12, 4, 3, 8, 9]\n",
      "Genrtn 321: mean = 8.29  stddev = 2.876786401525146  max = 19 [9, 9, 11, 13, 6, 11, 7, 6, 12, 9, 5, 12, 6, 8, 7, 13, 6, 11, 14, 7, 7, 12, 10, 9, 3, 5, 9, 9, 5, 10, 7, 8, 4, 12, 15, 6, 16, 10, 11, 14, 5, 5, 9, 7, 12, 6, 8, 3, 8, 10, 9, 8, 12, 10, 6, 5, 7, 11, 10, 4, 5, 6, 5, 5, 8, 10, 12, 10, 10, 10, 10, 5, 3, 9, 11, 10, 6, 8, 6, 10, 9, 9, 7, 4, 5, 14, 10, 9, 6, 10, 8, 6, 6, 5, 10, 7, 5, 11, 13, 9, 7, 8, 6, 9, 9, 4, 4, 9, 7, 7, 12, 5, 11, 10, 8, 8, 7, 12, 10, 8, 11, 11, 11, 9, 10, 4, 8, 8, 8, 8, 12, 6, 4, 9, 19, 3, 3, 8, 9, 13, 7, 11, 4, 11, 4, 12, 4, 7, 9, 9, 5, 10, 8, 11, 10, 9, 6, 11, 11, 6, 11, 12, 11, 10, 11, 6, 9, 5, 4, 6, 4, 5, 16, 8, 10, 1, 6, 11, 4, 8, 7, 10, 7, 7, 10, 8, 7, 7, 8, 6, 10, 10, 9, 4, 6, 8, 9, 9, 9, 8]\n",
      "Genrtn 322: mean = 8.365  stddev = 2.8760693663401096  max = 16 [9, 12, 11, 6, 9, 11, 7, 9, 5, 10, 11, 9, 8, 5, 9, 6, 6, 13, 11, 9, 6, 9, 5, 6, 7, 4, 13, 7, 8, 6, 7, 6, 11, 1, 13, 9, 6, 7, 9, 6, 12, 12, 6, 5, 10, 14, 7, 7, 9, 16, 10, 3, 8, 11, 7, 5, 6, 10, 5, 6, 4, 9, 12, 10, 14, 8, 9, 6, 6, 6, 12, 9, 8, 10, 11, 10, 7, 12, 8, 9, 11, 5, 9, 3, 5, 4, 7, 8, 11, 12, 6, 5, 12, 10, 11, 13, 8, 8, 13, 7, 5, 9, 13, 5, 13, 7, 8, 10, 4, 10, 8, 5, 3, 10, 13, 15, 11, 8, 6, 7, 8, 6, 7, 11, 8, 13, 13, 5, 7, 6, 7, 13, 8, 4, 13, 9, 12, 9, 6, 10, 6, 6, 10, 10, 7, 4, 12, 7, 5, 8, 14, 10, 1, 9, 7, 8, 3, 7, 4, 7, 6, 12, 6, 5, 7, 9, 13, 7, 10, 11, 10, 12, 9, 13, 7, 9, 11, 3, 5, 8, 8, 6, 9, 7, 3, 6, 6, 12, 8, 10, 12, 7, 8, 9, 11, 10, 9, 10, 10, 10]\n",
      "Genrtn 323: mean = 7.78  stddev = 2.8795138478569604  max = 17 [8, 10, 2, 7, 8, 6, 6, 8, 11, 2, 10, 9, 9, 10, 10, 14, 10, 9, 8, 9, 8, 5, 3, 5, 6, 7, 7, 2, 6, 8, 6, 12, 10, 5, 5, 8, 6, 6, 3, 5, 7, 8, 4, 11, 7, 13, 12, 9, 12, 7, 8, 11, 13, 11, 7, 7, 9, 9, 6, 9, 15, 10, 9, 7, 9, 5, 8, 5, 10, 6, 6, 7, 13, 1, 8, 7, 5, 11, 6, 3, 10, 4, 8, 11, 7, 5, 10, 7, 9, 8, 10, 7, 5, 4, 9, 9, 6, 11, 13, 8, 8, 7, 13, 8, 6, 9, 5, 10, 4, 5, 4, 9, 5, 6, 10, 16, 10, 8, 10, 6, 9, 7, 8, 6, 7, 14, 5, 8, 4, 7, 11, 9, 10, 12, 8, 11, 5, 10, 7, 2, 7, 6, 4, 17, 11, 11, 9, 12, 2, 12, 5, 8, 7, 10, 6, 7, 8, 3, 11, 9, 6, 3, 4, 7, 6, 6, 8, 8, 10, 4, 9, 6, 8, 4, 7, 7, 8, 12, 9, 5, 8, 16, 13, 8, 9, 8, 3, 7, 8, 9, 9, 7, 4, 6, 5, 9, 9, 6, 3, 7]\n",
      "Genrtn 324: mean = 8.155  stddev = 2.670388548507501  max = 14 [5, 4, 9, 11, 5, 8, 9, 7, 3, 7, 5, 13, 4, 8, 10, 8, 8, 8, 5, 9, 11, 10, 9, 10, 4, 14, 14, 14, 4, 10, 9, 9, 9, 12, 12, 7, 12, 5, 9, 6, 11, 7, 7, 7, 3, 12, 7, 9, 9, 9, 11, 4, 8, 6, 7, 5, 9, 4, 8, 10, 7, 10, 8, 7, 12, 8, 6, 7, 6, 7, 8, 8, 6, 8, 8, 6, 10, 6, 9, 10, 7, 3, 6, 13, 5, 4, 11, 9, 13, 2, 6, 5, 14, 5, 6, 7, 10, 8, 12, 10, 8, 7, 10, 6, 6, 10, 9, 8, 8, 8, 13, 8, 5, 10, 9, 9, 12, 6, 12, 10, 13, 3, 7, 13, 8, 10, 7, 6, 12, 3, 10, 4, 10, 2, 11, 5, 10, 6, 11, 10, 12, 14, 7, 8, 8, 8, 8, 6, 6, 11, 11, 9, 7, 5, 7, 9, 8, 9, 8, 8, 4, 8, 13, 10, 9, 12, 8, 10, 9, 8, 4, 2, 5, 9, 11, 8, 4, 12, 7, 10, 8, 6, 6, 10, 7, 8, 8, 9, 11, 6, 11, 7, 9, 7, 11, 10, 6, 6, 10, 6]\n",
      "Genrtn 325: mean = 8.115  stddev = 2.5123246207446996  max = 15 [10, 11, 9, 11, 7, 9, 4, 12, 11, 5, 9, 11, 7, 8, 4, 6, 9, 7, 7, 9, 10, 5, 10, 5, 6, 7, 7, 9, 10, 8, 5, 7, 7, 8, 10, 9, 5, 11, 10, 11, 13, 4, 7, 8, 4, 8, 7, 8, 6, 7, 7, 8, 6, 6, 9, 9, 11, 13, 8, 4, 13, 11, 10, 9, 10, 6, 11, 6, 12, 12, 8, 9, 6, 12, 5, 9, 9, 10, 7, 3, 10, 6, 11, 11, 11, 7, 10, 8, 12, 9, 9, 5, 4, 11, 7, 11, 12, 11, 13, 10, 7, 4, 4, 6, 8, 10, 9, 9, 6, 13, 8, 11, 7, 8, 5, 3, 10, 10, 8, 4, 4, 9, 7, 8, 7, 11, 9, 8, 7, 4, 12, 7, 8, 6, 8, 15, 7, 12, 8, 7, 8, 8, 9, 10, 12, 6, 6, 6, 11, 10, 6, 8, 6, 14, 7, 10, 9, 13, 6, 10, 8, 3, 5, 6, 5, 7, 8, 10, 6, 7, 7, 11, 5, 5, 11, 6, 10, 9, 10, 7, 5, 5, 9, 13, 10, 6, 6, 7, 7, 9, 7, 5, 6, 5, 5, 7, 8, 10, 3, 10]\n",
      "Genrtn 326: mean = 7.855  stddev = 2.8729731986219433  max = 16 [10, 12, 6, 7, 6, 9, 13, 6, 7, 8, 5, 3, 4, 10, 5, 5, 14, 7, 10, 4, 7, 11, 13, 1, 7, 10, 5, 6, 14, 7, 12, 10, 4, 7, 6, 7, 16, 10, 6, 8, 9, 9, 12, 12, 8, 5, 3, 10, 7, 11, 6, 4, 9, 7, 10, 7, 9, 7, 8, 8, 11, 10, 4, 3, 4, 8, 9, 14, 7, 10, 10, 8, 11, 14, 11, 8, 6, 5, 6, 10, 7, 7, 11, 5, 5, 10, 4, 5, 8, 14, 7, 8, 8, 10, 6, 8, 12, 11, 8, 13, 6, 6, 5, 3, 9, 5, 10, 13, 1, 8, 8, 9, 3, 11, 5, 11, 8, 8, 4, 9, 8, 11, 8, 11, 11, 7, 8, 6, 9, 11, 2, 4, 9, 4, 2, 5, 10, 4, 3, 6, 10, 5, 11, 7, 4, 9, 5, 4, 6, 8, 11, 7, 8, 6, 7, 4, 13, 10, 5, 9, 8, 9, 10, 6, 8, 7, 11, 11, 7, 11, 9, 12, 6, 5, 6, 9, 12, 8, 8, 6, 10, 4, 10, 8, 9, 5, 5, 3, 9, 7, 9, 9, 13, 9, 10, 9, 6, 10, 5, 7]\n",
      "Genrtn 327: mean = 7.955  stddev = 2.6024939961506153  max = 16 [4, 10, 9, 9, 7, 9, 10, 6, 9, 7, 8, 8, 6, 5, 12, 7, 4, 11, 4, 11, 9, 6, 9, 11, 8, 10, 9, 4, 8, 14, 8, 7, 7, 2, 7, 7, 4, 5, 12, 10, 6, 16, 4, 8, 13, 6, 11, 11, 7, 7, 8, 9, 10, 8, 7, 3, 7, 9, 5, 11, 9, 4, 8, 9, 5, 12, 9, 7, 7, 4, 12, 10, 10, 5, 4, 6, 9, 10, 4, 9, 9, 7, 5, 7, 9, 6, 6, 5, 8, 9, 6, 8, 7, 10, 11, 11, 10, 8, 8, 7, 11, 14, 11, 8, 7, 5, 6, 6, 7, 10, 8, 10, 7, 5, 8, 9, 7, 9, 5, 11, 8, 8, 9, 9, 6, 4, 5, 10, 4, 10, 7, 5, 8, 11, 8, 9, 13, 8, 10, 5, 6, 10, 9, 13, 14, 11, 6, 4, 9, 4, 9, 4, 8, 9, 8, 10, 9, 9, 4, 7, 8, 7, 5, 8, 9, 8, 10, 9, 7, 13, 2, 6, 9, 11, 4, 6, 9, 6, 8, 6, 11, 7, 6, 10, 12, 10, 12, 6, 12, 5, 7, 5, 8, 11, 5, 16, 5, 5, 6, 8]\n",
      "Genrtn 328: mean = 8.15  stddev = 2.803123258081956  max = 19 [8, 5, 10, 8, 8, 6, 11, 3, 7, 7, 8, 7, 5, 5, 13, 5, 11, 8, 5, 10, 6, 6, 6, 6, 10, 8, 6, 5, 10, 10, 10, 9, 4, 7, 3, 13, 7, 8, 11, 12, 8, 10, 8, 11, 7, 5, 11, 8, 12, 9, 7, 9, 15, 3, 9, 7, 1, 8, 8, 3, 5, 7, 17, 6, 5, 11, 6, 4, 8, 5, 7, 8, 11, 6, 12, 15, 8, 9, 10, 7, 6, 4, 7, 4, 7, 6, 9, 11, 10, 6, 8, 3, 9, 9, 8, 4, 9, 6, 11, 6, 8, 13, 6, 5, 10, 8, 11, 10, 11, 7, 9, 4, 7, 11, 6, 6, 7, 9, 12, 9, 11, 10, 9, 6, 19, 4, 9, 10, 10, 9, 10, 13, 11, 8, 9, 4, 6, 8, 5, 11, 14, 11, 8, 12, 12, 5, 11, 8, 6, 9, 9, 8, 2, 5, 9, 12, 6, 7, 7, 12, 8, 4, 6, 5, 8, 5, 7, 7, 4, 12, 5, 6, 10, 8, 10, 7, 13, 10, 7, 9, 8, 9, 8, 10, 8, 7, 7, 8, 14, 11, 9, 6, 10, 7, 7, 10, 9, 12, 9, 10]\n",
      "Genrtn 329: mean = 8.275  stddev = 2.9153687588365216  max = 18 [7, 12, 8, 8, 11, 9, 12, 13, 7, 8, 13, 5, 5, 7, 8, 6, 7, 11, 9, 6, 8, 5, 5, 5, 10, 6, 10, 10, 14, 18, 8, 7, 5, 5, 9, 7, 2, 10, 9, 9, 13, 9, 8, 10, 13, 8, 5, 8, 10, 14, 5, 11, 10, 8, 11, 7, 10, 11, 10, 5, 10, 9, 7, 16, 13, 8, 5, 5, 6, 9, 4, 6, 5, 6, 11, 9, 7, 14, 3, 14, 8, 5, 9, 10, 12, 4, 6, 12, 6, 9, 9, 8, 7, 12, 7, 13, 7, 6, 7, 8, 4, 9, 7, 5, 11, 8, 6, 9, 9, 8, 9, 10, 5, 4, 1, 3, 7, 10, 6, 8, 17, 8, 12, 10, 6, 7, 5, 8, 10, 9, 10, 10, 9, 12, 4, 13, 11, 9, 11, 7, 7, 8, 8, 12, 2, 11, 15, 5, 3, 9, 6, 10, 10, 6, 5, 10, 10, 6, 5, 7, 8, 9, 7, 4, 8, 13, 13, 7, 4, 13, 8, 8, 12, 8, 8, 9, 13, 9, 5, 9, 4, 6, 3, 6, 10, 7, 7, 9, 9, 8, 8, 9, 5, 10, 9, 9, 6, 6, 8, 7]\n",
      "Genrtn 330: mean = 8.015  stddev = 2.9316846692644147  max = 17 [10, 12, 7, 6, 7, 8, 9, 7, 8, 4, 10, 6, 11, 8, 6, 7, 7, 11, 4, 6, 8, 4, 7, 7, 11, 7, 8, 4, 10, 10, 11, 5, 6, 9, 10, 9, 12, 6, 8, 4, 8, 6, 7, 9, 10, 7, 7, 7, 5, 7, 6, 11, 8, 8, 11, 7, 7, 15, 6, 8, 7, 7, 13, 8, 9, 4, 9, 11, 11, 12, 8, 12, 6, 7, 10, 17, 10, 9, 8, 5, 6, 10, 1, 11, 12, 7, 12, 4, 13, 11, 8, 6, 15, 4, 14, 12, 7, 9, 9, 8, 5, 6, 7, 4, 4, 9, 6, 12, 6, 8, 6, 9, 12, 8, 6, 5, 4, 7, 7, 12, 9, 15, 6, 1, 4, 10, 3, 7, 11, 6, 13, 5, 7, 9, 7, 12, 7, 4, 8, 8, 14, 7, 5, 8, 14, 9, 5, 8, 6, 10, 6, 13, 12, 6, 8, 5, 12, 3, 5, 6, 10, 7, 13, 9, 10, 14, 11, 8, 3, 9, 6, 7, 7, 4, 7, 9, 7, 11, 8, 5, 11, 9, 5, 12, 3, 3, 9, 9, 8, 4, 4, 6, 9, 11, 10, 12, 4, 4, 5, 11]\n",
      "Genrtn 331: mean = 8.16  stddev = 3.0780513316057614  max = 18 [6, 9, 3, 3, 3, 5, 5, 11, 5, 5, 8, 6, 12, 10, 9, 9, 6, 8, 11, 9, 13, 7, 7, 4, 4, 4, 10, 7, 6, 8, 9, 3, 11, 10, 5, 12, 6, 7, 18, 8, 10, 18, 8, 10, 16, 6, 8, 8, 6, 8, 8, 5, 11, 11, 10, 7, 6, 7, 5, 6, 14, 8, 5, 15, 5, 4, 9, 3, 13, 9, 11, 9, 9, 6, 4, 11, 10, 8, 9, 6, 10, 15, 7, 14, 8, 8, 6, 9, 6, 8, 15, 11, 9, 7, 5, 9, 3, 12, 9, 12, 5, 6, 5, 7, 7, 7, 8, 8, 5, 10, 7, 6, 8, 7, 10, 7, 5, 11, 5, 4, 10, 7, 9, 2, 7, 7, 3, 7, 10, 7, 12, 9, 9, 5, 5, 5, 6, 8, 5, 13, 9, 8, 10, 5, 6, 11, 8, 11, 4, 8, 13, 14, 12, 12, 10, 6, 14, 11, 11, 9, 6, 8, 10, 14, 7, 9, 12, 9, 6, 3, 15, 11, 7, 3, 7, 8, 6, 11, 6, 6, 7, 11, 8, 5, 5, 8, 9, 11, 11, 5, 7, 4, 12, 6, 8, 7, 13, 9, 6, 13]\n",
      "Genrtn 332: mean = 7.83  stddev = 2.830388665890252  max = 15 [8, 5, 6, 12, 8, 10, 6, 6, 9, 5, 9, 10, 5, 6, 10, 7, 9, 4, 5, 10, 8, 7, 6, 7, 9, 6, 5, 6, 8, 4, 8, 12, 12, 7, 3, 12, 8, 7, 7, 6, 8, 6, 8, 8, 11, 12, 6, 10, 3, 8, 4, 3, 8, 6, 10, 8, 7, 13, 11, 13, 9, 6, 11, 4, 3, 9, 8, 9, 5, 5, 4, 9, 6, 8, 2, 12, 12, 6, 13, 10, 3, 5, 6, 10, 11, 5, 9, 15, 6, 8, 8, 8, 7, 4, 4, 6, 7, 11, 13, 11, 7, 7, 7, 11, 5, 2, 8, 7, 11, 4, 11, 10, 5, 13, 8, 12, 9, 10, 7, 11, 8, 11, 6, 2, 4, 7, 11, 3, 12, 9, 14, 11, 10, 8, 12, 6, 13, 8, 9, 15, 7, 9, 7, 6, 10, 14, 5, 7, 8, 3, 5, 9, 10, 6, 6, 8, 10, 6, 6, 3, 8, 5, 9, 6, 6, 4, 11, 7, 7, 12, 11, 7, 11, 8, 5, 4, 6, 4, 2, 8, 9, 6, 11, 14, 9, 11, 8, 9, 10, 8, 6, 9, 7, 5, 9, 7, 9, 5, 9, 6]\n",
      "Genrtn 333: mean = 7.935  stddev = 2.9867666463920477  max = 18 [14, 9, 7, 5, 10, 9, 6, 5, 5, 6, 10, 11, 7, 4, 13, 5, 7, 6, 8, 7, 14, 3, 10, 3, 12, 9, 4, 11, 1, 5, 5, 10, 6, 11, 3, 11, 10, 10, 10, 10, 9, 8, 12, 9, 4, 7, 10, 7, 12, 5, 12, 7, 8, 8, 13, 8, 7, 8, 6, 7, 8, 11, 12, 6, 6, 12, 6, 6, 6, 9, 6, 4, 5, 9, 10, 12, 9, 7, 13, 6, 6, 6, 13, 4, 11, 1, 8, 7, 8, 13, 11, 4, 11, 7, 8, 6, 8, 9, 6, 10, 11, 7, 9, 4, 8, 14, 14, 4, 11, 10, 7, 10, 10, 8, 4, 3, 8, 5, 11, 5, 8, 12, 11, 9, 7, 9, 8, 6, 9, 7, 11, 4, 18, 8, 2, 9, 8, 6, 4, 1, 6, 13, 8, 10, 4, 11, 7, 7, 8, 9, 3, 8, 4, 10, 17, 6, 7, 7, 7, 6, 4, 9, 11, 6, 3, 4, 8, 12, 9, 8, 6, 10, 6, 8, 13, 7, 6, 6, 7, 7, 5, 14, 3, 8, 8, 8, 4, 11, 7, 10, 7, 11, 9, 5, 7, 8, 10, 7, 10, 8]\n",
      "Genrtn 334: mean = 7.93  stddev = 2.924910255033477  max = 17 [6, 8, 3, 8, 15, 7, 8, 10, 17, 5, 4, 11, 9, 6, 8, 8, 9, 5, 13, 8, 11, 9, 8, 12, 13, 3, 13, 9, 5, 6, 6, 7, 6, 10, 12, 10, 13, 6, 6, 6, 3, 7, 5, 4, 4, 7, 11, 6, 7, 7, 4, 6, 4, 9, 5, 11, 13, 6, 13, 3, 7, 10, 8, 11, 11, 5, 6, 4, 4, 6, 12, 11, 6, 10, 11, 11, 3, 8, 9, 10, 9, 11, 9, 6, 8, 7, 9, 14, 7, 8, 9, 11, 6, 12, 8, 8, 11, 6, 7, 6, 6, 9, 6, 11, 8, 7, 6, 10, 11, 7, 11, 7, 10, 12, 9, 8, 10, 5, 7, 3, 11, 6, 5, 11, 11, 5, 15, 6, 12, 10, 10, 11, 3, 6, 8, 13, 3, 6, 8, 7, 6, 5, 6, 7, 4, 6, 13, 9, 6, 2, 7, 9, 6, 8, 5, 12, 8, 4, 7, 7, 6, 11, 10, 5, 8, 10, 6, 9, 9, 4, 9, 8, 11, 7, 5, 9, 11, 13, 13, 14, 8, 10, 3, 6, 8, 5, 6, 4, 7, 14, 7, 5, 11, 7, 5, 5, 6, 4, 5, 6]\n",
      "Genrtn 335: mean = 7.945  stddev = 2.7353199081643083  max = 16 [8, 8, 7, 7, 6, 5, 11, 12, 9, 11, 7, 8, 10, 10, 3, 11, 8, 6, 16, 9, 8, 11, 10, 6, 4, 7, 7, 12, 6, 14, 7, 7, 7, 3, 14, 9, 7, 7, 10, 7, 2, 12, 6, 8, 8, 4, 8, 10, 9, 12, 10, 8, 6, 5, 4, 4, 5, 7, 3, 9, 10, 12, 10, 6, 11, 10, 5, 3, 8, 5, 8, 8, 6, 4, 7, 6, 6, 6, 7, 10, 6, 11, 8, 7, 12, 5, 5, 2, 3, 3, 8, 7, 8, 14, 8, 10, 4, 8, 5, 5, 7, 8, 8, 4, 10, 14, 10, 9, 7, 6, 8, 8, 5, 11, 8, 14, 12, 7, 10, 9, 6, 6, 2, 11, 8, 8, 8, 6, 4, 7, 11, 6, 11, 9, 10, 5, 7, 10, 7, 12, 10, 5, 6, 8, 8, 9, 12, 11, 8, 5, 7, 8, 6, 11, 11, 11, 7, 9, 12, 5, 6, 14, 9, 11, 7, 7, 10, 3, 10, 6, 11, 10, 12, 10, 8, 7, 13, 14, 10, 9, 8, 10, 10, 7, 8, 8, 4, 8, 6, 4, 5, 9, 7, 9, 6, 7, 9, 4, 5, 8]\n",
      "Genrtn 336: mean = 8.22  stddev = 2.9413602295536667  max = 18 [8, 8, 10, 5, 10, 9, 3, 9, 9, 6, 12, 5, 8, 8, 7, 12, 8, 11, 7, 13, 11, 6, 7, 7, 8, 8, 12, 5, 5, 8, 7, 8, 7, 7, 9, 15, 7, 7, 11, 10, 4, 6, 3, 6, 7, 6, 6, 11, 12, 5, 9, 8, 15, 7, 10, 8, 11, 14, 4, 8, 8, 9, 6, 6, 8, 11, 8, 10, 16, 9, 8, 9, 5, 11, 7, 10, 11, 8, 7, 6, 10, 7, 9, 10, 9, 6, 10, 3, 6, 11, 10, 13, 7, 6, 7, 8, 18, 9, 6, 5, 6, 11, 4, 14, 13, 3, 14, 9, 10, 7, 5, 10, 10, 6, 9, 6, 14, 2, 4, 9, 7, 4, 14, 6, 5, 15, 7, 5, 12, 13, 8, 7, 8, 11, 6, 10, 5, 10, 9, 6, 7, 9, 6, 3, 10, 4, 6, 6, 7, 5, 4, 11, 12, 8, 8, 11, 9, 4, 8, 9, 9, 4, 7, 11, 11, 8, 10, 7, 10, 14, 2, 3, 11, 7, 10, 6, 8, 4, 7, 12, 12, 8, 9, 7, 8, 12, 5, 3, 15, 8, 9, 10, 9, 10, 6, 5, 5, 8, 7, 10]\n",
      "Genrtn 337: mean = 8.265  stddev = 2.700884114507692  max = 16 [9, 5, 9, 10, 13, 6, 16, 12, 11, 10, 9, 14, 10, 11, 8, 3, 7, 7, 7, 7, 8, 6, 9, 7, 7, 4, 6, 12, 10, 5, 7, 11, 9, 7, 12, 16, 6, 8, 9, 4, 11, 10, 10, 9, 9, 12, 3, 5, 7, 11, 10, 4, 10, 8, 9, 6, 3, 13, 7, 4, 11, 7, 3, 5, 4, 10, 4, 10, 7, 8, 11, 6, 11, 3, 7, 13, 8, 9, 6, 6, 8, 12, 8, 15, 6, 10, 4, 10, 8, 13, 11, 11, 6, 12, 5, 10, 12, 9, 12, 9, 6, 9, 6, 5, 9, 9, 11, 7, 7, 7, 7, 4, 5, 12, 8, 9, 5, 8, 10, 9, 7, 8, 6, 5, 11, 10, 9, 6, 8, 9, 11, 9, 6, 11, 8, 8, 5, 6, 1, 10, 7, 11, 9, 6, 7, 8, 9, 10, 8, 9, 8, 10, 8, 7, 10, 6, 6, 6, 9, 8, 5, 7, 7, 15, 10, 6, 7, 4, 9, 9, 9, 13, 9, 11, 7, 6, 14, 7, 7, 12, 8, 10, 11, 7, 9, 11, 7, 10, 8, 7, 8, 10, 11, 3, 3, 11, 7, 7, 7, 7]\n",
      "Genrtn 338: mean = 7.805  stddev = 2.752630560027989  max = 15 [7, 6, 10, 3, 7, 1, 9, 8, 8, 9, 12, 4, 8, 4, 10, 3, 7, 9, 6, 9, 6, 9, 7, 6, 12, 8, 7, 5, 7, 11, 6, 9, 6, 14, 7, 10, 4, 9, 11, 5, 6, 12, 5, 14, 8, 6, 11, 12, 8, 7, 5, 7, 8, 8, 8, 5, 11, 7, 11, 8, 1, 10, 8, 8, 12, 11, 7, 10, 8, 8, 9, 8, 5, 9, 7, 6, 10, 13, 4, 8, 5, 6, 3, 6, 11, 5, 10, 8, 15, 6, 7, 7, 7, 5, 9, 3, 3, 7, 8, 7, 10, 9, 6, 12, 5, 9, 9, 8, 10, 8, 8, 10, 9, 7, 5, 3, 11, 9, 11, 9, 11, 11, 12, 5, 3, 6, 8, 10, 10, 5, 13, 9, 10, 5, 3, 12, 8, 9, 6, 4, 8, 11, 11, 10, 8, 10, 5, 7, 3, 7, 14, 3, 8, 10, 7, 7, 8, 9, 4, 4, 12, 14, 7, 6, 5, 4, 5, 4, 10, 6, 6, 11, 9, 8, 7, 4, 6, 10, 14, 8, 8, 6, 7, 9, 8, 6, 10, 12, 8, 5, 12, 5, 7, 6, 7, 8, 8, 9, 13, 3]\n",
      "Genrtn 339: mean = 8.21  stddev = 2.6713105397912837  max = 16 [5, 9, 11, 8, 5, 9, 10, 2, 5, 10, 3, 14, 8, 6, 8, 2, 8, 6, 8, 9, 8, 6, 12, 16, 8, 9, 4, 12, 9, 9, 9, 7, 8, 9, 4, 7, 10, 10, 7, 12, 8, 12, 11, 8, 7, 11, 8, 9, 4, 12, 8, 11, 9, 7, 8, 6, 5, 6, 4, 9, 10, 2, 6, 5, 7, 10, 6, 8, 8, 9, 11, 11, 15, 7, 10, 8, 8, 15, 8, 11, 8, 5, 12, 7, 6, 11, 12, 9, 7, 8, 9, 7, 6, 4, 11, 9, 9, 15, 7, 9, 9, 12, 7, 6, 8, 7, 8, 9, 8, 6, 7, 7, 9, 9, 6, 10, 11, 7, 3, 9, 8, 5, 4, 6, 8, 9, 10, 10, 10, 9, 12, 7, 5, 7, 13, 7, 7, 6, 7, 13, 5, 8, 9, 7, 9, 8, 5, 7, 8, 4, 14, 5, 10, 8, 10, 8, 9, 9, 9, 5, 15, 8, 9, 4, 6, 3, 6, 14, 2, 11, 5, 11, 7, 9, 10, 4, 11, 11, 9, 6, 10, 8, 13, 11, 8, 9, 8, 11, 12, 5, 8, 9, 6, 7, 6, 8, 7, 10, 8, 8]\n",
      "Genrtn 340: mean = 7.975  stddev = 2.95031777949427  max = 17 [5, 4, 5, 5, 4, 4, 4, 6, 9, 12, 8, 6, 9, 12, 9, 11, 7, 4, 5, 10, 9, 11, 7, 5, 9, 5, 6, 13, 5, 8, 12, 6, 11, 6, 14, 4, 3, 8, 8, 12, 8, 3, 5, 7, 10, 14, 3, 8, 7, 12, 6, 5, 7, 11, 7, 7, 4, 8, 13, 12, 15, 12, 10, 5, 13, 11, 6, 11, 7, 8, 8, 5, 10, 11, 10, 7, 13, 8, 7, 6, 11, 9, 9, 11, 8, 8, 11, 4, 8, 4, 6, 5, 6, 3, 8, 8, 3, 2, 9, 5, 7, 11, 9, 8, 6, 8, 8, 12, 6, 7, 5, 10, 7, 10, 11, 14, 6, 4, 8, 10, 8, 7, 4, 11, 5, 13, 4, 11, 11, 9, 7, 5, 13, 12, 5, 7, 3, 7, 6, 15, 9, 7, 9, 9, 7, 5, 12, 4, 11, 6, 5, 10, 14, 12, 8, 5, 9, 6, 11, 12, 7, 9, 8, 9, 7, 10, 9, 6, 6, 7, 5, 5, 12, 7, 5, 6, 11, 10, 8, 5, 17, 6, 8, 4, 9, 7, 5, 10, 10, 6, 7, 7, 6, 11, 14, 9, 10, 6, 3, 8]\n",
      "Genrtn 341: mean = 8.015  stddev = 3.0503729280204412  max = 18 [6, 7, 7, 3, 9, 7, 14, 6, 4, 9, 6, 11, 7, 6, 9, 7, 6, 9, 6, 12, 6, 16, 7, 8, 5, 2, 6, 10, 7, 7, 9, 4, 6, 6, 9, 8, 8, 11, 8, 11, 5, 7, 7, 8, 11, 5, 6, 7, 5, 13, 5, 6, 11, 10, 8, 4, 3, 13, 10, 7, 7, 13, 7, 10, 7, 5, 10, 9, 14, 12, 9, 10, 15, 15, 5, 5, 4, 8, 4, 9, 5, 5, 10, 13, 10, 8, 9, 7, 9, 5, 10, 7, 4, 9, 8, 10, 7, 3, 4, 8, 4, 11, 5, 8, 9, 10, 16, 8, 13, 3, 8, 12, 5, 4, 11, 3, 10, 8, 7, 16, 9, 6, 9, 10, 11, 5, 8, 5, 5, 6, 10, 7, 2, 8, 7, 7, 4, 12, 7, 9, 6, 10, 4, 7, 9, 7, 7, 18, 13, 11, 11, 9, 8, 6, 7, 17, 9, 10, 9, 10, 9, 6, 3, 7, 13, 6, 12, 12, 7, 9, 7, 6, 10, 5, 7, 10, 9, 9, 6, 10, 13, 3, 9, 11, 9, 7, 10, 5, 8, 8, 10, 6, 2, 9, 11, 9, 2, 8, 5, 4]\n",
      "Genrtn 342: mean = 7.995  stddev = 3.0174451113483407  max = 17 [14, 9, 10, 13, 9, 7, 3, 7, 5, 7, 4, 6, 8, 4, 11, 10, 14, 8, 12, 9, 8, 6, 7, 11, 6, 4, 2, 11, 11, 8, 11, 15, 6, 8, 5, 10, 9, 9, 4, 3, 5, 4, 15, 9, 7, 11, 4, 8, 13, 12, 8, 11, 10, 15, 8, 16, 7, 10, 5, 8, 4, 17, 7, 4, 7, 6, 6, 8, 9, 7, 11, 8, 12, 8, 3, 5, 7, 9, 4, 9, 12, 5, 5, 8, 10, 6, 10, 7, 12, 6, 7, 2, 11, 9, 5, 14, 16, 5, 7, 5, 11, 8, 2, 7, 4, 7, 11, 4, 12, 4, 13, 8, 5, 7, 7, 6, 3, 12, 8, 9, 11, 11, 7, 4, 8, 9, 9, 10, 9, 7, 12, 9, 7, 8, 12, 9, 6, 8, 6, 11, 8, 7, 8, 9, 7, 10, 7, 4, 7, 6, 6, 12, 6, 6, 7, 11, 10, 8, 4, 10, 7, 10, 10, 7, 7, 9, 13, 14, 9, 6, 7, 12, 5, 7, 8, 6, 6, 5, 10, 8, 8, 8, 5, 7, 7, 6, 5, 4, 4, 6, 2, 5, 5, 9, 13, 6, 8, 10, 12, 6]\n",
      "Genrtn 343: mean = 8.45  stddev = 2.693974758604839  max = 17 [7, 11, 9, 5, 5, 8, 6, 7, 12, 13, 5, 6, 10, 5, 9, 4, 7, 7, 10, 9, 5, 14, 12, 8, 10, 9, 8, 10, 6, 10, 8, 7, 10, 5, 8, 5, 13, 9, 11, 7, 10, 12, 11, 7, 11, 8, 13, 9, 1, 7, 11, 10, 6, 8, 5, 12, 4, 10, 8, 7, 6, 8, 11, 9, 11, 14, 6, 4, 8, 6, 6, 12, 4, 8, 8, 8, 9, 9, 11, 12, 10, 11, 10, 17, 10, 14, 11, 10, 13, 8, 9, 8, 12, 7, 9, 4, 8, 5, 2, 6, 7, 7, 9, 13, 9, 9, 5, 10, 4, 13, 5, 11, 6, 17, 6, 11, 10, 13, 12, 9, 11, 6, 8, 8, 7, 4, 8, 8, 7, 9, 7, 5, 8, 8, 11, 10, 11, 8, 10, 8, 11, 9, 12, 7, 10, 9, 9, 8, 10, 9, 5, 9, 9, 7, 9, 6, 6, 9, 10, 10, 9, 5, 10, 14, 2, 6, 10, 12, 11, 9, 12, 4, 11, 7, 7, 6, 6, 6, 8, 9, 8, 6, 3, 7, 7, 9, 8, 8, 10, 11, 7, 6, 7, 5, 5, 9, 10, 6, 11, 7]\n",
      "Genrtn 344: mean = 7.795  stddev = 2.7609735601776415  max = 15 [11, 8, 9, 5, 3, 5, 3, 8, 8, 10, 14, 10, 6, 5, 3, 4, 7, 5, 2, 6, 6, 8, 10, 5, 11, 7, 7, 8, 8, 3, 7, 8, 11, 4, 8, 10, 12, 5, 7, 10, 6, 10, 10, 10, 8, 7, 2, 11, 8, 7, 11, 7, 6, 5, 8, 10, 5, 9, 11, 6, 8, 8, 14, 7, 4, 7, 10, 7, 12, 5, 8, 10, 11, 12, 9, 5, 6, 11, 9, 10, 13, 9, 12, 10, 7, 7, 7, 4, 13, 7, 14, 4, 10, 4, 9, 15, 8, 7, 6, 9, 5, 10, 10, 2, 8, 8, 9, 11, 10, 5, 12, 10, 6, 6, 7, 12, 6, 9, 4, 5, 5, 6, 7, 4, 8, 9, 7, 7, 10, 9, 10, 10, 6, 7, 9, 6, 11, 5, 10, 7, 5, 10, 6, 10, 7, 6, 7, 10, 8, 5, 8, 9, 1, 8, 4, 12, 8, 7, 5, 11, 10, 6, 5, 14, 8, 8, 10, 3, 9, 4, 10, 3, 13, 7, 7, 7, 9, 9, 3, 9, 6, 8, 12, 9, 4, 7, 7, 2, 8, 6, 9, 9, 13, 8, 3, 9, 12, 7, 7, 12]\n",
      "Genrtn 345: mean = 7.895  stddev = 2.7155063984457852  max = 16 [6, 8, 4, 9, 2, 9, 4, 8, 10, 4, 10, 7, 9, 9, 7, 8, 9, 8, 11, 10, 8, 10, 7, 4, 5, 11, 8, 8, 7, 7, 13, 7, 5, 15, 7, 16, 8, 8, 9, 7, 11, 3, 4, 2, 7, 6, 9, 6, 13, 9, 8, 5, 8, 5, 8, 7, 8, 11, 2, 7, 6, 4, 8, 10, 6, 10, 4, 9, 11, 5, 7, 10, 5, 10, 7, 7, 5, 7, 8, 7, 5, 10, 9, 9, 5, 5, 10, 10, 3, 9, 5, 6, 11, 11, 11, 3, 9, 5, 4, 10, 8, 7, 8, 7, 8, 9, 7, 8, 6, 11, 10, 5, 9, 11, 6, 10, 9, 12, 6, 6, 8, 10, 9, 10, 11, 5, 8, 7, 7, 11, 7, 10, 6, 12, 6, 6, 13, 6, 12, 7, 5, 9, 7, 6, 12, 3, 14, 14, 7, 8, 9, 7, 8, 5, 8, 6, 9, 9, 12, 9, 8, 5, 9, 6, 5, 9, 7, 11, 11, 3, 15, 10, 4, 11, 5, 11, 6, 14, 5, 4, 9, 10, 9, 7, 5, 9, 5, 10, 6, 10, 12, 10, 2, 4, 9, 7, 6, 12, 10, 10]\n",
      "Genrtn 346: mean = 8.29  stddev = 2.825933474093118  max = 18 [6, 5, 10, 12, 7, 6, 7, 10, 7, 10, 3, 5, 5, 5, 5, 9, 5, 10, 5, 16, 8, 7, 4, 15, 10, 7, 5, 15, 10, 12, 9, 15, 7, 6, 8, 10, 8, 9, 11, 12, 7, 9, 9, 8, 10, 2, 5, 11, 9, 8, 9, 11, 11, 8, 8, 6, 15, 9, 10, 7, 6, 8, 7, 9, 13, 6, 10, 10, 5, 9, 12, 4, 5, 6, 9, 10, 7, 10, 9, 16, 10, 6, 4, 4, 8, 9, 9, 8, 9, 7, 6, 14, 8, 9, 8, 6, 13, 10, 6, 9, 1, 7, 9, 7, 7, 13, 7, 7, 7, 7, 12, 8, 8, 8, 7, 6, 4, 8, 8, 2, 9, 8, 9, 13, 11, 13, 8, 5, 14, 7, 6, 10, 12, 9, 11, 7, 8, 9, 7, 9, 7, 10, 4, 6, 7, 11, 9, 6, 9, 9, 11, 7, 6, 12, 11, 10, 10, 4, 8, 6, 12, 8, 10, 7, 3, 6, 6, 4, 7, 7, 8, 7, 7, 4, 7, 9, 8, 5, 6, 12, 12, 11, 10, 8, 7, 11, 7, 9, 9, 4, 7, 18, 12, 4, 11, 10, 10, 5, 9, 8]\n",
      "Genrtn 347: mean = 7.915  stddev = 2.770879824171377  max = 16 [5, 7, 8, 10, 10, 9, 11, 5, 6, 7, 8, 9, 6, 7, 9, 9, 5, 7, 9, 12, 5, 4, 8, 14, 4, 6, 12, 7, 4, 10, 7, 9, 8, 10, 8, 5, 5, 10, 8, 6, 8, 11, 11, 9, 6, 8, 7, 11, 10, 1, 4, 6, 2, 12, 7, 7, 6, 8, 5, 6, 9, 3, 6, 7, 5, 12, 7, 9, 9, 9, 6, 5, 5, 10, 9, 2, 11, 9, 8, 11, 10, 2, 5, 15, 9, 11, 8, 10, 4, 6, 11, 5, 5, 7, 8, 5, 15, 9, 8, 8, 4, 8, 11, 12, 10, 5, 2, 11, 12, 6, 9, 10, 8, 6, 3, 9, 12, 7, 8, 7, 7, 14, 11, 7, 8, 11, 7, 9, 12, 10, 8, 12, 5, 13, 8, 4, 9, 7, 7, 6, 7, 8, 8, 7, 4, 11, 16, 7, 4, 7, 5, 10, 7, 7, 12, 6, 3, 5, 8, 9, 9, 7, 7, 6, 3, 8, 8, 11, 9, 11, 6, 9, 7, 5, 14, 10, 7, 4, 9, 8, 11, 11, 6, 8, 6, 8, 11, 9, 9, 14, 13, 5, 7, 10, 7, 10, 10, 8, 5, 4]\n",
      "Genrtn 348: mean = 7.505  stddev = 2.439257059024325  max = 13 [8, 8, 6, 10, 6, 9, 10, 7, 5, 9, 8, 7, 8, 9, 11, 8, 9, 8, 9, 8, 4, 7, 7, 8, 11, 9, 8, 8, 6, 6, 7, 6, 7, 4, 13, 3, 8, 12, 4, 8, 6, 7, 8, 2, 11, 4, 8, 6, 6, 10, 10, 12, 4, 4, 10, 6, 6, 8, 8, 6, 10, 8, 4, 4, 6, 2, 13, 8, 3, 6, 8, 7, 6, 6, 10, 11, 9, 8, 12, 6, 4, 7, 8, 10, 10, 9, 9, 0, 6, 11, 7, 7, 8, 6, 10, 11, 5, 10, 5, 9, 10, 6, 5, 4, 8, 12, 7, 9, 6, 9, 6, 8, 5, 6, 9, 8, 3, 4, 9, 9, 12, 6, 9, 9, 6, 9, 3, 13, 8, 6, 7, 9, 7, 11, 5, 6, 4, 8, 7, 8, 7, 8, 7, 6, 5, 8, 8, 9, 7, 11, 9, 4, 9, 6, 7, 4, 6, 9, 6, 6, 8, 7, 6, 6, 12, 10, 13, 7, 10, 5, 13, 5, 8, 5, 5, 6, 8, 11, 8, 6, 10, 2, 6, 13, 8, 9, 9, 7, 7, 5, 8, 8, 11, 6, 6, 7, 6, 5, 13, 8]\n",
      "Genrtn 349: mean = 8.325  stddev = 3.0098795656969397  max = 16 [13, 8, 8, 9, 5, 12, 9, 8, 10, 14, 5, 9, 10, 5, 9, 7, 7, 6, 12, 13, 15, 7, 10, 8, 7, 8, 6, 12, 9, 12, 10, 11, 13, 4, 8, 9, 8, 8, 8, 12, 11, 5, 12, 8, 12, 12, 12, 7, 13, 9, 10, 7, 7, 10, 5, 7, 10, 7, 5, 11, 4, 13, 5, 7, 5, 5, 8, 7, 8, 9, 9, 9, 7, 4, 10, 9, 13, 7, 6, 5, 9, 9, 9, 8, 10, 12, 7, 7, 9, 8, 13, 4, 9, 12, 6, 9, 4, 6, 16, 10, 13, 8, 8, 8, 11, 8, 10, 10, 12, 7, 8, 7, 6, 4, 8, 9, 6, 4, 9, 15, 2, 16, 11, 11, 9, 8, 4, 7, 9, 3, 8, 9, 7, 5, 6, 6, 7, 3, 9, 7, 7, 8, 11, 8, 6, 13, 8, 4, 9, 7, 14, 9, 8, 12, 7, 7, 11, 15, 7, 7, 5, 8, 7, 11, 16, 5, 6, 8, 5, 8, 5, 4, 6, 5, 6, 5, 9, 5, 14, 9, 4, 4, 3, 5, 14, 12, 10, 7, 16, 5, 2, 14, 6, 3, 5, 9, 8, 8, 7, 9]\n",
      "Genrtn 350: mean = 7.845  stddev = 2.810867303876154  max = 18 [10, 5, 10, 7, 7, 7, 7, 5, 5, 3, 11, 8, 7, 12, 5, 7, 7, 7, 7, 13, 8, 7, 8, 7, 9, 4, 5, 10, 9, 11, 5, 15, 7, 9, 6, 7, 7, 6, 8, 9, 8, 7, 6, 10, 16, 11, 5, 8, 6, 7, 8, 9, 3, 6, 11, 10, 9, 9, 6, 7, 7, 8, 6, 7, 5, 12, 13, 6, 6, 10, 13, 5, 18, 7, 9, 9, 5, 9, 7, 8, 6, 7, 9, 4, 5, 5, 9, 5, 8, 12, 10, 7, 7, 9, 10, 9, 8, 12, 14, 4, 4, 8, 11, 9, 7, 5, 12, 15, 8, 7, 5, 5, 7, 5, 6, 9, 7, 6, 8, 6, 9, 7, 15, 6, 9, 7, 7, 13, 7, 6, 5, 5, 8, 9, 9, 9, 9, 11, 8, 11, 6, 11, 2, 10, 5, 4, 8, 6, 7, 15, 8, 9, 10, 9, 8, 1, 11, 11, 16, 8, 4, 3, 13, 5, 8, 7, 5, 7, 10, 8, 7, 9, 9, 6, 6, 9, 2, 11, 9, 8, 2, 6, 5, 6, 9, 4, 10, 6, 7, 6, 4, 8, 8, 6, 7, 7, 6, 9, 14, 9]\n",
      "Genrtn 351: mean = 8.02  stddev = 2.925679408274256  max = 19 [11, 7, 6, 13, 4, 8, 7, 4, 5, 9, 7, 5, 7, 12, 13, 10, 8, 8, 7, 12, 11, 11, 10, 8, 11, 7, 9, 6, 11, 7, 7, 6, 7, 8, 9, 5, 9, 7, 19, 9, 9, 7, 5, 8, 7, 3, 11, 6, 5, 7, 9, 8, 3, 10, 12, 12, 4, 8, 9, 8, 5, 13, 12, 13, 6, 7, 7, 6, 5, 6, 5, 8, 9, 10, 6, 4, 6, 1, 13, 4, 9, 4, 10, 8, 3, 10, 7, 8, 14, 6, 9, 8, 9, 6, 9, 12, 12, 8, 10, 9, 6, 4, 4, 11, 6, 3, 11, 11, 13, 7, 10, 5, 8, 9, 7, 11, 4, 10, 5, 5, 5, 7, 9, 4, 5, 10, 5, 15, 5, 8, 9, 9, 11, 11, 5, 5, 8, 5, 12, 7, 7, 11, 8, 10, 6, 15, 10, 10, 5, 7, 6, 5, 3, 7, 8, 8, 7, 5, 11, 6, 10, 13, 11, 14, 8, 7, 5, 11, 8, 11, 10, 3, 10, 8, 9, 5, 6, 9, 4, 15, 5, 13, 6, 4, 6, 8, 10, 11, 4, 12, 6, 13, 7, 10, 7, 4, 8, 7, 9, 9]\n",
      "Genrtn 352: mean = 8.37  stddev = 2.700574013057224  max = 18 [8, 8, 8, 5, 8, 6, 15, 9, 5, 5, 11, 9, 9, 4, 9, 9, 11, 5, 10, 11, 13, 7, 5, 8, 10, 5, 10, 5, 3, 12, 9, 5, 11, 8, 13, 10, 12, 10, 9, 10, 10, 7, 9, 10, 9, 11, 10, 9, 8, 4, 7, 5, 10, 8, 10, 8, 7, 7, 10, 6, 5, 5, 11, 7, 6, 12, 11, 10, 9, 10, 10, 12, 7, 5, 7, 9, 10, 7, 10, 6, 8, 6, 5, 11, 14, 18, 5, 12, 5, 6, 9, 13, 7, 6, 11, 10, 6, 14, 7, 4, 9, 12, 7, 9, 8, 13, 8, 11, 9, 5, 11, 12, 8, 9, 10, 9, 8, 9, 7, 12, 7, 4, 7, 7, 7, 4, 11, 6, 10, 9, 6, 12, 13, 10, 6, 5, 16, 5, 6, 13, 4, 11, 9, 10, 6, 10, 5, 8, 6, 8, 5, 8, 6, 7, 5, 6, 7, 4, 7, 8, 12, 9, 9, 11, 9, 6, 9, 11, 7, 4, 11, 3, 7, 10, 4, 11, 15, 8, 5, 11, 5, 7, 6, 6, 7, 7, 7, 9, 11, 12, 8, 6, 7, 11, 7, 10, 9, 7, 11, 8]\n",
      "Genrtn 353: mean = 7.88  stddev = 2.786682615584344  max = 17 [10, 6, 11, 6, 13, 11, 10, 5, 3, 7, 6, 7, 5, 7, 9, 5, 8, 4, 13, 11, 7, 9, 11, 7, 1, 9, 7, 7, 4, 3, 12, 6, 3, 5, 8, 9, 7, 4, 14, 4, 7, 8, 7, 10, 10, 6, 8, 9, 8, 6, 6, 7, 8, 7, 9, 6, 5, 9, 6, 6, 5, 10, 6, 9, 10, 6, 9, 9, 10, 6, 11, 7, 8, 9, 6, 10, 5, 11, 10, 7, 11, 6, 6, 9, 13, 8, 4, 12, 7, 17, 8, 4, 5, 10, 6, 6, 10, 11, 8, 7, 9, 6, 11, 9, 9, 4, 9, 13, 9, 11, 8, 9, 11, 11, 13, 5, 4, 6, 12, 6, 8, 9, 5, 6, 11, 7, 13, 3, 10, 5, 12, 11, 7, 10, 8, 2, 9, 6, 4, 7, 9, 7, 9, 8, 4, 8, 6, 11, 7, 5, 12, 5, 7, 10, 11, 9, 10, 6, 8, 8, 6, 6, 4, 7, 4, 11, 7, 5, 8, 13, 10, 11, 7, 11, 11, 6, 8, 5, 5, 6, 12, 6, 10, 7, 9, 9, 8, 12, 17, 5, 12, 11, 5, 4, 1, 10, 5, 8, 5, 7]\n",
      "Genrtn 354: mean = 7.96  stddev = 2.7328373533746935  max = 16 [7, 6, 6, 12, 11, 6, 6, 8, 9, 4, 11, 6, 10, 5, 1, 2, 10, 8, 11, 8, 7, 5, 5, 6, 5, 11, 6, 12, 12, 10, 8, 6, 3, 7, 10, 10, 15, 13, 12, 13, 7, 10, 9, 7, 11, 5, 11, 9, 7, 8, 8, 5, 4, 11, 7, 10, 7, 2, 7, 8, 8, 12, 10, 5, 8, 9, 9, 8, 11, 4, 9, 9, 10, 10, 7, 5, 10, 5, 9, 4, 11, 16, 8, 4, 7, 7, 4, 13, 10, 7, 6, 8, 7, 10, 8, 8, 13, 7, 11, 8, 6, 9, 7, 7, 8, 9, 12, 4, 9, 11, 9, 10, 8, 6, 9, 6, 11, 8, 10, 10, 5, 5, 9, 3, 11, 7, 3, 6, 6, 6, 4, 11, 10, 8, 8, 10, 9, 9, 5, 6, 7, 7, 4, 10, 5, 6, 11, 8, 10, 7, 12, 12, 5, 5, 8, 10, 5, 7, 8, 8, 4, 5, 8, 8, 9, 5, 4, 7, 7, 11, 8, 9, 10, 6, 13, 6, 7, 4, 8, 11, 4, 2, 7, 8, 15, 4, 9, 5, 14, 9, 10, 11, 10, 11, 8, 12, 7, 8, 5, 7]\n",
      "Genrtn 355: mean = 8.11  stddev = 2.7654836828301845  max = 20 [7, 6, 13, 6, 9, 10, 8, 14, 9, 9, 6, 9, 6, 11, 4, 16, 9, 6, 14, 9, 4, 7, 14, 10, 4, 10, 5, 10, 10, 10, 5, 8, 9, 5, 10, 3, 6, 9, 7, 8, 8, 8, 7, 9, 7, 20, 11, 7, 10, 13, 8, 13, 7, 8, 7, 7, 5, 7, 7, 7, 8, 14, 8, 7, 9, 6, 10, 8, 12, 4, 7, 5, 5, 7, 10, 9, 11, 6, 2, 6, 8, 8, 8, 5, 11, 9, 4, 8, 10, 10, 8, 7, 7, 5, 9, 7, 5, 6, 8, 7, 7, 6, 4, 12, 9, 7, 12, 7, 5, 6, 4, 9, 6, 8, 16, 10, 7, 8, 10, 15, 7, 14, 10, 6, 11, 5, 9, 11, 7, 7, 2, 7, 7, 11, 6, 13, 7, 8, 7, 10, 5, 13, 4, 6, 11, 10, 8, 11, 7, 8, 6, 12, 11, 10, 8, 5, 9, 8, 10, 3, 7, 8, 8, 9, 7, 8, 9, 9, 11, 4, 10, 7, 9, 6, 5, 9, 9, 7, 4, 10, 11, 10, 8, 7, 5, 6, 9, 6, 14, 8, 7, 8, 6, 5, 7, 5, 5, 6, 12, 8]\n",
      "Genrtn 356: mean = 7.99  stddev = 2.8982580975475596  max = 16 [5, 6, 4, 7, 4, 15, 13, 7, 11, 6, 7, 1, 8, 10, 4, 15, 12, 4, 12, 5, 7, 5, 8, 6, 11, 6, 9, 7, 9, 4, 5, 6, 5, 7, 8, 8, 3, 6, 11, 8, 8, 10, 8, 5, 7, 9, 16, 9, 8, 11, 8, 13, 7, 6, 5, 8, 7, 8, 4, 6, 7, 1, 10, 6, 9, 8, 7, 16, 7, 9, 9, 13, 11, 7, 7, 9, 2, 7, 10, 11, 7, 7, 8, 4, 9, 8, 9, 10, 12, 11, 7, 11, 9, 9, 6, 6, 7, 11, 7, 3, 9, 5, 13, 9, 13, 8, 5, 6, 5, 8, 9, 7, 9, 5, 6, 14, 10, 11, 9, 8, 3, 5, 6, 8, 8, 9, 4, 9, 9, 5, 9, 6, 13, 8, 5, 8, 11, 11, 5, 5, 7, 8, 6, 9, 6, 12, 11, 7, 4, 10, 9, 9, 11, 7, 11, 11, 7, 9, 6, 3, 9, 6, 9, 7, 13, 9, 9, 8, 15, 10, 7, 13, 8, 8, 7, 10, 7, 5, 3, 4, 8, 7, 4, 8, 12, 14, 2, 6, 11, 6, 8, 9, 4, 8, 9, 11, 10, 16, 7, 7]\n",
      "Genrtn 357: mean = 7.885  stddev = 2.819889182219755  max = 15 [10, 7, 7, 6, 6, 9, 8, 8, 5, 11, 4, 5, 6, 7, 4, 7, 10, 9, 6, 5, 9, 11, 6, 9, 11, 5, 8, 4, 12, 6, 7, 13, 6, 9, 6, 6, 9, 5, 9, 10, 9, 7, 8, 6, 8, 9, 13, 9, 5, 8, 11, 5, 5, 8, 11, 13, 4, 8, 6, 6, 10, 10, 9, 8, 11, 11, 8, 6, 6, 9, 4, 2, 6, 10, 14, 14, 10, 5, 8, 6, 6, 9, 9, 5, 13, 4, 7, 8, 6, 5, 8, 3, 6, 5, 10, 11, 5, 4, 12, 7, 5, 8, 7, 7, 15, 10, 14, 13, 15, 7, 9, 9, 4, 6, 11, 13, 9, 8, 7, 10, 1, 7, 3, 11, 9, 8, 6, 8, 9, 4, 4, 7, 7, 9, 8, 8, 8, 6, 8, 8, 4, 10, 11, 8, 7, 8, 3, 6, 9, 9, 8, 13, 9, 8, 12, 2, 6, 12, 9, 3, 5, 5, 8, 3, 7, 7, 8, 5, 13, 5, 13, 8, 7, 5, 7, 9, 9, 9, 13, 10, 7, 6, 11, 6, 5, 7, 15, 7, 4, 6, 13, 12, 8, 7, 4, 12, 7, 10, 10, 11]\n",
      "Genrtn 358: mean = 8.105  stddev = 2.8167312615867353  max = 22 [5, 5, 10, 8, 8, 8, 14, 7, 9, 10, 5, 6, 9, 10, 7, 4, 9, 11, 8, 13, 10, 8, 11, 10, 9, 7, 8, 7, 9, 3, 4, 9, 7, 8, 8, 9, 10, 8, 6, 11, 11, 6, 11, 10, 6, 8, 9, 12, 8, 6, 4, 8, 7, 8, 6, 9, 8, 6, 15, 6, 5, 8, 8, 7, 11, 10, 1, 8, 8, 8, 16, 2, 15, 7, 11, 6, 8, 12, 12, 10, 4, 11, 5, 5, 10, 11, 8, 8, 7, 3, 6, 7, 6, 9, 8, 10, 3, 7, 13, 11, 10, 10, 10, 8, 8, 7, 9, 10, 6, 13, 3, 8, 6, 9, 10, 12, 8, 7, 7, 4, 10, 4, 6, 7, 7, 10, 4, 4, 9, 5, 9, 12, 10, 8, 22, 11, 10, 10, 11, 7, 12, 12, 5, 7, 9, 9, 8, 6, 6, 12, 9, 8, 6, 8, 5, 11, 12, 7, 6, 10, 7, 9, 7, 6, 6, 6, 10, 7, 3, 10, 8, 9, 3, 6, 6, 6, 6, 12, 8, 10, 10, 7, 5, 10, 12, 8, 5, 5, 7, 8, 11, 14, 4, 3, 8, 9, 6, 7, 5, 6]\n",
      "Genrtn 359: mean = 8.04  stddev = 2.861538047973502  max = 16 [8, 13, 6, 7, 6, 5, 6, 4, 6, 11, 13, 11, 10, 10, 11, 7, 5, 6, 14, 8, 13, 3, 6, 11, 11, 6, 11, 5, 9, 11, 9, 5, 9, 14, 11, 3, 13, 5, 2, 8, 10, 4, 3, 7, 7, 7, 5, 9, 6, 14, 5, 8, 11, 8, 7, 12, 9, 5, 9, 8, 7, 7, 7, 7, 8, 9, 9, 8, 8, 9, 5, 6, 7, 9, 11, 7, 6, 8, 6, 11, 10, 6, 15, 10, 2, 11, 8, 12, 7, 8, 9, 8, 8, 6, 9, 8, 11, 10, 10, 8, 4, 3, 12, 5, 11, 7, 5, 5, 5, 9, 5, 12, 9, 9, 7, 3, 5, 13, 6, 8, 14, 10, 6, 9, 4, 8, 12, 5, 8, 5, 6, 10, 4, 16, 8, 13, 8, 4, 7, 5, 6, 9, 10, 2, 10, 6, 14, 8, 8, 6, 8, 8, 9, 7, 8, 4, 8, 6, 11, 8, 9, 9, 3, 7, 8, 11, 7, 7, 6, 10, 8, 9, 9, 4, 12, 3, 7, 5, 7, 8, 8, 6, 8, 12, 11, 5, 9, 6, 12, 9, 7, 8, 13, 10, 5, 14, 5, 14, 7, 12]\n",
      "Genrtn 360: mean = 8.025  stddev = 2.6878197484206416  max = 16 [11, 4, 11, 8, 4, 8, 9, 8, 8, 5, 8, 9, 5, 9, 5, 7, 9, 7, 10, 8, 6, 8, 11, 10, 16, 12, 7, 8, 8, 10, 7, 11, 9, 6, 3, 13, 10, 7, 4, 4, 10, 8, 9, 6, 6, 15, 10, 13, 6, 14, 7, 8, 4, 13, 8, 6, 6, 4, 6, 5, 2, 4, 7, 13, 5, 10, 6, 7, 16, 9, 8, 12, 8, 5, 7, 7, 8, 8, 5, 9, 12, 8, 10, 13, 11, 6, 12, 8, 9, 12, 7, 8, 8, 13, 4, 10, 8, 10, 6, 9, 5, 9, 12, 8, 8, 9, 11, 6, 10, 8, 6, 7, 7, 11, 8, 12, 9, 8, 8, 9, 6, 7, 7, 7, 5, 5, 9, 11, 1, 7, 9, 7, 10, 7, 13, 6, 9, 6, 11, 15, 5, 10, 7, 8, 8, 8, 4, 11, 4, 11, 9, 3, 8, 5, 4, 7, 5, 6, 5, 7, 5, 6, 9, 10, 12, 7, 12, 7, 6, 9, 6, 5, 5, 8, 5, 9, 8, 7, 9, 6, 8, 12, 7, 10, 7, 7, 8, 9, 6, 5, 10, 7, 4, 6, 9, 10, 8, 13, 11, 6]\n",
      "Genrtn 361: mean = 7.98  stddev = 2.7981422408448076  max = 16 [13, 5, 13, 4, 12, 6, 6, 8, 4, 13, 10, 6, 6, 10, 8, 6, 12, 6, 5, 9, 7, 3, 13, 4, 10, 7, 4, 7, 10, 10, 6, 10, 6, 8, 5, 7, 10, 11, 7, 8, 7, 9, 9, 2, 5, 11, 11, 7, 10, 7, 3, 3, 8, 12, 6, 8, 4, 9, 13, 7, 8, 8, 6, 3, 16, 8, 8, 6, 10, 11, 7, 5, 8, 9, 4, 7, 5, 10, 5, 6, 9, 8, 12, 7, 9, 7, 12, 10, 13, 11, 10, 10, 5, 5, 5, 5, 11, 13, 9, 6, 5, 9, 10, 10, 12, 3, 6, 6, 10, 2, 6, 7, 4, 9, 7, 7, 7, 8, 9, 8, 6, 4, 6, 8, 11, 9, 11, 7, 6, 9, 4, 11, 11, 5, 10, 12, 12, 6, 8, 6, 12, 4, 7, 2, 14, 7, 11, 3, 12, 9, 8, 10, 5, 4, 10, 9, 9, 10, 10, 7, 7, 11, 7, 7, 9, 4, 6, 9, 5, 7, 5, 11, 12, 5, 8, 11, 7, 8, 11, 12, 6, 7, 7, 9, 5, 5, 7, 9, 12, 8, 12, 10, 11, 9, 7, 4, 10, 9, 9, 15]\n",
      "Genrtn 362: mean = 8.07  stddev = 2.8679435140881  max = 19 [7, 4, 8, 11, 7, 11, 9, 10, 8, 6, 9, 12, 9, 11, 9, 14, 11, 6, 11, 8, 9, 10, 7, 3, 7, 10, 7, 4, 7, 7, 14, 11, 9, 10, 7, 10, 8, 7, 7, 3, 8, 9, 8, 4, 3, 9, 10, 9, 9, 8, 9, 8, 10, 11, 10, 10, 8, 11, 10, 4, 2, 10, 10, 10, 12, 10, 6, 6, 6, 7, 5, 4, 7, 7, 10, 5, 5, 8, 10, 6, 8, 9, 6, 10, 6, 3, 3, 15, 7, 15, 10, 15, 6, 11, 6, 11, 19, 8, 5, 9, 7, 1, 7, 7, 10, 8, 5, 6, 8, 9, 3, 11, 6, 10, 9, 8, 5, 9, 5, 4, 7, 5, 5, 10, 10, 9, 8, 9, 6, 4, 9, 10, 12, 8, 6, 9, 7, 8, 8, 9, 4, 2, 6, 10, 9, 5, 7, 9, 6, 8, 12, 18, 7, 7, 9, 11, 6, 5, 9, 12, 8, 5, 8, 13, 10, 13, 6, 6, 7, 5, 7, 10, 7, 9, 7, 6, 8, 6, 4, 8, 13, 10, 10, 14, 11, 11, 7, 7, 10, 3, 5, 9, 3, 6, 13, 8, 5, 6, 8, 9]\n",
      "Genrtn 363: mean = 7.995  stddev = 2.7757836731272847  max = 15 [2, 15, 9, 2, 5, 9, 4, 8, 9, 7, 14, 6, 8, 8, 7, 11, 7, 6, 4, 7, 7, 2, 7, 10, 11, 9, 9, 7, 8, 10, 5, 2, 10, 4, 9, 7, 8, 5, 9, 7, 7, 3, 8, 12, 10, 6, 6, 7, 6, 13, 6, 5, 11, 9, 9, 10, 10, 13, 8, 9, 10, 6, 6, 11, 4, 9, 9, 4, 6, 8, 8, 14, 7, 12, 8, 6, 8, 7, 5, 7, 8, 8, 9, 7, 8, 9, 14, 8, 3, 8, 8, 1, 12, 5, 8, 4, 6, 7, 11, 10, 7, 7, 6, 8, 6, 5, 8, 7, 7, 10, 5, 6, 11, 3, 8, 7, 4, 11, 13, 13, 10, 10, 14, 12, 12, 8, 8, 7, 11, 7, 7, 5, 14, 7, 8, 13, 9, 7, 10, 10, 7, 8, 13, 9, 9, 4, 8, 8, 8, 5, 5, 7, 8, 14, 9, 9, 10, 6, 7, 6, 11, 6, 9, 2, 12, 10, 7, 10, 14, 9, 6, 4, 5, 7, 8, 6, 4, 6, 7, 9, 7, 10, 9, 7, 11, 5, 7, 10, 6, 9, 5, 8, 7, 5, 11, 14, 11, 13, 9, 11]\n",
      "Genrtn 364: mean = 7.965  stddev = 2.7209878720788154  max = 16 [10, 10, 6, 7, 5, 6, 7, 5, 6, 12, 8, 4, 12, 13, 11, 9, 7, 11, 11, 12, 6, 8, 8, 6, 8, 8, 6, 13, 6, 8, 12, 8, 4, 13, 5, 9, 10, 6, 6, 11, 7, 6, 8, 5, 6, 5, 8, 11, 6, 3, 6, 11, 8, 8, 5, 5, 9, 9, 8, 11, 12, 7, 5, 12, 4, 8, 11, 4, 11, 9, 15, 9, 9, 9, 6, 11, 5, 3, 3, 12, 9, 6, 7, 6, 8, 4, 8, 9, 10, 3, 7, 8, 8, 8, 6, 7, 6, 4, 6, 7, 11, 9, 8, 8, 4, 8, 9, 12, 4, 11, 2, 4, 5, 6, 8, 7, 9, 9, 4, 5, 6, 11, 10, 9, 8, 9, 12, 11, 11, 5, 8, 14, 5, 3, 9, 10, 13, 7, 12, 8, 8, 10, 6, 3, 6, 4, 8, 5, 13, 9, 9, 8, 7, 6, 11, 4, 9, 11, 11, 7, 12, 8, 7, 7, 10, 5, 8, 10, 8, 5, 10, 9, 9, 10, 10, 7, 8, 4, 10, 7, 5, 9, 6, 7, 9, 4, 10, 9, 15, 10, 6, 6, 8, 3, 8, 10, 12, 9, 8, 16]\n",
      "Genrtn 365: mean = 8.345  stddev = 2.8837432271268537  max = 18 [7, 3, 7, 9, 8, 9, 5, 9, 12, 8, 9, 7, 8, 8, 6, 5, 11, 4, 8, 5, 13, 7, 7, 9, 5, 7, 8, 6, 7, 13, 3, 8, 10, 8, 7, 5, 9, 15, 10, 7, 10, 10, 8, 7, 6, 7, 9, 8, 6, 7, 5, 7, 5, 5, 14, 13, 9, 12, 10, 7, 5, 8, 9, 6, 14, 9, 7, 9, 5, 8, 6, 8, 7, 8, 13, 9, 10, 4, 13, 9, 8, 4, 10, 18, 9, 13, 11, 7, 6, 13, 7, 5, 8, 10, 12, 6, 8, 11, 7, 11, 11, 11, 6, 5, 6, 5, 6, 13, 10, 11, 5, 10, 8, 6, 5, 12, 3, 7, 6, 9, 9, 8, 8, 7, 14, 6, 7, 3, 8, 6, 14, 7, 6, 8, 10, 12, 10, 14, 9, 7, 9, 8, 7, 7, 5, 10, 13, 3, 10, 17, 3, 6, 9, 10, 6, 11, 12, 8, 8, 13, 9, 7, 4, 7, 7, 16, 5, 15, 6, 7, 10, 13, 10, 7, 7, 8, 5, 7, 9, 11, 15, 10, 7, 11, 8, 7, 6, 5, 10, 5, 7, 6, 11, 10, 5, 10, 6, 10, 11, 8]\n",
      "Genrtn 366: mean = 8.065  stddev = 2.63643224832348  max = 15 [5, 3, 14, 7, 5, 13, 7, 13, 9, 6, 7, 10, 6, 10, 10, 15, 12, 11, 9, 6, 7, 7, 9, 6, 5, 7, 8, 5, 10, 5, 9, 6, 7, 5, 13, 7, 8, 8, 8, 11, 9, 8, 8, 7, 7, 14, 7, 11, 8, 4, 10, 6, 9, 9, 10, 5, 8, 7, 9, 8, 7, 3, 12, 10, 5, 14, 6, 4, 9, 4, 10, 8, 4, 5, 8, 10, 10, 9, 9, 5, 6, 7, 10, 11, 6, 5, 8, 9, 6, 10, 6, 6, 8, 7, 10, 13, 9, 12, 9, 6, 10, 12, 6, 10, 11, 7, 5, 13, 9, 9, 9, 5, 12, 8, 13, 11, 10, 5, 10, 6, 7, 8, 12, 5, 7, 12, 7, 5, 4, 12, 3, 10, 5, 9, 5, 5, 12, 8, 10, 9, 9, 6, 7, 12, 11, 4, 10, 8, 7, 3, 9, 9, 8, 9, 11, 8, 5, 10, 8, 10, 11, 5, 12, 4, 10, 7, 11, 10, 12, 5, 8, 10, 9, 10, 8, 9, 7, 8, 10, 5, 11, 6, 5, 7, 8, 4, 7, 5, 7, 13, 7, 6, 9, 6, 6, 4, 5, 10, 2, 5]\n",
      "Genrtn 367: mean = 7.765  stddev = 2.67577558849766  max = 15 [10, 4, 5, 9, 7, 8, 6, 10, 8, 6, 9, 8, 5, 6, 8, 15, 7, 8, 7, 12, 8, 10, 10, 8, 2, 10, 8, 7, 7, 5, 10, 1, 15, 9, 10, 5, 9, 7, 3, 11, 2, 7, 13, 6, 4, 7, 10, 3, 10, 5, 4, 9, 4, 6, 10, 8, 9, 7, 10, 7, 9, 10, 11, 6, 9, 14, 3, 8, 6, 4, 4, 7, 8, 13, 7, 10, 10, 4, 5, 7, 9, 6, 6, 6, 6, 8, 6, 9, 5, 8, 14, 5, 8, 9, 9, 9, 10, 11, 7, 7, 11, 13, 14, 8, 9, 9, 8, 7, 8, 6, 11, 4, 8, 10, 8, 5, 3, 5, 5, 12, 9, 6, 7, 6, 11, 6, 3, 8, 9, 3, 9, 9, 5, 8, 8, 8, 10, 10, 8, 8, 10, 14, 9, 6, 8, 12, 6, 11, 4, 6, 8, 5, 8, 8, 8, 8, 4, 12, 11, 9, 8, 9, 6, 11, 11, 5, 14, 8, 5, 6, 4, 7, 6, 10, 7, 6, 10, 11, 7, 7, 3, 6, 5, 10, 10, 5, 6, 8, 6, 7, 13, 7, 6, 6, 6, 10, 9, 11, 7, 5]\n",
      "Genrtn 368: mean = 7.905  stddev = 2.992653504834798  max = 16 [11, 6, 3, 8, 8, 6, 13, 7, 7, 7, 13, 12, 11, 8, 10, 6, 3, 9, 9, 7, 4, 9, 7, 9, 10, 6, 7, 5, 11, 13, 6, 5, 7, 6, 9, 6, 8, 7, 7, 11, 3, 11, 6, 7, 4, 2, 16, 9, 1, 5, 8, 6, 12, 6, 10, 11, 7, 12, 3, 4, 7, 5, 5, 6, 6, 10, 4, 8, 7, 11, 6, 7, 8, 16, 6, 7, 3, 9, 9, 9, 4, 4, 5, 5, 7, 9, 10, 1, 10, 12, 11, 9, 11, 7, 10, 14, 13, 7, 9, 5, 12, 5, 6, 7, 8, 5, 7, 8, 9, 10, 10, 6, 6, 5, 10, 5, 7, 9, 5, 13, 10, 12, 6, 10, 5, 7, 13, 4, 11, 4, 5, 6, 11, 7, 9, 6, 9, 9, 6, 13, 8, 10, 7, 6, 3, 9, 8, 13, 7, 2, 5, 13, 13, 7, 10, 8, 6, 9, 5, 10, 8, 11, 7, 9, 5, 10, 13, 12, 6, 10, 6, 5, 11, 11, 16, 4, 6, 14, 6, 8, 5, 7, 11, 11, 5, 4, 9, 13, 3, 4, 7, 7, 11, 8, 10, 5, 11, 7, 10, 8]\n",
      "Genrtn 369: mean = 8.325  stddev = 2.673831520496383  max = 22 [13, 8, 6, 12, 9, 10, 4, 5, 9, 7, 8, 9, 5, 7, 10, 8, 10, 6, 3, 6, 10, 5, 11, 7, 7, 10, 9, 7, 4, 8, 10, 6, 5, 8, 11, 6, 6, 8, 5, 6, 12, 7, 7, 7, 12, 5, 7, 10, 6, 7, 7, 7, 9, 4, 8, 6, 7, 9, 5, 5, 5, 6, 8, 6, 10, 8, 9, 10, 11, 7, 7, 4, 10, 6, 8, 4, 7, 11, 10, 6, 3, 6, 11, 8, 13, 9, 9, 11, 11, 9, 7, 9, 13, 5, 8, 9, 10, 8, 10, 5, 12, 11, 7, 10, 7, 6, 11, 11, 6, 14, 9, 5, 6, 10, 13, 10, 9, 7, 9, 5, 11, 5, 12, 8, 6, 8, 9, 9, 13, 9, 6, 8, 8, 10, 6, 10, 4, 9, 8, 12, 10, 4, 10, 10, 5, 7, 8, 14, 13, 10, 6, 11, 8, 11, 12, 22, 13, 7, 7, 9, 8, 15, 8, 11, 9, 7, 7, 11, 6, 10, 8, 7, 11, 12, 7, 7, 8, 7, 4, 5, 12, 10, 8, 10, 12, 8, 8, 4, 9, 7, 8, 11, 14, 9, 10, 7, 6, 10, 5, 5]\n",
      "Genrtn 370: mean = 7.695  stddev = 2.896890574391791  max = 15 [4, 9, 9, 1, 7, 11, 5, 13, 10, 9, 12, 9, 4, 3, 12, 6, 8, 11, 12, 7, 7, 7, 7, 7, 10, 11, 8, 10, 4, 12, 7, 5, 5, 5, 10, 9, 8, 6, 7, 8, 12, 8, 10, 5, 10, 9, 4, 9, 8, 6, 4, 13, 11, 8, 4, 10, 13, 9, 9, 13, 8, 6, 4, 11, 1, 11, 5, 3, 5, 6, 2, 6, 3, 12, 7, 12, 12, 4, 15, 3, 7, 2, 9, 4, 9, 13, 9, 9, 6, 9, 10, 9, 7, 6, 7, 8, 6, 9, 6, 8, 12, 8, 8, 6, 7, 13, 4, 6, 8, 10, 7, 12, 7, 7, 7, 6, 6, 4, 11, 14, 4, 8, 10, 9, 4, 9, 9, 10, 6, 3, 10, 8, 10, 3, 6, 8, 10, 3, 14, 7, 8, 4, 11, 7, 7, 3, 8, 6, 3, 8, 8, 8, 10, 7, 5, 9, 11, 9, 10, 4, 6, 9, 6, 11, 6, 9, 13, 8, 4, 7, 6, 9, 1, 10, 6, 7, 6, 5, 4, 6, 10, 10, 6, 8, 5, 7, 6, 9, 12, 8, 6, 11, 14, 6, 9, 9, 6, 2, 10, 7]\n",
      "Genrtn 371: mean = 8.06  stddev = 2.6127380274340557  max = 18 [3, 9, 7, 5, 7, 8, 7, 5, 12, 6, 1, 12, 13, 6, 10, 6, 15, 11, 9, 7, 7, 12, 6, 8, 10, 8, 10, 8, 11, 11, 5, 11, 9, 8, 9, 9, 10, 9, 9, 10, 12, 3, 5, 4, 6, 10, 6, 8, 9, 4, 5, 9, 5, 7, 18, 9, 7, 5, 5, 6, 7, 5, 5, 7, 9, 6, 10, 6, 6, 7, 8, 10, 10, 7, 9, 12, 11, 9, 11, 7, 13, 8, 7, 11, 8, 6, 3, 7, 8, 3, 11, 12, 7, 7, 7, 7, 9, 11, 8, 8, 8, 7, 5, 10, 10, 9, 7, 6, 5, 8, 12, 8, 12, 12, 10, 8, 10, 7, 10, 4, 9, 6, 5, 11, 8, 8, 10, 8, 9, 8, 9, 9, 5, 8, 7, 6, 9, 9, 12, 9, 5, 6, 8, 10, 12, 10, 8, 7, 5, 6, 8, 7, 7, 10, 8, 4, 7, 10, 7, 8, 10, 8, 10, 5, 3, 10, 7, 8, 11, 6, 3, 10, 11, 8, 6, 8, 12, 4, 9, 6, 10, 5, 10, 11, 7, 10, 11, 4, 7, 12, 9, 7, 5, 5, 10, 6, 17, 4, 11, 5]\n",
      "Genrtn 372: mean = 7.72  stddev = 2.7643444069073593  max = 16 [11, 11, 5, 5, 7, 8, 9, 1, 7, 9, 11, 10, 15, 7, 9, 5, 8, 4, 8, 5, 6, 8, 8, 9, 6, 11, 5, 9, 9, 6, 7, 3, 9, 7, 10, 4, 7, 6, 2, 3, 9, 9, 3, 3, 5, 5, 8, 6, 6, 8, 7, 2, 5, 10, 5, 6, 7, 6, 5, 6, 6, 9, 7, 4, 4, 9, 8, 13, 8, 9, 5, 12, 7, 10, 8, 6, 8, 14, 9, 9, 7, 3, 8, 7, 7, 4, 9, 6, 7, 6, 6, 4, 5, 6, 11, 13, 11, 9, 3, 10, 7, 13, 7, 10, 9, 6, 11, 13, 16, 8, 10, 7, 6, 9, 8, 9, 10, 13, 4, 13, 6, 12, 12, 12, 7, 11, 6, 8, 4, 10, 6, 4, 10, 8, 4, 7, 13, 6, 4, 7, 5, 8, 9, 10, 5, 6, 3, 10, 6, 11, 9, 13, 8, 6, 8, 9, 5, 10, 7, 5, 4, 7, 8, 11, 11, 6, 6, 11, 10, 5, 7, 9, 8, 8, 13, 10, 6, 9, 9, 6, 6, 6, 4, 10, 4, 11, 5, 9, 9, 12, 11, 11, 5, 7, 10, 10, 6, 11, 10, 6]\n",
      "Genrtn 373: mean = 7.905  stddev = 2.725064219426764  max = 18 [3, 6, 8, 8, 4, 12, 4, 9, 13, 10, 9, 7, 8, 4, 9, 9, 10, 6, 7, 3, 8, 10, 4, 11, 9, 9, 7, 6, 10, 11, 10, 5, 12, 8, 9, 9, 5, 7, 8, 9, 5, 11, 6, 5, 5, 6, 7, 12, 9, 18, 6, 6, 11, 8, 6, 6, 8, 5, 5, 6, 5, 7, 8, 9, 13, 7, 10, 10, 11, 7, 6, 13, 9, 10, 14, 9, 6, 4, 12, 9, 8, 6, 8, 14, 4, 13, 11, 9, 8, 5, 7, 5, 8, 9, 7, 13, 9, 4, 4, 4, 7, 8, 5, 4, 6, 9, 8, 6, 9, 12, 6, 9, 8, 8, 7, 7, 9, 8, 10, 9, 7, 10, 9, 12, 4, 5, 10, 8, 11, 9, 7, 8, 3, 9, 12, 5, 9, 6, 7, 10, 9, 9, 8, 3, 8, 7, 5, 5, 8, 4, 6, 10, 8, 7, 6, 9, 3, 5, 6, 13, 11, 11, 8, 7, 9, 5, 8, 5, 9, 13, 5, 7, 3, 5, 4, 7, 12, 9, 14, 5, 10, 10, 9, 8, 7, 9, 15, 11, 7, 6, 12, 6, 12, 9, 9, 8, 4, 5, 3, 7]\n",
      "Genrtn 374: mean = 7.85  stddev = 2.763602721087096  max = 17 [7, 7, 14, 10, 9, 9, 8, 8, 11, 11, 8, 10, 10, 14, 5, 3, 9, 6, 8, 6, 4, 12, 8, 6, 10, 9, 17, 9, 6, 12, 8, 7, 8, 10, 5, 8, 9, 6, 8, 8, 10, 5, 10, 6, 6, 8, 12, 8, 3, 7, 6, 10, 11, 2, 6, 4, 14, 9, 8, 11, 12, 5, 8, 10, 8, 10, 8, 9, 5, 8, 5, 5, 9, 9, 10, 7, 4, 7, 9, 9, 7, 10, 9, 3, 7, 6, 7, 5, 8, 7, 7, 12, 13, 7, 9, 7, 9, 15, 9, 11, 13, 6, 11, 7, 8, 9, 10, 3, 4, 4, 7, 9, 6, 10, 9, 5, 6, 6, 4, 4, 3, 3, 7, 10, 5, 9, 8, 4, 3, 8, 11, 9, 6, 6, 9, 7, 2, 11, 8, 7, 10, 12, 4, 8, 6, 10, 5, 9, 10, 6, 7, 4, 2, 14, 4, 10, 11, 8, 5, 7, 7, 10, 8, 11, 9, 10, 11, 9, 4, 10, 14, 9, 6, 4, 8, 7, 6, 8, 11, 8, 11, 13, 4, 8, 4, 8, 7, 9, 8, 6, 9, 10, 3, 6, 9, 2, 7, 6, 7, 10]\n",
      "Genrtn 375: mean = 8.225  stddev = 2.7557893606006973  max = 15 [10, 8, 7, 9, 5, 11, 10, 5, 5, 10, 15, 9, 10, 13, 6, 10, 10, 12, 10, 8, 7, 7, 6, 5, 8, 11, 10, 11, 12, 12, 10, 10, 10, 10, 8, 9, 11, 8, 12, 6, 11, 8, 9, 5, 3, 9, 8, 11, 6, 6, 5, 9, 7, 7, 9, 12, 11, 8, 10, 10, 11, 6, 8, 10, 9, 12, 6, 10, 9, 5, 11, 11, 8, 5, 12, 4, 10, 10, 6, 7, 6, 6, 4, 12, 3, 6, 8, 6, 6, 7, 7, 7, 7, 6, 8, 8, 4, 6, 15, 8, 6, 11, 8, 7, 12, 4, 2, 9, 8, 14, 2, 4, 8, 7, 4, 4, 6, 6, 10, 9, 13, 8, 7, 6, 9, 7, 5, 4, 6, 5, 7, 6, 1, 7, 5, 6, 10, 11, 12, 14, 6, 12, 8, 6, 5, 8, 7, 10, 8, 7, 8, 9, 5, 7, 9, 8, 9, 8, 11, 5, 4, 11, 4, 9, 11, 8, 9, 12, 8, 4, 8, 9, 11, 10, 8, 15, 11, 4, 14, 6, 9, 12, 8, 10, 7, 7, 3, 8, 11, 10, 6, 12, 9, 10, 13, 13, 8, 6, 13, 8]\n",
      "Genrtn 376: mean = 7.715  stddev = 2.5717260740599883  max = 15 [8, 5, 6, 10, 7, 11, 5, 9, 9, 7, 10, 9, 8, 2, 7, 9, 7, 5, 11, 9, 9, 12, 3, 7, 9, 3, 8, 10, 3, 8, 6, 8, 6, 8, 9, 7, 6, 7, 7, 10, 4, 9, 6, 10, 8, 10, 9, 10, 7, 6, 8, 10, 6, 9, 8, 4, 10, 5, 7, 5, 9, 11, 6, 7, 8, 8, 2, 8, 11, 5, 9, 15, 11, 4, 12, 4, 9, 6, 9, 6, 7, 5, 10, 9, 8, 3, 8, 7, 5, 9, 8, 8, 6, 2, 6, 4, 10, 11, 7, 10, 7, 6, 12, 9, 8, 9, 6, 6, 7, 7, 8, 12, 7, 6, 9, 9, 6, 7, 8, 8, 9, 3, 3, 7, 10, 7, 6, 10, 4, 11, 4, 4, 8, 12, 7, 9, 9, 3, 10, 6, 12, 8, 12, 8, 7, 5, 7, 10, 9, 4, 5, 8, 9, 6, 5, 5, 7, 9, 6, 9, 7, 11, 8, 11, 13, 8, 11, 13, 14, 8, 5, 9, 5, 3, 15, 6, 7, 14, 4, 7, 6, 9, 6, 11, 9, 9, 7, 8, 5, 6, 6, 11, 9, 14, 8, 7, 8, 3, 10, 8]\n",
      "Genrtn 377: mean = 7.9  stddev = 2.882707061079915  max = 18 [9, 12, 11, 8, 7, 6, 3, 7, 6, 8, 6, 4, 9, 12, 12, 12, 2, 5, 5, 7, 11, 10, 10, 9, 7, 9, 7, 8, 13, 6, 7, 5, 7, 9, 8, 9, 9, 6, 7, 5, 13, 8, 10, 7, 9, 6, 4, 7, 11, 6, 9, 10, 8, 10, 7, 9, 10, 7, 14, 9, 6, 15, 8, 5, 16, 7, 11, 14, 12, 5, 8, 5, 8, 5, 6, 10, 4, 6, 4, 7, 12, 5, 9, 6, 10, 9, 11, 8, 5, 3, 6, 10, 8, 9, 18, 8, 7, 9, 7, 4, 9, 8, 4, 6, 10, 9, 7, 5, 5, 9, 5, 10, 6, 5, 3, 8, 5, 18, 3, 10, 3, 9, 8, 8, 9, 5, 5, 6, 7, 3, 4, 6, 3, 8, 11, 5, 10, 8, 8, 10, 18, 4, 9, 8, 7, 10, 5, 13, 7, 5, 7, 8, 7, 8, 9, 5, 8, 8, 10, 9, 6, 9, 9, 3, 9, 8, 6, 8, 12, 6, 6, 9, 5, 10, 9, 13, 10, 14, 5, 4, 9, 6, 12, 5, 11, 8, 12, 7, 9, 10, 8, 4, 6, 7, 7, 7, 7, 7, 9, 9]\n",
      "Genrtn 378: mean = 7.84  stddev = 2.759420228961149  max = 17 [10, 4, 5, 7, 5, 8, 5, 4, 6, 11, 13, 6, 7, 8, 4, 6, 17, 6, 6, 5, 5, 9, 8, 10, 11, 9, 3, 7, 9, 11, 7, 8, 4, 5, 13, 8, 10, 4, 3, 9, 6, 5, 5, 13, 5, 3, 8, 9, 9, 12, 11, 10, 4, 4, 9, 8, 10, 6, 12, 4, 9, 6, 9, 8, 7, 7, 4, 6, 10, 11, 4, 9, 13, 4, 7, 7, 11, 8, 9, 10, 8, 5, 10, 11, 9, 6, 8, 11, 7, 11, 9, 10, 6, 7, 6, 9, 8, 6, 6, 10, 16, 6, 9, 9, 10, 16, 6, 7, 3, 8, 7, 8, 9, 6, 10, 7, 13, 7, 9, 9, 7, 10, 13, 8, 9, 5, 7, 5, 7, 11, 10, 5, 7, 6, 12, 12, 5, 6, 9, 5, 11, 11, 9, 7, 7, 8, 15, 6, 4, 15, 5, 8, 7, 7, 6, 7, 9, 7, 10, 3, 4, 7, 7, 7, 4, 8, 4, 11, 6, 9, 9, 11, 6, 2, 10, 3, 9, 7, 12, 11, 10, 7, 7, 8, 6, 10, 10, 10, 4, 7, 7, 9, 11, 5, 6, 6, 6, 7, 8, 10]\n",
      "Genrtn 379: mean = 7.62  stddev = 2.783091805887833  max = 15 [9, 14, 4, 6, 11, 8, 3, 5, 5, 11, 8, 9, 5, 7, 12, 11, 5, 8, 9, 12, 7, 7, 11, 6, 2, 7, 11, 7, 10, 7, 11, 7, 6, 5, 10, 9, 3, 7, 12, 12, 11, 5, 6, 8, 13, 10, 10, 10, 9, 6, 5, 7, 11, 7, 4, 8, 11, 7, 2, 7, 10, 11, 5, 4, 9, 14, 7, 5, 12, 6, 6, 10, 5, 6, 5, 8, 7, 6, 6, 10, 12, 10, 13, 7, 7, 11, 6, 6, 6, 7, 6, 9, 9, 8, 9, 4, 8, 8, 8, 5, 12, 12, 2, 12, 5, 6, 9, 13, 3, 6, 9, 9, 8, 12, 6, 8, 9, 7, 9, 5, 4, 6, 5, 5, 12, 2, 10, 8, 8, 4, 13, 6, 6, 8, 5, 6, 5, 8, 5, 8, 2, 7, 5, 7, 6, 6, 8, 4, 7, 9, 11, 7, 10, 4, 6, 5, 3, 12, 9, 4, 7, 4, 4, 8, 7, 10, 13, 6, 5, 10, 4, 6, 14, 11, 6, 7, 6, 7, 7, 12, 6, 15, 6, 6, 10, 5, 5, 9, 7, 8, 13, 8, 9, 7, 7, 6, 9, 3, 8, 8]\n",
      "Genrtn 380: mean = 7.98  stddev = 2.88437168201326  max = 18 [8, 6, 9, 6, 3, 8, 9, 6, 10, 8, 5, 6, 5, 9, 11, 5, 9, 5, 6, 12, 7, 8, 11, 8, 10, 1, 7, 8, 9, 14, 3, 12, 10, 7, 6, 8, 7, 12, 11, 4, 9, 7, 7, 6, 7, 10, 11, 3, 2, 10, 8, 10, 6, 5, 11, 8, 4, 12, 6, 7, 8, 10, 4, 11, 10, 8, 5, 8, 9, 7, 9, 4, 10, 5, 10, 6, 7, 9, 12, 10, 8, 4, 5, 8, 8, 8, 10, 9, 9, 7, 10, 7, 7, 10, 9, 9, 5, 11, 10, 7, 9, 7, 4, 5, 8, 4, 5, 8, 11, 6, 8, 14, 9, 13, 9, 4, 8, 6, 2, 10, 6, 4, 15, 3, 5, 11, 6, 13, 8, 8, 9, 12, 7, 5, 9, 18, 11, 7, 8, 4, 5, 6, 7, 12, 17, 3, 11, 4, 4, 9, 6, 10, 4, 10, 6, 6, 12, 8, 11, 7, 4, 9, 7, 7, 12, 10, 9, 12, 10, 5, 11, 7, 4, 11, 9, 10, 5, 3, 9, 7, 9, 9, 7, 4, 10, 16, 4, 11, 11, 9, 10, 7, 7, 12, 7, 10, 9, 9, 5, 11]\n",
      "Genrtn 381: mean = 8.325  stddev = 2.3873363818280824  max = 16 [7, 9, 6, 6, 6, 8, 10, 10, 10, 8, 7, 9, 10, 7, 8, 10, 10, 10, 11, 8, 10, 9, 6, 11, 6, 13, 6, 10, 7, 10, 7, 3, 7, 11, 12, 7, 9, 9, 10, 9, 10, 8, 5, 14, 8, 7, 7, 5, 4, 10, 8, 6, 11, 5, 5, 7, 5, 11, 11, 9, 6, 7, 12, 13, 8, 9, 12, 8, 9, 5, 9, 10, 10, 6, 8, 8, 13, 11, 7, 11, 5, 4, 8, 6, 6, 9, 10, 9, 10, 7, 12, 9, 9, 6, 11, 9, 9, 9, 10, 6, 9, 6, 8, 14, 5, 8, 7, 5, 7, 8, 8, 10, 8, 9, 7, 9, 9, 11, 14, 6, 7, 13, 14, 16, 10, 5, 7, 9, 11, 10, 7, 9, 8, 2, 8, 5, 6, 6, 8, 7, 7, 10, 7, 8, 7, 8, 7, 10, 11, 6, 7, 9, 9, 3, 6, 7, 7, 9, 8, 8, 8, 5, 8, 10, 9, 12, 12, 9, 6, 12, 8, 6, 6, 11, 5, 8, 8, 9, 7, 7, 6, 10, 7, 2, 8, 9, 9, 8, 12, 6, 4, 5, 12, 8, 10, 11, 9, 13, 8, 8]\n",
      "Genrtn 382: mean = 7.92  stddev = 2.7447404248853844  max = 17 [10, 9, 8, 14, 7, 5, 9, 6, 7, 8, 4, 6, 5, 6, 9, 2, 13, 11, 7, 6, 9, 9, 8, 12, 7, 10, 6, 5, 10, 6, 7, 6, 9, 9, 8, 10, 11, 14, 8, 8, 4, 5, 10, 8, 13, 13, 6, 9, 4, 3, 8, 8, 5, 10, 6, 3, 10, 1, 10, 9, 8, 6, 7, 10, 13, 4, 6, 7, 7, 8, 8, 13, 7, 11, 5, 6, 9, 10, 7, 5, 8, 6, 2, 8, 4, 7, 11, 8, 7, 7, 7, 5, 13, 7, 9, 11, 7, 7, 8, 9, 8, 10, 8, 9, 9, 7, 8, 13, 7, 9, 6, 10, 12, 9, 10, 6, 7, 8, 8, 12, 7, 8, 11, 9, 8, 14, 7, 12, 9, 4, 5, 3, 12, 5, 9, 12, 4, 4, 9, 8, 7, 4, 6, 11, 6, 6, 9, 12, 8, 11, 17, 3, 9, 11, 8, 9, 9, 10, 6, 8, 13, 7, 6, 7, 8, 9, 8, 12, 6, 7, 5, 6, 12, 6, 6, 7, 12, 9, 6, 10, 7, 11, 8, 4, 9, 8, 10, 14, 5, 10, 2, 6, 6, 4, 5, 8, 9, 3, 7, 3]\n",
      "Genrtn 383: mean = 7.82  stddev = 2.8421118908304788  max = 18 [4, 6, 9, 8, 8, 9, 5, 12, 15, 11, 6, 8, 12, 4, 10, 10, 8, 7, 8, 8, 3, 9, 5, 9, 6, 10, 7, 8, 8, 7, 6, 6, 9, 6, 11, 6, 5, 5, 7, 5, 6, 6, 2, 8, 8, 9, 5, 6, 11, 5, 6, 6, 7, 7, 13, 10, 5, 8, 7, 6, 10, 15, 9, 5, 10, 9, 9, 7, 15, 6, 9, 9, 12, 6, 12, 12, 4, 7, 2, 14, 8, 6, 12, 11, 5, 6, 10, 4, 10, 9, 10, 12, 6, 9, 4, 4, 6, 7, 10, 8, 6, 4, 7, 7, 7, 11, 5, 12, 8, 5, 6, 10, 2, 11, 7, 9, 7, 8, 6, 8, 6, 6, 4, 2, 7, 8, 9, 14, 8, 10, 8, 12, 4, 3, 18, 4, 7, 8, 4, 7, 9, 11, 5, 7, 9, 14, 12, 7, 7, 6, 6, 9, 5, 7, 6, 10, 5, 7, 3, 5, 7, 8, 4, 4, 10, 5, 11, 9, 7, 13, 8, 6, 9, 8, 10, 6, 7, 6, 2, 6, 9, 11, 8, 8, 10, 12, 13, 5, 11, 7, 9, 12, 12, 12, 7, 9, 7, 11, 8, 6]\n",
      "Genrtn 384: mean = 7.725  stddev = 2.668215695928648  max = 17 [4, 10, 7, 5, 11, 6, 7, 10, 12, 9, 7, 4, 3, 10, 9, 5, 9, 7, 5, 8, 6, 9, 7, 12, 14, 11, 11, 4, 5, 7, 13, 11, 10, 9, 11, 8, 7, 7, 13, 12, 7, 5, 6, 11, 6, 12, 6, 12, 8, 8, 3, 7, 4, 6, 3, 12, 4, 8, 7, 6, 6, 5, 11, 10, 7, 6, 14, 11, 9, 10, 5, 7, 9, 7, 11, 6, 7, 7, 9, 10, 10, 9, 6, 6, 8, 12, 11, 2, 4, 5, 7, 7, 7, 10, 6, 17, 9, 6, 3, 8, 11, 5, 9, 8, 9, 3, 11, 7, 9, 10, 8, 7, 3, 8, 4, 5, 8, 11, 8, 9, 10, 9, 6, 3, 12, 8, 9, 6, 10, 9, 8, 5, 8, 6, 11, 8, 10, 7, 9, 5, 8, 11, 7, 9, 7, 9, 10, 3, 6, 14, 11, 6, 9, 7, 10, 6, 6, 9, 8, 9, 9, 7, 9, 4, 4, 8, 5, 7, 11, 3, 9, 4, 9, 8, 9, 6, 9, 13, 7, 5, 6, 3, 5, 3, 8, 10, 6, 5, 6, 5, 9, 6, 4, 9, 4, 8, 8, 5, 7, 9]\n",
      "Genrtn 385: mean = 8.15  stddev = 2.770830200499482  max = 17 [7, 8, 9, 10, 8, 7, 8, 9, 9, 8, 8, 8, 3, 12, 12, 15, 7, 13, 12, 8, 5, 9, 9, 6, 6, 6, 8, 8, 4, 8, 6, 5, 9, 14, 3, 5, 8, 7, 9, 8, 12, 8, 3, 12, 8, 2, 8, 8, 9, 7, 14, 6, 15, 8, 12, 4, 11, 10, 6, 8, 7, 5, 11, 6, 7, 10, 9, 7, 7, 9, 13, 5, 4, 1, 13, 10, 5, 9, 13, 10, 10, 9, 6, 7, 7, 8, 6, 6, 9, 3, 3, 17, 6, 12, 11, 4, 7, 11, 5, 10, 9, 2, 8, 7, 5, 6, 12, 11, 8, 4, 6, 8, 5, 10, 7, 7, 5, 12, 11, 9, 9, 8, 7, 9, 7, 7, 10, 10, 9, 11, 15, 7, 7, 9, 11, 6, 10, 10, 7, 8, 8, 6, 10, 9, 4, 7, 11, 8, 7, 8, 9, 7, 12, 12, 7, 7, 9, 7, 6, 8, 9, 8, 6, 13, 9, 6, 8, 4, 8, 9, 9, 12, 4, 5, 9, 11, 12, 8, 8, 10, 5, 5, 10, 3, 7, 8, 5, 14, 8, 9, 8, 10, 9, 13, 3, 10, 8, 6, 7, 10]\n",
      "Genrtn 386: mean = 7.75  stddev = 2.67348087705897  max = 16 [9, 9, 6, 7, 7, 11, 5, 12, 7, 10, 3, 11, 5, 5, 8, 8, 12, 6, 10, 11, 7, 12, 6, 8, 8, 7, 10, 8, 3, 5, 13, 9, 10, 7, 13, 10, 6, 9, 4, 7, 11, 6, 7, 10, 5, 6, 16, 13, 4, 9, 7, 9, 6, 9, 8, 5, 5, 12, 8, 6, 10, 9, 7, 7, 9, 4, 8, 6, 7, 6, 11, 5, 9, 8, 6, 5, 10, 8, 8, 10, 3, 14, 11, 8, 10, 5, 7, 9, 6, 4, 5, 5, 11, 10, 10, 6, 11, 9, 4, 11, 4, 7, 6, 3, 9, 7, 10, 3, 10, 7, 6, 6, 8, 13, 8, 8, 6, 9, 10, 9, 6, 5, 4, 9, 2, 5, 12, 11, 7, 4, 7, 11, 6, 4, 9, 4, 6, 5, 10, 7, 7, 14, 5, 5, 7, 5, 5, 5, 8, 6, 7, 9, 8, 5, 11, 8, 6, 13, 6, 8, 11, 11, 4, 8, 6, 11, 10, 6, 8, 8, 9, 5, 5, 9, 13, 9, 8, 6, 7, 10, 5, 6, 3, 7, 7, 7, 7, 7, 12, 7, 6, 11, 13, 11, 3, 11, 10, 12, 8, 4]\n",
      "Genrtn 387: mean = 7.59  stddev = 2.753525013505416  max = 15 [4, 10, 12, 7, 9, 9, 14, 7, 6, 1, 6, 5, 9, 4, 6, 5, 3, 8, 9, 6, 10, 7, 3, 7, 10, 6, 7, 5, 6, 7, 5, 7, 12, 5, 8, 5, 3, 9, 6, 8, 8, 6, 8, 9, 3, 8, 2, 7, 7, 4, 7, 8, 6, 15, 6, 7, 7, 11, 9, 10, 9, 10, 4, 8, 11, 10, 6, 7, 7, 7, 11, 8, 6, 9, 10, 8, 7, 11, 7, 3, 9, 8, 5, 4, 15, 8, 2, 3, 5, 11, 7, 9, 8, 7, 9, 8, 5, 7, 10, 10, 14, 5, 3, 2, 4, 12, 12, 9, 11, 10, 10, 10, 7, 12, 9, 6, 6, 6, 7, 2, 11, 5, 8, 8, 13, 10, 9, 10, 5, 10, 10, 6, 9, 9, 4, 7, 8, 5, 6, 13, 5, 8, 11, 2, 8, 4, 8, 10, 8, 11, 9, 5, 11, 9, 11, 13, 8, 7, 7, 7, 7, 9, 8, 6, 11, 9, 4, 7, 6, 4, 8, 5, 6, 12, 7, 7, 5, 9, 9, 3, 6, 11, 8, 11, 7, 9, 8, 5, 6, 9, 11, 6, 8, 7, 1, 6, 10, 5, 10, 14]\n",
      "Genrtn 388: mean = 8.095  stddev = 2.6468802390739175  max = 18 [5, 13, 12, 9, 7, 10, 4, 8, 8, 10, 7, 7, 15, 7, 10, 9, 7, 9, 8, 7, 10, 7, 6, 9, 10, 9, 6, 11, 9, 4, 9, 9, 9, 6, 8, 7, 11, 12, 6, 6, 7, 8, 10, 13, 4, 8, 9, 6, 9, 12, 8, 8, 7, 9, 14, 5, 5, 5, 11, 10, 3, 6, 7, 8, 10, 10, 5, 4, 3, 9, 7, 7, 8, 2, 12, 6, 5, 14, 9, 14, 8, 4, 9, 10, 11, 11, 6, 13, 8, 5, 11, 10, 7, 10, 7, 7, 11, 9, 6, 9, 6, 8, 6, 6, 7, 7, 10, 10, 8, 8, 8, 10, 10, 13, 5, 5, 3, 8, 10, 10, 7, 10, 18, 9, 8, 5, 6, 7, 8, 9, 9, 8, 10, 7, 7, 7, 4, 11, 5, 6, 10, 9, 9, 9, 9, 12, 7, 8, 4, 6, 11, 8, 7, 6, 7, 12, 7, 12, 7, 7, 8, 6, 5, 6, 10, 6, 14, 11, 7, 5, 3, 11, 8, 5, 9, 7, 2, 7, 9, 8, 5, 10, 7, 13, 11, 7, 6, 6, 2, 9, 6, 11, 7, 7, 13, 7, 6, 6, 10, 12]\n",
      "Genrtn 389: mean = 7.955  stddev = 2.6912775776571247  max = 19 [9, 9, 5, 6, 0, 3, 10, 2, 6, 7, 10, 10, 7, 9, 5, 7, 8, 9, 6, 9, 12, 6, 6, 11, 8, 8, 7, 7, 6, 6, 5, 6, 9, 11, 9, 11, 4, 10, 8, 9, 7, 13, 7, 8, 7, 7, 9, 4, 7, 7, 8, 8, 6, 5, 11, 9, 3, 10, 10, 7, 10, 5, 7, 9, 13, 7, 5, 9, 6, 9, 7, 3, 8, 11, 8, 9, 8, 5, 7, 11, 8, 8, 4, 10, 11, 6, 9, 12, 8, 9, 6, 7, 8, 8, 17, 12, 12, 9, 7, 3, 10, 8, 8, 12, 8, 7, 7, 9, 9, 4, 10, 5, 8, 4, 13, 7, 8, 6, 19, 9, 4, 8, 10, 9, 8, 7, 13, 9, 5, 5, 11, 10, 4, 9, 8, 15, 8, 9, 9, 6, 8, 7, 9, 6, 7, 10, 6, 2, 11, 9, 7, 8, 5, 9, 7, 9, 8, 9, 7, 5, 9, 8, 10, 4, 8, 5, 9, 4, 6, 6, 6, 10, 7, 8, 9, 13, 5, 5, 12, 7, 10, 8, 6, 10, 7, 11, 6, 8, 14, 6, 7, 9, 15, 4, 10, 3, 8, 10, 12, 9]\n",
      "Genrtn 390: mean = 8.0  stddev = 2.7748873851023217  max = 16 [8, 5, 6, 8, 12, 9, 8, 7, 6, 5, 9, 3, 11, 7, 8, 7, 6, 5, 9, 8, 9, 8, 4, 8, 4, 5, 5, 9, 10, 7, 8, 11, 8, 9, 9, 8, 15, 13, 7, 10, 8, 7, 6, 6, 10, 5, 5, 8, 5, 0, 7, 13, 6, 12, 9, 11, 16, 4, 10, 12, 8, 9, 9, 6, 6, 10, 8, 8, 7, 11, 10, 4, 6, 9, 5, 12, 9, 10, 6, 8, 9, 12, 6, 13, 5, 6, 10, 10, 10, 2, 4, 6, 7, 10, 10, 9, 10, 5, 6, 5, 6, 8, 8, 7, 11, 12, 3, 7, 12, 6, 10, 9, 5, 4, 5, 8, 8, 8, 4, 7, 13, 11, 9, 5, 15, 10, 9, 10, 12, 9, 4, 6, 6, 9, 11, 14, 4, 7, 7, 7, 5, 9, 12, 12, 10, 7, 6, 9, 10, 4, 5, 4, 8, 9, 6, 7, 7, 14, 9, 3, 7, 10, 6, 3, 10, 11, 7, 10, 8, 8, 7, 6, 4, 5, 12, 8, 8, 9, 7, 9, 10, 6, 10, 6, 6, 6, 7, 13, 5, 11, 4, 11, 9, 11, 13, 10, 6, 14, 5, 10]\n",
      "Genrtn 391: mean = 7.58  stddev = 2.8431672479824326  max = 16 [6, 9, 7, 6, 9, 7, 7, 7, 6, 7, 10, 11, 8, 9, 6, 7, 11, 6, 10, 10, 8, 3, 12, 5, 6, 6, 5, 11, 3, 4, 8, 6, 4, 8, 3, 4, 10, 7, 7, 4, 9, 12, 5, 5, 10, 13, 5, 13, 9, 6, 10, 10, 10, 7, 6, 9, 9, 2, 7, 4, 6, 6, 10, 8, 9, 2, 2, 9, 6, 6, 7, 6, 6, 6, 4, 10, 5, 8, 12, 5, 5, 6, 11, 11, 8, 2, 12, 8, 6, 12, 5, 12, 5, 12, 11, 15, 7, 5, 5, 9, 7, 13, 7, 12, 7, 9, 4, 7, 10, 9, 7, 11, 9, 4, 9, 6, 6, 7, 7, 10, 10, 5, 9, 8, 9, 5, 4, 6, 10, 6, 7, 9, 8, 5, 15, 6, 7, 8, 8, 6, 13, 12, 7, 7, 12, 10, 8, 7, 9, 4, 16, 4, 4, 15, 14, 5, 9, 3, 4, 2, 8, 8, 8, 8, 8, 4, 10, 4, 9, 10, 5, 7, 10, 12, 4, 7, 8, 6, 11, 4, 10, 8, 9, 10, 8, 11, 2, 9, 3, 8, 5, 6, 6, 11, 6, 7, 7, 7, 7, 4]\n",
      "Genrtn 392: mean = 8.005  stddev = 2.8486795186542135  max = 17 [8, 4, 8, 9, 11, 3, 6, 8, 9, 9, 12, 13, 10, 7, 9, 8, 8, 6, 6, 11, 6, 5, 7, 8, 5, 14, 6, 4, 7, 6, 6, 6, 10, 3, 9, 11, 7, 6, 10, 9, 10, 7, 8, 7, 6, 12, 10, 10, 10, 9, 12, 14, 8, 10, 4, 12, 7, 6, 7, 5, 7, 7, 12, 9, 8, 10, 8, 8, 7, 8, 5, 6, 10, 3, 14, 11, 10, 8, 4, 6, 9, 8, 6, 7, 5, 11, 9, 8, 9, 14, 5, 5, 14, 7, 4, 10, 7, 10, 9, 6, 6, 15, 17, 12, 12, 15, 5, 5, 8, 10, 10, 9, 6, 12, 6, 6, 7, 6, 8, 14, 7, 9, 5, 8, 12, 2, 7, 7, 9, 10, 8, 10, 7, 13, 4, 6, 5, 7, 4, 6, 5, 7, 4, 13, 3, 11, 5, 8, 3, 4, 6, 7, 9, 14, 4, 7, 3, 5, 8, 13, 5, 10, 11, 6, 9, 8, 7, 11, 4, 8, 10, 6, 11, 7, 7, 3, 8, 5, 5, 6, 12, 9, 9, 8, 9, 9, 6, 9, 11, 7, 5, 9, 10, 11, 5, 7, 9, 9, 13, 5]\n",
      "Genrtn 393: mean = 7.87  stddev = 2.8148001705272083  max = 16 [5, 9, 6, 4, 5, 8, 9, 10, 12, 8, 3, 4, 4, 6, 9, 10, 12, 6, 6, 9, 7, 9, 9, 7, 2, 10, 4, 9, 10, 5, 6, 5, 5, 7, 7, 8, 6, 8, 5, 13, 6, 9, 5, 11, 4, 8, 4, 7, 8, 9, 4, 14, 5, 7, 7, 9, 7, 14, 16, 4, 14, 10, 5, 7, 14, 2, 4, 13, 12, 5, 11, 8, 7, 9, 5, 7, 10, 3, 6, 13, 11, 8, 7, 5, 9, 9, 5, 13, 6, 9, 4, 9, 3, 3, 10, 8, 6, 10, 6, 3, 7, 5, 10, 9, 5, 8, 6, 6, 12, 6, 7, 3, 7, 10, 8, 8, 5, 9, 6, 8, 7, 11, 8, 14, 15, 8, 7, 8, 10, 8, 15, 12, 10, 8, 9, 6, 9, 14, 8, 11, 11, 8, 6, 6, 5, 6, 8, 8, 10, 9, 11, 12, 10, 5, 7, 5, 6, 6, 10, 11, 3, 5, 8, 10, 10, 8, 9, 5, 10, 6, 6, 6, 13, 7, 10, 6, 6, 11, 7, 9, 6, 9, 8, 7, 8, 11, 10, 4, 7, 11, 8, 13, 8, 9, 8, 7, 6, 10, 7, 5]\n",
      "Genrtn 394: mean = 7.78  stddev = 2.700296280040396  max = 16 [9, 2, 9, 8, 6, 11, 7, 7, 6, 8, 9, 5, 6, 8, 6, 5, 7, 7, 7, 7, 6, 4, 8, 7, 10, 9, 7, 7, 13, 7, 12, 10, 9, 5, 6, 6, 9, 6, 7, 8, 5, 8, 15, 9, 8, 4, 9, 11, 2, 3, 15, 8, 10, 7, 4, 11, 5, 8, 7, 10, 2, 8, 8, 7, 8, 7, 6, 7, 7, 7, 8, 11, 8, 10, 11, 7, 6, 1, 9, 9, 13, 3, 7, 6, 8, 12, 6, 10, 7, 8, 10, 11, 5, 13, 11, 6, 7, 11, 16, 10, 5, 4, 9, 9, 5, 6, 9, 4, 4, 3, 11, 9, 13, 6, 12, 3, 4, 4, 8, 6, 5, 5, 7, 8, 8, 5, 13, 8, 8, 7, 4, 6, 9, 9, 7, 12, 5, 6, 9, 10, 9, 9, 5, 10, 8, 5, 8, 10, 9, 5, 12, 10, 4, 10, 10, 10, 3, 11, 8, 6, 5, 2, 8, 9, 7, 11, 8, 6, 10, 10, 10, 5, 12, 8, 7, 9, 10, 7, 12, 9, 8, 9, 7, 6, 2, 8, 8, 7, 7, 13, 6, 10, 10, 8, 10, 9, 12, 9, 3, 10]\n",
      "Genrtn 395: mean = 7.805  stddev = 2.682717838312483  max = 14 [10, 4, 7, 10, 4, 9, 13, 6, 10, 9, 6, 11, 3, 8, 7, 9, 6, 11, 7, 5, 10, 9, 8, 10, 10, 4, 5, 10, 5, 4, 10, 8, 7, 5, 6, 8, 12, 4, 8, 8, 9, 10, 8, 11, 10, 8, 9, 5, 5, 7, 6, 10, 10, 7, 9, 4, 6, 11, 5, 6, 6, 6, 10, 6, 5, 8, 5, 7, 9, 3, 11, 8, 6, 3, 7, 8, 8, 10, 8, 8, 10, 6, 10, 6, 10, 12, 13, 9, 2, 9, 2, 10, 10, 7, 7, 5, 6, 5, 9, 4, 12, 7, 12, 9, 10, 11, 11, 9, 4, 6, 4, 8, 10, 5, 4, 12, 11, 11, 11, 7, 5, 8, 12, 4, 6, 14, 3, 10, 8, 14, 10, 12, 6, 11, 10, 8, 7, 5, 6, 6, 7, 6, 7, 11, 10, 9, 11, 5, 7, 10, 6, 5, 6, 3, 6, 8, 4, 11, 10, 9, 13, 8, 9, 7, 12, 9, 6, 9, 11, 5, 10, 7, 7, 12, 11, 12, 8, 12, 6, 7, 13, 5, 2, 5, 3, 1, 9, 9, 7, 8, 9, 8, 5, 5, 7, 6, 8, 10, 6, 8]\n",
      "Genrtn 396: mean = 7.89  stddev = 2.5666904760800433  max = 16 [8, 9, 11, 8, 6, 7, 6, 6, 6, 8, 13, 9, 9, 11, 8, 7, 7, 10, 5, 4, 5, 7, 10, 7, 6, 8, 4, 7, 7, 8, 8, 5, 6, 6, 11, 6, 6, 9, 10, 11, 4, 6, 9, 8, 7, 7, 14, 8, 7, 12, 11, 8, 3, 9, 10, 8, 16, 7, 10, 4, 10, 11, 11, 6, 4, 7, 7, 8, 2, 11, 9, 8, 7, 10, 7, 8, 11, 10, 8, 8, 10, 4, 14, 12, 5, 6, 11, 9, 11, 6, 10, 4, 9, 4, 4, 10, 11, 8, 5, 8, 8, 6, 9, 6, 8, 11, 8, 8, 8, 4, 12, 9, 8, 4, 5, 7, 8, 9, 10, 8, 4, 6, 9, 14, 7, 13, 9, 4, 9, 7, 8, 7, 10, 5, 7, 6, 7, 8, 16, 3, 12, 9, 8, 12, 6, 8, 10, 6, 10, 6, 10, 5, 6, 6, 3, 9, 8, 4, 6, 6, 13, 9, 5, 10, 6, 9, 4, 5, 6, 9, 9, 9, 8, 6, 8, 8, 10, 10, 6, 4, 6, 6, 5, 6, 10, 11, 10, 6, 8, 8, 11, 11, 4, 8, 8, 13, 6, 5, 9, 11]\n",
      "Genrtn 397: mean = 7.655  stddev = 2.848855033166833  max = 18 [5, 8, 2, 5, 9, 6, 9, 7, 6, 8, 5, 12, 10, 8, 11, 9, 6, 4, 10, 8, 3, 9, 9, 6, 5, 6, 6, 7, 6, 6, 4, 5, 10, 9, 6, 10, 4, 11, 7, 8, 6, 5, 10, 5, 7, 6, 9, 11, 6, 12, 12, 6, 12, 8, 4, 9, 4, 6, 7, 6, 3, 8, 3, 12, 9, 8, 5, 8, 7, 6, 11, 5, 5, 6, 6, 8, 8, 13, 8, 7, 8, 18, 13, 8, 4, 2, 7, 3, 12, 12, 4, 11, 9, 11, 12, 7, 7, 7, 7, 11, 9, 11, 9, 9, 7, 11, 14, 8, 9, 4, 9, 4, 5, 9, 7, 4, 7, 11, 6, 11, 15, 7, 6, 9, 3, 9, 9, 5, 11, 11, 7, 11, 12, 4, 8, 4, 7, 5, 8, 8, 9, 4, 8, 8, 9, 14, 5, 9, 7, 6, 7, 10, 7, 11, 3, 5, 4, 5, 9, 5, 11, 7, 9, 5, 14, 11, 6, 7, 5, 10, 13, 4, 6, 4, 9, 5, 8, 9, 3, 10, 9, 12, 2, 2, 7, 8, 7, 8, 12, 9, 5, 5, 12, 10, 7, 5, 8, 7, 10, 7]\n",
      "Genrtn 398: mean = 8.22  stddev = 2.7224253892439365  max = 15 [7, 13, 8, 8, 9, 14, 3, 3, 7, 7, 6, 10, 11, 5, 4, 10, 6, 11, 5, 8, 10, 10, 10, 14, 4, 5, 12, 13, 9, 11, 9, 4, 6, 8, 7, 11, 4, 7, 9, 6, 8, 9, 7, 7, 5, 10, 13, 10, 8, 14, 10, 6, 4, 9, 5, 7, 5, 7, 9, 7, 6, 2, 15, 11, 6, 9, 9, 7, 7, 8, 12, 4, 7, 9, 6, 5, 7, 8, 10, 3, 8, 5, 7, 10, 11, 10, 5, 5, 7, 10, 5, 9, 3, 7, 9, 8, 4, 9, 10, 10, 8, 6, 12, 15, 8, 10, 8, 6, 6, 14, 10, 7, 6, 9, 10, 10, 11, 14, 5, 11, 3, 10, 12, 8, 6, 10, 10, 10, 7, 9, 12, 9, 10, 10, 7, 11, 10, 3, 13, 8, 12, 12, 7, 6, 6, 8, 7, 10, 6, 12, 13, 9, 12, 6, 10, 9, 6, 11, 13, 7, 6, 4, 10, 9, 5, 11, 3, 6, 8, 8, 7, 9, 8, 8, 7, 9, 7, 12, 10, 9, 7, 11, 11, 12, 7, 7, 7, 9, 6, 8, 7, 7, 5, 3, 11, 8, 5, 8, 6, 10]\n",
      "Genrtn 399: mean = 7.99  stddev = 2.578740002404275  max = 14 [7, 5, 5, 7, 10, 9, 9, 10, 13, 8, 10, 7, 9, 11, 9, 5, 12, 8, 5, 5, 4, 5, 10, 7, 6, 10, 10, 5, 9, 7, 7, 4, 8, 8, 9, 7, 11, 8, 9, 8, 5, 9, 10, 7, 11, 4, 11, 9, 5, 12, 9, 8, 10, 8, 5, 10, 13, 12, 7, 11, 5, 7, 9, 2, 9, 7, 9, 5, 5, 10, 6, 11, 8, 8, 11, 6, 10, 9, 9, 7, 4, 2, 7, 13, 8, 8, 9, 4, 10, 5, 7, 6, 4, 11, 10, 8, 7, 6, 7, 8, 11, 8, 8, 5, 6, 4, 9, 4, 6, 12, 7, 13, 3, 7, 10, 10, 9, 10, 13, 7, 13, 5, 6, 8, 4, 8, 11, 9, 5, 4, 12, 11, 10, 12, 5, 7, 6, 9, 11, 7, 7, 11, 6, 7, 12, 8, 10, 12, 6, 11, 7, 9, 12, 3, 11, 5, 5, 7, 11, 8, 7, 8, 8, 10, 14, 8, 8, 9, 7, 11, 8, 10, 8, 10, 5, 11, 4, 8, 6, 7, 4, 7, 10, 2, 12, 6, 6, 10, 6, 4, 6, 11, 7, 8, 10, 7, 14, 7, 6, 6]\n",
      "Genrtn 400: mean = 8.045  stddev = 2.7153222644835364  max = 17 [6, 12, 7, 8, 14, 8, 11, 5, 8, 7, 8, 11, 9, 5, 9, 7, 11, 4, 6, 10, 9, 11, 7, 3, 9, 8, 7, 10, 3, 9, 5, 10, 6, 11, 9, 13, 8, 12, 6, 7, 6, 11, 6, 3, 6, 10, 11, 11, 4, 10, 8, 7, 11, 10, 11, 10, 7, 2, 5, 6, 3, 6, 8, 7, 12, 9, 6, 6, 7, 5, 8, 8, 4, 9, 7, 10, 6, 8, 11, 7, 3, 12, 6, 8, 13, 7, 13, 12, 10, 8, 10, 8, 12, 7, 13, 8, 9, 7, 6, 10, 7, 7, 9, 9, 9, 4, 5, 9, 4, 7, 9, 8, 7, 6, 5, 7, 8, 8, 9, 5, 5, 7, 14, 6, 10, 11, 10, 4, 8, 9, 9, 9, 12, 8, 13, 7, 3, 9, 3, 6, 6, 8, 7, 3, 11, 7, 7, 6, 12, 9, 11, 8, 5, 6, 9, 10, 12, 7, 6, 7, 8, 5, 7, 10, 10, 13, 8, 7, 7, 5, 8, 7, 9, 12, 4, 4, 9, 8, 11, 9, 9, 5, 5, 10, 4, 13, 8, 11, 11, 7, 10, 11, 6, 5, 4, 12, 11, 12, 17, 2]\n",
      "Genrtn 401: mean = 8.3  stddev = 2.835489375751565  max = 18 [5, 8, 6, 7, 7, 7, 11, 7, 7, 7, 6, 9, 8, 6, 8, 10, 11, 7, 6, 7, 10, 5, 10, 10, 12, 12, 9, 9, 8, 7, 6, 13, 9, 8, 4, 10, 5, 6, 15, 18, 4, 12, 5, 8, 10, 8, 11, 2, 3, 7, 10, 7, 1, 6, 5, 15, 10, 8, 9, 10, 2, 5, 11, 5, 8, 7, 10, 8, 7, 10, 10, 10, 4, 12, 8, 7, 7, 14, 13, 9, 9, 2, 3, 6, 10, 11, 9, 8, 9, 8, 15, 10, 5, 11, 6, 8, 6, 8, 7, 13, 9, 11, 11, 8, 12, 7, 6, 8, 8, 11, 8, 7, 6, 8, 13, 3, 10, 14, 7, 8, 7, 10, 4, 10, 5, 10, 6, 12, 8, 8, 12, 7, 7, 8, 8, 11, 9, 12, 7, 11, 3, 9, 9, 11, 7, 3, 10, 7, 6, 11, 10, 9, 5, 11, 11, 4, 10, 11, 8, 10, 14, 9, 7, 11, 6, 7, 9, 11, 10, 13, 8, 10, 13, 14, 12, 8, 6, 11, 7, 10, 6, 8, 6, 9, 6, 8, 7, 5, 6, 6, 11, 3, 8, 3, 7, 8, 6, 7, 5, 9]\n",
      "Genrtn 402: mean = 7.9  stddev = 2.7820855486487113  max = 18 [7, 4, 14, 7, 6, 7, 10, 8, 9, 8, 9, 2, 7, 5, 13, 11, 8, 2, 9, 7, 11, 9, 6, 11, 10, 7, 4, 10, 12, 10, 5, 9, 6, 10, 6, 6, 6, 7, 4, 10, 7, 10, 8, 7, 9, 5, 12, 5, 9, 7, 4, 10, 5, 9, 10, 4, 7, 10, 4, 10, 5, 9, 8, 11, 11, 8, 15, 7, 11, 5, 15, 6, 9, 8, 3, 10, 9, 10, 10, 6, 10, 7, 12, 8, 10, 8, 7, 6, 7, 8, 6, 11, 8, 4, 5, 5, 10, 8, 10, 6, 9, 12, 6, 9, 8, 9, 6, 18, 4, 6, 5, 4, 13, 9, 9, 6, 4, 7, 6, 13, 7, 9, 8, 11, 8, 7, 7, 8, 6, 7, 9, 15, 6, 4, 12, 4, 6, 10, 13, 6, 6, 7, 12, 8, 7, 4, 6, 9, 8, 6, 13, 6, 9, 6, 13, 7, 10, 7, 10, 5, 13, 4, 7, 10, 2, 8, 8, 6, 4, 8, 5, 9, 8, 9, 10, 5, 8, 7, 9, 1, 6, 5, 4, 8, 7, 11, 10, 10, 7, 7, 6, 7, 9, 10, 14, 7, 13, 7, 5, 5]\n",
      "Genrtn 403: mean = 7.86  stddev = 2.7803596889611244  max = 15 [4, 12, 6, 7, 6, 5, 9, 9, 8, 9, 8, 6, 4, 12, 12, 6, 11, 7, 9, 10, 5, 10, 7, 8, 7, 5, 2, 11, 12, 8, 9, 5, 7, 11, 12, 5, 6, 10, 14, 8, 9, 8, 13, 9, 8, 3, 11, 2, 12, 7, 5, 11, 6, 13, 12, 13, 9, 7, 6, 8, 7, 9, 5, 7, 11, 8, 7, 7, 6, 8, 6, 3, 3, 8, 7, 9, 12, 11, 7, 9, 7, 8, 5, 6, 9, 9, 4, 11, 7, 15, 6, 4, 7, 8, 7, 11, 6, 7, 8, 6, 13, 7, 7, 6, 13, 14, 8, 14, 10, 7, 4, 5, 6, 11, 4, 13, 8, 5, 8, 5, 9, 8, 6, 9, 8, 9, 7, 2, 6, 8, 8, 10, 5, 7, 11, 6, 5, 15, 6, 15, 9, 6, 10, 6, 5, 9, 10, 5, 6, 6, 9, 9, 4, 9, 8, 4, 8, 7, 8, 9, 8, 6, 6, 8, 4, 12, 8, 7, 11, 5, 9, 8, 11, 6, 9, 8, 7, 10, 4, 11, 3, 14, 5, 4, 8, 12, 12, 8, 7, 4, 9, 5, 9, 8, 8, 3, 3, 7, 6, 9]\n",
      "Genrtn 404: mean = 8.015  stddev = 2.5912882896350995  max = 15 [11, 11, 3, 5, 8, 7, 7, 7, 6, 13, 10, 4, 8, 9, 3, 7, 8, 8, 10, 15, 7, 9, 11, 8, 12, 11, 9, 5, 5, 7, 11, 7, 11, 7, 9, 7, 9, 7, 10, 9, 6, 5, 6, 4, 9, 9, 6, 9, 5, 4, 8, 9, 6, 5, 6, 11, 7, 9, 9, 6, 7, 12, 8, 10, 15, 10, 7, 6, 7, 8, 8, 9, 9, 10, 7, 8, 13, 6, 6, 7, 6, 8, 10, 9, 6, 13, 13, 9, 12, 5, 7, 3, 10, 10, 6, 14, 8, 7, 11, 11, 3, 4, 8, 10, 6, 8, 10, 5, 10, 5, 4, 9, 8, 9, 11, 7, 9, 10, 5, 11, 5, 8, 12, 6, 7, 7, 4, 8, 6, 4, 12, 6, 5, 8, 12, 12, 5, 8, 9, 6, 8, 6, 9, 10, 3, 8, 12, 10, 9, 9, 10, 6, 8, 5, 7, 12, 12, 6, 6, 10, 8, 7, 9, 12, 8, 3, 11, 2, 9, 9, 8, 13, 11, 7, 12, 9, 6, 2, 5, 6, 8, 11, 8, 4, 5, 5, 11, 7, 5, 10, 7, 10, 8, 7, 8, 7, 8, 7, 9, 12]\n",
      "Genrtn 405: mean = 7.905  stddev = 2.726898421283785  max = 18 [10, 3, 3, 11, 5, 7, 11, 12, 11, 7, 12, 9, 6, 10, 9, 7, 4, 7, 9, 11, 6, 10, 4, 5, 8, 5, 12, 9, 11, 5, 5, 8, 7, 8, 4, 7, 4, 7, 4, 7, 9, 4, 8, 4, 8, 12, 7, 9, 6, 8, 6, 9, 9, 5, 6, 8, 5, 7, 11, 11, 9, 8, 6, 7, 5, 10, 8, 7, 13, 8, 5, 11, 9, 5, 11, 8, 6, 11, 12, 6, 7, 11, 8, 8, 15, 8, 8, 12, 5, 8, 10, 9, 7, 10, 15, 5, 7, 11, 10, 8, 8, 9, 4, 7, 10, 10, 5, 14, 7, 5, 7, 8, 10, 5, 4, 12, 9, 10, 6, 9, 4, 10, 6, 4, 7, 8, 4, 6, 8, 8, 9, 3, 6, 6, 3, 9, 11, 5, 6, 12, 7, 9, 6, 6, 8, 12, 11, 14, 13, 11, 12, 3, 7, 5, 8, 7, 4, 11, 6, 5, 8, 5, 10, 10, 6, 4, 4, 9, 11, 10, 8, 12, 10, 7, 10, 4, 9, 8, 8, 9, 8, 6, 18, 7, 9, 3, 6, 5, 11, 4, 13, 8, 10, 8, 9, 8, 6, 8, 7, 7]\n",
      "Genrtn 406: mean = 8.04  stddev = 2.6829834140374405  max = 17 [7, 9, 8, 7, 7, 5, 11, 5, 7, 10, 9, 6, 13, 12, 10, 7, 8, 10, 8, 7, 13, 9, 7, 9, 10, 7, 9, 5, 6, 9, 6, 12, 12, 4, 6, 13, 5, 5, 9, 5, 5, 8, 9, 10, 7, 5, 5, 12, 11, 5, 7, 11, 5, 5, 8, 5, 5, 8, 7, 6, 8, 11, 7, 8, 8, 6, 14, 11, 17, 6, 12, 12, 3, 12, 10, 12, 5, 9, 12, 10, 8, 3, 7, 6, 8, 6, 9, 6, 7, 5, 12, 3, 6, 11, 3, 3, 10, 10, 8, 8, 8, 8, 6, 8, 5, 6, 11, 9, 8, 6, 11, 9, 6, 7, 5, 9, 9, 6, 7, 6, 13, 6, 5, 10, 7, 4, 5, 10, 5, 5, 9, 6, 6, 5, 9, 11, 11, 10, 3, 9, 5, 10, 9, 5, 7, 8, 4, 12, 7, 9, 10, 6, 6, 8, 11, 9, 11, 6, 13, 10, 12, 9, 10, 13, 10, 9, 14, 5, 7, 4, 13, 14, 12, 8, 8, 10, 8, 7, 4, 7, 7, 9, 5, 11, 8, 7, 7, 6, 12, 9, 8, 5, 10, 5, 10, 9, 8, 9, 7, 4]\n",
      "Genrtn 407: mean = 7.82  stddev = 2.76904315603784  max = 15 [4, 10, 7, 14, 11, 5, 6, 15, 10, 6, 11, 11, 12, 14, 10, 6, 4, 12, 4, 5, 6, 10, 10, 8, 9, 6, 7, 10, 5, 11, 8, 9, 5, 12, 7, 10, 8, 11, 8, 8, 10, 10, 7, 8, 11, 7, 5, 10, 9, 2, 5, 9, 10, 6, 8, 4, 9, 9, 10, 10, 10, 13, 7, 6, 5, 6, 7, 7, 9, 9, 6, 7, 10, 11, 11, 7, 7, 6, 8, 11, 2, 6, 9, 4, 6, 6, 6, 6, 15, 7, 7, 7, 14, 6, 6, 12, 7, 11, 1, 11, 13, 6, 8, 9, 7, 8, 9, 5, 8, 4, 6, 6, 7, 2, 13, 7, 7, 8, 5, 9, 3, 9, 7, 5, 6, 6, 8, 7, 9, 7, 4, 6, 13, 11, 10, 6, 10, 10, 7, 13, 7, 8, 6, 9, 1, 8, 4, 7, 10, 4, 7, 8, 9, 6, 9, 9, 6, 3, 11, 6, 8, 5, 10, 10, 6, 12, 6, 8, 11, 5, 3, 3, 8, 6, 6, 8, 6, 8, 4, 8, 10, 4, 5, 6, 10, 5, 7, 7, 12, 12, 14, 8, 8, 8, 6, 12, 11, 10, 6, 4]\n",
      "Genrtn 408: mean = 7.97  stddev = 2.8581637461839025  max = 16 [10, 9, 10, 8, 5, 5, 10, 8, 7, 4, 14, 8, 10, 7, 7, 6, 8, 4, 7, 3, 10, 7, 8, 7, 8, 13, 10, 5, 5, 9, 6, 6, 14, 4, 13, 11, 14, 10, 9, 9, 9, 5, 4, 6, 7, 12, 7, 11, 13, 4, 11, 9, 8, 7, 8, 11, 3, 6, 9, 11, 10, 12, 11, 7, 5, 11, 13, 11, 11, 10, 8, 8, 13, 5, 5, 14, 7, 7, 2, 13, 16, 12, 9, 8, 12, 8, 13, 8, 8, 6, 4, 5, 8, 6, 10, 6, 7, 7, 12, 8, 6, 8, 5, 10, 4, 13, 8, 5, 7, 11, 4, 8, 11, 7, 11, 9, 11, 8, 6, 6, 11, 2, 9, 8, 4, 11, 3, 7, 8, 9, 11, 4, 8, 12, 6, 10, 8, 5, 7, 8, 3, 4, 12, 8, 7, 10, 7, 12, 6, 10, 6, 8, 7, 7, 6, 8, 6, 6, 12, 7, 6, 8, 3, 5, 5, 5, 14, 5, 5, 10, 4, 4, 8, 7, 15, 4, 7, 9, 3, 6, 8, 5, 5, 7, 8, 5, 11, 6, 8, 9, 8, 9, 7, 7, 13, 8, 5, 9, 9, 8]\n",
      "Genrtn 409: mean = 7.875  stddev = 2.7439706631084815  max = 17 [4, 9, 17, 8, 8, 5, 10, 8, 11, 11, 4, 6, 5, 7, 4, 8, 8, 9, 8, 9, 9, 8, 9, 5, 5, 10, 4, 7, 6, 9, 9, 7, 8, 12, 11, 5, 7, 6, 10, 5, 7, 17, 6, 6, 14, 4, 10, 7, 13, 9, 4, 5, 6, 7, 8, 7, 8, 8, 13, 6, 11, 5, 7, 13, 7, 9, 10, 8, 8, 7, 10, 8, 11, 8, 9, 6, 4, 4, 6, 7, 10, 12, 11, 10, 8, 7, 7, 10, 9, 4, 7, 9, 9, 10, 12, 6, 7, 10, 7, 5, 7, 11, 5, 11, 8, 12, 4, 9, 7, 8, 6, 5, 12, 6, 11, 7, 7, 13, 12, 6, 8, 6, 8, 9, 14, 6, 5, 8, 10, 4, 6, 13, 10, 10, 5, 14, 3, 13, 6, 9, 10, 6, 9, 8, 13, 9, 13, 5, 4, 5, 4, 12, 5, 9, 4, 7, 5, 7, 9, 6, 6, 5, 10, 9, 3, 9, 7, 4, 8, 4, 7, 5, 13, 6, 9, 8, 8, 3, 11, 7, 7, 10, 11, 7, 7, 5, 10, 6, 8, 7, 4, 7, 9, 5, 7, 9, 3, 11, 8, 4]\n",
      "Genrtn 410: mean = 8.3  stddev = 2.711088342345192  max = 17 [9, 8, 7, 9, 12, 8, 5, 7, 8, 9, 7, 3, 7, 8, 13, 10, 7, 9, 11, 5, 8, 9, 10, 9, 13, 8, 5, 5, 6, 9, 8, 9, 6, 12, 14, 11, 10, 8, 5, 6, 11, 8, 5, 7, 4, 7, 8, 8, 6, 9, 9, 8, 4, 8, 8, 12, 11, 10, 8, 10, 9, 10, 8, 6, 10, 4, 6, 11, 8, 10, 6, 11, 9, 8, 9, 10, 5, 5, 6, 5, 15, 7, 5, 8, 8, 8, 11, 12, 8, 12, 9, 5, 8, 10, 5, 7, 12, 9, 4, 7, 7, 5, 7, 7, 6, 15, 7, 9, 2, 7, 8, 10, 8, 8, 7, 4, 5, 9, 15, 12, 11, 9, 7, 10, 8, 8, 8, 13, 8, 9, 6, 13, 9, 6, 12, 7, 11, 12, 5, 9, 13, 10, 6, 4, 4, 11, 8, 10, 14, 11, 7, 8, 4, 7, 8, 7, 14, 11, 8, 8, 6, 8, 10, 14, 6, 12, 8, 5, 8, 7, 7, 8, 3, 6, 11, 13, 5, 9, 4, 9, 14, 11, 8, 5, 7, 8, 7, 9, 12, 11, 9, 2, 6, 7, 7, 7, 17, 5, 10, 7]\n",
      "Genrtn 411: mean = 8.025  stddev = 2.5306866657095264  max = 14 [10, 6, 10, 10, 8, 3, 10, 10, 13, 4, 8, 8, 10, 7, 10, 7, 10, 13, 4, 10, 11, 6, 8, 5, 6, 12, 8, 8, 4, 10, 8, 9, 9, 7, 6, 9, 4, 10, 7, 10, 6, 2, 12, 6, 8, 9, 5, 10, 7, 11, 6, 7, 6, 7, 6, 11, 11, 2, 12, 9, 4, 10, 7, 9, 9, 6, 7, 6, 6, 8, 11, 11, 8, 8, 6, 6, 7, 11, 5, 8, 7, 6, 9, 13, 7, 12, 9, 6, 13, 7, 6, 5, 8, 9, 5, 8, 11, 5, 3, 6, 7, 6, 8, 6, 5, 9, 9, 8, 6, 5, 9, 6, 14, 9, 5, 6, 6, 5, 6, 5, 8, 10, 13, 11, 7, 12, 7, 11, 3, 9, 7, 3, 10, 4, 6, 9, 9, 10, 8, 7, 8, 8, 7, 7, 7, 8, 6, 2, 11, 11, 7, 8, 12, 8, 11, 11, 9, 11, 6, 6, 10, 11, 10, 12, 8, 11, 12, 9, 6, 8, 12, 7, 10, 14, 6, 7, 5, 10, 10, 12, 9, 6, 5, 8, 8, 7, 9, 12, 10, 12, 10, 8, 11, 8, 4, 8, 5, 7, 5, 6]\n",
      "Genrtn 412: mean = 7.81  stddev = 2.7210108415807532  max = 19 [8, 10, 3, 13, 10, 7, 5, 8, 7, 9, 7, 10, 11, 8, 13, 10, 7, 7, 8, 5, 10, 3, 6, 8, 11, 6, 11, 6, 6, 5, 4, 6, 7, 9, 4, 6, 7, 7, 4, 9, 11, 7, 9, 8, 7, 10, 8, 7, 16, 10, 7, 8, 8, 11, 5, 12, 3, 10, 9, 8, 7, 5, 5, 4, 11, 4, 9, 12, 5, 9, 5, 6, 5, 10, 7, 11, 8, 4, 8, 6, 11, 4, 8, 11, 7, 7, 12, 5, 4, 9, 13, 6, 6, 5, 13, 10, 6, 10, 10, 4, 7, 3, 4, 9, 8, 5, 12, 4, 9, 10, 6, 4, 10, 10, 5, 6, 3, 5, 7, 19, 11, 8, 8, 7, 3, 7, 6, 7, 7, 5, 3, 8, 12, 8, 6, 4, 7, 10, 6, 11, 9, 6, 11, 7, 8, 6, 7, 10, 9, 11, 8, 5, 10, 7, 8, 7, 7, 10, 4, 6, 12, 4, 9, 7, 7, 8, 7, 9, 8, 11, 6, 12, 10, 6, 5, 14, 3, 6, 10, 9, 9, 7, 8, 9, 7, 9, 14, 9, 6, 8, 12, 11, 9, 7, 8, 8, 13, 4, 8, 10]\n",
      "Genrtn 413: mean = 7.725  stddev = 2.9187968411658938  max = 15 [3, 6, 7, 13, 7, 6, 10, 10, 6, 10, 5, 9, 6, 11, 4, 9, 10, 8, 5, 10, 8, 11, 9, 8, 9, 7, 9, 4, 13, 7, 8, 12, 11, 13, 2, 8, 8, 10, 9, 3, 9, 12, 5, 10, 5, 13, 11, 7, 8, 3, 13, 7, 5, 4, 12, 5, 10, 7, 8, 4, 8, 5, 6, 8, 6, 7, 6, 7, 3, 9, 9, 9, 3, 10, 4, 5, 7, 4, 7, 12, 12, 4, 4, 2, 5, 7, 6, 10, 7, 8, 8, 5, 14, 10, 6, 2, 9, 6, 14, 13, 6, 5, 15, 11, 5, 4, 7, 9, 9, 11, 5, 5, 6, 4, 8, 7, 6, 9, 7, 12, 8, 12, 10, 5, 6, 6, 15, 6, 9, 6, 7, 8, 3, 12, 6, 13, 3, 9, 7, 7, 5, 6, 13, 5, 6, 7, 10, 9, 5, 7, 4, 6, 5, 7, 7, 4, 6, 11, 7, 6, 10, 7, 10, 12, 7, 14, 12, 8, 12, 6, 6, 6, 8, 9, 4, 8, 9, 4, 5, 6, 6, 8, 9, 5, 14, 9, 10, 4, 11, 11, 5, 11, 14, 6, 8, 11, 9, 6, 5, 6]\n",
      "Genrtn 414: mean = 8.06  stddev = 2.5271327626383226  max = 14 [10, 5, 10, 9, 13, 12, 8, 10, 11, 6, 9, 5, 9, 7, 8, 14, 10, 8, 4, 7, 12, 7, 5, 9, 7, 9, 8, 9, 6, 8, 9, 7, 7, 8, 7, 6, 10, 4, 6, 7, 8, 8, 8, 12, 13, 9, 10, 8, 8, 7, 9, 9, 10, 7, 4, 11, 13, 9, 14, 4, 5, 9, 11, 6, 6, 5, 9, 10, 13, 4, 8, 5, 6, 11, 14, 8, 8, 11, 5, 8, 8, 12, 7, 6, 6, 9, 5, 7, 11, 8, 8, 9, 7, 12, 3, 8, 8, 9, 7, 5, 10, 5, 8, 8, 9, 5, 8, 8, 4, 10, 2, 10, 7, 8, 12, 7, 8, 9, 7, 6, 11, 4, 4, 8, 3, 10, 8, 5, 8, 9, 7, 5, 10, 5, 14, 9, 9, 9, 12, 2, 10, 3, 10, 11, 10, 14, 8, 11, 7, 13, 5, 6, 6, 10, 7, 7, 6, 11, 5, 7, 4, 10, 11, 4, 8, 6, 8, 7, 5, 4, 11, 9, 9, 10, 9, 6, 9, 9, 5, 11, 8, 10, 10, 5, 6, 10, 9, 12, 8, 9, 6, 9, 7, 5, 6, 11, 9, 8, 7, 8]\n",
      "Genrtn 415: mean = 8.005  stddev = 2.710161434306082  max = 15 [10, 7, 3, 4, 6, 9, 5, 11, 5, 7, 10, 6, 8, 5, 12, 12, 7, 12, 6, 4, 7, 5, 10, 14, 6, 7, 7, 6, 6, 7, 3, 14, 10, 12, 6, 9, 9, 10, 9, 5, 11, 9, 13, 4, 6, 9, 8, 13, 7, 2, 10, 4, 12, 12, 12, 5, 9, 6, 9, 5, 12, 6, 7, 10, 7, 10, 9, 11, 11, 3, 5, 7, 8, 9, 6, 7, 8, 8, 9, 7, 10, 4, 2, 10, 5, 5, 7, 13, 9, 10, 13, 9, 6, 10, 11, 10, 5, 7, 8, 6, 4, 6, 13, 10, 10, 11, 7, 13, 9, 15, 6, 15, 7, 8, 9, 13, 7, 6, 13, 5, 5, 8, 8, 9, 8, 6, 6, 9, 8, 6, 8, 7, 6, 6, 4, 8, 10, 9, 10, 4, 5, 4, 4, 13, 7, 10, 5, 6, 6, 6, 10, 7, 12, 5, 7, 11, 9, 13, 8, 11, 7, 8, 9, 12, 8, 9, 9, 7, 7, 11, 4, 7, 9, 6, 8, 7, 5, 6, 7, 9, 8, 11, 11, 10, 6, 6, 12, 8, 8, 8, 8, 8, 4, 8, 4, 9, 4, 8, 10, 7]\n",
      "Genrtn 416: mean = 7.98  stddev = 2.67761087538873  max = 17 [7, 12, 6, 13, 6, 8, 6, 11, 6, 6, 10, 5, 8, 9, 8, 5, 10, 7, 11, 7, 5, 6, 13, 12, 8, 10, 11, 7, 11, 10, 4, 7, 9, 8, 7, 4, 6, 10, 11, 16, 4, 9, 8, 6, 6, 9, 6, 7, 10, 5, 11, 7, 9, 8, 5, 9, 7, 7, 6, 7, 11, 8, 6, 13, 6, 4, 13, 3, 6, 7, 6, 9, 8, 6, 7, 7, 9, 9, 12, 5, 10, 13, 8, 11, 8, 8, 6, 11, 8, 4, 17, 10, 7, 8, 9, 15, 8, 10, 7, 12, 7, 9, 9, 5, 4, 8, 9, 8, 6, 8, 8, 12, 4, 9, 4, 11, 13, 6, 7, 10, 8, 4, 8, 3, 14, 5, 8, 7, 9, 9, 9, 6, 7, 8, 10, 8, 12, 10, 14, 5, 10, 4, 11, 9, 11, 3, 4, 12, 7, 2, 4, 8, 11, 7, 9, 7, 10, 9, 5, 10, 11, 7, 6, 8, 7, 5, 6, 9, 13, 10, 6, 6, 8, 10, 8, 6, 8, 6, 10, 9, 4, 5, 10, 6, 11, 5, 7, 6, 8, 8, 6, 9, 5, 5, 7, 7, 12, 4, 4, 7]\n",
      "Genrtn 417: mean = 8.17  stddev = 2.949762702320307  max = 19 [9, 6, 12, 12, 10, 7, 11, 6, 4, 5, 19, 8, 15, 13, 6, 10, 9, 11, 6, 9, 8, 8, 9, 9, 8, 5, 10, 14, 6, 13, 7, 9, 9, 3, 10, 4, 11, 6, 7, 6, 14, 7, 7, 6, 8, 6, 8, 12, 8, 8, 5, 12, 4, 9, 6, 13, 6, 6, 10, 13, 7, 8, 12, 7, 7, 10, 3, 7, 13, 12, 7, 4, 11, 5, 11, 6, 5, 8, 6, 5, 9, 7, 8, 9, 9, 7, 12, 9, 6, 8, 7, 10, 9, 8, 9, 4, 11, 9, 10, 7, 10, 14, 6, 6, 7, 11, 3, 9, 8, 12, 6, 9, 11, 9, 6, 12, 6, 4, 14, 10, 7, 8, 5, 4, 6, 14, 9, 8, 10, 3, 11, 4, 10, 12, 5, 3, 9, 10, 7, 3, 10, 5, 5, 13, 4, 8, 7, 8, 4, 7, 4, 9, 7, 6, 13, 6, 11, 6, 7, 18, 10, 6, 9, 7, 4, 8, 4, 9, 16, 9, 8, 5, 6, 9, 4, 8, 11, 9, 10, 9, 10, 8, 7, 6, 11, 9, 6, 8, 10, 8, 10, 6, 8, 3, 7, 6, 12, 7, 9, 3]\n",
      "Genrtn 418: mean = 8.215  stddev = 2.4736157745292617  max = 15 [9, 8, 8, 8, 6, 6, 13, 12, 7, 6, 5, 6, 5, 6, 6, 9, 9, 12, 11, 9, 8, 6, 11, 11, 5, 15, 10, 10, 10, 6, 5, 11, 8, 8, 6, 5, 3, 8, 9, 5, 6, 9, 6, 8, 7, 10, 7, 9, 5, 2, 9, 8, 10, 11, 5, 6, 11, 6, 15, 3, 8, 8, 9, 11, 8, 8, 12, 6, 9, 6, 11, 9, 7, 11, 10, 9, 8, 10, 9, 11, 10, 7, 7, 7, 10, 8, 7, 4, 6, 7, 3, 6, 11, 7, 6, 7, 6, 5, 9, 10, 7, 11, 6, 10, 11, 8, 5, 5, 9, 7, 10, 12, 5, 5, 13, 10, 10, 8, 9, 13, 9, 9, 11, 11, 4, 6, 8, 7, 9, 10, 8, 4, 9, 9, 7, 12, 12, 5, 9, 7, 6, 7, 10, 12, 11, 8, 8, 10, 12, 8, 7, 5, 5, 5, 7, 7, 6, 6, 6, 11, 7, 6, 9, 9, 5, 12, 5, 6, 12, 11, 12, 9, 7, 13, 8, 11, 7, 10, 9, 7, 13, 8, 14, 8, 9, 8, 10, 6, 6, 11, 4, 9, 7, 8, 7, 6, 9, 9, 12, 10]\n",
      "Genrtn 419: mean = 7.99  stddev = 2.7676524348263096  max = 15 [12, 5, 10, 3, 6, 9, 9, 9, 15, 6, 10, 4, 8, 7, 12, 7, 2, 10, 4, 5, 9, 7, 6, 5, 11, 8, 4, 5, 6, 11, 9, 7, 6, 11, 9, 7, 13, 7, 13, 6, 8, 11, 6, 7, 11, 5, 5, 3, 7, 9, 7, 14, 10, 6, 8, 12, 8, 9, 7, 10, 9, 6, 2, 15, 8, 8, 8, 15, 12, 8, 11, 8, 3, 9, 10, 6, 6, 13, 4, 7, 7, 10, 6, 8, 5, 12, 6, 3, 7, 9, 4, 9, 6, 10, 8, 10, 7, 11, 9, 6, 10, 10, 8, 10, 5, 11, 10, 8, 5, 13, 15, 8, 4, 12, 11, 12, 10, 9, 10, 10, 7, 6, 10, 8, 10, 6, 13, 8, 6, 9, 7, 10, 6, 5, 4, 7, 8, 10, 5, 8, 5, 5, 12, 8, 9, 6, 13, 10, 10, 7, 11, 11, 7, 10, 9, 6, 7, 4, 8, 4, 6, 5, 8, 6, 6, 5, 9, 9, 8, 3, 10, 9, 3, 9, 11, 4, 9, 9, 9, 5, 8, 9, 5, 9, 7, 8, 4, 13, 4, 8, 6, 8, 9, 11, 6, 10, 4, 13, 6, 4]\n",
      "Genrtn 420: mean = 8.12  stddev = 2.802784329911954  max = 17 [6, 4, 6, 13, 6, 8, 8, 9, 8, 5, 12, 5, 8, 5, 4, 6, 13, 8, 4, 5, 9, 9, 9, 15, 9, 7, 11, 8, 4, 11, 7, 9, 9, 7, 6, 7, 9, 11, 9, 9, 11, 7, 5, 5, 5, 8, 7, 5, 13, 6, 9, 6, 14, 11, 4, 6, 9, 8, 9, 6, 9, 9, 8, 7, 8, 5, 3, 5, 7, 5, 11, 5, 8, 6, 6, 7, 7, 3, 7, 8, 7, 8, 8, 9, 6, 5, 17, 16, 12, 9, 12, 7, 5, 10, 7, 12, 3, 7, 11, 7, 8, 9, 11, 7, 11, 8, 8, 6, 10, 5, 10, 5, 7, 5, 10, 10, 7, 10, 11, 17, 11, 8, 7, 8, 6, 4, 5, 7, 10, 12, 6, 5, 8, 9, 7, 9, 11, 10, 7, 5, 9, 5, 8, 6, 4, 12, 14, 5, 10, 10, 7, 8, 7, 11, 17, 6, 6, 8, 7, 7, 9, 7, 9, 6, 10, 7, 7, 6, 9, 7, 10, 4, 12, 4, 13, 10, 5, 9, 10, 6, 10, 2, 14, 10, 8, 8, 9, 11, 14, 8, 11, 12, 12, 4, 8, 7, 7, 8, 9, 11]\n",
      "Genrtn 421: mean = 8.06  stddev = 2.71411127258998  max = 14 [3, 9, 3, 8, 3, 14, 10, 8, 8, 6, 8, 7, 13, 13, 10, 10, 8, 9, 7, 7, 7, 7, 6, 8, 9, 7, 9, 6, 6, 10, 5, 9, 12, 10, 12, 11, 10, 10, 8, 4, 3, 7, 12, 10, 3, 9, 8, 6, 9, 12, 11, 5, 9, 5, 12, 8, 12, 5, 6, 8, 10, 7, 8, 8, 4, 7, 5, 13, 11, 9, 7, 10, 8, 9, 7, 9, 9, 6, 5, 8, 4, 8, 12, 9, 7, 10, 9, 6, 12, 5, 8, 6, 7, 14, 11, 8, 7, 6, 9, 9, 11, 7, 13, 5, 9, 8, 9, 5, 10, 10, 10, 14, 11, 5, 7, 7, 9, 5, 12, 9, 9, 3, 9, 9, 10, 9, 7, 11, 2, 7, 4, 3, 9, 8, 6, 11, 12, 7, 11, 8, 7, 11, 13, 12, 9, 6, 8, 3, 10, 8, 12, 11, 5, 6, 10, 7, 11, 7, 11, 6, 11, 5, 8, 13, 1, 7, 4, 8, 5, 4, 3, 4, 14, 11, 7, 6, 8, 10, 5, 8, 8, 10, 10, 5, 8, 8, 6, 7, 6, 5, 5, 8, 5, 5, 8, 5, 13, 12, 7, 8]\n",
      "Genrtn 422: mean = 7.78  stddev = 2.8620971332224205  max = 18 [7, 6, 6, 6, 13, 10, 8, 3, 11, 10, 4, 6, 11, 8, 12, 10, 8, 8, 13, 4, 7, 11, 8, 5, 7, 11, 8, 6, 6, 10, 4, 10, 6, 6, 7, 8, 14, 9, 7, 3, 7, 11, 7, 6, 17, 6, 1, 4, 8, 4, 5, 7, 7, 8, 9, 6, 7, 5, 8, 8, 10, 6, 9, 10, 11, 4, 4, 0, 5, 5, 12, 9, 11, 6, 2, 7, 6, 8, 9, 12, 9, 5, 4, 7, 8, 8, 11, 12, 10, 9, 11, 8, 11, 7, 4, 7, 7, 11, 6, 5, 9, 5, 8, 3, 4, 10, 7, 10, 6, 8, 8, 5, 5, 8, 5, 5, 8, 10, 11, 5, 5, 18, 3, 10, 8, 9, 10, 10, 6, 8, 9, 4, 6, 9, 8, 5, 9, 8, 9, 4, 7, 7, 11, 7, 7, 10, 8, 4, 3, 4, 8, 11, 10, 8, 10, 4, 13, 6, 6, 13, 7, 7, 5, 5, 5, 9, 9, 11, 7, 7, 7, 6, 4, 8, 10, 9, 8, 7, 6, 9, 12, 5, 11, 10, 10, 10, 11, 10, 3, 12, 7, 11, 15, 10, 5, 8, 9, 16, 8, 8]\n",
      "Genrtn 423: mean = 7.94  stddev = 2.673275144836386  max = 16 [7, 8, 11, 6, 6, 9, 14, 8, 4, 10, 8, 9, 12, 8, 9, 10, 10, 10, 10, 12, 4, 7, 5, 9, 16, 8, 6, 9, 9, 9, 8, 8, 7, 8, 4, 10, 11, 9, 9, 10, 12, 10, 6, 5, 4, 11, 7, 9, 3, 9, 7, 10, 6, 8, 6, 11, 3, 12, 5, 9, 13, 7, 4, 8, 7, 8, 7, 3, 7, 11, 1, 8, 7, 7, 6, 12, 15, 7, 7, 10, 7, 6, 7, 6, 9, 6, 6, 4, 5, 13, 8, 7, 8, 5, 6, 9, 9, 3, 8, 9, 8, 10, 4, 4, 6, 2, 12, 6, 9, 12, 10, 10, 9, 4, 5, 6, 8, 7, 7, 12, 6, 6, 4, 5, 9, 6, 3, 6, 9, 10, 7, 11, 10, 3, 6, 4, 7, 6, 4, 8, 6, 8, 14, 9, 8, 9, 8, 7, 11, 8, 7, 9, 9, 7, 9, 3, 14, 10, 9, 7, 6, 9, 12, 10, 8, 12, 12, 7, 9, 9, 8, 8, 4, 9, 11, 11, 10, 8, 7, 9, 8, 10, 9, 10, 6, 10, 6, 9, 6, 14, 13, 4, 8, 6, 7, 7, 8, 2, 7, 10]\n",
      "Genrtn 424: mean = 7.975  stddev = 2.8168022649806286  max = 17 [9, 8, 2, 5, 6, 11, 7, 7, 10, 5, 8, 9, 10, 1, 10, 9, 6, 11, 6, 13, 7, 8, 16, 7, 6, 11, 9, 5, 8, 9, 8, 8, 10, 9, 8, 8, 9, 11, 11, 9, 10, 14, 7, 6, 5, 10, 8, 12, 5, 5, 6, 8, 8, 9, 6, 3, 4, 9, 3, 8, 7, 4, 10, 12, 9, 11, 9, 8, 11, 7, 4, 10, 11, 4, 12, 8, 13, 3, 7, 8, 4, 5, 9, 5, 9, 9, 8, 11, 9, 12, 7, 16, 6, 7, 11, 4, 8, 5, 5, 6, 8, 8, 9, 11, 5, 8, 10, 10, 4, 6, 10, 8, 8, 7, 10, 5, 7, 8, 10, 2, 11, 9, 8, 6, 5, 9, 6, 11, 9, 6, 6, 11, 4, 8, 11, 17, 6, 6, 4, 7, 3, 7, 10, 7, 5, 4, 3, 6, 7, 9, 12, 11, 5, 14, 9, 10, 9, 9, 5, 6, 10, 5, 8, 6, 8, 11, 7, 10, 10, 5, 12, 8, 10, 13, 11, 5, 6, 4, 5, 8, 7, 9, 13, 6, 13, 6, 4, 8, 6, 7, 4, 10, 9, 7, 11, 15, 10, 6, 10, 7]\n",
      "Genrtn 425: mean = 7.835  stddev = 2.7545916212752846  max = 15 [12, 9, 11, 5, 9, 7, 5, 3, 10, 12, 4, 8, 6, 6, 9, 10, 8, 9, 5, 7, 11, 11, 7, 5, 13, 8, 6, 13, 9, 12, 5, 6, 6, 6, 5, 9, 10, 5, 3, 4, 5, 8, 7, 6, 6, 6, 8, 10, 6, 8, 5, 10, 6, 11, 9, 9, 10, 8, 8, 9, 7, 10, 9, 12, 9, 15, 5, 5, 6, 10, 4, 7, 8, 7, 14, 11, 7, 11, 8, 6, 5, 8, 5, 5, 11, 4, 6, 14, 7, 6, 7, 6, 6, 4, 13, 6, 5, 11, 11, 15, 7, 15, 3, 5, 15, 9, 11, 6, 8, 10, 3, 5, 10, 10, 8, 8, 11, 13, 3, 5, 12, 9, 5, 4, 4, 6, 7, 7, 7, 11, 7, 6, 6, 9, 4, 4, 7, 9, 7, 6, 8, 7, 7, 3, 8, 10, 9, 6, 5, 10, 9, 7, 12, 8, 9, 7, 10, 8, 14, 9, 14, 6, 5, 5, 9, 12, 5, 7, 9, 9, 5, 8, 8, 9, 6, 8, 5, 6, 8, 8, 10, 10, 9, 5, 4, 5, 11, 6, 9, 13, 10, 7, 4, 6, 9, 7, 5, 10, 6, 11]\n",
      "Genrtn 426: mean = 8.04  stddev = 2.9391155132114153  max = 18 [13, 9, 8, 10, 6, 5, 5, 10, 7, 5, 5, 9, 10, 11, 7, 11, 15, 4, 7, 14, 7, 8, 7, 7, 4, 11, 3, 6, 7, 10, 7, 12, 7, 6, 10, 7, 6, 13, 3, 17, 15, 6, 10, 10, 6, 8, 7, 12, 5, 9, 7, 7, 10, 10, 5, 7, 10, 14, 15, 6, 7, 11, 11, 11, 7, 13, 13, 7, 6, 8, 8, 5, 10, 11, 5, 8, 9, 7, 3, 5, 7, 11, 9, 9, 11, 8, 9, 11, 10, 5, 8, 5, 7, 9, 8, 6, 8, 6, 6, 7, 8, 4, 6, 17, 7, 6, 12, 9, 4, 5, 12, 8, 6, 15, 6, 4, 6, 5, 9, 8, 5, 7, 7, 10, 11, 6, 6, 5, 10, 8, 7, 1, 9, 18, 9, 9, 7, 11, 7, 6, 6, 9, 9, 9, 8, 6, 5, 4, 8, 7, 6, 9, 3, 6, 9, 11, 5, 11, 6, 5, 12, 7, 4, 11, 9, 6, 7, 9, 15, 3, 3, 8, 8, 5, 5, 7, 8, 5, 8, 11, 8, 9, 5, 4, 10, 10, 13, 11, 5, 10, 9, 8, 8, 11, 5, 8, 8, 11, 8, 5]\n",
      "Genrtn 427: mean = 8.23  stddev = 2.774364792164145  max = 15 [2, 11, 6, 12, 8, 4, 7, 9, 10, 11, 9, 10, 9, 8, 7, 10, 12, 7, 6, 10, 4, 6, 7, 6, 8, 10, 9, 5, 11, 7, 11, 4, 7, 9, 5, 13, 6, 10, 6, 9, 4, 6, 6, 8, 13, 9, 15, 8, 9, 4, 6, 12, 13, 10, 8, 13, 10, 4, 3, 5, 11, 7, 9, 14, 9, 11, 12, 7, 6, 10, 6, 8, 9, 11, 7, 6, 8, 11, 14, 7, 11, 11, 5, 6, 5, 6, 8, 9, 6, 7, 5, 8, 9, 7, 7, 7, 9, 4, 5, 11, 5, 8, 8, 10, 12, 4, 5, 11, 5, 10, 9, 4, 8, 6, 8, 14, 8, 6, 4, 12, 11, 6, 10, 8, 6, 6, 7, 6, 8, 8, 8, 10, 10, 6, 12, 10, 6, 3, 8, 10, 3, 8, 4, 8, 9, 12, 10, 10, 10, 6, 7, 11, 3, 11, 8, 11, 7, 14, 8, 11, 10, 7, 13, 10, 10, 11, 8, 14, 10, 7, 8, 8, 7, 8, 5, 7, 7, 7, 8, 15, 12, 9, 10, 6, 12, 13, 5, 6, 14, 4, 8, 10, 6, 4, 7, 5, 10, 5, 13, 4]\n",
      "Genrtn 428: mean = 8.355  stddev = 2.8176186754065924  max = 18 [3, 5, 4, 9, 10, 12, 10, 6, 7, 6, 7, 10, 7, 8, 5, 7, 5, 9, 10, 7, 11, 11, 13, 7, 7, 7, 7, 10, 5, 10, 4, 7, 13, 6, 5, 5, 11, 8, 9, 8, 8, 12, 13, 10, 12, 7, 8, 7, 7, 10, 9, 13, 6, 8, 6, 10, 10, 12, 3, 11, 8, 7, 10, 10, 11, 7, 11, 10, 12, 12, 13, 12, 9, 9, 3, 10, 5, 8, 12, 15, 4, 11, 5, 7, 7, 18, 6, 9, 9, 2, 11, 7, 11, 3, 12, 7, 7, 10, 9, 9, 5, 12, 4, 13, 9, 11, 10, 9, 9, 5, 12, 5, 6, 12, 7, 6, 7, 12, 16, 9, 6, 8, 10, 7, 14, 6, 10, 6, 5, 9, 6, 9, 6, 8, 5, 4, 4, 6, 7, 5, 6, 10, 5, 7, 13, 8, 8, 13, 8, 10, 5, 14, 6, 4, 7, 7, 9, 11, 7, 5, 8, 5, 8, 10, 10, 9, 14, 10, 9, 7, 7, 7, 7, 14, 10, 9, 7, 9, 12, 9, 4, 9, 9, 8, 6, 10, 9, 5, 12, 6, 7, 10, 6, 6, 9, 10, 12, 8, 5, 5]\n",
      "Genrtn 429: mean = 8.035  stddev = 2.9315141139008696  max = 18 [12, 3, 8, 10, 8, 10, 13, 9, 8, 5, 9, 16, 12, 4, 7, 6, 11, 11, 3, 12, 6, 7, 7, 5, 8, 13, 12, 4, 13, 7, 11, 10, 5, 3, 7, 9, 6, 8, 9, 10, 7, 10, 11, 8, 9, 8, 12, 10, 8, 3, 3, 9, 9, 7, 6, 12, 7, 9, 8, 10, 6, 7, 7, 8, 8, 1, 6, 7, 3, 2, 8, 7, 6, 8, 10, 8, 3, 10, 9, 9, 13, 12, 6, 5, 9, 9, 10, 8, 11, 9, 9, 12, 7, 14, 7, 11, 7, 7, 5, 8, 5, 8, 6, 12, 10, 7, 9, 5, 14, 10, 6, 5, 10, 10, 8, 13, 5, 9, 7, 8, 6, 2, 9, 8, 4, 9, 8, 5, 3, 8, 9, 6, 11, 6, 4, 5, 5, 4, 7, 7, 12, 8, 5, 9, 10, 6, 7, 9, 5, 11, 8, 4, 11, 7, 9, 3, 7, 9, 11, 6, 10, 7, 14, 3, 6, 3, 6, 14, 7, 2, 6, 10, 8, 18, 9, 5, 7, 7, 9, 7, 15, 13, 8, 9, 10, 6, 8, 14, 11, 5, 11, 8, 10, 6, 12, 8, 7, 7, 6, 10]\n",
      "Genrtn 430: mean = 8.13  stddev = 2.733697130261507  max = 16 [8, 8, 5, 7, 6, 13, 5, 5, 10, 10, 9, 11, 7, 8, 8, 7, 7, 9, 8, 9, 5, 5, 6, 8, 6, 8, 14, 9, 4, 9, 8, 11, 6, 8, 8, 10, 10, 7, 4, 8, 7, 7, 5, 15, 9, 6, 4, 6, 8, 8, 8, 6, 13, 9, 11, 16, 7, 11, 7, 12, 10, 5, 9, 11, 14, 9, 6, 6, 12, 6, 6, 10, 13, 6, 8, 12, 7, 6, 5, 8, 8, 9, 8, 7, 10, 15, 12, 8, 5, 11, 8, 8, 4, 8, 8, 10, 7, 7, 6, 8, 11, 8, 9, 5, 10, 7, 8, 5, 3, 9, 6, 7, 7, 7, 7, 9, 10, 6, 8, 10, 3, 10, 6, 15, 12, 9, 6, 10, 6, 8, 5, 12, 11, 7, 11, 6, 2, 5, 4, 6, 13, 2, 10, 9, 8, 10, 11, 9, 14, 10, 10, 5, 9, 5, 10, 7, 9, 12, 13, 6, 9, 8, 8, 10, 8, 6, 11, 11, 12, 11, 8, 9, 4, 7, 8, 5, 9, 6, 6, 6, 6, 1, 7, 6, 7, 8, 5, 10, 10, 2, 7, 6, 11, 3, 16, 10, 9, 10, 8, 9]\n",
      "Genrtn 431: mean = 7.945  stddev = 3.1403781619416473  max = 18 [5, 12, 6, 10, 14, 10, 8, 10, 10, 8, 10, 9, 9, 11, 8, 6, 3, 9, 9, 13, 5, 15, 13, 5, 9, 5, 5, 9, 6, 10, 8, 9, 4, 5, 5, 5, 6, 6, 6, 10, 7, 10, 7, 8, 6, 6, 8, 7, 8, 9, 7, 7, 8, 4, 10, 8, 8, 5, 13, 4, 6, 7, 7, 10, 4, 5, 4, 9, 12, 10, 18, 10, 10, 7, 7, 9, 6, 9, 3, 1, 15, 4, 9, 11, 4, 5, 4, 12, 5, 15, 10, 4, 7, 3, 12, 9, 8, 5, 6, 12, 6, 6, 5, 6, 4, 8, 10, 13, 3, 5, 4, 10, 4, 4, 14, 9, 6, 6, 4, 3, 6, 1, 10, 7, 6, 10, 10, 15, 7, 8, 14, 13, 8, 8, 4, 7, 7, 7, 9, 4, 10, 6, 11, 8, 8, 10, 10, 4, 14, 9, 10, 9, 7, 9, 2, 15, 6, 8, 9, 14, 10, 10, 7, 6, 12, 9, 12, 4, 10, 8, 10, 10, 6, 6, 12, 7, 5, 6, 8, 9, 6, 11, 11, 14, 4, 7, 7, 5, 12, 8, 2, 11, 12, 13, 5, 6, 7, 11, 6, 4]\n",
      "Genrtn 432: mean = 8.005  stddev = 2.7613357275058026  max = 16 [11, 9, 11, 13, 6, 11, 5, 7, 4, 12, 10, 6, 12, 8, 10, 10, 12, 10, 5, 5, 9, 10, 11, 6, 2, 5, 4, 8, 7, 9, 14, 7, 10, 6, 10, 8, 9, 9, 2, 9, 5, 5, 11, 7, 11, 8, 10, 6, 15, 9, 7, 4, 10, 11, 7, 12, 7, 6, 11, 3, 9, 10, 9, 12, 11, 6, 9, 12, 2, 8, 9, 6, 8, 8, 13, 13, 10, 8, 5, 7, 7, 3, 6, 8, 3, 8, 11, 6, 8, 3, 6, 11, 9, 8, 8, 6, 8, 6, 5, 9, 5, 8, 10, 8, 9, 7, 7, 9, 9, 6, 5, 6, 13, 8, 6, 13, 10, 6, 7, 12, 5, 3, 11, 10, 11, 7, 7, 11, 4, 5, 8, 10, 12, 4, 4, 12, 13, 8, 9, 4, 7, 7, 5, 7, 4, 5, 9, 7, 10, 6, 7, 6, 8, 11, 9, 7, 10, 6, 8, 7, 10, 9, 8, 7, 5, 6, 8, 7, 6, 8, 10, 4, 12, 7, 11, 9, 2, 11, 7, 5, 5, 9, 11, 4, 6, 7, 3, 11, 7, 5, 10, 10, 14, 8, 12, 16, 8, 9, 8, 7]\n",
      "Genrtn 433: mean = 8.005  stddev = 2.5719593698190493  max = 15 [7, 8, 11, 8, 5, 5, 11, 7, 11, 4, 9, 6, 10, 6, 11, 5, 6, 6, 7, 4, 6, 3, 12, 11, 11, 5, 5, 7, 3, 12, 7, 8, 8, 9, 7, 7, 7, 9, 1, 7, 9, 6, 5, 7, 11, 7, 11, 13, 7, 4, 6, 13, 5, 6, 11, 12, 8, 9, 10, 6, 8, 7, 6, 9, 5, 10, 11, 9, 6, 11, 11, 8, 8, 5, 9, 6, 9, 2, 9, 8, 9, 5, 8, 4, 7, 6, 7, 9, 11, 9, 12, 3, 11, 14, 11, 4, 9, 10, 8, 11, 7, 5, 10, 6, 6, 6, 13, 10, 10, 5, 9, 9, 5, 9, 6, 8, 9, 9, 5, 11, 7, 9, 6, 8, 6, 8, 6, 6, 4, 5, 5, 9, 7, 9, 8, 7, 13, 12, 12, 12, 13, 7, 4, 9, 9, 8, 8, 11, 9, 10, 6, 5, 9, 13, 9, 11, 7, 8, 4, 9, 9, 9, 9, 8, 7, 13, 6, 11, 10, 7, 6, 15, 8, 9, 8, 8, 10, 5, 8, 13, 8, 8, 5, 9, 10, 8, 7, 9, 11, 7, 5, 6, 9, 5, 9, 10, 9, 11, 3, 4]\n",
      "Genrtn 434: mean = 7.975  stddev = 2.850328928387038  max = 18 [8, 6, 8, 8, 11, 5, 5, 8, 9, 7, 7, 7, 8, 6, 10, 6, 7, 15, 4, 8, 9, 8, 5, 9, 7, 7, 7, 9, 11, 5, 10, 10, 5, 10, 7, 4, 11, 1, 6, 7, 9, 13, 4, 6, 12, 9, 10, 9, 7, 9, 10, 5, 6, 7, 6, 9, 11, 7, 6, 8, 8, 9, 10, 7, 2, 12, 8, 6, 7, 11, 6, 9, 15, 9, 12, 8, 8, 7, 6, 6, 11, 8, 7, 2, 6, 6, 14, 9, 11, 4, 5, 9, 7, 10, 9, 12, 7, 6, 9, 9, 14, 17, 5, 9, 12, 4, 9, 8, 4, 5, 11, 4, 6, 11, 4, 6, 7, 7, 8, 7, 11, 7, 7, 8, 13, 12, 5, 7, 8, 8, 3, 6, 2, 5, 9, 8, 13, 12, 11, 7, 10, 6, 6, 6, 15, 6, 8, 8, 16, 7, 13, 8, 6, 4, 7, 6, 8, 5, 11, 10, 9, 9, 12, 5, 6, 8, 3, 8, 10, 5, 8, 7, 10, 11, 7, 7, 6, 6, 8, 8, 10, 8, 8, 9, 6, 4, 7, 13, 7, 11, 10, 12, 5, 9, 3, 7, 18, 7, 6, 5]\n",
      "Genrtn 435: mean = 7.865  stddev = 2.83844587758865  max = 18 [11, 13, 4, 7, 9, 4, 4, 11, 9, 7, 8, 8, 9, 8, 4, 8, 6, 8, 10, 10, 7, 7, 9, 6, 7, 14, 11, 5, 10, 13, 5, 10, 8, 11, 5, 8, 7, 9, 7, 9, 8, 12, 10, 5, 5, 12, 6, 10, 6, 5, 7, 7, 6, 14, 12, 15, 6, 10, 12, 8, 5, 11, 9, 8, 9, 6, 6, 10, 8, 10, 6, 9, 2, 7, 7, 14, 6, 5, 6, 6, 5, 11, 6, 12, 9, 1, 7, 11, 9, 12, 2, 8, 10, 7, 5, 8, 9, 8, 5, 6, 9, 8, 5, 3, 9, 7, 11, 5, 4, 9, 9, 5, 8, 4, 4, 18, 11, 6, 11, 7, 6, 1, 11, 11, 1, 5, 9, 5, 11, 8, 11, 7, 5, 12, 4, 9, 2, 8, 11, 9, 10, 8, 7, 5, 9, 5, 8, 7, 7, 7, 8, 10, 5, 5, 9, 11, 7, 10, 7, 8, 6, 7, 5, 7, 9, 8, 7, 8, 7, 9, 8, 10, 17, 8, 13, 8, 8, 9, 3, 8, 9, 5, 10, 8, 7, 2, 8, 6, 13, 6, 9, 9, 6, 12, 6, 7, 3, 10, 8, 9]\n",
      "Genrtn 436: mean = 7.91  stddev = 2.818137682938859  max = 17 [6, 7, 4, 12, 8, 12, 12, 9, 11, 11, 4, 9, 10, 9, 7, 6, 10, 8, 8, 6, 9, 8, 5, 4, 6, 6, 8, 8, 7, 10, 4, 6, 8, 8, 9, 6, 12, 12, 4, 3, 4, 8, 3, 8, 10, 11, 8, 7, 6, 6, 6, 3, 5, 8, 6, 12, 10, 12, 7, 6, 9, 6, 4, 3, 11, 4, 8, 9, 8, 7, 7, 5, 6, 7, 9, 10, 8, 12, 8, 8, 17, 10, 9, 14, 7, 3, 4, 7, 11, 14, 11, 9, 11, 8, 8, 10, 10, 3, 13, 5, 8, 7, 7, 13, 10, 12, 12, 2, 6, 5, 5, 6, 10, 6, 8, 9, 6, 13, 10, 6, 8, 8, 9, 9, 9, 12, 10, 8, 8, 8, 5, 12, 4, 12, 6, 12, 9, 9, 9, 12, 10, 5, 8, 3, 10, 8, 10, 10, 4, 9, 7, 4, 8, 10, 4, 14, 8, 6, 7, 8, 8, 5, 6, 6, 3, 7, 10, 11, 3, 7, 5, 9, 5, 9, 6, 5, 9, 14, 10, 4, 5, 13, 13, 8, 9, 3, 6, 8, 11, 10, 9, 3, 6, 8, 3, 9, 7, 11, 8, 6]\n",
      "Genrtn 437: mean = 7.84  stddev = 2.8168067026333206  max = 16 [11, 7, 5, 7, 9, 7, 14, 8, 10, 5, 8, 3, 11, 9, 11, 8, 4, 9, 8, 10, 6, 8, 4, 5, 7, 6, 9, 13, 7, 8, 8, 5, 6, 10, 9, 8, 4, 5, 12, 8, 5, 9, 4, 6, 6, 2, 4, 9, 6, 10, 4, 5, 5, 11, 11, 16, 8, 5, 8, 6, 9, 10, 4, 5, 6, 6, 5, 11, 6, 6, 11, 10, 12, 6, 6, 9, 10, 3, 4, 14, 5, 11, 7, 9, 7, 11, 4, 9, 9, 6, 11, 4, 12, 8, 11, 10, 2, 7, 5, 4, 13, 11, 9, 7, 8, 3, 14, 6, 7, 5, 7, 7, 7, 9, 5, 10, 8, 10, 13, 3, 9, 4, 13, 9, 8, 7, 6, 11, 6, 8, 10, 12, 9, 10, 14, 7, 6, 10, 10, 12, 8, 3, 8, 9, 7, 11, 2, 10, 10, 10, 6, 9, 7, 8, 9, 12, 9, 10, 8, 6, 7, 5, 6, 5, 6, 5, 6, 11, 9, 9, 12, 8, 8, 4, 1, 7, 8, 4, 10, 8, 12, 11, 9, 4, 7, 12, 5, 12, 11, 5, 6, 7, 4, 7, 8, 7, 10, 13, 7, 10]\n",
      "Genrtn 438: mean = 7.96  stddev = 2.763765547219952  max = 15 [8, 9, 9, 15, 12, 3, 9, 7, 5, 7, 7, 7, 7, 6, 5, 11, 10, 9, 12, 7, 7, 5, 9, 9, 4, 8, 7, 4, 12, 4, 8, 8, 8, 7, 7, 10, 8, 7, 6, 6, 11, 7, 12, 11, 7, 6, 6, 11, 8, 11, 5, 8, 5, 9, 9, 6, 3, 2, 9, 8, 7, 5, 6, 10, 8, 14, 10, 0, 8, 5, 6, 9, 11, 12, 8, 8, 10, 2, 8, 8, 14, 6, 9, 4, 5, 15, 10, 6, 10, 11, 8, 11, 8, 12, 7, 10, 8, 5, 9, 7, 13, 7, 8, 9, 7, 9, 8, 10, 10, 10, 5, 11, 11, 7, 6, 7, 10, 6, 2, 4, 10, 6, 12, 8, 8, 7, 4, 4, 7, 4, 4, 10, 8, 7, 9, 4, 11, 11, 6, 6, 10, 6, 8, 8, 13, 8, 7, 10, 8, 10, 9, 11, 4, 8, 11, 9, 5, 6, 6, 7, 9, 11, 7, 13, 3, 10, 12, 8, 6, 8, 10, 5, 10, 5, 5, 13, 11, 10, 5, 9, 4, 13, 6, 8, 6, 5, 7, 15, 7, 12, 5, 8, 15, 5, 9, 7, 10, 5, 4, 8]\n",
      "Genrtn 439: mean = 8.31  stddev = 2.6521500711686734  max = 17 [11, 7, 7, 5, 7, 5, 6, 8, 9, 8, 9, 9, 9, 6, 9, 10, 8, 8, 9, 8, 6, 8, 5, 7, 11, 16, 12, 7, 8, 7, 8, 7, 9, 10, 6, 4, 8, 8, 10, 10, 11, 9, 14, 7, 11, 11, 6, 4, 5, 8, 10, 10, 11, 7, 11, 15, 13, 11, 5, 6, 10, 10, 8, 8, 7, 9, 5, 14, 8, 8, 9, 7, 10, 4, 11, 11, 8, 6, 3, 7, 7, 6, 7, 4, 8, 6, 6, 12, 9, 13, 3, 9, 10, 7, 8, 13, 8, 11, 14, 9, 8, 4, 7, 11, 7, 8, 8, 10, 5, 7, 7, 9, 6, 5, 5, 9, 7, 11, 9, 9, 11, 6, 12, 5, 12, 9, 8, 10, 4, 9, 6, 7, 7, 17, 8, 14, 6, 8, 11, 12, 13, 6, 8, 14, 6, 8, 7, 9, 6, 7, 3, 8, 5, 10, 9, 6, 9, 10, 11, 11, 12, 7, 12, 8, 6, 7, 8, 12, 11, 6, 5, 6, 9, 7, 6, 8, 7, 8, 4, 8, 11, 5, 12, 13, 8, 6, 8, 9, 7, 9, 4, 10, 8, 10, 5, 6, 1, 8, 10, 12]\n",
      "Genrtn 440: mean = 7.64  stddev = 2.7203676222157913  max = 16 [10, 9, 9, 7, 7, 6, 9, 11, 7, 7, 9, 7, 11, 6, 5, 8, 3, 7, 5, 6, 13, 11, 3, 8, 5, 6, 5, 7, 6, 4, 5, 9, 4, 7, 8, 9, 7, 12, 7, 5, 8, 6, 9, 9, 9, 7, 8, 3, 8, 8, 8, 3, 9, 8, 10, 8, 6, 8, 7, 2, 11, 13, 5, 7, 6, 5, 16, 8, 5, 6, 8, 6, 5, 7, 13, 9, 8, 7, 9, 10, 3, 5, 8, 11, 10, 2, 6, 9, 10, 8, 5, 9, 6, 11, 7, 8, 10, 8, 11, 6, 6, 8, 5, 8, 11, 5, 7, 13, 5, 8, 11, 6, 9, 11, 7, 3, 6, 11, 10, 6, 7, 10, 3, 10, 7, 10, 8, 6, 12, 7, 5, 9, 12, 7, 2, 3, 12, 10, 10, 11, 11, 9, 4, 6, 5, 15, 6, 9, 8, 6, 9, 12, 5, 7, 5, 7, 9, 9, 10, 10, 1, 7, 12, 6, 6, 9, 4, 8, 6, 10, 7, 6, 3, 7, 8, 9, 3, 3, 5, 11, 11, 6, 6, 13, 14, 13, 10, 6, 7, 6, 12, 5, 10, 4, 8, 8, 4, 6, 10, 8]\n",
      "Genrtn 441: mean = 7.87  stddev = 2.575480537686123  max = 15 [5, 9, 6, 6, 4, 8, 6, 6, 7, 11, 9, 6, 8, 6, 4, 9, 9, 12, 12, 7, 6, 5, 8, 3, 6, 11, 5, 5, 6, 4, 9, 7, 13, 8, 6, 9, 10, 5, 9, 6, 6, 5, 15, 6, 8, 8, 8, 5, 9, 9, 9, 7, 11, 10, 8, 10, 10, 15, 6, 9, 10, 11, 9, 8, 5, 5, 9, 9, 6, 7, 6, 10, 7, 8, 7, 7, 13, 6, 9, 4, 8, 9, 8, 13, 6, 13, 9, 6, 7, 6, 3, 7, 11, 7, 8, 5, 10, 10, 6, 5, 7, 10, 7, 7, 10, 5, 11, 4, 12, 8, 8, 12, 9, 9, 9, 5, 7, 8, 6, 13, 8, 12, 3, 8, 5, 9, 8, 5, 8, 9, 9, 7, 5, 8, 10, 9, 3, 4, 7, 3, 9, 3, 7, 12, 10, 10, 9, 10, 4, 11, 10, 8, 11, 7, 14, 8, 3, 6, 11, 3, 9, 8, 5, 7, 11, 11, 8, 8, 9, 11, 4, 5, 7, 4, 11, 12, 9, 10, 6, 12, 6, 11, 9, 11, 9, 12, 8, 6, 7, 6, 8, 5, 6, 8, 11, 7, 7, 8, 2, 9]\n",
      "Genrtn 442: mean = 7.91  stddev = 2.9123701687800607  max = 17 [11, 2, 10, 12, 7, 6, 11, 9, 15, 4, 9, 5, 8, 8, 7, 2, 9, 5, 9, 10, 6, 8, 5, 7, 11, 6, 10, 9, 3, 12, 12, 7, 9, 7, 7, 5, 6, 13, 7, 13, 11, 5, 6, 7, 10, 6, 6, 15, 10, 4, 7, 9, 13, 9, 6, 11, 6, 6, 7, 2, 10, 6, 8, 8, 5, 5, 7, 7, 6, 4, 8, 11, 9, 9, 6, 10, 11, 9, 6, 7, 7, 5, 3, 6, 8, 11, 10, 5, 14, 7, 11, 15, 9, 6, 8, 12, 7, 7, 6, 8, 6, 7, 3, 8, 7, 7, 8, 6, 7, 8, 6, 11, 5, 7, 10, 5, 3, 8, 4, 10, 4, 10, 11, 4, 7, 10, 5, 7, 11, 12, 3, 8, 8, 16, 5, 7, 6, 6, 10, 11, 8, 5, 17, 14, 12, 5, 6, 12, 8, 6, 11, 8, 8, 6, 8, 14, 9, 8, 7, 4, 7, 11, 9, 6, 3, 8, 10, 6, 10, 11, 9, 9, 3, 10, 12, 6, 9, 4, 6, 3, 9, 6, 3, 11, 13, 7, 9, 7, 10, 8, 8, 9, 14, 4, 7, 8, 3, 10, 9, 7]\n",
      "Genrtn 443: mean = 8.055  stddev = 2.9363199757519616  max = 16 [9, 7, 13, 8, 3, 6, 6, 15, 6, 6, 11, 12, 5, 6, 7, 7, 4, 6, 10, 3, 10, 10, 3, 8, 11, 10, 6, 8, 1, 8, 12, 5, 16, 4, 13, 13, 5, 8, 7, 11, 8, 9, 3, 8, 6, 10, 11, 6, 10, 5, 8, 3, 16, 10, 6, 8, 9, 3, 10, 5, 6, 13, 6, 7, 9, 10, 9, 8, 8, 7, 3, 9, 8, 9, 9, 5, 13, 8, 6, 11, 11, 6, 10, 11, 9, 9, 8, 9, 6, 9, 13, 6, 15, 8, 7, 9, 5, 9, 7, 6, 12, 6, 11, 12, 7, 11, 8, 7, 10, 8, 10, 10, 6, 11, 12, 5, 10, 4, 11, 11, 5, 12, 3, 7, 9, 16, 3, 6, 7, 8, 9, 8, 8, 11, 10, 11, 7, 11, 10, 11, 10, 8, 9, 4, 4, 11, 9, 11, 5, 6, 6, 10, 5, 10, 12, 3, 8, 10, 6, 7, 9, 7, 15, 9, 2, 7, 9, 8, 9, 6, 14, 9, 7, 12, 9, 5, 7, 2, 4, 8, 8, 7, 8, 11, 6, 4, 11, 7, 5, 6, 8, 3, 4, 8, 8, 5, 7, 8, 6, 5]\n",
      "Genrtn 444: mean = 8.115  stddev = 3.151471878345101  max = 17 [8, 16, 5, 11, 5, 7, 6, 8, 6, 14, 11, 9, 12, 10, 7, 2, 6, 6, 6, 5, 5, 13, 6, 5, 17, 7, 10, 5, 7, 7, 8, 6, 8, 12, 3, 9, 8, 11, 9, 12, 7, 11, 11, 10, 3, 6, 8, 14, 7, 5, 7, 9, 4, 5, 9, 5, 8, 8, 10, 12, 7, 9, 6, 8, 9, 12, 14, 17, 11, 15, 11, 9, 11, 12, 8, 9, 5, 5, 10, 8, 6, 8, 4, 13, 9, 5, 9, 7, 7, 2, 8, 7, 9, 4, 8, 8, 11, 10, 4, 12, 8, 7, 10, 5, 5, 5, 2, 10, 10, 5, 8, 10, 3, 7, 6, 8, 5, 6, 9, 8, 7, 8, 4, 10, 7, 9, 10, 9, 5, 5, 7, 14, 6, 10, 6, 8, 6, 16, 5, 11, 10, 15, 8, 11, 4, 9, 5, 5, 9, 14, 11, 8, 10, 9, 6, 4, 11, 2, 9, 5, 8, 4, 5, 15, 3, 11, 4, 5, 13, 9, 2, 12, 12, 7, 10, 6, 4, 8, 4, 12, 9, 7, 6, 13, 11, 15, 7, 4, 5, 6, 9, 13, 7, 9, 11, 8, 8, 6, 8, 8]\n",
      "Genrtn 445: mean = 7.83  stddev = 3.0085046119293217  max = 17 [5, 14, 5, 4, 5, 5, 12, 14, 4, 12, 8, 6, 5, 7, 7, 9, 6, 11, 10, 5, 7, 3, 6, 6, 11, 7, 8, 9, 4, 8, 5, 7, 2, 5, 8, 4, 11, 3, 10, 7, 4, 9, 14, 8, 6, 13, 5, 3, 5, 8, 12, 15, 10, 3, 9, 14, 8, 6, 9, 15, 5, 8, 10, 12, 5, 11, 14, 8, 8, 11, 7, 7, 12, 11, 8, 6, 10, 5, 9, 2, 8, 6, 7, 6, 13, 5, 5, 6, 11, 8, 9, 3, 12, 9, 8, 7, 6, 8, 7, 7, 6, 5, 14, 10, 6, 8, 13, 7, 13, 8, 9, 12, 8, 4, 9, 14, 6, 7, 6, 4, 14, 11, 9, 9, 8, 7, 6, 8, 10, 8, 5, 9, 5, 5, 6, 7, 6, 10, 8, 3, 10, 7, 8, 8, 7, 4, 5, 8, 9, 10, 7, 5, 4, 12, 8, 8, 10, 6, 6, 5, 6, 7, 12, 5, 6, 7, 6, 11, 6, 8, 5, 14, 9, 8, 8, 5, 9, 9, 13, 5, 7, 9, 13, 12, 5, 8, 3, 8, 8, 4, 10, 6, 2, 2, 10, 10, 6, 8, 8, 17]\n",
      "Genrtn 446: mean = 7.905  stddev = 2.633623929113646  max = 16 [16, 10, 10, 5, 5, 8, 4, 11, 10, 3, 8, 4, 9, 7, 7, 13, 5, 7, 9, 9, 9, 14, 10, 7, 8, 8, 10, 5, 7, 12, 5, 5, 4, 8, 3, 7, 8, 11, 6, 8, 7, 5, 11, 8, 3, 6, 9, 4, 6, 4, 5, 4, 6, 10, 12, 11, 8, 7, 7, 11, 11, 4, 10, 9, 6, 6, 7, 14, 9, 10, 8, 4, 6, 7, 6, 11, 6, 6, 7, 6, 7, 9, 10, 9, 6, 8, 11, 12, 11, 9, 7, 5, 7, 11, 7, 7, 7, 11, 7, 10, 7, 11, 9, 4, 11, 10, 13, 9, 12, 6, 6, 6, 6, 6, 11, 7, 8, 10, 5, 6, 8, 6, 12, 8, 7, 9, 4, 8, 7, 12, 8, 7, 10, 6, 4, 10, 7, 5, 10, 9, 8, 7, 8, 15, 6, 6, 11, 5, 11, 4, 7, 2, 7, 11, 6, 8, 3, 11, 8, 8, 6, 13, 5, 6, 6, 10, 8, 11, 8, 6, 5, 9, 13, 8, 11, 6, 6, 8, 6, 8, 9, 5, 5, 8, 3, 7, 10, 8, 11, 9, 11, 9, 11, 9, 9, 3, 13, 12, 8, 7]\n",
      "Genrtn 447: mean = 7.81  stddev = 2.7210108415807532  max = 14 [5, 11, 6, 6, 14, 10, 12, 10, 8, 4, 12, 8, 6, 7, 7, 8, 8, 4, 10, 2, 8, 6, 10, 5, 6, 6, 6, 10, 6, 4, 10, 13, 8, 10, 7, 14, 9, 9, 12, 7, 6, 8, 5, 4, 10, 8, 4, 7, 10, 11, 13, 8, 8, 7, 8, 10, 9, 10, 5, 9, 6, 14, 10, 12, 8, 7, 8, 0, 7, 7, 8, 9, 10, 6, 5, 7, 13, 7, 4, 11, 8, 6, 10, 7, 10, 10, 10, 8, 8, 12, 9, 3, 13, 5, 9, 4, 6, 11, 7, 6, 8, 8, 7, 10, 13, 4, 10, 6, 12, 5, 5, 10, 10, 4, 10, 8, 7, 10, 6, 11, 13, 8, 7, 5, 7, 8, 6, 13, 6, 9, 7, 6, 3, 7, 10, 6, 10, 9, 6, 9, 4, 8, 12, 5, 7, 8, 4, 7, 7, 10, 5, 10, 11, 7, 8, 8, 6, 11, 5, 8, 6, 2, 11, 5, 1, 5, 4, 6, 6, 6, 13, 5, 9, 3, 5, 2, 8, 7, 3, 7, 8, 6, 7, 6, 12, 11, 7, 9, 7, 10, 10, 9, 11, 11, 5, 6, 8, 11, 9, 10]\n",
      "Genrtn 448: mean = 8.02  stddev = 2.889567441677041  max = 16 [15, 6, 6, 6, 7, 7, 15, 4, 7, 8, 7, 7, 4, 8, 7, 16, 6, 6, 6, 15, 8, 6, 6, 8, 12, 9, 9, 10, 6, 10, 7, 3, 10, 11, 7, 13, 2, 8, 11, 8, 8, 7, 6, 9, 9, 9, 7, 9, 7, 16, 11, 8, 7, 6, 9, 8, 3, 13, 5, 6, 9, 7, 14, 5, 6, 7, 14, 5, 13, 5, 11, 9, 16, 9, 10, 11, 9, 8, 5, 8, 6, 6, 5, 4, 10, 6, 8, 8, 5, 6, 12, 14, 8, 13, 12, 4, 1, 13, 5, 9, 5, 9, 10, 8, 11, 14, 8, 5, 6, 8, 7, 5, 5, 8, 4, 8, 7, 6, 6, 7, 5, 4, 10, 12, 9, 9, 5, 8, 1, 6, 9, 5, 7, 6, 7, 5, 7, 7, 6, 11, 6, 5, 5, 7, 7, 7, 5, 8, 10, 11, 3, 12, 10, 6, 5, 11, 5, 7, 5, 6, 9, 11, 7, 10, 10, 10, 9, 8, 11, 12, 8, 11, 7, 6, 4, 7, 8, 7, 7, 14, 8, 10, 13, 6, 11, 10, 8, 6, 6, 11, 5, 8, 9, 7, 11, 10, 7, 9, 9, 11]\n",
      "Genrtn 449: mean = 7.66  stddev = 2.9789931184881917  max = 15 [5, 1, 2, 12, 10, 4, 13, 11, 13, 4, 8, 9, 9, 3, 9, 9, 6, 10, 9, 15, 11, 7, 7, 12, 7, 9, 5, 7, 11, 4, 9, 5, 7, 9, 10, 1, 3, 7, 7, 8, 5, 7, 14, 9, 9, 8, 13, 9, 7, 5, 10, 7, 9, 7, 9, 11, 2, 8, 7, 3, 8, 5, 10, 12, 1, 10, 8, 6, 13, 4, 8, 5, 4, 8, 6, 13, 7, 11, 6, 5, 8, 7, 7, 13, 12, 6, 4, 12, 7, 5, 13, 3, 8, 7, 7, 4, 7, 5, 12, 8, 4, 6, 6, 9, 12, 9, 7, 8, 3, 5, 5, 12, 14, 7, 10, 8, 4, 12, 5, 7, 12, 7, 4, 10, 7, 9, 15, 5, 9, 9, 12, 7, 4, 5, 6, 10, 3, 9, 5, 8, 5, 10, 6, 7, 10, 2, 7, 5, 11, 11, 11, 9, 5, 10, 15, 7, 4, 9, 8, 10, 5, 12, 7, 5, 9, 7, 9, 8, 6, 7, 6, 6, 9, 5, 4, 6, 7, 6, 6, 8, 5, 10, 6, 5, 9, 8, 6, 6, 8, 3, 9, 12, 3, 6, 7, 5, 10, 10, 9, 14]\n",
      "Genrtn 450: mean = 8.155  stddev = 2.9700126262357873  max = 16 [7, 8, 5, 14, 9, 11, 3, 14, 10, 11, 14, 9, 9, 14, 8, 10, 13, 6, 9, 6, 6, 7, 12, 4, 11, 10, 6, 13, 8, 9, 8, 4, 8, 9, 10, 9, 15, 6, 10, 4, 12, 10, 8, 6, 4, 10, 7, 7, 10, 6, 5, 3, 11, 7, 16, 8, 8, 13, 6, 10, 4, 4, 7, 6, 8, 4, 8, 8, 5, 6, 12, 6, 7, 13, 6, 11, 3, 4, 8, 10, 8, 8, 13, 11, 12, 11, 11, 6, 8, 4, 7, 10, 5, 6, 8, 5, 14, 5, 8, 6, 11, 10, 10, 11, 7, 5, 7, 8, 12, 9, 13, 5, 16, 5, 10, 7, 9, 8, 8, 9, 6, 6, 8, 6, 6, 5, 9, 7, 10, 6, 9, 12, 5, 8, 8, 10, 6, 9, 11, 6, 7, 6, 7, 12, 13, 3, 4, 10, 11, 6, 6, 7, 12, 8, 8, 6, 5, 6, 11, 7, 7, 4, 7, 8, 7, 3, 14, 12, 8, 15, 9, 4, 13, 5, 4, 8, 6, 8, 11, 6, 6, 5, 8, 3, 10, 11, 6, 13, 6, 4, 7, 3, 8, 9, 11, 8, 4, 11, 13, 6]\n",
      "Expected value = mutation_rate * length_of_target_sequence = 8.0\n",
      "Expected standard deviation = sqrt(mutation_rate * (1 - mutation_rate) * length_of_target_sequence) = 2.814249455894058\n"
     ]
    }
   ],
   "source": [
    "# Program Variability_in_the_number_of_touched_sites.py\n",
    "\n",
    "\n",
    "import datetime\n",
    "import random\n",
    "import matplotlib.pyplot as plt # Import matplotlib for plotting\n",
    "# target_sequence = 'Methinks it is like a weasel.'\n",
    "# alphabet = 'abcdefghijklmnopqrstuvwxyzABCDEFGHIJKLMNOPQRSTUVWXYZ .,'\n",
    "alphabet = '01' # Binary alphabet, binary strings\n",
    "length_of_target_sequence = 800\n",
    "target_sequence = '1'*length_of_target_sequence  #1111...1 (800 ones)\n",
    "population_size = 200\n",
    "include_clone_populationf3 = True\n",
    "include_mutate_allf3 = True\n",
    "include_crossover_allf3 = False\n",
    "mutation_rate = 0.01\n",
    "recombination_rate = 0\n",
    "# alphabet = 'abcdefghijklmnopqrstuvwxyzABCDEFGHIJKLMNOPQRSTUVWXYZ .,'\n",
    "# Boolean flag to print the generation, best chromosome and fitness.\n",
    "# This is the ancestral line of the solution.\n",
    "print_best_fitness = False\n",
    "show_graph = True\n",
    "\n",
    "\n",
    "def print_parametersf3():\n",
    "    print(f\"Lab: Simple Genetic Algorithm\")\n",
    "    print(f\"Purpose: solve an instance of the Shakespeare challenge\")\n",
    "    print(f\"Date of Experiment  = {datetime.datetime.now()}\")\n",
    "    print(f\"alphabet =  {alphabet}\")\n",
    "    print(f\"target_sequence = {target_sequence}\")\n",
    "    print(f\"length_of_target_sequence = {length_of_target_sequence}\")\n",
    "    print(f\"population_size = {population_size}\")\n",
    "    print(f\"include_clone_populationf3 = {include_clone_populationf3}\")\n",
    "    print(f\"include_mutate_allf3 = {include_mutate_allf3}\")\n",
    "    print(f\"include_crossover_allf3 = {include_crossover_allf3}\")\n",
    "    if include_mutate_allf3:\n",
    "        print(f\"mutation_rate = {mutation_rate}\")\n",
    "    if include_crossover_allf3:\n",
    "        print(f\"recombination_rate = {recombination_rate}\")\n",
    "    if include_clone_populationf3:\n",
    "        print(f\"print_best_fitness = {print_best_fitness}\")\n",
    "\n",
    "def max(data):\n",
    "    max_value = data[0]\n",
    "    for x in data:\n",
    "        if x > max_value:\n",
    "            max_value = x\n",
    "    return max_value\n",
    "\n",
    "\n",
    "\n",
    "def mean_stddev_and_max(data):\n",
    "    mean = sum(data) / len(data)\n",
    "    variance = sum((x - mean) ** 2 for x in data) / len(data)\n",
    "    stddev = variance ** 0.5\n",
    "    max_value = max(data)\n",
    "    return mean, stddev, max_value\n",
    "\n",
    "def create_populationf3(population_size, target_sequence, alphabet):\n",
    "    \"\"\"Creates a new population with random chromosomes.\"\"\"\n",
    "    # print(\"create_population8(population_size, target_sequence, alphabet)\")\n",
    "    population = []\n",
    "    for _ in range(population_size):\n",
    "        random_string = ''.join(random.choice(alphabet) for _ in range(len(target_sequence)))\n",
    "        population.append(random_string)\n",
    "    # print(\"initial population\")\n",
    "    # print(population)\n",
    "    return population\n",
    "\n",
    "def calculate_fitnessf3(chromosome, target_sequence):\n",
    "    \"\"\"Calculates the fitness of a chromosome based on its similarity to the target sequence.\"\"\"\n",
    "    #  print(\"\\n *calculate_fitness8(chromosome, target_sequence)\")\n",
    "    fitness = 0\n",
    "    for i in range(len(chromosome)):\n",
    "        if chromosome[i] == target_sequence[i]:\n",
    "            fitness += 1\n",
    "    # print(chromosome, \"  fitness: \", fitness)\n",
    "    return fitness\n",
    "\n",
    "def calculate_all_fitnessf3(population, target_sequence):\n",
    "    # print(\"\\n*calculate_all_fitness8(population, target_sequence)\")\n",
    "    \"\"\"Calculates the fitness of all chromosomes in the population.\"\"\"\n",
    "    fitness_scores = [calculate_fitnessf3(chromosome, target_sequence) for chromosome in population]\n",
    "    # print(\"fitness_scores: \", fitness_scores)\n",
    "    return fitness_scores\n",
    "\n",
    "def select_the_bestf3(population, target_sequence):\n",
    "    \"\"\"Selects the best chromosome for reproduction.\"\"\"\n",
    "    fitness_scores = calculate_all_fitnessf3(population, target_sequence)\n",
    "    best_fitness = max(fitness_scores)\n",
    "    best_chromosome_index = fitness_scores.index(best_fitness)\n",
    "    best_chromosome = population[best_chromosome_index]\n",
    "    # print(\"\\n*select_the_bestf3(population)\")\n",
    "    # print(\"best_fitness = \", best_fitness)\n",
    "    # print(\"The chro = \", best_chromosome )\n",
    "    return best_fitness, best_chromosome\n",
    "\n",
    "def clone_populationf3(best_chromosome, population_size):\n",
    "    \"\"\"Creates a new population by cloning the best chromosome.\"\"\"\n",
    "    return [best_chromosome] * population_size\n",
    "\n",
    "\n",
    "def mutatef3(chromosome, mutation_rate, alphabet):\n",
    "    \"\"\"Mutates a chromosome.\"\"\"\n",
    "    counter = 0\n",
    "    mutated_chromosome_list = list(chromosome)\n",
    "    for i in range(len(mutated_chromosome_list)):\n",
    "        if random.random() < mutation_rate:\n",
    "                mutated_chromosome_list[i] = random.choice(alphabet)\n",
    "                counter += 1\n",
    "    return \"\".join(mutated_chromosome_list), counter\n",
    "\n",
    "def mutate_allf3(population, mutation_rate, alphabet):\n",
    "    \"\"\"Mutates all chromosomes in the population.\"\"\"\n",
    "    mutated_population = []\n",
    "    touched_numbers = [] # List to store the number of touched sites for each chromosome\n",
    "    for chromosome in population:\n",
    "        mutated_chromosome, counter = mutatef3(chromosome, mutation_rate, alphabet)\n",
    "        mutated_population.append(mutated_chromosome)\n",
    "        touched_numbers.append(counter)\n",
    "    return mutated_population, touched_numbers\n",
    "\n",
    "def crossoverf3(parent1, parent2, target_sequence, recombination_rate):\n",
    "    \"\"\"Performs crossover between two parent chromosomes.\"\"\"\n",
    "    if random.random() < recombination_rate:\n",
    "        crossover_point = random.randint(0, len(target_sequence))\n",
    "        return parent1[:crossover_point] + parent2[crossover_point:]\n",
    "    else:\n",
    "        return parent1\n",
    "\n",
    "def crossover_allf3(population, target_sequence, recombination_rate):\n",
    "    \"\"\"Performs crossover on all chromosomes in the population.\"\"\"\n",
    "    recombinant_population = []\n",
    "    for i in range(len(population)):\n",
    "        parent1 =  population[i]\n",
    "        parent2 = random.choice(population)\n",
    "        child = crossoverf3(parent1, parent2, target_sequence, recombination_rate)\n",
    "        recombinant_population.append(child)\n",
    "    return recombinant_population\n",
    "\n",
    "\n",
    "\n",
    "def run_one_generationf3(population, target_sequence, mutation_rate, recombination_rate, alphabet):\n",
    "    \"\"\"Runs one generation of the genetic algorithm.\"\"\"\n",
    "    # Calculate fitness scores for the current population\n",
    "    best_fitness, best_chromosome  = select_the_bestf3(population, target_sequence)\n",
    "    # print(f\" best_chromosome {best_chromosome}, best_fitness {best_fitness}\")\n",
    "    # Clone the best to build the new population\n",
    "    new_population = []\n",
    "    if include_clone_populationf3:\n",
    "        new_population = clone_populationf3(best_chromosome, population_size)\n",
    "    if include_mutate_allf3:\n",
    "        new_population, touched_numbers = mutate_allf3(new_population, mutation_rate, alphabet)\n",
    "    if include_crossover_allf3:\n",
    "        new_population = crossover_allf3(new_population, target_sequence, recombination_rate)\n",
    "    return best_fitness, best_chromosome, new_population, touched_numbers\n",
    "\n",
    "\n",
    "\n",
    "def plot_Best_Fitnessf3(best_fitness_history):\n",
    "    # Plot the fitness history\n",
    "    plt.plot(best_fitness_history, label='Best Fitness', color='blue')\n",
    "    plt.axhline(y=length_of_target_sequence, color='red', linestyle='--', linewidth=2)\n",
    "    plt.xlabel('Generation')\n",
    "    plt.ylabel('Best Fitness')\n",
    "    plt.title('Genetic Algorithm - Fitness over Generations')\n",
    "    plt.grid(True)\n",
    "    plt.legend()\n",
    "    plt.show()\n",
    "\n",
    "\n",
    "def mainf3( target_sequence, mutation_rate, recombination_rate, alphabet):\n",
    "    print_parametersf3()\n",
    "    all_touched_numbers = [] # List to store the arrays of number of touched sites for each generation\n",
    "    population = create_populationf3(population_size, target_sequence, alphabet)\n",
    "    # print(population)\n",
    "    best_fitness, best_chromosome = select_the_bestf3(population, target_sequence)\n",
    "    generation = 0\n",
    "    best_fitness_history = [] # List to store best fitness of each generation\n",
    "    best_fitness_history.append(best_fitness)\n",
    "    if print_best_fitness:\n",
    "        print(\"Generation, best_chromosome and best_fitness\")\n",
    "    while best_fitness < len(target_sequence):\n",
    "        generation += 1\n",
    "        best_fitness, best_chromosome, population, touched_numbers = run_one_generationf3(population, target_sequence, mutation_rate, recombination_rate, alphabet)\n",
    "        if print_best_fitness:\n",
    "            print(f\" {generation}  {best_chromosome} {best_fitness}\")\n",
    "        best_fitness_history.append(best_fitness)\n",
    "        all_touched_numbers.append(touched_numbers) # Append the array of touched numbers for this generation to the main list\n",
    "    print(f\"\\nTarget sequence matched in generation {generation}\")\n",
    "    print(f\"Final chromosome: {best_chromosome}\")\n",
    "    totalCost = population_size * generation\n",
    "    print(f\"Total cost = population size * number of generations: {totalCost}\")\n",
    "    if show_graph:\n",
    "        plot_Best_Fitnessf3(best_fitness_history) \n",
    "    print(\"All touched numbers for each generation:\")\n",
    "    for gen_index, touched_numbers in enumerate(all_touched_numbers):\n",
    "        mean, stddev, max_value  = mean_stddev_and_max(touched_numbers)\n",
    "        print(f\"Genrtn {gen_index + 1}: mean = {mean}  stddev = { stddev}  max = {max_value} {touched_numbers}\")\n",
    "    print(f\"Expected value = mutation_rate * length_of_target_sequence = {mutation_rate * length_of_target_sequence}\")\n",
    "    print(f\"Expected standard deviation = sqrt(mutation_rate * (1 - mutation_rate) * length_of_target_sequence) = { (mutation_rate * (1 - mutation_rate) * length_of_target_sequence) ** 0.5}\") \n",
    "\n",
    "if __name__ == \"__main__\":  mainf3( target_sequence, mutation_rate, recombination_rate, alphabet)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "463207fa",
   "metadata": {},
   "source": [
    "**Exercise.** Run the previous program and redact your observations. Give your advice: Must we take the variability in the number of touched sites as irrelevant?\n",
    ">\n",
    "> *Answer.* \n",
    "> \n",
    "> For the mutation rate $\\mu = 0.01$ and length of target string $H = 800$, the expected number of touched by mutation sites is $8$ and the expected standard deviation is 2.8, and the maximal value oscillates from 14 to 23.  Thus, give to the maximum the value of 16 or 17, the double of the expected value of the number of touched sites, is a very conservative assignation. Therefore, our advice is that we must take this variability into consideration. The mean of MAX is a correct indicator of that variability. Here it is around 17.\n",
    "\n",
    "**Challenge.** Add to the previous code the possibility to report an estimation of the mean of MAX.\n",
    "\n",
    "\n",
    "We need to take the variability of the number of touched sites into account and the appropriate solution is to use the mean of MAX. A problem arises: the probability of being touched is the mutation rate that is very different from $1/2$.  So, the corresponding binomials are not symmetric, and we do not have a theory of MAX for this case. Our only option is to force the theory that was developed for the standard distribution, apply it for asymmetric bells, use it in the math models, calculate predictions and compare with observed. We do not exclude that a good approximation could appear. \n",
    "\n",
    "\n",
    "**Our recipes.** Let us list in one place the two formulas for the mean of MAX that we must use.\n",
    "\n",
    "We must consider two types of bells. \n",
    "> \n",
    "> First, *the binomials are symmetric, $p = 1/2$*. For this case, we have the following theorem:\n",
    "> \n",
    ">>  The expected value of the MAX of $m$ binomial variables $Bi(n, 1/2)$ is, as a very good approximation,:\n",
    ">>>\n",
    ">>> Mean of MAX = $\\mathbb{E}(MAX) = \\frac{n}{2} +  \\sqrt{\\frac{n}{k}\\ln m  }  $\n",
    ">>>\n",
    ">> where\n",
    ">>>\n",
    ">>> $k = 24.9 n^{-1.18} + 2.53$\n",
    ">>>\n",
    "\n",
    "> Second, *the binomial are asymmetric, $p \\ne 1/2$*. For this case, we have the following theorem:\n",
    "\n",
    "\n",
    "> The expected value of MAX in z-units as a function of the number of monkeys, $m$, whose performance follows a standard normal distribution, is, as a very good approximation,: \n",
    ">> \n",
    ">> Mean of MAX = $\\mathbb{E}(MAX) =  \\sqrt{k \\ln (m)} $ \n",
    ">>\n",
    ">> $k = 1.29$. \n",
    "\n",
    "This mean comes in z-units. Thus, to apply it, at our own risk, into a binomial random distribution $Bi(n, p)$, we must use:\n",
    ">\n",
    "> Mean of MAX = $\\mathbb{E}(MAX) = $ mean + stdv $\\times \\sqrt{k \\ln (m)} $ \n",
    ">> \n",
    ">> Mean  $= \\mathbb{E}(MAX) =  np +  \\sqrt{np(1-p)} \\sqrt{k \\ln (m)} $ \n",
    ">>\n",
    ">> $k = 1.29$. \n",
    "\n",
    "Let us test the second formula.\n",
    "\n",
    "**Example.** Let us try to reproduce the 17 of a previous example, which is the found value of the mean of MAX of the touched sites. \n",
    ">\n",
    "> *Implementation.*\n",
    "\n",
    "The parameters for the simulation were:\n",
    ">\n",
    "> length_of_target_sequence = 800  \n",
    "> \n",
    "> target_sequence = '1'*length_of_target_sequence  #1111...1 (800 ones)  \n",
    "> \n",
    "> population_size = 200  \n",
    "> \n",
    "> include_clone_populationf3 = True  \n",
    ">\n",
    "> include_mutate_allf3 = True  \n",
    "> \n",
    "> include_crossover_allf3 = False  \n",
    "> \n",
    "> mutation_rate = 0.01  \n",
    ">\n",
    "We see that the number of monkeys is $m = 200$. The length of the target string is $n = 800$. The expected value of touched sites is equal to the length of the target string times the mutation rate $\\mu = 0.01$. So, we have\n",
    ">\n",
    "> Expected number of touched sites $n = 800*0.01 = 8$ \n",
    "> \n",
    "The selection of the fittest does not follow the expected value but the MAX. We are used to ignoring the variability of MAX and assume that it is constant and equal to its expected value.\n",
    ">\n",
    "> The expected value of MAX is for our example \n",
    ">\n",
    ">> $\\mathbb{E}(MAX) =  800 (0.01) + \\sqrt{800 (0.01) (0.99)} \\sqrt{1.29 \\ln 200} $\n",
    ">>\n",
    ">> $\\mathbb{E}(MAX) = 8 + 2.8  \\sqrt{1.29 \\ln 200}$\n",
    ">>\n",
    ">> $\\mathbb{E}(MAX) = 8 + 2.8  \\sqrt{1.29 \\times 5.3} = 8 + 2.8 \\times 2.6 = 15.32$\n",
    "\n",
    "This value is very close to our appreciation of 17 as the mean of MAX.\n",
    "\n",
    "**Practical directive.** We will use the formula of asymmetric bells for the expected value of MAX for a family of binomial random variables $Bi(n,p)$. When $p = 1/2$ we will use the formula for the symmetric case. \n",
    "\n",
    "We will use these formulas systematically to make predictions. "
   ]
  },
  {
   "cell_type": "markdown",
   "id": "01c9890f",
   "metadata": {},
   "source": [
    "\n",
    "# MATH MODEL\n",
    "\n",
    "Our purpose is to formulate a mathematical prediction for the number of matched sites across generations of a GA that battles with the Shakespeare Challenge. This consists in matching a binary string with a length of $H$ bits. In the GA we only include mutation, with mutation rate denoted $\\mu = 0.01$, selection of the fittest and its cloning. We ignore, as yet, recombination. The population size is $m$. \n",
    "\n",
    "**Example.** Let us calculate the initial condition for our GA.\n",
    ">\n",
    "> *Development.* The initial population of binary strings of length $H$ is created at random. The probability of one equals that of zero. Thus, the corresponding bell $Bi(H,1/2)$ is symmetric. On the other hand, the average value of the number of ones is close to the expected number $1/2 \\times H = H/2$, but the members of the population will have different values. This variability is profited by MAX, which is the mathematical formulation of the selection of the fittest. The expected value of MAX derived from the family of $m$ binomial variables $Bi(H, 1/2)$ is the initial number of matched sites $I$ :\n",
    ">\n",
    ">  \n",
    ">  $ I = \\mathbb{E}(MAX) = \\frac{n}{2} +  \\sqrt{\\frac{n}{k}\\ln m  }  $\n",
    ">\n",
    "> $n = H$\n",
    "> \n",
    ">  $ I =  \\frac{H}{2} +  \\sqrt{\\frac{H}{k}\\ln m  }  $\n",
    "> \n",
    ">  where\n",
    "> \n",
    ">  $k = 24.9 n^{-1.18} + 2.53$\n",
    "\n",
    "Once the population is created, the fittest is picked and cloned to form the next population. To understand the evolution of the number of matched sites, or of ones, we propose to divide the accounting process in two steps. First, determine the number of touched by mutation sites, and from this number, we must count the number of ones that mutation creates: when mutation touches a site, a one or a zero is posited with equal probability.\n",
    "\n",
    "\n",
    "**Exercise.** Calculate the number of touched by mutation sites that we must insert in our math model of the Mutation-MAX Duo.  \n",
    ">\n",
    "> *Answer.* We will assume that the number of touched sites has a variability that is harvested by the selection of the fittest. We model it by the mean of MAX, which we ascribe to the winning chromosome.  Thus, we have $m$ binomial variables $Bi(H, \\mu)$. These binomials are extremely asymmetric. Forcing the general theory, developed for the symmetric case, to produce a prediction, we expect a number of touched sites to be $T$: \n",
    ">>\n",
    ">> $T= $ number of touched sites $ = \\mu H +  \\sqrt{H \\mu (1 - \\mu) } \\sqrt{c \\ln (m)} $ \n",
    ">>\n",
    ">> $c = 1.29$. \n",
    "\n",
    "Since the mutation rate depends on biophysical conditions, we will assume that it is independent of everything that we consider in our model. So, it is constant, and so will be $T$. For instance, if $H= 800$, $\\mu = 0.01$, $m = 200$, $T$, the number $T$ of touched sites is \n",
    "\n",
    ">>\n",
    ">> $T= $ number of touched sites $ = 0.01(800)+  \\sqrt{0.01(800)(1 - 0.01) } \\sqrt{1.29 \\ln (200)} $ \n",
    ">>\n",
    ">> $T= 8 +  \\sqrt{8 \\times 0.99 } \\sqrt{1.29 \\times 5.298} $ \n",
    ">>\n",
    ">> $T= 8 +  \\sqrt{8 \\times 0.99 } \\sqrt{6.834} $ \n",
    ">>\n",
    ">> $T= 8 +  (2.81)(2.6) = 15.3 = constant$ \n",
    "\n",
    "**Exercise.** Let the number of touched by mutation sites be $T$, and $s$ the number of sites from these that get solved. Find an expression for $s$ assuming that mutation is random. \n",
    ">\n",
    "> *Answer.* A char matches the target when it is 1, whose probability is $p = 1/2$. Hence, approximately the half of the touched sites are solved because each touched site is replaced by a random bit, 0 or 1. But there are fluctuations that are captured by MAX that comes from a family of binomial variables.  Thus, we take the MAX of $m$ binomial variables of the form $Bi(n, 1/2)$, where $n = T$, the number of touched sites. \n",
    "\n",
    "Henceforth\n",
    ">\n",
    "> $s = $ the number of solved sites among those that were touched\n",
    "> \n",
    ">  $ s = \\mathbb{E}(MAX) = \\frac{n}{2} +  \\sqrt{\\frac{n}{k}\\ln m  }  $\n",
    ">\n",
    "> $n = T$\n",
    "> \n",
    ">  $ s =  \\frac{T}{2} +  \\sqrt{\\frac{T}{k}\\ln m  }  $\n",
    "> \n",
    ">  where\n",
    "> \n",
    ">  $k = 24.9 T^{-1.18} + 2.53$\n",
    ">\n",
    "> If $T = 15.3$, \n",
    "> \n",
    "> $k = 24.9 (15.3)^{-1.18} + 2.53 = 24.9 (0.04) + 2.53$\n",
    ">\n",
    "> $k = 3.52\n",
    ">\n",
    "> For our working example,\n",
    "> \n",
    "> $ s = \\frac{15.3}{2} + \\sqrt{\\frac{15.3}{3.52}\\ln 200 } $\n",
    ">\n",
    "> $ s = 7.65 + \\sqrt{(4.3466) (5.3) } $\n",
    ">\n",
    "> $ s = 7.65 + 4.8 = 12.45 $ from a total of 15.\n",
    ">\n",
    "\n",
    "**Example.** Let us calculate now the change of the number of matched sites $M$ over generations. \n",
    "\n",
    "The population of the present generation consists of cloned chromosomes of the champion of the last generation. Let us consider the winning chromosome at generation $t$.\n",
    "\n",
    "The target string, the original one that serves as pattern, has length $H$. The winning chromosome has a fitness $M_t$ that is the number of sites that match the corresponding sites in the target string.  Let us turn mutation on. Each site can be or not touched by mutation, whose rate is $\\mu$. So, the expected number of touched sites in the winner chromosome is $\\mu H$. But, the actual number is different because the winner makes profit of fluctuations among the population. Thus, the number of touched sites is $T$. \n",
    "\n",
    "If a site is touched, mutation posits in there a random char than can be 1 or 0.  And each site matches or not the corresponding site of the target string. Since the char is chosen at random, the expected proportion of those sites that match is the half of touched ones, $\\frac{1}{2} \\mu H$. But the winner is different: the number of solved sites is $s$.\n",
    "\n",
    "If a site in the winning chromosome is not touched, we have two options, two branches: the site is already correct and matches the target string, else not. The proportion of untouched sites is $H - T$ and the global proportion of correct sites is $\\frac{M_t}{H}$.  Therefore, the expected number of right or matched sites among the untouched ones is \n",
    "\n",
    "$ (H-T)(\\frac{M_t}{H}) $.\n",
    "\n",
    "But we also have fluctuations among chromosomes that are included by MAX. To be right or not is modeled by a binomial distribution $Bi(n,p)$. In this case, $n= H-T$ and $p = \\frac{M_t}{H}$. We are in the asymmetric case. Hence, the number of right sites $r$ among those that were not touched by mutation is given by the corresponding expected value of MAX\n",
    "\n",
    ">> $r $ = number of untouched by mutation sites that were right in the winning chromosome of the past generation\n",
    ">>\n",
    ">> $ r = \\mathbb{E}(MAX) =  np +  \\sqrt{np(1-p)} \\sqrt{k \\ln (m)} $ \n",
    ">>\n",
    ">> $k = 1.29$. \n",
    ">> \n",
    ">>  $r =  (H-T)(\\frac{M_t}{H}) +  \\sqrt{(H-T)(\\frac{M_t}{H})(1-\\frac{M_t}{H})} \\sqrt{1.29 \\ln (m)} $ \n",
    ">>\n",
    "\n",
    "**Exercise.** Answer to the following \n",
    ">\n",
    "> *Objection.* The branch of touched sites, whose number is $T$, is dependent from the branch of untouched sites, whose number is $H-T$. Hence, the independence hypothesis is violated, and nothing good can be expected from the application of the cited theorems.\n",
    ">\n",
    "> *Answer.* The aforementioned theorems need the independence of the $m$ binomials, which model the behavior of $m$ monkeys, each one presenting one plausible solution to the Shakespeare challenge. Thus, no violation of this requirement is observed. Additionally, the sites inside a chromosome are also independent one from another, and what happens to one site is not exprofeso correlated to what happens to another one.\n",
    ">\n",
    "\n",
    "**Example.** Let us end the formulation of our model.\n",
    ">\n",
    "> *Realization.* The total number of correct sites of the next generation has two sources, those touched by mutation and those untouched, hence, we add the corresponding terms:\n",
    "\n",
    "$M_{t+1} =  s_t + r_t $\n",
    "\n",
    "And this is all to it.\n",
    "\n",
    "**Exercise.** Design a table of formulas with the complete model.\n",
    ">\n",
    "> *Answer.* Our table is the following:\n",
    "> \n",
    ">**************\n",
    "> *Complete Math Model* of the change in the number of matched sites $M$ in the winner chromosome of each generation:\n",
    ">*************\n",
    "\n",
    "> $c = 1.29$. \n",
    ">\n",
    "> $n = $ length of a subsequence to be matched, depends on context. \n",
    "> \n",
    "> $k = 24.9 n^{-1.18} + 2.53$\n",
    ">\n",
    "> $\\mu = $ mutation rate, constant\n",
    ">\n",
    "> $H = $ length of the target string, total number of sites\n",
    ">\n",
    "> $m = $ number of monkeys or of binomial distributions.\n",
    "> \n",
    "> $M_t = $ number of solved sites at generation $t$\n",
    ">\n",
    "> $I = M_o = $ initial number of matched sites\n",
    "> $ = \\frac{H}{2} +  \\sqrt{\\frac{H}{k}\\ln m  }  $\n",
    ">\n",
    "> $T= $ number of touched sites $ =  \\mu H +  \\sqrt{H \\mu (1 - \\mu) } \\sqrt{c \\ln (m)} $ \n",
    ">\n",
    ">  $ s = $ number of solved sites among touched $ =  \\frac{T}{2} +  \\sqrt{\\frac{T}{k}\\ln m  }  $\n",
    "> \n",
    "> $H-T = $  number of untouched sites \n",
    ">\n",
    ">\n",
    "> $p_t = \\frac{M_t}{H}$ proportion of matched sites in the winner chromosome of present generation.\n",
    ">\n",
    "> $\\kappa = 1.29$\n",
    "> \n",
    ">  $ r = $ number of untouched sites that were right in the winning chromosome of generation $t$.\n",
    ">\n",
    "> $ r =  (H-T)p_t +  \\sqrt{(H-T)p_t(1-p_t)} \\sqrt{\\kappa \\times \\ln (m)} $.\n",
    ">\n",
    "> $M_{t+1} =  s + r = $ prediction for the winner of the next generation\n",
    "\n",
    "********\n",
    "\n",
    "**Exercise.** Draw the graph for the evolution of $M_t$ according to the previous model. Redact your observations, diagnostics and conclusions.\n",
    ">\n",
    "> *Answer.* The following code draws the graphic of $M_t$ as a function of generation number $t$ according to the previous model. We use the usual parameters.\n",
    "\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "id": "4bde40c5",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "30\n",
      "Generation 0: T = 2.053047124330767\n",
      "Generation 0: s = 1.9348087813276753\n",
      "Generation 0: u = 797.9469528756692\n",
      "Generation 0: p = 0.5510696856365925\n",
      "Generation 0: M(n) = 478.3911007625884\n",
      "Generation 1: p = 0.5979888759532355\n",
      "Generation 1: M(n) = 515.3072024340853\n",
      "Generation 2: p = 0.6441340030426066\n",
      "Generation 2: M(n) = 551.2771274173801\n",
      "Generation 3: p = 0.6890964092717252\n",
      "Generation 3: M(n) = 585.9796801210024\n",
      "Generation 4: p = 0.732474600151253\n",
      "Generation 4: M(n) = 619.1017924120628\n",
      "Generation 5: p = 0.7738772405150784\n",
      "Generation 5: M(n) = 650.3407194182824\n",
      "Generation 6: p = 0.8129258992728531\n",
      "Generation 6: M(n) = 679.4059346607764\n",
      "Generation 7: p = 0.8492574183259706\n",
      "Generation 7: M(n) = 706.0205657523073\n",
      "Generation 8: p = 0.8825257071903841\n",
      "Generation 8: M(n) = 729.922089632708\n",
      "Generation 9: p = 0.912402612040885\n",
      "Generation 9: M(n) = 750.8617310581236\n",
      "Generation 10: p = 0.9385771638226545\n",
      "Generation 10: M(n) = 768.6013130062742\n",
      "Generation 11: p = 0.9607516412578427\n",
      "Generation 11: M(n) = 782.9042482860417\n",
      "Generation 12: p = 0.9786303103575521\n",
      "Generation 12: M(n) = 793.5095887109534\n",
      "Generation 13: p = 0.9918869858886917\n",
      "Generation 13: M(n) = 800.0328111911556\n",
      "Generation 14: p = 1.0000410139889444\n",
      "Generation 14: M(n) = nan\n",
      "Generation 15: p = nan\n",
      "Generation 15: M(n) = nan\n",
      "Generation 16: p = nan\n",
      "Generation 16: M(n) = nan\n",
      "Generation 17: p = nan\n",
      "Generation 17: M(n) = nan\n",
      "Generation 18: p = nan\n",
      "Generation 18: M(n) = nan\n",
      "Generation 19: p = nan\n",
      "Generation 19: M(n) = nan\n",
      "Generation 20: p = nan\n",
      "Generation 20: M(n) = nan\n",
      "Generation 21: p = nan\n",
      "Generation 21: M(n) = nan\n",
      "Generation 22: p = nan\n",
      "Generation 22: M(n) = nan\n",
      "Generation 23: p = nan\n",
      "Generation 23: M(n) = nan\n",
      "Generation 24: p = nan\n",
      "Generation 24: M(n) = nan\n",
      "Generation 25: p = nan\n",
      "Generation 25: M(n) = nan\n",
      "Generation 26: p = nan\n",
      "Generation 26: M(n) = nan\n",
      "Generation 27: p = nan\n",
      "Generation 27: M(n) = nan\n",
      "Generation 28: p = nan\n",
      "Generation 28: M(n) = nan\n",
      "Generation 29: p = nan\n",
      "Generation 29: M(n) = nan\n",
      "Generation 30: p = nan\n",
      "Generation 30: M(n) = nan\n",
      "Generation 31: p = nan\n",
      "Generation 31: M(n) = nan\n",
      "Generation 32: p = nan\n",
      "Generation 32: M(n) = nan\n",
      "Generation 33: p = nan\n",
      "Generation 33: M(n) = nan\n",
      "Generation 34: p = nan\n",
      "Generation 34: M(n) = nan\n",
      "Generation 35: p = nan\n",
      "Generation 35: M(n) = nan\n",
      "Generation 36: p = nan\n",
      "Generation 36: M(n) = nan\n",
      "Generation 37: p = nan\n",
      "Generation 37: M(n) = nan\n",
      "Generation 38: p = nan\n",
      "Generation 38: M(n) = nan\n",
      "Generation 39: p = nan\n",
      "Generation 39: M(n) = nan\n",
      "Generation 40: p = nan\n",
      "Generation 40: M(n) = nan\n",
      "Generation 41: p = nan\n",
      "Generation 41: M(n) = nan\n",
      "Generation 42: p = nan\n",
      "Generation 42: M(n) = nan\n",
      "Generation 43: p = nan\n",
      "Generation 43: M(n) = nan\n",
      "Generation 44: p = nan\n",
      "Generation 44: M(n) = nan\n",
      "Generation 45: p = nan\n",
      "Generation 45: M(n) = nan\n",
      "Generation 46: p = nan\n",
      "Generation 46: M(n) = nan\n",
      "Generation 47: p = nan\n",
      "Generation 47: M(n) = nan\n",
      "Generation 48: p = nan\n",
      "Generation 48: M(n) = nan\n",
      "Generation 49: p = nan\n",
      "Generation 49: M(n) = nan\n",
      "Generation 50: p = nan\n",
      "Generation 50: M(n) = nan\n",
      "Generation 51: p = nan\n",
      "Generation 51: M(n) = nan\n",
      "Generation 52: p = nan\n",
      "Generation 52: M(n) = nan\n",
      "Generation 53: p = nan\n",
      "Generation 53: M(n) = nan\n",
      "Generation 54: p = nan\n",
      "Generation 54: M(n) = nan\n",
      "Generation 55: p = nan\n",
      "Generation 55: M(n) = nan\n",
      "Generation 56: p = nan\n",
      "Generation 56: M(n) = nan\n",
      "Generation 57: p = nan\n",
      "Generation 57: M(n) = nan\n",
      "Generation 58: p = nan\n",
      "Generation 58: M(n) = nan\n",
      "Generation 59: p = nan\n",
      "Generation 59: M(n) = nan\n",
      "Generation 60: p = nan\n",
      "Generation 60: M(n) = nan\n",
      "Generation 61: p = nan\n",
      "Generation 61: M(n) = nan\n",
      "Generation 62: p = nan\n",
      "Generation 62: M(n) = nan\n",
      "Generation 63: p = nan\n",
      "Generation 63: M(n) = nan\n",
      "Generation 64: p = nan\n",
      "Generation 64: M(n) = nan\n",
      "Generation 65: p = nan\n",
      "Generation 65: M(n) = nan\n",
      "Generation 66: p = nan\n",
      "Generation 66: M(n) = nan\n",
      "Generation 67: p = nan\n",
      "Generation 67: M(n) = nan\n",
      "Generation 68: p = nan\n",
      "Generation 68: M(n) = nan\n",
      "Generation 69: p = nan\n",
      "Generation 69: M(n) = nan\n",
      "Generation 70: p = nan\n",
      "Generation 70: M(n) = nan\n",
      "Generation 71: p = nan\n",
      "Generation 71: M(n) = nan\n",
      "Generation 72: p = nan\n",
      "Generation 72: M(n) = nan\n",
      "Generation 73: p = nan\n",
      "Generation 73: M(n) = nan\n",
      "Generation 74: p = nan\n",
      "Generation 74: M(n) = nan\n",
      "Generation 75: p = nan\n",
      "Generation 75: M(n) = nan\n",
      "Generation 76: p = nan\n",
      "Generation 76: M(n) = nan\n",
      "Generation 77: p = nan\n",
      "Generation 77: M(n) = nan\n",
      "Generation 78: p = nan\n",
      "Generation 78: M(n) = nan\n",
      "Generation 79: p = nan\n",
      "Generation 79: M(n) = nan\n",
      "Generation 80: p = nan\n",
      "Generation 80: M(n) = nan\n",
      "Generation 81: p = nan\n",
      "Generation 81: M(n) = nan\n",
      "Generation 82: p = nan\n",
      "Generation 82: M(n) = nan\n",
      "Generation 83: p = nan\n",
      "Generation 83: M(n) = nan\n",
      "Generation 84: p = nan\n",
      "Generation 84: M(n) = nan\n",
      "Generation 85: p = nan\n",
      "Generation 85: M(n) = nan\n",
      "Generation 86: p = nan\n",
      "Generation 86: M(n) = nan\n",
      "Generation 87: p = nan\n",
      "Generation 87: M(n) = nan\n",
      "Generation 88: p = nan\n",
      "Generation 88: M(n) = nan\n",
      "Generation 89: p = nan\n",
      "Generation 89: M(n) = nan\n",
      "Generation 90: p = nan\n",
      "Generation 90: M(n) = nan\n",
      "Generation 91: p = nan\n",
      "Generation 91: M(n) = nan\n",
      "Generation 92: p = nan\n",
      "Generation 92: M(n) = nan\n",
      "Generation 93: p = nan\n",
      "Generation 93: M(n) = nan\n",
      "Generation 94: p = nan\n",
      "Generation 94: M(n) = nan\n",
      "Generation 95: p = nan\n",
      "Generation 95: M(n) = nan\n",
      "Generation 96: p = nan\n",
      "Generation 96: M(n) = nan\n",
      "Generation 97: p = nan\n",
      "Generation 97: M(n) = nan\n",
      "Generation 98: p = nan\n",
      "Generation 98: M(n) = nan\n",
      "Generation 99: p = nan\n",
      "Generation 99: M(n) = nan\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/tmp/ipykernel_10538/2268358999.py:50: RuntimeWarning: invalid value encountered in scalar power\n",
      "  return u_value * p_value  + ((u_value * p_value  * (1 - p_value )) ** 0.5) * (1.29 * np.log(m)) ** 0.5\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1000x600 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Program Theoretical_model.py\n",
    "# This program implements the theoretical model of the truncated evolution\n",
    "import numpy as np\n",
    "import matplotlib.pyplot as plt\n",
    "\n",
    "# Definition of parameters for the theoretical model\n",
    "\n",
    "n_generations = 100 # number of generations to make predictions by the model\n",
    "\n",
    "#$c = 1.29$. \n",
    "c = 1.29\n",
    "#$k = 24.9 n^{-1.18} + 2.53$\n",
    "def k(length_of_target_sequence):\n",
    "    return 24.9 * (length_of_target_sequence ** -1.18) + 2.53 #original definition of k\n",
    "    #return 2.53 # Simplified definition of k for large target sequence lengths\n",
    "    #return 10.3229 # Adjusted value of k for better fit with empirical data\n",
    "    #return 35\n",
    "\n",
    "kappa = 1.29 # Original value\n",
    "\n",
    "# $\\mu = $ mutation rate, constant\n",
    "mu = 0.0005  # Example mutation rate\n",
    "#$H = $ length of the target string, total number of sites\n",
    "H = 800\n",
    "#$m = $ number of monkeys or of binomial distributions.\n",
    "m = 200\n",
    "#$M_t = $ number of solved sites at generation $t$\n",
    "#$M_o = I = $ initial number of matched sites\n",
    "#$ = \\frac{H}{2} +  \\sqrt{\\frac{H}{k}\\ln m  }  $\n",
    "I = H / 2 + ((H / k(H)) * np.log(m)) ** 0.5\n",
    "\n",
    "#$T= $ number of touched sites $ =  \\mu H +  \\sqrt{H \\mu (1 - \\mu) } \\sqrt{c \\ln (m)} $ \n",
    "def T(mu, H, c, m):\n",
    "    return mu * H + (H * mu * (1 - mu)) ** 0.5 * (c * np.log(m)) ** 0.5\n",
    "\n",
    "#  $ s = $ number of solved sites among touched $ =  \\frac{T}{2} +  \\sqrt{\\frac{T}{k}\\ln m  }  $\n",
    "def s(T, m):\n",
    "    return T / 2 + ((T / k(T)) * np.log(m)) ** 0.5\n",
    "\n",
    "# $ u = $ number of untouched sites $ = H-T$\n",
    "def u(H, T):\n",
    "    return H - T\n",
    "\n",
    "# $ r =  (H-T)p +  \\sqrt{(H-T)p(1-p)} \\sqrt{1.29 \\ln (m)} $.\n",
    "\n",
    "# $p = \\frac{M_t}{H}$\n",
    "\n",
    "def p(M_t, H):\n",
    "    return M_t / H\n",
    "\n",
    "#$ r = $ number of untouched sites that were right from start \n",
    "#$ = u p + \\sqrt{u p (1-p)} \\sqrt{c \\ln m} $\n",
    "def r(u_value, H, p_value, M_t):\n",
    "    return u_value * p_value  + ((u_value * p_value  * (1 - p_value )) ** 0.5) * (kappa * np.log(m)) ** 0.5\n",
    "    #return u_value * p_value  + ((u_value * p_value  * (1 - p_value )) ** 0.5) * (0.01 * np.log(m)) ** 0.5\n",
    "\n",
    "\n",
    "\n",
    "#$M_{t+1} =  s + r $, number of matched sites at generation $t+1$.\n",
    "def M(s, r):\n",
    "    return s + r\n",
    "\n",
    "print(M(10,20) )\n",
    "M_values = []\n",
    "m_value  = I\n",
    "n = 0\n",
    "T_value = T(mu, H, c, m)\n",
    "print(f\"Generation {n}: T = {T_value}\")\n",
    "s_value = s(T_value,  m)\n",
    "print(f\"Generation {n}: s = {s_value}\")\n",
    "u_value = u(H, T_value)\n",
    "print(f\"Generation {n}: u = {u_value}\")\n",
    "# Generate a range of generations\n",
    "for n in range(n_generations):\n",
    "    p_value = p(m_value, H)\n",
    "    print(f\"Generation {n}: p = {p_value}\")\n",
    "    r_value = r(u_value, H, p_value, m_value)\n",
    "    # print(f\"Generation {n}: r = {r_value}\")\n",
    "    m_value = M(s_value, r_value)\n",
    "    M_values.append(m_value)\n",
    "    print(f\"Generation {n}: M(n) = {m_value}\")\n",
    "\n",
    "\n",
    "# Plot the function\n",
    "plt.figure(figsize=(10, 6))\n",
    "plt.axhline(y=H, color='red', linestyle='--', linewidth=2, label='Total number of sites (H)')\n",
    "plt.plot(M_values)\n",
    "plt.xlabel('Generation (n)')\n",
    "plt.ylabel('Number of Matched Sites (M)')\n",
    "plt.title('Theoretical Model: M(n)')\n",
    "plt.grid(True)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "b61a519b",
   "metadata": {},
   "source": [
    "*Our observations.* \n",
    "\n",
    "- The graph grows and tends to the correct limit, which is $H$. So, the graph is concave, as it should be. \n",
    "- The number of matched sites $M_t$ grows extremely fast and surpasses $H$, which cannot be. This causes $p$ to be greater than 1 and that $(1-p)< 0$. When this happens, the model begins to output nan (not a number) because the square root of a negative number $\\sqrt{p(1-p)}$ is demanded.\n",
    "- Why is the model too accelerated?  Our model assumes that MAX is used at every step. This seems to be false. The fuel of everything is randomness and that is why the final winner is not necessarily the same that was winner in all partial treks. \n",
    "\n",
    "**Control parameters.** Our math model is semiempirical. This means that we combined math reasoning with observations from our simulation to adjust the values of some constants that function as control parameters, i.e., constants that cause a trend in the form as the graph changes. Our model has three control parameters: $c$, $k$, and $\\kappa$. \n",
    "\n",
    "**Example.** Let us move the control parameters to fit the results of our simulations. The task is to decelerate the process. So, we choose kappa. This acts multiplicatively, so we must diminish it. The following code allows the comparison of observed with predicted to find the correct adjustment, if any. Or at least, upper and lower bounds. The code follows. It has an amendment: if the number of matched sites surpasses the length of the target string, it is given this value."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "31cd5928",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Lab: Simple Genetic Algorithm\n",
      "Purpose: solve an instance of the Shakespeare challenge\n",
      "Date of Experiment  = 2026-02-26 07:52:49.926365\n",
      "alphabet =  01\n",
      "target_sequence = 11111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111\n",
      "length_of_target_sequence = 800\n",
      "population_size = 200\n",
      "include_clone_populationf4 = True\n",
      "include_mutate_allf4 = True\n",
      "include_crossover_allf4 = False\n",
      "mutation_rate = 0.01\n",
      "print_best_fitness = False\n",
      "\n",
      "Target sequence matched in generation 339\n",
      "Final chromosome: 11111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111\n",
      "Total cost = population size * number of generations: 67800\n",
      "Parameters of the theoretical model:\n",
      "c = 1.29\n",
      "k(H) = 1.5\n",
      "I = 453.1579651807606\n",
      "mu = 0.01\n",
      "H = 800\n",
      "m = 200\n",
      "Generation 0: T = 15.357434938247703\n",
      "Generation 0: s = 15.04388613607459\n",
      "Generation 0: u = 784.6425650617523\n",
      "Generation 0: p = 0.5664474564759507\n",
      "Generation 0: M(n) = 459.5026713580699\n",
      "Generation 1: p = 0.5743783391975874\n",
      "Generation 1: M(n) = 465.7255795199788\n",
      "Generation 2: p = 0.5821569743999735\n",
      "Generation 2: M(n) = 471.82902779785866\n",
      "Generation 3: p = 0.5897862847473233\n",
      "Generation 3: M(n) = 477.8153094384554\n",
      "Generation 4: p = 0.5972691367980693\n",
      "Generation 4: M(n) = 483.6866736655303\n",
      "Generation 5: p = 0.6046083420819128\n",
      "Generation 5: M(n) = 489.4453265249601\n",
      "Generation 6: p = 0.6118066581562001\n",
      "Generation 6: M(n) = 495.09343171361405\n",
      "Generation 7: p = 0.6188667896420176\n",
      "Generation 7: M(n) = 500.63311139231917\n",
      "Generation 8: p = 0.625791389240399\n",
      "Generation 8: M(n) = 506.0664469832187\n",
      "Generation 9: p = 0.6325830587290234\n",
      "Generation 9: M(n) = 511.39547995182465\n",
      "Generation 10: p = 0.6392443499397809\n",
      "Generation 10: M(n) = 516.6222125740567\n",
      "Generation 11: p = 0.6457777657175708\n",
      "Generation 11: M(n) = 521.7486086885567\n",
      "Generation 12: p = 0.6521857608606959\n",
      "Generation 12: M(n) = 526.7765944345616\n",
      "Generation 13: p = 0.658470743043202\n",
      "Generation 13: M(n) = 531.7080589756105\n",
      "Generation 14: p = 0.6646350737195131\n",
      "Generation 14: M(n) = 536.5448552093602\n",
      "Generation 15: p = 0.6706810690117002\n",
      "Generation 15: M(n) = 541.2888004637731\n",
      "Generation 16: p = 0.6766110005797163\n",
      "Generation 16: M(n) = 545.941677179942\n",
      "Generation 17: p = 0.6824270964749275\n",
      "Generation 17: M(n) = 550.5052335818056\n",
      "Generation 18: p = 0.6881315419772569\n",
      "Generation 18: M(n) = 554.9811843330083\n",
      "Generation 19: p = 0.6937264804162604\n",
      "Generation 19: M(n) = 559.3712111811506\n",
      "Generation 20: p = 0.6992140139764382\n",
      "Generation 20: M(n) = 563.676963589671\n",
      "Generation 21: p = 0.7045962044870887\n",
      "Generation 21: M(n) = 567.9000593575988\n",
      "Generation 22: p = 0.7098750741969986\n",
      "Generation 22: M(n) = 572.0420852274092\n",
      "Generation 23: p = 0.7150526065342615\n",
      "Generation 23: M(n) = 576.1045974812093\n",
      "Generation 24: p = 0.7201307468515117\n",
      "Generation 24: M(n) = 580.0891225254801\n",
      "Generation 25: p = 0.7251114031568501\n",
      "Generation 25: M(n) = 583.9971574645917\n",
      "Generation 26: p = 0.7299964468307397\n",
      "Generation 26: M(n) = 587.8301706633113\n",
      "Generation 27: p = 0.7347877133291391\n",
      "Generation 27: M(n) = 591.5896022985097\n",
      "Generation 28: p = 0.7394870028731372\n",
      "Generation 28: M(n) = 595.2768649002803\n",
      "Generation 29: p = 0.7440960811253504\n",
      "Generation 29: M(n) = 598.8933438826672\n",
      "Generation 30: p = 0.748616679853334\n",
      "Generation 30: M(n) = 602.4403980642072\n",
      "Generation 31: p = 0.753050497580259\n",
      "Generation 31: M(n) = 605.9193601784779\n",
      "Generation 32: p = 0.7573992002230974\n",
      "Generation 32: M(n) = 609.3315373748454\n",
      "Generation 33: p = 0.7616644217185568\n",
      "Generation 33: M(n) = 612.6782117095992\n",
      "Generation 34: p = 0.765847764636999\n",
      "Generation 34: M(n) = 615.9606406276586\n",
      "Generation 35: p = 0.7699508007845732\n",
      "Generation 35: M(n) = 619.1800574350324\n",
      "Generation 36: p = 0.7739750717937904\n",
      "Generation 36: M(n) = 622.3376717622082\n",
      "Generation 37: p = 0.7779220897027602\n",
      "Generation 37: M(n) = 625.4346700186469\n",
      "Generation 38: p = 0.7817933375233086\n",
      "Generation 38: M(n) = 628.4722158385517\n",
      "Generation 39: p = 0.7855902697981897\n",
      "Generation 39: M(n) = 631.4514505180802\n",
      "Generation 40: p = 0.7893143131476001\n",
      "Generation 40: M(n) = 634.3734934441627\n",
      "Generation 41: p = 0.7929668668052033\n",
      "Generation 41: M(n) = 637.2394425150902\n",
      "Generation 42: p = 0.7965493031438627\n",
      "Generation 42: M(n) = 640.0503745530264\n",
      "Generation 43: p = 0.800062968191283\n",
      "Generation 43: M(n) = 642.8073457086019\n",
      "Generation 44: p = 0.8035091821357524\n",
      "Generation 44: M(n) = 645.5113918577421\n",
      "Generation 45: p = 0.8068892398221776\n",
      "Generation 45: M(n) = 648.1635289908754\n",
      "Generation 46: p = 0.8102044112385943\n",
      "Generation 46: M(n) = 650.764753594672\n",
      "Generation 47: p = 0.81345594199334\n",
      "Generation 47: M(n) = 653.3160430264528\n",
      "Generation 48: p = 0.816645053783066\n",
      "Generation 48: M(n) = 655.8183558814121\n",
      "Generation 49: p = 0.8197729448517651\n",
      "Generation 49: M(n) = 658.27263235279\n",
      "Generation 50: p = 0.8228407904409875\n",
      "Generation 50: M(n) = 660.6797945851307\n",
      "Generation 51: p = 0.8258497432314134\n",
      "Generation 51: M(n) = 663.0407470207603\n",
      "Generation 52: p = 0.8288009337759503\n",
      "Generation 52: M(n) = 665.3563767396117\n",
      "Generation 53: p = 0.8316954709245147\n",
      "Generation 53: M(n) = 667.6275537925278\n",
      "Generation 54: p = 0.8345344422406598\n",
      "Generation 54: M(n) = 669.8551315281646\n",
      "Generation 55: p = 0.8373189144102058\n",
      "Generation 55: M(n) = 672.0399469136203\n",
      "Generation 56: p = 0.8400499336420253\n",
      "Generation 56: M(n) = 674.182820848908\n",
      "Generation 57: p = 0.842728526061135\n",
      "Generation 57: M(n) = 676.2845584753933\n",
      "Generation 58: p = 0.8453556980942416\n",
      "Generation 58: M(n) = 678.3459494783085\n",
      "Generation 59: p = 0.8479324368478857\n",
      "Generation 59: M(n) = 680.3677683834618\n",
      "Generation 60: p = 0.8504597104793272\n",
      "Generation 60: M(n) = 682.3507748482491\n",
      "Generation 61: p = 0.8529384685603114\n",
      "Generation 61: M(n) = 684.29571394708\n",
      "Generation 62: p = 0.85536964243385\n",
      "Generation 62: M(n) = 686.2033164513246\n",
      "Generation 63: p = 0.8577541455641557\n",
      "Generation 63: M(n) = 688.0742991038853\n",
      "Generation 64: p = 0.8600928738798567\n",
      "Generation 64: M(n) = 689.9093648884995\n",
      "Generation 65: p = 0.8623867061106243\n",
      "Generation 65: M(n) = 691.7092032938704\n",
      "Generation 66: p = 0.864636504117338\n",
      "Generation 66: M(n) = 693.474490572729\n",
      "Generation 67: p = 0.8668431132159112\n",
      "Generation 67: M(n) = 695.2058899959221\n",
      "Generation 68: p = 0.8690073624949026\n",
      "Generation 68: M(n) = 696.9040521016229\n",
      "Generation 69: p = 0.8711300651270286\n",
      "Generation 69: M(n) = 698.5696149397576\n",
      "Generation 70: p = 0.873212018674697\n",
      "Generation 70: M(n) = 700.2032043117396\n",
      "Generation 71: p = 0.8752540053896745\n",
      "Generation 71: M(n) = 701.8054340056015\n",
      "Generation 72: p = 0.8772567925070018\n",
      "Generation 72: M(n) = 703.3769060266138\n",
      "Generation 73: p = 0.8792211325332673\n",
      "Generation 73: M(n) = 704.9182108234762\n",
      "Generation 74: p = 0.8811477635293453\n",
      "Generation 74: M(n) = 706.4299275101664\n",
      "Generation 75: p = 0.883037409387708\n",
      "Generation 75: M(n) = 707.9126240835304\n",
      "Generation 76: p = 0.884890780104413\n",
      "Generation 76: M(n) = 709.3668576366962\n",
      "Generation 77: p = 0.8867085720458703\n",
      "Generation 77: M(n) = 710.7931745683898\n",
      "Generation 78: p = 0.8884914682104872\n",
      "Generation 78: M(n) = 712.1921107882335\n",
      "Generation 79: p = 0.8902401384852919\n",
      "Generation 79: M(n) = 713.5641919181036\n",
      "Generation 80: p = 0.8919552398976295\n",
      "Generation 80: M(n) = 714.9099334896212\n",
      "Generation 81: p = 0.8936374168620265\n",
      "Generation 81: M(n) = 716.2298411378534\n",
      "Generation 82: p = 0.8952873014223168\n",
      "Generation 82: M(n) = 717.5244107912954\n",
      "Generation 83: p = 0.8969055134891193\n",
      "Generation 83: M(n) = 718.7941288582052\n",
      "Generation 84: p = 0.8984926610727565\n",
      "Generation 84: M(n) = 720.0394724093618\n",
      "Generation 85: p = 0.9000493405117023\n",
      "Generation 85: M(n) = 721.2609093573151\n",
      "Generation 86: p = 0.9015761366966438\n",
      "Generation 86: M(n) = 722.4588986321942\n",
      "Generation 87: p = 0.9030736232902428\n",
      "Generation 87: M(n) = 723.6338903541413\n",
      "Generation 88: p = 0.9045423629426765\n",
      "Generation 88: M(n) = 724.7863260024347\n",
      "Generation 89: p = 0.9059829075030434\n",
      "Generation 89: M(n) = 725.9166385813668\n",
      "Generation 90: p = 0.9073957982267085\n",
      "Generation 90: M(n) = 727.0252527829354\n",
      "Generation 91: p = 0.9087815659786692\n",
      "Generation 91: M(n) = 728.1125851464136\n",
      "Generation 92: p = 0.910140731433017\n",
      "Generation 92: M(n) = 729.1790442148564\n",
      "Generation 93: p = 0.9114738052685705\n",
      "Generation 93: M(n) = 730.2250306886018\n",
      "Generation 94: p = 0.9127812883607522\n",
      "Generation 94: M(n) = 731.2509375758261\n",
      "Generation 95: p = 0.9140636719697827\n",
      "Generation 95: M(n) = 732.2571503402089\n",
      "Generation 96: p = 0.9153214379252611\n",
      "Generation 96: M(n) = 733.244047045763\n",
      "Generation 97: p = 0.9165550588072037\n",
      "Generation 97: M(n) = 734.2119984988841\n",
      "Generation 98: p = 0.9177649981236051\n",
      "Generation 98: M(n) = 735.1613683876743\n",
      "Generation 99: p = 0.9189517104845929\n",
      "Generation 99: M(n) = 736.0925134185903\n",
      "Generation 100: p = 0.9201156417732379\n",
      "Generation 100: M(n) = 737.0057834504684\n",
      "Generation 101: p = 0.9212572293130854\n",
      "Generation 101: M(n) = 737.9015216259768\n",
      "Generation 102: p = 0.922376902032471\n",
      "Generation 102: M(n) = 738.7800645005452\n",
      "Generation 103: p = 0.9234750806256815\n",
      "Generation 103: M(n) = 739.6417421688178\n",
      "Generation 104: p = 0.9245521777110223\n",
      "Generation 104: M(n) = 740.4868783886801\n",
      "Generation 105: p = 0.9256085979858502\n",
      "Generation 105: M(n) = 741.3157907029043\n",
      "Generation 106: p = 0.9266447383786304\n",
      "Generation 106: M(n) = 742.1287905584595\n",
      "Generation 107: p = 0.9276609881980744\n",
      "Generation 107: M(n) = 742.9261834235316\n",
      "Generation 108: p = 0.9286577292794145\n",
      "Generation 108: M(n) = 743.7082689022967\n",
      "Generation 109: p = 0.9296353361278709\n",
      "Generation 109: M(n) = 744.4753408474915\n",
      "Generation 110: p = 0.9305941760593643\n",
      "Generation 110: M(n) = 745.227687470822\n",
      "Generation 111: p = 0.9315346093385276\n",
      "Generation 111: M(n) = 745.9655914512542\n",
      "Generation 112: p = 0.9324569893140677\n",
      "Generation 112: M(n) = 746.6893300412236\n",
      "Generation 113: p = 0.9333616625515294\n",
      "Generation 113: M(n) = 747.3991751708082\n",
      "Generation 114: p = 0.9342489689635103\n",
      "Generation 114: M(n) = 748.0953935499007\n",
      "Generation 115: p = 0.9351192419373758\n",
      "Generation 115: M(n) = 748.7782467684184\n",
      "Generation 116: p = 0.935972808460523\n",
      "Generation 116: M(n) = 749.4479913945914\n",
      "Generation 117: p = 0.9368099892432393\n",
      "Generation 117: M(n) = 750.1048790713625\n",
      "Generation 118: p = 0.937631098839203\n",
      "Generation 118: M(n) = 750.7491566109362\n",
      "Generation 119: p = 0.9384364457636702\n",
      "Generation 119: M(n) = 751.3810660875148\n",
      "Generation 120: p = 0.9392263326093935\n",
      "Generation 120: M(n) = 752.0008449282516\n",
      "Generation 121: p = 0.9400010561603145\n",
      "Generation 121: M(n) = 752.60872600246\n",
      "Generation 122: p = 0.940760907503075\n",
      "Generation 122: M(n) = 753.2049377091091\n",
      "Generation 123: p = 0.9415061721363864\n",
      "Generation 123: M(n) = 753.7897040626405\n",
      "Generation 124: p = 0.9422371300783006\n",
      "Generation 124: M(n) = 754.3632447771363\n",
      "Generation 125: p = 0.9429540559714203\n",
      "Generation 125: M(n) = 754.925775348873\n",
      "Generation 126: p = 0.9436572191860912\n",
      "Generation 126: M(n) = 755.4775071372894\n",
      "Generation 127: p = 0.9443468839216118\n",
      "Generation 127: M(n) = 756.0186474444009\n",
      "Generation 128: p = 0.9450233093055012\n",
      "Generation 128: M(n) = 756.5493995926887\n",
      "Generation 129: p = 0.9456867494908608\n",
      "Generation 129: M(n) = 757.0699630014943\n",
      "Generation 130: p = 0.946337453751868\n",
      "Generation 130: M(n) = 757.5805332619476\n",
      "Generation 131: p = 0.9469756665774345\n",
      "Generation 131: M(n) = 758.0813022104554\n",
      "Generation 132: p = 0.9476016277630692\n",
      "Generation 132: M(n) = 758.572458000781\n",
      "Generation 133: p = 0.9482155725009762\n",
      "Generation 133: M(n) = 759.0541851747384\n",
      "Generation 134: p = 0.9488177314684231\n",
      "Generation 134: M(n) = 759.5266647315309\n",
      "Generation 135: p = 0.9494083309144137\n",
      "Generation 135: M(n) = 759.9900741957571\n",
      "Generation 136: p = 0.9499875927446964\n",
      "Generation 136: M(n) = 760.4445876841124\n",
      "Generation 137: p = 0.9505557346051405\n",
      "Generation 137: M(n) = 760.8903759708103\n",
      "Generation 138: p = 0.9511129699635128\n",
      "Generation 138: M(n) = 761.3276065517466\n",
      "Generation 139: p = 0.9516595081896833\n",
      "Generation 139: M(n) = 761.7564437074333\n",
      "Generation 140: p = 0.9521955546342916\n",
      "Generation 140: M(n) = 762.177048564723\n",
      "Generation 141: p = 0.9527213107059037\n",
      "Generation 141: M(n) = 762.5895791573495\n",
      "Generation 142: p = 0.9532369739466868\n",
      "Generation 142: M(n) = 762.9941904853057\n",
      "Generation 143: p = 0.9537427381066321\n",
      "Generation 143: M(n) = 763.3910345730815\n",
      "Generation 144: p = 0.9542387932163519\n",
      "Generation 144: M(n) = 763.7802605267839\n",
      "Generation 145: p = 0.9547253256584799\n",
      "Generation 145: M(n) = 764.162014590161\n",
      "Generation 146: p = 0.9552025182377012\n",
      "Generation 146: M(n) = 764.5364401995496\n",
      "Generation 147: p = 0.955670550249437\n",
      "Generation 147: M(n) = 764.903678037769\n",
      "Generation 148: p = 0.9561295975472113\n",
      "Generation 148: M(n) = 765.2638660869793\n",
      "Generation 149: p = 0.9565798326087241\n",
      "Generation 149: M(n) = 765.6171396805255\n",
      "Generation 150: p = 0.9570214246006569\n",
      "Generation 150: M(n) = 765.9636315537863\n",
      "Generation 151: p = 0.9574545394422329\n",
      "Generation 151: M(n) = 766.3034718940469\n",
      "Generation 152: p = 0.9578793398675586\n",
      "Generation 152: M(n) = 766.6367883894137\n",
      "Generation 153: p = 0.9582959854867671\n",
      "Generation 153: M(n) = 766.9637062767912\n",
      "Generation 154: p = 0.958704632845989\n",
      "Generation 154: M(n) = 767.2843483889368\n",
      "Generation 155: p = 0.959105435486171\n",
      "Generation 155: M(n) = 767.5988352006127\n",
      "Generation 156: p = 0.9594985440007658\n",
      "Generation 156: M(n) = 767.9072848738521\n",
      "Generation 157: p = 0.9598841060923151\n",
      "Generation 157: M(n) = 768.2098133023559\n",
      "Generation 158: p = 0.9602622666279449\n",
      "Generation 158: M(n) = 768.5065341550376\n",
      "Generation 159: p = 0.9606331676937969\n",
      "Generation 159: M(n) = 768.7975589187319\n",
      "Generation 160: p = 0.9609969486484148\n",
      "Generation 160: M(n) = 769.0829969400837\n",
      "Generation 161: p = 0.9613537461751046\n",
      "Generation 161: M(n) = 769.3629554666334\n",
      "Generation 162: p = 0.9617036943332917\n",
      "Generation 162: M(n) = 769.6375396871119\n",
      "Generation 163: p = 0.96204692460889\n",
      "Generation 163: M(n) = 769.9068527709642\n",
      "Generation 164: p = 0.9623835659637052\n",
      "Generation 164: M(n) = 770.1709959071123\n",
      "Generation 165: p = 0.9627137448838904\n",
      "Generation 165: M(n) = 770.4300683419757\n",
      "Generation 166: p = 0.9630375854274696\n",
      "Generation 166: M(n) = 770.6841674167607\n",
      "Generation 167: p = 0.9633552092709509\n",
      "Generation 167: M(n) = 770.9333886040346\n",
      "Generation 168: p = 0.9636667357550432\n",
      "Generation 168: M(n) = 771.1778255435976\n",
      "Generation 169: p = 0.963972281929497\n",
      "Generation 169: M(n) = 771.4175700776657\n",
      "Generation 170: p = 0.9642719625970821\n",
      "Generation 170: M(n) = 771.6527122853792\n",
      "Generation 171: p = 0.9645658903567239\n",
      "Generation 171: M(n) = 771.8833405166473\n",
      "Generation 172: p = 0.9648541756458091\n",
      "Generation 172: M(n) = 772.1095414253447\n",
      "Generation 173: p = 0.9651369267816808\n",
      "Generation 173: M(n) = 772.3314000018693\n",
      "Generation 174: p = 0.9654142500023366\n",
      "Generation 174: M(n) = 772.5489996050758\n",
      "Generation 175: p = 0.9656862495063447\n",
      "Generation 175: M(n) = 772.7624219935963\n",
      "Generation 176: p = 0.9659530274919953\n",
      "Generation 176: M(n) = 772.971747356559\n",
      "Generation 177: p = 0.9662146841956988\n",
      "Generation 177: M(n) = 773.1770543437186\n",
      "Generation 178: p = 0.9664713179296482\n",
      "Generation 178: M(n) = 773.378420095006\n",
      "Generation 179: p = 0.9667230251187575\n",
      "Generation 179: M(n) = 773.5759202695133\n",
      "Generation 180: p = 0.9669699003368916\n",
      "Generation 180: M(n) = 773.7696290739201\n",
      "Generation 181: p = 0.9672120363424002\n",
      "Generation 181: M(n) = 773.9596192903762\n",
      "Generation 182: p = 0.9674495241129702\n",
      "Generation 182: M(n) = 774.1459623038471\n",
      "Generation 183: p = 0.9676824528798089\n",
      "Generation 183: M(n) = 774.3287281289361\n",
      "Generation 184: p = 0.96791091016117\n",
      "Generation 184: M(n) = 774.5079854361903\n",
      "Generation 185: p = 0.9681349817952379\n",
      "Generation 185: M(n) = 774.683801577903\n",
      "Generation 186: p = 0.9683547519723787\n",
      "Generation 186: M(n) = 774.8562426134188\n",
      "Generation 187: p = 0.9685703032667735\n",
      "Generation 187: M(n) = 775.025373333955\n",
      "Generation 188: p = 0.9687817166674438\n",
      "Generation 188: M(n) = 775.1912572869454\n",
      "Generation 189: p = 0.9689890716086818\n",
      "Generation 189: M(n) = 775.3539567999165\n",
      "Generation 190: p = 0.9691924459998957\n",
      "Generation 190: M(n) = 775.5135330039066\n",
      "Generation 191: p = 0.9693919162548832\n",
      "Generation 191: M(n) = 775.6700458564335\n",
      "Generation 192: p = 0.9695875573205419\n",
      "Generation 192: M(n) = 775.8235541640233\n",
      "Generation 193: p = 0.9697794427050291\n",
      "Generation 193: M(n) = 775.9741156043052\n",
      "Generation 194: p = 0.9699676445053815\n",
      "Generation 194: M(n) = 776.121786747683\n",
      "Generation 195: p = 0.9701522334346038\n",
      "Generation 195: M(n) = 776.26662307859\n",
      "Generation 196: p = 0.9703332788482375\n",
      "Generation 196: M(n) = 776.4086790163361\n",
      "Generation 197: p = 0.9705108487704202\n",
      "Generation 197: M(n) = 776.5480079355553\n",
      "Generation 198: p = 0.9706850099194442\n",
      "Generation 198: M(n) = 776.6846621862597\n",
      "Generation 199: p = 0.9708558277328246\n",
      "Generation 199: M(n) = 776.8186931135087\n",
      "Generation 200: p = 0.9710233663918859\n",
      "Generation 200: M(n) = 776.9501510767017\n",
      "Generation 201: p = 0.9711876888458771\n",
      "Generation 201: M(n) = 777.0790854684985\n",
      "Generation 202: p = 0.9713488568356232\n",
      "Generation 202: M(n) = 777.2055447333787\n",
      "Generation 203: p = 0.9715069309167234\n",
      "Generation 203: M(n) = 777.329576385843\n",
      "Generation 204: p = 0.9716619704823037\n",
      "Generation 204: M(n) = 777.451227028266\n",
      "Generation 205: p = 0.9718140337853325\n",
      "Generation 205: M(n) = 777.5705423684062\n",
      "Generation 206: p = 0.9719631779605078\n",
      "Generation 206: M(n) = 777.6875672365798\n",
      "Generation 207: p = 0.9721094590457247\n",
      "Generation 207: M(n) = 777.8023456025044\n",
      "Generation 208: p = 0.9722529320031305\n",
      "Generation 208: M(n) = 777.9149205918203\n",
      "Generation 209: p = 0.9723936507397754\n",
      "Generation 209: M(n) = 778.0253345022936\n",
      "Generation 210: p = 0.9725316681278671\n",
      "Generation 210: M(n) = 778.133628819709\n",
      "Generation 211: p = 0.9726670360246362\n",
      "Generation 211: M(n) = 778.2398442334569\n",
      "Generation 212: p = 0.9727998052918211\n",
      "Generation 212: M(n) = 778.3440206518222\n",
      "Generation 213: p = 0.9729300258147778\n",
      "Generation 213: M(n) = 778.4461972169787\n",
      "Generation 214: p = 0.9730577465212233\n",
      "Generation 214: M(n) = 778.5464123196956\n",
      "Generation 215: p = 0.9731830153996195\n",
      "Generation 215: M(n) = 778.6447036137628\n",
      "Generation 216: p = 0.9733058795172035\n",
      "Generation 216: M(n) = 778.741108030138\n",
      "Generation 217: p = 0.9734263850376724\n",
      "Generation 217: M(n) = 778.8356617908228\n",
      "Generation 218: p = 0.9735445772385285\n",
      "Generation 218: M(n) = 778.9284004224728\n",
      "Generation 219: p = 0.973660500528091\n",
      "Generation 219: M(n) = 779.0193587697455\n",
      "Generation 220: p = 0.9737741984621819\n",
      "Generation 220: M(n) = 779.1085710083928\n",
      "Generation 221: p = 0.973885713760491\n",
      "Generation 221: M(n) = 779.1960706581017\n",
      "Generation 222: p = 0.9739950883226272\n",
      "Generation 222: M(n) = 779.2818905950887\n",
      "Generation 223: p = 0.9741023632438609\n",
      "Generation 223: M(n) = 779.3660630644523\n",
      "Generation 224: p = 0.9742075788305654\n",
      "Generation 224: M(n) = 779.4486196922886\n",
      "Generation 225: p = 0.9743107746153608\n",
      "Generation 225: M(n) = 779.5295914975741\n",
      "Generation 226: p = 0.9744119893719676\n",
      "Generation 226: M(n) = 779.6090089038202\n",
      "Generation 227: p = 0.9745112611297752\n",
      "Generation 227: M(n) = 779.6869017505044\n",
      "Generation 228: p = 0.9746086271881305\n",
      "Generation 228: M(n) = 779.7632993042823\n",
      "Generation 229: p = 0.9747041241303529\n",
      "Generation 229: M(n) = 779.8382302699832\n",
      "Generation 230: p = 0.9747977878374791\n",
      "Generation 230: M(n) = 779.911722801396\n",
      "Generation 231: p = 0.974889653501745\n",
      "Generation 231: M(n) = 779.9838045118466\n",
      "Generation 232: p = 0.9749797556398083\n",
      "Generation 232: M(n) = 780.0545024845742\n",
      "Generation 233: p = 0.9750681281057177\n",
      "Generation 233: M(n) = 780.1238432829063\n",
      "Generation 234: p = 0.9751548041036329\n",
      "Generation 234: M(n) = 780.1918529602397\n",
      "Generation 235: p = 0.9752398162002995\n",
      "Generation 235: M(n) = 780.2585570698294\n",
      "Generation 236: p = 0.9753231963372868\n",
      "Generation 236: M(n) = 780.3239806743903\n",
      "Generation 237: p = 0.9754049758429879\n",
      "Generation 237: M(n) = 780.3881483555131\n",
      "Generation 238: p = 0.9754851854443913\n",
      "Generation 238: M(n) = 780.4510842229009\n",
      "Generation 239: p = 0.9755638552786262\n",
      "Generation 239: M(n) = 780.5128119234279\n",
      "Generation 240: p = 0.9756410149042849\n",
      "Generation 240: M(n) = 780.5733546500239\n",
      "Generation 241: p = 0.9757166933125299\n",
      "Generation 241: M(n) = 780.6327351503891\n",
      "Generation 242: p = 0.9757909189379863\n",
      "Generation 242: M(n) = 780.6909757355405\n",
      "Generation 243: p = 0.9758637196694256\n",
      "Generation 243: M(n) = 780.7480982881955\n",
      "Generation 244: p = 0.9759351228602443\n",
      "Generation 244: M(n) = 780.804124270993\n",
      "Generation 245: p = 0.9760051553387413\n",
      "Generation 245: M(n) = 780.8590747345586\n",
      "Generation 246: p = 0.9760738434181983\n",
      "Generation 246: M(n) = 780.9129703254127\n",
      "Generation 247: p = 0.9761412129067659\n",
      "Generation 247: M(n) = 780.9658312937295\n",
      "Generation 248: p = 0.9762072891171618\n",
      "Generation 248: M(n) = 781.017677500944\n",
      "Generation 249: p = 0.9762720968761801\n",
      "Generation 249: M(n) = 781.068528427216\n",
      "Generation 250: p = 0.9763356605340201\n",
      "Generation 250: M(n) = 781.1184031787483\n",
      "Generation 251: p = 0.9763980039734353\n",
      "Generation 251: M(n) = 781.1673204949659\n",
      "Generation 252: p = 0.9764591506187074\n",
      "Generation 252: M(n) = 781.215298755557\n",
      "Generation 253: p = 0.9765191234444462\n",
      "Generation 253: M(n) = 781.2623559873788\n",
      "Generation 254: p = 0.9765779449842235\n",
      "Generation 254: M(n) = 781.3085098712304\n",
      "Generation 255: p = 0.976635637339038\n",
      "Generation 255: M(n) = 781.3537777484966\n",
      "Generation 256: p = 0.9766922221856207\n",
      "Generation 256: M(n) = 781.3981766276629\n",
      "Generation 257: p = 0.9767477207845786\n",
      "Generation 257: M(n) = 781.4417231907065\n",
      "Generation 258: p = 0.9768021539883831\n",
      "Generation 258: M(n) = 781.4844337993642\n",
      "Generation 259: p = 0.9768555422492052\n",
      "Generation 259: M(n) = 781.5263245012799\n",
      "Generation 260: p = 0.9769079056265998\n",
      "Generation 260: M(n) = 781.5674110360341\n",
      "Generation 261: p = 0.9769592637950426\n",
      "Generation 261: M(n) = 781.6077088410578\n",
      "Generation 262: p = 0.9770096360513223\n",
      "Generation 262: M(n) = 781.6472330574331\n",
      "Generation 263: p = 0.9770590413217914\n",
      "Generation 263: M(n) = 781.6859985355816\n",
      "Generation 264: p = 0.977107498169477\n",
      "Generation 264: M(n) = 781.7240198408443\n",
      "Generation 265: p = 0.9771550248010554\n",
      "Generation 265: M(n) = 781.7613112589548\n",
      "Generation 266: p = 0.9772016390736935\n",
      "Generation 266: M(n) = 781.7978868014061\n",
      "Generation 267: p = 0.9772473585017576\n",
      "Generation 267: M(n) = 781.8337602107155\n",
      "Generation 268: p = 0.9772922002633944\n",
      "Generation 268: M(n) = 781.868944965588\n",
      "Generation 269: p = 0.977336181206985\n",
      "Generation 269: M(n) = 781.9034542859807\n",
      "Generation 270: p = 0.9773793178574759\n",
      "Generation 270: M(n) = 781.9373011380701\n",
      "Generation 271: p = 0.9774216264225877\n",
      "Generation 271: M(n) = 781.9704982391236\n",
      "Generation 272: p = 0.9774631227989045\n",
      "Generation 272: M(n) = 782.0030580622775\n",
      "Generation 273: p = 0.977503822577847\n",
      "Generation 273: M(n) = 782.0349928412244\n",
      "Generation 274: p = 0.9775437410515305\n",
      "Generation 274: M(n) = 782.0663145748089\n",
      "Generation 275: p = 0.9775828932185111\n",
      "Generation 275: M(n) = 782.0970350315362\n",
      "Generation 276: p = 0.9776212937894202\n",
      "Generation 276: M(n) = 782.1271657539942\n",
      "Generation 277: p = 0.9776589571924927\n",
      "Generation 277: M(n) = 782.1567180631899\n",
      "Generation 278: p = 0.9776958975789874\n",
      "Generation 278: M(n) = 782.1857030628036\n",
      "Generation 279: p = 0.9777321288285045\n",
      "Generation 279: M(n) = 782.2141316433599\n",
      "Generation 280: p = 0.9777676645541998\n",
      "Generation 280: M(n) = 782.2420144863208\n",
      "Generation 281: p = 0.9778025181079011\n",
      "Generation 281: M(n) = 782.2693620680985\n",
      "Generation 282: p = 0.9778367025851231\n",
      "Generation 282: M(n) = 782.2961846639913\n",
      "Generation 283: p = 0.9778702308299891\n",
      "Generation 283: M(n) = 782.3224923520451\n",
      "Generation 284: p = 0.9779031154400564\n",
      "Generation 284: M(n) = 782.3482950168392\n",
      "Generation 285: p = 0.977935368771049\n",
      "Generation 285: M(n) = 782.3736023532011\n",
      "Generation 286: p = 0.9779670029415014\n",
      "Generation 286: M(n) = 782.3984238698484\n",
      "Generation 287: p = 0.9779980298373105\n",
      "Generation 287: M(n) = 782.422768892962\n",
      "Generation 288: p = 0.9780284611162026\n",
      "Generation 288: M(n) = 782.44664656969\n",
      "Generation 289: p = 0.9780583082121125\n",
      "Generation 289: M(n) = 782.4700658715844\n",
      "Generation 290: p = 0.9780875823394806\n",
      "Generation 290: M(n) = 782.4930355979724\n",
      "Generation 291: p = 0.9781162944974655\n",
      "Generation 291: M(n) = 782.5155643792622\n",
      "Generation 292: p = 0.9781444554740777\n",
      "Generation 292: M(n) = 782.5376606801858\n",
      "Generation 293: p = 0.9781720758502322\n",
      "Generation 293: M(n) = 782.5593328029797\n",
      "Generation 294: p = 0.9781991660037247\n",
      "Generation 294: M(n) = 782.5805888905039\n",
      "Generation 295: p = 0.9782257361131299\n",
      "Generation 295: M(n) = 782.6014369293016\n",
      "Generation 296: p = 0.978251796161627\n",
      "Generation 296: M(n) = 782.6218847526001\n",
      "Generation 297: p = 0.97827735594075\n",
      "Generation 297: M(n) = 782.6419400432535\n",
      "Generation 298: p = 0.9783024250540668\n",
      "Generation 298: M(n) = 782.6616103366302\n",
      "Generation 299: p = 0.9783270129207878\n",
      "Generation 299: M(n) = 782.6809030234435\n",
      "Generation 300: p = 0.9783511287793044\n",
      "Generation 300: M(n) = 782.6998253525287\n",
      "Generation 301: p = 0.9783747816906608\n",
      "Generation 301: M(n) = 782.7183844335666\n",
      "Generation 302: p = 0.9783979805419583\n",
      "Generation 302: M(n) = 782.7365872397551\n",
      "Generation 303: p = 0.9784207340496939\n",
      "Generation 303: M(n) = 782.7544406104289\n",
      "Generation 304: p = 0.9784430507630362\n",
      "Generation 304: M(n) = 782.7719512536296\n",
      "Generation 305: p = 0.978464939067037\n",
      "Generation 305: M(n) = 782.7891257486257\n",
      "Generation 306: p = 0.9784864071857821\n",
      "Generation 306: M(n) = 782.8059705483848\n",
      "Generation 307: p = 0.9785074631854811\n",
      "Generation 307: M(n) = 782.8224919819986\n",
      "Generation 308: p = 0.9785281149774983\n",
      "Generation 308: M(n) = 782.8386962570601\n",
      "Generation 309: p = 0.9785483703213251\n",
      "Generation 309: M(n) = 782.8545894619966\n",
      "Generation 310: p = 0.9785682368274958\n",
      "Generation 310: M(n) = 782.8701775683571\n",
      "Generation 311: p = 0.9785877219604464\n",
      "Generation 311: M(n) = 782.8854664330561\n",
      "Generation 312: p = 0.9786068330413201\n",
      "Generation 312: M(n) = 782.9004618005739\n",
      "Generation 313: p = 0.9786255772507174\n",
      "Generation 313: M(n) = 782.9151693051155\n",
      "Generation 314: p = 0.9786439616313943\n",
      "Generation 314: M(n) = 782.9295944727269\n",
      "Generation 315: p = 0.9786619930909086\n",
      "Generation 315: M(n) = 782.943742723372\n",
      "Generation 316: p = 0.978679678404215\n",
      "Generation 316: M(n) = 782.9576193729686\n",
      "Generation 317: p = 0.9786970242162107\n",
      "Generation 317: M(n) = 782.9712296353861\n",
      "Generation 318: p = 0.9787140370442325\n",
      "Generation 318: M(n) = 782.984578624404\n",
      "Generation 319: p = 0.9787307232805049\n",
      "Generation 319: M(n) = 782.997671355634\n",
      "Generation 320: p = 0.9787470891945425\n",
      "Generation 320: M(n) = 783.010512748404\n",
      "Generation 321: p = 0.9787631409355051\n",
      "Generation 321: M(n) = 783.0231076276066\n",
      "Generation 322: p = 0.9787788845345082\n",
      "Generation 322: M(n) = 783.0354607255117\n",
      "Generation 323: p = 0.9787943259068896\n",
      "Generation 323: M(n) = 783.0475766835452\n",
      "Generation 324: p = 0.9788094708544315\n",
      "Generation 324: M(n) = 783.0594600540321\n",
      "Generation 325: p = 0.9788243250675401\n",
      "Generation 325: M(n) = 783.0711153019076\n",
      "Generation 326: p = 0.9788388941273846\n",
      "Generation 326: M(n) = 783.0825468063946\n",
      "Generation 327: p = 0.9788531835079932\n",
      "Generation 327: M(n) = 783.0937588626484\n",
      "Generation 328: p = 0.9788671985783105\n",
      "Generation 328: M(n) = 783.1047556833718\n",
      "Generation 329: p = 0.9788809446042147\n",
      "Generation 329: M(n) = 783.1155414003966\n",
      "Generation 330: p = 0.9788944267504958\n",
      "Generation 330: M(n) = 783.1261200662371\n",
      "Generation 331: p = 0.9789076500827965\n",
      "Generation 331: M(n) = 783.1364956556122\n",
      "Generation 332: p = 0.9789206195695153\n",
      "Generation 332: M(n) = 783.1466720669388\n",
      "Generation 333: p = 0.9789333400836735\n",
      "Generation 333: M(n) = 783.1566531237968\n",
      "Generation 334: p = 0.978945816404746\n",
      "Generation 334: M(n) = 783.1664425763656\n",
      "Generation 335: p = 0.978958053220457\n",
      "Generation 335: M(n) = 783.1760441028333\n",
      "Generation 336: p = 0.9789700551285416\n",
      "Generation 336: M(n) = 783.1854613107785\n",
      "Generation 337: p = 0.9789818266384731\n",
      "Generation 337: M(n) = 783.1946977385257\n",
      "Generation 338: p = 0.9789933721731572\n",
      "Generation 338: M(n) = 783.2037568564754\n"
     ]
    },
    {
     "data": {
      "image/png": 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X19e4ePGikZiYaISHhxuDBw82DMMwAgMDbX7n7X0fP/30UwMwvv/+e5tyL7/8cqq/9fa+r/Z83uT+oZEpua/4+PgwbNgwtm7d6tJh+yZNmtjcL126NCaTiaeeesq6z8vLi+LFi6e5omDbtm1tpmVFRERQvXp163SOgwcP8s8//9CuXTsAEhMTrbdGjRpx+vRp9u3bZ9Pms88+a1fsa9as4cEHH+SRRx6x2d+hQwcMw3DJKF6nTp1YsmQJFy9eZMaMGdSpUyfdRSNiYmIYMGAAxYsXx8vLCy8vL4KCgoiNjWXv3r23fa4NGzYQHR1Nt27dbnuOmMlkSvXf1HLlytn00Y8//kjOnDl5+umnbd738uXLExYWZl3NKaWvUvooRatWrdKcIpaWQYMGcfz4cWbOnMmrr75KUFAQU6dOpVKlSnzxxRd2tXEze+MvX748Pj4+vPLKK8yZMyfNVbUc1bhxYzw9Pa33UxbQSOszYI8WLVrg7e1tvfXs2dPm8RkzZuDv78/zzz8PWE5ob9myJb/++isHDhxw6jmDg4P59ddf2bJlCyNHjuSZZ55h//79DBw4kLJly1pHeG6lUaNGNqOwpUuXBkg1QpCy//jx407FerOMfpbSknI8uHmKYcuWLQkMDOTnn3+22V++fHkKFSpkve/n58cDDzxw29+BsmXLUqlSJWbNmmXdt3fvXjZv3mwz5euRRx5hx44ddOvWjRUrVji9oM3t1KlTh2zZslnvh4aGkjdvXuvruHbtGj///DPNmzcnICAg1TH62rVr1imujh5zmzZtajOzwJm/B/ZYtmwZAN27d79lucOHD9O2bVvCwsLw9PTE29ubWrVqATj9e5WiZcuW+Pj48Pnnn/PTTz9x5syZdKez2vs+rl27lmzZstG0aVObcm3btrW5n1nvq9z7lEzJfef555+nYsWKvPPOO05N2UlL7ty5be77+PgQEBCAn59fqv3Xrl1LVT8sLCzNfSlTvc6ePQtA//79bb5Ment7061bN4BUX+rsmYIHlnNC0iqbL18+6+MZ9dxzz+Hn58eECRP44Ycf6Ny5c7pl27Zty5QpU+jSpQsrVqxg8+bNbNmyhZCQEJspdelJOQ/InpW40uojX19fmz46e/YskZGR+Pj4pHrvz5w5Y33fU96nm/vSy8uL4ODg28aSIjQ0lI4dOzJ16lR27tzJ+vXr8fHxcXrVLXvjL1asGKtXryZv3rx0796dYsWKUaxYsQyde3Lz6045af52/VioUKE0v2yPGzeOLVu2sGXLllSPHTx4kF9++YXGjRtjGAaRkZFERkby3HPPAdz2PJ3bqVy5MgMGDOCrr77i1KlT9OnTh6NHj6Z7HuSN0jo+3Gp/WscIZ2T0s5SWixcv4uXllWoBFJPJZHPMSpHW776vr69dz9+pUyc2btxoXSBi1qxZ+Pr60qZNG2uZgQMHMnbsWP744w+eeuopgoODqVu3Llu3bnXm5aXrdq/j4sWLJCYmMnny5FSfs0aNGgHYHCscOebeXNaZvwf2OH/+PJ6enmn+PUoRExNDzZo12bRpE8OGDWPdunVs2bLFOn3d2d+rFIGBgbRu3ZqZM2cyY8YM6tWrR0RERJpl7X0fL168SGhoaKpyN7/OzHpf5d6n1fzkvmMymRg1ahT169dn2rRpqR5P+XJ989x/VyQV6UnrRNgzZ85Y/4DnyZMHsHxxaNGiRZptlCxZ0ua+vSv3BQcHc/r06VT7T506ZfPcGREQEMDzzz/Phx9+SPbs2dN9DVFRUfz444+8//77vPXWW9b98fHxXLp0ya7nSvmSd/P5Uc7KkycPwcHBLF++PM3HU/5bndJXZ86cIX/+/NbHExMTM/S78/jjj9OgQQO+++47zp07R968eR2qb2/8ADVr1qRmzZokJSWxdetWJk+eTO/evQkNDbWO9twJ9evX5+OPP2br1q02503davWxmTNnYhgGX3/9dZrXbZszZw7Dhg2zGSlzlre3N++//z4TJkxg165dGW7vVnx9fdNcPOZ2v1Ou+CylJTg4mMTERM6fP2+TUBmGwZkzZ6hSpYrTbd+sTZs29O3bl9mzZzN8+HDmzZtHs2bNbFZx9PLyom/fvvTt25fIyEhWr17N22+/TcOGDTlx4gQBAQEui+dWcuXKhaenJy+++GK6IztFihQBHD/m3nwsd+bvgT1CQkJISkrizJkz6f4zbs2aNZw6dYp169ZZR6MAl56j1qlTJ6ZPn87OnTv5/PPP0y1n7/sYHByc5kJAN//dzaz3Ve59GpmS+1K9evWoX78+Q4cOJSYmxuax0NBQ/Pz8bC6SCvD9999nWjxffPGFzQVIjx07xoYNG6wrg5UsWZISJUqwY8cOKleunObtxi/Fjqhbty579uzhzz//tNmfclHdm5fpdlbXrl15+umnee+991KNBqUwmUwYhpFq2d/p06eTlJRksy+9UY7q1auTI0cOpk6dmu5FXR3RpEkTLl68SFJSUprve8of15S+uvmP/5dffkliYuJtn+fs2bOpVqACy4IdBw4cICAggJw5c6ZbP73/9tsb/408PT159NFHrauQ3fy7kdn69OlDQEAA3bt358qVK7ctn7KoSbFixVi7dm2qW79+/Th9+rR1GpMj0vqyBtenM6X8FzyzFC5cONWxaM2aNamOWzdzxWcpLSkLAcyfP99m/zfffENsbGyaCwU4K1euXDRr1oy5c+fy448/cubMmXRXdQPImTMnzz33HN27d+fSpUtOX9DbGQEBAdSpU4ft27dTrly5ND9rKf9wyegx15G/B470bcq09E8//TTdMimJ3c2/V5999tlt27dXtWrV6NSpE82bN6d58+bplrP3faxTpw5XrlxJtbT6ggULbO5n5t9ZubdpZEruW6NGjaJSpUqcO3eOhx56yLrfZDLxwgsvMHPmTIoVK8bDDz/M5s2bUx14XencuXM0b96cl19+maioKN5//338/PwYOHCgtcxnn33GU089RcOGDenQoQP58+fn0qVL7N27lz///NPpFcv69OnD3Llzady4MUOHDiUiIoKlS5fyySef0LVrVx544AGXvMby5cvz3Xff3bJM9uzZefzxxxkzZgx58uShcOHCrF+/nhkzZqRKJMqUKQPAtGnTyJYtG35+fhQpUoTg4GDGjRtHly5dqFevHi+//DKhoaEcPHiQHTt2MGXKFIfifv755/n8889p1KgRvXr14pFHHsHb25uTJ0+ydu1annnmGZo3b07p0qV54YUXmDhxIt7e3tSrV49du3YxduzYdJf3vtG8efP47LPPaNu2LVWqVCFHjhycPHmS6dOns3v3bt577z3rNLC0lC1blm+//ZZPP/2USpUq4eHhQeXKle2Of+rUqaxZs4bGjRtTqFAhrl27Zp0al9YS9pmpWLFifPHFF7Rp04ayZcvStWtX60V7z507x8qVKwGs7+uyZcs4deoUo0aNslmaPEWZMmWYMmUKM2bMsJ7f2KFDB+bMmcORI0duedHnhg0bUqBAAZ5++mlKlSpFcnIyf/31F+PGjSMoKCjTL3r64osvMmjQIN577z1q1arFnj17mDJlCjly5LhlPVd9lm5Wv359GjZsyIABA4iOjqZGjRrs3LmT999/nwoVKqS5nHlGdOrUiUWLFvH6669ToECBVL+LTz/9tPX6UCEhIRw7doyJEycSERFBiRIlXBrL7UyaNInHHnuMmjVr0rVrVwoXLsyVK1c4ePAgP/zwg/UcHlccc+39e+BI39asWZMXX3yRYcOGcfbsWZo0aYKvry/bt28nICCAHj16UL16dXLlysVrr73G+++/j7e3N59//jk7duxw4Tt5/RIHt2Lv+9i+fXsmTJhA+/btGT58OCVKlOCnn36yrjB7o8z6Oyv3uKxa+ULkTrnVSk1t27Y1AJvV/AzDMKKioowuXboYoaGhRmBgoPH0008bR48eTXc1v/Pnz9vUf+mll4zAwMBUz3fzyoEpKwLNmzfP6NmzpxESEmL4+voaNWvWNLZu3Zqq/o4dO4xWrVoZefPmNby9vY2wsDDjiSeesK5edrvXm55jx44Zbdu2NYKDgw1vb2+jZMmSxpgxY1Ktlubsan7pSWulqZMnTxrPPvuskStXLiNbtmzGk08+aezatSvV6mWGYVkVrUiRIoanp2eqVZl++ukno1atWkZgYKAREBBgPPjgg8aoUaOsj6fXR2mtQGU2m42xY8caDz/8sOHn52cEBQUZpUqVMl599VXjwIED1nLx8fFGv379jLx581pXpNu4cWOasd9sz549Rr9+/YzKlSsbISEhhpeXl5ErVy6jVq1axrx582zKprWa36VLl4znnnvOyJkzp2EymWxegz3xb9y40WjevLkRERFh+Pr6GsHBwUatWrWMJUuW3DJuw0h/FbsxY8akKnvzZ+hWDh06ZPTo0cMoWbKk4e/vb/j6+hoRERFGy5YtjcWLF1tXa2zWrJnh4+NjnDt3Lt22nn/+ecPLy8s4c+aMYRiG8eyzzxr+/v7G5cuXbxnDokWLjLZt2xolSpQwgoKCDG9vb6NQoULGiy++aOzZs8ep9yHlc//VV1/Z7E/rsxsfH2+8+eabRsGCBQ1/f3+jVq1axl9//WXXan6u+CzdvOKbYVhW5BswYIARERFheHt7G+Hh4UbXrl1TvZfpHQNufp9uJSkpyShYsGC6q8yNGzfOqF69upEnTx7Dx8fHKFSokNG5c2fj6NGjdrVvGPat5te9e/dU+9N6H48cOWJ06tTJyJ8/v+Ht7W2EhIQY1atXN4YNG2ZTzp5j7q0+R4Zh398Dw3Csb5OSkowJEyYYZcqUMXx8fIwcOXIY1apVM3744QdrmQ0bNhjVqlUzAgICjJCQEKNLly7Gn3/+meoY7Mxqfrdy82p+hmH/366Uz0JQUJCRLVs249lnnzU2bNiQ5sq99ryvWs1PbmQyDBfMgxEREbmLhIWF8eKLLzJmzJisDkVERO5iSqZEROS+snv3bqpVq8bhw4ddssCKiIjcv5RMiYiIiIiIOEGr+YmIiIiIiDhByZSIiIiIiIgTlEyJiIiIiIg4QcmUiIiIiIiIE3TRXiA5OZlTp06RLVs269W9RURERETk/mMYBleuXCFfvnx4eNx67EnJFHDq1CkKFiyY1WGIiIiIiIibOHHiBAUKFLhlGSVTQLZs2QDLG5Y9e/YsjcVsNrNy5UoaNGiAt7d3lsYiqal/3Jv6x72pf9yb+se9qX/cm/rHvTnaP9HR0RQsWNCaI9yKkimwTu3Lnj27WyRTAQEBZM+eXR9GN6T+cW/qH/em/nFv6h/3pv5xb+of9+Zs/9hz+o8WoBAREREREXGCkikREREREREnKJkSERERERFxgpIpERERERERJyiZEhERERERcYKSKREREREREScomRIREREREXGCkikREREREREnKJkSERERERFxgpIpERERERERJyiZEhERERERcYKSKREREREREScomRIREREREXGCkikREREREREnZGkylZiYyLvvvkuRIkXw9/enaNGiDB06lOTkZGsZwzAYPHgw+fLlw9/fn9q1a7N7926bduLj4+nRowd58uQhMDCQpk2bcvLkyTv9ckRERERE5D6SpcnUqFGjmDp1KlOmTGHv3r2MHj2aMWPGMHnyZGuZ0aNHM378eKZMmcKWLVsICwujfv36XLlyxVqmd+/eLF68mIULF/Lbb78RExNDkyZNSEpKyoqXJSIiIiIi94EsTaY2btzIM888Q+PGjSlcuDDPPfccDRo0YOvWrYBlVGrixIm88847tGjRgjJlyjBnzhyuXr3KggULAIiKimLGjBmMGzeOevXqUaFCBebPn8/ff//N6tWrs/LliYiIiIjIbSQnw6xZsGNHVkfiuCxNph577DF+/vln9u/fD8COHTv47bffaNSoEQBHjhzhzJkzNGjQwFrH19eXWrVqsWHDBgC2bduG2Wy2KZMvXz7KlCljLXOz+Ph4oqOjbW4ARs6cGJ6et76FhmI2m21uRmjo7et5epL89NO2dY8dS1XGy8+Ppi1a4OXnZ7PfPGeOTd2kd96x6zkNH59U8SZXrmxfvKVLp36tgYF21U3q2tW27g8/2BevpyfmLVtsX2u7dvbVzZUrdbyFC9v3WmvVSl03jXJp9U/SuHG28Y4bZ/9rvblvatWyr27hwqnjzZXLvr5p18627pYt9sf7ww+2r7VrV/vqBgamfq2lS9vXN5Urp36tPj529U/SO+/Y1p0zx/7XeuyYbbxPP21f3Uw+RqQb711wjLixf+7VY0Rat7vlGJHSP7Rvf88eI1L1zV10jPDy8+OR4cPv6WOETd/cZccIU926APfMMSLJ04dET980b2ef6cS+fWbr7eB3f6Zb9ubb4f8ts6l7ul0frnkGcN4zlPqdCpCvfN6043XBMeLG/rntMSJnTrvzGS+7S2aCAQMGEBUVRalSpfD09CQpKYnhw4fTpk0bAM6cOQNAaGioTb3Q0FCOHTtmLePj40OuXLlSlUmpf7MPP/yQIUOGpNpvMgxMhnHLmBOjo/npp59s9jWOjsbrhvO80nPxyBF+v6Gu34ULNLSjHsCuTZs4fkPHPrRrF8XtqGskJ6eK94nTp8lmR91r58+z8qa6Ta9dw2RH3X/37WP7DXXDNm3iUTtf6+/r1hF16pT1/iMHDhBuR92kmJhUr/XJS5fwtaNu1MmTrL+p7jN2xrtv+3YO3FC3xPbtPGhn3ZvjrXXyJDntqBt/6RLLb6rbJCYGTzvqnjtwgM031M2xfz+17Yz3z40bOXND2Qr79lHInt/Da9dSvdYG58/jb0fdmNOnWXPz76HZjMmOeI/s2sXuG+oW2rSJCna+1jWrV3MtTx7r/RpHjpDHjro6RugYcbO77Rhx4dAhHSPskBXHCO+rV1m1apX1vo4RacuKY0TMv/8C2PTP3XyM8CT9NkYtKcOEJd7W+/nJy0kS7Ir36VcKsYfrdTvzENOJw4+464XSeOoMHyP+65eU/rndMcKe40eKLE2mFi1axPz581mwYAEPPfQQf/31F7179yZfvny89NJL1nImk+1LMgwj1b6b3arMwIED6du3r/V+dHQ0BQsWxDCZMG7Trmf27NaRsxv3GQm3/yXKXaSIbd1TpzA87BscLPPoo5S5oa7H5s0YP/54+4qenqnjDQ/HSCfRvJFvSEiquvj5YVy7dtu6+UuWJPzGuh4edr/WGrVrQ/ny16t++SXGtm23recRFJQqXq/cuTFiY29bN3uBAqnq2htvyQoVKHFj3xw8iPHFF3bVTdU348djHD1623o+uXOnqusRFITx3yjrreQtUcK2br58dr/WitWqwZNPXn/O5csx1q+/fUU/v9SvNSQE4/Ll21YNDA9P/Xvo7Y1hxzmRRcqUIeLGupGRGJ99dvt4gSfq1YN8+a7HO306xt69t62nY4SOETe7244ReYoV0zHCDllxjDAHBFC/fn28vf/7MqpjRJqy4hgRlD8/gE3/ZOUxIgEfopKzYb4hcbnR7zGP0eXFpjb7fkisTjEOWe+bSHuAIdHLjyC/64/5JZn4Ny5fmmVv5utnIsjret3keB9OmfPhb4oju+kKHuklcRk8RtSvX59Vq1Zd75/bHCMMw4DbDLCkMBmGnSUzQcGCBXnrrbfo3r27dd+wYcOYP38+//zzD4cPH6ZYsWL8+eefVKhQwVrmmWeeIWfOnMyZM4c1a9ZQt25dLl26ZDM69fDDD9OsWbM0R6BuFh0dTY4cOYiKiiJ79uyufZEOMpvN/PTTTzRq1Oj6wVLchvrHval/3Jv6x72pf9yb+idrxMfD5Mnw449wq/zcMJK5dOkyuXPnwmTK2isPXbsG/y0/4JT69WHCBHjoIdfFlNUc/fw4khtk6cjU1atX8bgpa/f09LQujV6kSBHCwsJYtWqVNZlKSEhg/fr1jBo1CoBKlSrh7e3NqlWraNWqFQCnT59m165djB49+g6+GhERERG5G1y9Cp99BocPp1/GMGDZsluXuc4DCHZRdBnn4QFdukCvXuDra389Pz/LgOttJmrJDbI0mXr66acZPnw4hQoV4qGHHmL79u2MHz+eTp06AZbpfb1792bEiBGUKFGCEiVKMGLECAICAmjbti0AOXLkoHPnzvTr14/g4GBy585N//79KVu2LPXq1cvKlyciIiKSrhMn4OefbUc8/P2hSRO40xNlrl2DH34AO2aC3vWioiwjL/ZekjQ8HN5+2/IzPYmJifz5559UrFgRL68s/XoNQNmy8MADWR3F/SFLe3vy5MkMGjSIbt26ce7cOfLly8err77Ke++9Zy3z5ptvEhcXR7du3bh8+TKPPvooK1euJFu2bNYyEyZMwMvLi1atWhEXF0fdunWZPXs2np6eWfGyRERERNIVEwOjRsHYsZYk5mahofDBB1Cx4vV9SUlgNmd8+lhiIuzZA/8tbgbAgQOWZOHIkQw3f1cpXBjatoVbfV3Mmxc6dICgoFu3ZTYb+PmdplEjA83CvL9kaTKVLVs2Jk6cyMSJE9MtYzKZGDx4MIMHD063jJ+fH5MnT7a52K+IiIhIZkhOttycqffFFzBwIJw+bdlXqZLNOhbs3m2ZVvbKKzfX9iYkpC7x8SZatXJuGtaaNdC3r+U50hIeDpUrO97u3ahmTejRwzKtTSQjsn4cUkREROQuEBUFw4bBxx9DXNzty99K0aKWkalmzWwTo4QE+OQTmDrVcl7P9ec2OH8+gBdegBdeyNhzBwZC7tzX7/v4WEZoBgywPCYi9lMyJSIiIve0P/+E99/P+DS2f/+FyMiMtZE9O7zzTvoLA/j4QO/eltuNoqIS6dr1IEuWlCI21rnVAby9oXt3eO89uOnynCLiJCVTIiIiclfbvt2yMltMTOrHoqJg6VK7LxlzW6VKWUaUqlVzrn5QkCVhclRAALRuvZ9p04qTkODcSTn+/pabiLiOkikREZH7XEICfP65iV9+KcY//3jc8oR8d7N7N8yZc/tkqV07y0ICGXltvr5QpQpZusCAr+/tF0MQkTtHyZSIiMh9yjBgyRLo3x8OHvQCymR1SE5r3RoefTT1fpMJHnvs/llYQUTuLCVTIiIi96BLl2yvX3SzY8fgrbcs1zkCCAszKFXqJAUK5MfDI+NLcN8pvr7w0ktQo0ZWRyIi9yMlUyIiIveQzZuhTx/YsMG+8r6+0K8f9OuXyK+//kmjRmF4e989yZSISFbS0VJERMRNJCfD7NlQpgzkzw8FClhGXU6cSL/OoUPw/POW8vnyWaa62ZNIeXpCy5awdy8MHw7ZsrnsZYiI3Dc0MiUiIuJisbEwcSL8/rtj9Y4dgz17bPfNnQtffQWPPw43z75LSoJ16ywLSNzopZdgxAjbi8GKiIjrKZkSERG5yeHD8Pnnzl2YNTERFiywXJPIGdmzw7vvQv36cPEiDB4Mv/0GK1akX6d+fcu1i3LkgDx5LCNaIiKS+ZRMiYjIPWvHDti3z7E6W7fCpEmpR3scVbgw9O3r2PQ5Ly9o0ADy5r2+74knYM2a9Kf6FS0KNWtaVq0TEZE7S8mUiIjcc44dgwEDYNEi59uoUwcefti5usWLQ+fO4Ofn/POnMJmgbt2MtyMidx/DMEg2kkkykkg2km1uKY9Z72Ok+diN+519zN7ncjaO4rmLU6dInax+u52iZEpERO4ZMTEwciSMGwfXrlkSkerVHbvIakAAdO0KjRtrtEfEVQzDIDE5Mc1bkpGU7mMZvSUlp992SpKSlJxkTVZS7qf5WBrbKWUTkxO5eOkiw84OI5lkp9pIa9vgNlejvke8UO4FJVMiIiJZJTnZslDD22/D6dOWfbVrw4QJUL58VkYmkjmSjWQSkhK4lniN+MR44pPirdvXEq8RnxRPfGI85mQzCUkJmJP++5nO/XTLJGeg7n/3UxKX+8LVrH16D5MHJkx4mDws26br27d67Mb9mfHY7eKoGFYxa9+4DFAyJSIid6UVKyzJUlQUXLgABw9a9hcrBmPHwjPPaGRJMo9hGJiTzcSZ47hqvkpc4n8/07l/LfGaTZJjs52UOglK2bYmS4nxRF+NxthjcC3xGuZkc1a/BS7hYfLAy8PL5uZp8ky1z5W3lPY9PTzxMHngafJMte1p+u9+Gttp1TOSDf768y8eqfIIPl4+dtdz5PlSyqeXtJh0wMsSSqZEROSu8NdfMGeOZfrewYOwerXt49mzw6BB0KOH5UK0cn8zDIOr5qvEJMQQkxBDrDnWun3jLTbBst8m+UlMPym68X6SkXTnX1g6T+nr6Yuflx++Xv/99PTFx9PHevP29Lb89PBO+356++28n14Zb09vvD28005q/ksS7gVmsxmfQz40Kt4Ib0fmFctdT8mUiIi4pRMnLKNPSUmweTPMmgXGDacPeHlZEqfatS3XX6pa1bIsuNydDMMg1hxL1LUoouOjiYr/7+d/96Pjo2+fGN2wPzYh9o6db2LCRIB3AP7e/pafXv6p7vt7+19PeG5IfNJKgm7cTnnM0/Bk84bN1KtTjyC/IJs63h7eGpUQySJKpkREJEtFRsI//1y/bxjw00+WqXrXrtmWbdkSypQBHx9o0QIeeOCOhirpMAyDmIQYLl+7zKW4S1yOu5xmQmS9f8P+lO3o+OhMO68m0DuQIJ+gVLdAH8v+QO/AdJMge+77ePpkejJjNps543+G4rmLa+RDxI0omRIRkTvKMCxJktkMn34Kw4bBlStpl61SxXIB2sBAywp71avf2VjvN+ZkM2dizhCTGGNJim5Ijmzup7E/MTnRJTF4mjzJ7pudHH45LD99LT+z+2ZPMyFKSYbSe8zf2/+emUomIu5HyZSIiNwRycmwdm0BevTwSnUB2tBQy5LkKfLkgbfegubNtYiEs5KNZCKvRXI+9jwXrl7g/NXzNts2P//bH2uOhZ3OP6ePpw+5/XOTyy9XqmTI+vPm/TfdD/AO0JQ1EblrKJkSEZFMt2ED9OrlydatlWz2588Pw4fDiy9aznuSW0tISuBszFnOxJxJdTsbe9YmQbp49aJTCySYMJHTL6clKfLPZU2ObH7evP+/+/5e/kqEROS+omRKREQyzfHjlhGmL74A8MDPL5FBg0x07eqJl5dl+t79nkQZhsHFuItpJkg33k7HnOZS3CWH28/um508AXkICQghJDDEum3zMzCEHN45+PO3P3nu6efw9dFyiCIi9lAyJSIiLpeYCB98AKNHW86PMpmgY8dkatZcTbt2dfH29szqEO+IpOQkzsae5WT0Sevt3+h/OXnF9n58UrzdbXp5eBEaGEpYUJjNLTQw1CZZCgkMIdg/GF8v+xIjs9nMfq/9Or9IRMQBSqZERMSlDMOyWMT06Zb7tWrBxInw0ENJ/PST/UmDuzMMg8vXLnM08qj1diLqhE2idPrKabun2gX7B6dKkNK65fbPrYRHRMRNKJkSERGXiIyEuDiYNs2SSHl4WK4N9eKLlpEpszmrI3RMyvS7G5OlY5HHOBp1/X5MQsxt2/EweZAvWz4KZC9AgewFyJ8tv3U75RYeFG73CJKIiLgPJVMiIpIhx45ZzotauNB2/+TJ0L591sRkL3OSmaORRzl46SAHLx3kwKUDHLp8yJo4xZpjb9tGaGAohXMWpnDOwhTMXpCCOQraJE6hQaF4eejPrYjIvUhHdxERcUpMDIwaZXtxXU9P8PWFgQOhW7esjS9FfGI8RyKPcODiAWvSdPCy5eexyGO3nYYXHhRuTZYK5yxMRI4I63ahHIXw9/a/Q69ERETcjZIpERFxSHIyzJtnSZhOn7bsSzkvqnz5rIvrwtUL7D2/l38u/MPeC9d/Hos8hoGRbj1/L3+K5y5O8dzFKZG7BMVyF6NIziKWkaYcBfHz8ruDr0JERO4mSqZERMRGcjJ88w1s2ZL242vXwtatlu2iRS0jU82a3ZmL6yYbyRyLPHY9WTq/l38uWn5ejLuYbr0gnyCbhCllu3ju4oQHhevaSCIi4hQlUyIiYrVxI/TuDZs337pctmwwaBD07GmZ1pcZzsWe4++zf7Pz7E7+Pmf5ufv8bq4lXku3TkSOCEqHlKZUcClK5SlF6ZDSPBD8AKGBoUqYRETE5ZRMiYjITRfXhaAgyyp8gYGpy+bMCV26QGioa577WuI19pzfY0mazv7NznOWn2djz6ZZ3sfThweCH6B0ntKWhOm/nw8EP0CgTxoBi4iIZBIlUyIi97HYWMsiEmPGXL+4bqdOMGwYhIW5/vliEmNYe3QtO87tYNvpbew4u4P9F/eTbCSnKmvCRLHcxSgXWo6yectafxbNVRRPj/vjor8iIuLelEyJiNyHkpPh888to1GnTln2Pf64ZRGJChVc8xyX4i6x7dQ2/jz9J9tOb2PbqW0cjjwMu1KXze2fm3Kh5SiXtxxlQy2J00MhD2mkSURE3JqSKRGR+8SqVZYRqMuXLbdDhyz7ixSxLCLRvLnzi0hcNV9l26lt/HHyDzb9u4ltp7dxNPJommWL5CxCpXyVqBhWkQrhFSgXWk6LQIiIyF1JyZSIyD3mjz8sS5fHx1/fd/Qo/Pyzbbls2eCdd6BXL/BzYPVvwzA4cOkAf5z8w5o87TizI83rNRXPXZyK4RWpFF6Jh0Me5vzf52ndtDXe3t7OvTgRERE3omRKROQeceYM9OsHCxak/biXF3TvDg0aWEagqlSBPHlu325MQgx/nPyD34//zqZ/N7Hp301ciruUqlx4UDjVClbj0fyPUiVfFSqEVyCnX07r42azmZ/2/uTkqxMREXE/SqZERO4Bly9D3bqwZ48lUXrhBShV6vrjXl7wzDNQsuTt27oUd4nfjv/GL8d+4dfjv7Lt1LZUo05+Xn5UCq9E1QJVqVqgKo/mf5QC2Qtoqp6IiNxXlEyJiNzFYmMhIQFatLAkUvnzw5IlULGi/W38G/2vNXH69fiv7DqXeoWIQjkK8Vihx6hWoBpVC1SlXGg5fDx9XPhKRERE7j5KpkRE7kIbN0Lfvpbzo1JkywZLl8LDD9+67oWrF1h7ZC2rD6/m5yM/c+jyoVRlSuUpxeOFHqdmRE1qFqpJRM4IF78CERGRu5+SKRGRu8jNF9dNERJiWeo8rUTqqvkqvx3/jdWHV7P68Gr+OvMXBob1cQ+TBxXCKlCzUE1qRtTksUKPkTcwbya/EhERkbufkikRkbtATAyMHp364rqDB0NwMHh7W86LAkhKTmLrqa3WkaffT/xOQlKCTXtl8pahXpF61Ctaj5oRNcnum/3OvygREZG7nJIpERE3EBtrWc78/PnUjyUkwMyZ1y+uW6sWTJhge3HdC1cvsGLPCn46+BPLDy5PtdpewewFqVfUkjw9UeQJwoLCMvHViIiI3B+UTImIZKHkZMtS5m+9Bf/+e+uyN15c1yCZraf+5KcDP7Hs4DI2ndxkM3Uvh28O6hatax19Kp67uFbaExERcTElUyIiWeSPP6B3b9i0yXK/cOHr14C62UMPwQsd4vj11Co6L/mOpQeWci72nE2Zh0MfplGJRjQq0YiqBari5aFDvIiISGbSX1oRkTvsxAnLSFTKxXWDguCddyyJlZ+fbdmLVy+y9MBSvvvnO96avIKr5qvWx4J8gqhftD6NSjTiyeJPUiB7gTv3IkRERETJlIjInRIbe30Ribi464tIDBsGYTecwnQs8hjf/fMd3+37jl+P/WpzwdxCOQrxTMlneKbkM9SMqKlrPYmIiGQhJVMiIpkkMRFmzIBvvrFs//MPnD5teezxxy2LSKRcXPdE1Am+2vMVi3YvYvO/m23aKRdajmYlm9GsVDPKh5XXuU8iIiJuQsmUiEgmWL0a+vSBXbts9xcubFlEokULOHXlXyb98TWLdi9i48mN1jImTNSMqEmzks14ptQzFM1V9M4GLyIiInbxyMonL1y4MCaTKdWte/fuAHTo0CHVY1WrVrVpIz4+nh49epAnTx4CAwNp2rQpJ0+ezIqXIyLCgQPQtCnUr29JpHLnhlGjYOFCWLIE1m89x+mCU3h8dk0KTChA7xW92XhyIyZMPB7xOFOemsKpfqdY32E9far1USIlIiLixrJ0ZGrLli0kJV0/F2DXrl3Ur1+fli1bWvc9+eSTzJo1y3rfx8f2/IDevXvzww8/sHDhQoKDg+nXrx9NmjRh27ZteHp6Zv6LEBEBIiPhgw9g8mQwmy0X0O3eHd57D/yzxbFk3xI+2zmP5R8vtzkHqkbBGrR+qDXPPvgs+bLly7oXICIiIg7L0mQqJCTE5v7IkSMpVqwYtWrVsu7z9fUlLCzti0tGRUUxY8YM5s2bR7169QCYP38+BQsWZPXq1TRs2DDzghcRwXIu1P/+B4MGwcWLln2NG8PoMcmc9/+VN3+bx1d7viI6Ptpap0q+KrQt25bnHnxOK/CJiIjcxdzmnKmEhATmz59P3759bU6uXrduHXnz5iVnzpzUqlWL4cOHkzdvXgC2bduG2WymQYMG1vL58uWjTJkybNiwId1kKj4+nvj4eOv96GjLlxyz2YzZbM6Ml2e3lOfP6jgkbeof93an++fKFWjUyJNNmywzpkuVMugz7B+OZJ9LoxVfcCzqmLVsRI4I2jzUhnZl21EyuGSqmO8H+vy4N/WPe1P/uDf1j3tztH8c6UeTYRiGU1G52Jdffknbtm05fvw4+fJZprosWrSIoKAgIiIiOHLkCIMGDSIxMZFt27bh6+vLggUL6Nixo01iBNCgQQOKFCnCZ599luZzDR48mCFDhqTav2DBAgICAlz/4kTknpOYaGLEiEf5889QArJH82jHjzlXYAG7Y6+vOBHgEUD1nNWpk7sOpQNL42HK0tNURURExA5Xr16lbdu2REVFkT179luWdZtkqmHDhvj4+PDDDz+kW+b06dNERESwcOFCWrRokW4yVb9+fYoVK8bUqVPTbCetkamCBQty4cKF275hmc1sNrNq1Srq16+Pt7d3lsYiqal/3Nud6p+YGOjRw5PPV+3G85FpBFT9nCuJlwHwMHnQsGhDXij7Ak1KNMHf2z/T4rjb6PPj3tQ/7k39497UP+7N0f6Jjo4mT548diVTbjHN79ixY6xevZpvv/32luXCw8OJiIjgwIEDAISFhZGQkMDly5fJlSuXtdy5c+eoXr16uu34+vri6+ubar+3t7fbfADcKRZJTf3j3jKzf2bOj6HvjEVEFf8fdNtEEnAl0XIx3c4VOtOpQiedB3Ub+vy4N/WPe1P/uDf1j3uzt38c6UO3SKZmzZpF3rx5ady48S3LXbx4kRMnThAeHg5ApUqV8Pb2ZtWqVbRq1QqwjF7t2rWL0aNHZ3rcInL/2H9xP6/NnMLay7Oh9hUAPE1eNCv1DF0qdqF+0fp4emgFURERkftJlidTycnJzJo1i5deegkvr+vhxMTEMHjwYJ599lnCw8M5evQob7/9Nnny5KF58+YA5MiRg86dO9OvXz+Cg4PJnTs3/fv3p2zZstbV/UREnJVsJLPswDImb57MikMrLDt9IWdScd6o+zKdK71EaFBo1gYpIiIiWSbLk6nVq1dz/PhxOnXqZLPf09OTv//+m7lz5xIZGUl4eDh16tRh0aJFZMuWzVpuwoQJeHl50apVK+Li4qhbty6zZ8/WNaZExGmR1yKZuX0mH2/5mMOXD1t2GibY35j6OV5n2cf18fTQYhIiIiL3uyxPpho0aEBaa2D4+/uzYsWK29b38/Nj8uTJTJ48OTPCE5H7yL4L+5j4x0Tm7pzLVfNVADzic5K8rRNs6UajasX4bg54Ko8SERER3CCZEhHJahtPbGT0htF8/8/3GFj+uRMQU4ara3uQvLMd+fMGMvIjaNsWNCAlIiIiKZRMich9KdlI5sf9PzL699H8fuJ36/6CV5ty4ss+XD1aC39/E2++DW+8AYGBWRisiIiIuCUlUyJyX4lPjOfzvz9nzIYx/HPhHwB8PH0om/wie6b348SJ0gC0awcffggFC2ZltCIiIuLOlEyJyH0hNiGWqVunMm7jOE7HnAYgu292Xq3UlV3Te7Lsy3wAPPooTJwIVatmYbAiIiJyV1AyJSL3tJiEGD7Z8gljN4zl/NXzAOTPlp8+VfvwcqWXef+t7Cz7Enx8YPp0eOEFMJmyOGgRERG5KyiZEpF7UkxCDB9v/pixG8dy4eoFAIrlKka3sm+zc/4LDB/mw2AzxMRYys+dC61bZ2HAIiIictdRMiUi95S4pDhGbRjFxE0TuRh3EbAkUQOqDeL0ina897QXsbHXy3t6wujRSqRERETEcUqmROSeEJsQy4SNExi9ZzRXkq4AUCJ3Cd6p+S4++9oysKUXx45Zylaten1xiezZISQkCwMXERGRu5aSKRG5qyUkJTD9z+kMXT+Us7FnAUsS9V6t9yh+7Xn6v+7F7/+tfF6ggGUU6vnndV6UiIiIZJySKRG5KyUbySzctZBBawdx+PJhAIrmLErT7E3pUftDhg7x48U5lrIBATBgAPTvb9kWERERcQUlUyJyVzEMg+UHlzPw54HsOLsDgNDAUN6r9R6tir9Er9ePU/Z1X65etZR/8UUYMcIyKiUiIiLiSkqmROSusfPsTvqt7Mfqw6sBy3Wi3qz+Jr2r9ubKpUCqPWJw8KDlorvVqlmuF/XII1kYsIiIiNzTlEyJiNs7E3OGQWsGMfOvmSQbyfh4+tDjkR4MfGwgwQHBxMRA48Zw8KCJ3LnjmDTJm3btvHRelIiIiGQqJVMi4rbizHGM3ziekb+PJCbBckGoVg+1YmTdkRTJVQSACxcsU/n+/BNCQgyGDv2N1q1rK5ESERGRTKdkSkTcjmEYfLXnK/qv7M+J6BMAPJL/EcY3GE+NQjX+KwOTJ8N770FUFPj7w+LFSVy4cDUrQxcREZH7iEdWByAicqM95/dQb149Wn/dmhPRJyiYvSCft/icjZ03WhMpgPffh169LIlU+fLw88/wyCNG1gUuIiIi9x2NTImIW7gSf4Uh64cwadMkEpMT8fPy460ab/FmjTfx9/a3KTtjBnzwgWV7zBjo0wc8PcFszoLARURE5L6lZEpEspRhGHyx6wv6r+zP6ZjTADQt2ZSJDSdaz4tKERUFw4bBhAmW++++a7l2lIiIiEhWUDIlIlnmwMUDvPrjq6w9uhaA4rmLM+nJSTQq0cimXFISTJ8OgwbB+fOWfV26wNChdzpiERERkeuUTInIHZeQlMCY38fwwS8fEJ8Uj7+XP+/UfId+1fvh5+VnU3bfPmjVCnbutNwvVQrGj4ennsqCwEVERERuoGRKRO6ojSc28sqPr7Dr3C4AGhZryKeNP001pQ/gzBlo2BCOHYNcuWDIEHjtNfD2vtNRi4iIiKSmZEpE7oioa1G8/fPbfLr1UwwMQgJCmPjkRNqUaYMpjYtCXbkCTZpYEqkSJeDXXyE0NAsCFxEREUmHkikRyXTLDy6ny5Iu/HvlXwA6lO/A2PpjCQ4ITlU2ORkWLIC33oJ//4WQEFi2TImUiIiIuB8lUyKSaaKuRdFvZT9mbJ8BQLFcxZj29DSeKPJEmuU3boTevWHzZsv9woXhyy+hWLE7E6+IiIiII5RMiUimWHVoFZ2XdOZE9AlMmOj1aC+G1x1OgHdAqrLHj1tGor74wnI/KAjeeceSWPn5pSouIiIi4haUTImIS12Jv8Ibq97gs22fAVA0V1FmPTOLxyMeT7P8p59C375w7RqYTNCpk+VaUmFhdzJqEREREccpmRIRl/n12K+0/649RyOPAvB6ldcZWW8kgT6BaZb/4gvo1s2y/fjjMHEiVKhwZ2IVERERySglUyKSYeYkM0PXD2XEbyNINpIpnLMwM5vOpE6ROunWWb8eOnSwbPfqBRMmWEamRERERO4WSqZEJEMOXjpIu2/bsflfy6oRHcp34KMnPyKbb7Z061y5As8/DwkJ0KIFjBunREpERETuPkqmRMQphmEw+6/Z9FjWg1hzLDn9cvJZk89o9VCr29YdNsxyQd7ixWH+fPD0vAMBi4iIiLiYkikRcdjluMu88uMrfL3nawBqRdRiXvN5FMxR8LZ1DxywTOkDy09//8yMVERERCTzKJkSEYds/nczrb5qxbGoY3h5eDGszjD6V++Pp8fth5eSk+H118FshiefhMaN70DAIiIiIplEyZSI2MUwDCZtmsSbq97EnGymWK5iLHxuIZXzVba7jf79YeVK8PHRghMiIiJy91MyJSK3FXktkk7fd2LxP4sBeO7B55j+9HRy+OWwq75hwNix16f3zZ4NpUplUrAiIiIid4iSKRG5pa2nttLqq1YciTyCt4c34xuOp3uV7pjsHFb680/o2RN+/91yf+RIaNMmEwMWERERuUOUTIlImgzDYOrWqfRe0ZuEpASK5CzCly2/dGha3/r10KCBZQn0gAB47z14881MDFpERETkDlIyJSKpXEu8Rrel3Zj11ywAmpVqxqxnZpHTL6fdbezZA82aWRKpp56CadOgQIHMiVdEREQkKyiZEhEbJ6NP0mJRC7ac2oKHyYMP637IG9XfsHtaH8Dp09CoEURGQo0a8O234OeXeTGLiIiIZAUlUyJi9euxX3nuq+c4F3uOXH65WPTcIuoXq+9QGzEx0KQJHDsGJUrA998rkRIREZF7k5IpEcEwDD7Z8gm9V/QmMTmRcqHlWNx6MUVzFXWoncREaNXKsuhESAgsWwbBwZkUtIiIiEgWUzIlcp9LSErgtR9fs54f9XyZ55n+9HQCfQIdascwoFs3SwLl7w8//ADFimVGxCIiIiLuQcmUyH3swtULPPvls/xy7Bc8TB6MrjeavtX6OnR+VIqRI+F//7NciPeLL+DRRzMhYBERERE3omRK5D6178I+Gi9ozKHLh8jum51Fzy3iyeJPOtzOyZMwcCDMn2+5/9FH8MwzLg5WRERExA0pmRK5D605soZnv3yWyGuRFM5ZmB/b/MhDeR9yqI2rV2HMGBg1CuLiLPsGDYLXX8+EgEVERETcUIaTqfj4eHx9fV0Ri4jcAdP/nE7XpV1JTE6kWoFqfPf8d+QNzGt3fcOwTOMbMMAyKgXw2GMwcSJUqpQ5MYuIiIi4Iw9HK6xYsYIOHTpQrFgxvL29CQgIIFu2bNSqVYvhw4dz6tSpzIhTRDIo2UjmjZVv8PIPL5OYnEibMm1Y89IahxKp/fuhenVo186SSEVEwJdfwi+/KJESERGR+4/dydR3331HyZIleemll/Dw8OCNN97g22+/ZcWKFcyYMYNatWqxevVqihYtymuvvcb58+czM24RcUB8YjxtvmnD2I1jARhSewift/gcPy/7LwB1+jTUrw9//AGBgTB8OOzdCy1bWhadEBEREbnf2D3Nb8SIEYwdO5bGjRvj4ZE6B2vVqhUA//77L5MmTWLu3Ln069fPdZGKiFOirkXRfFFz1h5di7eHN7OemUW7cu0caiMmBho3huPHLRfiXbsW8ufPpIBFRERE7hJ2j0xt3ryZp59+Os1E6kb58+dn9OjRdiVShQsXxmQypbp1794dsFxIdPDgweTLlw9/f39q167N7t27bdqIj4+nR48e5MmTh8DAQJo2bcrJlBM5RO5zp66c4vHZj7P26FqCfIL4qd1PDiVShgHffQfly8P27dcvxKtESkRERMSJc6ZcacuWLZw+fdp6W7VqFQAtW7YEYPTo0YwfP54pU6awZcsWwsLCqF+/PleuXLG20bt3bxYvXszChQv57bffiImJoUmTJiQlJWXJaxJxF/su7KP6jOrsPLuT0MBQfunwC/WK1rO7vmFA587QvDkcOgTh4fDjj7oQr4iIiEgKh1bzGzp0qF3l3nvvPbvKhYSE2NwfOXIkxYoVo1atWhiGwcSJE3nnnXdo0aIFAHPmzCE0NJQFCxbw6quvEhUVxYwZM5g3bx716lm+JM6fP5+CBQuyevVqGjZs6MCrE7l3/HHyD5osaMLFuIuUyF2C5S8sp2iuog61MWgQzJoFnp7w1luWW1BQJgUsIiIichdyKJlKmXKXN29eDMNIs4zJZLI7mbpRQkIC8+fPp2/fvphMJg4fPsyZM2do0KCBtYyvry+1atViw4YNvPrqq2zbtg2z2WxTJl++fJQpU4YNGzakm0zFx8cTHx9vvR8dHQ2A2WzGbDY7HLsrpTx/Vschabsb+mfFoRW0+qYVcYlxVA6vzPetvickMMShmGfMMDF8uOXw8OmniXToYPm8u/HLBu6O/rmfqX/cm/rHval/3Jv6x7052j+O9KNDydSTTz7J2rVrqVy5Mp06daJx48Z4eno60kS6vvvuOyIjI+nQoQMAZ86cASA0NNSmXGhoKMeOHbOW8fHxIVeuXKnKpNRPy4cffsiQIUNS7V+5ciUBAQEZeRkukzLlUdyTu/bPhsgNjD82nkQjkYrZKtI/T3+2rN/iUBvbtuVl+PBHAWjd+h/y5t3HTz9lRrSZx137RyzUP+5N/ePe1D/uTf3j3uztn6tXr9rdpkPJ1E8//cTp06eZPXs2b7zxBq+++irt27enU6dOlCxZ0pGmUpkxYwZPPfUU+fLls9lvumnNZcMwUu272e3KDBw4kL59+1rvR0dHU7BgQRo0aED27NmdiN51zGYzq1aton79+nh7e2dpLJKaO/fPvL/nMXbHWJKNZFqWbsnsprPx9nQsxu3bYfx4L5KTTbz4YjLTpxfDZLp7TpJy5/4R9Y+7U/+4N/WPe1P/uDdH+ydl1po9HEqmAMLDwxk4cCADBw7kl19+YdasWVSpUoWyZcuyevVq/P39HW2SY8eOsXr1ar799lvrvrCwMMAy+hQeHm7df+7cOetoVVhYGAkJCVy+fNlmdOrcuXNUr1493efz9fXF19c31X5vb2+3+QC4UyySmrv1z6dbPqXbT90A6FS+E9Oenoanh/2jxjExMHIkjB0L8fFQrx5Mn+6Bj0+WrlHjNHfrH7Gl/nFv6h/3pv5xb+of92Zv/zjShxn6plSlShXq1KlD6dKl2b59u9PzRGfNmkXevHlp3LixdV+RIkUICwuzGY5LSEhg/fr11kSpUqVKeHt725Q5ffo0u3btumUyJXIvGfP7GGsi1fORnvyv6f8cSqTOn4dKlSwX4U1JpL7+Gnx8MitiERERkXuDwyNTABs3bmTmzJl8+eWXPPDAA3Ts2JG2bds6NUUuOTmZWbNm8dJLL+HldT0ck8lE7969GTFiBCVKlKBEiRKMGDGCgIAA2rZtC0COHDno3Lkz/fr1Izg4mNy5c9O/f3/Kli1rXd1P5F5lGAaD1w1m6C+WVTbfqfkOH9T54LbTYG8UFwdNm8L+/ZZrR02ZAs88Aw40ISIiInLfciiZGj16NLNmzeLixYu0a9eO3377jbJly2YogNWrV3P8+HE6deqU6rE333yTuLg4unXrxuXLl3n00UdZuXIl2bJls5aZMGECXl5etGrViri4OOrWrcvs2bNdtjCGiDsyDIM3V73J2I1jAfiw7oe89dhbDrWRlATt2sEff0CuXLBqFZQunRnRioiIiNybHEqm3nrrLQoVKkSrVq0wmUzMmjUrzXLjx4+3u80GDRrccpn1wYMHM3jw4HTr+/n5MXnyZCZPnmz3c4rczQzDYMDqAdZE6qMnP6LHoz0cbqdfP1i82DKd7/vvlUiJiIiIOMqhZOrxxx/HZDKxe/fudMs4MsVIRBxjGAYDfx7ImA1jAPik0Sd0rdLVwTZg/HiYNMlyf+5cqFnT1ZGKiIiI3PscSqbWrVuXSWGIyO0YhsE7a95h1O+jAJjy1BSHE6k9e6BvX1ixwnJ/9Gho3drVkYqIiIjcH+7OdY9F7jOGYTBo7SA+/O1DwDK1r/sj3e2uf/Ei9OgB5cpZEilvbxg6FPr3z6yIRURERO59didTI0eOJDY21q6ymzZtYunSpU4HJSK2Bq8bzPBfhwMwseFEh86R2r4dHnjAslJfUhI0a2YZoRo0SKv2iYiIiGSE3cnUnj17iIiIoGvXrixbtozz589bH0tMTGTnzp188sknVK9eneeff96pZdJFJLWh64dalz8f32A8var2srvusWPQqBFcugRlysDPP1sWnShePLOiFREREbl/2H3O1Ny5c9m5cycff/wx7dq1IyoqCk9PT3x9fbl69SoAFSpU4JVXXuGll17C19c304IWuV9M2DiB99e9D8C4BuPoU62P3XUvX7YkUmfOWBKp336DHDkyK1IRERGR+49DC1CUK1eOzz77jKlTp7Jz506OHj1KXFwcefLkoXz58uTJkyez4hS578zcPpO+K/sCMKzOMPpW62t33fh4aNHCMp0vf3746SclUiIiIiKu5lAylcJkMvHwww/z8MMPuzoeEQG+3vM1L//wMgD9q/Xn7Zpv213XMKBTJ1i3DrJlg6VLoWDBTApURERE5D6m1fxE3MyKgyto+01bko1kulTowuj6ox26ftu778KCBeDlBV9/Dfqfh4iIiEjmUDIl4kZ+P/47zRc1x5xsptVDrZjaZKpDidS0aTBihGX7f/+DBg0yKVARERERUTIl4i7+OvMXjRc0Ji4xjieLP8m85vPw9PC0u/7PP0PX/67hO3gwdOiQKWGKiIiIyH+UTIm4gUOXDtFwfkOi4qN4rNBjfNPqG3w8feyun5BgSaSSk6F9e3jvvUwMVkREREQAFyVT0dHRfPfdd+zdu9cVzYncV87Hnuepz5/iXOw5yoeV58c2PxLgHeBQG5MmwYEDEBoKkyfrYrwiIiIid4JTyVSrVq2YMmUKAHFxcVSuXJlWrVpRrlw5vvnmG5cGKHIvu2q+StOFTTlw6QCFcxZmWbtl5PBzbA3z06dhqOWavowcCbpetoiIiMid4VQy9csvv1CzZk0AFi9ejGEYREZG8tFHHzFs2DCXBihyr0pKTqLtN2354+Qf5PLLxbJ2ywgLCnOoDbPZcm5UTAw88ohlip+IiIiI3BlOJVNRUVHkzp0bgOXLl/Pss88SEBBA48aNOXDggEsDFLkXGYZBz2U9+X7f9/h6+rKkzRJK5SnlYBvw2muwciUEBMBnn4GHzoIUERERuWOc+upVsGBBNm7cSGxsLMuXL6fBf+svX758GT8/P5cGKHIvGrNhDJ9s/QQTJj5v8TmPFXrM4TaGDYOZMy0J1KJFUL686+MUERERkfR5OVOpd+/etGvXjqCgIAoVKkTt2rUBy/S/smXLujI+kXvOgr8XMGD1AAAmNJzAsw8+63Abc+ZcX7Hv44+hSRNXRigiIiIi9nAqmerWrRuPPPIIJ06coH79+nj8N7eoaNGiOmdK5BZ+OfYLHb7rAEDfqn3pVbWXw22sXg1duli2BwywTPUTERERkTvPqWQKoHLlypQrV44jR45QrFgxvLy8aNy4sStjE7mnHL58mBaLWmBONtPywZaMaTDG4TZ27oQWLSAxEZ5/HkaMyIRARURERMQuTp0zdfXqVTp37kxAQAAPPfQQx48fB6Bnz56MHDnSpQGK3AuirkXx9BdPczHuIlXyVWFOszl4mBz7+J08CY0awZUrUKsWzJ6tBSdEREREspJTX8UGDhzIjh07WLdunc2CE/Xq1WPRokUuC07kXpCUnESbb9qw5/we8mfLz3fPf4e/t79DbURHQ+PG8O+/ULo0LF4Mvr6ZFLCIiIiI2MWpaX7fffcdixYtomrVqphMJuv+Bx98kEOHDrksOJF7wRur3mDZwWX4e/mzpM0S8mXL51B9sxmee84yxS80FH76CXLlyqRgRURERMRuTo1MnT9/nrx586baHxsba5Ncidzvpv85nQl/TABgbvO5VAyv6HAbr78Oq1ZBYCAsXQqFC7s4SBERERFxilPJVJUqVVi6dKn1fkoC9b///Y9q1aq5JjKRu9z6o+vpurQrAENqD+G5B59zuI1ff4Vp08Bkgi+/hEqVXB2liIiIiDjLqWl+H374IU8++SR79uwhMTGRSZMmsXv3bjZu3Mj69etdHaPIXefw5cM8++WzJCYn8nyZ5xn0+CCH20hKgh49LNsvv2xZfEJERERE3IdTI1PVq1fn999/5+rVqxQrVoyVK1cSGhrKxo0bqaR/nct9LjYhlmYLm1lX7pvZdKZT01+nT4cdOyBnTtDl20RERETcj9PXmSpbtixz5sxxZSwidz3DMHjlx1f4+9zfhAaGsrj1YodX7gOIi4NB/w1mDR0KISEuDlREREREMsypkSlPT0/OnTuXav/Fixfx9PTMcFAid6uPNn3Egr8X4OXhxVctvyJ/9vxOtTN/Ppw/b1lsomtX18YoIiIiIq7hVDJlGEaa++Pj4/Hx8clQQCJ3q1+P/Ur/Vf0BGFt/LDUjajrVjmHAxImW7Z49wcvp8WMRERERyUwOfU376KOPAMvqfdOnTycoKMj6WFJSEr/88gulSpVybYQid4FTV07R8quWJCYn0rZsW3o+2tPptlatgj17ICgIOnVyYZAiIiIi4lIOJVMTJliul2MYBlOnTrWZ0ufj40PhwoWZOnWqayMUcXMJSQk89+VznI09S9m8ZZnWZFqGrreWMirVqRPkyOGaGEVERETE9RxKpo4cOQJAnTp1+Pbbb8mVK1emBCVyN+m7oi8bT24kh28Ovm39LYE+gU63NX06LFtmua5UyrLoIiIiIuKenDobY+3ata6OQ+SuNG/HPD7e8jEA81vMp3ju4k63tXw5vPaaZfvdd6G4802JiIiIyB1gdzLVt29fPvjgAwIDA+nbt+8ty44fPz7DgYm4uz3n9/Dqj68C8N7j79HkgSZOt3XiBLRqZblQ74svwpAhropSRERERDKL3cnU9u3bMZvN1u30ZORcEZG7xVXzVVp91Yq4xDjqF63P+7Xfz1B7b7wBV65AtWqWqX76GImIiIi4P7uTqRun9mman9zv+q7qy+7zuwkNDGVe83l4mJy6ygAA69fDokXg4QGffAK6uoCIiIjI3cH5b4A3OHbsGHv27CE5OdkVzYm4tV8u/8LMv2ZiwsTnLT4nNCjU6bYSEy3XkgJ45RUoX941MYqIiIhI5nMomZozZw4TU9Zt/s8rr7xC0aJFKVu2LGXKlOHEiROujE/ErRy4dIBPTnwCwLuPv0vdonUz1N7//gc7d0LOnPDBBy4IUERERETuGIeSqalTp5LjhgvfLF++nFmzZjF37ly2bNlCzpw5GaIz5+UeFZ8YT7vF7biWfI2aBWvyXq33MtTepUuWVfvAkkjlyeOCIEVERETkjnFoafT9+/dTuXJl6/3vv/+epk2b0q5dOwBGjBhBx44dXRuhiJt4Y9Ub/HX2L7J5ZmNus7l4eTh1ZQGr996zJFRlylxfEl1ERERE7h4OjUzFxcWRPXt26/0NGzbw+OOPW+8XLVqUM2fOuC46ETexeO9iJm+eDECviF7kz5Y/Q+3t3QuffmrZnjQJvDKWl4mIiIhIFnAomYqIiGDbtm0AXLhwgd27d/PYY49ZHz9z5ozNNECRe8GJqBN0WtIJgL5V+1I5e+Xb1Li9CRMgORmaNoUnnshwcyIiIiKSBRz6f3j79u3p3r07u3fvZs2aNZQqVYpKlSpZH9+wYQNlypRxeZAiWSXZSOal714i8lokVfJV4YNaH7BqxaoMtXnhAsybZ9l+4w0XBCkiIiIiWcKhZGrAgAFcvXqVb7/9lrCwML766iubx3///XfatGnj0gBFstLEPyay9uhaArwD+LzF53h7eme4zc8+g2vXoFIlqFHDBUGKiIiISJZwKJny8PDggw8+4IN01nC+ObkSuZv9ffZvBv48EIDxDcZTIrgEZrM5Q20mJMDHH1u2+/QBkymjUYqIiIhIVnHJRXtF7jXXEq/R7tt2JCQl0OSBJrxS6RWXtDtiBJw+DeHh0LKlS5oUERERkSyiZEokDe+ueZe/z/1NSEAI05+ejskFQ0hz5kDKZdiGDwcfnww3KSIiIiJZSMmUyE3WHlnL+I3jAZjRdAahQaEZbnP1aujSxbL91lugy7GJiIiI3P2yPJn6999/eeGFFwgODiYgIIDy5ctbl18H6NChAyaTyeZWtWpVmzbi4+Pp0aMHefLkITAwkKZNm3Ly5Mk7/VLkHhB5LZKXvnsJA4OXK77M0yWfznCbO3dCixaQmAht2lhGpURERETk7pelydTly5epUaMG3t7eLFu2jD179jBu3Dhy5sxpU+7JJ5/k9OnT1ttPP/1k83jv3r1ZvHgxCxcu5LfffiMmJoYmTZqQlJR0B1+N3Au6/9SdE9EnKJ67OOMbjs9weydPQqNGcOUK1KoFs2aBR5b/C0NEREREXMHu1fz69u1rd6Pjx9v3JXTUqFEULFiQWbNmWfcVLlw4VTlfX1/CwsLSbCMqKooZM2Ywb9486tWrB8D8+fMpWLAgq1evpmHDhnbHLfe3r3Z/xYK/F+Bp8mRe83kE+QRlqL2oKEsi9e+/ULo0LF4Mvr4uClZEREREspzdydT27dtt7m/bto2kpCRKliwJwP79+/H09LS5iO/tLFmyhIYNG9KyZUvWr19P/vz56datGy+//LJNuXXr1pE3b15y5sxJrVq1GD58OHnz5rXGYTabadCggbV8vnz5KFOmDBs2bEgzmYqPjyc+Pt56Pzo6GgCz2Zzhpa8zKuX5szqO+8352PN0W9oNgDerv0ml0Epp9oG9/WM2w7PPevL33x6EhRksWZJIUJBlv2QefX7cm/rHval/3Jv6x72pf9ybo/3jSD+aDMMwHA1o/PjxrFu3jjlz5pArVy7AMmWvY8eO1KxZk379+tnVjp+fH2AZ9WrZsiWbN2+md+/efPbZZ7Rv3x6ARYsWERQUREREBEeOHGHQoEEkJiaybds2fH19WbBgAR07drRJjgAaNGhAkSJF+Oyzz1I97+DBgxmSsqzaDRYsWEBAQIBD74XcG8YeHctvkb8R4RfB2AfG4u2RsYvzzp79IN99VwI/v0SGD/+NYsWiXBSpiIiIiGSmq1ev0rZtW6KiosiePfstyzqVTOXPn5+VK1fy0EMP2ezftWsXDRo04NSpU3a14+PjQ+XKldmwYYN1X8+ePdmyZQsbN25Ms87p06eJiIhg4cKFtGjRIt1kqn79+hQrVoypU6emaiOtkamCBQty4cKF275hmc1sNrNq1Srq16+Pt3fGvtCLfb7b9x2tvmmFp8mT3zv8TsXwiumWtad/9u6FSpW8SEw08dVXiTzzjMMfMXGSPj/uTf3j3tQ/7k39497UP+7N0f6Jjo4mT548diVTdk/zu/kJzp49myqZOnfuHFeuXLG7nfDwcB588EGbfaVLl+abb765ZZ2IiAgOHDgAQFhYGAkJCVy+fNk6SpYSS/Xq1dNsw9fXF980Tl7x9vZ2mw+AO8VyL7t49SI9lvcA4M0ab/JooUftqpde/xgGvPGGZeW+pk3hueec+ohJBunz497UP+5N/ePe1D/uTf3j3uztH0f60Kl1xZo3b07Hjh35+uuvOXnyJCdPnuTrr7+mc+fOtGjRwu52atSowb59+2z27d+/n4iIiHTrXLx4kRMnThAeHg5ApUqV8Pb2ZtWqVdYyp0+fZteuXekmUyIpeq/ozdnYs5TOU5r3ar2X4faWLIGVKy0X5LVzHRYRERERuUs59W/zqVOn0r9/f1544QXrCVpeXl507tyZMWPG2N1Onz59qF69OiNGjKBVq1Zs3ryZadOmMW3aNABiYmIYPHgwzz77LOHh4Rw9epS3336bPHny0Lx5cwBy5MhB586d6devH8HBweTOnZv+/ftTtmxZ6+p+Imn5cf+PzN85Hw+TB7OemYWfl1+G2tu7Fzp0sGz37QvFimU8RhERERFxX04lUwEBAXzyySeMGTOGQ4cOYRgGxYsXJzAw0KF2qlSpwuLFixk4cCBDhw6lSJEiTJw4kXbt2gHg6enJ33//zdy5c4mMjCQ8PJw6deqwaNEismXLZm1nwoQJeHl50apVK+Li4qhbty6zZ8/G09PTmZcn94HIa5G8+uOrAPSt2pdHC9g3vS89Z85YlkGPjIRq1eC9jA9yiYiIiIiby9AJHSkX0X388cfx9/fHMAxMJpNDbTRp0oQmTZqk+Zi/vz8rVqy4bRt+fn5MnjyZyZMnO/Tccv/qu6Ivp66c4oHgBxhaZ2iG2oqNhSZN4OhRKF7cMtXP3981cYqIiIiI+3LqnKmLFy9St25dHnjgARo1asTp06cB6NKli93LootklRUHVzDrr1mYMDGz6Uz8vZ3PfBIToXVr2LYN8uSBZcssP0VERETk3udUMtWnTx+8vb05fvy4zXWZWrduzfLly10WnIirXTVf5bWlrwHQ45Ee1ChUw+m2DAN69IClS8HPD374wTIyJSIiIiL3B6em+a1cuZIVK1ZQoEABm/0lSpTg2LFjLglMJDN8sP4DjkYepWD2ggyvOzxDbY0eDVOngskECxZA1aouClJERERE7gpOjUzFxsbajEiluHDhQprXbxJxB7vO7WLsxrEATGk0hSCfIKfbWrTIxFtvWbYnTYL/FpcUERERkfuIU8nU448/zty5c633TSYTycnJjBkzhjp16rgsOBFXSTaSefXHV0lMTqRZqWY0LdnU6bYSEjzo0cOyUmTfvpapfiIiIiJy/3Fqmt+YMWOoXbs2W7duJSEhgTfffJPdu3dz6dIlfv/9d1fHKJJh0/+czoYTGwjyCeKjJz/KUFt//hlKZKSJ/PktU/1ERERE5P7k1MjUgw8+yM6dO3nkkUeoX78+sbGxtGjRgu3bt1NMVyoVN3M25iwDVg8AYFidYRTMUTBD7f3yS34A2rQBXcpMRERE5P7l9HWmwsLCGDJkiCtjEckUfVf2JfJaJBXDK/L6I69nqK3oaNi6NQyAtm1dEZ2IiIiI3K2cTqYiIyPZvHkz586dIzk52eax9u3bZzgwEVdYeWglC/5egIfJg2lNpuHpkbGhpO+/N5GQ4EnJkgblyzt2gWoRERERubc4lUz98MMPtGvXjtjYWLJly4bJdP1LpclkUjIlbiHOHEe3pd0AeL3K61TKVynDbS5aZJkZ27p1MiaT5viJiIiI3M+cOmeqX79+dOrUiStXrhAZGcnly5ett0uXLrk6RhGnDP91OIcuHyJ/tvx88MQHGW7vr79g9WrLPw5at06+dWERERERuec5lUz9+++/9OzZM81rTYm4g4OXDjJmwxgAPnrqI7L7Zs9Qe4YBPXtCcrKJGjX+pUQJV0QpIiIiInczp5Kphg0bsnXrVlfHIuIyfVb0ISEpgQbFGtC8VMavqPvll/Drr+Dvb9Chw24XRCgiIiIidzu7z5lasmSJdbtx48a88cYb7Nmzh7Jly+Lt7W1TtmlT5y+IKpJRPx34iR/3/4iXhxeTnpxkc06fM2JjoX9/y/YbbyQTEhLngihFRERE5G5ndzLVrFmzVPuGDh2aap/JZCIpKSlDQYk4Kz4xnt7LewPQ69FelMpTKsNtjhoFJ09CRAT065fM2rUZblJERERE7gF2J1M3L38u4o4mbZrEgUsHCA0M5b1a72W4vSNHYPRoy/a4ceDvn+EmRUREROQe4dQ5UyLu6NSVU3zwi2XVvlH1RmV40QmwTO+Lj4cnnoAWLTLcnIiIiIjcQ5xKpnr27MlHH32Uav+UKVPo3bt3RmMSccqA1QOISYihaoGqvPjwixlu7+ef4dtvwdMTJk2CDJ56JSIiIiL3GKeSqW+++YYaNWqk2l+9enW+/vrrDAcl4qjfj//O/J3zMWHioyc/wsOUsUFXsxl69bJsd+0KZcq4IEgRERERuac49Y3z4sWL5MiRI9X+7Nmzc+HChQwHJeKIpOQkeizrAUCnCp2okr9Khtv89FPYvRuCg2HIkAw3JyIiIiL3IKeSqeLFi7N8+fJU+5ctW0bRokUzHJSII6b/OZ3tZ7aTwzcHI+qOyHB7Fy/C++9btocNg9y5M9ykiIiIiNyD7F7N70Z9+/bl9ddf5/z58zzxxBMA/Pzzz4wbN46JEye6Mj6RW4q8Fsk7a94BYEjtIeQNzJvhNj/7DCIjoWxZePnlDDcnIiIiIvcop5KpTp06ER8fz/Dhw/ngA8vqaYULF+bTTz+lffv2Lg1Q5FZG/DqCi3EXKZ2nNN2qdMtwewkJ8PHHlu033rAsPiEiIiIikhankimArl270rVrV86fP4+/vz9BQUGujEvkto5GHmXSpkkAjKk/Bm9P7wy3+fXXcOoUhIVBq1YZbk5ERERE7mFOnTP1xBNPEBkZCUBISIg1kYqOjrZO+xPJbG///DYJSQk8UeQJGpVolOH2DAMmTLBsd+sGvr4ZblJERERE7mFOJVPr1q0jISEh1f5r167x66+/ZjgokdvZ/O9mvtj1BSZMjK0/FlMGLwJ1/rxlCfStWy1J1GuvuShQEREREblnOTTNb+fOndbtPXv2cObMGev9pKQkli9fTv78+V0XnUgaDMOg/8r+ALz48ItUCK+QofZ27YKaNS2LTgAMHAghIRkMUkRERETueQ4lU+XLl8dkMmEymdKczufv78/kyZNdFpxIWpbsW8Kvx3/Fz8uPYXWGZbi9oUMtiVSZMpbFJx5/POMxioiIiMi9z6Fk6siRIxiGQdGiRdm8eTMhN/z73sfHh7x58+Kp5c8kE5mTzLy5+k0A+lbtS8EcBTPU3rFj8M03lu0FCyzLoYuIiIiI2MOhZCoiIgKA5OTkTAlG5HambZvG/ov7CQkIYcBjAzLc3scfQ3Iy1K2rREpEREREHOP00uhgOW/q+PHjqRajaNq0aYaCEklL1LUoBq8fDFgu0JvdN3uG2ouJgf/9z7Ldu3fGYhMRERGR+49TydThw4dp3rw5f//9NyaTCcMwAKwrqiUlJbkuQpH/jPxtJBeuXqBUnlJ0qdglw+1Nm2Y5V6p4cWiU8ZXVRUREROQ+49TS6L169aJIkSKcPXuWgIAAdu/ezS+//ELlypVZt26di0MUgeNRx5nwh+UiUKPrjc7wBXrPn7csPAEwYAB4OPVJEBEREZH7mVMjUxs3bmTNmjWEhITg4eGBh4cHjz32GB9++CE9e/Zk+/btro5T7nND1w8lPimeWhG1aPJAkwy39847EBUFFSpAx44uCFBERERE7jtO/T8+KSmJoKAgAPLkycOpU6cAywIV+/btc110IsC+C/uY/ddsAD6s+2GGL9C7dStMn27Z/ugj0AKUIiIiIuIMp0amypQpw86dOylatCiPPvooo0ePxsfHh2nTplG0aFFXxyj3uffXvU+SkcTTDzxNtYLVMtTWqVPQogUYBrRpA4895qIgRUREROS+41Qy9e677xIbGwvAsGHDaNKkCTVr1iQ4OJhFixa5NEC5v/115i8W7bb8Tg17ImMX6L1yBZo0gRMn4IEHQNeXFhEREZGMcCqZatiwoXW7aNGi7Nmzh0uXLpErV64MT8ESudG7a94FoE2ZNpQLLZehtgYMgO3bISQEli2D4GBXRCgiIiIi96sMXWfqRrlz53ZVUyIA/H78d5YeWIqnyZMhtYdkqK0LF2DWLMv2ggWg2agiIiIiklEOJVOdOnWyq9zMmTOdCkYkhWEYvL3mbQA6VehEieASGWpv2jS4dg0qVYK6dV0RoYiIiIjc7xxKpmbPnk1ERAQVKlSwXqhXJDOsOryKX479gq+nL4MeH5ShthIS4OOPLdu9e4NmooqIiIiIKziUTL322mssXLiQw4cP06lTJ1544QVN7xOXMwyDt3+2jEp1q9KNgjkKZqi9r7+2rOIXFgatWrkiQhERERERB68z9cknn3D69GkGDBjADz/8QMGCBWnVqhUrVqzQSJW4zOJ/FrPt9DaCfIIY+NjADLVlNsMHH1i2u3cHHx8XBCgiIiIighMX7fX19aVNmzasWrWKPXv28NBDD9GtWzciIiKIiYnJjBjlPpKUnMSgtZZpfX2q9iEkMCRD7U2ZAv/8Y1nB7/XXXRGhiIiIiIiFw8nUjUwmEyaTCcMwSE5OdlVMch9b8PcC9pzfQy6/XPSr1i9DbZ07B4MHW7Y//BBy5sxweCIiIiIiVg4nU/Hx8XzxxRfUr1+fkiVL8vfffzNlyhSOHz9OUFBQZsQo94mk5CQ++MUyJ+/NGm+Swy9Hhtp7+22Ijras4NexoysiFBERERG5zqEFKLp168bChQspVKgQHTt2ZOHChQTryqfiIgt3LeTApQME+wfz+iMZm5O3dSukrND/0UfgkaExWBERERGR1BxKpqZOnUqhQoUoUqQI69evZ/369WmW+/bbb10SnNw/kpKTGPbrMAD6VutLkI/zo5yGAT17Wn6+8AJUr+6qKEVERERErnPo//Xt27enTp065MyZkxw5cqR7c8S///7LCy+8QHBwMAEBAZQvX55t27ZZHzcMg8GDB5MvXz78/f2pXbs2u3fvtmkjPj6eHj16kCdPHgIDA2natCknT550KA7JWl/v+Zp/LvxDLr9cGR6V+vxz2LgRAgNh1CgXBSgiIiIichOHL9rrSpcvX6ZGjRrUqVOHZcuWkTdvXg4dOkTOG1YKGD16NOPHj2f27Nk88MADDBs2jPr167Nv3z6yZcsGQO/evfnhhx+s0w779etHkyZN2LZtG56eni6NWVwv2Ui2nivVp2ofsvtmd7qtf/6xjEoBvPsu5MvnighFRERERFJzKJlytVGjRlGwYEFmzZpl3Ve4cGHrtmEYTJw4kXfeeYcWLVoAMGfOHEJDQ1mwYAGvvvoqUVFRzJgxg3nz5lGvXj0A5s+fT8GCBVm9ejUNGza8o69JHPft3m/ZfX43OXxz0OPRHk63c+YMPPUUXL4Mjz4Kffq4MEgRERERkZtkaTK1ZMkSGjZsSMuWLVm/fj358+enW7duvPzyywAcOXKEM2fO0KBBA2sdX19fatWqxYYNG3j11VfZtm0bZrPZpky+fPkoU6YMGzZsSDOZio+PJz4+3no/OjoaALPZjNlszqyXa5eU58/qOO6UZCOZIeuGAPB6ldcJ9Ax0+rW3bOnJ0aMeFCtm8O23iXh4WC7a60r3W//cbdQ/7k39497UP+5N/ePe1D/uzdH+caQfszSZOnz4MJ9++il9+/bl7bffZvPmzfTs2RNfX1/at2/PmTNnAAgNDbWpFxoayrFjxwA4c+YMPj4+5MqVK1WZlPo3+/DDDxkyZEiq/StXriQgIMAVLy3DVq1aldUh3BF/RP7BrvO78Pfwp3RkaX766Sen2jl6NBu//fYEXl7J9Ou3hi1bYl0cqa37pX/uVuof96b+cW/qH/em/nFv6h/3Zm//XL161e42szSZSk5OpnLlyowYMQKAChUqsHv3bj799FPat29vLWcymWzqGYaRat/NblVm4MCB9O3b13o/OjqaggUL0qBBA7Jnd/58HVcwm82sWrWK+vXr4+3tnaWxZDbDMHh/5vsA9Krai1a1Wznd1rvvWtZSeeop6NKllkviS8v91D93I/WPe1P/uDf1j3tT/7g39Y97c7R/Umat2cPuZKpixYr8/PPP5MqVi6FDh9K/f/8Mj+KEh4fz4IMP2uwrXbo033zzDQBhYWGAZfQpPDzcWubcuXPW0aqwsDASEhK4fPmyzejUuXPnqJ7Omti+vr74+vqm2u/t7e02HwB3iiWzLNm3hB1ndxDkE0T/Gv2dfr2GAV9+adl+4QUPvL0z/6JS90P/3M3UP+5N/ePe1D/uTf3j3tQ/7s3e/nGkD+3+1rl3715iYy1Tp4YMGUJMTIzdT5KeGjVqsG/fPpt9+/fvJyIiAoAiRYoQFhZmMySXkJDA+vXrrYlSpUqV8Pb2tilz+vRpdu3alW4yJVnPMAyGrh8KWM6VCg5w/uLPf/wBR49CUBA0aeKiAEVEREREbsPukany5cvTsWNHHnvsMQzDYOzYsQQFpX1h1ffee8+uNvv06UP16tUZMWIErVq1YvPmzUybNo1p06YBlul9vXv3ZsSIEZQoUYISJUowYsQIAgICaNu2LQA5cuSgc+fO9OvXj+DgYHLnzk3//v0pW7asdXU/cT8/HfiJbae3EeAdQN9qfW9f4RYWLLD8bNYM3OSUNxERERG5D9idTM2ePZv333+fH3/8EZPJxLJly/DySl3dZDLZnUxVqVKFxYsXM3DgQIYOHUqRIkWYOHEi7dq1s5Z58803iYuLo1u3bly+fJlHH32UlStXWq8xBTBhwgS8vLxo1aoVcXFx1K1bl9mzZ+saU27KMAyG/ToMgO5VuhMSGOJ0W7GxsGiRZfu//FpERERE5I6wO5kqWbIkCxcuBMDDw4Off/6ZvHnzZjiAJk2a0OQWc7NMJhODBw9m8ODB6Zbx8/Nj8uTJTJ48OcPxSOb79fiv/HHyD3w9fTM8KjVqFJw/DxERoIFIEREREbmTnFrNLzk52dVxyH1k5G8jAehQvgNhQWFOt3PkCIwebdkeNw50vqeIiIiI3ElOL41+6NAhJk6cyN69ezGZTJQuXZpevXpRrFgxV8Yn95idZ3ey7OAyPEwe9K/eP0Nt9e8P8fHwxBPQooWLAhQRERERsZNTa0ivWLGCBx98kM2bN1OuXDnKlCnDpk2beOihh3SxMrml0b9bhpKee/A5iucu7nQ7P/8M334Lnp4waRLc5rJjIiIiIiIu59TI1FtvvUWfPn0YOXJkqv0DBgygfv36LglO7i1HI4+ycJflvLsBNQY43Y7ZDL16Wba7dYMyZVwRnYiIiIiIY5wamdq7dy+dO3dOtb9Tp07s2bMnw0HJvWnchnEkGUnUK1qPiuEVnW7n009h924IDoYhQ1wYoIiIiIiIA5xKpkJCQvjrr79S7f/rr79cssKf3HvOx55nxvYZALxV4y3n2zkP779v2R4+HHLlckV0IiIiIiKOc2qa38svv8wrr7zC4cOHqV69OiaTid9++41Ro0bRr18/V8co94Apm6cQlxhHpfBKPFHkCafbefddiIyE8uWhSxeXhSciIiIi4jCnkqlBgwaRLVs2xo0bx8CBAwHIly8fgwcPpmfPni4NUO5+MQkxTN5suQbYgBoDMDm5WsT27fC//1m2P/rIsviEiIiIiEhWcSqZMplM9OnThz59+nDlyhUAsmXL5tLA5N4x/c/pXL52meK5i9OitHNrmBsG9Ohh+fn881CzpouDFBERERFxkNPXmUqhJEpuJSEpgfEbxwPwRvU38PRwbjjpgw/g998hIOD6hXpFRERERLKSUwtQiNjri7+/4ET0CUIDQ2n/cHun2pgz5/qiExMmQMGCLgxQRERERMRJSqYk0xiGwZgNYwDoU7UPfl5+DrexZcv1hSbeegteecWVEYqIiIiIOE/JlGSalYdWsvv8boJ8gnit8msO109Ohtdfh8REePZZy1LoIiIiIiLuwuFkymw2U6dOHfbv358Z8cg9ZOKmiQB0rtCZHH45HK4/dy5s3gzZssHkyeCh1F9ERERE3IjDX0+9vb3ZtWuX08tby/1h7/m9LD+4HBMmej7q+HL50dGWaX0AgwZBeLiLAxQRERERySCn/tffvn17ZsyY4epY5B4yadMkAJ4p9QxFcxV1uP4HH8DZs/DAA9Crl6ujExERERHJOKeWRk9ISGD69OmsWrWKypUrExgYaPP4+PHjXRKc3J0uXr3I3B1zAej9aG+H6+/bB5MsuRgTJoCPjwuDExERERFxEaeSqV27dlGxYkWAVOdOafqfTNs2jbjEOCqEVeDxiMcdqmsY0Ls3mM3QuDE0apQ5MYqIiIiIZJRTydTatWtdHYfcIxKSEpiyZQoAvav2dji5XroUli8Hb2/LqJSIiIiIiLvK0PpoBw8eZMWKFcTFxQGW6wrJ/e3rPV9z6sopwoLCaP1Qa4fqxsdDnz6W7T59oESJTAhQRERERMRFnEqmLl68SN26dXnggQdo1KgRp0+fBqBLly7069fPpQHK3cMwDCb8YRlO6la5G75evg7VnzgRDh6EsDB4991MCFBERERExIWcSqb69OmDt7c3x48fJyAgwLq/devWLF++3GXByd1lw4kNbD21FV9PX4cv0nvqFAwbZtkeOdJybSkREREREXfm1DlTK1euZMWKFRQoUMBmf4kSJTh27JhLApO7T8qo1AvlXiAkMMShusOGQUwMPPoovPhiZkQnIiIiIuJaTo1MxcbG2oxIpbhw4QK+vo5N7ZJ7w9HIoyz+ZzFgWXjCEZcuwZw5lu0RI8AjQ2fyiYiIiIjcGU59bX388ceZO3eu9b7JZCI5OZkxY8ZQp04dlwUnd4/JmyaTbCRTr2g9yuQt41Dd6dPh6lUoVw706yMiIiIidwunpvmNGTOG2rVrs3XrVhISEnjzzTfZvXs3ly5d4vfff3d1jOLmrsRfYfr26QD0qdrHobpmM0yebNnu0wd0mTIRERERuVs4NTL14IMPsnPnTh555BHq169PbGwsLVq0YPv27RQrVszVMYqbm79zPtHx0TwQ/ABPFn/SobqLF8PJk5A3Lzz/fCYFKCIiIiKSCZwamQIICwtjyJAhroxF7kKGYfDJ1k8Ay3LoHibH8vOJEy0/u3YFPz8XByciIiIikomcTqYuX77MjBkz2Lt3LyaTidKlS9OxY0dy587tyvjEzf12/Dd2nduFv5c/L5V/yaG6mzbBxo3g4wOvObaSuoiIiIhIlnNqmt/69espUqQIH330EZcvX+bSpUt89NFHFClShPXr17s6RnFjKaNS7cq2I6dfTofqTppk+dmmjeVCvSIiIiIidxOnRqa6d+9Oq1at+PTTT/H09AQgKSmJbt260b17d3bt2uXSIMU9nYk5wzd7vgGg+yPdHap78iR89ZVlu1cvV0cmIiIiIpL5nBqZOnToEP369bMmUgCenp707duXQ4cOuSw4cW/T/5yOOdlMtQLVKB9W3qG6U6ZAYiLUqgUVKmROfCIiIiIimcmpZKpixYrs3bs31f69e/dSvnz5jMYkd4HE5EQ+2/YZAN2qdHOo7rFj16f49e3r6shERERERO4Mu6f57dy507rds2dPevXqxcGDB6latSoAf/zxBx9//DEjR450fZTidn7c/yMno0+SJyAPzz34nEN1+/eHa9egdm14+unMiU9EREREJLPZnUyVL18ek8mEYRjWfW+++Waqcm3btqV169auiU7c1idbLAtPdK7QGT8v+9c0X7sWvv4aPDwso1O6SK+IiIiI3K3sTqaOHDmSmXHIXWT/xf2sOrwKEyZeq+zYmubvvGP52bUrlCuXCcGJiIiIiNwhdidTERERmRmH3EWmbp0KQOMHGlM4Z2G76x06ZLmulIcHvPtuJgUnIiIiInKHOH3R3n///Zfff/+dc+fOkZycbPNYz549MxyYuKer5qvM+msWAN0qO7bwxBdfWH7Wq6frSomIiIjI3c+pZGrWrFm89tpr+Pj4EBwcjOmGE19MJpOSqXvYF39/QeS1SIrkLELD4g3trmcY8Pnnlu02bTIpOBERERGRO8ipZOq9997jvffeY+DAgXh4OLW6utyFDMPg4y0fA9C1clc8TPb3/Y4d8M8/4OsLzZtnVoQiIiIiIneOU5nQ1atXef7555VI3Wc2/7uZ7We24+vpS8cKHR2qmzLFr0kTyJEjE4ITEREREbnDnMqGOnfuzFdffeXqWMTNTds2DYDWZVqTJyCP3fWio2H2bMu2pviJiIiIyL3CqWl+H374IU2aNGH58uWULVsWb29vm8fHjx/vkuDEfUTHR7Nw90IAXq74skN1hw2Dc+egeHFdpFdERERE7h1OJVMjRoxgxYoVlCxZEiDVAhRy71m4ayFXzVcplacUNQrWsLve/v0wcaJle8IE8PHJnPhERERERO40p5Kp8ePHM3PmTDp06ODicMRdTf9zOgBdKnRxKGHu1w/MZnjqKWjcOLOiExERERG585w6Z8rX15caNewfnZC7244zO9hyagveHt68+PCLdtfbuRN+/BE8PS2jUhq0FBEREZF7iVPJVK9evZg8ebKrYxE3NWP7DACeKfUMeQPz2l1v0iTLz2efhf9mhIqIiIiI3DOcmua3efNm1qxZw48//shDDz2UagGKb7/91iXBSdaLM8cxb+c8wDLFz17nzl2/SG/v3pkQmIiIiIhIFnNqZCpnzpy0aNGCWrVqkSdPHnLkyGFzs9fgwYMxmUw2t7CwMOvjHTp0SPV41apVbdqIj4+nR48e5MmTh8DAQJo2bcrJkyedeVmShsX/LCbyWiQROSKoX6y+3fWmToX4eHjkEbipy0RERERE7glOjUzNmjXLZQE89NBDrF692nrf09PT5vEnn3zS5vl8bloOrnfv3vzwww8sXLiQ4OBg+vXrR5MmTdi2bVuqtsRx//vzfwB0qtAJD5N9ubfZDJ98Ytnu3VvnSomIiIjIvcmpZMqlAXh52YxG3czX1zfdx6OiopgxYwbz5s2jXr16AMyfP5+CBQuyevVqGjZsmCkx3y8OXDzAuqPrMGGiY/mOdtdbvRrOnoW8eeG55zIxQBERERGRLORUMlWkSJFbLo99+PBhu9s6cOAA+fLlw9fXl0cffZQRI0ZQtGhR6+Pr1q0jb9685MyZk1q1ajF8+HDy5rUsgrBt2zbMZjMNGjSwls+XLx9lypRhw4YN6SZT8fHxxMfHW+9HR0cDYDabMZvNdseeGVKeP6vjAPjfNsuoVMNiDQkLCLM7pvnzPQEPnnsuCUjGDV6Ky7hT/0hq6h/3pv5xb+of96b+cW/qH/fmaP840o8mwzAMRwOalLJM2w1PuH37dpYvX84bb7zBW2+9ZVc7y5Yt4+rVqzzwwAOcPXuWYcOG8c8//7B7926Cg4NZtGgRQUFBREREcOTIEQYNGkRiYiLbtm3D19eXBQsW0LFjR5vECKBBgwYUKVKEzz77LM3nHTx4MEOGDEm1f8GCBQQEBNj5LtzbEo1EXt79MpcTLzOg8ACq5axmV734eE9eeulJrl3zYuTIXyhV6nImRyoiIiIi4jpXr16lbdu2REVFkT179luWdSqZSs/HH3/M1q1bnT6nKjY2lmLFivHmm2/St2/fVI+fPn2aiIgIFi5cSIsWLdJNpurXr0+xYsWYOnVqms+T1shUwYIFuXDhwm3fsMxmNptZtWoV9evXT7VK4p20ZP8Snvv6OfIG5OVIjyN4e9oXy1dfmWjXzovChQ327Uu8586Xcpf+kbSpf9yb+se9qX/cm/rHval/3Juj/RMdHU2ePHnsSqZces7UU089xcCBA51OpgIDAylbtiwHDhxI8/Hw8HAiIiKsj4eFhZGQkMDly5fJlSuXtdy5c+eoXr16us/j6+uLr69vqv3e3t5u8wHI6lhm75wNQIfyHQjws3+07ssvLT/btDHh4+Me72VmyOr+kVtT/7g39Y97U/+4N/WPe1P/uDd7+8eRPnRqafT0fP311+TOndvp+vHx8ezdu5fw8PA0H7948SInTpywPl6pUiW8vb1ZtWqVtczp06fZtWvXLZMpubWT0Sf56cBPAHSu2Nnuehcvwk+WarRtmxmRiYiIiIi4D6dGpipUqGCzAIVhGJw5c4bz58/zScqa2Hbo378/Tz/9NIUKFeLcuXMMGzaM6OhoXnrpJWJiYhg8eDDPPvss4eHhHD16lLfffps8efLQvHlzAHLkyEHnzp3p168fwcHB5M6dm/79+1O2bFnr6n7iuNl/zSbZSObxiMd5IPgBu+tNm2ZZFr1iRShTJhMDFBERERFxA04lU82aNbO57+HhQUhICLVr16ZUqVJ2t3Py5EnatGnDhQsXCAkJoWrVqvzxxx9EREQQFxfH33//zdy5c4mMjCQ8PJw6deqwaNEismXLZm1jwoQJeHl50apVK+Li4qhbty6zZ8/WNaacZBgGs/+aDUDnCvaPSiUkwJQplu3evV0fl4iIiIiIu3EqmXr//fdd8uQLFy5M9zF/f39WrFhx2zb8/PyYPHkykydPdklM97vfT/zOocuHCPIJ4tnSz9pd7+uv4dQpCAuDVq0yMUARERERETfh0nOm5O6XMirV8sGWBPoE2lXHMGDCBMt2t26QxtoeIiIiIiL3HIdGpjw8PG55sV4Ak8lEYmJihoKSrHHVfJUvd1uW4+tQvoPd9VauhK1bLUnUq69mUnAiIiIiIm7GoWRq8eLF6T62YcMGJk+ejAsvWyV32OK9i7mScIUiOYvwWKHH7KqTkAC9elm2u3aFvHkzMUARERERETfiUDL1zDPPpNr3zz//MHDgQH744QfatWvHBx984LLg5M6as2MOAC89/BIeJvtmgE6ZAvv2QUgIuOhUOhERERGRu4LT50ydOnWKl19+mXLlypGYmMhff/3FnDlzKFSokCvjkzvkRNQJVh9eDUD7h9vbVefsWRgyxLL94YeQM2cmBSciIiIi4oYcTqaioqIYMGAAxYsXZ/fu3fz888/88MMPlNGFhe5q83fOx8CgVkQtiuQqYledt9+G6GioVAk6dszkAEVERERE3IxD0/xGjx7NqFGjCAsL44svvkhz2p/cfQzDYPaO2YBlip89tmyBWbMs2x99BB5aF1JERETk/+3dd1gU59oG8HtpSxdUmkpRUQRFYhdM7IKiqFGjUXMiaizRGE0siV+ioilGY01MTMeSxHISNYoYUY9YghW7IiCCWDCoUXrf9/tjz85xYYEFhV3g/l0XF8vMOzPPzMMs+zDvvEN1TIWKqffffx9mZmZwd3fHxo0bsXHjRo3tduzY8VyCo+px6u4pxD2Kg7mxOUZ4jSi3vUIBvP22ckj0114D/PyqIUgiIiIiIj1ToWLq9ddfL3dodKp5VM+WGu45HFZyq3Lb//ILcPIkYGEBLFtWxcEREREREempChVTGzZsqKIwSFfyCvOw7eo2ANp18cvIAObNU75esABo1KgqoyMiIiIi0l+806WOC48Px5PcJ2hs1Rg93XqW2/6TT4D79wF3d2DWrCoPj4iIiIhIb7GYquN+vvwzAGCM9xgYGhiW2fbGDWDVKuXr1asBubyqoyMiIiIi0l8spuqwxzmPERYXBgB4re1r5bZfvx4oKAD8/YGBA6s6OiIiIiIi/cZiqg77PeZ35Bflw9veG20d2pbZtqgI2LpV+Xr6dIDjkBARERFRXcdiqg77+ZKyi99Y77Hltj12DLh3D7C1Bfr3r+rIiIiIiIj0H4upOio5LRlHbh0BoLxfqjy//qr8PmIEYGJSlZEREREREdUMLKbqqF8vK6ujnm494VzPucy2eXnAb78pX48eXdWRERERERHVDCym6iAhhNTF7zXv8gee2L8fePxY+Uyp7t2rOjoiIiIiopqBxVQddOnvS7j64CrkhnIM9xpebvtvvlF+Hz0aMCx79HQiIiIiojqDxVQdpLoqFeQRBBtTmzLbXr8O7NunHL3vzTerITgiIiIiohqCxVQdU6Qowq9XlPdLaTOK3xdfKL8PHgw0b16VkRERERER1SwspuqYY8nHcC/jHmxMbTDAfUCZbf/5B9i4Ufl61qyqj42IiIiIqCZhMVXHbL2ifPLusFbDIDeSl9n2hx+A7GzAxwfo0aM6oiMiIiIiqjlYTNUhBUUF+O2acozz0d5lj3FeUAB8+aXy9axZynumiIiIiIjof1hM1SGHEg/hUc4j2FvYo6dbzzLb7twJ3LkD2NsDr75aPfEREREREdUkLKbqkC1XtgAAXvF6BUYGRmW2XbNG+X3aNMDUtIoDIyIiIiKqgVhM1RG5hbnYGbMTADC6Tdld/E6dAk6cAExMgKlTqyM6IiIiIqKah8VUHbEvfh8y8jPgbO0MX2ffMtuqHtI7Zgzg4FANwRERERER1UAspuoIVRe/Ua1HwUBWetqFAA4eVL4eM6Y6IiMiIiIiqplYTNUBGXkZCIsLA1D+KH43byoHnjA2Bvz8qiM6IiIiIqKaicVUHbAnbg9yCnPQon4LtHNsV2bbyEjl986dAQuLqo+NiIiIiKimYjFVB6i6+L3a5lXIynlglKqY6tmzamMiIiIiIqrpWEzVco9zHmP/jf0AlMVUWYRgMUVEREREpC0WU7Xcruu7UKAogLe9N7zsvMps+/T9Ur5lD/hHRERERFTnsZiq5f597d8AlA/qLQ/vlyIiIiIi0h6LqVrscc5jHLypHOf8ldblF1OHDyu/s4sfEREREVH5WEzVYn/E/oECRQHa2LdBq4atymyblweEKUdPR79+1RAcEREREVENx2KqFvvt2m8AtOvit28fkJYGNG4MvPhiVUdGRERERFTzsZiqpZ7kPkFEQgQA7YqpX39Vfn/1VcDQsCojIyIiIiKqHVhM1VK7Y3ejQFGA1nat4WnnWWbbjAxgzx7l69GjqyE4IiIiIqJagMVULaUaxW+E14hy2+7aBeTmAi1bAu3bV3FgRERERES1BIupWigtN61SXfzGjAFksqqMjIiIiIio9mAxVQvtjt2N/KJ8eDb0RGv71mW2ffAAOHBA+Zpd/IiIiIiItMdiqhaqyIN6//1voKgI6NBB2c2PiIiIiIi0w2KqlknLTcP+hP0AtHtQ79Nd/IiIiIiISHsspmqZsLgw5Bflo1XDVmhtV3YXv1u3gL/+Ut4nNWpUNQVIRERERFRLsJiqZXZe3wkAGO45HLJyRpPYulX5vUcP5cN6iYiIiIhIeyymapHsgmzsu7EPADDMc1iZbYuKgI0bla/ZxY+IiIiIqOJYTNUiEQkRyC7Ihms9V7RzbFdm2++/B2JiABsbYET5j6IiIiIiIqJidFpMhYSEQCaTqX05OjpK84UQCAkJQaNGjWBmZoaePXvi6tWrauvIy8vDjBkz0LBhQ1hYWGDw4MG4c+dOde+KXtgRswMA8HKrl8vs4vfPP8CHHypfL1kC2NpWR3RERERERLWLzq9MtW7dGikpKdLX5cuXpXnLly/HqlWrsG7dOpw5cwaOjo7o168fMjIypDazZs3Czp07sXXrVhw/fhyZmZkYNGgQioqKdLE7OlNQVIA9cXsAlN/Fb9Ei4NEjoHVr4M03qyM6IiIiIqLax0jnARgZqV2NUhFCYM2aNfjggw8wbJiyONi4cSMcHBzw66+/YsqUKUhLS8OPP/6IzZs3o2/fvgCAn3/+Gc7Ozjh48CACAgKqdV90KTIpEk9yn8Dewh5+zn6ltsvIAL79Vvl67VrASOe/AURERERENZPOP0rHx8ejUaNGkMvl6NKlCz799FM0a9YMiYmJuH//Pvz9/aW2crkcPXr0QFRUFKZMmYLo6GgUFBSotWnUqBHatGmDqKioUoupvLw85OXlST+np6cDAAoKClBQUFBFe6od1fYrGsdvV38DAAS1CIKiSAFFkUJju337ZCgoMIK7u0D37oXQ8e7WOJXND1UP5ke/MT/6jfnRb8yPfmN+9FtF81ORPOq0mOrSpQs2bdqEli1b4u+//8bHH38MPz8/XL16Fffv3wcAODg4qC3j4OCAW7duAQDu378PExMT2Ba76cfBwUFaXpOlS5di8eLFJaZHRETA3Nz8WXfruThw4IDWbRVCgX9f/TcAoHF6Y4SHh5fa9rvvXgDgilatbiI8/MozRll3VSQ/VP2YH/3G/Og35ke/MT/6jfnRb9rmJzs7W+t16rSYGjBggPTa29sbvr6+aN68OTZu3IiuXbsCQImBFIQQ5T4/qbw28+fPx7vvviv9nJ6eDmdnZ/j7+8Pa2royu/LcFBQU4MCBA+jXrx+MjY21WubEnRN4fPExrOXWmPfKPJgYmmhsJwQwdaoy5dOmuaJvX5fnFnddUZn8UPVhfvQb86PfmB/9xvzoN+ZHv1U0P6pea9rQeTe/p1lYWMDb2xvx8fEYOnQoAOXVJycnJ6lNamqqdLXK0dER+fn5ePz4sdrVqdTUVPj5lX7fkFwuh1wuLzHd2NhYb06AisSyO343ACCoZRAsTC1KbXfuHHD/PmBhAfTubQQ92dUaSZ9+V6gk5ke/MT/6jfnRb8yPfmN+9Ju2+alIDnU+mt/T8vLyEBMTAycnJzRt2hSOjo5ql+Py8/Nx5MgRqVDq0KEDjI2N1dqkpKTgypUrZRZTtYkQQm1I9LLs3av83rcvoKGWJCIiIiKiCtDplak5c+YgKCgILi4uSE1Nxccff4z09HSMGzcOMpkMs2bNwqeffooWLVqgRYsW+PTTT2Fubo4xY8YAAOrVq4eJEydi9uzZaNCgAerXr485c+bA29tbGt2vtrv09yUkPkmEqZEp+rv3L7OtqpgaOLAaAiMiIiIiquV0WkzduXMHo0ePxsOHD2FnZ4euXbvi5MmTcHV1BQDMmzcPOTk5mDZtGh4/fowuXbogIiICVlZW0jpWr14NIyMjjBw5Ejk5OejTpw82bNgAQ0NDXe1Wtdp5fScAIKB5ACxMSu/id+kScPq08nVgYHVERkRERERUu+m0mNq6dWuZ82UyGUJCQhASElJqG1NTU3z55Zf48ssvn3N0NcMfsX8AAIa2GlpqGyGAt99Wfn/lFaBx42oKjoiIiIioFtOre6aoYm49uYUL9y/AQGaAgS1K77v3738DR44AZmbA559XY4BERERERLUYi6kabE/cHgCAn7Mf7CzsNLbJzQXmzFG+fu894L89KImIiIiI6BmxmKrBVF38hngMKbXNr78Ct28ru/bNnVtdkRERERER1X569Zwp0l5abhoikyIBlF5MCQGsWaN8PXMmYG5ePbERUdUqKipCQUGBrsOosIKCAhgZGSE3NxdFRUW6DoeKYX70G/Oj35gf/VY8P8bGxs9tsDoWUzXUvhv7UKgoRKuGrdCiQQuNbQ4fBi5fVj6k9403qjlAInruhBC4f/8+njx5outQKkUIAUdHR9y+fRsymUzX4VAxzI9+Y370G/Oj3zTlx8bGBo6Ojs+cLxZTNZQ2XfxUV6WCgwFb26qPiYiqlqqQsre3h7m5eY37g61QKJCZmQlLS0sYGLCXub5hfvQb86PfmB/99nR+ZDIZsrOzkZqaCgBwcnJ6pnWzmKqB8ovysS9+HwBgsMdgjW1u3gTCwpSv3367uiIjoqpSVFQkFVINGjTQdTiVolAokJ+fD1NTU37Y0EPMj35jfvQb86PfiufHzMwMAJCamgp7e/tn6vLHbNdAR28dRVpeGuwt7NGlcReNbX79VXnPVN++QMuW1RwgET13qnukzHnzIxER0TNT/T191nuQWUzVQH9cV3bxC2oZBEODkpW0EMAvvyhfjx1bnZERUVWraV37iIiI9NHz+nvKYqqGEUJgd9xuAKV38bt4Ebh+HZDLgZdfrs7oiIiIiIjqDhZTNczFvy8iOS0ZZkZm6Nusr8Y2W7Yovw8aBNSrV43BERHpCTc3N6xRjcKjZ4KDgzF06FBdh6EmJCQETk5OsLW1xa5duyq0bFJSEmQyGS5cuFAlsZXl0aNHsLe3R1JSUoWX7dSpE3bs2PH8gyKiOoXFVA2zO1Z5Vcq/uT/MjUveO6FQ/K+YGj26OiMjIipJJpNJX4aGhrC1tYWhoaE0LTg4uNzlK/rhniomJiYGixcvxvr163H9+nUMGDCgQss7OzsjJSUFbdq0AQBERkZCJpNVyxD+S5cuRVBQENzc3ACUXdj17NkTs2bNkn5esGAB3n//fSgUiiqPk4hqLxZTNcyeuD0AlPdLaRIVBdy+DVhbA4GB1RkZEVFJKSkp0tfq1athZWWFu3fvStPWrl2r6xBrBSEECgsLK7VsQkICAGDIkCFwcHCAXC6v0PKGhoZwdHSEkVH1DhCck5ODH3/8EW9U8kGKAwcORFpaGvbv3/+cIyOiuoTFVA1yP/M+zt47CwAY2HKgxja//qr8PmwY8N9RH4mIdMbR0VH6sra2hkwmU5v266+/onnz5jAxMYGHhwc2b94sLau62vDyyy9DJpNJPyckJEgf/C0tLdGpUyccPHiwQnGputqtWLECTk5OaNCgAaZPn642qpOmq2I2NjbYsGEDgP9dBdm+fTteeuklmJmZoVOnToiLi8OZM2fQsWNHWFpaon///njw4EGJGBYvXgx7e3tYW1tjypQpyM/Pl+YJIbB8+XI0a9YMZmZm8PHxwW+//SbNV1392b9/Pzp27Ai5XI5jx45p3NfLly+jd+/eMDMzQ4MGDTB58mRkZmYCUHbvCwpS/nPOyMgItqU8lPDx48cYO3Ys7OzsYGZmhhYtWiA0NFTtOFy4cAFJSUno1asXAMDW1lbt6mN5+1TWNjTZt28fjIyM4OvrW2qbshgaGiIwMBBbVN05iIgqgc+ZqkHC48MBAB0bdYSjpWOJ+QUFwPbtytfs4kdUh6xapfwqT/v2wO7d6tMGDwbOnSt/2XffVX49Rzt37sTMmTOxZs0a9O3bF2FhYRg/fjyaNGmCXr164cyZM7C3t0doaCj69+8vPQckMzMTgYGB+Pjjj2FqaoqNGzciKCgIsbGxcHFx0Xr7hw8fhpOTEw4fPowbN25g1KhReOGFFzBp0qQK7ceiRYuwZs0auLi4YMKECRg9ejSsra2xdu1amJubY+TIkVi4cCHWr18vLXPo0CGYmpri8OHDSEpKwvjx49GwYUN88sknAIAPP/wQO3bswPr169GiRQscPXoUr732Guzs7NCjRw9pPfPmzcOKFSvQrFkz2NjYlIgtOzsb/fv3R9euXXHmzBmkpqbijTfewFtvvYUNGzZgzpw5cHNzw/jx43H37l1kZGRo3McFCxbg2rVr2LdvHxo2bIgbN24gJyenRDtnZ2f8/vvvGD58OGJjY2FtbS09z6W8fdJ2GypHjx5Fx44dtcpRaTp37ozly5c/0zqIqG5jMVWDhMUpn8I7qMUgjfMPHgQePQLs7YHevaszMiLSqfR04O7d8ts5O5ec9uCBdsump1c8rnKsWLECwcHBmDZtGgDg3XffxcmTJ7FixQr06tULdnZ2AJRXgxwd//cPJB8fH/j4+Eg/f/zxx9i5cyd2796Nt956S+vt29raYt26dTA0NESrVq0wcOBAHDp0qMLF1Jw5cxAQEAAAmDlzJkaPHo1Dhw6hW7duAICJEydKV7NUTExM8NNPP8Hc3BytW7fGkiVLMHfuXHz00UfIycnBqlWr8J///Ee66tKsWTMcP34c3377rVoxtWTJEvTr16/U2H755Rfk5ORg06ZNsLCwAACsW7cOQUFBWLZsGRwcHKQizNHRsdTnmCUnJ6Ndu3ZS8aK6SlicoaEh6tevDwCwt7eX1p2VlVXuPmm7DZWkpCQ0atRI4zw/P78SD07NycnBCy+8oDatcePGSE5OhkKh4INWiahSWEzVEHmFeThw8wCA8rv4jRoFVHPXdSLSJWtroHHj8tv9tzgpMU2bZa2tKx5XOWJiYjB58mS1ad26dSv3PqqsrCwsXrwYYWFhuHfvHgoLC5GTk4Pk5OQKbb9169ZqT713cnLC5cuXK7QOAGjbtq302sHBAQDg7e2tNi01NVVtGR8fH7XCxdfXF5mZmbh9+zZSU1ORm5tbokjKz89Hu3bt1KaVd2UmJiYGPj4+UiEFKI+xQqFAbGysFG953nzzTQwfPhznzp2Dv78/hg4dCj8/P62WBYBr166Vu08V3UZOTg5MTU01ztu2bRs8PT3Vpo3V8OBFMzMzKBQK5OXlSVfQiIgqgh+5a4ijt44iMz8TjpaOaO/UvsT87Gxg507la3bxI6pjnqULXvFuf9Ws+EMThRDlPkhx7ty52L9/P1asWAF3d3eYmZlhxIgRavccacPY2LhELE+P7CaTySCEUGvz9D1Vmtajir34NG1HjHu67d69e9G4WKFbfHCIp4skTco6nhV5YOWAAQNw69Yt7N27FwcPHkSfPn0wffp0rFixQqvltdmnim6jYcOGePz4scZ5zs7OcHd3V5umqVj6559/YG5uzkKKiCqN17RriL3xewEAge6BMJCVTFtYGJCVBbi5AV27VnNwRESV4OnpiePHj6tNi4qKUruiYGxsjKKiIrU2x44dQ3BwMF5++WV4e3vD0dGxUs8ZKo+dnR1SUlKkn+Pj45Gdnf1c1n3x4kW1+4FOnjwJS0tLNGnSBF5eXpDL5UhOToa7u7val7Omrppl8PLywoULF5CVlSVN++uvv2BgYICWLVtWaF12dnYIDg7Gzz//jDVr1uC7777T2M7ExAQA1PKm7T5puw0AaNeuHa5du1ahfSjuypUraN++5D8oiYi0xStTNYAQQhoSfVBLzfdLqbr4jRkDVOCfjUREOjN37lyMHDkS7du3R58+fbBnzx7s2LFDbWQ+Nzc36f4juVwOW1tbuLu7Y8eOHQgKCoJMJsOCBQuq5FlBvXv3xrp169C1a1coFAq89957Ja5mVVZ+fj4mTpyIDz/8ELdu3cKiRYvw1ltvwcDAAFZWVpgzZw7eeecdKBQKvPjii0hPT0dUVBQsLS0xbtw4rbczduxYLFq0COPGjUNISAgePHiAGTNm4F//+pfWXfwAYOHChejQoQNat26NvLw8hIWFlehGp+Lq6gqZTIawsDAEBgbCzMxMq32qyDYAICAgAPPnz8fjx49LHYWwPMeOHYO/v3+lliUiAnhlqkaIfRSLm49vwsTQBH2b9S0x//FjIFw50B+7+BFRjTF06FCsXbsWn3/+OVq3bo1vv/0WoaGh6Nmzp9Rm5cqVOHDgAJydnaV7a1avXg1bW1v4+fkhKCgIAQEBVXJ1YeXKlXB2dkb37t0xZswYzJkzp9QBGiqqT58+aNGiBbp3746RI0ciKCgIISEh0vyPPvoICxcuxNKlS+Hp6YmAgADs2bMHTZs2rdB2zM3NsX//fvzzzz/o1KkTRowYgT59+mDdunUVWo+JiQnmz5+Ptm3bonv37jA0NMTWrVs1tm3cuDEWL16M999/Hw4ODtKgIOXtU0W2ASjvS+vYsSO2q4axraC7d+8iKioK48ePr9TyREQAIBPFO4TXQenp6ahXrx7S0tJgXQU3WVdEQUEBwsPDERgYKP0HdGXUSsw5MAf9mvVDxL8iSizz44/AG28A3t7ApUvVHXHdoik/pD9qc35yc3ORmJiIpk2blnrTvb5TKBRIT0+HtbU1R07TQzUxP+Hh4ZgzZw6uXLlS4Zjnzp2LtLS0MrsS6pOamJ+6hPnRb5ryU9bf1YrUBuzmVwOExf93SPRyuvjxqhQREdUlgYGBiI+Px927dyt8P5m9vT3mzJlTRZERUV3BYkrPPcl9gmO3lE+1H9ii5JDo9+4Bhw8rX7/6anVGRkREpHszZ86s1HJz5859zpEQUV3E65B6LiIhAkWiCK0atkLz+s1LzP/9d0AIwM8PqGBXeiIiIiIiegYspvRcWNx/u/i10NzFL0w5G8OGVVdEREREREQEsJjSawqhwJ83/gQABLYILDE/MxOIjFS+HliyByAREREREVUhFlN67FzKOTzIfgArEyt0c+lWYv6hQ0B+vrJ7n4eHDgIkIiIiIqrDWEzpsX3x+wAAfZr1gYmhSYn5e/cqvw8cyAf1EhERERFVNxZTemzfDWUxNcB9QIl5QvzvQb3s4kdEREREVP1YTOmpf3L+wam7pwBoLqYuXQLu3gXMzICePas5OCIiIiIiYjGlrw4mHoRCKNDarjWc65V8EKFqFL8+fYBiD20mIqJKCA4OxtChQ3UdRoVs2LABNjY2Vbb+yMhIyGQyPHnypMq2AQBJSUmQyWS4cOGCXqyHiEhbLKb01P6E/QCA/u79Nc7fulX5/eWXqysiIqLKCQ4Ohkwmg6GhIWxtbWFnZ4f+/fvj0qVLz20bISEheOGFF7RqJ5PJSnwdPHgQa9euxYYNG6S2PXv2xKxZs55bjFVh1KhRiIuLq7L1+/n5ISUlBfXq1auybVSWpuLX2dkZKSkpaNOmjW6CIqI6h8WUHlIIBSJuRgDQ3MXv8mXgyhXAxITPlyKimqF///64e/curl+/jgMHDsDIyAiDBml+fl5Va926NVJSUtS+unfvjnr16lXpVZ6qYGZmBnt7+ypbv4mJCRwdHSGrIaMcGRoawtHREUZGRroOhYjqCBZTeigxJxF/Z/0NC2MLvOjyYon5v/6q/D5wIFDD/u4T0XMkBJCVpZsvISoWq1wuh6OjIxwcHPDCCy/gvffew+3bt/HgwQOpzd27dzFq1CjY2tqiQYMGGDJkCJKSkqT5kZGR6Ny5MywsLGBjY4Nu3brh1q1b2LBhAxYvXoyLFy9KV5qevsJUnJGRERwdHdW+TExM1K50BAcH48iRI1i7dq20zqSkJKnb26FDh9CxY0eYm5vDz88PsbGxatvYs2cPOnToAFNTUzRr1gyLFy9GYWGhND8kJAQuLi6Qy+Vo1KgR3n77bWne119/jRYtWsDU1BQODg4YMWJEqftSvJuf6grd5s2b4ebmhnr16uHVV19FRkZGqeu4desWgoKC0KBBAzRu3Bje3t4I/+8IR8W7+am2FxYWBg8PD5ibm2PEiBHIysrCxo0b4ebmBltbW8yYMQNFRUXSNmQyGXbt2qW2XRsbm1LzVFRUhIkTJ6Jp06YwMzODh4cH1q5dq7afGzduxB9//CHlJzIyUmM3vyNHjqBz586Qy+VwcnLC+++/r5aLnj174u2338a8efNQv359ODo6IiQkpNTjRUT0NP7rRg+dyzgHQDkkutxIrjZPoQC2bFG+Hj26uiMjIn2SnQ1YWupm25mZgIVFZZfNxC+//AJ3d3c0aNAAAJCdnY1evXrhpZdewtGjR2FkZISPP/5Y6g5oYGCAoUOHYtKkSdiyZQvy8/Nx+vRpyGQyjBo1CleuXMGff/6JgwcPAsAzd0tbu3Yt4uLi0KZNGyxZsgQAYGdnJxV3H3zwAVauXAk7OztMnToVEyZMwF9//QUA2L9/P1577TV88cUXeOmll5CQkIDJkycDABYtWoTffvsNq1evxtatW9G6dWvcv38fFy9eBACcPXsWb7/9NjZv3gw/Pz/8888/OHbsWIViT0hIwK5duxAWFobHjx9j5MiR+Oyzz/DJJ59obD99+nTk5+cjMjISQggkJyfDsoxfrOzsbHzxxRfYunUrMjIyMGzYMAwbNgw2NjYIDw/HzZs3MXz4cLz44osYNWpUhWJXUSgUaNKkCbZv346GDRsiKioKkydPhpOTE0aOHIk5c+YgJiYG6enpCA0NBQDUr18f9+7dU1vP3bt3ERgYiODgYGzatAnXr1/HpEmTYGpqqlYwbdy4Ee+++y5OnTqFEydOIDg4GN26dUO/fv0qFT8R1R0spvTQuXRlMaWpi9+JE8CtW8oPUDrqIUNEVGFhYWGwtrYGAGRlZcHJyQlhYWEwMFB2kNi6dSsMDAzwww8/SF3KQkNDYWNjg8jISHTs2BFpaWkYNGgQmjdvDgDw9PSU1m9paSldcSrP5cuX1YoFLy8vnD59Wq1NvXr1YGJiAnNzc43r/OSTT9CjRw8AwPvvv4+BAwciNzcXpqam+OSTT/D+++9j3LhxAIBmzZrho48+wrx587Bo0SIkJyfD0dERffv2hbGxMVxcXNC5c2cAQHJyMiwsLDBo0CBYWVnB1dUV7dq10+4g/5dCocCGDRtgZWUFAPjXv/6FQ4cOlVpMJScnY/jw4fD29kZ6ejratm0r5UWTgoICrF+/XsrDiBEjsHnzZvz999+wtLSEl5cXevXqhcOHD1e6mDI2NsbixYuln5s2bYqoqChs374dI0eOhKWlJczMzJCXl1dmzr/++ms4Oztj3bp1kMlkaNWqFe7du4f33nsPCxculPazbdu2WLRoEQCgRYsWWLduHQ4dOsRiiojKxWJKzzzJfYLYLGV3EU2DT6iuSg0bphwWnYjqLnNz5RUiXW27Inr16oWvvvoKmZmZyM/PxzfffIMBAwbg9OnTcHV1RXR0NG7cuCEVACq5ublISEiAv78/goODERAQgH79+qFv374YOXIknJycKhy7h4cHdu/eLf0sl8vLaK1Z27ZtpdeqGFJTU+Hi4oLo6GicOXNGrXgpKipCbm4usrOz8corr2DNmjVo1qwZ+vfvj8DAQAQFBcHIyAj9+vWDq6urNK9///54+eWXYV6BA+7m5qZ2HJ2cnJCamlpq+7fffhtvvvkmIiIi8OKLL2L06NFlDuZhbm4uFVIA4ODgADc3N7UC1cHBocxtauObb77BDz/8gFu3biEnJwf5+flaDTLytJiYGPj6+qrd89WtWzdkZmbizp07cHFxAaCeT6D8Y0ZEpMJ7pvTMwcSDUEABjwYecLNxU5tXUABs3658PWZM9cdGRPpFJlN2tdPFV0XHI7CwsIC7uzuaNWuGzp0748cff0RWVha+//57AMqrKR06dMCFCxfUvuLi4jDmv294oaGhOHHiBPz8/LBt2za0bNkSJ0+erPBxMzExgbu7u/Tl7Fzy8RPlMTY2ll6rPqgrFArp++LFi9X24/Lly4iPj4epqSmcnZ0RGxuLr776CmZmZpg2bRq6d++OgoICWFlZ4dy5c9iyZQucnJywcOFC+Pj4VGho8qdjU8Wnik2TN954Azdv3sTYsWNx7do1dO7cGV9++WWF1l/eNmUyGUSxG+0KCgpK3cb27dvxzjvvYMKECYiIiMCFCxcwfvx45Ofnl7qMJkKIEoNnqOJ4enpFjxkRkQqLKT2jGsWvf/OSV6UOHQIePADs7JTPlyIiqqlkMhkMDAyQk5MDAGjfvj3i4+Nhb2+vVui4u7ur3f/Url07zJ8/H1FRUWjTpg1+/e+IPCYmJmoDHjwPlV1n+/btERsbW2I/3N3dpW5lZmZmGDx4ML744gtERkbixIkTuHz5MgDlABl9+/bF8uXLcenSJSQlJeE///nPc9234pydnTF16lRs3rwZ7777rlTkPi92dnZISUmRfo6Pj0d2dnap7Y8dOwY/Pz9MmzYN7dq1g7u7OxISEtTaaJMfLy8vREVFqRVyUVFRsLKyQuPGjSu5N0RE/8NiSo8IIRCRoCymApoHlJivGsVv5EiAo74SUU2Sl5eH+/fv4++//0ZMTAxmzJiBzMxMBAUFAQDGjh2Lhg0bYsiQITh27BgSExNx5MgRzJw5E3fu3EFiYiLmz5+PEydO4NatW4iIiEBcXJx035SbmxsSExNx4cIFPHz4EHl5ec8cs5ubG06dOoWkpCQ8fPhQ6ysVCxcuxKZNmxASEoKrV68iJiYG27Ztw4cffghAOSLejz/+iCtXruDmzZvYvHkzzMzM4OrqirCwMHzxxRe4cOECbt26hU2bNkGhUMDDw+OZ96c0s2bNwv79+5GYmIiLFy/i8OHDavejPQ+9e/fGunXrcO7cOZw9exZTp04tcTXoae7u7jh79iz279+PuLg4LFiwAGfOnFFr4+bmhkuXLiE2NhYPHz7UeKVr2rRpuH37NmbMmIHr16/jjz/+wKJFi/Duu++WeV8YEZG2+E6iR7IKstDfvT8ayRvhRWf1IdFzcoCdO5Wv2cWPiGqaP//8E40bN0arVq3g6+uLM2fO4N///jd69uwJQHkfztGjR+Hi4oJhw4bB09MTEyZMQE5ODqytrWFubo7r169j+PDhaNmyJSZPnoy33noLU6ZMAQAMHz4c/fv3R69evWBnZ4ctqhtMn8GcOXNgaGgILy8v2NnZITk5WavlAgICEBYWhgMHDqBTp07o2rUrVq1aBVdXVwDKIcG///57dOvWDW3btsWhQ4ewZ88eNGjQADY2NtixYwd69+4NT09PfPPNN9iyZQtat279zPtTmqKiIkyfPh2tW7fGiBEj0LJlS3z99dfPdRsrV66Es7MzunfvjjFjxmDOnDll3gc2depUDBs2DKNGjUKXLl3w6NEjTJs2Ta3NpEmT4OHhgY4dO8LOzk4aTfFpjRs3Rnh4OE6fPg0fHx9MnToVEydOlApbIqJnJRPFOzHXQenp6ahXrx7S0tKk0aZ0paCgAOHh4QgMDFT7r92//628IuXmBty8WfH7Fej5KC0/pB9qc35yc3ORmJiIpk2bwtTUVNfhVIpCoUB6ejqsra15VUAPMT/6jfnRb8yPftOUn7L+rlakNmC2a4ht25TfX32VhRQRERERkT5gMVUD5OcDEcpbqTBsmG5jISIiIiIiJRZTNcDx40BGBuDgAHTooOtoiIiIiIgIYDFVI+zdq/w+YADAbrhERERERPqBH81rAFUxFRio2ziIiIiIiOh/9KaYWrp0KWQyGWbNmiVNCw4OhkwmU/vq2rWr2nJ5eXmYMWMGGjZsCAsLCwwePBh37typ5uirTkICEBurfK6Uv7+uoyEiIiIiIhW9KKbOnDmD7777Dm3bti0xr3///khJSZG+wsPD1ebPmjULO3fuxNatW3H8+HFkZmZi0KBBlXpqvT5S7e6LLwL16uk2FiIiIiIi+h+dF1OZmZkYO3Ysvv/+e9ja2paYL5fL4ejoKH3Vr19fmpeWloYff/wRK1euRN++fdGuXTv8/PPPuHz5Mg4ePFidu1Fl9uxRfh84ULdxEBERERGROiNdBzB9+nQMHDgQffv2xccff1xifmRkJOzt7WFjY4MePXrgk08+gb29PQAgOjoaBQUF8H+q/1ujRo3Qpk0bREVFISAgQOM28/LykJeXJ/2cnp4OQPnAz4KCgue5exWm2n5BQQFSU4H//McIgAyBgQXQcWgE9fyQ/qnN+SkoKIAQAgqFAgqFQtfhVIrqGfGq/SD9wvzoN+ZHvzE/+k1TfhQKBYQQKCgogKGhoVr7inyO0GkxtXXrVpw7dw5nzpzROH/AgAF45ZVX4OrqisTERCxYsAC9e/dGdHQ05HI57t+/DxMTkxJXtBwcHHD//v1St7t06VIsXry4xPSIiAiYm5s/2049JwcOHEB4eFMUFbVFixaPER9/FPHxuo6KVA4cOKDrEKgMtTE/RkZGcHR0RGZmJvLz83UdzjPJyMiosnV/9tln2Lt3L44dOwYAmDZtGtLS0vDLL79U2TY1SU5Oho+PD44ePQpvb+9q3bY22rZtizfffBNvvvlmiXlVmZ/SZGdnY+rUqYiMjERGRgaSkpJQT4/7th8/fhxBQUFVEqetrS1+/vlnDCylS0pZ+dHF73tVHgtdbquy57Auzp+nlXVuV8agQYPg7e2NpUuXPpf1PYvi7+/l0ZTDp/OTn5+PnJwcHD16FIWFhWrLZmdnax2Xzoqp27dvY+bMmYiIiICpqanGNqNGjZJet2nTBh07doSrqyv27t2LYWU8vVYIAZlMVur8+fPn491335V+Tk9Ph7OzM/z9/WFtbV2JvXl+CgoKcODAAfTr1w/LlimPy5Qp1gjkUH564en8GBsb6zocKqY25yc3Nxe3b9+GpaVlqe+Z+mr8+PHYtGkTAGVR6OzsjJdffhkhISGwsLB4rtuSy+UwNDSU3su/+uorCCG0em9PSkpC8+bNER0djRdeeOGZ4rC0tAQAWFhY6PzviiYGBgYwNTVVi00IgYyMDFhZWZX5N7Qq/PLLLzh58iSOHz+Ohg0bwsHBodpi2LBhA9599138888/Wi+j+serlZVVleTXzMysxHq1yU/x3/fevXvDx8cHq1evfu4xqlTVsdAUe1Vta/z48Xjy5Al27twpTavoOVzd509pv7dnzpyBhYXFc7s4YGRkBBMTE714Hyv+/l6ep3NoZWVVIj+5ubkwMzND9+7dS/xdVfVa04bOiqno6Gikpqaiw1NPoS0qKsLRo0exbt065OXllbjk5uTkBFdXV8T/9xKNo6Mj8vPz8fjxY7WrU6mpqfDz8yt123K5HHK5vMR0Y2NjvfkAdueOMU6cMIBMBowebQhjY8PyF6Jqo0+/K1RSbcxPUVERZDIZDAwMYFDDHjgnk8nQv39//Pjjj/jnn39w4cIFTJ48GdnZ2Vi/fn2J9gUFBZXOn+qPpOoYaboXtzSqZZ7HMX6e66oqqt8nFVXXl+LTtfUseUtMTISnp6fGgaiq2tO5qswyVZFfTevVJj+aft8rm09tVeWxKB57VW1LNWL0s2zrWc8flaff68tS2u+tg4NDpbddmqr+HapIHID25+rTx0i17NP7opqu6TNDRd7LdHZk+vTpg8uXL+PChQvSV8eOHTF27FhcuHChRCEFAI8ePcLt27fh5OQEAOjQoQOMjY3VuvSkpKTgypUrZRZT+iw8XIYTJ5ywbJly/3v1Aho10nFQRKSXhBDIys/SyZeq/7m2VIMJNWnSBGPGjMHYsWOxa9cuAEBISAheeOEF/PTTT2jWrBnkcjmEEEhLS8PkyZNhb28Pa2tr9O7dGxcvXlRb72effQYHBwdYWVlh4sSJyM3NVZsfHByMoUOHSj8rFAosW7YM7u7ukMvlcHFxwSeffAIAaNq0KQCgXbt2kMlk6Nmzp7RcaGgoPD09YWpqilatWuHrr79W287p06fRrl07mJqaomPHjjh//ny5x8TNzQ2ffvopJkyYACsrK7i4uOC7776T5kdGRkImk+HJkyfStAsXLkAmkyEpKQmA8r/TNjY2CAsLg4eHB8zNzTFixAhkZWVh48aNcHNzg62tLWbMmFFilNuMjAyMGTMGlpaWaNSoEdatW6c2v7zjX1reNPn999/RunVryOVyuLm5YeXKldK8nj17YuXKlTh69GiJ4/60p7fn4uICS0tLvPnmmygqKsLy5cvh6OgIe3t7KZ8qq1atgre3NywsLODs7Ixp06YhMzNTOsbjx49HWlqa9IE6JCQEgPL+6nnz5sHZ2RlyuRwtWrTAjz/+qLbu6OhodOzYEebm5vDz80NsbKza/D179qBDhw4wNTVFs2bNsHjxYrXuRPHx8dJ/xb28vLTqovzbb7/B29sbZmZmaNCgAfr27YusrCwA6r/vwcHBOHLkCNauXSvtm+r35tq1awgMDISlpSUcHBzwr3/9Cw8fPtRqG6X566+/4OPjA1NTU3Tp0gWXL18GAGRlZcHa2hq//fZbiWNjYWGhsVtcWbEDz37cnxYSEoKNGzfijz/+kLYVGRkpzb958yZ69eoFc3Nz+Pj44MSJE2rLR0VFoXv37rCwsEDr1q0xc+ZMtWP1+PFjvP7667C1tYW5uTkGDBggXRQA1M9hLy8vyOVy3Lp1C/n5+Zg3bx4aN24MCwsLdOnSRYqrrN9bNzc3rFmzRlr/kydPMHnyZDg4OMDU1BRt2rRBWFgYAOXn6tGjR6NJkyYwNzeHt7c3tmzZovE4laay52VycjKGDBkCS0tLWFtbY+TIkfj777/V2pT3/g6U/95cLYQe6dGjh5g5c6YQQoiMjAwxe/ZsERUVJRITE8Xhw4eFr6+vaNy4sUhPT5eWmTp1qmjSpIk4ePCgOHfunOjdu7fw8fERhYWFWm83LS1NABBpaWnPe5cqzN5eIQAhff3wg64joqfl5+eLXbt2ifz8fF2HQhrU5vzk5OSIa9euiZycHGlaZl6mQAh08pWZl6l17OPGjRNDhgwRRUVF4vHjx6KoqEjMmDFDNGjQQAghxKJFi4SFhYUICAgQ586dExcvXhQKhUJ069ZNBAUFiTNnzoi4uDgxe/Zs0aBBA/Ho0SMhhBDbtm0TJiYm4vvvvxfXr18XH3zwgbCyshI+Pj4ltq0yb948YWtrKzZs2CBu3Lghjh07Jr7//nshhBCnT58WAMTBgwdFSkqKtJ3vvvtOODk5id9//13cvHlT/P7776J+/fpiw4YNyjxkZgo7OzsxatQoceXKFbFnzx7RrFkzAUCcP3++1OPi6uoq6tevL7766isRHx8vli5dKgwMDERMTIwQQojDhw8LAOLx48fSMufPnxcARGJiohBCiNDQUGFsbCz69esnzp07J44cOSIaNGgg/P39xciRI8XVq1fFnj17hImJidi6davatq2srMTSpUtFbGys+OKLL4ShoaHYsWOHKCoq0ur4l5a34s6ePSsMDAzEkiVLRGxsrAgNDRVmZmYiNDRUCCHEo0ePxKRJk4Svr6/acS9u0aJFwtLSUowYMUJcvXpV7N69W5iYmIiAgAAxY8YMcf36dfHTTz8JAOLEiRPScqtXrxb/+c9/xM2bN8WhQ4eEh4eHePPNN4UQQuTl5Yk1a9YIa2trkZKSIlJSUkRGRoYQQoiRI0cKZ2dnsWPHDpGQkCAOHjwoHUNVbrp06SIiIyPF1atXxUsvvST8/Pyk7f7555/C2tpabNiwQSQkJIiIiAjh5uYmQkJChBBCFBUViTZt2oiePXuK8+fPiyNHjoh27doJAGLnzp0l9r+oqEjExMQIIyMjsWrVKpGYmCguXbokvvrqKynmp3/fnzx5Inx9fcWkSZOkfSssLBT37t0TDRs2FPPnzxcxMTHi3Llzol+/fqJXr15CCCHu3btX5jaKUx0LT09PERERIS5duiQGDRok3NzcpPfiSZMmicDAQLXlXn75ZfH6669rXGdpsT+P415cRkaGGDlypOjfv7+0rby8PJGYmCgAiFatWomwsDARGxsrRowYIVxdXUVBQYEQQohLly4JS0tLsXr1anH9+nXx559/inbt2ong4GBp/YMHDxaenp7i6NGj4sKFCyIgIEC4u7tLx0Z1Dvv5+Ym//vpLXL9+XWRmZooxY8YIPz8/cfToUXHjxg3x+eefC7lcLuLi4sr8vXV1dRWrV6+Wfme6du0qWrduLSIiIkRCQoLYs2ePCA8PF0IIcefOHfH555+L8+fPi4SEBOl94OTJk1L8T38216Qy56VCoRDt2rUTL774ojh79qw4efKkaN++vejRo4e0Xm3e38t7b1bl8Pz582p/f1Q0/V1VqUhtoLfFVHZ2tvD39xd2dnbC2NhYuLi4iHHjxonk5GS1ZXJycsRbb70l6tevL8zMzMSgQYNKtCmPPhVTgYFFwtPzofDzKxKjRwuRlaXriOhptfnDem1Qm/NTm4qpEydOiAYNGoiRI0cKIZR/jI2NjUVqaqq0zKFDh4S1tbXIzc1VW1fz5s3Ft99+K4QQwtfXV0ydOlVtfpcuXUotptLT04VcLpeKp+Ke/sP7NGdnZ/Hrr7+qTfvoo4+Er6+vEEKIb7/9VtSvX19kPfWGvX79eq2Kqddee036WaFQCHt7e7F+/XohhPbFFABx48YNqc2UKVOEubm52offgIAAMWXKFLVt9+/fXy2ekSNHir59+4qioiKtjr+mvGkyZswY0a9fP7Vpc+fOFV5eXtLPM2fOVPsgpcmiRYuEubm52j9UAwIChJubm9oHJA8PD7F06dJS17N9+3apkBdCeQzr1aun1iY2NlYAEAcOHNC4DlVuDh48KE3bu3evACCdoy+99JL49NNP1ZbbvHmzcHJyEkIIsX//fmFoaChu374tzd+3b1+ZxVRkZKQAIJKSkjTGVfyfB5o+CC9YsED4+/urTbt9+7YAIGJjY0V0dHSZ2yhOdSyeLtYfPXokzMzMxLZt24QQQpw6dUoYGhqKu3fvCiGEePDggTA2NhaRkZGlrldT7M/juGtS/LgJ8b/3gx+e+q/21atXBQDpHx7/+te/xOTJk4UQQnp/O3LkiDAwMBA5OTkiLi5OABB//fWXtI6HDx8KMzMzsX37diHE/87hCxcuSG1u3LghZDKZdLxU+vTpI+bPny8tV/z3Vgj1Ymr//v3CwMBAxMbGlrrvxQUGBorZs2dLP2tTTFX0vIyIiBCGhoZqn9dVx/b06dNCCO3e38t7b66uYkrnQ6M/7enLqmZmZti/f3+5y5iamuLLL7/El19+WYWRVZ9du4oQHn4cgYGBMDbWff9UItJf5sbmyJyfqbNtV0RYWBisra1RWFiIgoICDBkyRO1929XVFXZ2dtLP0dHRyMzMRIMGDdTWk5OTg4SEBABATEwMpk6dqjbf19cXhw8f1hhDTEwM8vLy0KdPH63jfvDgAW7fvo2JEydi0qRJ0vTCwkJpNLGYmBj4+Pio3fDt6+ur1fqfvkdIJpPB0dERqampWscHKG/Kb968ufSzg4MD3NzcpJuvVdOKr7d4jL6+vtLN/tocf6Bk3jSJiYnBkCFD1KZ169YNa9asQVFRkcZu/aVxc3ODlZWV2n4ZGhqq3UNRfF8PHz6MTz/9FNeuXUN6ejoKCwuRm5uLrKysUgdAUd1u0KNHjzLjeTp/qlsQUlNT4eLigujoaJw5c0ate1NRURFyc3ORnZ2NmJgYuLi4oEmTJtL88n5v2rRpgz59+sDb2xsBAQHw9/fHiBEjKnRvYHR0NA4fPqz2+6GSkJAAf3//Sm3j6djr168PDw8PxMTEAAA6d+6M1q1bY9OmTXj//fexefNmuLi4oHv37lrH/bRnOe4VHZihtG21atUK0dHRuHHjhtroieK/Q28nJiYiPj4eRkZG6NKlizS/QYMGascGAExMTNS2c+7cOQgh0LJlS7VY8vLySpyTZblw4QKaNGlSYj0qRUVF+Oyzz7Bt2zbcvXtXenRQRQcGquh5GRMTA2dnZzg7O0vzvby8YGNjg5iYGHTq1Knc93dt3puri14VU0REpD2ZTAYLk+c7Gl5V6dWrF7766ivk5ubCw8OjxCBAxf94KxQKODk5qf2TTcXGxqZSMZiZmVV4GdVN5d9//73aByIAUhEgKnj/2NOK3+Qsk8mkbao+iDy9fk3PPtG0jrLWWxbVTdraHn9tPnQJDSPsVvaYVXRfb926hcDAQEydOhUfffQR6tevj+PHj2PixIllPkdG29+Vp7f99LFTfV+8eLHG0YdNTU01HoPyRoEzNDTE/v37cfLkSURERODLL7/EBx98gFOnTkn3/JVHoVAgKCgIy5YtKzHPyckJhoaGOHDgAKKioiq9DU3788Ybb2DdunV4//33ERoaivHjx1d61LtnOe7Pe1tTpkzB22+/DYVCgczMTFhaWsLAwAAuLi6Ii4vTuM7i54SZmZnazwqFAoaGhoiOji7xzwZNRXBpyvs9XrlyJVavXo01a9ZI9xXOmjWrwo/fqOh5qek9oazpmmjz3lxdWEwREVGVs7CwgLu7O9LT07UaJal9+/a4f/8+jIyM4ObmprGNp6cnTp48iddff12advLkyVLX2aJFC5iZmeHQoUN44403Ssw3MTEBALWBGhwcHNC4cWPcvHkTY8eO1bheLy8vbN68GTk5OdKHl7Li0Jbqik9KSop0VeDChQvPvF6V4jGePHkSLVq0AKDd8deWl5cXjh8/rjYtKioKLVu2rPIPPWfPnkVhYSFWrlwpFafbt29Xa2NiYlJicA5vb28oFAocOXIEffv2rdS227dvj9jYWLi7u2uc7+XlheTkZNy7dw+N/jvSVPHBDTSRyWTo1q0bunXrhoULF8LV1RU7d+5Ue+SLiqZ9a9++PX7//Xe4ubnByEjzx8CKbEPl5MmTcHFxAaAcdCEuLg6tWrWS5r/22muYN28evvjiC1y9ehXjxo0rcz81xa6N8o77897W1atX4e7uDoVCgfT0dFhbW0u/a15eXigsLMSpU6ekgdEePXqEuLg4eHp6lrredu3aoaioCKmpqXjppZcqHXPbtm1x584dxMXFabw6dezYMQwZMgSvvfYaAGWBEh8fX2Zsz4Pqd//27dvS1alr164hLS1N2nZ57+/avDdXF/YjIyIivdO3b1/4+vpi6NCh2L9/P5KSkhAVFYUPP/wQZ8+eBQDMnDkTP/30E3766SfExcVh0aJFuHr1aqnrNDU1xXvvvYd58+Zh06ZNSEhIwMmTJ6UR2uzt7WFmZoY///wTf//9N9LS0gAoR6taunQp1q5di7i4OFy+fBmhoaFYtWoVAGDMmDEwMDDAxIkTce3aNYSHh2PFihXPfAzc3d3h7OyMkJAQxMXFYe/evWqj4D2rv/76C8uXL0dcXBy++uor/Pbbb1K3Gm2Ov7Zmz56NQ4cO4aOPPkJcXBw2btyIdevWYc6cOc9tX0rTvHlzFBYW4ssvv8TNmzexefNmfPPNN2pt3NzckJmZiUOHDuHhw4fIzs6Gm5sbxo0bhwkTJmDXrl1ITExEZGRkiUKsLAsXLsSmTZsQEhKCq1evIiYmBtu2bcOHH34IQHmMPTw88Prrr+PixYs4duwYPvjggzLXefbsWSxduhRnz55FcnIyduzYgQcPHpT64dfNzQ2nTp1CUlISHj58CIVCgenTp+Off/7B6NGjcfr0ady8eRMRERGYMGECioqKcOrUKXz66adab0NlyZIlOHToEK5cuYLg4GA0bNhQbSRNW1tbDBs2DHPnzoW/v79a90ZtY9dGece9tG1dunQJsbGxePjwYZlXLZ/23nvv4cSJE5g+fTouXLiAhIQE7N69GzNmzACg/AfOkCFDMGnSJBw/fhwXL17Ea6+9hsaNG5fo+vq0li1bYuzYsXj99dexY8cOJCYm4syZM1i2bBnCw8OlmIv/3hbXo0cPdO/eHcOHD8eBAweQmJiIffv24c8//wSgfI9RXYWMiYnBlClTcP/+fa32/Vn07dsXbdu2xdixY3Hu3DmcPn0ar7/+Onr06IGOHTsC0O79vbz35urCYoqIiPSOTCZDeHg4unfvjgkTJqBly5Z49dVXkZSUJD1HZdSoUVi4cCHee+89dOjQAbdu3cKbb75Z5noXLFiA2bNnY+HChfD09MSoUaOkfvxGRkb44osv8O2336JRo0bSh5033ngDP/zwAzZs2ABvb2/06NEDGzZskLo8WVpaYs+ePbh27RratWuHDz74QGMXqooyNjbGli1bcP36dfj4+GDZsmX4+OOPn3m9KrNnz0Z0dDTatWuHjz76CCtWrJDuJ9Pm+Gurffv22L59O7Zu3Yo2bdpg4cKFWLJkCYKDg5/bvpTmhRdewKpVq7Bs2TK0adMGv/zyC5YuXarWxs/PD1OnTsWoUaNgZ2eH5cuXAwDWr1+PESNGYNq0aWjVqhUmTZpU7vDgTwsICEBYWBgOHDiATp06oWvXrli1ahVcXV0BKLtx7ty5E3l5eejcuTPeeOONEsNHF2dlZYWjR48iMDAQLVu2xIcffoiVK1diwIABGtvPmTMHhoaG8PLygp2dHZKTk9GoUSP89ddfKCoqQkBAANq0aYOZM2eiXr16MDAwgLW1dYW2ofLZZ59h5syZ6NChA1JSUrB7927paq/KxIkTkZ+fjwkTJpR7/DTFro3yjrsmkyZNgoeHBzp27Ag7Ozv89ddfWm2rbdu2OHLkCOLj49GjRw/06NEDixYtku6tApRDd3fo0AGDBg2Cr68vhBAIDw8v9wp9aGgoXn/9dcyePRseHh4YPHgwTp06JV3JKe33trjff/8dnTp1wujRo+Hl5YV58+ZJV7QWLFiA9u3bIyAgAD179oSjo6NaAVxVZDIZdu3aBVtbW3Tv3h19+/ZFs2bNsG3bNqmNNu/v5b03VxeZeJbO3rVEeno66tWrh7S0NJ0/4bmgoADh4eH/HYCidj10tDZgfvRbbc5Pbm4uEhMT0bRp00r1+9cHmrrBkP5gfvRbbcjPL7/8gpkzZ+LevXslCq2arjbkpzbTlJ+y/q5WpDbgPVNEREREVGWys7ORmJiIpUuXYsqUKbWukKK6jaUzEREREVWZ5cuX44UXXoCDgwPmz5+v63CInisWU0RERERUZUJCQlBQUIBDhw5VaGhvopqAxRQREREREVElsJgiIqpBOGYQERHRs3tef09ZTBER1QCq0Qk1PUuEiIiIKkb19/RZR//laH5ERDWAoaEhbGxspGcimZubQyaT6TiqilEoFMjPz0dubi6HDtZDzI9+Y370G/Oj357Oj0wmQ3Z2NlJTU2FjYwNDQ8NnWjeLKSKiGsLR0REApIKqphFCICcnB2ZmZjWuEKwLmB/9xvzoN+ZHv2nKj42NjfR39VmwmCIiqiFkMhmcnJxgb2+PgoICXYdTYQUFBTh69Ci6d+9e6x6qXBswP/qN+dFvzI9+K54fY2PjZ74ipcJiioiohjE0NHxufwSqk6GhIQoLC2FqasoPG3qI+dFvzI9+Y370W1Xmh506iYiIiIiIKoHFFBERERERUSWwmCIiIiIiIqoE3jOF/z20Kz09XceRKG+Qy87ORnp6Ovvc6iHmR78xP/qN+dFvzI9+Y370G/Oj3yqaH1VNoM2DfVlMAcjIyAAAODs76zgSIiIiIiLSBxkZGahXr16ZbWRCm5KrllMoFLh37x6srKx0/myA9PR0ODs74/bt27C2ttZpLFQS86PfmB/9xvzoN+ZHvzE/+o350W8VzY8QAhkZGWjUqFG5D2HmlSkABgYGaNKkia7DUGNtbc2TUY8xP/qN+dFvzI9+Y370G/Oj35gf/VaR/JR3RUqFA1AQERERERFVAospIiIiIiKiSmAxpWfkcjkWLVoEuVyu61BIA+ZHvzE/+o350W/Mj35jfvQb86PfqjI/HICCiIiIiIioEnhlioiIiIiIqBJYTBEREREREVUCiykiIiIiIqJKYDFFRERERERUCSym9MzXX3+Npk2bwtTUFB06dMCxY8d0HVKdExISAplMpvbl6OgozRdCICQkBI0aNYKZmRl69uyJq1ev6jDi2u3o0aMICgpCo0aNIJPJsGvXLrX52uQjLy8PM2bMQMOGDWFhYYHBgwfjzp071bgXtVd5+QkODi5xPnXt2lWtDfNTNZYuXYpOnTrBysoK9vb2GDp0KGJjY9Xa8PzRHW3yw/NHd9avX4+2bdtKD3n19fXFvn37pPk8d3SrvPxU57nDYkqPbNu2DbNmzcIHH3yA8+fP46WXXsKAAQOQnJys69DqnNatWyMlJUX6unz5sjRv+fLlWLVqFdatW4czZ87A0dER/fr1Q0ZGhg4jrr2ysrLg4+ODdevWaZyvTT5mzZqFnTt3YuvWrTh+/DgyMzMxaNAgFBUVVddu1Frl5QcA+vfvr3Y+hYeHq81nfqrGkSNHMH36dJw8eRIHDhxAYWEh/P39kZWVJbXh+aM72uQH4PmjK02aNMFnn32Gs2fP4uzZs+jduzeGDBkiFUw8d3SrvPwA1XjuCNIbnTt3FlOnTlWb1qpVK/H+++/rKKK6adGiRcLHx0fjPIVCIRwdHcVnn30mTcvNzRX16tUT33zzTTVFWHcBEDt37pR+1iYfT548EcbGxmLr1q1Sm7t37woDAwPx559/VlvsdUHx/AghxLhx48SQIUNKXYb5qT6pqakCgDhy5IgQguePvimeHyF4/ugbW1tb8cMPP/Dc0VOq/AhRvecOr0zpifz8fERHR8Pf319tur+/P6KionQUVd0VHx+PRo0aoWnTpnj11Vdx8+ZNAEBiYiLu37+vlie5XI4ePXowTzqgTT6io6NRUFCg1qZRo0Zo06YNc1ZNIiMjYW9vj5YtW2LSpElITU2V5jE/1SctLQ0AUL9+fQA8f/RN8fyo8PzRvaKiImzduhVZWVnw9fXluaNniudHpbrOHaNn3wV6Hh4+fIiioiI4ODioTXdwcMD9+/d1FFXd1KVLF2zatAktW7bE33//jY8//hh+fn64evWqlAtNebp165Yuwq3TtMnH/fv3YWJiAltb2xJteG5VvQEDBuCVV16Bq6srEhMTsWDBAvTu3RvR0dGQy+XMTzURQuDdd9/Fiy++iDZt2gDg+aNPNOUH4Pmja5cvX4avry9yc3NhaWmJnTt3wsvLS/qwzXNHt0rLD1C95w6LKT0jk8nUfhZClJhGVWvAgAHSa29vb/j6+qJ58+bYuHGjdPMi86RfKpMP5qx6jBo1Snrdpk0bdOzYEa6urti7dy+GDRtW6nLMz/P11ltv4dKlSzh+/HiJeTx/dK+0/PD80S0PDw9cuHABT548we+//45x48bhyJEj0nyeO7pVWn68vLyq9dxhNz890bBhQxgaGpaohlNTU0v854Oql4WFBby9vREfHy+N6sc86Qdt8uHo6Ij8/Hw8fvy41DZUfZycnODq6or4+HgAzE91mDFjBnbv3o3Dhw+jSZMm0nSeP/qhtPxowvOnepmYmMDd3R0dO3bE0qVL4ePjg7Vr1/Lc0ROl5UeTqjx3WEzpCRMTE3To0AEHDhxQm37gwAH4+fnpKCoClENnxsTEwMnJCU2bNoWjo6NanvLz83HkyBHmSQe0yUeHDh1gbGys1iYlJQVXrlxhznTg0aNHuH37NpycnAAwP1VJCIG33noLO3bswH/+8x80bdpUbT7PH90qLz+a8PzRLSEE8vLyeO7oKVV+NKnSc6dCw1VQldq6daswNjYWP/74o7h27ZqYNWuWsLCwEElJSboOrU6ZPXu2iIyMFDdv3hQnT54UgwYNElZWVlIePvvsM1GvXj2xY8cOcfnyZTF69Gjh5OQk0tPTdRx57ZSRkSHOnz8vzp8/LwCIVatWifPnz4tbt24JIbTLx9SpU0WTJk3EwYMHxblz50Tv3r2Fj4+PKCws1NVu1Rpl5ScjI0PMnj1bREVFicTERHH48GHh6+srGjduzPxUgzfffFPUq1dPREZGipSUFOkrOztbasPzR3fKyw/PH92aP3++OHr0qEhMTBSXLl0S//d//ycMDAxERESEEILnjq6VlZ/qPndYTOmZr776Sri6ugoTExPRvn17tSFSqXqMGjVKODk5CWNjY9GoUSMxbNgwcfXqVWm+QqEQixYtEo6OjkIul4vu3buLy5cv6zDi2u3w4cMCQImvcePGCSG0y0dOTo546623RP369YWZmZkYNGiQSE5O1sHe1D5l5Sc7O1v4+/sLOzs7YWxsLFxcXMS4ceNKHHvmp2poygsAERoaKrXh+aM75eWH549uTZgwQfo8ZmdnJ/r06SMVUkLw3NG1svJT3eeOTAghKnYti4iIiIiIiHjPFBERERERUSWwmCIiIiIiIqoEFlNERERERESVwGKKiIiIiIioElhMERERERERVQKLKSIiIiIiokpgMUVERERERFQJLKaIiIiIiIgqgcUUERGRFjZs2AAbG5tq2VZsbCwcHR2RkZGh9TJz5szB22+/XYVRERFRcSymiIjoubl//z5mzpwJd3d3mJqawsHBAS+++CK++eYbZGdn6zo8rbm5uWHNmjVq00aNGoW4uLhq2f4HH3yA6dOnw8rKSutl5s2bh9DQUCQmJlZhZERE9DQjXQdARES1w82bN9GtWzfY2Njg008/hbe3NwoLCxEXF4effvoJjRo1wuDBg3UWnxACRUVFMDKq3J8+MzMzmJmZPeeoSrpz5w52795dopgrj729Pfz9/fHNN99g2bJlVRMcERGp4ZUpIiJ6LqZNmwYjIyOcPXsWI0eOhKenJ7y9vTF8+HDs3bsXQUFBUtu0tDRMnjwZ9vb2sLa2Ru/evXHx4kVpfkhICF544QVs3rwZbm5uqFevHl599VW1bm9CCCxfvhzNmjWDmZkZfHx88Ntvv0nzIyMjIZPJsH//fnTs2BFyuRzHjh1DQkIChgwZAgcHB1haWqJTp044ePCgtFzPnj1x69YtvPPOO5DJZJDJZAA0d/Nbv349mjdvDhMTE3h4eGDz5s1q82UyGX744Qe8/PLLMDc3R4sWLbB79+4yj+P27dvh4+ODJk2aSNNU296/fz88PT1haWmJ/v37IyUlRW3ZwYMHY8uWLWWun4iInh8WU0RE9MwePXqEiIgITJ8+HRYWFhrbqIoSIQQGDhyI+/fvIzw8HNHR0Wjfvj369OmDf/75R2qfkJCAXbt2ISwsDGFhYThy5Ag+++wzaf6HH36I0NBQrF+/HlevXsU777yD1157DUeOHFHb7rx587B06VLExMSgbdu2yMzMRGBgIA4ePIjz588jICAAQUFBSE5OBgDs2LEDTZo0wZIlS5CSklKiYFHZuXMnZs6cidmzZ+PKlSuYMmUKxo8fj8OHD6u1W7x4MUaOHIlLly4hMDAQY8eOVdvP4o4ePYqOHTuWmJ6dnY0VK1Zg8+bNOHr0KJKTkzFnzhy1Np07d8bt27dx69atUtdPRETPkSAiInpGJ0+eFADEjh071KY3aNBAWFhYCAsLCzFv3jwhhBCHDh0S1tbWIjc3V61t8+bNxbfffiuEEGLRokXC3NxcpKenS/Pnzp0runTpIoQQIjMzU5iamoqoqCi1dUycOFGMHj1aCCHE4cOHBQCxa9eucuP38vISX375pfSzq6urWL16tVqb0NBQUa9ePelnPz8/MWnSJLU2r7zyiggMDJR+BiA+/PBD6efMzEwhk8nEvn37So3Fx8dHLFmypMS2AYgbN25I07766ivh4OCg1i4tLU0AEJGRkaXvLBERPTe8Z4qIiJ4b1dUnldOnT0OhUGDs2LHIy8sDAERHRyMzMxMNGjRQa5uTk4OEhATpZzc3N7UBGJycnJCamgoAuHbtGnJzc9GvXz+1deTn56Ndu3Zq04pf5cnKysLixYsRFhaGe/fuobCwEDk5OdKVKW3FxMRg8uTJatO6deuGtWvXqk1r27at9NrCwgJWVlbSfmiSk5MDU1PTEtPNzc3RvHlz6eenj4eK6p6umjTYBxFRTcZiioiInpm7uztkMhmuX7+uNr1Zs2YAoDZwg0KhgJOTEyIjI0us5+l7koyNjdXmyWQyKBQKaR0AsHfvXjRu3FitnVwuV/u5eLfDuXPnYv/+/VixYgXc3d1hZmaGESNGID8/X4s9VVe8eBRClJhW1n5o0rBhQzx+/LjEdE3rEUKoTVN1H7Szsys/eCIiemYspoiI6Jk1aNAA/fr1w7p16zBjxoxS75sCgPbt2+P+/fswMjKCm5tbpbbn5eUFuVyO5ORk9OjRo0LLHjt2DMHBwXj55ZcBAJmZmUhKSlJrY2JigqKiojLX4+npiePHj+P111+XpkVFRcHT07NC8RTXrl07XLt2rVLLXrlyBcbGxmjduvUzxUBERNphMUVERM/F119/jW7duqFjx44ICQlB27ZtYWBggDNnzuD69evo0KEDAKBv377w9fXF0KFDsWzZMnh4eODevXsIDw/H0KFDNQ6+UJyVlRXmzJmDd955BwqFAi+++CLS09MRFRUFS0tLjBs3rtRl3d3dsWPHDgQFBUEmk2HBggUlrhS5ubnh6NGjePXVVyGXy9GwYcMS65k7dy5GjhwpDZ6xZ88e7NixQ21kwMoICAjAG2+8gaKiIhgaGlZo2WPHjuGll16qliHciYiIxRQRET0nzZs3x/nz5/Hpp59i/vz5uHPnDuRyOby8vDBnzhxMmzYNgLJ7Wnh4OD744ANMmDABDx48gKOjI7p37w4HBwett/fRRx/B3t4eS5cuxc2bN2FjY4P27dvj//7v/8pcbvXq1ZgwYQL8/PzQsGFDvPfee0hPT1drs2TJEkyZMgXNmzdHXl5eie50ADB06FCsXbsWn3/+Od5++200bdoUoaGh6Nmzp9b7oElgYCCMjY1x8OBBBAQEVGjZLVu2YPHixc+0fSIi0p5MaPoLQURERDrz9ddf448//sD+/fu1Xmbv3r2YO3cuLl26VOkHExMRUcXw3ZaIiEjPTJ48GY8fP0ZGRobaiIZlycrKQmhoKAspIqJqxCtTRERERERElWCg6wCIiIiIiIhqIhZTRERERERElcBiioiIiIiIqBJYTBEREREREVUCiykiIiIiIqJKYDFFRERERERUCSymiIiIiIiIKoHFFBERERERUSWwmCIiIiIiIqqE/wd6fspQvSVnVQAAAABJRU5ErkJggg==",
      "text/plain": [
       "<Figure size 1000x600 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "## Program DuoMutationMax_VS_MatH_Model.py\n",
    "# This program compares the maximum number of touched sites \n",
    "# in a generation according to a simulation\n",
    "# with the prediction of the theoretical recursive model \n",
    "# of the number of matched sites at that generation.\n",
    "# The theoretical model implements the idea that \n",
    "# the fittest is the best at each step.\n",
    "# That is why the predictions are accelerated \n",
    "# compared to the empirical data, \n",
    "# which is based on a population of 200 monkeys.\n",
    "# Control parameters can be moved to make the predictions of the model \n",
    "# more or less accelerated.\n",
    "# We choose to move kappa, whose original value was 1.29.\n",
    "\n",
    "\n",
    "# SIMULATION\n",
    "\n",
    "# This part is based on the code of the program \n",
    "# Variability_in_the_number_of_touched_sites.py\n",
    "\n",
    "import datetime\n",
    "import random\n",
    "import matplotlib.pyplot as plt # Import matplotlib for plotting\n",
    "# target_sequence = 'Methinks it is like a weasel.'\n",
    "# alphabet = 'abcdefghijklmnopqrstuvwxyzABCDEFGHIJKLMNOPQRSTUVWXYZ .,'\n",
    "alphabet = '01' # Binary alphabet, binary strings\n",
    "length_of_target_sequence = 800\n",
    "target_sequence = '1'*length_of_target_sequence  #1111...1 (800 ones)\n",
    "population_size = 200\n",
    "include_clone_populationf4 = True\n",
    "include_mutate_allf4 = True\n",
    "include_crossover_allf4 = False\n",
    "mutation_rate = 0.01\n",
    "recombination_rate = 0\n",
    "# alphabet = 'abcdefghijklmnopqrstuvwxyzABCDEFGHIJKLMNOPQRSTUVWXYZ .,'\n",
    "# Boolean flag to print the generation, best chromosome and fitness.\n",
    "# This is the ancestral line of the solution.\n",
    "print_best_fitness = False\n",
    "\n",
    "\n",
    "\n",
    "\n",
    "def print_parametersf4():\n",
    "    print(f\"Lab: Simple Genetic Algorithm\")\n",
    "    print(f\"Purpose: solve an instance of the Shakespeare challenge\")\n",
    "    print(f\"Date of Experiment  = {datetime.datetime.now()}\")\n",
    "    print(f\"alphabet =  {alphabet}\")\n",
    "    print(f\"target_sequence = {target_sequence}\")\n",
    "    print(f\"length_of_target_sequence = {length_of_target_sequence}\")\n",
    "    print(f\"population_size = {population_size}\")\n",
    "    print(f\"include_clone_populationf4 = {include_clone_populationf4}\")\n",
    "    print(f\"include_mutate_allf4 = {include_mutate_allf4}\")\n",
    "    print(f\"include_crossover_allf4 = {include_crossover_allf4}\")\n",
    "    if include_mutate_allf4:\n",
    "        print(f\"mutation_rate = {mutation_rate}\")\n",
    "    if include_crossover_allf4:\n",
    "        print(f\"recombination_rate = {recombination_rate}\")\n",
    "    if include_clone_populationf4:\n",
    "        print(f\"print_best_fitness = {print_best_fitness}\")\n",
    "\n",
    "\n",
    "def create_populationf4(population_size, target_sequence, alphabet):\n",
    "    \"\"\"Creates a new population with random chromosomes.\"\"\"\n",
    "    # print(\"create_population8(population_size, target_sequence, alphabet)\")\n",
    "    population = []\n",
    "    for _ in range(population_size):\n",
    "        random_string = ''.join(random.choice(alphabet) for _ in range(len(target_sequence)))\n",
    "        population.append(random_string)\n",
    "    # print(\"initial population\")\n",
    "    # print(population)\n",
    "    return population\n",
    "\n",
    "def calculate_fitnessf4(chromosome, target_sequence):\n",
    "    \"\"\"Calculates the fitness of a chromosome based on its similarity to the target sequence.\"\"\"\n",
    "    #  print(\"\\n *calculate_fitness8(chromosome, target_sequence)\")\n",
    "    fitness = 0\n",
    "    for i in range(len(chromosome)):\n",
    "        if chromosome[i] == target_sequence[i]:\n",
    "            fitness += 1\n",
    "    # print(chromosome, \"  fitness: \", fitness)\n",
    "    return fitness\n",
    "\n",
    "def calculate_all_fitnessf4(population, target_sequence):\n",
    "    # print(\"\\n*calculate_all_fitness8(population, target_sequence)\")\n",
    "    \"\"\"Calculates the fitness of all chromosomes in the population.\"\"\"\n",
    "    fitness_scores = [calculate_fitnessf4(chromosome, target_sequence) for chromosome in population]\n",
    "    # print(\"fitness_scores: \", fitness_scores)\n",
    "    return fitness_scores\n",
    "\n",
    "def select_the_bestf4(population, target_sequence):\n",
    "    \"\"\"Selects the best chromosome for reproduction.\"\"\"\n",
    "    fitness_scores = calculate_all_fitnessf4(population, target_sequence)\n",
    "    best_fitness = max(fitness_scores)\n",
    "    best_chromosome_index = fitness_scores.index(best_fitness)\n",
    "    best_chromosome = population[best_chromosome_index]\n",
    "    # print(\"\\n*select_the_bestf4(population)\")\n",
    "    # print(\"best_fitness = \", best_fitness)\n",
    "    # print(\"The chro = \", best_chromosome )\n",
    "    return best_fitness, best_chromosome\n",
    "\n",
    "def clone_populationf4(best_chromosome, population_size):\n",
    "    \"\"\"Creates a new population by cloning the best chromosome.\"\"\"\n",
    "    return [best_chromosome] * population_size\n",
    "\n",
    "\n",
    "def mutatef4(chromosome, mutation_rate, alphabet):\n",
    "    \"\"\"Mutates a chromosome.\"\"\"\n",
    "    mutated_chromosome_list = list(chromosome)\n",
    "    for i in range(len(mutated_chromosome_list)):\n",
    "        if random.random() < mutation_rate:\n",
    "                mutated_chromosome_list[i] = random.choice(alphabet)\n",
    "    return \"\".join(mutated_chromosome_list)\n",
    "\n",
    "def mutate_allf4(population, mutation_rate, alphabet):\n",
    "    \"\"\"Mutates all chromosomes in the population.\"\"\"\n",
    "    mutated_population = []\n",
    "    for chromosome in population:\n",
    "        mutated_chromosome = mutatef4(chromosome, mutation_rate, alphabet)\n",
    "        mutated_population.append(mutated_chromosome)\n",
    "    return mutated_population\n",
    "\n",
    "def crossoverf4(parent1, parent2, target_sequence, recombination_rate):\n",
    "    \"\"\"Performs crossover between two parent chromosomes.\"\"\"\n",
    "    if random.random() < recombination_rate:\n",
    "        crossover_point = random.randint(0, len(target_sequence))\n",
    "        return parent1[:crossover_point] + parent2[crossover_point:]\n",
    "    else:\n",
    "        return parent1\n",
    "\n",
    "def crossover_allf4(population, target_sequence, recombination_rate):\n",
    "    \"\"\"Performs crossover on all chromosomes in the population.\"\"\"\n",
    "    recombinant_population = []\n",
    "    for i in range(len(population)):\n",
    "        parent1 =  population[i]\n",
    "        parent2 = random.choice(population)\n",
    "        child = crossoverf4(parent1, parent2, target_sequence, recombination_rate)\n",
    "        recombinant_population.append(child)\n",
    "    return recombinant_population\n",
    "\n",
    "\n",
    "\n",
    "def run_one_generationf4(population, target_sequence, mutation_rate, recombination_rate, alphabet):\n",
    "    \"\"\"Runs one generation of the genetic algorithm.\"\"\"\n",
    "    # Calculate fitness scores for the current population\n",
    "    best_fitness, best_chromosome  = select_the_bestf4(population, target_sequence)\n",
    "    # print(f\" best_chromosome {best_chromosome}, best_fitness {best_fitness}\")\n",
    "    # Clone the best to build the new population\n",
    "    new_population = []\n",
    "    if include_clone_populationf4:\n",
    "        new_population = clone_populationf4(best_chromosome, population_size)\n",
    "    if include_mutate_allf4:\n",
    "        new_population = mutate_allf4(new_population, mutation_rate, alphabet)\n",
    "    if include_crossover_allf4:\n",
    "        new_population = crossover_allf4(new_population, target_sequence, recombination_rate)\n",
    "    return best_fitness, best_chromosome, new_population\n",
    "\n",
    "\n",
    "\n",
    "\n",
    "\n",
    "def mainf4( target_sequence, mutation_rate, recombination_rate, alphabet):\n",
    "    print_parametersf4()\n",
    "    population = create_populationf4(population_size, target_sequence, alphabet)\n",
    "    # print(population)\n",
    "    best_fitness, best_chromosome = select_the_bestf4(population, target_sequence)\n",
    "    generation = 0\n",
    "    best_fitness_history = [] # List to store best fitness of each generation\n",
    "    best_fitness_history.append(best_fitness)\n",
    "    if print_best_fitness:\n",
    "        print(\"Generation, best_chromosome and best_fitness, M_t\")\n",
    "    while best_fitness < len(target_sequence):\n",
    "        generation += 1\n",
    "        best_fitness, best_chromosome, population = run_one_generationf4(population, target_sequence, mutation_rate, recombination_rate, alphabet)        \n",
    "        if print_best_fitness:\n",
    "            print(f\" {generation}  {best_chromosome} {best_fitness}\")\n",
    "        best_fitness_history.append(best_fitness)    \n",
    "    print(f\"\\nTarget sequence matched in generation {generation}\")\n",
    "    print(f\"Final chromosome: {best_chromosome}\")\n",
    "    totalCost = population_size * generation\n",
    "    print(f\"Total cost = population size * number of generations: {totalCost}\")\n",
    "    return generation, best_fitness_history\n",
    "\n",
    "generation, best_fitness_history =  mainf4( target_sequence, mutation_rate, recombination_rate, alphabet)\n",
    "\n",
    "############################\n",
    "\n",
    "# THEORETICAL MODEL\n",
    "\n",
    "# Program Theoretical_model.py\n",
    "# This program implements the theoretical model of the truncated evolution\n",
    "import numpy as np\n",
    "import matplotlib.pyplot as plt\n",
    "\n",
    "# Definition of parameters for the theoretical model\n",
    "\n",
    "n_generations = generation # number of generations to make predictions by the model\n",
    "\n",
    "#$c = 1.29$. \n",
    "c = 1.29\n",
    "#$k = 24.9 n^{-1.18} + 2.53$\n",
    "def k(length_of_target_sequence):\n",
    "    #return 24.9 * (length_of_target_sequence ** -1.18) + 2.53 #original definition of k\n",
    "    #return 2.53 # Simplified definition of k for large target sequence lengths\n",
    "    #return 10.3229 # Adjusted value of k for better fit with empirical data\n",
    "    return 1.5\n",
    "\n",
    "#kappa = 1.29 # Original value\n",
    "#kappa = 0.0045 # Adjusted value of kappa in the r-value formula for better fit with empirical data\n",
    "kappa = 0\n",
    "\n",
    "# $\\mu = $ mutation rate, constant\n",
    "mu = mutation_rate   # Example mutation rate\n",
    "#$H = $ length of the target string, total number of sites\n",
    "H = length_of_target_sequence \n",
    "#$m = $ number of monkeys or of binomial distributions.\n",
    "m = population_size\n",
    "#$M_t = $ number of solved sites at generation $t$\n",
    "#$M_o = I = $ initial number of matched sites\n",
    "#$ = \\frac{H}{2} +  \\sqrt{\\frac{H}{k}\\ln m  }  $\n",
    "I = H / 2 + ((H / k(H)) * np.log(m)) ** 0.5\n",
    "\n",
    "\n",
    "#$T= $ number of touched sites $ =  \\mu H +  \\sqrt{H \\mu (1 - \\mu) } \\sqrt{c \\ln (m)} $ \n",
    "def T(mu, H, c, m):\n",
    "    return mu * H + (H * mu * (1 - mu)) ** 0.5 * (c * np.log(m)) ** 0.5\n",
    "\n",
    "#  $ s = $ number of solved sites among touched $ =  \\frac{T}{2} +  \\sqrt{\\frac{T}{k}\\ln m  }  $\n",
    "def s(T, m):\n",
    "    return T / 2 + ((T / k(T)) * np.log(m)) ** 0.5\n",
    "\n",
    "# $ u = $ number of untouched sites $ = H-T$\n",
    "def u(H, T):\n",
    "    return H - T\n",
    "\n",
    "# $ r =  (H-T)p +  \\sqrt{(H-T)p(1-p)} \\sqrt{1.29 \\ln (m)} $.\n",
    "\n",
    "# $p = \\frac{M_t}{H}$\n",
    "\n",
    "def p(M_t, H):\n",
    "    return M_t / H\n",
    "\n",
    "#$ r = $ number of untouched sites that were right from start \n",
    "#$ = u p + \\sqrt{u p (1-p)} \\sqrt{c \\ln m} $\n",
    "def r(u_value, H, p_value, M_t):\n",
    "    return u_value * p_value  + ((u_value * p_value  * (1 - p_value )) ** 0.5) * (kappa * np.log(m)) ** 0.5\n",
    "    #return u_value * p_value  + ((u_value * p_value  * (1 - p_value )) ** 0.5) * (0.01 * np.log(m)) ** 0.5\n",
    "\n",
    "\n",
    "\n",
    "#$M_{t+1} =  s + r $, number of matched sites at generation $t+1$.\n",
    "def M(s, r):\n",
    "    return s + r\n",
    "\n",
    "print(\"Parameters of the theoretical model:\")\n",
    "print(f\"c = {c}\")\n",
    "print(f\"k(H) = {k(H)}\")\n",
    "print(f\"I = {I}\")\n",
    "print(f\"mu = {mu}\")\n",
    "print(f\"H = {H}\")\n",
    "print(f\"m = {m}\")\n",
    "\n",
    "M_values = []\n",
    "m_value  = I\n",
    "n = 0\n",
    "T_value = T(mu, H, c, m)\n",
    "print(f\"Generation {n}: T = {T_value}\")\n",
    "s_value = s(T_value,  m)\n",
    "print(f\"Generation {n}: s = {s_value}\")\n",
    "u_value = u(H, T_value)\n",
    "print(f\"Generation {n}: u = {u_value}\")\n",
    "# Generate a range of generations\n",
    "for n in range(n_generations):\n",
    "    p_value = p(m_value, H)\n",
    "    print(f\"Generation {n}: p = {p_value}\")\n",
    "    r_value = r(u_value, H, p_value, m_value)\n",
    "    # print(f\"Generation {n}: r = {r_value}\")\n",
    "    m_value = M(s_value, r_value)\n",
    "    if m_value > H:\n",
    "        m_value = H\n",
    "    M_values.append(m_value)\n",
    "    print(f\"Generation {n}: M(n) = {m_value}\")\n",
    "\n",
    "###########\n",
    "\n",
    "# PLOT FUNCTIONS\n",
    "\n",
    "plt.figure(figsize=(10, 6))\n",
    "# Red line for the total number of sites (H)\n",
    "plt.axhline(y=H, color='red', linestyle='--', linewidth=2, label='Total number of sites (H)')\n",
    "plt.plot(best_fitness_history, label='Best Fitness in simulation', color='blue')\n",
    "plt.plot(M_values, label = 'Predicted number of matched sites by the theoretical model', color='green')\n",
    "plt.axhline(y=length_of_target_sequence, color='red', linestyle='--', linewidth=2)\n",
    "\n",
    "plt.xlabel('Generation (n)')\n",
    "plt.ylabel('Number of Matched Sites (M)')\n",
    "plt.title('Number of Matched Sites in GA, Simulation vs Theoretical Model')\n",
    "plt.grid(True)\n",
    "plt.legend()\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "59aa93a6",
   "metadata": {},
   "source": [
    "*Comment.* We were unable to get a good fit with kappa alone. So, we played with kappa and k. A satisfactory upper bound was found for the values $k = 1.5$ and $kappa = 0.0015$. An acceptable fit for $k = 1.5 $, and $kappa = 0.000001 $. This is also a good upper bound for the 90\\% of the task, that was 800 bits long. For $k = 1.5 $ and $kappa = 0 $ results a good fit and an upper bound for more than 90\\% of the task. With $k= 2.1$ and $kappa = 0$ results an upper bound before 600 and a lower bound afterward. \n",
    "\n",
    "We have a math model that predicts the evolution of the number of matched sites as a function of the generation number. Can it be solved? That is not our aspiration. We prefer to be content with an upper bound. According to our trials in the previous example, one can have an upper bound with $kappa = 0$ and $k = constant = 1.5$. This assertion is very important. So, let us check it.  \n",
    "\n",
    "\n",
    "**Example.** In the following code we compare the evolution of the number of matched sites with that predicted by a simplified math model, in which $c = 1.29$, $kappa = 0$, and $k = constant = 1.5$. The code follows.\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "70a14955",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Lab: Simple Genetic Algorithm\n",
      "Purpose: solve an instance of the Shakespeare challenge\n",
      "Date of Experiment  = 2026-02-26 07:58:17.048350\n",
      "alphabet =  01\n",
      "target_sequence = 111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111\n",
      "length_of_target_sequence = 900\n",
      "population_size = 200\n",
      "include_clone_populationf5 = True\n",
      "include_mutate_allf5 = True\n",
      "include_crossover_allf5 = False\n",
      "mutation_rate = 0.01\n",
      "print_best_fitness = False\n",
      "\n",
      "Target sequence matched in generation 9098\n",
      "Final chromosome: 111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111\n",
      "Total cost = population size * number of generations: 1819600\n",
      "Parameters of the theoretical model\n",
      "c = 1.29\n",
      "k(H) = 1.5\n",
      "I = 506.3825364800913\n",
      "mu = 0.01\n",
      "H = 900\n",
      "m = 200\n",
      "Generation 0: T = 16.803738205460668\n",
      "Generation 0: s = 16.10604710157914\n",
      "Generation 0: u = 883.1962617945393\n",
      "Generation 0: p = 0.562647262755657\n",
      "Generation 0: M(n) = 513.0340062763054\n",
      "Generation 1: p = 0.5700377847514504\n",
      "Generation 1: M(n) = 519.5612876757003\n",
      "Generation 2: p = 0.577290319639667\n",
      "Generation 2: M(n) = 525.9666993775078\n",
      "Generation 3: p = 0.5844074437527864\n",
      "Generation 3: M(n) = 532.2525167889427\n",
      "Generation 4: p = 0.5913916853210475\n",
      "Generation 4: M(n) = 538.4209728335009\n",
      "Generation 5: p = 0.5982455253705565\n",
      "Generation 5: M(n) = 544.4742587441649\n",
      "Generation 6: p = 0.6049713986046277\n",
      "Generation 6: M(n) = 550.4145248418005\n",
      "Generation 7: p = 0.6115716942686672\n",
      "Generation 7: M(n) = 556.2438812990189\n",
      "Generation 8: p = 0.6180487569989098\n",
      "Generation 8: M(n) = 561.964398889778\n",
      "Generation 9: p = 0.6244048876553089\n",
      "Generation 9: M(n) = 567.5781097249873\n",
      "Generation 10: p = 0.6306423441388748\n",
      "Generation 10: M(n) = 573.0870079743787\n",
      "Generation 11: p = 0.6367633421937541\n",
      "Generation 11: M(n) = 578.4930505748998\n",
      "Generation 12: p = 0.6427700561943331\n",
      "Generation 12: M(n) = 583.7981579258801\n",
      "Generation 13: p = 0.6486646199176446\n",
      "Generation 13: M(n) = 589.0042145712185\n",
      "Generation 14: p = 0.654449127301354\n",
      "Generation 14: M(n) = 594.1130698688336\n",
      "Generation 15: p = 0.6601256331875929\n",
      "Generation 15: M(n) = 599.1265386476144\n",
      "Generation 16: p = 0.6656961540529049\n",
      "Generation 16: M(n) = 604.0464018521066\n",
      "Generation 17: p = 0.6711626687245629\n",
      "Generation 17: M(n) = 608.8744071751598\n",
      "Generation 18: p = 0.6765271190835109\n",
      "Generation 18: M(n) = 613.6122696787652\n",
      "Generation 19: p = 0.6817914107541836\n",
      "Generation 19: M(n) = 618.2616724032994\n",
      "Generation 20: p = 0.6869574137814437\n",
      "Generation 20: M(n) = 622.8242669653948\n",
      "Generation 21: p = 0.6920269632948831\n",
      "Generation 21: M(n) = 627.3016741446468\n",
      "Generation 22: p = 0.6970018601607186\n",
      "Generation 22: M(n) = 631.6954844593661\n",
      "Generation 23: p = 0.7018838716215179\n",
      "Generation 23: M(n) = 636.007258731582\n",
      "Generation 24: p = 0.7066747319239801\n",
      "Generation 24: M(n) = 640.2385286414966\n",
      "Generation 25: p = 0.7113761429349962\n",
      "Generation 25: M(n) = 644.3907972715857\n",
      "Generation 26: p = 0.7159897747462064\n",
      "Generation 26: M(n) = 648.4655396405429\n",
      "Generation 27: p = 0.72051726626727\n",
      "Generation 27: M(n) = 652.4642032272527\n",
      "Generation 28: p = 0.7249602258080585\n",
      "Generation 28: M(n) = 656.3882084849815\n",
      "Generation 29: p = 0.7293202316499795\n",
      "Generation 29: M(n) = 660.2389493459685\n",
      "Generation 30: p = 0.7335988326066317\n",
      "Generation 30: M(n) = 664.0177937165943\n",
      "Generation 31: p = 0.7377975485739936\n",
      "Generation 31: M(n) = 667.7260839633053\n",
      "Generation 32: p = 0.7419178710703392\n",
      "Generation 32: M(n) = 671.3651373894658\n",
      "Generation 33: p = 0.7459612637660731\n",
      "Generation 33: M(n) = 674.9362467033052\n",
      "Generation 34: p = 0.7499291630036724\n",
      "Generation 34: M(n) = 678.4406804771304\n",
      "Generation 35: p = 0.7538229783079227\n",
      "Generation 35: M(n) = 681.8796835979625\n",
      "Generation 36: p = 0.757644092886625\n",
      "Generation 36: M(n) = 685.2544777097611\n",
      "Generation 37: p = 0.7613938641219568\n",
      "Generation 37: M(n) = 688.5662616473908\n",
      "Generation 38: p = 0.7650736240526564\n",
      "Generation 38: M(n) = 691.816211862486\n",
      "Generation 39: p = 0.7686846798472067\n",
      "Generation 39: M(n) = 695.0054828413644\n",
      "Generation 40: p = 0.7722283142681826\n",
      "Generation 40: M(n) = 698.1352075151367\n",
      "Generation 41: p = 0.7757057861279296\n",
      "Generation 41: M(n) = 701.206497662161\n",
      "Generation 42: p = 0.7791183307357344\n",
      "Generation 42: M(n) = 704.2204443029814\n",
      "Generation 43: p = 0.782467160336646\n",
      "Generation 43: M(n) = 707.1781180878933\n",
      "Generation 44: p = 0.7857534645421036\n",
      "Generation 44: M(n) = 710.0805696772732\n",
      "Generation 45: p = 0.7889784107525257\n",
      "Generation 45: M(n) = 712.9288301148065\n",
      "Generation 46: p = 0.7921431445720072\n",
      "Generation 46: M(n) = 715.7239111937472\n",
      "Generation 47: p = 0.7952487902152746\n",
      "Generation 47: M(n) = 718.4668058163395\n",
      "Generation 48: p = 0.7982964509070439\n",
      "Generation 48: M(n) = 721.1584883465283\n",
      "Generation 49: p = 0.8012872092739204\n",
      "Generation 49: M(n) = 723.7999149560843\n",
      "Generation 50: p = 0.8042221277289826\n",
      "Generation 50: M(n) = 726.3920239642671\n",
      "Generation 51: p = 0.8071022488491857\n",
      "Generation 51: M(n) = 728.935736171146\n",
      "Generation 52: p = 0.8099285957457177\n",
      "Generation 52: M(n) = 731.4319551846977\n",
      "Generation 53: p = 0.8127021724274419\n",
      "Generation 53: M(n) = 733.881567741797\n",
      "Generation 54: p = 0.8154239641575521\n",
      "Generation 54: M(n) = 736.2854440232136\n",
      "Generation 55: p = 0.8180949378035707\n",
      "Generation 55: M(n) = 738.644437962729\n",
      "Generation 56: p = 0.82071604218081\n",
      "Generation 56: M(n) = 740.95938755048\n",
      "Generation 57: p = 0.8232882083894222\n",
      "Generation 57: M(n) = 743.2311151306405\n",
      "Generation 58: p = 0.8258123501451562\n",
      "Generation 58: M(n) = 745.4604276935443\n",
      "Generation 59: p = 0.828289364103938\n",
      "Generation 59: M(n) = 747.6481171623533\n",
      "Generation 60: p = 0.8307201301803926\n",
      "Generation 60: M(n) = 749.7949606743749\n",
      "Generation 61: p = 0.8331055118604166\n",
      "Generation 61: M(n) = 751.9017208571253\n",
      "Generation 62: p = 0.835446356507917\n",
      "Generation 62: M(n) = 753.9691460992394\n",
      "Generation 63: p = 0.8377434956658216\n",
      "Generation 63: M(n) = 755.9979708163227\n",
      "Generation 64: p = 0.8399977453514696\n",
      "Generation 64: M(n) = 757.9889157118386\n",
      "Generation 65: p = 0.8422099063464873\n",
      "Generation 65: M(n) = 759.9426880331258\n",
      "Generation 66: p = 0.8443807644812509\n",
      "Generation 66: M(n) = 761.8599818226353\n",
      "Generation 67: p = 0.8465110909140392\n",
      "Generation 67: M(n) = 763.741478164476\n",
      "Generation 68: p = 0.8486016424049734\n",
      "Generation 68: M(n) = 765.5878454263581\n",
      "Generation 69: p = 0.8506531615848423\n",
      "Generation 69: M(n) = 767.3997394970181\n",
      "Generation 70: p = 0.852666377218909\n",
      "Generation 70: M(n) = 769.1778040192122\n",
      "Generation 71: p = 0.8546420044657913\n",
      "Generation 71: M(n) = 770.922670618358\n",
      "Generation 72: p = 0.8565807451315088\n",
      "Generation 72: M(n) = 772.6349591269088\n",
      "Generation 73: p = 0.8584832879187876\n",
      "Generation 73: M(n) = 774.3152778045376\n",
      "Generation 74: p = 0.8603503086717084\n",
      "Generation 74: M(n) = 775.96422355421\n",
      "Generation 75: p = 0.8621824706157889\n",
      "Generation 75: M(n) = 777.5823821342242\n",
      "Generation 76: p = 0.8639804245935825\n",
      "Generation 76: M(n) = 779.17032836629\n",
      "Generation 77: p = 0.8657448092958778\n",
      "Generation 77: M(n) = 780.7286263397248\n",
      "Generation 78: p = 0.8674762514885831\n",
      "Generation 78: M(n) = 782.2578296118354\n",
      "Generation 79: p = 0.8691753662353727\n",
      "Generation 79: M(n) = 783.75848140456\n",
      "Generation 80: p = 0.8708427571161778\n",
      "Generation 80: M(n) = 785.2311147974373\n",
      "Generation 81: p = 0.872479016441597\n",
      "Generation 81: M(n) = 786.676252916974\n",
      "Generation 82: p = 0.8740847254633045\n",
      "Generation 82: M(n) = 788.0944091224759\n",
      "Generation 83: p = 0.8756604545805288\n",
      "Generation 83: M(n) = 789.4860871884091\n",
      "Generation 84: p = 0.8772067635426768\n",
      "Generation 84: M(n) = 790.8517814833576\n",
      "Generation 85: p = 0.8787242016481751\n",
      "Generation 85: M(n) = 792.1919771456384\n",
      "Generation 86: p = 0.8802133079395982\n",
      "Generation 86: M(n) = 793.507150255638\n",
      "Generation 87: p = 0.8816746113951532\n",
      "Generation 87: M(n) = 794.7977680049316\n",
      "Generation 88: p = 0.8831086311165907\n",
      "Generation 88: M(n) = 796.0642888622448\n",
      "Generation 89: p = 0.8845158765136053\n",
      "Generation 89: M(n) = 797.3071627363157\n",
      "Generation 90: p = 0.8858968474847952\n",
      "Generation 90: M(n) = 798.5268311357174\n",
      "Generation 91: p = 0.8872520345952416\n",
      "Generation 91: M(n) = 799.7237273256958\n",
      "Generation 92: p = 0.8885819192507731\n",
      "Generation 92: M(n) = 800.8982764820792\n",
      "Generation 93: p = 0.8898869738689769\n",
      "Generation 93: M(n) = 802.0508958423144\n",
      "Generation 94: p = 0.891167662047016\n",
      "Generation 94: M(n) = 803.181994853683\n",
      "Generation 95: p = 0.8924244387263145\n",
      "Generation 95: M(n) = 804.29197531875\n",
      "Generation 96: p = 0.8936577503541667\n",
      "Generation 96: M(n) = 805.3812315380968\n",
      "Generation 97: p = 0.8948680350423298\n",
      "Generation 97: M(n) = 806.4501504503896\n",
      "Generation 98: p = 0.8960557227226551\n",
      "Generation 98: M(n) = 807.4991117698323\n",
      "Generation 99: p = 0.8972212352998137\n",
      "Generation 99: M(n) = 808.5284881210533\n",
      "Generation 100: p = 0.8983649868011704\n",
      "Generation 100: M(n) = 809.5386451714735\n",
      "Generation 101: p = 0.8994873835238595\n",
      "Generation 101: M(n) = 810.529941761203\n",
      "Generation 102: p = 0.9005888241791145\n",
      "Generation 102: M(n) = 811.5027300305127\n",
      "Generation 103: p = 0.901669700033903\n",
      "Generation 103: M(n) = 812.4573555449259\n",
      "Generation 104: p = 0.9027303950499177\n",
      "Generation 104: M(n) = 813.3941574179742\n",
      "Generation 105: p = 0.9037712860199713\n",
      "Generation 105: M(n) = 814.3134684316611\n",
      "Generation 106: p = 0.9047927427018457\n",
      "Generation 106: M(n) = 815.2156151546777\n",
      "Generation 107: p = 0.9057951279496419\n",
      "Generation 107: M(n) = 816.1009180584093\n",
      "Generation 108: p = 0.906778797842677\n",
      "Generation 108: M(n) = 816.9696916307778\n",
      "Generation 109: p = 0.9077441018119753\n",
      "Generation 109: M(n) = 817.8222444879574\n",
      "Generation 110: p = 0.9086913827643971\n",
      "Generation 110: M(n) = 818.6588794840055\n",
      "Generation 111: p = 0.9096209772044506\n",
      "Generation 111: M(n) = 819.4798938184457\n",
      "Generation 112: p = 0.9105332153538286\n",
      "Generation 112: M(n) = 820.2855791418427\n",
      "Generation 113: p = 0.9114284212687142\n",
      "Generation 113: M(n) = 821.0762216594061\n",
      "Generation 114: p = 0.9123069129548956\n",
      "Generation 114: M(n) = 821.8521022326591\n",
      "Generation 115: p = 0.9131690024807324\n",
      "Generation 115: M(n) = 822.6134964792104\n",
      "Generation 116: p = 0.9140149960880116\n",
      "Generation 116: M(n) = 823.3606748706615\n",
      "Generation 117: p = 0.914845194300735\n",
      "Generation 117: M(n) = 824.0939028286873\n",
      "Generation 118: p = 0.9156598920318748\n",
      "Generation 118: M(n) = 824.8134408193224\n",
      "Generation 119: p = 0.916459378688136\n",
      "Generation 119: M(n) = 825.519544445487\n",
      "Generation 120: p = 0.9172439382727633\n",
      "Generation 120: M(n) = 826.2124645377849\n",
      "Generation 121: p = 0.9180138494864276\n",
      "Generation 121: M(n) = 826.8924472436069\n",
      "Generation 122: p = 0.9187693858262298\n",
      "Generation 122: M(n) = 827.5597341145701\n",
      "Generation 123: p = 0.9195108156828556\n",
      "Generation 123: M(n) = 828.2145621923249\n",
      "Generation 124: p = 0.9202384024359166\n",
      "Generation 124: M(n) = 828.8571640927596\n",
      "Generation 125: p = 0.9209524045475107\n",
      "Generation 125: M(n) = 829.487768088633\n",
      "Generation 126: p = 0.9216530756540366\n",
      "Generation 126: M(n) = 830.106598190664\n",
      "Generation 127: p = 0.9223406646562934\n",
      "Generation 127: M(n) = 830.7138742271082\n",
      "Generation 128: p = 0.923015415807898\n",
      "Generation 128: M(n) = 831.309811921847\n",
      "Generation 129: p = 0.9236775688020522\n",
      "Generation 129: M(n) = 831.89462297102\n",
      "Generation 130: p = 0.9243273588566889\n",
      "Generation 130: M(n) = 832.4685151182265\n",
      "Generation 131: p = 0.9249650167980294\n",
      "Generation 131: M(n) = 833.0316922283221\n",
      "Generation 132: p = 0.9255907691425801\n",
      "Generation 132: M(n) = 833.5843543598384\n",
      "Generation 133: p = 0.9262048381775981\n",
      "Generation 133: M(n) = 834.1266978360501\n",
      "Generation 134: p = 0.9268074420400556\n",
      "Generation 134: M(n) = 834.6589153147154\n",
      "Generation 135: p = 0.9273987947941282\n",
      "Generation 135: M(n) = 835.1811958565143\n",
      "Generation 136: p = 0.927979106507238\n",
      "Generation 136: M(n) = 835.6937249922084\n",
      "Generation 137: p = 0.928548583324676\n",
      "Generation 137: M(n) = 836.1966847885483\n",
      "Generation 138: p = 0.9291074275428314\n",
      "Generation 138: M(n) = 836.6902539129486\n",
      "Generation 139: p = 0.929655837681054\n",
      "Generation 139: M(n) = 837.1746076969571\n",
      "Generation 140: p = 0.9301940085521745\n",
      "Generation 140: M(n) = 837.6499181985374\n",
      "Generation 141: p = 0.9307221313317082\n",
      "Generation 141: M(n) = 838.1163542631901\n",
      "Generation 142: p = 0.9312403936257668\n",
      "Generation 142: M(n) = 838.5740815839317\n",
      "Generation 143: p = 0.931748979537702\n",
      "Generation 143: M(n) = 839.0232627601542\n",
      "Generation 144: p = 0.9322480697335047\n",
      "Generation 144: M(n) = 839.4640573553855\n",
      "Generation 145: p = 0.9327378415059839\n",
      "Generation 145: M(n) = 839.8966219539717\n",
      "Generation 146: p = 0.9332184688377463\n",
      "Generation 146: M(n) = 840.3211102167004\n",
      "Generation 147: p = 0.9336901224630004\n",
      "Generation 147: M(n) = 840.7376729353867\n",
      "Generation 148: p = 0.9341529699282075\n",
      "Generation 148: M(n) = 841.1464580864388\n",
      "Generation 149: p = 0.9346071756515987\n",
      "Generation 149: M(n) = 841.5476108834234\n",
      "Generation 150: p = 0.9350529009815816\n",
      "Generation 150: M(n) = 841.9412738286514\n",
      "Generation 151: p = 0.9354903042540572\n",
      "Generation 151: M(n) = 842.3275867637986\n",
      "Generation 152: p = 0.9359195408486651\n",
      "Generation 152: M(n) = 842.7066869195818\n",
      "Generation 153: p = 0.9363407632439797\n",
      "Generation 153: M(n) = 843.0787089645079\n",
      "Generation 154: p = 0.9367541210716754\n",
      "Generation 154: M(n) = 843.4437850527122\n",
      "Generation 155: p = 0.9371597611696802\n",
      "Generation 155: M(n) = 843.802044870904\n",
      "Generation 156: p = 0.9375578276343377\n",
      "Generation 156: M(n) = 844.1536156844352\n",
      "Generation 157: p = 0.9379484618715946\n",
      "Generation 157: M(n) = 844.4986223825096\n",
      "Generation 158: p = 0.9383318026472328\n",
      "Generation 158: M(n) = 844.8371875225466\n",
      "Generation 159: p = 0.9387079861361629\n",
      "Generation 159: M(n) = 845.1694313737185\n",
      "Generation 160: p = 0.9390771459707983\n",
      "Generation 160: M(n) = 845.4954719596731\n",
      "Generation 161: p = 0.9394394132885256\n",
      "Generation 161: M(n) = 845.8154251004603\n",
      "Generation 162: p = 0.9397949167782892\n",
      "Generation 162: M(n) = 846.1294044536743\n",
      "Generation 163: p = 0.9401437827263047\n",
      "Generation 163: M(n) = 846.4375215548291\n",
      "Generation 164: p = 0.9404861350609213\n",
      "Generation 164: M(n) = 846.7398858569791\n",
      "Generation 165: p = 0.9408220953966434\n",
      "Generation 165: M(n) = 847.0366047696001\n",
      "Generation 166: p = 0.9411517830773335\n",
      "Generation 166: M(n) = 847.3277836967452\n",
      "Generation 167: p = 0.9414753152186057\n",
      "Generation 167: M(n) = 847.6135260744873\n",
      "Generation 168: p = 0.9417928067494303\n",
      "Generation 168: M(n) = 847.893933407663\n",
      "Generation 169: p = 0.9421043704529589\n",
      "Generation 169: M(n) = 848.1691053059303\n",
      "Generation 170: p = 0.9424101170065893\n",
      "Generation 170: M(n) = 848.4391395191532\n",
      "Generation 171: p = 0.9427101550212813\n",
      "Generation 171: M(n) = 848.7041319721254\n",
      "Generation 172: p = 0.9430045910801393\n",
      "Generation 172: M(n) = 848.9641767986463\n",
      "Generation 173: p = 0.9432935297762737\n",
      "Generation 173: M(n) = 849.21936637496\n",
      "Generation 174: p = 0.9435770737499556\n",
      "Generation 174: M(n) = 849.4697913525703\n",
      "Generation 175: p = 0.9438553237250781\n",
      "Generation 175: M(n) = 849.7155406904428\n",
      "Generation 176: p = 0.9441283785449365\n",
      "Generation 176: M(n) = 849.9567016866068\n",
      "Generation 177: p = 0.9443963352073409\n",
      "Generation 177: M(n) = 850.1933600091653\n",
      "Generation 178: p = 0.9446592888990726\n",
      "Generation 178: M(n) = 850.4255997267278\n",
      "Generation 179: p = 0.9449173330296976\n",
      "Generation 179: M(n) = 850.6535033382738\n",
      "Generation 180: p = 0.9451705592647487\n",
      "Generation 180: M(n) = 850.8771518024593\n",
      "Generation 181: p = 0.945419057558288\n",
      "Generation 181: M(n) = 851.0966245663756\n",
      "Generation 182: p = 0.9456629161848618\n",
      "Generation 182: M(n) = 851.3119995937718\n",
      "Generation 183: p = 0.9459022217708576\n",
      "Generation 183: M(n) = 851.5233533927499\n",
      "Generation 184: p = 0.9461370593252776\n",
      "Generation 184: M(n) = 851.7307610429426\n",
      "Generation 185: p = 0.9463675122699362\n",
      "Generation 185: M(n) = 851.9342962221846\n",
      "Generation 186: p = 0.9465936624690939\n",
      "Generation 186: M(n) = 852.1340312326848\n",
      "Generation 187: p = 0.9468155902585387\n",
      "Generation 187: M(n) = 852.3300370267108\n",
      "Generation 188: p = 0.9470333744741231\n",
      "Generation 188: M(n) = 852.5223832317927\n",
      "Generation 189: p = 0.9472470924797697\n",
      "Generation 189: M(n) = 852.711138175458\n",
      "Generation 190: p = 0.9474568201949534\n",
      "Generation 190: M(n) = 852.8963689095029\n",
      "Generation 191: p = 0.9476626321216699\n",
      "Generation 191: M(n) = 853.0781412338117\n",
      "Generation 192: p = 0.9478646013709019\n",
      "Generation 192: M(n) = 853.2565197197308\n",
      "Generation 193: p = 0.9480627996885898\n",
      "Generation 193: M(n) = 853.4315677330068\n",
      "Generation 194: p = 0.9482572974811186\n",
      "Generation 194: M(n) = 853.6033474562955\n",
      "Generation 195: p = 0.9484481638403284\n",
      "Generation 195: M(n) = 853.7719199112519\n",
      "Generation 196: p = 0.9486354665680576\n",
      "Generation 196: M(n) = 853.9373449802064\n",
      "Generation 197: p = 0.9488192722002293\n",
      "Generation 197: M(n) = 854.0996814274372\n",
      "Generation 198: p = 0.9489996460304858\n",
      "Generation 198: M(n) = 854.2589869200452\n",
      "Generation 199: p = 0.9491766521333835\n",
      "Generation 199: M(n) = 854.4153180484393\n",
      "Generation 200: p = 0.9493503533871548\n",
      "Generation 200: M(n) = 854.5687303464391\n",
      "Generation 201: p = 0.9495208114960435\n",
      "Generation 201: M(n) = 854.7192783110022\n",
      "Generation 202: p = 0.9496880870122246\n",
      "Generation 202: M(n) = 854.8670154215831\n",
      "Generation 203: p = 0.9498522393573146\n",
      "Generation 203: M(n) = 855.0119941591314\n",
      "Generation 204: p = 0.9500133268434794\n",
      "Generation 204: M(n) = 855.154266024734\n",
      "Generation 205: p = 0.9501714066941489\n",
      "Generation 205: M(n) = 855.2938815579104\n",
      "Generation 206: p = 0.9503265350643448\n",
      "Generation 206: M(n) = 855.4308903545657\n",
      "Generation 207: p = 0.9504787670606285\n",
      "Generation 207: M(n) = 855.5653410846089\n",
      "Generation 208: p = 0.9506281567606766\n",
      "Generation 208: M(n) = 855.697281509242\n",
      "Generation 209: p = 0.950774757232491\n",
      "Generation 209: M(n) = 855.8267584979259\n",
      "Generation 210: p = 0.9509186205532509\n",
      "Generation 210: M(n) = 855.9538180450304\n",
      "Generation 211: p = 0.9510597978278116\n",
      "Generation 211: M(n) = 856.0785052861727\n",
      "Generation 212: p = 0.9511983392068586\n",
      "Generation 212: M(n) = 856.2008645142508\n",
      "Generation 213: p = 0.9513342939047231\n",
      "Generation 213: M(n) = 856.3209391951782\n",
      "Generation 214: p = 0.9514677102168647\n",
      "Generation 214: M(n) = 856.438771983324\n",
      "Generation 215: p = 0.9515986355370267\n",
      "Generation 215: M(n) = 856.5544047366654\n",
      "Generation 216: p = 0.9517271163740727\n",
      "Generation 216: M(n) = 856.6678785316567\n",
      "Generation 217: p = 0.9518531983685075\n",
      "Generation 217: M(n) = 856.779233677821\n",
      "Generation 218: p = 0.95197692630869\n",
      "Generation 218: M(n) = 856.8885097320698\n",
      "Generation 219: p = 0.9520983441467442\n",
      "Generation 219: M(n) = 856.9957455127544\n",
      "Generation 220: p = 0.9522174950141715\n",
      "Generation 220: M(n) = 857.1009791134558\n",
      "Generation 221: p = 0.952334421237173\n",
      "Generation 221: M(n) = 857.2042479165165\n",
      "Generation 222: p = 0.9524491643516849\n",
      "Generation 222: M(n) = 857.30558860632\n",
      "Generation 223: p = 0.9525617651181334\n",
      "Generation 223: M(n) = 857.4050371823225\n",
      "Generation 224: p = 0.9526722635359139\n",
      "Generation 224: M(n) = 857.5026289718405\n",
      "Generation 225: p = 0.9527806988576005\n",
      "Generation 225: M(n) = 857.5983986426006\n",
      "Generation 226: p = 0.9528871096028896\n",
      "Generation 226: M(n) = 857.6923802150546\n",
      "Generation 227: p = 0.952991533572283\n",
      "Generation 227: M(n) = 857.7846070744647\n",
      "Generation 228: p = 0.9530940078605163\n",
      "Generation 228: M(n) = 857.8751119827624\n",
      "Generation 229: p = 0.953194568869736\n",
      "Generation 229: M(n) = 857.9639270901876\n",
      "Generation 230: p = 0.9532932523224306\n",
      "Generation 230: M(n) = 858.0510839467083\n",
      "Generation 231: p = 0.9533900932741204\n",
      "Generation 231: M(n) = 858.1366135132295\n",
      "Generation 232: p = 0.9534851261258105\n",
      "Generation 232: M(n) = 858.2205461725898\n",
      "Generation 233: p = 0.9535783846362109\n",
      "Generation 233: M(n) = 858.302911740356\n",
      "Generation 234: p = 0.9536699019337288\n",
      "Generation 234: M(n) = 858.3837394754133\n",
      "Generation 235: p = 0.953759710528237\n",
      "Generation 235: M(n) = 858.46305809036\n",
      "Generation 236: p = 0.9538478423226223\n",
      "Generation 236: M(n) = 858.5408957617063\n",
      "Generation 237: p = 0.9539343286241182\n",
      "Generation 237: M(n) = 858.617280139884\n",
      "Generation 238: p = 0.9540192001554266\n",
      "Generation 238: M(n) = 858.6922383590684\n",
      "Generation 239: p = 0.9541024870656315\n",
      "Generation 239: M(n) = 858.7657970468177\n",
      "Generation 240: p = 0.9541842189409085\n",
      "Generation 240: M(n) = 858.8379823335318\n",
      "Generation 241: p = 0.9542644248150354\n",
      "Generation 241: M(n) = 858.9088198617346\n",
      "Generation 242: p = 0.9543431331797051\n",
      "Generation 242: M(n) = 858.9783347951828\n",
      "Generation 243: p = 0.9544203719946476\n",
      "Generation 243: M(n) = 859.0465518278055\n",
      "Generation 244: p = 0.9544961686975617\n",
      "Generation 244: M(n) = 859.1134951924756\n",
      "Generation 245: p = 0.9545705502138618\n",
      "Generation 245: M(n) = 859.1791886696185\n",
      "Generation 246: p = 0.9546435429662428\n",
      "Generation 246: M(n) = 859.2436555956594\n",
      "Generation 247: p = 0.954715172884066\n",
      "Generation 247: M(n) = 859.3069188713137\n",
      "Generation 248: p = 0.9547854654125707\n",
      "Generation 248: M(n) = 859.369000969721\n",
      "Generation 249: p = 0.9548544455219122\n",
      "Generation 249: M(n) = 859.4299239444297\n",
      "Generation 250: p = 0.954922137716033\n",
      "Generation 250: M(n) = 859.4897094372297\n",
      "Generation 251: p = 0.9549885660413664\n",
      "Generation 251: M(n) = 859.5483786858415\n",
      "Generation 252: p = 0.9550537540953794\n",
      "Generation 252: M(n) = 859.6059525314595\n",
      "Generation 253: p = 0.955117725034955\n",
      "Generation 253: M(n) = 859.662451426156\n",
      "Generation 254: p = 0.9551805015846179\n",
      "Generation 254: M(n) = 859.7178954401467\n",
      "Generation 255: p = 0.9552421060446074\n",
      "Generation 255: M(n) = 859.7723042689192\n",
      "Generation 256: p = 0.9553025602987991\n",
      "Generation 256: M(n) = 859.825697240231\n",
      "Generation 257: p = 0.9553618858224788\n",
      "Generation 257: M(n) = 859.8780933209739\n",
      "Generation 258: p = 0.955420103689971\n",
      "Generation 258: M(n) = 859.9295111239127\n",
      "Generation 259: p = 0.9554772345821252\n",
      "Generation 259: M(n) = 859.9799689142963\n",
      "Generation 260: p = 0.9555332987936626\n",
      "Generation 260: M(n) = 860.0294846163465\n",
      "Generation 261: p = 0.955588316240385\n",
      "Generation 261: M(n) = 860.0780758196253\n",
      "Generation 262: p = 0.9556423064662503\n",
      "Generation 262: M(n) = 860.1257597852829\n",
      "Generation 263: p = 0.9556952886503143\n",
      "Generation 263: M(n) = 860.17255345219\n",
      "Generation 264: p = 0.9557472816135444\n",
      "Generation 264: M(n) = 860.2184734429544\n",
      "Generation 265: p = 0.9557983038255049\n",
      "Generation 265: M(n) = 860.2635360698264\n",
      "Generation 266: p = 0.9558483734109182\n",
      "Generation 266: M(n) = 860.307757340493\n",
      "Generation 267: p = 0.9558975081561034\n",
      "Generation 267: M(n) = 860.3511529637649\n",
      "Generation 268: p = 0.9559457255152943\n",
      "Generation 268: M(n) = 860.3937383551558\n",
      "Generation 269: p = 0.9559930426168398\n",
      "Generation 269: M(n) = 860.4355286423598\n",
      "Generation 270: p = 0.9560394762692886\n",
      "Generation 270: M(n) = 860.4765386706241\n",
      "Generation 271: p = 0.9560850429673601\n",
      "Generation 271: M(n) = 860.516783008023\n",
      "Generation 272: p = 0.9561297588978034\n",
      "Generation 272: M(n) = 860.5562759506332\n",
      "Generation 273: p = 0.956173639945148\n",
      "Generation 273: M(n) = 860.5950315276117\n",
      "Generation 274: p = 0.9562167016973463\n",
      "Generation 274: M(n) = 860.6330635061795\n",
      "Generation 275: p = 0.9562589594513106\n",
      "Generation 275: M(n) = 860.6703853965126\n",
      "Generation 276: p = 0.9563004282183474\n",
      "Generation 276: M(n) = 860.7070104565407\n",
      "Generation 277: p = 0.9563411227294897\n",
      "Generation 277: M(n) = 860.7429516966572\n",
      "Generation 278: p = 0.9563810574407302\n",
      "Generation 278: M(n) = 860.7782218843406\n",
      "Generation 279: p = 0.9564202465381563\n",
      "Generation 279: M(n) = 860.8128335486905\n",
      "Generation 280: p = 0.9564587039429895\n",
      "Generation 280: M(n) = 860.8467989848774\n",
      "Generation 281: p = 0.9564964433165305\n",
      "Generation 281: M(n) = 860.8801302585114\n",
      "Generation 282: p = 0.9565334780650127\n",
      "Generation 282: M(n) = 860.9128392099273\n",
      "Generation 283: p = 0.9565698213443636\n",
      "Generation 283: M(n) = 860.9449374583915\n",
      "Generation 284: p = 0.9566054860648794\n",
      "Generation 284: M(n) = 860.9764364062289\n",
      "Generation 285: p = 0.9566404848958099\n",
      "Generation 285: M(n) = 861.0073472428738\n",
      "Generation 286: p = 0.9566748302698598\n",
      "Generation 286: M(n) = 861.0376809488447\n",
      "Generation 287: p = 0.9567085343876052\n",
      "Generation 287: M(n) = 861.0674482996445\n",
      "Generation 288: p = 0.9567416092218273\n",
      "Generation 288: M(n) = 861.096659869589\n",
      "Generation 289: p = 0.9567740665217656\n",
      "Generation 289: M(n) = 861.1253260355624\n",
      "Generation 290: p = 0.9568059178172915\n",
      "Generation 290: M(n) = 861.1534569807042\n",
      "Generation 291: p = 0.9568371744230046\n",
      "Generation 291: M(n) = 861.1810626980264\n",
      "Generation 292: p = 0.9568678474422515\n",
      "Generation 292: M(n) = 861.2081529939633\n",
      "Generation 293: p = 0.9568979477710703\n",
      "Generation 293: M(n) = 861.2347374918547\n",
      "Generation 294: p = 0.9569274861020608\n",
      "Generation 294: M(n) = 861.2608256353652\n",
      "Generation 295: p = 0.9569564729281835\n",
      "Generation 295: M(n) = 861.2864266918381\n",
      "Generation 296: p = 0.9569849185464867\n",
      "Generation 296: M(n) = 861.3115497555879\n",
      "Generation 297: p = 0.9570128330617643\n",
      "Generation 297: M(n) = 861.3362037511309\n",
      "Generation 298: p = 0.9570402263901455\n",
      "Generation 298: M(n) = 861.3603974363552\n",
      "Generation 299: p = 0.957067108262617\n",
      "Generation 299: M(n) = 861.3841394056321\n",
      "Generation 300: p = 0.9570934882284802\n",
      "Generation 300: M(n) = 861.4074380928688\n",
      "Generation 301: p = 0.9571193756587432\n",
      "Generation 301: M(n) = 861.4303017745045\n",
      "Generation 302: p = 0.9571447797494494\n",
      "Generation 302: M(n) = 861.4527385724506\n",
      "Generation 303: p = 0.9571697095249451\n",
      "Generation 303: M(n) = 861.4747564569757\n",
      "Generation 304: p = 0.9571941738410841\n",
      "Generation 304: M(n) = 861.496363249537\n",
      "Generation 305: p = 0.9572181813883744\n",
      "Generation 305: M(n) = 861.5175666255587\n",
      "Generation 306: p = 0.9572417406950653\n",
      "Generation 306: M(n) = 861.5383741171586\n",
      "Generation 307: p = 0.9572648601301762\n",
      "Generation 307: M(n) = 861.5587931158233\n",
      "Generation 308: p = 0.9572875479064703\n",
      "Generation 308: M(n) = 861.5788308750347\n",
      "Generation 309: p = 0.9573098120833718\n",
      "Generation 309: M(n) = 861.5984945128461\n",
      "Generation 310: p = 0.957331660569829\n",
      "Generation 310: M(n) = 861.6177910144108\n",
      "Generation 311: p = 0.9573531011271231\n",
      "Generation 311: M(n) = 861.6367272344638\n",
      "Generation 312: p = 0.9573741413716265\n",
      "Generation 312: M(n) = 861.6553098997565\n",
      "Generation 313: p = 0.9573947887775073\n",
      "Generation 313: M(n) = 861.6735456114461\n",
      "Generation 314: p = 0.9574150506793846\n",
      "Generation 314: M(n) = 861.6914408474411\n",
      "Generation 315: p = 0.9574349342749345\n",
      "Generation 315: M(n) = 861.7090019647018\n",
      "Generation 316: p = 0.9574544466274464\n",
      "Generation 316: M(n) = 861.7262352014991\n",
      "Generation 317: p = 0.9574735946683324\n",
      "Generation 317: M(n) = 861.7431466796303\n",
      "Generation 318: p = 0.9574923851995892\n",
      "Generation 318: M(n) = 861.7597424065934\n",
      "Generation 319: p = 0.957510824896215\n",
      "Generation 319: M(n) = 861.7760282777219\n",
      "Generation 320: p = 0.95752892030858\n",
      "Generation 320: M(n) = 861.7920100782783\n",
      "Generation 321: p = 0.9575466778647537\n",
      "Generation 321: M(n) = 861.8076934855095\n",
      "Generation 322: p = 0.9575641038727883\n",
      "Generation 322: M(n) = 861.8230840706638\n",
      "Generation 323: p = 0.9575812045229597\n",
      "Generation 323: M(n) = 861.8381873009694\n",
      "Generation 324: p = 0.9575979858899659\n",
      "Generation 324: M(n) = 861.8530085415771\n",
      "Generation 325: p = 0.9576144539350856\n",
      "Generation 325: M(n) = 861.8675530574658\n",
      "Generation 326: p = 0.9576306145082953\n",
      "Generation 326: M(n) = 861.8818260153131\n",
      "Generation 327: p = 0.9576464733503479\n",
      "Generation 327: M(n) = 861.8958324853303\n",
      "Generation 328: p = 0.9576620360948115\n",
      "Generation 328: M(n) = 861.9095774430639\n",
      "Generation 329: p = 0.957677308270071\n",
      "Generation 329: M(n) = 861.9230657711626\n",
      "Generation 330: p = 0.9576922953012917\n",
      "Generation 330: M(n) = 861.936302261112\n",
      "Generation 331: p = 0.9577070025123466\n",
      "Generation 331: M(n) = 861.9492916149371\n",
      "Generation 332: p = 0.9577214351277079\n",
      "Generation 332: M(n) = 861.9620384468722\n",
      "Generation 333: p = 0.9577355982743024\n",
      "Generation 333: M(n) = 861.9745472849997\n",
      "Generation 334: p = 0.957749496983333\n",
      "Generation 334: M(n) = 861.9868225728593\n",
      "Generation 335: p = 0.9577631361920659\n",
      "Generation 335: M(n) = 861.998868671026\n",
      "Generation 336: p = 0.9577765207455844\n",
      "Generation 336: M(n) = 862.0106898586594\n",
      "Generation 337: p = 0.9577896553985104\n",
      "Generation 337: M(n) = 862.0222903350235\n",
      "Generation 338: p = 0.9578025448166928\n",
      "Generation 338: M(n) = 862.0336742209789\n",
      "Generation 339: p = 0.9578151935788655\n",
      "Generation 339: M(n) = 862.0448455604461\n",
      "Generation 340: p = 0.9578276061782734\n",
      "Generation 340: M(n) = 862.0558083218424\n",
      "Generation 341: p = 0.9578397870242693\n",
      "Generation 341: M(n) = 862.0665663994915\n",
      "Generation 342: p = 0.9578517404438794\n",
      "Generation 342: M(n) = 862.0771236150068\n",
      "Generation 343: p = 0.9578634706833409\n",
      "Generation 343: M(n) = 862.0874837186491\n",
      "Generation 344: p = 0.9578749819096101\n",
      "Generation 344: M(n) = 862.0976503906587\n",
      "Generation 345: p = 0.957886278211843\n",
      "Generation 345: M(n) = 862.107627242563\n",
      "Generation 346: p = 0.9578973636028478\n",
      "Generation 346: M(n) = 862.117417818459\n",
      "Generation 347: p = 0.95790824202051\n",
      "Generation 347: M(n) = 862.1270255962723\n",
      "Generation 348: p = 0.9579189173291915\n",
      "Generation 348: M(n) = 862.1364539889935\n",
      "Generation 349: p = 0.9579293933211038\n",
      "Generation 349: M(n) = 862.145706345889\n",
      "Generation 350: p = 0.9579396737176545\n",
      "Generation 350: M(n) = 862.1547859536923\n",
      "Generation 351: p = 0.9579497621707692\n",
      "Generation 351: M(n) = 862.1636960377705\n",
      "Generation 352: p = 0.9579596622641894\n",
      "Generation 352: M(n) = 862.1724397632706\n",
      "Generation 353: p = 0.9579693775147451\n",
      "Generation 353: M(n) = 862.1810202362439\n",
      "Generation 354: p = 0.9579789113736042\n",
      "Generation 354: M(n) = 862.1894405047487\n",
      "Generation 355: p = 0.9579882672274986\n",
      "Generation 355: M(n) = 862.1977035599341\n",
      "Generation 356: p = 0.9579974483999267\n",
      "Generation 356: M(n) = 862.2058123371015\n",
      "Generation 357: p = 0.958006458152335\n",
      "Generation 357: M(n) = 862.2137697167482\n",
      "Generation 358: p = 0.9580152996852758\n",
      "Generation 358: M(n) = 862.22157852559\n",
      "Generation 359: p = 0.9580239761395444\n",
      "Generation 359: M(n) = 862.2292415375657\n",
      "Generation 360: p = 0.9580324905972952\n",
      "Generation 360: M(n) = 862.2367614748224\n",
      "Generation 361: p = 0.958040846083136\n",
      "Generation 361: M(n) = 862.2441410086825\n",
      "Generation 362: p = 0.9580490455652028\n",
      "Generation 362: M(n) = 862.2513827605925\n",
      "Generation 363: p = 0.9580570919562139\n",
      "Generation 363: M(n) = 862.2584893030545\n",
      "Generation 364: p = 0.958064988114505\n",
      "Generation 364: M(n) = 862.2654631605398\n",
      "Generation 365: p = 0.9580727368450441\n",
      "Generation 365: M(n) = 862.2723068103855\n",
      "Generation 366: p = 0.9580803409004284\n",
      "Generation 366: M(n) = 862.2790226836754\n",
      "Generation 367: p = 0.9580878029818616\n",
      "Generation 367: M(n) = 862.2856131661024\n",
      "Generation 368: p = 0.9580951257401138\n",
      "Generation 368: M(n) = 862.2920805988167\n",
      "Generation 369: p = 0.958102311776463\n",
      "Generation 369: M(n) = 862.2984272792575\n",
      "Generation 370: p = 0.9581093636436194\n",
      "Generation 370: M(n) = 862.3046554619688\n",
      "Generation 371: p = 0.9581162838466319\n",
      "Generation 371: M(n) = 862.3107673594002\n",
      "Generation 372: p = 0.958123074843778\n",
      "Generation 372: M(n) = 862.3167651426935\n",
      "Generation 373: p = 0.9581297390474373\n",
      "Generation 373: M(n) = 862.3226509424532\n",
      "Generation 374: p = 0.9581362788249479\n",
      "Generation 374: M(n) = 862.3284268495036\n",
      "Generation 375: p = 0.9581426964994484\n",
      "Generation 375: M(n) = 862.3340949156318\n",
      "Generation 376: p = 0.958148994350702\n",
      "Generation 376: M(n) = 862.3396571543163\n",
      "Generation 377: p = 0.958155174615907\n",
      "Generation 377: M(n) = 862.3451155414423\n",
      "Generation 378: p = 0.9581612394904915\n",
      "Generation 378: M(n) = 862.3504720160036\n",
      "Generation 379: p = 0.9581671911288928\n",
      "Generation 379: M(n) = 862.3557284807912\n",
      "Generation 380: p = 0.9581730316453235\n",
      "Generation 380: M(n) = 862.3608868030697\n",
      "Generation 381: p = 0.9581787631145219\n",
      "Generation 381: M(n) = 862.3659488152402\n",
      "Generation 382: p = 0.9581843875724891\n",
      "Generation 382: M(n) = 862.3709163154916\n",
      "Generation 383: p = 0.958189907017213\n",
      "Generation 383: M(n) = 862.3757910684388\n",
      "Generation 384: p = 0.9581953234093765\n",
      "Generation 384: M(n) = 862.3805748057501\n",
      "Generation 385: p = 0.9582006386730557\n",
      "Generation 385: M(n) = 862.385269226762\n",
      "Generation 386: p = 0.9582058546964023\n",
      "Generation 386: M(n) = 862.3898759990832\n",
      "Generation 387: p = 0.9582109733323146\n",
      "Generation 387: M(n) = 862.3943967591864\n",
      "Generation 388: p = 0.958215996399096\n",
      "Generation 388: M(n) = 862.3988331129905\n",
      "Generation 389: p = 0.9582209256811005\n",
      "Generation 389: M(n) = 862.4031866364302\n",
      "Generation 390: p = 0.9582257629293669\n",
      "Generation 390: M(n) = 862.4074588760164\n",
      "Generation 391: p = 0.9582305098622405\n",
      "Generation 391: M(n) = 862.4116513493854\n",
      "Generation 392: p = 0.9582351681659838\n",
      "Generation 392: M(n) = 862.4157655458378\n",
      "Generation 393: p = 0.9582397394953753\n",
      "Generation 393: M(n) = 862.4198029268678\n",
      "Generation 394: p = 0.9582442254742976\n",
      "Generation 394: M(n) = 862.4237649266825\n",
      "Generation 395: p = 0.9582486276963138\n",
      "Generation 395: M(n) = 862.4276529527108\n",
      "Generation 396: p = 0.9582529477252342\n",
      "Generation 396: M(n) = 862.431468386104\n",
      "Generation 397: p = 0.9582571870956711\n",
      "Generation 397: M(n) = 862.4352125822263\n",
      "Generation 398: p = 0.9582613473135848\n",
      "Generation 398: M(n) = 862.438886871136\n",
      "Generation 399: p = 0.9582654298568177\n",
      "Generation 399: M(n) = 862.4424925580579\n",
      "Generation 400: p = 0.9582694361756199\n",
      "Generation 400: M(n) = 862.4460309238475\n",
      "Generation 401: p = 0.9582733676931638\n",
      "Generation 401: M(n) = 862.4495032254455\n",
      "Generation 402: p = 0.9582772258060506\n",
      "Generation 402: M(n) = 862.4529106963247\n",
      "Generation 403: p = 0.9582810118848052\n",
      "Generation 403: M(n) = 862.4562545469275\n",
      "Generation 404: p = 0.958284727274364\n",
      "Generation 404: M(n) = 862.4595359650971\n",
      "Generation 405: p = 0.9582883732945523\n",
      "Generation 405: M(n) = 862.4627561164978\n",
      "Generation 406: p = 0.9582919512405531\n",
      "Generation 406: M(n) = 862.4659161450306\n",
      "Generation 407: p = 0.9582954623833674\n",
      "Generation 407: M(n) = 862.4690171732387\n",
      "Generation 408: p = 0.9582989079702653\n",
      "Generation 408: M(n) = 862.4720603027067\n",
      "Generation 409: p = 0.9583022892252296\n",
      "Generation 409: M(n) = 862.4750466144513\n",
      "Generation 410: p = 0.9583056073493904\n",
      "Generation 410: M(n) = 862.4779771693063\n",
      "Generation 411: p = 0.9583088635214515\n",
      "Generation 411: M(n) = 862.4808530082985\n",
      "Generation 412: p = 0.9583120588981094\n",
      "Generation 412: M(n) = 862.4836751530178\n",
      "Generation 413: p = 0.9583151946144642\n",
      "Generation 413: M(n) = 862.4864446059804\n",
      "Generation 414: p = 0.9583182717844226\n",
      "Generation 414: M(n) = 862.4891623509845\n",
      "Generation 415: p = 0.9583212915010939\n",
      "Generation 415: M(n) = 862.4918293534603\n",
      "Generation 416: p = 0.9583242548371781\n",
      "Generation 416: M(n) = 862.4944465608123\n",
      "Generation 417: p = 0.958327162845347\n",
      "Generation 417: M(n) = 862.4970149027564\n",
      "Generation 418: p = 0.9583300165586183\n",
      "Generation 418: M(n) = 862.4995352916497\n",
      "Generation 419: p = 0.9583328169907219\n",
      "Generation 419: M(n) = 862.5020086228151\n",
      "Generation 420: p = 0.9583355651364612\n",
      "Generation 420: M(n) = 862.504435774859\n",
      "Generation 421: p = 0.9583382619720655\n",
      "Generation 421: M(n) = 862.5068176099833\n",
      "Generation 422: p = 0.958340908455537\n",
      "Generation 422: M(n) = 862.5091549742922\n",
      "Generation 423: p = 0.9583435055269913\n",
      "Generation 423: M(n) = 862.5114486980923\n",
      "Generation 424: p = 0.9583460541089914\n",
      "Generation 424: M(n) = 862.5136995961877\n",
      "Generation 425: p = 0.9583485551068752\n",
      "Generation 425: M(n) = 862.5159084681694\n",
      "Generation 426: p = 0.9583510094090771\n",
      "Generation 426: M(n) = 862.5180760986995\n",
      "Generation 427: p = 0.9583534178874439\n",
      "Generation 427: M(n) = 862.5202032577896\n",
      "Generation 428: p = 0.958355781397544\n",
      "Generation 428: M(n) = 862.5222907010747\n",
      "Generation 429: p = 0.9583581007789719\n",
      "Generation 429: M(n) = 862.5243391700815\n",
      "Generation 430: p = 0.9583603768556461\n",
      "Generation 430: M(n) = 862.5263493924917\n",
      "Generation 431: p = 0.9583626104361019\n",
      "Generation 431: M(n) = 862.5283220824007\n",
      "Generation 432: p = 0.9583648023137785\n",
      "Generation 432: M(n) = 862.530257940571\n",
      "Generation 433: p = 0.9583669532673011\n",
      "Generation 433: M(n) = 862.5321576546814\n",
      "Generation 434: p = 0.9583690640607572\n",
      "Generation 434: M(n) = 862.5340218995713\n",
      "Generation 435: p = 0.958371135443968\n",
      "Generation 435: M(n) = 862.5358513374798\n",
      "Generation 436: p = 0.9583731681527553\n",
      "Generation 436: M(n) = 862.5376466182821\n",
      "Generation 437: p = 0.9583751629092023\n",
      "Generation 437: M(n) = 862.5394083797192\n",
      "Generation 438: p = 0.9583771204219103\n",
      "Generation 438: M(n) = 862.5411372476253\n",
      "Generation 439: p = 0.9583790413862504\n",
      "Generation 439: M(n) = 862.5428338361496\n",
      "Generation 440: p = 0.9583809264846107\n",
      "Generation 440: M(n) = 862.5444987479746\n",
      "Generation 441: p = 0.9583827763866384\n",
      "Generation 441: M(n) = 862.54613257453\n",
      "Generation 442: p = 0.9583845917494778\n",
      "Generation 442: M(n) = 862.5477358962036\n",
      "Generation 443: p = 0.9583863732180039\n",
      "Generation 443: M(n) = 862.5493092825463\n",
      "Generation 444: p = 0.9583881214250515\n",
      "Generation 444: M(n) = 862.5508532924756\n",
      "Generation 445: p = 0.9583898369916396\n",
      "Generation 445: M(n) = 862.5523684744732\n",
      "Generation 446: p = 0.9583915205271923\n",
      "Generation 446: M(n) = 862.5538553667799\n",
      "Generation 447: p = 0.9583931726297554\n",
      "Generation 447: M(n) = 862.5553144975877\n",
      "Generation 448: p = 0.9583947938862085\n",
      "Generation 448: M(n) = 862.5567463852265\n",
      "Generation 449: p = 0.9583963848724738\n",
      "Generation 449: M(n) = 862.5581515383486\n",
      "Generation 450: p = 0.9583979461537206\n",
      "Generation 450: M(n) = 862.5595304561094\n",
      "Generation 451: p = 0.9583994782845661\n",
      "Generation 451: M(n) = 862.5608836283446\n",
      "Generation 452: p = 0.9584009818092718\n",
      "Generation 452: M(n) = 862.5622115357443\n",
      "Generation 453: p = 0.9584024572619381\n",
      "Generation 453: M(n) = 862.5635146500235\n",
      "Generation 454: p = 0.9584039051666928\n",
      "Generation 454: M(n) = 862.5647934340905\n",
      "Generation 455: p = 0.9584053260378783\n",
      "Generation 455: M(n) = 862.5660483422099\n",
      "Generation 456: p = 0.9584067203802332\n",
      "Generation 456: M(n) = 862.5672798201655\n",
      "Generation 457: p = 0.9584080886890728\n",
      "Generation 457: M(n) = 862.5684883054175\n",
      "Generation 458: p = 0.958409431450464\n",
      "Generation 458: M(n) = 862.5696742272587\n",
      "Generation 459: p = 0.9584107491413986\n",
      "Generation 459: M(n) = 862.5708380069664\n",
      "Generation 460: p = 0.9584120422299627\n",
      "Generation 460: M(n) = 862.5719800579524\n",
      "Generation 461: p = 0.9584133111755027\n",
      "Generation 461: M(n) = 862.5731007859097\n",
      "Generation 462: p = 0.9584145564287885\n",
      "Generation 462: M(n) = 862.5742005889567\n",
      "Generation 463: p = 0.9584157784321742\n",
      "Generation 463: M(n) = 862.5752798577788\n",
      "Generation 464: p = 0.9584169776197542\n",
      "Generation 464: M(n) = 862.5763389757667\n",
      "Generation 465: p = 0.9584181544175185\n",
      "Generation 465: M(n) = 862.577378319153\n",
      "Generation 466: p = 0.9584193092435034\n",
      "Generation 466: M(n) = 862.5783982571459\n",
      "Generation 467: p = 0.9584204425079399\n",
      "Generation 467: M(n) = 862.5793991520599\n",
      "Generation 468: p = 0.9584215546133998\n",
      "Generation 468: M(n) = 862.5803813594448\n",
      "Generation 469: p = 0.9584226459549386\n",
      "Generation 469: M(n) = 862.5813452282122\n",
      "Generation 470: p = 0.9584237169202358\n",
      "Generation 470: M(n) = 862.5822911007591\n",
      "Generation 471: p = 0.9584247678897323\n",
      "Generation 471: M(n) = 862.5832193130898\n",
      "Generation 472: p = 0.9584257992367664\n",
      "Generation 472: M(n) = 862.5841301949349\n",
      "Generation 473: p = 0.9584268113277055\n",
      "Generation 473: M(n) = 862.5850240698688\n",
      "Generation 474: p = 0.9584278045220764\n",
      "Generation 474: M(n) = 862.5859012554245\n",
      "Generation 475: p = 0.9584287791726939\n",
      "Generation 475: M(n) = 862.5867620632064\n",
      "Generation 476: p = 0.9584297356257848\n",
      "Generation 476: M(n) = 862.5876067990009\n",
      "Generation 477: p = 0.9584306742211122\n",
      "Generation 477: M(n) = 862.5884357628853\n",
      "Generation 478: p = 0.9584315952920948\n",
      "Generation 478: M(n) = 862.589249249334\n",
      "Generation 479: p = 0.9584324991659267\n",
      "Generation 479: M(n) = 862.5900475473235\n",
      "Generation 480: p = 0.9584333861636928\n",
      "Generation 480: M(n) = 862.5908309404348\n",
      "Generation 481: p = 0.9584342566004831\n",
      "Generation 481: M(n) = 862.5915997069541\n",
      "Generation 482: p = 0.9584351107855045\n",
      "Generation 482: M(n) = 862.5923541199719\n",
      "Generation 483: p = 0.958435949022191\n",
      "Generation 483: M(n) = 862.5930944474799\n",
      "Generation 484: p = 0.958436771608311\n",
      "Generation 484: M(n) = 862.5938209524661\n",
      "Generation 485: p = 0.9584375788360735\n",
      "Generation 485: M(n) = 862.5945338930084\n",
      "Generation 486: p = 0.9584383709922315\n",
      "Generation 486: M(n) = 862.5952335223658\n",
      "Generation 487: p = 0.9584391483581842\n",
      "Generation 487: M(n) = 862.5959200890693\n",
      "Generation 488: p = 0.958439911210077\n",
      "Generation 488: M(n) = 862.5965938370093\n",
      "Generation 489: p = 0.9584406598188993\n",
      "Generation 489: M(n) = 862.5972550055227\n",
      "Generation 490: p = 0.9584413944505807\n",
      "Generation 490: M(n) = 862.5979038294776\n",
      "Generation 491: p = 0.9584421153660861\n",
      "Generation 491: M(n) = 862.598540539357\n",
      "Generation 492: p = 0.9584428228215078\n",
      "Generation 492: M(n) = 862.5991653613409\n",
      "Generation 493: p = 0.9584435170681564\n",
      "Generation 493: M(n) = 862.5997785173856\n",
      "Generation 494: p = 0.9584441983526507\n",
      "Generation 494: M(n) = 862.6003802253042\n",
      "Generation 495: p = 0.9584448669170047\n",
      "Generation 495: M(n) = 862.6009706988424\n",
      "Generation 496: p = 0.9584455229987138\n",
      "Generation 496: M(n) = 862.6015501477553\n",
      "Generation 497: p = 0.9584461668308393\n",
      "Generation 497: M(n) = 862.6021187778817\n",
      "Generation 498: p = 0.9584467986420908\n",
      "Generation 498: M(n) = 862.6026767912173\n",
      "Generation 499: p = 0.9584474186569081\n",
      "Generation 499: M(n) = 862.6032243859862\n",
      "Generation 500: p = 0.9584480270955402\n",
      "Generation 500: M(n) = 862.6037617567116\n",
      "Generation 501: p = 0.958448624174124\n",
      "Generation 501: M(n) = 862.6042890942848\n",
      "Generation 502: p = 0.9584492101047609\n",
      "Generation 502: M(n) = 862.604806586033\n",
      "Generation 503: p = 0.9584497850955922\n",
      "Generation 503: M(n) = 862.6053144157858\n",
      "Generation 504: p = 0.958450349350873\n",
      "Generation 504: M(n) = 862.6058127639404\n",
      "Generation 505: p = 0.958450903071045\n",
      "Generation 505: M(n) = 862.6063018075264\n",
      "Generation 506: p = 0.9584514464528071\n",
      "Generation 506: M(n) = 862.6067817202675\n",
      "Generation 507: p = 0.958451979689186\n",
      "Generation 507: M(n) = 862.607252672644\n",
      "Generation 508: p = 0.9584525029696045\n",
      "Generation 508: M(n) = 862.6077148319534\n",
      "Generation 509: p = 0.9584530164799483\n",
      "Generation 509: M(n) = 862.6081683623695\n",
      "Generation 510: p = 0.9584535204026328\n",
      "Generation 510: M(n) = 862.6086134250006\n",
      "Generation 511: p = 0.9584540149166674\n",
      "Generation 511: M(n) = 862.6090501779474\n",
      "Generation 512: p = 0.9584545001977194\n",
      "Generation 512: M(n) = 862.6094787763584\n",
      "Generation 513: p = 0.958454976418176\n",
      "Generation 513: M(n) = 862.6098993724855\n",
      "Generation 514: p = 0.9584554437472061\n",
      "Generation 514: M(n) = 862.610312115738\n",
      "Generation 515: p = 0.95845590235082\n",
      "Generation 515: M(n) = 862.6107171527353\n",
      "Generation 516: p = 0.9584563523919282\n",
      "Generation 516: M(n) = 862.6111146273597\n",
      "Generation 517: p = 0.9584567940303996\n",
      "Generation 517: M(n) = 862.6115046808068\n",
      "Generation 518: p = 0.9584572274231187\n",
      "Generation 518: M(n) = 862.6118874516362\n",
      "Generation 519: p = 0.9584576527240403\n",
      "Generation 519: M(n) = 862.6122630758202\n",
      "Generation 520: p = 0.9584580700842447\n",
      "Generation 520: M(n) = 862.6126316867926\n",
      "Generation 521: p = 0.9584584796519918\n",
      "Generation 521: M(n) = 862.6129934154959\n",
      "Generation 522: p = 0.9584588815727733\n",
      "Generation 522: M(n) = 862.6133483904275\n",
      "Generation 523: p = 0.9584592759893639\n",
      "Generation 523: M(n) = 862.6136967376859\n",
      "Generation 524: p = 0.9584596630418732\n",
      "Generation 524: M(n) = 862.6140385810154\n",
      "Generation 525: p = 0.9584600428677948\n",
      "Generation 525: M(n) = 862.6143740418495\n",
      "Generation 526: p = 0.958460415602055\n",
      "Generation 526: M(n) = 862.6147032393546\n",
      "Generation 527: p = 0.9584607813770607\n",
      "Generation 527: M(n) = 862.6150262904723\n",
      "Generation 528: p = 0.958461140322747\n",
      "Generation 528: M(n) = 862.6153433099606\n",
      "Generation 529: p = 0.9584614925666229\n",
      "Generation 529: M(n) = 862.6156544104351\n",
      "Generation 530: p = 0.9584618382338168\n",
      "Generation 530: M(n) = 862.6159597024086\n",
      "Generation 531: p = 0.9584621774471207\n",
      "Generation 531: M(n) = 862.6162592943306\n",
      "Generation 532: p = 0.958462510327034\n",
      "Generation 532: M(n) = 862.6165532926257\n",
      "Generation 533: p = 0.9584628369918063\n",
      "Generation 533: M(n) = 862.6168418017314\n",
      "Generation 534: p = 0.9584631575574794\n",
      "Generation 534: M(n) = 862.6171249241355\n",
      "Generation 535: p = 0.9584634721379284\n",
      "Generation 535: M(n) = 862.6174027604121\n",
      "Generation 536: p = 0.9584637808449024\n",
      "Generation 536: M(n) = 862.6176754092575\n",
      "Generation 537: p = 0.9584640837880638\n",
      "Generation 537: M(n) = 862.6179429675252\n",
      "Generation 538: p = 0.958464381075028\n",
      "Generation 538: M(n) = 862.6182055302606\n",
      "Generation 539: p = 0.9584646728114007\n",
      "Generation 539: M(n) = 862.6184631907345\n",
      "Generation 540: p = 0.9584649591008161\n",
      "Generation 540: M(n) = 862.6187160404759\n",
      "Generation 541: p = 0.9584652400449732\n",
      "Generation 541: M(n) = 862.6189641693053\n",
      "Generation 542: p = 0.9584655157436726\n",
      "Generation 542: M(n) = 862.6192076653659\n",
      "Generation 543: p = 0.958465786294851\n",
      "Generation 543: M(n) = 862.6194466151553\n",
      "Generation 544: p = 0.958466051794617\n",
      "Generation 544: M(n) = 862.6196811035561\n",
      "Generation 545: p = 0.9584663123372845\n",
      "Generation 545: M(n) = 862.6199112138662\n",
      "Generation 546: p = 0.9584665680154069\n",
      "Generation 546: M(n) = 862.620137027828\n",
      "Generation 547: p = 0.9584668189198089\n",
      "Generation 547: M(n) = 862.620358625658\n",
      "Generation 548: p = 0.95846706513962\n",
      "Generation 548: M(n) = 862.6205760860747\n",
      "Generation 549: p = 0.9584673067623053\n",
      "Generation 549: M(n) = 862.6207894863271\n",
      "Generation 550: p = 0.9584675438736968\n",
      "Generation 550: M(n) = 862.6209989022218\n",
      "Generation 551: p = 0.9584677765580242\n",
      "Generation 551: M(n) = 862.6212044081499\n",
      "Generation 552: p = 0.9584680048979443\n",
      "Generation 552: M(n) = 862.6214060771138\n",
      "Generation 553: p = 0.9584682289745708\n",
      "Generation 553: M(n) = 862.6216039807526\n",
      "Generation 554: p = 0.9584684488675029\n",
      "Generation 554: M(n) = 862.6217981893683\n",
      "Generation 555: p = 0.9584686646548537\n",
      "Generation 555: M(n) = 862.6219887719499\n",
      "Generation 556: p = 0.9584688764132776\n",
      "Generation 556: M(n) = 862.6221757961982\n",
      "Generation 557: p = 0.958469084217998\n",
      "Generation 557: M(n) = 862.6223593285505\n",
      "Generation 558: p = 0.9584692881428338\n",
      "Generation 558: M(n) = 862.6225394342032\n",
      "Generation 559: p = 0.9584694882602258\n",
      "Generation 559: M(n) = 862.6227161771357\n",
      "Generation 560: p = 0.9584696846412618\n",
      "Generation 560: M(n) = 862.6228896201326\n",
      "Generation 561: p = 0.9584698773557029\n",
      "Generation 561: M(n) = 862.6230598248065\n",
      "Generation 562: p = 0.9584700664720073\n",
      "Generation 562: M(n) = 862.6232268516196\n",
      "Generation 563: p = 0.9584702520573551\n",
      "Generation 563: M(n) = 862.6233907599051\n",
      "Generation 564: p = 0.9584704341776723\n",
      "Generation 564: M(n) = 862.6235516078884\n",
      "Generation 565: p = 0.9584706128976538\n",
      "Generation 565: M(n) = 862.6237094527079\n",
      "Generation 566: p = 0.9584707882807866\n",
      "Generation 566: M(n) = 862.6238643504352\n",
      "Generation 567: p = 0.9584709603893724\n",
      "Generation 567: M(n) = 862.6240163560948\n",
      "Generation 568: p = 0.9584711292845498\n",
      "Generation 568: M(n) = 862.6241655236842\n",
      "Generation 569: p = 0.9584712950263157\n",
      "Generation 569: M(n) = 862.6243119061921\n",
      "Generation 570: p = 0.9584714576735468\n",
      "Generation 570: M(n) = 862.6244555556187\n",
      "Generation 571: p = 0.9584716172840209\n",
      "Generation 571: M(n) = 862.6245965229928\n",
      "Generation 572: p = 0.9584717739144364\n",
      "Generation 572: M(n) = 862.6247348583902\n",
      "Generation 573: p = 0.9584719276204335\n",
      "Generation 573: M(n) = 862.6248706109523\n",
      "Generation 574: p = 0.9584720784566136\n",
      "Generation 574: M(n) = 862.6250038289027\n",
      "Generation 575: p = 0.9584722264765585\n",
      "Generation 575: M(n) = 862.6251345595647\n",
      "Generation 576: p = 0.9584723717328496\n",
      "Generation 576: M(n) = 862.625262849378\n",
      "Generation 577: p = 0.9584725142770867\n",
      "Generation 577: M(n) = 862.6253887439153\n",
      "Generation 578: p = 0.9584726541599059\n",
      "Generation 578: M(n) = 862.6255122878983\n",
      "Generation 579: p = 0.9584727914309982\n",
      "Generation 579: M(n) = 862.6256335252139\n",
      "Generation 580: p = 0.9584729261391265\n",
      "Generation 580: M(n) = 862.6257524989293\n",
      "Generation 581: p = 0.9584730583321437\n",
      "Generation 581: M(n) = 862.6258692513079\n",
      "Generation 582: p = 0.9584731880570088\n",
      "Generation 582: M(n) = 862.6259838238237\n",
      "Generation 583: p = 0.9584733153598042\n",
      "Generation 583: M(n) = 862.6260962571768\n",
      "Generation 584: p = 0.958473440285752\n",
      "Generation 584: M(n) = 862.6262065913069\n",
      "Generation 585: p = 0.9584735628792298\n",
      "Generation 585: M(n) = 862.6263148654082\n",
      "Generation 586: p = 0.9584736831837869\n",
      "Generation 586: M(n) = 862.6264211179433\n",
      "Generation 587: p = 0.9584738012421592\n",
      "Generation 587: M(n) = 862.6265253866565\n",
      "Generation 588: p = 0.9584739170962849\n",
      "Generation 588: M(n) = 862.6266277085872\n",
      "Generation 589: p = 0.9584740307873191\n",
      "Generation 589: M(n) = 862.6267281200835\n",
      "Generation 590: p = 0.9584741423556483\n",
      "Generation 590: M(n) = 862.6268266568148\n",
      "Generation 591: p = 0.9584742518409054\n",
      "Generation 591: M(n) = 862.6269233537846\n",
      "Generation 592: p = 0.9584743592819829\n",
      "Generation 592: M(n) = 862.6270182453426\n",
      "Generation 593: p = 0.9584744647170473\n",
      "Generation 593: M(n) = 862.6271113651974\n",
      "Generation 594: p = 0.9584745681835526\n",
      "Generation 594: M(n) = 862.6272027464281\n",
      "Generation 595: p = 0.9584746697182535\n",
      "Generation 595: M(n) = 862.6272924214963\n",
      "Generation 596: p = 0.9584747693572182\n",
      "Generation 596: M(n) = 862.6273804222575\n",
      "Generation 597: p = 0.9584748671358416\n",
      "Generation 597: M(n) = 862.6274667799722\n",
      "Generation 598: p = 0.958474963088858\n",
      "Generation 598: M(n) = 862.6275515253176\n",
      "Generation 599: p = 0.9584750572503529\n",
      "Generation 599: M(n) = 862.6276346883978\n",
      "Generation 600: p = 0.9584751496537753\n",
      "Generation 600: M(n) = 862.6277162987551\n",
      "Generation 601: p = 0.9584752403319501\n",
      "Generation 601: M(n) = 862.6277963853801\n",
      "Generation 602: p = 0.958475329317089\n",
      "Generation 602: M(n) = 862.6278749767222\n",
      "Generation 603: p = 0.9584754166408024\n",
      "Generation 603: M(n) = 862.6279521006994\n",
      "Generation 604: p = 0.9584755023341105\n",
      "Generation 604: M(n) = 862.6280277847088\n",
      "Generation 605: p = 0.9584755864274542\n",
      "Generation 605: M(n) = 862.6281020556356\n",
      "Generation 606: p = 0.9584756689507062\n",
      "Generation 606: M(n) = 862.6281749398632\n",
      "Generation 607: p = 0.9584757499331814\n",
      "Generation 607: M(n) = 862.6282464632826\n",
      "Generation 608: p = 0.9584758294036474\n",
      "Generation 608: M(n) = 862.6283166513011\n",
      "Generation 609: p = 0.9584759073903346\n",
      "Generation 609: M(n) = 862.6283855288517\n",
      "Generation 610: p = 0.9584759839209464\n",
      "Generation 610: M(n) = 862.6284531204019\n",
      "Generation 611: p = 0.9584760590226687\n",
      "Generation 611: M(n) = 862.6285194499624\n",
      "Generation 612: p = 0.9584761327221805\n",
      "Generation 612: M(n) = 862.6285845410956\n",
      "Generation 613: p = 0.9584762050456618\n",
      "Generation 613: M(n) = 862.628648416924\n",
      "Generation 614: p = 0.9584762760188044\n",
      "Generation 614: M(n) = 862.6287111001382\n",
      "Generation 615: p = 0.9584763456668202\n",
      "Generation 615: M(n) = 862.6287726130054\n",
      "Generation 616: p = 0.9584764140144504\n",
      "Generation 616: M(n) = 862.6288329773769\n",
      "Generation 617: p = 0.9584764810859743\n",
      "Generation 617: M(n) = 862.6288922146961\n",
      "Generation 618: p = 0.9584765469052179\n",
      "Generation 618: M(n) = 862.628950346006\n",
      "Generation 619: p = 0.9584766114955623\n",
      "Generation 619: M(n) = 862.6290073919567\n",
      "Generation 620: p = 0.9584766748799519\n",
      "Generation 620: M(n) = 862.6290633728127\n",
      "Generation 621: p = 0.958476737080903\n",
      "Generation 621: M(n) = 862.6291183084602\n",
      "Generation 622: p = 0.9584767981205113\n",
      "Generation 622: M(n) = 862.629172218414\n",
      "Generation 623: p = 0.95847685802046\n",
      "Generation 623: M(n) = 862.6292251218248\n",
      "Generation 624: p = 0.9584769168020275\n",
      "Generation 624: M(n) = 862.6292770374855\n",
      "Generation 625: p = 0.958476974486095\n",
      "Generation 625: M(n) = 862.6293279838383\n",
      "Generation 626: p = 0.9584770310931536\n",
      "Generation 626: M(n) = 862.6293779789809\n",
      "Generation 627: p = 0.9584770866433121\n",
      "Generation 627: M(n) = 862.6294270406731\n",
      "Generation 628: p = 0.9584771411563034\n",
      "Generation 628: M(n) = 862.6294751863434\n",
      "Generation 629: p = 0.9584771946514926\n",
      "Generation 629: M(n) = 862.6295224330944\n",
      "Generation 630: p = 0.9584772471478826\n",
      "Generation 630: M(n) = 862.6295687977099\n",
      "Generation 631: p = 0.9584772986641221\n",
      "Generation 631: M(n) = 862.62961429666\n",
      "Generation 632: p = 0.958477349218511\n",
      "Generation 632: M(n) = 862.6296589461073\n",
      "Generation 633: p = 0.9584773988290081\n",
      "Generation 633: M(n) = 862.6297027619129\n",
      "Generation 634: p = 0.9584774475132365\n",
      "Generation 634: M(n) = 862.6297457596414\n",
      "Generation 635: p = 0.9584774952884905\n",
      "Generation 635: M(n) = 862.6297879545671\n",
      "Generation 636: p = 0.9584775421717412\n",
      "Generation 636: M(n) = 862.6298293616788\n",
      "Generation 637: p = 0.9584775881796431\n",
      "Generation 637: M(n) = 862.6298699956859\n",
      "Generation 638: p = 0.9584776333285399\n",
      "Generation 638: M(n) = 862.6299098710227\n",
      "Generation 639: p = 0.9584776776344697\n",
      "Generation 639: M(n) = 862.6299490018542\n",
      "Generation 640: p = 0.9584777211131714\n",
      "Generation 640: M(n) = 862.6299874020812\n",
      "Generation 641: p = 0.9584777637800902\n",
      "Generation 641: M(n) = 862.6300250853443\n",
      "Generation 642: p = 0.9584778056503825\n",
      "Generation 642: M(n) = 862.63006206503\n",
      "Generation 643: p = 0.9584778467389222\n",
      "Generation 643: M(n) = 862.6300983542747\n",
      "Generation 644: p = 0.9584778870603051\n",
      "Generation 644: M(n) = 862.6301339659693\n",
      "Generation 645: p = 0.9584779266288548\n",
      "Generation 645: M(n) = 862.6301689127645\n",
      "Generation 646: p = 0.9584779654586272\n",
      "Generation 646: M(n) = 862.6302032070743\n",
      "Generation 647: p = 0.9584780035634158\n",
      "Generation 647: M(n) = 862.6302368610811\n",
      "Generation 648: p = 0.9584780409567568\n",
      "Generation 648: M(n) = 862.6302698867402\n",
      "Generation 649: p = 0.9584780776519335\n",
      "Generation 649: M(n) = 862.6303022957829\n",
      "Generation 650: p = 0.958478113661981\n",
      "Generation 650: M(n) = 862.6303340997223\n",
      "Generation 651: p = 0.9584781489996914\n",
      "Generation 651: M(n) = 862.6303653098561\n",
      "Generation 652: p = 0.9584781836776178\n",
      "Generation 652: M(n) = 862.630395937271\n",
      "Generation 653: p = 0.958478217708079\n",
      "Generation 653: M(n) = 862.6304259928471\n",
      "Generation 654: p = 0.9584782511031634\n",
      "Generation 654: M(n) = 862.6304554872609\n",
      "Generation 655: p = 0.9584782838747343\n",
      "Generation 655: M(n) = 862.6304844309898\n",
      "Generation 656: p = 0.9584783160344331\n",
      "Generation 656: M(n) = 862.6305128343155\n",
      "Generation 657: p = 0.9584783475936839\n",
      "Generation 657: M(n) = 862.6305407073278\n",
      "Generation 658: p = 0.9584783785636976\n",
      "Generation 658: M(n) = 862.6305680599281\n",
      "Generation 659: p = 0.9584784089554756\n",
      "Generation 659: M(n) = 862.630594901833\n",
      "Generation 660: p = 0.9584784387798144\n",
      "Generation 660: M(n) = 862.6306212425775\n",
      "Generation 661: p = 0.9584784680473083\n",
      "Generation 661: M(n) = 862.6306470915187\n",
      "Generation 662: p = 0.9584784967683541\n",
      "Generation 662: M(n) = 862.6306724578388\n",
      "Generation 663: p = 0.9584785249531542\n",
      "Generation 663: M(n) = 862.630697350549\n",
      "Generation 664: p = 0.9584785526117211\n",
      "Generation 664: M(n) = 862.6307217784919\n",
      "Generation 665: p = 0.9584785797538798\n",
      "Generation 665: M(n) = 862.630745750345\n",
      "Generation 666: p = 0.9584786063892722\n",
      "Generation 666: M(n) = 862.630769274624\n",
      "Generation 667: p = 0.95847863252736\n",
      "Generation 667: M(n) = 862.6307923596854\n",
      "Generation 668: p = 0.9584786581774283\n",
      "Generation 668: M(n) = 862.6308150137298\n",
      "Generation 669: p = 0.9584786833485887\n",
      "Generation 669: M(n) = 862.6308372448046\n",
      "Generation 670: p = 0.958478708049783\n",
      "Generation 670: M(n) = 862.6308590608071\n",
      "Generation 671: p = 0.9584787322897856\n",
      "Generation 671: M(n) = 862.6308804694868\n",
      "Generation 672: p = 0.9584787560772076\n",
      "Generation 672: M(n) = 862.6309014784489\n",
      "Generation 673: p = 0.9584787794204987\n",
      "Generation 673: M(n) = 862.6309220951565\n",
      "Generation 674: p = 0.9584788023279517\n",
      "Generation 674: M(n) = 862.6309423269332\n",
      "Generation 675: p = 0.9584788248077036\n",
      "Generation 675: M(n) = 862.6309621809661\n",
      "Generation 676: p = 0.9584788468677401\n",
      "Generation 676: M(n) = 862.6309816643079\n",
      "Generation 677: p = 0.9584788685158977\n",
      "Generation 677: M(n) = 862.6310007838798\n",
      "Generation 678: p = 0.9584788897598665\n",
      "Generation 678: M(n) = 862.6310195464736\n",
      "Generation 679: p = 0.9584789106071928\n",
      "Generation 679: M(n) = 862.6310379587543\n",
      "Generation 680: p = 0.9584789310652826\n",
      "Generation 680: M(n) = 862.6310560272626\n",
      "Generation 681: p = 0.9584789511414029\n",
      "Generation 681: M(n) = 862.6310737584171\n",
      "Generation 682: p = 0.9584789708426856\n",
      "Generation 682: M(n) = 862.6310911585164\n",
      "Generation 683: p = 0.9584789901761293\n",
      "Generation 683: M(n) = 862.6311082337414\n",
      "Generation 684: p = 0.9584790091486016\n",
      "Generation 684: M(n) = 862.6311249901581\n",
      "Generation 685: p = 0.9584790277668424\n",
      "Generation 685: M(n) = 862.6311414337188\n",
      "Generation 686: p = 0.9584790460374653\n",
      "Generation 686: M(n) = 862.6311575702646\n",
      "Generation 687: p = 0.9584790639669606\n",
      "Generation 687: M(n) = 862.6311734055279\n",
      "Generation 688: p = 0.9584790815616976\n",
      "Generation 688: M(n) = 862.6311889451338\n",
      "Generation 689: p = 0.9584790988279264\n",
      "Generation 689: M(n) = 862.6312041946026\n",
      "Generation 690: p = 0.9584791157717806\n",
      "Generation 690: M(n) = 862.6312191593512\n",
      "Generation 691: p = 0.9584791323992791\n",
      "Generation 691: M(n) = 862.6312338446958\n",
      "Generation 692: p = 0.9584791487163287\n",
      "Generation 692: M(n) = 862.6312482558529\n",
      "Generation 693: p = 0.9584791647287255\n",
      "Generation 693: M(n) = 862.631262397942\n",
      "Generation 694: p = 0.9584791804421577\n",
      "Generation 694: M(n) = 862.6312762759866\n",
      "Generation 695: p = 0.9584791958622073\n",
      "Generation 695: M(n) = 862.6312898949167\n",
      "Generation 696: p = 0.9584792109943518\n",
      "Generation 696: M(n) = 862.6313032595702\n",
      "Generation 697: p = 0.9584792258439669\n",
      "Generation 697: M(n) = 862.6313163746947\n",
      "Generation 698: p = 0.9584792404163275\n",
      "Generation 698: M(n) = 862.6313292449491\n",
      "Generation 699: p = 0.9584792547166101\n",
      "Generation 699: M(n) = 862.6313418749053\n",
      "Generation 700: p = 0.9584792687498948\n",
      "Generation 700: M(n) = 862.6313542690498\n",
      "Generation 701: p = 0.9584792825211664\n",
      "Generation 701: M(n) = 862.6313664317854\n",
      "Generation 702: p = 0.9584792960353171\n",
      "Generation 702: M(n) = 862.6313783674328\n",
      "Generation 703: p = 0.9584793092971476\n",
      "Generation 703: M(n) = 862.631390080232\n",
      "Generation 704: p = 0.9584793223113689\n",
      "Generation 704: M(n) = 862.6314015743435\n",
      "Generation 705: p = 0.9584793350826039\n",
      "Generation 705: M(n) = 862.6314128538505\n",
      "Generation 706: p = 0.9584793476153894\n",
      "Generation 706: M(n) = 862.63142392276\n",
      "Generation 707: p = 0.9584793599141778\n",
      "Generation 707: M(n) = 862.6314347850038\n",
      "Generation 708: p = 0.9584793719833375\n",
      "Generation 708: M(n) = 862.6314454444406\n",
      "Generation 709: p = 0.9584793838271563\n",
      "Generation 709: M(n) = 862.6314559048569\n",
      "Generation 710: p = 0.9584793954498411\n",
      "Generation 710: M(n) = 862.6314661699688\n",
      "Generation 711: p = 0.9584794068555209\n",
      "Generation 711: M(n) = 862.6314762434225\n",
      "Generation 712: p = 0.9584794180482472\n",
      "Generation 712: M(n) = 862.6314861287966\n",
      "Generation 713: p = 0.9584794290319962\n",
      "Generation 713: M(n) = 862.6314958296026\n",
      "Generation 714: p = 0.9584794398106695\n",
      "Generation 714: M(n) = 862.6315053492866\n",
      "Generation 715: p = 0.9584794503880962\n",
      "Generation 715: M(n) = 862.6315146912303\n",
      "Generation 716: p = 0.9584794607680337\n",
      "Generation 716: M(n) = 862.6315238587523\n",
      "Generation 717: p = 0.9584794709541692\n",
      "Generation 717: M(n) = 862.6315328551091\n",
      "Generation 718: p = 0.9584794809501211\n",
      "Generation 718: M(n) = 862.6315416834965\n",
      "Generation 719: p = 0.9584794907594405\n",
      "Generation 719: M(n) = 862.6315503470507\n",
      "Generation 720: p = 0.9584795003856119\n",
      "Generation 720: M(n) = 862.6315588488493\n",
      "Generation 721: p = 0.9584795098320548\n",
      "Generation 721: M(n) = 862.6315671919123\n",
      "Generation 722: p = 0.9584795191021247\n",
      "Generation 722: M(n) = 862.6315753792035\n",
      "Generation 723: p = 0.958479528199115\n",
      "Generation 723: M(n) = 862.6315834136312\n",
      "Generation 724: p = 0.9584795371262569\n",
      "Generation 724: M(n) = 862.6315912980496\n",
      "Generation 725: p = 0.9584795458867217\n",
      "Generation 725: M(n) = 862.6315990352593\n",
      "Generation 726: p = 0.9584795544836215\n",
      "Generation 726: M(n) = 862.6316066280092\n",
      "Generation 727: p = 0.9584795629200102\n",
      "Generation 727: M(n) = 862.6316140789961\n",
      "Generation 728: p = 0.9584795711988846\n",
      "Generation 728: M(n) = 862.631621390867\n",
      "Generation 729: p = 0.9584795793231856\n",
      "Generation 729: M(n) = 862.6316285662193\n",
      "Generation 730: p = 0.9584795872957993\n",
      "Generation 730: M(n) = 862.6316356076019\n",
      "Generation 731: p = 0.9584795951195576\n",
      "Generation 731: M(n) = 862.631642517516\n",
      "Generation 732: p = 0.95847960279724\n",
      "Generation 732: M(n) = 862.6316492984164\n",
      "Generation 733: p = 0.9584796103315738\n",
      "Generation 733: M(n) = 862.6316559527119\n",
      "Generation 734: p = 0.9584796177252354\n",
      "Generation 734: M(n) = 862.631662482766\n",
      "Generation 735: p = 0.9584796249808512\n",
      "Generation 735: M(n) = 862.6316688908988\n",
      "Generation 736: p = 0.9584796321009987\n",
      "Generation 736: M(n) = 862.6316751793865\n",
      "Generation 737: p = 0.9584796390882073\n",
      "Generation 737: M(n) = 862.631681350463\n",
      "Generation 738: p = 0.9584796459449589\n",
      "Generation 738: M(n) = 862.6316874063205\n",
      "Generation 739: p = 0.9584796526736894\n",
      "Generation 739: M(n) = 862.63169334911\n",
      "Generation 740: p = 0.9584796592767889\n",
      "Generation 740: M(n) = 862.6316991809429\n",
      "Generation 741: p = 0.9584796657566031\n",
      "Generation 741: M(n) = 862.6317049038905\n",
      "Generation 742: p = 0.958479672115434\n",
      "Generation 742: M(n) = 862.6317105199862\n",
      "Generation 743: p = 0.9584796783555403\n",
      "Generation 743: M(n) = 862.6317160312248\n",
      "Generation 744: p = 0.9584796844791387\n",
      "Generation 744: M(n) = 862.631721439564\n",
      "Generation 745: p = 0.9584796904884044\n",
      "Generation 745: M(n) = 862.631726746925\n",
      "Generation 746: p = 0.9584796963854723\n",
      "Generation 746: M(n) = 862.6317319551932\n",
      "Generation 747: p = 0.9584797021724369\n",
      "Generation 747: M(n) = 862.6317370662189\n",
      "Generation 748: p = 0.9584797078513543\n",
      "Generation 748: M(n) = 862.6317420818174\n",
      "Generation 749: p = 0.9584797134242415\n",
      "Generation 749: M(n) = 862.6317470037706\n",
      "Generation 750: p = 0.9584797188930784\n",
      "Generation 750: M(n) = 862.6317518338268\n",
      "Generation 751: p = 0.9584797242598075\n",
      "Generation 751: M(n) = 862.631756573702\n",
      "Generation 752: p = 0.9584797295263355\n",
      "Generation 752: M(n) = 862.6317612250798\n",
      "Generation 753: p = 0.9584797346945331\n",
      "Generation 753: M(n) = 862.6317657896126\n",
      "Generation 754: p = 0.9584797397662362\n",
      "Generation 754: M(n) = 862.6317702689219\n",
      "Generation 755: p = 0.9584797447432465\n",
      "Generation 755: M(n) = 862.6317746645987\n",
      "Generation 756: p = 0.9584797496273318\n",
      "Generation 756: M(n) = 862.6317789782046\n",
      "Generation 757: p = 0.9584797544202273\n",
      "Generation 757: M(n) = 862.6317832112719\n",
      "Generation 758: p = 0.9584797591236355\n",
      "Generation 758: M(n) = 862.6317873653045\n",
      "Generation 759: p = 0.9584797637392272\n",
      "Generation 759: M(n) = 862.6317914417779\n",
      "Generation 760: p = 0.9584797682686421\n",
      "Generation 760: M(n) = 862.6317954421402\n",
      "Generation 761: p = 0.958479772713489\n",
      "Generation 761: M(n) = 862.6317993678124\n",
      "Generation 762: p = 0.9584797770753472\n",
      "Generation 762: M(n) = 862.6318032201891\n",
      "Generation 763: p = 0.9584797813557657\n",
      "Generation 763: M(n) = 862.6318070006388\n",
      "Generation 764: p = 0.9584797855562653\n",
      "Generation 764: M(n) = 862.6318107105044\n",
      "Generation 765: p = 0.9584797896783382\n",
      "Generation 765: M(n) = 862.6318143511038\n",
      "Generation 766: p = 0.9584797937234487\n",
      "Generation 766: M(n) = 862.6318179237302\n",
      "Generation 767: p = 0.9584797976930335\n",
      "Generation 767: M(n) = 862.6318214296526\n",
      "Generation 768: p = 0.9584798015885029\n",
      "Generation 768: M(n) = 862.6318248701166\n",
      "Generation 769: p = 0.9584798054112407\n",
      "Generation 769: M(n) = 862.6318282463444\n",
      "Generation 770: p = 0.9584798091626049\n",
      "Generation 770: M(n) = 862.6318315595353\n",
      "Generation 771: p = 0.958479812843928\n",
      "Generation 771: M(n) = 862.631834810866\n",
      "Generation 772: p = 0.9584798164565178\n",
      "Generation 772: M(n) = 862.6318380014918\n",
      "Generation 773: p = 0.9584798200016575\n",
      "Generation 773: M(n) = 862.631841132546\n",
      "Generation 774: p = 0.9584798234806067\n",
      "Generation 774: M(n) = 862.6318442051409\n",
      "Generation 775: p = 0.958479826894601\n",
      "Generation 775: M(n) = 862.6318472203678\n",
      "Generation 776: p = 0.9584798302448532\n",
      "Generation 776: M(n) = 862.6318501792981\n",
      "Generation 777: p = 0.9584798335325535\n",
      "Generation 777: M(n) = 862.6318530829827\n",
      "Generation 778: p = 0.9584798367588697\n",
      "Generation 778: M(n) = 862.6318559324532\n",
      "Generation 779: p = 0.958479839924948\n",
      "Generation 779: M(n) = 862.6318587287217\n",
      "Generation 780: p = 0.958479843031913\n",
      "Generation 780: M(n) = 862.6318614727816\n",
      "Generation 781: p = 0.9584798460808684\n",
      "Generation 781: M(n) = 862.6318641656076\n",
      "Generation 782: p = 0.9584798490728973\n",
      "Generation 782: M(n) = 862.6318668081562\n",
      "Generation 783: p = 0.9584798520090625\n",
      "Generation 783: M(n) = 862.6318694013664\n",
      "Generation 784: p = 0.9584798548904071\n",
      "Generation 784: M(n) = 862.6318719461592\n",
      "Generation 785: p = 0.9584798577179546\n",
      "Generation 785: M(n) = 862.6318744434386\n",
      "Generation 786: p = 0.9584798604927096\n",
      "Generation 786: M(n) = 862.6318768940919\n",
      "Generation 787: p = 0.9584798632156576\n",
      "Generation 787: M(n) = 862.6318792989892\n",
      "Generation 788: p = 0.9584798658877658\n",
      "Generation 788: M(n) = 862.6318816589853\n",
      "Generation 789: p = 0.9584798685099837\n",
      "Generation 789: M(n) = 862.6318839749183\n",
      "Generation 790: p = 0.9584798710832426\n",
      "Generation 790: M(n) = 862.631886247611\n",
      "Generation 791: p = 0.9584798736084567\n",
      "Generation 791: M(n) = 862.6318884778706\n",
      "Generation 792: p = 0.9584798760865229\n",
      "Generation 792: M(n) = 862.6318906664894\n",
      "Generation 793: p = 0.9584798785183216\n",
      "Generation 793: M(n) = 862.631892814245\n",
      "Generation 794: p = 0.9584798809047167\n",
      "Generation 794: M(n) = 862.6318949219002\n",
      "Generation 795: p = 0.9584798832465558\n",
      "Generation 795: M(n) = 862.6318969902037\n",
      "Generation 796: p = 0.9584798855446708\n",
      "Generation 796: M(n) = 862.6318990198903\n",
      "Generation 797: p = 0.9584798877998781\n",
      "Generation 797: M(n) = 862.631901011681\n",
      "Generation 798: p = 0.9584798900129788\n",
      "Generation 798: M(n) = 862.6319029662833\n",
      "Generation 799: p = 0.9584798921847593\n",
      "Generation 799: M(n) = 862.6319048843916\n",
      "Generation 800: p = 0.9584798943159907\n",
      "Generation 800: M(n) = 862.6319067666873\n",
      "Generation 801: p = 0.9584798964074304\n",
      "Generation 801: M(n) = 862.631908613839\n",
      "Generation 802: p = 0.9584798984598211\n",
      "Generation 802: M(n) = 862.6319104265027\n",
      "Generation 803: p = 0.9584799004738919\n",
      "Generation 803: M(n) = 862.6319122053226\n",
      "Generation 804: p = 0.9584799024503584\n",
      "Generation 804: M(n) = 862.6319139509304\n",
      "Generation 805: p = 0.9584799043899227\n",
      "Generation 805: M(n) = 862.6319156639463\n",
      "Generation 806: p = 0.9584799062932736\n",
      "Generation 806: M(n) = 862.6319173449788\n",
      "Generation 807: p = 0.9584799081610875\n",
      "Generation 807: M(n) = 862.631918994625\n",
      "Generation 808: p = 0.9584799099940278\n",
      "Generation 808: M(n) = 862.6319206134709\n",
      "Generation 809: p = 0.9584799117927455\n",
      "Generation 809: M(n) = 862.6319222020918\n",
      "Generation 810: p = 0.9584799135578798\n",
      "Generation 810: M(n) = 862.6319237610518\n",
      "Generation 811: p = 0.9584799152900575\n",
      "Generation 811: M(n) = 862.6319252909046\n",
      "Generation 812: p = 0.958479916989894\n",
      "Generation 812: M(n) = 862.6319267921939\n",
      "Generation 813: p = 0.9584799186579932\n",
      "Generation 813: M(n) = 862.6319282654529\n",
      "Generation 814: p = 0.9584799202949477\n",
      "Generation 814: M(n) = 862.631929711205\n",
      "Generation 815: p = 0.9584799219013389\n",
      "Generation 815: M(n) = 862.6319311299636\n",
      "Generation 816: p = 0.9584799234777374\n",
      "Generation 816: M(n) = 862.6319325222329\n",
      "Generation 817: p = 0.9584799250247032\n",
      "Generation 817: M(n) = 862.6319338885073\n",
      "Generation 818: p = 0.9584799265427859\n",
      "Generation 818: M(n) = 862.6319352292724\n",
      "Generation 819: p = 0.9584799280325248\n",
      "Generation 819: M(n) = 862.6319365450041\n",
      "Generation 820: p = 0.958479929494449\n",
      "Generation 820: M(n) = 862.6319378361701\n",
      "Generation 821: p = 0.9584799309290779\n",
      "Generation 821: M(n) = 862.631939103229\n",
      "Generation 822: p = 0.9584799323369211\n",
      "Generation 822: M(n) = 862.6319403466308\n",
      "Generation 823: p = 0.9584799337184787\n",
      "Generation 823: M(n) = 862.6319415668174\n",
      "Generation 824: p = 0.9584799350742416\n",
      "Generation 824: M(n) = 862.631942764222\n",
      "Generation 825: p = 0.9584799364046911\n",
      "Generation 825: M(n) = 862.6319439392701\n",
      "Generation 826: p = 0.9584799377103\n",
      "Generation 826: M(n) = 862.631945092379\n",
      "Generation 827: p = 0.9584799389915323\n",
      "Generation 827: M(n) = 862.6319462239586\n",
      "Generation 828: p = 0.9584799402488429\n",
      "Generation 828: M(n) = 862.6319473344106\n",
      "Generation 829: p = 0.9584799414826785\n",
      "Generation 829: M(n) = 862.6319484241295\n",
      "Generation 830: p = 0.9584799426934772\n",
      "Generation 830: M(n) = 862.6319494935025\n",
      "Generation 831: p = 0.9584799438816695\n",
      "Generation 831: M(n) = 862.6319505429094\n",
      "Generation 832: p = 0.9584799450476771\n",
      "Generation 832: M(n) = 862.631951572723\n",
      "Generation 833: p = 0.9584799461919145\n",
      "Generation 833: M(n) = 862.6319525833092\n",
      "Generation 834: p = 0.9584799473147879\n",
      "Generation 834: M(n) = 862.6319535750268\n",
      "Generation 835: p = 0.9584799484166965\n",
      "Generation 835: M(n) = 862.6319545482284\n",
      "Generation 836: p = 0.9584799494980315\n",
      "Generation 836: M(n) = 862.6319555032594\n",
      "Generation 837: p = 0.9584799505591771\n",
      "Generation 837: M(n) = 862.6319564404592\n",
      "Generation 838: p = 0.9584799516005102\n",
      "Generation 838: M(n) = 862.6319573601608\n",
      "Generation 839: p = 0.9584799526224008\n",
      "Generation 839: M(n) = 862.6319582626907\n",
      "Generation 840: p = 0.9584799536252119\n",
      "Generation 840: M(n) = 862.6319591483697\n",
      "Generation 841: p = 0.9584799546092997\n",
      "Generation 841: M(n) = 862.6319600175124\n",
      "Generation 842: p = 0.9584799555750138\n",
      "Generation 842: M(n) = 862.6319608704274\n",
      "Generation 843: p = 0.9584799565226971\n",
      "Generation 843: M(n) = 862.6319617074179\n",
      "Generation 844: p = 0.9584799574526865\n",
      "Generation 844: M(n) = 862.631962528781\n",
      "Generation 845: p = 0.9584799583653122\n",
      "Generation 845: M(n) = 862.6319633348086\n",
      "Generation 846: p = 0.9584799592608985\n",
      "Generation 846: M(n) = 862.631964125787\n",
      "Generation 847: p = 0.9584799601397633\n",
      "Generation 847: M(n) = 862.6319649019972\n",
      "Generation 848: p = 0.9584799610022191\n",
      "Generation 848: M(n) = 862.6319656637149\n",
      "Generation 849: p = 0.9584799618485722\n",
      "Generation 849: M(n) = 862.6319664112108\n",
      "Generation 850: p = 0.958479962679123\n",
      "Generation 850: M(n) = 862.6319671447502\n",
      "Generation 851: p = 0.9584799634941669\n",
      "Generation 851: M(n) = 862.6319678645938\n",
      "Generation 852: p = 0.9584799642939931\n",
      "Generation 852: M(n) = 862.6319685709974\n",
      "Generation 853: p = 0.958479965078886\n",
      "Generation 853: M(n) = 862.6319692642119\n",
      "Generation 854: p = 0.9584799658491243\n",
      "Generation 854: M(n) = 862.6319699444834\n",
      "Generation 855: p = 0.9584799666049816\n",
      "Generation 855: M(n) = 862.6319706120538\n",
      "Generation 856: p = 0.9584799673467265\n",
      "Generation 856: M(n) = 862.6319712671601\n",
      "Generation 857: p = 0.9584799680746223\n",
      "Generation 857: M(n) = 862.631971910035\n",
      "Generation 858: p = 0.9584799687889277\n",
      "Generation 858: M(n) = 862.6319725409069\n",
      "Generation 859: p = 0.9584799694898966\n",
      "Generation 859: M(n) = 862.6319731599999\n",
      "Generation 860: p = 0.9584799701777776\n",
      "Generation 860: M(n) = 862.6319737675339\n",
      "Generation 861: p = 0.9584799708528154\n",
      "Generation 861: M(n) = 862.6319743637248\n",
      "Generation 862: p = 0.9584799715152498\n",
      "Generation 862: M(n) = 862.6319749487843\n",
      "Generation 863: p = 0.9584799721653159\n",
      "Generation 863: M(n) = 862.6319755229202\n",
      "Generation 864: p = 0.9584799728032447\n",
      "Generation 864: M(n) = 862.6319760863366\n",
      "Generation 865: p = 0.9584799734292629\n",
      "Generation 865: M(n) = 862.6319766392336\n",
      "Generation 866: p = 0.9584799740435929\n",
      "Generation 866: M(n) = 862.6319771818074\n",
      "Generation 867: p = 0.9584799746464527\n",
      "Generation 867: M(n) = 862.631977714251\n",
      "Generation 868: p = 0.9584799752380566\n",
      "Generation 868: M(n) = 862.6319782367534\n",
      "Generation 869: p = 0.9584799758186149\n",
      "Generation 869: M(n) = 862.6319787495003\n",
      "Generation 870: p = 0.9584799763883336\n",
      "Generation 870: M(n) = 862.6319792526737\n",
      "Generation 871: p = 0.9584799769474152\n",
      "Generation 871: M(n) = 862.6319797464524\n",
      "Generation 872: p = 0.9584799774960583\n",
      "Generation 872: M(n) = 862.631980231012\n",
      "Generation 873: p = 0.9584799780344577\n",
      "Generation 873: M(n) = 862.6319807065244\n",
      "Generation 874: p = 0.9584799785628049\n",
      "Generation 874: M(n) = 862.6319811731586\n",
      "Generation 875: p = 0.9584799790812873\n",
      "Generation 875: M(n) = 862.6319816310804\n",
      "Generation 876: p = 0.9584799795900893\n",
      "Generation 876: M(n) = 862.6319820804524\n",
      "Generation 877: p = 0.9584799800893916\n",
      "Generation 877: M(n) = 862.6319825214343\n",
      "Generation 878: p = 0.9584799805793714\n",
      "Generation 878: M(n) = 862.6319829541826\n",
      "Generation 879: p = 0.9584799810602029\n",
      "Generation 879: M(n) = 862.6319833788513\n",
      "Generation 880: p = 0.9584799815320569\n",
      "Generation 880: M(n) = 862.6319837955909\n",
      "Generation 881: p = 0.9584799819951011\n",
      "Generation 881: M(n) = 862.6319842045498\n",
      "Generation 882: p = 0.9584799824494997\n",
      "Generation 882: M(n) = 862.631984605873\n",
      "Generation 883: p = 0.9584799828954144\n",
      "Generation 883: M(n) = 862.6319849997031\n",
      "Generation 884: p = 0.9584799833330035\n",
      "Generation 884: M(n) = 862.6319853861802\n",
      "Generation 885: p = 0.9584799837624224\n",
      "Generation 885: M(n) = 862.6319857654413\n",
      "Generation 886: p = 0.9584799841838236\n",
      "Generation 886: M(n) = 862.6319861376213\n",
      "Generation 887: p = 0.9584799845973571\n",
      "Generation 887: M(n) = 862.6319865028526\n",
      "Generation 888: p = 0.9584799850031696\n",
      "Generation 888: M(n) = 862.6319868612646\n",
      "Generation 889: p = 0.9584799854014051\n",
      "Generation 889: M(n) = 862.6319872129848\n",
      "Generation 890: p = 0.9584799857922053\n",
      "Generation 890: M(n) = 862.631987558138\n",
      "Generation 891: p = 0.9584799861757088\n",
      "Generation 891: M(n) = 862.6319878968469\n",
      "Generation 892: p = 0.9584799865520521\n",
      "Generation 892: M(n) = 862.6319882292319\n",
      "Generation 893: p = 0.9584799869213687\n",
      "Generation 893: M(n) = 862.6319885554109\n",
      "Generation 894: p = 0.9584799872837899\n",
      "Generation 894: M(n) = 862.6319888754999\n",
      "Generation 895: p = 0.9584799876394444\n",
      "Generation 895: M(n) = 862.6319891896127\n",
      "Generation 896: p = 0.9584799879884586\n",
      "Generation 896: M(n) = 862.6319894978607\n",
      "Generation 897: p = 0.9584799883309563\n",
      "Generation 897: M(n) = 862.6319898003534\n",
      "Generation 898: p = 0.9584799886670593\n",
      "Generation 898: M(n) = 862.6319900971984\n",
      "Generation 899: p = 0.958479988996887\n",
      "Generation 899: M(n) = 862.631990388501\n",
      "Generation 900: p = 0.9584799893205567\n",
      "Generation 900: M(n) = 862.6319906743647\n",
      "Generation 901: p = 0.958479989638183\n",
      "Generation 901: M(n) = 862.6319909548912\n",
      "Generation 902: p = 0.9584799899498792\n",
      "Generation 902: M(n) = 862.63199123018\n",
      "Generation 903: p = 0.9584799902557556\n",
      "Generation 903: M(n) = 862.6319915003289\n",
      "Generation 904: p = 0.958479990555921\n",
      "Generation 904: M(n) = 862.631991765434\n",
      "Generation 905: p = 0.9584799908504822\n",
      "Generation 905: M(n) = 862.6319920255893\n",
      "Generation 906: p = 0.9584799911395436\n",
      "Generation 906: M(n) = 862.6319922808873\n",
      "Generation 907: p = 0.958479991423208\n",
      "Generation 907: M(n) = 862.6319925314186\n",
      "Generation 908: p = 0.9584799917015763\n",
      "Generation 908: M(n) = 862.6319927772723\n",
      "Generation 909: p = 0.958479991974747\n",
      "Generation 909: M(n) = 862.6319930185357\n",
      "Generation 910: p = 0.9584799922428174\n",
      "Generation 910: M(n) = 862.6319932552946\n",
      "Generation 911: p = 0.9584799925058829\n",
      "Generation 911: M(n) = 862.6319934876329\n",
      "Generation 912: p = 0.9584799927640366\n",
      "Generation 912: M(n) = 862.6319937156334\n",
      "Generation 913: p = 0.9584799930173704\n",
      "Generation 913: M(n) = 862.6319939393768\n",
      "Generation 914: p = 0.9584799932659742\n",
      "Generation 914: M(n) = 862.6319941589428\n",
      "Generation 915: p = 0.9584799935099364\n",
      "Generation 915: M(n) = 862.6319943744093\n",
      "Generation 916: p = 0.9584799937493437\n",
      "Generation 916: M(n) = 862.6319945858529\n",
      "Generation 917: p = 0.958479993984281\n",
      "Generation 917: M(n) = 862.6319947933487\n",
      "Generation 918: p = 0.9584799942148319\n",
      "Generation 918: M(n) = 862.6319949969703\n",
      "Generation 919: p = 0.9584799944410781\n",
      "Generation 919: M(n) = 862.6319951967902\n",
      "Generation 920: p = 0.9584799946631002\n",
      "Generation 920: M(n) = 862.6319953928793\n",
      "Generation 921: p = 0.958479994880977\n",
      "Generation 921: M(n) = 862.6319955853072\n",
      "Generation 922: p = 0.9584799950947858\n",
      "Generation 922: M(n) = 862.6319957741423\n",
      "Generation 923: p = 0.9584799953046026\n",
      "Generation 923: M(n) = 862.6319959594517\n",
      "Generation 924: p = 0.9584799955105019\n",
      "Generation 924: M(n) = 862.6319961413012\n",
      "Generation 925: p = 0.9584799957125569\n",
      "Generation 925: M(n) = 862.6319963197554\n",
      "Generation 926: p = 0.9584799959108394\n",
      "Generation 926: M(n) = 862.6319964948779\n",
      "Generation 927: p = 0.9584799961054198\n",
      "Generation 927: M(n) = 862.6319966667305\n",
      "Generation 928: p = 0.9584799962963673\n",
      "Generation 928: M(n) = 862.6319968353746\n",
      "Generation 929: p = 0.9584799964837496\n",
      "Generation 929: M(n) = 862.63199700087\n",
      "Generation 930: p = 0.9584799966676333\n",
      "Generation 930: M(n) = 862.6319971632754\n",
      "Generation 931: p = 0.9584799968480838\n",
      "Generation 931: M(n) = 862.6319973226487\n",
      "Generation 932: p = 0.9584799970251652\n",
      "Generation 932: M(n) = 862.6319974790462\n",
      "Generation 933: p = 0.9584799971989402\n",
      "Generation 933: M(n) = 862.6319976325236\n",
      "Generation 934: p = 0.9584799973694706\n",
      "Generation 934: M(n) = 862.6319977831355\n",
      "Generation 935: p = 0.9584799975368172\n",
      "Generation 935: M(n) = 862.6319979309354\n",
      "Generation 936: p = 0.9584799977010393\n",
      "Generation 936: M(n) = 862.6319980759757\n",
      "Generation 937: p = 0.9584799978621953\n",
      "Generation 937: M(n) = 862.631998218308\n",
      "Generation 938: p = 0.9584799980203422\n",
      "Generation 938: M(n) = 862.6319983579829\n",
      "Generation 939: p = 0.9584799981755365\n",
      "Generation 939: M(n) = 862.6319984950499\n",
      "Generation 940: p = 0.9584799983278331\n",
      "Generation 940: M(n) = 862.6319986295576\n",
      "Generation 941: p = 0.9584799984772863\n",
      "Generation 941: M(n) = 862.6319987615541\n",
      "Generation 942: p = 0.958479998623949\n",
      "Generation 942: M(n) = 862.631998891086\n",
      "Generation 943: p = 0.9584799987678734\n",
      "Generation 943: M(n) = 862.6319990181995\n",
      "Generation 944: p = 0.9584799989091106\n",
      "Generation 944: M(n) = 862.6319991429398\n",
      "Generation 945: p = 0.9584799990477109\n",
      "Generation 945: M(n) = 862.6319992653509\n",
      "Generation 946: p = 0.9584799991837233\n",
      "Generation 946: M(n) = 862.6319993854767\n",
      "Generation 947: p = 0.9584799993171963\n",
      "Generation 947: M(n) = 862.6319995033596\n",
      "Generation 948: p = 0.9584799994481773\n",
      "Generation 948: M(n) = 862.6319996190415\n",
      "Generation 949: p = 0.9584799995767128\n",
      "Generation 949: M(n) = 862.6319997325635\n",
      "Generation 950: p = 0.9584799997028484\n",
      "Generation 950: M(n) = 862.631999843966\n",
      "Generation 951: p = 0.9584799998266289\n",
      "Generation 951: M(n) = 862.6319999532885\n",
      "Generation 952: p = 0.9584799999480984\n",
      "Generation 952: M(n) = 862.6320000605699\n",
      "Generation 953: p = 0.9584800000672999\n",
      "Generation 953: M(n) = 862.6320001658482\n",
      "Generation 954: p = 0.9584800001842758\n",
      "Generation 954: M(n) = 862.6320002691609\n",
      "Generation 955: p = 0.9584800002990677\n",
      "Generation 955: M(n) = 862.6320003705446\n",
      "Generation 956: p = 0.9584800004117162\n",
      "Generation 956: M(n) = 862.6320004700355\n",
      "Generation 957: p = 0.9584800005222616\n",
      "Generation 957: M(n) = 862.6320005676687\n",
      "Generation 958: p = 0.958480000630743\n",
      "Generation 958: M(n) = 862.6320006634791\n",
      "Generation 959: p = 0.958480000737199\n",
      "Generation 959: M(n) = 862.6320007575006\n",
      "Generation 960: p = 0.9584800008416673\n",
      "Generation 960: M(n) = 862.6320008497665\n",
      "Generation 961: p = 0.9584800009441851\n",
      "Generation 961: M(n) = 862.6320009403099\n",
      "Generation 962: p = 0.9584800010447888\n",
      "Generation 962: M(n) = 862.6320010291628\n",
      "Generation 963: p = 0.9584800011435142\n",
      "Generation 963: M(n) = 862.6320011163566\n",
      "Generation 964: p = 0.9584800012403962\n",
      "Generation 964: M(n) = 862.6320012019225\n",
      "Generation 965: p = 0.9584800013354695\n",
      "Generation 965: M(n) = 862.6320012858909\n",
      "Generation 966: p = 0.9584800014287677\n",
      "Generation 966: M(n) = 862.6320013682914\n",
      "Generation 967: p = 0.9584800015203238\n",
      "Generation 967: M(n) = 862.6320014491534\n",
      "Generation 968: p = 0.9584800016101706\n",
      "Generation 968: M(n) = 862.6320015285058\n",
      "Generation 969: p = 0.9584800016983398\n",
      "Generation 969: M(n) = 862.6320016063765\n",
      "Generation 970: p = 0.9584800017848628\n",
      "Generation 970: M(n) = 862.6320016827933\n",
      "Generation 971: p = 0.9584800018697703\n",
      "Generation 971: M(n) = 862.6320017577833\n",
      "Generation 972: p = 0.9584800019530926\n",
      "Generation 972: M(n) = 862.6320018313733\n",
      "Generation 973: p = 0.9584800020348592\n",
      "Generation 973: M(n) = 862.6320019035892\n",
      "Generation 974: p = 0.9584800021150991\n",
      "Generation 974: M(n) = 862.6320019744568\n",
      "Generation 975: p = 0.9584800021938409\n",
      "Generation 975: M(n) = 862.6320020440013\n",
      "Generation 976: p = 0.9584800022711125\n",
      "Generation 976: M(n) = 862.6320021122473\n",
      "Generation 977: p = 0.9584800023469414\n",
      "Generation 977: M(n) = 862.6320021792191\n",
      "Generation 978: p = 0.9584800024213546\n",
      "Generation 978: M(n) = 862.6320022449405\n",
      "Generation 979: p = 0.9584800024943784\n",
      "Generation 979: M(n) = 862.6320023094348\n",
      "Generation 980: p = 0.9584800025660387\n",
      "Generation 980: M(n) = 862.632002372725\n",
      "Generation 981: p = 0.9584800026363611\n",
      "Generation 981: M(n) = 862.6320024348335\n",
      "Generation 982: p = 0.9584800027053705\n",
      "Generation 982: M(n) = 862.6320024957823\n",
      "Generation 983: p = 0.9584800027730915\n",
      "Generation 983: M(n) = 862.6320025555933\n",
      "Generation 984: p = 0.9584800028395482\n",
      "Generation 984: M(n) = 862.6320026142876\n",
      "Generation 985: p = 0.958480002904764\n",
      "Generation 985: M(n) = 862.6320026718859\n",
      "Generation 986: p = 0.958480002968762\n",
      "Generation 986: M(n) = 862.6320027284087\n",
      "Generation 987: p = 0.9584800030315652\n",
      "Generation 987: M(n) = 862.6320027838763\n",
      "Generation 988: p = 0.9584800030931958\n",
      "Generation 988: M(n) = 862.6320028383082\n",
      "Generation 989: p = 0.9584800031536758\n",
      "Generation 989: M(n) = 862.6320028917238\n",
      "Generation 990: p = 0.9584800032130264\n",
      "Generation 990: M(n) = 862.6320029441421\n",
      "Generation 991: p = 0.9584800032712689\n",
      "Generation 991: M(n) = 862.6320029955817\n",
      "Generation 992: p = 0.9584800033284241\n",
      "Generation 992: M(n) = 862.632003046061\n",
      "Generation 993: p = 0.9584800033845122\n",
      "Generation 993: M(n) = 862.6320030955977\n",
      "Generation 994: p = 0.958480003439553\n",
      "Generation 994: M(n) = 862.6320031442095\n",
      "Generation 995: p = 0.9584800034935661\n",
      "Generation 995: M(n) = 862.6320031919137\n",
      "Generation 996: p = 0.9584800035465707\n",
      "Generation 996: M(n) = 862.6320032387272\n",
      "Generation 997: p = 0.9584800035985858\n",
      "Generation 997: M(n) = 862.6320032846667\n",
      "Generation 998: p = 0.9584800036496296\n",
      "Generation 998: M(n) = 862.6320033297484\n",
      "Generation 999: p = 0.9584800036997204\n",
      "Generation 999: M(n) = 862.6320033739885\n",
      "Generation 1000: p = 0.9584800037488761\n",
      "Generation 1000: M(n) = 862.6320034174025\n",
      "Generation 1001: p = 0.958480003797114\n",
      "Generation 1001: M(n) = 862.632003460006\n",
      "Generation 1002: p = 0.9584800038444511\n",
      "Generation 1002: M(n) = 862.632003501814\n",
      "Generation 1003: p = 0.9584800038909044\n",
      "Generation 1003: M(n) = 862.6320035428414\n",
      "Generation 1004: p = 0.9584800039364905\n",
      "Generation 1004: M(n) = 862.6320035831028\n",
      "Generation 1005: p = 0.9584800039812253\n",
      "Generation 1005: M(n) = 862.6320036226125\n",
      "Generation 1006: p = 0.958480004025125\n",
      "Generation 1006: M(n) = 862.6320036613846\n",
      "Generation 1007: p = 0.9584800040682051\n",
      "Generation 1007: M(n) = 862.6320036994327\n",
      "Generation 1008: p = 0.9584800041104808\n",
      "Generation 1008: M(n) = 862.6320037367705\n",
      "Generation 1009: p = 0.9584800041519672\n",
      "Generation 1009: M(n) = 862.6320037734112\n",
      "Generation 1010: p = 0.9584800041926791\n",
      "Generation 1010: M(n) = 862.6320038093677\n",
      "Generation 1011: p = 0.9584800042326308\n",
      "Generation 1011: M(n) = 862.6320038446529\n",
      "Generation 1012: p = 0.9584800042718365\n",
      "Generation 1012: M(n) = 862.6320038792793\n",
      "Generation 1013: p = 0.9584800043103103\n",
      "Generation 1013: M(n) = 862.6320039132592\n",
      "Generation 1014: p = 0.9584800043480657\n",
      "Generation 1014: M(n) = 862.6320039466045\n",
      "Generation 1015: p = 0.9584800043851162\n",
      "Generation 1015: M(n) = 862.6320039793274\n",
      "Generation 1016: p = 0.9584800044214749\n",
      "Generation 1016: M(n) = 862.6320040114392\n",
      "Generation 1017: p = 0.9584800044571546\n",
      "Generation 1017: M(n) = 862.6320040429515\n",
      "Generation 1018: p = 0.9584800044921683\n",
      "Generation 1018: M(n) = 862.6320040738755\n",
      "Generation 1019: p = 0.9584800045265283\n",
      "Generation 1019: M(n) = 862.632004104222\n",
      "Generation 1020: p = 0.9584800045602466\n",
      "Generation 1020: M(n) = 862.6320041340019\n",
      "Generation 1021: p = 0.9584800045933355\n",
      "Generation 1021: M(n) = 862.6320041632259\n",
      "Generation 1022: p = 0.9584800046258066\n",
      "Generation 1022: M(n) = 862.6320041919043\n",
      "Generation 1023: p = 0.9584800046576715\n",
      "Generation 1023: M(n) = 862.6320042200472\n",
      "Generation 1024: p = 0.9584800046889413\n",
      "Generation 1024: M(n) = 862.6320042476647\n",
      "Generation 1025: p = 0.9584800047196274\n",
      "Generation 1025: M(n) = 862.6320042747665\n",
      "Generation 1026: p = 0.9584800047497405\n",
      "Generation 1026: M(n) = 862.6320043013623\n",
      "Generation 1027: p = 0.9584800047792914\n",
      "Generation 1027: M(n) = 862.6320043274615\n",
      "Generation 1028: p = 0.9584800048082905\n",
      "Generation 1028: M(n) = 862.6320043530734\n",
      "Generation 1029: p = 0.9584800048367482\n",
      "Generation 1029: M(n) = 862.6320043782072\n",
      "Generation 1030: p = 0.9584800048646747\n",
      "Generation 1030: M(n) = 862.6320044028716\n",
      "Generation 1031: p = 0.9584800048920796\n",
      "Generation 1031: M(n) = 862.6320044270757\n",
      "Generation 1032: p = 0.958480004918973\n",
      "Generation 1032: M(n) = 862.6320044508277\n",
      "Generation 1033: p = 0.9584800049453641\n",
      "Generation 1033: M(n) = 862.6320044741362\n",
      "Generation 1034: p = 0.9584800049712625\n",
      "Generation 1034: M(n) = 862.6320044970097\n",
      "Generation 1035: p = 0.9584800049966774\n",
      "Generation 1035: M(n) = 862.632004519456\n",
      "Generation 1036: p = 0.9584800050216178\n",
      "Generation 1036: M(n) = 862.6320045414833\n",
      "Generation 1037: p = 0.9584800050460925\n",
      "Generation 1037: M(n) = 862.6320045630993\n",
      "Generation 1038: p = 0.9584800050701103\n",
      "Generation 1038: M(n) = 862.6320045843116\n",
      "Generation 1039: p = 0.9584800050936796\n",
      "Generation 1039: M(n) = 862.6320046051279\n",
      "Generation 1040: p = 0.9584800051168088\n",
      "Generation 1040: M(n) = 862.6320046255555\n",
      "Generation 1041: p = 0.9584800051395062\n",
      "Generation 1041: M(n) = 862.6320046456018\n",
      "Generation 1042: p = 0.9584800051617798\n",
      "Generation 1042: M(n) = 862.6320046652738\n",
      "Generation 1043: p = 0.9584800051836376\n",
      "Generation 1043: M(n) = 862.6320046845785\n",
      "Generation 1044: p = 0.9584800052050872\n",
      "Generation 1044: M(n) = 862.6320047035227\n",
      "Generation 1045: p = 0.9584800052261364\n",
      "Generation 1045: M(n) = 862.6320047221134\n",
      "Generation 1046: p = 0.9584800052467927\n",
      "Generation 1046: M(n) = 862.6320047403568\n",
      "Generation 1047: p = 0.9584800052670631\n",
      "Generation 1047: M(n) = 862.6320047582597\n",
      "Generation 1048: p = 0.9584800052869552\n",
      "Generation 1048: M(n) = 862.6320047758282\n",
      "Generation 1049: p = 0.9584800053064758\n",
      "Generation 1049: M(n) = 862.6320047930687\n",
      "Generation 1050: p = 0.9584800053256319\n",
      "Generation 1050: M(n) = 862.6320048099874\n",
      "Generation 1051: p = 0.9584800053444305\n",
      "Generation 1051: M(n) = 862.6320048265902\n",
      "Generation 1052: p = 0.958480005362878\n",
      "Generation 1052: M(n) = 862.632004842883\n",
      "Generation 1053: p = 0.9584800053809811\n",
      "Generation 1053: M(n) = 862.6320048588716\n",
      "Generation 1054: p = 0.9584800053987462\n",
      "Generation 1054: M(n) = 862.6320048745616\n",
      "Generation 1055: p = 0.9584800054161796\n",
      "Generation 1055: M(n) = 862.6320048899588\n",
      "Generation 1056: p = 0.9584800054332876\n",
      "Generation 1056: M(n) = 862.6320049050685\n",
      "Generation 1057: p = 0.9584800054500761\n",
      "Generation 1057: M(n) = 862.632004919896\n",
      "Generation 1058: p = 0.9584800054665511\n",
      "Generation 1058: M(n) = 862.6320049344467\n",
      "Generation 1059: p = 0.9584800054827186\n",
      "Generation 1059: M(n) = 862.6320049487258\n",
      "Generation 1060: p = 0.9584800054985843\n",
      "Generation 1060: M(n) = 862.6320049627383\n",
      "Generation 1061: p = 0.9584800055141537\n",
      "Generation 1061: M(n) = 862.6320049764892\n",
      "Generation 1062: p = 0.9584800055294324\n",
      "Generation 1062: M(n) = 862.6320049899832\n",
      "Generation 1063: p = 0.9584800055444258\n",
      "Generation 1063: M(n) = 862.6320050032253\n",
      "Generation 1064: p = 0.9584800055591393\n",
      "Generation 1064: M(n) = 862.6320050162202\n",
      "Generation 1065: p = 0.958480005573578\n",
      "Generation 1065: M(n) = 862.6320050289725\n",
      "Generation 1066: p = 0.9584800055877472\n",
      "Generation 1066: M(n) = 862.6320050414865\n",
      "Generation 1067: p = 0.9584800056016517\n",
      "Generation 1067: M(n) = 862.632005053767\n",
      "Generation 1068: p = 0.9584800056152967\n",
      "Generation 1068: M(n) = 862.6320050658182\n",
      "Generation 1069: p = 0.958480005628687\n",
      "Generation 1069: M(n) = 862.6320050776445\n",
      "Generation 1070: p = 0.9584800056418272\n",
      "Generation 1070: M(n) = 862.6320050892499\n",
      "Generation 1071: p = 0.9584800056547221\n",
      "Generation 1071: M(n) = 862.6320051006386\n",
      "Generation 1072: p = 0.9584800056673762\n",
      "Generation 1072: M(n) = 862.6320051118147\n",
      "Generation 1073: p = 0.9584800056797941\n",
      "Generation 1073: M(n) = 862.6320051227821\n",
      "Generation 1074: p = 0.9584800056919801\n",
      "Generation 1074: M(n) = 862.6320051335448\n",
      "Generation 1075: p = 0.9584800057039387\n",
      "Generation 1075: M(n) = 862.6320051441065\n",
      "Generation 1076: p = 0.9584800057156739\n",
      "Generation 1076: M(n) = 862.632005154471\n",
      "Generation 1077: p = 0.95848000572719\n",
      "Generation 1077: M(n) = 862.632005164642\n",
      "Generation 1078: p = 0.9584800057384911\n",
      "Generation 1078: M(n) = 862.6320051746231\n",
      "Generation 1079: p = 0.9584800057495813\n",
      "Generation 1079: M(n) = 862.6320051844178\n",
      "Generation 1080: p = 0.9584800057604642\n",
      "Generation 1080: M(n) = 862.6320051940296\n",
      "Generation 1081: p = 0.958480005771144\n",
      "Generation 1081: M(n) = 862.632005203462\n",
      "Generation 1082: p = 0.9584800057816244\n",
      "Generation 1082: M(n) = 862.6320052127182\n",
      "Generation 1083: p = 0.9584800057919092\n",
      "Generation 1083: M(n) = 862.6320052218017\n",
      "Generation 1084: p = 0.9584800058020019\n",
      "Generation 1084: M(n) = 862.6320052307155\n",
      "Generation 1085: p = 0.9584800058119062\n",
      "Generation 1085: M(n) = 862.632005239463\n",
      "Generation 1086: p = 0.9584800058216255\n",
      "Generation 1086: M(n) = 862.6320052480471\n",
      "Generation 1087: p = 0.9584800058311634\n",
      "Generation 1087: M(n) = 862.632005256471\n",
      "Generation 1088: p = 0.9584800058405233\n",
      "Generation 1088: M(n) = 862.6320052647375\n",
      "Generation 1089: p = 0.9584800058497083\n",
      "Generation 1089: M(n) = 862.6320052728497\n",
      "Generation 1090: p = 0.958480005858722\n",
      "Generation 1090: M(n) = 862.6320052808105\n",
      "Generation 1091: p = 0.9584800058675672\n",
      "Generation 1091: M(n) = 862.6320052886226\n",
      "Generation 1092: p = 0.9584800058762474\n",
      "Generation 1092: M(n) = 862.6320052962889\n",
      "Generation 1093: p = 0.9584800058847655\n",
      "Generation 1093: M(n) = 862.6320053038121\n",
      "Generation 1094: p = 0.9584800058931245\n",
      "Generation 1094: M(n) = 862.6320053111948\n",
      "Generation 1095: p = 0.9584800059013275\n",
      "Generation 1095: M(n) = 862.6320053184396\n",
      "Generation 1096: p = 0.9584800059093773\n",
      "Generation 1096: M(n) = 862.6320053255491\n",
      "Generation 1097: p = 0.9584800059172768\n",
      "Generation 1097: M(n) = 862.6320053325259\n",
      "Generation 1098: p = 0.9584800059250287\n",
      "Generation 1098: M(n) = 862.6320053393724\n",
      "Generation 1099: p = 0.958480005932636\n",
      "Generation 1099: M(n) = 862.6320053460912\n",
      "Generation 1100: p = 0.9584800059401013\n",
      "Generation 1100: M(n) = 862.6320053526845\n",
      "Generation 1101: p = 0.9584800059474272\n",
      "Generation 1101: M(n) = 862.6320053591546\n",
      "Generation 1102: p = 0.9584800059546162\n",
      "Generation 1102: M(n) = 862.632005365504\n",
      "Generation 1103: p = 0.9584800059616712\n",
      "Generation 1103: M(n) = 862.6320053717349\n",
      "Generation 1104: p = 0.9584800059685943\n",
      "Generation 1104: M(n) = 862.6320053778494\n",
      "Generation 1105: p = 0.9584800059753882\n",
      "Generation 1105: M(n) = 862.6320053838497\n",
      "Generation 1106: p = 0.9584800059820552\n",
      "Generation 1106: M(n) = 862.632005389738\n",
      "Generation 1107: p = 0.9584800059885977\n",
      "Generation 1107: M(n) = 862.6320053955163\n",
      "Generation 1108: p = 0.9584800059950181\n",
      "Generation 1108: M(n) = 862.6320054011868\n",
      "Generation 1109: p = 0.9584800060013187\n",
      "Generation 1109: M(n) = 862.6320054067514\n",
      "Generation 1110: p = 0.9584800060075016\n",
      "Generation 1110: M(n) = 862.6320054122122\n",
      "Generation 1111: p = 0.9584800060135691\n",
      "Generation 1111: M(n) = 862.6320054175709\n",
      "Generation 1112: p = 0.9584800060195232\n",
      "Generation 1112: M(n) = 862.6320054228296\n",
      "Generation 1113: p = 0.9584800060253662\n",
      "Generation 1113: M(n) = 862.6320054279901\n",
      "Generation 1114: p = 0.9584800060311001\n",
      "Generation 1114: M(n) = 862.6320054330542\n",
      "Generation 1115: p = 0.9584800060367269\n",
      "Generation 1115: M(n) = 862.6320054380238\n",
      "Generation 1116: p = 0.9584800060422487\n",
      "Generation 1116: M(n) = 862.6320054429007\n",
      "Generation 1117: p = 0.9584800060476674\n",
      "Generation 1117: M(n) = 862.6320054476864\n",
      "Generation 1118: p = 0.9584800060529849\n",
      "Generation 1118: M(n) = 862.6320054523828\n",
      "Generation 1119: p = 0.9584800060582032\n",
      "Generation 1119: M(n) = 862.6320054569916\n",
      "Generation 1120: p = 0.958480006063324\n",
      "Generation 1120: M(n) = 862.6320054615143\n",
      "Generation 1121: p = 0.9584800060683492\n",
      "Generation 1121: M(n) = 862.6320054659525\n",
      "Generation 1122: p = 0.9584800060732805\n",
      "Generation 1122: M(n) = 862.6320054703078\n",
      "Generation 1123: p = 0.9584800060781198\n",
      "Generation 1123: M(n) = 862.6320054745819\n",
      "Generation 1124: p = 0.9584800060828688\n",
      "Generation 1124: M(n) = 862.6320054787761\n",
      "Generation 1125: p = 0.958480006087529\n",
      "Generation 1125: M(n) = 862.632005482892\n",
      "Generation 1126: p = 0.9584800060921023\n",
      "Generation 1126: M(n) = 862.6320054869311\n",
      "Generation 1127: p = 0.9584800060965901\n",
      "Generation 1127: M(n) = 862.6320054908948\n",
      "Generation 1128: p = 0.9584800061009943\n",
      "Generation 1128: M(n) = 862.6320054947845\n",
      "Generation 1129: p = 0.9584800061053161\n",
      "Generation 1129: M(n) = 862.6320054986015\n",
      "Generation 1130: p = 0.9584800061095573\n",
      "Generation 1130: M(n) = 862.6320055023474\n",
      "Generation 1131: p = 0.9584800061137193\n",
      "Generation 1131: M(n) = 862.6320055060232\n",
      "Generation 1132: p = 0.9584800061178036\n",
      "Generation 1132: M(n) = 862.6320055096304\n",
      "Generation 1133: p = 0.9584800061218116\n",
      "Generation 1133: M(n) = 862.6320055131703\n",
      "Generation 1134: p = 0.9584800061257448\n",
      "Generation 1134: M(n) = 862.6320055166441\n",
      "Generation 1135: p = 0.9584800061296045\n",
      "Generation 1135: M(n) = 862.632005520053\n",
      "Generation 1136: p = 0.9584800061333922\n",
      "Generation 1136: M(n) = 862.6320055233983\n",
      "Generation 1137: p = 0.9584800061371093\n",
      "Generation 1137: M(n) = 862.6320055266812\n",
      "Generation 1138: p = 0.9584800061407568\n",
      "Generation 1138: M(n) = 862.6320055299026\n",
      "Generation 1139: p = 0.9584800061443363\n",
      "Generation 1139: M(n) = 862.632005533064\n",
      "Generation 1140: p = 0.9584800061478489\n",
      "Generation 1140: M(n) = 862.6320055361664\n",
      "Generation 1141: p = 0.958480006151296\n",
      "Generation 1141: M(n) = 862.6320055392108\n",
      "Generation 1142: p = 0.9584800061546787\n",
      "Generation 1142: M(n) = 862.6320055421984\n",
      "Generation 1143: p = 0.9584800061579982\n",
      "Generation 1143: M(n) = 862.6320055451303\n",
      "Generation 1144: p = 0.9584800061612558\n",
      "Generation 1144: M(n) = 862.6320055480073\n",
      "Generation 1145: p = 0.9584800061644526\n",
      "Generation 1145: M(n) = 862.6320055508307\n",
      "Generation 1146: p = 0.9584800061675897\n",
      "Generation 1146: M(n) = 862.6320055536013\n",
      "Generation 1147: p = 0.9584800061706681\n",
      "Generation 1147: M(n) = 862.6320055563202\n",
      "Generation 1148: p = 0.9584800061736891\n",
      "Generation 1148: M(n) = 862.6320055589883\n",
      "Generation 1149: p = 0.9584800061766537\n",
      "Generation 1149: M(n) = 862.6320055616067\n",
      "Generation 1150: p = 0.958480006179563\n",
      "Generation 1150: M(n) = 862.6320055641761\n",
      "Generation 1151: p = 0.9584800061824179\n",
      "Generation 1151: M(n) = 862.6320055666976\n",
      "Generation 1152: p = 0.9584800061852196\n",
      "Generation 1152: M(n) = 862.632005569172\n",
      "Generation 1153: p = 0.9584800061879688\n",
      "Generation 1153: M(n) = 862.6320055716001\n",
      "Generation 1154: p = 0.9584800061906668\n",
      "Generation 1154: M(n) = 862.632005573983\n",
      "Generation 1155: p = 0.9584800061933144\n",
      "Generation 1155: M(n) = 862.6320055763214\n",
      "Generation 1156: p = 0.9584800061959127\n",
      "Generation 1156: M(n) = 862.6320055786161\n",
      "Generation 1157: p = 0.9584800061984624\n",
      "Generation 1157: M(n) = 862.632005580868\n",
      "Generation 1158: p = 0.9584800062009645\n",
      "Generation 1158: M(n) = 862.6320055830779\n",
      "Generation 1159: p = 0.9584800062034199\n",
      "Generation 1159: M(n) = 862.6320055852465\n",
      "Generation 1160: p = 0.9584800062058294\n",
      "Generation 1160: M(n) = 862.6320055873745\n",
      "Generation 1161: p = 0.9584800062081938\n",
      "Generation 1161: M(n) = 862.6320055894628\n",
      "Generation 1162: p = 0.9584800062105142\n",
      "Generation 1162: M(n) = 862.6320055915121\n",
      "Generation 1163: p = 0.9584800062127912\n",
      "Generation 1163: M(n) = 862.6320055935231\n",
      "Generation 1164: p = 0.9584800062150257\n",
      "Generation 1164: M(n) = 862.6320055954967\n",
      "Generation 1165: p = 0.9584800062172185\n",
      "Generation 1165: M(n) = 862.6320055974334\n",
      "Generation 1166: p = 0.9584800062193704\n",
      "Generation 1166: M(n) = 862.6320055993339\n",
      "Generation 1167: p = 0.9584800062214821\n",
      "Generation 1167: M(n) = 862.6320056011989\n",
      "Generation 1168: p = 0.9584800062235543\n",
      "Generation 1168: M(n) = 862.6320056030291\n",
      "Generation 1169: p = 0.9584800062255879\n",
      "Generation 1169: M(n) = 862.6320056048252\n",
      "Generation 1170: p = 0.9584800062275836\n",
      "Generation 1170: M(n) = 862.6320056065877\n",
      "Generation 1171: p = 0.9584800062295419\n",
      "Generation 1171: M(n) = 862.6320056083173\n",
      "Generation 1172: p = 0.9584800062314637\n",
      "Generation 1172: M(n) = 862.6320056100146\n",
      "Generation 1173: p = 0.9584800062333496\n",
      "Generation 1173: M(n) = 862.6320056116803\n",
      "Generation 1174: p = 0.9584800062352002\n",
      "Generation 1174: M(n) = 862.6320056133147\n",
      "Generation 1175: p = 0.9584800062370163\n",
      "Generation 1175: M(n) = 862.6320056149187\n",
      "Generation 1176: p = 0.9584800062387986\n",
      "Generation 1176: M(n) = 862.6320056164927\n",
      "Generation 1177: p = 0.9584800062405475\n",
      "Generation 1177: M(n) = 862.6320056180374\n",
      "Generation 1178: p = 0.9584800062422638\n",
      "Generation 1178: M(n) = 862.6320056195533\n",
      "Generation 1179: p = 0.9584800062439481\n",
      "Generation 1179: M(n) = 862.6320056210409\n",
      "Generation 1180: p = 0.958480006245601\n",
      "Generation 1180: M(n) = 862.6320056225006\n",
      "Generation 1181: p = 0.958480006247223\n",
      "Generation 1181: M(n) = 862.6320056239332\n",
      "Generation 1182: p = 0.9584800062488147\n",
      "Generation 1182: M(n) = 862.6320056253389\n",
      "Generation 1183: p = 0.9584800062503765\n",
      "Generation 1183: M(n) = 862.6320056267184\n",
      "Generation 1184: p = 0.9584800062519093\n",
      "Generation 1184: M(n) = 862.6320056280721\n",
      "Generation 1185: p = 0.9584800062534135\n",
      "Generation 1185: M(n) = 862.6320056294006\n",
      "Generation 1186: p = 0.9584800062548896\n",
      "Generation 1186: M(n) = 862.6320056307043\n",
      "Generation 1187: p = 0.9584800062563381\n",
      "Generation 1187: M(n) = 862.6320056319836\n",
      "Generation 1188: p = 0.9584800062577595\n",
      "Generation 1188: M(n) = 862.632005633239\n",
      "Generation 1189: p = 0.9584800062591545\n",
      "Generation 1189: M(n) = 862.632005634471\n",
      "Generation 1190: p = 0.9584800062605234\n",
      "Generation 1190: M(n) = 862.6320056356801\n",
      "Generation 1191: p = 0.9584800062618668\n",
      "Generation 1191: M(n) = 862.6320056368666\n",
      "Generation 1192: p = 0.9584800062631851\n",
      "Generation 1192: M(n) = 862.6320056380308\n",
      "Generation 1193: p = 0.9584800062644787\n",
      "Generation 1193: M(n) = 862.6320056391734\n",
      "Generation 1194: p = 0.9584800062657481\n",
      "Generation 1194: M(n) = 862.6320056402946\n",
      "Generation 1195: p = 0.9584800062669939\n",
      "Generation 1195: M(n) = 862.6320056413948\n",
      "Generation 1196: p = 0.9584800062682165\n",
      "Generation 1196: M(n) = 862.6320056424746\n",
      "Generation 1197: p = 0.9584800062694162\n",
      "Generation 1197: M(n) = 862.6320056435342\n",
      "Generation 1198: p = 0.9584800062705935\n",
      "Generation 1198: M(n) = 862.632005644574\n",
      "Generation 1199: p = 0.9584800062717488\n",
      "Generation 1199: M(n) = 862.6320056455943\n",
      "Generation 1200: p = 0.9584800062728825\n",
      "Generation 1200: M(n) = 862.6320056465956\n",
      "Generation 1201: p = 0.9584800062739952\n",
      "Generation 1201: M(n) = 862.6320056475784\n",
      "Generation 1202: p = 0.958480006275087\n",
      "Generation 1202: M(n) = 862.6320056485425\n",
      "Generation 1203: p = 0.9584800062761584\n",
      "Generation 1203: M(n) = 862.6320056494887\n",
      "Generation 1204: p = 0.9584800062772098\n",
      "Generation 1204: M(n) = 862.6320056504173\n",
      "Generation 1205: p = 0.9584800062782415\n",
      "Generation 1205: M(n) = 862.6320056513285\n",
      "Generation 1206: p = 0.9584800062792539\n",
      "Generation 1206: M(n) = 862.6320056522228\n",
      "Generation 1207: p = 0.9584800062802475\n",
      "Generation 1207: M(n) = 862.6320056531004\n",
      "Generation 1208: p = 0.9584800062812227\n",
      "Generation 1208: M(n) = 862.6320056539615\n",
      "Generation 1209: p = 0.9584800062821794\n",
      "Generation 1209: M(n) = 862.6320056548066\n",
      "Generation 1210: p = 0.9584800062831184\n",
      "Generation 1210: M(n) = 862.6320056556358\n",
      "Generation 1211: p = 0.9584800062840397\n",
      "Generation 1211: M(n) = 862.6320056564496\n",
      "Generation 1212: p = 0.958480006284944\n",
      "Generation 1212: M(n) = 862.6320056572482\n",
      "Generation 1213: p = 0.9584800062858313\n",
      "Generation 1213: M(n) = 862.6320056580319\n",
      "Generation 1214: p = 0.958480006286702\n",
      "Generation 1214: M(n) = 862.632005658801\n",
      "Generation 1215: p = 0.9584800062875566\n",
      "Generation 1215: M(n) = 862.6320056595557\n",
      "Generation 1216: p = 0.9584800062883952\n",
      "Generation 1216: M(n) = 862.6320056602964\n",
      "Generation 1217: p = 0.9584800062892183\n",
      "Generation 1217: M(n) = 862.6320056610233\n",
      "Generation 1218: p = 0.9584800062900259\n",
      "Generation 1218: M(n) = 862.6320056617366\n",
      "Generation 1219: p = 0.9584800062908184\n",
      "Generation 1219: M(n) = 862.6320056624365\n",
      "Generation 1220: p = 0.9584800062915961\n",
      "Generation 1220: M(n) = 862.6320056631233\n",
      "Generation 1221: p = 0.9584800062923593\n",
      "Generation 1221: M(n) = 862.6320056637974\n",
      "Generation 1222: p = 0.9584800062931081\n",
      "Generation 1222: M(n) = 862.6320056644588\n",
      "Generation 1223: p = 0.9584800062938431\n",
      "Generation 1223: M(n) = 862.632005665108\n",
      "Generation 1224: p = 0.9584800062945644\n",
      "Generation 1224: M(n) = 862.6320056657449\n",
      "Generation 1225: p = 0.9584800062952722\n",
      "Generation 1225: M(n) = 862.6320056663701\n",
      "Generation 1226: p = 0.9584800062959667\n",
      "Generation 1226: M(n) = 862.6320056669834\n",
      "Generation 1227: p = 0.9584800062966483\n",
      "Generation 1227: M(n) = 862.6320056675854\n",
      "Generation 1228: p = 0.9584800062973171\n",
      "Generation 1228: M(n) = 862.6320056681761\n",
      "Generation 1229: p = 0.9584800062979735\n",
      "Generation 1229: M(n) = 862.6320056687558\n",
      "Generation 1230: p = 0.9584800062986176\n",
      "Generation 1230: M(n) = 862.6320056693247\n",
      "Generation 1231: p = 0.9584800062992497\n",
      "Generation 1231: M(n) = 862.6320056698829\n",
      "Generation 1232: p = 0.95848000629987\n",
      "Generation 1232: M(n) = 862.6320056704308\n",
      "Generation 1233: p = 0.9584800063004786\n",
      "Generation 1233: M(n) = 862.6320056709683\n",
      "Generation 1234: p = 0.9584800063010759\n",
      "Generation 1234: M(n) = 862.6320056714959\n",
      "Generation 1235: p = 0.9584800063016621\n",
      "Generation 1235: M(n) = 862.6320056720136\n",
      "Generation 1236: p = 0.9584800063022374\n",
      "Generation 1236: M(n) = 862.6320056725217\n",
      "Generation 1237: p = 0.9584800063028018\n",
      "Generation 1237: M(n) = 862.6320056730202\n",
      "Generation 1238: p = 0.9584800063033558\n",
      "Generation 1238: M(n) = 862.6320056735095\n",
      "Generation 1239: p = 0.9584800063038995\n",
      "Generation 1239: M(n) = 862.6320056739896\n",
      "Generation 1240: p = 0.9584800063044329\n",
      "Generation 1240: M(n) = 862.6320056744607\n",
      "Generation 1241: p = 0.9584800063049563\n",
      "Generation 1241: M(n) = 862.6320056749231\n",
      "Generation 1242: p = 0.9584800063054701\n",
      "Generation 1242: M(n) = 862.6320056753768\n",
      "Generation 1243: p = 0.9584800063059743\n",
      "Generation 1243: M(n) = 862.6320056758221\n",
      "Generation 1244: p = 0.958480006306469\n",
      "Generation 1244: M(n) = 862.632005676259\n",
      "Generation 1245: p = 0.9584800063069545\n",
      "Generation 1245: M(n) = 862.6320056766879\n",
      "Generation 1246: p = 0.9584800063074309\n",
      "Generation 1246: M(n) = 862.6320056771086\n",
      "Generation 1247: p = 0.9584800063078984\n",
      "Generation 1247: M(n) = 862.6320056775215\n",
      "Generation 1248: p = 0.9584800063083573\n",
      "Generation 1248: M(n) = 862.6320056779267\n",
      "Generation 1249: p = 0.9584800063088075\n",
      "Generation 1249: M(n) = 862.6320056783244\n",
      "Generation 1250: p = 0.9584800063092493\n",
      "Generation 1250: M(n) = 862.6320056787147\n",
      "Generation 1251: p = 0.958480006309683\n",
      "Generation 1251: M(n) = 862.6320056790976\n",
      "Generation 1252: p = 0.9584800063101084\n",
      "Generation 1252: M(n) = 862.6320056794734\n",
      "Generation 1253: p = 0.958480006310526\n",
      "Generation 1253: M(n) = 862.6320056798421\n",
      "Generation 1254: p = 0.9584800063109357\n",
      "Generation 1254: M(n) = 862.632005680204\n",
      "Generation 1255: p = 0.9584800063113378\n",
      "Generation 1255: M(n) = 862.6320056805591\n",
      "Generation 1256: p = 0.9584800063117324\n",
      "Generation 1256: M(n) = 862.6320056809076\n",
      "Generation 1257: p = 0.9584800063121195\n",
      "Generation 1257: M(n) = 862.6320056812496\n",
      "Generation 1258: p = 0.9584800063124995\n",
      "Generation 1258: M(n) = 862.6320056815852\n",
      "Generation 1259: p = 0.9584800063128724\n",
      "Generation 1259: M(n) = 862.6320056819145\n",
      "Generation 1260: p = 0.9584800063132384\n",
      "Generation 1260: M(n) = 862.6320056822377\n",
      "Generation 1261: p = 0.9584800063135974\n",
      "Generation 1261: M(n) = 862.6320056825548\n",
      "Generation 1262: p = 0.9584800063139498\n",
      "Generation 1262: M(n) = 862.6320056828661\n",
      "Generation 1263: p = 0.9584800063142956\n",
      "Generation 1263: M(n) = 862.6320056831715\n",
      "Generation 1264: p = 0.958480006314635\n",
      "Generation 1264: M(n) = 862.6320056834712\n",
      "Generation 1265: p = 0.958480006314968\n",
      "Generation 1265: M(n) = 862.6320056837653\n",
      "Generation 1266: p = 0.9584800063152948\n",
      "Generation 1266: M(n) = 862.632005684054\n",
      "Generation 1267: p = 0.9584800063156156\n",
      "Generation 1267: M(n) = 862.6320056843373\n",
      "Generation 1268: p = 0.9584800063159303\n",
      "Generation 1268: M(n) = 862.6320056846153\n",
      "Generation 1269: p = 0.9584800063162392\n",
      "Generation 1269: M(n) = 862.632005684888\n",
      "Generation 1270: p = 0.9584800063165422\n",
      "Generation 1270: M(n) = 862.6320056851556\n",
      "Generation 1271: p = 0.9584800063168396\n",
      "Generation 1271: M(n) = 862.6320056854183\n",
      "Generation 1272: p = 0.9584800063171315\n",
      "Generation 1272: M(n) = 862.6320056856761\n",
      "Generation 1273: p = 0.9584800063174178\n",
      "Generation 1273: M(n) = 862.632005685929\n",
      "Generation 1274: p = 0.9584800063176989\n",
      "Generation 1274: M(n) = 862.6320056861773\n",
      "Generation 1275: p = 0.9584800063179748\n",
      "Generation 1275: M(n) = 862.6320056864209\n",
      "Generation 1276: p = 0.9584800063182455\n",
      "Generation 1276: M(n) = 862.63200568666\n",
      "Generation 1277: p = 0.9584800063185112\n",
      "Generation 1277: M(n) = 862.6320056868947\n",
      "Generation 1278: p = 0.9584800063187718\n",
      "Generation 1278: M(n) = 862.6320056871249\n",
      "Generation 1279: p = 0.9584800063190276\n",
      "Generation 1279: M(n) = 862.6320056873508\n",
      "Generation 1280: p = 0.9584800063192787\n",
      "Generation 1280: M(n) = 862.6320056875725\n",
      "Generation 1281: p = 0.958480006319525\n",
      "Generation 1281: M(n) = 862.6320056877901\n",
      "Generation 1282: p = 0.9584800063197667\n",
      "Generation 1282: M(n) = 862.6320056880036\n",
      "Generation 1283: p = 0.958480006320004\n",
      "Generation 1283: M(n) = 862.6320056882131\n",
      "Generation 1284: p = 0.9584800063202368\n",
      "Generation 1284: M(n) = 862.6320056884186\n",
      "Generation 1285: p = 0.9584800063204651\n",
      "Generation 1285: M(n) = 862.6320056886204\n",
      "Generation 1286: p = 0.9584800063206894\n",
      "Generation 1286: M(n) = 862.6320056888185\n",
      "Generation 1287: p = 0.9584800063209095\n",
      "Generation 1287: M(n) = 862.6320056890128\n",
      "Generation 1288: p = 0.9584800063211253\n",
      "Generation 1288: M(n) = 862.6320056892034\n",
      "Generation 1289: p = 0.9584800063213371\n",
      "Generation 1289: M(n) = 862.6320056893906\n",
      "Generation 1290: p = 0.9584800063215451\n",
      "Generation 1290: M(n) = 862.6320056895742\n",
      "Generation 1291: p = 0.958480006321749\n",
      "Generation 1291: M(n) = 862.6320056897542\n",
      "Generation 1292: p = 0.9584800063219492\n",
      "Generation 1292: M(n) = 862.6320056899311\n",
      "Generation 1293: p = 0.9584800063221457\n",
      "Generation 1293: M(n) = 862.6320056901046\n",
      "Generation 1294: p = 0.9584800063223384\n",
      "Generation 1294: M(n) = 862.6320056902748\n",
      "Generation 1295: p = 0.9584800063225276\n",
      "Generation 1295: M(n) = 862.6320056904419\n",
      "Generation 1296: p = 0.9584800063227132\n",
      "Generation 1296: M(n) = 862.6320056906059\n",
      "Generation 1297: p = 0.9584800063228954\n",
      "Generation 1297: M(n) = 862.6320056907668\n",
      "Generation 1298: p = 0.9584800063230743\n",
      "Generation 1298: M(n) = 862.6320056909248\n",
      "Generation 1299: p = 0.9584800063232497\n",
      "Generation 1299: M(n) = 862.6320056910797\n",
      "Generation 1300: p = 0.9584800063234219\n",
      "Generation 1300: M(n) = 862.6320056912318\n",
      "Generation 1301: p = 0.9584800063235909\n",
      "Generation 1301: M(n) = 862.632005691381\n",
      "Generation 1302: p = 0.9584800063237566\n",
      "Generation 1302: M(n) = 862.6320056915274\n",
      "Generation 1303: p = 0.9584800063239194\n",
      "Generation 1303: M(n) = 862.6320056916711\n",
      "Generation 1304: p = 0.958480006324079\n",
      "Generation 1304: M(n) = 862.6320056918122\n",
      "Generation 1305: p = 0.9584800063242358\n",
      "Generation 1305: M(n) = 862.6320056919506\n",
      "Generation 1306: p = 0.9584800063243895\n",
      "Generation 1306: M(n) = 862.6320056920863\n",
      "Generation 1307: p = 0.9584800063245403\n",
      "Generation 1307: M(n) = 862.6320056922195\n",
      "Generation 1308: p = 0.9584800063246883\n",
      "Generation 1308: M(n) = 862.6320056923503\n",
      "Generation 1309: p = 0.9584800063248337\n",
      "Generation 1309: M(n) = 862.6320056924786\n",
      "Generation 1310: p = 0.9584800063249762\n",
      "Generation 1310: M(n) = 862.6320056926045\n",
      "Generation 1311: p = 0.9584800063251161\n",
      "Generation 1311: M(n) = 862.6320056927281\n",
      "Generation 1312: p = 0.9584800063252534\n",
      "Generation 1312: M(n) = 862.6320056928494\n",
      "Generation 1313: p = 0.9584800063253882\n",
      "Generation 1313: M(n) = 862.6320056929684\n",
      "Generation 1314: p = 0.9584800063255204\n",
      "Generation 1314: M(n) = 862.6320056930851\n",
      "Generation 1315: p = 0.9584800063256501\n",
      "Generation 1315: M(n) = 862.6320056931997\n",
      "Generation 1316: p = 0.9584800063257775\n",
      "Generation 1316: M(n) = 862.6320056933122\n",
      "Generation 1317: p = 0.9584800063259025\n",
      "Generation 1317: M(n) = 862.6320056934226\n",
      "Generation 1318: p = 0.958480006326025\n",
      "Generation 1318: M(n) = 862.6320056935308\n",
      "Generation 1319: p = 0.9584800063261454\n",
      "Generation 1319: M(n) = 862.6320056936371\n",
      "Generation 1320: p = 0.9584800063262634\n",
      "Generation 1320: M(n) = 862.6320056937413\n",
      "Generation 1321: p = 0.9584800063263793\n",
      "Generation 1321: M(n) = 862.6320056938438\n",
      "Generation 1322: p = 0.9584800063264931\n",
      "Generation 1322: M(n) = 862.6320056939443\n",
      "Generation 1323: p = 0.9584800063266048\n",
      "Generation 1323: M(n) = 862.6320056940428\n",
      "Generation 1324: p = 0.9584800063267143\n",
      "Generation 1324: M(n) = 862.6320056941396\n",
      "Generation 1325: p = 0.9584800063268217\n",
      "Generation 1325: M(n) = 862.6320056942345\n",
      "Generation 1326: p = 0.9584800063269272\n",
      "Generation 1326: M(n) = 862.6320056943276\n",
      "Generation 1327: p = 0.9584800063270307\n",
      "Generation 1327: M(n) = 862.632005694419\n",
      "Generation 1328: p = 0.9584800063271323\n",
      "Generation 1328: M(n) = 862.6320056945087\n",
      "Generation 1329: p = 0.958480006327232\n",
      "Generation 1329: M(n) = 862.6320056945968\n",
      "Generation 1330: p = 0.9584800063273298\n",
      "Generation 1330: M(n) = 862.6320056946832\n",
      "Generation 1331: p = 0.9584800063274258\n",
      "Generation 1331: M(n) = 862.632005694768\n",
      "Generation 1332: p = 0.9584800063275201\n",
      "Generation 1332: M(n) = 862.6320056948513\n",
      "Generation 1333: p = 0.9584800063276125\n",
      "Generation 1333: M(n) = 862.6320056949329\n",
      "Generation 1334: p = 0.9584800063277032\n",
      "Generation 1334: M(n) = 862.632005695013\n",
      "Generation 1335: p = 0.9584800063277923\n",
      "Generation 1335: M(n) = 862.6320056950917\n",
      "Generation 1336: p = 0.9584800063278797\n",
      "Generation 1336: M(n) = 862.6320056951688\n",
      "Generation 1337: p = 0.9584800063279654\n",
      "Generation 1337: M(n) = 862.6320056952445\n",
      "Generation 1338: p = 0.9584800063280494\n",
      "Generation 1338: M(n) = 862.6320056953188\n",
      "Generation 1339: p = 0.9584800063281319\n",
      "Generation 1339: M(n) = 862.6320056953916\n",
      "Generation 1340: p = 0.958480006328213\n",
      "Generation 1340: M(n) = 862.6320056954632\n",
      "Generation 1341: p = 0.9584800063282924\n",
      "Generation 1341: M(n) = 862.6320056955334\n",
      "Generation 1342: p = 0.9584800063283705\n",
      "Generation 1342: M(n) = 862.6320056956024\n",
      "Generation 1343: p = 0.9584800063284471\n",
      "Generation 1343: M(n) = 862.63200569567\n",
      "Generation 1344: p = 0.9584800063285223\n",
      "Generation 1344: M(n) = 862.6320056957364\n",
      "Generation 1345: p = 0.9584800063285961\n",
      "Generation 1345: M(n) = 862.6320056958016\n",
      "Generation 1346: p = 0.9584800063286685\n",
      "Generation 1346: M(n) = 862.6320056958656\n",
      "Generation 1347: p = 0.9584800063287395\n",
      "Generation 1347: M(n) = 862.6320056959283\n",
      "Generation 1348: p = 0.9584800063288093\n",
      "Generation 1348: M(n) = 862.6320056959898\n",
      "Generation 1349: p = 0.9584800063288776\n",
      "Generation 1349: M(n) = 862.6320056960502\n",
      "Generation 1350: p = 0.9584800063289447\n",
      "Generation 1350: M(n) = 862.6320056961094\n",
      "Generation 1351: p = 0.9584800063290105\n",
      "Generation 1351: M(n) = 862.6320056961677\n",
      "Generation 1352: p = 0.9584800063290752\n",
      "Generation 1352: M(n) = 862.6320056962247\n",
      "Generation 1353: p = 0.9584800063291385\n",
      "Generation 1353: M(n) = 862.6320056962807\n",
      "Generation 1354: p = 0.9584800063292007\n",
      "Generation 1354: M(n) = 862.6320056963356\n",
      "Generation 1355: p = 0.9584800063292618\n",
      "Generation 1355: M(n) = 862.6320056963896\n",
      "Generation 1356: p = 0.9584800063293217\n",
      "Generation 1356: M(n) = 862.6320056964424\n",
      "Generation 1357: p = 0.9584800063293805\n",
      "Generation 1357: M(n) = 862.6320056964944\n",
      "Generation 1358: p = 0.9584800063294382\n",
      "Generation 1358: M(n) = 862.6320056965453\n",
      "Generation 1359: p = 0.9584800063294948\n",
      "Generation 1359: M(n) = 862.6320056965953\n",
      "Generation 1360: p = 0.9584800063295503\n",
      "Generation 1360: M(n) = 862.6320056966443\n",
      "Generation 1361: p = 0.9584800063296048\n",
      "Generation 1361: M(n) = 862.6320056966925\n",
      "Generation 1362: p = 0.9584800063296584\n",
      "Generation 1362: M(n) = 862.6320056967398\n",
      "Generation 1363: p = 0.958480006329711\n",
      "Generation 1363: M(n) = 862.6320056967862\n",
      "Generation 1364: p = 0.9584800063297625\n",
      "Generation 1364: M(n) = 862.6320056968318\n",
      "Generation 1365: p = 0.9584800063298131\n",
      "Generation 1365: M(n) = 862.6320056968765\n",
      "Generation 1366: p = 0.9584800063298627\n",
      "Generation 1366: M(n) = 862.6320056969203\n",
      "Generation 1367: p = 0.9584800063299114\n",
      "Generation 1367: M(n) = 862.6320056969632\n",
      "Generation 1368: p = 0.9584800063299591\n",
      "Generation 1368: M(n) = 862.6320056970054\n",
      "Generation 1369: p = 0.958480006330006\n",
      "Generation 1369: M(n) = 862.6320056970468\n",
      "Generation 1370: p = 0.958480006330052\n",
      "Generation 1370: M(n) = 862.6320056970875\n",
      "Generation 1371: p = 0.9584800063300972\n",
      "Generation 1371: M(n) = 862.6320056971274\n",
      "Generation 1372: p = 0.9584800063301415\n",
      "Generation 1372: M(n) = 862.6320056971665\n",
      "Generation 1373: p = 0.958480006330185\n",
      "Generation 1373: M(n) = 862.6320056972049\n",
      "Generation 1374: p = 0.9584800063302277\n",
      "Generation 1374: M(n) = 862.6320056972426\n",
      "Generation 1375: p = 0.9584800063302695\n",
      "Generation 1375: M(n) = 862.6320056972796\n",
      "Generation 1376: p = 0.9584800063303107\n",
      "Generation 1376: M(n) = 862.632005697316\n",
      "Generation 1377: p = 0.9584800063303511\n",
      "Generation 1377: M(n) = 862.6320056973517\n",
      "Generation 1378: p = 0.9584800063303908\n",
      "Generation 1378: M(n) = 862.6320056973866\n",
      "Generation 1379: p = 0.9584800063304295\n",
      "Generation 1379: M(n) = 862.6320056974208\n",
      "Generation 1380: p = 0.9584800063304676\n",
      "Generation 1380: M(n) = 862.6320056974545\n",
      "Generation 1381: p = 0.958480006330505\n",
      "Generation 1381: M(n) = 862.6320056974876\n",
      "Generation 1382: p = 0.9584800063305418\n",
      "Generation 1382: M(n) = 862.63200569752\n",
      "Generation 1383: p = 0.9584800063305777\n",
      "Generation 1383: M(n) = 862.6320056975518\n",
      "Generation 1384: p = 0.9584800063306131\n",
      "Generation 1384: M(n) = 862.632005697583\n",
      "Generation 1385: p = 0.9584800063306478\n",
      "Generation 1385: M(n) = 862.6320056976136\n",
      "Generation 1386: p = 0.9584800063306819\n",
      "Generation 1386: M(n) = 862.6320056976438\n",
      "Generation 1387: p = 0.9584800063307153\n",
      "Generation 1387: M(n) = 862.6320056976732\n",
      "Generation 1388: p = 0.958480006330748\n",
      "Generation 1388: M(n) = 862.6320056977022\n",
      "Generation 1389: p = 0.9584800063307802\n",
      "Generation 1389: M(n) = 862.6320056977306\n",
      "Generation 1390: p = 0.9584800063308118\n",
      "Generation 1390: M(n) = 862.6320056977585\n",
      "Generation 1391: p = 0.9584800063308427\n",
      "Generation 1391: M(n) = 862.6320056977859\n",
      "Generation 1392: p = 0.9584800063308732\n",
      "Generation 1392: M(n) = 862.6320056978127\n",
      "Generation 1393: p = 0.958480006330903\n",
      "Generation 1393: M(n) = 862.6320056978391\n",
      "Generation 1394: p = 0.9584800063309323\n",
      "Generation 1394: M(n) = 862.632005697865\n",
      "Generation 1395: p = 0.9584800063309611\n",
      "Generation 1395: M(n) = 862.6320056978903\n",
      "Generation 1396: p = 0.9584800063309893\n",
      "Generation 1396: M(n) = 862.6320056979152\n",
      "Generation 1397: p = 0.9584800063310169\n",
      "Generation 1397: M(n) = 862.6320056979397\n",
      "Generation 1398: p = 0.9584800063310441\n",
      "Generation 1398: M(n) = 862.6320056979637\n",
      "Generation 1399: p = 0.9584800063310708\n",
      "Generation 1399: M(n) = 862.6320056979872\n",
      "Generation 1400: p = 0.9584800063310969\n",
      "Generation 1400: M(n) = 862.6320056980103\n",
      "Generation 1401: p = 0.9584800063311225\n",
      "Generation 1401: M(n) = 862.6320056980329\n",
      "Generation 1402: p = 0.9584800063311477\n",
      "Generation 1402: M(n) = 862.6320056980552\n",
      "Generation 1403: p = 0.9584800063311725\n",
      "Generation 1403: M(n) = 862.632005698077\n",
      "Generation 1404: p = 0.9584800063311967\n",
      "Generation 1404: M(n) = 862.6320056980984\n",
      "Generation 1405: p = 0.9584800063312204\n",
      "Generation 1405: M(n) = 862.6320056981194\n",
      "Generation 1406: p = 0.9584800063312439\n",
      "Generation 1406: M(n) = 862.6320056981401\n",
      "Generation 1407: p = 0.9584800063312668\n",
      "Generation 1407: M(n) = 862.6320056981604\n",
      "Generation 1408: p = 0.9584800063312893\n",
      "Generation 1408: M(n) = 862.6320056981803\n",
      "Generation 1409: p = 0.9584800063313114\n",
      "Generation 1409: M(n) = 862.6320056981997\n",
      "Generation 1410: p = 0.958480006331333\n",
      "Generation 1410: M(n) = 862.6320056982188\n",
      "Generation 1411: p = 0.9584800063313542\n",
      "Generation 1411: M(n) = 862.6320056982375\n",
      "Generation 1412: p = 0.9584800063313751\n",
      "Generation 1412: M(n) = 862.632005698256\n",
      "Generation 1413: p = 0.9584800063313955\n",
      "Generation 1413: M(n) = 862.632005698274\n",
      "Generation 1414: p = 0.9584800063314156\n",
      "Generation 1414: M(n) = 862.6320056982918\n",
      "Generation 1415: p = 0.9584800063314353\n",
      "Generation 1415: M(n) = 862.6320056983092\n",
      "Generation 1416: p = 0.9584800063314546\n",
      "Generation 1416: M(n) = 862.6320056983262\n",
      "Generation 1417: p = 0.9584800063314736\n",
      "Generation 1417: M(n) = 862.6320056983429\n",
      "Generation 1418: p = 0.9584800063314921\n",
      "Generation 1418: M(n) = 862.6320056983593\n",
      "Generation 1419: p = 0.9584800063315103\n",
      "Generation 1419: M(n) = 862.6320056983755\n",
      "Generation 1420: p = 0.9584800063315283\n",
      "Generation 1420: M(n) = 862.6320056983914\n",
      "Generation 1421: p = 0.958480006331546\n",
      "Generation 1421: M(n) = 862.6320056984069\n",
      "Generation 1422: p = 0.9584800063315633\n",
      "Generation 1422: M(n) = 862.6320056984222\n",
      "Generation 1423: p = 0.9584800063315801\n",
      "Generation 1423: M(n) = 862.6320056984371\n",
      "Generation 1424: p = 0.9584800063315967\n",
      "Generation 1424: M(n) = 862.6320056984517\n",
      "Generation 1425: p = 0.958480006331613\n",
      "Generation 1425: M(n) = 862.6320056984662\n",
      "Generation 1426: p = 0.9584800063316291\n",
      "Generation 1426: M(n) = 862.6320056984804\n",
      "Generation 1427: p = 0.9584800063316449\n",
      "Generation 1427: M(n) = 862.6320056984943\n",
      "Generation 1428: p = 0.9584800063316603\n",
      "Generation 1428: M(n) = 862.6320056985079\n",
      "Generation 1429: p = 0.9584800063316754\n",
      "Generation 1429: M(n) = 862.6320056985212\n",
      "Generation 1430: p = 0.9584800063316902\n",
      "Generation 1430: M(n) = 862.6320056985343\n",
      "Generation 1431: p = 0.9584800063317047\n",
      "Generation 1431: M(n) = 862.6320056985471\n",
      "Generation 1432: p = 0.958480006331719\n",
      "Generation 1432: M(n) = 862.6320056985597\n",
      "Generation 1433: p = 0.958480006331733\n",
      "Generation 1433: M(n) = 862.6320056985721\n",
      "Generation 1434: p = 0.9584800063317468\n",
      "Generation 1434: M(n) = 862.6320056985843\n",
      "Generation 1435: p = 0.9584800063317603\n",
      "Generation 1435: M(n) = 862.6320056985962\n",
      "Generation 1436: p = 0.9584800063317735\n",
      "Generation 1436: M(n) = 862.6320056986079\n",
      "Generation 1437: p = 0.9584800063317866\n",
      "Generation 1437: M(n) = 862.6320056986195\n",
      "Generation 1438: p = 0.9584800063317995\n",
      "Generation 1438: M(n) = 862.6320056986309\n",
      "Generation 1439: p = 0.9584800063318121\n",
      "Generation 1439: M(n) = 862.6320056986419\n",
      "Generation 1440: p = 0.9584800063318244\n",
      "Generation 1440: M(n) = 862.6320056986528\n",
      "Generation 1441: p = 0.9584800063318365\n",
      "Generation 1441: M(n) = 862.6320056986635\n",
      "Generation 1442: p = 0.9584800063318484\n",
      "Generation 1442: M(n) = 862.632005698674\n",
      "Generation 1443: p = 0.95848000633186\n",
      "Generation 1443: M(n) = 862.6320056986843\n",
      "Generation 1444: p = 0.9584800063318715\n",
      "Generation 1444: M(n) = 862.6320056986945\n",
      "Generation 1445: p = 0.9584800063318827\n",
      "Generation 1445: M(n) = 862.6320056987043\n",
      "Generation 1446: p = 0.9584800063318937\n",
      "Generation 1446: M(n) = 862.632005698714\n",
      "Generation 1447: p = 0.9584800063319044\n",
      "Generation 1447: M(n) = 862.6320056987236\n",
      "Generation 1448: p = 0.9584800063319151\n",
      "Generation 1448: M(n) = 862.6320056987329\n",
      "Generation 1449: p = 0.9584800063319254\n",
      "Generation 1449: M(n) = 862.6320056987421\n",
      "Generation 1450: p = 0.9584800063319356\n",
      "Generation 1450: M(n) = 862.6320056987511\n",
      "Generation 1451: p = 0.9584800063319456\n",
      "Generation 1451: M(n) = 862.6320056987599\n",
      "Generation 1452: p = 0.9584800063319555\n",
      "Generation 1452: M(n) = 862.6320056987686\n",
      "Generation 1453: p = 0.9584800063319651\n",
      "Generation 1453: M(n) = 862.6320056987771\n",
      "Generation 1454: p = 0.9584800063319746\n",
      "Generation 1454: M(n) = 862.6320056987855\n",
      "Generation 1455: p = 0.9584800063319839\n",
      "Generation 1455: M(n) = 862.6320056987937\n",
      "Generation 1456: p = 0.958480006331993\n",
      "Generation 1456: M(n) = 862.6320056988018\n",
      "Generation 1457: p = 0.9584800063320019\n",
      "Generation 1457: M(n) = 862.6320056988096\n",
      "Generation 1458: p = 0.9584800063320107\n",
      "Generation 1458: M(n) = 862.6320056988174\n",
      "Generation 1459: p = 0.9584800063320192\n",
      "Generation 1459: M(n) = 862.632005698825\n",
      "Generation 1460: p = 0.9584800063320278\n",
      "Generation 1460: M(n) = 862.6320056988325\n",
      "Generation 1461: p = 0.9584800063320361\n",
      "Generation 1461: M(n) = 862.6320056988399\n",
      "Generation 1462: p = 0.9584800063320443\n",
      "Generation 1462: M(n) = 862.632005698847\n",
      "Generation 1463: p = 0.9584800063320522\n",
      "Generation 1463: M(n) = 862.6320056988541\n",
      "Generation 1464: p = 0.9584800063320601\n",
      "Generation 1464: M(n) = 862.632005698861\n",
      "Generation 1465: p = 0.9584800063320678\n",
      "Generation 1465: M(n) = 862.6320056988677\n",
      "Generation 1466: p = 0.9584800063320752\n",
      "Generation 1466: M(n) = 862.6320056988743\n",
      "Generation 1467: p = 0.9584800063320825\n",
      "Generation 1467: M(n) = 862.6320056988808\n",
      "Generation 1468: p = 0.9584800063320897\n",
      "Generation 1468: M(n) = 862.6320056988872\n",
      "Generation 1469: p = 0.9584800063320968\n",
      "Generation 1469: M(n) = 862.6320056988934\n",
      "Generation 1470: p = 0.9584800063321038\n",
      "Generation 1470: M(n) = 862.6320056988997\n",
      "Generation 1471: p = 0.9584800063321107\n",
      "Generation 1471: M(n) = 862.6320056989057\n",
      "Generation 1472: p = 0.9584800063321174\n",
      "Generation 1472: M(n) = 862.6320056989116\n",
      "Generation 1473: p = 0.958480006332124\n",
      "Generation 1473: M(n) = 862.6320056989175\n",
      "Generation 1474: p = 0.9584800063321306\n",
      "Generation 1474: M(n) = 862.6320056989233\n",
      "Generation 1475: p = 0.958480006332137\n",
      "Generation 1475: M(n) = 862.632005698929\n",
      "Generation 1476: p = 0.9584800063321434\n",
      "Generation 1476: M(n) = 862.6320056989346\n",
      "Generation 1477: p = 0.9584800063321495\n",
      "Generation 1477: M(n) = 862.6320056989399\n",
      "Generation 1478: p = 0.9584800063321555\n",
      "Generation 1478: M(n) = 862.6320056989452\n",
      "Generation 1479: p = 0.9584800063321613\n",
      "Generation 1479: M(n) = 862.6320056989505\n",
      "Generation 1480: p = 0.9584800063321672\n",
      "Generation 1480: M(n) = 862.6320056989556\n",
      "Generation 1481: p = 0.9584800063321729\n",
      "Generation 1481: M(n) = 862.6320056989606\n",
      "Generation 1482: p = 0.9584800063321784\n",
      "Generation 1482: M(n) = 862.6320056989655\n",
      "Generation 1483: p = 0.9584800063321839\n",
      "Generation 1483: M(n) = 862.6320056989704\n",
      "Generation 1484: p = 0.9584800063321893\n",
      "Generation 1484: M(n) = 862.6320056989751\n",
      "Generation 1485: p = 0.9584800063321947\n",
      "Generation 1485: M(n) = 862.6320056989798\n",
      "Generation 1486: p = 0.9584800063321998\n",
      "Generation 1486: M(n) = 862.6320056989844\n",
      "Generation 1487: p = 0.9584800063322049\n",
      "Generation 1487: M(n) = 862.6320056989889\n",
      "Generation 1488: p = 0.9584800063322099\n",
      "Generation 1488: M(n) = 862.6320056989932\n",
      "Generation 1489: p = 0.9584800063322146\n",
      "Generation 1489: M(n) = 862.6320056989975\n",
      "Generation 1490: p = 0.9584800063322195\n",
      "Generation 1490: M(n) = 862.6320056990018\n",
      "Generation 1491: p = 0.9584800063322242\n",
      "Generation 1491: M(n) = 862.632005699006\n",
      "Generation 1492: p = 0.9584800063322289\n",
      "Generation 1492: M(n) = 862.63200569901\n",
      "Generation 1493: p = 0.9584800063322334\n",
      "Generation 1493: M(n) = 862.632005699014\n",
      "Generation 1494: p = 0.9584800063322378\n",
      "Generation 1494: M(n) = 862.632005699018\n",
      "Generation 1495: p = 0.9584800063322423\n",
      "Generation 1495: M(n) = 862.6320056990219\n",
      "Generation 1496: p = 0.9584800063322465\n",
      "Generation 1496: M(n) = 862.6320056990256\n",
      "Generation 1497: p = 0.9584800063322507\n",
      "Generation 1497: M(n) = 862.6320056990294\n",
      "Generation 1498: p = 0.9584800063322548\n",
      "Generation 1498: M(n) = 862.632005699033\n",
      "Generation 1499: p = 0.9584800063322589\n",
      "Generation 1499: M(n) = 862.6320056990367\n",
      "Generation 1500: p = 0.9584800063322629\n",
      "Generation 1500: M(n) = 862.6320056990402\n",
      "Generation 1501: p = 0.9584800063322668\n",
      "Generation 1501: M(n) = 862.6320056990436\n",
      "Generation 1502: p = 0.9584800063322707\n",
      "Generation 1502: M(n) = 862.632005699047\n",
      "Generation 1503: p = 0.9584800063322745\n",
      "Generation 1503: M(n) = 862.6320056990503\n",
      "Generation 1504: p = 0.9584800063322781\n",
      "Generation 1504: M(n) = 862.6320056990536\n",
      "Generation 1505: p = 0.9584800063322818\n",
      "Generation 1505: M(n) = 862.6320056990568\n",
      "Generation 1506: p = 0.9584800063322854\n",
      "Generation 1506: M(n) = 862.63200569906\n",
      "Generation 1507: p = 0.9584800063322888\n",
      "Generation 1507: M(n) = 862.632005699063\n",
      "Generation 1508: p = 0.9584800063322922\n",
      "Generation 1508: M(n) = 862.632005699066\n",
      "Generation 1509: p = 0.9584800063322956\n",
      "Generation 1509: M(n) = 862.6320056990689\n",
      "Generation 1510: p = 0.9584800063322988\n",
      "Generation 1510: M(n) = 862.6320056990718\n",
      "Generation 1511: p = 0.958480006332302\n",
      "Generation 1511: M(n) = 862.6320056990746\n",
      "Generation 1512: p = 0.9584800063323051\n",
      "Generation 1512: M(n) = 862.6320056990774\n",
      "Generation 1513: p = 0.9584800063323081\n",
      "Generation 1513: M(n) = 862.6320056990801\n",
      "Generation 1514: p = 0.9584800063323112\n",
      "Generation 1514: M(n) = 862.6320056990828\n",
      "Generation 1515: p = 0.9584800063323142\n",
      "Generation 1515: M(n) = 862.6320056990854\n",
      "Generation 1516: p = 0.9584800063323171\n",
      "Generation 1516: M(n) = 862.632005699088\n",
      "Generation 1517: p = 0.95848000633232\n",
      "Generation 1517: M(n) = 862.6320056990905\n",
      "Generation 1518: p = 0.9584800063323228\n",
      "Generation 1518: M(n) = 862.632005699093\n",
      "Generation 1519: p = 0.9584800063323256\n",
      "Generation 1519: M(n) = 862.6320056990954\n",
      "Generation 1520: p = 0.9584800063323282\n",
      "Generation 1520: M(n) = 862.6320056990978\n",
      "Generation 1521: p = 0.9584800063323309\n",
      "Generation 1521: M(n) = 862.6320056991002\n",
      "Generation 1522: p = 0.9584800063323335\n",
      "Generation 1522: M(n) = 862.6320056991025\n",
      "Generation 1523: p = 0.9584800063323361\n",
      "Generation 1523: M(n) = 862.6320056991048\n",
      "Generation 1524: p = 0.9584800063323387\n",
      "Generation 1524: M(n) = 862.632005699107\n",
      "Generation 1525: p = 0.9584800063323411\n",
      "Generation 1525: M(n) = 862.6320056991092\n",
      "Generation 1526: p = 0.9584800063323435\n",
      "Generation 1526: M(n) = 862.6320056991113\n",
      "Generation 1527: p = 0.958480006332346\n",
      "Generation 1527: M(n) = 862.6320056991135\n",
      "Generation 1528: p = 0.9584800063323483\n",
      "Generation 1528: M(n) = 862.6320056991156\n",
      "Generation 1529: p = 0.9584800063323506\n",
      "Generation 1529: M(n) = 862.6320056991176\n",
      "Generation 1530: p = 0.9584800063323529\n",
      "Generation 1530: M(n) = 862.6320056991195\n",
      "Generation 1531: p = 0.9584800063323551\n",
      "Generation 1531: M(n) = 862.6320056991216\n",
      "Generation 1532: p = 0.9584800063323573\n",
      "Generation 1532: M(n) = 862.6320056991235\n",
      "Generation 1533: p = 0.9584800063323594\n",
      "Generation 1533: M(n) = 862.6320056991253\n",
      "Generation 1534: p = 0.9584800063323615\n",
      "Generation 1534: M(n) = 862.6320056991273\n",
      "Generation 1535: p = 0.9584800063323636\n",
      "Generation 1535: M(n) = 862.6320056991291\n",
      "Generation 1536: p = 0.9584800063323656\n",
      "Generation 1536: M(n) = 862.6320056991309\n",
      "Generation 1537: p = 0.9584800063323676\n",
      "Generation 1537: M(n) = 862.6320056991326\n",
      "Generation 1538: p = 0.9584800063323695\n",
      "Generation 1538: M(n) = 862.6320056991343\n",
      "Generation 1539: p = 0.9584800063323714\n",
      "Generation 1539: M(n) = 862.6320056991359\n",
      "Generation 1540: p = 0.9584800063323732\n",
      "Generation 1540: M(n) = 862.6320056991375\n",
      "Generation 1541: p = 0.958480006332375\n",
      "Generation 1541: M(n) = 862.6320056991391\n",
      "Generation 1542: p = 0.9584800063323767\n",
      "Generation 1542: M(n) = 862.6320056991407\n",
      "Generation 1543: p = 0.9584800063323785\n",
      "Generation 1543: M(n) = 862.6320056991423\n",
      "Generation 1544: p = 0.9584800063323803\n",
      "Generation 1544: M(n) = 862.6320056991437\n",
      "Generation 1545: p = 0.958480006332382\n",
      "Generation 1545: M(n) = 862.6320056991452\n",
      "Generation 1546: p = 0.9584800063323836\n",
      "Generation 1546: M(n) = 862.6320056991467\n",
      "Generation 1547: p = 0.9584800063323852\n",
      "Generation 1547: M(n) = 862.6320056991481\n",
      "Generation 1548: p = 0.9584800063323867\n",
      "Generation 1548: M(n) = 862.6320056991494\n",
      "Generation 1549: p = 0.9584800063323883\n",
      "Generation 1549: M(n) = 862.6320056991508\n",
      "Generation 1550: p = 0.9584800063323897\n",
      "Generation 1550: M(n) = 862.6320056991522\n",
      "Generation 1551: p = 0.9584800063323913\n",
      "Generation 1551: M(n) = 862.6320056991535\n",
      "Generation 1552: p = 0.9584800063323928\n",
      "Generation 1552: M(n) = 862.6320056991549\n",
      "Generation 1553: p = 0.9584800063323943\n",
      "Generation 1553: M(n) = 862.6320056991561\n",
      "Generation 1554: p = 0.9584800063323957\n",
      "Generation 1554: M(n) = 862.6320056991574\n",
      "Generation 1555: p = 0.958480006332397\n",
      "Generation 1555: M(n) = 862.6320056991586\n",
      "Generation 1556: p = 0.9584800063323985\n",
      "Generation 1556: M(n) = 862.6320056991599\n",
      "Generation 1557: p = 0.9584800063323998\n",
      "Generation 1557: M(n) = 862.632005699161\n",
      "Generation 1558: p = 0.9584800063324012\n",
      "Generation 1558: M(n) = 862.6320056991622\n",
      "Generation 1559: p = 0.9584800063324024\n",
      "Generation 1559: M(n) = 862.6320056991633\n",
      "Generation 1560: p = 0.9584800063324037\n",
      "Generation 1560: M(n) = 862.6320056991644\n",
      "Generation 1561: p = 0.9584800063324049\n",
      "Generation 1561: M(n) = 862.6320056991656\n",
      "Generation 1562: p = 0.9584800063324062\n",
      "Generation 1562: M(n) = 862.6320056991666\n",
      "Generation 1563: p = 0.9584800063324074\n",
      "Generation 1563: M(n) = 862.6320056991677\n",
      "Generation 1564: p = 0.9584800063324086\n",
      "Generation 1564: M(n) = 862.6320056991688\n",
      "Generation 1565: p = 0.9584800063324097\n",
      "Generation 1565: M(n) = 862.6320056991698\n",
      "Generation 1566: p = 0.9584800063324108\n",
      "Generation 1566: M(n) = 862.6320056991708\n",
      "Generation 1567: p = 0.958480006332412\n",
      "Generation 1567: M(n) = 862.6320056991718\n",
      "Generation 1568: p = 0.9584800063324131\n",
      "Generation 1568: M(n) = 862.6320056991729\n",
      "Generation 1569: p = 0.9584800063324143\n",
      "Generation 1569: M(n) = 862.6320056991738\n",
      "Generation 1570: p = 0.9584800063324153\n",
      "Generation 1570: M(n) = 862.6320056991747\n",
      "Generation 1571: p = 0.9584800063324163\n",
      "Generation 1571: M(n) = 862.6320056991756\n",
      "Generation 1572: p = 0.9584800063324173\n",
      "Generation 1572: M(n) = 862.6320056991765\n",
      "Generation 1573: p = 0.9584800063324184\n",
      "Generation 1573: M(n) = 862.6320056991774\n",
      "Generation 1574: p = 0.9584800063324194\n",
      "Generation 1574: M(n) = 862.6320056991783\n",
      "Generation 1575: p = 0.9584800063324204\n",
      "Generation 1575: M(n) = 862.6320056991792\n",
      "Generation 1576: p = 0.9584800063324214\n",
      "Generation 1576: M(n) = 862.63200569918\n",
      "Generation 1577: p = 0.9584800063324223\n",
      "Generation 1577: M(n) = 862.6320056991808\n",
      "Generation 1578: p = 0.9584800063324231\n",
      "Generation 1578: M(n) = 862.6320056991816\n",
      "Generation 1579: p = 0.958480006332424\n",
      "Generation 1579: M(n) = 862.6320056991824\n",
      "Generation 1580: p = 0.9584800063324249\n",
      "Generation 1580: M(n) = 862.6320056991832\n",
      "Generation 1581: p = 0.9584800063324258\n",
      "Generation 1581: M(n) = 862.632005699184\n",
      "Generation 1582: p = 0.9584800063324267\n",
      "Generation 1582: M(n) = 862.6320056991848\n",
      "Generation 1583: p = 0.9584800063324276\n",
      "Generation 1583: M(n) = 862.6320056991856\n",
      "Generation 1584: p = 0.9584800063324285\n",
      "Generation 1584: M(n) = 862.6320056991864\n",
      "Generation 1585: p = 0.9584800063324294\n",
      "Generation 1585: M(n) = 862.6320056991872\n",
      "Generation 1586: p = 0.9584800063324302\n",
      "Generation 1586: M(n) = 862.6320056991879\n",
      "Generation 1587: p = 0.9584800063324309\n",
      "Generation 1587: M(n) = 862.6320056991885\n",
      "Generation 1588: p = 0.9584800063324317\n",
      "Generation 1588: M(n) = 862.6320056991892\n",
      "Generation 1589: p = 0.9584800063324325\n",
      "Generation 1589: M(n) = 862.6320056991899\n",
      "Generation 1590: p = 0.9584800063324332\n",
      "Generation 1590: M(n) = 862.6320056991906\n",
      "Generation 1591: p = 0.958480006332434\n",
      "Generation 1591: M(n) = 862.6320056991913\n",
      "Generation 1592: p = 0.9584800063324348\n",
      "Generation 1592: M(n) = 862.632005699192\n",
      "Generation 1593: p = 0.9584800063324355\n",
      "Generation 1593: M(n) = 862.6320056991925\n",
      "Generation 1594: p = 0.9584800063324361\n",
      "Generation 1594: M(n) = 862.6320056991931\n",
      "Generation 1595: p = 0.9584800063324368\n",
      "Generation 1595: M(n) = 862.6320056991937\n",
      "Generation 1596: p = 0.9584800063324374\n",
      "Generation 1596: M(n) = 862.6320056991942\n",
      "Generation 1597: p = 0.958480006332438\n",
      "Generation 1597: M(n) = 862.6320056991948\n",
      "Generation 1598: p = 0.9584800063324387\n",
      "Generation 1598: M(n) = 862.6320056991954\n",
      "Generation 1599: p = 0.9584800063324392\n",
      "Generation 1599: M(n) = 862.6320056991958\n",
      "Generation 1600: p = 0.9584800063324398\n",
      "Generation 1600: M(n) = 862.6320056991964\n",
      "Generation 1601: p = 0.9584800063324405\n",
      "Generation 1601: M(n) = 862.632005699197\n",
      "Generation 1602: p = 0.958480006332441\n",
      "Generation 1602: M(n) = 862.6320056991974\n",
      "Generation 1603: p = 0.9584800063324416\n",
      "Generation 1603: M(n) = 862.6320056991979\n",
      "Generation 1604: p = 0.958480006332442\n",
      "Generation 1604: M(n) = 862.6320056991983\n",
      "Generation 1605: p = 0.9584800063324426\n",
      "Generation 1605: M(n) = 862.6320056991988\n",
      "Generation 1606: p = 0.9584800063324431\n",
      "Generation 1606: M(n) = 862.6320056991993\n",
      "Generation 1607: p = 0.9584800063324437\n",
      "Generation 1607: M(n) = 862.6320056991998\n",
      "Generation 1608: p = 0.9584800063324442\n",
      "Generation 1608: M(n) = 862.6320056992002\n",
      "Generation 1609: p = 0.9584800063324447\n",
      "Generation 1609: M(n) = 862.6320056992007\n",
      "Generation 1610: p = 0.9584800063324452\n",
      "Generation 1610: M(n) = 862.6320056992012\n",
      "Generation 1611: p = 0.9584800063324457\n",
      "Generation 1611: M(n) = 862.6320056992015\n",
      "Generation 1612: p = 0.9584800063324461\n",
      "Generation 1612: M(n) = 862.632005699202\n",
      "Generation 1613: p = 0.9584800063324466\n",
      "Generation 1613: M(n) = 862.6320056992023\n",
      "Generation 1614: p = 0.958480006332447\n",
      "Generation 1614: M(n) = 862.6320056992028\n",
      "Generation 1615: p = 0.9584800063324475\n",
      "Generation 1615: M(n) = 862.6320056992031\n",
      "Generation 1616: p = 0.9584800063324479\n",
      "Generation 1616: M(n) = 862.6320056992035\n",
      "Generation 1617: p = 0.9584800063324483\n",
      "Generation 1617: M(n) = 862.6320056992039\n",
      "Generation 1618: p = 0.9584800063324488\n",
      "Generation 1618: M(n) = 862.6320056992043\n",
      "Generation 1619: p = 0.9584800063324492\n",
      "Generation 1619: M(n) = 862.6320056992047\n",
      "Generation 1620: p = 0.9584800063324497\n",
      "Generation 1620: M(n) = 862.632005699205\n",
      "Generation 1621: p = 0.95848000633245\n",
      "Generation 1621: M(n) = 862.6320056992054\n",
      "Generation 1622: p = 0.9584800063324505\n",
      "Generation 1622: M(n) = 862.6320056992057\n",
      "Generation 1623: p = 0.9584800063324508\n",
      "Generation 1623: M(n) = 862.632005699206\n",
      "Generation 1624: p = 0.9584800063324511\n",
      "Generation 1624: M(n) = 862.6320056992064\n",
      "Generation 1625: p = 0.9584800063324516\n",
      "Generation 1625: M(n) = 862.6320056992067\n",
      "Generation 1626: p = 0.9584800063324519\n",
      "Generation 1626: M(n) = 862.6320056992071\n",
      "Generation 1627: p = 0.9584800063324523\n",
      "Generation 1627: M(n) = 862.6320056992074\n",
      "Generation 1628: p = 0.9584800063324527\n",
      "Generation 1628: M(n) = 862.6320056992078\n",
      "Generation 1629: p = 0.958480006332453\n",
      "Generation 1629: M(n) = 862.632005699208\n",
      "Generation 1630: p = 0.9584800063324533\n",
      "Generation 1630: M(n) = 862.6320056992083\n",
      "Generation 1631: p = 0.9584800063324537\n",
      "Generation 1631: M(n) = 862.6320056992085\n",
      "Generation 1632: p = 0.9584800063324539\n",
      "Generation 1632: M(n) = 862.6320056992088\n",
      "Generation 1633: p = 0.9584800063324542\n",
      "Generation 1633: M(n) = 862.6320056992091\n",
      "Generation 1634: p = 0.9584800063324546\n",
      "Generation 1634: M(n) = 862.6320056992093\n",
      "Generation 1635: p = 0.9584800063324548\n",
      "Generation 1635: M(n) = 862.6320056992096\n",
      "Generation 1636: p = 0.9584800063324551\n",
      "Generation 1636: M(n) = 862.6320056992099\n",
      "Generation 1637: p = 0.9584800063324554\n",
      "Generation 1637: M(n) = 862.6320056992101\n",
      "Generation 1638: p = 0.9584800063324557\n",
      "Generation 1638: M(n) = 862.6320056992104\n",
      "Generation 1639: p = 0.958480006332456\n",
      "Generation 1639: M(n) = 862.6320056992107\n",
      "Generation 1640: p = 0.9584800063324563\n",
      "Generation 1640: M(n) = 862.6320056992109\n",
      "Generation 1641: p = 0.9584800063324566\n",
      "Generation 1641: M(n) = 862.6320056992112\n",
      "Generation 1642: p = 0.9584800063324569\n",
      "Generation 1642: M(n) = 862.6320056992114\n",
      "Generation 1643: p = 0.9584800063324571\n",
      "Generation 1643: M(n) = 862.6320056992116\n",
      "Generation 1644: p = 0.9584800063324573\n",
      "Generation 1644: M(n) = 862.6320056992118\n",
      "Generation 1645: p = 0.9584800063324576\n",
      "Generation 1645: M(n) = 862.6320056992121\n",
      "Generation 1646: p = 0.9584800063324579\n",
      "Generation 1646: M(n) = 862.6320056992123\n",
      "Generation 1647: p = 0.9584800063324581\n",
      "Generation 1647: M(n) = 862.6320056992125\n",
      "Generation 1648: p = 0.9584800063324583\n",
      "Generation 1648: M(n) = 862.6320056992128\n",
      "Generation 1649: p = 0.9584800063324587\n",
      "Generation 1649: M(n) = 862.632005699213\n",
      "Generation 1650: p = 0.9584800063324589\n",
      "Generation 1650: M(n) = 862.6320056992132\n",
      "Generation 1651: p = 0.9584800063324591\n",
      "Generation 1651: M(n) = 862.6320056992134\n",
      "Generation 1652: p = 0.9584800063324593\n",
      "Generation 1652: M(n) = 862.6320056992136\n",
      "Generation 1653: p = 0.9584800063324596\n",
      "Generation 1653: M(n) = 862.6320056992138\n",
      "Generation 1654: p = 0.9584800063324598\n",
      "Generation 1654: M(n) = 862.632005699214\n",
      "Generation 1655: p = 0.95848000633246\n",
      "Generation 1655: M(n) = 862.6320056992142\n",
      "Generation 1656: p = 0.9584800063324602\n",
      "Generation 1656: M(n) = 862.6320056992143\n",
      "Generation 1657: p = 0.9584800063324603\n",
      "Generation 1657: M(n) = 862.6320056992145\n",
      "Generation 1658: p = 0.9584800063324606\n",
      "Generation 1658: M(n) = 862.6320056992147\n",
      "Generation 1659: p = 0.9584800063324608\n",
      "Generation 1659: M(n) = 862.6320056992149\n",
      "Generation 1660: p = 0.958480006332461\n",
      "Generation 1660: M(n) = 862.632005699215\n",
      "Generation 1661: p = 0.9584800063324611\n",
      "Generation 1661: M(n) = 862.6320056992151\n",
      "Generation 1662: p = 0.9584800063324612\n",
      "Generation 1662: M(n) = 862.6320056992153\n",
      "Generation 1663: p = 0.9584800063324614\n",
      "Generation 1663: M(n) = 862.6320056992155\n",
      "Generation 1664: p = 0.9584800063324617\n",
      "Generation 1664: M(n) = 862.6320056992157\n",
      "Generation 1665: p = 0.9584800063324619\n",
      "Generation 1665: M(n) = 862.6320056992158\n",
      "Generation 1666: p = 0.958480006332462\n",
      "Generation 1666: M(n) = 862.6320056992159\n",
      "Generation 1667: p = 0.9584800063324621\n",
      "Generation 1667: M(n) = 862.632005699216\n",
      "Generation 1668: p = 0.9584800063324623\n",
      "Generation 1668: M(n) = 862.6320056992163\n",
      "Generation 1669: p = 0.9584800063324626\n",
      "Generation 1669: M(n) = 862.6320056992164\n",
      "Generation 1670: p = 0.9584800063324627\n",
      "Generation 1670: M(n) = 862.6320056992165\n",
      "Generation 1671: p = 0.9584800063324628\n",
      "Generation 1671: M(n) = 862.6320056992166\n",
      "Generation 1672: p = 0.9584800063324629\n",
      "Generation 1672: M(n) = 862.6320056992167\n",
      "Generation 1673: p = 0.958480006332463\n",
      "Generation 1673: M(n) = 862.6320056992168\n",
      "Generation 1674: p = 0.9584800063324632\n",
      "Generation 1674: M(n) = 862.6320056992171\n",
      "Generation 1675: p = 0.9584800063324634\n",
      "Generation 1675: M(n) = 862.6320056992172\n",
      "Generation 1676: p = 0.9584800063324636\n",
      "Generation 1676: M(n) = 862.6320056992173\n",
      "Generation 1677: p = 0.9584800063324637\n",
      "Generation 1677: M(n) = 862.6320056992174\n",
      "Generation 1678: p = 0.9584800063324638\n",
      "Generation 1678: M(n) = 862.6320056992175\n",
      "Generation 1679: p = 0.9584800063324639\n",
      "Generation 1679: M(n) = 862.6320056992176\n",
      "Generation 1680: p = 0.958480006332464\n",
      "Generation 1680: M(n) = 862.6320056992178\n",
      "Generation 1681: p = 0.9584800063324642\n",
      "Generation 1681: M(n) = 862.6320056992179\n",
      "Generation 1682: p = 0.9584800063324643\n",
      "Generation 1682: M(n) = 862.632005699218\n",
      "Generation 1683: p = 0.9584800063324644\n",
      "Generation 1683: M(n) = 862.6320056992181\n",
      "Generation 1684: p = 0.9584800063324646\n",
      "Generation 1684: M(n) = 862.6320056992182\n",
      "Generation 1685: p = 0.9584800063324647\n",
      "Generation 1685: M(n) = 862.6320056992183\n",
      "Generation 1686: p = 0.9584800063324648\n",
      "Generation 1686: M(n) = 862.6320056992184\n",
      "Generation 1687: p = 0.9584800063324649\n",
      "Generation 1687: M(n) = 862.6320056992186\n",
      "Generation 1688: p = 0.9584800063324651\n",
      "Generation 1688: M(n) = 862.6320056992187\n",
      "Generation 1689: p = 0.9584800063324652\n",
      "Generation 1689: M(n) = 862.6320056992188\n",
      "Generation 1690: p = 0.9584800063324653\n",
      "Generation 1690: M(n) = 862.6320056992189\n",
      "Generation 1691: p = 0.9584800063324654\n",
      "Generation 1691: M(n) = 862.632005699219\n",
      "Generation 1692: p = 0.9584800063324656\n",
      "Generation 1692: M(n) = 862.6320056992191\n",
      "Generation 1693: p = 0.9584800063324657\n",
      "Generation 1693: M(n) = 862.6320056992192\n",
      "Generation 1694: p = 0.9584800063324658\n",
      "Generation 1694: M(n) = 862.6320056992192\n",
      "Generation 1695: p = 0.9584800063324658\n",
      "Generation 1695: M(n) = 862.6320056992192\n",
      "Generation 1696: p = 0.9584800063324658\n",
      "Generation 1696: M(n) = 862.6320056992192\n",
      "Generation 1697: p = 0.9584800063324658\n",
      "Generation 1697: M(n) = 862.6320056992192\n",
      "Generation 1698: p = 0.9584800063324658\n",
      "Generation 1698: M(n) = 862.6320056992192\n",
      "Generation 1699: p = 0.9584800063324658\n",
      "Generation 1699: M(n) = 862.6320056992192\n",
      "Generation 1700: p = 0.9584800063324658\n",
      "Generation 1700: M(n) = 862.6320056992192\n",
      "Generation 1701: p = 0.9584800063324658\n",
      "Generation 1701: M(n) = 862.6320056992192\n",
      "Generation 1702: p = 0.9584800063324658\n",
      "Generation 1702: M(n) = 862.6320056992192\n",
      "Generation 1703: p = 0.9584800063324658\n",
      "Generation 1703: M(n) = 862.6320056992192\n",
      "Generation 1704: p = 0.9584800063324658\n",
      "Generation 1704: M(n) = 862.6320056992192\n",
      "Generation 1705: p = 0.9584800063324658\n",
      "Generation 1705: M(n) = 862.6320056992192\n",
      "Generation 1706: p = 0.9584800063324658\n",
      "Generation 1706: M(n) = 862.6320056992192\n",
      "Generation 1707: p = 0.9584800063324658\n",
      "Generation 1707: M(n) = 862.6320056992192\n",
      "Generation 1708: p = 0.9584800063324658\n",
      "Generation 1708: M(n) = 862.6320056992192\n",
      "Generation 1709: p = 0.9584800063324658\n",
      "Generation 1709: M(n) = 862.6320056992192\n",
      "Generation 1710: p = 0.9584800063324658\n",
      "Generation 1710: M(n) = 862.6320056992192\n",
      "Generation 1711: p = 0.9584800063324658\n",
      "Generation 1711: M(n) = 862.6320056992192\n",
      "Generation 1712: p = 0.9584800063324658\n",
      "Generation 1712: M(n) = 862.6320056992192\n",
      "Generation 1713: p = 0.9584800063324658\n",
      "Generation 1713: M(n) = 862.6320056992192\n",
      "Generation 1714: p = 0.9584800063324658\n",
      "Generation 1714: M(n) = 862.6320056992192\n",
      "Generation 1715: p = 0.9584800063324658\n",
      "Generation 1715: M(n) = 862.6320056992192\n",
      "Generation 1716: p = 0.9584800063324658\n",
      "Generation 1716: M(n) = 862.6320056992192\n",
      "Generation 1717: p = 0.9584800063324658\n",
      "Generation 1717: M(n) = 862.6320056992192\n",
      "Generation 1718: p = 0.9584800063324658\n",
      "Generation 1718: M(n) = 862.6320056992192\n",
      "Generation 1719: p = 0.9584800063324658\n",
      "Generation 1719: M(n) = 862.6320056992192\n",
      "Generation 1720: p = 0.9584800063324658\n",
      "Generation 1720: M(n) = 862.6320056992192\n",
      "Generation 1721: p = 0.9584800063324658\n",
      "Generation 1721: M(n) = 862.6320056992192\n",
      "Generation 1722: p = 0.9584800063324658\n",
      "Generation 1722: M(n) = 862.6320056992192\n",
      "Generation 1723: p = 0.9584800063324658\n",
      "Generation 1723: M(n) = 862.6320056992192\n",
      "Generation 1724: p = 0.9584800063324658\n",
      "Generation 1724: M(n) = 862.6320056992192\n",
      "Generation 1725: p = 0.9584800063324658\n",
      "Generation 1725: M(n) = 862.6320056992192\n",
      "Generation 1726: p = 0.9584800063324658\n",
      "Generation 1726: M(n) = 862.6320056992192\n",
      "Generation 1727: p = 0.9584800063324658\n",
      "Generation 1727: M(n) = 862.6320056992192\n",
      "Generation 1728: p = 0.9584800063324658\n",
      "Generation 1728: M(n) = 862.6320056992192\n",
      "Generation 1729: p = 0.9584800063324658\n",
      "Generation 1729: M(n) = 862.6320056992192\n",
      "Generation 1730: p = 0.9584800063324658\n",
      "Generation 1730: M(n) = 862.6320056992192\n",
      "Generation 1731: p = 0.9584800063324658\n",
      "Generation 1731: M(n) = 862.6320056992192\n",
      "Generation 1732: p = 0.9584800063324658\n",
      "Generation 1732: M(n) = 862.6320056992192\n",
      "Generation 1733: p = 0.9584800063324658\n",
      "Generation 1733: M(n) = 862.6320056992192\n",
      "Generation 1734: p = 0.9584800063324658\n",
      "Generation 1734: M(n) = 862.6320056992192\n",
      "Generation 1735: p = 0.9584800063324658\n",
      "Generation 1735: M(n) = 862.6320056992192\n",
      "Generation 1736: p = 0.9584800063324658\n",
      "Generation 1736: M(n) = 862.6320056992192\n",
      "Generation 1737: p = 0.9584800063324658\n",
      "Generation 1737: M(n) = 862.6320056992192\n",
      "Generation 1738: p = 0.9584800063324658\n",
      "Generation 1738: M(n) = 862.6320056992192\n",
      "Generation 1739: p = 0.9584800063324658\n",
      "Generation 1739: M(n) = 862.6320056992192\n",
      "Generation 1740: p = 0.9584800063324658\n",
      "Generation 1740: M(n) = 862.6320056992192\n",
      "Generation 1741: p = 0.9584800063324658\n",
      "Generation 1741: M(n) = 862.6320056992192\n",
      "Generation 1742: p = 0.9584800063324658\n",
      "Generation 1742: M(n) = 862.6320056992192\n",
      "Generation 1743: p = 0.9584800063324658\n",
      "Generation 1743: M(n) = 862.6320056992192\n",
      "Generation 1744: p = 0.9584800063324658\n",
      "Generation 1744: M(n) = 862.6320056992192\n",
      "Generation 1745: p = 0.9584800063324658\n",
      "Generation 1745: M(n) = 862.6320056992192\n",
      "Generation 1746: p = 0.9584800063324658\n",
      "Generation 1746: M(n) = 862.6320056992192\n",
      "Generation 1747: p = 0.9584800063324658\n",
      "Generation 1747: M(n) = 862.6320056992192\n",
      "Generation 1748: p = 0.9584800063324658\n",
      "Generation 1748: M(n) = 862.6320056992192\n",
      "Generation 1749: p = 0.9584800063324658\n",
      "Generation 1749: M(n) = 862.6320056992192\n",
      "Generation 1750: p = 0.9584800063324658\n",
      "Generation 1750: M(n) = 862.6320056992192\n",
      "Generation 1751: p = 0.9584800063324658\n",
      "Generation 1751: M(n) = 862.6320056992192\n",
      "Generation 1752: p = 0.9584800063324658\n",
      "Generation 1752: M(n) = 862.6320056992192\n",
      "Generation 1753: p = 0.9584800063324658\n",
      "Generation 1753: M(n) = 862.6320056992192\n",
      "Generation 1754: p = 0.9584800063324658\n",
      "Generation 1754: M(n) = 862.6320056992192\n",
      "Generation 1755: p = 0.9584800063324658\n",
      "Generation 1755: M(n) = 862.6320056992192\n",
      "Generation 1756: p = 0.9584800063324658\n",
      "Generation 1756: M(n) = 862.6320056992192\n",
      "Generation 1757: p = 0.9584800063324658\n",
      "Generation 1757: M(n) = 862.6320056992192\n",
      "Generation 1758: p = 0.9584800063324658\n",
      "Generation 1758: M(n) = 862.6320056992192\n",
      "Generation 1759: p = 0.9584800063324658\n",
      "Generation 1759: M(n) = 862.6320056992192\n",
      "Generation 1760: p = 0.9584800063324658\n",
      "Generation 1760: M(n) = 862.6320056992192\n",
      "Generation 1761: p = 0.9584800063324658\n",
      "Generation 1761: M(n) = 862.6320056992192\n",
      "Generation 1762: p = 0.9584800063324658\n",
      "Generation 1762: M(n) = 862.6320056992192\n",
      "Generation 1763: p = 0.9584800063324658\n",
      "Generation 1763: M(n) = 862.6320056992192\n",
      "Generation 1764: p = 0.9584800063324658\n",
      "Generation 1764: M(n) = 862.6320056992192\n",
      "Generation 1765: p = 0.9584800063324658\n",
      "Generation 1765: M(n) = 862.6320056992192\n",
      "Generation 1766: p = 0.9584800063324658\n",
      "Generation 1766: M(n) = 862.6320056992192\n",
      "Generation 1767: p = 0.9584800063324658\n",
      "Generation 1767: M(n) = 862.6320056992192\n",
      "Generation 1768: p = 0.9584800063324658\n",
      "Generation 1768: M(n) = 862.6320056992192\n",
      "Generation 1769: p = 0.9584800063324658\n",
      "Generation 1769: M(n) = 862.6320056992192\n",
      "Generation 1770: p = 0.9584800063324658\n",
      "Generation 1770: M(n) = 862.6320056992192\n",
      "Generation 1771: p = 0.9584800063324658\n",
      "Generation 1771: M(n) = 862.6320056992192\n",
      "Generation 1772: p = 0.9584800063324658\n",
      "Generation 1772: M(n) = 862.6320056992192\n",
      "Generation 1773: p = 0.9584800063324658\n",
      "Generation 1773: M(n) = 862.6320056992192\n",
      "Generation 1774: p = 0.9584800063324658\n",
      "Generation 1774: M(n) = 862.6320056992192\n",
      "Generation 1775: p = 0.9584800063324658\n",
      "Generation 1775: M(n) = 862.6320056992192\n",
      "Generation 1776: p = 0.9584800063324658\n",
      "Generation 1776: M(n) = 862.6320056992192\n",
      "Generation 1777: p = 0.9584800063324658\n",
      "Generation 1777: M(n) = 862.6320056992192\n",
      "Generation 1778: p = 0.9584800063324658\n",
      "Generation 1778: M(n) = 862.6320056992192\n",
      "Generation 1779: p = 0.9584800063324658\n",
      "Generation 1779: M(n) = 862.6320056992192\n",
      "Generation 1780: p = 0.9584800063324658\n",
      "Generation 1780: M(n) = 862.6320056992192\n",
      "Generation 1781: p = 0.9584800063324658\n",
      "Generation 1781: M(n) = 862.6320056992192\n",
      "Generation 1782: p = 0.9584800063324658\n",
      "Generation 1782: M(n) = 862.6320056992192\n",
      "Generation 1783: p = 0.9584800063324658\n",
      "Generation 1783: M(n) = 862.6320056992192\n",
      "Generation 1784: p = 0.9584800063324658\n",
      "Generation 1784: M(n) = 862.6320056992192\n",
      "Generation 1785: p = 0.9584800063324658\n",
      "Generation 1785: M(n) = 862.6320056992192\n",
      "Generation 1786: p = 0.9584800063324658\n",
      "Generation 1786: M(n) = 862.6320056992192\n",
      "Generation 1787: p = 0.9584800063324658\n",
      "Generation 1787: M(n) = 862.6320056992192\n",
      "Generation 1788: p = 0.9584800063324658\n",
      "Generation 1788: M(n) = 862.6320056992192\n",
      "Generation 1789: p = 0.9584800063324658\n",
      "Generation 1789: M(n) = 862.6320056992192\n",
      "Generation 1790: p = 0.9584800063324658\n",
      "Generation 1790: M(n) = 862.6320056992192\n",
      "Generation 1791: p = 0.9584800063324658\n",
      "Generation 1791: M(n) = 862.6320056992192\n",
      "Generation 1792: p = 0.9584800063324658\n",
      "Generation 1792: M(n) = 862.6320056992192\n",
      "Generation 1793: p = 0.9584800063324658\n",
      "Generation 1793: M(n) = 862.6320056992192\n",
      "Generation 1794: p = 0.9584800063324658\n",
      "Generation 1794: M(n) = 862.6320056992192\n",
      "Generation 1795: p = 0.9584800063324658\n",
      "Generation 1795: M(n) = 862.6320056992192\n",
      "Generation 1796: p = 0.9584800063324658\n",
      "Generation 1796: M(n) = 862.6320056992192\n",
      "Generation 1797: p = 0.9584800063324658\n",
      "Generation 1797: M(n) = 862.6320056992192\n",
      "Generation 1798: p = 0.9584800063324658\n",
      "Generation 1798: M(n) = 862.6320056992192\n",
      "Generation 1799: p = 0.9584800063324658\n",
      "Generation 1799: M(n) = 862.6320056992192\n",
      "Generation 1800: p = 0.9584800063324658\n",
      "Generation 1800: M(n) = 862.6320056992192\n",
      "Generation 1801: p = 0.9584800063324658\n",
      "Generation 1801: M(n) = 862.6320056992192\n",
      "Generation 1802: p = 0.9584800063324658\n",
      "Generation 1802: M(n) = 862.6320056992192\n",
      "Generation 1803: p = 0.9584800063324658\n",
      "Generation 1803: M(n) = 862.6320056992192\n",
      "Generation 1804: p = 0.9584800063324658\n",
      "Generation 1804: M(n) = 862.6320056992192\n",
      "Generation 1805: p = 0.9584800063324658\n",
      "Generation 1805: M(n) = 862.6320056992192\n",
      "Generation 1806: p = 0.9584800063324658\n",
      "Generation 1806: M(n) = 862.6320056992192\n",
      "Generation 1807: p = 0.9584800063324658\n",
      "Generation 1807: M(n) = 862.6320056992192\n",
      "Generation 1808: p = 0.9584800063324658\n",
      "Generation 1808: M(n) = 862.6320056992192\n",
      "Generation 1809: p = 0.9584800063324658\n",
      "Generation 1809: M(n) = 862.6320056992192\n",
      "Generation 1810: p = 0.9584800063324658\n",
      "Generation 1810: M(n) = 862.6320056992192\n",
      "Generation 1811: p = 0.9584800063324658\n",
      "Generation 1811: M(n) = 862.6320056992192\n",
      "Generation 1812: p = 0.9584800063324658\n",
      "Generation 1812: M(n) = 862.6320056992192\n",
      "Generation 1813: p = 0.9584800063324658\n",
      "Generation 1813: M(n) = 862.6320056992192\n",
      "Generation 1814: p = 0.9584800063324658\n",
      "Generation 1814: M(n) = 862.6320056992192\n",
      "Generation 1815: p = 0.9584800063324658\n",
      "Generation 1815: M(n) = 862.6320056992192\n",
      "Generation 1816: p = 0.9584800063324658\n",
      "Generation 1816: M(n) = 862.6320056992192\n",
      "Generation 1817: p = 0.9584800063324658\n",
      "Generation 1817: M(n) = 862.6320056992192\n",
      "Generation 1818: p = 0.9584800063324658\n",
      "Generation 1818: M(n) = 862.6320056992192\n",
      "Generation 1819: p = 0.9584800063324658\n",
      "Generation 1819: M(n) = 862.6320056992192\n",
      "Generation 1820: p = 0.9584800063324658\n",
      "Generation 1820: M(n) = 862.6320056992192\n",
      "Generation 1821: p = 0.9584800063324658\n",
      "Generation 1821: M(n) = 862.6320056992192\n",
      "Generation 1822: p = 0.9584800063324658\n",
      "Generation 1822: M(n) = 862.6320056992192\n",
      "Generation 1823: p = 0.9584800063324658\n",
      "Generation 1823: M(n) = 862.6320056992192\n",
      "Generation 1824: p = 0.9584800063324658\n",
      "Generation 1824: M(n) = 862.6320056992192\n",
      "Generation 1825: p = 0.9584800063324658\n",
      "Generation 1825: M(n) = 862.6320056992192\n",
      "Generation 1826: p = 0.9584800063324658\n",
      "Generation 1826: M(n) = 862.6320056992192\n",
      "Generation 1827: p = 0.9584800063324658\n",
      "Generation 1827: M(n) = 862.6320056992192\n",
      "Generation 1828: p = 0.9584800063324658\n",
      "Generation 1828: M(n) = 862.6320056992192\n",
      "Generation 1829: p = 0.9584800063324658\n",
      "Generation 1829: M(n) = 862.6320056992192\n",
      "Generation 1830: p = 0.9584800063324658\n",
      "Generation 1830: M(n) = 862.6320056992192\n",
      "Generation 1831: p = 0.9584800063324658\n",
      "Generation 1831: M(n) = 862.6320056992192\n",
      "Generation 1832: p = 0.9584800063324658\n",
      "Generation 1832: M(n) = 862.6320056992192\n",
      "Generation 1833: p = 0.9584800063324658\n",
      "Generation 1833: M(n) = 862.6320056992192\n",
      "Generation 1834: p = 0.9584800063324658\n",
      "Generation 1834: M(n) = 862.6320056992192\n",
      "Generation 1835: p = 0.9584800063324658\n",
      "Generation 1835: M(n) = 862.6320056992192\n",
      "Generation 1836: p = 0.9584800063324658\n",
      "Generation 1836: M(n) = 862.6320056992192\n",
      "Generation 1837: p = 0.9584800063324658\n",
      "Generation 1837: M(n) = 862.6320056992192\n",
      "Generation 1838: p = 0.9584800063324658\n",
      "Generation 1838: M(n) = 862.6320056992192\n",
      "Generation 1839: p = 0.9584800063324658\n",
      "Generation 1839: M(n) = 862.6320056992192\n",
      "Generation 1840: p = 0.9584800063324658\n",
      "Generation 1840: M(n) = 862.6320056992192\n",
      "Generation 1841: p = 0.9584800063324658\n",
      "Generation 1841: M(n) = 862.6320056992192\n",
      "Generation 1842: p = 0.9584800063324658\n",
      "Generation 1842: M(n) = 862.6320056992192\n",
      "Generation 1843: p = 0.9584800063324658\n",
      "Generation 1843: M(n) = 862.6320056992192\n",
      "Generation 1844: p = 0.9584800063324658\n",
      "Generation 1844: M(n) = 862.6320056992192\n",
      "Generation 1845: p = 0.9584800063324658\n",
      "Generation 1845: M(n) = 862.6320056992192\n",
      "Generation 1846: p = 0.9584800063324658\n",
      "Generation 1846: M(n) = 862.6320056992192\n",
      "Generation 1847: p = 0.9584800063324658\n",
      "Generation 1847: M(n) = 862.6320056992192\n",
      "Generation 1848: p = 0.9584800063324658\n",
      "Generation 1848: M(n) = 862.6320056992192\n",
      "Generation 1849: p = 0.9584800063324658\n",
      "Generation 1849: M(n) = 862.6320056992192\n",
      "Generation 1850: p = 0.9584800063324658\n",
      "Generation 1850: M(n) = 862.6320056992192\n",
      "Generation 1851: p = 0.9584800063324658\n",
      "Generation 1851: M(n) = 862.6320056992192\n",
      "Generation 1852: p = 0.9584800063324658\n",
      "Generation 1852: M(n) = 862.6320056992192\n",
      "Generation 1853: p = 0.9584800063324658\n",
      "Generation 1853: M(n) = 862.6320056992192\n",
      "Generation 1854: p = 0.9584800063324658\n",
      "Generation 1854: M(n) = 862.6320056992192\n",
      "Generation 1855: p = 0.9584800063324658\n",
      "Generation 1855: M(n) = 862.6320056992192\n",
      "Generation 1856: p = 0.9584800063324658\n",
      "Generation 1856: M(n) = 862.6320056992192\n",
      "Generation 1857: p = 0.9584800063324658\n",
      "Generation 1857: M(n) = 862.6320056992192\n",
      "Generation 1858: p = 0.9584800063324658\n",
      "Generation 1858: M(n) = 862.6320056992192\n",
      "Generation 1859: p = 0.9584800063324658\n",
      "Generation 1859: M(n) = 862.6320056992192\n",
      "Generation 1860: p = 0.9584800063324658\n",
      "Generation 1860: M(n) = 862.6320056992192\n",
      "Generation 1861: p = 0.9584800063324658\n",
      "Generation 1861: M(n) = 862.6320056992192\n",
      "Generation 1862: p = 0.9584800063324658\n",
      "Generation 1862: M(n) = 862.6320056992192\n",
      "Generation 1863: p = 0.9584800063324658\n",
      "Generation 1863: M(n) = 862.6320056992192\n",
      "Generation 1864: p = 0.9584800063324658\n",
      "Generation 1864: M(n) = 862.6320056992192\n",
      "Generation 1865: p = 0.9584800063324658\n",
      "Generation 1865: M(n) = 862.6320056992192\n",
      "Generation 1866: p = 0.9584800063324658\n",
      "Generation 1866: M(n) = 862.6320056992192\n",
      "Generation 1867: p = 0.9584800063324658\n",
      "Generation 1867: M(n) = 862.6320056992192\n",
      "Generation 1868: p = 0.9584800063324658\n",
      "Generation 1868: M(n) = 862.6320056992192\n",
      "Generation 1869: p = 0.9584800063324658\n",
      "Generation 1869: M(n) = 862.6320056992192\n",
      "Generation 1870: p = 0.9584800063324658\n",
      "Generation 1870: M(n) = 862.6320056992192\n",
      "Generation 1871: p = 0.9584800063324658\n",
      "Generation 1871: M(n) = 862.6320056992192\n",
      "Generation 1872: p = 0.9584800063324658\n",
      "Generation 1872: M(n) = 862.6320056992192\n",
      "Generation 1873: p = 0.9584800063324658\n",
      "Generation 1873: M(n) = 862.6320056992192\n",
      "Generation 1874: p = 0.9584800063324658\n",
      "Generation 1874: M(n) = 862.6320056992192\n",
      "Generation 1875: p = 0.9584800063324658\n",
      "Generation 1875: M(n) = 862.6320056992192\n",
      "Generation 1876: p = 0.9584800063324658\n",
      "Generation 1876: M(n) = 862.6320056992192\n",
      "Generation 1877: p = 0.9584800063324658\n",
      "Generation 1877: M(n) = 862.6320056992192\n",
      "Generation 1878: p = 0.9584800063324658\n",
      "Generation 1878: M(n) = 862.6320056992192\n",
      "Generation 1879: p = 0.9584800063324658\n",
      "Generation 1879: M(n) = 862.6320056992192\n",
      "Generation 1880: p = 0.9584800063324658\n",
      "Generation 1880: M(n) = 862.6320056992192\n",
      "Generation 1881: p = 0.9584800063324658\n",
      "Generation 1881: M(n) = 862.6320056992192\n",
      "Generation 1882: p = 0.9584800063324658\n",
      "Generation 1882: M(n) = 862.6320056992192\n",
      "Generation 1883: p = 0.9584800063324658\n",
      "Generation 1883: M(n) = 862.6320056992192\n",
      "Generation 1884: p = 0.9584800063324658\n",
      "Generation 1884: M(n) = 862.6320056992192\n",
      "Generation 1885: p = 0.9584800063324658\n",
      "Generation 1885: M(n) = 862.6320056992192\n",
      "Generation 1886: p = 0.9584800063324658\n",
      "Generation 1886: M(n) = 862.6320056992192\n",
      "Generation 1887: p = 0.9584800063324658\n",
      "Generation 1887: M(n) = 862.6320056992192\n",
      "Generation 1888: p = 0.9584800063324658\n",
      "Generation 1888: M(n) = 862.6320056992192\n",
      "Generation 1889: p = 0.9584800063324658\n",
      "Generation 1889: M(n) = 862.6320056992192\n",
      "Generation 1890: p = 0.9584800063324658\n",
      "Generation 1890: M(n) = 862.6320056992192\n",
      "Generation 1891: p = 0.9584800063324658\n",
      "Generation 1891: M(n) = 862.6320056992192\n",
      "Generation 1892: p = 0.9584800063324658\n",
      "Generation 1892: M(n) = 862.6320056992192\n",
      "Generation 1893: p = 0.9584800063324658\n",
      "Generation 1893: M(n) = 862.6320056992192\n",
      "Generation 1894: p = 0.9584800063324658\n",
      "Generation 1894: M(n) = 862.6320056992192\n",
      "Generation 1895: p = 0.9584800063324658\n",
      "Generation 1895: M(n) = 862.6320056992192\n",
      "Generation 1896: p = 0.9584800063324658\n",
      "Generation 1896: M(n) = 862.6320056992192\n",
      "Generation 1897: p = 0.9584800063324658\n",
      "Generation 1897: M(n) = 862.6320056992192\n",
      "Generation 1898: p = 0.9584800063324658\n",
      "Generation 1898: M(n) = 862.6320056992192\n",
      "Generation 1899: p = 0.9584800063324658\n",
      "Generation 1899: M(n) = 862.6320056992192\n",
      "Generation 1900: p = 0.9584800063324658\n",
      "Generation 1900: M(n) = 862.6320056992192\n",
      "Generation 1901: p = 0.9584800063324658\n",
      "Generation 1901: M(n) = 862.6320056992192\n",
      "Generation 1902: p = 0.9584800063324658\n",
      "Generation 1902: M(n) = 862.6320056992192\n",
      "Generation 1903: p = 0.9584800063324658\n",
      "Generation 1903: M(n) = 862.6320056992192\n",
      "Generation 1904: p = 0.9584800063324658\n",
      "Generation 1904: M(n) = 862.6320056992192\n",
      "Generation 1905: p = 0.9584800063324658\n",
      "Generation 1905: M(n) = 862.6320056992192\n",
      "Generation 1906: p = 0.9584800063324658\n",
      "Generation 1906: M(n) = 862.6320056992192\n",
      "Generation 1907: p = 0.9584800063324658\n",
      "Generation 1907: M(n) = 862.6320056992192\n",
      "Generation 1908: p = 0.9584800063324658\n",
      "Generation 1908: M(n) = 862.6320056992192\n",
      "Generation 1909: p = 0.9584800063324658\n",
      "Generation 1909: M(n) = 862.6320056992192\n",
      "Generation 1910: p = 0.9584800063324658\n",
      "Generation 1910: M(n) = 862.6320056992192\n",
      "Generation 1911: p = 0.9584800063324658\n",
      "Generation 1911: M(n) = 862.6320056992192\n",
      "Generation 1912: p = 0.9584800063324658\n",
      "Generation 1912: M(n) = 862.6320056992192\n",
      "Generation 1913: p = 0.9584800063324658\n",
      "Generation 1913: M(n) = 862.6320056992192\n",
      "Generation 1914: p = 0.9584800063324658\n",
      "Generation 1914: M(n) = 862.6320056992192\n",
      "Generation 1915: p = 0.9584800063324658\n",
      "Generation 1915: M(n) = 862.6320056992192\n",
      "Generation 1916: p = 0.9584800063324658\n",
      "Generation 1916: M(n) = 862.6320056992192\n",
      "Generation 1917: p = 0.9584800063324658\n",
      "Generation 1917: M(n) = 862.6320056992192\n",
      "Generation 1918: p = 0.9584800063324658\n",
      "Generation 1918: M(n) = 862.6320056992192\n",
      "Generation 1919: p = 0.9584800063324658\n",
      "Generation 1919: M(n) = 862.6320056992192\n",
      "Generation 1920: p = 0.9584800063324658\n",
      "Generation 1920: M(n) = 862.6320056992192\n",
      "Generation 1921: p = 0.9584800063324658\n",
      "Generation 1921: M(n) = 862.6320056992192\n",
      "Generation 1922: p = 0.9584800063324658\n",
      "Generation 1922: M(n) = 862.6320056992192\n",
      "Generation 1923: p = 0.9584800063324658\n",
      "Generation 1923: M(n) = 862.6320056992192\n",
      "Generation 1924: p = 0.9584800063324658\n",
      "Generation 1924: M(n) = 862.6320056992192\n",
      "Generation 1925: p = 0.9584800063324658\n",
      "Generation 1925: M(n) = 862.6320056992192\n",
      "Generation 1926: p = 0.9584800063324658\n",
      "Generation 1926: M(n) = 862.6320056992192\n",
      "Generation 1927: p = 0.9584800063324658\n",
      "Generation 1927: M(n) = 862.6320056992192\n",
      "Generation 1928: p = 0.9584800063324658\n",
      "Generation 1928: M(n) = 862.6320056992192\n",
      "Generation 1929: p = 0.9584800063324658\n",
      "Generation 1929: M(n) = 862.6320056992192\n",
      "Generation 1930: p = 0.9584800063324658\n",
      "Generation 1930: M(n) = 862.6320056992192\n",
      "Generation 1931: p = 0.9584800063324658\n",
      "Generation 1931: M(n) = 862.6320056992192\n",
      "Generation 1932: p = 0.9584800063324658\n",
      "Generation 1932: M(n) = 862.6320056992192\n",
      "Generation 1933: p = 0.9584800063324658\n",
      "Generation 1933: M(n) = 862.6320056992192\n",
      "Generation 1934: p = 0.9584800063324658\n",
      "Generation 1934: M(n) = 862.6320056992192\n",
      "Generation 1935: p = 0.9584800063324658\n",
      "Generation 1935: M(n) = 862.6320056992192\n",
      "Generation 1936: p = 0.9584800063324658\n",
      "Generation 1936: M(n) = 862.6320056992192\n",
      "Generation 1937: p = 0.9584800063324658\n",
      "Generation 1937: M(n) = 862.6320056992192\n",
      "Generation 1938: p = 0.9584800063324658\n",
      "Generation 1938: M(n) = 862.6320056992192\n",
      "Generation 1939: p = 0.9584800063324658\n",
      "Generation 1939: M(n) = 862.6320056992192\n",
      "Generation 1940: p = 0.9584800063324658\n",
      "Generation 1940: M(n) = 862.6320056992192\n",
      "Generation 1941: p = 0.9584800063324658\n",
      "Generation 1941: M(n) = 862.6320056992192\n",
      "Generation 1942: p = 0.9584800063324658\n",
      "Generation 1942: M(n) = 862.6320056992192\n",
      "Generation 1943: p = 0.9584800063324658\n",
      "Generation 1943: M(n) = 862.6320056992192\n",
      "Generation 1944: p = 0.9584800063324658\n",
      "Generation 1944: M(n) = 862.6320056992192\n",
      "Generation 1945: p = 0.9584800063324658\n",
      "Generation 1945: M(n) = 862.6320056992192\n",
      "Generation 1946: p = 0.9584800063324658\n",
      "Generation 1946: M(n) = 862.6320056992192\n",
      "Generation 1947: p = 0.9584800063324658\n",
      "Generation 1947: M(n) = 862.6320056992192\n",
      "Generation 1948: p = 0.9584800063324658\n",
      "Generation 1948: M(n) = 862.6320056992192\n",
      "Generation 1949: p = 0.9584800063324658\n",
      "Generation 1949: M(n) = 862.6320056992192\n",
      "Generation 1950: p = 0.9584800063324658\n",
      "Generation 1950: M(n) = 862.6320056992192\n",
      "Generation 1951: p = 0.9584800063324658\n",
      "Generation 1951: M(n) = 862.6320056992192\n",
      "Generation 1952: p = 0.9584800063324658\n",
      "Generation 1952: M(n) = 862.6320056992192\n",
      "Generation 1953: p = 0.9584800063324658\n",
      "Generation 1953: M(n) = 862.6320056992192\n",
      "Generation 1954: p = 0.9584800063324658\n",
      "Generation 1954: M(n) = 862.6320056992192\n",
      "Generation 1955: p = 0.9584800063324658\n",
      "Generation 1955: M(n) = 862.6320056992192\n",
      "Generation 1956: p = 0.9584800063324658\n",
      "Generation 1956: M(n) = 862.6320056992192\n",
      "Generation 1957: p = 0.9584800063324658\n",
      "Generation 1957: M(n) = 862.6320056992192\n",
      "Generation 1958: p = 0.9584800063324658\n",
      "Generation 1958: M(n) = 862.6320056992192\n",
      "Generation 1959: p = 0.9584800063324658\n",
      "Generation 1959: M(n) = 862.6320056992192\n",
      "Generation 1960: p = 0.9584800063324658\n",
      "Generation 1960: M(n) = 862.6320056992192\n",
      "Generation 1961: p = 0.9584800063324658\n",
      "Generation 1961: M(n) = 862.6320056992192\n",
      "Generation 1962: p = 0.9584800063324658\n",
      "Generation 1962: M(n) = 862.6320056992192\n",
      "Generation 1963: p = 0.9584800063324658\n",
      "Generation 1963: M(n) = 862.6320056992192\n",
      "Generation 1964: p = 0.9584800063324658\n",
      "Generation 1964: M(n) = 862.6320056992192\n",
      "Generation 1965: p = 0.9584800063324658\n",
      "Generation 1965: M(n) = 862.6320056992192\n",
      "Generation 1966: p = 0.9584800063324658\n",
      "Generation 1966: M(n) = 862.6320056992192\n",
      "Generation 1967: p = 0.9584800063324658\n",
      "Generation 1967: M(n) = 862.6320056992192\n",
      "Generation 1968: p = 0.9584800063324658\n",
      "Generation 1968: M(n) = 862.6320056992192\n",
      "Generation 1969: p = 0.9584800063324658\n",
      "Generation 1969: M(n) = 862.6320056992192\n",
      "Generation 1970: p = 0.9584800063324658\n",
      "Generation 1970: M(n) = 862.6320056992192\n",
      "Generation 1971: p = 0.9584800063324658\n",
      "Generation 1971: M(n) = 862.6320056992192\n",
      "Generation 1972: p = 0.9584800063324658\n",
      "Generation 1972: M(n) = 862.6320056992192\n",
      "Generation 1973: p = 0.9584800063324658\n",
      "Generation 1973: M(n) = 862.6320056992192\n",
      "Generation 1974: p = 0.9584800063324658\n",
      "Generation 1974: M(n) = 862.6320056992192\n",
      "Generation 1975: p = 0.9584800063324658\n",
      "Generation 1975: M(n) = 862.6320056992192\n",
      "Generation 1976: p = 0.9584800063324658\n",
      "Generation 1976: M(n) = 862.6320056992192\n",
      "Generation 1977: p = 0.9584800063324658\n",
      "Generation 1977: M(n) = 862.6320056992192\n",
      "Generation 1978: p = 0.9584800063324658\n",
      "Generation 1978: M(n) = 862.6320056992192\n",
      "Generation 1979: p = 0.9584800063324658\n",
      "Generation 1979: M(n) = 862.6320056992192\n",
      "Generation 1980: p = 0.9584800063324658\n",
      "Generation 1980: M(n) = 862.6320056992192\n",
      "Generation 1981: p = 0.9584800063324658\n",
      "Generation 1981: M(n) = 862.6320056992192\n",
      "Generation 1982: p = 0.9584800063324658\n",
      "Generation 1982: M(n) = 862.6320056992192\n",
      "Generation 1983: p = 0.9584800063324658\n",
      "Generation 1983: M(n) = 862.6320056992192\n",
      "Generation 1984: p = 0.9584800063324658\n",
      "Generation 1984: M(n) = 862.6320056992192\n",
      "Generation 1985: p = 0.9584800063324658\n",
      "Generation 1985: M(n) = 862.6320056992192\n",
      "Generation 1986: p = 0.9584800063324658\n",
      "Generation 1986: M(n) = 862.6320056992192\n",
      "Generation 1987: p = 0.9584800063324658\n",
      "Generation 1987: M(n) = 862.6320056992192\n",
      "Generation 1988: p = 0.9584800063324658\n",
      "Generation 1988: M(n) = 862.6320056992192\n",
      "Generation 1989: p = 0.9584800063324658\n",
      "Generation 1989: M(n) = 862.6320056992192\n",
      "Generation 1990: p = 0.9584800063324658\n",
      "Generation 1990: M(n) = 862.6320056992192\n",
      "Generation 1991: p = 0.9584800063324658\n",
      "Generation 1991: M(n) = 862.6320056992192\n",
      "Generation 1992: p = 0.9584800063324658\n",
      "Generation 1992: M(n) = 862.6320056992192\n",
      "Generation 1993: p = 0.9584800063324658\n",
      "Generation 1993: M(n) = 862.6320056992192\n",
      "Generation 1994: p = 0.9584800063324658\n",
      "Generation 1994: M(n) = 862.6320056992192\n",
      "Generation 1995: p = 0.9584800063324658\n",
      "Generation 1995: M(n) = 862.6320056992192\n",
      "Generation 1996: p = 0.9584800063324658\n",
      "Generation 1996: M(n) = 862.6320056992192\n",
      "Generation 1997: p = 0.9584800063324658\n",
      "Generation 1997: M(n) = 862.6320056992192\n",
      "Generation 1998: p = 0.9584800063324658\n",
      "Generation 1998: M(n) = 862.6320056992192\n",
      "Generation 1999: p = 0.9584800063324658\n",
      "Generation 1999: M(n) = 862.6320056992192\n",
      "Generation 2000: p = 0.9584800063324658\n",
      "Generation 2000: M(n) = 862.6320056992192\n",
      "Generation 2001: p = 0.9584800063324658\n",
      "Generation 2001: M(n) = 862.6320056992192\n",
      "Generation 2002: p = 0.9584800063324658\n",
      "Generation 2002: M(n) = 862.6320056992192\n",
      "Generation 2003: p = 0.9584800063324658\n",
      "Generation 2003: M(n) = 862.6320056992192\n",
      "Generation 2004: p = 0.9584800063324658\n",
      "Generation 2004: M(n) = 862.6320056992192\n",
      "Generation 2005: p = 0.9584800063324658\n",
      "Generation 2005: M(n) = 862.6320056992192\n",
      "Generation 2006: p = 0.9584800063324658\n",
      "Generation 2006: M(n) = 862.6320056992192\n",
      "Generation 2007: p = 0.9584800063324658\n",
      "Generation 2007: M(n) = 862.6320056992192\n",
      "Generation 2008: p = 0.9584800063324658\n",
      "Generation 2008: M(n) = 862.6320056992192\n",
      "Generation 2009: p = 0.9584800063324658\n",
      "Generation 2009: M(n) = 862.6320056992192\n",
      "Generation 2010: p = 0.9584800063324658\n",
      "Generation 2010: M(n) = 862.6320056992192\n",
      "Generation 2011: p = 0.9584800063324658\n",
      "Generation 2011: M(n) = 862.6320056992192\n",
      "Generation 2012: p = 0.9584800063324658\n",
      "Generation 2012: M(n) = 862.6320056992192\n",
      "Generation 2013: p = 0.9584800063324658\n",
      "Generation 2013: M(n) = 862.6320056992192\n",
      "Generation 2014: p = 0.9584800063324658\n",
      "Generation 2014: M(n) = 862.6320056992192\n",
      "Generation 2015: p = 0.9584800063324658\n",
      "Generation 2015: M(n) = 862.6320056992192\n",
      "Generation 2016: p = 0.9584800063324658\n",
      "Generation 2016: M(n) = 862.6320056992192\n",
      "Generation 2017: p = 0.9584800063324658\n",
      "Generation 2017: M(n) = 862.6320056992192\n",
      "Generation 2018: p = 0.9584800063324658\n",
      "Generation 2018: M(n) = 862.6320056992192\n",
      "Generation 2019: p = 0.9584800063324658\n",
      "Generation 2019: M(n) = 862.6320056992192\n",
      "Generation 2020: p = 0.9584800063324658\n",
      "Generation 2020: M(n) = 862.6320056992192\n",
      "Generation 2021: p = 0.9584800063324658\n",
      "Generation 2021: M(n) = 862.6320056992192\n",
      "Generation 2022: p = 0.9584800063324658\n",
      "Generation 2022: M(n) = 862.6320056992192\n",
      "Generation 2023: p = 0.9584800063324658\n",
      "Generation 2023: M(n) = 862.6320056992192\n",
      "Generation 2024: p = 0.9584800063324658\n",
      "Generation 2024: M(n) = 862.6320056992192\n",
      "Generation 2025: p = 0.9584800063324658\n",
      "Generation 2025: M(n) = 862.6320056992192\n",
      "Generation 2026: p = 0.9584800063324658\n",
      "Generation 2026: M(n) = 862.6320056992192\n",
      "Generation 2027: p = 0.9584800063324658\n",
      "Generation 2027: M(n) = 862.6320056992192\n",
      "Generation 2028: p = 0.9584800063324658\n",
      "Generation 2028: M(n) = 862.6320056992192\n",
      "Generation 2029: p = 0.9584800063324658\n",
      "Generation 2029: M(n) = 862.6320056992192\n",
      "Generation 2030: p = 0.9584800063324658\n",
      "Generation 2030: M(n) = 862.6320056992192\n",
      "Generation 2031: p = 0.9584800063324658\n",
      "Generation 2031: M(n) = 862.6320056992192\n",
      "Generation 2032: p = 0.9584800063324658\n",
      "Generation 2032: M(n) = 862.6320056992192\n",
      "Generation 2033: p = 0.9584800063324658\n",
      "Generation 2033: M(n) = 862.6320056992192\n",
      "Generation 2034: p = 0.9584800063324658\n",
      "Generation 2034: M(n) = 862.6320056992192\n",
      "Generation 2035: p = 0.9584800063324658\n",
      "Generation 2035: M(n) = 862.6320056992192\n",
      "Generation 2036: p = 0.9584800063324658\n",
      "Generation 2036: M(n) = 862.6320056992192\n",
      "Generation 2037: p = 0.9584800063324658\n",
      "Generation 2037: M(n) = 862.6320056992192\n",
      "Generation 2038: p = 0.9584800063324658\n",
      "Generation 2038: M(n) = 862.6320056992192\n",
      "Generation 2039: p = 0.9584800063324658\n",
      "Generation 2039: M(n) = 862.6320056992192\n",
      "Generation 2040: p = 0.9584800063324658\n",
      "Generation 2040: M(n) = 862.6320056992192\n",
      "Generation 2041: p = 0.9584800063324658\n",
      "Generation 2041: M(n) = 862.6320056992192\n",
      "Generation 2042: p = 0.9584800063324658\n",
      "Generation 2042: M(n) = 862.6320056992192\n",
      "Generation 2043: p = 0.9584800063324658\n",
      "Generation 2043: M(n) = 862.6320056992192\n",
      "Generation 2044: p = 0.9584800063324658\n",
      "Generation 2044: M(n) = 862.6320056992192\n",
      "Generation 2045: p = 0.9584800063324658\n",
      "Generation 2045: M(n) = 862.6320056992192\n",
      "Generation 2046: p = 0.9584800063324658\n",
      "Generation 2046: M(n) = 862.6320056992192\n",
      "Generation 2047: p = 0.9584800063324658\n",
      "Generation 2047: M(n) = 862.6320056992192\n",
      "Generation 2048: p = 0.9584800063324658\n",
      "Generation 2048: M(n) = 862.6320056992192\n",
      "Generation 2049: p = 0.9584800063324658\n",
      "Generation 2049: M(n) = 862.6320056992192\n",
      "Generation 2050: p = 0.9584800063324658\n",
      "Generation 2050: M(n) = 862.6320056992192\n",
      "Generation 2051: p = 0.9584800063324658\n",
      "Generation 2051: M(n) = 862.6320056992192\n",
      "Generation 2052: p = 0.9584800063324658\n",
      "Generation 2052: M(n) = 862.6320056992192\n",
      "Generation 2053: p = 0.9584800063324658\n",
      "Generation 2053: M(n) = 862.6320056992192\n",
      "Generation 2054: p = 0.9584800063324658\n",
      "Generation 2054: M(n) = 862.6320056992192\n",
      "Generation 2055: p = 0.9584800063324658\n",
      "Generation 2055: M(n) = 862.6320056992192\n",
      "Generation 2056: p = 0.9584800063324658\n",
      "Generation 2056: M(n) = 862.6320056992192\n",
      "Generation 2057: p = 0.9584800063324658\n",
      "Generation 2057: M(n) = 862.6320056992192\n",
      "Generation 2058: p = 0.9584800063324658\n",
      "Generation 2058: M(n) = 862.6320056992192\n",
      "Generation 2059: p = 0.9584800063324658\n",
      "Generation 2059: M(n) = 862.6320056992192\n",
      "Generation 2060: p = 0.9584800063324658\n",
      "Generation 2060: M(n) = 862.6320056992192\n",
      "Generation 2061: p = 0.9584800063324658\n",
      "Generation 2061: M(n) = 862.6320056992192\n",
      "Generation 2062: p = 0.9584800063324658\n",
      "Generation 2062: M(n) = 862.6320056992192\n",
      "Generation 2063: p = 0.9584800063324658\n",
      "Generation 2063: M(n) = 862.6320056992192\n",
      "Generation 2064: p = 0.9584800063324658\n",
      "Generation 2064: M(n) = 862.6320056992192\n",
      "Generation 2065: p = 0.9584800063324658\n",
      "Generation 2065: M(n) = 862.6320056992192\n",
      "Generation 2066: p = 0.9584800063324658\n",
      "Generation 2066: M(n) = 862.6320056992192\n",
      "Generation 2067: p = 0.9584800063324658\n",
      "Generation 2067: M(n) = 862.6320056992192\n",
      "Generation 2068: p = 0.9584800063324658\n",
      "Generation 2068: M(n) = 862.6320056992192\n",
      "Generation 2069: p = 0.9584800063324658\n",
      "Generation 2069: M(n) = 862.6320056992192\n",
      "Generation 2070: p = 0.9584800063324658\n",
      "Generation 2070: M(n) = 862.6320056992192\n",
      "Generation 2071: p = 0.9584800063324658\n",
      "Generation 2071: M(n) = 862.6320056992192\n",
      "Generation 2072: p = 0.9584800063324658\n",
      "Generation 2072: M(n) = 862.6320056992192\n",
      "Generation 2073: p = 0.9584800063324658\n",
      "Generation 2073: M(n) = 862.6320056992192\n",
      "Generation 2074: p = 0.9584800063324658\n",
      "Generation 2074: M(n) = 862.6320056992192\n",
      "Generation 2075: p = 0.9584800063324658\n",
      "Generation 2075: M(n) = 862.6320056992192\n",
      "Generation 2076: p = 0.9584800063324658\n",
      "Generation 2076: M(n) = 862.6320056992192\n",
      "Generation 2077: p = 0.9584800063324658\n",
      "Generation 2077: M(n) = 862.6320056992192\n",
      "Generation 2078: p = 0.9584800063324658\n",
      "Generation 2078: M(n) = 862.6320056992192\n",
      "Generation 2079: p = 0.9584800063324658\n",
      "Generation 2079: M(n) = 862.6320056992192\n",
      "Generation 2080: p = 0.9584800063324658\n",
      "Generation 2080: M(n) = 862.6320056992192\n",
      "Generation 2081: p = 0.9584800063324658\n",
      "Generation 2081: M(n) = 862.6320056992192\n",
      "Generation 2082: p = 0.9584800063324658\n",
      "Generation 2082: M(n) = 862.6320056992192\n",
      "Generation 2083: p = 0.9584800063324658\n",
      "Generation 2083: M(n) = 862.6320056992192\n",
      "Generation 2084: p = 0.9584800063324658\n",
      "Generation 2084: M(n) = 862.6320056992192\n",
      "Generation 2085: p = 0.9584800063324658\n",
      "Generation 2085: M(n) = 862.6320056992192\n",
      "Generation 2086: p = 0.9584800063324658\n",
      "Generation 2086: M(n) = 862.6320056992192\n",
      "Generation 2087: p = 0.9584800063324658\n",
      "Generation 2087: M(n) = 862.6320056992192\n",
      "Generation 2088: p = 0.9584800063324658\n",
      "Generation 2088: M(n) = 862.6320056992192\n",
      "Generation 2089: p = 0.9584800063324658\n",
      "Generation 2089: M(n) = 862.6320056992192\n",
      "Generation 2090: p = 0.9584800063324658\n",
      "Generation 2090: M(n) = 862.6320056992192\n",
      "Generation 2091: p = 0.9584800063324658\n",
      "Generation 2091: M(n) = 862.6320056992192\n",
      "Generation 2092: p = 0.9584800063324658\n",
      "Generation 2092: M(n) = 862.6320056992192\n",
      "Generation 2093: p = 0.9584800063324658\n",
      "Generation 2093: M(n) = 862.6320056992192\n",
      "Generation 2094: p = 0.9584800063324658\n",
      "Generation 2094: M(n) = 862.6320056992192\n",
      "Generation 2095: p = 0.9584800063324658\n",
      "Generation 2095: M(n) = 862.6320056992192\n",
      "Generation 2096: p = 0.9584800063324658\n",
      "Generation 2096: M(n) = 862.6320056992192\n",
      "Generation 2097: p = 0.9584800063324658\n",
      "Generation 2097: M(n) = 862.6320056992192\n",
      "Generation 2098: p = 0.9584800063324658\n",
      "Generation 2098: M(n) = 862.6320056992192\n",
      "Generation 2099: p = 0.9584800063324658\n",
      "Generation 2099: M(n) = 862.6320056992192\n",
      "Generation 2100: p = 0.9584800063324658\n",
      "Generation 2100: M(n) = 862.6320056992192\n",
      "Generation 2101: p = 0.9584800063324658\n",
      "Generation 2101: M(n) = 862.6320056992192\n",
      "Generation 2102: p = 0.9584800063324658\n",
      "Generation 2102: M(n) = 862.6320056992192\n",
      "Generation 2103: p = 0.9584800063324658\n",
      "Generation 2103: M(n) = 862.6320056992192\n",
      "Generation 2104: p = 0.9584800063324658\n",
      "Generation 2104: M(n) = 862.6320056992192\n",
      "Generation 2105: p = 0.9584800063324658\n",
      "Generation 2105: M(n) = 862.6320056992192\n",
      "Generation 2106: p = 0.9584800063324658\n",
      "Generation 2106: M(n) = 862.6320056992192\n",
      "Generation 2107: p = 0.9584800063324658\n",
      "Generation 2107: M(n) = 862.6320056992192\n",
      "Generation 2108: p = 0.9584800063324658\n",
      "Generation 2108: M(n) = 862.6320056992192\n",
      "Generation 2109: p = 0.9584800063324658\n",
      "Generation 2109: M(n) = 862.6320056992192\n",
      "Generation 2110: p = 0.9584800063324658\n",
      "Generation 2110: M(n) = 862.6320056992192\n",
      "Generation 2111: p = 0.9584800063324658\n",
      "Generation 2111: M(n) = 862.6320056992192\n",
      "Generation 2112: p = 0.9584800063324658\n",
      "Generation 2112: M(n) = 862.6320056992192\n",
      "Generation 2113: p = 0.9584800063324658\n",
      "Generation 2113: M(n) = 862.6320056992192\n",
      "Generation 2114: p = 0.9584800063324658\n",
      "Generation 2114: M(n) = 862.6320056992192\n",
      "Generation 2115: p = 0.9584800063324658\n",
      "Generation 2115: M(n) = 862.6320056992192\n",
      "Generation 2116: p = 0.9584800063324658\n",
      "Generation 2116: M(n) = 862.6320056992192\n",
      "Generation 2117: p = 0.9584800063324658\n",
      "Generation 2117: M(n) = 862.6320056992192\n",
      "Generation 2118: p = 0.9584800063324658\n",
      "Generation 2118: M(n) = 862.6320056992192\n",
      "Generation 2119: p = 0.9584800063324658\n",
      "Generation 2119: M(n) = 862.6320056992192\n",
      "Generation 2120: p = 0.9584800063324658\n",
      "Generation 2120: M(n) = 862.6320056992192\n",
      "Generation 2121: p = 0.9584800063324658\n",
      "Generation 2121: M(n) = 862.6320056992192\n",
      "Generation 2122: p = 0.9584800063324658\n",
      "Generation 2122: M(n) = 862.6320056992192\n",
      "Generation 2123: p = 0.9584800063324658\n",
      "Generation 2123: M(n) = 862.6320056992192\n",
      "Generation 2124: p = 0.9584800063324658\n",
      "Generation 2124: M(n) = 862.6320056992192\n",
      "Generation 2125: p = 0.9584800063324658\n",
      "Generation 2125: M(n) = 862.6320056992192\n",
      "Generation 2126: p = 0.9584800063324658\n",
      "Generation 2126: M(n) = 862.6320056992192\n",
      "Generation 2127: p = 0.9584800063324658\n",
      "Generation 2127: M(n) = 862.6320056992192\n",
      "Generation 2128: p = 0.9584800063324658\n",
      "Generation 2128: M(n) = 862.6320056992192\n",
      "Generation 2129: p = 0.9584800063324658\n",
      "Generation 2129: M(n) = 862.6320056992192\n",
      "Generation 2130: p = 0.9584800063324658\n",
      "Generation 2130: M(n) = 862.6320056992192\n",
      "Generation 2131: p = 0.9584800063324658\n",
      "Generation 2131: M(n) = 862.6320056992192\n",
      "Generation 2132: p = 0.9584800063324658\n",
      "Generation 2132: M(n) = 862.6320056992192\n",
      "Generation 2133: p = 0.9584800063324658\n",
      "Generation 2133: M(n) = 862.6320056992192\n",
      "Generation 2134: p = 0.9584800063324658\n",
      "Generation 2134: M(n) = 862.6320056992192\n",
      "Generation 2135: p = 0.9584800063324658\n",
      "Generation 2135: M(n) = 862.6320056992192\n",
      "Generation 2136: p = 0.9584800063324658\n",
      "Generation 2136: M(n) = 862.6320056992192\n",
      "Generation 2137: p = 0.9584800063324658\n",
      "Generation 2137: M(n) = 862.6320056992192\n",
      "Generation 2138: p = 0.9584800063324658\n",
      "Generation 2138: M(n) = 862.6320056992192\n",
      "Generation 2139: p = 0.9584800063324658\n",
      "Generation 2139: M(n) = 862.6320056992192\n",
      "Generation 2140: p = 0.9584800063324658\n",
      "Generation 2140: M(n) = 862.6320056992192\n",
      "Generation 2141: p = 0.9584800063324658\n",
      "Generation 2141: M(n) = 862.6320056992192\n",
      "Generation 2142: p = 0.9584800063324658\n",
      "Generation 2142: M(n) = 862.6320056992192\n",
      "Generation 2143: p = 0.9584800063324658\n",
      "Generation 2143: M(n) = 862.6320056992192\n",
      "Generation 2144: p = 0.9584800063324658\n",
      "Generation 2144: M(n) = 862.6320056992192\n",
      "Generation 2145: p = 0.9584800063324658\n",
      "Generation 2145: M(n) = 862.6320056992192\n",
      "Generation 2146: p = 0.9584800063324658\n",
      "Generation 2146: M(n) = 862.6320056992192\n",
      "Generation 2147: p = 0.9584800063324658\n",
      "Generation 2147: M(n) = 862.6320056992192\n",
      "Generation 2148: p = 0.9584800063324658\n",
      "Generation 2148: M(n) = 862.6320056992192\n",
      "Generation 2149: p = 0.9584800063324658\n",
      "Generation 2149: M(n) = 862.6320056992192\n",
      "Generation 2150: p = 0.9584800063324658\n",
      "Generation 2150: M(n) = 862.6320056992192\n",
      "Generation 2151: p = 0.9584800063324658\n",
      "Generation 2151: M(n) = 862.6320056992192\n",
      "Generation 2152: p = 0.9584800063324658\n",
      "Generation 2152: M(n) = 862.6320056992192\n",
      "Generation 2153: p = 0.9584800063324658\n",
      "Generation 2153: M(n) = 862.6320056992192\n",
      "Generation 2154: p = 0.9584800063324658\n",
      "Generation 2154: M(n) = 862.6320056992192\n",
      "Generation 2155: p = 0.9584800063324658\n",
      "Generation 2155: M(n) = 862.6320056992192\n",
      "Generation 2156: p = 0.9584800063324658\n",
      "Generation 2156: M(n) = 862.6320056992192\n",
      "Generation 2157: p = 0.9584800063324658\n",
      "Generation 2157: M(n) = 862.6320056992192\n",
      "Generation 2158: p = 0.9584800063324658\n",
      "Generation 2158: M(n) = 862.6320056992192\n",
      "Generation 2159: p = 0.9584800063324658\n",
      "Generation 2159: M(n) = 862.6320056992192\n",
      "Generation 2160: p = 0.9584800063324658\n",
      "Generation 2160: M(n) = 862.6320056992192\n",
      "Generation 2161: p = 0.9584800063324658\n",
      "Generation 2161: M(n) = 862.6320056992192\n",
      "Generation 2162: p = 0.9584800063324658\n",
      "Generation 2162: M(n) = 862.6320056992192\n",
      "Generation 2163: p = 0.9584800063324658\n",
      "Generation 2163: M(n) = 862.6320056992192\n",
      "Generation 2164: p = 0.9584800063324658\n",
      "Generation 2164: M(n) = 862.6320056992192\n",
      "Generation 2165: p = 0.9584800063324658\n",
      "Generation 2165: M(n) = 862.6320056992192\n",
      "Generation 2166: p = 0.9584800063324658\n",
      "Generation 2166: M(n) = 862.6320056992192\n",
      "Generation 2167: p = 0.9584800063324658\n",
      "Generation 2167: M(n) = 862.6320056992192\n",
      "Generation 2168: p = 0.9584800063324658\n",
      "Generation 2168: M(n) = 862.6320056992192\n",
      "Generation 2169: p = 0.9584800063324658\n",
      "Generation 2169: M(n) = 862.6320056992192\n",
      "Generation 2170: p = 0.9584800063324658\n",
      "Generation 2170: M(n) = 862.6320056992192\n",
      "Generation 2171: p = 0.9584800063324658\n",
      "Generation 2171: M(n) = 862.6320056992192\n",
      "Generation 2172: p = 0.9584800063324658\n",
      "Generation 2172: M(n) = 862.6320056992192\n",
      "Generation 2173: p = 0.9584800063324658\n",
      "Generation 2173: M(n) = 862.6320056992192\n",
      "Generation 2174: p = 0.9584800063324658\n",
      "Generation 2174: M(n) = 862.6320056992192\n",
      "Generation 2175: p = 0.9584800063324658\n",
      "Generation 2175: M(n) = 862.6320056992192\n",
      "Generation 2176: p = 0.9584800063324658\n",
      "Generation 2176: M(n) = 862.6320056992192\n",
      "Generation 2177: p = 0.9584800063324658\n",
      "Generation 2177: M(n) = 862.6320056992192\n",
      "Generation 2178: p = 0.9584800063324658\n",
      "Generation 2178: M(n) = 862.6320056992192\n",
      "Generation 2179: p = 0.9584800063324658\n",
      "Generation 2179: M(n) = 862.6320056992192\n",
      "Generation 2180: p = 0.9584800063324658\n",
      "Generation 2180: M(n) = 862.6320056992192\n",
      "Generation 2181: p = 0.9584800063324658\n",
      "Generation 2181: M(n) = 862.6320056992192\n",
      "Generation 2182: p = 0.9584800063324658\n",
      "Generation 2182: M(n) = 862.6320056992192\n",
      "Generation 2183: p = 0.9584800063324658\n",
      "Generation 2183: M(n) = 862.6320056992192\n",
      "Generation 2184: p = 0.9584800063324658\n",
      "Generation 2184: M(n) = 862.6320056992192\n",
      "Generation 2185: p = 0.9584800063324658\n",
      "Generation 2185: M(n) = 862.6320056992192\n",
      "Generation 2186: p = 0.9584800063324658\n",
      "Generation 2186: M(n) = 862.6320056992192\n",
      "Generation 2187: p = 0.9584800063324658\n",
      "Generation 2187: M(n) = 862.6320056992192\n",
      "Generation 2188: p = 0.9584800063324658\n",
      "Generation 2188: M(n) = 862.6320056992192\n",
      "Generation 2189: p = 0.9584800063324658\n",
      "Generation 2189: M(n) = 862.6320056992192\n",
      "Generation 2190: p = 0.9584800063324658\n",
      "Generation 2190: M(n) = 862.6320056992192\n",
      "Generation 2191: p = 0.9584800063324658\n",
      "Generation 2191: M(n) = 862.6320056992192\n",
      "Generation 2192: p = 0.9584800063324658\n",
      "Generation 2192: M(n) = 862.6320056992192\n",
      "Generation 2193: p = 0.9584800063324658\n",
      "Generation 2193: M(n) = 862.6320056992192\n",
      "Generation 2194: p = 0.9584800063324658\n",
      "Generation 2194: M(n) = 862.6320056992192\n",
      "Generation 2195: p = 0.9584800063324658\n",
      "Generation 2195: M(n) = 862.6320056992192\n",
      "Generation 2196: p = 0.9584800063324658\n",
      "Generation 2196: M(n) = 862.6320056992192\n",
      "Generation 2197: p = 0.9584800063324658\n",
      "Generation 2197: M(n) = 862.6320056992192\n",
      "Generation 2198: p = 0.9584800063324658\n",
      "Generation 2198: M(n) = 862.6320056992192\n",
      "Generation 2199: p = 0.9584800063324658\n",
      "Generation 2199: M(n) = 862.6320056992192\n",
      "Generation 2200: p = 0.9584800063324658\n",
      "Generation 2200: M(n) = 862.6320056992192\n",
      "Generation 2201: p = 0.9584800063324658\n",
      "Generation 2201: M(n) = 862.6320056992192\n",
      "Generation 2202: p = 0.9584800063324658\n",
      "Generation 2202: M(n) = 862.6320056992192\n",
      "Generation 2203: p = 0.9584800063324658\n",
      "Generation 2203: M(n) = 862.6320056992192\n",
      "Generation 2204: p = 0.9584800063324658\n",
      "Generation 2204: M(n) = 862.6320056992192\n",
      "Generation 2205: p = 0.9584800063324658\n",
      "Generation 2205: M(n) = 862.6320056992192\n",
      "Generation 2206: p = 0.9584800063324658\n",
      "Generation 2206: M(n) = 862.6320056992192\n",
      "Generation 2207: p = 0.9584800063324658\n",
      "Generation 2207: M(n) = 862.6320056992192\n",
      "Generation 2208: p = 0.9584800063324658\n",
      "Generation 2208: M(n) = 862.6320056992192\n",
      "Generation 2209: p = 0.9584800063324658\n",
      "Generation 2209: M(n) = 862.6320056992192\n",
      "Generation 2210: p = 0.9584800063324658\n",
      "Generation 2210: M(n) = 862.6320056992192\n",
      "Generation 2211: p = 0.9584800063324658\n",
      "Generation 2211: M(n) = 862.6320056992192\n",
      "Generation 2212: p = 0.9584800063324658\n",
      "Generation 2212: M(n) = 862.6320056992192\n",
      "Generation 2213: p = 0.9584800063324658\n",
      "Generation 2213: M(n) = 862.6320056992192\n",
      "Generation 2214: p = 0.9584800063324658\n",
      "Generation 2214: M(n) = 862.6320056992192\n",
      "Generation 2215: p = 0.9584800063324658\n",
      "Generation 2215: M(n) = 862.6320056992192\n",
      "Generation 2216: p = 0.9584800063324658\n",
      "Generation 2216: M(n) = 862.6320056992192\n",
      "Generation 2217: p = 0.9584800063324658\n",
      "Generation 2217: M(n) = 862.6320056992192\n",
      "Generation 2218: p = 0.9584800063324658\n",
      "Generation 2218: M(n) = 862.6320056992192\n",
      "Generation 2219: p = 0.9584800063324658\n",
      "Generation 2219: M(n) = 862.6320056992192\n",
      "Generation 2220: p = 0.9584800063324658\n",
      "Generation 2220: M(n) = 862.6320056992192\n",
      "Generation 2221: p = 0.9584800063324658\n",
      "Generation 2221: M(n) = 862.6320056992192\n",
      "Generation 2222: p = 0.9584800063324658\n",
      "Generation 2222: M(n) = 862.6320056992192\n",
      "Generation 2223: p = 0.9584800063324658\n",
      "Generation 2223: M(n) = 862.6320056992192\n",
      "Generation 2224: p = 0.9584800063324658\n",
      "Generation 2224: M(n) = 862.6320056992192\n",
      "Generation 2225: p = 0.9584800063324658\n",
      "Generation 2225: M(n) = 862.6320056992192\n",
      "Generation 2226: p = 0.9584800063324658\n",
      "Generation 2226: M(n) = 862.6320056992192\n",
      "Generation 2227: p = 0.9584800063324658\n",
      "Generation 2227: M(n) = 862.6320056992192\n",
      "Generation 2228: p = 0.9584800063324658\n",
      "Generation 2228: M(n) = 862.6320056992192\n",
      "Generation 2229: p = 0.9584800063324658\n",
      "Generation 2229: M(n) = 862.6320056992192\n",
      "Generation 2230: p = 0.9584800063324658\n",
      "Generation 2230: M(n) = 862.6320056992192\n",
      "Generation 2231: p = 0.9584800063324658\n",
      "Generation 2231: M(n) = 862.6320056992192\n",
      "Generation 2232: p = 0.9584800063324658\n",
      "Generation 2232: M(n) = 862.6320056992192\n",
      "Generation 2233: p = 0.9584800063324658\n",
      "Generation 2233: M(n) = 862.6320056992192\n",
      "Generation 2234: p = 0.9584800063324658\n",
      "Generation 2234: M(n) = 862.6320056992192\n",
      "Generation 2235: p = 0.9584800063324658\n",
      "Generation 2235: M(n) = 862.6320056992192\n",
      "Generation 2236: p = 0.9584800063324658\n",
      "Generation 2236: M(n) = 862.6320056992192\n",
      "Generation 2237: p = 0.9584800063324658\n",
      "Generation 2237: M(n) = 862.6320056992192\n",
      "Generation 2238: p = 0.9584800063324658\n",
      "Generation 2238: M(n) = 862.6320056992192\n",
      "Generation 2239: p = 0.9584800063324658\n",
      "Generation 2239: M(n) = 862.6320056992192\n",
      "Generation 2240: p = 0.9584800063324658\n",
      "Generation 2240: M(n) = 862.6320056992192\n",
      "Generation 2241: p = 0.9584800063324658\n",
      "Generation 2241: M(n) = 862.6320056992192\n",
      "Generation 2242: p = 0.9584800063324658\n",
      "Generation 2242: M(n) = 862.6320056992192\n",
      "Generation 2243: p = 0.9584800063324658\n",
      "Generation 2243: M(n) = 862.6320056992192\n",
      "Generation 2244: p = 0.9584800063324658\n",
      "Generation 2244: M(n) = 862.6320056992192\n",
      "Generation 2245: p = 0.9584800063324658\n",
      "Generation 2245: M(n) = 862.6320056992192\n",
      "Generation 2246: p = 0.9584800063324658\n",
      "Generation 2246: M(n) = 862.6320056992192\n",
      "Generation 2247: p = 0.9584800063324658\n",
      "Generation 2247: M(n) = 862.6320056992192\n",
      "Generation 2248: p = 0.9584800063324658\n",
      "Generation 2248: M(n) = 862.6320056992192\n",
      "Generation 2249: p = 0.9584800063324658\n",
      "Generation 2249: M(n) = 862.6320056992192\n",
      "Generation 2250: p = 0.9584800063324658\n",
      "Generation 2250: M(n) = 862.6320056992192\n",
      "Generation 2251: p = 0.9584800063324658\n",
      "Generation 2251: M(n) = 862.6320056992192\n",
      "Generation 2252: p = 0.9584800063324658\n",
      "Generation 2252: M(n) = 862.6320056992192\n",
      "Generation 2253: p = 0.9584800063324658\n",
      "Generation 2253: M(n) = 862.6320056992192\n",
      "Generation 2254: p = 0.9584800063324658\n",
      "Generation 2254: M(n) = 862.6320056992192\n",
      "Generation 2255: p = 0.9584800063324658\n",
      "Generation 2255: M(n) = 862.6320056992192\n",
      "Generation 2256: p = 0.9584800063324658\n",
      "Generation 2256: M(n) = 862.6320056992192\n",
      "Generation 2257: p = 0.9584800063324658\n",
      "Generation 2257: M(n) = 862.6320056992192\n",
      "Generation 2258: p = 0.9584800063324658\n",
      "Generation 2258: M(n) = 862.6320056992192\n",
      "Generation 2259: p = 0.9584800063324658\n",
      "Generation 2259: M(n) = 862.6320056992192\n",
      "Generation 2260: p = 0.9584800063324658\n",
      "Generation 2260: M(n) = 862.6320056992192\n",
      "Generation 2261: p = 0.9584800063324658\n",
      "Generation 2261: M(n) = 862.6320056992192\n",
      "Generation 2262: p = 0.9584800063324658\n",
      "Generation 2262: M(n) = 862.6320056992192\n",
      "Generation 2263: p = 0.9584800063324658\n",
      "Generation 2263: M(n) = 862.6320056992192\n",
      "Generation 2264: p = 0.9584800063324658\n",
      "Generation 2264: M(n) = 862.6320056992192\n",
      "Generation 2265: p = 0.9584800063324658\n",
      "Generation 2265: M(n) = 862.6320056992192\n",
      "Generation 2266: p = 0.9584800063324658\n",
      "Generation 2266: M(n) = 862.6320056992192\n",
      "Generation 2267: p = 0.9584800063324658\n",
      "Generation 2267: M(n) = 862.6320056992192\n",
      "Generation 2268: p = 0.9584800063324658\n",
      "Generation 2268: M(n) = 862.6320056992192\n",
      "Generation 2269: p = 0.9584800063324658\n",
      "Generation 2269: M(n) = 862.6320056992192\n",
      "Generation 2270: p = 0.9584800063324658\n",
      "Generation 2270: M(n) = 862.6320056992192\n",
      "Generation 2271: p = 0.9584800063324658\n",
      "Generation 2271: M(n) = 862.6320056992192\n",
      "Generation 2272: p = 0.9584800063324658\n",
      "Generation 2272: M(n) = 862.6320056992192\n",
      "Generation 2273: p = 0.9584800063324658\n",
      "Generation 2273: M(n) = 862.6320056992192\n",
      "Generation 2274: p = 0.9584800063324658\n",
      "Generation 2274: M(n) = 862.6320056992192\n",
      "Generation 2275: p = 0.9584800063324658\n",
      "Generation 2275: M(n) = 862.6320056992192\n",
      "Generation 2276: p = 0.9584800063324658\n",
      "Generation 2276: M(n) = 862.6320056992192\n",
      "Generation 2277: p = 0.9584800063324658\n",
      "Generation 2277: M(n) = 862.6320056992192\n",
      "Generation 2278: p = 0.9584800063324658\n",
      "Generation 2278: M(n) = 862.6320056992192\n",
      "Generation 2279: p = 0.9584800063324658\n",
      "Generation 2279: M(n) = 862.6320056992192\n",
      "Generation 2280: p = 0.9584800063324658\n",
      "Generation 2280: M(n) = 862.6320056992192\n",
      "Generation 2281: p = 0.9584800063324658\n",
      "Generation 2281: M(n) = 862.6320056992192\n",
      "Generation 2282: p = 0.9584800063324658\n",
      "Generation 2282: M(n) = 862.6320056992192\n",
      "Generation 2283: p = 0.9584800063324658\n",
      "Generation 2283: M(n) = 862.6320056992192\n",
      "Generation 2284: p = 0.9584800063324658\n",
      "Generation 2284: M(n) = 862.6320056992192\n",
      "Generation 2285: p = 0.9584800063324658\n",
      "Generation 2285: M(n) = 862.6320056992192\n",
      "Generation 2286: p = 0.9584800063324658\n",
      "Generation 2286: M(n) = 862.6320056992192\n",
      "Generation 2287: p = 0.9584800063324658\n",
      "Generation 2287: M(n) = 862.6320056992192\n",
      "Generation 2288: p = 0.9584800063324658\n",
      "Generation 2288: M(n) = 862.6320056992192\n",
      "Generation 2289: p = 0.9584800063324658\n",
      "Generation 2289: M(n) = 862.6320056992192\n",
      "Generation 2290: p = 0.9584800063324658\n",
      "Generation 2290: M(n) = 862.6320056992192\n",
      "Generation 2291: p = 0.9584800063324658\n",
      "Generation 2291: M(n) = 862.6320056992192\n",
      "Generation 2292: p = 0.9584800063324658\n",
      "Generation 2292: M(n) = 862.6320056992192\n",
      "Generation 2293: p = 0.9584800063324658\n",
      "Generation 2293: M(n) = 862.6320056992192\n",
      "Generation 2294: p = 0.9584800063324658\n",
      "Generation 2294: M(n) = 862.6320056992192\n",
      "Generation 2295: p = 0.9584800063324658\n",
      "Generation 2295: M(n) = 862.6320056992192\n",
      "Generation 2296: p = 0.9584800063324658\n",
      "Generation 2296: M(n) = 862.6320056992192\n",
      "Generation 2297: p = 0.9584800063324658\n",
      "Generation 2297: M(n) = 862.6320056992192\n",
      "Generation 2298: p = 0.9584800063324658\n",
      "Generation 2298: M(n) = 862.6320056992192\n",
      "Generation 2299: p = 0.9584800063324658\n",
      "Generation 2299: M(n) = 862.6320056992192\n",
      "Generation 2300: p = 0.9584800063324658\n",
      "Generation 2300: M(n) = 862.6320056992192\n",
      "Generation 2301: p = 0.9584800063324658\n",
      "Generation 2301: M(n) = 862.6320056992192\n",
      "Generation 2302: p = 0.9584800063324658\n",
      "Generation 2302: M(n) = 862.6320056992192\n",
      "Generation 2303: p = 0.9584800063324658\n",
      "Generation 2303: M(n) = 862.6320056992192\n",
      "Generation 2304: p = 0.9584800063324658\n",
      "Generation 2304: M(n) = 862.6320056992192\n",
      "Generation 2305: p = 0.9584800063324658\n",
      "Generation 2305: M(n) = 862.6320056992192\n",
      "Generation 2306: p = 0.9584800063324658\n",
      "Generation 2306: M(n) = 862.6320056992192\n",
      "Generation 2307: p = 0.9584800063324658\n",
      "Generation 2307: M(n) = 862.6320056992192\n",
      "Generation 2308: p = 0.9584800063324658\n",
      "Generation 2308: M(n) = 862.6320056992192\n",
      "Generation 2309: p = 0.9584800063324658\n",
      "Generation 2309: M(n) = 862.6320056992192\n",
      "Generation 2310: p = 0.9584800063324658\n",
      "Generation 2310: M(n) = 862.6320056992192\n",
      "Generation 2311: p = 0.9584800063324658\n",
      "Generation 2311: M(n) = 862.6320056992192\n",
      "Generation 2312: p = 0.9584800063324658\n",
      "Generation 2312: M(n) = 862.6320056992192\n",
      "Generation 2313: p = 0.9584800063324658\n",
      "Generation 2313: M(n) = 862.6320056992192\n",
      "Generation 2314: p = 0.9584800063324658\n",
      "Generation 2314: M(n) = 862.6320056992192\n",
      "Generation 2315: p = 0.9584800063324658\n",
      "Generation 2315: M(n) = 862.6320056992192\n",
      "Generation 2316: p = 0.9584800063324658\n",
      "Generation 2316: M(n) = 862.6320056992192\n",
      "Generation 2317: p = 0.9584800063324658\n",
      "Generation 2317: M(n) = 862.6320056992192\n",
      "Generation 2318: p = 0.9584800063324658\n",
      "Generation 2318: M(n) = 862.6320056992192\n",
      "Generation 2319: p = 0.9584800063324658\n",
      "Generation 2319: M(n) = 862.6320056992192\n",
      "Generation 2320: p = 0.9584800063324658\n",
      "Generation 2320: M(n) = 862.6320056992192\n",
      "Generation 2321: p = 0.9584800063324658\n",
      "Generation 2321: M(n) = 862.6320056992192\n",
      "Generation 2322: p = 0.9584800063324658\n",
      "Generation 2322: M(n) = 862.6320056992192\n",
      "Generation 2323: p = 0.9584800063324658\n",
      "Generation 2323: M(n) = 862.6320056992192\n",
      "Generation 2324: p = 0.9584800063324658\n",
      "Generation 2324: M(n) = 862.6320056992192\n",
      "Generation 2325: p = 0.9584800063324658\n",
      "Generation 2325: M(n) = 862.6320056992192\n",
      "Generation 2326: p = 0.9584800063324658\n",
      "Generation 2326: M(n) = 862.6320056992192\n",
      "Generation 2327: p = 0.9584800063324658\n",
      "Generation 2327: M(n) = 862.6320056992192\n",
      "Generation 2328: p = 0.9584800063324658\n",
      "Generation 2328: M(n) = 862.6320056992192\n",
      "Generation 2329: p = 0.9584800063324658\n",
      "Generation 2329: M(n) = 862.6320056992192\n",
      "Generation 2330: p = 0.9584800063324658\n",
      "Generation 2330: M(n) = 862.6320056992192\n",
      "Generation 2331: p = 0.9584800063324658\n",
      "Generation 2331: M(n) = 862.6320056992192\n",
      "Generation 2332: p = 0.9584800063324658\n",
      "Generation 2332: M(n) = 862.6320056992192\n",
      "Generation 2333: p = 0.9584800063324658\n",
      "Generation 2333: M(n) = 862.6320056992192\n",
      "Generation 2334: p = 0.9584800063324658\n",
      "Generation 2334: M(n) = 862.6320056992192\n",
      "Generation 2335: p = 0.9584800063324658\n",
      "Generation 2335: M(n) = 862.6320056992192\n",
      "Generation 2336: p = 0.9584800063324658\n",
      "Generation 2336: M(n) = 862.6320056992192\n",
      "Generation 2337: p = 0.9584800063324658\n",
      "Generation 2337: M(n) = 862.6320056992192\n",
      "Generation 2338: p = 0.9584800063324658\n",
      "Generation 2338: M(n) = 862.6320056992192\n",
      "Generation 2339: p = 0.9584800063324658\n",
      "Generation 2339: M(n) = 862.6320056992192\n",
      "Generation 2340: p = 0.9584800063324658\n",
      "Generation 2340: M(n) = 862.6320056992192\n",
      "Generation 2341: p = 0.9584800063324658\n",
      "Generation 2341: M(n) = 862.6320056992192\n",
      "Generation 2342: p = 0.9584800063324658\n",
      "Generation 2342: M(n) = 862.6320056992192\n",
      "Generation 2343: p = 0.9584800063324658\n",
      "Generation 2343: M(n) = 862.6320056992192\n",
      "Generation 2344: p = 0.9584800063324658\n",
      "Generation 2344: M(n) = 862.6320056992192\n",
      "Generation 2345: p = 0.9584800063324658\n",
      "Generation 2345: M(n) = 862.6320056992192\n",
      "Generation 2346: p = 0.9584800063324658\n",
      "Generation 2346: M(n) = 862.6320056992192\n",
      "Generation 2347: p = 0.9584800063324658\n",
      "Generation 2347: M(n) = 862.6320056992192\n",
      "Generation 2348: p = 0.9584800063324658\n",
      "Generation 2348: M(n) = 862.6320056992192\n",
      "Generation 2349: p = 0.9584800063324658\n",
      "Generation 2349: M(n) = 862.6320056992192\n",
      "Generation 2350: p = 0.9584800063324658\n",
      "Generation 2350: M(n) = 862.6320056992192\n",
      "Generation 2351: p = 0.9584800063324658\n",
      "Generation 2351: M(n) = 862.6320056992192\n",
      "Generation 2352: p = 0.9584800063324658\n",
      "Generation 2352: M(n) = 862.6320056992192\n",
      "Generation 2353: p = 0.9584800063324658\n",
      "Generation 2353: M(n) = 862.6320056992192\n",
      "Generation 2354: p = 0.9584800063324658\n",
      "Generation 2354: M(n) = 862.6320056992192\n",
      "Generation 2355: p = 0.9584800063324658\n",
      "Generation 2355: M(n) = 862.6320056992192\n",
      "Generation 2356: p = 0.9584800063324658\n",
      "Generation 2356: M(n) = 862.6320056992192\n",
      "Generation 2357: p = 0.9584800063324658\n",
      "Generation 2357: M(n) = 862.6320056992192\n",
      "Generation 2358: p = 0.9584800063324658\n",
      "Generation 2358: M(n) = 862.6320056992192\n",
      "Generation 2359: p = 0.9584800063324658\n",
      "Generation 2359: M(n) = 862.6320056992192\n",
      "Generation 2360: p = 0.9584800063324658\n",
      "Generation 2360: M(n) = 862.6320056992192\n",
      "Generation 2361: p = 0.9584800063324658\n",
      "Generation 2361: M(n) = 862.6320056992192\n",
      "Generation 2362: p = 0.9584800063324658\n",
      "Generation 2362: M(n) = 862.6320056992192\n",
      "Generation 2363: p = 0.9584800063324658\n",
      "Generation 2363: M(n) = 862.6320056992192\n",
      "Generation 2364: p = 0.9584800063324658\n",
      "Generation 2364: M(n) = 862.6320056992192\n",
      "Generation 2365: p = 0.9584800063324658\n",
      "Generation 2365: M(n) = 862.6320056992192\n",
      "Generation 2366: p = 0.9584800063324658\n",
      "Generation 2366: M(n) = 862.6320056992192\n",
      "Generation 2367: p = 0.9584800063324658\n",
      "Generation 2367: M(n) = 862.6320056992192\n",
      "Generation 2368: p = 0.9584800063324658\n",
      "Generation 2368: M(n) = 862.6320056992192\n",
      "Generation 2369: p = 0.9584800063324658\n",
      "Generation 2369: M(n) = 862.6320056992192\n",
      "Generation 2370: p = 0.9584800063324658\n",
      "Generation 2370: M(n) = 862.6320056992192\n",
      "Generation 2371: p = 0.9584800063324658\n",
      "Generation 2371: M(n) = 862.6320056992192\n",
      "Generation 2372: p = 0.9584800063324658\n",
      "Generation 2372: M(n) = 862.6320056992192\n",
      "Generation 2373: p = 0.9584800063324658\n",
      "Generation 2373: M(n) = 862.6320056992192\n",
      "Generation 2374: p = 0.9584800063324658\n",
      "Generation 2374: M(n) = 862.6320056992192\n",
      "Generation 2375: p = 0.9584800063324658\n",
      "Generation 2375: M(n) = 862.6320056992192\n",
      "Generation 2376: p = 0.9584800063324658\n",
      "Generation 2376: M(n) = 862.6320056992192\n",
      "Generation 2377: p = 0.9584800063324658\n",
      "Generation 2377: M(n) = 862.6320056992192\n",
      "Generation 2378: p = 0.9584800063324658\n",
      "Generation 2378: M(n) = 862.6320056992192\n",
      "Generation 2379: p = 0.9584800063324658\n",
      "Generation 2379: M(n) = 862.6320056992192\n",
      "Generation 2380: p = 0.9584800063324658\n",
      "Generation 2380: M(n) = 862.6320056992192\n",
      "Generation 2381: p = 0.9584800063324658\n",
      "Generation 2381: M(n) = 862.6320056992192\n",
      "Generation 2382: p = 0.9584800063324658\n",
      "Generation 2382: M(n) = 862.6320056992192\n",
      "Generation 2383: p = 0.9584800063324658\n",
      "Generation 2383: M(n) = 862.6320056992192\n",
      "Generation 2384: p = 0.9584800063324658\n",
      "Generation 2384: M(n) = 862.6320056992192\n",
      "Generation 2385: p = 0.9584800063324658\n",
      "Generation 2385: M(n) = 862.6320056992192\n",
      "Generation 2386: p = 0.9584800063324658\n",
      "Generation 2386: M(n) = 862.6320056992192\n",
      "Generation 2387: p = 0.9584800063324658\n",
      "Generation 2387: M(n) = 862.6320056992192\n",
      "Generation 2388: p = 0.9584800063324658\n",
      "Generation 2388: M(n) = 862.6320056992192\n",
      "Generation 2389: p = 0.9584800063324658\n",
      "Generation 2389: M(n) = 862.6320056992192\n",
      "Generation 2390: p = 0.9584800063324658\n",
      "Generation 2390: M(n) = 862.6320056992192\n",
      "Generation 2391: p = 0.9584800063324658\n",
      "Generation 2391: M(n) = 862.6320056992192\n",
      "Generation 2392: p = 0.9584800063324658\n",
      "Generation 2392: M(n) = 862.6320056992192\n",
      "Generation 2393: p = 0.9584800063324658\n",
      "Generation 2393: M(n) = 862.6320056992192\n",
      "Generation 2394: p = 0.9584800063324658\n",
      "Generation 2394: M(n) = 862.6320056992192\n",
      "Generation 2395: p = 0.9584800063324658\n",
      "Generation 2395: M(n) = 862.6320056992192\n",
      "Generation 2396: p = 0.9584800063324658\n",
      "Generation 2396: M(n) = 862.6320056992192\n",
      "Generation 2397: p = 0.9584800063324658\n",
      "Generation 2397: M(n) = 862.6320056992192\n",
      "Generation 2398: p = 0.9584800063324658\n",
      "Generation 2398: M(n) = 862.6320056992192\n",
      "Generation 2399: p = 0.9584800063324658\n",
      "Generation 2399: M(n) = 862.6320056992192\n",
      "Generation 2400: p = 0.9584800063324658\n",
      "Generation 2400: M(n) = 862.6320056992192\n",
      "Generation 2401: p = 0.9584800063324658\n",
      "Generation 2401: M(n) = 862.6320056992192\n",
      "Generation 2402: p = 0.9584800063324658\n",
      "Generation 2402: M(n) = 862.6320056992192\n",
      "Generation 2403: p = 0.9584800063324658\n",
      "Generation 2403: M(n) = 862.6320056992192\n",
      "Generation 2404: p = 0.9584800063324658\n",
      "Generation 2404: M(n) = 862.6320056992192\n",
      "Generation 2405: p = 0.9584800063324658\n",
      "Generation 2405: M(n) = 862.6320056992192\n",
      "Generation 2406: p = 0.9584800063324658\n",
      "Generation 2406: M(n) = 862.6320056992192\n",
      "Generation 2407: p = 0.9584800063324658\n",
      "Generation 2407: M(n) = 862.6320056992192\n",
      "Generation 2408: p = 0.9584800063324658\n",
      "Generation 2408: M(n) = 862.6320056992192\n",
      "Generation 2409: p = 0.9584800063324658\n",
      "Generation 2409: M(n) = 862.6320056992192\n",
      "Generation 2410: p = 0.9584800063324658\n",
      "Generation 2410: M(n) = 862.6320056992192\n",
      "Generation 2411: p = 0.9584800063324658\n",
      "Generation 2411: M(n) = 862.6320056992192\n",
      "Generation 2412: p = 0.9584800063324658\n",
      "Generation 2412: M(n) = 862.6320056992192\n",
      "Generation 2413: p = 0.9584800063324658\n",
      "Generation 2413: M(n) = 862.6320056992192\n",
      "Generation 2414: p = 0.9584800063324658\n",
      "Generation 2414: M(n) = 862.6320056992192\n",
      "Generation 2415: p = 0.9584800063324658\n",
      "Generation 2415: M(n) = 862.6320056992192\n",
      "Generation 2416: p = 0.9584800063324658\n",
      "Generation 2416: M(n) = 862.6320056992192\n",
      "Generation 2417: p = 0.9584800063324658\n",
      "Generation 2417: M(n) = 862.6320056992192\n",
      "Generation 2418: p = 0.9584800063324658\n",
      "Generation 2418: M(n) = 862.6320056992192\n",
      "Generation 2419: p = 0.9584800063324658\n",
      "Generation 2419: M(n) = 862.6320056992192\n",
      "Generation 2420: p = 0.9584800063324658\n",
      "Generation 2420: M(n) = 862.6320056992192\n",
      "Generation 2421: p = 0.9584800063324658\n",
      "Generation 2421: M(n) = 862.6320056992192\n",
      "Generation 2422: p = 0.9584800063324658\n",
      "Generation 2422: M(n) = 862.6320056992192\n",
      "Generation 2423: p = 0.9584800063324658\n",
      "Generation 2423: M(n) = 862.6320056992192\n",
      "Generation 2424: p = 0.9584800063324658\n",
      "Generation 2424: M(n) = 862.6320056992192\n",
      "Generation 2425: p = 0.9584800063324658\n",
      "Generation 2425: M(n) = 862.6320056992192\n",
      "Generation 2426: p = 0.9584800063324658\n",
      "Generation 2426: M(n) = 862.6320056992192\n",
      "Generation 2427: p = 0.9584800063324658\n",
      "Generation 2427: M(n) = 862.6320056992192\n",
      "Generation 2428: p = 0.9584800063324658\n",
      "Generation 2428: M(n) = 862.6320056992192\n",
      "Generation 2429: p = 0.9584800063324658\n",
      "Generation 2429: M(n) = 862.6320056992192\n",
      "Generation 2430: p = 0.9584800063324658\n",
      "Generation 2430: M(n) = 862.6320056992192\n",
      "Generation 2431: p = 0.9584800063324658\n",
      "Generation 2431: M(n) = 862.6320056992192\n",
      "Generation 2432: p = 0.9584800063324658\n",
      "Generation 2432: M(n) = 862.6320056992192\n",
      "Generation 2433: p = 0.9584800063324658\n",
      "Generation 2433: M(n) = 862.6320056992192\n",
      "Generation 2434: p = 0.9584800063324658\n",
      "Generation 2434: M(n) = 862.6320056992192\n",
      "Generation 2435: p = 0.9584800063324658\n",
      "Generation 2435: M(n) = 862.6320056992192\n",
      "Generation 2436: p = 0.9584800063324658\n",
      "Generation 2436: M(n) = 862.6320056992192\n",
      "Generation 2437: p = 0.9584800063324658\n",
      "Generation 2437: M(n) = 862.6320056992192\n",
      "Generation 2438: p = 0.9584800063324658\n",
      "Generation 2438: M(n) = 862.6320056992192\n",
      "Generation 2439: p = 0.9584800063324658\n",
      "Generation 2439: M(n) = 862.6320056992192\n",
      "Generation 2440: p = 0.9584800063324658\n",
      "Generation 2440: M(n) = 862.6320056992192\n",
      "Generation 2441: p = 0.9584800063324658\n",
      "Generation 2441: M(n) = 862.6320056992192\n",
      "Generation 2442: p = 0.9584800063324658\n",
      "Generation 2442: M(n) = 862.6320056992192\n",
      "Generation 2443: p = 0.9584800063324658\n",
      "Generation 2443: M(n) = 862.6320056992192\n",
      "Generation 2444: p = 0.9584800063324658\n",
      "Generation 2444: M(n) = 862.6320056992192\n",
      "Generation 2445: p = 0.9584800063324658\n",
      "Generation 2445: M(n) = 862.6320056992192\n",
      "Generation 2446: p = 0.9584800063324658\n",
      "Generation 2446: M(n) = 862.6320056992192\n",
      "Generation 2447: p = 0.9584800063324658\n",
      "Generation 2447: M(n) = 862.6320056992192\n",
      "Generation 2448: p = 0.9584800063324658\n",
      "Generation 2448: M(n) = 862.6320056992192\n",
      "Generation 2449: p = 0.9584800063324658\n",
      "Generation 2449: M(n) = 862.6320056992192\n",
      "Generation 2450: p = 0.9584800063324658\n",
      "Generation 2450: M(n) = 862.6320056992192\n",
      "Generation 2451: p = 0.9584800063324658\n",
      "Generation 2451: M(n) = 862.6320056992192\n",
      "Generation 2452: p = 0.9584800063324658\n",
      "Generation 2452: M(n) = 862.6320056992192\n",
      "Generation 2453: p = 0.9584800063324658\n",
      "Generation 2453: M(n) = 862.6320056992192\n",
      "Generation 2454: p = 0.9584800063324658\n",
      "Generation 2454: M(n) = 862.6320056992192\n",
      "Generation 2455: p = 0.9584800063324658\n",
      "Generation 2455: M(n) = 862.6320056992192\n",
      "Generation 2456: p = 0.9584800063324658\n",
      "Generation 2456: M(n) = 862.6320056992192\n",
      "Generation 2457: p = 0.9584800063324658\n",
      "Generation 2457: M(n) = 862.6320056992192\n",
      "Generation 2458: p = 0.9584800063324658\n",
      "Generation 2458: M(n) = 862.6320056992192\n",
      "Generation 2459: p = 0.9584800063324658\n",
      "Generation 2459: M(n) = 862.6320056992192\n",
      "Generation 2460: p = 0.9584800063324658\n",
      "Generation 2460: M(n) = 862.6320056992192\n",
      "Generation 2461: p = 0.9584800063324658\n",
      "Generation 2461: M(n) = 862.6320056992192\n",
      "Generation 2462: p = 0.9584800063324658\n",
      "Generation 2462: M(n) = 862.6320056992192\n",
      "Generation 2463: p = 0.9584800063324658\n",
      "Generation 2463: M(n) = 862.6320056992192\n",
      "Generation 2464: p = 0.9584800063324658\n",
      "Generation 2464: M(n) = 862.6320056992192\n",
      "Generation 2465: p = 0.9584800063324658\n",
      "Generation 2465: M(n) = 862.6320056992192\n",
      "Generation 2466: p = 0.9584800063324658\n",
      "Generation 2466: M(n) = 862.6320056992192\n",
      "Generation 2467: p = 0.9584800063324658\n",
      "Generation 2467: M(n) = 862.6320056992192\n",
      "Generation 2468: p = 0.9584800063324658\n",
      "Generation 2468: M(n) = 862.6320056992192\n",
      "Generation 2469: p = 0.9584800063324658\n",
      "Generation 2469: M(n) = 862.6320056992192\n",
      "Generation 2470: p = 0.9584800063324658\n",
      "Generation 2470: M(n) = 862.6320056992192\n",
      "Generation 2471: p = 0.9584800063324658\n",
      "Generation 2471: M(n) = 862.6320056992192\n",
      "Generation 2472: p = 0.9584800063324658\n",
      "Generation 2472: M(n) = 862.6320056992192\n",
      "Generation 2473: p = 0.9584800063324658\n",
      "Generation 2473: M(n) = 862.6320056992192\n",
      "Generation 2474: p = 0.9584800063324658\n",
      "Generation 2474: M(n) = 862.6320056992192\n",
      "Generation 2475: p = 0.9584800063324658\n",
      "Generation 2475: M(n) = 862.6320056992192\n",
      "Generation 2476: p = 0.9584800063324658\n",
      "Generation 2476: M(n) = 862.6320056992192\n",
      "Generation 2477: p = 0.9584800063324658\n",
      "Generation 2477: M(n) = 862.6320056992192\n",
      "Generation 2478: p = 0.9584800063324658\n",
      "Generation 2478: M(n) = 862.6320056992192\n",
      "Generation 2479: p = 0.9584800063324658\n",
      "Generation 2479: M(n) = 862.6320056992192\n",
      "Generation 2480: p = 0.9584800063324658\n",
      "Generation 2480: M(n) = 862.6320056992192\n",
      "Generation 2481: p = 0.9584800063324658\n",
      "Generation 2481: M(n) = 862.6320056992192\n",
      "Generation 2482: p = 0.9584800063324658\n",
      "Generation 2482: M(n) = 862.6320056992192\n",
      "Generation 2483: p = 0.9584800063324658\n",
      "Generation 2483: M(n) = 862.6320056992192\n",
      "Generation 2484: p = 0.9584800063324658\n",
      "Generation 2484: M(n) = 862.6320056992192\n",
      "Generation 2485: p = 0.9584800063324658\n",
      "Generation 2485: M(n) = 862.6320056992192\n",
      "Generation 2486: p = 0.9584800063324658\n",
      "Generation 2486: M(n) = 862.6320056992192\n",
      "Generation 2487: p = 0.9584800063324658\n",
      "Generation 2487: M(n) = 862.6320056992192\n",
      "Generation 2488: p = 0.9584800063324658\n",
      "Generation 2488: M(n) = 862.6320056992192\n",
      "Generation 2489: p = 0.9584800063324658\n",
      "Generation 2489: M(n) = 862.6320056992192\n",
      "Generation 2490: p = 0.9584800063324658\n",
      "Generation 2490: M(n) = 862.6320056992192\n",
      "Generation 2491: p = 0.9584800063324658\n",
      "Generation 2491: M(n) = 862.6320056992192\n",
      "Generation 2492: p = 0.9584800063324658\n",
      "Generation 2492: M(n) = 862.6320056992192\n",
      "Generation 2493: p = 0.9584800063324658\n",
      "Generation 2493: M(n) = 862.6320056992192\n",
      "Generation 2494: p = 0.9584800063324658\n",
      "Generation 2494: M(n) = 862.6320056992192\n",
      "Generation 2495: p = 0.9584800063324658\n",
      "Generation 2495: M(n) = 862.6320056992192\n",
      "Generation 2496: p = 0.9584800063324658\n",
      "Generation 2496: M(n) = 862.6320056992192\n",
      "Generation 2497: p = 0.9584800063324658\n",
      "Generation 2497: M(n) = 862.6320056992192\n",
      "Generation 2498: p = 0.9584800063324658\n",
      "Generation 2498: M(n) = 862.6320056992192\n",
      "Generation 2499: p = 0.9584800063324658\n",
      "Generation 2499: M(n) = 862.6320056992192\n",
      "Generation 2500: p = 0.9584800063324658\n",
      "Generation 2500: M(n) = 862.6320056992192\n",
      "Generation 2501: p = 0.9584800063324658\n",
      "Generation 2501: M(n) = 862.6320056992192\n",
      "Generation 2502: p = 0.9584800063324658\n",
      "Generation 2502: M(n) = 862.6320056992192\n",
      "Generation 2503: p = 0.9584800063324658\n",
      "Generation 2503: M(n) = 862.6320056992192\n",
      "Generation 2504: p = 0.9584800063324658\n",
      "Generation 2504: M(n) = 862.6320056992192\n",
      "Generation 2505: p = 0.9584800063324658\n",
      "Generation 2505: M(n) = 862.6320056992192\n",
      "Generation 2506: p = 0.9584800063324658\n",
      "Generation 2506: M(n) = 862.6320056992192\n",
      "Generation 2507: p = 0.9584800063324658\n",
      "Generation 2507: M(n) = 862.6320056992192\n",
      "Generation 2508: p = 0.9584800063324658\n",
      "Generation 2508: M(n) = 862.6320056992192\n",
      "Generation 2509: p = 0.9584800063324658\n",
      "Generation 2509: M(n) = 862.6320056992192\n",
      "Generation 2510: p = 0.9584800063324658\n",
      "Generation 2510: M(n) = 862.6320056992192\n",
      "Generation 2511: p = 0.9584800063324658\n",
      "Generation 2511: M(n) = 862.6320056992192\n",
      "Generation 2512: p = 0.9584800063324658\n",
      "Generation 2512: M(n) = 862.6320056992192\n",
      "Generation 2513: p = 0.9584800063324658\n",
      "Generation 2513: M(n) = 862.6320056992192\n",
      "Generation 2514: p = 0.9584800063324658\n",
      "Generation 2514: M(n) = 862.6320056992192\n",
      "Generation 2515: p = 0.9584800063324658\n",
      "Generation 2515: M(n) = 862.6320056992192\n",
      "Generation 2516: p = 0.9584800063324658\n",
      "Generation 2516: M(n) = 862.6320056992192\n",
      "Generation 2517: p = 0.9584800063324658\n",
      "Generation 2517: M(n) = 862.6320056992192\n",
      "Generation 2518: p = 0.9584800063324658\n",
      "Generation 2518: M(n) = 862.6320056992192\n",
      "Generation 2519: p = 0.9584800063324658\n",
      "Generation 2519: M(n) = 862.6320056992192\n",
      "Generation 2520: p = 0.9584800063324658\n",
      "Generation 2520: M(n) = 862.6320056992192\n",
      "Generation 2521: p = 0.9584800063324658\n",
      "Generation 2521: M(n) = 862.6320056992192\n",
      "Generation 2522: p = 0.9584800063324658\n",
      "Generation 2522: M(n) = 862.6320056992192\n",
      "Generation 2523: p = 0.9584800063324658\n",
      "Generation 2523: M(n) = 862.6320056992192\n",
      "Generation 2524: p = 0.9584800063324658\n",
      "Generation 2524: M(n) = 862.6320056992192\n",
      "Generation 2525: p = 0.9584800063324658\n",
      "Generation 2525: M(n) = 862.6320056992192\n",
      "Generation 2526: p = 0.9584800063324658\n",
      "Generation 2526: M(n) = 862.6320056992192\n",
      "Generation 2527: p = 0.9584800063324658\n",
      "Generation 2527: M(n) = 862.6320056992192\n",
      "Generation 2528: p = 0.9584800063324658\n",
      "Generation 2528: M(n) = 862.6320056992192\n",
      "Generation 2529: p = 0.9584800063324658\n",
      "Generation 2529: M(n) = 862.6320056992192\n",
      "Generation 2530: p = 0.9584800063324658\n",
      "Generation 2530: M(n) = 862.6320056992192\n",
      "Generation 2531: p = 0.9584800063324658\n",
      "Generation 2531: M(n) = 862.6320056992192\n",
      "Generation 2532: p = 0.9584800063324658\n",
      "Generation 2532: M(n) = 862.6320056992192\n",
      "Generation 2533: p = 0.9584800063324658\n",
      "Generation 2533: M(n) = 862.6320056992192\n",
      "Generation 2534: p = 0.9584800063324658\n",
      "Generation 2534: M(n) = 862.6320056992192\n",
      "Generation 2535: p = 0.9584800063324658\n",
      "Generation 2535: M(n) = 862.6320056992192\n",
      "Generation 2536: p = 0.9584800063324658\n",
      "Generation 2536: M(n) = 862.6320056992192\n",
      "Generation 2537: p = 0.9584800063324658\n",
      "Generation 2537: M(n) = 862.6320056992192\n",
      "Generation 2538: p = 0.9584800063324658\n",
      "Generation 2538: M(n) = 862.6320056992192\n",
      "Generation 2539: p = 0.9584800063324658\n",
      "Generation 2539: M(n) = 862.6320056992192\n",
      "Generation 2540: p = 0.9584800063324658\n",
      "Generation 2540: M(n) = 862.6320056992192\n",
      "Generation 2541: p = 0.9584800063324658\n",
      "Generation 2541: M(n) = 862.6320056992192\n",
      "Generation 2542: p = 0.9584800063324658\n",
      "Generation 2542: M(n) = 862.6320056992192\n",
      "Generation 2543: p = 0.9584800063324658\n",
      "Generation 2543: M(n) = 862.6320056992192\n",
      "Generation 2544: p = 0.9584800063324658\n",
      "Generation 2544: M(n) = 862.6320056992192\n",
      "Generation 2545: p = 0.9584800063324658\n",
      "Generation 2545: M(n) = 862.6320056992192\n",
      "Generation 2546: p = 0.9584800063324658\n",
      "Generation 2546: M(n) = 862.6320056992192\n",
      "Generation 2547: p = 0.9584800063324658\n",
      "Generation 2547: M(n) = 862.6320056992192\n",
      "Generation 2548: p = 0.9584800063324658\n",
      "Generation 2548: M(n) = 862.6320056992192\n",
      "Generation 2549: p = 0.9584800063324658\n",
      "Generation 2549: M(n) = 862.6320056992192\n",
      "Generation 2550: p = 0.9584800063324658\n",
      "Generation 2550: M(n) = 862.6320056992192\n",
      "Generation 2551: p = 0.9584800063324658\n",
      "Generation 2551: M(n) = 862.6320056992192\n",
      "Generation 2552: p = 0.9584800063324658\n",
      "Generation 2552: M(n) = 862.6320056992192\n",
      "Generation 2553: p = 0.9584800063324658\n",
      "Generation 2553: M(n) = 862.6320056992192\n",
      "Generation 2554: p = 0.9584800063324658\n",
      "Generation 2554: M(n) = 862.6320056992192\n",
      "Generation 2555: p = 0.9584800063324658\n",
      "Generation 2555: M(n) = 862.6320056992192\n",
      "Generation 2556: p = 0.9584800063324658\n",
      "Generation 2556: M(n) = 862.6320056992192\n",
      "Generation 2557: p = 0.9584800063324658\n",
      "Generation 2557: M(n) = 862.6320056992192\n",
      "Generation 2558: p = 0.9584800063324658\n",
      "Generation 2558: M(n) = 862.6320056992192\n",
      "Generation 2559: p = 0.9584800063324658\n",
      "Generation 2559: M(n) = 862.6320056992192\n",
      "Generation 2560: p = 0.9584800063324658\n",
      "Generation 2560: M(n) = 862.6320056992192\n",
      "Generation 2561: p = 0.9584800063324658\n",
      "Generation 2561: M(n) = 862.6320056992192\n",
      "Generation 2562: p = 0.9584800063324658\n",
      "Generation 2562: M(n) = 862.6320056992192\n",
      "Generation 2563: p = 0.9584800063324658\n",
      "Generation 2563: M(n) = 862.6320056992192\n",
      "Generation 2564: p = 0.9584800063324658\n",
      "Generation 2564: M(n) = 862.6320056992192\n",
      "Generation 2565: p = 0.9584800063324658\n",
      "Generation 2565: M(n) = 862.6320056992192\n",
      "Generation 2566: p = 0.9584800063324658\n",
      "Generation 2566: M(n) = 862.6320056992192\n",
      "Generation 2567: p = 0.9584800063324658\n",
      "Generation 2567: M(n) = 862.6320056992192\n",
      "Generation 2568: p = 0.9584800063324658\n",
      "Generation 2568: M(n) = 862.6320056992192\n",
      "Generation 2569: p = 0.9584800063324658\n",
      "Generation 2569: M(n) = 862.6320056992192\n",
      "Generation 2570: p = 0.9584800063324658\n",
      "Generation 2570: M(n) = 862.6320056992192\n",
      "Generation 2571: p = 0.9584800063324658\n",
      "Generation 2571: M(n) = 862.6320056992192\n",
      "Generation 2572: p = 0.9584800063324658\n",
      "Generation 2572: M(n) = 862.6320056992192\n",
      "Generation 2573: p = 0.9584800063324658\n",
      "Generation 2573: M(n) = 862.6320056992192\n",
      "Generation 2574: p = 0.9584800063324658\n",
      "Generation 2574: M(n) = 862.6320056992192\n",
      "Generation 2575: p = 0.9584800063324658\n",
      "Generation 2575: M(n) = 862.6320056992192\n",
      "Generation 2576: p = 0.9584800063324658\n",
      "Generation 2576: M(n) = 862.6320056992192\n",
      "Generation 2577: p = 0.9584800063324658\n",
      "Generation 2577: M(n) = 862.6320056992192\n",
      "Generation 2578: p = 0.9584800063324658\n",
      "Generation 2578: M(n) = 862.6320056992192\n",
      "Generation 2579: p = 0.9584800063324658\n",
      "Generation 2579: M(n) = 862.6320056992192\n",
      "Generation 2580: p = 0.9584800063324658\n",
      "Generation 2580: M(n) = 862.6320056992192\n",
      "Generation 2581: p = 0.9584800063324658\n",
      "Generation 2581: M(n) = 862.6320056992192\n",
      "Generation 2582: p = 0.9584800063324658\n",
      "Generation 2582: M(n) = 862.6320056992192\n",
      "Generation 2583: p = 0.9584800063324658\n",
      "Generation 2583: M(n) = 862.6320056992192\n",
      "Generation 2584: p = 0.9584800063324658\n",
      "Generation 2584: M(n) = 862.6320056992192\n",
      "Generation 2585: p = 0.9584800063324658\n",
      "Generation 2585: M(n) = 862.6320056992192\n",
      "Generation 2586: p = 0.9584800063324658\n",
      "Generation 2586: M(n) = 862.6320056992192\n",
      "Generation 2587: p = 0.9584800063324658\n",
      "Generation 2587: M(n) = 862.6320056992192\n",
      "Generation 2588: p = 0.9584800063324658\n",
      "Generation 2588: M(n) = 862.6320056992192\n",
      "Generation 2589: p = 0.9584800063324658\n",
      "Generation 2589: M(n) = 862.6320056992192\n",
      "Generation 2590: p = 0.9584800063324658\n",
      "Generation 2590: M(n) = 862.6320056992192\n",
      "Generation 2591: p = 0.9584800063324658\n",
      "Generation 2591: M(n) = 862.6320056992192\n",
      "Generation 2592: p = 0.9584800063324658\n",
      "Generation 2592: M(n) = 862.6320056992192\n",
      "Generation 2593: p = 0.9584800063324658\n",
      "Generation 2593: M(n) = 862.6320056992192\n",
      "Generation 2594: p = 0.9584800063324658\n",
      "Generation 2594: M(n) = 862.6320056992192\n",
      "Generation 2595: p = 0.9584800063324658\n",
      "Generation 2595: M(n) = 862.6320056992192\n",
      "Generation 2596: p = 0.9584800063324658\n",
      "Generation 2596: M(n) = 862.6320056992192\n",
      "Generation 2597: p = 0.9584800063324658\n",
      "Generation 2597: M(n) = 862.6320056992192\n",
      "Generation 2598: p = 0.9584800063324658\n",
      "Generation 2598: M(n) = 862.6320056992192\n",
      "Generation 2599: p = 0.9584800063324658\n",
      "Generation 2599: M(n) = 862.6320056992192\n",
      "Generation 2600: p = 0.9584800063324658\n",
      "Generation 2600: M(n) = 862.6320056992192\n",
      "Generation 2601: p = 0.9584800063324658\n",
      "Generation 2601: M(n) = 862.6320056992192\n",
      "Generation 2602: p = 0.9584800063324658\n",
      "Generation 2602: M(n) = 862.6320056992192\n",
      "Generation 2603: p = 0.9584800063324658\n",
      "Generation 2603: M(n) = 862.6320056992192\n",
      "Generation 2604: p = 0.9584800063324658\n",
      "Generation 2604: M(n) = 862.6320056992192\n",
      "Generation 2605: p = 0.9584800063324658\n",
      "Generation 2605: M(n) = 862.6320056992192\n",
      "Generation 2606: p = 0.9584800063324658\n",
      "Generation 2606: M(n) = 862.6320056992192\n",
      "Generation 2607: p = 0.9584800063324658\n",
      "Generation 2607: M(n) = 862.6320056992192\n",
      "Generation 2608: p = 0.9584800063324658\n",
      "Generation 2608: M(n) = 862.6320056992192\n",
      "Generation 2609: p = 0.9584800063324658\n",
      "Generation 2609: M(n) = 862.6320056992192\n",
      "Generation 2610: p = 0.9584800063324658\n",
      "Generation 2610: M(n) = 862.6320056992192\n",
      "Generation 2611: p = 0.9584800063324658\n",
      "Generation 2611: M(n) = 862.6320056992192\n",
      "Generation 2612: p = 0.9584800063324658\n",
      "Generation 2612: M(n) = 862.6320056992192\n",
      "Generation 2613: p = 0.9584800063324658\n",
      "Generation 2613: M(n) = 862.6320056992192\n",
      "Generation 2614: p = 0.9584800063324658\n",
      "Generation 2614: M(n) = 862.6320056992192\n",
      "Generation 2615: p = 0.9584800063324658\n",
      "Generation 2615: M(n) = 862.6320056992192\n",
      "Generation 2616: p = 0.9584800063324658\n",
      "Generation 2616: M(n) = 862.6320056992192\n",
      "Generation 2617: p = 0.9584800063324658\n",
      "Generation 2617: M(n) = 862.6320056992192\n",
      "Generation 2618: p = 0.9584800063324658\n",
      "Generation 2618: M(n) = 862.6320056992192\n",
      "Generation 2619: p = 0.9584800063324658\n",
      "Generation 2619: M(n) = 862.6320056992192\n",
      "Generation 2620: p = 0.9584800063324658\n",
      "Generation 2620: M(n) = 862.6320056992192\n",
      "Generation 2621: p = 0.9584800063324658\n",
      "Generation 2621: M(n) = 862.6320056992192\n",
      "Generation 2622: p = 0.9584800063324658\n",
      "Generation 2622: M(n) = 862.6320056992192\n",
      "Generation 2623: p = 0.9584800063324658\n",
      "Generation 2623: M(n) = 862.6320056992192\n",
      "Generation 2624: p = 0.9584800063324658\n",
      "Generation 2624: M(n) = 862.6320056992192\n",
      "Generation 2625: p = 0.9584800063324658\n",
      "Generation 2625: M(n) = 862.6320056992192\n",
      "Generation 2626: p = 0.9584800063324658\n",
      "Generation 2626: M(n) = 862.6320056992192\n",
      "Generation 2627: p = 0.9584800063324658\n",
      "Generation 2627: M(n) = 862.6320056992192\n",
      "Generation 2628: p = 0.9584800063324658\n",
      "Generation 2628: M(n) = 862.6320056992192\n",
      "Generation 2629: p = 0.9584800063324658\n",
      "Generation 2629: M(n) = 862.6320056992192\n",
      "Generation 2630: p = 0.9584800063324658\n",
      "Generation 2630: M(n) = 862.6320056992192\n",
      "Generation 2631: p = 0.9584800063324658\n",
      "Generation 2631: M(n) = 862.6320056992192\n",
      "Generation 2632: p = 0.9584800063324658\n",
      "Generation 2632: M(n) = 862.6320056992192\n",
      "Generation 2633: p = 0.9584800063324658\n",
      "Generation 2633: M(n) = 862.6320056992192\n",
      "Generation 2634: p = 0.9584800063324658\n",
      "Generation 2634: M(n) = 862.6320056992192\n",
      "Generation 2635: p = 0.9584800063324658\n",
      "Generation 2635: M(n) = 862.6320056992192\n",
      "Generation 2636: p = 0.9584800063324658\n",
      "Generation 2636: M(n) = 862.6320056992192\n",
      "Generation 2637: p = 0.9584800063324658\n",
      "Generation 2637: M(n) = 862.6320056992192\n",
      "Generation 2638: p = 0.9584800063324658\n",
      "Generation 2638: M(n) = 862.6320056992192\n",
      "Generation 2639: p = 0.9584800063324658\n",
      "Generation 2639: M(n) = 862.6320056992192\n",
      "Generation 2640: p = 0.9584800063324658\n",
      "Generation 2640: M(n) = 862.6320056992192\n",
      "Generation 2641: p = 0.9584800063324658\n",
      "Generation 2641: M(n) = 862.6320056992192\n",
      "Generation 2642: p = 0.9584800063324658\n",
      "Generation 2642: M(n) = 862.6320056992192\n",
      "Generation 2643: p = 0.9584800063324658\n",
      "Generation 2643: M(n) = 862.6320056992192\n",
      "Generation 2644: p = 0.9584800063324658\n",
      "Generation 2644: M(n) = 862.6320056992192\n",
      "Generation 2645: p = 0.9584800063324658\n",
      "Generation 2645: M(n) = 862.6320056992192\n",
      "Generation 2646: p = 0.9584800063324658\n",
      "Generation 2646: M(n) = 862.6320056992192\n",
      "Generation 2647: p = 0.9584800063324658\n",
      "Generation 2647: M(n) = 862.6320056992192\n",
      "Generation 2648: p = 0.9584800063324658\n",
      "Generation 2648: M(n) = 862.6320056992192\n",
      "Generation 2649: p = 0.9584800063324658\n",
      "Generation 2649: M(n) = 862.6320056992192\n",
      "Generation 2650: p = 0.9584800063324658\n",
      "Generation 2650: M(n) = 862.6320056992192\n",
      "Generation 2651: p = 0.9584800063324658\n",
      "Generation 2651: M(n) = 862.6320056992192\n",
      "Generation 2652: p = 0.9584800063324658\n",
      "Generation 2652: M(n) = 862.6320056992192\n",
      "Generation 2653: p = 0.9584800063324658\n",
      "Generation 2653: M(n) = 862.6320056992192\n",
      "Generation 2654: p = 0.9584800063324658\n",
      "Generation 2654: M(n) = 862.6320056992192\n",
      "Generation 2655: p = 0.9584800063324658\n",
      "Generation 2655: M(n) = 862.6320056992192\n",
      "Generation 2656: p = 0.9584800063324658\n",
      "Generation 2656: M(n) = 862.6320056992192\n",
      "Generation 2657: p = 0.9584800063324658\n",
      "Generation 2657: M(n) = 862.6320056992192\n",
      "Generation 2658: p = 0.9584800063324658\n",
      "Generation 2658: M(n) = 862.6320056992192\n",
      "Generation 2659: p = 0.9584800063324658\n",
      "Generation 2659: M(n) = 862.6320056992192\n",
      "Generation 2660: p = 0.9584800063324658\n",
      "Generation 2660: M(n) = 862.6320056992192\n",
      "Generation 2661: p = 0.9584800063324658\n",
      "Generation 2661: M(n) = 862.6320056992192\n",
      "Generation 2662: p = 0.9584800063324658\n",
      "Generation 2662: M(n) = 862.6320056992192\n",
      "Generation 2663: p = 0.9584800063324658\n",
      "Generation 2663: M(n) = 862.6320056992192\n",
      "Generation 2664: p = 0.9584800063324658\n",
      "Generation 2664: M(n) = 862.6320056992192\n",
      "Generation 2665: p = 0.9584800063324658\n",
      "Generation 2665: M(n) = 862.6320056992192\n",
      "Generation 2666: p = 0.9584800063324658\n",
      "Generation 2666: M(n) = 862.6320056992192\n",
      "Generation 2667: p = 0.9584800063324658\n",
      "Generation 2667: M(n) = 862.6320056992192\n",
      "Generation 2668: p = 0.9584800063324658\n",
      "Generation 2668: M(n) = 862.6320056992192\n",
      "Generation 2669: p = 0.9584800063324658\n",
      "Generation 2669: M(n) = 862.6320056992192\n",
      "Generation 2670: p = 0.9584800063324658\n",
      "Generation 2670: M(n) = 862.6320056992192\n",
      "Generation 2671: p = 0.9584800063324658\n",
      "Generation 2671: M(n) = 862.6320056992192\n",
      "Generation 2672: p = 0.9584800063324658\n",
      "Generation 2672: M(n) = 862.6320056992192\n",
      "Generation 2673: p = 0.9584800063324658\n",
      "Generation 2673: M(n) = 862.6320056992192\n",
      "Generation 2674: p = 0.9584800063324658\n",
      "Generation 2674: M(n) = 862.6320056992192\n",
      "Generation 2675: p = 0.9584800063324658\n",
      "Generation 2675: M(n) = 862.6320056992192\n",
      "Generation 2676: p = 0.9584800063324658\n",
      "Generation 2676: M(n) = 862.6320056992192\n",
      "Generation 2677: p = 0.9584800063324658\n",
      "Generation 2677: M(n) = 862.6320056992192\n",
      "Generation 2678: p = 0.9584800063324658\n",
      "Generation 2678: M(n) = 862.6320056992192\n",
      "Generation 2679: p = 0.9584800063324658\n",
      "Generation 2679: M(n) = 862.6320056992192\n",
      "Generation 2680: p = 0.9584800063324658\n",
      "Generation 2680: M(n) = 862.6320056992192\n",
      "Generation 2681: p = 0.9584800063324658\n",
      "Generation 2681: M(n) = 862.6320056992192\n",
      "Generation 2682: p = 0.9584800063324658\n",
      "Generation 2682: M(n) = 862.6320056992192\n",
      "Generation 2683: p = 0.9584800063324658\n",
      "Generation 2683: M(n) = 862.6320056992192\n",
      "Generation 2684: p = 0.9584800063324658\n",
      "Generation 2684: M(n) = 862.6320056992192\n",
      "Generation 2685: p = 0.9584800063324658\n",
      "Generation 2685: M(n) = 862.6320056992192\n",
      "Generation 2686: p = 0.9584800063324658\n",
      "Generation 2686: M(n) = 862.6320056992192\n",
      "Generation 2687: p = 0.9584800063324658\n",
      "Generation 2687: M(n) = 862.6320056992192\n",
      "Generation 2688: p = 0.9584800063324658\n",
      "Generation 2688: M(n) = 862.6320056992192\n",
      "Generation 2689: p = 0.9584800063324658\n",
      "Generation 2689: M(n) = 862.6320056992192\n",
      "Generation 2690: p = 0.9584800063324658\n",
      "Generation 2690: M(n) = 862.6320056992192\n",
      "Generation 2691: p = 0.9584800063324658\n",
      "Generation 2691: M(n) = 862.6320056992192\n",
      "Generation 2692: p = 0.9584800063324658\n",
      "Generation 2692: M(n) = 862.6320056992192\n",
      "Generation 2693: p = 0.9584800063324658\n",
      "Generation 2693: M(n) = 862.6320056992192\n",
      "Generation 2694: p = 0.9584800063324658\n",
      "Generation 2694: M(n) = 862.6320056992192\n",
      "Generation 2695: p = 0.9584800063324658\n",
      "Generation 2695: M(n) = 862.6320056992192\n",
      "Generation 2696: p = 0.9584800063324658\n",
      "Generation 2696: M(n) = 862.6320056992192\n",
      "Generation 2697: p = 0.9584800063324658\n",
      "Generation 2697: M(n) = 862.6320056992192\n",
      "Generation 2698: p = 0.9584800063324658\n",
      "Generation 2698: M(n) = 862.6320056992192\n",
      "Generation 2699: p = 0.9584800063324658\n",
      "Generation 2699: M(n) = 862.6320056992192\n",
      "Generation 2700: p = 0.9584800063324658\n",
      "Generation 2700: M(n) = 862.6320056992192\n",
      "Generation 2701: p = 0.9584800063324658\n",
      "Generation 2701: M(n) = 862.6320056992192\n",
      "Generation 2702: p = 0.9584800063324658\n",
      "Generation 2702: M(n) = 862.6320056992192\n",
      "Generation 2703: p = 0.9584800063324658\n",
      "Generation 2703: M(n) = 862.6320056992192\n",
      "Generation 2704: p = 0.9584800063324658\n",
      "Generation 2704: M(n) = 862.6320056992192\n",
      "Generation 2705: p = 0.9584800063324658\n",
      "Generation 2705: M(n) = 862.6320056992192\n",
      "Generation 2706: p = 0.9584800063324658\n",
      "Generation 2706: M(n) = 862.6320056992192\n",
      "Generation 2707: p = 0.9584800063324658\n",
      "Generation 2707: M(n) = 862.6320056992192\n",
      "Generation 2708: p = 0.9584800063324658\n",
      "Generation 2708: M(n) = 862.6320056992192\n",
      "Generation 2709: p = 0.9584800063324658\n",
      "Generation 2709: M(n) = 862.6320056992192\n",
      "Generation 2710: p = 0.9584800063324658\n",
      "Generation 2710: M(n) = 862.6320056992192\n",
      "Generation 2711: p = 0.9584800063324658\n",
      "Generation 2711: M(n) = 862.6320056992192\n",
      "Generation 2712: p = 0.9584800063324658\n",
      "Generation 2712: M(n) = 862.6320056992192\n",
      "Generation 2713: p = 0.9584800063324658\n",
      "Generation 2713: M(n) = 862.6320056992192\n",
      "Generation 2714: p = 0.9584800063324658\n",
      "Generation 2714: M(n) = 862.6320056992192\n",
      "Generation 2715: p = 0.9584800063324658\n",
      "Generation 2715: M(n) = 862.6320056992192\n",
      "Generation 2716: p = 0.9584800063324658\n",
      "Generation 2716: M(n) = 862.6320056992192\n",
      "Generation 2717: p = 0.9584800063324658\n",
      "Generation 2717: M(n) = 862.6320056992192\n",
      "Generation 2718: p = 0.9584800063324658\n",
      "Generation 2718: M(n) = 862.6320056992192\n",
      "Generation 2719: p = 0.9584800063324658\n",
      "Generation 2719: M(n) = 862.6320056992192\n",
      "Generation 2720: p = 0.9584800063324658\n",
      "Generation 2720: M(n) = 862.6320056992192\n",
      "Generation 2721: p = 0.9584800063324658\n",
      "Generation 2721: M(n) = 862.6320056992192\n",
      "Generation 2722: p = 0.9584800063324658\n",
      "Generation 2722: M(n) = 862.6320056992192\n",
      "Generation 2723: p = 0.9584800063324658\n",
      "Generation 2723: M(n) = 862.6320056992192\n",
      "Generation 2724: p = 0.9584800063324658\n",
      "Generation 2724: M(n) = 862.6320056992192\n",
      "Generation 2725: p = 0.9584800063324658\n",
      "Generation 2725: M(n) = 862.6320056992192\n",
      "Generation 2726: p = 0.9584800063324658\n",
      "Generation 2726: M(n) = 862.6320056992192\n",
      "Generation 2727: p = 0.9584800063324658\n",
      "Generation 2727: M(n) = 862.6320056992192\n",
      "Generation 2728: p = 0.9584800063324658\n",
      "Generation 2728: M(n) = 862.6320056992192\n",
      "Generation 2729: p = 0.9584800063324658\n",
      "Generation 2729: M(n) = 862.6320056992192\n",
      "Generation 2730: p = 0.9584800063324658\n",
      "Generation 2730: M(n) = 862.6320056992192\n",
      "Generation 2731: p = 0.9584800063324658\n",
      "Generation 2731: M(n) = 862.6320056992192\n",
      "Generation 2732: p = 0.9584800063324658\n",
      "Generation 2732: M(n) = 862.6320056992192\n",
      "Generation 2733: p = 0.9584800063324658\n",
      "Generation 2733: M(n) = 862.6320056992192\n",
      "Generation 2734: p = 0.9584800063324658\n",
      "Generation 2734: M(n) = 862.6320056992192\n",
      "Generation 2735: p = 0.9584800063324658\n",
      "Generation 2735: M(n) = 862.6320056992192\n",
      "Generation 2736: p = 0.9584800063324658\n",
      "Generation 2736: M(n) = 862.6320056992192\n",
      "Generation 2737: p = 0.9584800063324658\n",
      "Generation 2737: M(n) = 862.6320056992192\n",
      "Generation 2738: p = 0.9584800063324658\n",
      "Generation 2738: M(n) = 862.6320056992192\n",
      "Generation 2739: p = 0.9584800063324658\n",
      "Generation 2739: M(n) = 862.6320056992192\n",
      "Generation 2740: p = 0.9584800063324658\n",
      "Generation 2740: M(n) = 862.6320056992192\n",
      "Generation 2741: p = 0.9584800063324658\n",
      "Generation 2741: M(n) = 862.6320056992192\n",
      "Generation 2742: p = 0.9584800063324658\n",
      "Generation 2742: M(n) = 862.6320056992192\n",
      "Generation 2743: p = 0.9584800063324658\n",
      "Generation 2743: M(n) = 862.6320056992192\n",
      "Generation 2744: p = 0.9584800063324658\n",
      "Generation 2744: M(n) = 862.6320056992192\n",
      "Generation 2745: p = 0.9584800063324658\n",
      "Generation 2745: M(n) = 862.6320056992192\n",
      "Generation 2746: p = 0.9584800063324658\n",
      "Generation 2746: M(n) = 862.6320056992192\n",
      "Generation 2747: p = 0.9584800063324658\n",
      "Generation 2747: M(n) = 862.6320056992192\n",
      "Generation 2748: p = 0.9584800063324658\n",
      "Generation 2748: M(n) = 862.6320056992192\n",
      "Generation 2749: p = 0.9584800063324658\n",
      "Generation 2749: M(n) = 862.6320056992192\n",
      "Generation 2750: p = 0.9584800063324658\n",
      "Generation 2750: M(n) = 862.6320056992192\n",
      "Generation 2751: p = 0.9584800063324658\n",
      "Generation 2751: M(n) = 862.6320056992192\n",
      "Generation 2752: p = 0.9584800063324658\n",
      "Generation 2752: M(n) = 862.6320056992192\n",
      "Generation 2753: p = 0.9584800063324658\n",
      "Generation 2753: M(n) = 862.6320056992192\n",
      "Generation 2754: p = 0.9584800063324658\n",
      "Generation 2754: M(n) = 862.6320056992192\n",
      "Generation 2755: p = 0.9584800063324658\n",
      "Generation 2755: M(n) = 862.6320056992192\n",
      "Generation 2756: p = 0.9584800063324658\n",
      "Generation 2756: M(n) = 862.6320056992192\n",
      "Generation 2757: p = 0.9584800063324658\n",
      "Generation 2757: M(n) = 862.6320056992192\n",
      "Generation 2758: p = 0.9584800063324658\n",
      "Generation 2758: M(n) = 862.6320056992192\n",
      "Generation 2759: p = 0.9584800063324658\n",
      "Generation 2759: M(n) = 862.6320056992192\n",
      "Generation 2760: p = 0.9584800063324658\n",
      "Generation 2760: M(n) = 862.6320056992192\n",
      "Generation 2761: p = 0.9584800063324658\n",
      "Generation 2761: M(n) = 862.6320056992192\n",
      "Generation 2762: p = 0.9584800063324658\n",
      "Generation 2762: M(n) = 862.6320056992192\n",
      "Generation 2763: p = 0.9584800063324658\n",
      "Generation 2763: M(n) = 862.6320056992192\n",
      "Generation 2764: p = 0.9584800063324658\n",
      "Generation 2764: M(n) = 862.6320056992192\n",
      "Generation 2765: p = 0.9584800063324658\n",
      "Generation 2765: M(n) = 862.6320056992192\n",
      "Generation 2766: p = 0.9584800063324658\n",
      "Generation 2766: M(n) = 862.6320056992192\n",
      "Generation 2767: p = 0.9584800063324658\n",
      "Generation 2767: M(n) = 862.6320056992192\n",
      "Generation 2768: p = 0.9584800063324658\n",
      "Generation 2768: M(n) = 862.6320056992192\n",
      "Generation 2769: p = 0.9584800063324658\n",
      "Generation 2769: M(n) = 862.6320056992192\n",
      "Generation 2770: p = 0.9584800063324658\n",
      "Generation 2770: M(n) = 862.6320056992192\n",
      "Generation 2771: p = 0.9584800063324658\n",
      "Generation 2771: M(n) = 862.6320056992192\n",
      "Generation 2772: p = 0.9584800063324658\n",
      "Generation 2772: M(n) = 862.6320056992192\n",
      "Generation 2773: p = 0.9584800063324658\n",
      "Generation 2773: M(n) = 862.6320056992192\n",
      "Generation 2774: p = 0.9584800063324658\n",
      "Generation 2774: M(n) = 862.6320056992192\n",
      "Generation 2775: p = 0.9584800063324658\n",
      "Generation 2775: M(n) = 862.6320056992192\n",
      "Generation 2776: p = 0.9584800063324658\n",
      "Generation 2776: M(n) = 862.6320056992192\n",
      "Generation 2777: p = 0.9584800063324658\n",
      "Generation 2777: M(n) = 862.6320056992192\n",
      "Generation 2778: p = 0.9584800063324658\n",
      "Generation 2778: M(n) = 862.6320056992192\n",
      "Generation 2779: p = 0.9584800063324658\n",
      "Generation 2779: M(n) = 862.6320056992192\n",
      "Generation 2780: p = 0.9584800063324658\n",
      "Generation 2780: M(n) = 862.6320056992192\n",
      "Generation 2781: p = 0.9584800063324658\n",
      "Generation 2781: M(n) = 862.6320056992192\n",
      "Generation 2782: p = 0.9584800063324658\n",
      "Generation 2782: M(n) = 862.6320056992192\n",
      "Generation 2783: p = 0.9584800063324658\n",
      "Generation 2783: M(n) = 862.6320056992192\n",
      "Generation 2784: p = 0.9584800063324658\n",
      "Generation 2784: M(n) = 862.6320056992192\n",
      "Generation 2785: p = 0.9584800063324658\n",
      "Generation 2785: M(n) = 862.6320056992192\n",
      "Generation 2786: p = 0.9584800063324658\n",
      "Generation 2786: M(n) = 862.6320056992192\n",
      "Generation 2787: p = 0.9584800063324658\n",
      "Generation 2787: M(n) = 862.6320056992192\n",
      "Generation 2788: p = 0.9584800063324658\n",
      "Generation 2788: M(n) = 862.6320056992192\n",
      "Generation 2789: p = 0.9584800063324658\n",
      "Generation 2789: M(n) = 862.6320056992192\n",
      "Generation 2790: p = 0.9584800063324658\n",
      "Generation 2790: M(n) = 862.6320056992192\n",
      "Generation 2791: p = 0.9584800063324658\n",
      "Generation 2791: M(n) = 862.6320056992192\n",
      "Generation 2792: p = 0.9584800063324658\n",
      "Generation 2792: M(n) = 862.6320056992192\n",
      "Generation 2793: p = 0.9584800063324658\n",
      "Generation 2793: M(n) = 862.6320056992192\n",
      "Generation 2794: p = 0.9584800063324658\n",
      "Generation 2794: M(n) = 862.6320056992192\n",
      "Generation 2795: p = 0.9584800063324658\n",
      "Generation 2795: M(n) = 862.6320056992192\n",
      "Generation 2796: p = 0.9584800063324658\n",
      "Generation 2796: M(n) = 862.6320056992192\n",
      "Generation 2797: p = 0.9584800063324658\n",
      "Generation 2797: M(n) = 862.6320056992192\n",
      "Generation 2798: p = 0.9584800063324658\n",
      "Generation 2798: M(n) = 862.6320056992192\n",
      "Generation 2799: p = 0.9584800063324658\n",
      "Generation 2799: M(n) = 862.6320056992192\n",
      "Generation 2800: p = 0.9584800063324658\n",
      "Generation 2800: M(n) = 862.6320056992192\n",
      "Generation 2801: p = 0.9584800063324658\n",
      "Generation 2801: M(n) = 862.6320056992192\n",
      "Generation 2802: p = 0.9584800063324658\n",
      "Generation 2802: M(n) = 862.6320056992192\n",
      "Generation 2803: p = 0.9584800063324658\n",
      "Generation 2803: M(n) = 862.6320056992192\n",
      "Generation 2804: p = 0.9584800063324658\n",
      "Generation 2804: M(n) = 862.6320056992192\n",
      "Generation 2805: p = 0.9584800063324658\n",
      "Generation 2805: M(n) = 862.6320056992192\n",
      "Generation 2806: p = 0.9584800063324658\n",
      "Generation 2806: M(n) = 862.6320056992192\n",
      "Generation 2807: p = 0.9584800063324658\n",
      "Generation 2807: M(n) = 862.6320056992192\n",
      "Generation 2808: p = 0.9584800063324658\n",
      "Generation 2808: M(n) = 862.6320056992192\n",
      "Generation 2809: p = 0.9584800063324658\n",
      "Generation 2809: M(n) = 862.6320056992192\n",
      "Generation 2810: p = 0.9584800063324658\n",
      "Generation 2810: M(n) = 862.6320056992192\n",
      "Generation 2811: p = 0.9584800063324658\n",
      "Generation 2811: M(n) = 862.6320056992192\n",
      "Generation 2812: p = 0.9584800063324658\n",
      "Generation 2812: M(n) = 862.6320056992192\n",
      "Generation 2813: p = 0.9584800063324658\n",
      "Generation 2813: M(n) = 862.6320056992192\n",
      "Generation 2814: p = 0.9584800063324658\n",
      "Generation 2814: M(n) = 862.6320056992192\n",
      "Generation 2815: p = 0.9584800063324658\n",
      "Generation 2815: M(n) = 862.6320056992192\n",
      "Generation 2816: p = 0.9584800063324658\n",
      "Generation 2816: M(n) = 862.6320056992192\n",
      "Generation 2817: p = 0.9584800063324658\n",
      "Generation 2817: M(n) = 862.6320056992192\n",
      "Generation 2818: p = 0.9584800063324658\n",
      "Generation 2818: M(n) = 862.6320056992192\n",
      "Generation 2819: p = 0.9584800063324658\n",
      "Generation 2819: M(n) = 862.6320056992192\n",
      "Generation 2820: p = 0.9584800063324658\n",
      "Generation 2820: M(n) = 862.6320056992192\n",
      "Generation 2821: p = 0.9584800063324658\n",
      "Generation 2821: M(n) = 862.6320056992192\n",
      "Generation 2822: p = 0.9584800063324658\n",
      "Generation 2822: M(n) = 862.6320056992192\n",
      "Generation 2823: p = 0.9584800063324658\n",
      "Generation 2823: M(n) = 862.6320056992192\n",
      "Generation 2824: p = 0.9584800063324658\n",
      "Generation 2824: M(n) = 862.6320056992192\n",
      "Generation 2825: p = 0.9584800063324658\n",
      "Generation 2825: M(n) = 862.6320056992192\n",
      "Generation 2826: p = 0.9584800063324658\n",
      "Generation 2826: M(n) = 862.6320056992192\n",
      "Generation 2827: p = 0.9584800063324658\n",
      "Generation 2827: M(n) = 862.6320056992192\n",
      "Generation 2828: p = 0.9584800063324658\n",
      "Generation 2828: M(n) = 862.6320056992192\n",
      "Generation 2829: p = 0.9584800063324658\n",
      "Generation 2829: M(n) = 862.6320056992192\n",
      "Generation 2830: p = 0.9584800063324658\n",
      "Generation 2830: M(n) = 862.6320056992192\n",
      "Generation 2831: p = 0.9584800063324658\n",
      "Generation 2831: M(n) = 862.6320056992192\n",
      "Generation 2832: p = 0.9584800063324658\n",
      "Generation 2832: M(n) = 862.6320056992192\n",
      "Generation 2833: p = 0.9584800063324658\n",
      "Generation 2833: M(n) = 862.6320056992192\n",
      "Generation 2834: p = 0.9584800063324658\n",
      "Generation 2834: M(n) = 862.6320056992192\n",
      "Generation 2835: p = 0.9584800063324658\n",
      "Generation 2835: M(n) = 862.6320056992192\n",
      "Generation 2836: p = 0.9584800063324658\n",
      "Generation 2836: M(n) = 862.6320056992192\n",
      "Generation 2837: p = 0.9584800063324658\n",
      "Generation 2837: M(n) = 862.6320056992192\n",
      "Generation 2838: p = 0.9584800063324658\n",
      "Generation 2838: M(n) = 862.6320056992192\n",
      "Generation 2839: p = 0.9584800063324658\n",
      "Generation 2839: M(n) = 862.6320056992192\n",
      "Generation 2840: p = 0.9584800063324658\n",
      "Generation 2840: M(n) = 862.6320056992192\n",
      "Generation 2841: p = 0.9584800063324658\n",
      "Generation 2841: M(n) = 862.6320056992192\n",
      "Generation 2842: p = 0.9584800063324658\n",
      "Generation 2842: M(n) = 862.6320056992192\n",
      "Generation 2843: p = 0.9584800063324658\n",
      "Generation 2843: M(n) = 862.6320056992192\n",
      "Generation 2844: p = 0.9584800063324658\n",
      "Generation 2844: M(n) = 862.6320056992192\n",
      "Generation 2845: p = 0.9584800063324658\n",
      "Generation 2845: M(n) = 862.6320056992192\n",
      "Generation 2846: p = 0.9584800063324658\n",
      "Generation 2846: M(n) = 862.6320056992192\n",
      "Generation 2847: p = 0.9584800063324658\n",
      "Generation 2847: M(n) = 862.6320056992192\n",
      "Generation 2848: p = 0.9584800063324658\n",
      "Generation 2848: M(n) = 862.6320056992192\n",
      "Generation 2849: p = 0.9584800063324658\n",
      "Generation 2849: M(n) = 862.6320056992192\n",
      "Generation 2850: p = 0.9584800063324658\n",
      "Generation 2850: M(n) = 862.6320056992192\n",
      "Generation 2851: p = 0.9584800063324658\n",
      "Generation 2851: M(n) = 862.6320056992192\n",
      "Generation 2852: p = 0.9584800063324658\n",
      "Generation 2852: M(n) = 862.6320056992192\n",
      "Generation 2853: p = 0.9584800063324658\n",
      "Generation 2853: M(n) = 862.6320056992192\n",
      "Generation 2854: p = 0.9584800063324658\n",
      "Generation 2854: M(n) = 862.6320056992192\n",
      "Generation 2855: p = 0.9584800063324658\n",
      "Generation 2855: M(n) = 862.6320056992192\n",
      "Generation 2856: p = 0.9584800063324658\n",
      "Generation 2856: M(n) = 862.6320056992192\n",
      "Generation 2857: p = 0.9584800063324658\n",
      "Generation 2857: M(n) = 862.6320056992192\n",
      "Generation 2858: p = 0.9584800063324658\n",
      "Generation 2858: M(n) = 862.6320056992192\n",
      "Generation 2859: p = 0.9584800063324658\n",
      "Generation 2859: M(n) = 862.6320056992192\n",
      "Generation 2860: p = 0.9584800063324658\n",
      "Generation 2860: M(n) = 862.6320056992192\n",
      "Generation 2861: p = 0.9584800063324658\n",
      "Generation 2861: M(n) = 862.6320056992192\n",
      "Generation 2862: p = 0.9584800063324658\n",
      "Generation 2862: M(n) = 862.6320056992192\n",
      "Generation 2863: p = 0.9584800063324658\n",
      "Generation 2863: M(n) = 862.6320056992192\n",
      "Generation 2864: p = 0.9584800063324658\n",
      "Generation 2864: M(n) = 862.6320056992192\n",
      "Generation 2865: p = 0.9584800063324658\n",
      "Generation 2865: M(n) = 862.6320056992192\n",
      "Generation 2866: p = 0.9584800063324658\n",
      "Generation 2866: M(n) = 862.6320056992192\n",
      "Generation 2867: p = 0.9584800063324658\n",
      "Generation 2867: M(n) = 862.6320056992192\n",
      "Generation 2868: p = 0.9584800063324658\n",
      "Generation 2868: M(n) = 862.6320056992192\n",
      "Generation 2869: p = 0.9584800063324658\n",
      "Generation 2869: M(n) = 862.6320056992192\n",
      "Generation 2870: p = 0.9584800063324658\n",
      "Generation 2870: M(n) = 862.6320056992192\n",
      "Generation 2871: p = 0.9584800063324658\n",
      "Generation 2871: M(n) = 862.6320056992192\n",
      "Generation 2872: p = 0.9584800063324658\n",
      "Generation 2872: M(n) = 862.6320056992192\n",
      "Generation 2873: p = 0.9584800063324658\n",
      "Generation 2873: M(n) = 862.6320056992192\n",
      "Generation 2874: p = 0.9584800063324658\n",
      "Generation 2874: M(n) = 862.6320056992192\n",
      "Generation 2875: p = 0.9584800063324658\n",
      "Generation 2875: M(n) = 862.6320056992192\n",
      "Generation 2876: p = 0.9584800063324658\n",
      "Generation 2876: M(n) = 862.6320056992192\n",
      "Generation 2877: p = 0.9584800063324658\n",
      "Generation 2877: M(n) = 862.6320056992192\n",
      "Generation 2878: p = 0.9584800063324658\n",
      "Generation 2878: M(n) = 862.6320056992192\n",
      "Generation 2879: p = 0.9584800063324658\n",
      "Generation 2879: M(n) = 862.6320056992192\n",
      "Generation 2880: p = 0.9584800063324658\n",
      "Generation 2880: M(n) = 862.6320056992192\n",
      "Generation 2881: p = 0.9584800063324658\n",
      "Generation 2881: M(n) = 862.6320056992192\n",
      "Generation 2882: p = 0.9584800063324658\n",
      "Generation 2882: M(n) = 862.6320056992192\n",
      "Generation 2883: p = 0.9584800063324658\n",
      "Generation 2883: M(n) = 862.6320056992192\n",
      "Generation 2884: p = 0.9584800063324658\n",
      "Generation 2884: M(n) = 862.6320056992192\n",
      "Generation 2885: p = 0.9584800063324658\n",
      "Generation 2885: M(n) = 862.6320056992192\n",
      "Generation 2886: p = 0.9584800063324658\n",
      "Generation 2886: M(n) = 862.6320056992192\n",
      "Generation 2887: p = 0.9584800063324658\n",
      "Generation 2887: M(n) = 862.6320056992192\n",
      "Generation 2888: p = 0.9584800063324658\n",
      "Generation 2888: M(n) = 862.6320056992192\n",
      "Generation 2889: p = 0.9584800063324658\n",
      "Generation 2889: M(n) = 862.6320056992192\n",
      "Generation 2890: p = 0.9584800063324658\n",
      "Generation 2890: M(n) = 862.6320056992192\n",
      "Generation 2891: p = 0.9584800063324658\n",
      "Generation 2891: M(n) = 862.6320056992192\n",
      "Generation 2892: p = 0.9584800063324658\n",
      "Generation 2892: M(n) = 862.6320056992192\n",
      "Generation 2893: p = 0.9584800063324658\n",
      "Generation 2893: M(n) = 862.6320056992192\n",
      "Generation 2894: p = 0.9584800063324658\n",
      "Generation 2894: M(n) = 862.6320056992192\n",
      "Generation 2895: p = 0.9584800063324658\n",
      "Generation 2895: M(n) = 862.6320056992192\n",
      "Generation 2896: p = 0.9584800063324658\n",
      "Generation 2896: M(n) = 862.6320056992192\n",
      "Generation 2897: p = 0.9584800063324658\n",
      "Generation 2897: M(n) = 862.6320056992192\n",
      "Generation 2898: p = 0.9584800063324658\n",
      "Generation 2898: M(n) = 862.6320056992192\n",
      "Generation 2899: p = 0.9584800063324658\n",
      "Generation 2899: M(n) = 862.6320056992192\n",
      "Generation 2900: p = 0.9584800063324658\n",
      "Generation 2900: M(n) = 862.6320056992192\n",
      "Generation 2901: p = 0.9584800063324658\n",
      "Generation 2901: M(n) = 862.6320056992192\n",
      "Generation 2902: p = 0.9584800063324658\n",
      "Generation 2902: M(n) = 862.6320056992192\n",
      "Generation 2903: p = 0.9584800063324658\n",
      "Generation 2903: M(n) = 862.6320056992192\n",
      "Generation 2904: p = 0.9584800063324658\n",
      "Generation 2904: M(n) = 862.6320056992192\n",
      "Generation 2905: p = 0.9584800063324658\n",
      "Generation 2905: M(n) = 862.6320056992192\n",
      "Generation 2906: p = 0.9584800063324658\n",
      "Generation 2906: M(n) = 862.6320056992192\n",
      "Generation 2907: p = 0.9584800063324658\n",
      "Generation 2907: M(n) = 862.6320056992192\n",
      "Generation 2908: p = 0.9584800063324658\n",
      "Generation 2908: M(n) = 862.6320056992192\n",
      "Generation 2909: p = 0.9584800063324658\n",
      "Generation 2909: M(n) = 862.6320056992192\n",
      "Generation 2910: p = 0.9584800063324658\n",
      "Generation 2910: M(n) = 862.6320056992192\n",
      "Generation 2911: p = 0.9584800063324658\n",
      "Generation 2911: M(n) = 862.6320056992192\n",
      "Generation 2912: p = 0.9584800063324658\n",
      "Generation 2912: M(n) = 862.6320056992192\n",
      "Generation 2913: p = 0.9584800063324658\n",
      "Generation 2913: M(n) = 862.6320056992192\n",
      "Generation 2914: p = 0.9584800063324658\n",
      "Generation 2914: M(n) = 862.6320056992192\n",
      "Generation 2915: p = 0.9584800063324658\n",
      "Generation 2915: M(n) = 862.6320056992192\n",
      "Generation 2916: p = 0.9584800063324658\n",
      "Generation 2916: M(n) = 862.6320056992192\n",
      "Generation 2917: p = 0.9584800063324658\n",
      "Generation 2917: M(n) = 862.6320056992192\n",
      "Generation 2918: p = 0.9584800063324658\n",
      "Generation 2918: M(n) = 862.6320056992192\n",
      "Generation 2919: p = 0.9584800063324658\n",
      "Generation 2919: M(n) = 862.6320056992192\n",
      "Generation 2920: p = 0.9584800063324658\n",
      "Generation 2920: M(n) = 862.6320056992192\n",
      "Generation 2921: p = 0.9584800063324658\n",
      "Generation 2921: M(n) = 862.6320056992192\n",
      "Generation 2922: p = 0.9584800063324658\n",
      "Generation 2922: M(n) = 862.6320056992192\n",
      "Generation 2923: p = 0.9584800063324658\n",
      "Generation 2923: M(n) = 862.6320056992192\n",
      "Generation 2924: p = 0.9584800063324658\n",
      "Generation 2924: M(n) = 862.6320056992192\n",
      "Generation 2925: p = 0.9584800063324658\n",
      "Generation 2925: M(n) = 862.6320056992192\n",
      "Generation 2926: p = 0.9584800063324658\n",
      "Generation 2926: M(n) = 862.6320056992192\n",
      "Generation 2927: p = 0.9584800063324658\n",
      "Generation 2927: M(n) = 862.6320056992192\n",
      "Generation 2928: p = 0.9584800063324658\n",
      "Generation 2928: M(n) = 862.6320056992192\n",
      "Generation 2929: p = 0.9584800063324658\n",
      "Generation 2929: M(n) = 862.6320056992192\n",
      "Generation 2930: p = 0.9584800063324658\n",
      "Generation 2930: M(n) = 862.6320056992192\n",
      "Generation 2931: p = 0.9584800063324658\n",
      "Generation 2931: M(n) = 862.6320056992192\n",
      "Generation 2932: p = 0.9584800063324658\n",
      "Generation 2932: M(n) = 862.6320056992192\n",
      "Generation 2933: p = 0.9584800063324658\n",
      "Generation 2933: M(n) = 862.6320056992192\n",
      "Generation 2934: p = 0.9584800063324658\n",
      "Generation 2934: M(n) = 862.6320056992192\n",
      "Generation 2935: p = 0.9584800063324658\n",
      "Generation 2935: M(n) = 862.6320056992192\n",
      "Generation 2936: p = 0.9584800063324658\n",
      "Generation 2936: M(n) = 862.6320056992192\n",
      "Generation 2937: p = 0.9584800063324658\n",
      "Generation 2937: M(n) = 862.6320056992192\n",
      "Generation 2938: p = 0.9584800063324658\n",
      "Generation 2938: M(n) = 862.6320056992192\n",
      "Generation 2939: p = 0.9584800063324658\n",
      "Generation 2939: M(n) = 862.6320056992192\n",
      "Generation 2940: p = 0.9584800063324658\n",
      "Generation 2940: M(n) = 862.6320056992192\n",
      "Generation 2941: p = 0.9584800063324658\n",
      "Generation 2941: M(n) = 862.6320056992192\n",
      "Generation 2942: p = 0.9584800063324658\n",
      "Generation 2942: M(n) = 862.6320056992192\n",
      "Generation 2943: p = 0.9584800063324658\n",
      "Generation 2943: M(n) = 862.6320056992192\n",
      "Generation 2944: p = 0.9584800063324658\n",
      "Generation 2944: M(n) = 862.6320056992192\n",
      "Generation 2945: p = 0.9584800063324658\n",
      "Generation 2945: M(n) = 862.6320056992192\n",
      "Generation 2946: p = 0.9584800063324658\n",
      "Generation 2946: M(n) = 862.6320056992192\n",
      "Generation 2947: p = 0.9584800063324658\n",
      "Generation 2947: M(n) = 862.6320056992192\n",
      "Generation 2948: p = 0.9584800063324658\n",
      "Generation 2948: M(n) = 862.6320056992192\n",
      "Generation 2949: p = 0.9584800063324658\n",
      "Generation 2949: M(n) = 862.6320056992192\n",
      "Generation 2950: p = 0.9584800063324658\n",
      "Generation 2950: M(n) = 862.6320056992192\n",
      "Generation 2951: p = 0.9584800063324658\n",
      "Generation 2951: M(n) = 862.6320056992192\n",
      "Generation 2952: p = 0.9584800063324658\n",
      "Generation 2952: M(n) = 862.6320056992192\n",
      "Generation 2953: p = 0.9584800063324658\n",
      "Generation 2953: M(n) = 862.6320056992192\n",
      "Generation 2954: p = 0.9584800063324658\n",
      "Generation 2954: M(n) = 862.6320056992192\n",
      "Generation 2955: p = 0.9584800063324658\n",
      "Generation 2955: M(n) = 862.6320056992192\n",
      "Generation 2956: p = 0.9584800063324658\n",
      "Generation 2956: M(n) = 862.6320056992192\n",
      "Generation 2957: p = 0.9584800063324658\n",
      "Generation 2957: M(n) = 862.6320056992192\n",
      "Generation 2958: p = 0.9584800063324658\n",
      "Generation 2958: M(n) = 862.6320056992192\n",
      "Generation 2959: p = 0.9584800063324658\n",
      "Generation 2959: M(n) = 862.6320056992192\n",
      "Generation 2960: p = 0.9584800063324658\n",
      "Generation 2960: M(n) = 862.6320056992192\n",
      "Generation 2961: p = 0.9584800063324658\n",
      "Generation 2961: M(n) = 862.6320056992192\n",
      "Generation 2962: p = 0.9584800063324658\n",
      "Generation 2962: M(n) = 862.6320056992192\n",
      "Generation 2963: p = 0.9584800063324658\n",
      "Generation 2963: M(n) = 862.6320056992192\n",
      "Generation 2964: p = 0.9584800063324658\n",
      "Generation 2964: M(n) = 862.6320056992192\n",
      "Generation 2965: p = 0.9584800063324658\n",
      "Generation 2965: M(n) = 862.6320056992192\n",
      "Generation 2966: p = 0.9584800063324658\n",
      "Generation 2966: M(n) = 862.6320056992192\n",
      "Generation 2967: p = 0.9584800063324658\n",
      "Generation 2967: M(n) = 862.6320056992192\n",
      "Generation 2968: p = 0.9584800063324658\n",
      "Generation 2968: M(n) = 862.6320056992192\n",
      "Generation 2969: p = 0.9584800063324658\n",
      "Generation 2969: M(n) = 862.6320056992192\n",
      "Generation 2970: p = 0.9584800063324658\n",
      "Generation 2970: M(n) = 862.6320056992192\n",
      "Generation 2971: p = 0.9584800063324658\n",
      "Generation 2971: M(n) = 862.6320056992192\n",
      "Generation 2972: p = 0.9584800063324658\n",
      "Generation 2972: M(n) = 862.6320056992192\n",
      "Generation 2973: p = 0.9584800063324658\n",
      "Generation 2973: M(n) = 862.6320056992192\n",
      "Generation 2974: p = 0.9584800063324658\n",
      "Generation 2974: M(n) = 862.6320056992192\n",
      "Generation 2975: p = 0.9584800063324658\n",
      "Generation 2975: M(n) = 862.6320056992192\n",
      "Generation 2976: p = 0.9584800063324658\n",
      "Generation 2976: M(n) = 862.6320056992192\n",
      "Generation 2977: p = 0.9584800063324658\n",
      "Generation 2977: M(n) = 862.6320056992192\n",
      "Generation 2978: p = 0.9584800063324658\n",
      "Generation 2978: M(n) = 862.6320056992192\n",
      "Generation 2979: p = 0.9584800063324658\n",
      "Generation 2979: M(n) = 862.6320056992192\n",
      "Generation 2980: p = 0.9584800063324658\n",
      "Generation 2980: M(n) = 862.6320056992192\n",
      "Generation 2981: p = 0.9584800063324658\n",
      "Generation 2981: M(n) = 862.6320056992192\n",
      "Generation 2982: p = 0.9584800063324658\n",
      "Generation 2982: M(n) = 862.6320056992192\n",
      "Generation 2983: p = 0.9584800063324658\n",
      "Generation 2983: M(n) = 862.6320056992192\n",
      "Generation 2984: p = 0.9584800063324658\n",
      "Generation 2984: M(n) = 862.6320056992192\n",
      "Generation 2985: p = 0.9584800063324658\n",
      "Generation 2985: M(n) = 862.6320056992192\n",
      "Generation 2986: p = 0.9584800063324658\n",
      "Generation 2986: M(n) = 862.6320056992192\n",
      "Generation 2987: p = 0.9584800063324658\n",
      "Generation 2987: M(n) = 862.6320056992192\n",
      "Generation 2988: p = 0.9584800063324658\n",
      "Generation 2988: M(n) = 862.6320056992192\n",
      "Generation 2989: p = 0.9584800063324658\n",
      "Generation 2989: M(n) = 862.6320056992192\n",
      "Generation 2990: p = 0.9584800063324658\n",
      "Generation 2990: M(n) = 862.6320056992192\n",
      "Generation 2991: p = 0.9584800063324658\n",
      "Generation 2991: M(n) = 862.6320056992192\n",
      "Generation 2992: p = 0.9584800063324658\n",
      "Generation 2992: M(n) = 862.6320056992192\n",
      "Generation 2993: p = 0.9584800063324658\n",
      "Generation 2993: M(n) = 862.6320056992192\n",
      "Generation 2994: p = 0.9584800063324658\n",
      "Generation 2994: M(n) = 862.6320056992192\n",
      "Generation 2995: p = 0.9584800063324658\n",
      "Generation 2995: M(n) = 862.6320056992192\n",
      "Generation 2996: p = 0.9584800063324658\n",
      "Generation 2996: M(n) = 862.6320056992192\n",
      "Generation 2997: p = 0.9584800063324658\n",
      "Generation 2997: M(n) = 862.6320056992192\n",
      "Generation 2998: p = 0.9584800063324658\n",
      "Generation 2998: M(n) = 862.6320056992192\n",
      "Generation 2999: p = 0.9584800063324658\n",
      "Generation 2999: M(n) = 862.6320056992192\n",
      "Generation 3000: p = 0.9584800063324658\n",
      "Generation 3000: M(n) = 862.6320056992192\n",
      "Generation 3001: p = 0.9584800063324658\n",
      "Generation 3001: M(n) = 862.6320056992192\n",
      "Generation 3002: p = 0.9584800063324658\n",
      "Generation 3002: M(n) = 862.6320056992192\n",
      "Generation 3003: p = 0.9584800063324658\n",
      "Generation 3003: M(n) = 862.6320056992192\n",
      "Generation 3004: p = 0.9584800063324658\n",
      "Generation 3004: M(n) = 862.6320056992192\n",
      "Generation 3005: p = 0.9584800063324658\n",
      "Generation 3005: M(n) = 862.6320056992192\n",
      "Generation 3006: p = 0.9584800063324658\n",
      "Generation 3006: M(n) = 862.6320056992192\n",
      "Generation 3007: p = 0.9584800063324658\n",
      "Generation 3007: M(n) = 862.6320056992192\n",
      "Generation 3008: p = 0.9584800063324658\n",
      "Generation 3008: M(n) = 862.6320056992192\n",
      "Generation 3009: p = 0.9584800063324658\n",
      "Generation 3009: M(n) = 862.6320056992192\n",
      "Generation 3010: p = 0.9584800063324658\n",
      "Generation 3010: M(n) = 862.6320056992192\n",
      "Generation 3011: p = 0.9584800063324658\n",
      "Generation 3011: M(n) = 862.6320056992192\n",
      "Generation 3012: p = 0.9584800063324658\n",
      "Generation 3012: M(n) = 862.6320056992192\n",
      "Generation 3013: p = 0.9584800063324658\n",
      "Generation 3013: M(n) = 862.6320056992192\n",
      "Generation 3014: p = 0.9584800063324658\n",
      "Generation 3014: M(n) = 862.6320056992192\n",
      "Generation 3015: p = 0.9584800063324658\n",
      "Generation 3015: M(n) = 862.6320056992192\n",
      "Generation 3016: p = 0.9584800063324658\n",
      "Generation 3016: M(n) = 862.6320056992192\n",
      "Generation 3017: p = 0.9584800063324658\n",
      "Generation 3017: M(n) = 862.6320056992192\n",
      "Generation 3018: p = 0.9584800063324658\n",
      "Generation 3018: M(n) = 862.6320056992192\n",
      "Generation 3019: p = 0.9584800063324658\n",
      "Generation 3019: M(n) = 862.6320056992192\n",
      "Generation 3020: p = 0.9584800063324658\n",
      "Generation 3020: M(n) = 862.6320056992192\n",
      "Generation 3021: p = 0.9584800063324658\n",
      "Generation 3021: M(n) = 862.6320056992192\n",
      "Generation 3022: p = 0.9584800063324658\n",
      "Generation 3022: M(n) = 862.6320056992192\n",
      "Generation 3023: p = 0.9584800063324658\n",
      "Generation 3023: M(n) = 862.6320056992192\n",
      "Generation 3024: p = 0.9584800063324658\n",
      "Generation 3024: M(n) = 862.6320056992192\n",
      "Generation 3025: p = 0.9584800063324658\n",
      "Generation 3025: M(n) = 862.6320056992192\n",
      "Generation 3026: p = 0.9584800063324658\n",
      "Generation 3026: M(n) = 862.6320056992192\n",
      "Generation 3027: p = 0.9584800063324658\n",
      "Generation 3027: M(n) = 862.6320056992192\n",
      "Generation 3028: p = 0.9584800063324658\n",
      "Generation 3028: M(n) = 862.6320056992192\n",
      "Generation 3029: p = 0.9584800063324658\n",
      "Generation 3029: M(n) = 862.6320056992192\n",
      "Generation 3030: p = 0.9584800063324658\n",
      "Generation 3030: M(n) = 862.6320056992192\n",
      "Generation 3031: p = 0.9584800063324658\n",
      "Generation 3031: M(n) = 862.6320056992192\n",
      "Generation 3032: p = 0.9584800063324658\n",
      "Generation 3032: M(n) = 862.6320056992192\n",
      "Generation 3033: p = 0.9584800063324658\n",
      "Generation 3033: M(n) = 862.6320056992192\n",
      "Generation 3034: p = 0.9584800063324658\n",
      "Generation 3034: M(n) = 862.6320056992192\n",
      "Generation 3035: p = 0.9584800063324658\n",
      "Generation 3035: M(n) = 862.6320056992192\n",
      "Generation 3036: p = 0.9584800063324658\n",
      "Generation 3036: M(n) = 862.6320056992192\n",
      "Generation 3037: p = 0.9584800063324658\n",
      "Generation 3037: M(n) = 862.6320056992192\n",
      "Generation 3038: p = 0.9584800063324658\n",
      "Generation 3038: M(n) = 862.6320056992192\n",
      "Generation 3039: p = 0.9584800063324658\n",
      "Generation 3039: M(n) = 862.6320056992192\n",
      "Generation 3040: p = 0.9584800063324658\n",
      "Generation 3040: M(n) = 862.6320056992192\n",
      "Generation 3041: p = 0.9584800063324658\n",
      "Generation 3041: M(n) = 862.6320056992192\n",
      "Generation 3042: p = 0.9584800063324658\n",
      "Generation 3042: M(n) = 862.6320056992192\n",
      "Generation 3043: p = 0.9584800063324658\n",
      "Generation 3043: M(n) = 862.6320056992192\n",
      "Generation 3044: p = 0.9584800063324658\n",
      "Generation 3044: M(n) = 862.6320056992192\n",
      "Generation 3045: p = 0.9584800063324658\n",
      "Generation 3045: M(n) = 862.6320056992192\n",
      "Generation 3046: p = 0.9584800063324658\n",
      "Generation 3046: M(n) = 862.6320056992192\n",
      "Generation 3047: p = 0.9584800063324658\n",
      "Generation 3047: M(n) = 862.6320056992192\n",
      "Generation 3048: p = 0.9584800063324658\n",
      "Generation 3048: M(n) = 862.6320056992192\n",
      "Generation 3049: p = 0.9584800063324658\n",
      "Generation 3049: M(n) = 862.6320056992192\n",
      "Generation 3050: p = 0.9584800063324658\n",
      "Generation 3050: M(n) = 862.6320056992192\n",
      "Generation 3051: p = 0.9584800063324658\n",
      "Generation 3051: M(n) = 862.6320056992192\n",
      "Generation 3052: p = 0.9584800063324658\n",
      "Generation 3052: M(n) = 862.6320056992192\n",
      "Generation 3053: p = 0.9584800063324658\n",
      "Generation 3053: M(n) = 862.6320056992192\n",
      "Generation 3054: p = 0.9584800063324658\n",
      "Generation 3054: M(n) = 862.6320056992192\n",
      "Generation 3055: p = 0.9584800063324658\n",
      "Generation 3055: M(n) = 862.6320056992192\n",
      "Generation 3056: p = 0.9584800063324658\n",
      "Generation 3056: M(n) = 862.6320056992192\n",
      "Generation 3057: p = 0.9584800063324658\n",
      "Generation 3057: M(n) = 862.6320056992192\n",
      "Generation 3058: p = 0.9584800063324658\n",
      "Generation 3058: M(n) = 862.6320056992192\n",
      "Generation 3059: p = 0.9584800063324658\n",
      "Generation 3059: M(n) = 862.6320056992192\n",
      "Generation 3060: p = 0.9584800063324658\n",
      "Generation 3060: M(n) = 862.6320056992192\n",
      "Generation 3061: p = 0.9584800063324658\n",
      "Generation 3061: M(n) = 862.6320056992192\n",
      "Generation 3062: p = 0.9584800063324658\n",
      "Generation 3062: M(n) = 862.6320056992192\n",
      "Generation 3063: p = 0.9584800063324658\n",
      "Generation 3063: M(n) = 862.6320056992192\n",
      "Generation 3064: p = 0.9584800063324658\n",
      "Generation 3064: M(n) = 862.6320056992192\n",
      "Generation 3065: p = 0.9584800063324658\n",
      "Generation 3065: M(n) = 862.6320056992192\n",
      "Generation 3066: p = 0.9584800063324658\n",
      "Generation 3066: M(n) = 862.6320056992192\n",
      "Generation 3067: p = 0.9584800063324658\n",
      "Generation 3067: M(n) = 862.6320056992192\n",
      "Generation 3068: p = 0.9584800063324658\n",
      "Generation 3068: M(n) = 862.6320056992192\n",
      "Generation 3069: p = 0.9584800063324658\n",
      "Generation 3069: M(n) = 862.6320056992192\n",
      "Generation 3070: p = 0.9584800063324658\n",
      "Generation 3070: M(n) = 862.6320056992192\n",
      "Generation 3071: p = 0.9584800063324658\n",
      "Generation 3071: M(n) = 862.6320056992192\n",
      "Generation 3072: p = 0.9584800063324658\n",
      "Generation 3072: M(n) = 862.6320056992192\n",
      "Generation 3073: p = 0.9584800063324658\n",
      "Generation 3073: M(n) = 862.6320056992192\n",
      "Generation 3074: p = 0.9584800063324658\n",
      "Generation 3074: M(n) = 862.6320056992192\n",
      "Generation 3075: p = 0.9584800063324658\n",
      "Generation 3075: M(n) = 862.6320056992192\n",
      "Generation 3076: p = 0.9584800063324658\n",
      "Generation 3076: M(n) = 862.6320056992192\n",
      "Generation 3077: p = 0.9584800063324658\n",
      "Generation 3077: M(n) = 862.6320056992192\n",
      "Generation 3078: p = 0.9584800063324658\n",
      "Generation 3078: M(n) = 862.6320056992192\n",
      "Generation 3079: p = 0.9584800063324658\n",
      "Generation 3079: M(n) = 862.6320056992192\n",
      "Generation 3080: p = 0.9584800063324658\n",
      "Generation 3080: M(n) = 862.6320056992192\n",
      "Generation 3081: p = 0.9584800063324658\n",
      "Generation 3081: M(n) = 862.6320056992192\n",
      "Generation 3082: p = 0.9584800063324658\n",
      "Generation 3082: M(n) = 862.6320056992192\n",
      "Generation 3083: p = 0.9584800063324658\n",
      "Generation 3083: M(n) = 862.6320056992192\n",
      "Generation 3084: p = 0.9584800063324658\n",
      "Generation 3084: M(n) = 862.6320056992192\n",
      "Generation 3085: p = 0.9584800063324658\n",
      "Generation 3085: M(n) = 862.6320056992192\n",
      "Generation 3086: p = 0.9584800063324658\n",
      "Generation 3086: M(n) = 862.6320056992192\n",
      "Generation 3087: p = 0.9584800063324658\n",
      "Generation 3087: M(n) = 862.6320056992192\n",
      "Generation 3088: p = 0.9584800063324658\n",
      "Generation 3088: M(n) = 862.6320056992192\n",
      "Generation 3089: p = 0.9584800063324658\n",
      "Generation 3089: M(n) = 862.6320056992192\n",
      "Generation 3090: p = 0.9584800063324658\n",
      "Generation 3090: M(n) = 862.6320056992192\n",
      "Generation 3091: p = 0.9584800063324658\n",
      "Generation 3091: M(n) = 862.6320056992192\n",
      "Generation 3092: p = 0.9584800063324658\n",
      "Generation 3092: M(n) = 862.6320056992192\n",
      "Generation 3093: p = 0.9584800063324658\n",
      "Generation 3093: M(n) = 862.6320056992192\n",
      "Generation 3094: p = 0.9584800063324658\n",
      "Generation 3094: M(n) = 862.6320056992192\n",
      "Generation 3095: p = 0.9584800063324658\n",
      "Generation 3095: M(n) = 862.6320056992192\n",
      "Generation 3096: p = 0.9584800063324658\n",
      "Generation 3096: M(n) = 862.6320056992192\n",
      "Generation 3097: p = 0.9584800063324658\n",
      "Generation 3097: M(n) = 862.6320056992192\n",
      "Generation 3098: p = 0.9584800063324658\n",
      "Generation 3098: M(n) = 862.6320056992192\n",
      "Generation 3099: p = 0.9584800063324658\n",
      "Generation 3099: M(n) = 862.6320056992192\n",
      "Generation 3100: p = 0.9584800063324658\n",
      "Generation 3100: M(n) = 862.6320056992192\n",
      "Generation 3101: p = 0.9584800063324658\n",
      "Generation 3101: M(n) = 862.6320056992192\n",
      "Generation 3102: p = 0.9584800063324658\n",
      "Generation 3102: M(n) = 862.6320056992192\n",
      "Generation 3103: p = 0.9584800063324658\n",
      "Generation 3103: M(n) = 862.6320056992192\n",
      "Generation 3104: p = 0.9584800063324658\n",
      "Generation 3104: M(n) = 862.6320056992192\n",
      "Generation 3105: p = 0.9584800063324658\n",
      "Generation 3105: M(n) = 862.6320056992192\n",
      "Generation 3106: p = 0.9584800063324658\n",
      "Generation 3106: M(n) = 862.6320056992192\n",
      "Generation 3107: p = 0.9584800063324658\n",
      "Generation 3107: M(n) = 862.6320056992192\n",
      "Generation 3108: p = 0.9584800063324658\n",
      "Generation 3108: M(n) = 862.6320056992192\n",
      "Generation 3109: p = 0.9584800063324658\n",
      "Generation 3109: M(n) = 862.6320056992192\n",
      "Generation 3110: p = 0.9584800063324658\n",
      "Generation 3110: M(n) = 862.6320056992192\n",
      "Generation 3111: p = 0.9584800063324658\n",
      "Generation 3111: M(n) = 862.6320056992192\n",
      "Generation 3112: p = 0.9584800063324658\n",
      "Generation 3112: M(n) = 862.6320056992192\n",
      "Generation 3113: p = 0.9584800063324658\n",
      "Generation 3113: M(n) = 862.6320056992192\n",
      "Generation 3114: p = 0.9584800063324658\n",
      "Generation 3114: M(n) = 862.6320056992192\n",
      "Generation 3115: p = 0.9584800063324658\n",
      "Generation 3115: M(n) = 862.6320056992192\n",
      "Generation 3116: p = 0.9584800063324658\n",
      "Generation 3116: M(n) = 862.6320056992192\n",
      "Generation 3117: p = 0.9584800063324658\n",
      "Generation 3117: M(n) = 862.6320056992192\n",
      "Generation 3118: p = 0.9584800063324658\n",
      "Generation 3118: M(n) = 862.6320056992192\n",
      "Generation 3119: p = 0.9584800063324658\n",
      "Generation 3119: M(n) = 862.6320056992192\n",
      "Generation 3120: p = 0.9584800063324658\n",
      "Generation 3120: M(n) = 862.6320056992192\n",
      "Generation 3121: p = 0.9584800063324658\n",
      "Generation 3121: M(n) = 862.6320056992192\n",
      "Generation 3122: p = 0.9584800063324658\n",
      "Generation 3122: M(n) = 862.6320056992192\n",
      "Generation 3123: p = 0.9584800063324658\n",
      "Generation 3123: M(n) = 862.6320056992192\n",
      "Generation 3124: p = 0.9584800063324658\n",
      "Generation 3124: M(n) = 862.6320056992192\n",
      "Generation 3125: p = 0.9584800063324658\n",
      "Generation 3125: M(n) = 862.6320056992192\n",
      "Generation 3126: p = 0.9584800063324658\n",
      "Generation 3126: M(n) = 862.6320056992192\n",
      "Generation 3127: p = 0.9584800063324658\n",
      "Generation 3127: M(n) = 862.6320056992192\n",
      "Generation 3128: p = 0.9584800063324658\n",
      "Generation 3128: M(n) = 862.6320056992192\n",
      "Generation 3129: p = 0.9584800063324658\n",
      "Generation 3129: M(n) = 862.6320056992192\n",
      "Generation 3130: p = 0.9584800063324658\n",
      "Generation 3130: M(n) = 862.6320056992192\n",
      "Generation 3131: p = 0.9584800063324658\n",
      "Generation 3131: M(n) = 862.6320056992192\n",
      "Generation 3132: p = 0.9584800063324658\n",
      "Generation 3132: M(n) = 862.6320056992192\n",
      "Generation 3133: p = 0.9584800063324658\n",
      "Generation 3133: M(n) = 862.6320056992192\n",
      "Generation 3134: p = 0.9584800063324658\n",
      "Generation 3134: M(n) = 862.6320056992192\n",
      "Generation 3135: p = 0.9584800063324658\n",
      "Generation 3135: M(n) = 862.6320056992192\n",
      "Generation 3136: p = 0.9584800063324658\n",
      "Generation 3136: M(n) = 862.6320056992192\n",
      "Generation 3137: p = 0.9584800063324658\n",
      "Generation 3137: M(n) = 862.6320056992192\n",
      "Generation 3138: p = 0.9584800063324658\n",
      "Generation 3138: M(n) = 862.6320056992192\n",
      "Generation 3139: p = 0.9584800063324658\n",
      "Generation 3139: M(n) = 862.6320056992192\n",
      "Generation 3140: p = 0.9584800063324658\n",
      "Generation 3140: M(n) = 862.6320056992192\n",
      "Generation 3141: p = 0.9584800063324658\n",
      "Generation 3141: M(n) = 862.6320056992192\n",
      "Generation 3142: p = 0.9584800063324658\n",
      "Generation 3142: M(n) = 862.6320056992192\n",
      "Generation 3143: p = 0.9584800063324658\n",
      "Generation 3143: M(n) = 862.6320056992192\n",
      "Generation 3144: p = 0.9584800063324658\n",
      "Generation 3144: M(n) = 862.6320056992192\n",
      "Generation 3145: p = 0.9584800063324658\n",
      "Generation 3145: M(n) = 862.6320056992192\n",
      "Generation 3146: p = 0.9584800063324658\n",
      "Generation 3146: M(n) = 862.6320056992192\n",
      "Generation 3147: p = 0.9584800063324658\n",
      "Generation 3147: M(n) = 862.6320056992192\n",
      "Generation 3148: p = 0.9584800063324658\n",
      "Generation 3148: M(n) = 862.6320056992192\n",
      "Generation 3149: p = 0.9584800063324658\n",
      "Generation 3149: M(n) = 862.6320056992192\n",
      "Generation 3150: p = 0.9584800063324658\n",
      "Generation 3150: M(n) = 862.6320056992192\n",
      "Generation 3151: p = 0.9584800063324658\n",
      "Generation 3151: M(n) = 862.6320056992192\n",
      "Generation 3152: p = 0.9584800063324658\n",
      "Generation 3152: M(n) = 862.6320056992192\n",
      "Generation 3153: p = 0.9584800063324658\n",
      "Generation 3153: M(n) = 862.6320056992192\n",
      "Generation 3154: p = 0.9584800063324658\n",
      "Generation 3154: M(n) = 862.6320056992192\n",
      "Generation 3155: p = 0.9584800063324658\n",
      "Generation 3155: M(n) = 862.6320056992192\n",
      "Generation 3156: p = 0.9584800063324658\n",
      "Generation 3156: M(n) = 862.6320056992192\n",
      "Generation 3157: p = 0.9584800063324658\n",
      "Generation 3157: M(n) = 862.6320056992192\n",
      "Generation 3158: p = 0.9584800063324658\n",
      "Generation 3158: M(n) = 862.6320056992192\n",
      "Generation 3159: p = 0.9584800063324658\n",
      "Generation 3159: M(n) = 862.6320056992192\n",
      "Generation 3160: p = 0.9584800063324658\n",
      "Generation 3160: M(n) = 862.6320056992192\n",
      "Generation 3161: p = 0.9584800063324658\n",
      "Generation 3161: M(n) = 862.6320056992192\n",
      "Generation 3162: p = 0.9584800063324658\n",
      "Generation 3162: M(n) = 862.6320056992192\n",
      "Generation 3163: p = 0.9584800063324658\n",
      "Generation 3163: M(n) = 862.6320056992192\n",
      "Generation 3164: p = 0.9584800063324658\n",
      "Generation 3164: M(n) = 862.6320056992192\n",
      "Generation 3165: p = 0.9584800063324658\n",
      "Generation 3165: M(n) = 862.6320056992192\n",
      "Generation 3166: p = 0.9584800063324658\n",
      "Generation 3166: M(n) = 862.6320056992192\n",
      "Generation 3167: p = 0.9584800063324658\n",
      "Generation 3167: M(n) = 862.6320056992192\n",
      "Generation 3168: p = 0.9584800063324658\n",
      "Generation 3168: M(n) = 862.6320056992192\n",
      "Generation 3169: p = 0.9584800063324658\n",
      "Generation 3169: M(n) = 862.6320056992192\n",
      "Generation 3170: p = 0.9584800063324658\n",
      "Generation 3170: M(n) = 862.6320056992192\n",
      "Generation 3171: p = 0.9584800063324658\n",
      "Generation 3171: M(n) = 862.6320056992192\n",
      "Generation 3172: p = 0.9584800063324658\n",
      "Generation 3172: M(n) = 862.6320056992192\n",
      "Generation 3173: p = 0.9584800063324658\n",
      "Generation 3173: M(n) = 862.6320056992192\n",
      "Generation 3174: p = 0.9584800063324658\n",
      "Generation 3174: M(n) = 862.6320056992192\n",
      "Generation 3175: p = 0.9584800063324658\n",
      "Generation 3175: M(n) = 862.6320056992192\n",
      "Generation 3176: p = 0.9584800063324658\n",
      "Generation 3176: M(n) = 862.6320056992192\n",
      "Generation 3177: p = 0.9584800063324658\n",
      "Generation 3177: M(n) = 862.6320056992192\n",
      "Generation 3178: p = 0.9584800063324658\n",
      "Generation 3178: M(n) = 862.6320056992192\n",
      "Generation 3179: p = 0.9584800063324658\n",
      "Generation 3179: M(n) = 862.6320056992192\n",
      "Generation 3180: p = 0.9584800063324658\n",
      "Generation 3180: M(n) = 862.6320056992192\n",
      "Generation 3181: p = 0.9584800063324658\n",
      "Generation 3181: M(n) = 862.6320056992192\n",
      "Generation 3182: p = 0.9584800063324658\n",
      "Generation 3182: M(n) = 862.6320056992192\n",
      "Generation 3183: p = 0.9584800063324658\n",
      "Generation 3183: M(n) = 862.6320056992192\n",
      "Generation 3184: p = 0.9584800063324658\n",
      "Generation 3184: M(n) = 862.6320056992192\n",
      "Generation 3185: p = 0.9584800063324658\n",
      "Generation 3185: M(n) = 862.6320056992192\n",
      "Generation 3186: p = 0.9584800063324658\n",
      "Generation 3186: M(n) = 862.6320056992192\n",
      "Generation 3187: p = 0.9584800063324658\n",
      "Generation 3187: M(n) = 862.6320056992192\n",
      "Generation 3188: p = 0.9584800063324658\n",
      "Generation 3188: M(n) = 862.6320056992192\n",
      "Generation 3189: p = 0.9584800063324658\n",
      "Generation 3189: M(n) = 862.6320056992192\n",
      "Generation 3190: p = 0.9584800063324658\n",
      "Generation 3190: M(n) = 862.6320056992192\n",
      "Generation 3191: p = 0.9584800063324658\n",
      "Generation 3191: M(n) = 862.6320056992192\n",
      "Generation 3192: p = 0.9584800063324658\n",
      "Generation 3192: M(n) = 862.6320056992192\n",
      "Generation 3193: p = 0.9584800063324658\n",
      "Generation 3193: M(n) = 862.6320056992192\n",
      "Generation 3194: p = 0.9584800063324658\n",
      "Generation 3194: M(n) = 862.6320056992192\n",
      "Generation 3195: p = 0.9584800063324658\n",
      "Generation 3195: M(n) = 862.6320056992192\n",
      "Generation 3196: p = 0.9584800063324658\n",
      "Generation 3196: M(n) = 862.6320056992192\n",
      "Generation 3197: p = 0.9584800063324658\n",
      "Generation 3197: M(n) = 862.6320056992192\n",
      "Generation 3198: p = 0.9584800063324658\n",
      "Generation 3198: M(n) = 862.6320056992192\n",
      "Generation 3199: p = 0.9584800063324658\n",
      "Generation 3199: M(n) = 862.6320056992192\n",
      "Generation 3200: p = 0.9584800063324658\n",
      "Generation 3200: M(n) = 862.6320056992192\n",
      "Generation 3201: p = 0.9584800063324658\n",
      "Generation 3201: M(n) = 862.6320056992192\n",
      "Generation 3202: p = 0.9584800063324658\n",
      "Generation 3202: M(n) = 862.6320056992192\n",
      "Generation 3203: p = 0.9584800063324658\n",
      "Generation 3203: M(n) = 862.6320056992192\n",
      "Generation 3204: p = 0.9584800063324658\n",
      "Generation 3204: M(n) = 862.6320056992192\n",
      "Generation 3205: p = 0.9584800063324658\n",
      "Generation 3205: M(n) = 862.6320056992192\n",
      "Generation 3206: p = 0.9584800063324658\n",
      "Generation 3206: M(n) = 862.6320056992192\n",
      "Generation 3207: p = 0.9584800063324658\n",
      "Generation 3207: M(n) = 862.6320056992192\n",
      "Generation 3208: p = 0.9584800063324658\n",
      "Generation 3208: M(n) = 862.6320056992192\n",
      "Generation 3209: p = 0.9584800063324658\n",
      "Generation 3209: M(n) = 862.6320056992192\n",
      "Generation 3210: p = 0.9584800063324658\n",
      "Generation 3210: M(n) = 862.6320056992192\n",
      "Generation 3211: p = 0.9584800063324658\n",
      "Generation 3211: M(n) = 862.6320056992192\n",
      "Generation 3212: p = 0.9584800063324658\n",
      "Generation 3212: M(n) = 862.6320056992192\n",
      "Generation 3213: p = 0.9584800063324658\n",
      "Generation 3213: M(n) = 862.6320056992192\n",
      "Generation 3214: p = 0.9584800063324658\n",
      "Generation 3214: M(n) = 862.6320056992192\n",
      "Generation 3215: p = 0.9584800063324658\n",
      "Generation 3215: M(n) = 862.6320056992192\n",
      "Generation 3216: p = 0.9584800063324658\n",
      "Generation 3216: M(n) = 862.6320056992192\n",
      "Generation 3217: p = 0.9584800063324658\n",
      "Generation 3217: M(n) = 862.6320056992192\n",
      "Generation 3218: p = 0.9584800063324658\n",
      "Generation 3218: M(n) = 862.6320056992192\n",
      "Generation 3219: p = 0.9584800063324658\n",
      "Generation 3219: M(n) = 862.6320056992192\n",
      "Generation 3220: p = 0.9584800063324658\n",
      "Generation 3220: M(n) = 862.6320056992192\n",
      "Generation 3221: p = 0.9584800063324658\n",
      "Generation 3221: M(n) = 862.6320056992192\n",
      "Generation 3222: p = 0.9584800063324658\n",
      "Generation 3222: M(n) = 862.6320056992192\n",
      "Generation 3223: p = 0.9584800063324658\n",
      "Generation 3223: M(n) = 862.6320056992192\n",
      "Generation 3224: p = 0.9584800063324658\n",
      "Generation 3224: M(n) = 862.6320056992192\n",
      "Generation 3225: p = 0.9584800063324658\n",
      "Generation 3225: M(n) = 862.6320056992192\n",
      "Generation 3226: p = 0.9584800063324658\n",
      "Generation 3226: M(n) = 862.6320056992192\n",
      "Generation 3227: p = 0.9584800063324658\n",
      "Generation 3227: M(n) = 862.6320056992192\n",
      "Generation 3228: p = 0.9584800063324658\n",
      "Generation 3228: M(n) = 862.6320056992192\n",
      "Generation 3229: p = 0.9584800063324658\n",
      "Generation 3229: M(n) = 862.6320056992192\n",
      "Generation 3230: p = 0.9584800063324658\n",
      "Generation 3230: M(n) = 862.6320056992192\n",
      "Generation 3231: p = 0.9584800063324658\n",
      "Generation 3231: M(n) = 862.6320056992192\n",
      "Generation 3232: p = 0.9584800063324658\n",
      "Generation 3232: M(n) = 862.6320056992192\n",
      "Generation 3233: p = 0.9584800063324658\n",
      "Generation 3233: M(n) = 862.6320056992192\n",
      "Generation 3234: p = 0.9584800063324658\n",
      "Generation 3234: M(n) = 862.6320056992192\n",
      "Generation 3235: p = 0.9584800063324658\n",
      "Generation 3235: M(n) = 862.6320056992192\n",
      "Generation 3236: p = 0.9584800063324658\n",
      "Generation 3236: M(n) = 862.6320056992192\n",
      "Generation 3237: p = 0.9584800063324658\n",
      "Generation 3237: M(n) = 862.6320056992192\n",
      "Generation 3238: p = 0.9584800063324658\n",
      "Generation 3238: M(n) = 862.6320056992192\n",
      "Generation 3239: p = 0.9584800063324658\n",
      "Generation 3239: M(n) = 862.6320056992192\n",
      "Generation 3240: p = 0.9584800063324658\n",
      "Generation 3240: M(n) = 862.6320056992192\n",
      "Generation 3241: p = 0.9584800063324658\n",
      "Generation 3241: M(n) = 862.6320056992192\n",
      "Generation 3242: p = 0.9584800063324658\n",
      "Generation 3242: M(n) = 862.6320056992192\n",
      "Generation 3243: p = 0.9584800063324658\n",
      "Generation 3243: M(n) = 862.6320056992192\n",
      "Generation 3244: p = 0.9584800063324658\n",
      "Generation 3244: M(n) = 862.6320056992192\n",
      "Generation 3245: p = 0.9584800063324658\n",
      "Generation 3245: M(n) = 862.6320056992192\n",
      "Generation 3246: p = 0.9584800063324658\n",
      "Generation 3246: M(n) = 862.6320056992192\n",
      "Generation 3247: p = 0.9584800063324658\n",
      "Generation 3247: M(n) = 862.6320056992192\n",
      "Generation 3248: p = 0.9584800063324658\n",
      "Generation 3248: M(n) = 862.6320056992192\n",
      "Generation 3249: p = 0.9584800063324658\n",
      "Generation 3249: M(n) = 862.6320056992192\n",
      "Generation 3250: p = 0.9584800063324658\n",
      "Generation 3250: M(n) = 862.6320056992192\n",
      "Generation 3251: p = 0.9584800063324658\n",
      "Generation 3251: M(n) = 862.6320056992192\n",
      "Generation 3252: p = 0.9584800063324658\n",
      "Generation 3252: M(n) = 862.6320056992192\n",
      "Generation 3253: p = 0.9584800063324658\n",
      "Generation 3253: M(n) = 862.6320056992192\n",
      "Generation 3254: p = 0.9584800063324658\n",
      "Generation 3254: M(n) = 862.6320056992192\n",
      "Generation 3255: p = 0.9584800063324658\n",
      "Generation 3255: M(n) = 862.6320056992192\n",
      "Generation 3256: p = 0.9584800063324658\n",
      "Generation 3256: M(n) = 862.6320056992192\n",
      "Generation 3257: p = 0.9584800063324658\n",
      "Generation 3257: M(n) = 862.6320056992192\n",
      "Generation 3258: p = 0.9584800063324658\n",
      "Generation 3258: M(n) = 862.6320056992192\n",
      "Generation 3259: p = 0.9584800063324658\n",
      "Generation 3259: M(n) = 862.6320056992192\n",
      "Generation 3260: p = 0.9584800063324658\n",
      "Generation 3260: M(n) = 862.6320056992192\n",
      "Generation 3261: p = 0.9584800063324658\n",
      "Generation 3261: M(n) = 862.6320056992192\n",
      "Generation 3262: p = 0.9584800063324658\n",
      "Generation 3262: M(n) = 862.6320056992192\n",
      "Generation 3263: p = 0.9584800063324658\n",
      "Generation 3263: M(n) = 862.6320056992192\n",
      "Generation 3264: p = 0.9584800063324658\n",
      "Generation 3264: M(n) = 862.6320056992192\n",
      "Generation 3265: p = 0.9584800063324658\n",
      "Generation 3265: M(n) = 862.6320056992192\n",
      "Generation 3266: p = 0.9584800063324658\n",
      "Generation 3266: M(n) = 862.6320056992192\n",
      "Generation 3267: p = 0.9584800063324658\n",
      "Generation 3267: M(n) = 862.6320056992192\n",
      "Generation 3268: p = 0.9584800063324658\n",
      "Generation 3268: M(n) = 862.6320056992192\n",
      "Generation 3269: p = 0.9584800063324658\n",
      "Generation 3269: M(n) = 862.6320056992192\n",
      "Generation 3270: p = 0.9584800063324658\n",
      "Generation 3270: M(n) = 862.6320056992192\n",
      "Generation 3271: p = 0.9584800063324658\n",
      "Generation 3271: M(n) = 862.6320056992192\n",
      "Generation 3272: p = 0.9584800063324658\n",
      "Generation 3272: M(n) = 862.6320056992192\n",
      "Generation 3273: p = 0.9584800063324658\n",
      "Generation 3273: M(n) = 862.6320056992192\n",
      "Generation 3274: p = 0.9584800063324658\n",
      "Generation 3274: M(n) = 862.6320056992192\n",
      "Generation 3275: p = 0.9584800063324658\n",
      "Generation 3275: M(n) = 862.6320056992192\n",
      "Generation 3276: p = 0.9584800063324658\n",
      "Generation 3276: M(n) = 862.6320056992192\n",
      "Generation 3277: p = 0.9584800063324658\n",
      "Generation 3277: M(n) = 862.6320056992192\n",
      "Generation 3278: p = 0.9584800063324658\n",
      "Generation 3278: M(n) = 862.6320056992192\n",
      "Generation 3279: p = 0.9584800063324658\n",
      "Generation 3279: M(n) = 862.6320056992192\n",
      "Generation 3280: p = 0.9584800063324658\n",
      "Generation 3280: M(n) = 862.6320056992192\n",
      "Generation 3281: p = 0.9584800063324658\n",
      "Generation 3281: M(n) = 862.6320056992192\n",
      "Generation 3282: p = 0.9584800063324658\n",
      "Generation 3282: M(n) = 862.6320056992192\n",
      "Generation 3283: p = 0.9584800063324658\n",
      "Generation 3283: M(n) = 862.6320056992192\n",
      "Generation 3284: p = 0.9584800063324658\n",
      "Generation 3284: M(n) = 862.6320056992192\n",
      "Generation 3285: p = 0.9584800063324658\n",
      "Generation 3285: M(n) = 862.6320056992192\n",
      "Generation 3286: p = 0.9584800063324658\n",
      "Generation 3286: M(n) = 862.6320056992192\n",
      "Generation 3287: p = 0.9584800063324658\n",
      "Generation 3287: M(n) = 862.6320056992192\n",
      "Generation 3288: p = 0.9584800063324658\n",
      "Generation 3288: M(n) = 862.6320056992192\n",
      "Generation 3289: p = 0.9584800063324658\n",
      "Generation 3289: M(n) = 862.6320056992192\n",
      "Generation 3290: p = 0.9584800063324658\n",
      "Generation 3290: M(n) = 862.6320056992192\n",
      "Generation 3291: p = 0.9584800063324658\n",
      "Generation 3291: M(n) = 862.6320056992192\n",
      "Generation 3292: p = 0.9584800063324658\n",
      "Generation 3292: M(n) = 862.6320056992192\n",
      "Generation 3293: p = 0.9584800063324658\n",
      "Generation 3293: M(n) = 862.6320056992192\n",
      "Generation 3294: p = 0.9584800063324658\n",
      "Generation 3294: M(n) = 862.6320056992192\n",
      "Generation 3295: p = 0.9584800063324658\n",
      "Generation 3295: M(n) = 862.6320056992192\n",
      "Generation 3296: p = 0.9584800063324658\n",
      "Generation 3296: M(n) = 862.6320056992192\n",
      "Generation 3297: p = 0.9584800063324658\n",
      "Generation 3297: M(n) = 862.6320056992192\n",
      "Generation 3298: p = 0.9584800063324658\n",
      "Generation 3298: M(n) = 862.6320056992192\n",
      "Generation 3299: p = 0.9584800063324658\n",
      "Generation 3299: M(n) = 862.6320056992192\n",
      "Generation 3300: p = 0.9584800063324658\n",
      "Generation 3300: M(n) = 862.6320056992192\n",
      "Generation 3301: p = 0.9584800063324658\n",
      "Generation 3301: M(n) = 862.6320056992192\n",
      "Generation 3302: p = 0.9584800063324658\n",
      "Generation 3302: M(n) = 862.6320056992192\n",
      "Generation 3303: p = 0.9584800063324658\n",
      "Generation 3303: M(n) = 862.6320056992192\n",
      "Generation 3304: p = 0.9584800063324658\n",
      "Generation 3304: M(n) = 862.6320056992192\n",
      "Generation 3305: p = 0.9584800063324658\n",
      "Generation 3305: M(n) = 862.6320056992192\n",
      "Generation 3306: p = 0.9584800063324658\n",
      "Generation 3306: M(n) = 862.6320056992192\n",
      "Generation 3307: p = 0.9584800063324658\n",
      "Generation 3307: M(n) = 862.6320056992192\n",
      "Generation 3308: p = 0.9584800063324658\n",
      "Generation 3308: M(n) = 862.6320056992192\n",
      "Generation 3309: p = 0.9584800063324658\n",
      "Generation 3309: M(n) = 862.6320056992192\n",
      "Generation 3310: p = 0.9584800063324658\n",
      "Generation 3310: M(n) = 862.6320056992192\n",
      "Generation 3311: p = 0.9584800063324658\n",
      "Generation 3311: M(n) = 862.6320056992192\n",
      "Generation 3312: p = 0.9584800063324658\n",
      "Generation 3312: M(n) = 862.6320056992192\n",
      "Generation 3313: p = 0.9584800063324658\n",
      "Generation 3313: M(n) = 862.6320056992192\n",
      "Generation 3314: p = 0.9584800063324658\n",
      "Generation 3314: M(n) = 862.6320056992192\n",
      "Generation 3315: p = 0.9584800063324658\n",
      "Generation 3315: M(n) = 862.6320056992192\n",
      "Generation 3316: p = 0.9584800063324658\n",
      "Generation 3316: M(n) = 862.6320056992192\n",
      "Generation 3317: p = 0.9584800063324658\n",
      "Generation 3317: M(n) = 862.6320056992192\n",
      "Generation 3318: p = 0.9584800063324658\n",
      "Generation 3318: M(n) = 862.6320056992192\n",
      "Generation 3319: p = 0.9584800063324658\n",
      "Generation 3319: M(n) = 862.6320056992192\n",
      "Generation 3320: p = 0.9584800063324658\n",
      "Generation 3320: M(n) = 862.6320056992192\n",
      "Generation 3321: p = 0.9584800063324658\n",
      "Generation 3321: M(n) = 862.6320056992192\n",
      "Generation 3322: p = 0.9584800063324658\n",
      "Generation 3322: M(n) = 862.6320056992192\n",
      "Generation 3323: p = 0.9584800063324658\n",
      "Generation 3323: M(n) = 862.6320056992192\n",
      "Generation 3324: p = 0.9584800063324658\n",
      "Generation 3324: M(n) = 862.6320056992192\n",
      "Generation 3325: p = 0.9584800063324658\n",
      "Generation 3325: M(n) = 862.6320056992192\n",
      "Generation 3326: p = 0.9584800063324658\n",
      "Generation 3326: M(n) = 862.6320056992192\n",
      "Generation 3327: p = 0.9584800063324658\n",
      "Generation 3327: M(n) = 862.6320056992192\n",
      "Generation 3328: p = 0.9584800063324658\n",
      "Generation 3328: M(n) = 862.6320056992192\n",
      "Generation 3329: p = 0.9584800063324658\n",
      "Generation 3329: M(n) = 862.6320056992192\n",
      "Generation 3330: p = 0.9584800063324658\n",
      "Generation 3330: M(n) = 862.6320056992192\n",
      "Generation 3331: p = 0.9584800063324658\n",
      "Generation 3331: M(n) = 862.6320056992192\n",
      "Generation 3332: p = 0.9584800063324658\n",
      "Generation 3332: M(n) = 862.6320056992192\n",
      "Generation 3333: p = 0.9584800063324658\n",
      "Generation 3333: M(n) = 862.6320056992192\n",
      "Generation 3334: p = 0.9584800063324658\n",
      "Generation 3334: M(n) = 862.6320056992192\n",
      "Generation 3335: p = 0.9584800063324658\n",
      "Generation 3335: M(n) = 862.6320056992192\n",
      "Generation 3336: p = 0.9584800063324658\n",
      "Generation 3336: M(n) = 862.6320056992192\n",
      "Generation 3337: p = 0.9584800063324658\n",
      "Generation 3337: M(n) = 862.6320056992192\n",
      "Generation 3338: p = 0.9584800063324658\n",
      "Generation 3338: M(n) = 862.6320056992192\n",
      "Generation 3339: p = 0.9584800063324658\n",
      "Generation 3339: M(n) = 862.6320056992192\n",
      "Generation 3340: p = 0.9584800063324658\n",
      "Generation 3340: M(n) = 862.6320056992192\n",
      "Generation 3341: p = 0.9584800063324658\n",
      "Generation 3341: M(n) = 862.6320056992192\n",
      "Generation 3342: p = 0.9584800063324658\n",
      "Generation 3342: M(n) = 862.6320056992192\n",
      "Generation 3343: p = 0.9584800063324658\n",
      "Generation 3343: M(n) = 862.6320056992192\n",
      "Generation 3344: p = 0.9584800063324658\n",
      "Generation 3344: M(n) = 862.6320056992192\n",
      "Generation 3345: p = 0.9584800063324658\n",
      "Generation 3345: M(n) = 862.6320056992192\n",
      "Generation 3346: p = 0.9584800063324658\n",
      "Generation 3346: M(n) = 862.6320056992192\n",
      "Generation 3347: p = 0.9584800063324658\n",
      "Generation 3347: M(n) = 862.6320056992192\n",
      "Generation 3348: p = 0.9584800063324658\n",
      "Generation 3348: M(n) = 862.6320056992192\n",
      "Generation 3349: p = 0.9584800063324658\n",
      "Generation 3349: M(n) = 862.6320056992192\n",
      "Generation 3350: p = 0.9584800063324658\n",
      "Generation 3350: M(n) = 862.6320056992192\n",
      "Generation 3351: p = 0.9584800063324658\n",
      "Generation 3351: M(n) = 862.6320056992192\n",
      "Generation 3352: p = 0.9584800063324658\n",
      "Generation 3352: M(n) = 862.6320056992192\n",
      "Generation 3353: p = 0.9584800063324658\n",
      "Generation 3353: M(n) = 862.6320056992192\n",
      "Generation 3354: p = 0.9584800063324658\n",
      "Generation 3354: M(n) = 862.6320056992192\n",
      "Generation 3355: p = 0.9584800063324658\n",
      "Generation 3355: M(n) = 862.6320056992192\n",
      "Generation 3356: p = 0.9584800063324658\n",
      "Generation 3356: M(n) = 862.6320056992192\n",
      "Generation 3357: p = 0.9584800063324658\n",
      "Generation 3357: M(n) = 862.6320056992192\n",
      "Generation 3358: p = 0.9584800063324658\n",
      "Generation 3358: M(n) = 862.6320056992192\n",
      "Generation 3359: p = 0.9584800063324658\n",
      "Generation 3359: M(n) = 862.6320056992192\n",
      "Generation 3360: p = 0.9584800063324658\n",
      "Generation 3360: M(n) = 862.6320056992192\n",
      "Generation 3361: p = 0.9584800063324658\n",
      "Generation 3361: M(n) = 862.6320056992192\n",
      "Generation 3362: p = 0.9584800063324658\n",
      "Generation 3362: M(n) = 862.6320056992192\n",
      "Generation 3363: p = 0.9584800063324658\n",
      "Generation 3363: M(n) = 862.6320056992192\n",
      "Generation 3364: p = 0.9584800063324658\n",
      "Generation 3364: M(n) = 862.6320056992192\n",
      "Generation 3365: p = 0.9584800063324658\n",
      "Generation 3365: M(n) = 862.6320056992192\n",
      "Generation 3366: p = 0.9584800063324658\n",
      "Generation 3366: M(n) = 862.6320056992192\n",
      "Generation 3367: p = 0.9584800063324658\n",
      "Generation 3367: M(n) = 862.6320056992192\n",
      "Generation 3368: p = 0.9584800063324658\n",
      "Generation 3368: M(n) = 862.6320056992192\n",
      "Generation 3369: p = 0.9584800063324658\n",
      "Generation 3369: M(n) = 862.6320056992192\n",
      "Generation 3370: p = 0.9584800063324658\n",
      "Generation 3370: M(n) = 862.6320056992192\n",
      "Generation 3371: p = 0.9584800063324658\n",
      "Generation 3371: M(n) = 862.6320056992192\n",
      "Generation 3372: p = 0.9584800063324658\n",
      "Generation 3372: M(n) = 862.6320056992192\n",
      "Generation 3373: p = 0.9584800063324658\n",
      "Generation 3373: M(n) = 862.6320056992192\n",
      "Generation 3374: p = 0.9584800063324658\n",
      "Generation 3374: M(n) = 862.6320056992192\n",
      "Generation 3375: p = 0.9584800063324658\n",
      "Generation 3375: M(n) = 862.6320056992192\n",
      "Generation 3376: p = 0.9584800063324658\n",
      "Generation 3376: M(n) = 862.6320056992192\n",
      "Generation 3377: p = 0.9584800063324658\n",
      "Generation 3377: M(n) = 862.6320056992192\n",
      "Generation 3378: p = 0.9584800063324658\n",
      "Generation 3378: M(n) = 862.6320056992192\n",
      "Generation 3379: p = 0.9584800063324658\n",
      "Generation 3379: M(n) = 862.6320056992192\n",
      "Generation 3380: p = 0.9584800063324658\n",
      "Generation 3380: M(n) = 862.6320056992192\n",
      "Generation 3381: p = 0.9584800063324658\n",
      "Generation 3381: M(n) = 862.6320056992192\n",
      "Generation 3382: p = 0.9584800063324658\n",
      "Generation 3382: M(n) = 862.6320056992192\n",
      "Generation 3383: p = 0.9584800063324658\n",
      "Generation 3383: M(n) = 862.6320056992192\n",
      "Generation 3384: p = 0.9584800063324658\n",
      "Generation 3384: M(n) = 862.6320056992192\n",
      "Generation 3385: p = 0.9584800063324658\n",
      "Generation 3385: M(n) = 862.6320056992192\n",
      "Generation 3386: p = 0.9584800063324658\n",
      "Generation 3386: M(n) = 862.6320056992192\n",
      "Generation 3387: p = 0.9584800063324658\n",
      "Generation 3387: M(n) = 862.6320056992192\n",
      "Generation 3388: p = 0.9584800063324658\n",
      "Generation 3388: M(n) = 862.6320056992192\n",
      "Generation 3389: p = 0.9584800063324658\n",
      "Generation 3389: M(n) = 862.6320056992192\n",
      "Generation 3390: p = 0.9584800063324658\n",
      "Generation 3390: M(n) = 862.6320056992192\n",
      "Generation 3391: p = 0.9584800063324658\n",
      "Generation 3391: M(n) = 862.6320056992192\n",
      "Generation 3392: p = 0.9584800063324658\n",
      "Generation 3392: M(n) = 862.6320056992192\n",
      "Generation 3393: p = 0.9584800063324658\n",
      "Generation 3393: M(n) = 862.6320056992192\n",
      "Generation 3394: p = 0.9584800063324658\n",
      "Generation 3394: M(n) = 862.6320056992192\n",
      "Generation 3395: p = 0.9584800063324658\n",
      "Generation 3395: M(n) = 862.6320056992192\n",
      "Generation 3396: p = 0.9584800063324658\n",
      "Generation 3396: M(n) = 862.6320056992192\n",
      "Generation 3397: p = 0.9584800063324658\n",
      "Generation 3397: M(n) = 862.6320056992192\n",
      "Generation 3398: p = 0.9584800063324658\n",
      "Generation 3398: M(n) = 862.6320056992192\n",
      "Generation 3399: p = 0.9584800063324658\n",
      "Generation 3399: M(n) = 862.6320056992192\n",
      "Generation 3400: p = 0.9584800063324658\n",
      "Generation 3400: M(n) = 862.6320056992192\n",
      "Generation 3401: p = 0.9584800063324658\n",
      "Generation 3401: M(n) = 862.6320056992192\n",
      "Generation 3402: p = 0.9584800063324658\n",
      "Generation 3402: M(n) = 862.6320056992192\n",
      "Generation 3403: p = 0.9584800063324658\n",
      "Generation 3403: M(n) = 862.6320056992192\n",
      "Generation 3404: p = 0.9584800063324658\n",
      "Generation 3404: M(n) = 862.6320056992192\n",
      "Generation 3405: p = 0.9584800063324658\n",
      "Generation 3405: M(n) = 862.6320056992192\n",
      "Generation 3406: p = 0.9584800063324658\n",
      "Generation 3406: M(n) = 862.6320056992192\n",
      "Generation 3407: p = 0.9584800063324658\n",
      "Generation 3407: M(n) = 862.6320056992192\n",
      "Generation 3408: p = 0.9584800063324658\n",
      "Generation 3408: M(n) = 862.6320056992192\n",
      "Generation 3409: p = 0.9584800063324658\n",
      "Generation 3409: M(n) = 862.6320056992192\n",
      "Generation 3410: p = 0.9584800063324658\n",
      "Generation 3410: M(n) = 862.6320056992192\n",
      "Generation 3411: p = 0.9584800063324658\n",
      "Generation 3411: M(n) = 862.6320056992192\n",
      "Generation 3412: p = 0.9584800063324658\n",
      "Generation 3412: M(n) = 862.6320056992192\n",
      "Generation 3413: p = 0.9584800063324658\n",
      "Generation 3413: M(n) = 862.6320056992192\n",
      "Generation 3414: p = 0.9584800063324658\n",
      "Generation 3414: M(n) = 862.6320056992192\n",
      "Generation 3415: p = 0.9584800063324658\n",
      "Generation 3415: M(n) = 862.6320056992192\n",
      "Generation 3416: p = 0.9584800063324658\n",
      "Generation 3416: M(n) = 862.6320056992192\n",
      "Generation 3417: p = 0.9584800063324658\n",
      "Generation 3417: M(n) = 862.6320056992192\n",
      "Generation 3418: p = 0.9584800063324658\n",
      "Generation 3418: M(n) = 862.6320056992192\n",
      "Generation 3419: p = 0.9584800063324658\n",
      "Generation 3419: M(n) = 862.6320056992192\n",
      "Generation 3420: p = 0.9584800063324658\n",
      "Generation 3420: M(n) = 862.6320056992192\n",
      "Generation 3421: p = 0.9584800063324658\n",
      "Generation 3421: M(n) = 862.6320056992192\n",
      "Generation 3422: p = 0.9584800063324658\n",
      "Generation 3422: M(n) = 862.6320056992192\n",
      "Generation 3423: p = 0.9584800063324658\n",
      "Generation 3423: M(n) = 862.6320056992192\n",
      "Generation 3424: p = 0.9584800063324658\n",
      "Generation 3424: M(n) = 862.6320056992192\n",
      "Generation 3425: p = 0.9584800063324658\n",
      "Generation 3425: M(n) = 862.6320056992192\n",
      "Generation 3426: p = 0.9584800063324658\n",
      "Generation 3426: M(n) = 862.6320056992192\n",
      "Generation 3427: p = 0.9584800063324658\n",
      "Generation 3427: M(n) = 862.6320056992192\n",
      "Generation 3428: p = 0.9584800063324658\n",
      "Generation 3428: M(n) = 862.6320056992192\n",
      "Generation 3429: p = 0.9584800063324658\n",
      "Generation 3429: M(n) = 862.6320056992192\n",
      "Generation 3430: p = 0.9584800063324658\n",
      "Generation 3430: M(n) = 862.6320056992192\n",
      "Generation 3431: p = 0.9584800063324658\n",
      "Generation 3431: M(n) = 862.6320056992192\n",
      "Generation 3432: p = 0.9584800063324658\n",
      "Generation 3432: M(n) = 862.6320056992192\n",
      "Generation 3433: p = 0.9584800063324658\n",
      "Generation 3433: M(n) = 862.6320056992192\n",
      "Generation 3434: p = 0.9584800063324658\n",
      "Generation 3434: M(n) = 862.6320056992192\n",
      "Generation 3435: p = 0.9584800063324658\n",
      "Generation 3435: M(n) = 862.6320056992192\n",
      "Generation 3436: p = 0.9584800063324658\n",
      "Generation 3436: M(n) = 862.6320056992192\n",
      "Generation 3437: p = 0.9584800063324658\n",
      "Generation 3437: M(n) = 862.6320056992192\n",
      "Generation 3438: p = 0.9584800063324658\n",
      "Generation 3438: M(n) = 862.6320056992192\n",
      "Generation 3439: p = 0.9584800063324658\n",
      "Generation 3439: M(n) = 862.6320056992192\n",
      "Generation 3440: p = 0.9584800063324658\n",
      "Generation 3440: M(n) = 862.6320056992192\n",
      "Generation 3441: p = 0.9584800063324658\n",
      "Generation 3441: M(n) = 862.6320056992192\n",
      "Generation 3442: p = 0.9584800063324658\n",
      "Generation 3442: M(n) = 862.6320056992192\n",
      "Generation 3443: p = 0.9584800063324658\n",
      "Generation 3443: M(n) = 862.6320056992192\n",
      "Generation 3444: p = 0.9584800063324658\n",
      "Generation 3444: M(n) = 862.6320056992192\n",
      "Generation 3445: p = 0.9584800063324658\n",
      "Generation 3445: M(n) = 862.6320056992192\n",
      "Generation 3446: p = 0.9584800063324658\n",
      "Generation 3446: M(n) = 862.6320056992192\n",
      "Generation 3447: p = 0.9584800063324658\n",
      "Generation 3447: M(n) = 862.6320056992192\n",
      "Generation 3448: p = 0.9584800063324658\n",
      "Generation 3448: M(n) = 862.6320056992192\n",
      "Generation 3449: p = 0.9584800063324658\n",
      "Generation 3449: M(n) = 862.6320056992192\n",
      "Generation 3450: p = 0.9584800063324658\n",
      "Generation 3450: M(n) = 862.6320056992192\n",
      "Generation 3451: p = 0.9584800063324658\n",
      "Generation 3451: M(n) = 862.6320056992192\n",
      "Generation 3452: p = 0.9584800063324658\n",
      "Generation 3452: M(n) = 862.6320056992192\n",
      "Generation 3453: p = 0.9584800063324658\n",
      "Generation 3453: M(n) = 862.6320056992192\n",
      "Generation 3454: p = 0.9584800063324658\n",
      "Generation 3454: M(n) = 862.6320056992192\n",
      "Generation 3455: p = 0.9584800063324658\n",
      "Generation 3455: M(n) = 862.6320056992192\n",
      "Generation 3456: p = 0.9584800063324658\n",
      "Generation 3456: M(n) = 862.6320056992192\n",
      "Generation 3457: p = 0.9584800063324658\n",
      "Generation 3457: M(n) = 862.6320056992192\n",
      "Generation 3458: p = 0.9584800063324658\n",
      "Generation 3458: M(n) = 862.6320056992192\n",
      "Generation 3459: p = 0.9584800063324658\n",
      "Generation 3459: M(n) = 862.6320056992192\n",
      "Generation 3460: p = 0.9584800063324658\n",
      "Generation 3460: M(n) = 862.6320056992192\n",
      "Generation 3461: p = 0.9584800063324658\n",
      "Generation 3461: M(n) = 862.6320056992192\n",
      "Generation 3462: p = 0.9584800063324658\n",
      "Generation 3462: M(n) = 862.6320056992192\n",
      "Generation 3463: p = 0.9584800063324658\n",
      "Generation 3463: M(n) = 862.6320056992192\n",
      "Generation 3464: p = 0.9584800063324658\n",
      "Generation 3464: M(n) = 862.6320056992192\n",
      "Generation 3465: p = 0.9584800063324658\n",
      "Generation 3465: M(n) = 862.6320056992192\n",
      "Generation 3466: p = 0.9584800063324658\n",
      "Generation 3466: M(n) = 862.6320056992192\n",
      "Generation 3467: p = 0.9584800063324658\n",
      "Generation 3467: M(n) = 862.6320056992192\n",
      "Generation 3468: p = 0.9584800063324658\n",
      "Generation 3468: M(n) = 862.6320056992192\n",
      "Generation 3469: p = 0.9584800063324658\n",
      "Generation 3469: M(n) = 862.6320056992192\n",
      "Generation 3470: p = 0.9584800063324658\n",
      "Generation 3470: M(n) = 862.6320056992192\n",
      "Generation 3471: p = 0.9584800063324658\n",
      "Generation 3471: M(n) = 862.6320056992192\n",
      "Generation 3472: p = 0.9584800063324658\n",
      "Generation 3472: M(n) = 862.6320056992192\n",
      "Generation 3473: p = 0.9584800063324658\n",
      "Generation 3473: M(n) = 862.6320056992192\n",
      "Generation 3474: p = 0.9584800063324658\n",
      "Generation 3474: M(n) = 862.6320056992192\n",
      "Generation 3475: p = 0.9584800063324658\n",
      "Generation 3475: M(n) = 862.6320056992192\n",
      "Generation 3476: p = 0.9584800063324658\n",
      "Generation 3476: M(n) = 862.6320056992192\n",
      "Generation 3477: p = 0.9584800063324658\n",
      "Generation 3477: M(n) = 862.6320056992192\n",
      "Generation 3478: p = 0.9584800063324658\n",
      "Generation 3478: M(n) = 862.6320056992192\n",
      "Generation 3479: p = 0.9584800063324658\n",
      "Generation 3479: M(n) = 862.6320056992192\n",
      "Generation 3480: p = 0.9584800063324658\n",
      "Generation 3480: M(n) = 862.6320056992192\n",
      "Generation 3481: p = 0.9584800063324658\n",
      "Generation 3481: M(n) = 862.6320056992192\n",
      "Generation 3482: p = 0.9584800063324658\n",
      "Generation 3482: M(n) = 862.6320056992192\n",
      "Generation 3483: p = 0.9584800063324658\n",
      "Generation 3483: M(n) = 862.6320056992192\n",
      "Generation 3484: p = 0.9584800063324658\n",
      "Generation 3484: M(n) = 862.6320056992192\n",
      "Generation 3485: p = 0.9584800063324658\n",
      "Generation 3485: M(n) = 862.6320056992192\n",
      "Generation 3486: p = 0.9584800063324658\n",
      "Generation 3486: M(n) = 862.6320056992192\n",
      "Generation 3487: p = 0.9584800063324658\n",
      "Generation 3487: M(n) = 862.6320056992192\n",
      "Generation 3488: p = 0.9584800063324658\n",
      "Generation 3488: M(n) = 862.6320056992192\n",
      "Generation 3489: p = 0.9584800063324658\n",
      "Generation 3489: M(n) = 862.6320056992192\n",
      "Generation 3490: p = 0.9584800063324658\n",
      "Generation 3490: M(n) = 862.6320056992192\n",
      "Generation 3491: p = 0.9584800063324658\n",
      "Generation 3491: M(n) = 862.6320056992192\n",
      "Generation 3492: p = 0.9584800063324658\n",
      "Generation 3492: M(n) = 862.6320056992192\n",
      "Generation 3493: p = 0.9584800063324658\n",
      "Generation 3493: M(n) = 862.6320056992192\n",
      "Generation 3494: p = 0.9584800063324658\n",
      "Generation 3494: M(n) = 862.6320056992192\n",
      "Generation 3495: p = 0.9584800063324658\n",
      "Generation 3495: M(n) = 862.6320056992192\n",
      "Generation 3496: p = 0.9584800063324658\n",
      "Generation 3496: M(n) = 862.6320056992192\n",
      "Generation 3497: p = 0.9584800063324658\n",
      "Generation 3497: M(n) = 862.6320056992192\n",
      "Generation 3498: p = 0.9584800063324658\n",
      "Generation 3498: M(n) = 862.6320056992192\n",
      "Generation 3499: p = 0.9584800063324658\n",
      "Generation 3499: M(n) = 862.6320056992192\n",
      "Generation 3500: p = 0.9584800063324658\n",
      "Generation 3500: M(n) = 862.6320056992192\n",
      "Generation 3501: p = 0.9584800063324658\n",
      "Generation 3501: M(n) = 862.6320056992192\n",
      "Generation 3502: p = 0.9584800063324658\n",
      "Generation 3502: M(n) = 862.6320056992192\n",
      "Generation 3503: p = 0.9584800063324658\n",
      "Generation 3503: M(n) = 862.6320056992192\n",
      "Generation 3504: p = 0.9584800063324658\n",
      "Generation 3504: M(n) = 862.6320056992192\n",
      "Generation 3505: p = 0.9584800063324658\n",
      "Generation 3505: M(n) = 862.6320056992192\n",
      "Generation 3506: p = 0.9584800063324658\n",
      "Generation 3506: M(n) = 862.6320056992192\n",
      "Generation 3507: p = 0.9584800063324658\n",
      "Generation 3507: M(n) = 862.6320056992192\n",
      "Generation 3508: p = 0.9584800063324658\n",
      "Generation 3508: M(n) = 862.6320056992192\n",
      "Generation 3509: p = 0.9584800063324658\n",
      "Generation 3509: M(n) = 862.6320056992192\n",
      "Generation 3510: p = 0.9584800063324658\n",
      "Generation 3510: M(n) = 862.6320056992192\n",
      "Generation 3511: p = 0.9584800063324658\n",
      "Generation 3511: M(n) = 862.6320056992192\n",
      "Generation 3512: p = 0.9584800063324658\n",
      "Generation 3512: M(n) = 862.6320056992192\n",
      "Generation 3513: p = 0.9584800063324658\n",
      "Generation 3513: M(n) = 862.6320056992192\n",
      "Generation 3514: p = 0.9584800063324658\n",
      "Generation 3514: M(n) = 862.6320056992192\n",
      "Generation 3515: p = 0.9584800063324658\n",
      "Generation 3515: M(n) = 862.6320056992192\n",
      "Generation 3516: p = 0.9584800063324658\n",
      "Generation 3516: M(n) = 862.6320056992192\n",
      "Generation 3517: p = 0.9584800063324658\n",
      "Generation 3517: M(n) = 862.6320056992192\n",
      "Generation 3518: p = 0.9584800063324658\n",
      "Generation 3518: M(n) = 862.6320056992192\n",
      "Generation 3519: p = 0.9584800063324658\n",
      "Generation 3519: M(n) = 862.6320056992192\n",
      "Generation 3520: p = 0.9584800063324658\n",
      "Generation 3520: M(n) = 862.6320056992192\n",
      "Generation 3521: p = 0.9584800063324658\n",
      "Generation 3521: M(n) = 862.6320056992192\n",
      "Generation 3522: p = 0.9584800063324658\n",
      "Generation 3522: M(n) = 862.6320056992192\n",
      "Generation 3523: p = 0.9584800063324658\n",
      "Generation 3523: M(n) = 862.6320056992192\n",
      "Generation 3524: p = 0.9584800063324658\n",
      "Generation 3524: M(n) = 862.6320056992192\n",
      "Generation 3525: p = 0.9584800063324658\n",
      "Generation 3525: M(n) = 862.6320056992192\n",
      "Generation 3526: p = 0.9584800063324658\n",
      "Generation 3526: M(n) = 862.6320056992192\n",
      "Generation 3527: p = 0.9584800063324658\n",
      "Generation 3527: M(n) = 862.6320056992192\n",
      "Generation 3528: p = 0.9584800063324658\n",
      "Generation 3528: M(n) = 862.6320056992192\n",
      "Generation 3529: p = 0.9584800063324658\n",
      "Generation 3529: M(n) = 862.6320056992192\n",
      "Generation 3530: p = 0.9584800063324658\n",
      "Generation 3530: M(n) = 862.6320056992192\n",
      "Generation 3531: p = 0.9584800063324658\n",
      "Generation 3531: M(n) = 862.6320056992192\n",
      "Generation 3532: p = 0.9584800063324658\n",
      "Generation 3532: M(n) = 862.6320056992192\n",
      "Generation 3533: p = 0.9584800063324658\n",
      "Generation 3533: M(n) = 862.6320056992192\n",
      "Generation 3534: p = 0.9584800063324658\n",
      "Generation 3534: M(n) = 862.6320056992192\n",
      "Generation 3535: p = 0.9584800063324658\n",
      "Generation 3535: M(n) = 862.6320056992192\n",
      "Generation 3536: p = 0.9584800063324658\n",
      "Generation 3536: M(n) = 862.6320056992192\n",
      "Generation 3537: p = 0.9584800063324658\n",
      "Generation 3537: M(n) = 862.6320056992192\n",
      "Generation 3538: p = 0.9584800063324658\n",
      "Generation 3538: M(n) = 862.6320056992192\n",
      "Generation 3539: p = 0.9584800063324658\n",
      "Generation 3539: M(n) = 862.6320056992192\n",
      "Generation 3540: p = 0.9584800063324658\n",
      "Generation 3540: M(n) = 862.6320056992192\n",
      "Generation 3541: p = 0.9584800063324658\n",
      "Generation 3541: M(n) = 862.6320056992192\n",
      "Generation 3542: p = 0.9584800063324658\n",
      "Generation 3542: M(n) = 862.6320056992192\n",
      "Generation 3543: p = 0.9584800063324658\n",
      "Generation 3543: M(n) = 862.6320056992192\n",
      "Generation 3544: p = 0.9584800063324658\n",
      "Generation 3544: M(n) = 862.6320056992192\n",
      "Generation 3545: p = 0.9584800063324658\n",
      "Generation 3545: M(n) = 862.6320056992192\n",
      "Generation 3546: p = 0.9584800063324658\n",
      "Generation 3546: M(n) = 862.6320056992192\n",
      "Generation 3547: p = 0.9584800063324658\n",
      "Generation 3547: M(n) = 862.6320056992192\n",
      "Generation 3548: p = 0.9584800063324658\n",
      "Generation 3548: M(n) = 862.6320056992192\n",
      "Generation 3549: p = 0.9584800063324658\n",
      "Generation 3549: M(n) = 862.6320056992192\n",
      "Generation 3550: p = 0.9584800063324658\n",
      "Generation 3550: M(n) = 862.6320056992192\n",
      "Generation 3551: p = 0.9584800063324658\n",
      "Generation 3551: M(n) = 862.6320056992192\n",
      "Generation 3552: p = 0.9584800063324658\n",
      "Generation 3552: M(n) = 862.6320056992192\n",
      "Generation 3553: p = 0.9584800063324658\n",
      "Generation 3553: M(n) = 862.6320056992192\n",
      "Generation 3554: p = 0.9584800063324658\n",
      "Generation 3554: M(n) = 862.6320056992192\n",
      "Generation 3555: p = 0.9584800063324658\n",
      "Generation 3555: M(n) = 862.6320056992192\n",
      "Generation 3556: p = 0.9584800063324658\n",
      "Generation 3556: M(n) = 862.6320056992192\n",
      "Generation 3557: p = 0.9584800063324658\n",
      "Generation 3557: M(n) = 862.6320056992192\n",
      "Generation 3558: p = 0.9584800063324658\n",
      "Generation 3558: M(n) = 862.6320056992192\n",
      "Generation 3559: p = 0.9584800063324658\n",
      "Generation 3559: M(n) = 862.6320056992192\n",
      "Generation 3560: p = 0.9584800063324658\n",
      "Generation 3560: M(n) = 862.6320056992192\n",
      "Generation 3561: p = 0.9584800063324658\n",
      "Generation 3561: M(n) = 862.6320056992192\n",
      "Generation 3562: p = 0.9584800063324658\n",
      "Generation 3562: M(n) = 862.6320056992192\n",
      "Generation 3563: p = 0.9584800063324658\n",
      "Generation 3563: M(n) = 862.6320056992192\n",
      "Generation 3564: p = 0.9584800063324658\n",
      "Generation 3564: M(n) = 862.6320056992192\n",
      "Generation 3565: p = 0.9584800063324658\n",
      "Generation 3565: M(n) = 862.6320056992192\n",
      "Generation 3566: p = 0.9584800063324658\n",
      "Generation 3566: M(n) = 862.6320056992192\n",
      "Generation 3567: p = 0.9584800063324658\n",
      "Generation 3567: M(n) = 862.6320056992192\n",
      "Generation 3568: p = 0.9584800063324658\n",
      "Generation 3568: M(n) = 862.6320056992192\n",
      "Generation 3569: p = 0.9584800063324658\n",
      "Generation 3569: M(n) = 862.6320056992192\n",
      "Generation 3570: p = 0.9584800063324658\n",
      "Generation 3570: M(n) = 862.6320056992192\n",
      "Generation 3571: p = 0.9584800063324658\n",
      "Generation 3571: M(n) = 862.6320056992192\n",
      "Generation 3572: p = 0.9584800063324658\n",
      "Generation 3572: M(n) = 862.6320056992192\n",
      "Generation 3573: p = 0.9584800063324658\n",
      "Generation 3573: M(n) = 862.6320056992192\n",
      "Generation 3574: p = 0.9584800063324658\n",
      "Generation 3574: M(n) = 862.6320056992192\n",
      "Generation 3575: p = 0.9584800063324658\n",
      "Generation 3575: M(n) = 862.6320056992192\n",
      "Generation 3576: p = 0.9584800063324658\n",
      "Generation 3576: M(n) = 862.6320056992192\n",
      "Generation 3577: p = 0.9584800063324658\n",
      "Generation 3577: M(n) = 862.6320056992192\n",
      "Generation 3578: p = 0.9584800063324658\n",
      "Generation 3578: M(n) = 862.6320056992192\n",
      "Generation 3579: p = 0.9584800063324658\n",
      "Generation 3579: M(n) = 862.6320056992192\n",
      "Generation 3580: p = 0.9584800063324658\n",
      "Generation 3580: M(n) = 862.6320056992192\n",
      "Generation 3581: p = 0.9584800063324658\n",
      "Generation 3581: M(n) = 862.6320056992192\n",
      "Generation 3582: p = 0.9584800063324658\n",
      "Generation 3582: M(n) = 862.6320056992192\n",
      "Generation 3583: p = 0.9584800063324658\n",
      "Generation 3583: M(n) = 862.6320056992192\n",
      "Generation 3584: p = 0.9584800063324658\n",
      "Generation 3584: M(n) = 862.6320056992192\n",
      "Generation 3585: p = 0.9584800063324658\n",
      "Generation 3585: M(n) = 862.6320056992192\n",
      "Generation 3586: p = 0.9584800063324658\n",
      "Generation 3586: M(n) = 862.6320056992192\n",
      "Generation 3587: p = 0.9584800063324658\n",
      "Generation 3587: M(n) = 862.6320056992192\n",
      "Generation 3588: p = 0.9584800063324658\n",
      "Generation 3588: M(n) = 862.6320056992192\n",
      "Generation 3589: p = 0.9584800063324658\n",
      "Generation 3589: M(n) = 862.6320056992192\n",
      "Generation 3590: p = 0.9584800063324658\n",
      "Generation 3590: M(n) = 862.6320056992192\n",
      "Generation 3591: p = 0.9584800063324658\n",
      "Generation 3591: M(n) = 862.6320056992192\n",
      "Generation 3592: p = 0.9584800063324658\n",
      "Generation 3592: M(n) = 862.6320056992192\n",
      "Generation 3593: p = 0.9584800063324658\n",
      "Generation 3593: M(n) = 862.6320056992192\n",
      "Generation 3594: p = 0.9584800063324658\n",
      "Generation 3594: M(n) = 862.6320056992192\n",
      "Generation 3595: p = 0.9584800063324658\n",
      "Generation 3595: M(n) = 862.6320056992192\n",
      "Generation 3596: p = 0.9584800063324658\n",
      "Generation 3596: M(n) = 862.6320056992192\n",
      "Generation 3597: p = 0.9584800063324658\n",
      "Generation 3597: M(n) = 862.6320056992192\n",
      "Generation 3598: p = 0.9584800063324658\n",
      "Generation 3598: M(n) = 862.6320056992192\n",
      "Generation 3599: p = 0.9584800063324658\n",
      "Generation 3599: M(n) = 862.6320056992192\n",
      "Generation 3600: p = 0.9584800063324658\n",
      "Generation 3600: M(n) = 862.6320056992192\n",
      "Generation 3601: p = 0.9584800063324658\n",
      "Generation 3601: M(n) = 862.6320056992192\n",
      "Generation 3602: p = 0.9584800063324658\n",
      "Generation 3602: M(n) = 862.6320056992192\n",
      "Generation 3603: p = 0.9584800063324658\n",
      "Generation 3603: M(n) = 862.6320056992192\n",
      "Generation 3604: p = 0.9584800063324658\n",
      "Generation 3604: M(n) = 862.6320056992192\n",
      "Generation 3605: p = 0.9584800063324658\n",
      "Generation 3605: M(n) = 862.6320056992192\n",
      "Generation 3606: p = 0.9584800063324658\n",
      "Generation 3606: M(n) = 862.6320056992192\n",
      "Generation 3607: p = 0.9584800063324658\n",
      "Generation 3607: M(n) = 862.6320056992192\n",
      "Generation 3608: p = 0.9584800063324658\n",
      "Generation 3608: M(n) = 862.6320056992192\n",
      "Generation 3609: p = 0.9584800063324658\n",
      "Generation 3609: M(n) = 862.6320056992192\n",
      "Generation 3610: p = 0.9584800063324658\n",
      "Generation 3610: M(n) = 862.6320056992192\n",
      "Generation 3611: p = 0.9584800063324658\n",
      "Generation 3611: M(n) = 862.6320056992192\n",
      "Generation 3612: p = 0.9584800063324658\n",
      "Generation 3612: M(n) = 862.6320056992192\n",
      "Generation 3613: p = 0.9584800063324658\n",
      "Generation 3613: M(n) = 862.6320056992192\n",
      "Generation 3614: p = 0.9584800063324658\n",
      "Generation 3614: M(n) = 862.6320056992192\n",
      "Generation 3615: p = 0.9584800063324658\n",
      "Generation 3615: M(n) = 862.6320056992192\n",
      "Generation 3616: p = 0.9584800063324658\n",
      "Generation 3616: M(n) = 862.6320056992192\n",
      "Generation 3617: p = 0.9584800063324658\n",
      "Generation 3617: M(n) = 862.6320056992192\n",
      "Generation 3618: p = 0.9584800063324658\n",
      "Generation 3618: M(n) = 862.6320056992192\n",
      "Generation 3619: p = 0.9584800063324658\n",
      "Generation 3619: M(n) = 862.6320056992192\n",
      "Generation 3620: p = 0.9584800063324658\n",
      "Generation 3620: M(n) = 862.6320056992192\n",
      "Generation 3621: p = 0.9584800063324658\n",
      "Generation 3621: M(n) = 862.6320056992192\n",
      "Generation 3622: p = 0.9584800063324658\n",
      "Generation 3622: M(n) = 862.6320056992192\n",
      "Generation 3623: p = 0.9584800063324658\n",
      "Generation 3623: M(n) = 862.6320056992192\n",
      "Generation 3624: p = 0.9584800063324658\n",
      "Generation 3624: M(n) = 862.6320056992192\n",
      "Generation 3625: p = 0.9584800063324658\n",
      "Generation 3625: M(n) = 862.6320056992192\n",
      "Generation 3626: p = 0.9584800063324658\n",
      "Generation 3626: M(n) = 862.6320056992192\n",
      "Generation 3627: p = 0.9584800063324658\n",
      "Generation 3627: M(n) = 862.6320056992192\n",
      "Generation 3628: p = 0.9584800063324658\n",
      "Generation 3628: M(n) = 862.6320056992192\n",
      "Generation 3629: p = 0.9584800063324658\n",
      "Generation 3629: M(n) = 862.6320056992192\n",
      "Generation 3630: p = 0.9584800063324658\n",
      "Generation 3630: M(n) = 862.6320056992192\n",
      "Generation 3631: p = 0.9584800063324658\n",
      "Generation 3631: M(n) = 862.6320056992192\n",
      "Generation 3632: p = 0.9584800063324658\n",
      "Generation 3632: M(n) = 862.6320056992192\n",
      "Generation 3633: p = 0.9584800063324658\n",
      "Generation 3633: M(n) = 862.6320056992192\n",
      "Generation 3634: p = 0.9584800063324658\n",
      "Generation 3634: M(n) = 862.6320056992192\n",
      "Generation 3635: p = 0.9584800063324658\n",
      "Generation 3635: M(n) = 862.6320056992192\n",
      "Generation 3636: p = 0.9584800063324658\n",
      "Generation 3636: M(n) = 862.6320056992192\n",
      "Generation 3637: p = 0.9584800063324658\n",
      "Generation 3637: M(n) = 862.6320056992192\n",
      "Generation 3638: p = 0.9584800063324658\n",
      "Generation 3638: M(n) = 862.6320056992192\n",
      "Generation 3639: p = 0.9584800063324658\n",
      "Generation 3639: M(n) = 862.6320056992192\n",
      "Generation 3640: p = 0.9584800063324658\n",
      "Generation 3640: M(n) = 862.6320056992192\n",
      "Generation 3641: p = 0.9584800063324658\n",
      "Generation 3641: M(n) = 862.6320056992192\n",
      "Generation 3642: p = 0.9584800063324658\n",
      "Generation 3642: M(n) = 862.6320056992192\n",
      "Generation 3643: p = 0.9584800063324658\n",
      "Generation 3643: M(n) = 862.6320056992192\n",
      "Generation 3644: p = 0.9584800063324658\n",
      "Generation 3644: M(n) = 862.6320056992192\n",
      "Generation 3645: p = 0.9584800063324658\n",
      "Generation 3645: M(n) = 862.6320056992192\n",
      "Generation 3646: p = 0.9584800063324658\n",
      "Generation 3646: M(n) = 862.6320056992192\n",
      "Generation 3647: p = 0.9584800063324658\n",
      "Generation 3647: M(n) = 862.6320056992192\n",
      "Generation 3648: p = 0.9584800063324658\n",
      "Generation 3648: M(n) = 862.6320056992192\n",
      "Generation 3649: p = 0.9584800063324658\n",
      "Generation 3649: M(n) = 862.6320056992192\n",
      "Generation 3650: p = 0.9584800063324658\n",
      "Generation 3650: M(n) = 862.6320056992192\n",
      "Generation 3651: p = 0.9584800063324658\n",
      "Generation 3651: M(n) = 862.6320056992192\n",
      "Generation 3652: p = 0.9584800063324658\n",
      "Generation 3652: M(n) = 862.6320056992192\n",
      "Generation 3653: p = 0.9584800063324658\n",
      "Generation 3653: M(n) = 862.6320056992192\n",
      "Generation 3654: p = 0.9584800063324658\n",
      "Generation 3654: M(n) = 862.6320056992192\n",
      "Generation 3655: p = 0.9584800063324658\n",
      "Generation 3655: M(n) = 862.6320056992192\n",
      "Generation 3656: p = 0.9584800063324658\n",
      "Generation 3656: M(n) = 862.6320056992192\n",
      "Generation 3657: p = 0.9584800063324658\n",
      "Generation 3657: M(n) = 862.6320056992192\n",
      "Generation 3658: p = 0.9584800063324658\n",
      "Generation 3658: M(n) = 862.6320056992192\n",
      "Generation 3659: p = 0.9584800063324658\n",
      "Generation 3659: M(n) = 862.6320056992192\n",
      "Generation 3660: p = 0.9584800063324658\n",
      "Generation 3660: M(n) = 862.6320056992192\n",
      "Generation 3661: p = 0.9584800063324658\n",
      "Generation 3661: M(n) = 862.6320056992192\n",
      "Generation 3662: p = 0.9584800063324658\n",
      "Generation 3662: M(n) = 862.6320056992192\n",
      "Generation 3663: p = 0.9584800063324658\n",
      "Generation 3663: M(n) = 862.6320056992192\n",
      "Generation 3664: p = 0.9584800063324658\n",
      "Generation 3664: M(n) = 862.6320056992192\n",
      "Generation 3665: p = 0.9584800063324658\n",
      "Generation 3665: M(n) = 862.6320056992192\n",
      "Generation 3666: p = 0.9584800063324658\n",
      "Generation 3666: M(n) = 862.6320056992192\n",
      "Generation 3667: p = 0.9584800063324658\n",
      "Generation 3667: M(n) = 862.6320056992192\n",
      "Generation 3668: p = 0.9584800063324658\n",
      "Generation 3668: M(n) = 862.6320056992192\n",
      "Generation 3669: p = 0.9584800063324658\n",
      "Generation 3669: M(n) = 862.6320056992192\n",
      "Generation 3670: p = 0.9584800063324658\n",
      "Generation 3670: M(n) = 862.6320056992192\n",
      "Generation 3671: p = 0.9584800063324658\n",
      "Generation 3671: M(n) = 862.6320056992192\n",
      "Generation 3672: p = 0.9584800063324658\n",
      "Generation 3672: M(n) = 862.6320056992192\n",
      "Generation 3673: p = 0.9584800063324658\n",
      "Generation 3673: M(n) = 862.6320056992192\n",
      "Generation 3674: p = 0.9584800063324658\n",
      "Generation 3674: M(n) = 862.6320056992192\n",
      "Generation 3675: p = 0.9584800063324658\n",
      "Generation 3675: M(n) = 862.6320056992192\n",
      "Generation 3676: p = 0.9584800063324658\n",
      "Generation 3676: M(n) = 862.6320056992192\n",
      "Generation 3677: p = 0.9584800063324658\n",
      "Generation 3677: M(n) = 862.6320056992192\n",
      "Generation 3678: p = 0.9584800063324658\n",
      "Generation 3678: M(n) = 862.6320056992192\n",
      "Generation 3679: p = 0.9584800063324658\n",
      "Generation 3679: M(n) = 862.6320056992192\n",
      "Generation 3680: p = 0.9584800063324658\n",
      "Generation 3680: M(n) = 862.6320056992192\n",
      "Generation 3681: p = 0.9584800063324658\n",
      "Generation 3681: M(n) = 862.6320056992192\n",
      "Generation 3682: p = 0.9584800063324658\n",
      "Generation 3682: M(n) = 862.6320056992192\n",
      "Generation 3683: p = 0.9584800063324658\n",
      "Generation 3683: M(n) = 862.6320056992192\n",
      "Generation 3684: p = 0.9584800063324658\n",
      "Generation 3684: M(n) = 862.6320056992192\n",
      "Generation 3685: p = 0.9584800063324658\n",
      "Generation 3685: M(n) = 862.6320056992192\n",
      "Generation 3686: p = 0.9584800063324658\n",
      "Generation 3686: M(n) = 862.6320056992192\n",
      "Generation 3687: p = 0.9584800063324658\n",
      "Generation 3687: M(n) = 862.6320056992192\n",
      "Generation 3688: p = 0.9584800063324658\n",
      "Generation 3688: M(n) = 862.6320056992192\n",
      "Generation 3689: p = 0.9584800063324658\n",
      "Generation 3689: M(n) = 862.6320056992192\n",
      "Generation 3690: p = 0.9584800063324658\n",
      "Generation 3690: M(n) = 862.6320056992192\n",
      "Generation 3691: p = 0.9584800063324658\n",
      "Generation 3691: M(n) = 862.6320056992192\n",
      "Generation 3692: p = 0.9584800063324658\n",
      "Generation 3692: M(n) = 862.6320056992192\n",
      "Generation 3693: p = 0.9584800063324658\n",
      "Generation 3693: M(n) = 862.6320056992192\n",
      "Generation 3694: p = 0.9584800063324658\n",
      "Generation 3694: M(n) = 862.6320056992192\n",
      "Generation 3695: p = 0.9584800063324658\n",
      "Generation 3695: M(n) = 862.6320056992192\n",
      "Generation 3696: p = 0.9584800063324658\n",
      "Generation 3696: M(n) = 862.6320056992192\n",
      "Generation 3697: p = 0.9584800063324658\n",
      "Generation 3697: M(n) = 862.6320056992192\n",
      "Generation 3698: p = 0.9584800063324658\n",
      "Generation 3698: M(n) = 862.6320056992192\n",
      "Generation 3699: p = 0.9584800063324658\n",
      "Generation 3699: M(n) = 862.6320056992192\n",
      "Generation 3700: p = 0.9584800063324658\n",
      "Generation 3700: M(n) = 862.6320056992192\n",
      "Generation 3701: p = 0.9584800063324658\n",
      "Generation 3701: M(n) = 862.6320056992192\n",
      "Generation 3702: p = 0.9584800063324658\n",
      "Generation 3702: M(n) = 862.6320056992192\n",
      "Generation 3703: p = 0.9584800063324658\n",
      "Generation 3703: M(n) = 862.6320056992192\n",
      "Generation 3704: p = 0.9584800063324658\n",
      "Generation 3704: M(n) = 862.6320056992192\n",
      "Generation 3705: p = 0.9584800063324658\n",
      "Generation 3705: M(n) = 862.6320056992192\n",
      "Generation 3706: p = 0.9584800063324658\n",
      "Generation 3706: M(n) = 862.6320056992192\n",
      "Generation 3707: p = 0.9584800063324658\n",
      "Generation 3707: M(n) = 862.6320056992192\n",
      "Generation 3708: p = 0.9584800063324658\n",
      "Generation 3708: M(n) = 862.6320056992192\n",
      "Generation 3709: p = 0.9584800063324658\n",
      "Generation 3709: M(n) = 862.6320056992192\n",
      "Generation 3710: p = 0.9584800063324658\n",
      "Generation 3710: M(n) = 862.6320056992192\n",
      "Generation 3711: p = 0.9584800063324658\n",
      "Generation 3711: M(n) = 862.6320056992192\n",
      "Generation 3712: p = 0.9584800063324658\n",
      "Generation 3712: M(n) = 862.6320056992192\n",
      "Generation 3713: p = 0.9584800063324658\n",
      "Generation 3713: M(n) = 862.6320056992192\n",
      "Generation 3714: p = 0.9584800063324658\n",
      "Generation 3714: M(n) = 862.6320056992192\n",
      "Generation 3715: p = 0.9584800063324658\n",
      "Generation 3715: M(n) = 862.6320056992192\n",
      "Generation 3716: p = 0.9584800063324658\n",
      "Generation 3716: M(n) = 862.6320056992192\n",
      "Generation 3717: p = 0.9584800063324658\n",
      "Generation 3717: M(n) = 862.6320056992192\n",
      "Generation 3718: p = 0.9584800063324658\n",
      "Generation 3718: M(n) = 862.6320056992192\n",
      "Generation 3719: p = 0.9584800063324658\n",
      "Generation 3719: M(n) = 862.6320056992192\n",
      "Generation 3720: p = 0.9584800063324658\n",
      "Generation 3720: M(n) = 862.6320056992192\n",
      "Generation 3721: p = 0.9584800063324658\n",
      "Generation 3721: M(n) = 862.6320056992192\n",
      "Generation 3722: p = 0.9584800063324658\n",
      "Generation 3722: M(n) = 862.6320056992192\n",
      "Generation 3723: p = 0.9584800063324658\n",
      "Generation 3723: M(n) = 862.6320056992192\n",
      "Generation 3724: p = 0.9584800063324658\n",
      "Generation 3724: M(n) = 862.6320056992192\n",
      "Generation 3725: p = 0.9584800063324658\n",
      "Generation 3725: M(n) = 862.6320056992192\n",
      "Generation 3726: p = 0.9584800063324658\n",
      "Generation 3726: M(n) = 862.6320056992192\n",
      "Generation 3727: p = 0.9584800063324658\n",
      "Generation 3727: M(n) = 862.6320056992192\n",
      "Generation 3728: p = 0.9584800063324658\n",
      "Generation 3728: M(n) = 862.6320056992192\n",
      "Generation 3729: p = 0.9584800063324658\n",
      "Generation 3729: M(n) = 862.6320056992192\n",
      "Generation 3730: p = 0.9584800063324658\n",
      "Generation 3730: M(n) = 862.6320056992192\n",
      "Generation 3731: p = 0.9584800063324658\n",
      "Generation 3731: M(n) = 862.6320056992192\n",
      "Generation 3732: p = 0.9584800063324658\n",
      "Generation 3732: M(n) = 862.6320056992192\n",
      "Generation 3733: p = 0.9584800063324658\n",
      "Generation 3733: M(n) = 862.6320056992192\n",
      "Generation 3734: p = 0.9584800063324658\n",
      "Generation 3734: M(n) = 862.6320056992192\n",
      "Generation 3735: p = 0.9584800063324658\n",
      "Generation 3735: M(n) = 862.6320056992192\n",
      "Generation 3736: p = 0.9584800063324658\n",
      "Generation 3736: M(n) = 862.6320056992192\n",
      "Generation 3737: p = 0.9584800063324658\n",
      "Generation 3737: M(n) = 862.6320056992192\n",
      "Generation 3738: p = 0.9584800063324658\n",
      "Generation 3738: M(n) = 862.6320056992192\n",
      "Generation 3739: p = 0.9584800063324658\n",
      "Generation 3739: M(n) = 862.6320056992192\n",
      "Generation 3740: p = 0.9584800063324658\n",
      "Generation 3740: M(n) = 862.6320056992192\n",
      "Generation 3741: p = 0.9584800063324658\n",
      "Generation 3741: M(n) = 862.6320056992192\n",
      "Generation 3742: p = 0.9584800063324658\n",
      "Generation 3742: M(n) = 862.6320056992192\n",
      "Generation 3743: p = 0.9584800063324658\n",
      "Generation 3743: M(n) = 862.6320056992192\n",
      "Generation 3744: p = 0.9584800063324658\n",
      "Generation 3744: M(n) = 862.6320056992192\n",
      "Generation 3745: p = 0.9584800063324658\n",
      "Generation 3745: M(n) = 862.6320056992192\n",
      "Generation 3746: p = 0.9584800063324658\n",
      "Generation 3746: M(n) = 862.6320056992192\n",
      "Generation 3747: p = 0.9584800063324658\n",
      "Generation 3747: M(n) = 862.6320056992192\n",
      "Generation 3748: p = 0.9584800063324658\n",
      "Generation 3748: M(n) = 862.6320056992192\n",
      "Generation 3749: p = 0.9584800063324658\n",
      "Generation 3749: M(n) = 862.6320056992192\n",
      "Generation 3750: p = 0.9584800063324658\n",
      "Generation 3750: M(n) = 862.6320056992192\n",
      "Generation 3751: p = 0.9584800063324658\n",
      "Generation 3751: M(n) = 862.6320056992192\n",
      "Generation 3752: p = 0.9584800063324658\n",
      "Generation 3752: M(n) = 862.6320056992192\n",
      "Generation 3753: p = 0.9584800063324658\n",
      "Generation 3753: M(n) = 862.6320056992192\n",
      "Generation 3754: p = 0.9584800063324658\n",
      "Generation 3754: M(n) = 862.6320056992192\n",
      "Generation 3755: p = 0.9584800063324658\n",
      "Generation 3755: M(n) = 862.6320056992192\n",
      "Generation 3756: p = 0.9584800063324658\n",
      "Generation 3756: M(n) = 862.6320056992192\n",
      "Generation 3757: p = 0.9584800063324658\n",
      "Generation 3757: M(n) = 862.6320056992192\n",
      "Generation 3758: p = 0.9584800063324658\n",
      "Generation 3758: M(n) = 862.6320056992192\n",
      "Generation 3759: p = 0.9584800063324658\n",
      "Generation 3759: M(n) = 862.6320056992192\n",
      "Generation 3760: p = 0.9584800063324658\n",
      "Generation 3760: M(n) = 862.6320056992192\n",
      "Generation 3761: p = 0.9584800063324658\n",
      "Generation 3761: M(n) = 862.6320056992192\n",
      "Generation 3762: p = 0.9584800063324658\n",
      "Generation 3762: M(n) = 862.6320056992192\n",
      "Generation 3763: p = 0.9584800063324658\n",
      "Generation 3763: M(n) = 862.6320056992192\n",
      "Generation 3764: p = 0.9584800063324658\n",
      "Generation 3764: M(n) = 862.6320056992192\n",
      "Generation 3765: p = 0.9584800063324658\n",
      "Generation 3765: M(n) = 862.6320056992192\n",
      "Generation 3766: p = 0.9584800063324658\n",
      "Generation 3766: M(n) = 862.6320056992192\n",
      "Generation 3767: p = 0.9584800063324658\n",
      "Generation 3767: M(n) = 862.6320056992192\n",
      "Generation 3768: p = 0.9584800063324658\n",
      "Generation 3768: M(n) = 862.6320056992192\n",
      "Generation 3769: p = 0.9584800063324658\n",
      "Generation 3769: M(n) = 862.6320056992192\n",
      "Generation 3770: p = 0.9584800063324658\n",
      "Generation 3770: M(n) = 862.6320056992192\n",
      "Generation 3771: p = 0.9584800063324658\n",
      "Generation 3771: M(n) = 862.6320056992192\n",
      "Generation 3772: p = 0.9584800063324658\n",
      "Generation 3772: M(n) = 862.6320056992192\n",
      "Generation 3773: p = 0.9584800063324658\n",
      "Generation 3773: M(n) = 862.6320056992192\n",
      "Generation 3774: p = 0.9584800063324658\n",
      "Generation 3774: M(n) = 862.6320056992192\n",
      "Generation 3775: p = 0.9584800063324658\n",
      "Generation 3775: M(n) = 862.6320056992192\n",
      "Generation 3776: p = 0.9584800063324658\n",
      "Generation 3776: M(n) = 862.6320056992192\n",
      "Generation 3777: p = 0.9584800063324658\n",
      "Generation 3777: M(n) = 862.6320056992192\n",
      "Generation 3778: p = 0.9584800063324658\n",
      "Generation 3778: M(n) = 862.6320056992192\n",
      "Generation 3779: p = 0.9584800063324658\n",
      "Generation 3779: M(n) = 862.6320056992192\n",
      "Generation 3780: p = 0.9584800063324658\n",
      "Generation 3780: M(n) = 862.6320056992192\n",
      "Generation 3781: p = 0.9584800063324658\n",
      "Generation 3781: M(n) = 862.6320056992192\n",
      "Generation 3782: p = 0.9584800063324658\n",
      "Generation 3782: M(n) = 862.6320056992192\n",
      "Generation 3783: p = 0.9584800063324658\n",
      "Generation 3783: M(n) = 862.6320056992192\n",
      "Generation 3784: p = 0.9584800063324658\n",
      "Generation 3784: M(n) = 862.6320056992192\n",
      "Generation 3785: p = 0.9584800063324658\n",
      "Generation 3785: M(n) = 862.6320056992192\n",
      "Generation 3786: p = 0.9584800063324658\n",
      "Generation 3786: M(n) = 862.6320056992192\n",
      "Generation 3787: p = 0.9584800063324658\n",
      "Generation 3787: M(n) = 862.6320056992192\n",
      "Generation 3788: p = 0.9584800063324658\n",
      "Generation 3788: M(n) = 862.6320056992192\n",
      "Generation 3789: p = 0.9584800063324658\n",
      "Generation 3789: M(n) = 862.6320056992192\n",
      "Generation 3790: p = 0.9584800063324658\n",
      "Generation 3790: M(n) = 862.6320056992192\n",
      "Generation 3791: p = 0.9584800063324658\n",
      "Generation 3791: M(n) = 862.6320056992192\n",
      "Generation 3792: p = 0.9584800063324658\n",
      "Generation 3792: M(n) = 862.6320056992192\n",
      "Generation 3793: p = 0.9584800063324658\n",
      "Generation 3793: M(n) = 862.6320056992192\n",
      "Generation 3794: p = 0.9584800063324658\n",
      "Generation 3794: M(n) = 862.6320056992192\n",
      "Generation 3795: p = 0.9584800063324658\n",
      "Generation 3795: M(n) = 862.6320056992192\n",
      "Generation 3796: p = 0.9584800063324658\n",
      "Generation 3796: M(n) = 862.6320056992192\n",
      "Generation 3797: p = 0.9584800063324658\n",
      "Generation 3797: M(n) = 862.6320056992192\n",
      "Generation 3798: p = 0.9584800063324658\n",
      "Generation 3798: M(n) = 862.6320056992192\n",
      "Generation 3799: p = 0.9584800063324658\n",
      "Generation 3799: M(n) = 862.6320056992192\n",
      "Generation 3800: p = 0.9584800063324658\n",
      "Generation 3800: M(n) = 862.6320056992192\n",
      "Generation 3801: p = 0.9584800063324658\n",
      "Generation 3801: M(n) = 862.6320056992192\n",
      "Generation 3802: p = 0.9584800063324658\n",
      "Generation 3802: M(n) = 862.6320056992192\n",
      "Generation 3803: p = 0.9584800063324658\n",
      "Generation 3803: M(n) = 862.6320056992192\n",
      "Generation 3804: p = 0.9584800063324658\n",
      "Generation 3804: M(n) = 862.6320056992192\n",
      "Generation 3805: p = 0.9584800063324658\n",
      "Generation 3805: M(n) = 862.6320056992192\n",
      "Generation 3806: p = 0.9584800063324658\n",
      "Generation 3806: M(n) = 862.6320056992192\n",
      "Generation 3807: p = 0.9584800063324658\n",
      "Generation 3807: M(n) = 862.6320056992192\n",
      "Generation 3808: p = 0.9584800063324658\n",
      "Generation 3808: M(n) = 862.6320056992192\n",
      "Generation 3809: p = 0.9584800063324658\n",
      "Generation 3809: M(n) = 862.6320056992192\n",
      "Generation 3810: p = 0.9584800063324658\n",
      "Generation 3810: M(n) = 862.6320056992192\n",
      "Generation 3811: p = 0.9584800063324658\n",
      "Generation 3811: M(n) = 862.6320056992192\n",
      "Generation 3812: p = 0.9584800063324658\n",
      "Generation 3812: M(n) = 862.6320056992192\n",
      "Generation 3813: p = 0.9584800063324658\n",
      "Generation 3813: M(n) = 862.6320056992192\n",
      "Generation 3814: p = 0.9584800063324658\n",
      "Generation 3814: M(n) = 862.6320056992192\n",
      "Generation 3815: p = 0.9584800063324658\n",
      "Generation 3815: M(n) = 862.6320056992192\n",
      "Generation 3816: p = 0.9584800063324658\n",
      "Generation 3816: M(n) = 862.6320056992192\n",
      "Generation 3817: p = 0.9584800063324658\n",
      "Generation 3817: M(n) = 862.6320056992192\n",
      "Generation 3818: p = 0.9584800063324658\n",
      "Generation 3818: M(n) = 862.6320056992192\n",
      "Generation 3819: p = 0.9584800063324658\n",
      "Generation 3819: M(n) = 862.6320056992192\n",
      "Generation 3820: p = 0.9584800063324658\n",
      "Generation 3820: M(n) = 862.6320056992192\n",
      "Generation 3821: p = 0.9584800063324658\n",
      "Generation 3821: M(n) = 862.6320056992192\n",
      "Generation 3822: p = 0.9584800063324658\n",
      "Generation 3822: M(n) = 862.6320056992192\n",
      "Generation 3823: p = 0.9584800063324658\n",
      "Generation 3823: M(n) = 862.6320056992192\n",
      "Generation 3824: p = 0.9584800063324658\n",
      "Generation 3824: M(n) = 862.6320056992192\n",
      "Generation 3825: p = 0.9584800063324658\n",
      "Generation 3825: M(n) = 862.6320056992192\n",
      "Generation 3826: p = 0.9584800063324658\n",
      "Generation 3826: M(n) = 862.6320056992192\n",
      "Generation 3827: p = 0.9584800063324658\n",
      "Generation 3827: M(n) = 862.6320056992192\n",
      "Generation 3828: p = 0.9584800063324658\n",
      "Generation 3828: M(n) = 862.6320056992192\n",
      "Generation 3829: p = 0.9584800063324658\n",
      "Generation 3829: M(n) = 862.6320056992192\n",
      "Generation 3830: p = 0.9584800063324658\n",
      "Generation 3830: M(n) = 862.6320056992192\n",
      "Generation 3831: p = 0.9584800063324658\n",
      "Generation 3831: M(n) = 862.6320056992192\n",
      "Generation 3832: p = 0.9584800063324658\n",
      "Generation 3832: M(n) = 862.6320056992192\n",
      "Generation 3833: p = 0.9584800063324658\n",
      "Generation 3833: M(n) = 862.6320056992192\n",
      "Generation 3834: p = 0.9584800063324658\n",
      "Generation 3834: M(n) = 862.6320056992192\n",
      "Generation 3835: p = 0.9584800063324658\n",
      "Generation 3835: M(n) = 862.6320056992192\n",
      "Generation 3836: p = 0.9584800063324658\n",
      "Generation 3836: M(n) = 862.6320056992192\n",
      "Generation 3837: p = 0.9584800063324658\n",
      "Generation 3837: M(n) = 862.6320056992192\n",
      "Generation 3838: p = 0.9584800063324658\n",
      "Generation 3838: M(n) = 862.6320056992192\n",
      "Generation 3839: p = 0.9584800063324658\n",
      "Generation 3839: M(n) = 862.6320056992192\n",
      "Generation 3840: p = 0.9584800063324658\n",
      "Generation 3840: M(n) = 862.6320056992192\n",
      "Generation 3841: p = 0.9584800063324658\n",
      "Generation 3841: M(n) = 862.6320056992192\n",
      "Generation 3842: p = 0.9584800063324658\n",
      "Generation 3842: M(n) = 862.6320056992192\n",
      "Generation 3843: p = 0.9584800063324658\n",
      "Generation 3843: M(n) = 862.6320056992192\n",
      "Generation 3844: p = 0.9584800063324658\n",
      "Generation 3844: M(n) = 862.6320056992192\n",
      "Generation 3845: p = 0.9584800063324658\n",
      "Generation 3845: M(n) = 862.6320056992192\n",
      "Generation 3846: p = 0.9584800063324658\n",
      "Generation 3846: M(n) = 862.6320056992192\n",
      "Generation 3847: p = 0.9584800063324658\n",
      "Generation 3847: M(n) = 862.6320056992192\n",
      "Generation 3848: p = 0.9584800063324658\n",
      "Generation 3848: M(n) = 862.6320056992192\n",
      "Generation 3849: p = 0.9584800063324658\n",
      "Generation 3849: M(n) = 862.6320056992192\n",
      "Generation 3850: p = 0.9584800063324658\n",
      "Generation 3850: M(n) = 862.6320056992192\n",
      "Generation 3851: p = 0.9584800063324658\n",
      "Generation 3851: M(n) = 862.6320056992192\n",
      "Generation 3852: p = 0.9584800063324658\n",
      "Generation 3852: M(n) = 862.6320056992192\n",
      "Generation 3853: p = 0.9584800063324658\n",
      "Generation 3853: M(n) = 862.6320056992192\n",
      "Generation 3854: p = 0.9584800063324658\n",
      "Generation 3854: M(n) = 862.6320056992192\n",
      "Generation 3855: p = 0.9584800063324658\n",
      "Generation 3855: M(n) = 862.6320056992192\n",
      "Generation 3856: p = 0.9584800063324658\n",
      "Generation 3856: M(n) = 862.6320056992192\n",
      "Generation 3857: p = 0.9584800063324658\n",
      "Generation 3857: M(n) = 862.6320056992192\n",
      "Generation 3858: p = 0.9584800063324658\n",
      "Generation 3858: M(n) = 862.6320056992192\n",
      "Generation 3859: p = 0.9584800063324658\n",
      "Generation 3859: M(n) = 862.6320056992192\n",
      "Generation 3860: p = 0.9584800063324658\n",
      "Generation 3860: M(n) = 862.6320056992192\n",
      "Generation 3861: p = 0.9584800063324658\n",
      "Generation 3861: M(n) = 862.6320056992192\n",
      "Generation 3862: p = 0.9584800063324658\n",
      "Generation 3862: M(n) = 862.6320056992192\n",
      "Generation 3863: p = 0.9584800063324658\n",
      "Generation 3863: M(n) = 862.6320056992192\n",
      "Generation 3864: p = 0.9584800063324658\n",
      "Generation 3864: M(n) = 862.6320056992192\n",
      "Generation 3865: p = 0.9584800063324658\n",
      "Generation 3865: M(n) = 862.6320056992192\n",
      "Generation 3866: p = 0.9584800063324658\n",
      "Generation 3866: M(n) = 862.6320056992192\n",
      "Generation 3867: p = 0.9584800063324658\n",
      "Generation 3867: M(n) = 862.6320056992192\n",
      "Generation 3868: p = 0.9584800063324658\n",
      "Generation 3868: M(n) = 862.6320056992192\n",
      "Generation 3869: p = 0.9584800063324658\n",
      "Generation 3869: M(n) = 862.6320056992192\n",
      "Generation 3870: p = 0.9584800063324658\n",
      "Generation 3870: M(n) = 862.6320056992192\n",
      "Generation 3871: p = 0.9584800063324658\n",
      "Generation 3871: M(n) = 862.6320056992192\n",
      "Generation 3872: p = 0.9584800063324658\n",
      "Generation 3872: M(n) = 862.6320056992192\n",
      "Generation 3873: p = 0.9584800063324658\n",
      "Generation 3873: M(n) = 862.6320056992192\n",
      "Generation 3874: p = 0.9584800063324658\n",
      "Generation 3874: M(n) = 862.6320056992192\n",
      "Generation 3875: p = 0.9584800063324658\n",
      "Generation 3875: M(n) = 862.6320056992192\n",
      "Generation 3876: p = 0.9584800063324658\n",
      "Generation 3876: M(n) = 862.6320056992192\n",
      "Generation 3877: p = 0.9584800063324658\n",
      "Generation 3877: M(n) = 862.6320056992192\n",
      "Generation 3878: p = 0.9584800063324658\n",
      "Generation 3878: M(n) = 862.6320056992192\n",
      "Generation 3879: p = 0.9584800063324658\n",
      "Generation 3879: M(n) = 862.6320056992192\n",
      "Generation 3880: p = 0.9584800063324658\n",
      "Generation 3880: M(n) = 862.6320056992192\n",
      "Generation 3881: p = 0.9584800063324658\n",
      "Generation 3881: M(n) = 862.6320056992192\n",
      "Generation 3882: p = 0.9584800063324658\n",
      "Generation 3882: M(n) = 862.6320056992192\n",
      "Generation 3883: p = 0.9584800063324658\n",
      "Generation 3883: M(n) = 862.6320056992192\n",
      "Generation 3884: p = 0.9584800063324658\n",
      "Generation 3884: M(n) = 862.6320056992192\n",
      "Generation 3885: p = 0.9584800063324658\n",
      "Generation 3885: M(n) = 862.6320056992192\n",
      "Generation 3886: p = 0.9584800063324658\n",
      "Generation 3886: M(n) = 862.6320056992192\n",
      "Generation 3887: p = 0.9584800063324658\n",
      "Generation 3887: M(n) = 862.6320056992192\n",
      "Generation 3888: p = 0.9584800063324658\n",
      "Generation 3888: M(n) = 862.6320056992192\n",
      "Generation 3889: p = 0.9584800063324658\n",
      "Generation 3889: M(n) = 862.6320056992192\n",
      "Generation 3890: p = 0.9584800063324658\n",
      "Generation 3890: M(n) = 862.6320056992192\n",
      "Generation 3891: p = 0.9584800063324658\n",
      "Generation 3891: M(n) = 862.6320056992192\n",
      "Generation 3892: p = 0.9584800063324658\n",
      "Generation 3892: M(n) = 862.6320056992192\n",
      "Generation 3893: p = 0.9584800063324658\n",
      "Generation 3893: M(n) = 862.6320056992192\n",
      "Generation 3894: p = 0.9584800063324658\n",
      "Generation 3894: M(n) = 862.6320056992192\n",
      "Generation 3895: p = 0.9584800063324658\n",
      "Generation 3895: M(n) = 862.6320056992192\n",
      "Generation 3896: p = 0.9584800063324658\n",
      "Generation 3896: M(n) = 862.6320056992192\n",
      "Generation 3897: p = 0.9584800063324658\n",
      "Generation 3897: M(n) = 862.6320056992192\n",
      "Generation 3898: p = 0.9584800063324658\n",
      "Generation 3898: M(n) = 862.6320056992192\n",
      "Generation 3899: p = 0.9584800063324658\n",
      "Generation 3899: M(n) = 862.6320056992192\n",
      "Generation 3900: p = 0.9584800063324658\n",
      "Generation 3900: M(n) = 862.6320056992192\n",
      "Generation 3901: p = 0.9584800063324658\n",
      "Generation 3901: M(n) = 862.6320056992192\n",
      "Generation 3902: p = 0.9584800063324658\n",
      "Generation 3902: M(n) = 862.6320056992192\n",
      "Generation 3903: p = 0.9584800063324658\n",
      "Generation 3903: M(n) = 862.6320056992192\n",
      "Generation 3904: p = 0.9584800063324658\n",
      "Generation 3904: M(n) = 862.6320056992192\n",
      "Generation 3905: p = 0.9584800063324658\n",
      "Generation 3905: M(n) = 862.6320056992192\n",
      "Generation 3906: p = 0.9584800063324658\n",
      "Generation 3906: M(n) = 862.6320056992192\n",
      "Generation 3907: p = 0.9584800063324658\n",
      "Generation 3907: M(n) = 862.6320056992192\n",
      "Generation 3908: p = 0.9584800063324658\n",
      "Generation 3908: M(n) = 862.6320056992192\n",
      "Generation 3909: p = 0.9584800063324658\n",
      "Generation 3909: M(n) = 862.6320056992192\n",
      "Generation 3910: p = 0.9584800063324658\n",
      "Generation 3910: M(n) = 862.6320056992192\n",
      "Generation 3911: p = 0.9584800063324658\n",
      "Generation 3911: M(n) = 862.6320056992192\n",
      "Generation 3912: p = 0.9584800063324658\n",
      "Generation 3912: M(n) = 862.6320056992192\n",
      "Generation 3913: p = 0.9584800063324658\n",
      "Generation 3913: M(n) = 862.6320056992192\n",
      "Generation 3914: p = 0.9584800063324658\n",
      "Generation 3914: M(n) = 862.6320056992192\n",
      "Generation 3915: p = 0.9584800063324658\n",
      "Generation 3915: M(n) = 862.6320056992192\n",
      "Generation 3916: p = 0.9584800063324658\n",
      "Generation 3916: M(n) = 862.6320056992192\n",
      "Generation 3917: p = 0.9584800063324658\n",
      "Generation 3917: M(n) = 862.6320056992192\n",
      "Generation 3918: p = 0.9584800063324658\n",
      "Generation 3918: M(n) = 862.6320056992192\n",
      "Generation 3919: p = 0.9584800063324658\n",
      "Generation 3919: M(n) = 862.6320056992192\n",
      "Generation 3920: p = 0.9584800063324658\n",
      "Generation 3920: M(n) = 862.6320056992192\n",
      "Generation 3921: p = 0.9584800063324658\n",
      "Generation 3921: M(n) = 862.6320056992192\n",
      "Generation 3922: p = 0.9584800063324658\n",
      "Generation 3922: M(n) = 862.6320056992192\n",
      "Generation 3923: p = 0.9584800063324658\n",
      "Generation 3923: M(n) = 862.6320056992192\n",
      "Generation 3924: p = 0.9584800063324658\n",
      "Generation 3924: M(n) = 862.6320056992192\n",
      "Generation 3925: p = 0.9584800063324658\n",
      "Generation 3925: M(n) = 862.6320056992192\n",
      "Generation 3926: p = 0.9584800063324658\n",
      "Generation 3926: M(n) = 862.6320056992192\n",
      "Generation 3927: p = 0.9584800063324658\n",
      "Generation 3927: M(n) = 862.6320056992192\n",
      "Generation 3928: p = 0.9584800063324658\n",
      "Generation 3928: M(n) = 862.6320056992192\n",
      "Generation 3929: p = 0.9584800063324658\n",
      "Generation 3929: M(n) = 862.6320056992192\n",
      "Generation 3930: p = 0.9584800063324658\n",
      "Generation 3930: M(n) = 862.6320056992192\n",
      "Generation 3931: p = 0.9584800063324658\n",
      "Generation 3931: M(n) = 862.6320056992192\n",
      "Generation 3932: p = 0.9584800063324658\n",
      "Generation 3932: M(n) = 862.6320056992192\n",
      "Generation 3933: p = 0.9584800063324658\n",
      "Generation 3933: M(n) = 862.6320056992192\n",
      "Generation 3934: p = 0.9584800063324658\n",
      "Generation 3934: M(n) = 862.6320056992192\n",
      "Generation 3935: p = 0.9584800063324658\n",
      "Generation 3935: M(n) = 862.6320056992192\n",
      "Generation 3936: p = 0.9584800063324658\n",
      "Generation 3936: M(n) = 862.6320056992192\n",
      "Generation 3937: p = 0.9584800063324658\n",
      "Generation 3937: M(n) = 862.6320056992192\n",
      "Generation 3938: p = 0.9584800063324658\n",
      "Generation 3938: M(n) = 862.6320056992192\n",
      "Generation 3939: p = 0.9584800063324658\n",
      "Generation 3939: M(n) = 862.6320056992192\n",
      "Generation 3940: p = 0.9584800063324658\n",
      "Generation 3940: M(n) = 862.6320056992192\n",
      "Generation 3941: p = 0.9584800063324658\n",
      "Generation 3941: M(n) = 862.6320056992192\n",
      "Generation 3942: p = 0.9584800063324658\n",
      "Generation 3942: M(n) = 862.6320056992192\n",
      "Generation 3943: p = 0.9584800063324658\n",
      "Generation 3943: M(n) = 862.6320056992192\n",
      "Generation 3944: p = 0.9584800063324658\n",
      "Generation 3944: M(n) = 862.6320056992192\n",
      "Generation 3945: p = 0.9584800063324658\n",
      "Generation 3945: M(n) = 862.6320056992192\n",
      "Generation 3946: p = 0.9584800063324658\n",
      "Generation 3946: M(n) = 862.6320056992192\n",
      "Generation 3947: p = 0.9584800063324658\n",
      "Generation 3947: M(n) = 862.6320056992192\n",
      "Generation 3948: p = 0.9584800063324658\n",
      "Generation 3948: M(n) = 862.6320056992192\n",
      "Generation 3949: p = 0.9584800063324658\n",
      "Generation 3949: M(n) = 862.6320056992192\n",
      "Generation 3950: p = 0.9584800063324658\n",
      "Generation 3950: M(n) = 862.6320056992192\n",
      "Generation 3951: p = 0.9584800063324658\n",
      "Generation 3951: M(n) = 862.6320056992192\n",
      "Generation 3952: p = 0.9584800063324658\n",
      "Generation 3952: M(n) = 862.6320056992192\n",
      "Generation 3953: p = 0.9584800063324658\n",
      "Generation 3953: M(n) = 862.6320056992192\n",
      "Generation 3954: p = 0.9584800063324658\n",
      "Generation 3954: M(n) = 862.6320056992192\n",
      "Generation 3955: p = 0.9584800063324658\n",
      "Generation 3955: M(n) = 862.6320056992192\n",
      "Generation 3956: p = 0.9584800063324658\n",
      "Generation 3956: M(n) = 862.6320056992192\n",
      "Generation 3957: p = 0.9584800063324658\n",
      "Generation 3957: M(n) = 862.6320056992192\n",
      "Generation 3958: p = 0.9584800063324658\n",
      "Generation 3958: M(n) = 862.6320056992192\n",
      "Generation 3959: p = 0.9584800063324658\n",
      "Generation 3959: M(n) = 862.6320056992192\n",
      "Generation 3960: p = 0.9584800063324658\n",
      "Generation 3960: M(n) = 862.6320056992192\n",
      "Generation 3961: p = 0.9584800063324658\n",
      "Generation 3961: M(n) = 862.6320056992192\n",
      "Generation 3962: p = 0.9584800063324658\n",
      "Generation 3962: M(n) = 862.6320056992192\n",
      "Generation 3963: p = 0.9584800063324658\n",
      "Generation 3963: M(n) = 862.6320056992192\n",
      "Generation 3964: p = 0.9584800063324658\n",
      "Generation 3964: M(n) = 862.6320056992192\n",
      "Generation 3965: p = 0.9584800063324658\n",
      "Generation 3965: M(n) = 862.6320056992192\n",
      "Generation 3966: p = 0.9584800063324658\n",
      "Generation 3966: M(n) = 862.6320056992192\n",
      "Generation 3967: p = 0.9584800063324658\n",
      "Generation 3967: M(n) = 862.6320056992192\n",
      "Generation 3968: p = 0.9584800063324658\n",
      "Generation 3968: M(n) = 862.6320056992192\n",
      "Generation 3969: p = 0.9584800063324658\n",
      "Generation 3969: M(n) = 862.6320056992192\n",
      "Generation 3970: p = 0.9584800063324658\n",
      "Generation 3970: M(n) = 862.6320056992192\n",
      "Generation 3971: p = 0.9584800063324658\n",
      "Generation 3971: M(n) = 862.6320056992192\n",
      "Generation 3972: p = 0.9584800063324658\n",
      "Generation 3972: M(n) = 862.6320056992192\n",
      "Generation 3973: p = 0.9584800063324658\n",
      "Generation 3973: M(n) = 862.6320056992192\n",
      "Generation 3974: p = 0.9584800063324658\n",
      "Generation 3974: M(n) = 862.6320056992192\n",
      "Generation 3975: p = 0.9584800063324658\n",
      "Generation 3975: M(n) = 862.6320056992192\n",
      "Generation 3976: p = 0.9584800063324658\n",
      "Generation 3976: M(n) = 862.6320056992192\n",
      "Generation 3977: p = 0.9584800063324658\n",
      "Generation 3977: M(n) = 862.6320056992192\n",
      "Generation 3978: p = 0.9584800063324658\n",
      "Generation 3978: M(n) = 862.6320056992192\n",
      "Generation 3979: p = 0.9584800063324658\n",
      "Generation 3979: M(n) = 862.6320056992192\n",
      "Generation 3980: p = 0.9584800063324658\n",
      "Generation 3980: M(n) = 862.6320056992192\n",
      "Generation 3981: p = 0.9584800063324658\n",
      "Generation 3981: M(n) = 862.6320056992192\n",
      "Generation 3982: p = 0.9584800063324658\n",
      "Generation 3982: M(n) = 862.6320056992192\n",
      "Generation 3983: p = 0.9584800063324658\n",
      "Generation 3983: M(n) = 862.6320056992192\n",
      "Generation 3984: p = 0.9584800063324658\n",
      "Generation 3984: M(n) = 862.6320056992192\n",
      "Generation 3985: p = 0.9584800063324658\n",
      "Generation 3985: M(n) = 862.6320056992192\n",
      "Generation 3986: p = 0.9584800063324658\n",
      "Generation 3986: M(n) = 862.6320056992192\n",
      "Generation 3987: p = 0.9584800063324658\n",
      "Generation 3987: M(n) = 862.6320056992192\n",
      "Generation 3988: p = 0.9584800063324658\n",
      "Generation 3988: M(n) = 862.6320056992192\n",
      "Generation 3989: p = 0.9584800063324658\n",
      "Generation 3989: M(n) = 862.6320056992192\n",
      "Generation 3990: p = 0.9584800063324658\n",
      "Generation 3990: M(n) = 862.6320056992192\n",
      "Generation 3991: p = 0.9584800063324658\n",
      "Generation 3991: M(n) = 862.6320056992192\n",
      "Generation 3992: p = 0.9584800063324658\n",
      "Generation 3992: M(n) = 862.6320056992192\n",
      "Generation 3993: p = 0.9584800063324658\n",
      "Generation 3993: M(n) = 862.6320056992192\n",
      "Generation 3994: p = 0.9584800063324658\n",
      "Generation 3994: M(n) = 862.6320056992192\n",
      "Generation 3995: p = 0.9584800063324658\n",
      "Generation 3995: M(n) = 862.6320056992192\n",
      "Generation 3996: p = 0.9584800063324658\n",
      "Generation 3996: M(n) = 862.6320056992192\n",
      "Generation 3997: p = 0.9584800063324658\n",
      "Generation 3997: M(n) = 862.6320056992192\n",
      "Generation 3998: p = 0.9584800063324658\n",
      "Generation 3998: M(n) = 862.6320056992192\n",
      "Generation 3999: p = 0.9584800063324658\n",
      "Generation 3999: M(n) = 862.6320056992192\n",
      "Generation 4000: p = 0.9584800063324658\n",
      "Generation 4000: M(n) = 862.6320056992192\n",
      "Generation 4001: p = 0.9584800063324658\n",
      "Generation 4001: M(n) = 862.6320056992192\n",
      "Generation 4002: p = 0.9584800063324658\n",
      "Generation 4002: M(n) = 862.6320056992192\n",
      "Generation 4003: p = 0.9584800063324658\n",
      "Generation 4003: M(n) = 862.6320056992192\n",
      "Generation 4004: p = 0.9584800063324658\n",
      "Generation 4004: M(n) = 862.6320056992192\n",
      "Generation 4005: p = 0.9584800063324658\n",
      "Generation 4005: M(n) = 862.6320056992192\n",
      "Generation 4006: p = 0.9584800063324658\n",
      "Generation 4006: M(n) = 862.6320056992192\n",
      "Generation 4007: p = 0.9584800063324658\n",
      "Generation 4007: M(n) = 862.6320056992192\n",
      "Generation 4008: p = 0.9584800063324658\n",
      "Generation 4008: M(n) = 862.6320056992192\n",
      "Generation 4009: p = 0.9584800063324658\n",
      "Generation 4009: M(n) = 862.6320056992192\n",
      "Generation 4010: p = 0.9584800063324658\n",
      "Generation 4010: M(n) = 862.6320056992192\n",
      "Generation 4011: p = 0.9584800063324658\n",
      "Generation 4011: M(n) = 862.6320056992192\n",
      "Generation 4012: p = 0.9584800063324658\n",
      "Generation 4012: M(n) = 862.6320056992192\n",
      "Generation 4013: p = 0.9584800063324658\n",
      "Generation 4013: M(n) = 862.6320056992192\n",
      "Generation 4014: p = 0.9584800063324658\n",
      "Generation 4014: M(n) = 862.6320056992192\n",
      "Generation 4015: p = 0.9584800063324658\n",
      "Generation 4015: M(n) = 862.6320056992192\n",
      "Generation 4016: p = 0.9584800063324658\n",
      "Generation 4016: M(n) = 862.6320056992192\n",
      "Generation 4017: p = 0.9584800063324658\n",
      "Generation 4017: M(n) = 862.6320056992192\n",
      "Generation 4018: p = 0.9584800063324658\n",
      "Generation 4018: M(n) = 862.6320056992192\n",
      "Generation 4019: p = 0.9584800063324658\n",
      "Generation 4019: M(n) = 862.6320056992192\n",
      "Generation 4020: p = 0.9584800063324658\n",
      "Generation 4020: M(n) = 862.6320056992192\n",
      "Generation 4021: p = 0.9584800063324658\n",
      "Generation 4021: M(n) = 862.6320056992192\n",
      "Generation 4022: p = 0.9584800063324658\n",
      "Generation 4022: M(n) = 862.6320056992192\n",
      "Generation 4023: p = 0.9584800063324658\n",
      "Generation 4023: M(n) = 862.6320056992192\n",
      "Generation 4024: p = 0.9584800063324658\n",
      "Generation 4024: M(n) = 862.6320056992192\n",
      "Generation 4025: p = 0.9584800063324658\n",
      "Generation 4025: M(n) = 862.6320056992192\n",
      "Generation 4026: p = 0.9584800063324658\n",
      "Generation 4026: M(n) = 862.6320056992192\n",
      "Generation 4027: p = 0.9584800063324658\n",
      "Generation 4027: M(n) = 862.6320056992192\n",
      "Generation 4028: p = 0.9584800063324658\n",
      "Generation 4028: M(n) = 862.6320056992192\n",
      "Generation 4029: p = 0.9584800063324658\n",
      "Generation 4029: M(n) = 862.6320056992192\n",
      "Generation 4030: p = 0.9584800063324658\n",
      "Generation 4030: M(n) = 862.6320056992192\n",
      "Generation 4031: p = 0.9584800063324658\n",
      "Generation 4031: M(n) = 862.6320056992192\n",
      "Generation 4032: p = 0.9584800063324658\n",
      "Generation 4032: M(n) = 862.6320056992192\n",
      "Generation 4033: p = 0.9584800063324658\n",
      "Generation 4033: M(n) = 862.6320056992192\n",
      "Generation 4034: p = 0.9584800063324658\n",
      "Generation 4034: M(n) = 862.6320056992192\n",
      "Generation 4035: p = 0.9584800063324658\n",
      "Generation 4035: M(n) = 862.6320056992192\n",
      "Generation 4036: p = 0.9584800063324658\n",
      "Generation 4036: M(n) = 862.6320056992192\n",
      "Generation 4037: p = 0.9584800063324658\n",
      "Generation 4037: M(n) = 862.6320056992192\n",
      "Generation 4038: p = 0.9584800063324658\n",
      "Generation 4038: M(n) = 862.6320056992192\n",
      "Generation 4039: p = 0.9584800063324658\n",
      "Generation 4039: M(n) = 862.6320056992192\n",
      "Generation 4040: p = 0.9584800063324658\n",
      "Generation 4040: M(n) = 862.6320056992192\n",
      "Generation 4041: p = 0.9584800063324658\n",
      "Generation 4041: M(n) = 862.6320056992192\n",
      "Generation 4042: p = 0.9584800063324658\n",
      "Generation 4042: M(n) = 862.6320056992192\n",
      "Generation 4043: p = 0.9584800063324658\n",
      "Generation 4043: M(n) = 862.6320056992192\n",
      "Generation 4044: p = 0.9584800063324658\n",
      "Generation 4044: M(n) = 862.6320056992192\n",
      "Generation 4045: p = 0.9584800063324658\n",
      "Generation 4045: M(n) = 862.6320056992192\n",
      "Generation 4046: p = 0.9584800063324658\n",
      "Generation 4046: M(n) = 862.6320056992192\n",
      "Generation 4047: p = 0.9584800063324658\n",
      "Generation 4047: M(n) = 862.6320056992192\n",
      "Generation 4048: p = 0.9584800063324658\n",
      "Generation 4048: M(n) = 862.6320056992192\n",
      "Generation 4049: p = 0.9584800063324658\n",
      "Generation 4049: M(n) = 862.6320056992192\n",
      "Generation 4050: p = 0.9584800063324658\n",
      "Generation 4050: M(n) = 862.6320056992192\n",
      "Generation 4051: p = 0.9584800063324658\n",
      "Generation 4051: M(n) = 862.6320056992192\n",
      "Generation 4052: p = 0.9584800063324658\n",
      "Generation 4052: M(n) = 862.6320056992192\n",
      "Generation 4053: p = 0.9584800063324658\n",
      "Generation 4053: M(n) = 862.6320056992192\n",
      "Generation 4054: p = 0.9584800063324658\n",
      "Generation 4054: M(n) = 862.6320056992192\n",
      "Generation 4055: p = 0.9584800063324658\n",
      "Generation 4055: M(n) = 862.6320056992192\n",
      "Generation 4056: p = 0.9584800063324658\n",
      "Generation 4056: M(n) = 862.6320056992192\n",
      "Generation 4057: p = 0.9584800063324658\n",
      "Generation 4057: M(n) = 862.6320056992192\n",
      "Generation 4058: p = 0.9584800063324658\n",
      "Generation 4058: M(n) = 862.6320056992192\n",
      "Generation 4059: p = 0.9584800063324658\n",
      "Generation 4059: M(n) = 862.6320056992192\n",
      "Generation 4060: p = 0.9584800063324658\n",
      "Generation 4060: M(n) = 862.6320056992192\n",
      "Generation 4061: p = 0.9584800063324658\n",
      "Generation 4061: M(n) = 862.6320056992192\n",
      "Generation 4062: p = 0.9584800063324658\n",
      "Generation 4062: M(n) = 862.6320056992192\n",
      "Generation 4063: p = 0.9584800063324658\n",
      "Generation 4063: M(n) = 862.6320056992192\n",
      "Generation 4064: p = 0.9584800063324658\n",
      "Generation 4064: M(n) = 862.6320056992192\n",
      "Generation 4065: p = 0.9584800063324658\n",
      "Generation 4065: M(n) = 862.6320056992192\n",
      "Generation 4066: p = 0.9584800063324658\n",
      "Generation 4066: M(n) = 862.6320056992192\n",
      "Generation 4067: p = 0.9584800063324658\n",
      "Generation 4067: M(n) = 862.6320056992192\n",
      "Generation 4068: p = 0.9584800063324658\n",
      "Generation 4068: M(n) = 862.6320056992192\n",
      "Generation 4069: p = 0.9584800063324658\n",
      "Generation 4069: M(n) = 862.6320056992192\n",
      "Generation 4070: p = 0.9584800063324658\n",
      "Generation 4070: M(n) = 862.6320056992192\n",
      "Generation 4071: p = 0.9584800063324658\n",
      "Generation 4071: M(n) = 862.6320056992192\n",
      "Generation 4072: p = 0.9584800063324658\n",
      "Generation 4072: M(n) = 862.6320056992192\n",
      "Generation 4073: p = 0.9584800063324658\n",
      "Generation 4073: M(n) = 862.6320056992192\n",
      "Generation 4074: p = 0.9584800063324658\n",
      "Generation 4074: M(n) = 862.6320056992192\n",
      "Generation 4075: p = 0.9584800063324658\n",
      "Generation 4075: M(n) = 862.6320056992192\n",
      "Generation 4076: p = 0.9584800063324658\n",
      "Generation 4076: M(n) = 862.6320056992192\n",
      "Generation 4077: p = 0.9584800063324658\n",
      "Generation 4077: M(n) = 862.6320056992192\n",
      "Generation 4078: p = 0.9584800063324658\n",
      "Generation 4078: M(n) = 862.6320056992192\n",
      "Generation 4079: p = 0.9584800063324658\n",
      "Generation 4079: M(n) = 862.6320056992192\n",
      "Generation 4080: p = 0.9584800063324658\n",
      "Generation 4080: M(n) = 862.6320056992192\n",
      "Generation 4081: p = 0.9584800063324658\n",
      "Generation 4081: M(n) = 862.6320056992192\n",
      "Generation 4082: p = 0.9584800063324658\n",
      "Generation 4082: M(n) = 862.6320056992192\n",
      "Generation 4083: p = 0.9584800063324658\n",
      "Generation 4083: M(n) = 862.6320056992192\n",
      "Generation 4084: p = 0.9584800063324658\n",
      "Generation 4084: M(n) = 862.6320056992192\n",
      "Generation 4085: p = 0.9584800063324658\n",
      "Generation 4085: M(n) = 862.6320056992192\n",
      "Generation 4086: p = 0.9584800063324658\n",
      "Generation 4086: M(n) = 862.6320056992192\n",
      "Generation 4087: p = 0.9584800063324658\n",
      "Generation 4087: M(n) = 862.6320056992192\n",
      "Generation 4088: p = 0.9584800063324658\n",
      "Generation 4088: M(n) = 862.6320056992192\n",
      "Generation 4089: p = 0.9584800063324658\n",
      "Generation 4089: M(n) = 862.6320056992192\n",
      "Generation 4090: p = 0.9584800063324658\n",
      "Generation 4090: M(n) = 862.6320056992192\n",
      "Generation 4091: p = 0.9584800063324658\n",
      "Generation 4091: M(n) = 862.6320056992192\n",
      "Generation 4092: p = 0.9584800063324658\n",
      "Generation 4092: M(n) = 862.6320056992192\n",
      "Generation 4093: p = 0.9584800063324658\n",
      "Generation 4093: M(n) = 862.6320056992192\n",
      "Generation 4094: p = 0.9584800063324658\n",
      "Generation 4094: M(n) = 862.6320056992192\n",
      "Generation 4095: p = 0.9584800063324658\n",
      "Generation 4095: M(n) = 862.6320056992192\n",
      "Generation 4096: p = 0.9584800063324658\n",
      "Generation 4096: M(n) = 862.6320056992192\n",
      "Generation 4097: p = 0.9584800063324658\n",
      "Generation 4097: M(n) = 862.6320056992192\n",
      "Generation 4098: p = 0.9584800063324658\n",
      "Generation 4098: M(n) = 862.6320056992192\n",
      "Generation 4099: p = 0.9584800063324658\n",
      "Generation 4099: M(n) = 862.6320056992192\n",
      "Generation 4100: p = 0.9584800063324658\n",
      "Generation 4100: M(n) = 862.6320056992192\n",
      "Generation 4101: p = 0.9584800063324658\n",
      "Generation 4101: M(n) = 862.6320056992192\n",
      "Generation 4102: p = 0.9584800063324658\n",
      "Generation 4102: M(n) = 862.6320056992192\n",
      "Generation 4103: p = 0.9584800063324658\n",
      "Generation 4103: M(n) = 862.6320056992192\n",
      "Generation 4104: p = 0.9584800063324658\n",
      "Generation 4104: M(n) = 862.6320056992192\n",
      "Generation 4105: p = 0.9584800063324658\n",
      "Generation 4105: M(n) = 862.6320056992192\n",
      "Generation 4106: p = 0.9584800063324658\n",
      "Generation 4106: M(n) = 862.6320056992192\n",
      "Generation 4107: p = 0.9584800063324658\n",
      "Generation 4107: M(n) = 862.6320056992192\n",
      "Generation 4108: p = 0.9584800063324658\n",
      "Generation 4108: M(n) = 862.6320056992192\n",
      "Generation 4109: p = 0.9584800063324658\n",
      "Generation 4109: M(n) = 862.6320056992192\n",
      "Generation 4110: p = 0.9584800063324658\n",
      "Generation 4110: M(n) = 862.6320056992192\n",
      "Generation 4111: p = 0.9584800063324658\n",
      "Generation 4111: M(n) = 862.6320056992192\n",
      "Generation 4112: p = 0.9584800063324658\n",
      "Generation 4112: M(n) = 862.6320056992192\n",
      "Generation 4113: p = 0.9584800063324658\n",
      "Generation 4113: M(n) = 862.6320056992192\n",
      "Generation 4114: p = 0.9584800063324658\n",
      "Generation 4114: M(n) = 862.6320056992192\n",
      "Generation 4115: p = 0.9584800063324658\n",
      "Generation 4115: M(n) = 862.6320056992192\n",
      "Generation 4116: p = 0.9584800063324658\n",
      "Generation 4116: M(n) = 862.6320056992192\n",
      "Generation 4117: p = 0.9584800063324658\n",
      "Generation 4117: M(n) = 862.6320056992192\n",
      "Generation 4118: p = 0.9584800063324658\n",
      "Generation 4118: M(n) = 862.6320056992192\n",
      "Generation 4119: p = 0.9584800063324658\n",
      "Generation 4119: M(n) = 862.6320056992192\n",
      "Generation 4120: p = 0.9584800063324658\n",
      "Generation 4120: M(n) = 862.6320056992192\n",
      "Generation 4121: p = 0.9584800063324658\n",
      "Generation 4121: M(n) = 862.6320056992192\n",
      "Generation 4122: p = 0.9584800063324658\n",
      "Generation 4122: M(n) = 862.6320056992192\n",
      "Generation 4123: p = 0.9584800063324658\n",
      "Generation 4123: M(n) = 862.6320056992192\n",
      "Generation 4124: p = 0.9584800063324658\n",
      "Generation 4124: M(n) = 862.6320056992192\n",
      "Generation 4125: p = 0.9584800063324658\n",
      "Generation 4125: M(n) = 862.6320056992192\n",
      "Generation 4126: p = 0.9584800063324658\n",
      "Generation 4126: M(n) = 862.6320056992192\n",
      "Generation 4127: p = 0.9584800063324658\n",
      "Generation 4127: M(n) = 862.6320056992192\n",
      "Generation 4128: p = 0.9584800063324658\n",
      "Generation 4128: M(n) = 862.6320056992192\n",
      "Generation 4129: p = 0.9584800063324658\n",
      "Generation 4129: M(n) = 862.6320056992192\n",
      "Generation 4130: p = 0.9584800063324658\n",
      "Generation 4130: M(n) = 862.6320056992192\n",
      "Generation 4131: p = 0.9584800063324658\n",
      "Generation 4131: M(n) = 862.6320056992192\n",
      "Generation 4132: p = 0.9584800063324658\n",
      "Generation 4132: M(n) = 862.6320056992192\n",
      "Generation 4133: p = 0.9584800063324658\n",
      "Generation 4133: M(n) = 862.6320056992192\n",
      "Generation 4134: p = 0.9584800063324658\n",
      "Generation 4134: M(n) = 862.6320056992192\n",
      "Generation 4135: p = 0.9584800063324658\n",
      "Generation 4135: M(n) = 862.6320056992192\n",
      "Generation 4136: p = 0.9584800063324658\n",
      "Generation 4136: M(n) = 862.6320056992192\n",
      "Generation 4137: p = 0.9584800063324658\n",
      "Generation 4137: M(n) = 862.6320056992192\n",
      "Generation 4138: p = 0.9584800063324658\n",
      "Generation 4138: M(n) = 862.6320056992192\n",
      "Generation 4139: p = 0.9584800063324658\n",
      "Generation 4139: M(n) = 862.6320056992192\n",
      "Generation 4140: p = 0.9584800063324658\n",
      "Generation 4140: M(n) = 862.6320056992192\n",
      "Generation 4141: p = 0.9584800063324658\n",
      "Generation 4141: M(n) = 862.6320056992192\n",
      "Generation 4142: p = 0.9584800063324658\n",
      "Generation 4142: M(n) = 862.6320056992192\n",
      "Generation 4143: p = 0.9584800063324658\n",
      "Generation 4143: M(n) = 862.6320056992192\n",
      "Generation 4144: p = 0.9584800063324658\n",
      "Generation 4144: M(n) = 862.6320056992192\n",
      "Generation 4145: p = 0.9584800063324658\n",
      "Generation 4145: M(n) = 862.6320056992192\n",
      "Generation 4146: p = 0.9584800063324658\n",
      "Generation 4146: M(n) = 862.6320056992192\n",
      "Generation 4147: p = 0.9584800063324658\n",
      "Generation 4147: M(n) = 862.6320056992192\n",
      "Generation 4148: p = 0.9584800063324658\n",
      "Generation 4148: M(n) = 862.6320056992192\n",
      "Generation 4149: p = 0.9584800063324658\n",
      "Generation 4149: M(n) = 862.6320056992192\n",
      "Generation 4150: p = 0.9584800063324658\n",
      "Generation 4150: M(n) = 862.6320056992192\n",
      "Generation 4151: p = 0.9584800063324658\n",
      "Generation 4151: M(n) = 862.6320056992192\n",
      "Generation 4152: p = 0.9584800063324658\n",
      "Generation 4152: M(n) = 862.6320056992192\n",
      "Generation 4153: p = 0.9584800063324658\n",
      "Generation 4153: M(n) = 862.6320056992192\n",
      "Generation 4154: p = 0.9584800063324658\n",
      "Generation 4154: M(n) = 862.6320056992192\n",
      "Generation 4155: p = 0.9584800063324658\n",
      "Generation 4155: M(n) = 862.6320056992192\n",
      "Generation 4156: p = 0.9584800063324658\n",
      "Generation 4156: M(n) = 862.6320056992192\n",
      "Generation 4157: p = 0.9584800063324658\n",
      "Generation 4157: M(n) = 862.6320056992192\n",
      "Generation 4158: p = 0.9584800063324658\n",
      "Generation 4158: M(n) = 862.6320056992192\n",
      "Generation 4159: p = 0.9584800063324658\n",
      "Generation 4159: M(n) = 862.6320056992192\n",
      "Generation 4160: p = 0.9584800063324658\n",
      "Generation 4160: M(n) = 862.6320056992192\n",
      "Generation 4161: p = 0.9584800063324658\n",
      "Generation 4161: M(n) = 862.6320056992192\n",
      "Generation 4162: p = 0.9584800063324658\n",
      "Generation 4162: M(n) = 862.6320056992192\n",
      "Generation 4163: p = 0.9584800063324658\n",
      "Generation 4163: M(n) = 862.6320056992192\n",
      "Generation 4164: p = 0.9584800063324658\n",
      "Generation 4164: M(n) = 862.6320056992192\n",
      "Generation 4165: p = 0.9584800063324658\n",
      "Generation 4165: M(n) = 862.6320056992192\n",
      "Generation 4166: p = 0.9584800063324658\n",
      "Generation 4166: M(n) = 862.6320056992192\n",
      "Generation 4167: p = 0.9584800063324658\n",
      "Generation 4167: M(n) = 862.6320056992192\n",
      "Generation 4168: p = 0.9584800063324658\n",
      "Generation 4168: M(n) = 862.6320056992192\n",
      "Generation 4169: p = 0.9584800063324658\n",
      "Generation 4169: M(n) = 862.6320056992192\n",
      "Generation 4170: p = 0.9584800063324658\n",
      "Generation 4170: M(n) = 862.6320056992192\n",
      "Generation 4171: p = 0.9584800063324658\n",
      "Generation 4171: M(n) = 862.6320056992192\n",
      "Generation 4172: p = 0.9584800063324658\n",
      "Generation 4172: M(n) = 862.6320056992192\n",
      "Generation 4173: p = 0.9584800063324658\n",
      "Generation 4173: M(n) = 862.6320056992192\n",
      "Generation 4174: p = 0.9584800063324658\n",
      "Generation 4174: M(n) = 862.6320056992192\n",
      "Generation 4175: p = 0.9584800063324658\n",
      "Generation 4175: M(n) = 862.6320056992192\n",
      "Generation 4176: p = 0.9584800063324658\n",
      "Generation 4176: M(n) = 862.6320056992192\n",
      "Generation 4177: p = 0.9584800063324658\n",
      "Generation 4177: M(n) = 862.6320056992192\n",
      "Generation 4178: p = 0.9584800063324658\n",
      "Generation 4178: M(n) = 862.6320056992192\n",
      "Generation 4179: p = 0.9584800063324658\n",
      "Generation 4179: M(n) = 862.6320056992192\n",
      "Generation 4180: p = 0.9584800063324658\n",
      "Generation 4180: M(n) = 862.6320056992192\n",
      "Generation 4181: p = 0.9584800063324658\n",
      "Generation 4181: M(n) = 862.6320056992192\n",
      "Generation 4182: p = 0.9584800063324658\n",
      "Generation 4182: M(n) = 862.6320056992192\n",
      "Generation 4183: p = 0.9584800063324658\n",
      "Generation 4183: M(n) = 862.6320056992192\n",
      "Generation 4184: p = 0.9584800063324658\n",
      "Generation 4184: M(n) = 862.6320056992192\n",
      "Generation 4185: p = 0.9584800063324658\n",
      "Generation 4185: M(n) = 862.6320056992192\n",
      "Generation 4186: p = 0.9584800063324658\n",
      "Generation 4186: M(n) = 862.6320056992192\n",
      "Generation 4187: p = 0.9584800063324658\n",
      "Generation 4187: M(n) = 862.6320056992192\n",
      "Generation 4188: p = 0.9584800063324658\n",
      "Generation 4188: M(n) = 862.6320056992192\n",
      "Generation 4189: p = 0.9584800063324658\n",
      "Generation 4189: M(n) = 862.6320056992192\n",
      "Generation 4190: p = 0.9584800063324658\n",
      "Generation 4190: M(n) = 862.6320056992192\n",
      "Generation 4191: p = 0.9584800063324658\n",
      "Generation 4191: M(n) = 862.6320056992192\n",
      "Generation 4192: p = 0.9584800063324658\n",
      "Generation 4192: M(n) = 862.6320056992192\n",
      "Generation 4193: p = 0.9584800063324658\n",
      "Generation 4193: M(n) = 862.6320056992192\n",
      "Generation 4194: p = 0.9584800063324658\n",
      "Generation 4194: M(n) = 862.6320056992192\n",
      "Generation 4195: p = 0.9584800063324658\n",
      "Generation 4195: M(n) = 862.6320056992192\n",
      "Generation 4196: p = 0.9584800063324658\n",
      "Generation 4196: M(n) = 862.6320056992192\n",
      "Generation 4197: p = 0.9584800063324658\n",
      "Generation 4197: M(n) = 862.6320056992192\n",
      "Generation 4198: p = 0.9584800063324658\n",
      "Generation 4198: M(n) = 862.6320056992192\n",
      "Generation 4199: p = 0.9584800063324658\n",
      "Generation 4199: M(n) = 862.6320056992192\n",
      "Generation 4200: p = 0.9584800063324658\n",
      "Generation 4200: M(n) = 862.6320056992192\n",
      "Generation 4201: p = 0.9584800063324658\n",
      "Generation 4201: M(n) = 862.6320056992192\n",
      "Generation 4202: p = 0.9584800063324658\n",
      "Generation 4202: M(n) = 862.6320056992192\n",
      "Generation 4203: p = 0.9584800063324658\n",
      "Generation 4203: M(n) = 862.6320056992192\n",
      "Generation 4204: p = 0.9584800063324658\n",
      "Generation 4204: M(n) = 862.6320056992192\n",
      "Generation 4205: p = 0.9584800063324658\n",
      "Generation 4205: M(n) = 862.6320056992192\n",
      "Generation 4206: p = 0.9584800063324658\n",
      "Generation 4206: M(n) = 862.6320056992192\n",
      "Generation 4207: p = 0.9584800063324658\n",
      "Generation 4207: M(n) = 862.6320056992192\n",
      "Generation 4208: p = 0.9584800063324658\n",
      "Generation 4208: M(n) = 862.6320056992192\n",
      "Generation 4209: p = 0.9584800063324658\n",
      "Generation 4209: M(n) = 862.6320056992192\n",
      "Generation 4210: p = 0.9584800063324658\n",
      "Generation 4210: M(n) = 862.6320056992192\n",
      "Generation 4211: p = 0.9584800063324658\n",
      "Generation 4211: M(n) = 862.6320056992192\n",
      "Generation 4212: p = 0.9584800063324658\n",
      "Generation 4212: M(n) = 862.6320056992192\n",
      "Generation 4213: p = 0.9584800063324658\n",
      "Generation 4213: M(n) = 862.6320056992192\n",
      "Generation 4214: p = 0.9584800063324658\n",
      "Generation 4214: M(n) = 862.6320056992192\n",
      "Generation 4215: p = 0.9584800063324658\n",
      "Generation 4215: M(n) = 862.6320056992192\n",
      "Generation 4216: p = 0.9584800063324658\n",
      "Generation 4216: M(n) = 862.6320056992192\n",
      "Generation 4217: p = 0.9584800063324658\n",
      "Generation 4217: M(n) = 862.6320056992192\n",
      "Generation 4218: p = 0.9584800063324658\n",
      "Generation 4218: M(n) = 862.6320056992192\n",
      "Generation 4219: p = 0.9584800063324658\n",
      "Generation 4219: M(n) = 862.6320056992192\n",
      "Generation 4220: p = 0.9584800063324658\n",
      "Generation 4220: M(n) = 862.6320056992192\n",
      "Generation 4221: p = 0.9584800063324658\n",
      "Generation 4221: M(n) = 862.6320056992192\n",
      "Generation 4222: p = 0.9584800063324658\n",
      "Generation 4222: M(n) = 862.6320056992192\n",
      "Generation 4223: p = 0.9584800063324658\n",
      "Generation 4223: M(n) = 862.6320056992192\n",
      "Generation 4224: p = 0.9584800063324658\n",
      "Generation 4224: M(n) = 862.6320056992192\n",
      "Generation 4225: p = 0.9584800063324658\n",
      "Generation 4225: M(n) = 862.6320056992192\n",
      "Generation 4226: p = 0.9584800063324658\n",
      "Generation 4226: M(n) = 862.6320056992192\n",
      "Generation 4227: p = 0.9584800063324658\n",
      "Generation 4227: M(n) = 862.6320056992192\n",
      "Generation 4228: p = 0.9584800063324658\n",
      "Generation 4228: M(n) = 862.6320056992192\n",
      "Generation 4229: p = 0.9584800063324658\n",
      "Generation 4229: M(n) = 862.6320056992192\n",
      "Generation 4230: p = 0.9584800063324658\n",
      "Generation 4230: M(n) = 862.6320056992192\n",
      "Generation 4231: p = 0.9584800063324658\n",
      "Generation 4231: M(n) = 862.6320056992192\n",
      "Generation 4232: p = 0.9584800063324658\n",
      "Generation 4232: M(n) = 862.6320056992192\n",
      "Generation 4233: p = 0.9584800063324658\n",
      "Generation 4233: M(n) = 862.6320056992192\n",
      "Generation 4234: p = 0.9584800063324658\n",
      "Generation 4234: M(n) = 862.6320056992192\n",
      "Generation 4235: p = 0.9584800063324658\n",
      "Generation 4235: M(n) = 862.6320056992192\n",
      "Generation 4236: p = 0.9584800063324658\n",
      "Generation 4236: M(n) = 862.6320056992192\n",
      "Generation 4237: p = 0.9584800063324658\n",
      "Generation 4237: M(n) = 862.6320056992192\n",
      "Generation 4238: p = 0.9584800063324658\n",
      "Generation 4238: M(n) = 862.6320056992192\n",
      "Generation 4239: p = 0.9584800063324658\n",
      "Generation 4239: M(n) = 862.6320056992192\n",
      "Generation 4240: p = 0.9584800063324658\n",
      "Generation 4240: M(n) = 862.6320056992192\n",
      "Generation 4241: p = 0.9584800063324658\n",
      "Generation 4241: M(n) = 862.6320056992192\n",
      "Generation 4242: p = 0.9584800063324658\n",
      "Generation 4242: M(n) = 862.6320056992192\n",
      "Generation 4243: p = 0.9584800063324658\n",
      "Generation 4243: M(n) = 862.6320056992192\n",
      "Generation 4244: p = 0.9584800063324658\n",
      "Generation 4244: M(n) = 862.6320056992192\n",
      "Generation 4245: p = 0.9584800063324658\n",
      "Generation 4245: M(n) = 862.6320056992192\n",
      "Generation 4246: p = 0.9584800063324658\n",
      "Generation 4246: M(n) = 862.6320056992192\n",
      "Generation 4247: p = 0.9584800063324658\n",
      "Generation 4247: M(n) = 862.6320056992192\n",
      "Generation 4248: p = 0.9584800063324658\n",
      "Generation 4248: M(n) = 862.6320056992192\n",
      "Generation 4249: p = 0.9584800063324658\n",
      "Generation 4249: M(n) = 862.6320056992192\n",
      "Generation 4250: p = 0.9584800063324658\n",
      "Generation 4250: M(n) = 862.6320056992192\n",
      "Generation 4251: p = 0.9584800063324658\n",
      "Generation 4251: M(n) = 862.6320056992192\n",
      "Generation 4252: p = 0.9584800063324658\n",
      "Generation 4252: M(n) = 862.6320056992192\n",
      "Generation 4253: p = 0.9584800063324658\n",
      "Generation 4253: M(n) = 862.6320056992192\n",
      "Generation 4254: p = 0.9584800063324658\n",
      "Generation 4254: M(n) = 862.6320056992192\n",
      "Generation 4255: p = 0.9584800063324658\n",
      "Generation 4255: M(n) = 862.6320056992192\n",
      "Generation 4256: p = 0.9584800063324658\n",
      "Generation 4256: M(n) = 862.6320056992192\n",
      "Generation 4257: p = 0.9584800063324658\n",
      "Generation 4257: M(n) = 862.6320056992192\n",
      "Generation 4258: p = 0.9584800063324658\n",
      "Generation 4258: M(n) = 862.6320056992192\n",
      "Generation 4259: p = 0.9584800063324658\n",
      "Generation 4259: M(n) = 862.6320056992192\n",
      "Generation 4260: p = 0.9584800063324658\n",
      "Generation 4260: M(n) = 862.6320056992192\n",
      "Generation 4261: p = 0.9584800063324658\n",
      "Generation 4261: M(n) = 862.6320056992192\n",
      "Generation 4262: p = 0.9584800063324658\n",
      "Generation 4262: M(n) = 862.6320056992192\n",
      "Generation 4263: p = 0.9584800063324658\n",
      "Generation 4263: M(n) = 862.6320056992192\n",
      "Generation 4264: p = 0.9584800063324658\n",
      "Generation 4264: M(n) = 862.6320056992192\n",
      "Generation 4265: p = 0.9584800063324658\n",
      "Generation 4265: M(n) = 862.6320056992192\n",
      "Generation 4266: p = 0.9584800063324658\n",
      "Generation 4266: M(n) = 862.6320056992192\n",
      "Generation 4267: p = 0.9584800063324658\n",
      "Generation 4267: M(n) = 862.6320056992192\n",
      "Generation 4268: p = 0.9584800063324658\n",
      "Generation 4268: M(n) = 862.6320056992192\n",
      "Generation 4269: p = 0.9584800063324658\n",
      "Generation 4269: M(n) = 862.6320056992192\n",
      "Generation 4270: p = 0.9584800063324658\n",
      "Generation 4270: M(n) = 862.6320056992192\n",
      "Generation 4271: p = 0.9584800063324658\n",
      "Generation 4271: M(n) = 862.6320056992192\n",
      "Generation 4272: p = 0.9584800063324658\n",
      "Generation 4272: M(n) = 862.6320056992192\n",
      "Generation 4273: p = 0.9584800063324658\n",
      "Generation 4273: M(n) = 862.6320056992192\n",
      "Generation 4274: p = 0.9584800063324658\n",
      "Generation 4274: M(n) = 862.6320056992192\n",
      "Generation 4275: p = 0.9584800063324658\n",
      "Generation 4275: M(n) = 862.6320056992192\n",
      "Generation 4276: p = 0.9584800063324658\n",
      "Generation 4276: M(n) = 862.6320056992192\n",
      "Generation 4277: p = 0.9584800063324658\n",
      "Generation 4277: M(n) = 862.6320056992192\n",
      "Generation 4278: p = 0.9584800063324658\n",
      "Generation 4278: M(n) = 862.6320056992192\n",
      "Generation 4279: p = 0.9584800063324658\n",
      "Generation 4279: M(n) = 862.6320056992192\n",
      "Generation 4280: p = 0.9584800063324658\n",
      "Generation 4280: M(n) = 862.6320056992192\n",
      "Generation 4281: p = 0.9584800063324658\n",
      "Generation 4281: M(n) = 862.6320056992192\n",
      "Generation 4282: p = 0.9584800063324658\n",
      "Generation 4282: M(n) = 862.6320056992192\n",
      "Generation 4283: p = 0.9584800063324658\n",
      "Generation 4283: M(n) = 862.6320056992192\n",
      "Generation 4284: p = 0.9584800063324658\n",
      "Generation 4284: M(n) = 862.6320056992192\n",
      "Generation 4285: p = 0.9584800063324658\n",
      "Generation 4285: M(n) = 862.6320056992192\n",
      "Generation 4286: p = 0.9584800063324658\n",
      "Generation 4286: M(n) = 862.6320056992192\n",
      "Generation 4287: p = 0.9584800063324658\n",
      "Generation 4287: M(n) = 862.6320056992192\n",
      "Generation 4288: p = 0.9584800063324658\n",
      "Generation 4288: M(n) = 862.6320056992192\n",
      "Generation 4289: p = 0.9584800063324658\n",
      "Generation 4289: M(n) = 862.6320056992192\n",
      "Generation 4290: p = 0.9584800063324658\n",
      "Generation 4290: M(n) = 862.6320056992192\n",
      "Generation 4291: p = 0.9584800063324658\n",
      "Generation 4291: M(n) = 862.6320056992192\n",
      "Generation 4292: p = 0.9584800063324658\n",
      "Generation 4292: M(n) = 862.6320056992192\n",
      "Generation 4293: p = 0.9584800063324658\n",
      "Generation 4293: M(n) = 862.6320056992192\n",
      "Generation 4294: p = 0.9584800063324658\n",
      "Generation 4294: M(n) = 862.6320056992192\n",
      "Generation 4295: p = 0.9584800063324658\n",
      "Generation 4295: M(n) = 862.6320056992192\n",
      "Generation 4296: p = 0.9584800063324658\n",
      "Generation 4296: M(n) = 862.6320056992192\n",
      "Generation 4297: p = 0.9584800063324658\n",
      "Generation 4297: M(n) = 862.6320056992192\n",
      "Generation 4298: p = 0.9584800063324658\n",
      "Generation 4298: M(n) = 862.6320056992192\n",
      "Generation 4299: p = 0.9584800063324658\n",
      "Generation 4299: M(n) = 862.6320056992192\n",
      "Generation 4300: p = 0.9584800063324658\n",
      "Generation 4300: M(n) = 862.6320056992192\n",
      "Generation 4301: p = 0.9584800063324658\n",
      "Generation 4301: M(n) = 862.6320056992192\n",
      "Generation 4302: p = 0.9584800063324658\n",
      "Generation 4302: M(n) = 862.6320056992192\n",
      "Generation 4303: p = 0.9584800063324658\n",
      "Generation 4303: M(n) = 862.6320056992192\n",
      "Generation 4304: p = 0.9584800063324658\n",
      "Generation 4304: M(n) = 862.6320056992192\n",
      "Generation 4305: p = 0.9584800063324658\n",
      "Generation 4305: M(n) = 862.6320056992192\n",
      "Generation 4306: p = 0.9584800063324658\n",
      "Generation 4306: M(n) = 862.6320056992192\n",
      "Generation 4307: p = 0.9584800063324658\n",
      "Generation 4307: M(n) = 862.6320056992192\n",
      "Generation 4308: p = 0.9584800063324658\n",
      "Generation 4308: M(n) = 862.6320056992192\n",
      "Generation 4309: p = 0.9584800063324658\n",
      "Generation 4309: M(n) = 862.6320056992192\n",
      "Generation 4310: p = 0.9584800063324658\n",
      "Generation 4310: M(n) = 862.6320056992192\n",
      "Generation 4311: p = 0.9584800063324658\n",
      "Generation 4311: M(n) = 862.6320056992192\n",
      "Generation 4312: p = 0.9584800063324658\n",
      "Generation 4312: M(n) = 862.6320056992192\n",
      "Generation 4313: p = 0.9584800063324658\n",
      "Generation 4313: M(n) = 862.6320056992192\n",
      "Generation 4314: p = 0.9584800063324658\n",
      "Generation 4314: M(n) = 862.6320056992192\n",
      "Generation 4315: p = 0.9584800063324658\n",
      "Generation 4315: M(n) = 862.6320056992192\n",
      "Generation 4316: p = 0.9584800063324658\n",
      "Generation 4316: M(n) = 862.6320056992192\n",
      "Generation 4317: p = 0.9584800063324658\n",
      "Generation 4317: M(n) = 862.6320056992192\n",
      "Generation 4318: p = 0.9584800063324658\n",
      "Generation 4318: M(n) = 862.6320056992192\n",
      "Generation 4319: p = 0.9584800063324658\n",
      "Generation 4319: M(n) = 862.6320056992192\n",
      "Generation 4320: p = 0.9584800063324658\n",
      "Generation 4320: M(n) = 862.6320056992192\n",
      "Generation 4321: p = 0.9584800063324658\n",
      "Generation 4321: M(n) = 862.6320056992192\n",
      "Generation 4322: p = 0.9584800063324658\n",
      "Generation 4322: M(n) = 862.6320056992192\n",
      "Generation 4323: p = 0.9584800063324658\n",
      "Generation 4323: M(n) = 862.6320056992192\n",
      "Generation 4324: p = 0.9584800063324658\n",
      "Generation 4324: M(n) = 862.6320056992192\n",
      "Generation 4325: p = 0.9584800063324658\n",
      "Generation 4325: M(n) = 862.6320056992192\n",
      "Generation 4326: p = 0.9584800063324658\n",
      "Generation 4326: M(n) = 862.6320056992192\n",
      "Generation 4327: p = 0.9584800063324658\n",
      "Generation 4327: M(n) = 862.6320056992192\n",
      "Generation 4328: p = 0.9584800063324658\n",
      "Generation 4328: M(n) = 862.6320056992192\n",
      "Generation 4329: p = 0.9584800063324658\n",
      "Generation 4329: M(n) = 862.6320056992192\n",
      "Generation 4330: p = 0.9584800063324658\n",
      "Generation 4330: M(n) = 862.6320056992192\n",
      "Generation 4331: p = 0.9584800063324658\n",
      "Generation 4331: M(n) = 862.6320056992192\n",
      "Generation 4332: p = 0.9584800063324658\n",
      "Generation 4332: M(n) = 862.6320056992192\n",
      "Generation 4333: p = 0.9584800063324658\n",
      "Generation 4333: M(n) = 862.6320056992192\n",
      "Generation 4334: p = 0.9584800063324658\n",
      "Generation 4334: M(n) = 862.6320056992192\n",
      "Generation 4335: p = 0.9584800063324658\n",
      "Generation 4335: M(n) = 862.6320056992192\n",
      "Generation 4336: p = 0.9584800063324658\n",
      "Generation 4336: M(n) = 862.6320056992192\n",
      "Generation 4337: p = 0.9584800063324658\n",
      "Generation 4337: M(n) = 862.6320056992192\n",
      "Generation 4338: p = 0.9584800063324658\n",
      "Generation 4338: M(n) = 862.6320056992192\n",
      "Generation 4339: p = 0.9584800063324658\n",
      "Generation 4339: M(n) = 862.6320056992192\n",
      "Generation 4340: p = 0.9584800063324658\n",
      "Generation 4340: M(n) = 862.6320056992192\n",
      "Generation 4341: p = 0.9584800063324658\n",
      "Generation 4341: M(n) = 862.6320056992192\n",
      "Generation 4342: p = 0.9584800063324658\n",
      "Generation 4342: M(n) = 862.6320056992192\n",
      "Generation 4343: p = 0.9584800063324658\n",
      "Generation 4343: M(n) = 862.6320056992192\n",
      "Generation 4344: p = 0.9584800063324658\n",
      "Generation 4344: M(n) = 862.6320056992192\n",
      "Generation 4345: p = 0.9584800063324658\n",
      "Generation 4345: M(n) = 862.6320056992192\n",
      "Generation 4346: p = 0.9584800063324658\n",
      "Generation 4346: M(n) = 862.6320056992192\n",
      "Generation 4347: p = 0.9584800063324658\n",
      "Generation 4347: M(n) = 862.6320056992192\n",
      "Generation 4348: p = 0.9584800063324658\n",
      "Generation 4348: M(n) = 862.6320056992192\n",
      "Generation 4349: p = 0.9584800063324658\n",
      "Generation 4349: M(n) = 862.6320056992192\n",
      "Generation 4350: p = 0.9584800063324658\n",
      "Generation 4350: M(n) = 862.6320056992192\n",
      "Generation 4351: p = 0.9584800063324658\n",
      "Generation 4351: M(n) = 862.6320056992192\n",
      "Generation 4352: p = 0.9584800063324658\n",
      "Generation 4352: M(n) = 862.6320056992192\n",
      "Generation 4353: p = 0.9584800063324658\n",
      "Generation 4353: M(n) = 862.6320056992192\n",
      "Generation 4354: p = 0.9584800063324658\n",
      "Generation 4354: M(n) = 862.6320056992192\n",
      "Generation 4355: p = 0.9584800063324658\n",
      "Generation 4355: M(n) = 862.6320056992192\n",
      "Generation 4356: p = 0.9584800063324658\n",
      "Generation 4356: M(n) = 862.6320056992192\n",
      "Generation 4357: p = 0.9584800063324658\n",
      "Generation 4357: M(n) = 862.6320056992192\n",
      "Generation 4358: p = 0.9584800063324658\n",
      "Generation 4358: M(n) = 862.6320056992192\n",
      "Generation 4359: p = 0.9584800063324658\n",
      "Generation 4359: M(n) = 862.6320056992192\n",
      "Generation 4360: p = 0.9584800063324658\n",
      "Generation 4360: M(n) = 862.6320056992192\n",
      "Generation 4361: p = 0.9584800063324658\n",
      "Generation 4361: M(n) = 862.6320056992192\n",
      "Generation 4362: p = 0.9584800063324658\n",
      "Generation 4362: M(n) = 862.6320056992192\n",
      "Generation 4363: p = 0.9584800063324658\n",
      "Generation 4363: M(n) = 862.6320056992192\n",
      "Generation 4364: p = 0.9584800063324658\n",
      "Generation 4364: M(n) = 862.6320056992192\n",
      "Generation 4365: p = 0.9584800063324658\n",
      "Generation 4365: M(n) = 862.6320056992192\n",
      "Generation 4366: p = 0.9584800063324658\n",
      "Generation 4366: M(n) = 862.6320056992192\n",
      "Generation 4367: p = 0.9584800063324658\n",
      "Generation 4367: M(n) = 862.6320056992192\n",
      "Generation 4368: p = 0.9584800063324658\n",
      "Generation 4368: M(n) = 862.6320056992192\n",
      "Generation 4369: p = 0.9584800063324658\n",
      "Generation 4369: M(n) = 862.6320056992192\n",
      "Generation 4370: p = 0.9584800063324658\n",
      "Generation 4370: M(n) = 862.6320056992192\n",
      "Generation 4371: p = 0.9584800063324658\n",
      "Generation 4371: M(n) = 862.6320056992192\n",
      "Generation 4372: p = 0.9584800063324658\n",
      "Generation 4372: M(n) = 862.6320056992192\n",
      "Generation 4373: p = 0.9584800063324658\n",
      "Generation 4373: M(n) = 862.6320056992192\n",
      "Generation 4374: p = 0.9584800063324658\n",
      "Generation 4374: M(n) = 862.6320056992192\n",
      "Generation 4375: p = 0.9584800063324658\n",
      "Generation 4375: M(n) = 862.6320056992192\n",
      "Generation 4376: p = 0.9584800063324658\n",
      "Generation 4376: M(n) = 862.6320056992192\n",
      "Generation 4377: p = 0.9584800063324658\n",
      "Generation 4377: M(n) = 862.6320056992192\n",
      "Generation 4378: p = 0.9584800063324658\n",
      "Generation 4378: M(n) = 862.6320056992192\n",
      "Generation 4379: p = 0.9584800063324658\n",
      "Generation 4379: M(n) = 862.6320056992192\n",
      "Generation 4380: p = 0.9584800063324658\n",
      "Generation 4380: M(n) = 862.6320056992192\n",
      "Generation 4381: p = 0.9584800063324658\n",
      "Generation 4381: M(n) = 862.6320056992192\n",
      "Generation 4382: p = 0.9584800063324658\n",
      "Generation 4382: M(n) = 862.6320056992192\n",
      "Generation 4383: p = 0.9584800063324658\n",
      "Generation 4383: M(n) = 862.6320056992192\n",
      "Generation 4384: p = 0.9584800063324658\n",
      "Generation 4384: M(n) = 862.6320056992192\n",
      "Generation 4385: p = 0.9584800063324658\n",
      "Generation 4385: M(n) = 862.6320056992192\n",
      "Generation 4386: p = 0.9584800063324658\n",
      "Generation 4386: M(n) = 862.6320056992192\n",
      "Generation 4387: p = 0.9584800063324658\n",
      "Generation 4387: M(n) = 862.6320056992192\n",
      "Generation 4388: p = 0.9584800063324658\n",
      "Generation 4388: M(n) = 862.6320056992192\n",
      "Generation 4389: p = 0.9584800063324658\n",
      "Generation 4389: M(n) = 862.6320056992192\n",
      "Generation 4390: p = 0.9584800063324658\n",
      "Generation 4390: M(n) = 862.6320056992192\n",
      "Generation 4391: p = 0.9584800063324658\n",
      "Generation 4391: M(n) = 862.6320056992192\n",
      "Generation 4392: p = 0.9584800063324658\n",
      "Generation 4392: M(n) = 862.6320056992192\n",
      "Generation 4393: p = 0.9584800063324658\n",
      "Generation 4393: M(n) = 862.6320056992192\n",
      "Generation 4394: p = 0.9584800063324658\n",
      "Generation 4394: M(n) = 862.6320056992192\n",
      "Generation 4395: p = 0.9584800063324658\n",
      "Generation 4395: M(n) = 862.6320056992192\n",
      "Generation 4396: p = 0.9584800063324658\n",
      "Generation 4396: M(n) = 862.6320056992192\n",
      "Generation 4397: p = 0.9584800063324658\n",
      "Generation 4397: M(n) = 862.6320056992192\n",
      "Generation 4398: p = 0.9584800063324658\n",
      "Generation 4398: M(n) = 862.6320056992192\n",
      "Generation 4399: p = 0.9584800063324658\n",
      "Generation 4399: M(n) = 862.6320056992192\n",
      "Generation 4400: p = 0.9584800063324658\n",
      "Generation 4400: M(n) = 862.6320056992192\n",
      "Generation 4401: p = 0.9584800063324658\n",
      "Generation 4401: M(n) = 862.6320056992192\n",
      "Generation 4402: p = 0.9584800063324658\n",
      "Generation 4402: M(n) = 862.6320056992192\n",
      "Generation 4403: p = 0.9584800063324658\n",
      "Generation 4403: M(n) = 862.6320056992192\n",
      "Generation 4404: p = 0.9584800063324658\n",
      "Generation 4404: M(n) = 862.6320056992192\n",
      "Generation 4405: p = 0.9584800063324658\n",
      "Generation 4405: M(n) = 862.6320056992192\n",
      "Generation 4406: p = 0.9584800063324658\n",
      "Generation 4406: M(n) = 862.6320056992192\n",
      "Generation 4407: p = 0.9584800063324658\n",
      "Generation 4407: M(n) = 862.6320056992192\n",
      "Generation 4408: p = 0.9584800063324658\n",
      "Generation 4408: M(n) = 862.6320056992192\n",
      "Generation 4409: p = 0.9584800063324658\n",
      "Generation 4409: M(n) = 862.6320056992192\n",
      "Generation 4410: p = 0.9584800063324658\n",
      "Generation 4410: M(n) = 862.6320056992192\n",
      "Generation 4411: p = 0.9584800063324658\n",
      "Generation 4411: M(n) = 862.6320056992192\n",
      "Generation 4412: p = 0.9584800063324658\n",
      "Generation 4412: M(n) = 862.6320056992192\n",
      "Generation 4413: p = 0.9584800063324658\n",
      "Generation 4413: M(n) = 862.6320056992192\n",
      "Generation 4414: p = 0.9584800063324658\n",
      "Generation 4414: M(n) = 862.6320056992192\n",
      "Generation 4415: p = 0.9584800063324658\n",
      "Generation 4415: M(n) = 862.6320056992192\n",
      "Generation 4416: p = 0.9584800063324658\n",
      "Generation 4416: M(n) = 862.6320056992192\n",
      "Generation 4417: p = 0.9584800063324658\n",
      "Generation 4417: M(n) = 862.6320056992192\n",
      "Generation 4418: p = 0.9584800063324658\n",
      "Generation 4418: M(n) = 862.6320056992192\n",
      "Generation 4419: p = 0.9584800063324658\n",
      "Generation 4419: M(n) = 862.6320056992192\n",
      "Generation 4420: p = 0.9584800063324658\n",
      "Generation 4420: M(n) = 862.6320056992192\n",
      "Generation 4421: p = 0.9584800063324658\n",
      "Generation 4421: M(n) = 862.6320056992192\n",
      "Generation 4422: p = 0.9584800063324658\n",
      "Generation 4422: M(n) = 862.6320056992192\n",
      "Generation 4423: p = 0.9584800063324658\n",
      "Generation 4423: M(n) = 862.6320056992192\n",
      "Generation 4424: p = 0.9584800063324658\n",
      "Generation 4424: M(n) = 862.6320056992192\n",
      "Generation 4425: p = 0.9584800063324658\n",
      "Generation 4425: M(n) = 862.6320056992192\n",
      "Generation 4426: p = 0.9584800063324658\n",
      "Generation 4426: M(n) = 862.6320056992192\n",
      "Generation 4427: p = 0.9584800063324658\n",
      "Generation 4427: M(n) = 862.6320056992192\n",
      "Generation 4428: p = 0.9584800063324658\n",
      "Generation 4428: M(n) = 862.6320056992192\n",
      "Generation 4429: p = 0.9584800063324658\n",
      "Generation 4429: M(n) = 862.6320056992192\n",
      "Generation 4430: p = 0.9584800063324658\n",
      "Generation 4430: M(n) = 862.6320056992192\n",
      "Generation 4431: p = 0.9584800063324658\n",
      "Generation 4431: M(n) = 862.6320056992192\n",
      "Generation 4432: p = 0.9584800063324658\n",
      "Generation 4432: M(n) = 862.6320056992192\n",
      "Generation 4433: p = 0.9584800063324658\n",
      "Generation 4433: M(n) = 862.6320056992192\n",
      "Generation 4434: p = 0.9584800063324658\n",
      "Generation 4434: M(n) = 862.6320056992192\n",
      "Generation 4435: p = 0.9584800063324658\n",
      "Generation 4435: M(n) = 862.6320056992192\n",
      "Generation 4436: p = 0.9584800063324658\n",
      "Generation 4436: M(n) = 862.6320056992192\n",
      "Generation 4437: p = 0.9584800063324658\n",
      "Generation 4437: M(n) = 862.6320056992192\n",
      "Generation 4438: p = 0.9584800063324658\n",
      "Generation 4438: M(n) = 862.6320056992192\n",
      "Generation 4439: p = 0.9584800063324658\n",
      "Generation 4439: M(n) = 862.6320056992192\n",
      "Generation 4440: p = 0.9584800063324658\n",
      "Generation 4440: M(n) = 862.6320056992192\n",
      "Generation 4441: p = 0.9584800063324658\n",
      "Generation 4441: M(n) = 862.6320056992192\n",
      "Generation 4442: p = 0.9584800063324658\n",
      "Generation 4442: M(n) = 862.6320056992192\n",
      "Generation 4443: p = 0.9584800063324658\n",
      "Generation 4443: M(n) = 862.6320056992192\n",
      "Generation 4444: p = 0.9584800063324658\n",
      "Generation 4444: M(n) = 862.6320056992192\n",
      "Generation 4445: p = 0.9584800063324658\n",
      "Generation 4445: M(n) = 862.6320056992192\n",
      "Generation 4446: p = 0.9584800063324658\n",
      "Generation 4446: M(n) = 862.6320056992192\n",
      "Generation 4447: p = 0.9584800063324658\n",
      "Generation 4447: M(n) = 862.6320056992192\n",
      "Generation 4448: p = 0.9584800063324658\n",
      "Generation 4448: M(n) = 862.6320056992192\n",
      "Generation 4449: p = 0.9584800063324658\n",
      "Generation 4449: M(n) = 862.6320056992192\n",
      "Generation 4450: p = 0.9584800063324658\n",
      "Generation 4450: M(n) = 862.6320056992192\n",
      "Generation 4451: p = 0.9584800063324658\n",
      "Generation 4451: M(n) = 862.6320056992192\n",
      "Generation 4452: p = 0.9584800063324658\n",
      "Generation 4452: M(n) = 862.6320056992192\n",
      "Generation 4453: p = 0.9584800063324658\n",
      "Generation 4453: M(n) = 862.6320056992192\n",
      "Generation 4454: p = 0.9584800063324658\n",
      "Generation 4454: M(n) = 862.6320056992192\n",
      "Generation 4455: p = 0.9584800063324658\n",
      "Generation 4455: M(n) = 862.6320056992192\n",
      "Generation 4456: p = 0.9584800063324658\n",
      "Generation 4456: M(n) = 862.6320056992192\n",
      "Generation 4457: p = 0.9584800063324658\n",
      "Generation 4457: M(n) = 862.6320056992192\n",
      "Generation 4458: p = 0.9584800063324658\n",
      "Generation 4458: M(n) = 862.6320056992192\n",
      "Generation 4459: p = 0.9584800063324658\n",
      "Generation 4459: M(n) = 862.6320056992192\n",
      "Generation 4460: p = 0.9584800063324658\n",
      "Generation 4460: M(n) = 862.6320056992192\n",
      "Generation 4461: p = 0.9584800063324658\n",
      "Generation 4461: M(n) = 862.6320056992192\n",
      "Generation 4462: p = 0.9584800063324658\n",
      "Generation 4462: M(n) = 862.6320056992192\n",
      "Generation 4463: p = 0.9584800063324658\n",
      "Generation 4463: M(n) = 862.6320056992192\n",
      "Generation 4464: p = 0.9584800063324658\n",
      "Generation 4464: M(n) = 862.6320056992192\n",
      "Generation 4465: p = 0.9584800063324658\n",
      "Generation 4465: M(n) = 862.6320056992192\n",
      "Generation 4466: p = 0.9584800063324658\n",
      "Generation 4466: M(n) = 862.6320056992192\n",
      "Generation 4467: p = 0.9584800063324658\n",
      "Generation 4467: M(n) = 862.6320056992192\n",
      "Generation 4468: p = 0.9584800063324658\n",
      "Generation 4468: M(n) = 862.6320056992192\n",
      "Generation 4469: p = 0.9584800063324658\n",
      "Generation 4469: M(n) = 862.6320056992192\n",
      "Generation 4470: p = 0.9584800063324658\n",
      "Generation 4470: M(n) = 862.6320056992192\n",
      "Generation 4471: p = 0.9584800063324658\n",
      "Generation 4471: M(n) = 862.6320056992192\n",
      "Generation 4472: p = 0.9584800063324658\n",
      "Generation 4472: M(n) = 862.6320056992192\n",
      "Generation 4473: p = 0.9584800063324658\n",
      "Generation 4473: M(n) = 862.6320056992192\n",
      "Generation 4474: p = 0.9584800063324658\n",
      "Generation 4474: M(n) = 862.6320056992192\n",
      "Generation 4475: p = 0.9584800063324658\n",
      "Generation 4475: M(n) = 862.6320056992192\n",
      "Generation 4476: p = 0.9584800063324658\n",
      "Generation 4476: M(n) = 862.6320056992192\n",
      "Generation 4477: p = 0.9584800063324658\n",
      "Generation 4477: M(n) = 862.6320056992192\n",
      "Generation 4478: p = 0.9584800063324658\n",
      "Generation 4478: M(n) = 862.6320056992192\n",
      "Generation 4479: p = 0.9584800063324658\n",
      "Generation 4479: M(n) = 862.6320056992192\n",
      "Generation 4480: p = 0.9584800063324658\n",
      "Generation 4480: M(n) = 862.6320056992192\n",
      "Generation 4481: p = 0.9584800063324658\n",
      "Generation 4481: M(n) = 862.6320056992192\n",
      "Generation 4482: p = 0.9584800063324658\n",
      "Generation 4482: M(n) = 862.6320056992192\n",
      "Generation 4483: p = 0.9584800063324658\n",
      "Generation 4483: M(n) = 862.6320056992192\n",
      "Generation 4484: p = 0.9584800063324658\n",
      "Generation 4484: M(n) = 862.6320056992192\n",
      "Generation 4485: p = 0.9584800063324658\n",
      "Generation 4485: M(n) = 862.6320056992192\n",
      "Generation 4486: p = 0.9584800063324658\n",
      "Generation 4486: M(n) = 862.6320056992192\n",
      "Generation 4487: p = 0.9584800063324658\n",
      "Generation 4487: M(n) = 862.6320056992192\n",
      "Generation 4488: p = 0.9584800063324658\n",
      "Generation 4488: M(n) = 862.6320056992192\n",
      "Generation 4489: p = 0.9584800063324658\n",
      "Generation 4489: M(n) = 862.6320056992192\n",
      "Generation 4490: p = 0.9584800063324658\n",
      "Generation 4490: M(n) = 862.6320056992192\n",
      "Generation 4491: p = 0.9584800063324658\n",
      "Generation 4491: M(n) = 862.6320056992192\n",
      "Generation 4492: p = 0.9584800063324658\n",
      "Generation 4492: M(n) = 862.6320056992192\n",
      "Generation 4493: p = 0.9584800063324658\n",
      "Generation 4493: M(n) = 862.6320056992192\n",
      "Generation 4494: p = 0.9584800063324658\n",
      "Generation 4494: M(n) = 862.6320056992192\n",
      "Generation 4495: p = 0.9584800063324658\n",
      "Generation 4495: M(n) = 862.6320056992192\n",
      "Generation 4496: p = 0.9584800063324658\n",
      "Generation 4496: M(n) = 862.6320056992192\n",
      "Generation 4497: p = 0.9584800063324658\n",
      "Generation 4497: M(n) = 862.6320056992192\n",
      "Generation 4498: p = 0.9584800063324658\n",
      "Generation 4498: M(n) = 862.6320056992192\n",
      "Generation 4499: p = 0.9584800063324658\n",
      "Generation 4499: M(n) = 862.6320056992192\n",
      "Generation 4500: p = 0.9584800063324658\n",
      "Generation 4500: M(n) = 862.6320056992192\n",
      "Generation 4501: p = 0.9584800063324658\n",
      "Generation 4501: M(n) = 862.6320056992192\n",
      "Generation 4502: p = 0.9584800063324658\n",
      "Generation 4502: M(n) = 862.6320056992192\n",
      "Generation 4503: p = 0.9584800063324658\n",
      "Generation 4503: M(n) = 862.6320056992192\n",
      "Generation 4504: p = 0.9584800063324658\n",
      "Generation 4504: M(n) = 862.6320056992192\n",
      "Generation 4505: p = 0.9584800063324658\n",
      "Generation 4505: M(n) = 862.6320056992192\n",
      "Generation 4506: p = 0.9584800063324658\n",
      "Generation 4506: M(n) = 862.6320056992192\n",
      "Generation 4507: p = 0.9584800063324658\n",
      "Generation 4507: M(n) = 862.6320056992192\n",
      "Generation 4508: p = 0.9584800063324658\n",
      "Generation 4508: M(n) = 862.6320056992192\n",
      "Generation 4509: p = 0.9584800063324658\n",
      "Generation 4509: M(n) = 862.6320056992192\n",
      "Generation 4510: p = 0.9584800063324658\n",
      "Generation 4510: M(n) = 862.6320056992192\n",
      "Generation 4511: p = 0.9584800063324658\n",
      "Generation 4511: M(n) = 862.6320056992192\n",
      "Generation 4512: p = 0.9584800063324658\n",
      "Generation 4512: M(n) = 862.6320056992192\n",
      "Generation 4513: p = 0.9584800063324658\n",
      "Generation 4513: M(n) = 862.6320056992192\n",
      "Generation 4514: p = 0.9584800063324658\n",
      "Generation 4514: M(n) = 862.6320056992192\n",
      "Generation 4515: p = 0.9584800063324658\n",
      "Generation 4515: M(n) = 862.6320056992192\n",
      "Generation 4516: p = 0.9584800063324658\n",
      "Generation 4516: M(n) = 862.6320056992192\n",
      "Generation 4517: p = 0.9584800063324658\n",
      "Generation 4517: M(n) = 862.6320056992192\n",
      "Generation 4518: p = 0.9584800063324658\n",
      "Generation 4518: M(n) = 862.6320056992192\n",
      "Generation 4519: p = 0.9584800063324658\n",
      "Generation 4519: M(n) = 862.6320056992192\n",
      "Generation 4520: p = 0.9584800063324658\n",
      "Generation 4520: M(n) = 862.6320056992192\n",
      "Generation 4521: p = 0.9584800063324658\n",
      "Generation 4521: M(n) = 862.6320056992192\n",
      "Generation 4522: p = 0.9584800063324658\n",
      "Generation 4522: M(n) = 862.6320056992192\n",
      "Generation 4523: p = 0.9584800063324658\n",
      "Generation 4523: M(n) = 862.6320056992192\n",
      "Generation 4524: p = 0.9584800063324658\n",
      "Generation 4524: M(n) = 862.6320056992192\n",
      "Generation 4525: p = 0.9584800063324658\n",
      "Generation 4525: M(n) = 862.6320056992192\n",
      "Generation 4526: p = 0.9584800063324658\n",
      "Generation 4526: M(n) = 862.6320056992192\n",
      "Generation 4527: p = 0.9584800063324658\n",
      "Generation 4527: M(n) = 862.6320056992192\n",
      "Generation 4528: p = 0.9584800063324658\n",
      "Generation 4528: M(n) = 862.6320056992192\n",
      "Generation 4529: p = 0.9584800063324658\n",
      "Generation 4529: M(n) = 862.6320056992192\n",
      "Generation 4530: p = 0.9584800063324658\n",
      "Generation 4530: M(n) = 862.6320056992192\n",
      "Generation 4531: p = 0.9584800063324658\n",
      "Generation 4531: M(n) = 862.6320056992192\n",
      "Generation 4532: p = 0.9584800063324658\n",
      "Generation 4532: M(n) = 862.6320056992192\n",
      "Generation 4533: p = 0.9584800063324658\n",
      "Generation 4533: M(n) = 862.6320056992192\n",
      "Generation 4534: p = 0.9584800063324658\n",
      "Generation 4534: M(n) = 862.6320056992192\n",
      "Generation 4535: p = 0.9584800063324658\n",
      "Generation 4535: M(n) = 862.6320056992192\n",
      "Generation 4536: p = 0.9584800063324658\n",
      "Generation 4536: M(n) = 862.6320056992192\n",
      "Generation 4537: p = 0.9584800063324658\n",
      "Generation 4537: M(n) = 862.6320056992192\n",
      "Generation 4538: p = 0.9584800063324658\n",
      "Generation 4538: M(n) = 862.6320056992192\n",
      "Generation 4539: p = 0.9584800063324658\n",
      "Generation 4539: M(n) = 862.6320056992192\n",
      "Generation 4540: p = 0.9584800063324658\n",
      "Generation 4540: M(n) = 862.6320056992192\n",
      "Generation 4541: p = 0.9584800063324658\n",
      "Generation 4541: M(n) = 862.6320056992192\n",
      "Generation 4542: p = 0.9584800063324658\n",
      "Generation 4542: M(n) = 862.6320056992192\n",
      "Generation 4543: p = 0.9584800063324658\n",
      "Generation 4543: M(n) = 862.6320056992192\n",
      "Generation 4544: p = 0.9584800063324658\n",
      "Generation 4544: M(n) = 862.6320056992192\n",
      "Generation 4545: p = 0.9584800063324658\n",
      "Generation 4545: M(n) = 862.6320056992192\n",
      "Generation 4546: p = 0.9584800063324658\n",
      "Generation 4546: M(n) = 862.6320056992192\n",
      "Generation 4547: p = 0.9584800063324658\n",
      "Generation 4547: M(n) = 862.6320056992192\n",
      "Generation 4548: p = 0.9584800063324658\n",
      "Generation 4548: M(n) = 862.6320056992192\n",
      "Generation 4549: p = 0.9584800063324658\n",
      "Generation 4549: M(n) = 862.6320056992192\n",
      "Generation 4550: p = 0.9584800063324658\n",
      "Generation 4550: M(n) = 862.6320056992192\n",
      "Generation 4551: p = 0.9584800063324658\n",
      "Generation 4551: M(n) = 862.6320056992192\n",
      "Generation 4552: p = 0.9584800063324658\n",
      "Generation 4552: M(n) = 862.6320056992192\n",
      "Generation 4553: p = 0.9584800063324658\n",
      "Generation 4553: M(n) = 862.6320056992192\n",
      "Generation 4554: p = 0.9584800063324658\n",
      "Generation 4554: M(n) = 862.6320056992192\n",
      "Generation 4555: p = 0.9584800063324658\n",
      "Generation 4555: M(n) = 862.6320056992192\n",
      "Generation 4556: p = 0.9584800063324658\n",
      "Generation 4556: M(n) = 862.6320056992192\n",
      "Generation 4557: p = 0.9584800063324658\n",
      "Generation 4557: M(n) = 862.6320056992192\n",
      "Generation 4558: p = 0.9584800063324658\n",
      "Generation 4558: M(n) = 862.6320056992192\n",
      "Generation 4559: p = 0.9584800063324658\n",
      "Generation 4559: M(n) = 862.6320056992192\n",
      "Generation 4560: p = 0.9584800063324658\n",
      "Generation 4560: M(n) = 862.6320056992192\n",
      "Generation 4561: p = 0.9584800063324658\n",
      "Generation 4561: M(n) = 862.6320056992192\n",
      "Generation 4562: p = 0.9584800063324658\n",
      "Generation 4562: M(n) = 862.6320056992192\n",
      "Generation 4563: p = 0.9584800063324658\n",
      "Generation 4563: M(n) = 862.6320056992192\n",
      "Generation 4564: p = 0.9584800063324658\n",
      "Generation 4564: M(n) = 862.6320056992192\n",
      "Generation 4565: p = 0.9584800063324658\n",
      "Generation 4565: M(n) = 862.6320056992192\n",
      "Generation 4566: p = 0.9584800063324658\n",
      "Generation 4566: M(n) = 862.6320056992192\n",
      "Generation 4567: p = 0.9584800063324658\n",
      "Generation 4567: M(n) = 862.6320056992192\n",
      "Generation 4568: p = 0.9584800063324658\n",
      "Generation 4568: M(n) = 862.6320056992192\n",
      "Generation 4569: p = 0.9584800063324658\n",
      "Generation 4569: M(n) = 862.6320056992192\n",
      "Generation 4570: p = 0.9584800063324658\n",
      "Generation 4570: M(n) = 862.6320056992192\n",
      "Generation 4571: p = 0.9584800063324658\n",
      "Generation 4571: M(n) = 862.6320056992192\n",
      "Generation 4572: p = 0.9584800063324658\n",
      "Generation 4572: M(n) = 862.6320056992192\n",
      "Generation 4573: p = 0.9584800063324658\n",
      "Generation 4573: M(n) = 862.6320056992192\n",
      "Generation 4574: p = 0.9584800063324658\n",
      "Generation 4574: M(n) = 862.6320056992192\n",
      "Generation 4575: p = 0.9584800063324658\n",
      "Generation 4575: M(n) = 862.6320056992192\n",
      "Generation 4576: p = 0.9584800063324658\n",
      "Generation 4576: M(n) = 862.6320056992192\n",
      "Generation 4577: p = 0.9584800063324658\n",
      "Generation 4577: M(n) = 862.6320056992192\n",
      "Generation 4578: p = 0.9584800063324658\n",
      "Generation 4578: M(n) = 862.6320056992192\n",
      "Generation 4579: p = 0.9584800063324658\n",
      "Generation 4579: M(n) = 862.6320056992192\n",
      "Generation 4580: p = 0.9584800063324658\n",
      "Generation 4580: M(n) = 862.6320056992192\n",
      "Generation 4581: p = 0.9584800063324658\n",
      "Generation 4581: M(n) = 862.6320056992192\n",
      "Generation 4582: p = 0.9584800063324658\n",
      "Generation 4582: M(n) = 862.6320056992192\n",
      "Generation 4583: p = 0.9584800063324658\n",
      "Generation 4583: M(n) = 862.6320056992192\n",
      "Generation 4584: p = 0.9584800063324658\n",
      "Generation 4584: M(n) = 862.6320056992192\n",
      "Generation 4585: p = 0.9584800063324658\n",
      "Generation 4585: M(n) = 862.6320056992192\n",
      "Generation 4586: p = 0.9584800063324658\n",
      "Generation 4586: M(n) = 862.6320056992192\n",
      "Generation 4587: p = 0.9584800063324658\n",
      "Generation 4587: M(n) = 862.6320056992192\n",
      "Generation 4588: p = 0.9584800063324658\n",
      "Generation 4588: M(n) = 862.6320056992192\n",
      "Generation 4589: p = 0.9584800063324658\n",
      "Generation 4589: M(n) = 862.6320056992192\n",
      "Generation 4590: p = 0.9584800063324658\n",
      "Generation 4590: M(n) = 862.6320056992192\n",
      "Generation 4591: p = 0.9584800063324658\n",
      "Generation 4591: M(n) = 862.6320056992192\n",
      "Generation 4592: p = 0.9584800063324658\n",
      "Generation 4592: M(n) = 862.6320056992192\n",
      "Generation 4593: p = 0.9584800063324658\n",
      "Generation 4593: M(n) = 862.6320056992192\n",
      "Generation 4594: p = 0.9584800063324658\n",
      "Generation 4594: M(n) = 862.6320056992192\n",
      "Generation 4595: p = 0.9584800063324658\n",
      "Generation 4595: M(n) = 862.6320056992192\n",
      "Generation 4596: p = 0.9584800063324658\n",
      "Generation 4596: M(n) = 862.6320056992192\n",
      "Generation 4597: p = 0.9584800063324658\n",
      "Generation 4597: M(n) = 862.6320056992192\n",
      "Generation 4598: p = 0.9584800063324658\n",
      "Generation 4598: M(n) = 862.6320056992192\n",
      "Generation 4599: p = 0.9584800063324658\n",
      "Generation 4599: M(n) = 862.6320056992192\n",
      "Generation 4600: p = 0.9584800063324658\n",
      "Generation 4600: M(n) = 862.6320056992192\n",
      "Generation 4601: p = 0.9584800063324658\n",
      "Generation 4601: M(n) = 862.6320056992192\n",
      "Generation 4602: p = 0.9584800063324658\n",
      "Generation 4602: M(n) = 862.6320056992192\n",
      "Generation 4603: p = 0.9584800063324658\n",
      "Generation 4603: M(n) = 862.6320056992192\n",
      "Generation 4604: p = 0.9584800063324658\n",
      "Generation 4604: M(n) = 862.6320056992192\n",
      "Generation 4605: p = 0.9584800063324658\n",
      "Generation 4605: M(n) = 862.6320056992192\n",
      "Generation 4606: p = 0.9584800063324658\n",
      "Generation 4606: M(n) = 862.6320056992192\n",
      "Generation 4607: p = 0.9584800063324658\n",
      "Generation 4607: M(n) = 862.6320056992192\n",
      "Generation 4608: p = 0.9584800063324658\n",
      "Generation 4608: M(n) = 862.6320056992192\n",
      "Generation 4609: p = 0.9584800063324658\n",
      "Generation 4609: M(n) = 862.6320056992192\n",
      "Generation 4610: p = 0.9584800063324658\n",
      "Generation 4610: M(n) = 862.6320056992192\n",
      "Generation 4611: p = 0.9584800063324658\n",
      "Generation 4611: M(n) = 862.6320056992192\n",
      "Generation 4612: p = 0.9584800063324658\n",
      "Generation 4612: M(n) = 862.6320056992192\n",
      "Generation 4613: p = 0.9584800063324658\n",
      "Generation 4613: M(n) = 862.6320056992192\n",
      "Generation 4614: p = 0.9584800063324658\n",
      "Generation 4614: M(n) = 862.6320056992192\n",
      "Generation 4615: p = 0.9584800063324658\n",
      "Generation 4615: M(n) = 862.6320056992192\n",
      "Generation 4616: p = 0.9584800063324658\n",
      "Generation 4616: M(n) = 862.6320056992192\n",
      "Generation 4617: p = 0.9584800063324658\n",
      "Generation 4617: M(n) = 862.6320056992192\n",
      "Generation 4618: p = 0.9584800063324658\n",
      "Generation 4618: M(n) = 862.6320056992192\n",
      "Generation 4619: p = 0.9584800063324658\n",
      "Generation 4619: M(n) = 862.6320056992192\n",
      "Generation 4620: p = 0.9584800063324658\n",
      "Generation 4620: M(n) = 862.6320056992192\n",
      "Generation 4621: p = 0.9584800063324658\n",
      "Generation 4621: M(n) = 862.6320056992192\n",
      "Generation 4622: p = 0.9584800063324658\n",
      "Generation 4622: M(n) = 862.6320056992192\n",
      "Generation 4623: p = 0.9584800063324658\n",
      "Generation 4623: M(n) = 862.6320056992192\n",
      "Generation 4624: p = 0.9584800063324658\n",
      "Generation 4624: M(n) = 862.6320056992192\n",
      "Generation 4625: p = 0.9584800063324658\n",
      "Generation 4625: M(n) = 862.6320056992192\n",
      "Generation 4626: p = 0.9584800063324658\n",
      "Generation 4626: M(n) = 862.6320056992192\n",
      "Generation 4627: p = 0.9584800063324658\n",
      "Generation 4627: M(n) = 862.6320056992192\n",
      "Generation 4628: p = 0.9584800063324658\n",
      "Generation 4628: M(n) = 862.6320056992192\n",
      "Generation 4629: p = 0.9584800063324658\n",
      "Generation 4629: M(n) = 862.6320056992192\n",
      "Generation 4630: p = 0.9584800063324658\n",
      "Generation 4630: M(n) = 862.6320056992192\n",
      "Generation 4631: p = 0.9584800063324658\n",
      "Generation 4631: M(n) = 862.6320056992192\n",
      "Generation 4632: p = 0.9584800063324658\n",
      "Generation 4632: M(n) = 862.6320056992192\n",
      "Generation 4633: p = 0.9584800063324658\n",
      "Generation 4633: M(n) = 862.6320056992192\n",
      "Generation 4634: p = 0.9584800063324658\n",
      "Generation 4634: M(n) = 862.6320056992192\n",
      "Generation 4635: p = 0.9584800063324658\n",
      "Generation 4635: M(n) = 862.6320056992192\n",
      "Generation 4636: p = 0.9584800063324658\n",
      "Generation 4636: M(n) = 862.6320056992192\n",
      "Generation 4637: p = 0.9584800063324658\n",
      "Generation 4637: M(n) = 862.6320056992192\n",
      "Generation 4638: p = 0.9584800063324658\n",
      "Generation 4638: M(n) = 862.6320056992192\n",
      "Generation 4639: p = 0.9584800063324658\n",
      "Generation 4639: M(n) = 862.6320056992192\n",
      "Generation 4640: p = 0.9584800063324658\n",
      "Generation 4640: M(n) = 862.6320056992192\n",
      "Generation 4641: p = 0.9584800063324658\n",
      "Generation 4641: M(n) = 862.6320056992192\n",
      "Generation 4642: p = 0.9584800063324658\n",
      "Generation 4642: M(n) = 862.6320056992192\n",
      "Generation 4643: p = 0.9584800063324658\n",
      "Generation 4643: M(n) = 862.6320056992192\n",
      "Generation 4644: p = 0.9584800063324658\n",
      "Generation 4644: M(n) = 862.6320056992192\n",
      "Generation 4645: p = 0.9584800063324658\n",
      "Generation 4645: M(n) = 862.6320056992192\n",
      "Generation 4646: p = 0.9584800063324658\n",
      "Generation 4646: M(n) = 862.6320056992192\n",
      "Generation 4647: p = 0.9584800063324658\n",
      "Generation 4647: M(n) = 862.6320056992192\n",
      "Generation 4648: p = 0.9584800063324658\n",
      "Generation 4648: M(n) = 862.6320056992192\n",
      "Generation 4649: p = 0.9584800063324658\n",
      "Generation 4649: M(n) = 862.6320056992192\n",
      "Generation 4650: p = 0.9584800063324658\n",
      "Generation 4650: M(n) = 862.6320056992192\n",
      "Generation 4651: p = 0.9584800063324658\n",
      "Generation 4651: M(n) = 862.6320056992192\n",
      "Generation 4652: p = 0.9584800063324658\n",
      "Generation 4652: M(n) = 862.6320056992192\n",
      "Generation 4653: p = 0.9584800063324658\n",
      "Generation 4653: M(n) = 862.6320056992192\n",
      "Generation 4654: p = 0.9584800063324658\n",
      "Generation 4654: M(n) = 862.6320056992192\n",
      "Generation 4655: p = 0.9584800063324658\n",
      "Generation 4655: M(n) = 862.6320056992192\n",
      "Generation 4656: p = 0.9584800063324658\n",
      "Generation 4656: M(n) = 862.6320056992192\n",
      "Generation 4657: p = 0.9584800063324658\n",
      "Generation 4657: M(n) = 862.6320056992192\n",
      "Generation 4658: p = 0.9584800063324658\n",
      "Generation 4658: M(n) = 862.6320056992192\n",
      "Generation 4659: p = 0.9584800063324658\n",
      "Generation 4659: M(n) = 862.6320056992192\n",
      "Generation 4660: p = 0.9584800063324658\n",
      "Generation 4660: M(n) = 862.6320056992192\n",
      "Generation 4661: p = 0.9584800063324658\n",
      "Generation 4661: M(n) = 862.6320056992192\n",
      "Generation 4662: p = 0.9584800063324658\n",
      "Generation 4662: M(n) = 862.6320056992192\n",
      "Generation 4663: p = 0.9584800063324658\n",
      "Generation 4663: M(n) = 862.6320056992192\n",
      "Generation 4664: p = 0.9584800063324658\n",
      "Generation 4664: M(n) = 862.6320056992192\n",
      "Generation 4665: p = 0.9584800063324658\n",
      "Generation 4665: M(n) = 862.6320056992192\n",
      "Generation 4666: p = 0.9584800063324658\n",
      "Generation 4666: M(n) = 862.6320056992192\n",
      "Generation 4667: p = 0.9584800063324658\n",
      "Generation 4667: M(n) = 862.6320056992192\n",
      "Generation 4668: p = 0.9584800063324658\n",
      "Generation 4668: M(n) = 862.6320056992192\n",
      "Generation 4669: p = 0.9584800063324658\n",
      "Generation 4669: M(n) = 862.6320056992192\n",
      "Generation 4670: p = 0.9584800063324658\n",
      "Generation 4670: M(n) = 862.6320056992192\n",
      "Generation 4671: p = 0.9584800063324658\n",
      "Generation 4671: M(n) = 862.6320056992192\n",
      "Generation 4672: p = 0.9584800063324658\n",
      "Generation 4672: M(n) = 862.6320056992192\n",
      "Generation 4673: p = 0.9584800063324658\n",
      "Generation 4673: M(n) = 862.6320056992192\n",
      "Generation 4674: p = 0.9584800063324658\n",
      "Generation 4674: M(n) = 862.6320056992192\n",
      "Generation 4675: p = 0.9584800063324658\n",
      "Generation 4675: M(n) = 862.6320056992192\n",
      "Generation 4676: p = 0.9584800063324658\n",
      "Generation 4676: M(n) = 862.6320056992192\n",
      "Generation 4677: p = 0.9584800063324658\n",
      "Generation 4677: M(n) = 862.6320056992192\n",
      "Generation 4678: p = 0.9584800063324658\n",
      "Generation 4678: M(n) = 862.6320056992192\n",
      "Generation 4679: p = 0.9584800063324658\n",
      "Generation 4679: M(n) = 862.6320056992192\n",
      "Generation 4680: p = 0.9584800063324658\n",
      "Generation 4680: M(n) = 862.6320056992192\n",
      "Generation 4681: p = 0.9584800063324658\n",
      "Generation 4681: M(n) = 862.6320056992192\n",
      "Generation 4682: p = 0.9584800063324658\n",
      "Generation 4682: M(n) = 862.6320056992192\n",
      "Generation 4683: p = 0.9584800063324658\n",
      "Generation 4683: M(n) = 862.6320056992192\n",
      "Generation 4684: p = 0.9584800063324658\n",
      "Generation 4684: M(n) = 862.6320056992192\n",
      "Generation 4685: p = 0.9584800063324658\n",
      "Generation 4685: M(n) = 862.6320056992192\n",
      "Generation 4686: p = 0.9584800063324658\n",
      "Generation 4686: M(n) = 862.6320056992192\n",
      "Generation 4687: p = 0.9584800063324658\n",
      "Generation 4687: M(n) = 862.6320056992192\n",
      "Generation 4688: p = 0.9584800063324658\n",
      "Generation 4688: M(n) = 862.6320056992192\n",
      "Generation 4689: p = 0.9584800063324658\n",
      "Generation 4689: M(n) = 862.6320056992192\n",
      "Generation 4690: p = 0.9584800063324658\n",
      "Generation 4690: M(n) = 862.6320056992192\n",
      "Generation 4691: p = 0.9584800063324658\n",
      "Generation 4691: M(n) = 862.6320056992192\n",
      "Generation 4692: p = 0.9584800063324658\n",
      "Generation 4692: M(n) = 862.6320056992192\n",
      "Generation 4693: p = 0.9584800063324658\n",
      "Generation 4693: M(n) = 862.6320056992192\n",
      "Generation 4694: p = 0.9584800063324658\n",
      "Generation 4694: M(n) = 862.6320056992192\n",
      "Generation 4695: p = 0.9584800063324658\n",
      "Generation 4695: M(n) = 862.6320056992192\n",
      "Generation 4696: p = 0.9584800063324658\n",
      "Generation 4696: M(n) = 862.6320056992192\n",
      "Generation 4697: p = 0.9584800063324658\n",
      "Generation 4697: M(n) = 862.6320056992192\n",
      "Generation 4698: p = 0.9584800063324658\n",
      "Generation 4698: M(n) = 862.6320056992192\n",
      "Generation 4699: p = 0.9584800063324658\n",
      "Generation 4699: M(n) = 862.6320056992192\n",
      "Generation 4700: p = 0.9584800063324658\n",
      "Generation 4700: M(n) = 862.6320056992192\n",
      "Generation 4701: p = 0.9584800063324658\n",
      "Generation 4701: M(n) = 862.6320056992192\n",
      "Generation 4702: p = 0.9584800063324658\n",
      "Generation 4702: M(n) = 862.6320056992192\n",
      "Generation 4703: p = 0.9584800063324658\n",
      "Generation 4703: M(n) = 862.6320056992192\n",
      "Generation 4704: p = 0.9584800063324658\n",
      "Generation 4704: M(n) = 862.6320056992192\n",
      "Generation 4705: p = 0.9584800063324658\n",
      "Generation 4705: M(n) = 862.6320056992192\n",
      "Generation 4706: p = 0.9584800063324658\n",
      "Generation 4706: M(n) = 862.6320056992192\n",
      "Generation 4707: p = 0.9584800063324658\n",
      "Generation 4707: M(n) = 862.6320056992192\n",
      "Generation 4708: p = 0.9584800063324658\n",
      "Generation 4708: M(n) = 862.6320056992192\n",
      "Generation 4709: p = 0.9584800063324658\n",
      "Generation 4709: M(n) = 862.6320056992192\n",
      "Generation 4710: p = 0.9584800063324658\n",
      "Generation 4710: M(n) = 862.6320056992192\n",
      "Generation 4711: p = 0.9584800063324658\n",
      "Generation 4711: M(n) = 862.6320056992192\n",
      "Generation 4712: p = 0.9584800063324658\n",
      "Generation 4712: M(n) = 862.6320056992192\n",
      "Generation 4713: p = 0.9584800063324658\n",
      "Generation 4713: M(n) = 862.6320056992192\n",
      "Generation 4714: p = 0.9584800063324658\n",
      "Generation 4714: M(n) = 862.6320056992192\n",
      "Generation 4715: p = 0.9584800063324658\n",
      "Generation 4715: M(n) = 862.6320056992192\n",
      "Generation 4716: p = 0.9584800063324658\n",
      "Generation 4716: M(n) = 862.6320056992192\n",
      "Generation 4717: p = 0.9584800063324658\n",
      "Generation 4717: M(n) = 862.6320056992192\n",
      "Generation 4718: p = 0.9584800063324658\n",
      "Generation 4718: M(n) = 862.6320056992192\n",
      "Generation 4719: p = 0.9584800063324658\n",
      "Generation 4719: M(n) = 862.6320056992192\n",
      "Generation 4720: p = 0.9584800063324658\n",
      "Generation 4720: M(n) = 862.6320056992192\n",
      "Generation 4721: p = 0.9584800063324658\n",
      "Generation 4721: M(n) = 862.6320056992192\n",
      "Generation 4722: p = 0.9584800063324658\n",
      "Generation 4722: M(n) = 862.6320056992192\n",
      "Generation 4723: p = 0.9584800063324658\n",
      "Generation 4723: M(n) = 862.6320056992192\n",
      "Generation 4724: p = 0.9584800063324658\n",
      "Generation 4724: M(n) = 862.6320056992192\n",
      "Generation 4725: p = 0.9584800063324658\n",
      "Generation 4725: M(n) = 862.6320056992192\n",
      "Generation 4726: p = 0.9584800063324658\n",
      "Generation 4726: M(n) = 862.6320056992192\n",
      "Generation 4727: p = 0.9584800063324658\n",
      "Generation 4727: M(n) = 862.6320056992192\n",
      "Generation 4728: p = 0.9584800063324658\n",
      "Generation 4728: M(n) = 862.6320056992192\n",
      "Generation 4729: p = 0.9584800063324658\n",
      "Generation 4729: M(n) = 862.6320056992192\n",
      "Generation 4730: p = 0.9584800063324658\n",
      "Generation 4730: M(n) = 862.6320056992192\n",
      "Generation 4731: p = 0.9584800063324658\n",
      "Generation 4731: M(n) = 862.6320056992192\n",
      "Generation 4732: p = 0.9584800063324658\n",
      "Generation 4732: M(n) = 862.6320056992192\n",
      "Generation 4733: p = 0.9584800063324658\n",
      "Generation 4733: M(n) = 862.6320056992192\n",
      "Generation 4734: p = 0.9584800063324658\n",
      "Generation 4734: M(n) = 862.6320056992192\n",
      "Generation 4735: p = 0.9584800063324658\n",
      "Generation 4735: M(n) = 862.6320056992192\n",
      "Generation 4736: p = 0.9584800063324658\n",
      "Generation 4736: M(n) = 862.6320056992192\n",
      "Generation 4737: p = 0.9584800063324658\n",
      "Generation 4737: M(n) = 862.6320056992192\n",
      "Generation 4738: p = 0.9584800063324658\n",
      "Generation 4738: M(n) = 862.6320056992192\n",
      "Generation 4739: p = 0.9584800063324658\n",
      "Generation 4739: M(n) = 862.6320056992192\n",
      "Generation 4740: p = 0.9584800063324658\n",
      "Generation 4740: M(n) = 862.6320056992192\n",
      "Generation 4741: p = 0.9584800063324658\n",
      "Generation 4741: M(n) = 862.6320056992192\n",
      "Generation 4742: p = 0.9584800063324658\n",
      "Generation 4742: M(n) = 862.6320056992192\n",
      "Generation 4743: p = 0.9584800063324658\n",
      "Generation 4743: M(n) = 862.6320056992192\n",
      "Generation 4744: p = 0.9584800063324658\n",
      "Generation 4744: M(n) = 862.6320056992192\n",
      "Generation 4745: p = 0.9584800063324658\n",
      "Generation 4745: M(n) = 862.6320056992192\n",
      "Generation 4746: p = 0.9584800063324658\n",
      "Generation 4746: M(n) = 862.6320056992192\n",
      "Generation 4747: p = 0.9584800063324658\n",
      "Generation 4747: M(n) = 862.6320056992192\n",
      "Generation 4748: p = 0.9584800063324658\n",
      "Generation 4748: M(n) = 862.6320056992192\n",
      "Generation 4749: p = 0.9584800063324658\n",
      "Generation 4749: M(n) = 862.6320056992192\n",
      "Generation 4750: p = 0.9584800063324658\n",
      "Generation 4750: M(n) = 862.6320056992192\n",
      "Generation 4751: p = 0.9584800063324658\n",
      "Generation 4751: M(n) = 862.6320056992192\n",
      "Generation 4752: p = 0.9584800063324658\n",
      "Generation 4752: M(n) = 862.6320056992192\n",
      "Generation 4753: p = 0.9584800063324658\n",
      "Generation 4753: M(n) = 862.6320056992192\n",
      "Generation 4754: p = 0.9584800063324658\n",
      "Generation 4754: M(n) = 862.6320056992192\n",
      "Generation 4755: p = 0.9584800063324658\n",
      "Generation 4755: M(n) = 862.6320056992192\n",
      "Generation 4756: p = 0.9584800063324658\n",
      "Generation 4756: M(n) = 862.6320056992192\n",
      "Generation 4757: p = 0.9584800063324658\n",
      "Generation 4757: M(n) = 862.6320056992192\n",
      "Generation 4758: p = 0.9584800063324658\n",
      "Generation 4758: M(n) = 862.6320056992192\n",
      "Generation 4759: p = 0.9584800063324658\n",
      "Generation 4759: M(n) = 862.6320056992192\n",
      "Generation 4760: p = 0.9584800063324658\n",
      "Generation 4760: M(n) = 862.6320056992192\n",
      "Generation 4761: p = 0.9584800063324658\n",
      "Generation 4761: M(n) = 862.6320056992192\n",
      "Generation 4762: p = 0.9584800063324658\n",
      "Generation 4762: M(n) = 862.6320056992192\n",
      "Generation 4763: p = 0.9584800063324658\n",
      "Generation 4763: M(n) = 862.6320056992192\n",
      "Generation 4764: p = 0.9584800063324658\n",
      "Generation 4764: M(n) = 862.6320056992192\n",
      "Generation 4765: p = 0.9584800063324658\n",
      "Generation 4765: M(n) = 862.6320056992192\n",
      "Generation 4766: p = 0.9584800063324658\n",
      "Generation 4766: M(n) = 862.6320056992192\n",
      "Generation 4767: p = 0.9584800063324658\n",
      "Generation 4767: M(n) = 862.6320056992192\n",
      "Generation 4768: p = 0.9584800063324658\n",
      "Generation 4768: M(n) = 862.6320056992192\n",
      "Generation 4769: p = 0.9584800063324658\n",
      "Generation 4769: M(n) = 862.6320056992192\n",
      "Generation 4770: p = 0.9584800063324658\n",
      "Generation 4770: M(n) = 862.6320056992192\n",
      "Generation 4771: p = 0.9584800063324658\n",
      "Generation 4771: M(n) = 862.6320056992192\n",
      "Generation 4772: p = 0.9584800063324658\n",
      "Generation 4772: M(n) = 862.6320056992192\n",
      "Generation 4773: p = 0.9584800063324658\n",
      "Generation 4773: M(n) = 862.6320056992192\n",
      "Generation 4774: p = 0.9584800063324658\n",
      "Generation 4774: M(n) = 862.6320056992192\n",
      "Generation 4775: p = 0.9584800063324658\n",
      "Generation 4775: M(n) = 862.6320056992192\n",
      "Generation 4776: p = 0.9584800063324658\n",
      "Generation 4776: M(n) = 862.6320056992192\n",
      "Generation 4777: p = 0.9584800063324658\n",
      "Generation 4777: M(n) = 862.6320056992192\n",
      "Generation 4778: p = 0.9584800063324658\n",
      "Generation 4778: M(n) = 862.6320056992192\n",
      "Generation 4779: p = 0.9584800063324658\n",
      "Generation 4779: M(n) = 862.6320056992192\n",
      "Generation 4780: p = 0.9584800063324658\n",
      "Generation 4780: M(n) = 862.6320056992192\n",
      "Generation 4781: p = 0.9584800063324658\n",
      "Generation 4781: M(n) = 862.6320056992192\n",
      "Generation 4782: p = 0.9584800063324658\n",
      "Generation 4782: M(n) = 862.6320056992192\n",
      "Generation 4783: p = 0.9584800063324658\n",
      "Generation 4783: M(n) = 862.6320056992192\n",
      "Generation 4784: p = 0.9584800063324658\n",
      "Generation 4784: M(n) = 862.6320056992192\n",
      "Generation 4785: p = 0.9584800063324658\n",
      "Generation 4785: M(n) = 862.6320056992192\n",
      "Generation 4786: p = 0.9584800063324658\n",
      "Generation 4786: M(n) = 862.6320056992192\n",
      "Generation 4787: p = 0.9584800063324658\n",
      "Generation 4787: M(n) = 862.6320056992192\n",
      "Generation 4788: p = 0.9584800063324658\n",
      "Generation 4788: M(n) = 862.6320056992192\n",
      "Generation 4789: p = 0.9584800063324658\n",
      "Generation 4789: M(n) = 862.6320056992192\n",
      "Generation 4790: p = 0.9584800063324658\n",
      "Generation 4790: M(n) = 862.6320056992192\n",
      "Generation 4791: p = 0.9584800063324658\n",
      "Generation 4791: M(n) = 862.6320056992192\n",
      "Generation 4792: p = 0.9584800063324658\n",
      "Generation 4792: M(n) = 862.6320056992192\n",
      "Generation 4793: p = 0.9584800063324658\n",
      "Generation 4793: M(n) = 862.6320056992192\n",
      "Generation 4794: p = 0.9584800063324658\n",
      "Generation 4794: M(n) = 862.6320056992192\n",
      "Generation 4795: p = 0.9584800063324658\n",
      "Generation 4795: M(n) = 862.6320056992192\n",
      "Generation 4796: p = 0.9584800063324658\n",
      "Generation 4796: M(n) = 862.6320056992192\n",
      "Generation 4797: p = 0.9584800063324658\n",
      "Generation 4797: M(n) = 862.6320056992192\n",
      "Generation 4798: p = 0.9584800063324658\n",
      "Generation 4798: M(n) = 862.6320056992192\n",
      "Generation 4799: p = 0.9584800063324658\n",
      "Generation 4799: M(n) = 862.6320056992192\n",
      "Generation 4800: p = 0.9584800063324658\n",
      "Generation 4800: M(n) = 862.6320056992192\n",
      "Generation 4801: p = 0.9584800063324658\n",
      "Generation 4801: M(n) = 862.6320056992192\n",
      "Generation 4802: p = 0.9584800063324658\n",
      "Generation 4802: M(n) = 862.6320056992192\n",
      "Generation 4803: p = 0.9584800063324658\n",
      "Generation 4803: M(n) = 862.6320056992192\n",
      "Generation 4804: p = 0.9584800063324658\n",
      "Generation 4804: M(n) = 862.6320056992192\n",
      "Generation 4805: p = 0.9584800063324658\n",
      "Generation 4805: M(n) = 862.6320056992192\n",
      "Generation 4806: p = 0.9584800063324658\n",
      "Generation 4806: M(n) = 862.6320056992192\n",
      "Generation 4807: p = 0.9584800063324658\n",
      "Generation 4807: M(n) = 862.6320056992192\n",
      "Generation 4808: p = 0.9584800063324658\n",
      "Generation 4808: M(n) = 862.6320056992192\n",
      "Generation 4809: p = 0.9584800063324658\n",
      "Generation 4809: M(n) = 862.6320056992192\n",
      "Generation 4810: p = 0.9584800063324658\n",
      "Generation 4810: M(n) = 862.6320056992192\n",
      "Generation 4811: p = 0.9584800063324658\n",
      "Generation 4811: M(n) = 862.6320056992192\n",
      "Generation 4812: p = 0.9584800063324658\n",
      "Generation 4812: M(n) = 862.6320056992192\n",
      "Generation 4813: p = 0.9584800063324658\n",
      "Generation 4813: M(n) = 862.6320056992192\n",
      "Generation 4814: p = 0.9584800063324658\n",
      "Generation 4814: M(n) = 862.6320056992192\n",
      "Generation 4815: p = 0.9584800063324658\n",
      "Generation 4815: M(n) = 862.6320056992192\n",
      "Generation 4816: p = 0.9584800063324658\n",
      "Generation 4816: M(n) = 862.6320056992192\n",
      "Generation 4817: p = 0.9584800063324658\n",
      "Generation 4817: M(n) = 862.6320056992192\n",
      "Generation 4818: p = 0.9584800063324658\n",
      "Generation 4818: M(n) = 862.6320056992192\n",
      "Generation 4819: p = 0.9584800063324658\n",
      "Generation 4819: M(n) = 862.6320056992192\n",
      "Generation 4820: p = 0.9584800063324658\n",
      "Generation 4820: M(n) = 862.6320056992192\n",
      "Generation 4821: p = 0.9584800063324658\n",
      "Generation 4821: M(n) = 862.6320056992192\n",
      "Generation 4822: p = 0.9584800063324658\n",
      "Generation 4822: M(n) = 862.6320056992192\n",
      "Generation 4823: p = 0.9584800063324658\n",
      "Generation 4823: M(n) = 862.6320056992192\n",
      "Generation 4824: p = 0.9584800063324658\n",
      "Generation 4824: M(n) = 862.6320056992192\n",
      "Generation 4825: p = 0.9584800063324658\n",
      "Generation 4825: M(n) = 862.6320056992192\n",
      "Generation 4826: p = 0.9584800063324658\n",
      "Generation 4826: M(n) = 862.6320056992192\n",
      "Generation 4827: p = 0.9584800063324658\n",
      "Generation 4827: M(n) = 862.6320056992192\n",
      "Generation 4828: p = 0.9584800063324658\n",
      "Generation 4828: M(n) = 862.6320056992192\n",
      "Generation 4829: p = 0.9584800063324658\n",
      "Generation 4829: M(n) = 862.6320056992192\n",
      "Generation 4830: p = 0.9584800063324658\n",
      "Generation 4830: M(n) = 862.6320056992192\n",
      "Generation 4831: p = 0.9584800063324658\n",
      "Generation 4831: M(n) = 862.6320056992192\n",
      "Generation 4832: p = 0.9584800063324658\n",
      "Generation 4832: M(n) = 862.6320056992192\n",
      "Generation 4833: p = 0.9584800063324658\n",
      "Generation 4833: M(n) = 862.6320056992192\n",
      "Generation 4834: p = 0.9584800063324658\n",
      "Generation 4834: M(n) = 862.6320056992192\n",
      "Generation 4835: p = 0.9584800063324658\n",
      "Generation 4835: M(n) = 862.6320056992192\n",
      "Generation 4836: p = 0.9584800063324658\n",
      "Generation 4836: M(n) = 862.6320056992192\n",
      "Generation 4837: p = 0.9584800063324658\n",
      "Generation 4837: M(n) = 862.6320056992192\n",
      "Generation 4838: p = 0.9584800063324658\n",
      "Generation 4838: M(n) = 862.6320056992192\n",
      "Generation 4839: p = 0.9584800063324658\n",
      "Generation 4839: M(n) = 862.6320056992192\n",
      "Generation 4840: p = 0.9584800063324658\n",
      "Generation 4840: M(n) = 862.6320056992192\n",
      "Generation 4841: p = 0.9584800063324658\n",
      "Generation 4841: M(n) = 862.6320056992192\n",
      "Generation 4842: p = 0.9584800063324658\n",
      "Generation 4842: M(n) = 862.6320056992192\n",
      "Generation 4843: p = 0.9584800063324658\n",
      "Generation 4843: M(n) = 862.6320056992192\n",
      "Generation 4844: p = 0.9584800063324658\n",
      "Generation 4844: M(n) = 862.6320056992192\n",
      "Generation 4845: p = 0.9584800063324658\n",
      "Generation 4845: M(n) = 862.6320056992192\n",
      "Generation 4846: p = 0.9584800063324658\n",
      "Generation 4846: M(n) = 862.6320056992192\n",
      "Generation 4847: p = 0.9584800063324658\n",
      "Generation 4847: M(n) = 862.6320056992192\n",
      "Generation 4848: p = 0.9584800063324658\n",
      "Generation 4848: M(n) = 862.6320056992192\n",
      "Generation 4849: p = 0.9584800063324658\n",
      "Generation 4849: M(n) = 862.6320056992192\n",
      "Generation 4850: p = 0.9584800063324658\n",
      "Generation 4850: M(n) = 862.6320056992192\n",
      "Generation 4851: p = 0.9584800063324658\n",
      "Generation 4851: M(n) = 862.6320056992192\n",
      "Generation 4852: p = 0.9584800063324658\n",
      "Generation 4852: M(n) = 862.6320056992192\n",
      "Generation 4853: p = 0.9584800063324658\n",
      "Generation 4853: M(n) = 862.6320056992192\n",
      "Generation 4854: p = 0.9584800063324658\n",
      "Generation 4854: M(n) = 862.6320056992192\n",
      "Generation 4855: p = 0.9584800063324658\n",
      "Generation 4855: M(n) = 862.6320056992192\n",
      "Generation 4856: p = 0.9584800063324658\n",
      "Generation 4856: M(n) = 862.6320056992192\n",
      "Generation 4857: p = 0.9584800063324658\n",
      "Generation 4857: M(n) = 862.6320056992192\n",
      "Generation 4858: p = 0.9584800063324658\n",
      "Generation 4858: M(n) = 862.6320056992192\n",
      "Generation 4859: p = 0.9584800063324658\n",
      "Generation 4859: M(n) = 862.6320056992192\n",
      "Generation 4860: p = 0.9584800063324658\n",
      "Generation 4860: M(n) = 862.6320056992192\n",
      "Generation 4861: p = 0.9584800063324658\n",
      "Generation 4861: M(n) = 862.6320056992192\n",
      "Generation 4862: p = 0.9584800063324658\n",
      "Generation 4862: M(n) = 862.6320056992192\n",
      "Generation 4863: p = 0.9584800063324658\n",
      "Generation 4863: M(n) = 862.6320056992192\n",
      "Generation 4864: p = 0.9584800063324658\n",
      "Generation 4864: M(n) = 862.6320056992192\n",
      "Generation 4865: p = 0.9584800063324658\n",
      "Generation 4865: M(n) = 862.6320056992192\n",
      "Generation 4866: p = 0.9584800063324658\n",
      "Generation 4866: M(n) = 862.6320056992192\n",
      "Generation 4867: p = 0.9584800063324658\n",
      "Generation 4867: M(n) = 862.6320056992192\n",
      "Generation 4868: p = 0.9584800063324658\n",
      "Generation 4868: M(n) = 862.6320056992192\n",
      "Generation 4869: p = 0.9584800063324658\n",
      "Generation 4869: M(n) = 862.6320056992192\n",
      "Generation 4870: p = 0.9584800063324658\n",
      "Generation 4870: M(n) = 862.6320056992192\n",
      "Generation 4871: p = 0.9584800063324658\n",
      "Generation 4871: M(n) = 862.6320056992192\n",
      "Generation 4872: p = 0.9584800063324658\n",
      "Generation 4872: M(n) = 862.6320056992192\n",
      "Generation 4873: p = 0.9584800063324658\n",
      "Generation 4873: M(n) = 862.6320056992192\n",
      "Generation 4874: p = 0.9584800063324658\n",
      "Generation 4874: M(n) = 862.6320056992192\n",
      "Generation 4875: p = 0.9584800063324658\n",
      "Generation 4875: M(n) = 862.6320056992192\n",
      "Generation 4876: p = 0.9584800063324658\n",
      "Generation 4876: M(n) = 862.6320056992192\n",
      "Generation 4877: p = 0.9584800063324658\n",
      "Generation 4877: M(n) = 862.6320056992192\n",
      "Generation 4878: p = 0.9584800063324658\n",
      "Generation 4878: M(n) = 862.6320056992192\n",
      "Generation 4879: p = 0.9584800063324658\n",
      "Generation 4879: M(n) = 862.6320056992192\n",
      "Generation 4880: p = 0.9584800063324658\n",
      "Generation 4880: M(n) = 862.6320056992192\n",
      "Generation 4881: p = 0.9584800063324658\n",
      "Generation 4881: M(n) = 862.6320056992192\n",
      "Generation 4882: p = 0.9584800063324658\n",
      "Generation 4882: M(n) = 862.6320056992192\n",
      "Generation 4883: p = 0.9584800063324658\n",
      "Generation 4883: M(n) = 862.6320056992192\n",
      "Generation 4884: p = 0.9584800063324658\n",
      "Generation 4884: M(n) = 862.6320056992192\n",
      "Generation 4885: p = 0.9584800063324658\n",
      "Generation 4885: M(n) = 862.6320056992192\n",
      "Generation 4886: p = 0.9584800063324658\n",
      "Generation 4886: M(n) = 862.6320056992192\n",
      "Generation 4887: p = 0.9584800063324658\n",
      "Generation 4887: M(n) = 862.6320056992192\n",
      "Generation 4888: p = 0.9584800063324658\n",
      "Generation 4888: M(n) = 862.6320056992192\n",
      "Generation 4889: p = 0.9584800063324658\n",
      "Generation 4889: M(n) = 862.6320056992192\n",
      "Generation 4890: p = 0.9584800063324658\n",
      "Generation 4890: M(n) = 862.6320056992192\n",
      "Generation 4891: p = 0.9584800063324658\n",
      "Generation 4891: M(n) = 862.6320056992192\n",
      "Generation 4892: p = 0.9584800063324658\n",
      "Generation 4892: M(n) = 862.6320056992192\n",
      "Generation 4893: p = 0.9584800063324658\n",
      "Generation 4893: M(n) = 862.6320056992192\n",
      "Generation 4894: p = 0.9584800063324658\n",
      "Generation 4894: M(n) = 862.6320056992192\n",
      "Generation 4895: p = 0.9584800063324658\n",
      "Generation 4895: M(n) = 862.6320056992192\n",
      "Generation 4896: p = 0.9584800063324658\n",
      "Generation 4896: M(n) = 862.6320056992192\n",
      "Generation 4897: p = 0.9584800063324658\n",
      "Generation 4897: M(n) = 862.6320056992192\n",
      "Generation 4898: p = 0.9584800063324658\n",
      "Generation 4898: M(n) = 862.6320056992192\n",
      "Generation 4899: p = 0.9584800063324658\n",
      "Generation 4899: M(n) = 862.6320056992192\n",
      "Generation 4900: p = 0.9584800063324658\n",
      "Generation 4900: M(n) = 862.6320056992192\n",
      "Generation 4901: p = 0.9584800063324658\n",
      "Generation 4901: M(n) = 862.6320056992192\n",
      "Generation 4902: p = 0.9584800063324658\n",
      "Generation 4902: M(n) = 862.6320056992192\n",
      "Generation 4903: p = 0.9584800063324658\n",
      "Generation 4903: M(n) = 862.6320056992192\n",
      "Generation 4904: p = 0.9584800063324658\n",
      "Generation 4904: M(n) = 862.6320056992192\n",
      "Generation 4905: p = 0.9584800063324658\n",
      "Generation 4905: M(n) = 862.6320056992192\n",
      "Generation 4906: p = 0.9584800063324658\n",
      "Generation 4906: M(n) = 862.6320056992192\n",
      "Generation 4907: p = 0.9584800063324658\n",
      "Generation 4907: M(n) = 862.6320056992192\n",
      "Generation 4908: p = 0.9584800063324658\n",
      "Generation 4908: M(n) = 862.6320056992192\n",
      "Generation 4909: p = 0.9584800063324658\n",
      "Generation 4909: M(n) = 862.6320056992192\n",
      "Generation 4910: p = 0.9584800063324658\n",
      "Generation 4910: M(n) = 862.6320056992192\n",
      "Generation 4911: p = 0.9584800063324658\n",
      "Generation 4911: M(n) = 862.6320056992192\n",
      "Generation 4912: p = 0.9584800063324658\n",
      "Generation 4912: M(n) = 862.6320056992192\n",
      "Generation 4913: p = 0.9584800063324658\n",
      "Generation 4913: M(n) = 862.6320056992192\n",
      "Generation 4914: p = 0.9584800063324658\n",
      "Generation 4914: M(n) = 862.6320056992192\n",
      "Generation 4915: p = 0.9584800063324658\n",
      "Generation 4915: M(n) = 862.6320056992192\n",
      "Generation 4916: p = 0.9584800063324658\n",
      "Generation 4916: M(n) = 862.6320056992192\n",
      "Generation 4917: p = 0.9584800063324658\n",
      "Generation 4917: M(n) = 862.6320056992192\n",
      "Generation 4918: p = 0.9584800063324658\n",
      "Generation 4918: M(n) = 862.6320056992192\n",
      "Generation 4919: p = 0.9584800063324658\n",
      "Generation 4919: M(n) = 862.6320056992192\n",
      "Generation 4920: p = 0.9584800063324658\n",
      "Generation 4920: M(n) = 862.6320056992192\n",
      "Generation 4921: p = 0.9584800063324658\n",
      "Generation 4921: M(n) = 862.6320056992192\n",
      "Generation 4922: p = 0.9584800063324658\n",
      "Generation 4922: M(n) = 862.6320056992192\n",
      "Generation 4923: p = 0.9584800063324658\n",
      "Generation 4923: M(n) = 862.6320056992192\n",
      "Generation 4924: p = 0.9584800063324658\n",
      "Generation 4924: M(n) = 862.6320056992192\n",
      "Generation 4925: p = 0.9584800063324658\n",
      "Generation 4925: M(n) = 862.6320056992192\n",
      "Generation 4926: p = 0.9584800063324658\n",
      "Generation 4926: M(n) = 862.6320056992192\n",
      "Generation 4927: p = 0.9584800063324658\n",
      "Generation 4927: M(n) = 862.6320056992192\n",
      "Generation 4928: p = 0.9584800063324658\n",
      "Generation 4928: M(n) = 862.6320056992192\n",
      "Generation 4929: p = 0.9584800063324658\n",
      "Generation 4929: M(n) = 862.6320056992192\n",
      "Generation 4930: p = 0.9584800063324658\n",
      "Generation 4930: M(n) = 862.6320056992192\n",
      "Generation 4931: p = 0.9584800063324658\n",
      "Generation 4931: M(n) = 862.6320056992192\n",
      "Generation 4932: p = 0.9584800063324658\n",
      "Generation 4932: M(n) = 862.6320056992192\n",
      "Generation 4933: p = 0.9584800063324658\n",
      "Generation 4933: M(n) = 862.6320056992192\n",
      "Generation 4934: p = 0.9584800063324658\n",
      "Generation 4934: M(n) = 862.6320056992192\n",
      "Generation 4935: p = 0.9584800063324658\n",
      "Generation 4935: M(n) = 862.6320056992192\n",
      "Generation 4936: p = 0.9584800063324658\n",
      "Generation 4936: M(n) = 862.6320056992192\n",
      "Generation 4937: p = 0.9584800063324658\n",
      "Generation 4937: M(n) = 862.6320056992192\n",
      "Generation 4938: p = 0.9584800063324658\n",
      "Generation 4938: M(n) = 862.6320056992192\n",
      "Generation 4939: p = 0.9584800063324658\n",
      "Generation 4939: M(n) = 862.6320056992192\n",
      "Generation 4940: p = 0.9584800063324658\n",
      "Generation 4940: M(n) = 862.6320056992192\n",
      "Generation 4941: p = 0.9584800063324658\n",
      "Generation 4941: M(n) = 862.6320056992192\n",
      "Generation 4942: p = 0.9584800063324658\n",
      "Generation 4942: M(n) = 862.6320056992192\n",
      "Generation 4943: p = 0.9584800063324658\n",
      "Generation 4943: M(n) = 862.6320056992192\n",
      "Generation 4944: p = 0.9584800063324658\n",
      "Generation 4944: M(n) = 862.6320056992192\n",
      "Generation 4945: p = 0.9584800063324658\n",
      "Generation 4945: M(n) = 862.6320056992192\n",
      "Generation 4946: p = 0.9584800063324658\n",
      "Generation 4946: M(n) = 862.6320056992192\n",
      "Generation 4947: p = 0.9584800063324658\n",
      "Generation 4947: M(n) = 862.6320056992192\n",
      "Generation 4948: p = 0.9584800063324658\n",
      "Generation 4948: M(n) = 862.6320056992192\n",
      "Generation 4949: p = 0.9584800063324658\n",
      "Generation 4949: M(n) = 862.6320056992192\n",
      "Generation 4950: p = 0.9584800063324658\n",
      "Generation 4950: M(n) = 862.6320056992192\n",
      "Generation 4951: p = 0.9584800063324658\n",
      "Generation 4951: M(n) = 862.6320056992192\n",
      "Generation 4952: p = 0.9584800063324658\n",
      "Generation 4952: M(n) = 862.6320056992192\n",
      "Generation 4953: p = 0.9584800063324658\n",
      "Generation 4953: M(n) = 862.6320056992192\n",
      "Generation 4954: p = 0.9584800063324658\n",
      "Generation 4954: M(n) = 862.6320056992192\n",
      "Generation 4955: p = 0.9584800063324658\n",
      "Generation 4955: M(n) = 862.6320056992192\n",
      "Generation 4956: p = 0.9584800063324658\n",
      "Generation 4956: M(n) = 862.6320056992192\n",
      "Generation 4957: p = 0.9584800063324658\n",
      "Generation 4957: M(n) = 862.6320056992192\n",
      "Generation 4958: p = 0.9584800063324658\n",
      "Generation 4958: M(n) = 862.6320056992192\n",
      "Generation 4959: p = 0.9584800063324658\n",
      "Generation 4959: M(n) = 862.6320056992192\n",
      "Generation 4960: p = 0.9584800063324658\n",
      "Generation 4960: M(n) = 862.6320056992192\n",
      "Generation 4961: p = 0.9584800063324658\n",
      "Generation 4961: M(n) = 862.6320056992192\n",
      "Generation 4962: p = 0.9584800063324658\n",
      "Generation 4962: M(n) = 862.6320056992192\n",
      "Generation 4963: p = 0.9584800063324658\n",
      "Generation 4963: M(n) = 862.6320056992192\n",
      "Generation 4964: p = 0.9584800063324658\n",
      "Generation 4964: M(n) = 862.6320056992192\n",
      "Generation 4965: p = 0.9584800063324658\n",
      "Generation 4965: M(n) = 862.6320056992192\n",
      "Generation 4966: p = 0.9584800063324658\n",
      "Generation 4966: M(n) = 862.6320056992192\n",
      "Generation 4967: p = 0.9584800063324658\n",
      "Generation 4967: M(n) = 862.6320056992192\n",
      "Generation 4968: p = 0.9584800063324658\n",
      "Generation 4968: M(n) = 862.6320056992192\n",
      "Generation 4969: p = 0.9584800063324658\n",
      "Generation 4969: M(n) = 862.6320056992192\n",
      "Generation 4970: p = 0.9584800063324658\n",
      "Generation 4970: M(n) = 862.6320056992192\n",
      "Generation 4971: p = 0.9584800063324658\n",
      "Generation 4971: M(n) = 862.6320056992192\n",
      "Generation 4972: p = 0.9584800063324658\n",
      "Generation 4972: M(n) = 862.6320056992192\n",
      "Generation 4973: p = 0.9584800063324658\n",
      "Generation 4973: M(n) = 862.6320056992192\n",
      "Generation 4974: p = 0.9584800063324658\n",
      "Generation 4974: M(n) = 862.6320056992192\n",
      "Generation 4975: p = 0.9584800063324658\n",
      "Generation 4975: M(n) = 862.6320056992192\n",
      "Generation 4976: p = 0.9584800063324658\n",
      "Generation 4976: M(n) = 862.6320056992192\n",
      "Generation 4977: p = 0.9584800063324658\n",
      "Generation 4977: M(n) = 862.6320056992192\n",
      "Generation 4978: p = 0.9584800063324658\n",
      "Generation 4978: M(n) = 862.6320056992192\n",
      "Generation 4979: p = 0.9584800063324658\n",
      "Generation 4979: M(n) = 862.6320056992192\n",
      "Generation 4980: p = 0.9584800063324658\n",
      "Generation 4980: M(n) = 862.6320056992192\n",
      "Generation 4981: p = 0.9584800063324658\n",
      "Generation 4981: M(n) = 862.6320056992192\n",
      "Generation 4982: p = 0.9584800063324658\n",
      "Generation 4982: M(n) = 862.6320056992192\n",
      "Generation 4983: p = 0.9584800063324658\n",
      "Generation 4983: M(n) = 862.6320056992192\n",
      "Generation 4984: p = 0.9584800063324658\n",
      "Generation 4984: M(n) = 862.6320056992192\n",
      "Generation 4985: p = 0.9584800063324658\n",
      "Generation 4985: M(n) = 862.6320056992192\n",
      "Generation 4986: p = 0.9584800063324658\n",
      "Generation 4986: M(n) = 862.6320056992192\n",
      "Generation 4987: p = 0.9584800063324658\n",
      "Generation 4987: M(n) = 862.6320056992192\n",
      "Generation 4988: p = 0.9584800063324658\n",
      "Generation 4988: M(n) = 862.6320056992192\n",
      "Generation 4989: p = 0.9584800063324658\n",
      "Generation 4989: M(n) = 862.6320056992192\n",
      "Generation 4990: p = 0.9584800063324658\n",
      "Generation 4990: M(n) = 862.6320056992192\n",
      "Generation 4991: p = 0.9584800063324658\n",
      "Generation 4991: M(n) = 862.6320056992192\n",
      "Generation 4992: p = 0.9584800063324658\n",
      "Generation 4992: M(n) = 862.6320056992192\n",
      "Generation 4993: p = 0.9584800063324658\n",
      "Generation 4993: M(n) = 862.6320056992192\n",
      "Generation 4994: p = 0.9584800063324658\n",
      "Generation 4994: M(n) = 862.6320056992192\n",
      "Generation 4995: p = 0.9584800063324658\n",
      "Generation 4995: M(n) = 862.6320056992192\n",
      "Generation 4996: p = 0.9584800063324658\n",
      "Generation 4996: M(n) = 862.6320056992192\n",
      "Generation 4997: p = 0.9584800063324658\n",
      "Generation 4997: M(n) = 862.6320056992192\n",
      "Generation 4998: p = 0.9584800063324658\n",
      "Generation 4998: M(n) = 862.6320056992192\n",
      "Generation 4999: p = 0.9584800063324658\n",
      "Generation 4999: M(n) = 862.6320056992192\n",
      "Generation 5000: p = 0.9584800063324658\n",
      "Generation 5000: M(n) = 862.6320056992192\n",
      "Generation 5001: p = 0.9584800063324658\n",
      "Generation 5001: M(n) = 862.6320056992192\n",
      "Generation 5002: p = 0.9584800063324658\n",
      "Generation 5002: M(n) = 862.6320056992192\n",
      "Generation 5003: p = 0.9584800063324658\n",
      "Generation 5003: M(n) = 862.6320056992192\n",
      "Generation 5004: p = 0.9584800063324658\n",
      "Generation 5004: M(n) = 862.6320056992192\n",
      "Generation 5005: p = 0.9584800063324658\n",
      "Generation 5005: M(n) = 862.6320056992192\n",
      "Generation 5006: p = 0.9584800063324658\n",
      "Generation 5006: M(n) = 862.6320056992192\n",
      "Generation 5007: p = 0.9584800063324658\n",
      "Generation 5007: M(n) = 862.6320056992192\n",
      "Generation 5008: p = 0.9584800063324658\n",
      "Generation 5008: M(n) = 862.6320056992192\n",
      "Generation 5009: p = 0.9584800063324658\n",
      "Generation 5009: M(n) = 862.6320056992192\n",
      "Generation 5010: p = 0.9584800063324658\n",
      "Generation 5010: M(n) = 862.6320056992192\n",
      "Generation 5011: p = 0.9584800063324658\n",
      "Generation 5011: M(n) = 862.6320056992192\n",
      "Generation 5012: p = 0.9584800063324658\n",
      "Generation 5012: M(n) = 862.6320056992192\n",
      "Generation 5013: p = 0.9584800063324658\n",
      "Generation 5013: M(n) = 862.6320056992192\n",
      "Generation 5014: p = 0.9584800063324658\n",
      "Generation 5014: M(n) = 862.6320056992192\n",
      "Generation 5015: p = 0.9584800063324658\n",
      "Generation 5015: M(n) = 862.6320056992192\n",
      "Generation 5016: p = 0.9584800063324658\n",
      "Generation 5016: M(n) = 862.6320056992192\n",
      "Generation 5017: p = 0.9584800063324658\n",
      "Generation 5017: M(n) = 862.6320056992192\n",
      "Generation 5018: p = 0.9584800063324658\n",
      "Generation 5018: M(n) = 862.6320056992192\n",
      "Generation 5019: p = 0.9584800063324658\n",
      "Generation 5019: M(n) = 862.6320056992192\n",
      "Generation 5020: p = 0.9584800063324658\n",
      "Generation 5020: M(n) = 862.6320056992192\n",
      "Generation 5021: p = 0.9584800063324658\n",
      "Generation 5021: M(n) = 862.6320056992192\n",
      "Generation 5022: p = 0.9584800063324658\n",
      "Generation 5022: M(n) = 862.6320056992192\n",
      "Generation 5023: p = 0.9584800063324658\n",
      "Generation 5023: M(n) = 862.6320056992192\n",
      "Generation 5024: p = 0.9584800063324658\n",
      "Generation 5024: M(n) = 862.6320056992192\n",
      "Generation 5025: p = 0.9584800063324658\n",
      "Generation 5025: M(n) = 862.6320056992192\n",
      "Generation 5026: p = 0.9584800063324658\n",
      "Generation 5026: M(n) = 862.6320056992192\n",
      "Generation 5027: p = 0.9584800063324658\n",
      "Generation 5027: M(n) = 862.6320056992192\n",
      "Generation 5028: p = 0.9584800063324658\n",
      "Generation 5028: M(n) = 862.6320056992192\n",
      "Generation 5029: p = 0.9584800063324658\n",
      "Generation 5029: M(n) = 862.6320056992192\n",
      "Generation 5030: p = 0.9584800063324658\n",
      "Generation 5030: M(n) = 862.6320056992192\n",
      "Generation 5031: p = 0.9584800063324658\n",
      "Generation 5031: M(n) = 862.6320056992192\n",
      "Generation 5032: p = 0.9584800063324658\n",
      "Generation 5032: M(n) = 862.6320056992192\n",
      "Generation 5033: p = 0.9584800063324658\n",
      "Generation 5033: M(n) = 862.6320056992192\n",
      "Generation 5034: p = 0.9584800063324658\n",
      "Generation 5034: M(n) = 862.6320056992192\n",
      "Generation 5035: p = 0.9584800063324658\n",
      "Generation 5035: M(n) = 862.6320056992192\n",
      "Generation 5036: p = 0.9584800063324658\n",
      "Generation 5036: M(n) = 862.6320056992192\n",
      "Generation 5037: p = 0.9584800063324658\n",
      "Generation 5037: M(n) = 862.6320056992192\n",
      "Generation 5038: p = 0.9584800063324658\n",
      "Generation 5038: M(n) = 862.6320056992192\n",
      "Generation 5039: p = 0.9584800063324658\n",
      "Generation 5039: M(n) = 862.6320056992192\n",
      "Generation 5040: p = 0.9584800063324658\n",
      "Generation 5040: M(n) = 862.6320056992192\n",
      "Generation 5041: p = 0.9584800063324658\n",
      "Generation 5041: M(n) = 862.6320056992192\n",
      "Generation 5042: p = 0.9584800063324658\n",
      "Generation 5042: M(n) = 862.6320056992192\n",
      "Generation 5043: p = 0.9584800063324658\n",
      "Generation 5043: M(n) = 862.6320056992192\n",
      "Generation 5044: p = 0.9584800063324658\n",
      "Generation 5044: M(n) = 862.6320056992192\n",
      "Generation 5045: p = 0.9584800063324658\n",
      "Generation 5045: M(n) = 862.6320056992192\n",
      "Generation 5046: p = 0.9584800063324658\n",
      "Generation 5046: M(n) = 862.6320056992192\n",
      "Generation 5047: p = 0.9584800063324658\n",
      "Generation 5047: M(n) = 862.6320056992192\n",
      "Generation 5048: p = 0.9584800063324658\n",
      "Generation 5048: M(n) = 862.6320056992192\n",
      "Generation 5049: p = 0.9584800063324658\n",
      "Generation 5049: M(n) = 862.6320056992192\n",
      "Generation 5050: p = 0.9584800063324658\n",
      "Generation 5050: M(n) = 862.6320056992192\n",
      "Generation 5051: p = 0.9584800063324658\n",
      "Generation 5051: M(n) = 862.6320056992192\n",
      "Generation 5052: p = 0.9584800063324658\n",
      "Generation 5052: M(n) = 862.6320056992192\n",
      "Generation 5053: p = 0.9584800063324658\n",
      "Generation 5053: M(n) = 862.6320056992192\n",
      "Generation 5054: p = 0.9584800063324658\n",
      "Generation 5054: M(n) = 862.6320056992192\n",
      "Generation 5055: p = 0.9584800063324658\n",
      "Generation 5055: M(n) = 862.6320056992192\n",
      "Generation 5056: p = 0.9584800063324658\n",
      "Generation 5056: M(n) = 862.6320056992192\n",
      "Generation 5057: p = 0.9584800063324658\n",
      "Generation 5057: M(n) = 862.6320056992192\n",
      "Generation 5058: p = 0.9584800063324658\n",
      "Generation 5058: M(n) = 862.6320056992192\n",
      "Generation 5059: p = 0.9584800063324658\n",
      "Generation 5059: M(n) = 862.6320056992192\n",
      "Generation 5060: p = 0.9584800063324658\n",
      "Generation 5060: M(n) = 862.6320056992192\n",
      "Generation 5061: p = 0.9584800063324658\n",
      "Generation 5061: M(n) = 862.6320056992192\n",
      "Generation 5062: p = 0.9584800063324658\n",
      "Generation 5062: M(n) = 862.6320056992192\n",
      "Generation 5063: p = 0.9584800063324658\n",
      "Generation 5063: M(n) = 862.6320056992192\n",
      "Generation 5064: p = 0.9584800063324658\n",
      "Generation 5064: M(n) = 862.6320056992192\n",
      "Generation 5065: p = 0.9584800063324658\n",
      "Generation 5065: M(n) = 862.6320056992192\n",
      "Generation 5066: p = 0.9584800063324658\n",
      "Generation 5066: M(n) = 862.6320056992192\n",
      "Generation 5067: p = 0.9584800063324658\n",
      "Generation 5067: M(n) = 862.6320056992192\n",
      "Generation 5068: p = 0.9584800063324658\n",
      "Generation 5068: M(n) = 862.6320056992192\n",
      "Generation 5069: p = 0.9584800063324658\n",
      "Generation 5069: M(n) = 862.6320056992192\n",
      "Generation 5070: p = 0.9584800063324658\n",
      "Generation 5070: M(n) = 862.6320056992192\n",
      "Generation 5071: p = 0.9584800063324658\n",
      "Generation 5071: M(n) = 862.6320056992192\n",
      "Generation 5072: p = 0.9584800063324658\n",
      "Generation 5072: M(n) = 862.6320056992192\n",
      "Generation 5073: p = 0.9584800063324658\n",
      "Generation 5073: M(n) = 862.6320056992192\n",
      "Generation 5074: p = 0.9584800063324658\n",
      "Generation 5074: M(n) = 862.6320056992192\n",
      "Generation 5075: p = 0.9584800063324658\n",
      "Generation 5075: M(n) = 862.6320056992192\n",
      "Generation 5076: p = 0.9584800063324658\n",
      "Generation 5076: M(n) = 862.6320056992192\n",
      "Generation 5077: p = 0.9584800063324658\n",
      "Generation 5077: M(n) = 862.6320056992192\n",
      "Generation 5078: p = 0.9584800063324658\n",
      "Generation 5078: M(n) = 862.6320056992192\n",
      "Generation 5079: p = 0.9584800063324658\n",
      "Generation 5079: M(n) = 862.6320056992192\n",
      "Generation 5080: p = 0.9584800063324658\n",
      "Generation 5080: M(n) = 862.6320056992192\n",
      "Generation 5081: p = 0.9584800063324658\n",
      "Generation 5081: M(n) = 862.6320056992192\n",
      "Generation 5082: p = 0.9584800063324658\n",
      "Generation 5082: M(n) = 862.6320056992192\n",
      "Generation 5083: p = 0.9584800063324658\n",
      "Generation 5083: M(n) = 862.6320056992192\n",
      "Generation 5084: p = 0.9584800063324658\n",
      "Generation 5084: M(n) = 862.6320056992192\n",
      "Generation 5085: p = 0.9584800063324658\n",
      "Generation 5085: M(n) = 862.6320056992192\n",
      "Generation 5086: p = 0.9584800063324658\n",
      "Generation 5086: M(n) = 862.6320056992192\n",
      "Generation 5087: p = 0.9584800063324658\n",
      "Generation 5087: M(n) = 862.6320056992192\n",
      "Generation 5088: p = 0.9584800063324658\n",
      "Generation 5088: M(n) = 862.6320056992192\n",
      "Generation 5089: p = 0.9584800063324658\n",
      "Generation 5089: M(n) = 862.6320056992192\n",
      "Generation 5090: p = 0.9584800063324658\n",
      "Generation 5090: M(n) = 862.6320056992192\n",
      "Generation 5091: p = 0.9584800063324658\n",
      "Generation 5091: M(n) = 862.6320056992192\n",
      "Generation 5092: p = 0.9584800063324658\n",
      "Generation 5092: M(n) = 862.6320056992192\n",
      "Generation 5093: p = 0.9584800063324658\n",
      "Generation 5093: M(n) = 862.6320056992192\n",
      "Generation 5094: p = 0.9584800063324658\n",
      "Generation 5094: M(n) = 862.6320056992192\n",
      "Generation 5095: p = 0.9584800063324658\n",
      "Generation 5095: M(n) = 862.6320056992192\n",
      "Generation 5096: p = 0.9584800063324658\n",
      "Generation 5096: M(n) = 862.6320056992192\n",
      "Generation 5097: p = 0.9584800063324658\n",
      "Generation 5097: M(n) = 862.6320056992192\n",
      "Generation 5098: p = 0.9584800063324658\n",
      "Generation 5098: M(n) = 862.6320056992192\n",
      "Generation 5099: p = 0.9584800063324658\n",
      "Generation 5099: M(n) = 862.6320056992192\n",
      "Generation 5100: p = 0.9584800063324658\n",
      "Generation 5100: M(n) = 862.6320056992192\n",
      "Generation 5101: p = 0.9584800063324658\n",
      "Generation 5101: M(n) = 862.6320056992192\n",
      "Generation 5102: p = 0.9584800063324658\n",
      "Generation 5102: M(n) = 862.6320056992192\n",
      "Generation 5103: p = 0.9584800063324658\n",
      "Generation 5103: M(n) = 862.6320056992192\n",
      "Generation 5104: p = 0.9584800063324658\n",
      "Generation 5104: M(n) = 862.6320056992192\n",
      "Generation 5105: p = 0.9584800063324658\n",
      "Generation 5105: M(n) = 862.6320056992192\n",
      "Generation 5106: p = 0.9584800063324658\n",
      "Generation 5106: M(n) = 862.6320056992192\n",
      "Generation 5107: p = 0.9584800063324658\n",
      "Generation 5107: M(n) = 862.6320056992192\n",
      "Generation 5108: p = 0.9584800063324658\n",
      "Generation 5108: M(n) = 862.6320056992192\n",
      "Generation 5109: p = 0.9584800063324658\n",
      "Generation 5109: M(n) = 862.6320056992192\n",
      "Generation 5110: p = 0.9584800063324658\n",
      "Generation 5110: M(n) = 862.6320056992192\n",
      "Generation 5111: p = 0.9584800063324658\n",
      "Generation 5111: M(n) = 862.6320056992192\n",
      "Generation 5112: p = 0.9584800063324658\n",
      "Generation 5112: M(n) = 862.6320056992192\n",
      "Generation 5113: p = 0.9584800063324658\n",
      "Generation 5113: M(n) = 862.6320056992192\n",
      "Generation 5114: p = 0.9584800063324658\n",
      "Generation 5114: M(n) = 862.6320056992192\n",
      "Generation 5115: p = 0.9584800063324658\n",
      "Generation 5115: M(n) = 862.6320056992192\n",
      "Generation 5116: p = 0.9584800063324658\n",
      "Generation 5116: M(n) = 862.6320056992192\n",
      "Generation 5117: p = 0.9584800063324658\n",
      "Generation 5117: M(n) = 862.6320056992192\n",
      "Generation 5118: p = 0.9584800063324658\n",
      "Generation 5118: M(n) = 862.6320056992192\n",
      "Generation 5119: p = 0.9584800063324658\n",
      "Generation 5119: M(n) = 862.6320056992192\n",
      "Generation 5120: p = 0.9584800063324658\n",
      "Generation 5120: M(n) = 862.6320056992192\n",
      "Generation 5121: p = 0.9584800063324658\n",
      "Generation 5121: M(n) = 862.6320056992192\n",
      "Generation 5122: p = 0.9584800063324658\n",
      "Generation 5122: M(n) = 862.6320056992192\n",
      "Generation 5123: p = 0.9584800063324658\n",
      "Generation 5123: M(n) = 862.6320056992192\n",
      "Generation 5124: p = 0.9584800063324658\n",
      "Generation 5124: M(n) = 862.6320056992192\n",
      "Generation 5125: p = 0.9584800063324658\n",
      "Generation 5125: M(n) = 862.6320056992192\n",
      "Generation 5126: p = 0.9584800063324658\n",
      "Generation 5126: M(n) = 862.6320056992192\n",
      "Generation 5127: p = 0.9584800063324658\n",
      "Generation 5127: M(n) = 862.6320056992192\n",
      "Generation 5128: p = 0.9584800063324658\n",
      "Generation 5128: M(n) = 862.6320056992192\n",
      "Generation 5129: p = 0.9584800063324658\n",
      "Generation 5129: M(n) = 862.6320056992192\n",
      "Generation 5130: p = 0.9584800063324658\n",
      "Generation 5130: M(n) = 862.6320056992192\n",
      "Generation 5131: p = 0.9584800063324658\n",
      "Generation 5131: M(n) = 862.6320056992192\n",
      "Generation 5132: p = 0.9584800063324658\n",
      "Generation 5132: M(n) = 862.6320056992192\n",
      "Generation 5133: p = 0.9584800063324658\n",
      "Generation 5133: M(n) = 862.6320056992192\n",
      "Generation 5134: p = 0.9584800063324658\n",
      "Generation 5134: M(n) = 862.6320056992192\n",
      "Generation 5135: p = 0.9584800063324658\n",
      "Generation 5135: M(n) = 862.6320056992192\n",
      "Generation 5136: p = 0.9584800063324658\n",
      "Generation 5136: M(n) = 862.6320056992192\n",
      "Generation 5137: p = 0.9584800063324658\n",
      "Generation 5137: M(n) = 862.6320056992192\n",
      "Generation 5138: p = 0.9584800063324658\n",
      "Generation 5138: M(n) = 862.6320056992192\n",
      "Generation 5139: p = 0.9584800063324658\n",
      "Generation 5139: M(n) = 862.6320056992192\n",
      "Generation 5140: p = 0.9584800063324658\n",
      "Generation 5140: M(n) = 862.6320056992192\n",
      "Generation 5141: p = 0.9584800063324658\n",
      "Generation 5141: M(n) = 862.6320056992192\n",
      "Generation 5142: p = 0.9584800063324658\n",
      "Generation 5142: M(n) = 862.6320056992192\n",
      "Generation 5143: p = 0.9584800063324658\n",
      "Generation 5143: M(n) = 862.6320056992192\n",
      "Generation 5144: p = 0.9584800063324658\n",
      "Generation 5144: M(n) = 862.6320056992192\n",
      "Generation 5145: p = 0.9584800063324658\n",
      "Generation 5145: M(n) = 862.6320056992192\n",
      "Generation 5146: p = 0.9584800063324658\n",
      "Generation 5146: M(n) = 862.6320056992192\n",
      "Generation 5147: p = 0.9584800063324658\n",
      "Generation 5147: M(n) = 862.6320056992192\n",
      "Generation 5148: p = 0.9584800063324658\n",
      "Generation 5148: M(n) = 862.6320056992192\n",
      "Generation 5149: p = 0.9584800063324658\n",
      "Generation 5149: M(n) = 862.6320056992192\n",
      "Generation 5150: p = 0.9584800063324658\n",
      "Generation 5150: M(n) = 862.6320056992192\n",
      "Generation 5151: p = 0.9584800063324658\n",
      "Generation 5151: M(n) = 862.6320056992192\n",
      "Generation 5152: p = 0.9584800063324658\n",
      "Generation 5152: M(n) = 862.6320056992192\n",
      "Generation 5153: p = 0.9584800063324658\n",
      "Generation 5153: M(n) = 862.6320056992192\n",
      "Generation 5154: p = 0.9584800063324658\n",
      "Generation 5154: M(n) = 862.6320056992192\n",
      "Generation 5155: p = 0.9584800063324658\n",
      "Generation 5155: M(n) = 862.6320056992192\n",
      "Generation 5156: p = 0.9584800063324658\n",
      "Generation 5156: M(n) = 862.6320056992192\n",
      "Generation 5157: p = 0.9584800063324658\n",
      "Generation 5157: M(n) = 862.6320056992192\n",
      "Generation 5158: p = 0.9584800063324658\n",
      "Generation 5158: M(n) = 862.6320056992192\n",
      "Generation 5159: p = 0.9584800063324658\n",
      "Generation 5159: M(n) = 862.6320056992192\n",
      "Generation 5160: p = 0.9584800063324658\n",
      "Generation 5160: M(n) = 862.6320056992192\n",
      "Generation 5161: p = 0.9584800063324658\n",
      "Generation 5161: M(n) = 862.6320056992192\n",
      "Generation 5162: p = 0.9584800063324658\n",
      "Generation 5162: M(n) = 862.6320056992192\n",
      "Generation 5163: p = 0.9584800063324658\n",
      "Generation 5163: M(n) = 862.6320056992192\n",
      "Generation 5164: p = 0.9584800063324658\n",
      "Generation 5164: M(n) = 862.6320056992192\n",
      "Generation 5165: p = 0.9584800063324658\n",
      "Generation 5165: M(n) = 862.6320056992192\n",
      "Generation 5166: p = 0.9584800063324658\n",
      "Generation 5166: M(n) = 862.6320056992192\n",
      "Generation 5167: p = 0.9584800063324658\n",
      "Generation 5167: M(n) = 862.6320056992192\n",
      "Generation 5168: p = 0.9584800063324658\n",
      "Generation 5168: M(n) = 862.6320056992192\n",
      "Generation 5169: p = 0.9584800063324658\n",
      "Generation 5169: M(n) = 862.6320056992192\n",
      "Generation 5170: p = 0.9584800063324658\n",
      "Generation 5170: M(n) = 862.6320056992192\n",
      "Generation 5171: p = 0.9584800063324658\n",
      "Generation 5171: M(n) = 862.6320056992192\n",
      "Generation 5172: p = 0.9584800063324658\n",
      "Generation 5172: M(n) = 862.6320056992192\n",
      "Generation 5173: p = 0.9584800063324658\n",
      "Generation 5173: M(n) = 862.6320056992192\n",
      "Generation 5174: p = 0.9584800063324658\n",
      "Generation 5174: M(n) = 862.6320056992192\n",
      "Generation 5175: p = 0.9584800063324658\n",
      "Generation 5175: M(n) = 862.6320056992192\n",
      "Generation 5176: p = 0.9584800063324658\n",
      "Generation 5176: M(n) = 862.6320056992192\n",
      "Generation 5177: p = 0.9584800063324658\n",
      "Generation 5177: M(n) = 862.6320056992192\n",
      "Generation 5178: p = 0.9584800063324658\n",
      "Generation 5178: M(n) = 862.6320056992192\n",
      "Generation 5179: p = 0.9584800063324658\n",
      "Generation 5179: M(n) = 862.6320056992192\n",
      "Generation 5180: p = 0.9584800063324658\n",
      "Generation 5180: M(n) = 862.6320056992192\n",
      "Generation 5181: p = 0.9584800063324658\n",
      "Generation 5181: M(n) = 862.6320056992192\n",
      "Generation 5182: p = 0.9584800063324658\n",
      "Generation 5182: M(n) = 862.6320056992192\n",
      "Generation 5183: p = 0.9584800063324658\n",
      "Generation 5183: M(n) = 862.6320056992192\n",
      "Generation 5184: p = 0.9584800063324658\n",
      "Generation 5184: M(n) = 862.6320056992192\n",
      "Generation 5185: p = 0.9584800063324658\n",
      "Generation 5185: M(n) = 862.6320056992192\n",
      "Generation 5186: p = 0.9584800063324658\n",
      "Generation 5186: M(n) = 862.6320056992192\n",
      "Generation 5187: p = 0.9584800063324658\n",
      "Generation 5187: M(n) = 862.6320056992192\n",
      "Generation 5188: p = 0.9584800063324658\n",
      "Generation 5188: M(n) = 862.6320056992192\n",
      "Generation 5189: p = 0.9584800063324658\n",
      "Generation 5189: M(n) = 862.6320056992192\n",
      "Generation 5190: p = 0.9584800063324658\n",
      "Generation 5190: M(n) = 862.6320056992192\n",
      "Generation 5191: p = 0.9584800063324658\n",
      "Generation 5191: M(n) = 862.6320056992192\n",
      "Generation 5192: p = 0.9584800063324658\n",
      "Generation 5192: M(n) = 862.6320056992192\n",
      "Generation 5193: p = 0.9584800063324658\n",
      "Generation 5193: M(n) = 862.6320056992192\n",
      "Generation 5194: p = 0.9584800063324658\n",
      "Generation 5194: M(n) = 862.6320056992192\n",
      "Generation 5195: p = 0.9584800063324658\n",
      "Generation 5195: M(n) = 862.6320056992192\n",
      "Generation 5196: p = 0.9584800063324658\n",
      "Generation 5196: M(n) = 862.6320056992192\n",
      "Generation 5197: p = 0.9584800063324658\n",
      "Generation 5197: M(n) = 862.6320056992192\n",
      "Generation 5198: p = 0.9584800063324658\n",
      "Generation 5198: M(n) = 862.6320056992192\n",
      "Generation 5199: p = 0.9584800063324658\n",
      "Generation 5199: M(n) = 862.6320056992192\n",
      "Generation 5200: p = 0.9584800063324658\n",
      "Generation 5200: M(n) = 862.6320056992192\n",
      "Generation 5201: p = 0.9584800063324658\n",
      "Generation 5201: M(n) = 862.6320056992192\n",
      "Generation 5202: p = 0.9584800063324658\n",
      "Generation 5202: M(n) = 862.6320056992192\n",
      "Generation 5203: p = 0.9584800063324658\n",
      "Generation 5203: M(n) = 862.6320056992192\n",
      "Generation 5204: p = 0.9584800063324658\n",
      "Generation 5204: M(n) = 862.6320056992192\n",
      "Generation 5205: p = 0.9584800063324658\n",
      "Generation 5205: M(n) = 862.6320056992192\n",
      "Generation 5206: p = 0.9584800063324658\n",
      "Generation 5206: M(n) = 862.6320056992192\n",
      "Generation 5207: p = 0.9584800063324658\n",
      "Generation 5207: M(n) = 862.6320056992192\n",
      "Generation 5208: p = 0.9584800063324658\n",
      "Generation 5208: M(n) = 862.6320056992192\n",
      "Generation 5209: p = 0.9584800063324658\n",
      "Generation 5209: M(n) = 862.6320056992192\n",
      "Generation 5210: p = 0.9584800063324658\n",
      "Generation 5210: M(n) = 862.6320056992192\n",
      "Generation 5211: p = 0.9584800063324658\n",
      "Generation 5211: M(n) = 862.6320056992192\n",
      "Generation 5212: p = 0.9584800063324658\n",
      "Generation 5212: M(n) = 862.6320056992192\n",
      "Generation 5213: p = 0.9584800063324658\n",
      "Generation 5213: M(n) = 862.6320056992192\n",
      "Generation 5214: p = 0.9584800063324658\n",
      "Generation 5214: M(n) = 862.6320056992192\n",
      "Generation 5215: p = 0.9584800063324658\n",
      "Generation 5215: M(n) = 862.6320056992192\n",
      "Generation 5216: p = 0.9584800063324658\n",
      "Generation 5216: M(n) = 862.6320056992192\n",
      "Generation 5217: p = 0.9584800063324658\n",
      "Generation 5217: M(n) = 862.6320056992192\n",
      "Generation 5218: p = 0.9584800063324658\n",
      "Generation 5218: M(n) = 862.6320056992192\n",
      "Generation 5219: p = 0.9584800063324658\n",
      "Generation 5219: M(n) = 862.6320056992192\n",
      "Generation 5220: p = 0.9584800063324658\n",
      "Generation 5220: M(n) = 862.6320056992192\n",
      "Generation 5221: p = 0.9584800063324658\n",
      "Generation 5221: M(n) = 862.6320056992192\n",
      "Generation 5222: p = 0.9584800063324658\n",
      "Generation 5222: M(n) = 862.6320056992192\n",
      "Generation 5223: p = 0.9584800063324658\n",
      "Generation 5223: M(n) = 862.6320056992192\n",
      "Generation 5224: p = 0.9584800063324658\n",
      "Generation 5224: M(n) = 862.6320056992192\n",
      "Generation 5225: p = 0.9584800063324658\n",
      "Generation 5225: M(n) = 862.6320056992192\n",
      "Generation 5226: p = 0.9584800063324658\n",
      "Generation 5226: M(n) = 862.6320056992192\n",
      "Generation 5227: p = 0.9584800063324658\n",
      "Generation 5227: M(n) = 862.6320056992192\n",
      "Generation 5228: p = 0.9584800063324658\n",
      "Generation 5228: M(n) = 862.6320056992192\n",
      "Generation 5229: p = 0.9584800063324658\n",
      "Generation 5229: M(n) = 862.6320056992192\n",
      "Generation 5230: p = 0.9584800063324658\n",
      "Generation 5230: M(n) = 862.6320056992192\n",
      "Generation 5231: p = 0.9584800063324658\n",
      "Generation 5231: M(n) = 862.6320056992192\n",
      "Generation 5232: p = 0.9584800063324658\n",
      "Generation 5232: M(n) = 862.6320056992192\n",
      "Generation 5233: p = 0.9584800063324658\n",
      "Generation 5233: M(n) = 862.6320056992192\n",
      "Generation 5234: p = 0.9584800063324658\n",
      "Generation 5234: M(n) = 862.6320056992192\n",
      "Generation 5235: p = 0.9584800063324658\n",
      "Generation 5235: M(n) = 862.6320056992192\n",
      "Generation 5236: p = 0.9584800063324658\n",
      "Generation 5236: M(n) = 862.6320056992192\n",
      "Generation 5237: p = 0.9584800063324658\n",
      "Generation 5237: M(n) = 862.6320056992192\n",
      "Generation 5238: p = 0.9584800063324658\n",
      "Generation 5238: M(n) = 862.6320056992192\n",
      "Generation 5239: p = 0.9584800063324658\n",
      "Generation 5239: M(n) = 862.6320056992192\n",
      "Generation 5240: p = 0.9584800063324658\n",
      "Generation 5240: M(n) = 862.6320056992192\n",
      "Generation 5241: p = 0.9584800063324658\n",
      "Generation 5241: M(n) = 862.6320056992192\n",
      "Generation 5242: p = 0.9584800063324658\n",
      "Generation 5242: M(n) = 862.6320056992192\n",
      "Generation 5243: p = 0.9584800063324658\n",
      "Generation 5243: M(n) = 862.6320056992192\n",
      "Generation 5244: p = 0.9584800063324658\n",
      "Generation 5244: M(n) = 862.6320056992192\n",
      "Generation 5245: p = 0.9584800063324658\n",
      "Generation 5245: M(n) = 862.6320056992192\n",
      "Generation 5246: p = 0.9584800063324658\n",
      "Generation 5246: M(n) = 862.6320056992192\n",
      "Generation 5247: p = 0.9584800063324658\n",
      "Generation 5247: M(n) = 862.6320056992192\n",
      "Generation 5248: p = 0.9584800063324658\n",
      "Generation 5248: M(n) = 862.6320056992192\n",
      "Generation 5249: p = 0.9584800063324658\n",
      "Generation 5249: M(n) = 862.6320056992192\n",
      "Generation 5250: p = 0.9584800063324658\n",
      "Generation 5250: M(n) = 862.6320056992192\n",
      "Generation 5251: p = 0.9584800063324658\n",
      "Generation 5251: M(n) = 862.6320056992192\n",
      "Generation 5252: p = 0.9584800063324658\n",
      "Generation 5252: M(n) = 862.6320056992192\n",
      "Generation 5253: p = 0.9584800063324658\n",
      "Generation 5253: M(n) = 862.6320056992192\n",
      "Generation 5254: p = 0.9584800063324658\n",
      "Generation 5254: M(n) = 862.6320056992192\n",
      "Generation 5255: p = 0.9584800063324658\n",
      "Generation 5255: M(n) = 862.6320056992192\n",
      "Generation 5256: p = 0.9584800063324658\n",
      "Generation 5256: M(n) = 862.6320056992192\n",
      "Generation 5257: p = 0.9584800063324658\n",
      "Generation 5257: M(n) = 862.6320056992192\n",
      "Generation 5258: p = 0.9584800063324658\n",
      "Generation 5258: M(n) = 862.6320056992192\n",
      "Generation 5259: p = 0.9584800063324658\n",
      "Generation 5259: M(n) = 862.6320056992192\n",
      "Generation 5260: p = 0.9584800063324658\n",
      "Generation 5260: M(n) = 862.6320056992192\n",
      "Generation 5261: p = 0.9584800063324658\n",
      "Generation 5261: M(n) = 862.6320056992192\n",
      "Generation 5262: p = 0.9584800063324658\n",
      "Generation 5262: M(n) = 862.6320056992192\n",
      "Generation 5263: p = 0.9584800063324658\n",
      "Generation 5263: M(n) = 862.6320056992192\n",
      "Generation 5264: p = 0.9584800063324658\n",
      "Generation 5264: M(n) = 862.6320056992192\n",
      "Generation 5265: p = 0.9584800063324658\n",
      "Generation 5265: M(n) = 862.6320056992192\n",
      "Generation 5266: p = 0.9584800063324658\n",
      "Generation 5266: M(n) = 862.6320056992192\n",
      "Generation 5267: p = 0.9584800063324658\n",
      "Generation 5267: M(n) = 862.6320056992192\n",
      "Generation 5268: p = 0.9584800063324658\n",
      "Generation 5268: M(n) = 862.6320056992192\n",
      "Generation 5269: p = 0.9584800063324658\n",
      "Generation 5269: M(n) = 862.6320056992192\n",
      "Generation 5270: p = 0.9584800063324658\n",
      "Generation 5270: M(n) = 862.6320056992192\n",
      "Generation 5271: p = 0.9584800063324658\n",
      "Generation 5271: M(n) = 862.6320056992192\n",
      "Generation 5272: p = 0.9584800063324658\n",
      "Generation 5272: M(n) = 862.6320056992192\n",
      "Generation 5273: p = 0.9584800063324658\n",
      "Generation 5273: M(n) = 862.6320056992192\n",
      "Generation 5274: p = 0.9584800063324658\n",
      "Generation 5274: M(n) = 862.6320056992192\n",
      "Generation 5275: p = 0.9584800063324658\n",
      "Generation 5275: M(n) = 862.6320056992192\n",
      "Generation 5276: p = 0.9584800063324658\n",
      "Generation 5276: M(n) = 862.6320056992192\n",
      "Generation 5277: p = 0.9584800063324658\n",
      "Generation 5277: M(n) = 862.6320056992192\n",
      "Generation 5278: p = 0.9584800063324658\n",
      "Generation 5278: M(n) = 862.6320056992192\n",
      "Generation 5279: p = 0.9584800063324658\n",
      "Generation 5279: M(n) = 862.6320056992192\n",
      "Generation 5280: p = 0.9584800063324658\n",
      "Generation 5280: M(n) = 862.6320056992192\n",
      "Generation 5281: p = 0.9584800063324658\n",
      "Generation 5281: M(n) = 862.6320056992192\n",
      "Generation 5282: p = 0.9584800063324658\n",
      "Generation 5282: M(n) = 862.6320056992192\n",
      "Generation 5283: p = 0.9584800063324658\n",
      "Generation 5283: M(n) = 862.6320056992192\n",
      "Generation 5284: p = 0.9584800063324658\n",
      "Generation 5284: M(n) = 862.6320056992192\n",
      "Generation 5285: p = 0.9584800063324658\n",
      "Generation 5285: M(n) = 862.6320056992192\n",
      "Generation 5286: p = 0.9584800063324658\n",
      "Generation 5286: M(n) = 862.6320056992192\n",
      "Generation 5287: p = 0.9584800063324658\n",
      "Generation 5287: M(n) = 862.6320056992192\n",
      "Generation 5288: p = 0.9584800063324658\n",
      "Generation 5288: M(n) = 862.6320056992192\n",
      "Generation 5289: p = 0.9584800063324658\n",
      "Generation 5289: M(n) = 862.6320056992192\n",
      "Generation 5290: p = 0.9584800063324658\n",
      "Generation 5290: M(n) = 862.6320056992192\n",
      "Generation 5291: p = 0.9584800063324658\n",
      "Generation 5291: M(n) = 862.6320056992192\n",
      "Generation 5292: p = 0.9584800063324658\n",
      "Generation 5292: M(n) = 862.6320056992192\n",
      "Generation 5293: p = 0.9584800063324658\n",
      "Generation 5293: M(n) = 862.6320056992192\n",
      "Generation 5294: p = 0.9584800063324658\n",
      "Generation 5294: M(n) = 862.6320056992192\n",
      "Generation 5295: p = 0.9584800063324658\n",
      "Generation 5295: M(n) = 862.6320056992192\n",
      "Generation 5296: p = 0.9584800063324658\n",
      "Generation 5296: M(n) = 862.6320056992192\n",
      "Generation 5297: p = 0.9584800063324658\n",
      "Generation 5297: M(n) = 862.6320056992192\n",
      "Generation 5298: p = 0.9584800063324658\n",
      "Generation 5298: M(n) = 862.6320056992192\n",
      "Generation 5299: p = 0.9584800063324658\n",
      "Generation 5299: M(n) = 862.6320056992192\n",
      "Generation 5300: p = 0.9584800063324658\n",
      "Generation 5300: M(n) = 862.6320056992192\n",
      "Generation 5301: p = 0.9584800063324658\n",
      "Generation 5301: M(n) = 862.6320056992192\n",
      "Generation 5302: p = 0.9584800063324658\n",
      "Generation 5302: M(n) = 862.6320056992192\n",
      "Generation 5303: p = 0.9584800063324658\n",
      "Generation 5303: M(n) = 862.6320056992192\n",
      "Generation 5304: p = 0.9584800063324658\n",
      "Generation 5304: M(n) = 862.6320056992192\n",
      "Generation 5305: p = 0.9584800063324658\n",
      "Generation 5305: M(n) = 862.6320056992192\n",
      "Generation 5306: p = 0.9584800063324658\n",
      "Generation 5306: M(n) = 862.6320056992192\n",
      "Generation 5307: p = 0.9584800063324658\n",
      "Generation 5307: M(n) = 862.6320056992192\n",
      "Generation 5308: p = 0.9584800063324658\n",
      "Generation 5308: M(n) = 862.6320056992192\n",
      "Generation 5309: p = 0.9584800063324658\n",
      "Generation 5309: M(n) = 862.6320056992192\n",
      "Generation 5310: p = 0.9584800063324658\n",
      "Generation 5310: M(n) = 862.6320056992192\n",
      "Generation 5311: p = 0.9584800063324658\n",
      "Generation 5311: M(n) = 862.6320056992192\n",
      "Generation 5312: p = 0.9584800063324658\n",
      "Generation 5312: M(n) = 862.6320056992192\n",
      "Generation 5313: p = 0.9584800063324658\n",
      "Generation 5313: M(n) = 862.6320056992192\n",
      "Generation 5314: p = 0.9584800063324658\n",
      "Generation 5314: M(n) = 862.6320056992192\n",
      "Generation 5315: p = 0.9584800063324658\n",
      "Generation 5315: M(n) = 862.6320056992192\n",
      "Generation 5316: p = 0.9584800063324658\n",
      "Generation 5316: M(n) = 862.6320056992192\n",
      "Generation 5317: p = 0.9584800063324658\n",
      "Generation 5317: M(n) = 862.6320056992192\n",
      "Generation 5318: p = 0.9584800063324658\n",
      "Generation 5318: M(n) = 862.6320056992192\n",
      "Generation 5319: p = 0.9584800063324658\n",
      "Generation 5319: M(n) = 862.6320056992192\n",
      "Generation 5320: p = 0.9584800063324658\n",
      "Generation 5320: M(n) = 862.6320056992192\n",
      "Generation 5321: p = 0.9584800063324658\n",
      "Generation 5321: M(n) = 862.6320056992192\n",
      "Generation 5322: p = 0.9584800063324658\n",
      "Generation 5322: M(n) = 862.6320056992192\n",
      "Generation 5323: p = 0.9584800063324658\n",
      "Generation 5323: M(n) = 862.6320056992192\n",
      "Generation 5324: p = 0.9584800063324658\n",
      "Generation 5324: M(n) = 862.6320056992192\n",
      "Generation 5325: p = 0.9584800063324658\n",
      "Generation 5325: M(n) = 862.6320056992192\n",
      "Generation 5326: p = 0.9584800063324658\n",
      "Generation 5326: M(n) = 862.6320056992192\n",
      "Generation 5327: p = 0.9584800063324658\n",
      "Generation 5327: M(n) = 862.6320056992192\n",
      "Generation 5328: p = 0.9584800063324658\n",
      "Generation 5328: M(n) = 862.6320056992192\n",
      "Generation 5329: p = 0.9584800063324658\n",
      "Generation 5329: M(n) = 862.6320056992192\n",
      "Generation 5330: p = 0.9584800063324658\n",
      "Generation 5330: M(n) = 862.6320056992192\n",
      "Generation 5331: p = 0.9584800063324658\n",
      "Generation 5331: M(n) = 862.6320056992192\n",
      "Generation 5332: p = 0.9584800063324658\n",
      "Generation 5332: M(n) = 862.6320056992192\n",
      "Generation 5333: p = 0.9584800063324658\n",
      "Generation 5333: M(n) = 862.6320056992192\n",
      "Generation 5334: p = 0.9584800063324658\n",
      "Generation 5334: M(n) = 862.6320056992192\n",
      "Generation 5335: p = 0.9584800063324658\n",
      "Generation 5335: M(n) = 862.6320056992192\n",
      "Generation 5336: p = 0.9584800063324658\n",
      "Generation 5336: M(n) = 862.6320056992192\n",
      "Generation 5337: p = 0.9584800063324658\n",
      "Generation 5337: M(n) = 862.6320056992192\n",
      "Generation 5338: p = 0.9584800063324658\n",
      "Generation 5338: M(n) = 862.6320056992192\n",
      "Generation 5339: p = 0.9584800063324658\n",
      "Generation 5339: M(n) = 862.6320056992192\n",
      "Generation 5340: p = 0.9584800063324658\n",
      "Generation 5340: M(n) = 862.6320056992192\n",
      "Generation 5341: p = 0.9584800063324658\n",
      "Generation 5341: M(n) = 862.6320056992192\n",
      "Generation 5342: p = 0.9584800063324658\n",
      "Generation 5342: M(n) = 862.6320056992192\n",
      "Generation 5343: p = 0.9584800063324658\n",
      "Generation 5343: M(n) = 862.6320056992192\n",
      "Generation 5344: p = 0.9584800063324658\n",
      "Generation 5344: M(n) = 862.6320056992192\n",
      "Generation 5345: p = 0.9584800063324658\n",
      "Generation 5345: M(n) = 862.6320056992192\n",
      "Generation 5346: p = 0.9584800063324658\n",
      "Generation 5346: M(n) = 862.6320056992192\n",
      "Generation 5347: p = 0.9584800063324658\n",
      "Generation 5347: M(n) = 862.6320056992192\n",
      "Generation 5348: p = 0.9584800063324658\n",
      "Generation 5348: M(n) = 862.6320056992192\n",
      "Generation 5349: p = 0.9584800063324658\n",
      "Generation 5349: M(n) = 862.6320056992192\n",
      "Generation 5350: p = 0.9584800063324658\n",
      "Generation 5350: M(n) = 862.6320056992192\n",
      "Generation 5351: p = 0.9584800063324658\n",
      "Generation 5351: M(n) = 862.6320056992192\n",
      "Generation 5352: p = 0.9584800063324658\n",
      "Generation 5352: M(n) = 862.6320056992192\n",
      "Generation 5353: p = 0.9584800063324658\n",
      "Generation 5353: M(n) = 862.6320056992192\n",
      "Generation 5354: p = 0.9584800063324658\n",
      "Generation 5354: M(n) = 862.6320056992192\n",
      "Generation 5355: p = 0.9584800063324658\n",
      "Generation 5355: M(n) = 862.6320056992192\n",
      "Generation 5356: p = 0.9584800063324658\n",
      "Generation 5356: M(n) = 862.6320056992192\n",
      "Generation 5357: p = 0.9584800063324658\n",
      "Generation 5357: M(n) = 862.6320056992192\n",
      "Generation 5358: p = 0.9584800063324658\n",
      "Generation 5358: M(n) = 862.6320056992192\n",
      "Generation 5359: p = 0.9584800063324658\n",
      "Generation 5359: M(n) = 862.6320056992192\n",
      "Generation 5360: p = 0.9584800063324658\n",
      "Generation 5360: M(n) = 862.6320056992192\n",
      "Generation 5361: p = 0.9584800063324658\n",
      "Generation 5361: M(n) = 862.6320056992192\n",
      "Generation 5362: p = 0.9584800063324658\n",
      "Generation 5362: M(n) = 862.6320056992192\n",
      "Generation 5363: p = 0.9584800063324658\n",
      "Generation 5363: M(n) = 862.6320056992192\n",
      "Generation 5364: p = 0.9584800063324658\n",
      "Generation 5364: M(n) = 862.6320056992192\n",
      "Generation 5365: p = 0.9584800063324658\n",
      "Generation 5365: M(n) = 862.6320056992192\n",
      "Generation 5366: p = 0.9584800063324658\n",
      "Generation 5366: M(n) = 862.6320056992192\n",
      "Generation 5367: p = 0.9584800063324658\n",
      "Generation 5367: M(n) = 862.6320056992192\n",
      "Generation 5368: p = 0.9584800063324658\n",
      "Generation 5368: M(n) = 862.6320056992192\n",
      "Generation 5369: p = 0.9584800063324658\n",
      "Generation 5369: M(n) = 862.6320056992192\n",
      "Generation 5370: p = 0.9584800063324658\n",
      "Generation 5370: M(n) = 862.6320056992192\n",
      "Generation 5371: p = 0.9584800063324658\n",
      "Generation 5371: M(n) = 862.6320056992192\n",
      "Generation 5372: p = 0.9584800063324658\n",
      "Generation 5372: M(n) = 862.6320056992192\n",
      "Generation 5373: p = 0.9584800063324658\n",
      "Generation 5373: M(n) = 862.6320056992192\n",
      "Generation 5374: p = 0.9584800063324658\n",
      "Generation 5374: M(n) = 862.6320056992192\n",
      "Generation 5375: p = 0.9584800063324658\n",
      "Generation 5375: M(n) = 862.6320056992192\n",
      "Generation 5376: p = 0.9584800063324658\n",
      "Generation 5376: M(n) = 862.6320056992192\n",
      "Generation 5377: p = 0.9584800063324658\n",
      "Generation 5377: M(n) = 862.6320056992192\n",
      "Generation 5378: p = 0.9584800063324658\n",
      "Generation 5378: M(n) = 862.6320056992192\n",
      "Generation 5379: p = 0.9584800063324658\n",
      "Generation 5379: M(n) = 862.6320056992192\n",
      "Generation 5380: p = 0.9584800063324658\n",
      "Generation 5380: M(n) = 862.6320056992192\n",
      "Generation 5381: p = 0.9584800063324658\n",
      "Generation 5381: M(n) = 862.6320056992192\n",
      "Generation 5382: p = 0.9584800063324658\n",
      "Generation 5382: M(n) = 862.6320056992192\n",
      "Generation 5383: p = 0.9584800063324658\n",
      "Generation 5383: M(n) = 862.6320056992192\n",
      "Generation 5384: p = 0.9584800063324658\n",
      "Generation 5384: M(n) = 862.6320056992192\n",
      "Generation 5385: p = 0.9584800063324658\n",
      "Generation 5385: M(n) = 862.6320056992192\n",
      "Generation 5386: p = 0.9584800063324658\n",
      "Generation 5386: M(n) = 862.6320056992192\n",
      "Generation 5387: p = 0.9584800063324658\n",
      "Generation 5387: M(n) = 862.6320056992192\n",
      "Generation 5388: p = 0.9584800063324658\n",
      "Generation 5388: M(n) = 862.6320056992192\n",
      "Generation 5389: p = 0.9584800063324658\n",
      "Generation 5389: M(n) = 862.6320056992192\n",
      "Generation 5390: p = 0.9584800063324658\n",
      "Generation 5390: M(n) = 862.6320056992192\n",
      "Generation 5391: p = 0.9584800063324658\n",
      "Generation 5391: M(n) = 862.6320056992192\n",
      "Generation 5392: p = 0.9584800063324658\n",
      "Generation 5392: M(n) = 862.6320056992192\n",
      "Generation 5393: p = 0.9584800063324658\n",
      "Generation 5393: M(n) = 862.6320056992192\n",
      "Generation 5394: p = 0.9584800063324658\n",
      "Generation 5394: M(n) = 862.6320056992192\n",
      "Generation 5395: p = 0.9584800063324658\n",
      "Generation 5395: M(n) = 862.6320056992192\n",
      "Generation 5396: p = 0.9584800063324658\n",
      "Generation 5396: M(n) = 862.6320056992192\n",
      "Generation 5397: p = 0.9584800063324658\n",
      "Generation 5397: M(n) = 862.6320056992192\n",
      "Generation 5398: p = 0.9584800063324658\n",
      "Generation 5398: M(n) = 862.6320056992192\n",
      "Generation 5399: p = 0.9584800063324658\n",
      "Generation 5399: M(n) = 862.6320056992192\n",
      "Generation 5400: p = 0.9584800063324658\n",
      "Generation 5400: M(n) = 862.6320056992192\n",
      "Generation 5401: p = 0.9584800063324658\n",
      "Generation 5401: M(n) = 862.6320056992192\n",
      "Generation 5402: p = 0.9584800063324658\n",
      "Generation 5402: M(n) = 862.6320056992192\n",
      "Generation 5403: p = 0.9584800063324658\n",
      "Generation 5403: M(n) = 862.6320056992192\n",
      "Generation 5404: p = 0.9584800063324658\n",
      "Generation 5404: M(n) = 862.6320056992192\n",
      "Generation 5405: p = 0.9584800063324658\n",
      "Generation 5405: M(n) = 862.6320056992192\n",
      "Generation 5406: p = 0.9584800063324658\n",
      "Generation 5406: M(n) = 862.6320056992192\n",
      "Generation 5407: p = 0.9584800063324658\n",
      "Generation 5407: M(n) = 862.6320056992192\n",
      "Generation 5408: p = 0.9584800063324658\n",
      "Generation 5408: M(n) = 862.6320056992192\n",
      "Generation 5409: p = 0.9584800063324658\n",
      "Generation 5409: M(n) = 862.6320056992192\n",
      "Generation 5410: p = 0.9584800063324658\n",
      "Generation 5410: M(n) = 862.6320056992192\n",
      "Generation 5411: p = 0.9584800063324658\n",
      "Generation 5411: M(n) = 862.6320056992192\n",
      "Generation 5412: p = 0.9584800063324658\n",
      "Generation 5412: M(n) = 862.6320056992192\n",
      "Generation 5413: p = 0.9584800063324658\n",
      "Generation 5413: M(n) = 862.6320056992192\n",
      "Generation 5414: p = 0.9584800063324658\n",
      "Generation 5414: M(n) = 862.6320056992192\n",
      "Generation 5415: p = 0.9584800063324658\n",
      "Generation 5415: M(n) = 862.6320056992192\n",
      "Generation 5416: p = 0.9584800063324658\n",
      "Generation 5416: M(n) = 862.6320056992192\n",
      "Generation 5417: p = 0.9584800063324658\n",
      "Generation 5417: M(n) = 862.6320056992192\n",
      "Generation 5418: p = 0.9584800063324658\n",
      "Generation 5418: M(n) = 862.6320056992192\n",
      "Generation 5419: p = 0.9584800063324658\n",
      "Generation 5419: M(n) = 862.6320056992192\n",
      "Generation 5420: p = 0.9584800063324658\n",
      "Generation 5420: M(n) = 862.6320056992192\n",
      "Generation 5421: p = 0.9584800063324658\n",
      "Generation 5421: M(n) = 862.6320056992192\n",
      "Generation 5422: p = 0.9584800063324658\n",
      "Generation 5422: M(n) = 862.6320056992192\n",
      "Generation 5423: p = 0.9584800063324658\n",
      "Generation 5423: M(n) = 862.6320056992192\n",
      "Generation 5424: p = 0.9584800063324658\n",
      "Generation 5424: M(n) = 862.6320056992192\n",
      "Generation 5425: p = 0.9584800063324658\n",
      "Generation 5425: M(n) = 862.6320056992192\n",
      "Generation 5426: p = 0.9584800063324658\n",
      "Generation 5426: M(n) = 862.6320056992192\n",
      "Generation 5427: p = 0.9584800063324658\n",
      "Generation 5427: M(n) = 862.6320056992192\n",
      "Generation 5428: p = 0.9584800063324658\n",
      "Generation 5428: M(n) = 862.6320056992192\n",
      "Generation 5429: p = 0.9584800063324658\n",
      "Generation 5429: M(n) = 862.6320056992192\n",
      "Generation 5430: p = 0.9584800063324658\n",
      "Generation 5430: M(n) = 862.6320056992192\n",
      "Generation 5431: p = 0.9584800063324658\n",
      "Generation 5431: M(n) = 862.6320056992192\n",
      "Generation 5432: p = 0.9584800063324658\n",
      "Generation 5432: M(n) = 862.6320056992192\n",
      "Generation 5433: p = 0.9584800063324658\n",
      "Generation 5433: M(n) = 862.6320056992192\n",
      "Generation 5434: p = 0.9584800063324658\n",
      "Generation 5434: M(n) = 862.6320056992192\n",
      "Generation 5435: p = 0.9584800063324658\n",
      "Generation 5435: M(n) = 862.6320056992192\n",
      "Generation 5436: p = 0.9584800063324658\n",
      "Generation 5436: M(n) = 862.6320056992192\n",
      "Generation 5437: p = 0.9584800063324658\n",
      "Generation 5437: M(n) = 862.6320056992192\n",
      "Generation 5438: p = 0.9584800063324658\n",
      "Generation 5438: M(n) = 862.6320056992192\n",
      "Generation 5439: p = 0.9584800063324658\n",
      "Generation 5439: M(n) = 862.6320056992192\n",
      "Generation 5440: p = 0.9584800063324658\n",
      "Generation 5440: M(n) = 862.6320056992192\n",
      "Generation 5441: p = 0.9584800063324658\n",
      "Generation 5441: M(n) = 862.6320056992192\n",
      "Generation 5442: p = 0.9584800063324658\n",
      "Generation 5442: M(n) = 862.6320056992192\n",
      "Generation 5443: p = 0.9584800063324658\n",
      "Generation 5443: M(n) = 862.6320056992192\n",
      "Generation 5444: p = 0.9584800063324658\n",
      "Generation 5444: M(n) = 862.6320056992192\n",
      "Generation 5445: p = 0.9584800063324658\n",
      "Generation 5445: M(n) = 862.6320056992192\n",
      "Generation 5446: p = 0.9584800063324658\n",
      "Generation 5446: M(n) = 862.6320056992192\n",
      "Generation 5447: p = 0.9584800063324658\n",
      "Generation 5447: M(n) = 862.6320056992192\n",
      "Generation 5448: p = 0.9584800063324658\n",
      "Generation 5448: M(n) = 862.6320056992192\n",
      "Generation 5449: p = 0.9584800063324658\n",
      "Generation 5449: M(n) = 862.6320056992192\n",
      "Generation 5450: p = 0.9584800063324658\n",
      "Generation 5450: M(n) = 862.6320056992192\n",
      "Generation 5451: p = 0.9584800063324658\n",
      "Generation 5451: M(n) = 862.6320056992192\n",
      "Generation 5452: p = 0.9584800063324658\n",
      "Generation 5452: M(n) = 862.6320056992192\n",
      "Generation 5453: p = 0.9584800063324658\n",
      "Generation 5453: M(n) = 862.6320056992192\n",
      "Generation 5454: p = 0.9584800063324658\n",
      "Generation 5454: M(n) = 862.6320056992192\n",
      "Generation 5455: p = 0.9584800063324658\n",
      "Generation 5455: M(n) = 862.6320056992192\n",
      "Generation 5456: p = 0.9584800063324658\n",
      "Generation 5456: M(n) = 862.6320056992192\n",
      "Generation 5457: p = 0.9584800063324658\n",
      "Generation 5457: M(n) = 862.6320056992192\n",
      "Generation 5458: p = 0.9584800063324658\n",
      "Generation 5458: M(n) = 862.6320056992192\n",
      "Generation 5459: p = 0.9584800063324658\n",
      "Generation 5459: M(n) = 862.6320056992192\n",
      "Generation 5460: p = 0.9584800063324658\n",
      "Generation 5460: M(n) = 862.6320056992192\n",
      "Generation 5461: p = 0.9584800063324658\n",
      "Generation 5461: M(n) = 862.6320056992192\n",
      "Generation 5462: p = 0.9584800063324658\n",
      "Generation 5462: M(n) = 862.6320056992192\n",
      "Generation 5463: p = 0.9584800063324658\n",
      "Generation 5463: M(n) = 862.6320056992192\n",
      "Generation 5464: p = 0.9584800063324658\n",
      "Generation 5464: M(n) = 862.6320056992192\n",
      "Generation 5465: p = 0.9584800063324658\n",
      "Generation 5465: M(n) = 862.6320056992192\n",
      "Generation 5466: p = 0.9584800063324658\n",
      "Generation 5466: M(n) = 862.6320056992192\n",
      "Generation 5467: p = 0.9584800063324658\n",
      "Generation 5467: M(n) = 862.6320056992192\n",
      "Generation 5468: p = 0.9584800063324658\n",
      "Generation 5468: M(n) = 862.6320056992192\n",
      "Generation 5469: p = 0.9584800063324658\n",
      "Generation 5469: M(n) = 862.6320056992192\n",
      "Generation 5470: p = 0.9584800063324658\n",
      "Generation 5470: M(n) = 862.6320056992192\n",
      "Generation 5471: p = 0.9584800063324658\n",
      "Generation 5471: M(n) = 862.6320056992192\n",
      "Generation 5472: p = 0.9584800063324658\n",
      "Generation 5472: M(n) = 862.6320056992192\n",
      "Generation 5473: p = 0.9584800063324658\n",
      "Generation 5473: M(n) = 862.6320056992192\n",
      "Generation 5474: p = 0.9584800063324658\n",
      "Generation 5474: M(n) = 862.6320056992192\n",
      "Generation 5475: p = 0.9584800063324658\n",
      "Generation 5475: M(n) = 862.6320056992192\n",
      "Generation 5476: p = 0.9584800063324658\n",
      "Generation 5476: M(n) = 862.6320056992192\n",
      "Generation 5477: p = 0.9584800063324658\n",
      "Generation 5477: M(n) = 862.6320056992192\n",
      "Generation 5478: p = 0.9584800063324658\n",
      "Generation 5478: M(n) = 862.6320056992192\n",
      "Generation 5479: p = 0.9584800063324658\n",
      "Generation 5479: M(n) = 862.6320056992192\n",
      "Generation 5480: p = 0.9584800063324658\n",
      "Generation 5480: M(n) = 862.6320056992192\n",
      "Generation 5481: p = 0.9584800063324658\n",
      "Generation 5481: M(n) = 862.6320056992192\n",
      "Generation 5482: p = 0.9584800063324658\n",
      "Generation 5482: M(n) = 862.6320056992192\n",
      "Generation 5483: p = 0.9584800063324658\n",
      "Generation 5483: M(n) = 862.6320056992192\n",
      "Generation 5484: p = 0.9584800063324658\n",
      "Generation 5484: M(n) = 862.6320056992192\n",
      "Generation 5485: p = 0.9584800063324658\n",
      "Generation 5485: M(n) = 862.6320056992192\n",
      "Generation 5486: p = 0.9584800063324658\n",
      "Generation 5486: M(n) = 862.6320056992192\n",
      "Generation 5487: p = 0.9584800063324658\n",
      "Generation 5487: M(n) = 862.6320056992192\n",
      "Generation 5488: p = 0.9584800063324658\n",
      "Generation 5488: M(n) = 862.6320056992192\n",
      "Generation 5489: p = 0.9584800063324658\n",
      "Generation 5489: M(n) = 862.6320056992192\n",
      "Generation 5490: p = 0.9584800063324658\n",
      "Generation 5490: M(n) = 862.6320056992192\n",
      "Generation 5491: p = 0.9584800063324658\n",
      "Generation 5491: M(n) = 862.6320056992192\n",
      "Generation 5492: p = 0.9584800063324658\n",
      "Generation 5492: M(n) = 862.6320056992192\n",
      "Generation 5493: p = 0.9584800063324658\n",
      "Generation 5493: M(n) = 862.6320056992192\n",
      "Generation 5494: p = 0.9584800063324658\n",
      "Generation 5494: M(n) = 862.6320056992192\n",
      "Generation 5495: p = 0.9584800063324658\n",
      "Generation 5495: M(n) = 862.6320056992192\n",
      "Generation 5496: p = 0.9584800063324658\n",
      "Generation 5496: M(n) = 862.6320056992192\n",
      "Generation 5497: p = 0.9584800063324658\n",
      "Generation 5497: M(n) = 862.6320056992192\n",
      "Generation 5498: p = 0.9584800063324658\n",
      "Generation 5498: M(n) = 862.6320056992192\n",
      "Generation 5499: p = 0.9584800063324658\n",
      "Generation 5499: M(n) = 862.6320056992192\n",
      "Generation 5500: p = 0.9584800063324658\n",
      "Generation 5500: M(n) = 862.6320056992192\n",
      "Generation 5501: p = 0.9584800063324658\n",
      "Generation 5501: M(n) = 862.6320056992192\n",
      "Generation 5502: p = 0.9584800063324658\n",
      "Generation 5502: M(n) = 862.6320056992192\n",
      "Generation 5503: p = 0.9584800063324658\n",
      "Generation 5503: M(n) = 862.6320056992192\n",
      "Generation 5504: p = 0.9584800063324658\n",
      "Generation 5504: M(n) = 862.6320056992192\n",
      "Generation 5505: p = 0.9584800063324658\n",
      "Generation 5505: M(n) = 862.6320056992192\n",
      "Generation 5506: p = 0.9584800063324658\n",
      "Generation 5506: M(n) = 862.6320056992192\n",
      "Generation 5507: p = 0.9584800063324658\n",
      "Generation 5507: M(n) = 862.6320056992192\n",
      "Generation 5508: p = 0.9584800063324658\n",
      "Generation 5508: M(n) = 862.6320056992192\n",
      "Generation 5509: p = 0.9584800063324658\n",
      "Generation 5509: M(n) = 862.6320056992192\n",
      "Generation 5510: p = 0.9584800063324658\n",
      "Generation 5510: M(n) = 862.6320056992192\n",
      "Generation 5511: p = 0.9584800063324658\n",
      "Generation 5511: M(n) = 862.6320056992192\n",
      "Generation 5512: p = 0.9584800063324658\n",
      "Generation 5512: M(n) = 862.6320056992192\n",
      "Generation 5513: p = 0.9584800063324658\n",
      "Generation 5513: M(n) = 862.6320056992192\n",
      "Generation 5514: p = 0.9584800063324658\n",
      "Generation 5514: M(n) = 862.6320056992192\n",
      "Generation 5515: p = 0.9584800063324658\n",
      "Generation 5515: M(n) = 862.6320056992192\n",
      "Generation 5516: p = 0.9584800063324658\n",
      "Generation 5516: M(n) = 862.6320056992192\n",
      "Generation 5517: p = 0.9584800063324658\n",
      "Generation 5517: M(n) = 862.6320056992192\n",
      "Generation 5518: p = 0.9584800063324658\n",
      "Generation 5518: M(n) = 862.6320056992192\n",
      "Generation 5519: p = 0.9584800063324658\n",
      "Generation 5519: M(n) = 862.6320056992192\n",
      "Generation 5520: p = 0.9584800063324658\n",
      "Generation 5520: M(n) = 862.6320056992192\n",
      "Generation 5521: p = 0.9584800063324658\n",
      "Generation 5521: M(n) = 862.6320056992192\n",
      "Generation 5522: p = 0.9584800063324658\n",
      "Generation 5522: M(n) = 862.6320056992192\n",
      "Generation 5523: p = 0.9584800063324658\n",
      "Generation 5523: M(n) = 862.6320056992192\n",
      "Generation 5524: p = 0.9584800063324658\n",
      "Generation 5524: M(n) = 862.6320056992192\n",
      "Generation 5525: p = 0.9584800063324658\n",
      "Generation 5525: M(n) = 862.6320056992192\n",
      "Generation 5526: p = 0.9584800063324658\n",
      "Generation 5526: M(n) = 862.6320056992192\n",
      "Generation 5527: p = 0.9584800063324658\n",
      "Generation 5527: M(n) = 862.6320056992192\n",
      "Generation 5528: p = 0.9584800063324658\n",
      "Generation 5528: M(n) = 862.6320056992192\n",
      "Generation 5529: p = 0.9584800063324658\n",
      "Generation 5529: M(n) = 862.6320056992192\n",
      "Generation 5530: p = 0.9584800063324658\n",
      "Generation 5530: M(n) = 862.6320056992192\n",
      "Generation 5531: p = 0.9584800063324658\n",
      "Generation 5531: M(n) = 862.6320056992192\n",
      "Generation 5532: p = 0.9584800063324658\n",
      "Generation 5532: M(n) = 862.6320056992192\n",
      "Generation 5533: p = 0.9584800063324658\n",
      "Generation 5533: M(n) = 862.6320056992192\n",
      "Generation 5534: p = 0.9584800063324658\n",
      "Generation 5534: M(n) = 862.6320056992192\n",
      "Generation 5535: p = 0.9584800063324658\n",
      "Generation 5535: M(n) = 862.6320056992192\n",
      "Generation 5536: p = 0.9584800063324658\n",
      "Generation 5536: M(n) = 862.6320056992192\n",
      "Generation 5537: p = 0.9584800063324658\n",
      "Generation 5537: M(n) = 862.6320056992192\n",
      "Generation 5538: p = 0.9584800063324658\n",
      "Generation 5538: M(n) = 862.6320056992192\n",
      "Generation 5539: p = 0.9584800063324658\n",
      "Generation 5539: M(n) = 862.6320056992192\n",
      "Generation 5540: p = 0.9584800063324658\n",
      "Generation 5540: M(n) = 862.6320056992192\n",
      "Generation 5541: p = 0.9584800063324658\n",
      "Generation 5541: M(n) = 862.6320056992192\n",
      "Generation 5542: p = 0.9584800063324658\n",
      "Generation 5542: M(n) = 862.6320056992192\n",
      "Generation 5543: p = 0.9584800063324658\n",
      "Generation 5543: M(n) = 862.6320056992192\n",
      "Generation 5544: p = 0.9584800063324658\n",
      "Generation 5544: M(n) = 862.6320056992192\n",
      "Generation 5545: p = 0.9584800063324658\n",
      "Generation 5545: M(n) = 862.6320056992192\n",
      "Generation 5546: p = 0.9584800063324658\n",
      "Generation 5546: M(n) = 862.6320056992192\n",
      "Generation 5547: p = 0.9584800063324658\n",
      "Generation 5547: M(n) = 862.6320056992192\n",
      "Generation 5548: p = 0.9584800063324658\n",
      "Generation 5548: M(n) = 862.6320056992192\n",
      "Generation 5549: p = 0.9584800063324658\n",
      "Generation 5549: M(n) = 862.6320056992192\n",
      "Generation 5550: p = 0.9584800063324658\n",
      "Generation 5550: M(n) = 862.6320056992192\n",
      "Generation 5551: p = 0.9584800063324658\n",
      "Generation 5551: M(n) = 862.6320056992192\n",
      "Generation 5552: p = 0.9584800063324658\n",
      "Generation 5552: M(n) = 862.6320056992192\n",
      "Generation 5553: p = 0.9584800063324658\n",
      "Generation 5553: M(n) = 862.6320056992192\n",
      "Generation 5554: p = 0.9584800063324658\n",
      "Generation 5554: M(n) = 862.6320056992192\n",
      "Generation 5555: p = 0.9584800063324658\n",
      "Generation 5555: M(n) = 862.6320056992192\n",
      "Generation 5556: p = 0.9584800063324658\n",
      "Generation 5556: M(n) = 862.6320056992192\n",
      "Generation 5557: p = 0.9584800063324658\n",
      "Generation 5557: M(n) = 862.6320056992192\n",
      "Generation 5558: p = 0.9584800063324658\n",
      "Generation 5558: M(n) = 862.6320056992192\n",
      "Generation 5559: p = 0.9584800063324658\n",
      "Generation 5559: M(n) = 862.6320056992192\n",
      "Generation 5560: p = 0.9584800063324658\n",
      "Generation 5560: M(n) = 862.6320056992192\n",
      "Generation 5561: p = 0.9584800063324658\n",
      "Generation 5561: M(n) = 862.6320056992192\n",
      "Generation 5562: p = 0.9584800063324658\n",
      "Generation 5562: M(n) = 862.6320056992192\n",
      "Generation 5563: p = 0.9584800063324658\n",
      "Generation 5563: M(n) = 862.6320056992192\n",
      "Generation 5564: p = 0.9584800063324658\n",
      "Generation 5564: M(n) = 862.6320056992192\n",
      "Generation 5565: p = 0.9584800063324658\n",
      "Generation 5565: M(n) = 862.6320056992192\n",
      "Generation 5566: p = 0.9584800063324658\n",
      "Generation 5566: M(n) = 862.6320056992192\n",
      "Generation 5567: p = 0.9584800063324658\n",
      "Generation 5567: M(n) = 862.6320056992192\n",
      "Generation 5568: p = 0.9584800063324658\n",
      "Generation 5568: M(n) = 862.6320056992192\n",
      "Generation 5569: p = 0.9584800063324658\n",
      "Generation 5569: M(n) = 862.6320056992192\n",
      "Generation 5570: p = 0.9584800063324658\n",
      "Generation 5570: M(n) = 862.6320056992192\n",
      "Generation 5571: p = 0.9584800063324658\n",
      "Generation 5571: M(n) = 862.6320056992192\n",
      "Generation 5572: p = 0.9584800063324658\n",
      "Generation 5572: M(n) = 862.6320056992192\n",
      "Generation 5573: p = 0.9584800063324658\n",
      "Generation 5573: M(n) = 862.6320056992192\n",
      "Generation 5574: p = 0.9584800063324658\n",
      "Generation 5574: M(n) = 862.6320056992192\n",
      "Generation 5575: p = 0.9584800063324658\n",
      "Generation 5575: M(n) = 862.6320056992192\n",
      "Generation 5576: p = 0.9584800063324658\n",
      "Generation 5576: M(n) = 862.6320056992192\n",
      "Generation 5577: p = 0.9584800063324658\n",
      "Generation 5577: M(n) = 862.6320056992192\n",
      "Generation 5578: p = 0.9584800063324658\n",
      "Generation 5578: M(n) = 862.6320056992192\n",
      "Generation 5579: p = 0.9584800063324658\n",
      "Generation 5579: M(n) = 862.6320056992192\n",
      "Generation 5580: p = 0.9584800063324658\n",
      "Generation 5580: M(n) = 862.6320056992192\n",
      "Generation 5581: p = 0.9584800063324658\n",
      "Generation 5581: M(n) = 862.6320056992192\n",
      "Generation 5582: p = 0.9584800063324658\n",
      "Generation 5582: M(n) = 862.6320056992192\n",
      "Generation 5583: p = 0.9584800063324658\n",
      "Generation 5583: M(n) = 862.6320056992192\n",
      "Generation 5584: p = 0.9584800063324658\n",
      "Generation 5584: M(n) = 862.6320056992192\n",
      "Generation 5585: p = 0.9584800063324658\n",
      "Generation 5585: M(n) = 862.6320056992192\n",
      "Generation 5586: p = 0.9584800063324658\n",
      "Generation 5586: M(n) = 862.6320056992192\n",
      "Generation 5587: p = 0.9584800063324658\n",
      "Generation 5587: M(n) = 862.6320056992192\n",
      "Generation 5588: p = 0.9584800063324658\n",
      "Generation 5588: M(n) = 862.6320056992192\n",
      "Generation 5589: p = 0.9584800063324658\n",
      "Generation 5589: M(n) = 862.6320056992192\n",
      "Generation 5590: p = 0.9584800063324658\n",
      "Generation 5590: M(n) = 862.6320056992192\n",
      "Generation 5591: p = 0.9584800063324658\n",
      "Generation 5591: M(n) = 862.6320056992192\n",
      "Generation 5592: p = 0.9584800063324658\n",
      "Generation 5592: M(n) = 862.6320056992192\n",
      "Generation 5593: p = 0.9584800063324658\n",
      "Generation 5593: M(n) = 862.6320056992192\n",
      "Generation 5594: p = 0.9584800063324658\n",
      "Generation 5594: M(n) = 862.6320056992192\n",
      "Generation 5595: p = 0.9584800063324658\n",
      "Generation 5595: M(n) = 862.6320056992192\n",
      "Generation 5596: p = 0.9584800063324658\n",
      "Generation 5596: M(n) = 862.6320056992192\n",
      "Generation 5597: p = 0.9584800063324658\n",
      "Generation 5597: M(n) = 862.6320056992192\n",
      "Generation 5598: p = 0.9584800063324658\n",
      "Generation 5598: M(n) = 862.6320056992192\n",
      "Generation 5599: p = 0.9584800063324658\n",
      "Generation 5599: M(n) = 862.6320056992192\n",
      "Generation 5600: p = 0.9584800063324658\n",
      "Generation 5600: M(n) = 862.6320056992192\n",
      "Generation 5601: p = 0.9584800063324658\n",
      "Generation 5601: M(n) = 862.6320056992192\n",
      "Generation 5602: p = 0.9584800063324658\n",
      "Generation 5602: M(n) = 862.6320056992192\n",
      "Generation 5603: p = 0.9584800063324658\n",
      "Generation 5603: M(n) = 862.6320056992192\n",
      "Generation 5604: p = 0.9584800063324658\n",
      "Generation 5604: M(n) = 862.6320056992192\n",
      "Generation 5605: p = 0.9584800063324658\n",
      "Generation 5605: M(n) = 862.6320056992192\n",
      "Generation 5606: p = 0.9584800063324658\n",
      "Generation 5606: M(n) = 862.6320056992192\n",
      "Generation 5607: p = 0.9584800063324658\n",
      "Generation 5607: M(n) = 862.6320056992192\n",
      "Generation 5608: p = 0.9584800063324658\n",
      "Generation 5608: M(n) = 862.6320056992192\n",
      "Generation 5609: p = 0.9584800063324658\n",
      "Generation 5609: M(n) = 862.6320056992192\n",
      "Generation 5610: p = 0.9584800063324658\n",
      "Generation 5610: M(n) = 862.6320056992192\n",
      "Generation 5611: p = 0.9584800063324658\n",
      "Generation 5611: M(n) = 862.6320056992192\n",
      "Generation 5612: p = 0.9584800063324658\n",
      "Generation 5612: M(n) = 862.6320056992192\n",
      "Generation 5613: p = 0.9584800063324658\n",
      "Generation 5613: M(n) = 862.6320056992192\n",
      "Generation 5614: p = 0.9584800063324658\n",
      "Generation 5614: M(n) = 862.6320056992192\n",
      "Generation 5615: p = 0.9584800063324658\n",
      "Generation 5615: M(n) = 862.6320056992192\n",
      "Generation 5616: p = 0.9584800063324658\n",
      "Generation 5616: M(n) = 862.6320056992192\n",
      "Generation 5617: p = 0.9584800063324658\n",
      "Generation 5617: M(n) = 862.6320056992192\n",
      "Generation 5618: p = 0.9584800063324658\n",
      "Generation 5618: M(n) = 862.6320056992192\n",
      "Generation 5619: p = 0.9584800063324658\n",
      "Generation 5619: M(n) = 862.6320056992192\n",
      "Generation 5620: p = 0.9584800063324658\n",
      "Generation 5620: M(n) = 862.6320056992192\n",
      "Generation 5621: p = 0.9584800063324658\n",
      "Generation 5621: M(n) = 862.6320056992192\n",
      "Generation 5622: p = 0.9584800063324658\n",
      "Generation 5622: M(n) = 862.6320056992192\n",
      "Generation 5623: p = 0.9584800063324658\n",
      "Generation 5623: M(n) = 862.6320056992192\n",
      "Generation 5624: p = 0.9584800063324658\n",
      "Generation 5624: M(n) = 862.6320056992192\n",
      "Generation 5625: p = 0.9584800063324658\n",
      "Generation 5625: M(n) = 862.6320056992192\n",
      "Generation 5626: p = 0.9584800063324658\n",
      "Generation 5626: M(n) = 862.6320056992192\n",
      "Generation 5627: p = 0.9584800063324658\n",
      "Generation 5627: M(n) = 862.6320056992192\n",
      "Generation 5628: p = 0.9584800063324658\n",
      "Generation 5628: M(n) = 862.6320056992192\n",
      "Generation 5629: p = 0.9584800063324658\n",
      "Generation 5629: M(n) = 862.6320056992192\n",
      "Generation 5630: p = 0.9584800063324658\n",
      "Generation 5630: M(n) = 862.6320056992192\n",
      "Generation 5631: p = 0.9584800063324658\n",
      "Generation 5631: M(n) = 862.6320056992192\n",
      "Generation 5632: p = 0.9584800063324658\n",
      "Generation 5632: M(n) = 862.6320056992192\n",
      "Generation 5633: p = 0.9584800063324658\n",
      "Generation 5633: M(n) = 862.6320056992192\n",
      "Generation 5634: p = 0.9584800063324658\n",
      "Generation 5634: M(n) = 862.6320056992192\n",
      "Generation 5635: p = 0.9584800063324658\n",
      "Generation 5635: M(n) = 862.6320056992192\n",
      "Generation 5636: p = 0.9584800063324658\n",
      "Generation 5636: M(n) = 862.6320056992192\n",
      "Generation 5637: p = 0.9584800063324658\n",
      "Generation 5637: M(n) = 862.6320056992192\n",
      "Generation 5638: p = 0.9584800063324658\n",
      "Generation 5638: M(n) = 862.6320056992192\n",
      "Generation 5639: p = 0.9584800063324658\n",
      "Generation 5639: M(n) = 862.6320056992192\n",
      "Generation 5640: p = 0.9584800063324658\n",
      "Generation 5640: M(n) = 862.6320056992192\n",
      "Generation 5641: p = 0.9584800063324658\n",
      "Generation 5641: M(n) = 862.6320056992192\n",
      "Generation 5642: p = 0.9584800063324658\n",
      "Generation 5642: M(n) = 862.6320056992192\n",
      "Generation 5643: p = 0.9584800063324658\n",
      "Generation 5643: M(n) = 862.6320056992192\n",
      "Generation 5644: p = 0.9584800063324658\n",
      "Generation 5644: M(n) = 862.6320056992192\n",
      "Generation 5645: p = 0.9584800063324658\n",
      "Generation 5645: M(n) = 862.6320056992192\n",
      "Generation 5646: p = 0.9584800063324658\n",
      "Generation 5646: M(n) = 862.6320056992192\n",
      "Generation 5647: p = 0.9584800063324658\n",
      "Generation 5647: M(n) = 862.6320056992192\n",
      "Generation 5648: p = 0.9584800063324658\n",
      "Generation 5648: M(n) = 862.6320056992192\n",
      "Generation 5649: p = 0.9584800063324658\n",
      "Generation 5649: M(n) = 862.6320056992192\n",
      "Generation 5650: p = 0.9584800063324658\n",
      "Generation 5650: M(n) = 862.6320056992192\n",
      "Generation 5651: p = 0.9584800063324658\n",
      "Generation 5651: M(n) = 862.6320056992192\n",
      "Generation 5652: p = 0.9584800063324658\n",
      "Generation 5652: M(n) = 862.6320056992192\n",
      "Generation 5653: p = 0.9584800063324658\n",
      "Generation 5653: M(n) = 862.6320056992192\n",
      "Generation 5654: p = 0.9584800063324658\n",
      "Generation 5654: M(n) = 862.6320056992192\n",
      "Generation 5655: p = 0.9584800063324658\n",
      "Generation 5655: M(n) = 862.6320056992192\n",
      "Generation 5656: p = 0.9584800063324658\n",
      "Generation 5656: M(n) = 862.6320056992192\n",
      "Generation 5657: p = 0.9584800063324658\n",
      "Generation 5657: M(n) = 862.6320056992192\n",
      "Generation 5658: p = 0.9584800063324658\n",
      "Generation 5658: M(n) = 862.6320056992192\n",
      "Generation 5659: p = 0.9584800063324658\n",
      "Generation 5659: M(n) = 862.6320056992192\n",
      "Generation 5660: p = 0.9584800063324658\n",
      "Generation 5660: M(n) = 862.6320056992192\n",
      "Generation 5661: p = 0.9584800063324658\n",
      "Generation 5661: M(n) = 862.6320056992192\n",
      "Generation 5662: p = 0.9584800063324658\n",
      "Generation 5662: M(n) = 862.6320056992192\n",
      "Generation 5663: p = 0.9584800063324658\n",
      "Generation 5663: M(n) = 862.6320056992192\n",
      "Generation 5664: p = 0.9584800063324658\n",
      "Generation 5664: M(n) = 862.6320056992192\n",
      "Generation 5665: p = 0.9584800063324658\n",
      "Generation 5665: M(n) = 862.6320056992192\n",
      "Generation 5666: p = 0.9584800063324658\n",
      "Generation 5666: M(n) = 862.6320056992192\n",
      "Generation 5667: p = 0.9584800063324658\n",
      "Generation 5667: M(n) = 862.6320056992192\n",
      "Generation 5668: p = 0.9584800063324658\n",
      "Generation 5668: M(n) = 862.6320056992192\n",
      "Generation 5669: p = 0.9584800063324658\n",
      "Generation 5669: M(n) = 862.6320056992192\n",
      "Generation 5670: p = 0.9584800063324658\n",
      "Generation 5670: M(n) = 862.6320056992192\n",
      "Generation 5671: p = 0.9584800063324658\n",
      "Generation 5671: M(n) = 862.6320056992192\n",
      "Generation 5672: p = 0.9584800063324658\n",
      "Generation 5672: M(n) = 862.6320056992192\n",
      "Generation 5673: p = 0.9584800063324658\n",
      "Generation 5673: M(n) = 862.6320056992192\n",
      "Generation 5674: p = 0.9584800063324658\n",
      "Generation 5674: M(n) = 862.6320056992192\n",
      "Generation 5675: p = 0.9584800063324658\n",
      "Generation 5675: M(n) = 862.6320056992192\n",
      "Generation 5676: p = 0.9584800063324658\n",
      "Generation 5676: M(n) = 862.6320056992192\n",
      "Generation 5677: p = 0.9584800063324658\n",
      "Generation 5677: M(n) = 862.6320056992192\n",
      "Generation 5678: p = 0.9584800063324658\n",
      "Generation 5678: M(n) = 862.6320056992192\n",
      "Generation 5679: p = 0.9584800063324658\n",
      "Generation 5679: M(n) = 862.6320056992192\n",
      "Generation 5680: p = 0.9584800063324658\n",
      "Generation 5680: M(n) = 862.6320056992192\n",
      "Generation 5681: p = 0.9584800063324658\n",
      "Generation 5681: M(n) = 862.6320056992192\n",
      "Generation 5682: p = 0.9584800063324658\n",
      "Generation 5682: M(n) = 862.6320056992192\n",
      "Generation 5683: p = 0.9584800063324658\n",
      "Generation 5683: M(n) = 862.6320056992192\n",
      "Generation 5684: p = 0.9584800063324658\n",
      "Generation 5684: M(n) = 862.6320056992192\n",
      "Generation 5685: p = 0.9584800063324658\n",
      "Generation 5685: M(n) = 862.6320056992192\n",
      "Generation 5686: p = 0.9584800063324658\n",
      "Generation 5686: M(n) = 862.6320056992192\n",
      "Generation 5687: p = 0.9584800063324658\n",
      "Generation 5687: M(n) = 862.6320056992192\n",
      "Generation 5688: p = 0.9584800063324658\n",
      "Generation 5688: M(n) = 862.6320056992192\n",
      "Generation 5689: p = 0.9584800063324658\n",
      "Generation 5689: M(n) = 862.6320056992192\n",
      "Generation 5690: p = 0.9584800063324658\n",
      "Generation 5690: M(n) = 862.6320056992192\n",
      "Generation 5691: p = 0.9584800063324658\n",
      "Generation 5691: M(n) = 862.6320056992192\n",
      "Generation 5692: p = 0.9584800063324658\n",
      "Generation 5692: M(n) = 862.6320056992192\n",
      "Generation 5693: p = 0.9584800063324658\n",
      "Generation 5693: M(n) = 862.6320056992192\n",
      "Generation 5694: p = 0.9584800063324658\n",
      "Generation 5694: M(n) = 862.6320056992192\n",
      "Generation 5695: p = 0.9584800063324658\n",
      "Generation 5695: M(n) = 862.6320056992192\n",
      "Generation 5696: p = 0.9584800063324658\n",
      "Generation 5696: M(n) = 862.6320056992192\n",
      "Generation 5697: p = 0.9584800063324658\n",
      "Generation 5697: M(n) = 862.6320056992192\n",
      "Generation 5698: p = 0.9584800063324658\n",
      "Generation 5698: M(n) = 862.6320056992192\n",
      "Generation 5699: p = 0.9584800063324658\n",
      "Generation 5699: M(n) = 862.6320056992192\n",
      "Generation 5700: p = 0.9584800063324658\n",
      "Generation 5700: M(n) = 862.6320056992192\n",
      "Generation 5701: p = 0.9584800063324658\n",
      "Generation 5701: M(n) = 862.6320056992192\n",
      "Generation 5702: p = 0.9584800063324658\n",
      "Generation 5702: M(n) = 862.6320056992192\n",
      "Generation 5703: p = 0.9584800063324658\n",
      "Generation 5703: M(n) = 862.6320056992192\n",
      "Generation 5704: p = 0.9584800063324658\n",
      "Generation 5704: M(n) = 862.6320056992192\n",
      "Generation 5705: p = 0.9584800063324658\n",
      "Generation 5705: M(n) = 862.6320056992192\n",
      "Generation 5706: p = 0.9584800063324658\n",
      "Generation 5706: M(n) = 862.6320056992192\n",
      "Generation 5707: p = 0.9584800063324658\n",
      "Generation 5707: M(n) = 862.6320056992192\n",
      "Generation 5708: p = 0.9584800063324658\n",
      "Generation 5708: M(n) = 862.6320056992192\n",
      "Generation 5709: p = 0.9584800063324658\n",
      "Generation 5709: M(n) = 862.6320056992192\n",
      "Generation 5710: p = 0.9584800063324658\n",
      "Generation 5710: M(n) = 862.6320056992192\n",
      "Generation 5711: p = 0.9584800063324658\n",
      "Generation 5711: M(n) = 862.6320056992192\n",
      "Generation 5712: p = 0.9584800063324658\n",
      "Generation 5712: M(n) = 862.6320056992192\n",
      "Generation 5713: p = 0.9584800063324658\n",
      "Generation 5713: M(n) = 862.6320056992192\n",
      "Generation 5714: p = 0.9584800063324658\n",
      "Generation 5714: M(n) = 862.6320056992192\n",
      "Generation 5715: p = 0.9584800063324658\n",
      "Generation 5715: M(n) = 862.6320056992192\n",
      "Generation 5716: p = 0.9584800063324658\n",
      "Generation 5716: M(n) = 862.6320056992192\n",
      "Generation 5717: p = 0.9584800063324658\n",
      "Generation 5717: M(n) = 862.6320056992192\n",
      "Generation 5718: p = 0.9584800063324658\n",
      "Generation 5718: M(n) = 862.6320056992192\n",
      "Generation 5719: p = 0.9584800063324658\n",
      "Generation 5719: M(n) = 862.6320056992192\n",
      "Generation 5720: p = 0.9584800063324658\n",
      "Generation 5720: M(n) = 862.6320056992192\n",
      "Generation 5721: p = 0.9584800063324658\n",
      "Generation 5721: M(n) = 862.6320056992192\n",
      "Generation 5722: p = 0.9584800063324658\n",
      "Generation 5722: M(n) = 862.6320056992192\n",
      "Generation 5723: p = 0.9584800063324658\n",
      "Generation 5723: M(n) = 862.6320056992192\n",
      "Generation 5724: p = 0.9584800063324658\n",
      "Generation 5724: M(n) = 862.6320056992192\n",
      "Generation 5725: p = 0.9584800063324658\n",
      "Generation 5725: M(n) = 862.6320056992192\n",
      "Generation 5726: p = 0.9584800063324658\n",
      "Generation 5726: M(n) = 862.6320056992192\n",
      "Generation 5727: p = 0.9584800063324658\n",
      "Generation 5727: M(n) = 862.6320056992192\n",
      "Generation 5728: p = 0.9584800063324658\n",
      "Generation 5728: M(n) = 862.6320056992192\n",
      "Generation 5729: p = 0.9584800063324658\n",
      "Generation 5729: M(n) = 862.6320056992192\n",
      "Generation 5730: p = 0.9584800063324658\n",
      "Generation 5730: M(n) = 862.6320056992192\n",
      "Generation 5731: p = 0.9584800063324658\n",
      "Generation 5731: M(n) = 862.6320056992192\n",
      "Generation 5732: p = 0.9584800063324658\n",
      "Generation 5732: M(n) = 862.6320056992192\n",
      "Generation 5733: p = 0.9584800063324658\n",
      "Generation 5733: M(n) = 862.6320056992192\n",
      "Generation 5734: p = 0.9584800063324658\n",
      "Generation 5734: M(n) = 862.6320056992192\n",
      "Generation 5735: p = 0.9584800063324658\n",
      "Generation 5735: M(n) = 862.6320056992192\n",
      "Generation 5736: p = 0.9584800063324658\n",
      "Generation 5736: M(n) = 862.6320056992192\n",
      "Generation 5737: p = 0.9584800063324658\n",
      "Generation 5737: M(n) = 862.6320056992192\n",
      "Generation 5738: p = 0.9584800063324658\n",
      "Generation 5738: M(n) = 862.6320056992192\n",
      "Generation 5739: p = 0.9584800063324658\n",
      "Generation 5739: M(n) = 862.6320056992192\n",
      "Generation 5740: p = 0.9584800063324658\n",
      "Generation 5740: M(n) = 862.6320056992192\n",
      "Generation 5741: p = 0.9584800063324658\n",
      "Generation 5741: M(n) = 862.6320056992192\n",
      "Generation 5742: p = 0.9584800063324658\n",
      "Generation 5742: M(n) = 862.6320056992192\n",
      "Generation 5743: p = 0.9584800063324658\n",
      "Generation 5743: M(n) = 862.6320056992192\n",
      "Generation 5744: p = 0.9584800063324658\n",
      "Generation 5744: M(n) = 862.6320056992192\n",
      "Generation 5745: p = 0.9584800063324658\n",
      "Generation 5745: M(n) = 862.6320056992192\n",
      "Generation 5746: p = 0.9584800063324658\n",
      "Generation 5746: M(n) = 862.6320056992192\n",
      "Generation 5747: p = 0.9584800063324658\n",
      "Generation 5747: M(n) = 862.6320056992192\n",
      "Generation 5748: p = 0.9584800063324658\n",
      "Generation 5748: M(n) = 862.6320056992192\n",
      "Generation 5749: p = 0.9584800063324658\n",
      "Generation 5749: M(n) = 862.6320056992192\n",
      "Generation 5750: p = 0.9584800063324658\n",
      "Generation 5750: M(n) = 862.6320056992192\n",
      "Generation 5751: p = 0.9584800063324658\n",
      "Generation 5751: M(n) = 862.6320056992192\n",
      "Generation 5752: p = 0.9584800063324658\n",
      "Generation 5752: M(n) = 862.6320056992192\n",
      "Generation 5753: p = 0.9584800063324658\n",
      "Generation 5753: M(n) = 862.6320056992192\n",
      "Generation 5754: p = 0.9584800063324658\n",
      "Generation 5754: M(n) = 862.6320056992192\n",
      "Generation 5755: p = 0.9584800063324658\n",
      "Generation 5755: M(n) = 862.6320056992192\n",
      "Generation 5756: p = 0.9584800063324658\n",
      "Generation 5756: M(n) = 862.6320056992192\n",
      "Generation 5757: p = 0.9584800063324658\n",
      "Generation 5757: M(n) = 862.6320056992192\n",
      "Generation 5758: p = 0.9584800063324658\n",
      "Generation 5758: M(n) = 862.6320056992192\n",
      "Generation 5759: p = 0.9584800063324658\n",
      "Generation 5759: M(n) = 862.6320056992192\n",
      "Generation 5760: p = 0.9584800063324658\n",
      "Generation 5760: M(n) = 862.6320056992192\n",
      "Generation 5761: p = 0.9584800063324658\n",
      "Generation 5761: M(n) = 862.6320056992192\n",
      "Generation 5762: p = 0.9584800063324658\n",
      "Generation 5762: M(n) = 862.6320056992192\n",
      "Generation 5763: p = 0.9584800063324658\n",
      "Generation 5763: M(n) = 862.6320056992192\n",
      "Generation 5764: p = 0.9584800063324658\n",
      "Generation 5764: M(n) = 862.6320056992192\n",
      "Generation 5765: p = 0.9584800063324658\n",
      "Generation 5765: M(n) = 862.6320056992192\n",
      "Generation 5766: p = 0.9584800063324658\n",
      "Generation 5766: M(n) = 862.6320056992192\n",
      "Generation 5767: p = 0.9584800063324658\n",
      "Generation 5767: M(n) = 862.6320056992192\n",
      "Generation 5768: p = 0.9584800063324658\n",
      "Generation 5768: M(n) = 862.6320056992192\n",
      "Generation 5769: p = 0.9584800063324658\n",
      "Generation 5769: M(n) = 862.6320056992192\n",
      "Generation 5770: p = 0.9584800063324658\n",
      "Generation 5770: M(n) = 862.6320056992192\n",
      "Generation 5771: p = 0.9584800063324658\n",
      "Generation 5771: M(n) = 862.6320056992192\n",
      "Generation 5772: p = 0.9584800063324658\n",
      "Generation 5772: M(n) = 862.6320056992192\n",
      "Generation 5773: p = 0.9584800063324658\n",
      "Generation 5773: M(n) = 862.6320056992192\n",
      "Generation 5774: p = 0.9584800063324658\n",
      "Generation 5774: M(n) = 862.6320056992192\n",
      "Generation 5775: p = 0.9584800063324658\n",
      "Generation 5775: M(n) = 862.6320056992192\n",
      "Generation 5776: p = 0.9584800063324658\n",
      "Generation 5776: M(n) = 862.6320056992192\n",
      "Generation 5777: p = 0.9584800063324658\n",
      "Generation 5777: M(n) = 862.6320056992192\n",
      "Generation 5778: p = 0.9584800063324658\n",
      "Generation 5778: M(n) = 862.6320056992192\n",
      "Generation 5779: p = 0.9584800063324658\n",
      "Generation 5779: M(n) = 862.6320056992192\n",
      "Generation 5780: p = 0.9584800063324658\n",
      "Generation 5780: M(n) = 862.6320056992192\n",
      "Generation 5781: p = 0.9584800063324658\n",
      "Generation 5781: M(n) = 862.6320056992192\n",
      "Generation 5782: p = 0.9584800063324658\n",
      "Generation 5782: M(n) = 862.6320056992192\n",
      "Generation 5783: p = 0.9584800063324658\n",
      "Generation 5783: M(n) = 862.6320056992192\n",
      "Generation 5784: p = 0.9584800063324658\n",
      "Generation 5784: M(n) = 862.6320056992192\n",
      "Generation 5785: p = 0.9584800063324658\n",
      "Generation 5785: M(n) = 862.6320056992192\n",
      "Generation 5786: p = 0.9584800063324658\n",
      "Generation 5786: M(n) = 862.6320056992192\n",
      "Generation 5787: p = 0.9584800063324658\n",
      "Generation 5787: M(n) = 862.6320056992192\n",
      "Generation 5788: p = 0.9584800063324658\n",
      "Generation 5788: M(n) = 862.6320056992192\n",
      "Generation 5789: p = 0.9584800063324658\n",
      "Generation 5789: M(n) = 862.6320056992192\n",
      "Generation 5790: p = 0.9584800063324658\n",
      "Generation 5790: M(n) = 862.6320056992192\n",
      "Generation 5791: p = 0.9584800063324658\n",
      "Generation 5791: M(n) = 862.6320056992192\n",
      "Generation 5792: p = 0.9584800063324658\n",
      "Generation 5792: M(n) = 862.6320056992192\n",
      "Generation 5793: p = 0.9584800063324658\n",
      "Generation 5793: M(n) = 862.6320056992192\n",
      "Generation 5794: p = 0.9584800063324658\n",
      "Generation 5794: M(n) = 862.6320056992192\n",
      "Generation 5795: p = 0.9584800063324658\n",
      "Generation 5795: M(n) = 862.6320056992192\n",
      "Generation 5796: p = 0.9584800063324658\n",
      "Generation 5796: M(n) = 862.6320056992192\n",
      "Generation 5797: p = 0.9584800063324658\n",
      "Generation 5797: M(n) = 862.6320056992192\n",
      "Generation 5798: p = 0.9584800063324658\n",
      "Generation 5798: M(n) = 862.6320056992192\n",
      "Generation 5799: p = 0.9584800063324658\n",
      "Generation 5799: M(n) = 862.6320056992192\n",
      "Generation 5800: p = 0.9584800063324658\n",
      "Generation 5800: M(n) = 862.6320056992192\n",
      "Generation 5801: p = 0.9584800063324658\n",
      "Generation 5801: M(n) = 862.6320056992192\n",
      "Generation 5802: p = 0.9584800063324658\n",
      "Generation 5802: M(n) = 862.6320056992192\n",
      "Generation 5803: p = 0.9584800063324658\n",
      "Generation 5803: M(n) = 862.6320056992192\n",
      "Generation 5804: p = 0.9584800063324658\n",
      "Generation 5804: M(n) = 862.6320056992192\n",
      "Generation 5805: p = 0.9584800063324658\n",
      "Generation 5805: M(n) = 862.6320056992192\n",
      "Generation 5806: p = 0.9584800063324658\n",
      "Generation 5806: M(n) = 862.6320056992192\n",
      "Generation 5807: p = 0.9584800063324658\n",
      "Generation 5807: M(n) = 862.6320056992192\n",
      "Generation 5808: p = 0.9584800063324658\n",
      "Generation 5808: M(n) = 862.6320056992192\n",
      "Generation 5809: p = 0.9584800063324658\n",
      "Generation 5809: M(n) = 862.6320056992192\n",
      "Generation 5810: p = 0.9584800063324658\n",
      "Generation 5810: M(n) = 862.6320056992192\n",
      "Generation 5811: p = 0.9584800063324658\n",
      "Generation 5811: M(n) = 862.6320056992192\n",
      "Generation 5812: p = 0.9584800063324658\n",
      "Generation 5812: M(n) = 862.6320056992192\n",
      "Generation 5813: p = 0.9584800063324658\n",
      "Generation 5813: M(n) = 862.6320056992192\n",
      "Generation 5814: p = 0.9584800063324658\n",
      "Generation 5814: M(n) = 862.6320056992192\n",
      "Generation 5815: p = 0.9584800063324658\n",
      "Generation 5815: M(n) = 862.6320056992192\n",
      "Generation 5816: p = 0.9584800063324658\n",
      "Generation 5816: M(n) = 862.6320056992192\n",
      "Generation 5817: p = 0.9584800063324658\n",
      "Generation 5817: M(n) = 862.6320056992192\n",
      "Generation 5818: p = 0.9584800063324658\n",
      "Generation 5818: M(n) = 862.6320056992192\n",
      "Generation 5819: p = 0.9584800063324658\n",
      "Generation 5819: M(n) = 862.6320056992192\n",
      "Generation 5820: p = 0.9584800063324658\n",
      "Generation 5820: M(n) = 862.6320056992192\n",
      "Generation 5821: p = 0.9584800063324658\n",
      "Generation 5821: M(n) = 862.6320056992192\n",
      "Generation 5822: p = 0.9584800063324658\n",
      "Generation 5822: M(n) = 862.6320056992192\n",
      "Generation 5823: p = 0.9584800063324658\n",
      "Generation 5823: M(n) = 862.6320056992192\n",
      "Generation 5824: p = 0.9584800063324658\n",
      "Generation 5824: M(n) = 862.6320056992192\n",
      "Generation 5825: p = 0.9584800063324658\n",
      "Generation 5825: M(n) = 862.6320056992192\n",
      "Generation 5826: p = 0.9584800063324658\n",
      "Generation 5826: M(n) = 862.6320056992192\n",
      "Generation 5827: p = 0.9584800063324658\n",
      "Generation 5827: M(n) = 862.6320056992192\n",
      "Generation 5828: p = 0.9584800063324658\n",
      "Generation 5828: M(n) = 862.6320056992192\n",
      "Generation 5829: p = 0.9584800063324658\n",
      "Generation 5829: M(n) = 862.6320056992192\n",
      "Generation 5830: p = 0.9584800063324658\n",
      "Generation 5830: M(n) = 862.6320056992192\n",
      "Generation 5831: p = 0.9584800063324658\n",
      "Generation 5831: M(n) = 862.6320056992192\n",
      "Generation 5832: p = 0.9584800063324658\n",
      "Generation 5832: M(n) = 862.6320056992192\n",
      "Generation 5833: p = 0.9584800063324658\n",
      "Generation 5833: M(n) = 862.6320056992192\n",
      "Generation 5834: p = 0.9584800063324658\n",
      "Generation 5834: M(n) = 862.6320056992192\n",
      "Generation 5835: p = 0.9584800063324658\n",
      "Generation 5835: M(n) = 862.6320056992192\n",
      "Generation 5836: p = 0.9584800063324658\n",
      "Generation 5836: M(n) = 862.6320056992192\n",
      "Generation 5837: p = 0.9584800063324658\n",
      "Generation 5837: M(n) = 862.6320056992192\n",
      "Generation 5838: p = 0.9584800063324658\n",
      "Generation 5838: M(n) = 862.6320056992192\n",
      "Generation 5839: p = 0.9584800063324658\n",
      "Generation 5839: M(n) = 862.6320056992192\n",
      "Generation 5840: p = 0.9584800063324658\n",
      "Generation 5840: M(n) = 862.6320056992192\n",
      "Generation 5841: p = 0.9584800063324658\n",
      "Generation 5841: M(n) = 862.6320056992192\n",
      "Generation 5842: p = 0.9584800063324658\n",
      "Generation 5842: M(n) = 862.6320056992192\n",
      "Generation 5843: p = 0.9584800063324658\n",
      "Generation 5843: M(n) = 862.6320056992192\n",
      "Generation 5844: p = 0.9584800063324658\n",
      "Generation 5844: M(n) = 862.6320056992192\n",
      "Generation 5845: p = 0.9584800063324658\n",
      "Generation 5845: M(n) = 862.6320056992192\n",
      "Generation 5846: p = 0.9584800063324658\n",
      "Generation 5846: M(n) = 862.6320056992192\n",
      "Generation 5847: p = 0.9584800063324658\n",
      "Generation 5847: M(n) = 862.6320056992192\n",
      "Generation 5848: p = 0.9584800063324658\n",
      "Generation 5848: M(n) = 862.6320056992192\n",
      "Generation 5849: p = 0.9584800063324658\n",
      "Generation 5849: M(n) = 862.6320056992192\n",
      "Generation 5850: p = 0.9584800063324658\n",
      "Generation 5850: M(n) = 862.6320056992192\n",
      "Generation 5851: p = 0.9584800063324658\n",
      "Generation 5851: M(n) = 862.6320056992192\n",
      "Generation 5852: p = 0.9584800063324658\n",
      "Generation 5852: M(n) = 862.6320056992192\n",
      "Generation 5853: p = 0.9584800063324658\n",
      "Generation 5853: M(n) = 862.6320056992192\n",
      "Generation 5854: p = 0.9584800063324658\n",
      "Generation 5854: M(n) = 862.6320056992192\n",
      "Generation 5855: p = 0.9584800063324658\n",
      "Generation 5855: M(n) = 862.6320056992192\n",
      "Generation 5856: p = 0.9584800063324658\n",
      "Generation 5856: M(n) = 862.6320056992192\n",
      "Generation 5857: p = 0.9584800063324658\n",
      "Generation 5857: M(n) = 862.6320056992192\n",
      "Generation 5858: p = 0.9584800063324658\n",
      "Generation 5858: M(n) = 862.6320056992192\n",
      "Generation 5859: p = 0.9584800063324658\n",
      "Generation 5859: M(n) = 862.6320056992192\n",
      "Generation 5860: p = 0.9584800063324658\n",
      "Generation 5860: M(n) = 862.6320056992192\n",
      "Generation 5861: p = 0.9584800063324658\n",
      "Generation 5861: M(n) = 862.6320056992192\n",
      "Generation 5862: p = 0.9584800063324658\n",
      "Generation 5862: M(n) = 862.6320056992192\n",
      "Generation 5863: p = 0.9584800063324658\n",
      "Generation 5863: M(n) = 862.6320056992192\n",
      "Generation 5864: p = 0.9584800063324658\n",
      "Generation 5864: M(n) = 862.6320056992192\n",
      "Generation 5865: p = 0.9584800063324658\n",
      "Generation 5865: M(n) = 862.6320056992192\n",
      "Generation 5866: p = 0.9584800063324658\n",
      "Generation 5866: M(n) = 862.6320056992192\n",
      "Generation 5867: p = 0.9584800063324658\n",
      "Generation 5867: M(n) = 862.6320056992192\n",
      "Generation 5868: p = 0.9584800063324658\n",
      "Generation 5868: M(n) = 862.6320056992192\n",
      "Generation 5869: p = 0.9584800063324658\n",
      "Generation 5869: M(n) = 862.6320056992192\n",
      "Generation 5870: p = 0.9584800063324658\n",
      "Generation 5870: M(n) = 862.6320056992192\n",
      "Generation 5871: p = 0.9584800063324658\n",
      "Generation 5871: M(n) = 862.6320056992192\n",
      "Generation 5872: p = 0.9584800063324658\n",
      "Generation 5872: M(n) = 862.6320056992192\n",
      "Generation 5873: p = 0.9584800063324658\n",
      "Generation 5873: M(n) = 862.6320056992192\n",
      "Generation 5874: p = 0.9584800063324658\n",
      "Generation 5874: M(n) = 862.6320056992192\n",
      "Generation 5875: p = 0.9584800063324658\n",
      "Generation 5875: M(n) = 862.6320056992192\n",
      "Generation 5876: p = 0.9584800063324658\n",
      "Generation 5876: M(n) = 862.6320056992192\n",
      "Generation 5877: p = 0.9584800063324658\n",
      "Generation 5877: M(n) = 862.6320056992192\n",
      "Generation 5878: p = 0.9584800063324658\n",
      "Generation 5878: M(n) = 862.6320056992192\n",
      "Generation 5879: p = 0.9584800063324658\n",
      "Generation 5879: M(n) = 862.6320056992192\n",
      "Generation 5880: p = 0.9584800063324658\n",
      "Generation 5880: M(n) = 862.6320056992192\n",
      "Generation 5881: p = 0.9584800063324658\n",
      "Generation 5881: M(n) = 862.6320056992192\n",
      "Generation 5882: p = 0.9584800063324658\n",
      "Generation 5882: M(n) = 862.6320056992192\n",
      "Generation 5883: p = 0.9584800063324658\n",
      "Generation 5883: M(n) = 862.6320056992192\n",
      "Generation 5884: p = 0.9584800063324658\n",
      "Generation 5884: M(n) = 862.6320056992192\n",
      "Generation 5885: p = 0.9584800063324658\n",
      "Generation 5885: M(n) = 862.6320056992192\n",
      "Generation 5886: p = 0.9584800063324658\n",
      "Generation 5886: M(n) = 862.6320056992192\n",
      "Generation 5887: p = 0.9584800063324658\n",
      "Generation 5887: M(n) = 862.6320056992192\n",
      "Generation 5888: p = 0.9584800063324658\n",
      "Generation 5888: M(n) = 862.6320056992192\n",
      "Generation 5889: p = 0.9584800063324658\n",
      "Generation 5889: M(n) = 862.6320056992192\n",
      "Generation 5890: p = 0.9584800063324658\n",
      "Generation 5890: M(n) = 862.6320056992192\n",
      "Generation 5891: p = 0.9584800063324658\n",
      "Generation 5891: M(n) = 862.6320056992192\n",
      "Generation 5892: p = 0.9584800063324658\n",
      "Generation 5892: M(n) = 862.6320056992192\n",
      "Generation 5893: p = 0.9584800063324658\n",
      "Generation 5893: M(n) = 862.6320056992192\n",
      "Generation 5894: p = 0.9584800063324658\n",
      "Generation 5894: M(n) = 862.6320056992192\n",
      "Generation 5895: p = 0.9584800063324658\n",
      "Generation 5895: M(n) = 862.6320056992192\n",
      "Generation 5896: p = 0.9584800063324658\n",
      "Generation 5896: M(n) = 862.6320056992192\n",
      "Generation 5897: p = 0.9584800063324658\n",
      "Generation 5897: M(n) = 862.6320056992192\n",
      "Generation 5898: p = 0.9584800063324658\n",
      "Generation 5898: M(n) = 862.6320056992192\n",
      "Generation 5899: p = 0.9584800063324658\n",
      "Generation 5899: M(n) = 862.6320056992192\n",
      "Generation 5900: p = 0.9584800063324658\n",
      "Generation 5900: M(n) = 862.6320056992192\n",
      "Generation 5901: p = 0.9584800063324658\n",
      "Generation 5901: M(n) = 862.6320056992192\n",
      "Generation 5902: p = 0.9584800063324658\n",
      "Generation 5902: M(n) = 862.6320056992192\n",
      "Generation 5903: p = 0.9584800063324658\n",
      "Generation 5903: M(n) = 862.6320056992192\n",
      "Generation 5904: p = 0.9584800063324658\n",
      "Generation 5904: M(n) = 862.6320056992192\n",
      "Generation 5905: p = 0.9584800063324658\n",
      "Generation 5905: M(n) = 862.6320056992192\n",
      "Generation 5906: p = 0.9584800063324658\n",
      "Generation 5906: M(n) = 862.6320056992192\n",
      "Generation 5907: p = 0.9584800063324658\n",
      "Generation 5907: M(n) = 862.6320056992192\n",
      "Generation 5908: p = 0.9584800063324658\n",
      "Generation 5908: M(n) = 862.6320056992192\n",
      "Generation 5909: p = 0.9584800063324658\n",
      "Generation 5909: M(n) = 862.6320056992192\n",
      "Generation 5910: p = 0.9584800063324658\n",
      "Generation 5910: M(n) = 862.6320056992192\n",
      "Generation 5911: p = 0.9584800063324658\n",
      "Generation 5911: M(n) = 862.6320056992192\n",
      "Generation 5912: p = 0.9584800063324658\n",
      "Generation 5912: M(n) = 862.6320056992192\n",
      "Generation 5913: p = 0.9584800063324658\n",
      "Generation 5913: M(n) = 862.6320056992192\n",
      "Generation 5914: p = 0.9584800063324658\n",
      "Generation 5914: M(n) = 862.6320056992192\n",
      "Generation 5915: p = 0.9584800063324658\n",
      "Generation 5915: M(n) = 862.6320056992192\n",
      "Generation 5916: p = 0.9584800063324658\n",
      "Generation 5916: M(n) = 862.6320056992192\n",
      "Generation 5917: p = 0.9584800063324658\n",
      "Generation 5917: M(n) = 862.6320056992192\n",
      "Generation 5918: p = 0.9584800063324658\n",
      "Generation 5918: M(n) = 862.6320056992192\n",
      "Generation 5919: p = 0.9584800063324658\n",
      "Generation 5919: M(n) = 862.6320056992192\n",
      "Generation 5920: p = 0.9584800063324658\n",
      "Generation 5920: M(n) = 862.6320056992192\n",
      "Generation 5921: p = 0.9584800063324658\n",
      "Generation 5921: M(n) = 862.6320056992192\n",
      "Generation 5922: p = 0.9584800063324658\n",
      "Generation 5922: M(n) = 862.6320056992192\n",
      "Generation 5923: p = 0.9584800063324658\n",
      "Generation 5923: M(n) = 862.6320056992192\n",
      "Generation 5924: p = 0.9584800063324658\n",
      "Generation 5924: M(n) = 862.6320056992192\n",
      "Generation 5925: p = 0.9584800063324658\n",
      "Generation 5925: M(n) = 862.6320056992192\n",
      "Generation 5926: p = 0.9584800063324658\n",
      "Generation 5926: M(n) = 862.6320056992192\n",
      "Generation 5927: p = 0.9584800063324658\n",
      "Generation 5927: M(n) = 862.6320056992192\n",
      "Generation 5928: p = 0.9584800063324658\n",
      "Generation 5928: M(n) = 862.6320056992192\n",
      "Generation 5929: p = 0.9584800063324658\n",
      "Generation 5929: M(n) = 862.6320056992192\n",
      "Generation 5930: p = 0.9584800063324658\n",
      "Generation 5930: M(n) = 862.6320056992192\n",
      "Generation 5931: p = 0.9584800063324658\n",
      "Generation 5931: M(n) = 862.6320056992192\n",
      "Generation 5932: p = 0.9584800063324658\n",
      "Generation 5932: M(n) = 862.6320056992192\n",
      "Generation 5933: p = 0.9584800063324658\n",
      "Generation 5933: M(n) = 862.6320056992192\n",
      "Generation 5934: p = 0.9584800063324658\n",
      "Generation 5934: M(n) = 862.6320056992192\n",
      "Generation 5935: p = 0.9584800063324658\n",
      "Generation 5935: M(n) = 862.6320056992192\n",
      "Generation 5936: p = 0.9584800063324658\n",
      "Generation 5936: M(n) = 862.6320056992192\n",
      "Generation 5937: p = 0.9584800063324658\n",
      "Generation 5937: M(n) = 862.6320056992192\n",
      "Generation 5938: p = 0.9584800063324658\n",
      "Generation 5938: M(n) = 862.6320056992192\n",
      "Generation 5939: p = 0.9584800063324658\n",
      "Generation 5939: M(n) = 862.6320056992192\n",
      "Generation 5940: p = 0.9584800063324658\n",
      "Generation 5940: M(n) = 862.6320056992192\n",
      "Generation 5941: p = 0.9584800063324658\n",
      "Generation 5941: M(n) = 862.6320056992192\n",
      "Generation 5942: p = 0.9584800063324658\n",
      "Generation 5942: M(n) = 862.6320056992192\n",
      "Generation 5943: p = 0.9584800063324658\n",
      "Generation 5943: M(n) = 862.6320056992192\n",
      "Generation 5944: p = 0.9584800063324658\n",
      "Generation 5944: M(n) = 862.6320056992192\n",
      "Generation 5945: p = 0.9584800063324658\n",
      "Generation 5945: M(n) = 862.6320056992192\n",
      "Generation 5946: p = 0.9584800063324658\n",
      "Generation 5946: M(n) = 862.6320056992192\n",
      "Generation 5947: p = 0.9584800063324658\n",
      "Generation 5947: M(n) = 862.6320056992192\n",
      "Generation 5948: p = 0.9584800063324658\n",
      "Generation 5948: M(n) = 862.6320056992192\n",
      "Generation 5949: p = 0.9584800063324658\n",
      "Generation 5949: M(n) = 862.6320056992192\n",
      "Generation 5950: p = 0.9584800063324658\n",
      "Generation 5950: M(n) = 862.6320056992192\n",
      "Generation 5951: p = 0.9584800063324658\n",
      "Generation 5951: M(n) = 862.6320056992192\n",
      "Generation 5952: p = 0.9584800063324658\n",
      "Generation 5952: M(n) = 862.6320056992192\n",
      "Generation 5953: p = 0.9584800063324658\n",
      "Generation 5953: M(n) = 862.6320056992192\n",
      "Generation 5954: p = 0.9584800063324658\n",
      "Generation 5954: M(n) = 862.6320056992192\n",
      "Generation 5955: p = 0.9584800063324658\n",
      "Generation 5955: M(n) = 862.6320056992192\n",
      "Generation 5956: p = 0.9584800063324658\n",
      "Generation 5956: M(n) = 862.6320056992192\n",
      "Generation 5957: p = 0.9584800063324658\n",
      "Generation 5957: M(n) = 862.6320056992192\n",
      "Generation 5958: p = 0.9584800063324658\n",
      "Generation 5958: M(n) = 862.6320056992192\n",
      "Generation 5959: p = 0.9584800063324658\n",
      "Generation 5959: M(n) = 862.6320056992192\n",
      "Generation 5960: p = 0.9584800063324658\n",
      "Generation 5960: M(n) = 862.6320056992192\n",
      "Generation 5961: p = 0.9584800063324658\n",
      "Generation 5961: M(n) = 862.6320056992192\n",
      "Generation 5962: p = 0.9584800063324658\n",
      "Generation 5962: M(n) = 862.6320056992192\n",
      "Generation 5963: p = 0.9584800063324658\n",
      "Generation 5963: M(n) = 862.6320056992192\n",
      "Generation 5964: p = 0.9584800063324658\n",
      "Generation 5964: M(n) = 862.6320056992192\n",
      "Generation 5965: p = 0.9584800063324658\n",
      "Generation 5965: M(n) = 862.6320056992192\n",
      "Generation 5966: p = 0.9584800063324658\n",
      "Generation 5966: M(n) = 862.6320056992192\n",
      "Generation 5967: p = 0.9584800063324658\n",
      "Generation 5967: M(n) = 862.6320056992192\n",
      "Generation 5968: p = 0.9584800063324658\n",
      "Generation 5968: M(n) = 862.6320056992192\n",
      "Generation 5969: p = 0.9584800063324658\n",
      "Generation 5969: M(n) = 862.6320056992192\n",
      "Generation 5970: p = 0.9584800063324658\n",
      "Generation 5970: M(n) = 862.6320056992192\n",
      "Generation 5971: p = 0.9584800063324658\n",
      "Generation 5971: M(n) = 862.6320056992192\n",
      "Generation 5972: p = 0.9584800063324658\n",
      "Generation 5972: M(n) = 862.6320056992192\n",
      "Generation 5973: p = 0.9584800063324658\n",
      "Generation 5973: M(n) = 862.6320056992192\n",
      "Generation 5974: p = 0.9584800063324658\n",
      "Generation 5974: M(n) = 862.6320056992192\n",
      "Generation 5975: p = 0.9584800063324658\n",
      "Generation 5975: M(n) = 862.6320056992192\n",
      "Generation 5976: p = 0.9584800063324658\n",
      "Generation 5976: M(n) = 862.6320056992192\n",
      "Generation 5977: p = 0.9584800063324658\n",
      "Generation 5977: M(n) = 862.6320056992192\n",
      "Generation 5978: p = 0.9584800063324658\n",
      "Generation 5978: M(n) = 862.6320056992192\n",
      "Generation 5979: p = 0.9584800063324658\n",
      "Generation 5979: M(n) = 862.6320056992192\n",
      "Generation 5980: p = 0.9584800063324658\n",
      "Generation 5980: M(n) = 862.6320056992192\n",
      "Generation 5981: p = 0.9584800063324658\n",
      "Generation 5981: M(n) = 862.6320056992192\n",
      "Generation 5982: p = 0.9584800063324658\n",
      "Generation 5982: M(n) = 862.6320056992192\n",
      "Generation 5983: p = 0.9584800063324658\n",
      "Generation 5983: M(n) = 862.6320056992192\n",
      "Generation 5984: p = 0.9584800063324658\n",
      "Generation 5984: M(n) = 862.6320056992192\n",
      "Generation 5985: p = 0.9584800063324658\n",
      "Generation 5985: M(n) = 862.6320056992192\n",
      "Generation 5986: p = 0.9584800063324658\n",
      "Generation 5986: M(n) = 862.6320056992192\n",
      "Generation 5987: p = 0.9584800063324658\n",
      "Generation 5987: M(n) = 862.6320056992192\n",
      "Generation 5988: p = 0.9584800063324658\n",
      "Generation 5988: M(n) = 862.6320056992192\n",
      "Generation 5989: p = 0.9584800063324658\n",
      "Generation 5989: M(n) = 862.6320056992192\n",
      "Generation 5990: p = 0.9584800063324658\n",
      "Generation 5990: M(n) = 862.6320056992192\n",
      "Generation 5991: p = 0.9584800063324658\n",
      "Generation 5991: M(n) = 862.6320056992192\n",
      "Generation 5992: p = 0.9584800063324658\n",
      "Generation 5992: M(n) = 862.6320056992192\n",
      "Generation 5993: p = 0.9584800063324658\n",
      "Generation 5993: M(n) = 862.6320056992192\n",
      "Generation 5994: p = 0.9584800063324658\n",
      "Generation 5994: M(n) = 862.6320056992192\n",
      "Generation 5995: p = 0.9584800063324658\n",
      "Generation 5995: M(n) = 862.6320056992192\n",
      "Generation 5996: p = 0.9584800063324658\n",
      "Generation 5996: M(n) = 862.6320056992192\n",
      "Generation 5997: p = 0.9584800063324658\n",
      "Generation 5997: M(n) = 862.6320056992192\n",
      "Generation 5998: p = 0.9584800063324658\n",
      "Generation 5998: M(n) = 862.6320056992192\n",
      "Generation 5999: p = 0.9584800063324658\n",
      "Generation 5999: M(n) = 862.6320056992192\n",
      "Generation 6000: p = 0.9584800063324658\n",
      "Generation 6000: M(n) = 862.6320056992192\n",
      "Generation 6001: p = 0.9584800063324658\n",
      "Generation 6001: M(n) = 862.6320056992192\n",
      "Generation 6002: p = 0.9584800063324658\n",
      "Generation 6002: M(n) = 862.6320056992192\n",
      "Generation 6003: p = 0.9584800063324658\n",
      "Generation 6003: M(n) = 862.6320056992192\n",
      "Generation 6004: p = 0.9584800063324658\n",
      "Generation 6004: M(n) = 862.6320056992192\n",
      "Generation 6005: p = 0.9584800063324658\n",
      "Generation 6005: M(n) = 862.6320056992192\n",
      "Generation 6006: p = 0.9584800063324658\n",
      "Generation 6006: M(n) = 862.6320056992192\n",
      "Generation 6007: p = 0.9584800063324658\n",
      "Generation 6007: M(n) = 862.6320056992192\n",
      "Generation 6008: p = 0.9584800063324658\n",
      "Generation 6008: M(n) = 862.6320056992192\n",
      "Generation 6009: p = 0.9584800063324658\n",
      "Generation 6009: M(n) = 862.6320056992192\n",
      "Generation 6010: p = 0.9584800063324658\n",
      "Generation 6010: M(n) = 862.6320056992192\n",
      "Generation 6011: p = 0.9584800063324658\n",
      "Generation 6011: M(n) = 862.6320056992192\n",
      "Generation 6012: p = 0.9584800063324658\n",
      "Generation 6012: M(n) = 862.6320056992192\n",
      "Generation 6013: p = 0.9584800063324658\n",
      "Generation 6013: M(n) = 862.6320056992192\n",
      "Generation 6014: p = 0.9584800063324658\n",
      "Generation 6014: M(n) = 862.6320056992192\n",
      "Generation 6015: p = 0.9584800063324658\n",
      "Generation 6015: M(n) = 862.6320056992192\n",
      "Generation 6016: p = 0.9584800063324658\n",
      "Generation 6016: M(n) = 862.6320056992192\n",
      "Generation 6017: p = 0.9584800063324658\n",
      "Generation 6017: M(n) = 862.6320056992192\n",
      "Generation 6018: p = 0.9584800063324658\n",
      "Generation 6018: M(n) = 862.6320056992192\n",
      "Generation 6019: p = 0.9584800063324658\n",
      "Generation 6019: M(n) = 862.6320056992192\n",
      "Generation 6020: p = 0.9584800063324658\n",
      "Generation 6020: M(n) = 862.6320056992192\n",
      "Generation 6021: p = 0.9584800063324658\n",
      "Generation 6021: M(n) = 862.6320056992192\n",
      "Generation 6022: p = 0.9584800063324658\n",
      "Generation 6022: M(n) = 862.6320056992192\n",
      "Generation 6023: p = 0.9584800063324658\n",
      "Generation 6023: M(n) = 862.6320056992192\n",
      "Generation 6024: p = 0.9584800063324658\n",
      "Generation 6024: M(n) = 862.6320056992192\n",
      "Generation 6025: p = 0.9584800063324658\n",
      "Generation 6025: M(n) = 862.6320056992192\n",
      "Generation 6026: p = 0.9584800063324658\n",
      "Generation 6026: M(n) = 862.6320056992192\n",
      "Generation 6027: p = 0.9584800063324658\n",
      "Generation 6027: M(n) = 862.6320056992192\n",
      "Generation 6028: p = 0.9584800063324658\n",
      "Generation 6028: M(n) = 862.6320056992192\n",
      "Generation 6029: p = 0.9584800063324658\n",
      "Generation 6029: M(n) = 862.6320056992192\n",
      "Generation 6030: p = 0.9584800063324658\n",
      "Generation 6030: M(n) = 862.6320056992192\n",
      "Generation 6031: p = 0.9584800063324658\n",
      "Generation 6031: M(n) = 862.6320056992192\n",
      "Generation 6032: p = 0.9584800063324658\n",
      "Generation 6032: M(n) = 862.6320056992192\n",
      "Generation 6033: p = 0.9584800063324658\n",
      "Generation 6033: M(n) = 862.6320056992192\n",
      "Generation 6034: p = 0.9584800063324658\n",
      "Generation 6034: M(n) = 862.6320056992192\n",
      "Generation 6035: p = 0.9584800063324658\n",
      "Generation 6035: M(n) = 862.6320056992192\n",
      "Generation 6036: p = 0.9584800063324658\n",
      "Generation 6036: M(n) = 862.6320056992192\n",
      "Generation 6037: p = 0.9584800063324658\n",
      "Generation 6037: M(n) = 862.6320056992192\n",
      "Generation 6038: p = 0.9584800063324658\n",
      "Generation 6038: M(n) = 862.6320056992192\n",
      "Generation 6039: p = 0.9584800063324658\n",
      "Generation 6039: M(n) = 862.6320056992192\n",
      "Generation 6040: p = 0.9584800063324658\n",
      "Generation 6040: M(n) = 862.6320056992192\n",
      "Generation 6041: p = 0.9584800063324658\n",
      "Generation 6041: M(n) = 862.6320056992192\n",
      "Generation 6042: p = 0.9584800063324658\n",
      "Generation 6042: M(n) = 862.6320056992192\n",
      "Generation 6043: p = 0.9584800063324658\n",
      "Generation 6043: M(n) = 862.6320056992192\n",
      "Generation 6044: p = 0.9584800063324658\n",
      "Generation 6044: M(n) = 862.6320056992192\n",
      "Generation 6045: p = 0.9584800063324658\n",
      "Generation 6045: M(n) = 862.6320056992192\n",
      "Generation 6046: p = 0.9584800063324658\n",
      "Generation 6046: M(n) = 862.6320056992192\n",
      "Generation 6047: p = 0.9584800063324658\n",
      "Generation 6047: M(n) = 862.6320056992192\n",
      "Generation 6048: p = 0.9584800063324658\n",
      "Generation 6048: M(n) = 862.6320056992192\n",
      "Generation 6049: p = 0.9584800063324658\n",
      "Generation 6049: M(n) = 862.6320056992192\n",
      "Generation 6050: p = 0.9584800063324658\n",
      "Generation 6050: M(n) = 862.6320056992192\n",
      "Generation 6051: p = 0.9584800063324658\n",
      "Generation 6051: M(n) = 862.6320056992192\n",
      "Generation 6052: p = 0.9584800063324658\n",
      "Generation 6052: M(n) = 862.6320056992192\n",
      "Generation 6053: p = 0.9584800063324658\n",
      "Generation 6053: M(n) = 862.6320056992192\n",
      "Generation 6054: p = 0.9584800063324658\n",
      "Generation 6054: M(n) = 862.6320056992192\n",
      "Generation 6055: p = 0.9584800063324658\n",
      "Generation 6055: M(n) = 862.6320056992192\n",
      "Generation 6056: p = 0.9584800063324658\n",
      "Generation 6056: M(n) = 862.6320056992192\n",
      "Generation 6057: p = 0.9584800063324658\n",
      "Generation 6057: M(n) = 862.6320056992192\n",
      "Generation 6058: p = 0.9584800063324658\n",
      "Generation 6058: M(n) = 862.6320056992192\n",
      "Generation 6059: p = 0.9584800063324658\n",
      "Generation 6059: M(n) = 862.6320056992192\n",
      "Generation 6060: p = 0.9584800063324658\n",
      "Generation 6060: M(n) = 862.6320056992192\n",
      "Generation 6061: p = 0.9584800063324658\n",
      "Generation 6061: M(n) = 862.6320056992192\n",
      "Generation 6062: p = 0.9584800063324658\n",
      "Generation 6062: M(n) = 862.6320056992192\n",
      "Generation 6063: p = 0.9584800063324658\n",
      "Generation 6063: M(n) = 862.6320056992192\n",
      "Generation 6064: p = 0.9584800063324658\n",
      "Generation 6064: M(n) = 862.6320056992192\n",
      "Generation 6065: p = 0.9584800063324658\n",
      "Generation 6065: M(n) = 862.6320056992192\n",
      "Generation 6066: p = 0.9584800063324658\n",
      "Generation 6066: M(n) = 862.6320056992192\n",
      "Generation 6067: p = 0.9584800063324658\n",
      "Generation 6067: M(n) = 862.6320056992192\n",
      "Generation 6068: p = 0.9584800063324658\n",
      "Generation 6068: M(n) = 862.6320056992192\n",
      "Generation 6069: p = 0.9584800063324658\n",
      "Generation 6069: M(n) = 862.6320056992192\n",
      "Generation 6070: p = 0.9584800063324658\n",
      "Generation 6070: M(n) = 862.6320056992192\n",
      "Generation 6071: p = 0.9584800063324658\n",
      "Generation 6071: M(n) = 862.6320056992192\n",
      "Generation 6072: p = 0.9584800063324658\n",
      "Generation 6072: M(n) = 862.6320056992192\n",
      "Generation 6073: p = 0.9584800063324658\n",
      "Generation 6073: M(n) = 862.6320056992192\n",
      "Generation 6074: p = 0.9584800063324658\n",
      "Generation 6074: M(n) = 862.6320056992192\n",
      "Generation 6075: p = 0.9584800063324658\n",
      "Generation 6075: M(n) = 862.6320056992192\n",
      "Generation 6076: p = 0.9584800063324658\n",
      "Generation 6076: M(n) = 862.6320056992192\n",
      "Generation 6077: p = 0.9584800063324658\n",
      "Generation 6077: M(n) = 862.6320056992192\n",
      "Generation 6078: p = 0.9584800063324658\n",
      "Generation 6078: M(n) = 862.6320056992192\n",
      "Generation 6079: p = 0.9584800063324658\n",
      "Generation 6079: M(n) = 862.6320056992192\n",
      "Generation 6080: p = 0.9584800063324658\n",
      "Generation 6080: M(n) = 862.6320056992192\n",
      "Generation 6081: p = 0.9584800063324658\n",
      "Generation 6081: M(n) = 862.6320056992192\n",
      "Generation 6082: p = 0.9584800063324658\n",
      "Generation 6082: M(n) = 862.6320056992192\n",
      "Generation 6083: p = 0.9584800063324658\n",
      "Generation 6083: M(n) = 862.6320056992192\n",
      "Generation 6084: p = 0.9584800063324658\n",
      "Generation 6084: M(n) = 862.6320056992192\n",
      "Generation 6085: p = 0.9584800063324658\n",
      "Generation 6085: M(n) = 862.6320056992192\n",
      "Generation 6086: p = 0.9584800063324658\n",
      "Generation 6086: M(n) = 862.6320056992192\n",
      "Generation 6087: p = 0.9584800063324658\n",
      "Generation 6087: M(n) = 862.6320056992192\n",
      "Generation 6088: p = 0.9584800063324658\n",
      "Generation 6088: M(n) = 862.6320056992192\n",
      "Generation 6089: p = 0.9584800063324658\n",
      "Generation 6089: M(n) = 862.6320056992192\n",
      "Generation 6090: p = 0.9584800063324658\n",
      "Generation 6090: M(n) = 862.6320056992192\n",
      "Generation 6091: p = 0.9584800063324658\n",
      "Generation 6091: M(n) = 862.6320056992192\n",
      "Generation 6092: p = 0.9584800063324658\n",
      "Generation 6092: M(n) = 862.6320056992192\n",
      "Generation 6093: p = 0.9584800063324658\n",
      "Generation 6093: M(n) = 862.6320056992192\n",
      "Generation 6094: p = 0.9584800063324658\n",
      "Generation 6094: M(n) = 862.6320056992192\n",
      "Generation 6095: p = 0.9584800063324658\n",
      "Generation 6095: M(n) = 862.6320056992192\n",
      "Generation 6096: p = 0.9584800063324658\n",
      "Generation 6096: M(n) = 862.6320056992192\n",
      "Generation 6097: p = 0.9584800063324658\n",
      "Generation 6097: M(n) = 862.6320056992192\n",
      "Generation 6098: p = 0.9584800063324658\n",
      "Generation 6098: M(n) = 862.6320056992192\n",
      "Generation 6099: p = 0.9584800063324658\n",
      "Generation 6099: M(n) = 862.6320056992192\n",
      "Generation 6100: p = 0.9584800063324658\n",
      "Generation 6100: M(n) = 862.6320056992192\n",
      "Generation 6101: p = 0.9584800063324658\n",
      "Generation 6101: M(n) = 862.6320056992192\n",
      "Generation 6102: p = 0.9584800063324658\n",
      "Generation 6102: M(n) = 862.6320056992192\n",
      "Generation 6103: p = 0.9584800063324658\n",
      "Generation 6103: M(n) = 862.6320056992192\n",
      "Generation 6104: p = 0.9584800063324658\n",
      "Generation 6104: M(n) = 862.6320056992192\n",
      "Generation 6105: p = 0.9584800063324658\n",
      "Generation 6105: M(n) = 862.6320056992192\n",
      "Generation 6106: p = 0.9584800063324658\n",
      "Generation 6106: M(n) = 862.6320056992192\n",
      "Generation 6107: p = 0.9584800063324658\n",
      "Generation 6107: M(n) = 862.6320056992192\n",
      "Generation 6108: p = 0.9584800063324658\n",
      "Generation 6108: M(n) = 862.6320056992192\n",
      "Generation 6109: p = 0.9584800063324658\n",
      "Generation 6109: M(n) = 862.6320056992192\n",
      "Generation 6110: p = 0.9584800063324658\n",
      "Generation 6110: M(n) = 862.6320056992192\n",
      "Generation 6111: p = 0.9584800063324658\n",
      "Generation 6111: M(n) = 862.6320056992192\n",
      "Generation 6112: p = 0.9584800063324658\n",
      "Generation 6112: M(n) = 862.6320056992192\n",
      "Generation 6113: p = 0.9584800063324658\n",
      "Generation 6113: M(n) = 862.6320056992192\n",
      "Generation 6114: p = 0.9584800063324658\n",
      "Generation 6114: M(n) = 862.6320056992192\n",
      "Generation 6115: p = 0.9584800063324658\n",
      "Generation 6115: M(n) = 862.6320056992192\n",
      "Generation 6116: p = 0.9584800063324658\n",
      "Generation 6116: M(n) = 862.6320056992192\n",
      "Generation 6117: p = 0.9584800063324658\n",
      "Generation 6117: M(n) = 862.6320056992192\n",
      "Generation 6118: p = 0.9584800063324658\n",
      "Generation 6118: M(n) = 862.6320056992192\n",
      "Generation 6119: p = 0.9584800063324658\n",
      "Generation 6119: M(n) = 862.6320056992192\n",
      "Generation 6120: p = 0.9584800063324658\n",
      "Generation 6120: M(n) = 862.6320056992192\n",
      "Generation 6121: p = 0.9584800063324658\n",
      "Generation 6121: M(n) = 862.6320056992192\n",
      "Generation 6122: p = 0.9584800063324658\n",
      "Generation 6122: M(n) = 862.6320056992192\n",
      "Generation 6123: p = 0.9584800063324658\n",
      "Generation 6123: M(n) = 862.6320056992192\n",
      "Generation 6124: p = 0.9584800063324658\n",
      "Generation 6124: M(n) = 862.6320056992192\n",
      "Generation 6125: p = 0.9584800063324658\n",
      "Generation 6125: M(n) = 862.6320056992192\n",
      "Generation 6126: p = 0.9584800063324658\n",
      "Generation 6126: M(n) = 862.6320056992192\n",
      "Generation 6127: p = 0.9584800063324658\n",
      "Generation 6127: M(n) = 862.6320056992192\n",
      "Generation 6128: p = 0.9584800063324658\n",
      "Generation 6128: M(n) = 862.6320056992192\n",
      "Generation 6129: p = 0.9584800063324658\n",
      "Generation 6129: M(n) = 862.6320056992192\n",
      "Generation 6130: p = 0.9584800063324658\n",
      "Generation 6130: M(n) = 862.6320056992192\n",
      "Generation 6131: p = 0.9584800063324658\n",
      "Generation 6131: M(n) = 862.6320056992192\n",
      "Generation 6132: p = 0.9584800063324658\n",
      "Generation 6132: M(n) = 862.6320056992192\n",
      "Generation 6133: p = 0.9584800063324658\n",
      "Generation 6133: M(n) = 862.6320056992192\n",
      "Generation 6134: p = 0.9584800063324658\n",
      "Generation 6134: M(n) = 862.6320056992192\n",
      "Generation 6135: p = 0.9584800063324658\n",
      "Generation 6135: M(n) = 862.6320056992192\n",
      "Generation 6136: p = 0.9584800063324658\n",
      "Generation 6136: M(n) = 862.6320056992192\n",
      "Generation 6137: p = 0.9584800063324658\n",
      "Generation 6137: M(n) = 862.6320056992192\n",
      "Generation 6138: p = 0.9584800063324658\n",
      "Generation 6138: M(n) = 862.6320056992192\n",
      "Generation 6139: p = 0.9584800063324658\n",
      "Generation 6139: M(n) = 862.6320056992192\n",
      "Generation 6140: p = 0.9584800063324658\n",
      "Generation 6140: M(n) = 862.6320056992192\n",
      "Generation 6141: p = 0.9584800063324658\n",
      "Generation 6141: M(n) = 862.6320056992192\n",
      "Generation 6142: p = 0.9584800063324658\n",
      "Generation 6142: M(n) = 862.6320056992192\n",
      "Generation 6143: p = 0.9584800063324658\n",
      "Generation 6143: M(n) = 862.6320056992192\n",
      "Generation 6144: p = 0.9584800063324658\n",
      "Generation 6144: M(n) = 862.6320056992192\n",
      "Generation 6145: p = 0.9584800063324658\n",
      "Generation 6145: M(n) = 862.6320056992192\n",
      "Generation 6146: p = 0.9584800063324658\n",
      "Generation 6146: M(n) = 862.6320056992192\n",
      "Generation 6147: p = 0.9584800063324658\n",
      "Generation 6147: M(n) = 862.6320056992192\n",
      "Generation 6148: p = 0.9584800063324658\n",
      "Generation 6148: M(n) = 862.6320056992192\n",
      "Generation 6149: p = 0.9584800063324658\n",
      "Generation 6149: M(n) = 862.6320056992192\n",
      "Generation 6150: p = 0.9584800063324658\n",
      "Generation 6150: M(n) = 862.6320056992192\n",
      "Generation 6151: p = 0.9584800063324658\n",
      "Generation 6151: M(n) = 862.6320056992192\n",
      "Generation 6152: p = 0.9584800063324658\n",
      "Generation 6152: M(n) = 862.6320056992192\n",
      "Generation 6153: p = 0.9584800063324658\n",
      "Generation 6153: M(n) = 862.6320056992192\n",
      "Generation 6154: p = 0.9584800063324658\n",
      "Generation 6154: M(n) = 862.6320056992192\n",
      "Generation 6155: p = 0.9584800063324658\n",
      "Generation 6155: M(n) = 862.6320056992192\n",
      "Generation 6156: p = 0.9584800063324658\n",
      "Generation 6156: M(n) = 862.6320056992192\n",
      "Generation 6157: p = 0.9584800063324658\n",
      "Generation 6157: M(n) = 862.6320056992192\n",
      "Generation 6158: p = 0.9584800063324658\n",
      "Generation 6158: M(n) = 862.6320056992192\n",
      "Generation 6159: p = 0.9584800063324658\n",
      "Generation 6159: M(n) = 862.6320056992192\n",
      "Generation 6160: p = 0.9584800063324658\n",
      "Generation 6160: M(n) = 862.6320056992192\n",
      "Generation 6161: p = 0.9584800063324658\n",
      "Generation 6161: M(n) = 862.6320056992192\n",
      "Generation 6162: p = 0.9584800063324658\n",
      "Generation 6162: M(n) = 862.6320056992192\n",
      "Generation 6163: p = 0.9584800063324658\n",
      "Generation 6163: M(n) = 862.6320056992192\n",
      "Generation 6164: p = 0.9584800063324658\n",
      "Generation 6164: M(n) = 862.6320056992192\n",
      "Generation 6165: p = 0.9584800063324658\n",
      "Generation 6165: M(n) = 862.6320056992192\n",
      "Generation 6166: p = 0.9584800063324658\n",
      "Generation 6166: M(n) = 862.6320056992192\n",
      "Generation 6167: p = 0.9584800063324658\n",
      "Generation 6167: M(n) = 862.6320056992192\n",
      "Generation 6168: p = 0.9584800063324658\n",
      "Generation 6168: M(n) = 862.6320056992192\n",
      "Generation 6169: p = 0.9584800063324658\n",
      "Generation 6169: M(n) = 862.6320056992192\n",
      "Generation 6170: p = 0.9584800063324658\n",
      "Generation 6170: M(n) = 862.6320056992192\n",
      "Generation 6171: p = 0.9584800063324658\n",
      "Generation 6171: M(n) = 862.6320056992192\n",
      "Generation 6172: p = 0.9584800063324658\n",
      "Generation 6172: M(n) = 862.6320056992192\n",
      "Generation 6173: p = 0.9584800063324658\n",
      "Generation 6173: M(n) = 862.6320056992192\n",
      "Generation 6174: p = 0.9584800063324658\n",
      "Generation 6174: M(n) = 862.6320056992192\n",
      "Generation 6175: p = 0.9584800063324658\n",
      "Generation 6175: M(n) = 862.6320056992192\n",
      "Generation 6176: p = 0.9584800063324658\n",
      "Generation 6176: M(n) = 862.6320056992192\n",
      "Generation 6177: p = 0.9584800063324658\n",
      "Generation 6177: M(n) = 862.6320056992192\n",
      "Generation 6178: p = 0.9584800063324658\n",
      "Generation 6178: M(n) = 862.6320056992192\n",
      "Generation 6179: p = 0.9584800063324658\n",
      "Generation 6179: M(n) = 862.6320056992192\n",
      "Generation 6180: p = 0.9584800063324658\n",
      "Generation 6180: M(n) = 862.6320056992192\n",
      "Generation 6181: p = 0.9584800063324658\n",
      "Generation 6181: M(n) = 862.6320056992192\n",
      "Generation 6182: p = 0.9584800063324658\n",
      "Generation 6182: M(n) = 862.6320056992192\n",
      "Generation 6183: p = 0.9584800063324658\n",
      "Generation 6183: M(n) = 862.6320056992192\n",
      "Generation 6184: p = 0.9584800063324658\n",
      "Generation 6184: M(n) = 862.6320056992192\n",
      "Generation 6185: p = 0.9584800063324658\n",
      "Generation 6185: M(n) = 862.6320056992192\n",
      "Generation 6186: p = 0.9584800063324658\n",
      "Generation 6186: M(n) = 862.6320056992192\n",
      "Generation 6187: p = 0.9584800063324658\n",
      "Generation 6187: M(n) = 862.6320056992192\n",
      "Generation 6188: p = 0.9584800063324658\n",
      "Generation 6188: M(n) = 862.6320056992192\n",
      "Generation 6189: p = 0.9584800063324658\n",
      "Generation 6189: M(n) = 862.6320056992192\n",
      "Generation 6190: p = 0.9584800063324658\n",
      "Generation 6190: M(n) = 862.6320056992192\n",
      "Generation 6191: p = 0.9584800063324658\n",
      "Generation 6191: M(n) = 862.6320056992192\n",
      "Generation 6192: p = 0.9584800063324658\n",
      "Generation 6192: M(n) = 862.6320056992192\n",
      "Generation 6193: p = 0.9584800063324658\n",
      "Generation 6193: M(n) = 862.6320056992192\n",
      "Generation 6194: p = 0.9584800063324658\n",
      "Generation 6194: M(n) = 862.6320056992192\n",
      "Generation 6195: p = 0.9584800063324658\n",
      "Generation 6195: M(n) = 862.6320056992192\n",
      "Generation 6196: p = 0.9584800063324658\n",
      "Generation 6196: M(n) = 862.6320056992192\n",
      "Generation 6197: p = 0.9584800063324658\n",
      "Generation 6197: M(n) = 862.6320056992192\n",
      "Generation 6198: p = 0.9584800063324658\n",
      "Generation 6198: M(n) = 862.6320056992192\n",
      "Generation 6199: p = 0.9584800063324658\n",
      "Generation 6199: M(n) = 862.6320056992192\n",
      "Generation 6200: p = 0.9584800063324658\n",
      "Generation 6200: M(n) = 862.6320056992192\n",
      "Generation 6201: p = 0.9584800063324658\n",
      "Generation 6201: M(n) = 862.6320056992192\n",
      "Generation 6202: p = 0.9584800063324658\n",
      "Generation 6202: M(n) = 862.6320056992192\n",
      "Generation 6203: p = 0.9584800063324658\n",
      "Generation 6203: M(n) = 862.6320056992192\n",
      "Generation 6204: p = 0.9584800063324658\n",
      "Generation 6204: M(n) = 862.6320056992192\n",
      "Generation 6205: p = 0.9584800063324658\n",
      "Generation 6205: M(n) = 862.6320056992192\n",
      "Generation 6206: p = 0.9584800063324658\n",
      "Generation 6206: M(n) = 862.6320056992192\n",
      "Generation 6207: p = 0.9584800063324658\n",
      "Generation 6207: M(n) = 862.6320056992192\n",
      "Generation 6208: p = 0.9584800063324658\n",
      "Generation 6208: M(n) = 862.6320056992192\n",
      "Generation 6209: p = 0.9584800063324658\n",
      "Generation 6209: M(n) = 862.6320056992192\n",
      "Generation 6210: p = 0.9584800063324658\n",
      "Generation 6210: M(n) = 862.6320056992192\n",
      "Generation 6211: p = 0.9584800063324658\n",
      "Generation 6211: M(n) = 862.6320056992192\n",
      "Generation 6212: p = 0.9584800063324658\n",
      "Generation 6212: M(n) = 862.6320056992192\n",
      "Generation 6213: p = 0.9584800063324658\n",
      "Generation 6213: M(n) = 862.6320056992192\n",
      "Generation 6214: p = 0.9584800063324658\n",
      "Generation 6214: M(n) = 862.6320056992192\n",
      "Generation 6215: p = 0.9584800063324658\n",
      "Generation 6215: M(n) = 862.6320056992192\n",
      "Generation 6216: p = 0.9584800063324658\n",
      "Generation 6216: M(n) = 862.6320056992192\n",
      "Generation 6217: p = 0.9584800063324658\n",
      "Generation 6217: M(n) = 862.6320056992192\n",
      "Generation 6218: p = 0.9584800063324658\n",
      "Generation 6218: M(n) = 862.6320056992192\n",
      "Generation 6219: p = 0.9584800063324658\n",
      "Generation 6219: M(n) = 862.6320056992192\n",
      "Generation 6220: p = 0.9584800063324658\n",
      "Generation 6220: M(n) = 862.6320056992192\n",
      "Generation 6221: p = 0.9584800063324658\n",
      "Generation 6221: M(n) = 862.6320056992192\n",
      "Generation 6222: p = 0.9584800063324658\n",
      "Generation 6222: M(n) = 862.6320056992192\n",
      "Generation 6223: p = 0.9584800063324658\n",
      "Generation 6223: M(n) = 862.6320056992192\n",
      "Generation 6224: p = 0.9584800063324658\n",
      "Generation 6224: M(n) = 862.6320056992192\n",
      "Generation 6225: p = 0.9584800063324658\n",
      "Generation 6225: M(n) = 862.6320056992192\n",
      "Generation 6226: p = 0.9584800063324658\n",
      "Generation 6226: M(n) = 862.6320056992192\n",
      "Generation 6227: p = 0.9584800063324658\n",
      "Generation 6227: M(n) = 862.6320056992192\n",
      "Generation 6228: p = 0.9584800063324658\n",
      "Generation 6228: M(n) = 862.6320056992192\n",
      "Generation 6229: p = 0.9584800063324658\n",
      "Generation 6229: M(n) = 862.6320056992192\n",
      "Generation 6230: p = 0.9584800063324658\n",
      "Generation 6230: M(n) = 862.6320056992192\n",
      "Generation 6231: p = 0.9584800063324658\n",
      "Generation 6231: M(n) = 862.6320056992192\n",
      "Generation 6232: p = 0.9584800063324658\n",
      "Generation 6232: M(n) = 862.6320056992192\n",
      "Generation 6233: p = 0.9584800063324658\n",
      "Generation 6233: M(n) = 862.6320056992192\n",
      "Generation 6234: p = 0.9584800063324658\n",
      "Generation 6234: M(n) = 862.6320056992192\n",
      "Generation 6235: p = 0.9584800063324658\n",
      "Generation 6235: M(n) = 862.6320056992192\n",
      "Generation 6236: p = 0.9584800063324658\n",
      "Generation 6236: M(n) = 862.6320056992192\n",
      "Generation 6237: p = 0.9584800063324658\n",
      "Generation 6237: M(n) = 862.6320056992192\n",
      "Generation 6238: p = 0.9584800063324658\n",
      "Generation 6238: M(n) = 862.6320056992192\n",
      "Generation 6239: p = 0.9584800063324658\n",
      "Generation 6239: M(n) = 862.6320056992192\n",
      "Generation 6240: p = 0.9584800063324658\n",
      "Generation 6240: M(n) = 862.6320056992192\n",
      "Generation 6241: p = 0.9584800063324658\n",
      "Generation 6241: M(n) = 862.6320056992192\n",
      "Generation 6242: p = 0.9584800063324658\n",
      "Generation 6242: M(n) = 862.6320056992192\n",
      "Generation 6243: p = 0.9584800063324658\n",
      "Generation 6243: M(n) = 862.6320056992192\n",
      "Generation 6244: p = 0.9584800063324658\n",
      "Generation 6244: M(n) = 862.6320056992192\n",
      "Generation 6245: p = 0.9584800063324658\n",
      "Generation 6245: M(n) = 862.6320056992192\n",
      "Generation 6246: p = 0.9584800063324658\n",
      "Generation 6246: M(n) = 862.6320056992192\n",
      "Generation 6247: p = 0.9584800063324658\n",
      "Generation 6247: M(n) = 862.6320056992192\n",
      "Generation 6248: p = 0.9584800063324658\n",
      "Generation 6248: M(n) = 862.6320056992192\n",
      "Generation 6249: p = 0.9584800063324658\n",
      "Generation 6249: M(n) = 862.6320056992192\n",
      "Generation 6250: p = 0.9584800063324658\n",
      "Generation 6250: M(n) = 862.6320056992192\n",
      "Generation 6251: p = 0.9584800063324658\n",
      "Generation 6251: M(n) = 862.6320056992192\n",
      "Generation 6252: p = 0.9584800063324658\n",
      "Generation 6252: M(n) = 862.6320056992192\n",
      "Generation 6253: p = 0.9584800063324658\n",
      "Generation 6253: M(n) = 862.6320056992192\n",
      "Generation 6254: p = 0.9584800063324658\n",
      "Generation 6254: M(n) = 862.6320056992192\n",
      "Generation 6255: p = 0.9584800063324658\n",
      "Generation 6255: M(n) = 862.6320056992192\n",
      "Generation 6256: p = 0.9584800063324658\n",
      "Generation 6256: M(n) = 862.6320056992192\n",
      "Generation 6257: p = 0.9584800063324658\n",
      "Generation 6257: M(n) = 862.6320056992192\n",
      "Generation 6258: p = 0.9584800063324658\n",
      "Generation 6258: M(n) = 862.6320056992192\n",
      "Generation 6259: p = 0.9584800063324658\n",
      "Generation 6259: M(n) = 862.6320056992192\n",
      "Generation 6260: p = 0.9584800063324658\n",
      "Generation 6260: M(n) = 862.6320056992192\n",
      "Generation 6261: p = 0.9584800063324658\n",
      "Generation 6261: M(n) = 862.6320056992192\n",
      "Generation 6262: p = 0.9584800063324658\n",
      "Generation 6262: M(n) = 862.6320056992192\n",
      "Generation 6263: p = 0.9584800063324658\n",
      "Generation 6263: M(n) = 862.6320056992192\n",
      "Generation 6264: p = 0.9584800063324658\n",
      "Generation 6264: M(n) = 862.6320056992192\n",
      "Generation 6265: p = 0.9584800063324658\n",
      "Generation 6265: M(n) = 862.6320056992192\n",
      "Generation 6266: p = 0.9584800063324658\n",
      "Generation 6266: M(n) = 862.6320056992192\n",
      "Generation 6267: p = 0.9584800063324658\n",
      "Generation 6267: M(n) = 862.6320056992192\n",
      "Generation 6268: p = 0.9584800063324658\n",
      "Generation 6268: M(n) = 862.6320056992192\n",
      "Generation 6269: p = 0.9584800063324658\n",
      "Generation 6269: M(n) = 862.6320056992192\n",
      "Generation 6270: p = 0.9584800063324658\n",
      "Generation 6270: M(n) = 862.6320056992192\n",
      "Generation 6271: p = 0.9584800063324658\n",
      "Generation 6271: M(n) = 862.6320056992192\n",
      "Generation 6272: p = 0.9584800063324658\n",
      "Generation 6272: M(n) = 862.6320056992192\n",
      "Generation 6273: p = 0.9584800063324658\n",
      "Generation 6273: M(n) = 862.6320056992192\n",
      "Generation 6274: p = 0.9584800063324658\n",
      "Generation 6274: M(n) = 862.6320056992192\n",
      "Generation 6275: p = 0.9584800063324658\n",
      "Generation 6275: M(n) = 862.6320056992192\n",
      "Generation 6276: p = 0.9584800063324658\n",
      "Generation 6276: M(n) = 862.6320056992192\n",
      "Generation 6277: p = 0.9584800063324658\n",
      "Generation 6277: M(n) = 862.6320056992192\n",
      "Generation 6278: p = 0.9584800063324658\n",
      "Generation 6278: M(n) = 862.6320056992192\n",
      "Generation 6279: p = 0.9584800063324658\n",
      "Generation 6279: M(n) = 862.6320056992192\n",
      "Generation 6280: p = 0.9584800063324658\n",
      "Generation 6280: M(n) = 862.6320056992192\n",
      "Generation 6281: p = 0.9584800063324658\n",
      "Generation 6281: M(n) = 862.6320056992192\n",
      "Generation 6282: p = 0.9584800063324658\n",
      "Generation 6282: M(n) = 862.6320056992192\n",
      "Generation 6283: p = 0.9584800063324658\n",
      "Generation 6283: M(n) = 862.6320056992192\n",
      "Generation 6284: p = 0.9584800063324658\n",
      "Generation 6284: M(n) = 862.6320056992192\n",
      "Generation 6285: p = 0.9584800063324658\n",
      "Generation 6285: M(n) = 862.6320056992192\n",
      "Generation 6286: p = 0.9584800063324658\n",
      "Generation 6286: M(n) = 862.6320056992192\n",
      "Generation 6287: p = 0.9584800063324658\n",
      "Generation 6287: M(n) = 862.6320056992192\n",
      "Generation 6288: p = 0.9584800063324658\n",
      "Generation 6288: M(n) = 862.6320056992192\n",
      "Generation 6289: p = 0.9584800063324658\n",
      "Generation 6289: M(n) = 862.6320056992192\n",
      "Generation 6290: p = 0.9584800063324658\n",
      "Generation 6290: M(n) = 862.6320056992192\n",
      "Generation 6291: p = 0.9584800063324658\n",
      "Generation 6291: M(n) = 862.6320056992192\n",
      "Generation 6292: p = 0.9584800063324658\n",
      "Generation 6292: M(n) = 862.6320056992192\n",
      "Generation 6293: p = 0.9584800063324658\n",
      "Generation 6293: M(n) = 862.6320056992192\n",
      "Generation 6294: p = 0.9584800063324658\n",
      "Generation 6294: M(n) = 862.6320056992192\n",
      "Generation 6295: p = 0.9584800063324658\n",
      "Generation 6295: M(n) = 862.6320056992192\n",
      "Generation 6296: p = 0.9584800063324658\n",
      "Generation 6296: M(n) = 862.6320056992192\n",
      "Generation 6297: p = 0.9584800063324658\n",
      "Generation 6297: M(n) = 862.6320056992192\n",
      "Generation 6298: p = 0.9584800063324658\n",
      "Generation 6298: M(n) = 862.6320056992192\n",
      "Generation 6299: p = 0.9584800063324658\n",
      "Generation 6299: M(n) = 862.6320056992192\n",
      "Generation 6300: p = 0.9584800063324658\n",
      "Generation 6300: M(n) = 862.6320056992192\n",
      "Generation 6301: p = 0.9584800063324658\n",
      "Generation 6301: M(n) = 862.6320056992192\n",
      "Generation 6302: p = 0.9584800063324658\n",
      "Generation 6302: M(n) = 862.6320056992192\n",
      "Generation 6303: p = 0.9584800063324658\n",
      "Generation 6303: M(n) = 862.6320056992192\n",
      "Generation 6304: p = 0.9584800063324658\n",
      "Generation 6304: M(n) = 862.6320056992192\n",
      "Generation 6305: p = 0.9584800063324658\n",
      "Generation 6305: M(n) = 862.6320056992192\n",
      "Generation 6306: p = 0.9584800063324658\n",
      "Generation 6306: M(n) = 862.6320056992192\n",
      "Generation 6307: p = 0.9584800063324658\n",
      "Generation 6307: M(n) = 862.6320056992192\n",
      "Generation 6308: p = 0.9584800063324658\n",
      "Generation 6308: M(n) = 862.6320056992192\n",
      "Generation 6309: p = 0.9584800063324658\n",
      "Generation 6309: M(n) = 862.6320056992192\n",
      "Generation 6310: p = 0.9584800063324658\n",
      "Generation 6310: M(n) = 862.6320056992192\n",
      "Generation 6311: p = 0.9584800063324658\n",
      "Generation 6311: M(n) = 862.6320056992192\n",
      "Generation 6312: p = 0.9584800063324658\n",
      "Generation 6312: M(n) = 862.6320056992192\n",
      "Generation 6313: p = 0.9584800063324658\n",
      "Generation 6313: M(n) = 862.6320056992192\n",
      "Generation 6314: p = 0.9584800063324658\n",
      "Generation 6314: M(n) = 862.6320056992192\n",
      "Generation 6315: p = 0.9584800063324658\n",
      "Generation 6315: M(n) = 862.6320056992192\n",
      "Generation 6316: p = 0.9584800063324658\n",
      "Generation 6316: M(n) = 862.6320056992192\n",
      "Generation 6317: p = 0.9584800063324658\n",
      "Generation 6317: M(n) = 862.6320056992192\n",
      "Generation 6318: p = 0.9584800063324658\n",
      "Generation 6318: M(n) = 862.6320056992192\n",
      "Generation 6319: p = 0.9584800063324658\n",
      "Generation 6319: M(n) = 862.6320056992192\n",
      "Generation 6320: p = 0.9584800063324658\n",
      "Generation 6320: M(n) = 862.6320056992192\n",
      "Generation 6321: p = 0.9584800063324658\n",
      "Generation 6321: M(n) = 862.6320056992192\n",
      "Generation 6322: p = 0.9584800063324658\n",
      "Generation 6322: M(n) = 862.6320056992192\n",
      "Generation 6323: p = 0.9584800063324658\n",
      "Generation 6323: M(n) = 862.6320056992192\n",
      "Generation 6324: p = 0.9584800063324658\n",
      "Generation 6324: M(n) = 862.6320056992192\n",
      "Generation 6325: p = 0.9584800063324658\n",
      "Generation 6325: M(n) = 862.6320056992192\n",
      "Generation 6326: p = 0.9584800063324658\n",
      "Generation 6326: M(n) = 862.6320056992192\n",
      "Generation 6327: p = 0.9584800063324658\n",
      "Generation 6327: M(n) = 862.6320056992192\n",
      "Generation 6328: p = 0.9584800063324658\n",
      "Generation 6328: M(n) = 862.6320056992192\n",
      "Generation 6329: p = 0.9584800063324658\n",
      "Generation 6329: M(n) = 862.6320056992192\n",
      "Generation 6330: p = 0.9584800063324658\n",
      "Generation 6330: M(n) = 862.6320056992192\n",
      "Generation 6331: p = 0.9584800063324658\n",
      "Generation 6331: M(n) = 862.6320056992192\n",
      "Generation 6332: p = 0.9584800063324658\n",
      "Generation 6332: M(n) = 862.6320056992192\n",
      "Generation 6333: p = 0.9584800063324658\n",
      "Generation 6333: M(n) = 862.6320056992192\n",
      "Generation 6334: p = 0.9584800063324658\n",
      "Generation 6334: M(n) = 862.6320056992192\n",
      "Generation 6335: p = 0.9584800063324658\n",
      "Generation 6335: M(n) = 862.6320056992192\n",
      "Generation 6336: p = 0.9584800063324658\n",
      "Generation 6336: M(n) = 862.6320056992192\n",
      "Generation 6337: p = 0.9584800063324658\n",
      "Generation 6337: M(n) = 862.6320056992192\n",
      "Generation 6338: p = 0.9584800063324658\n",
      "Generation 6338: M(n) = 862.6320056992192\n",
      "Generation 6339: p = 0.9584800063324658\n",
      "Generation 6339: M(n) = 862.6320056992192\n",
      "Generation 6340: p = 0.9584800063324658\n",
      "Generation 6340: M(n) = 862.6320056992192\n",
      "Generation 6341: p = 0.9584800063324658\n",
      "Generation 6341: M(n) = 862.6320056992192\n",
      "Generation 6342: p = 0.9584800063324658\n",
      "Generation 6342: M(n) = 862.6320056992192\n",
      "Generation 6343: p = 0.9584800063324658\n",
      "Generation 6343: M(n) = 862.6320056992192\n",
      "Generation 6344: p = 0.9584800063324658\n",
      "Generation 6344: M(n) = 862.6320056992192\n",
      "Generation 6345: p = 0.9584800063324658\n",
      "Generation 6345: M(n) = 862.6320056992192\n",
      "Generation 6346: p = 0.9584800063324658\n",
      "Generation 6346: M(n) = 862.6320056992192\n",
      "Generation 6347: p = 0.9584800063324658\n",
      "Generation 6347: M(n) = 862.6320056992192\n",
      "Generation 6348: p = 0.9584800063324658\n",
      "Generation 6348: M(n) = 862.6320056992192\n",
      "Generation 6349: p = 0.9584800063324658\n",
      "Generation 6349: M(n) = 862.6320056992192\n",
      "Generation 6350: p = 0.9584800063324658\n",
      "Generation 6350: M(n) = 862.6320056992192\n",
      "Generation 6351: p = 0.9584800063324658\n",
      "Generation 6351: M(n) = 862.6320056992192\n",
      "Generation 6352: p = 0.9584800063324658\n",
      "Generation 6352: M(n) = 862.6320056992192\n",
      "Generation 6353: p = 0.9584800063324658\n",
      "Generation 6353: M(n) = 862.6320056992192\n",
      "Generation 6354: p = 0.9584800063324658\n",
      "Generation 6354: M(n) = 862.6320056992192\n",
      "Generation 6355: p = 0.9584800063324658\n",
      "Generation 6355: M(n) = 862.6320056992192\n",
      "Generation 6356: p = 0.9584800063324658\n",
      "Generation 6356: M(n) = 862.6320056992192\n",
      "Generation 6357: p = 0.9584800063324658\n",
      "Generation 6357: M(n) = 862.6320056992192\n",
      "Generation 6358: p = 0.9584800063324658\n",
      "Generation 6358: M(n) = 862.6320056992192\n",
      "Generation 6359: p = 0.9584800063324658\n",
      "Generation 6359: M(n) = 862.6320056992192\n",
      "Generation 6360: p = 0.9584800063324658\n",
      "Generation 6360: M(n) = 862.6320056992192\n",
      "Generation 6361: p = 0.9584800063324658\n",
      "Generation 6361: M(n) = 862.6320056992192\n",
      "Generation 6362: p = 0.9584800063324658\n",
      "Generation 6362: M(n) = 862.6320056992192\n",
      "Generation 6363: p = 0.9584800063324658\n",
      "Generation 6363: M(n) = 862.6320056992192\n",
      "Generation 6364: p = 0.9584800063324658\n",
      "Generation 6364: M(n) = 862.6320056992192\n",
      "Generation 6365: p = 0.9584800063324658\n",
      "Generation 6365: M(n) = 862.6320056992192\n",
      "Generation 6366: p = 0.9584800063324658\n",
      "Generation 6366: M(n) = 862.6320056992192\n",
      "Generation 6367: p = 0.9584800063324658\n",
      "Generation 6367: M(n) = 862.6320056992192\n",
      "Generation 6368: p = 0.9584800063324658\n",
      "Generation 6368: M(n) = 862.6320056992192\n",
      "Generation 6369: p = 0.9584800063324658\n",
      "Generation 6369: M(n) = 862.6320056992192\n",
      "Generation 6370: p = 0.9584800063324658\n",
      "Generation 6370: M(n) = 862.6320056992192\n",
      "Generation 6371: p = 0.9584800063324658\n",
      "Generation 6371: M(n) = 862.6320056992192\n",
      "Generation 6372: p = 0.9584800063324658\n",
      "Generation 6372: M(n) = 862.6320056992192\n",
      "Generation 6373: p = 0.9584800063324658\n",
      "Generation 6373: M(n) = 862.6320056992192\n",
      "Generation 6374: p = 0.9584800063324658\n",
      "Generation 6374: M(n) = 862.6320056992192\n",
      "Generation 6375: p = 0.9584800063324658\n",
      "Generation 6375: M(n) = 862.6320056992192\n",
      "Generation 6376: p = 0.9584800063324658\n",
      "Generation 6376: M(n) = 862.6320056992192\n",
      "Generation 6377: p = 0.9584800063324658\n",
      "Generation 6377: M(n) = 862.6320056992192\n",
      "Generation 6378: p = 0.9584800063324658\n",
      "Generation 6378: M(n) = 862.6320056992192\n",
      "Generation 6379: p = 0.9584800063324658\n",
      "Generation 6379: M(n) = 862.6320056992192\n",
      "Generation 6380: p = 0.9584800063324658\n",
      "Generation 6380: M(n) = 862.6320056992192\n",
      "Generation 6381: p = 0.9584800063324658\n",
      "Generation 6381: M(n) = 862.6320056992192\n",
      "Generation 6382: p = 0.9584800063324658\n",
      "Generation 6382: M(n) = 862.6320056992192\n",
      "Generation 6383: p = 0.9584800063324658\n",
      "Generation 6383: M(n) = 862.6320056992192\n",
      "Generation 6384: p = 0.9584800063324658\n",
      "Generation 6384: M(n) = 862.6320056992192\n",
      "Generation 6385: p = 0.9584800063324658\n",
      "Generation 6385: M(n) = 862.6320056992192\n",
      "Generation 6386: p = 0.9584800063324658\n",
      "Generation 6386: M(n) = 862.6320056992192\n",
      "Generation 6387: p = 0.9584800063324658\n",
      "Generation 6387: M(n) = 862.6320056992192\n",
      "Generation 6388: p = 0.9584800063324658\n",
      "Generation 6388: M(n) = 862.6320056992192\n",
      "Generation 6389: p = 0.9584800063324658\n",
      "Generation 6389: M(n) = 862.6320056992192\n",
      "Generation 6390: p = 0.9584800063324658\n",
      "Generation 6390: M(n) = 862.6320056992192\n",
      "Generation 6391: p = 0.9584800063324658\n",
      "Generation 6391: M(n) = 862.6320056992192\n",
      "Generation 6392: p = 0.9584800063324658\n",
      "Generation 6392: M(n) = 862.6320056992192\n",
      "Generation 6393: p = 0.9584800063324658\n",
      "Generation 6393: M(n) = 862.6320056992192\n",
      "Generation 6394: p = 0.9584800063324658\n",
      "Generation 6394: M(n) = 862.6320056992192\n",
      "Generation 6395: p = 0.9584800063324658\n",
      "Generation 6395: M(n) = 862.6320056992192\n",
      "Generation 6396: p = 0.9584800063324658\n",
      "Generation 6396: M(n) = 862.6320056992192\n",
      "Generation 6397: p = 0.9584800063324658\n",
      "Generation 6397: M(n) = 862.6320056992192\n",
      "Generation 6398: p = 0.9584800063324658\n",
      "Generation 6398: M(n) = 862.6320056992192\n",
      "Generation 6399: p = 0.9584800063324658\n",
      "Generation 6399: M(n) = 862.6320056992192\n",
      "Generation 6400: p = 0.9584800063324658\n",
      "Generation 6400: M(n) = 862.6320056992192\n",
      "Generation 6401: p = 0.9584800063324658\n",
      "Generation 6401: M(n) = 862.6320056992192\n",
      "Generation 6402: p = 0.9584800063324658\n",
      "Generation 6402: M(n) = 862.6320056992192\n",
      "Generation 6403: p = 0.9584800063324658\n",
      "Generation 6403: M(n) = 862.6320056992192\n",
      "Generation 6404: p = 0.9584800063324658\n",
      "Generation 6404: M(n) = 862.6320056992192\n",
      "Generation 6405: p = 0.9584800063324658\n",
      "Generation 6405: M(n) = 862.6320056992192\n",
      "Generation 6406: p = 0.9584800063324658\n",
      "Generation 6406: M(n) = 862.6320056992192\n",
      "Generation 6407: p = 0.9584800063324658\n",
      "Generation 6407: M(n) = 862.6320056992192\n",
      "Generation 6408: p = 0.9584800063324658\n",
      "Generation 6408: M(n) = 862.6320056992192\n",
      "Generation 6409: p = 0.9584800063324658\n",
      "Generation 6409: M(n) = 862.6320056992192\n",
      "Generation 6410: p = 0.9584800063324658\n",
      "Generation 6410: M(n) = 862.6320056992192\n",
      "Generation 6411: p = 0.9584800063324658\n",
      "Generation 6411: M(n) = 862.6320056992192\n",
      "Generation 6412: p = 0.9584800063324658\n",
      "Generation 6412: M(n) = 862.6320056992192\n",
      "Generation 6413: p = 0.9584800063324658\n",
      "Generation 6413: M(n) = 862.6320056992192\n",
      "Generation 6414: p = 0.9584800063324658\n",
      "Generation 6414: M(n) = 862.6320056992192\n",
      "Generation 6415: p = 0.9584800063324658\n",
      "Generation 6415: M(n) = 862.6320056992192\n",
      "Generation 6416: p = 0.9584800063324658\n",
      "Generation 6416: M(n) = 862.6320056992192\n",
      "Generation 6417: p = 0.9584800063324658\n",
      "Generation 6417: M(n) = 862.6320056992192\n",
      "Generation 6418: p = 0.9584800063324658\n",
      "Generation 6418: M(n) = 862.6320056992192\n",
      "Generation 6419: p = 0.9584800063324658\n",
      "Generation 6419: M(n) = 862.6320056992192\n",
      "Generation 6420: p = 0.9584800063324658\n",
      "Generation 6420: M(n) = 862.6320056992192\n",
      "Generation 6421: p = 0.9584800063324658\n",
      "Generation 6421: M(n) = 862.6320056992192\n",
      "Generation 6422: p = 0.9584800063324658\n",
      "Generation 6422: M(n) = 862.6320056992192\n",
      "Generation 6423: p = 0.9584800063324658\n",
      "Generation 6423: M(n) = 862.6320056992192\n",
      "Generation 6424: p = 0.9584800063324658\n",
      "Generation 6424: M(n) = 862.6320056992192\n",
      "Generation 6425: p = 0.9584800063324658\n",
      "Generation 6425: M(n) = 862.6320056992192\n",
      "Generation 6426: p = 0.9584800063324658\n",
      "Generation 6426: M(n) = 862.6320056992192\n",
      "Generation 6427: p = 0.9584800063324658\n",
      "Generation 6427: M(n) = 862.6320056992192\n",
      "Generation 6428: p = 0.9584800063324658\n",
      "Generation 6428: M(n) = 862.6320056992192\n",
      "Generation 6429: p = 0.9584800063324658\n",
      "Generation 6429: M(n) = 862.6320056992192\n",
      "Generation 6430: p = 0.9584800063324658\n",
      "Generation 6430: M(n) = 862.6320056992192\n",
      "Generation 6431: p = 0.9584800063324658\n",
      "Generation 6431: M(n) = 862.6320056992192\n",
      "Generation 6432: p = 0.9584800063324658\n",
      "Generation 6432: M(n) = 862.6320056992192\n",
      "Generation 6433: p = 0.9584800063324658\n",
      "Generation 6433: M(n) = 862.6320056992192\n",
      "Generation 6434: p = 0.9584800063324658\n",
      "Generation 6434: M(n) = 862.6320056992192\n",
      "Generation 6435: p = 0.9584800063324658\n",
      "Generation 6435: M(n) = 862.6320056992192\n",
      "Generation 6436: p = 0.9584800063324658\n",
      "Generation 6436: M(n) = 862.6320056992192\n",
      "Generation 6437: p = 0.9584800063324658\n",
      "Generation 6437: M(n) = 862.6320056992192\n",
      "Generation 6438: p = 0.9584800063324658\n",
      "Generation 6438: M(n) = 862.6320056992192\n",
      "Generation 6439: p = 0.9584800063324658\n",
      "Generation 6439: M(n) = 862.6320056992192\n",
      "Generation 6440: p = 0.9584800063324658\n",
      "Generation 6440: M(n) = 862.6320056992192\n",
      "Generation 6441: p = 0.9584800063324658\n",
      "Generation 6441: M(n) = 862.6320056992192\n",
      "Generation 6442: p = 0.9584800063324658\n",
      "Generation 6442: M(n) = 862.6320056992192\n",
      "Generation 6443: p = 0.9584800063324658\n",
      "Generation 6443: M(n) = 862.6320056992192\n",
      "Generation 6444: p = 0.9584800063324658\n",
      "Generation 6444: M(n) = 862.6320056992192\n",
      "Generation 6445: p = 0.9584800063324658\n",
      "Generation 6445: M(n) = 862.6320056992192\n",
      "Generation 6446: p = 0.9584800063324658\n",
      "Generation 6446: M(n) = 862.6320056992192\n",
      "Generation 6447: p = 0.9584800063324658\n",
      "Generation 6447: M(n) = 862.6320056992192\n",
      "Generation 6448: p = 0.9584800063324658\n",
      "Generation 6448: M(n) = 862.6320056992192\n",
      "Generation 6449: p = 0.9584800063324658\n",
      "Generation 6449: M(n) = 862.6320056992192\n",
      "Generation 6450: p = 0.9584800063324658\n",
      "Generation 6450: M(n) = 862.6320056992192\n",
      "Generation 6451: p = 0.9584800063324658\n",
      "Generation 6451: M(n) = 862.6320056992192\n",
      "Generation 6452: p = 0.9584800063324658\n",
      "Generation 6452: M(n) = 862.6320056992192\n",
      "Generation 6453: p = 0.9584800063324658\n",
      "Generation 6453: M(n) = 862.6320056992192\n",
      "Generation 6454: p = 0.9584800063324658\n",
      "Generation 6454: M(n) = 862.6320056992192\n",
      "Generation 6455: p = 0.9584800063324658\n",
      "Generation 6455: M(n) = 862.6320056992192\n",
      "Generation 6456: p = 0.9584800063324658\n",
      "Generation 6456: M(n) = 862.6320056992192\n",
      "Generation 6457: p = 0.9584800063324658\n",
      "Generation 6457: M(n) = 862.6320056992192\n",
      "Generation 6458: p = 0.9584800063324658\n",
      "Generation 6458: M(n) = 862.6320056992192\n",
      "Generation 6459: p = 0.9584800063324658\n",
      "Generation 6459: M(n) = 862.6320056992192\n",
      "Generation 6460: p = 0.9584800063324658\n",
      "Generation 6460: M(n) = 862.6320056992192\n",
      "Generation 6461: p = 0.9584800063324658\n",
      "Generation 6461: M(n) = 862.6320056992192\n",
      "Generation 6462: p = 0.9584800063324658\n",
      "Generation 6462: M(n) = 862.6320056992192\n",
      "Generation 6463: p = 0.9584800063324658\n",
      "Generation 6463: M(n) = 862.6320056992192\n",
      "Generation 6464: p = 0.9584800063324658\n",
      "Generation 6464: M(n) = 862.6320056992192\n",
      "Generation 6465: p = 0.9584800063324658\n",
      "Generation 6465: M(n) = 862.6320056992192\n",
      "Generation 6466: p = 0.9584800063324658\n",
      "Generation 6466: M(n) = 862.6320056992192\n",
      "Generation 6467: p = 0.9584800063324658\n",
      "Generation 6467: M(n) = 862.6320056992192\n",
      "Generation 6468: p = 0.9584800063324658\n",
      "Generation 6468: M(n) = 862.6320056992192\n",
      "Generation 6469: p = 0.9584800063324658\n",
      "Generation 6469: M(n) = 862.6320056992192\n",
      "Generation 6470: p = 0.9584800063324658\n",
      "Generation 6470: M(n) = 862.6320056992192\n",
      "Generation 6471: p = 0.9584800063324658\n",
      "Generation 6471: M(n) = 862.6320056992192\n",
      "Generation 6472: p = 0.9584800063324658\n",
      "Generation 6472: M(n) = 862.6320056992192\n",
      "Generation 6473: p = 0.9584800063324658\n",
      "Generation 6473: M(n) = 862.6320056992192\n",
      "Generation 6474: p = 0.9584800063324658\n",
      "Generation 6474: M(n) = 862.6320056992192\n",
      "Generation 6475: p = 0.9584800063324658\n",
      "Generation 6475: M(n) = 862.6320056992192\n",
      "Generation 6476: p = 0.9584800063324658\n",
      "Generation 6476: M(n) = 862.6320056992192\n",
      "Generation 6477: p = 0.9584800063324658\n",
      "Generation 6477: M(n) = 862.6320056992192\n",
      "Generation 6478: p = 0.9584800063324658\n",
      "Generation 6478: M(n) = 862.6320056992192\n",
      "Generation 6479: p = 0.9584800063324658\n",
      "Generation 6479: M(n) = 862.6320056992192\n",
      "Generation 6480: p = 0.9584800063324658\n",
      "Generation 6480: M(n) = 862.6320056992192\n",
      "Generation 6481: p = 0.9584800063324658\n",
      "Generation 6481: M(n) = 862.6320056992192\n",
      "Generation 6482: p = 0.9584800063324658\n",
      "Generation 6482: M(n) = 862.6320056992192\n",
      "Generation 6483: p = 0.9584800063324658\n",
      "Generation 6483: M(n) = 862.6320056992192\n",
      "Generation 6484: p = 0.9584800063324658\n",
      "Generation 6484: M(n) = 862.6320056992192\n",
      "Generation 6485: p = 0.9584800063324658\n",
      "Generation 6485: M(n) = 862.6320056992192\n",
      "Generation 6486: p = 0.9584800063324658\n",
      "Generation 6486: M(n) = 862.6320056992192\n",
      "Generation 6487: p = 0.9584800063324658\n",
      "Generation 6487: M(n) = 862.6320056992192\n",
      "Generation 6488: p = 0.9584800063324658\n",
      "Generation 6488: M(n) = 862.6320056992192\n",
      "Generation 6489: p = 0.9584800063324658\n",
      "Generation 6489: M(n) = 862.6320056992192\n",
      "Generation 6490: p = 0.9584800063324658\n",
      "Generation 6490: M(n) = 862.6320056992192\n",
      "Generation 6491: p = 0.9584800063324658\n",
      "Generation 6491: M(n) = 862.6320056992192\n",
      "Generation 6492: p = 0.9584800063324658\n",
      "Generation 6492: M(n) = 862.6320056992192\n",
      "Generation 6493: p = 0.9584800063324658\n",
      "Generation 6493: M(n) = 862.6320056992192\n",
      "Generation 6494: p = 0.9584800063324658\n",
      "Generation 6494: M(n) = 862.6320056992192\n",
      "Generation 6495: p = 0.9584800063324658\n",
      "Generation 6495: M(n) = 862.6320056992192\n",
      "Generation 6496: p = 0.9584800063324658\n",
      "Generation 6496: M(n) = 862.6320056992192\n",
      "Generation 6497: p = 0.9584800063324658\n",
      "Generation 6497: M(n) = 862.6320056992192\n",
      "Generation 6498: p = 0.9584800063324658\n",
      "Generation 6498: M(n) = 862.6320056992192\n",
      "Generation 6499: p = 0.9584800063324658\n",
      "Generation 6499: M(n) = 862.6320056992192\n",
      "Generation 6500: p = 0.9584800063324658\n",
      "Generation 6500: M(n) = 862.6320056992192\n",
      "Generation 6501: p = 0.9584800063324658\n",
      "Generation 6501: M(n) = 862.6320056992192\n",
      "Generation 6502: p = 0.9584800063324658\n",
      "Generation 6502: M(n) = 862.6320056992192\n",
      "Generation 6503: p = 0.9584800063324658\n",
      "Generation 6503: M(n) = 862.6320056992192\n",
      "Generation 6504: p = 0.9584800063324658\n",
      "Generation 6504: M(n) = 862.6320056992192\n",
      "Generation 6505: p = 0.9584800063324658\n",
      "Generation 6505: M(n) = 862.6320056992192\n",
      "Generation 6506: p = 0.9584800063324658\n",
      "Generation 6506: M(n) = 862.6320056992192\n",
      "Generation 6507: p = 0.9584800063324658\n",
      "Generation 6507: M(n) = 862.6320056992192\n",
      "Generation 6508: p = 0.9584800063324658\n",
      "Generation 6508: M(n) = 862.6320056992192\n",
      "Generation 6509: p = 0.9584800063324658\n",
      "Generation 6509: M(n) = 862.6320056992192\n",
      "Generation 6510: p = 0.9584800063324658\n",
      "Generation 6510: M(n) = 862.6320056992192\n",
      "Generation 6511: p = 0.9584800063324658\n",
      "Generation 6511: M(n) = 862.6320056992192\n",
      "Generation 6512: p = 0.9584800063324658\n",
      "Generation 6512: M(n) = 862.6320056992192\n",
      "Generation 6513: p = 0.9584800063324658\n",
      "Generation 6513: M(n) = 862.6320056992192\n",
      "Generation 6514: p = 0.9584800063324658\n",
      "Generation 6514: M(n) = 862.6320056992192\n",
      "Generation 6515: p = 0.9584800063324658\n",
      "Generation 6515: M(n) = 862.6320056992192\n",
      "Generation 6516: p = 0.9584800063324658\n",
      "Generation 6516: M(n) = 862.6320056992192\n",
      "Generation 6517: p = 0.9584800063324658\n",
      "Generation 6517: M(n) = 862.6320056992192\n",
      "Generation 6518: p = 0.9584800063324658\n",
      "Generation 6518: M(n) = 862.6320056992192\n",
      "Generation 6519: p = 0.9584800063324658\n",
      "Generation 6519: M(n) = 862.6320056992192\n",
      "Generation 6520: p = 0.9584800063324658\n",
      "Generation 6520: M(n) = 862.6320056992192\n",
      "Generation 6521: p = 0.9584800063324658\n",
      "Generation 6521: M(n) = 862.6320056992192\n",
      "Generation 6522: p = 0.9584800063324658\n",
      "Generation 6522: M(n) = 862.6320056992192\n",
      "Generation 6523: p = 0.9584800063324658\n",
      "Generation 6523: M(n) = 862.6320056992192\n",
      "Generation 6524: p = 0.9584800063324658\n",
      "Generation 6524: M(n) = 862.6320056992192\n",
      "Generation 6525: p = 0.9584800063324658\n",
      "Generation 6525: M(n) = 862.6320056992192\n",
      "Generation 6526: p = 0.9584800063324658\n",
      "Generation 6526: M(n) = 862.6320056992192\n",
      "Generation 6527: p = 0.9584800063324658\n",
      "Generation 6527: M(n) = 862.6320056992192\n",
      "Generation 6528: p = 0.9584800063324658\n",
      "Generation 6528: M(n) = 862.6320056992192\n",
      "Generation 6529: p = 0.9584800063324658\n",
      "Generation 6529: M(n) = 862.6320056992192\n",
      "Generation 6530: p = 0.9584800063324658\n",
      "Generation 6530: M(n) = 862.6320056992192\n",
      "Generation 6531: p = 0.9584800063324658\n",
      "Generation 6531: M(n) = 862.6320056992192\n",
      "Generation 6532: p = 0.9584800063324658\n",
      "Generation 6532: M(n) = 862.6320056992192\n",
      "Generation 6533: p = 0.9584800063324658\n",
      "Generation 6533: M(n) = 862.6320056992192\n",
      "Generation 6534: p = 0.9584800063324658\n",
      "Generation 6534: M(n) = 862.6320056992192\n",
      "Generation 6535: p = 0.9584800063324658\n",
      "Generation 6535: M(n) = 862.6320056992192\n",
      "Generation 6536: p = 0.9584800063324658\n",
      "Generation 6536: M(n) = 862.6320056992192\n",
      "Generation 6537: p = 0.9584800063324658\n",
      "Generation 6537: M(n) = 862.6320056992192\n",
      "Generation 6538: p = 0.9584800063324658\n",
      "Generation 6538: M(n) = 862.6320056992192\n",
      "Generation 6539: p = 0.9584800063324658\n",
      "Generation 6539: M(n) = 862.6320056992192\n",
      "Generation 6540: p = 0.9584800063324658\n",
      "Generation 6540: M(n) = 862.6320056992192\n",
      "Generation 6541: p = 0.9584800063324658\n",
      "Generation 6541: M(n) = 862.6320056992192\n",
      "Generation 6542: p = 0.9584800063324658\n",
      "Generation 6542: M(n) = 862.6320056992192\n",
      "Generation 6543: p = 0.9584800063324658\n",
      "Generation 6543: M(n) = 862.6320056992192\n",
      "Generation 6544: p = 0.9584800063324658\n",
      "Generation 6544: M(n) = 862.6320056992192\n",
      "Generation 6545: p = 0.9584800063324658\n",
      "Generation 6545: M(n) = 862.6320056992192\n",
      "Generation 6546: p = 0.9584800063324658\n",
      "Generation 6546: M(n) = 862.6320056992192\n",
      "Generation 6547: p = 0.9584800063324658\n",
      "Generation 6547: M(n) = 862.6320056992192\n",
      "Generation 6548: p = 0.9584800063324658\n",
      "Generation 6548: M(n) = 862.6320056992192\n",
      "Generation 6549: p = 0.9584800063324658\n",
      "Generation 6549: M(n) = 862.6320056992192\n",
      "Generation 6550: p = 0.9584800063324658\n",
      "Generation 6550: M(n) = 862.6320056992192\n",
      "Generation 6551: p = 0.9584800063324658\n",
      "Generation 6551: M(n) = 862.6320056992192\n",
      "Generation 6552: p = 0.9584800063324658\n",
      "Generation 6552: M(n) = 862.6320056992192\n",
      "Generation 6553: p = 0.9584800063324658\n",
      "Generation 6553: M(n) = 862.6320056992192\n",
      "Generation 6554: p = 0.9584800063324658\n",
      "Generation 6554: M(n) = 862.6320056992192\n",
      "Generation 6555: p = 0.9584800063324658\n",
      "Generation 6555: M(n) = 862.6320056992192\n",
      "Generation 6556: p = 0.9584800063324658\n",
      "Generation 6556: M(n) = 862.6320056992192\n",
      "Generation 6557: p = 0.9584800063324658\n",
      "Generation 6557: M(n) = 862.6320056992192\n",
      "Generation 6558: p = 0.9584800063324658\n",
      "Generation 6558: M(n) = 862.6320056992192\n",
      "Generation 6559: p = 0.9584800063324658\n",
      "Generation 6559: M(n) = 862.6320056992192\n",
      "Generation 6560: p = 0.9584800063324658\n",
      "Generation 6560: M(n) = 862.6320056992192\n",
      "Generation 6561: p = 0.9584800063324658\n",
      "Generation 6561: M(n) = 862.6320056992192\n",
      "Generation 6562: p = 0.9584800063324658\n",
      "Generation 6562: M(n) = 862.6320056992192\n",
      "Generation 6563: p = 0.9584800063324658\n",
      "Generation 6563: M(n) = 862.6320056992192\n",
      "Generation 6564: p = 0.9584800063324658\n",
      "Generation 6564: M(n) = 862.6320056992192\n",
      "Generation 6565: p = 0.9584800063324658\n",
      "Generation 6565: M(n) = 862.6320056992192\n",
      "Generation 6566: p = 0.9584800063324658\n",
      "Generation 6566: M(n) = 862.6320056992192\n",
      "Generation 6567: p = 0.9584800063324658\n",
      "Generation 6567: M(n) = 862.6320056992192\n",
      "Generation 6568: p = 0.9584800063324658\n",
      "Generation 6568: M(n) = 862.6320056992192\n",
      "Generation 6569: p = 0.9584800063324658\n",
      "Generation 6569: M(n) = 862.6320056992192\n",
      "Generation 6570: p = 0.9584800063324658\n",
      "Generation 6570: M(n) = 862.6320056992192\n",
      "Generation 6571: p = 0.9584800063324658\n",
      "Generation 6571: M(n) = 862.6320056992192\n",
      "Generation 6572: p = 0.9584800063324658\n",
      "Generation 6572: M(n) = 862.6320056992192\n",
      "Generation 6573: p = 0.9584800063324658\n",
      "Generation 6573: M(n) = 862.6320056992192\n",
      "Generation 6574: p = 0.9584800063324658\n",
      "Generation 6574: M(n) = 862.6320056992192\n",
      "Generation 6575: p = 0.9584800063324658\n",
      "Generation 6575: M(n) = 862.6320056992192\n",
      "Generation 6576: p = 0.9584800063324658\n",
      "Generation 6576: M(n) = 862.6320056992192\n",
      "Generation 6577: p = 0.9584800063324658\n",
      "Generation 6577: M(n) = 862.6320056992192\n",
      "Generation 6578: p = 0.9584800063324658\n",
      "Generation 6578: M(n) = 862.6320056992192\n",
      "Generation 6579: p = 0.9584800063324658\n",
      "Generation 6579: M(n) = 862.6320056992192\n",
      "Generation 6580: p = 0.9584800063324658\n",
      "Generation 6580: M(n) = 862.6320056992192\n",
      "Generation 6581: p = 0.9584800063324658\n",
      "Generation 6581: M(n) = 862.6320056992192\n",
      "Generation 6582: p = 0.9584800063324658\n",
      "Generation 6582: M(n) = 862.6320056992192\n",
      "Generation 6583: p = 0.9584800063324658\n",
      "Generation 6583: M(n) = 862.6320056992192\n",
      "Generation 6584: p = 0.9584800063324658\n",
      "Generation 6584: M(n) = 862.6320056992192\n",
      "Generation 6585: p = 0.9584800063324658\n",
      "Generation 6585: M(n) = 862.6320056992192\n",
      "Generation 6586: p = 0.9584800063324658\n",
      "Generation 6586: M(n) = 862.6320056992192\n",
      "Generation 6587: p = 0.9584800063324658\n",
      "Generation 6587: M(n) = 862.6320056992192\n",
      "Generation 6588: p = 0.9584800063324658\n",
      "Generation 6588: M(n) = 862.6320056992192\n",
      "Generation 6589: p = 0.9584800063324658\n",
      "Generation 6589: M(n) = 862.6320056992192\n",
      "Generation 6590: p = 0.9584800063324658\n",
      "Generation 6590: M(n) = 862.6320056992192\n",
      "Generation 6591: p = 0.9584800063324658\n",
      "Generation 6591: M(n) = 862.6320056992192\n",
      "Generation 6592: p = 0.9584800063324658\n",
      "Generation 6592: M(n) = 862.6320056992192\n",
      "Generation 6593: p = 0.9584800063324658\n",
      "Generation 6593: M(n) = 862.6320056992192\n",
      "Generation 6594: p = 0.9584800063324658\n",
      "Generation 6594: M(n) = 862.6320056992192\n",
      "Generation 6595: p = 0.9584800063324658\n",
      "Generation 6595: M(n) = 862.6320056992192\n",
      "Generation 6596: p = 0.9584800063324658\n",
      "Generation 6596: M(n) = 862.6320056992192\n",
      "Generation 6597: p = 0.9584800063324658\n",
      "Generation 6597: M(n) = 862.6320056992192\n",
      "Generation 6598: p = 0.9584800063324658\n",
      "Generation 6598: M(n) = 862.6320056992192\n",
      "Generation 6599: p = 0.9584800063324658\n",
      "Generation 6599: M(n) = 862.6320056992192\n",
      "Generation 6600: p = 0.9584800063324658\n",
      "Generation 6600: M(n) = 862.6320056992192\n",
      "Generation 6601: p = 0.9584800063324658\n",
      "Generation 6601: M(n) = 862.6320056992192\n",
      "Generation 6602: p = 0.9584800063324658\n",
      "Generation 6602: M(n) = 862.6320056992192\n",
      "Generation 6603: p = 0.9584800063324658\n",
      "Generation 6603: M(n) = 862.6320056992192\n",
      "Generation 6604: p = 0.9584800063324658\n",
      "Generation 6604: M(n) = 862.6320056992192\n",
      "Generation 6605: p = 0.9584800063324658\n",
      "Generation 6605: M(n) = 862.6320056992192\n",
      "Generation 6606: p = 0.9584800063324658\n",
      "Generation 6606: M(n) = 862.6320056992192\n",
      "Generation 6607: p = 0.9584800063324658\n",
      "Generation 6607: M(n) = 862.6320056992192\n",
      "Generation 6608: p = 0.9584800063324658\n",
      "Generation 6608: M(n) = 862.6320056992192\n",
      "Generation 6609: p = 0.9584800063324658\n",
      "Generation 6609: M(n) = 862.6320056992192\n",
      "Generation 6610: p = 0.9584800063324658\n",
      "Generation 6610: M(n) = 862.6320056992192\n",
      "Generation 6611: p = 0.9584800063324658\n",
      "Generation 6611: M(n) = 862.6320056992192\n",
      "Generation 6612: p = 0.9584800063324658\n",
      "Generation 6612: M(n) = 862.6320056992192\n",
      "Generation 6613: p = 0.9584800063324658\n",
      "Generation 6613: M(n) = 862.6320056992192\n",
      "Generation 6614: p = 0.9584800063324658\n",
      "Generation 6614: M(n) = 862.6320056992192\n",
      "Generation 6615: p = 0.9584800063324658\n",
      "Generation 6615: M(n) = 862.6320056992192\n",
      "Generation 6616: p = 0.9584800063324658\n",
      "Generation 6616: M(n) = 862.6320056992192\n",
      "Generation 6617: p = 0.9584800063324658\n",
      "Generation 6617: M(n) = 862.6320056992192\n",
      "Generation 6618: p = 0.9584800063324658\n",
      "Generation 6618: M(n) = 862.6320056992192\n",
      "Generation 6619: p = 0.9584800063324658\n",
      "Generation 6619: M(n) = 862.6320056992192\n",
      "Generation 6620: p = 0.9584800063324658\n",
      "Generation 6620: M(n) = 862.6320056992192\n",
      "Generation 6621: p = 0.9584800063324658\n",
      "Generation 6621: M(n) = 862.6320056992192\n",
      "Generation 6622: p = 0.9584800063324658\n",
      "Generation 6622: M(n) = 862.6320056992192\n",
      "Generation 6623: p = 0.9584800063324658\n",
      "Generation 6623: M(n) = 862.6320056992192\n",
      "Generation 6624: p = 0.9584800063324658\n",
      "Generation 6624: M(n) = 862.6320056992192\n",
      "Generation 6625: p = 0.9584800063324658\n",
      "Generation 6625: M(n) = 862.6320056992192\n",
      "Generation 6626: p = 0.9584800063324658\n",
      "Generation 6626: M(n) = 862.6320056992192\n",
      "Generation 6627: p = 0.9584800063324658\n",
      "Generation 6627: M(n) = 862.6320056992192\n",
      "Generation 6628: p = 0.9584800063324658\n",
      "Generation 6628: M(n) = 862.6320056992192\n",
      "Generation 6629: p = 0.9584800063324658\n",
      "Generation 6629: M(n) = 862.6320056992192\n",
      "Generation 6630: p = 0.9584800063324658\n",
      "Generation 6630: M(n) = 862.6320056992192\n",
      "Generation 6631: p = 0.9584800063324658\n",
      "Generation 6631: M(n) = 862.6320056992192\n",
      "Generation 6632: p = 0.9584800063324658\n",
      "Generation 6632: M(n) = 862.6320056992192\n",
      "Generation 6633: p = 0.9584800063324658\n",
      "Generation 6633: M(n) = 862.6320056992192\n",
      "Generation 6634: p = 0.9584800063324658\n",
      "Generation 6634: M(n) = 862.6320056992192\n",
      "Generation 6635: p = 0.9584800063324658\n",
      "Generation 6635: M(n) = 862.6320056992192\n",
      "Generation 6636: p = 0.9584800063324658\n",
      "Generation 6636: M(n) = 862.6320056992192\n",
      "Generation 6637: p = 0.9584800063324658\n",
      "Generation 6637: M(n) = 862.6320056992192\n",
      "Generation 6638: p = 0.9584800063324658\n",
      "Generation 6638: M(n) = 862.6320056992192\n",
      "Generation 6639: p = 0.9584800063324658\n",
      "Generation 6639: M(n) = 862.6320056992192\n",
      "Generation 6640: p = 0.9584800063324658\n",
      "Generation 6640: M(n) = 862.6320056992192\n",
      "Generation 6641: p = 0.9584800063324658\n",
      "Generation 6641: M(n) = 862.6320056992192\n",
      "Generation 6642: p = 0.9584800063324658\n",
      "Generation 6642: M(n) = 862.6320056992192\n",
      "Generation 6643: p = 0.9584800063324658\n",
      "Generation 6643: M(n) = 862.6320056992192\n",
      "Generation 6644: p = 0.9584800063324658\n",
      "Generation 6644: M(n) = 862.6320056992192\n",
      "Generation 6645: p = 0.9584800063324658\n",
      "Generation 6645: M(n) = 862.6320056992192\n",
      "Generation 6646: p = 0.9584800063324658\n",
      "Generation 6646: M(n) = 862.6320056992192\n",
      "Generation 6647: p = 0.9584800063324658\n",
      "Generation 6647: M(n) = 862.6320056992192\n",
      "Generation 6648: p = 0.9584800063324658\n",
      "Generation 6648: M(n) = 862.6320056992192\n",
      "Generation 6649: p = 0.9584800063324658\n",
      "Generation 6649: M(n) = 862.6320056992192\n",
      "Generation 6650: p = 0.9584800063324658\n",
      "Generation 6650: M(n) = 862.6320056992192\n",
      "Generation 6651: p = 0.9584800063324658\n",
      "Generation 6651: M(n) = 862.6320056992192\n",
      "Generation 6652: p = 0.9584800063324658\n",
      "Generation 6652: M(n) = 862.6320056992192\n",
      "Generation 6653: p = 0.9584800063324658\n",
      "Generation 6653: M(n) = 862.6320056992192\n",
      "Generation 6654: p = 0.9584800063324658\n",
      "Generation 6654: M(n) = 862.6320056992192\n",
      "Generation 6655: p = 0.9584800063324658\n",
      "Generation 6655: M(n) = 862.6320056992192\n",
      "Generation 6656: p = 0.9584800063324658\n",
      "Generation 6656: M(n) = 862.6320056992192\n",
      "Generation 6657: p = 0.9584800063324658\n",
      "Generation 6657: M(n) = 862.6320056992192\n",
      "Generation 6658: p = 0.9584800063324658\n",
      "Generation 6658: M(n) = 862.6320056992192\n",
      "Generation 6659: p = 0.9584800063324658\n",
      "Generation 6659: M(n) = 862.6320056992192\n",
      "Generation 6660: p = 0.9584800063324658\n",
      "Generation 6660: M(n) = 862.6320056992192\n",
      "Generation 6661: p = 0.9584800063324658\n",
      "Generation 6661: M(n) = 862.6320056992192\n",
      "Generation 6662: p = 0.9584800063324658\n",
      "Generation 6662: M(n) = 862.6320056992192\n",
      "Generation 6663: p = 0.9584800063324658\n",
      "Generation 6663: M(n) = 862.6320056992192\n",
      "Generation 6664: p = 0.9584800063324658\n",
      "Generation 6664: M(n) = 862.6320056992192\n",
      "Generation 6665: p = 0.9584800063324658\n",
      "Generation 6665: M(n) = 862.6320056992192\n",
      "Generation 6666: p = 0.9584800063324658\n",
      "Generation 6666: M(n) = 862.6320056992192\n",
      "Generation 6667: p = 0.9584800063324658\n",
      "Generation 6667: M(n) = 862.6320056992192\n",
      "Generation 6668: p = 0.9584800063324658\n",
      "Generation 6668: M(n) = 862.6320056992192\n",
      "Generation 6669: p = 0.9584800063324658\n",
      "Generation 6669: M(n) = 862.6320056992192\n",
      "Generation 6670: p = 0.9584800063324658\n",
      "Generation 6670: M(n) = 862.6320056992192\n",
      "Generation 6671: p = 0.9584800063324658\n",
      "Generation 6671: M(n) = 862.6320056992192\n",
      "Generation 6672: p = 0.9584800063324658\n",
      "Generation 6672: M(n) = 862.6320056992192\n",
      "Generation 6673: p = 0.9584800063324658\n",
      "Generation 6673: M(n) = 862.6320056992192\n",
      "Generation 6674: p = 0.9584800063324658\n",
      "Generation 6674: M(n) = 862.6320056992192\n",
      "Generation 6675: p = 0.9584800063324658\n",
      "Generation 6675: M(n) = 862.6320056992192\n",
      "Generation 6676: p = 0.9584800063324658\n",
      "Generation 6676: M(n) = 862.6320056992192\n",
      "Generation 6677: p = 0.9584800063324658\n",
      "Generation 6677: M(n) = 862.6320056992192\n",
      "Generation 6678: p = 0.9584800063324658\n",
      "Generation 6678: M(n) = 862.6320056992192\n",
      "Generation 6679: p = 0.9584800063324658\n",
      "Generation 6679: M(n) = 862.6320056992192\n",
      "Generation 6680: p = 0.9584800063324658\n",
      "Generation 6680: M(n) = 862.6320056992192\n",
      "Generation 6681: p = 0.9584800063324658\n",
      "Generation 6681: M(n) = 862.6320056992192\n",
      "Generation 6682: p = 0.9584800063324658\n",
      "Generation 6682: M(n) = 862.6320056992192\n",
      "Generation 6683: p = 0.9584800063324658\n",
      "Generation 6683: M(n) = 862.6320056992192\n",
      "Generation 6684: p = 0.9584800063324658\n",
      "Generation 6684: M(n) = 862.6320056992192\n",
      "Generation 6685: p = 0.9584800063324658\n",
      "Generation 6685: M(n) = 862.6320056992192\n",
      "Generation 6686: p = 0.9584800063324658\n",
      "Generation 6686: M(n) = 862.6320056992192\n",
      "Generation 6687: p = 0.9584800063324658\n",
      "Generation 6687: M(n) = 862.6320056992192\n",
      "Generation 6688: p = 0.9584800063324658\n",
      "Generation 6688: M(n) = 862.6320056992192\n",
      "Generation 6689: p = 0.9584800063324658\n",
      "Generation 6689: M(n) = 862.6320056992192\n",
      "Generation 6690: p = 0.9584800063324658\n",
      "Generation 6690: M(n) = 862.6320056992192\n",
      "Generation 6691: p = 0.9584800063324658\n",
      "Generation 6691: M(n) = 862.6320056992192\n",
      "Generation 6692: p = 0.9584800063324658\n",
      "Generation 6692: M(n) = 862.6320056992192\n",
      "Generation 6693: p = 0.9584800063324658\n",
      "Generation 6693: M(n) = 862.6320056992192\n",
      "Generation 6694: p = 0.9584800063324658\n",
      "Generation 6694: M(n) = 862.6320056992192\n",
      "Generation 6695: p = 0.9584800063324658\n",
      "Generation 6695: M(n) = 862.6320056992192\n",
      "Generation 6696: p = 0.9584800063324658\n",
      "Generation 6696: M(n) = 862.6320056992192\n",
      "Generation 6697: p = 0.9584800063324658\n",
      "Generation 6697: M(n) = 862.6320056992192\n",
      "Generation 6698: p = 0.9584800063324658\n",
      "Generation 6698: M(n) = 862.6320056992192\n",
      "Generation 6699: p = 0.9584800063324658\n",
      "Generation 6699: M(n) = 862.6320056992192\n",
      "Generation 6700: p = 0.9584800063324658\n",
      "Generation 6700: M(n) = 862.6320056992192\n",
      "Generation 6701: p = 0.9584800063324658\n",
      "Generation 6701: M(n) = 862.6320056992192\n",
      "Generation 6702: p = 0.9584800063324658\n",
      "Generation 6702: M(n) = 862.6320056992192\n",
      "Generation 6703: p = 0.9584800063324658\n",
      "Generation 6703: M(n) = 862.6320056992192\n",
      "Generation 6704: p = 0.9584800063324658\n",
      "Generation 6704: M(n) = 862.6320056992192\n",
      "Generation 6705: p = 0.9584800063324658\n",
      "Generation 6705: M(n) = 862.6320056992192\n",
      "Generation 6706: p = 0.9584800063324658\n",
      "Generation 6706: M(n) = 862.6320056992192\n",
      "Generation 6707: p = 0.9584800063324658\n",
      "Generation 6707: M(n) = 862.6320056992192\n",
      "Generation 6708: p = 0.9584800063324658\n",
      "Generation 6708: M(n) = 862.6320056992192\n",
      "Generation 6709: p = 0.9584800063324658\n",
      "Generation 6709: M(n) = 862.6320056992192\n",
      "Generation 6710: p = 0.9584800063324658\n",
      "Generation 6710: M(n) = 862.6320056992192\n",
      "Generation 6711: p = 0.9584800063324658\n",
      "Generation 6711: M(n) = 862.6320056992192\n",
      "Generation 6712: p = 0.9584800063324658\n",
      "Generation 6712: M(n) = 862.6320056992192\n",
      "Generation 6713: p = 0.9584800063324658\n",
      "Generation 6713: M(n) = 862.6320056992192\n",
      "Generation 6714: p = 0.9584800063324658\n",
      "Generation 6714: M(n) = 862.6320056992192\n",
      "Generation 6715: p = 0.9584800063324658\n",
      "Generation 6715: M(n) = 862.6320056992192\n",
      "Generation 6716: p = 0.9584800063324658\n",
      "Generation 6716: M(n) = 862.6320056992192\n",
      "Generation 6717: p = 0.9584800063324658\n",
      "Generation 6717: M(n) = 862.6320056992192\n",
      "Generation 6718: p = 0.9584800063324658\n",
      "Generation 6718: M(n) = 862.6320056992192\n",
      "Generation 6719: p = 0.9584800063324658\n",
      "Generation 6719: M(n) = 862.6320056992192\n",
      "Generation 6720: p = 0.9584800063324658\n",
      "Generation 6720: M(n) = 862.6320056992192\n",
      "Generation 6721: p = 0.9584800063324658\n",
      "Generation 6721: M(n) = 862.6320056992192\n",
      "Generation 6722: p = 0.9584800063324658\n",
      "Generation 6722: M(n) = 862.6320056992192\n",
      "Generation 6723: p = 0.9584800063324658\n",
      "Generation 6723: M(n) = 862.6320056992192\n",
      "Generation 6724: p = 0.9584800063324658\n",
      "Generation 6724: M(n) = 862.6320056992192\n",
      "Generation 6725: p = 0.9584800063324658\n",
      "Generation 6725: M(n) = 862.6320056992192\n",
      "Generation 6726: p = 0.9584800063324658\n",
      "Generation 6726: M(n) = 862.6320056992192\n",
      "Generation 6727: p = 0.9584800063324658\n",
      "Generation 6727: M(n) = 862.6320056992192\n",
      "Generation 6728: p = 0.9584800063324658\n",
      "Generation 6728: M(n) = 862.6320056992192\n",
      "Generation 6729: p = 0.9584800063324658\n",
      "Generation 6729: M(n) = 862.6320056992192\n",
      "Generation 6730: p = 0.9584800063324658\n",
      "Generation 6730: M(n) = 862.6320056992192\n",
      "Generation 6731: p = 0.9584800063324658\n",
      "Generation 6731: M(n) = 862.6320056992192\n",
      "Generation 6732: p = 0.9584800063324658\n",
      "Generation 6732: M(n) = 862.6320056992192\n",
      "Generation 6733: p = 0.9584800063324658\n",
      "Generation 6733: M(n) = 862.6320056992192\n",
      "Generation 6734: p = 0.9584800063324658\n",
      "Generation 6734: M(n) = 862.6320056992192\n",
      "Generation 6735: p = 0.9584800063324658\n",
      "Generation 6735: M(n) = 862.6320056992192\n",
      "Generation 6736: p = 0.9584800063324658\n",
      "Generation 6736: M(n) = 862.6320056992192\n",
      "Generation 6737: p = 0.9584800063324658\n",
      "Generation 6737: M(n) = 862.6320056992192\n",
      "Generation 6738: p = 0.9584800063324658\n",
      "Generation 6738: M(n) = 862.6320056992192\n",
      "Generation 6739: p = 0.9584800063324658\n",
      "Generation 6739: M(n) = 862.6320056992192\n",
      "Generation 6740: p = 0.9584800063324658\n",
      "Generation 6740: M(n) = 862.6320056992192\n",
      "Generation 6741: p = 0.9584800063324658\n",
      "Generation 6741: M(n) = 862.6320056992192\n",
      "Generation 6742: p = 0.9584800063324658\n",
      "Generation 6742: M(n) = 862.6320056992192\n",
      "Generation 6743: p = 0.9584800063324658\n",
      "Generation 6743: M(n) = 862.6320056992192\n",
      "Generation 6744: p = 0.9584800063324658\n",
      "Generation 6744: M(n) = 862.6320056992192\n",
      "Generation 6745: p = 0.9584800063324658\n",
      "Generation 6745: M(n) = 862.6320056992192\n",
      "Generation 6746: p = 0.9584800063324658\n",
      "Generation 6746: M(n) = 862.6320056992192\n",
      "Generation 6747: p = 0.9584800063324658\n",
      "Generation 6747: M(n) = 862.6320056992192\n",
      "Generation 6748: p = 0.9584800063324658\n",
      "Generation 6748: M(n) = 862.6320056992192\n",
      "Generation 6749: p = 0.9584800063324658\n",
      "Generation 6749: M(n) = 862.6320056992192\n",
      "Generation 6750: p = 0.9584800063324658\n",
      "Generation 6750: M(n) = 862.6320056992192\n",
      "Generation 6751: p = 0.9584800063324658\n",
      "Generation 6751: M(n) = 862.6320056992192\n",
      "Generation 6752: p = 0.9584800063324658\n",
      "Generation 6752: M(n) = 862.6320056992192\n",
      "Generation 6753: p = 0.9584800063324658\n",
      "Generation 6753: M(n) = 862.6320056992192\n",
      "Generation 6754: p = 0.9584800063324658\n",
      "Generation 6754: M(n) = 862.6320056992192\n",
      "Generation 6755: p = 0.9584800063324658\n",
      "Generation 6755: M(n) = 862.6320056992192\n",
      "Generation 6756: p = 0.9584800063324658\n",
      "Generation 6756: M(n) = 862.6320056992192\n",
      "Generation 6757: p = 0.9584800063324658\n",
      "Generation 6757: M(n) = 862.6320056992192\n",
      "Generation 6758: p = 0.9584800063324658\n",
      "Generation 6758: M(n) = 862.6320056992192\n",
      "Generation 6759: p = 0.9584800063324658\n",
      "Generation 6759: M(n) = 862.6320056992192\n",
      "Generation 6760: p = 0.9584800063324658\n",
      "Generation 6760: M(n) = 862.6320056992192\n",
      "Generation 6761: p = 0.9584800063324658\n",
      "Generation 6761: M(n) = 862.6320056992192\n",
      "Generation 6762: p = 0.9584800063324658\n",
      "Generation 6762: M(n) = 862.6320056992192\n",
      "Generation 6763: p = 0.9584800063324658\n",
      "Generation 6763: M(n) = 862.6320056992192\n",
      "Generation 6764: p = 0.9584800063324658\n",
      "Generation 6764: M(n) = 862.6320056992192\n",
      "Generation 6765: p = 0.9584800063324658\n",
      "Generation 6765: M(n) = 862.6320056992192\n",
      "Generation 6766: p = 0.9584800063324658\n",
      "Generation 6766: M(n) = 862.6320056992192\n",
      "Generation 6767: p = 0.9584800063324658\n",
      "Generation 6767: M(n) = 862.6320056992192\n",
      "Generation 6768: p = 0.9584800063324658\n",
      "Generation 6768: M(n) = 862.6320056992192\n",
      "Generation 6769: p = 0.9584800063324658\n",
      "Generation 6769: M(n) = 862.6320056992192\n",
      "Generation 6770: p = 0.9584800063324658\n",
      "Generation 6770: M(n) = 862.6320056992192\n",
      "Generation 6771: p = 0.9584800063324658\n",
      "Generation 6771: M(n) = 862.6320056992192\n",
      "Generation 6772: p = 0.9584800063324658\n",
      "Generation 6772: M(n) = 862.6320056992192\n",
      "Generation 6773: p = 0.9584800063324658\n",
      "Generation 6773: M(n) = 862.6320056992192\n",
      "Generation 6774: p = 0.9584800063324658\n",
      "Generation 6774: M(n) = 862.6320056992192\n",
      "Generation 6775: p = 0.9584800063324658\n",
      "Generation 6775: M(n) = 862.6320056992192\n",
      "Generation 6776: p = 0.9584800063324658\n",
      "Generation 6776: M(n) = 862.6320056992192\n",
      "Generation 6777: p = 0.9584800063324658\n",
      "Generation 6777: M(n) = 862.6320056992192\n",
      "Generation 6778: p = 0.9584800063324658\n",
      "Generation 6778: M(n) = 862.6320056992192\n",
      "Generation 6779: p = 0.9584800063324658\n",
      "Generation 6779: M(n) = 862.6320056992192\n",
      "Generation 6780: p = 0.9584800063324658\n",
      "Generation 6780: M(n) = 862.6320056992192\n",
      "Generation 6781: p = 0.9584800063324658\n",
      "Generation 6781: M(n) = 862.6320056992192\n",
      "Generation 6782: p = 0.9584800063324658\n",
      "Generation 6782: M(n) = 862.6320056992192\n",
      "Generation 6783: p = 0.9584800063324658\n",
      "Generation 6783: M(n) = 862.6320056992192\n",
      "Generation 6784: p = 0.9584800063324658\n",
      "Generation 6784: M(n) = 862.6320056992192\n",
      "Generation 6785: p = 0.9584800063324658\n",
      "Generation 6785: M(n) = 862.6320056992192\n",
      "Generation 6786: p = 0.9584800063324658\n",
      "Generation 6786: M(n) = 862.6320056992192\n",
      "Generation 6787: p = 0.9584800063324658\n",
      "Generation 6787: M(n) = 862.6320056992192\n",
      "Generation 6788: p = 0.9584800063324658\n",
      "Generation 6788: M(n) = 862.6320056992192\n",
      "Generation 6789: p = 0.9584800063324658\n",
      "Generation 6789: M(n) = 862.6320056992192\n",
      "Generation 6790: p = 0.9584800063324658\n",
      "Generation 6790: M(n) = 862.6320056992192\n",
      "Generation 6791: p = 0.9584800063324658\n",
      "Generation 6791: M(n) = 862.6320056992192\n",
      "Generation 6792: p = 0.9584800063324658\n",
      "Generation 6792: M(n) = 862.6320056992192\n",
      "Generation 6793: p = 0.9584800063324658\n",
      "Generation 6793: M(n) = 862.6320056992192\n",
      "Generation 6794: p = 0.9584800063324658\n",
      "Generation 6794: M(n) = 862.6320056992192\n",
      "Generation 6795: p = 0.9584800063324658\n",
      "Generation 6795: M(n) = 862.6320056992192\n",
      "Generation 6796: p = 0.9584800063324658\n",
      "Generation 6796: M(n) = 862.6320056992192\n",
      "Generation 6797: p = 0.9584800063324658\n",
      "Generation 6797: M(n) = 862.6320056992192\n",
      "Generation 6798: p = 0.9584800063324658\n",
      "Generation 6798: M(n) = 862.6320056992192\n",
      "Generation 6799: p = 0.9584800063324658\n",
      "Generation 6799: M(n) = 862.6320056992192\n",
      "Generation 6800: p = 0.9584800063324658\n",
      "Generation 6800: M(n) = 862.6320056992192\n",
      "Generation 6801: p = 0.9584800063324658\n",
      "Generation 6801: M(n) = 862.6320056992192\n",
      "Generation 6802: p = 0.9584800063324658\n",
      "Generation 6802: M(n) = 862.6320056992192\n",
      "Generation 6803: p = 0.9584800063324658\n",
      "Generation 6803: M(n) = 862.6320056992192\n",
      "Generation 6804: p = 0.9584800063324658\n",
      "Generation 6804: M(n) = 862.6320056992192\n",
      "Generation 6805: p = 0.9584800063324658\n",
      "Generation 6805: M(n) = 862.6320056992192\n",
      "Generation 6806: p = 0.9584800063324658\n",
      "Generation 6806: M(n) = 862.6320056992192\n",
      "Generation 6807: p = 0.9584800063324658\n",
      "Generation 6807: M(n) = 862.6320056992192\n",
      "Generation 6808: p = 0.9584800063324658\n",
      "Generation 6808: M(n) = 862.6320056992192\n",
      "Generation 6809: p = 0.9584800063324658\n",
      "Generation 6809: M(n) = 862.6320056992192\n",
      "Generation 6810: p = 0.9584800063324658\n",
      "Generation 6810: M(n) = 862.6320056992192\n",
      "Generation 6811: p = 0.9584800063324658\n",
      "Generation 6811: M(n) = 862.6320056992192\n",
      "Generation 6812: p = 0.9584800063324658\n",
      "Generation 6812: M(n) = 862.6320056992192\n",
      "Generation 6813: p = 0.9584800063324658\n",
      "Generation 6813: M(n) = 862.6320056992192\n",
      "Generation 6814: p = 0.9584800063324658\n",
      "Generation 6814: M(n) = 862.6320056992192\n",
      "Generation 6815: p = 0.9584800063324658\n",
      "Generation 6815: M(n) = 862.6320056992192\n",
      "Generation 6816: p = 0.9584800063324658\n",
      "Generation 6816: M(n) = 862.6320056992192\n",
      "Generation 6817: p = 0.9584800063324658\n",
      "Generation 6817: M(n) = 862.6320056992192\n",
      "Generation 6818: p = 0.9584800063324658\n",
      "Generation 6818: M(n) = 862.6320056992192\n",
      "Generation 6819: p = 0.9584800063324658\n",
      "Generation 6819: M(n) = 862.6320056992192\n",
      "Generation 6820: p = 0.9584800063324658\n",
      "Generation 6820: M(n) = 862.6320056992192\n",
      "Generation 6821: p = 0.9584800063324658\n",
      "Generation 6821: M(n) = 862.6320056992192\n",
      "Generation 6822: p = 0.9584800063324658\n",
      "Generation 6822: M(n) = 862.6320056992192\n",
      "Generation 6823: p = 0.9584800063324658\n",
      "Generation 6823: M(n) = 862.6320056992192\n",
      "Generation 6824: p = 0.9584800063324658\n",
      "Generation 6824: M(n) = 862.6320056992192\n",
      "Generation 6825: p = 0.9584800063324658\n",
      "Generation 6825: M(n) = 862.6320056992192\n",
      "Generation 6826: p = 0.9584800063324658\n",
      "Generation 6826: M(n) = 862.6320056992192\n",
      "Generation 6827: p = 0.9584800063324658\n",
      "Generation 6827: M(n) = 862.6320056992192\n",
      "Generation 6828: p = 0.9584800063324658\n",
      "Generation 6828: M(n) = 862.6320056992192\n",
      "Generation 6829: p = 0.9584800063324658\n",
      "Generation 6829: M(n) = 862.6320056992192\n",
      "Generation 6830: p = 0.9584800063324658\n",
      "Generation 6830: M(n) = 862.6320056992192\n",
      "Generation 6831: p = 0.9584800063324658\n",
      "Generation 6831: M(n) = 862.6320056992192\n",
      "Generation 6832: p = 0.9584800063324658\n",
      "Generation 6832: M(n) = 862.6320056992192\n",
      "Generation 6833: p = 0.9584800063324658\n",
      "Generation 6833: M(n) = 862.6320056992192\n",
      "Generation 6834: p = 0.9584800063324658\n",
      "Generation 6834: M(n) = 862.6320056992192\n",
      "Generation 6835: p = 0.9584800063324658\n",
      "Generation 6835: M(n) = 862.6320056992192\n",
      "Generation 6836: p = 0.9584800063324658\n",
      "Generation 6836: M(n) = 862.6320056992192\n",
      "Generation 6837: p = 0.9584800063324658\n",
      "Generation 6837: M(n) = 862.6320056992192\n",
      "Generation 6838: p = 0.9584800063324658\n",
      "Generation 6838: M(n) = 862.6320056992192\n",
      "Generation 6839: p = 0.9584800063324658\n",
      "Generation 6839: M(n) = 862.6320056992192\n",
      "Generation 6840: p = 0.9584800063324658\n",
      "Generation 6840: M(n) = 862.6320056992192\n",
      "Generation 6841: p = 0.9584800063324658\n",
      "Generation 6841: M(n) = 862.6320056992192\n",
      "Generation 6842: p = 0.9584800063324658\n",
      "Generation 6842: M(n) = 862.6320056992192\n",
      "Generation 6843: p = 0.9584800063324658\n",
      "Generation 6843: M(n) = 862.6320056992192\n",
      "Generation 6844: p = 0.9584800063324658\n",
      "Generation 6844: M(n) = 862.6320056992192\n",
      "Generation 6845: p = 0.9584800063324658\n",
      "Generation 6845: M(n) = 862.6320056992192\n",
      "Generation 6846: p = 0.9584800063324658\n",
      "Generation 6846: M(n) = 862.6320056992192\n",
      "Generation 6847: p = 0.9584800063324658\n",
      "Generation 6847: M(n) = 862.6320056992192\n",
      "Generation 6848: p = 0.9584800063324658\n",
      "Generation 6848: M(n) = 862.6320056992192\n",
      "Generation 6849: p = 0.9584800063324658\n",
      "Generation 6849: M(n) = 862.6320056992192\n",
      "Generation 6850: p = 0.9584800063324658\n",
      "Generation 6850: M(n) = 862.6320056992192\n",
      "Generation 6851: p = 0.9584800063324658\n",
      "Generation 6851: M(n) = 862.6320056992192\n",
      "Generation 6852: p = 0.9584800063324658\n",
      "Generation 6852: M(n) = 862.6320056992192\n",
      "Generation 6853: p = 0.9584800063324658\n",
      "Generation 6853: M(n) = 862.6320056992192\n",
      "Generation 6854: p = 0.9584800063324658\n",
      "Generation 6854: M(n) = 862.6320056992192\n",
      "Generation 6855: p = 0.9584800063324658\n",
      "Generation 6855: M(n) = 862.6320056992192\n",
      "Generation 6856: p = 0.9584800063324658\n",
      "Generation 6856: M(n) = 862.6320056992192\n",
      "Generation 6857: p = 0.9584800063324658\n",
      "Generation 6857: M(n) = 862.6320056992192\n",
      "Generation 6858: p = 0.9584800063324658\n",
      "Generation 6858: M(n) = 862.6320056992192\n",
      "Generation 6859: p = 0.9584800063324658\n",
      "Generation 6859: M(n) = 862.6320056992192\n",
      "Generation 6860: p = 0.9584800063324658\n",
      "Generation 6860: M(n) = 862.6320056992192\n",
      "Generation 6861: p = 0.9584800063324658\n",
      "Generation 6861: M(n) = 862.6320056992192\n",
      "Generation 6862: p = 0.9584800063324658\n",
      "Generation 6862: M(n) = 862.6320056992192\n",
      "Generation 6863: p = 0.9584800063324658\n",
      "Generation 6863: M(n) = 862.6320056992192\n",
      "Generation 6864: p = 0.9584800063324658\n",
      "Generation 6864: M(n) = 862.6320056992192\n",
      "Generation 6865: p = 0.9584800063324658\n",
      "Generation 6865: M(n) = 862.6320056992192\n",
      "Generation 6866: p = 0.9584800063324658\n",
      "Generation 6866: M(n) = 862.6320056992192\n",
      "Generation 6867: p = 0.9584800063324658\n",
      "Generation 6867: M(n) = 862.6320056992192\n",
      "Generation 6868: p = 0.9584800063324658\n",
      "Generation 6868: M(n) = 862.6320056992192\n",
      "Generation 6869: p = 0.9584800063324658\n",
      "Generation 6869: M(n) = 862.6320056992192\n",
      "Generation 6870: p = 0.9584800063324658\n",
      "Generation 6870: M(n) = 862.6320056992192\n",
      "Generation 6871: p = 0.9584800063324658\n",
      "Generation 6871: M(n) = 862.6320056992192\n",
      "Generation 6872: p = 0.9584800063324658\n",
      "Generation 6872: M(n) = 862.6320056992192\n",
      "Generation 6873: p = 0.9584800063324658\n",
      "Generation 6873: M(n) = 862.6320056992192\n",
      "Generation 6874: p = 0.9584800063324658\n",
      "Generation 6874: M(n) = 862.6320056992192\n",
      "Generation 6875: p = 0.9584800063324658\n",
      "Generation 6875: M(n) = 862.6320056992192\n",
      "Generation 6876: p = 0.9584800063324658\n",
      "Generation 6876: M(n) = 862.6320056992192\n",
      "Generation 6877: p = 0.9584800063324658\n",
      "Generation 6877: M(n) = 862.6320056992192\n",
      "Generation 6878: p = 0.9584800063324658\n",
      "Generation 6878: M(n) = 862.6320056992192\n",
      "Generation 6879: p = 0.9584800063324658\n",
      "Generation 6879: M(n) = 862.6320056992192\n",
      "Generation 6880: p = 0.9584800063324658\n",
      "Generation 6880: M(n) = 862.6320056992192\n",
      "Generation 6881: p = 0.9584800063324658\n",
      "Generation 6881: M(n) = 862.6320056992192\n",
      "Generation 6882: p = 0.9584800063324658\n",
      "Generation 6882: M(n) = 862.6320056992192\n",
      "Generation 6883: p = 0.9584800063324658\n",
      "Generation 6883: M(n) = 862.6320056992192\n",
      "Generation 6884: p = 0.9584800063324658\n",
      "Generation 6884: M(n) = 862.6320056992192\n",
      "Generation 6885: p = 0.9584800063324658\n",
      "Generation 6885: M(n) = 862.6320056992192\n",
      "Generation 6886: p = 0.9584800063324658\n",
      "Generation 6886: M(n) = 862.6320056992192\n",
      "Generation 6887: p = 0.9584800063324658\n",
      "Generation 6887: M(n) = 862.6320056992192\n",
      "Generation 6888: p = 0.9584800063324658\n",
      "Generation 6888: M(n) = 862.6320056992192\n",
      "Generation 6889: p = 0.9584800063324658\n",
      "Generation 6889: M(n) = 862.6320056992192\n",
      "Generation 6890: p = 0.9584800063324658\n",
      "Generation 6890: M(n) = 862.6320056992192\n",
      "Generation 6891: p = 0.9584800063324658\n",
      "Generation 6891: M(n) = 862.6320056992192\n",
      "Generation 6892: p = 0.9584800063324658\n",
      "Generation 6892: M(n) = 862.6320056992192\n",
      "Generation 6893: p = 0.9584800063324658\n",
      "Generation 6893: M(n) = 862.6320056992192\n",
      "Generation 6894: p = 0.9584800063324658\n",
      "Generation 6894: M(n) = 862.6320056992192\n",
      "Generation 6895: p = 0.9584800063324658\n",
      "Generation 6895: M(n) = 862.6320056992192\n",
      "Generation 6896: p = 0.9584800063324658\n",
      "Generation 6896: M(n) = 862.6320056992192\n",
      "Generation 6897: p = 0.9584800063324658\n",
      "Generation 6897: M(n) = 862.6320056992192\n",
      "Generation 6898: p = 0.9584800063324658\n",
      "Generation 6898: M(n) = 862.6320056992192\n",
      "Generation 6899: p = 0.9584800063324658\n",
      "Generation 6899: M(n) = 862.6320056992192\n",
      "Generation 6900: p = 0.9584800063324658\n",
      "Generation 6900: M(n) = 862.6320056992192\n",
      "Generation 6901: p = 0.9584800063324658\n",
      "Generation 6901: M(n) = 862.6320056992192\n",
      "Generation 6902: p = 0.9584800063324658\n",
      "Generation 6902: M(n) = 862.6320056992192\n",
      "Generation 6903: p = 0.9584800063324658\n",
      "Generation 6903: M(n) = 862.6320056992192\n",
      "Generation 6904: p = 0.9584800063324658\n",
      "Generation 6904: M(n) = 862.6320056992192\n",
      "Generation 6905: p = 0.9584800063324658\n",
      "Generation 6905: M(n) = 862.6320056992192\n",
      "Generation 6906: p = 0.9584800063324658\n",
      "Generation 6906: M(n) = 862.6320056992192\n",
      "Generation 6907: p = 0.9584800063324658\n",
      "Generation 6907: M(n) = 862.6320056992192\n",
      "Generation 6908: p = 0.9584800063324658\n",
      "Generation 6908: M(n) = 862.6320056992192\n",
      "Generation 6909: p = 0.9584800063324658\n",
      "Generation 6909: M(n) = 862.6320056992192\n",
      "Generation 6910: p = 0.9584800063324658\n",
      "Generation 6910: M(n) = 862.6320056992192\n",
      "Generation 6911: p = 0.9584800063324658\n",
      "Generation 6911: M(n) = 862.6320056992192\n",
      "Generation 6912: p = 0.9584800063324658\n",
      "Generation 6912: M(n) = 862.6320056992192\n",
      "Generation 6913: p = 0.9584800063324658\n",
      "Generation 6913: M(n) = 862.6320056992192\n",
      "Generation 6914: p = 0.9584800063324658\n",
      "Generation 6914: M(n) = 862.6320056992192\n",
      "Generation 6915: p = 0.9584800063324658\n",
      "Generation 6915: M(n) = 862.6320056992192\n",
      "Generation 6916: p = 0.9584800063324658\n",
      "Generation 6916: M(n) = 862.6320056992192\n",
      "Generation 6917: p = 0.9584800063324658\n",
      "Generation 6917: M(n) = 862.6320056992192\n",
      "Generation 6918: p = 0.9584800063324658\n",
      "Generation 6918: M(n) = 862.6320056992192\n",
      "Generation 6919: p = 0.9584800063324658\n",
      "Generation 6919: M(n) = 862.6320056992192\n",
      "Generation 6920: p = 0.9584800063324658\n",
      "Generation 6920: M(n) = 862.6320056992192\n",
      "Generation 6921: p = 0.9584800063324658\n",
      "Generation 6921: M(n) = 862.6320056992192\n",
      "Generation 6922: p = 0.9584800063324658\n",
      "Generation 6922: M(n) = 862.6320056992192\n",
      "Generation 6923: p = 0.9584800063324658\n",
      "Generation 6923: M(n) = 862.6320056992192\n",
      "Generation 6924: p = 0.9584800063324658\n",
      "Generation 6924: M(n) = 862.6320056992192\n",
      "Generation 6925: p = 0.9584800063324658\n",
      "Generation 6925: M(n) = 862.6320056992192\n",
      "Generation 6926: p = 0.9584800063324658\n",
      "Generation 6926: M(n) = 862.6320056992192\n",
      "Generation 6927: p = 0.9584800063324658\n",
      "Generation 6927: M(n) = 862.6320056992192\n",
      "Generation 6928: p = 0.9584800063324658\n",
      "Generation 6928: M(n) = 862.6320056992192\n",
      "Generation 6929: p = 0.9584800063324658\n",
      "Generation 6929: M(n) = 862.6320056992192\n",
      "Generation 6930: p = 0.9584800063324658\n",
      "Generation 6930: M(n) = 862.6320056992192\n",
      "Generation 6931: p = 0.9584800063324658\n",
      "Generation 6931: M(n) = 862.6320056992192\n",
      "Generation 6932: p = 0.9584800063324658\n",
      "Generation 6932: M(n) = 862.6320056992192\n",
      "Generation 6933: p = 0.9584800063324658\n",
      "Generation 6933: M(n) = 862.6320056992192\n",
      "Generation 6934: p = 0.9584800063324658\n",
      "Generation 6934: M(n) = 862.6320056992192\n",
      "Generation 6935: p = 0.9584800063324658\n",
      "Generation 6935: M(n) = 862.6320056992192\n",
      "Generation 6936: p = 0.9584800063324658\n",
      "Generation 6936: M(n) = 862.6320056992192\n",
      "Generation 6937: p = 0.9584800063324658\n",
      "Generation 6937: M(n) = 862.6320056992192\n",
      "Generation 6938: p = 0.9584800063324658\n",
      "Generation 6938: M(n) = 862.6320056992192\n",
      "Generation 6939: p = 0.9584800063324658\n",
      "Generation 6939: M(n) = 862.6320056992192\n",
      "Generation 6940: p = 0.9584800063324658\n",
      "Generation 6940: M(n) = 862.6320056992192\n",
      "Generation 6941: p = 0.9584800063324658\n",
      "Generation 6941: M(n) = 862.6320056992192\n",
      "Generation 6942: p = 0.9584800063324658\n",
      "Generation 6942: M(n) = 862.6320056992192\n",
      "Generation 6943: p = 0.9584800063324658\n",
      "Generation 6943: M(n) = 862.6320056992192\n",
      "Generation 6944: p = 0.9584800063324658\n",
      "Generation 6944: M(n) = 862.6320056992192\n",
      "Generation 6945: p = 0.9584800063324658\n",
      "Generation 6945: M(n) = 862.6320056992192\n",
      "Generation 6946: p = 0.9584800063324658\n",
      "Generation 6946: M(n) = 862.6320056992192\n",
      "Generation 6947: p = 0.9584800063324658\n",
      "Generation 6947: M(n) = 862.6320056992192\n",
      "Generation 6948: p = 0.9584800063324658\n",
      "Generation 6948: M(n) = 862.6320056992192\n",
      "Generation 6949: p = 0.9584800063324658\n",
      "Generation 6949: M(n) = 862.6320056992192\n",
      "Generation 6950: p = 0.9584800063324658\n",
      "Generation 6950: M(n) = 862.6320056992192\n",
      "Generation 6951: p = 0.9584800063324658\n",
      "Generation 6951: M(n) = 862.6320056992192\n",
      "Generation 6952: p = 0.9584800063324658\n",
      "Generation 6952: M(n) = 862.6320056992192\n",
      "Generation 6953: p = 0.9584800063324658\n",
      "Generation 6953: M(n) = 862.6320056992192\n",
      "Generation 6954: p = 0.9584800063324658\n",
      "Generation 6954: M(n) = 862.6320056992192\n",
      "Generation 6955: p = 0.9584800063324658\n",
      "Generation 6955: M(n) = 862.6320056992192\n",
      "Generation 6956: p = 0.9584800063324658\n",
      "Generation 6956: M(n) = 862.6320056992192\n",
      "Generation 6957: p = 0.9584800063324658\n",
      "Generation 6957: M(n) = 862.6320056992192\n",
      "Generation 6958: p = 0.9584800063324658\n",
      "Generation 6958: M(n) = 862.6320056992192\n",
      "Generation 6959: p = 0.9584800063324658\n",
      "Generation 6959: M(n) = 862.6320056992192\n",
      "Generation 6960: p = 0.9584800063324658\n",
      "Generation 6960: M(n) = 862.6320056992192\n",
      "Generation 6961: p = 0.9584800063324658\n",
      "Generation 6961: M(n) = 862.6320056992192\n",
      "Generation 6962: p = 0.9584800063324658\n",
      "Generation 6962: M(n) = 862.6320056992192\n",
      "Generation 6963: p = 0.9584800063324658\n",
      "Generation 6963: M(n) = 862.6320056992192\n",
      "Generation 6964: p = 0.9584800063324658\n",
      "Generation 6964: M(n) = 862.6320056992192\n",
      "Generation 6965: p = 0.9584800063324658\n",
      "Generation 6965: M(n) = 862.6320056992192\n",
      "Generation 6966: p = 0.9584800063324658\n",
      "Generation 6966: M(n) = 862.6320056992192\n",
      "Generation 6967: p = 0.9584800063324658\n",
      "Generation 6967: M(n) = 862.6320056992192\n",
      "Generation 6968: p = 0.9584800063324658\n",
      "Generation 6968: M(n) = 862.6320056992192\n",
      "Generation 6969: p = 0.9584800063324658\n",
      "Generation 6969: M(n) = 862.6320056992192\n",
      "Generation 6970: p = 0.9584800063324658\n",
      "Generation 6970: M(n) = 862.6320056992192\n",
      "Generation 6971: p = 0.9584800063324658\n",
      "Generation 6971: M(n) = 862.6320056992192\n",
      "Generation 6972: p = 0.9584800063324658\n",
      "Generation 6972: M(n) = 862.6320056992192\n",
      "Generation 6973: p = 0.9584800063324658\n",
      "Generation 6973: M(n) = 862.6320056992192\n",
      "Generation 6974: p = 0.9584800063324658\n",
      "Generation 6974: M(n) = 862.6320056992192\n",
      "Generation 6975: p = 0.9584800063324658\n",
      "Generation 6975: M(n) = 862.6320056992192\n",
      "Generation 6976: p = 0.9584800063324658\n",
      "Generation 6976: M(n) = 862.6320056992192\n",
      "Generation 6977: p = 0.9584800063324658\n",
      "Generation 6977: M(n) = 862.6320056992192\n",
      "Generation 6978: p = 0.9584800063324658\n",
      "Generation 6978: M(n) = 862.6320056992192\n",
      "Generation 6979: p = 0.9584800063324658\n",
      "Generation 6979: M(n) = 862.6320056992192\n",
      "Generation 6980: p = 0.9584800063324658\n",
      "Generation 6980: M(n) = 862.6320056992192\n",
      "Generation 6981: p = 0.9584800063324658\n",
      "Generation 6981: M(n) = 862.6320056992192\n",
      "Generation 6982: p = 0.9584800063324658\n",
      "Generation 6982: M(n) = 862.6320056992192\n",
      "Generation 6983: p = 0.9584800063324658\n",
      "Generation 6983: M(n) = 862.6320056992192\n",
      "Generation 6984: p = 0.9584800063324658\n",
      "Generation 6984: M(n) = 862.6320056992192\n",
      "Generation 6985: p = 0.9584800063324658\n",
      "Generation 6985: M(n) = 862.6320056992192\n",
      "Generation 6986: p = 0.9584800063324658\n",
      "Generation 6986: M(n) = 862.6320056992192\n",
      "Generation 6987: p = 0.9584800063324658\n",
      "Generation 6987: M(n) = 862.6320056992192\n",
      "Generation 6988: p = 0.9584800063324658\n",
      "Generation 6988: M(n) = 862.6320056992192\n",
      "Generation 6989: p = 0.9584800063324658\n",
      "Generation 6989: M(n) = 862.6320056992192\n",
      "Generation 6990: p = 0.9584800063324658\n",
      "Generation 6990: M(n) = 862.6320056992192\n",
      "Generation 6991: p = 0.9584800063324658\n",
      "Generation 6991: M(n) = 862.6320056992192\n",
      "Generation 6992: p = 0.9584800063324658\n",
      "Generation 6992: M(n) = 862.6320056992192\n",
      "Generation 6993: p = 0.9584800063324658\n",
      "Generation 6993: M(n) = 862.6320056992192\n",
      "Generation 6994: p = 0.9584800063324658\n",
      "Generation 6994: M(n) = 862.6320056992192\n",
      "Generation 6995: p = 0.9584800063324658\n",
      "Generation 6995: M(n) = 862.6320056992192\n",
      "Generation 6996: p = 0.9584800063324658\n",
      "Generation 6996: M(n) = 862.6320056992192\n",
      "Generation 6997: p = 0.9584800063324658\n",
      "Generation 6997: M(n) = 862.6320056992192\n",
      "Generation 6998: p = 0.9584800063324658\n",
      "Generation 6998: M(n) = 862.6320056992192\n",
      "Generation 6999: p = 0.9584800063324658\n",
      "Generation 6999: M(n) = 862.6320056992192\n",
      "Generation 7000: p = 0.9584800063324658\n",
      "Generation 7000: M(n) = 862.6320056992192\n",
      "Generation 7001: p = 0.9584800063324658\n",
      "Generation 7001: M(n) = 862.6320056992192\n",
      "Generation 7002: p = 0.9584800063324658\n",
      "Generation 7002: M(n) = 862.6320056992192\n",
      "Generation 7003: p = 0.9584800063324658\n",
      "Generation 7003: M(n) = 862.6320056992192\n",
      "Generation 7004: p = 0.9584800063324658\n",
      "Generation 7004: M(n) = 862.6320056992192\n",
      "Generation 7005: p = 0.9584800063324658\n",
      "Generation 7005: M(n) = 862.6320056992192\n",
      "Generation 7006: p = 0.9584800063324658\n",
      "Generation 7006: M(n) = 862.6320056992192\n",
      "Generation 7007: p = 0.9584800063324658\n",
      "Generation 7007: M(n) = 862.6320056992192\n",
      "Generation 7008: p = 0.9584800063324658\n",
      "Generation 7008: M(n) = 862.6320056992192\n",
      "Generation 7009: p = 0.9584800063324658\n",
      "Generation 7009: M(n) = 862.6320056992192\n",
      "Generation 7010: p = 0.9584800063324658\n",
      "Generation 7010: M(n) = 862.6320056992192\n",
      "Generation 7011: p = 0.9584800063324658\n",
      "Generation 7011: M(n) = 862.6320056992192\n",
      "Generation 7012: p = 0.9584800063324658\n",
      "Generation 7012: M(n) = 862.6320056992192\n",
      "Generation 7013: p = 0.9584800063324658\n",
      "Generation 7013: M(n) = 862.6320056992192\n",
      "Generation 7014: p = 0.9584800063324658\n",
      "Generation 7014: M(n) = 862.6320056992192\n",
      "Generation 7015: p = 0.9584800063324658\n",
      "Generation 7015: M(n) = 862.6320056992192\n",
      "Generation 7016: p = 0.9584800063324658\n",
      "Generation 7016: M(n) = 862.6320056992192\n",
      "Generation 7017: p = 0.9584800063324658\n",
      "Generation 7017: M(n) = 862.6320056992192\n",
      "Generation 7018: p = 0.9584800063324658\n",
      "Generation 7018: M(n) = 862.6320056992192\n",
      "Generation 7019: p = 0.9584800063324658\n",
      "Generation 7019: M(n) = 862.6320056992192\n",
      "Generation 7020: p = 0.9584800063324658\n",
      "Generation 7020: M(n) = 862.6320056992192\n",
      "Generation 7021: p = 0.9584800063324658\n",
      "Generation 7021: M(n) = 862.6320056992192\n",
      "Generation 7022: p = 0.9584800063324658\n",
      "Generation 7022: M(n) = 862.6320056992192\n",
      "Generation 7023: p = 0.9584800063324658\n",
      "Generation 7023: M(n) = 862.6320056992192\n",
      "Generation 7024: p = 0.9584800063324658\n",
      "Generation 7024: M(n) = 862.6320056992192\n",
      "Generation 7025: p = 0.9584800063324658\n",
      "Generation 7025: M(n) = 862.6320056992192\n",
      "Generation 7026: p = 0.9584800063324658\n",
      "Generation 7026: M(n) = 862.6320056992192\n",
      "Generation 7027: p = 0.9584800063324658\n",
      "Generation 7027: M(n) = 862.6320056992192\n",
      "Generation 7028: p = 0.9584800063324658\n",
      "Generation 7028: M(n) = 862.6320056992192\n",
      "Generation 7029: p = 0.9584800063324658\n",
      "Generation 7029: M(n) = 862.6320056992192\n",
      "Generation 7030: p = 0.9584800063324658\n",
      "Generation 7030: M(n) = 862.6320056992192\n",
      "Generation 7031: p = 0.9584800063324658\n",
      "Generation 7031: M(n) = 862.6320056992192\n",
      "Generation 7032: p = 0.9584800063324658\n",
      "Generation 7032: M(n) = 862.6320056992192\n",
      "Generation 7033: p = 0.9584800063324658\n",
      "Generation 7033: M(n) = 862.6320056992192\n",
      "Generation 7034: p = 0.9584800063324658\n",
      "Generation 7034: M(n) = 862.6320056992192\n",
      "Generation 7035: p = 0.9584800063324658\n",
      "Generation 7035: M(n) = 862.6320056992192\n",
      "Generation 7036: p = 0.9584800063324658\n",
      "Generation 7036: M(n) = 862.6320056992192\n",
      "Generation 7037: p = 0.9584800063324658\n",
      "Generation 7037: M(n) = 862.6320056992192\n",
      "Generation 7038: p = 0.9584800063324658\n",
      "Generation 7038: M(n) = 862.6320056992192\n",
      "Generation 7039: p = 0.9584800063324658\n",
      "Generation 7039: M(n) = 862.6320056992192\n",
      "Generation 7040: p = 0.9584800063324658\n",
      "Generation 7040: M(n) = 862.6320056992192\n",
      "Generation 7041: p = 0.9584800063324658\n",
      "Generation 7041: M(n) = 862.6320056992192\n",
      "Generation 7042: p = 0.9584800063324658\n",
      "Generation 7042: M(n) = 862.6320056992192\n",
      "Generation 7043: p = 0.9584800063324658\n",
      "Generation 7043: M(n) = 862.6320056992192\n",
      "Generation 7044: p = 0.9584800063324658\n",
      "Generation 7044: M(n) = 862.6320056992192\n",
      "Generation 7045: p = 0.9584800063324658\n",
      "Generation 7045: M(n) = 862.6320056992192\n",
      "Generation 7046: p = 0.9584800063324658\n",
      "Generation 7046: M(n) = 862.6320056992192\n",
      "Generation 7047: p = 0.9584800063324658\n",
      "Generation 7047: M(n) = 862.6320056992192\n",
      "Generation 7048: p = 0.9584800063324658\n",
      "Generation 7048: M(n) = 862.6320056992192\n",
      "Generation 7049: p = 0.9584800063324658\n",
      "Generation 7049: M(n) = 862.6320056992192\n",
      "Generation 7050: p = 0.9584800063324658\n",
      "Generation 7050: M(n) = 862.6320056992192\n",
      "Generation 7051: p = 0.9584800063324658\n",
      "Generation 7051: M(n) = 862.6320056992192\n",
      "Generation 7052: p = 0.9584800063324658\n",
      "Generation 7052: M(n) = 862.6320056992192\n",
      "Generation 7053: p = 0.9584800063324658\n",
      "Generation 7053: M(n) = 862.6320056992192\n",
      "Generation 7054: p = 0.9584800063324658\n",
      "Generation 7054: M(n) = 862.6320056992192\n",
      "Generation 7055: p = 0.9584800063324658\n",
      "Generation 7055: M(n) = 862.6320056992192\n",
      "Generation 7056: p = 0.9584800063324658\n",
      "Generation 7056: M(n) = 862.6320056992192\n",
      "Generation 7057: p = 0.9584800063324658\n",
      "Generation 7057: M(n) = 862.6320056992192\n",
      "Generation 7058: p = 0.9584800063324658\n",
      "Generation 7058: M(n) = 862.6320056992192\n",
      "Generation 7059: p = 0.9584800063324658\n",
      "Generation 7059: M(n) = 862.6320056992192\n",
      "Generation 7060: p = 0.9584800063324658\n",
      "Generation 7060: M(n) = 862.6320056992192\n",
      "Generation 7061: p = 0.9584800063324658\n",
      "Generation 7061: M(n) = 862.6320056992192\n",
      "Generation 7062: p = 0.9584800063324658\n",
      "Generation 7062: M(n) = 862.6320056992192\n",
      "Generation 7063: p = 0.9584800063324658\n",
      "Generation 7063: M(n) = 862.6320056992192\n",
      "Generation 7064: p = 0.9584800063324658\n",
      "Generation 7064: M(n) = 862.6320056992192\n",
      "Generation 7065: p = 0.9584800063324658\n",
      "Generation 7065: M(n) = 862.6320056992192\n",
      "Generation 7066: p = 0.9584800063324658\n",
      "Generation 7066: M(n) = 862.6320056992192\n",
      "Generation 7067: p = 0.9584800063324658\n",
      "Generation 7067: M(n) = 862.6320056992192\n",
      "Generation 7068: p = 0.9584800063324658\n",
      "Generation 7068: M(n) = 862.6320056992192\n",
      "Generation 7069: p = 0.9584800063324658\n",
      "Generation 7069: M(n) = 862.6320056992192\n",
      "Generation 7070: p = 0.9584800063324658\n",
      "Generation 7070: M(n) = 862.6320056992192\n",
      "Generation 7071: p = 0.9584800063324658\n",
      "Generation 7071: M(n) = 862.6320056992192\n",
      "Generation 7072: p = 0.9584800063324658\n",
      "Generation 7072: M(n) = 862.6320056992192\n",
      "Generation 7073: p = 0.9584800063324658\n",
      "Generation 7073: M(n) = 862.6320056992192\n",
      "Generation 7074: p = 0.9584800063324658\n",
      "Generation 7074: M(n) = 862.6320056992192\n",
      "Generation 7075: p = 0.9584800063324658\n",
      "Generation 7075: M(n) = 862.6320056992192\n",
      "Generation 7076: p = 0.9584800063324658\n",
      "Generation 7076: M(n) = 862.6320056992192\n",
      "Generation 7077: p = 0.9584800063324658\n",
      "Generation 7077: M(n) = 862.6320056992192\n",
      "Generation 7078: p = 0.9584800063324658\n",
      "Generation 7078: M(n) = 862.6320056992192\n",
      "Generation 7079: p = 0.9584800063324658\n",
      "Generation 7079: M(n) = 862.6320056992192\n",
      "Generation 7080: p = 0.9584800063324658\n",
      "Generation 7080: M(n) = 862.6320056992192\n",
      "Generation 7081: p = 0.9584800063324658\n",
      "Generation 7081: M(n) = 862.6320056992192\n",
      "Generation 7082: p = 0.9584800063324658\n",
      "Generation 7082: M(n) = 862.6320056992192\n",
      "Generation 7083: p = 0.9584800063324658\n",
      "Generation 7083: M(n) = 862.6320056992192\n",
      "Generation 7084: p = 0.9584800063324658\n",
      "Generation 7084: M(n) = 862.6320056992192\n",
      "Generation 7085: p = 0.9584800063324658\n",
      "Generation 7085: M(n) = 862.6320056992192\n",
      "Generation 7086: p = 0.9584800063324658\n",
      "Generation 7086: M(n) = 862.6320056992192\n",
      "Generation 7087: p = 0.9584800063324658\n",
      "Generation 7087: M(n) = 862.6320056992192\n",
      "Generation 7088: p = 0.9584800063324658\n",
      "Generation 7088: M(n) = 862.6320056992192\n",
      "Generation 7089: p = 0.9584800063324658\n",
      "Generation 7089: M(n) = 862.6320056992192\n",
      "Generation 7090: p = 0.9584800063324658\n",
      "Generation 7090: M(n) = 862.6320056992192\n",
      "Generation 7091: p = 0.9584800063324658\n",
      "Generation 7091: M(n) = 862.6320056992192\n",
      "Generation 7092: p = 0.9584800063324658\n",
      "Generation 7092: M(n) = 862.6320056992192\n",
      "Generation 7093: p = 0.9584800063324658\n",
      "Generation 7093: M(n) = 862.6320056992192\n",
      "Generation 7094: p = 0.9584800063324658\n",
      "Generation 7094: M(n) = 862.6320056992192\n",
      "Generation 7095: p = 0.9584800063324658\n",
      "Generation 7095: M(n) = 862.6320056992192\n",
      "Generation 7096: p = 0.9584800063324658\n",
      "Generation 7096: M(n) = 862.6320056992192\n",
      "Generation 7097: p = 0.9584800063324658\n",
      "Generation 7097: M(n) = 862.6320056992192\n",
      "Generation 7098: p = 0.9584800063324658\n",
      "Generation 7098: M(n) = 862.6320056992192\n",
      "Generation 7099: p = 0.9584800063324658\n",
      "Generation 7099: M(n) = 862.6320056992192\n",
      "Generation 7100: p = 0.9584800063324658\n",
      "Generation 7100: M(n) = 862.6320056992192\n",
      "Generation 7101: p = 0.9584800063324658\n",
      "Generation 7101: M(n) = 862.6320056992192\n",
      "Generation 7102: p = 0.9584800063324658\n",
      "Generation 7102: M(n) = 862.6320056992192\n",
      "Generation 7103: p = 0.9584800063324658\n",
      "Generation 7103: M(n) = 862.6320056992192\n",
      "Generation 7104: p = 0.9584800063324658\n",
      "Generation 7104: M(n) = 862.6320056992192\n",
      "Generation 7105: p = 0.9584800063324658\n",
      "Generation 7105: M(n) = 862.6320056992192\n",
      "Generation 7106: p = 0.9584800063324658\n",
      "Generation 7106: M(n) = 862.6320056992192\n",
      "Generation 7107: p = 0.9584800063324658\n",
      "Generation 7107: M(n) = 862.6320056992192\n",
      "Generation 7108: p = 0.9584800063324658\n",
      "Generation 7108: M(n) = 862.6320056992192\n",
      "Generation 7109: p = 0.9584800063324658\n",
      "Generation 7109: M(n) = 862.6320056992192\n",
      "Generation 7110: p = 0.9584800063324658\n",
      "Generation 7110: M(n) = 862.6320056992192\n",
      "Generation 7111: p = 0.9584800063324658\n",
      "Generation 7111: M(n) = 862.6320056992192\n",
      "Generation 7112: p = 0.9584800063324658\n",
      "Generation 7112: M(n) = 862.6320056992192\n",
      "Generation 7113: p = 0.9584800063324658\n",
      "Generation 7113: M(n) = 862.6320056992192\n",
      "Generation 7114: p = 0.9584800063324658\n",
      "Generation 7114: M(n) = 862.6320056992192\n",
      "Generation 7115: p = 0.9584800063324658\n",
      "Generation 7115: M(n) = 862.6320056992192\n",
      "Generation 7116: p = 0.9584800063324658\n",
      "Generation 7116: M(n) = 862.6320056992192\n",
      "Generation 7117: p = 0.9584800063324658\n",
      "Generation 7117: M(n) = 862.6320056992192\n",
      "Generation 7118: p = 0.9584800063324658\n",
      "Generation 7118: M(n) = 862.6320056992192\n",
      "Generation 7119: p = 0.9584800063324658\n",
      "Generation 7119: M(n) = 862.6320056992192\n",
      "Generation 7120: p = 0.9584800063324658\n",
      "Generation 7120: M(n) = 862.6320056992192\n",
      "Generation 7121: p = 0.9584800063324658\n",
      "Generation 7121: M(n) = 862.6320056992192\n",
      "Generation 7122: p = 0.9584800063324658\n",
      "Generation 7122: M(n) = 862.6320056992192\n",
      "Generation 7123: p = 0.9584800063324658\n",
      "Generation 7123: M(n) = 862.6320056992192\n",
      "Generation 7124: p = 0.9584800063324658\n",
      "Generation 7124: M(n) = 862.6320056992192\n",
      "Generation 7125: p = 0.9584800063324658\n",
      "Generation 7125: M(n) = 862.6320056992192\n",
      "Generation 7126: p = 0.9584800063324658\n",
      "Generation 7126: M(n) = 862.6320056992192\n",
      "Generation 7127: p = 0.9584800063324658\n",
      "Generation 7127: M(n) = 862.6320056992192\n",
      "Generation 7128: p = 0.9584800063324658\n",
      "Generation 7128: M(n) = 862.6320056992192\n",
      "Generation 7129: p = 0.9584800063324658\n",
      "Generation 7129: M(n) = 862.6320056992192\n",
      "Generation 7130: p = 0.9584800063324658\n",
      "Generation 7130: M(n) = 862.6320056992192\n",
      "Generation 7131: p = 0.9584800063324658\n",
      "Generation 7131: M(n) = 862.6320056992192\n",
      "Generation 7132: p = 0.9584800063324658\n",
      "Generation 7132: M(n) = 862.6320056992192\n",
      "Generation 7133: p = 0.9584800063324658\n",
      "Generation 7133: M(n) = 862.6320056992192\n",
      "Generation 7134: p = 0.9584800063324658\n",
      "Generation 7134: M(n) = 862.6320056992192\n",
      "Generation 7135: p = 0.9584800063324658\n",
      "Generation 7135: M(n) = 862.6320056992192\n",
      "Generation 7136: p = 0.9584800063324658\n",
      "Generation 7136: M(n) = 862.6320056992192\n",
      "Generation 7137: p = 0.9584800063324658\n",
      "Generation 7137: M(n) = 862.6320056992192\n",
      "Generation 7138: p = 0.9584800063324658\n",
      "Generation 7138: M(n) = 862.6320056992192\n",
      "Generation 7139: p = 0.9584800063324658\n",
      "Generation 7139: M(n) = 862.6320056992192\n",
      "Generation 7140: p = 0.9584800063324658\n",
      "Generation 7140: M(n) = 862.6320056992192\n",
      "Generation 7141: p = 0.9584800063324658\n",
      "Generation 7141: M(n) = 862.6320056992192\n",
      "Generation 7142: p = 0.9584800063324658\n",
      "Generation 7142: M(n) = 862.6320056992192\n",
      "Generation 7143: p = 0.9584800063324658\n",
      "Generation 7143: M(n) = 862.6320056992192\n",
      "Generation 7144: p = 0.9584800063324658\n",
      "Generation 7144: M(n) = 862.6320056992192\n",
      "Generation 7145: p = 0.9584800063324658\n",
      "Generation 7145: M(n) = 862.6320056992192\n",
      "Generation 7146: p = 0.9584800063324658\n",
      "Generation 7146: M(n) = 862.6320056992192\n",
      "Generation 7147: p = 0.9584800063324658\n",
      "Generation 7147: M(n) = 862.6320056992192\n",
      "Generation 7148: p = 0.9584800063324658\n",
      "Generation 7148: M(n) = 862.6320056992192\n",
      "Generation 7149: p = 0.9584800063324658\n",
      "Generation 7149: M(n) = 862.6320056992192\n",
      "Generation 7150: p = 0.9584800063324658\n",
      "Generation 7150: M(n) = 862.6320056992192\n",
      "Generation 7151: p = 0.9584800063324658\n",
      "Generation 7151: M(n) = 862.6320056992192\n",
      "Generation 7152: p = 0.9584800063324658\n",
      "Generation 7152: M(n) = 862.6320056992192\n",
      "Generation 7153: p = 0.9584800063324658\n",
      "Generation 7153: M(n) = 862.6320056992192\n",
      "Generation 7154: p = 0.9584800063324658\n",
      "Generation 7154: M(n) = 862.6320056992192\n",
      "Generation 7155: p = 0.9584800063324658\n",
      "Generation 7155: M(n) = 862.6320056992192\n",
      "Generation 7156: p = 0.9584800063324658\n",
      "Generation 7156: M(n) = 862.6320056992192\n",
      "Generation 7157: p = 0.9584800063324658\n",
      "Generation 7157: M(n) = 862.6320056992192\n",
      "Generation 7158: p = 0.9584800063324658\n",
      "Generation 7158: M(n) = 862.6320056992192\n",
      "Generation 7159: p = 0.9584800063324658\n",
      "Generation 7159: M(n) = 862.6320056992192\n",
      "Generation 7160: p = 0.9584800063324658\n",
      "Generation 7160: M(n) = 862.6320056992192\n",
      "Generation 7161: p = 0.9584800063324658\n",
      "Generation 7161: M(n) = 862.6320056992192\n",
      "Generation 7162: p = 0.9584800063324658\n",
      "Generation 7162: M(n) = 862.6320056992192\n",
      "Generation 7163: p = 0.9584800063324658\n",
      "Generation 7163: M(n) = 862.6320056992192\n",
      "Generation 7164: p = 0.9584800063324658\n",
      "Generation 7164: M(n) = 862.6320056992192\n",
      "Generation 7165: p = 0.9584800063324658\n",
      "Generation 7165: M(n) = 862.6320056992192\n",
      "Generation 7166: p = 0.9584800063324658\n",
      "Generation 7166: M(n) = 862.6320056992192\n",
      "Generation 7167: p = 0.9584800063324658\n",
      "Generation 7167: M(n) = 862.6320056992192\n",
      "Generation 7168: p = 0.9584800063324658\n",
      "Generation 7168: M(n) = 862.6320056992192\n",
      "Generation 7169: p = 0.9584800063324658\n",
      "Generation 7169: M(n) = 862.6320056992192\n",
      "Generation 7170: p = 0.9584800063324658\n",
      "Generation 7170: M(n) = 862.6320056992192\n",
      "Generation 7171: p = 0.9584800063324658\n",
      "Generation 7171: M(n) = 862.6320056992192\n",
      "Generation 7172: p = 0.9584800063324658\n",
      "Generation 7172: M(n) = 862.6320056992192\n",
      "Generation 7173: p = 0.9584800063324658\n",
      "Generation 7173: M(n) = 862.6320056992192\n",
      "Generation 7174: p = 0.9584800063324658\n",
      "Generation 7174: M(n) = 862.6320056992192\n",
      "Generation 7175: p = 0.9584800063324658\n",
      "Generation 7175: M(n) = 862.6320056992192\n",
      "Generation 7176: p = 0.9584800063324658\n",
      "Generation 7176: M(n) = 862.6320056992192\n",
      "Generation 7177: p = 0.9584800063324658\n",
      "Generation 7177: M(n) = 862.6320056992192\n",
      "Generation 7178: p = 0.9584800063324658\n",
      "Generation 7178: M(n) = 862.6320056992192\n",
      "Generation 7179: p = 0.9584800063324658\n",
      "Generation 7179: M(n) = 862.6320056992192\n",
      "Generation 7180: p = 0.9584800063324658\n",
      "Generation 7180: M(n) = 862.6320056992192\n",
      "Generation 7181: p = 0.9584800063324658\n",
      "Generation 7181: M(n) = 862.6320056992192\n",
      "Generation 7182: p = 0.9584800063324658\n",
      "Generation 7182: M(n) = 862.6320056992192\n",
      "Generation 7183: p = 0.9584800063324658\n",
      "Generation 7183: M(n) = 862.6320056992192\n",
      "Generation 7184: p = 0.9584800063324658\n",
      "Generation 7184: M(n) = 862.6320056992192\n",
      "Generation 7185: p = 0.9584800063324658\n",
      "Generation 7185: M(n) = 862.6320056992192\n",
      "Generation 7186: p = 0.9584800063324658\n",
      "Generation 7186: M(n) = 862.6320056992192\n",
      "Generation 7187: p = 0.9584800063324658\n",
      "Generation 7187: M(n) = 862.6320056992192\n",
      "Generation 7188: p = 0.9584800063324658\n",
      "Generation 7188: M(n) = 862.6320056992192\n",
      "Generation 7189: p = 0.9584800063324658\n",
      "Generation 7189: M(n) = 862.6320056992192\n",
      "Generation 7190: p = 0.9584800063324658\n",
      "Generation 7190: M(n) = 862.6320056992192\n",
      "Generation 7191: p = 0.9584800063324658\n",
      "Generation 7191: M(n) = 862.6320056992192\n",
      "Generation 7192: p = 0.9584800063324658\n",
      "Generation 7192: M(n) = 862.6320056992192\n",
      "Generation 7193: p = 0.9584800063324658\n",
      "Generation 7193: M(n) = 862.6320056992192\n",
      "Generation 7194: p = 0.9584800063324658\n",
      "Generation 7194: M(n) = 862.6320056992192\n",
      "Generation 7195: p = 0.9584800063324658\n",
      "Generation 7195: M(n) = 862.6320056992192\n",
      "Generation 7196: p = 0.9584800063324658\n",
      "Generation 7196: M(n) = 862.6320056992192\n",
      "Generation 7197: p = 0.9584800063324658\n",
      "Generation 7197: M(n) = 862.6320056992192\n",
      "Generation 7198: p = 0.9584800063324658\n",
      "Generation 7198: M(n) = 862.6320056992192\n",
      "Generation 7199: p = 0.9584800063324658\n",
      "Generation 7199: M(n) = 862.6320056992192\n",
      "Generation 7200: p = 0.9584800063324658\n",
      "Generation 7200: M(n) = 862.6320056992192\n",
      "Generation 7201: p = 0.9584800063324658\n",
      "Generation 7201: M(n) = 862.6320056992192\n",
      "Generation 7202: p = 0.9584800063324658\n",
      "Generation 7202: M(n) = 862.6320056992192\n",
      "Generation 7203: p = 0.9584800063324658\n",
      "Generation 7203: M(n) = 862.6320056992192\n",
      "Generation 7204: p = 0.9584800063324658\n",
      "Generation 7204: M(n) = 862.6320056992192\n",
      "Generation 7205: p = 0.9584800063324658\n",
      "Generation 7205: M(n) = 862.6320056992192\n",
      "Generation 7206: p = 0.9584800063324658\n",
      "Generation 7206: M(n) = 862.6320056992192\n",
      "Generation 7207: p = 0.9584800063324658\n",
      "Generation 7207: M(n) = 862.6320056992192\n",
      "Generation 7208: p = 0.9584800063324658\n",
      "Generation 7208: M(n) = 862.6320056992192\n",
      "Generation 7209: p = 0.9584800063324658\n",
      "Generation 7209: M(n) = 862.6320056992192\n",
      "Generation 7210: p = 0.9584800063324658\n",
      "Generation 7210: M(n) = 862.6320056992192\n",
      "Generation 7211: p = 0.9584800063324658\n",
      "Generation 7211: M(n) = 862.6320056992192\n",
      "Generation 7212: p = 0.9584800063324658\n",
      "Generation 7212: M(n) = 862.6320056992192\n",
      "Generation 7213: p = 0.9584800063324658\n",
      "Generation 7213: M(n) = 862.6320056992192\n",
      "Generation 7214: p = 0.9584800063324658\n",
      "Generation 7214: M(n) = 862.6320056992192\n",
      "Generation 7215: p = 0.9584800063324658\n",
      "Generation 7215: M(n) = 862.6320056992192\n",
      "Generation 7216: p = 0.9584800063324658\n",
      "Generation 7216: M(n) = 862.6320056992192\n",
      "Generation 7217: p = 0.9584800063324658\n",
      "Generation 7217: M(n) = 862.6320056992192\n",
      "Generation 7218: p = 0.9584800063324658\n",
      "Generation 7218: M(n) = 862.6320056992192\n",
      "Generation 7219: p = 0.9584800063324658\n",
      "Generation 7219: M(n) = 862.6320056992192\n",
      "Generation 7220: p = 0.9584800063324658\n",
      "Generation 7220: M(n) = 862.6320056992192\n",
      "Generation 7221: p = 0.9584800063324658\n",
      "Generation 7221: M(n) = 862.6320056992192\n",
      "Generation 7222: p = 0.9584800063324658\n",
      "Generation 7222: M(n) = 862.6320056992192\n",
      "Generation 7223: p = 0.9584800063324658\n",
      "Generation 7223: M(n) = 862.6320056992192\n",
      "Generation 7224: p = 0.9584800063324658\n",
      "Generation 7224: M(n) = 862.6320056992192\n",
      "Generation 7225: p = 0.9584800063324658\n",
      "Generation 7225: M(n) = 862.6320056992192\n",
      "Generation 7226: p = 0.9584800063324658\n",
      "Generation 7226: M(n) = 862.6320056992192\n",
      "Generation 7227: p = 0.9584800063324658\n",
      "Generation 7227: M(n) = 862.6320056992192\n",
      "Generation 7228: p = 0.9584800063324658\n",
      "Generation 7228: M(n) = 862.6320056992192\n",
      "Generation 7229: p = 0.9584800063324658\n",
      "Generation 7229: M(n) = 862.6320056992192\n",
      "Generation 7230: p = 0.9584800063324658\n",
      "Generation 7230: M(n) = 862.6320056992192\n",
      "Generation 7231: p = 0.9584800063324658\n",
      "Generation 7231: M(n) = 862.6320056992192\n",
      "Generation 7232: p = 0.9584800063324658\n",
      "Generation 7232: M(n) = 862.6320056992192\n",
      "Generation 7233: p = 0.9584800063324658\n",
      "Generation 7233: M(n) = 862.6320056992192\n",
      "Generation 7234: p = 0.9584800063324658\n",
      "Generation 7234: M(n) = 862.6320056992192\n",
      "Generation 7235: p = 0.9584800063324658\n",
      "Generation 7235: M(n) = 862.6320056992192\n",
      "Generation 7236: p = 0.9584800063324658\n",
      "Generation 7236: M(n) = 862.6320056992192\n",
      "Generation 7237: p = 0.9584800063324658\n",
      "Generation 7237: M(n) = 862.6320056992192\n",
      "Generation 7238: p = 0.9584800063324658\n",
      "Generation 7238: M(n) = 862.6320056992192\n",
      "Generation 7239: p = 0.9584800063324658\n",
      "Generation 7239: M(n) = 862.6320056992192\n",
      "Generation 7240: p = 0.9584800063324658\n",
      "Generation 7240: M(n) = 862.6320056992192\n",
      "Generation 7241: p = 0.9584800063324658\n",
      "Generation 7241: M(n) = 862.6320056992192\n",
      "Generation 7242: p = 0.9584800063324658\n",
      "Generation 7242: M(n) = 862.6320056992192\n",
      "Generation 7243: p = 0.9584800063324658\n",
      "Generation 7243: M(n) = 862.6320056992192\n",
      "Generation 7244: p = 0.9584800063324658\n",
      "Generation 7244: M(n) = 862.6320056992192\n",
      "Generation 7245: p = 0.9584800063324658\n",
      "Generation 7245: M(n) = 862.6320056992192\n",
      "Generation 7246: p = 0.9584800063324658\n",
      "Generation 7246: M(n) = 862.6320056992192\n",
      "Generation 7247: p = 0.9584800063324658\n",
      "Generation 7247: M(n) = 862.6320056992192\n",
      "Generation 7248: p = 0.9584800063324658\n",
      "Generation 7248: M(n) = 862.6320056992192\n",
      "Generation 7249: p = 0.9584800063324658\n",
      "Generation 7249: M(n) = 862.6320056992192\n",
      "Generation 7250: p = 0.9584800063324658\n",
      "Generation 7250: M(n) = 862.6320056992192\n",
      "Generation 7251: p = 0.9584800063324658\n",
      "Generation 7251: M(n) = 862.6320056992192\n",
      "Generation 7252: p = 0.9584800063324658\n",
      "Generation 7252: M(n) = 862.6320056992192\n",
      "Generation 7253: p = 0.9584800063324658\n",
      "Generation 7253: M(n) = 862.6320056992192\n",
      "Generation 7254: p = 0.9584800063324658\n",
      "Generation 7254: M(n) = 862.6320056992192\n",
      "Generation 7255: p = 0.9584800063324658\n",
      "Generation 7255: M(n) = 862.6320056992192\n",
      "Generation 7256: p = 0.9584800063324658\n",
      "Generation 7256: M(n) = 862.6320056992192\n",
      "Generation 7257: p = 0.9584800063324658\n",
      "Generation 7257: M(n) = 862.6320056992192\n",
      "Generation 7258: p = 0.9584800063324658\n",
      "Generation 7258: M(n) = 862.6320056992192\n",
      "Generation 7259: p = 0.9584800063324658\n",
      "Generation 7259: M(n) = 862.6320056992192\n",
      "Generation 7260: p = 0.9584800063324658\n",
      "Generation 7260: M(n) = 862.6320056992192\n",
      "Generation 7261: p = 0.9584800063324658\n",
      "Generation 7261: M(n) = 862.6320056992192\n",
      "Generation 7262: p = 0.9584800063324658\n",
      "Generation 7262: M(n) = 862.6320056992192\n",
      "Generation 7263: p = 0.9584800063324658\n",
      "Generation 7263: M(n) = 862.6320056992192\n",
      "Generation 7264: p = 0.9584800063324658\n",
      "Generation 7264: M(n) = 862.6320056992192\n",
      "Generation 7265: p = 0.9584800063324658\n",
      "Generation 7265: M(n) = 862.6320056992192\n",
      "Generation 7266: p = 0.9584800063324658\n",
      "Generation 7266: M(n) = 862.6320056992192\n",
      "Generation 7267: p = 0.9584800063324658\n",
      "Generation 7267: M(n) = 862.6320056992192\n",
      "Generation 7268: p = 0.9584800063324658\n",
      "Generation 7268: M(n) = 862.6320056992192\n",
      "Generation 7269: p = 0.9584800063324658\n",
      "Generation 7269: M(n) = 862.6320056992192\n",
      "Generation 7270: p = 0.9584800063324658\n",
      "Generation 7270: M(n) = 862.6320056992192\n",
      "Generation 7271: p = 0.9584800063324658\n",
      "Generation 7271: M(n) = 862.6320056992192\n",
      "Generation 7272: p = 0.9584800063324658\n",
      "Generation 7272: M(n) = 862.6320056992192\n",
      "Generation 7273: p = 0.9584800063324658\n",
      "Generation 7273: M(n) = 862.6320056992192\n",
      "Generation 7274: p = 0.9584800063324658\n",
      "Generation 7274: M(n) = 862.6320056992192\n",
      "Generation 7275: p = 0.9584800063324658\n",
      "Generation 7275: M(n) = 862.6320056992192\n",
      "Generation 7276: p = 0.9584800063324658\n",
      "Generation 7276: M(n) = 862.6320056992192\n",
      "Generation 7277: p = 0.9584800063324658\n",
      "Generation 7277: M(n) = 862.6320056992192\n",
      "Generation 7278: p = 0.9584800063324658\n",
      "Generation 7278: M(n) = 862.6320056992192\n",
      "Generation 7279: p = 0.9584800063324658\n",
      "Generation 7279: M(n) = 862.6320056992192\n",
      "Generation 7280: p = 0.9584800063324658\n",
      "Generation 7280: M(n) = 862.6320056992192\n",
      "Generation 7281: p = 0.9584800063324658\n",
      "Generation 7281: M(n) = 862.6320056992192\n",
      "Generation 7282: p = 0.9584800063324658\n",
      "Generation 7282: M(n) = 862.6320056992192\n",
      "Generation 7283: p = 0.9584800063324658\n",
      "Generation 7283: M(n) = 862.6320056992192\n",
      "Generation 7284: p = 0.9584800063324658\n",
      "Generation 7284: M(n) = 862.6320056992192\n",
      "Generation 7285: p = 0.9584800063324658\n",
      "Generation 7285: M(n) = 862.6320056992192\n",
      "Generation 7286: p = 0.9584800063324658\n",
      "Generation 7286: M(n) = 862.6320056992192\n",
      "Generation 7287: p = 0.9584800063324658\n",
      "Generation 7287: M(n) = 862.6320056992192\n",
      "Generation 7288: p = 0.9584800063324658\n",
      "Generation 7288: M(n) = 862.6320056992192\n",
      "Generation 7289: p = 0.9584800063324658\n",
      "Generation 7289: M(n) = 862.6320056992192\n",
      "Generation 7290: p = 0.9584800063324658\n",
      "Generation 7290: M(n) = 862.6320056992192\n",
      "Generation 7291: p = 0.9584800063324658\n",
      "Generation 7291: M(n) = 862.6320056992192\n",
      "Generation 7292: p = 0.9584800063324658\n",
      "Generation 7292: M(n) = 862.6320056992192\n",
      "Generation 7293: p = 0.9584800063324658\n",
      "Generation 7293: M(n) = 862.6320056992192\n",
      "Generation 7294: p = 0.9584800063324658\n",
      "Generation 7294: M(n) = 862.6320056992192\n",
      "Generation 7295: p = 0.9584800063324658\n",
      "Generation 7295: M(n) = 862.6320056992192\n",
      "Generation 7296: p = 0.9584800063324658\n",
      "Generation 7296: M(n) = 862.6320056992192\n",
      "Generation 7297: p = 0.9584800063324658\n",
      "Generation 7297: M(n) = 862.6320056992192\n",
      "Generation 7298: p = 0.9584800063324658\n",
      "Generation 7298: M(n) = 862.6320056992192\n",
      "Generation 7299: p = 0.9584800063324658\n",
      "Generation 7299: M(n) = 862.6320056992192\n",
      "Generation 7300: p = 0.9584800063324658\n",
      "Generation 7300: M(n) = 862.6320056992192\n",
      "Generation 7301: p = 0.9584800063324658\n",
      "Generation 7301: M(n) = 862.6320056992192\n",
      "Generation 7302: p = 0.9584800063324658\n",
      "Generation 7302: M(n) = 862.6320056992192\n",
      "Generation 7303: p = 0.9584800063324658\n",
      "Generation 7303: M(n) = 862.6320056992192\n",
      "Generation 7304: p = 0.9584800063324658\n",
      "Generation 7304: M(n) = 862.6320056992192\n",
      "Generation 7305: p = 0.9584800063324658\n",
      "Generation 7305: M(n) = 862.6320056992192\n",
      "Generation 7306: p = 0.9584800063324658\n",
      "Generation 7306: M(n) = 862.6320056992192\n",
      "Generation 7307: p = 0.9584800063324658\n",
      "Generation 7307: M(n) = 862.6320056992192\n",
      "Generation 7308: p = 0.9584800063324658\n",
      "Generation 7308: M(n) = 862.6320056992192\n",
      "Generation 7309: p = 0.9584800063324658\n",
      "Generation 7309: M(n) = 862.6320056992192\n",
      "Generation 7310: p = 0.9584800063324658\n",
      "Generation 7310: M(n) = 862.6320056992192\n",
      "Generation 7311: p = 0.9584800063324658\n",
      "Generation 7311: M(n) = 862.6320056992192\n",
      "Generation 7312: p = 0.9584800063324658\n",
      "Generation 7312: M(n) = 862.6320056992192\n",
      "Generation 7313: p = 0.9584800063324658\n",
      "Generation 7313: M(n) = 862.6320056992192\n",
      "Generation 7314: p = 0.9584800063324658\n",
      "Generation 7314: M(n) = 862.6320056992192\n",
      "Generation 7315: p = 0.9584800063324658\n",
      "Generation 7315: M(n) = 862.6320056992192\n",
      "Generation 7316: p = 0.9584800063324658\n",
      "Generation 7316: M(n) = 862.6320056992192\n",
      "Generation 7317: p = 0.9584800063324658\n",
      "Generation 7317: M(n) = 862.6320056992192\n",
      "Generation 7318: p = 0.9584800063324658\n",
      "Generation 7318: M(n) = 862.6320056992192\n",
      "Generation 7319: p = 0.9584800063324658\n",
      "Generation 7319: M(n) = 862.6320056992192\n",
      "Generation 7320: p = 0.9584800063324658\n",
      "Generation 7320: M(n) = 862.6320056992192\n",
      "Generation 7321: p = 0.9584800063324658\n",
      "Generation 7321: M(n) = 862.6320056992192\n",
      "Generation 7322: p = 0.9584800063324658\n",
      "Generation 7322: M(n) = 862.6320056992192\n",
      "Generation 7323: p = 0.9584800063324658\n",
      "Generation 7323: M(n) = 862.6320056992192\n",
      "Generation 7324: p = 0.9584800063324658\n",
      "Generation 7324: M(n) = 862.6320056992192\n",
      "Generation 7325: p = 0.9584800063324658\n",
      "Generation 7325: M(n) = 862.6320056992192\n",
      "Generation 7326: p = 0.9584800063324658\n",
      "Generation 7326: M(n) = 862.6320056992192\n",
      "Generation 7327: p = 0.9584800063324658\n",
      "Generation 7327: M(n) = 862.6320056992192\n",
      "Generation 7328: p = 0.9584800063324658\n",
      "Generation 7328: M(n) = 862.6320056992192\n",
      "Generation 7329: p = 0.9584800063324658\n",
      "Generation 7329: M(n) = 862.6320056992192\n",
      "Generation 7330: p = 0.9584800063324658\n",
      "Generation 7330: M(n) = 862.6320056992192\n",
      "Generation 7331: p = 0.9584800063324658\n",
      "Generation 7331: M(n) = 862.6320056992192\n",
      "Generation 7332: p = 0.9584800063324658\n",
      "Generation 7332: M(n) = 862.6320056992192\n",
      "Generation 7333: p = 0.9584800063324658\n",
      "Generation 7333: M(n) = 862.6320056992192\n",
      "Generation 7334: p = 0.9584800063324658\n",
      "Generation 7334: M(n) = 862.6320056992192\n",
      "Generation 7335: p = 0.9584800063324658\n",
      "Generation 7335: M(n) = 862.6320056992192\n",
      "Generation 7336: p = 0.9584800063324658\n",
      "Generation 7336: M(n) = 862.6320056992192\n",
      "Generation 7337: p = 0.9584800063324658\n",
      "Generation 7337: M(n) = 862.6320056992192\n",
      "Generation 7338: p = 0.9584800063324658\n",
      "Generation 7338: M(n) = 862.6320056992192\n",
      "Generation 7339: p = 0.9584800063324658\n",
      "Generation 7339: M(n) = 862.6320056992192\n",
      "Generation 7340: p = 0.9584800063324658\n",
      "Generation 7340: M(n) = 862.6320056992192\n",
      "Generation 7341: p = 0.9584800063324658\n",
      "Generation 7341: M(n) = 862.6320056992192\n",
      "Generation 7342: p = 0.9584800063324658\n",
      "Generation 7342: M(n) = 862.6320056992192\n",
      "Generation 7343: p = 0.9584800063324658\n",
      "Generation 7343: M(n) = 862.6320056992192\n",
      "Generation 7344: p = 0.9584800063324658\n",
      "Generation 7344: M(n) = 862.6320056992192\n",
      "Generation 7345: p = 0.9584800063324658\n",
      "Generation 7345: M(n) = 862.6320056992192\n",
      "Generation 7346: p = 0.9584800063324658\n",
      "Generation 7346: M(n) = 862.6320056992192\n",
      "Generation 7347: p = 0.9584800063324658\n",
      "Generation 7347: M(n) = 862.6320056992192\n",
      "Generation 7348: p = 0.9584800063324658\n",
      "Generation 7348: M(n) = 862.6320056992192\n",
      "Generation 7349: p = 0.9584800063324658\n",
      "Generation 7349: M(n) = 862.6320056992192\n",
      "Generation 7350: p = 0.9584800063324658\n",
      "Generation 7350: M(n) = 862.6320056992192\n",
      "Generation 7351: p = 0.9584800063324658\n",
      "Generation 7351: M(n) = 862.6320056992192\n",
      "Generation 7352: p = 0.9584800063324658\n",
      "Generation 7352: M(n) = 862.6320056992192\n",
      "Generation 7353: p = 0.9584800063324658\n",
      "Generation 7353: M(n) = 862.6320056992192\n",
      "Generation 7354: p = 0.9584800063324658\n",
      "Generation 7354: M(n) = 862.6320056992192\n",
      "Generation 7355: p = 0.9584800063324658\n",
      "Generation 7355: M(n) = 862.6320056992192\n",
      "Generation 7356: p = 0.9584800063324658\n",
      "Generation 7356: M(n) = 862.6320056992192\n",
      "Generation 7357: p = 0.9584800063324658\n",
      "Generation 7357: M(n) = 862.6320056992192\n",
      "Generation 7358: p = 0.9584800063324658\n",
      "Generation 7358: M(n) = 862.6320056992192\n",
      "Generation 7359: p = 0.9584800063324658\n",
      "Generation 7359: M(n) = 862.6320056992192\n",
      "Generation 7360: p = 0.9584800063324658\n",
      "Generation 7360: M(n) = 862.6320056992192\n",
      "Generation 7361: p = 0.9584800063324658\n",
      "Generation 7361: M(n) = 862.6320056992192\n",
      "Generation 7362: p = 0.9584800063324658\n",
      "Generation 7362: M(n) = 862.6320056992192\n",
      "Generation 7363: p = 0.9584800063324658\n",
      "Generation 7363: M(n) = 862.6320056992192\n",
      "Generation 7364: p = 0.9584800063324658\n",
      "Generation 7364: M(n) = 862.6320056992192\n",
      "Generation 7365: p = 0.9584800063324658\n",
      "Generation 7365: M(n) = 862.6320056992192\n",
      "Generation 7366: p = 0.9584800063324658\n",
      "Generation 7366: M(n) = 862.6320056992192\n",
      "Generation 7367: p = 0.9584800063324658\n",
      "Generation 7367: M(n) = 862.6320056992192\n",
      "Generation 7368: p = 0.9584800063324658\n",
      "Generation 7368: M(n) = 862.6320056992192\n",
      "Generation 7369: p = 0.9584800063324658\n",
      "Generation 7369: M(n) = 862.6320056992192\n",
      "Generation 7370: p = 0.9584800063324658\n",
      "Generation 7370: M(n) = 862.6320056992192\n",
      "Generation 7371: p = 0.9584800063324658\n",
      "Generation 7371: M(n) = 862.6320056992192\n",
      "Generation 7372: p = 0.9584800063324658\n",
      "Generation 7372: M(n) = 862.6320056992192\n",
      "Generation 7373: p = 0.9584800063324658\n",
      "Generation 7373: M(n) = 862.6320056992192\n",
      "Generation 7374: p = 0.9584800063324658\n",
      "Generation 7374: M(n) = 862.6320056992192\n",
      "Generation 7375: p = 0.9584800063324658\n",
      "Generation 7375: M(n) = 862.6320056992192\n",
      "Generation 7376: p = 0.9584800063324658\n",
      "Generation 7376: M(n) = 862.6320056992192\n",
      "Generation 7377: p = 0.9584800063324658\n",
      "Generation 7377: M(n) = 862.6320056992192\n",
      "Generation 7378: p = 0.9584800063324658\n",
      "Generation 7378: M(n) = 862.6320056992192\n",
      "Generation 7379: p = 0.9584800063324658\n",
      "Generation 7379: M(n) = 862.6320056992192\n",
      "Generation 7380: p = 0.9584800063324658\n",
      "Generation 7380: M(n) = 862.6320056992192\n",
      "Generation 7381: p = 0.9584800063324658\n",
      "Generation 7381: M(n) = 862.6320056992192\n",
      "Generation 7382: p = 0.9584800063324658\n",
      "Generation 7382: M(n) = 862.6320056992192\n",
      "Generation 7383: p = 0.9584800063324658\n",
      "Generation 7383: M(n) = 862.6320056992192\n",
      "Generation 7384: p = 0.9584800063324658\n",
      "Generation 7384: M(n) = 862.6320056992192\n",
      "Generation 7385: p = 0.9584800063324658\n",
      "Generation 7385: M(n) = 862.6320056992192\n",
      "Generation 7386: p = 0.9584800063324658\n",
      "Generation 7386: M(n) = 862.6320056992192\n",
      "Generation 7387: p = 0.9584800063324658\n",
      "Generation 7387: M(n) = 862.6320056992192\n",
      "Generation 7388: p = 0.9584800063324658\n",
      "Generation 7388: M(n) = 862.6320056992192\n",
      "Generation 7389: p = 0.9584800063324658\n",
      "Generation 7389: M(n) = 862.6320056992192\n",
      "Generation 7390: p = 0.9584800063324658\n",
      "Generation 7390: M(n) = 862.6320056992192\n",
      "Generation 7391: p = 0.9584800063324658\n",
      "Generation 7391: M(n) = 862.6320056992192\n",
      "Generation 7392: p = 0.9584800063324658\n",
      "Generation 7392: M(n) = 862.6320056992192\n",
      "Generation 7393: p = 0.9584800063324658\n",
      "Generation 7393: M(n) = 862.6320056992192\n",
      "Generation 7394: p = 0.9584800063324658\n",
      "Generation 7394: M(n) = 862.6320056992192\n",
      "Generation 7395: p = 0.9584800063324658\n",
      "Generation 7395: M(n) = 862.6320056992192\n",
      "Generation 7396: p = 0.9584800063324658\n",
      "Generation 7396: M(n) = 862.6320056992192\n",
      "Generation 7397: p = 0.9584800063324658\n",
      "Generation 7397: M(n) = 862.6320056992192\n",
      "Generation 7398: p = 0.9584800063324658\n",
      "Generation 7398: M(n) = 862.6320056992192\n",
      "Generation 7399: p = 0.9584800063324658\n",
      "Generation 7399: M(n) = 862.6320056992192\n",
      "Generation 7400: p = 0.9584800063324658\n",
      "Generation 7400: M(n) = 862.6320056992192\n",
      "Generation 7401: p = 0.9584800063324658\n",
      "Generation 7401: M(n) = 862.6320056992192\n",
      "Generation 7402: p = 0.9584800063324658\n",
      "Generation 7402: M(n) = 862.6320056992192\n",
      "Generation 7403: p = 0.9584800063324658\n",
      "Generation 7403: M(n) = 862.6320056992192\n",
      "Generation 7404: p = 0.9584800063324658\n",
      "Generation 7404: M(n) = 862.6320056992192\n",
      "Generation 7405: p = 0.9584800063324658\n",
      "Generation 7405: M(n) = 862.6320056992192\n",
      "Generation 7406: p = 0.9584800063324658\n",
      "Generation 7406: M(n) = 862.6320056992192\n",
      "Generation 7407: p = 0.9584800063324658\n",
      "Generation 7407: M(n) = 862.6320056992192\n",
      "Generation 7408: p = 0.9584800063324658\n",
      "Generation 7408: M(n) = 862.6320056992192\n",
      "Generation 7409: p = 0.9584800063324658\n",
      "Generation 7409: M(n) = 862.6320056992192\n",
      "Generation 7410: p = 0.9584800063324658\n",
      "Generation 7410: M(n) = 862.6320056992192\n",
      "Generation 7411: p = 0.9584800063324658\n",
      "Generation 7411: M(n) = 862.6320056992192\n",
      "Generation 7412: p = 0.9584800063324658\n",
      "Generation 7412: M(n) = 862.6320056992192\n",
      "Generation 7413: p = 0.9584800063324658\n",
      "Generation 7413: M(n) = 862.6320056992192\n",
      "Generation 7414: p = 0.9584800063324658\n",
      "Generation 7414: M(n) = 862.6320056992192\n",
      "Generation 7415: p = 0.9584800063324658\n",
      "Generation 7415: M(n) = 862.6320056992192\n",
      "Generation 7416: p = 0.9584800063324658\n",
      "Generation 7416: M(n) = 862.6320056992192\n",
      "Generation 7417: p = 0.9584800063324658\n",
      "Generation 7417: M(n) = 862.6320056992192\n",
      "Generation 7418: p = 0.9584800063324658\n",
      "Generation 7418: M(n) = 862.6320056992192\n",
      "Generation 7419: p = 0.9584800063324658\n",
      "Generation 7419: M(n) = 862.6320056992192\n",
      "Generation 7420: p = 0.9584800063324658\n",
      "Generation 7420: M(n) = 862.6320056992192\n",
      "Generation 7421: p = 0.9584800063324658\n",
      "Generation 7421: M(n) = 862.6320056992192\n",
      "Generation 7422: p = 0.9584800063324658\n",
      "Generation 7422: M(n) = 862.6320056992192\n",
      "Generation 7423: p = 0.9584800063324658\n",
      "Generation 7423: M(n) = 862.6320056992192\n",
      "Generation 7424: p = 0.9584800063324658\n",
      "Generation 7424: M(n) = 862.6320056992192\n",
      "Generation 7425: p = 0.9584800063324658\n",
      "Generation 7425: M(n) = 862.6320056992192\n",
      "Generation 7426: p = 0.9584800063324658\n",
      "Generation 7426: M(n) = 862.6320056992192\n",
      "Generation 7427: p = 0.9584800063324658\n",
      "Generation 7427: M(n) = 862.6320056992192\n",
      "Generation 7428: p = 0.9584800063324658\n",
      "Generation 7428: M(n) = 862.6320056992192\n",
      "Generation 7429: p = 0.9584800063324658\n",
      "Generation 7429: M(n) = 862.6320056992192\n",
      "Generation 7430: p = 0.9584800063324658\n",
      "Generation 7430: M(n) = 862.6320056992192\n",
      "Generation 7431: p = 0.9584800063324658\n",
      "Generation 7431: M(n) = 862.6320056992192\n",
      "Generation 7432: p = 0.9584800063324658\n",
      "Generation 7432: M(n) = 862.6320056992192\n",
      "Generation 7433: p = 0.9584800063324658\n",
      "Generation 7433: M(n) = 862.6320056992192\n",
      "Generation 7434: p = 0.9584800063324658\n",
      "Generation 7434: M(n) = 862.6320056992192\n",
      "Generation 7435: p = 0.9584800063324658\n",
      "Generation 7435: M(n) = 862.6320056992192\n",
      "Generation 7436: p = 0.9584800063324658\n",
      "Generation 7436: M(n) = 862.6320056992192\n",
      "Generation 7437: p = 0.9584800063324658\n",
      "Generation 7437: M(n) = 862.6320056992192\n",
      "Generation 7438: p = 0.9584800063324658\n",
      "Generation 7438: M(n) = 862.6320056992192\n",
      "Generation 7439: p = 0.9584800063324658\n",
      "Generation 7439: M(n) = 862.6320056992192\n",
      "Generation 7440: p = 0.9584800063324658\n",
      "Generation 7440: M(n) = 862.6320056992192\n",
      "Generation 7441: p = 0.9584800063324658\n",
      "Generation 7441: M(n) = 862.6320056992192\n",
      "Generation 7442: p = 0.9584800063324658\n",
      "Generation 7442: M(n) = 862.6320056992192\n",
      "Generation 7443: p = 0.9584800063324658\n",
      "Generation 7443: M(n) = 862.6320056992192\n",
      "Generation 7444: p = 0.9584800063324658\n",
      "Generation 7444: M(n) = 862.6320056992192\n",
      "Generation 7445: p = 0.9584800063324658\n",
      "Generation 7445: M(n) = 862.6320056992192\n",
      "Generation 7446: p = 0.9584800063324658\n",
      "Generation 7446: M(n) = 862.6320056992192\n",
      "Generation 7447: p = 0.9584800063324658\n",
      "Generation 7447: M(n) = 862.6320056992192\n",
      "Generation 7448: p = 0.9584800063324658\n",
      "Generation 7448: M(n) = 862.6320056992192\n",
      "Generation 7449: p = 0.9584800063324658\n",
      "Generation 7449: M(n) = 862.6320056992192\n",
      "Generation 7450: p = 0.9584800063324658\n",
      "Generation 7450: M(n) = 862.6320056992192\n",
      "Generation 7451: p = 0.9584800063324658\n",
      "Generation 7451: M(n) = 862.6320056992192\n",
      "Generation 7452: p = 0.9584800063324658\n",
      "Generation 7452: M(n) = 862.6320056992192\n",
      "Generation 7453: p = 0.9584800063324658\n",
      "Generation 7453: M(n) = 862.6320056992192\n",
      "Generation 7454: p = 0.9584800063324658\n",
      "Generation 7454: M(n) = 862.6320056992192\n",
      "Generation 7455: p = 0.9584800063324658\n",
      "Generation 7455: M(n) = 862.6320056992192\n",
      "Generation 7456: p = 0.9584800063324658\n",
      "Generation 7456: M(n) = 862.6320056992192\n",
      "Generation 7457: p = 0.9584800063324658\n",
      "Generation 7457: M(n) = 862.6320056992192\n",
      "Generation 7458: p = 0.9584800063324658\n",
      "Generation 7458: M(n) = 862.6320056992192\n",
      "Generation 7459: p = 0.9584800063324658\n",
      "Generation 7459: M(n) = 862.6320056992192\n",
      "Generation 7460: p = 0.9584800063324658\n",
      "Generation 7460: M(n) = 862.6320056992192\n",
      "Generation 7461: p = 0.9584800063324658\n",
      "Generation 7461: M(n) = 862.6320056992192\n",
      "Generation 7462: p = 0.9584800063324658\n",
      "Generation 7462: M(n) = 862.6320056992192\n",
      "Generation 7463: p = 0.9584800063324658\n",
      "Generation 7463: M(n) = 862.6320056992192\n",
      "Generation 7464: p = 0.9584800063324658\n",
      "Generation 7464: M(n) = 862.6320056992192\n",
      "Generation 7465: p = 0.9584800063324658\n",
      "Generation 7465: M(n) = 862.6320056992192\n",
      "Generation 7466: p = 0.9584800063324658\n",
      "Generation 7466: M(n) = 862.6320056992192\n",
      "Generation 7467: p = 0.9584800063324658\n",
      "Generation 7467: M(n) = 862.6320056992192\n",
      "Generation 7468: p = 0.9584800063324658\n",
      "Generation 7468: M(n) = 862.6320056992192\n",
      "Generation 7469: p = 0.9584800063324658\n",
      "Generation 7469: M(n) = 862.6320056992192\n",
      "Generation 7470: p = 0.9584800063324658\n",
      "Generation 7470: M(n) = 862.6320056992192\n",
      "Generation 7471: p = 0.9584800063324658\n",
      "Generation 7471: M(n) = 862.6320056992192\n",
      "Generation 7472: p = 0.9584800063324658\n",
      "Generation 7472: M(n) = 862.6320056992192\n",
      "Generation 7473: p = 0.9584800063324658\n",
      "Generation 7473: M(n) = 862.6320056992192\n",
      "Generation 7474: p = 0.9584800063324658\n",
      "Generation 7474: M(n) = 862.6320056992192\n",
      "Generation 7475: p = 0.9584800063324658\n",
      "Generation 7475: M(n) = 862.6320056992192\n",
      "Generation 7476: p = 0.9584800063324658\n",
      "Generation 7476: M(n) = 862.6320056992192\n",
      "Generation 7477: p = 0.9584800063324658\n",
      "Generation 7477: M(n) = 862.6320056992192\n",
      "Generation 7478: p = 0.9584800063324658\n",
      "Generation 7478: M(n) = 862.6320056992192\n",
      "Generation 7479: p = 0.9584800063324658\n",
      "Generation 7479: M(n) = 862.6320056992192\n",
      "Generation 7480: p = 0.9584800063324658\n",
      "Generation 7480: M(n) = 862.6320056992192\n",
      "Generation 7481: p = 0.9584800063324658\n",
      "Generation 7481: M(n) = 862.6320056992192\n",
      "Generation 7482: p = 0.9584800063324658\n",
      "Generation 7482: M(n) = 862.6320056992192\n",
      "Generation 7483: p = 0.9584800063324658\n",
      "Generation 7483: M(n) = 862.6320056992192\n",
      "Generation 7484: p = 0.9584800063324658\n",
      "Generation 7484: M(n) = 862.6320056992192\n",
      "Generation 7485: p = 0.9584800063324658\n",
      "Generation 7485: M(n) = 862.6320056992192\n",
      "Generation 7486: p = 0.9584800063324658\n",
      "Generation 7486: M(n) = 862.6320056992192\n",
      "Generation 7487: p = 0.9584800063324658\n",
      "Generation 7487: M(n) = 862.6320056992192\n",
      "Generation 7488: p = 0.9584800063324658\n",
      "Generation 7488: M(n) = 862.6320056992192\n",
      "Generation 7489: p = 0.9584800063324658\n",
      "Generation 7489: M(n) = 862.6320056992192\n",
      "Generation 7490: p = 0.9584800063324658\n",
      "Generation 7490: M(n) = 862.6320056992192\n",
      "Generation 7491: p = 0.9584800063324658\n",
      "Generation 7491: M(n) = 862.6320056992192\n",
      "Generation 7492: p = 0.9584800063324658\n",
      "Generation 7492: M(n) = 862.6320056992192\n",
      "Generation 7493: p = 0.9584800063324658\n",
      "Generation 7493: M(n) = 862.6320056992192\n",
      "Generation 7494: p = 0.9584800063324658\n",
      "Generation 7494: M(n) = 862.6320056992192\n",
      "Generation 7495: p = 0.9584800063324658\n",
      "Generation 7495: M(n) = 862.6320056992192\n",
      "Generation 7496: p = 0.9584800063324658\n",
      "Generation 7496: M(n) = 862.6320056992192\n",
      "Generation 7497: p = 0.9584800063324658\n",
      "Generation 7497: M(n) = 862.6320056992192\n",
      "Generation 7498: p = 0.9584800063324658\n",
      "Generation 7498: M(n) = 862.6320056992192\n",
      "Generation 7499: p = 0.9584800063324658\n",
      "Generation 7499: M(n) = 862.6320056992192\n",
      "Generation 7500: p = 0.9584800063324658\n",
      "Generation 7500: M(n) = 862.6320056992192\n",
      "Generation 7501: p = 0.9584800063324658\n",
      "Generation 7501: M(n) = 862.6320056992192\n",
      "Generation 7502: p = 0.9584800063324658\n",
      "Generation 7502: M(n) = 862.6320056992192\n",
      "Generation 7503: p = 0.9584800063324658\n",
      "Generation 7503: M(n) = 862.6320056992192\n",
      "Generation 7504: p = 0.9584800063324658\n",
      "Generation 7504: M(n) = 862.6320056992192\n",
      "Generation 7505: p = 0.9584800063324658\n",
      "Generation 7505: M(n) = 862.6320056992192\n",
      "Generation 7506: p = 0.9584800063324658\n",
      "Generation 7506: M(n) = 862.6320056992192\n",
      "Generation 7507: p = 0.9584800063324658\n",
      "Generation 7507: M(n) = 862.6320056992192\n",
      "Generation 7508: p = 0.9584800063324658\n",
      "Generation 7508: M(n) = 862.6320056992192\n",
      "Generation 7509: p = 0.9584800063324658\n",
      "Generation 7509: M(n) = 862.6320056992192\n",
      "Generation 7510: p = 0.9584800063324658\n",
      "Generation 7510: M(n) = 862.6320056992192\n",
      "Generation 7511: p = 0.9584800063324658\n",
      "Generation 7511: M(n) = 862.6320056992192\n",
      "Generation 7512: p = 0.9584800063324658\n",
      "Generation 7512: M(n) = 862.6320056992192\n",
      "Generation 7513: p = 0.9584800063324658\n",
      "Generation 7513: M(n) = 862.6320056992192\n",
      "Generation 7514: p = 0.9584800063324658\n",
      "Generation 7514: M(n) = 862.6320056992192\n",
      "Generation 7515: p = 0.9584800063324658\n",
      "Generation 7515: M(n) = 862.6320056992192\n",
      "Generation 7516: p = 0.9584800063324658\n",
      "Generation 7516: M(n) = 862.6320056992192\n",
      "Generation 7517: p = 0.9584800063324658\n",
      "Generation 7517: M(n) = 862.6320056992192\n",
      "Generation 7518: p = 0.9584800063324658\n",
      "Generation 7518: M(n) = 862.6320056992192\n",
      "Generation 7519: p = 0.9584800063324658\n",
      "Generation 7519: M(n) = 862.6320056992192\n",
      "Generation 7520: p = 0.9584800063324658\n",
      "Generation 7520: M(n) = 862.6320056992192\n",
      "Generation 7521: p = 0.9584800063324658\n",
      "Generation 7521: M(n) = 862.6320056992192\n",
      "Generation 7522: p = 0.9584800063324658\n",
      "Generation 7522: M(n) = 862.6320056992192\n",
      "Generation 7523: p = 0.9584800063324658\n",
      "Generation 7523: M(n) = 862.6320056992192\n",
      "Generation 7524: p = 0.9584800063324658\n",
      "Generation 7524: M(n) = 862.6320056992192\n",
      "Generation 7525: p = 0.9584800063324658\n",
      "Generation 7525: M(n) = 862.6320056992192\n",
      "Generation 7526: p = 0.9584800063324658\n",
      "Generation 7526: M(n) = 862.6320056992192\n",
      "Generation 7527: p = 0.9584800063324658\n",
      "Generation 7527: M(n) = 862.6320056992192\n",
      "Generation 7528: p = 0.9584800063324658\n",
      "Generation 7528: M(n) = 862.6320056992192\n",
      "Generation 7529: p = 0.9584800063324658\n",
      "Generation 7529: M(n) = 862.6320056992192\n",
      "Generation 7530: p = 0.9584800063324658\n",
      "Generation 7530: M(n) = 862.6320056992192\n",
      "Generation 7531: p = 0.9584800063324658\n",
      "Generation 7531: M(n) = 862.6320056992192\n",
      "Generation 7532: p = 0.9584800063324658\n",
      "Generation 7532: M(n) = 862.6320056992192\n",
      "Generation 7533: p = 0.9584800063324658\n",
      "Generation 7533: M(n) = 862.6320056992192\n",
      "Generation 7534: p = 0.9584800063324658\n",
      "Generation 7534: M(n) = 862.6320056992192\n",
      "Generation 7535: p = 0.9584800063324658\n",
      "Generation 7535: M(n) = 862.6320056992192\n",
      "Generation 7536: p = 0.9584800063324658\n",
      "Generation 7536: M(n) = 862.6320056992192\n",
      "Generation 7537: p = 0.9584800063324658\n",
      "Generation 7537: M(n) = 862.6320056992192\n",
      "Generation 7538: p = 0.9584800063324658\n",
      "Generation 7538: M(n) = 862.6320056992192\n",
      "Generation 7539: p = 0.9584800063324658\n",
      "Generation 7539: M(n) = 862.6320056992192\n",
      "Generation 7540: p = 0.9584800063324658\n",
      "Generation 7540: M(n) = 862.6320056992192\n",
      "Generation 7541: p = 0.9584800063324658\n",
      "Generation 7541: M(n) = 862.6320056992192\n",
      "Generation 7542: p = 0.9584800063324658\n",
      "Generation 7542: M(n) = 862.6320056992192\n",
      "Generation 7543: p = 0.9584800063324658\n",
      "Generation 7543: M(n) = 862.6320056992192\n",
      "Generation 7544: p = 0.9584800063324658\n",
      "Generation 7544: M(n) = 862.6320056992192\n",
      "Generation 7545: p = 0.9584800063324658\n",
      "Generation 7545: M(n) = 862.6320056992192\n",
      "Generation 7546: p = 0.9584800063324658\n",
      "Generation 7546: M(n) = 862.6320056992192\n",
      "Generation 7547: p = 0.9584800063324658\n",
      "Generation 7547: M(n) = 862.6320056992192\n",
      "Generation 7548: p = 0.9584800063324658\n",
      "Generation 7548: M(n) = 862.6320056992192\n",
      "Generation 7549: p = 0.9584800063324658\n",
      "Generation 7549: M(n) = 862.6320056992192\n",
      "Generation 7550: p = 0.9584800063324658\n",
      "Generation 7550: M(n) = 862.6320056992192\n",
      "Generation 7551: p = 0.9584800063324658\n",
      "Generation 7551: M(n) = 862.6320056992192\n",
      "Generation 7552: p = 0.9584800063324658\n",
      "Generation 7552: M(n) = 862.6320056992192\n",
      "Generation 7553: p = 0.9584800063324658\n",
      "Generation 7553: M(n) = 862.6320056992192\n",
      "Generation 7554: p = 0.9584800063324658\n",
      "Generation 7554: M(n) = 862.6320056992192\n",
      "Generation 7555: p = 0.9584800063324658\n",
      "Generation 7555: M(n) = 862.6320056992192\n",
      "Generation 7556: p = 0.9584800063324658\n",
      "Generation 7556: M(n) = 862.6320056992192\n",
      "Generation 7557: p = 0.9584800063324658\n",
      "Generation 7557: M(n) = 862.6320056992192\n",
      "Generation 7558: p = 0.9584800063324658\n",
      "Generation 7558: M(n) = 862.6320056992192\n",
      "Generation 7559: p = 0.9584800063324658\n",
      "Generation 7559: M(n) = 862.6320056992192\n",
      "Generation 7560: p = 0.9584800063324658\n",
      "Generation 7560: M(n) = 862.6320056992192\n",
      "Generation 7561: p = 0.9584800063324658\n",
      "Generation 7561: M(n) = 862.6320056992192\n",
      "Generation 7562: p = 0.9584800063324658\n",
      "Generation 7562: M(n) = 862.6320056992192\n",
      "Generation 7563: p = 0.9584800063324658\n",
      "Generation 7563: M(n) = 862.6320056992192\n",
      "Generation 7564: p = 0.9584800063324658\n",
      "Generation 7564: M(n) = 862.6320056992192\n",
      "Generation 7565: p = 0.9584800063324658\n",
      "Generation 7565: M(n) = 862.6320056992192\n",
      "Generation 7566: p = 0.9584800063324658\n",
      "Generation 7566: M(n) = 862.6320056992192\n",
      "Generation 7567: p = 0.9584800063324658\n",
      "Generation 7567: M(n) = 862.6320056992192\n",
      "Generation 7568: p = 0.9584800063324658\n",
      "Generation 7568: M(n) = 862.6320056992192\n",
      "Generation 7569: p = 0.9584800063324658\n",
      "Generation 7569: M(n) = 862.6320056992192\n",
      "Generation 7570: p = 0.9584800063324658\n",
      "Generation 7570: M(n) = 862.6320056992192\n",
      "Generation 7571: p = 0.9584800063324658\n",
      "Generation 7571: M(n) = 862.6320056992192\n",
      "Generation 7572: p = 0.9584800063324658\n",
      "Generation 7572: M(n) = 862.6320056992192\n",
      "Generation 7573: p = 0.9584800063324658\n",
      "Generation 7573: M(n) = 862.6320056992192\n",
      "Generation 7574: p = 0.9584800063324658\n",
      "Generation 7574: M(n) = 862.6320056992192\n",
      "Generation 7575: p = 0.9584800063324658\n",
      "Generation 7575: M(n) = 862.6320056992192\n",
      "Generation 7576: p = 0.9584800063324658\n",
      "Generation 7576: M(n) = 862.6320056992192\n",
      "Generation 7577: p = 0.9584800063324658\n",
      "Generation 7577: M(n) = 862.6320056992192\n",
      "Generation 7578: p = 0.9584800063324658\n",
      "Generation 7578: M(n) = 862.6320056992192\n",
      "Generation 7579: p = 0.9584800063324658\n",
      "Generation 7579: M(n) = 862.6320056992192\n",
      "Generation 7580: p = 0.9584800063324658\n",
      "Generation 7580: M(n) = 862.6320056992192\n",
      "Generation 7581: p = 0.9584800063324658\n",
      "Generation 7581: M(n) = 862.6320056992192\n",
      "Generation 7582: p = 0.9584800063324658\n",
      "Generation 7582: M(n) = 862.6320056992192\n",
      "Generation 7583: p = 0.9584800063324658\n",
      "Generation 7583: M(n) = 862.6320056992192\n",
      "Generation 7584: p = 0.9584800063324658\n",
      "Generation 7584: M(n) = 862.6320056992192\n",
      "Generation 7585: p = 0.9584800063324658\n",
      "Generation 7585: M(n) = 862.6320056992192\n",
      "Generation 7586: p = 0.9584800063324658\n",
      "Generation 7586: M(n) = 862.6320056992192\n",
      "Generation 7587: p = 0.9584800063324658\n",
      "Generation 7587: M(n) = 862.6320056992192\n",
      "Generation 7588: p = 0.9584800063324658\n",
      "Generation 7588: M(n) = 862.6320056992192\n",
      "Generation 7589: p = 0.9584800063324658\n",
      "Generation 7589: M(n) = 862.6320056992192\n",
      "Generation 7590: p = 0.9584800063324658\n",
      "Generation 7590: M(n) = 862.6320056992192\n",
      "Generation 7591: p = 0.9584800063324658\n",
      "Generation 7591: M(n) = 862.6320056992192\n",
      "Generation 7592: p = 0.9584800063324658\n",
      "Generation 7592: M(n) = 862.6320056992192\n",
      "Generation 7593: p = 0.9584800063324658\n",
      "Generation 7593: M(n) = 862.6320056992192\n",
      "Generation 7594: p = 0.9584800063324658\n",
      "Generation 7594: M(n) = 862.6320056992192\n",
      "Generation 7595: p = 0.9584800063324658\n",
      "Generation 7595: M(n) = 862.6320056992192\n",
      "Generation 7596: p = 0.9584800063324658\n",
      "Generation 7596: M(n) = 862.6320056992192\n",
      "Generation 7597: p = 0.9584800063324658\n",
      "Generation 7597: M(n) = 862.6320056992192\n",
      "Generation 7598: p = 0.9584800063324658\n",
      "Generation 7598: M(n) = 862.6320056992192\n",
      "Generation 7599: p = 0.9584800063324658\n",
      "Generation 7599: M(n) = 862.6320056992192\n",
      "Generation 7600: p = 0.9584800063324658\n",
      "Generation 7600: M(n) = 862.6320056992192\n",
      "Generation 7601: p = 0.9584800063324658\n",
      "Generation 7601: M(n) = 862.6320056992192\n",
      "Generation 7602: p = 0.9584800063324658\n",
      "Generation 7602: M(n) = 862.6320056992192\n",
      "Generation 7603: p = 0.9584800063324658\n",
      "Generation 7603: M(n) = 862.6320056992192\n",
      "Generation 7604: p = 0.9584800063324658\n",
      "Generation 7604: M(n) = 862.6320056992192\n",
      "Generation 7605: p = 0.9584800063324658\n",
      "Generation 7605: M(n) = 862.6320056992192\n",
      "Generation 7606: p = 0.9584800063324658\n",
      "Generation 7606: M(n) = 862.6320056992192\n",
      "Generation 7607: p = 0.9584800063324658\n",
      "Generation 7607: M(n) = 862.6320056992192\n",
      "Generation 7608: p = 0.9584800063324658\n",
      "Generation 7608: M(n) = 862.6320056992192\n",
      "Generation 7609: p = 0.9584800063324658\n",
      "Generation 7609: M(n) = 862.6320056992192\n",
      "Generation 7610: p = 0.9584800063324658\n",
      "Generation 7610: M(n) = 862.6320056992192\n",
      "Generation 7611: p = 0.9584800063324658\n",
      "Generation 7611: M(n) = 862.6320056992192\n",
      "Generation 7612: p = 0.9584800063324658\n",
      "Generation 7612: M(n) = 862.6320056992192\n",
      "Generation 7613: p = 0.9584800063324658\n",
      "Generation 7613: M(n) = 862.6320056992192\n",
      "Generation 7614: p = 0.9584800063324658\n",
      "Generation 7614: M(n) = 862.6320056992192\n",
      "Generation 7615: p = 0.9584800063324658\n",
      "Generation 7615: M(n) = 862.6320056992192\n",
      "Generation 7616: p = 0.9584800063324658\n",
      "Generation 7616: M(n) = 862.6320056992192\n",
      "Generation 7617: p = 0.9584800063324658\n",
      "Generation 7617: M(n) = 862.6320056992192\n",
      "Generation 7618: p = 0.9584800063324658\n",
      "Generation 7618: M(n) = 862.6320056992192\n",
      "Generation 7619: p = 0.9584800063324658\n",
      "Generation 7619: M(n) = 862.6320056992192\n",
      "Generation 7620: p = 0.9584800063324658\n",
      "Generation 7620: M(n) = 862.6320056992192\n",
      "Generation 7621: p = 0.9584800063324658\n",
      "Generation 7621: M(n) = 862.6320056992192\n",
      "Generation 7622: p = 0.9584800063324658\n",
      "Generation 7622: M(n) = 862.6320056992192\n",
      "Generation 7623: p = 0.9584800063324658\n",
      "Generation 7623: M(n) = 862.6320056992192\n",
      "Generation 7624: p = 0.9584800063324658\n",
      "Generation 7624: M(n) = 862.6320056992192\n",
      "Generation 7625: p = 0.9584800063324658\n",
      "Generation 7625: M(n) = 862.6320056992192\n",
      "Generation 7626: p = 0.9584800063324658\n",
      "Generation 7626: M(n) = 862.6320056992192\n",
      "Generation 7627: p = 0.9584800063324658\n",
      "Generation 7627: M(n) = 862.6320056992192\n",
      "Generation 7628: p = 0.9584800063324658\n",
      "Generation 7628: M(n) = 862.6320056992192\n",
      "Generation 7629: p = 0.9584800063324658\n",
      "Generation 7629: M(n) = 862.6320056992192\n",
      "Generation 7630: p = 0.9584800063324658\n",
      "Generation 7630: M(n) = 862.6320056992192\n",
      "Generation 7631: p = 0.9584800063324658\n",
      "Generation 7631: M(n) = 862.6320056992192\n",
      "Generation 7632: p = 0.9584800063324658\n",
      "Generation 7632: M(n) = 862.6320056992192\n",
      "Generation 7633: p = 0.9584800063324658\n",
      "Generation 7633: M(n) = 862.6320056992192\n",
      "Generation 7634: p = 0.9584800063324658\n",
      "Generation 7634: M(n) = 862.6320056992192\n",
      "Generation 7635: p = 0.9584800063324658\n",
      "Generation 7635: M(n) = 862.6320056992192\n",
      "Generation 7636: p = 0.9584800063324658\n",
      "Generation 7636: M(n) = 862.6320056992192\n",
      "Generation 7637: p = 0.9584800063324658\n",
      "Generation 7637: M(n) = 862.6320056992192\n",
      "Generation 7638: p = 0.9584800063324658\n",
      "Generation 7638: M(n) = 862.6320056992192\n",
      "Generation 7639: p = 0.9584800063324658\n",
      "Generation 7639: M(n) = 862.6320056992192\n",
      "Generation 7640: p = 0.9584800063324658\n",
      "Generation 7640: M(n) = 862.6320056992192\n",
      "Generation 7641: p = 0.9584800063324658\n",
      "Generation 7641: M(n) = 862.6320056992192\n",
      "Generation 7642: p = 0.9584800063324658\n",
      "Generation 7642: M(n) = 862.6320056992192\n",
      "Generation 7643: p = 0.9584800063324658\n",
      "Generation 7643: M(n) = 862.6320056992192\n",
      "Generation 7644: p = 0.9584800063324658\n",
      "Generation 7644: M(n) = 862.6320056992192\n",
      "Generation 7645: p = 0.9584800063324658\n",
      "Generation 7645: M(n) = 862.6320056992192\n",
      "Generation 7646: p = 0.9584800063324658\n",
      "Generation 7646: M(n) = 862.6320056992192\n",
      "Generation 7647: p = 0.9584800063324658\n",
      "Generation 7647: M(n) = 862.6320056992192\n",
      "Generation 7648: p = 0.9584800063324658\n",
      "Generation 7648: M(n) = 862.6320056992192\n",
      "Generation 7649: p = 0.9584800063324658\n",
      "Generation 7649: M(n) = 862.6320056992192\n",
      "Generation 7650: p = 0.9584800063324658\n",
      "Generation 7650: M(n) = 862.6320056992192\n",
      "Generation 7651: p = 0.9584800063324658\n",
      "Generation 7651: M(n) = 862.6320056992192\n",
      "Generation 7652: p = 0.9584800063324658\n",
      "Generation 7652: M(n) = 862.6320056992192\n",
      "Generation 7653: p = 0.9584800063324658\n",
      "Generation 7653: M(n) = 862.6320056992192\n",
      "Generation 7654: p = 0.9584800063324658\n",
      "Generation 7654: M(n) = 862.6320056992192\n",
      "Generation 7655: p = 0.9584800063324658\n",
      "Generation 7655: M(n) = 862.6320056992192\n",
      "Generation 7656: p = 0.9584800063324658\n",
      "Generation 7656: M(n) = 862.6320056992192\n",
      "Generation 7657: p = 0.9584800063324658\n",
      "Generation 7657: M(n) = 862.6320056992192\n",
      "Generation 7658: p = 0.9584800063324658\n",
      "Generation 7658: M(n) = 862.6320056992192\n",
      "Generation 7659: p = 0.9584800063324658\n",
      "Generation 7659: M(n) = 862.6320056992192\n",
      "Generation 7660: p = 0.9584800063324658\n",
      "Generation 7660: M(n) = 862.6320056992192\n",
      "Generation 7661: p = 0.9584800063324658\n",
      "Generation 7661: M(n) = 862.6320056992192\n",
      "Generation 7662: p = 0.9584800063324658\n",
      "Generation 7662: M(n) = 862.6320056992192\n",
      "Generation 7663: p = 0.9584800063324658\n",
      "Generation 7663: M(n) = 862.6320056992192\n",
      "Generation 7664: p = 0.9584800063324658\n",
      "Generation 7664: M(n) = 862.6320056992192\n",
      "Generation 7665: p = 0.9584800063324658\n",
      "Generation 7665: M(n) = 862.6320056992192\n",
      "Generation 7666: p = 0.9584800063324658\n",
      "Generation 7666: M(n) = 862.6320056992192\n",
      "Generation 7667: p = 0.9584800063324658\n",
      "Generation 7667: M(n) = 862.6320056992192\n",
      "Generation 7668: p = 0.9584800063324658\n",
      "Generation 7668: M(n) = 862.6320056992192\n",
      "Generation 7669: p = 0.9584800063324658\n",
      "Generation 7669: M(n) = 862.6320056992192\n",
      "Generation 7670: p = 0.9584800063324658\n",
      "Generation 7670: M(n) = 862.6320056992192\n",
      "Generation 7671: p = 0.9584800063324658\n",
      "Generation 7671: M(n) = 862.6320056992192\n",
      "Generation 7672: p = 0.9584800063324658\n",
      "Generation 7672: M(n) = 862.6320056992192\n",
      "Generation 7673: p = 0.9584800063324658\n",
      "Generation 7673: M(n) = 862.6320056992192\n",
      "Generation 7674: p = 0.9584800063324658\n",
      "Generation 7674: M(n) = 862.6320056992192\n",
      "Generation 7675: p = 0.9584800063324658\n",
      "Generation 7675: M(n) = 862.6320056992192\n",
      "Generation 7676: p = 0.9584800063324658\n",
      "Generation 7676: M(n) = 862.6320056992192\n",
      "Generation 7677: p = 0.9584800063324658\n",
      "Generation 7677: M(n) = 862.6320056992192\n",
      "Generation 7678: p = 0.9584800063324658\n",
      "Generation 7678: M(n) = 862.6320056992192\n",
      "Generation 7679: p = 0.9584800063324658\n",
      "Generation 7679: M(n) = 862.6320056992192\n",
      "Generation 7680: p = 0.9584800063324658\n",
      "Generation 7680: M(n) = 862.6320056992192\n",
      "Generation 7681: p = 0.9584800063324658\n",
      "Generation 7681: M(n) = 862.6320056992192\n",
      "Generation 7682: p = 0.9584800063324658\n",
      "Generation 7682: M(n) = 862.6320056992192\n",
      "Generation 7683: p = 0.9584800063324658\n",
      "Generation 7683: M(n) = 862.6320056992192\n",
      "Generation 7684: p = 0.9584800063324658\n",
      "Generation 7684: M(n) = 862.6320056992192\n",
      "Generation 7685: p = 0.9584800063324658\n",
      "Generation 7685: M(n) = 862.6320056992192\n",
      "Generation 7686: p = 0.9584800063324658\n",
      "Generation 7686: M(n) = 862.6320056992192\n",
      "Generation 7687: p = 0.9584800063324658\n",
      "Generation 7687: M(n) = 862.6320056992192\n",
      "Generation 7688: p = 0.9584800063324658\n",
      "Generation 7688: M(n) = 862.6320056992192\n",
      "Generation 7689: p = 0.9584800063324658\n",
      "Generation 7689: M(n) = 862.6320056992192\n",
      "Generation 7690: p = 0.9584800063324658\n",
      "Generation 7690: M(n) = 862.6320056992192\n",
      "Generation 7691: p = 0.9584800063324658\n",
      "Generation 7691: M(n) = 862.6320056992192\n",
      "Generation 7692: p = 0.9584800063324658\n",
      "Generation 7692: M(n) = 862.6320056992192\n",
      "Generation 7693: p = 0.9584800063324658\n",
      "Generation 7693: M(n) = 862.6320056992192\n",
      "Generation 7694: p = 0.9584800063324658\n",
      "Generation 7694: M(n) = 862.6320056992192\n",
      "Generation 7695: p = 0.9584800063324658\n",
      "Generation 7695: M(n) = 862.6320056992192\n",
      "Generation 7696: p = 0.9584800063324658\n",
      "Generation 7696: M(n) = 862.6320056992192\n",
      "Generation 7697: p = 0.9584800063324658\n",
      "Generation 7697: M(n) = 862.6320056992192\n",
      "Generation 7698: p = 0.9584800063324658\n",
      "Generation 7698: M(n) = 862.6320056992192\n",
      "Generation 7699: p = 0.9584800063324658\n",
      "Generation 7699: M(n) = 862.6320056992192\n",
      "Generation 7700: p = 0.9584800063324658\n",
      "Generation 7700: M(n) = 862.6320056992192\n",
      "Generation 7701: p = 0.9584800063324658\n",
      "Generation 7701: M(n) = 862.6320056992192\n",
      "Generation 7702: p = 0.9584800063324658\n",
      "Generation 7702: M(n) = 862.6320056992192\n",
      "Generation 7703: p = 0.9584800063324658\n",
      "Generation 7703: M(n) = 862.6320056992192\n",
      "Generation 7704: p = 0.9584800063324658\n",
      "Generation 7704: M(n) = 862.6320056992192\n",
      "Generation 7705: p = 0.9584800063324658\n",
      "Generation 7705: M(n) = 862.6320056992192\n",
      "Generation 7706: p = 0.9584800063324658\n",
      "Generation 7706: M(n) = 862.6320056992192\n",
      "Generation 7707: p = 0.9584800063324658\n",
      "Generation 7707: M(n) = 862.6320056992192\n",
      "Generation 7708: p = 0.9584800063324658\n",
      "Generation 7708: M(n) = 862.6320056992192\n",
      "Generation 7709: p = 0.9584800063324658\n",
      "Generation 7709: M(n) = 862.6320056992192\n",
      "Generation 7710: p = 0.9584800063324658\n",
      "Generation 7710: M(n) = 862.6320056992192\n",
      "Generation 7711: p = 0.9584800063324658\n",
      "Generation 7711: M(n) = 862.6320056992192\n",
      "Generation 7712: p = 0.9584800063324658\n",
      "Generation 7712: M(n) = 862.6320056992192\n",
      "Generation 7713: p = 0.9584800063324658\n",
      "Generation 7713: M(n) = 862.6320056992192\n",
      "Generation 7714: p = 0.9584800063324658\n",
      "Generation 7714: M(n) = 862.6320056992192\n",
      "Generation 7715: p = 0.9584800063324658\n",
      "Generation 7715: M(n) = 862.6320056992192\n",
      "Generation 7716: p = 0.9584800063324658\n",
      "Generation 7716: M(n) = 862.6320056992192\n",
      "Generation 7717: p = 0.9584800063324658\n",
      "Generation 7717: M(n) = 862.6320056992192\n",
      "Generation 7718: p = 0.9584800063324658\n",
      "Generation 7718: M(n) = 862.6320056992192\n",
      "Generation 7719: p = 0.9584800063324658\n",
      "Generation 7719: M(n) = 862.6320056992192\n",
      "Generation 7720: p = 0.9584800063324658\n",
      "Generation 7720: M(n) = 862.6320056992192\n",
      "Generation 7721: p = 0.9584800063324658\n",
      "Generation 7721: M(n) = 862.6320056992192\n",
      "Generation 7722: p = 0.9584800063324658\n",
      "Generation 7722: M(n) = 862.6320056992192\n",
      "Generation 7723: p = 0.9584800063324658\n",
      "Generation 7723: M(n) = 862.6320056992192\n",
      "Generation 7724: p = 0.9584800063324658\n",
      "Generation 7724: M(n) = 862.6320056992192\n",
      "Generation 7725: p = 0.9584800063324658\n",
      "Generation 7725: M(n) = 862.6320056992192\n",
      "Generation 7726: p = 0.9584800063324658\n",
      "Generation 7726: M(n) = 862.6320056992192\n",
      "Generation 7727: p = 0.9584800063324658\n",
      "Generation 7727: M(n) = 862.6320056992192\n",
      "Generation 7728: p = 0.9584800063324658\n",
      "Generation 7728: M(n) = 862.6320056992192\n",
      "Generation 7729: p = 0.9584800063324658\n",
      "Generation 7729: M(n) = 862.6320056992192\n",
      "Generation 7730: p = 0.9584800063324658\n",
      "Generation 7730: M(n) = 862.6320056992192\n",
      "Generation 7731: p = 0.9584800063324658\n",
      "Generation 7731: M(n) = 862.6320056992192\n",
      "Generation 7732: p = 0.9584800063324658\n",
      "Generation 7732: M(n) = 862.6320056992192\n",
      "Generation 7733: p = 0.9584800063324658\n",
      "Generation 7733: M(n) = 862.6320056992192\n",
      "Generation 7734: p = 0.9584800063324658\n",
      "Generation 7734: M(n) = 862.6320056992192\n",
      "Generation 7735: p = 0.9584800063324658\n",
      "Generation 7735: M(n) = 862.6320056992192\n",
      "Generation 7736: p = 0.9584800063324658\n",
      "Generation 7736: M(n) = 862.6320056992192\n",
      "Generation 7737: p = 0.9584800063324658\n",
      "Generation 7737: M(n) = 862.6320056992192\n",
      "Generation 7738: p = 0.9584800063324658\n",
      "Generation 7738: M(n) = 862.6320056992192\n",
      "Generation 7739: p = 0.9584800063324658\n",
      "Generation 7739: M(n) = 862.6320056992192\n",
      "Generation 7740: p = 0.9584800063324658\n",
      "Generation 7740: M(n) = 862.6320056992192\n",
      "Generation 7741: p = 0.9584800063324658\n",
      "Generation 7741: M(n) = 862.6320056992192\n",
      "Generation 7742: p = 0.9584800063324658\n",
      "Generation 7742: M(n) = 862.6320056992192\n",
      "Generation 7743: p = 0.9584800063324658\n",
      "Generation 7743: M(n) = 862.6320056992192\n",
      "Generation 7744: p = 0.9584800063324658\n",
      "Generation 7744: M(n) = 862.6320056992192\n",
      "Generation 7745: p = 0.9584800063324658\n",
      "Generation 7745: M(n) = 862.6320056992192\n",
      "Generation 7746: p = 0.9584800063324658\n",
      "Generation 7746: M(n) = 862.6320056992192\n",
      "Generation 7747: p = 0.9584800063324658\n",
      "Generation 7747: M(n) = 862.6320056992192\n",
      "Generation 7748: p = 0.9584800063324658\n",
      "Generation 7748: M(n) = 862.6320056992192\n",
      "Generation 7749: p = 0.9584800063324658\n",
      "Generation 7749: M(n) = 862.6320056992192\n",
      "Generation 7750: p = 0.9584800063324658\n",
      "Generation 7750: M(n) = 862.6320056992192\n",
      "Generation 7751: p = 0.9584800063324658\n",
      "Generation 7751: M(n) = 862.6320056992192\n",
      "Generation 7752: p = 0.9584800063324658\n",
      "Generation 7752: M(n) = 862.6320056992192\n",
      "Generation 7753: p = 0.9584800063324658\n",
      "Generation 7753: M(n) = 862.6320056992192\n",
      "Generation 7754: p = 0.9584800063324658\n",
      "Generation 7754: M(n) = 862.6320056992192\n",
      "Generation 7755: p = 0.9584800063324658\n",
      "Generation 7755: M(n) = 862.6320056992192\n",
      "Generation 7756: p = 0.9584800063324658\n",
      "Generation 7756: M(n) = 862.6320056992192\n",
      "Generation 7757: p = 0.9584800063324658\n",
      "Generation 7757: M(n) = 862.6320056992192\n",
      "Generation 7758: p = 0.9584800063324658\n",
      "Generation 7758: M(n) = 862.6320056992192\n",
      "Generation 7759: p = 0.9584800063324658\n",
      "Generation 7759: M(n) = 862.6320056992192\n",
      "Generation 7760: p = 0.9584800063324658\n",
      "Generation 7760: M(n) = 862.6320056992192\n",
      "Generation 7761: p = 0.9584800063324658\n",
      "Generation 7761: M(n) = 862.6320056992192\n",
      "Generation 7762: p = 0.9584800063324658\n",
      "Generation 7762: M(n) = 862.6320056992192\n",
      "Generation 7763: p = 0.9584800063324658\n",
      "Generation 7763: M(n) = 862.6320056992192\n",
      "Generation 7764: p = 0.9584800063324658\n",
      "Generation 7764: M(n) = 862.6320056992192\n",
      "Generation 7765: p = 0.9584800063324658\n",
      "Generation 7765: M(n) = 862.6320056992192\n",
      "Generation 7766: p = 0.9584800063324658\n",
      "Generation 7766: M(n) = 862.6320056992192\n",
      "Generation 7767: p = 0.9584800063324658\n",
      "Generation 7767: M(n) = 862.6320056992192\n",
      "Generation 7768: p = 0.9584800063324658\n",
      "Generation 7768: M(n) = 862.6320056992192\n",
      "Generation 7769: p = 0.9584800063324658\n",
      "Generation 7769: M(n) = 862.6320056992192\n",
      "Generation 7770: p = 0.9584800063324658\n",
      "Generation 7770: M(n) = 862.6320056992192\n",
      "Generation 7771: p = 0.9584800063324658\n",
      "Generation 7771: M(n) = 862.6320056992192\n",
      "Generation 7772: p = 0.9584800063324658\n",
      "Generation 7772: M(n) = 862.6320056992192\n",
      "Generation 7773: p = 0.9584800063324658\n",
      "Generation 7773: M(n) = 862.6320056992192\n",
      "Generation 7774: p = 0.9584800063324658\n",
      "Generation 7774: M(n) = 862.6320056992192\n",
      "Generation 7775: p = 0.9584800063324658\n",
      "Generation 7775: M(n) = 862.6320056992192\n",
      "Generation 7776: p = 0.9584800063324658\n",
      "Generation 7776: M(n) = 862.6320056992192\n",
      "Generation 7777: p = 0.9584800063324658\n",
      "Generation 7777: M(n) = 862.6320056992192\n",
      "Generation 7778: p = 0.9584800063324658\n",
      "Generation 7778: M(n) = 862.6320056992192\n",
      "Generation 7779: p = 0.9584800063324658\n",
      "Generation 7779: M(n) = 862.6320056992192\n",
      "Generation 7780: p = 0.9584800063324658\n",
      "Generation 7780: M(n) = 862.6320056992192\n",
      "Generation 7781: p = 0.9584800063324658\n",
      "Generation 7781: M(n) = 862.6320056992192\n",
      "Generation 7782: p = 0.9584800063324658\n",
      "Generation 7782: M(n) = 862.6320056992192\n",
      "Generation 7783: p = 0.9584800063324658\n",
      "Generation 7783: M(n) = 862.6320056992192\n",
      "Generation 7784: p = 0.9584800063324658\n",
      "Generation 7784: M(n) = 862.6320056992192\n",
      "Generation 7785: p = 0.9584800063324658\n",
      "Generation 7785: M(n) = 862.6320056992192\n",
      "Generation 7786: p = 0.9584800063324658\n",
      "Generation 7786: M(n) = 862.6320056992192\n",
      "Generation 7787: p = 0.9584800063324658\n",
      "Generation 7787: M(n) = 862.6320056992192\n",
      "Generation 7788: p = 0.9584800063324658\n",
      "Generation 7788: M(n) = 862.6320056992192\n",
      "Generation 7789: p = 0.9584800063324658\n",
      "Generation 7789: M(n) = 862.6320056992192\n",
      "Generation 7790: p = 0.9584800063324658\n",
      "Generation 7790: M(n) = 862.6320056992192\n",
      "Generation 7791: p = 0.9584800063324658\n",
      "Generation 7791: M(n) = 862.6320056992192\n",
      "Generation 7792: p = 0.9584800063324658\n",
      "Generation 7792: M(n) = 862.6320056992192\n",
      "Generation 7793: p = 0.9584800063324658\n",
      "Generation 7793: M(n) = 862.6320056992192\n",
      "Generation 7794: p = 0.9584800063324658\n",
      "Generation 7794: M(n) = 862.6320056992192\n",
      "Generation 7795: p = 0.9584800063324658\n",
      "Generation 7795: M(n) = 862.6320056992192\n",
      "Generation 7796: p = 0.9584800063324658\n",
      "Generation 7796: M(n) = 862.6320056992192\n",
      "Generation 7797: p = 0.9584800063324658\n",
      "Generation 7797: M(n) = 862.6320056992192\n",
      "Generation 7798: p = 0.9584800063324658\n",
      "Generation 7798: M(n) = 862.6320056992192\n",
      "Generation 7799: p = 0.9584800063324658\n",
      "Generation 7799: M(n) = 862.6320056992192\n",
      "Generation 7800: p = 0.9584800063324658\n",
      "Generation 7800: M(n) = 862.6320056992192\n",
      "Generation 7801: p = 0.9584800063324658\n",
      "Generation 7801: M(n) = 862.6320056992192\n",
      "Generation 7802: p = 0.9584800063324658\n",
      "Generation 7802: M(n) = 862.6320056992192\n",
      "Generation 7803: p = 0.9584800063324658\n",
      "Generation 7803: M(n) = 862.6320056992192\n",
      "Generation 7804: p = 0.9584800063324658\n",
      "Generation 7804: M(n) = 862.6320056992192\n",
      "Generation 7805: p = 0.9584800063324658\n",
      "Generation 7805: M(n) = 862.6320056992192\n",
      "Generation 7806: p = 0.9584800063324658\n",
      "Generation 7806: M(n) = 862.6320056992192\n",
      "Generation 7807: p = 0.9584800063324658\n",
      "Generation 7807: M(n) = 862.6320056992192\n",
      "Generation 7808: p = 0.9584800063324658\n",
      "Generation 7808: M(n) = 862.6320056992192\n",
      "Generation 7809: p = 0.9584800063324658\n",
      "Generation 7809: M(n) = 862.6320056992192\n",
      "Generation 7810: p = 0.9584800063324658\n",
      "Generation 7810: M(n) = 862.6320056992192\n",
      "Generation 7811: p = 0.9584800063324658\n",
      "Generation 7811: M(n) = 862.6320056992192\n",
      "Generation 7812: p = 0.9584800063324658\n",
      "Generation 7812: M(n) = 862.6320056992192\n",
      "Generation 7813: p = 0.9584800063324658\n",
      "Generation 7813: M(n) = 862.6320056992192\n",
      "Generation 7814: p = 0.9584800063324658\n",
      "Generation 7814: M(n) = 862.6320056992192\n",
      "Generation 7815: p = 0.9584800063324658\n",
      "Generation 7815: M(n) = 862.6320056992192\n",
      "Generation 7816: p = 0.9584800063324658\n",
      "Generation 7816: M(n) = 862.6320056992192\n",
      "Generation 7817: p = 0.9584800063324658\n",
      "Generation 7817: M(n) = 862.6320056992192\n",
      "Generation 7818: p = 0.9584800063324658\n",
      "Generation 7818: M(n) = 862.6320056992192\n",
      "Generation 7819: p = 0.9584800063324658\n",
      "Generation 7819: M(n) = 862.6320056992192\n",
      "Generation 7820: p = 0.9584800063324658\n",
      "Generation 7820: M(n) = 862.6320056992192\n",
      "Generation 7821: p = 0.9584800063324658\n",
      "Generation 7821: M(n) = 862.6320056992192\n",
      "Generation 7822: p = 0.9584800063324658\n",
      "Generation 7822: M(n) = 862.6320056992192\n",
      "Generation 7823: p = 0.9584800063324658\n",
      "Generation 7823: M(n) = 862.6320056992192\n",
      "Generation 7824: p = 0.9584800063324658\n",
      "Generation 7824: M(n) = 862.6320056992192\n",
      "Generation 7825: p = 0.9584800063324658\n",
      "Generation 7825: M(n) = 862.6320056992192\n",
      "Generation 7826: p = 0.9584800063324658\n",
      "Generation 7826: M(n) = 862.6320056992192\n",
      "Generation 7827: p = 0.9584800063324658\n",
      "Generation 7827: M(n) = 862.6320056992192\n",
      "Generation 7828: p = 0.9584800063324658\n",
      "Generation 7828: M(n) = 862.6320056992192\n",
      "Generation 7829: p = 0.9584800063324658\n",
      "Generation 7829: M(n) = 862.6320056992192\n",
      "Generation 7830: p = 0.9584800063324658\n",
      "Generation 7830: M(n) = 862.6320056992192\n",
      "Generation 7831: p = 0.9584800063324658\n",
      "Generation 7831: M(n) = 862.6320056992192\n",
      "Generation 7832: p = 0.9584800063324658\n",
      "Generation 7832: M(n) = 862.6320056992192\n",
      "Generation 7833: p = 0.9584800063324658\n",
      "Generation 7833: M(n) = 862.6320056992192\n",
      "Generation 7834: p = 0.9584800063324658\n",
      "Generation 7834: M(n) = 862.6320056992192\n",
      "Generation 7835: p = 0.9584800063324658\n",
      "Generation 7835: M(n) = 862.6320056992192\n",
      "Generation 7836: p = 0.9584800063324658\n",
      "Generation 7836: M(n) = 862.6320056992192\n",
      "Generation 7837: p = 0.9584800063324658\n",
      "Generation 7837: M(n) = 862.6320056992192\n",
      "Generation 7838: p = 0.9584800063324658\n",
      "Generation 7838: M(n) = 862.6320056992192\n",
      "Generation 7839: p = 0.9584800063324658\n",
      "Generation 7839: M(n) = 862.6320056992192\n",
      "Generation 7840: p = 0.9584800063324658\n",
      "Generation 7840: M(n) = 862.6320056992192\n",
      "Generation 7841: p = 0.9584800063324658\n",
      "Generation 7841: M(n) = 862.6320056992192\n",
      "Generation 7842: p = 0.9584800063324658\n",
      "Generation 7842: M(n) = 862.6320056992192\n",
      "Generation 7843: p = 0.9584800063324658\n",
      "Generation 7843: M(n) = 862.6320056992192\n",
      "Generation 7844: p = 0.9584800063324658\n",
      "Generation 7844: M(n) = 862.6320056992192\n",
      "Generation 7845: p = 0.9584800063324658\n",
      "Generation 7845: M(n) = 862.6320056992192\n",
      "Generation 7846: p = 0.9584800063324658\n",
      "Generation 7846: M(n) = 862.6320056992192\n",
      "Generation 7847: p = 0.9584800063324658\n",
      "Generation 7847: M(n) = 862.6320056992192\n",
      "Generation 7848: p = 0.9584800063324658\n",
      "Generation 7848: M(n) = 862.6320056992192\n",
      "Generation 7849: p = 0.9584800063324658\n",
      "Generation 7849: M(n) = 862.6320056992192\n",
      "Generation 7850: p = 0.9584800063324658\n",
      "Generation 7850: M(n) = 862.6320056992192\n",
      "Generation 7851: p = 0.9584800063324658\n",
      "Generation 7851: M(n) = 862.6320056992192\n",
      "Generation 7852: p = 0.9584800063324658\n",
      "Generation 7852: M(n) = 862.6320056992192\n",
      "Generation 7853: p = 0.9584800063324658\n",
      "Generation 7853: M(n) = 862.6320056992192\n",
      "Generation 7854: p = 0.9584800063324658\n",
      "Generation 7854: M(n) = 862.6320056992192\n",
      "Generation 7855: p = 0.9584800063324658\n",
      "Generation 7855: M(n) = 862.6320056992192\n",
      "Generation 7856: p = 0.9584800063324658\n",
      "Generation 7856: M(n) = 862.6320056992192\n",
      "Generation 7857: p = 0.9584800063324658\n",
      "Generation 7857: M(n) = 862.6320056992192\n",
      "Generation 7858: p = 0.9584800063324658\n",
      "Generation 7858: M(n) = 862.6320056992192\n",
      "Generation 7859: p = 0.9584800063324658\n",
      "Generation 7859: M(n) = 862.6320056992192\n",
      "Generation 7860: p = 0.9584800063324658\n",
      "Generation 7860: M(n) = 862.6320056992192\n",
      "Generation 7861: p = 0.9584800063324658\n",
      "Generation 7861: M(n) = 862.6320056992192\n",
      "Generation 7862: p = 0.9584800063324658\n",
      "Generation 7862: M(n) = 862.6320056992192\n",
      "Generation 7863: p = 0.9584800063324658\n",
      "Generation 7863: M(n) = 862.6320056992192\n",
      "Generation 7864: p = 0.9584800063324658\n",
      "Generation 7864: M(n) = 862.6320056992192\n",
      "Generation 7865: p = 0.9584800063324658\n",
      "Generation 7865: M(n) = 862.6320056992192\n",
      "Generation 7866: p = 0.9584800063324658\n",
      "Generation 7866: M(n) = 862.6320056992192\n",
      "Generation 7867: p = 0.9584800063324658\n",
      "Generation 7867: M(n) = 862.6320056992192\n",
      "Generation 7868: p = 0.9584800063324658\n",
      "Generation 7868: M(n) = 862.6320056992192\n",
      "Generation 7869: p = 0.9584800063324658\n",
      "Generation 7869: M(n) = 862.6320056992192\n",
      "Generation 7870: p = 0.9584800063324658\n",
      "Generation 7870: M(n) = 862.6320056992192\n",
      "Generation 7871: p = 0.9584800063324658\n",
      "Generation 7871: M(n) = 862.6320056992192\n",
      "Generation 7872: p = 0.9584800063324658\n",
      "Generation 7872: M(n) = 862.6320056992192\n",
      "Generation 7873: p = 0.9584800063324658\n",
      "Generation 7873: M(n) = 862.6320056992192\n",
      "Generation 7874: p = 0.9584800063324658\n",
      "Generation 7874: M(n) = 862.6320056992192\n",
      "Generation 7875: p = 0.9584800063324658\n",
      "Generation 7875: M(n) = 862.6320056992192\n",
      "Generation 7876: p = 0.9584800063324658\n",
      "Generation 7876: M(n) = 862.6320056992192\n",
      "Generation 7877: p = 0.9584800063324658\n",
      "Generation 7877: M(n) = 862.6320056992192\n",
      "Generation 7878: p = 0.9584800063324658\n",
      "Generation 7878: M(n) = 862.6320056992192\n",
      "Generation 7879: p = 0.9584800063324658\n",
      "Generation 7879: M(n) = 862.6320056992192\n",
      "Generation 7880: p = 0.9584800063324658\n",
      "Generation 7880: M(n) = 862.6320056992192\n",
      "Generation 7881: p = 0.9584800063324658\n",
      "Generation 7881: M(n) = 862.6320056992192\n",
      "Generation 7882: p = 0.9584800063324658\n",
      "Generation 7882: M(n) = 862.6320056992192\n",
      "Generation 7883: p = 0.9584800063324658\n",
      "Generation 7883: M(n) = 862.6320056992192\n",
      "Generation 7884: p = 0.9584800063324658\n",
      "Generation 7884: M(n) = 862.6320056992192\n",
      "Generation 7885: p = 0.9584800063324658\n",
      "Generation 7885: M(n) = 862.6320056992192\n",
      "Generation 7886: p = 0.9584800063324658\n",
      "Generation 7886: M(n) = 862.6320056992192\n",
      "Generation 7887: p = 0.9584800063324658\n",
      "Generation 7887: M(n) = 862.6320056992192\n",
      "Generation 7888: p = 0.9584800063324658\n",
      "Generation 7888: M(n) = 862.6320056992192\n",
      "Generation 7889: p = 0.9584800063324658\n",
      "Generation 7889: M(n) = 862.6320056992192\n",
      "Generation 7890: p = 0.9584800063324658\n",
      "Generation 7890: M(n) = 862.6320056992192\n",
      "Generation 7891: p = 0.9584800063324658\n",
      "Generation 7891: M(n) = 862.6320056992192\n",
      "Generation 7892: p = 0.9584800063324658\n",
      "Generation 7892: M(n) = 862.6320056992192\n",
      "Generation 7893: p = 0.9584800063324658\n",
      "Generation 7893: M(n) = 862.6320056992192\n",
      "Generation 7894: p = 0.9584800063324658\n",
      "Generation 7894: M(n) = 862.6320056992192\n",
      "Generation 7895: p = 0.9584800063324658\n",
      "Generation 7895: M(n) = 862.6320056992192\n",
      "Generation 7896: p = 0.9584800063324658\n",
      "Generation 7896: M(n) = 862.6320056992192\n",
      "Generation 7897: p = 0.9584800063324658\n",
      "Generation 7897: M(n) = 862.6320056992192\n",
      "Generation 7898: p = 0.9584800063324658\n",
      "Generation 7898: M(n) = 862.6320056992192\n",
      "Generation 7899: p = 0.9584800063324658\n",
      "Generation 7899: M(n) = 862.6320056992192\n",
      "Generation 7900: p = 0.9584800063324658\n",
      "Generation 7900: M(n) = 862.6320056992192\n",
      "Generation 7901: p = 0.9584800063324658\n",
      "Generation 7901: M(n) = 862.6320056992192\n",
      "Generation 7902: p = 0.9584800063324658\n",
      "Generation 7902: M(n) = 862.6320056992192\n",
      "Generation 7903: p = 0.9584800063324658\n",
      "Generation 7903: M(n) = 862.6320056992192\n",
      "Generation 7904: p = 0.9584800063324658\n",
      "Generation 7904: M(n) = 862.6320056992192\n",
      "Generation 7905: p = 0.9584800063324658\n",
      "Generation 7905: M(n) = 862.6320056992192\n",
      "Generation 7906: p = 0.9584800063324658\n",
      "Generation 7906: M(n) = 862.6320056992192\n",
      "Generation 7907: p = 0.9584800063324658\n",
      "Generation 7907: M(n) = 862.6320056992192\n",
      "Generation 7908: p = 0.9584800063324658\n",
      "Generation 7908: M(n) = 862.6320056992192\n",
      "Generation 7909: p = 0.9584800063324658\n",
      "Generation 7909: M(n) = 862.6320056992192\n",
      "Generation 7910: p = 0.9584800063324658\n",
      "Generation 7910: M(n) = 862.6320056992192\n",
      "Generation 7911: p = 0.9584800063324658\n",
      "Generation 7911: M(n) = 862.6320056992192\n",
      "Generation 7912: p = 0.9584800063324658\n",
      "Generation 7912: M(n) = 862.6320056992192\n",
      "Generation 7913: p = 0.9584800063324658\n",
      "Generation 7913: M(n) = 862.6320056992192\n",
      "Generation 7914: p = 0.9584800063324658\n",
      "Generation 7914: M(n) = 862.6320056992192\n",
      "Generation 7915: p = 0.9584800063324658\n",
      "Generation 7915: M(n) = 862.6320056992192\n",
      "Generation 7916: p = 0.9584800063324658\n",
      "Generation 7916: M(n) = 862.6320056992192\n",
      "Generation 7917: p = 0.9584800063324658\n",
      "Generation 7917: M(n) = 862.6320056992192\n",
      "Generation 7918: p = 0.9584800063324658\n",
      "Generation 7918: M(n) = 862.6320056992192\n",
      "Generation 7919: p = 0.9584800063324658\n",
      "Generation 7919: M(n) = 862.6320056992192\n",
      "Generation 7920: p = 0.9584800063324658\n",
      "Generation 7920: M(n) = 862.6320056992192\n",
      "Generation 7921: p = 0.9584800063324658\n",
      "Generation 7921: M(n) = 862.6320056992192\n",
      "Generation 7922: p = 0.9584800063324658\n",
      "Generation 7922: M(n) = 862.6320056992192\n",
      "Generation 7923: p = 0.9584800063324658\n",
      "Generation 7923: M(n) = 862.6320056992192\n",
      "Generation 7924: p = 0.9584800063324658\n",
      "Generation 7924: M(n) = 862.6320056992192\n",
      "Generation 7925: p = 0.9584800063324658\n",
      "Generation 7925: M(n) = 862.6320056992192\n",
      "Generation 7926: p = 0.9584800063324658\n",
      "Generation 7926: M(n) = 862.6320056992192\n",
      "Generation 7927: p = 0.9584800063324658\n",
      "Generation 7927: M(n) = 862.6320056992192\n",
      "Generation 7928: p = 0.9584800063324658\n",
      "Generation 7928: M(n) = 862.6320056992192\n",
      "Generation 7929: p = 0.9584800063324658\n",
      "Generation 7929: M(n) = 862.6320056992192\n",
      "Generation 7930: p = 0.9584800063324658\n",
      "Generation 7930: M(n) = 862.6320056992192\n",
      "Generation 7931: p = 0.9584800063324658\n",
      "Generation 7931: M(n) = 862.6320056992192\n",
      "Generation 7932: p = 0.9584800063324658\n",
      "Generation 7932: M(n) = 862.6320056992192\n",
      "Generation 7933: p = 0.9584800063324658\n",
      "Generation 7933: M(n) = 862.6320056992192\n",
      "Generation 7934: p = 0.9584800063324658\n",
      "Generation 7934: M(n) = 862.6320056992192\n",
      "Generation 7935: p = 0.9584800063324658\n",
      "Generation 7935: M(n) = 862.6320056992192\n",
      "Generation 7936: p = 0.9584800063324658\n",
      "Generation 7936: M(n) = 862.6320056992192\n",
      "Generation 7937: p = 0.9584800063324658\n",
      "Generation 7937: M(n) = 862.6320056992192\n",
      "Generation 7938: p = 0.9584800063324658\n",
      "Generation 7938: M(n) = 862.6320056992192\n",
      "Generation 7939: p = 0.9584800063324658\n",
      "Generation 7939: M(n) = 862.6320056992192\n",
      "Generation 7940: p = 0.9584800063324658\n",
      "Generation 7940: M(n) = 862.6320056992192\n",
      "Generation 7941: p = 0.9584800063324658\n",
      "Generation 7941: M(n) = 862.6320056992192\n",
      "Generation 7942: p = 0.9584800063324658\n",
      "Generation 7942: M(n) = 862.6320056992192\n",
      "Generation 7943: p = 0.9584800063324658\n",
      "Generation 7943: M(n) = 862.6320056992192\n",
      "Generation 7944: p = 0.9584800063324658\n",
      "Generation 7944: M(n) = 862.6320056992192\n",
      "Generation 7945: p = 0.9584800063324658\n",
      "Generation 7945: M(n) = 862.6320056992192\n",
      "Generation 7946: p = 0.9584800063324658\n",
      "Generation 7946: M(n) = 862.6320056992192\n",
      "Generation 7947: p = 0.9584800063324658\n",
      "Generation 7947: M(n) = 862.6320056992192\n",
      "Generation 7948: p = 0.9584800063324658\n",
      "Generation 7948: M(n) = 862.6320056992192\n",
      "Generation 7949: p = 0.9584800063324658\n",
      "Generation 7949: M(n) = 862.6320056992192\n",
      "Generation 7950: p = 0.9584800063324658\n",
      "Generation 7950: M(n) = 862.6320056992192\n",
      "Generation 7951: p = 0.9584800063324658\n",
      "Generation 7951: M(n) = 862.6320056992192\n",
      "Generation 7952: p = 0.9584800063324658\n",
      "Generation 7952: M(n) = 862.6320056992192\n",
      "Generation 7953: p = 0.9584800063324658\n",
      "Generation 7953: M(n) = 862.6320056992192\n",
      "Generation 7954: p = 0.9584800063324658\n",
      "Generation 7954: M(n) = 862.6320056992192\n",
      "Generation 7955: p = 0.9584800063324658\n",
      "Generation 7955: M(n) = 862.6320056992192\n",
      "Generation 7956: p = 0.9584800063324658\n",
      "Generation 7956: M(n) = 862.6320056992192\n",
      "Generation 7957: p = 0.9584800063324658\n",
      "Generation 7957: M(n) = 862.6320056992192\n",
      "Generation 7958: p = 0.9584800063324658\n",
      "Generation 7958: M(n) = 862.6320056992192\n",
      "Generation 7959: p = 0.9584800063324658\n",
      "Generation 7959: M(n) = 862.6320056992192\n",
      "Generation 7960: p = 0.9584800063324658\n",
      "Generation 7960: M(n) = 862.6320056992192\n",
      "Generation 7961: p = 0.9584800063324658\n",
      "Generation 7961: M(n) = 862.6320056992192\n",
      "Generation 7962: p = 0.9584800063324658\n",
      "Generation 7962: M(n) = 862.6320056992192\n",
      "Generation 7963: p = 0.9584800063324658\n",
      "Generation 7963: M(n) = 862.6320056992192\n",
      "Generation 7964: p = 0.9584800063324658\n",
      "Generation 7964: M(n) = 862.6320056992192\n",
      "Generation 7965: p = 0.9584800063324658\n",
      "Generation 7965: M(n) = 862.6320056992192\n",
      "Generation 7966: p = 0.9584800063324658\n",
      "Generation 7966: M(n) = 862.6320056992192\n",
      "Generation 7967: p = 0.9584800063324658\n",
      "Generation 7967: M(n) = 862.6320056992192\n",
      "Generation 7968: p = 0.9584800063324658\n",
      "Generation 7968: M(n) = 862.6320056992192\n",
      "Generation 7969: p = 0.9584800063324658\n",
      "Generation 7969: M(n) = 862.6320056992192\n",
      "Generation 7970: p = 0.9584800063324658\n",
      "Generation 7970: M(n) = 862.6320056992192\n",
      "Generation 7971: p = 0.9584800063324658\n",
      "Generation 7971: M(n) = 862.6320056992192\n",
      "Generation 7972: p = 0.9584800063324658\n",
      "Generation 7972: M(n) = 862.6320056992192\n",
      "Generation 7973: p = 0.9584800063324658\n",
      "Generation 7973: M(n) = 862.6320056992192\n",
      "Generation 7974: p = 0.9584800063324658\n",
      "Generation 7974: M(n) = 862.6320056992192\n",
      "Generation 7975: p = 0.9584800063324658\n",
      "Generation 7975: M(n) = 862.6320056992192\n",
      "Generation 7976: p = 0.9584800063324658\n",
      "Generation 7976: M(n) = 862.6320056992192\n",
      "Generation 7977: p = 0.9584800063324658\n",
      "Generation 7977: M(n) = 862.6320056992192\n",
      "Generation 7978: p = 0.9584800063324658\n",
      "Generation 7978: M(n) = 862.6320056992192\n",
      "Generation 7979: p = 0.9584800063324658\n",
      "Generation 7979: M(n) = 862.6320056992192\n",
      "Generation 7980: p = 0.9584800063324658\n",
      "Generation 7980: M(n) = 862.6320056992192\n",
      "Generation 7981: p = 0.9584800063324658\n",
      "Generation 7981: M(n) = 862.6320056992192\n",
      "Generation 7982: p = 0.9584800063324658\n",
      "Generation 7982: M(n) = 862.6320056992192\n",
      "Generation 7983: p = 0.9584800063324658\n",
      "Generation 7983: M(n) = 862.6320056992192\n",
      "Generation 7984: p = 0.9584800063324658\n",
      "Generation 7984: M(n) = 862.6320056992192\n",
      "Generation 7985: p = 0.9584800063324658\n",
      "Generation 7985: M(n) = 862.6320056992192\n",
      "Generation 7986: p = 0.9584800063324658\n",
      "Generation 7986: M(n) = 862.6320056992192\n",
      "Generation 7987: p = 0.9584800063324658\n",
      "Generation 7987: M(n) = 862.6320056992192\n",
      "Generation 7988: p = 0.9584800063324658\n",
      "Generation 7988: M(n) = 862.6320056992192\n",
      "Generation 7989: p = 0.9584800063324658\n",
      "Generation 7989: M(n) = 862.6320056992192\n",
      "Generation 7990: p = 0.9584800063324658\n",
      "Generation 7990: M(n) = 862.6320056992192\n",
      "Generation 7991: p = 0.9584800063324658\n",
      "Generation 7991: M(n) = 862.6320056992192\n",
      "Generation 7992: p = 0.9584800063324658\n",
      "Generation 7992: M(n) = 862.6320056992192\n",
      "Generation 7993: p = 0.9584800063324658\n",
      "Generation 7993: M(n) = 862.6320056992192\n",
      "Generation 7994: p = 0.9584800063324658\n",
      "Generation 7994: M(n) = 862.6320056992192\n",
      "Generation 7995: p = 0.9584800063324658\n",
      "Generation 7995: M(n) = 862.6320056992192\n",
      "Generation 7996: p = 0.9584800063324658\n",
      "Generation 7996: M(n) = 862.6320056992192\n",
      "Generation 7997: p = 0.9584800063324658\n",
      "Generation 7997: M(n) = 862.6320056992192\n",
      "Generation 7998: p = 0.9584800063324658\n",
      "Generation 7998: M(n) = 862.6320056992192\n",
      "Generation 7999: p = 0.9584800063324658\n",
      "Generation 7999: M(n) = 862.6320056992192\n",
      "Generation 8000: p = 0.9584800063324658\n",
      "Generation 8000: M(n) = 862.6320056992192\n",
      "Generation 8001: p = 0.9584800063324658\n",
      "Generation 8001: M(n) = 862.6320056992192\n",
      "Generation 8002: p = 0.9584800063324658\n",
      "Generation 8002: M(n) = 862.6320056992192\n",
      "Generation 8003: p = 0.9584800063324658\n",
      "Generation 8003: M(n) = 862.6320056992192\n",
      "Generation 8004: p = 0.9584800063324658\n",
      "Generation 8004: M(n) = 862.6320056992192\n",
      "Generation 8005: p = 0.9584800063324658\n",
      "Generation 8005: M(n) = 862.6320056992192\n",
      "Generation 8006: p = 0.9584800063324658\n",
      "Generation 8006: M(n) = 862.6320056992192\n",
      "Generation 8007: p = 0.9584800063324658\n",
      "Generation 8007: M(n) = 862.6320056992192\n",
      "Generation 8008: p = 0.9584800063324658\n",
      "Generation 8008: M(n) = 862.6320056992192\n",
      "Generation 8009: p = 0.9584800063324658\n",
      "Generation 8009: M(n) = 862.6320056992192\n",
      "Generation 8010: p = 0.9584800063324658\n",
      "Generation 8010: M(n) = 862.6320056992192\n",
      "Generation 8011: p = 0.9584800063324658\n",
      "Generation 8011: M(n) = 862.6320056992192\n",
      "Generation 8012: p = 0.9584800063324658\n",
      "Generation 8012: M(n) = 862.6320056992192\n",
      "Generation 8013: p = 0.9584800063324658\n",
      "Generation 8013: M(n) = 862.6320056992192\n",
      "Generation 8014: p = 0.9584800063324658\n",
      "Generation 8014: M(n) = 862.6320056992192\n",
      "Generation 8015: p = 0.9584800063324658\n",
      "Generation 8015: M(n) = 862.6320056992192\n",
      "Generation 8016: p = 0.9584800063324658\n",
      "Generation 8016: M(n) = 862.6320056992192\n",
      "Generation 8017: p = 0.9584800063324658\n",
      "Generation 8017: M(n) = 862.6320056992192\n",
      "Generation 8018: p = 0.9584800063324658\n",
      "Generation 8018: M(n) = 862.6320056992192\n",
      "Generation 8019: p = 0.9584800063324658\n",
      "Generation 8019: M(n) = 862.6320056992192\n",
      "Generation 8020: p = 0.9584800063324658\n",
      "Generation 8020: M(n) = 862.6320056992192\n",
      "Generation 8021: p = 0.9584800063324658\n",
      "Generation 8021: M(n) = 862.6320056992192\n",
      "Generation 8022: p = 0.9584800063324658\n",
      "Generation 8022: M(n) = 862.6320056992192\n",
      "Generation 8023: p = 0.9584800063324658\n",
      "Generation 8023: M(n) = 862.6320056992192\n",
      "Generation 8024: p = 0.9584800063324658\n",
      "Generation 8024: M(n) = 862.6320056992192\n",
      "Generation 8025: p = 0.9584800063324658\n",
      "Generation 8025: M(n) = 862.6320056992192\n",
      "Generation 8026: p = 0.9584800063324658\n",
      "Generation 8026: M(n) = 862.6320056992192\n",
      "Generation 8027: p = 0.9584800063324658\n",
      "Generation 8027: M(n) = 862.6320056992192\n",
      "Generation 8028: p = 0.9584800063324658\n",
      "Generation 8028: M(n) = 862.6320056992192\n",
      "Generation 8029: p = 0.9584800063324658\n",
      "Generation 8029: M(n) = 862.6320056992192\n",
      "Generation 8030: p = 0.9584800063324658\n",
      "Generation 8030: M(n) = 862.6320056992192\n",
      "Generation 8031: p = 0.9584800063324658\n",
      "Generation 8031: M(n) = 862.6320056992192\n",
      "Generation 8032: p = 0.9584800063324658\n",
      "Generation 8032: M(n) = 862.6320056992192\n",
      "Generation 8033: p = 0.9584800063324658\n",
      "Generation 8033: M(n) = 862.6320056992192\n",
      "Generation 8034: p = 0.9584800063324658\n",
      "Generation 8034: M(n) = 862.6320056992192\n",
      "Generation 8035: p = 0.9584800063324658\n",
      "Generation 8035: M(n) = 862.6320056992192\n",
      "Generation 8036: p = 0.9584800063324658\n",
      "Generation 8036: M(n) = 862.6320056992192\n",
      "Generation 8037: p = 0.9584800063324658\n",
      "Generation 8037: M(n) = 862.6320056992192\n",
      "Generation 8038: p = 0.9584800063324658\n",
      "Generation 8038: M(n) = 862.6320056992192\n",
      "Generation 8039: p = 0.9584800063324658\n",
      "Generation 8039: M(n) = 862.6320056992192\n",
      "Generation 8040: p = 0.9584800063324658\n",
      "Generation 8040: M(n) = 862.6320056992192\n",
      "Generation 8041: p = 0.9584800063324658\n",
      "Generation 8041: M(n) = 862.6320056992192\n",
      "Generation 8042: p = 0.9584800063324658\n",
      "Generation 8042: M(n) = 862.6320056992192\n",
      "Generation 8043: p = 0.9584800063324658\n",
      "Generation 8043: M(n) = 862.6320056992192\n",
      "Generation 8044: p = 0.9584800063324658\n",
      "Generation 8044: M(n) = 862.6320056992192\n",
      "Generation 8045: p = 0.9584800063324658\n",
      "Generation 8045: M(n) = 862.6320056992192\n",
      "Generation 8046: p = 0.9584800063324658\n",
      "Generation 8046: M(n) = 862.6320056992192\n",
      "Generation 8047: p = 0.9584800063324658\n",
      "Generation 8047: M(n) = 862.6320056992192\n",
      "Generation 8048: p = 0.9584800063324658\n",
      "Generation 8048: M(n) = 862.6320056992192\n",
      "Generation 8049: p = 0.9584800063324658\n",
      "Generation 8049: M(n) = 862.6320056992192\n",
      "Generation 8050: p = 0.9584800063324658\n",
      "Generation 8050: M(n) = 862.6320056992192\n",
      "Generation 8051: p = 0.9584800063324658\n",
      "Generation 8051: M(n) = 862.6320056992192\n",
      "Generation 8052: p = 0.9584800063324658\n",
      "Generation 8052: M(n) = 862.6320056992192\n",
      "Generation 8053: p = 0.9584800063324658\n",
      "Generation 8053: M(n) = 862.6320056992192\n",
      "Generation 8054: p = 0.9584800063324658\n",
      "Generation 8054: M(n) = 862.6320056992192\n",
      "Generation 8055: p = 0.9584800063324658\n",
      "Generation 8055: M(n) = 862.6320056992192\n",
      "Generation 8056: p = 0.9584800063324658\n",
      "Generation 8056: M(n) = 862.6320056992192\n",
      "Generation 8057: p = 0.9584800063324658\n",
      "Generation 8057: M(n) = 862.6320056992192\n",
      "Generation 8058: p = 0.9584800063324658\n",
      "Generation 8058: M(n) = 862.6320056992192\n",
      "Generation 8059: p = 0.9584800063324658\n",
      "Generation 8059: M(n) = 862.6320056992192\n",
      "Generation 8060: p = 0.9584800063324658\n",
      "Generation 8060: M(n) = 862.6320056992192\n",
      "Generation 8061: p = 0.9584800063324658\n",
      "Generation 8061: M(n) = 862.6320056992192\n",
      "Generation 8062: p = 0.9584800063324658\n",
      "Generation 8062: M(n) = 862.6320056992192\n",
      "Generation 8063: p = 0.9584800063324658\n",
      "Generation 8063: M(n) = 862.6320056992192\n",
      "Generation 8064: p = 0.9584800063324658\n",
      "Generation 8064: M(n) = 862.6320056992192\n",
      "Generation 8065: p = 0.9584800063324658\n",
      "Generation 8065: M(n) = 862.6320056992192\n",
      "Generation 8066: p = 0.9584800063324658\n",
      "Generation 8066: M(n) = 862.6320056992192\n",
      "Generation 8067: p = 0.9584800063324658\n",
      "Generation 8067: M(n) = 862.6320056992192\n",
      "Generation 8068: p = 0.9584800063324658\n",
      "Generation 8068: M(n) = 862.6320056992192\n",
      "Generation 8069: p = 0.9584800063324658\n",
      "Generation 8069: M(n) = 862.6320056992192\n",
      "Generation 8070: p = 0.9584800063324658\n",
      "Generation 8070: M(n) = 862.6320056992192\n",
      "Generation 8071: p = 0.9584800063324658\n",
      "Generation 8071: M(n) = 862.6320056992192\n",
      "Generation 8072: p = 0.9584800063324658\n",
      "Generation 8072: M(n) = 862.6320056992192\n",
      "Generation 8073: p = 0.9584800063324658\n",
      "Generation 8073: M(n) = 862.6320056992192\n",
      "Generation 8074: p = 0.9584800063324658\n",
      "Generation 8074: M(n) = 862.6320056992192\n",
      "Generation 8075: p = 0.9584800063324658\n",
      "Generation 8075: M(n) = 862.6320056992192\n",
      "Generation 8076: p = 0.9584800063324658\n",
      "Generation 8076: M(n) = 862.6320056992192\n",
      "Generation 8077: p = 0.9584800063324658\n",
      "Generation 8077: M(n) = 862.6320056992192\n",
      "Generation 8078: p = 0.9584800063324658\n",
      "Generation 8078: M(n) = 862.6320056992192\n",
      "Generation 8079: p = 0.9584800063324658\n",
      "Generation 8079: M(n) = 862.6320056992192\n",
      "Generation 8080: p = 0.9584800063324658\n",
      "Generation 8080: M(n) = 862.6320056992192\n",
      "Generation 8081: p = 0.9584800063324658\n",
      "Generation 8081: M(n) = 862.6320056992192\n",
      "Generation 8082: p = 0.9584800063324658\n",
      "Generation 8082: M(n) = 862.6320056992192\n",
      "Generation 8083: p = 0.9584800063324658\n",
      "Generation 8083: M(n) = 862.6320056992192\n",
      "Generation 8084: p = 0.9584800063324658\n",
      "Generation 8084: M(n) = 862.6320056992192\n",
      "Generation 8085: p = 0.9584800063324658\n",
      "Generation 8085: M(n) = 862.6320056992192\n",
      "Generation 8086: p = 0.9584800063324658\n",
      "Generation 8086: M(n) = 862.6320056992192\n",
      "Generation 8087: p = 0.9584800063324658\n",
      "Generation 8087: M(n) = 862.6320056992192\n",
      "Generation 8088: p = 0.9584800063324658\n",
      "Generation 8088: M(n) = 862.6320056992192\n",
      "Generation 8089: p = 0.9584800063324658\n",
      "Generation 8089: M(n) = 862.6320056992192\n",
      "Generation 8090: p = 0.9584800063324658\n",
      "Generation 8090: M(n) = 862.6320056992192\n",
      "Generation 8091: p = 0.9584800063324658\n",
      "Generation 8091: M(n) = 862.6320056992192\n",
      "Generation 8092: p = 0.9584800063324658\n",
      "Generation 8092: M(n) = 862.6320056992192\n",
      "Generation 8093: p = 0.9584800063324658\n",
      "Generation 8093: M(n) = 862.6320056992192\n",
      "Generation 8094: p = 0.9584800063324658\n",
      "Generation 8094: M(n) = 862.6320056992192\n",
      "Generation 8095: p = 0.9584800063324658\n",
      "Generation 8095: M(n) = 862.6320056992192\n",
      "Generation 8096: p = 0.9584800063324658\n",
      "Generation 8096: M(n) = 862.6320056992192\n",
      "Generation 8097: p = 0.9584800063324658\n",
      "Generation 8097: M(n) = 862.6320056992192\n",
      "Generation 8098: p = 0.9584800063324658\n",
      "Generation 8098: M(n) = 862.6320056992192\n",
      "Generation 8099: p = 0.9584800063324658\n",
      "Generation 8099: M(n) = 862.6320056992192\n",
      "Generation 8100: p = 0.9584800063324658\n",
      "Generation 8100: M(n) = 862.6320056992192\n",
      "Generation 8101: p = 0.9584800063324658\n",
      "Generation 8101: M(n) = 862.6320056992192\n",
      "Generation 8102: p = 0.9584800063324658\n",
      "Generation 8102: M(n) = 862.6320056992192\n",
      "Generation 8103: p = 0.9584800063324658\n",
      "Generation 8103: M(n) = 862.6320056992192\n",
      "Generation 8104: p = 0.9584800063324658\n",
      "Generation 8104: M(n) = 862.6320056992192\n",
      "Generation 8105: p = 0.9584800063324658\n",
      "Generation 8105: M(n) = 862.6320056992192\n",
      "Generation 8106: p = 0.9584800063324658\n",
      "Generation 8106: M(n) = 862.6320056992192\n",
      "Generation 8107: p = 0.9584800063324658\n",
      "Generation 8107: M(n) = 862.6320056992192\n",
      "Generation 8108: p = 0.9584800063324658\n",
      "Generation 8108: M(n) = 862.6320056992192\n",
      "Generation 8109: p = 0.9584800063324658\n",
      "Generation 8109: M(n) = 862.6320056992192\n",
      "Generation 8110: p = 0.9584800063324658\n",
      "Generation 8110: M(n) = 862.6320056992192\n",
      "Generation 8111: p = 0.9584800063324658\n",
      "Generation 8111: M(n) = 862.6320056992192\n",
      "Generation 8112: p = 0.9584800063324658\n",
      "Generation 8112: M(n) = 862.6320056992192\n",
      "Generation 8113: p = 0.9584800063324658\n",
      "Generation 8113: M(n) = 862.6320056992192\n",
      "Generation 8114: p = 0.9584800063324658\n",
      "Generation 8114: M(n) = 862.6320056992192\n",
      "Generation 8115: p = 0.9584800063324658\n",
      "Generation 8115: M(n) = 862.6320056992192\n",
      "Generation 8116: p = 0.9584800063324658\n",
      "Generation 8116: M(n) = 862.6320056992192\n",
      "Generation 8117: p = 0.9584800063324658\n",
      "Generation 8117: M(n) = 862.6320056992192\n",
      "Generation 8118: p = 0.9584800063324658\n",
      "Generation 8118: M(n) = 862.6320056992192\n",
      "Generation 8119: p = 0.9584800063324658\n",
      "Generation 8119: M(n) = 862.6320056992192\n",
      "Generation 8120: p = 0.9584800063324658\n",
      "Generation 8120: M(n) = 862.6320056992192\n",
      "Generation 8121: p = 0.9584800063324658\n",
      "Generation 8121: M(n) = 862.6320056992192\n",
      "Generation 8122: p = 0.9584800063324658\n",
      "Generation 8122: M(n) = 862.6320056992192\n",
      "Generation 8123: p = 0.9584800063324658\n",
      "Generation 8123: M(n) = 862.6320056992192\n",
      "Generation 8124: p = 0.9584800063324658\n",
      "Generation 8124: M(n) = 862.6320056992192\n",
      "Generation 8125: p = 0.9584800063324658\n",
      "Generation 8125: M(n) = 862.6320056992192\n",
      "Generation 8126: p = 0.9584800063324658\n",
      "Generation 8126: M(n) = 862.6320056992192\n",
      "Generation 8127: p = 0.9584800063324658\n",
      "Generation 8127: M(n) = 862.6320056992192\n",
      "Generation 8128: p = 0.9584800063324658\n",
      "Generation 8128: M(n) = 862.6320056992192\n",
      "Generation 8129: p = 0.9584800063324658\n",
      "Generation 8129: M(n) = 862.6320056992192\n",
      "Generation 8130: p = 0.9584800063324658\n",
      "Generation 8130: M(n) = 862.6320056992192\n",
      "Generation 8131: p = 0.9584800063324658\n",
      "Generation 8131: M(n) = 862.6320056992192\n",
      "Generation 8132: p = 0.9584800063324658\n",
      "Generation 8132: M(n) = 862.6320056992192\n",
      "Generation 8133: p = 0.9584800063324658\n",
      "Generation 8133: M(n) = 862.6320056992192\n",
      "Generation 8134: p = 0.9584800063324658\n",
      "Generation 8134: M(n) = 862.6320056992192\n",
      "Generation 8135: p = 0.9584800063324658\n",
      "Generation 8135: M(n) = 862.6320056992192\n",
      "Generation 8136: p = 0.9584800063324658\n",
      "Generation 8136: M(n) = 862.6320056992192\n",
      "Generation 8137: p = 0.9584800063324658\n",
      "Generation 8137: M(n) = 862.6320056992192\n",
      "Generation 8138: p = 0.9584800063324658\n",
      "Generation 8138: M(n) = 862.6320056992192\n",
      "Generation 8139: p = 0.9584800063324658\n",
      "Generation 8139: M(n) = 862.6320056992192\n",
      "Generation 8140: p = 0.9584800063324658\n",
      "Generation 8140: M(n) = 862.6320056992192\n",
      "Generation 8141: p = 0.9584800063324658\n",
      "Generation 8141: M(n) = 862.6320056992192\n",
      "Generation 8142: p = 0.9584800063324658\n",
      "Generation 8142: M(n) = 862.6320056992192\n",
      "Generation 8143: p = 0.9584800063324658\n",
      "Generation 8143: M(n) = 862.6320056992192\n",
      "Generation 8144: p = 0.9584800063324658\n",
      "Generation 8144: M(n) = 862.6320056992192\n",
      "Generation 8145: p = 0.9584800063324658\n",
      "Generation 8145: M(n) = 862.6320056992192\n",
      "Generation 8146: p = 0.9584800063324658\n",
      "Generation 8146: M(n) = 862.6320056992192\n",
      "Generation 8147: p = 0.9584800063324658\n",
      "Generation 8147: M(n) = 862.6320056992192\n",
      "Generation 8148: p = 0.9584800063324658\n",
      "Generation 8148: M(n) = 862.6320056992192\n",
      "Generation 8149: p = 0.9584800063324658\n",
      "Generation 8149: M(n) = 862.6320056992192\n",
      "Generation 8150: p = 0.9584800063324658\n",
      "Generation 8150: M(n) = 862.6320056992192\n",
      "Generation 8151: p = 0.9584800063324658\n",
      "Generation 8151: M(n) = 862.6320056992192\n",
      "Generation 8152: p = 0.9584800063324658\n",
      "Generation 8152: M(n) = 862.6320056992192\n",
      "Generation 8153: p = 0.9584800063324658\n",
      "Generation 8153: M(n) = 862.6320056992192\n",
      "Generation 8154: p = 0.9584800063324658\n",
      "Generation 8154: M(n) = 862.6320056992192\n",
      "Generation 8155: p = 0.9584800063324658\n",
      "Generation 8155: M(n) = 862.6320056992192\n",
      "Generation 8156: p = 0.9584800063324658\n",
      "Generation 8156: M(n) = 862.6320056992192\n",
      "Generation 8157: p = 0.9584800063324658\n",
      "Generation 8157: M(n) = 862.6320056992192\n",
      "Generation 8158: p = 0.9584800063324658\n",
      "Generation 8158: M(n) = 862.6320056992192\n",
      "Generation 8159: p = 0.9584800063324658\n",
      "Generation 8159: M(n) = 862.6320056992192\n",
      "Generation 8160: p = 0.9584800063324658\n",
      "Generation 8160: M(n) = 862.6320056992192\n",
      "Generation 8161: p = 0.9584800063324658\n",
      "Generation 8161: M(n) = 862.6320056992192\n",
      "Generation 8162: p = 0.9584800063324658\n",
      "Generation 8162: M(n) = 862.6320056992192\n",
      "Generation 8163: p = 0.9584800063324658\n",
      "Generation 8163: M(n) = 862.6320056992192\n",
      "Generation 8164: p = 0.9584800063324658\n",
      "Generation 8164: M(n) = 862.6320056992192\n",
      "Generation 8165: p = 0.9584800063324658\n",
      "Generation 8165: M(n) = 862.6320056992192\n",
      "Generation 8166: p = 0.9584800063324658\n",
      "Generation 8166: M(n) = 862.6320056992192\n",
      "Generation 8167: p = 0.9584800063324658\n",
      "Generation 8167: M(n) = 862.6320056992192\n",
      "Generation 8168: p = 0.9584800063324658\n",
      "Generation 8168: M(n) = 862.6320056992192\n",
      "Generation 8169: p = 0.9584800063324658\n",
      "Generation 8169: M(n) = 862.6320056992192\n",
      "Generation 8170: p = 0.9584800063324658\n",
      "Generation 8170: M(n) = 862.6320056992192\n",
      "Generation 8171: p = 0.9584800063324658\n",
      "Generation 8171: M(n) = 862.6320056992192\n",
      "Generation 8172: p = 0.9584800063324658\n",
      "Generation 8172: M(n) = 862.6320056992192\n",
      "Generation 8173: p = 0.9584800063324658\n",
      "Generation 8173: M(n) = 862.6320056992192\n",
      "Generation 8174: p = 0.9584800063324658\n",
      "Generation 8174: M(n) = 862.6320056992192\n",
      "Generation 8175: p = 0.9584800063324658\n",
      "Generation 8175: M(n) = 862.6320056992192\n",
      "Generation 8176: p = 0.9584800063324658\n",
      "Generation 8176: M(n) = 862.6320056992192\n",
      "Generation 8177: p = 0.9584800063324658\n",
      "Generation 8177: M(n) = 862.6320056992192\n",
      "Generation 8178: p = 0.9584800063324658\n",
      "Generation 8178: M(n) = 862.6320056992192\n",
      "Generation 8179: p = 0.9584800063324658\n",
      "Generation 8179: M(n) = 862.6320056992192\n",
      "Generation 8180: p = 0.9584800063324658\n",
      "Generation 8180: M(n) = 862.6320056992192\n",
      "Generation 8181: p = 0.9584800063324658\n",
      "Generation 8181: M(n) = 862.6320056992192\n",
      "Generation 8182: p = 0.9584800063324658\n",
      "Generation 8182: M(n) = 862.6320056992192\n",
      "Generation 8183: p = 0.9584800063324658\n",
      "Generation 8183: M(n) = 862.6320056992192\n",
      "Generation 8184: p = 0.9584800063324658\n",
      "Generation 8184: M(n) = 862.6320056992192\n",
      "Generation 8185: p = 0.9584800063324658\n",
      "Generation 8185: M(n) = 862.6320056992192\n",
      "Generation 8186: p = 0.9584800063324658\n",
      "Generation 8186: M(n) = 862.6320056992192\n",
      "Generation 8187: p = 0.9584800063324658\n",
      "Generation 8187: M(n) = 862.6320056992192\n",
      "Generation 8188: p = 0.9584800063324658\n",
      "Generation 8188: M(n) = 862.6320056992192\n",
      "Generation 8189: p = 0.9584800063324658\n",
      "Generation 8189: M(n) = 862.6320056992192\n",
      "Generation 8190: p = 0.9584800063324658\n",
      "Generation 8190: M(n) = 862.6320056992192\n",
      "Generation 8191: p = 0.9584800063324658\n",
      "Generation 8191: M(n) = 862.6320056992192\n",
      "Generation 8192: p = 0.9584800063324658\n",
      "Generation 8192: M(n) = 862.6320056992192\n",
      "Generation 8193: p = 0.9584800063324658\n",
      "Generation 8193: M(n) = 862.6320056992192\n",
      "Generation 8194: p = 0.9584800063324658\n",
      "Generation 8194: M(n) = 862.6320056992192\n",
      "Generation 8195: p = 0.9584800063324658\n",
      "Generation 8195: M(n) = 862.6320056992192\n",
      "Generation 8196: p = 0.9584800063324658\n",
      "Generation 8196: M(n) = 862.6320056992192\n",
      "Generation 8197: p = 0.9584800063324658\n",
      "Generation 8197: M(n) = 862.6320056992192\n",
      "Generation 8198: p = 0.9584800063324658\n",
      "Generation 8198: M(n) = 862.6320056992192\n",
      "Generation 8199: p = 0.9584800063324658\n",
      "Generation 8199: M(n) = 862.6320056992192\n",
      "Generation 8200: p = 0.9584800063324658\n",
      "Generation 8200: M(n) = 862.6320056992192\n",
      "Generation 8201: p = 0.9584800063324658\n",
      "Generation 8201: M(n) = 862.6320056992192\n",
      "Generation 8202: p = 0.9584800063324658\n",
      "Generation 8202: M(n) = 862.6320056992192\n",
      "Generation 8203: p = 0.9584800063324658\n",
      "Generation 8203: M(n) = 862.6320056992192\n",
      "Generation 8204: p = 0.9584800063324658\n",
      "Generation 8204: M(n) = 862.6320056992192\n",
      "Generation 8205: p = 0.9584800063324658\n",
      "Generation 8205: M(n) = 862.6320056992192\n",
      "Generation 8206: p = 0.9584800063324658\n",
      "Generation 8206: M(n) = 862.6320056992192\n",
      "Generation 8207: p = 0.9584800063324658\n",
      "Generation 8207: M(n) = 862.6320056992192\n",
      "Generation 8208: p = 0.9584800063324658\n",
      "Generation 8208: M(n) = 862.6320056992192\n",
      "Generation 8209: p = 0.9584800063324658\n",
      "Generation 8209: M(n) = 862.6320056992192\n",
      "Generation 8210: p = 0.9584800063324658\n",
      "Generation 8210: M(n) = 862.6320056992192\n",
      "Generation 8211: p = 0.9584800063324658\n",
      "Generation 8211: M(n) = 862.6320056992192\n",
      "Generation 8212: p = 0.9584800063324658\n",
      "Generation 8212: M(n) = 862.6320056992192\n",
      "Generation 8213: p = 0.9584800063324658\n",
      "Generation 8213: M(n) = 862.6320056992192\n",
      "Generation 8214: p = 0.9584800063324658\n",
      "Generation 8214: M(n) = 862.6320056992192\n",
      "Generation 8215: p = 0.9584800063324658\n",
      "Generation 8215: M(n) = 862.6320056992192\n",
      "Generation 8216: p = 0.9584800063324658\n",
      "Generation 8216: M(n) = 862.6320056992192\n",
      "Generation 8217: p = 0.9584800063324658\n",
      "Generation 8217: M(n) = 862.6320056992192\n",
      "Generation 8218: p = 0.9584800063324658\n",
      "Generation 8218: M(n) = 862.6320056992192\n",
      "Generation 8219: p = 0.9584800063324658\n",
      "Generation 8219: M(n) = 862.6320056992192\n",
      "Generation 8220: p = 0.9584800063324658\n",
      "Generation 8220: M(n) = 862.6320056992192\n",
      "Generation 8221: p = 0.9584800063324658\n",
      "Generation 8221: M(n) = 862.6320056992192\n",
      "Generation 8222: p = 0.9584800063324658\n",
      "Generation 8222: M(n) = 862.6320056992192\n",
      "Generation 8223: p = 0.9584800063324658\n",
      "Generation 8223: M(n) = 862.6320056992192\n",
      "Generation 8224: p = 0.9584800063324658\n",
      "Generation 8224: M(n) = 862.6320056992192\n",
      "Generation 8225: p = 0.9584800063324658\n",
      "Generation 8225: M(n) = 862.6320056992192\n",
      "Generation 8226: p = 0.9584800063324658\n",
      "Generation 8226: M(n) = 862.6320056992192\n",
      "Generation 8227: p = 0.9584800063324658\n",
      "Generation 8227: M(n) = 862.6320056992192\n",
      "Generation 8228: p = 0.9584800063324658\n",
      "Generation 8228: M(n) = 862.6320056992192\n",
      "Generation 8229: p = 0.9584800063324658\n",
      "Generation 8229: M(n) = 862.6320056992192\n",
      "Generation 8230: p = 0.9584800063324658\n",
      "Generation 8230: M(n) = 862.6320056992192\n",
      "Generation 8231: p = 0.9584800063324658\n",
      "Generation 8231: M(n) = 862.6320056992192\n",
      "Generation 8232: p = 0.9584800063324658\n",
      "Generation 8232: M(n) = 862.6320056992192\n",
      "Generation 8233: p = 0.9584800063324658\n",
      "Generation 8233: M(n) = 862.6320056992192\n",
      "Generation 8234: p = 0.9584800063324658\n",
      "Generation 8234: M(n) = 862.6320056992192\n",
      "Generation 8235: p = 0.9584800063324658\n",
      "Generation 8235: M(n) = 862.6320056992192\n",
      "Generation 8236: p = 0.9584800063324658\n",
      "Generation 8236: M(n) = 862.6320056992192\n",
      "Generation 8237: p = 0.9584800063324658\n",
      "Generation 8237: M(n) = 862.6320056992192\n",
      "Generation 8238: p = 0.9584800063324658\n",
      "Generation 8238: M(n) = 862.6320056992192\n",
      "Generation 8239: p = 0.9584800063324658\n",
      "Generation 8239: M(n) = 862.6320056992192\n",
      "Generation 8240: p = 0.9584800063324658\n",
      "Generation 8240: M(n) = 862.6320056992192\n",
      "Generation 8241: p = 0.9584800063324658\n",
      "Generation 8241: M(n) = 862.6320056992192\n",
      "Generation 8242: p = 0.9584800063324658\n",
      "Generation 8242: M(n) = 862.6320056992192\n",
      "Generation 8243: p = 0.9584800063324658\n",
      "Generation 8243: M(n) = 862.6320056992192\n",
      "Generation 8244: p = 0.9584800063324658\n",
      "Generation 8244: M(n) = 862.6320056992192\n",
      "Generation 8245: p = 0.9584800063324658\n",
      "Generation 8245: M(n) = 862.6320056992192\n",
      "Generation 8246: p = 0.9584800063324658\n",
      "Generation 8246: M(n) = 862.6320056992192\n",
      "Generation 8247: p = 0.9584800063324658\n",
      "Generation 8247: M(n) = 862.6320056992192\n",
      "Generation 8248: p = 0.9584800063324658\n",
      "Generation 8248: M(n) = 862.6320056992192\n",
      "Generation 8249: p = 0.9584800063324658\n",
      "Generation 8249: M(n) = 862.6320056992192\n",
      "Generation 8250: p = 0.9584800063324658\n",
      "Generation 8250: M(n) = 862.6320056992192\n",
      "Generation 8251: p = 0.9584800063324658\n",
      "Generation 8251: M(n) = 862.6320056992192\n",
      "Generation 8252: p = 0.9584800063324658\n",
      "Generation 8252: M(n) = 862.6320056992192\n",
      "Generation 8253: p = 0.9584800063324658\n",
      "Generation 8253: M(n) = 862.6320056992192\n",
      "Generation 8254: p = 0.9584800063324658\n",
      "Generation 8254: M(n) = 862.6320056992192\n",
      "Generation 8255: p = 0.9584800063324658\n",
      "Generation 8255: M(n) = 862.6320056992192\n",
      "Generation 8256: p = 0.9584800063324658\n",
      "Generation 8256: M(n) = 862.6320056992192\n",
      "Generation 8257: p = 0.9584800063324658\n",
      "Generation 8257: M(n) = 862.6320056992192\n",
      "Generation 8258: p = 0.9584800063324658\n",
      "Generation 8258: M(n) = 862.6320056992192\n",
      "Generation 8259: p = 0.9584800063324658\n",
      "Generation 8259: M(n) = 862.6320056992192\n",
      "Generation 8260: p = 0.9584800063324658\n",
      "Generation 8260: M(n) = 862.6320056992192\n",
      "Generation 8261: p = 0.9584800063324658\n",
      "Generation 8261: M(n) = 862.6320056992192\n",
      "Generation 8262: p = 0.9584800063324658\n",
      "Generation 8262: M(n) = 862.6320056992192\n",
      "Generation 8263: p = 0.9584800063324658\n",
      "Generation 8263: M(n) = 862.6320056992192\n",
      "Generation 8264: p = 0.9584800063324658\n",
      "Generation 8264: M(n) = 862.6320056992192\n",
      "Generation 8265: p = 0.9584800063324658\n",
      "Generation 8265: M(n) = 862.6320056992192\n",
      "Generation 8266: p = 0.9584800063324658\n",
      "Generation 8266: M(n) = 862.6320056992192\n",
      "Generation 8267: p = 0.9584800063324658\n",
      "Generation 8267: M(n) = 862.6320056992192\n",
      "Generation 8268: p = 0.9584800063324658\n",
      "Generation 8268: M(n) = 862.6320056992192\n",
      "Generation 8269: p = 0.9584800063324658\n",
      "Generation 8269: M(n) = 862.6320056992192\n",
      "Generation 8270: p = 0.9584800063324658\n",
      "Generation 8270: M(n) = 862.6320056992192\n",
      "Generation 8271: p = 0.9584800063324658\n",
      "Generation 8271: M(n) = 862.6320056992192\n",
      "Generation 8272: p = 0.9584800063324658\n",
      "Generation 8272: M(n) = 862.6320056992192\n",
      "Generation 8273: p = 0.9584800063324658\n",
      "Generation 8273: M(n) = 862.6320056992192\n",
      "Generation 8274: p = 0.9584800063324658\n",
      "Generation 8274: M(n) = 862.6320056992192\n",
      "Generation 8275: p = 0.9584800063324658\n",
      "Generation 8275: M(n) = 862.6320056992192\n",
      "Generation 8276: p = 0.9584800063324658\n",
      "Generation 8276: M(n) = 862.6320056992192\n",
      "Generation 8277: p = 0.9584800063324658\n",
      "Generation 8277: M(n) = 862.6320056992192\n",
      "Generation 8278: p = 0.9584800063324658\n",
      "Generation 8278: M(n) = 862.6320056992192\n",
      "Generation 8279: p = 0.9584800063324658\n",
      "Generation 8279: M(n) = 862.6320056992192\n",
      "Generation 8280: p = 0.9584800063324658\n",
      "Generation 8280: M(n) = 862.6320056992192\n",
      "Generation 8281: p = 0.9584800063324658\n",
      "Generation 8281: M(n) = 862.6320056992192\n",
      "Generation 8282: p = 0.9584800063324658\n",
      "Generation 8282: M(n) = 862.6320056992192\n",
      "Generation 8283: p = 0.9584800063324658\n",
      "Generation 8283: M(n) = 862.6320056992192\n",
      "Generation 8284: p = 0.9584800063324658\n",
      "Generation 8284: M(n) = 862.6320056992192\n",
      "Generation 8285: p = 0.9584800063324658\n",
      "Generation 8285: M(n) = 862.6320056992192\n",
      "Generation 8286: p = 0.9584800063324658\n",
      "Generation 8286: M(n) = 862.6320056992192\n",
      "Generation 8287: p = 0.9584800063324658\n",
      "Generation 8287: M(n) = 862.6320056992192\n",
      "Generation 8288: p = 0.9584800063324658\n",
      "Generation 8288: M(n) = 862.6320056992192\n",
      "Generation 8289: p = 0.9584800063324658\n",
      "Generation 8289: M(n) = 862.6320056992192\n",
      "Generation 8290: p = 0.9584800063324658\n",
      "Generation 8290: M(n) = 862.6320056992192\n",
      "Generation 8291: p = 0.9584800063324658\n",
      "Generation 8291: M(n) = 862.6320056992192\n",
      "Generation 8292: p = 0.9584800063324658\n",
      "Generation 8292: M(n) = 862.6320056992192\n",
      "Generation 8293: p = 0.9584800063324658\n",
      "Generation 8293: M(n) = 862.6320056992192\n",
      "Generation 8294: p = 0.9584800063324658\n",
      "Generation 8294: M(n) = 862.6320056992192\n",
      "Generation 8295: p = 0.9584800063324658\n",
      "Generation 8295: M(n) = 862.6320056992192\n",
      "Generation 8296: p = 0.9584800063324658\n",
      "Generation 8296: M(n) = 862.6320056992192\n",
      "Generation 8297: p = 0.9584800063324658\n",
      "Generation 8297: M(n) = 862.6320056992192\n",
      "Generation 8298: p = 0.9584800063324658\n",
      "Generation 8298: M(n) = 862.6320056992192\n",
      "Generation 8299: p = 0.9584800063324658\n",
      "Generation 8299: M(n) = 862.6320056992192\n",
      "Generation 8300: p = 0.9584800063324658\n",
      "Generation 8300: M(n) = 862.6320056992192\n",
      "Generation 8301: p = 0.9584800063324658\n",
      "Generation 8301: M(n) = 862.6320056992192\n",
      "Generation 8302: p = 0.9584800063324658\n",
      "Generation 8302: M(n) = 862.6320056992192\n",
      "Generation 8303: p = 0.9584800063324658\n",
      "Generation 8303: M(n) = 862.6320056992192\n",
      "Generation 8304: p = 0.9584800063324658\n",
      "Generation 8304: M(n) = 862.6320056992192\n",
      "Generation 8305: p = 0.9584800063324658\n",
      "Generation 8305: M(n) = 862.6320056992192\n",
      "Generation 8306: p = 0.9584800063324658\n",
      "Generation 8306: M(n) = 862.6320056992192\n",
      "Generation 8307: p = 0.9584800063324658\n",
      "Generation 8307: M(n) = 862.6320056992192\n",
      "Generation 8308: p = 0.9584800063324658\n",
      "Generation 8308: M(n) = 862.6320056992192\n",
      "Generation 8309: p = 0.9584800063324658\n",
      "Generation 8309: M(n) = 862.6320056992192\n",
      "Generation 8310: p = 0.9584800063324658\n",
      "Generation 8310: M(n) = 862.6320056992192\n",
      "Generation 8311: p = 0.9584800063324658\n",
      "Generation 8311: M(n) = 862.6320056992192\n",
      "Generation 8312: p = 0.9584800063324658\n",
      "Generation 8312: M(n) = 862.6320056992192\n",
      "Generation 8313: p = 0.9584800063324658\n",
      "Generation 8313: M(n) = 862.6320056992192\n",
      "Generation 8314: p = 0.9584800063324658\n",
      "Generation 8314: M(n) = 862.6320056992192\n",
      "Generation 8315: p = 0.9584800063324658\n",
      "Generation 8315: M(n) = 862.6320056992192\n",
      "Generation 8316: p = 0.9584800063324658\n",
      "Generation 8316: M(n) = 862.6320056992192\n",
      "Generation 8317: p = 0.9584800063324658\n",
      "Generation 8317: M(n) = 862.6320056992192\n",
      "Generation 8318: p = 0.9584800063324658\n",
      "Generation 8318: M(n) = 862.6320056992192\n",
      "Generation 8319: p = 0.9584800063324658\n",
      "Generation 8319: M(n) = 862.6320056992192\n",
      "Generation 8320: p = 0.9584800063324658\n",
      "Generation 8320: M(n) = 862.6320056992192\n",
      "Generation 8321: p = 0.9584800063324658\n",
      "Generation 8321: M(n) = 862.6320056992192\n",
      "Generation 8322: p = 0.9584800063324658\n",
      "Generation 8322: M(n) = 862.6320056992192\n",
      "Generation 8323: p = 0.9584800063324658\n",
      "Generation 8323: M(n) = 862.6320056992192\n",
      "Generation 8324: p = 0.9584800063324658\n",
      "Generation 8324: M(n) = 862.6320056992192\n",
      "Generation 8325: p = 0.9584800063324658\n",
      "Generation 8325: M(n) = 862.6320056992192\n",
      "Generation 8326: p = 0.9584800063324658\n",
      "Generation 8326: M(n) = 862.6320056992192\n",
      "Generation 8327: p = 0.9584800063324658\n",
      "Generation 8327: M(n) = 862.6320056992192\n",
      "Generation 8328: p = 0.9584800063324658\n",
      "Generation 8328: M(n) = 862.6320056992192\n",
      "Generation 8329: p = 0.9584800063324658\n",
      "Generation 8329: M(n) = 862.6320056992192\n",
      "Generation 8330: p = 0.9584800063324658\n",
      "Generation 8330: M(n) = 862.6320056992192\n",
      "Generation 8331: p = 0.9584800063324658\n",
      "Generation 8331: M(n) = 862.6320056992192\n",
      "Generation 8332: p = 0.9584800063324658\n",
      "Generation 8332: M(n) = 862.6320056992192\n",
      "Generation 8333: p = 0.9584800063324658\n",
      "Generation 8333: M(n) = 862.6320056992192\n",
      "Generation 8334: p = 0.9584800063324658\n",
      "Generation 8334: M(n) = 862.6320056992192\n",
      "Generation 8335: p = 0.9584800063324658\n",
      "Generation 8335: M(n) = 862.6320056992192\n",
      "Generation 8336: p = 0.9584800063324658\n",
      "Generation 8336: M(n) = 862.6320056992192\n",
      "Generation 8337: p = 0.9584800063324658\n",
      "Generation 8337: M(n) = 862.6320056992192\n",
      "Generation 8338: p = 0.9584800063324658\n",
      "Generation 8338: M(n) = 862.6320056992192\n",
      "Generation 8339: p = 0.9584800063324658\n",
      "Generation 8339: M(n) = 862.6320056992192\n",
      "Generation 8340: p = 0.9584800063324658\n",
      "Generation 8340: M(n) = 862.6320056992192\n",
      "Generation 8341: p = 0.9584800063324658\n",
      "Generation 8341: M(n) = 862.6320056992192\n",
      "Generation 8342: p = 0.9584800063324658\n",
      "Generation 8342: M(n) = 862.6320056992192\n",
      "Generation 8343: p = 0.9584800063324658\n",
      "Generation 8343: M(n) = 862.6320056992192\n",
      "Generation 8344: p = 0.9584800063324658\n",
      "Generation 8344: M(n) = 862.6320056992192\n",
      "Generation 8345: p = 0.9584800063324658\n",
      "Generation 8345: M(n) = 862.6320056992192\n",
      "Generation 8346: p = 0.9584800063324658\n",
      "Generation 8346: M(n) = 862.6320056992192\n",
      "Generation 8347: p = 0.9584800063324658\n",
      "Generation 8347: M(n) = 862.6320056992192\n",
      "Generation 8348: p = 0.9584800063324658\n",
      "Generation 8348: M(n) = 862.6320056992192\n",
      "Generation 8349: p = 0.9584800063324658\n",
      "Generation 8349: M(n) = 862.6320056992192\n",
      "Generation 8350: p = 0.9584800063324658\n",
      "Generation 8350: M(n) = 862.6320056992192\n",
      "Generation 8351: p = 0.9584800063324658\n",
      "Generation 8351: M(n) = 862.6320056992192\n",
      "Generation 8352: p = 0.9584800063324658\n",
      "Generation 8352: M(n) = 862.6320056992192\n",
      "Generation 8353: p = 0.9584800063324658\n",
      "Generation 8353: M(n) = 862.6320056992192\n",
      "Generation 8354: p = 0.9584800063324658\n",
      "Generation 8354: M(n) = 862.6320056992192\n",
      "Generation 8355: p = 0.9584800063324658\n",
      "Generation 8355: M(n) = 862.6320056992192\n",
      "Generation 8356: p = 0.9584800063324658\n",
      "Generation 8356: M(n) = 862.6320056992192\n",
      "Generation 8357: p = 0.9584800063324658\n",
      "Generation 8357: M(n) = 862.6320056992192\n",
      "Generation 8358: p = 0.9584800063324658\n",
      "Generation 8358: M(n) = 862.6320056992192\n",
      "Generation 8359: p = 0.9584800063324658\n",
      "Generation 8359: M(n) = 862.6320056992192\n",
      "Generation 8360: p = 0.9584800063324658\n",
      "Generation 8360: M(n) = 862.6320056992192\n",
      "Generation 8361: p = 0.9584800063324658\n",
      "Generation 8361: M(n) = 862.6320056992192\n",
      "Generation 8362: p = 0.9584800063324658\n",
      "Generation 8362: M(n) = 862.6320056992192\n",
      "Generation 8363: p = 0.9584800063324658\n",
      "Generation 8363: M(n) = 862.6320056992192\n",
      "Generation 8364: p = 0.9584800063324658\n",
      "Generation 8364: M(n) = 862.6320056992192\n",
      "Generation 8365: p = 0.9584800063324658\n",
      "Generation 8365: M(n) = 862.6320056992192\n",
      "Generation 8366: p = 0.9584800063324658\n",
      "Generation 8366: M(n) = 862.6320056992192\n",
      "Generation 8367: p = 0.9584800063324658\n",
      "Generation 8367: M(n) = 862.6320056992192\n",
      "Generation 8368: p = 0.9584800063324658\n",
      "Generation 8368: M(n) = 862.6320056992192\n",
      "Generation 8369: p = 0.9584800063324658\n",
      "Generation 8369: M(n) = 862.6320056992192\n",
      "Generation 8370: p = 0.9584800063324658\n",
      "Generation 8370: M(n) = 862.6320056992192\n",
      "Generation 8371: p = 0.9584800063324658\n",
      "Generation 8371: M(n) = 862.6320056992192\n",
      "Generation 8372: p = 0.9584800063324658\n",
      "Generation 8372: M(n) = 862.6320056992192\n",
      "Generation 8373: p = 0.9584800063324658\n",
      "Generation 8373: M(n) = 862.6320056992192\n",
      "Generation 8374: p = 0.9584800063324658\n",
      "Generation 8374: M(n) = 862.6320056992192\n",
      "Generation 8375: p = 0.9584800063324658\n",
      "Generation 8375: M(n) = 862.6320056992192\n",
      "Generation 8376: p = 0.9584800063324658\n",
      "Generation 8376: M(n) = 862.6320056992192\n",
      "Generation 8377: p = 0.9584800063324658\n",
      "Generation 8377: M(n) = 862.6320056992192\n",
      "Generation 8378: p = 0.9584800063324658\n",
      "Generation 8378: M(n) = 862.6320056992192\n",
      "Generation 8379: p = 0.9584800063324658\n",
      "Generation 8379: M(n) = 862.6320056992192\n",
      "Generation 8380: p = 0.9584800063324658\n",
      "Generation 8380: M(n) = 862.6320056992192\n",
      "Generation 8381: p = 0.9584800063324658\n",
      "Generation 8381: M(n) = 862.6320056992192\n",
      "Generation 8382: p = 0.9584800063324658\n",
      "Generation 8382: M(n) = 862.6320056992192\n",
      "Generation 8383: p = 0.9584800063324658\n",
      "Generation 8383: M(n) = 862.6320056992192\n",
      "Generation 8384: p = 0.9584800063324658\n",
      "Generation 8384: M(n) = 862.6320056992192\n",
      "Generation 8385: p = 0.9584800063324658\n",
      "Generation 8385: M(n) = 862.6320056992192\n",
      "Generation 8386: p = 0.9584800063324658\n",
      "Generation 8386: M(n) = 862.6320056992192\n",
      "Generation 8387: p = 0.9584800063324658\n",
      "Generation 8387: M(n) = 862.6320056992192\n",
      "Generation 8388: p = 0.9584800063324658\n",
      "Generation 8388: M(n) = 862.6320056992192\n",
      "Generation 8389: p = 0.9584800063324658\n",
      "Generation 8389: M(n) = 862.6320056992192\n",
      "Generation 8390: p = 0.9584800063324658\n",
      "Generation 8390: M(n) = 862.6320056992192\n",
      "Generation 8391: p = 0.9584800063324658\n",
      "Generation 8391: M(n) = 862.6320056992192\n",
      "Generation 8392: p = 0.9584800063324658\n",
      "Generation 8392: M(n) = 862.6320056992192\n",
      "Generation 8393: p = 0.9584800063324658\n",
      "Generation 8393: M(n) = 862.6320056992192\n",
      "Generation 8394: p = 0.9584800063324658\n",
      "Generation 8394: M(n) = 862.6320056992192\n",
      "Generation 8395: p = 0.9584800063324658\n",
      "Generation 8395: M(n) = 862.6320056992192\n",
      "Generation 8396: p = 0.9584800063324658\n",
      "Generation 8396: M(n) = 862.6320056992192\n",
      "Generation 8397: p = 0.9584800063324658\n",
      "Generation 8397: M(n) = 862.6320056992192\n",
      "Generation 8398: p = 0.9584800063324658\n",
      "Generation 8398: M(n) = 862.6320056992192\n",
      "Generation 8399: p = 0.9584800063324658\n",
      "Generation 8399: M(n) = 862.6320056992192\n",
      "Generation 8400: p = 0.9584800063324658\n",
      "Generation 8400: M(n) = 862.6320056992192\n",
      "Generation 8401: p = 0.9584800063324658\n",
      "Generation 8401: M(n) = 862.6320056992192\n",
      "Generation 8402: p = 0.9584800063324658\n",
      "Generation 8402: M(n) = 862.6320056992192\n",
      "Generation 8403: p = 0.9584800063324658\n",
      "Generation 8403: M(n) = 862.6320056992192\n",
      "Generation 8404: p = 0.9584800063324658\n",
      "Generation 8404: M(n) = 862.6320056992192\n",
      "Generation 8405: p = 0.9584800063324658\n",
      "Generation 8405: M(n) = 862.6320056992192\n",
      "Generation 8406: p = 0.9584800063324658\n",
      "Generation 8406: M(n) = 862.6320056992192\n",
      "Generation 8407: p = 0.9584800063324658\n",
      "Generation 8407: M(n) = 862.6320056992192\n",
      "Generation 8408: p = 0.9584800063324658\n",
      "Generation 8408: M(n) = 862.6320056992192\n",
      "Generation 8409: p = 0.9584800063324658\n",
      "Generation 8409: M(n) = 862.6320056992192\n",
      "Generation 8410: p = 0.9584800063324658\n",
      "Generation 8410: M(n) = 862.6320056992192\n",
      "Generation 8411: p = 0.9584800063324658\n",
      "Generation 8411: M(n) = 862.6320056992192\n",
      "Generation 8412: p = 0.9584800063324658\n",
      "Generation 8412: M(n) = 862.6320056992192\n",
      "Generation 8413: p = 0.9584800063324658\n",
      "Generation 8413: M(n) = 862.6320056992192\n",
      "Generation 8414: p = 0.9584800063324658\n",
      "Generation 8414: M(n) = 862.6320056992192\n",
      "Generation 8415: p = 0.9584800063324658\n",
      "Generation 8415: M(n) = 862.6320056992192\n",
      "Generation 8416: p = 0.9584800063324658\n",
      "Generation 8416: M(n) = 862.6320056992192\n",
      "Generation 8417: p = 0.9584800063324658\n",
      "Generation 8417: M(n) = 862.6320056992192\n",
      "Generation 8418: p = 0.9584800063324658\n",
      "Generation 8418: M(n) = 862.6320056992192\n",
      "Generation 8419: p = 0.9584800063324658\n",
      "Generation 8419: M(n) = 862.6320056992192\n",
      "Generation 8420: p = 0.9584800063324658\n",
      "Generation 8420: M(n) = 862.6320056992192\n",
      "Generation 8421: p = 0.9584800063324658\n",
      "Generation 8421: M(n) = 862.6320056992192\n",
      "Generation 8422: p = 0.9584800063324658\n",
      "Generation 8422: M(n) = 862.6320056992192\n",
      "Generation 8423: p = 0.9584800063324658\n",
      "Generation 8423: M(n) = 862.6320056992192\n",
      "Generation 8424: p = 0.9584800063324658\n",
      "Generation 8424: M(n) = 862.6320056992192\n",
      "Generation 8425: p = 0.9584800063324658\n",
      "Generation 8425: M(n) = 862.6320056992192\n",
      "Generation 8426: p = 0.9584800063324658\n",
      "Generation 8426: M(n) = 862.6320056992192\n",
      "Generation 8427: p = 0.9584800063324658\n",
      "Generation 8427: M(n) = 862.6320056992192\n",
      "Generation 8428: p = 0.9584800063324658\n",
      "Generation 8428: M(n) = 862.6320056992192\n",
      "Generation 8429: p = 0.9584800063324658\n",
      "Generation 8429: M(n) = 862.6320056992192\n",
      "Generation 8430: p = 0.9584800063324658\n",
      "Generation 8430: M(n) = 862.6320056992192\n",
      "Generation 8431: p = 0.9584800063324658\n",
      "Generation 8431: M(n) = 862.6320056992192\n",
      "Generation 8432: p = 0.9584800063324658\n",
      "Generation 8432: M(n) = 862.6320056992192\n",
      "Generation 8433: p = 0.9584800063324658\n",
      "Generation 8433: M(n) = 862.6320056992192\n",
      "Generation 8434: p = 0.9584800063324658\n",
      "Generation 8434: M(n) = 862.6320056992192\n",
      "Generation 8435: p = 0.9584800063324658\n",
      "Generation 8435: M(n) = 862.6320056992192\n",
      "Generation 8436: p = 0.9584800063324658\n",
      "Generation 8436: M(n) = 862.6320056992192\n",
      "Generation 8437: p = 0.9584800063324658\n",
      "Generation 8437: M(n) = 862.6320056992192\n",
      "Generation 8438: p = 0.9584800063324658\n",
      "Generation 8438: M(n) = 862.6320056992192\n",
      "Generation 8439: p = 0.9584800063324658\n",
      "Generation 8439: M(n) = 862.6320056992192\n",
      "Generation 8440: p = 0.9584800063324658\n",
      "Generation 8440: M(n) = 862.6320056992192\n",
      "Generation 8441: p = 0.9584800063324658\n",
      "Generation 8441: M(n) = 862.6320056992192\n",
      "Generation 8442: p = 0.9584800063324658\n",
      "Generation 8442: M(n) = 862.6320056992192\n",
      "Generation 8443: p = 0.9584800063324658\n",
      "Generation 8443: M(n) = 862.6320056992192\n",
      "Generation 8444: p = 0.9584800063324658\n",
      "Generation 8444: M(n) = 862.6320056992192\n",
      "Generation 8445: p = 0.9584800063324658\n",
      "Generation 8445: M(n) = 862.6320056992192\n",
      "Generation 8446: p = 0.9584800063324658\n",
      "Generation 8446: M(n) = 862.6320056992192\n",
      "Generation 8447: p = 0.9584800063324658\n",
      "Generation 8447: M(n) = 862.6320056992192\n",
      "Generation 8448: p = 0.9584800063324658\n",
      "Generation 8448: M(n) = 862.6320056992192\n",
      "Generation 8449: p = 0.9584800063324658\n",
      "Generation 8449: M(n) = 862.6320056992192\n",
      "Generation 8450: p = 0.9584800063324658\n",
      "Generation 8450: M(n) = 862.6320056992192\n",
      "Generation 8451: p = 0.9584800063324658\n",
      "Generation 8451: M(n) = 862.6320056992192\n",
      "Generation 8452: p = 0.9584800063324658\n",
      "Generation 8452: M(n) = 862.6320056992192\n",
      "Generation 8453: p = 0.9584800063324658\n",
      "Generation 8453: M(n) = 862.6320056992192\n",
      "Generation 8454: p = 0.9584800063324658\n",
      "Generation 8454: M(n) = 862.6320056992192\n",
      "Generation 8455: p = 0.9584800063324658\n",
      "Generation 8455: M(n) = 862.6320056992192\n",
      "Generation 8456: p = 0.9584800063324658\n",
      "Generation 8456: M(n) = 862.6320056992192\n",
      "Generation 8457: p = 0.9584800063324658\n",
      "Generation 8457: M(n) = 862.6320056992192\n",
      "Generation 8458: p = 0.9584800063324658\n",
      "Generation 8458: M(n) = 862.6320056992192\n",
      "Generation 8459: p = 0.9584800063324658\n",
      "Generation 8459: M(n) = 862.6320056992192\n",
      "Generation 8460: p = 0.9584800063324658\n",
      "Generation 8460: M(n) = 862.6320056992192\n",
      "Generation 8461: p = 0.9584800063324658\n",
      "Generation 8461: M(n) = 862.6320056992192\n",
      "Generation 8462: p = 0.9584800063324658\n",
      "Generation 8462: M(n) = 862.6320056992192\n",
      "Generation 8463: p = 0.9584800063324658\n",
      "Generation 8463: M(n) = 862.6320056992192\n",
      "Generation 8464: p = 0.9584800063324658\n",
      "Generation 8464: M(n) = 862.6320056992192\n",
      "Generation 8465: p = 0.9584800063324658\n",
      "Generation 8465: M(n) = 862.6320056992192\n",
      "Generation 8466: p = 0.9584800063324658\n",
      "Generation 8466: M(n) = 862.6320056992192\n",
      "Generation 8467: p = 0.9584800063324658\n",
      "Generation 8467: M(n) = 862.6320056992192\n",
      "Generation 8468: p = 0.9584800063324658\n",
      "Generation 8468: M(n) = 862.6320056992192\n",
      "Generation 8469: p = 0.9584800063324658\n",
      "Generation 8469: M(n) = 862.6320056992192\n",
      "Generation 8470: p = 0.9584800063324658\n",
      "Generation 8470: M(n) = 862.6320056992192\n",
      "Generation 8471: p = 0.9584800063324658\n",
      "Generation 8471: M(n) = 862.6320056992192\n",
      "Generation 8472: p = 0.9584800063324658\n",
      "Generation 8472: M(n) = 862.6320056992192\n",
      "Generation 8473: p = 0.9584800063324658\n",
      "Generation 8473: M(n) = 862.6320056992192\n",
      "Generation 8474: p = 0.9584800063324658\n",
      "Generation 8474: M(n) = 862.6320056992192\n",
      "Generation 8475: p = 0.9584800063324658\n",
      "Generation 8475: M(n) = 862.6320056992192\n",
      "Generation 8476: p = 0.9584800063324658\n",
      "Generation 8476: M(n) = 862.6320056992192\n",
      "Generation 8477: p = 0.9584800063324658\n",
      "Generation 8477: M(n) = 862.6320056992192\n",
      "Generation 8478: p = 0.9584800063324658\n",
      "Generation 8478: M(n) = 862.6320056992192\n",
      "Generation 8479: p = 0.9584800063324658\n",
      "Generation 8479: M(n) = 862.6320056992192\n",
      "Generation 8480: p = 0.9584800063324658\n",
      "Generation 8480: M(n) = 862.6320056992192\n",
      "Generation 8481: p = 0.9584800063324658\n",
      "Generation 8481: M(n) = 862.6320056992192\n",
      "Generation 8482: p = 0.9584800063324658\n",
      "Generation 8482: M(n) = 862.6320056992192\n",
      "Generation 8483: p = 0.9584800063324658\n",
      "Generation 8483: M(n) = 862.6320056992192\n",
      "Generation 8484: p = 0.9584800063324658\n",
      "Generation 8484: M(n) = 862.6320056992192\n",
      "Generation 8485: p = 0.9584800063324658\n",
      "Generation 8485: M(n) = 862.6320056992192\n",
      "Generation 8486: p = 0.9584800063324658\n",
      "Generation 8486: M(n) = 862.6320056992192\n",
      "Generation 8487: p = 0.9584800063324658\n",
      "Generation 8487: M(n) = 862.6320056992192\n",
      "Generation 8488: p = 0.9584800063324658\n",
      "Generation 8488: M(n) = 862.6320056992192\n",
      "Generation 8489: p = 0.9584800063324658\n",
      "Generation 8489: M(n) = 862.6320056992192\n",
      "Generation 8490: p = 0.9584800063324658\n",
      "Generation 8490: M(n) = 862.6320056992192\n",
      "Generation 8491: p = 0.9584800063324658\n",
      "Generation 8491: M(n) = 862.6320056992192\n",
      "Generation 8492: p = 0.9584800063324658\n",
      "Generation 8492: M(n) = 862.6320056992192\n",
      "Generation 8493: p = 0.9584800063324658\n",
      "Generation 8493: M(n) = 862.6320056992192\n",
      "Generation 8494: p = 0.9584800063324658\n",
      "Generation 8494: M(n) = 862.6320056992192\n",
      "Generation 8495: p = 0.9584800063324658\n",
      "Generation 8495: M(n) = 862.6320056992192\n",
      "Generation 8496: p = 0.9584800063324658\n",
      "Generation 8496: M(n) = 862.6320056992192\n",
      "Generation 8497: p = 0.9584800063324658\n",
      "Generation 8497: M(n) = 862.6320056992192\n",
      "Generation 8498: p = 0.9584800063324658\n",
      "Generation 8498: M(n) = 862.6320056992192\n",
      "Generation 8499: p = 0.9584800063324658\n",
      "Generation 8499: M(n) = 862.6320056992192\n",
      "Generation 8500: p = 0.9584800063324658\n",
      "Generation 8500: M(n) = 862.6320056992192\n",
      "Generation 8501: p = 0.9584800063324658\n",
      "Generation 8501: M(n) = 862.6320056992192\n",
      "Generation 8502: p = 0.9584800063324658\n",
      "Generation 8502: M(n) = 862.6320056992192\n",
      "Generation 8503: p = 0.9584800063324658\n",
      "Generation 8503: M(n) = 862.6320056992192\n",
      "Generation 8504: p = 0.9584800063324658\n",
      "Generation 8504: M(n) = 862.6320056992192\n",
      "Generation 8505: p = 0.9584800063324658\n",
      "Generation 8505: M(n) = 862.6320056992192\n",
      "Generation 8506: p = 0.9584800063324658\n",
      "Generation 8506: M(n) = 862.6320056992192\n",
      "Generation 8507: p = 0.9584800063324658\n",
      "Generation 8507: M(n) = 862.6320056992192\n",
      "Generation 8508: p = 0.9584800063324658\n",
      "Generation 8508: M(n) = 862.6320056992192\n",
      "Generation 8509: p = 0.9584800063324658\n",
      "Generation 8509: M(n) = 862.6320056992192\n",
      "Generation 8510: p = 0.9584800063324658\n",
      "Generation 8510: M(n) = 862.6320056992192\n",
      "Generation 8511: p = 0.9584800063324658\n",
      "Generation 8511: M(n) = 862.6320056992192\n",
      "Generation 8512: p = 0.9584800063324658\n",
      "Generation 8512: M(n) = 862.6320056992192\n",
      "Generation 8513: p = 0.9584800063324658\n",
      "Generation 8513: M(n) = 862.6320056992192\n",
      "Generation 8514: p = 0.9584800063324658\n",
      "Generation 8514: M(n) = 862.6320056992192\n",
      "Generation 8515: p = 0.9584800063324658\n",
      "Generation 8515: M(n) = 862.6320056992192\n",
      "Generation 8516: p = 0.9584800063324658\n",
      "Generation 8516: M(n) = 862.6320056992192\n",
      "Generation 8517: p = 0.9584800063324658\n",
      "Generation 8517: M(n) = 862.6320056992192\n",
      "Generation 8518: p = 0.9584800063324658\n",
      "Generation 8518: M(n) = 862.6320056992192\n",
      "Generation 8519: p = 0.9584800063324658\n",
      "Generation 8519: M(n) = 862.6320056992192\n",
      "Generation 8520: p = 0.9584800063324658\n",
      "Generation 8520: M(n) = 862.6320056992192\n",
      "Generation 8521: p = 0.9584800063324658\n",
      "Generation 8521: M(n) = 862.6320056992192\n",
      "Generation 8522: p = 0.9584800063324658\n",
      "Generation 8522: M(n) = 862.6320056992192\n",
      "Generation 8523: p = 0.9584800063324658\n",
      "Generation 8523: M(n) = 862.6320056992192\n",
      "Generation 8524: p = 0.9584800063324658\n",
      "Generation 8524: M(n) = 862.6320056992192\n",
      "Generation 8525: p = 0.9584800063324658\n",
      "Generation 8525: M(n) = 862.6320056992192\n",
      "Generation 8526: p = 0.9584800063324658\n",
      "Generation 8526: M(n) = 862.6320056992192\n",
      "Generation 8527: p = 0.9584800063324658\n",
      "Generation 8527: M(n) = 862.6320056992192\n",
      "Generation 8528: p = 0.9584800063324658\n",
      "Generation 8528: M(n) = 862.6320056992192\n",
      "Generation 8529: p = 0.9584800063324658\n",
      "Generation 8529: M(n) = 862.6320056992192\n",
      "Generation 8530: p = 0.9584800063324658\n",
      "Generation 8530: M(n) = 862.6320056992192\n",
      "Generation 8531: p = 0.9584800063324658\n",
      "Generation 8531: M(n) = 862.6320056992192\n",
      "Generation 8532: p = 0.9584800063324658\n",
      "Generation 8532: M(n) = 862.6320056992192\n",
      "Generation 8533: p = 0.9584800063324658\n",
      "Generation 8533: M(n) = 862.6320056992192\n",
      "Generation 8534: p = 0.9584800063324658\n",
      "Generation 8534: M(n) = 862.6320056992192\n",
      "Generation 8535: p = 0.9584800063324658\n",
      "Generation 8535: M(n) = 862.6320056992192\n",
      "Generation 8536: p = 0.9584800063324658\n",
      "Generation 8536: M(n) = 862.6320056992192\n",
      "Generation 8537: p = 0.9584800063324658\n",
      "Generation 8537: M(n) = 862.6320056992192\n",
      "Generation 8538: p = 0.9584800063324658\n",
      "Generation 8538: M(n) = 862.6320056992192\n",
      "Generation 8539: p = 0.9584800063324658\n",
      "Generation 8539: M(n) = 862.6320056992192\n",
      "Generation 8540: p = 0.9584800063324658\n",
      "Generation 8540: M(n) = 862.6320056992192\n",
      "Generation 8541: p = 0.9584800063324658\n",
      "Generation 8541: M(n) = 862.6320056992192\n",
      "Generation 8542: p = 0.9584800063324658\n",
      "Generation 8542: M(n) = 862.6320056992192\n",
      "Generation 8543: p = 0.9584800063324658\n",
      "Generation 8543: M(n) = 862.6320056992192\n",
      "Generation 8544: p = 0.9584800063324658\n",
      "Generation 8544: M(n) = 862.6320056992192\n",
      "Generation 8545: p = 0.9584800063324658\n",
      "Generation 8545: M(n) = 862.6320056992192\n",
      "Generation 8546: p = 0.9584800063324658\n",
      "Generation 8546: M(n) = 862.6320056992192\n",
      "Generation 8547: p = 0.9584800063324658\n",
      "Generation 8547: M(n) = 862.6320056992192\n",
      "Generation 8548: p = 0.9584800063324658\n",
      "Generation 8548: M(n) = 862.6320056992192\n",
      "Generation 8549: p = 0.9584800063324658\n",
      "Generation 8549: M(n) = 862.6320056992192\n",
      "Generation 8550: p = 0.9584800063324658\n",
      "Generation 8550: M(n) = 862.6320056992192\n",
      "Generation 8551: p = 0.9584800063324658\n",
      "Generation 8551: M(n) = 862.6320056992192\n",
      "Generation 8552: p = 0.9584800063324658\n",
      "Generation 8552: M(n) = 862.6320056992192\n",
      "Generation 8553: p = 0.9584800063324658\n",
      "Generation 8553: M(n) = 862.6320056992192\n",
      "Generation 8554: p = 0.9584800063324658\n",
      "Generation 8554: M(n) = 862.6320056992192\n",
      "Generation 8555: p = 0.9584800063324658\n",
      "Generation 8555: M(n) = 862.6320056992192\n",
      "Generation 8556: p = 0.9584800063324658\n",
      "Generation 8556: M(n) = 862.6320056992192\n",
      "Generation 8557: p = 0.9584800063324658\n",
      "Generation 8557: M(n) = 862.6320056992192\n",
      "Generation 8558: p = 0.9584800063324658\n",
      "Generation 8558: M(n) = 862.6320056992192\n",
      "Generation 8559: p = 0.9584800063324658\n",
      "Generation 8559: M(n) = 862.6320056992192\n",
      "Generation 8560: p = 0.9584800063324658\n",
      "Generation 8560: M(n) = 862.6320056992192\n",
      "Generation 8561: p = 0.9584800063324658\n",
      "Generation 8561: M(n) = 862.6320056992192\n",
      "Generation 8562: p = 0.9584800063324658\n",
      "Generation 8562: M(n) = 862.6320056992192\n",
      "Generation 8563: p = 0.9584800063324658\n",
      "Generation 8563: M(n) = 862.6320056992192\n",
      "Generation 8564: p = 0.9584800063324658\n",
      "Generation 8564: M(n) = 862.6320056992192\n",
      "Generation 8565: p = 0.9584800063324658\n",
      "Generation 8565: M(n) = 862.6320056992192\n",
      "Generation 8566: p = 0.9584800063324658\n",
      "Generation 8566: M(n) = 862.6320056992192\n",
      "Generation 8567: p = 0.9584800063324658\n",
      "Generation 8567: M(n) = 862.6320056992192\n",
      "Generation 8568: p = 0.9584800063324658\n",
      "Generation 8568: M(n) = 862.6320056992192\n",
      "Generation 8569: p = 0.9584800063324658\n",
      "Generation 8569: M(n) = 862.6320056992192\n",
      "Generation 8570: p = 0.9584800063324658\n",
      "Generation 8570: M(n) = 862.6320056992192\n",
      "Generation 8571: p = 0.9584800063324658\n",
      "Generation 8571: M(n) = 862.6320056992192\n",
      "Generation 8572: p = 0.9584800063324658\n",
      "Generation 8572: M(n) = 862.6320056992192\n",
      "Generation 8573: p = 0.9584800063324658\n",
      "Generation 8573: M(n) = 862.6320056992192\n",
      "Generation 8574: p = 0.9584800063324658\n",
      "Generation 8574: M(n) = 862.6320056992192\n",
      "Generation 8575: p = 0.9584800063324658\n",
      "Generation 8575: M(n) = 862.6320056992192\n",
      "Generation 8576: p = 0.9584800063324658\n",
      "Generation 8576: M(n) = 862.6320056992192\n",
      "Generation 8577: p = 0.9584800063324658\n",
      "Generation 8577: M(n) = 862.6320056992192\n",
      "Generation 8578: p = 0.9584800063324658\n",
      "Generation 8578: M(n) = 862.6320056992192\n",
      "Generation 8579: p = 0.9584800063324658\n",
      "Generation 8579: M(n) = 862.6320056992192\n",
      "Generation 8580: p = 0.9584800063324658\n",
      "Generation 8580: M(n) = 862.6320056992192\n",
      "Generation 8581: p = 0.9584800063324658\n",
      "Generation 8581: M(n) = 862.6320056992192\n",
      "Generation 8582: p = 0.9584800063324658\n",
      "Generation 8582: M(n) = 862.6320056992192\n",
      "Generation 8583: p = 0.9584800063324658\n",
      "Generation 8583: M(n) = 862.6320056992192\n",
      "Generation 8584: p = 0.9584800063324658\n",
      "Generation 8584: M(n) = 862.6320056992192\n",
      "Generation 8585: p = 0.9584800063324658\n",
      "Generation 8585: M(n) = 862.6320056992192\n",
      "Generation 8586: p = 0.9584800063324658\n",
      "Generation 8586: M(n) = 862.6320056992192\n",
      "Generation 8587: p = 0.9584800063324658\n",
      "Generation 8587: M(n) = 862.6320056992192\n",
      "Generation 8588: p = 0.9584800063324658\n",
      "Generation 8588: M(n) = 862.6320056992192\n",
      "Generation 8589: p = 0.9584800063324658\n",
      "Generation 8589: M(n) = 862.6320056992192\n",
      "Generation 8590: p = 0.9584800063324658\n",
      "Generation 8590: M(n) = 862.6320056992192\n",
      "Generation 8591: p = 0.9584800063324658\n",
      "Generation 8591: M(n) = 862.6320056992192\n",
      "Generation 8592: p = 0.9584800063324658\n",
      "Generation 8592: M(n) = 862.6320056992192\n",
      "Generation 8593: p = 0.9584800063324658\n",
      "Generation 8593: M(n) = 862.6320056992192\n",
      "Generation 8594: p = 0.9584800063324658\n",
      "Generation 8594: M(n) = 862.6320056992192\n",
      "Generation 8595: p = 0.9584800063324658\n",
      "Generation 8595: M(n) = 862.6320056992192\n",
      "Generation 8596: p = 0.9584800063324658\n",
      "Generation 8596: M(n) = 862.6320056992192\n",
      "Generation 8597: p = 0.9584800063324658\n",
      "Generation 8597: M(n) = 862.6320056992192\n",
      "Generation 8598: p = 0.9584800063324658\n",
      "Generation 8598: M(n) = 862.6320056992192\n",
      "Generation 8599: p = 0.9584800063324658\n",
      "Generation 8599: M(n) = 862.6320056992192\n",
      "Generation 8600: p = 0.9584800063324658\n",
      "Generation 8600: M(n) = 862.6320056992192\n",
      "Generation 8601: p = 0.9584800063324658\n",
      "Generation 8601: M(n) = 862.6320056992192\n",
      "Generation 8602: p = 0.9584800063324658\n",
      "Generation 8602: M(n) = 862.6320056992192\n",
      "Generation 8603: p = 0.9584800063324658\n",
      "Generation 8603: M(n) = 862.6320056992192\n",
      "Generation 8604: p = 0.9584800063324658\n",
      "Generation 8604: M(n) = 862.6320056992192\n",
      "Generation 8605: p = 0.9584800063324658\n",
      "Generation 8605: M(n) = 862.6320056992192\n",
      "Generation 8606: p = 0.9584800063324658\n",
      "Generation 8606: M(n) = 862.6320056992192\n",
      "Generation 8607: p = 0.9584800063324658\n",
      "Generation 8607: M(n) = 862.6320056992192\n",
      "Generation 8608: p = 0.9584800063324658\n",
      "Generation 8608: M(n) = 862.6320056992192\n",
      "Generation 8609: p = 0.9584800063324658\n",
      "Generation 8609: M(n) = 862.6320056992192\n",
      "Generation 8610: p = 0.9584800063324658\n",
      "Generation 8610: M(n) = 862.6320056992192\n",
      "Generation 8611: p = 0.9584800063324658\n",
      "Generation 8611: M(n) = 862.6320056992192\n",
      "Generation 8612: p = 0.9584800063324658\n",
      "Generation 8612: M(n) = 862.6320056992192\n",
      "Generation 8613: p = 0.9584800063324658\n",
      "Generation 8613: M(n) = 862.6320056992192\n",
      "Generation 8614: p = 0.9584800063324658\n",
      "Generation 8614: M(n) = 862.6320056992192\n",
      "Generation 8615: p = 0.9584800063324658\n",
      "Generation 8615: M(n) = 862.6320056992192\n",
      "Generation 8616: p = 0.9584800063324658\n",
      "Generation 8616: M(n) = 862.6320056992192\n",
      "Generation 8617: p = 0.9584800063324658\n",
      "Generation 8617: M(n) = 862.6320056992192\n",
      "Generation 8618: p = 0.9584800063324658\n",
      "Generation 8618: M(n) = 862.6320056992192\n",
      "Generation 8619: p = 0.9584800063324658\n",
      "Generation 8619: M(n) = 862.6320056992192\n",
      "Generation 8620: p = 0.9584800063324658\n",
      "Generation 8620: M(n) = 862.6320056992192\n",
      "Generation 8621: p = 0.9584800063324658\n",
      "Generation 8621: M(n) = 862.6320056992192\n",
      "Generation 8622: p = 0.9584800063324658\n",
      "Generation 8622: M(n) = 862.6320056992192\n",
      "Generation 8623: p = 0.9584800063324658\n",
      "Generation 8623: M(n) = 862.6320056992192\n",
      "Generation 8624: p = 0.9584800063324658\n",
      "Generation 8624: M(n) = 862.6320056992192\n",
      "Generation 8625: p = 0.9584800063324658\n",
      "Generation 8625: M(n) = 862.6320056992192\n",
      "Generation 8626: p = 0.9584800063324658\n",
      "Generation 8626: M(n) = 862.6320056992192\n",
      "Generation 8627: p = 0.9584800063324658\n",
      "Generation 8627: M(n) = 862.6320056992192\n",
      "Generation 8628: p = 0.9584800063324658\n",
      "Generation 8628: M(n) = 862.6320056992192\n",
      "Generation 8629: p = 0.9584800063324658\n",
      "Generation 8629: M(n) = 862.6320056992192\n",
      "Generation 8630: p = 0.9584800063324658\n",
      "Generation 8630: M(n) = 862.6320056992192\n",
      "Generation 8631: p = 0.9584800063324658\n",
      "Generation 8631: M(n) = 862.6320056992192\n",
      "Generation 8632: p = 0.9584800063324658\n",
      "Generation 8632: M(n) = 862.6320056992192\n",
      "Generation 8633: p = 0.9584800063324658\n",
      "Generation 8633: M(n) = 862.6320056992192\n",
      "Generation 8634: p = 0.9584800063324658\n",
      "Generation 8634: M(n) = 862.6320056992192\n",
      "Generation 8635: p = 0.9584800063324658\n",
      "Generation 8635: M(n) = 862.6320056992192\n",
      "Generation 8636: p = 0.9584800063324658\n",
      "Generation 8636: M(n) = 862.6320056992192\n",
      "Generation 8637: p = 0.9584800063324658\n",
      "Generation 8637: M(n) = 862.6320056992192\n",
      "Generation 8638: p = 0.9584800063324658\n",
      "Generation 8638: M(n) = 862.6320056992192\n",
      "Generation 8639: p = 0.9584800063324658\n",
      "Generation 8639: M(n) = 862.6320056992192\n",
      "Generation 8640: p = 0.9584800063324658\n",
      "Generation 8640: M(n) = 862.6320056992192\n",
      "Generation 8641: p = 0.9584800063324658\n",
      "Generation 8641: M(n) = 862.6320056992192\n",
      "Generation 8642: p = 0.9584800063324658\n",
      "Generation 8642: M(n) = 862.6320056992192\n",
      "Generation 8643: p = 0.9584800063324658\n",
      "Generation 8643: M(n) = 862.6320056992192\n",
      "Generation 8644: p = 0.9584800063324658\n",
      "Generation 8644: M(n) = 862.6320056992192\n",
      "Generation 8645: p = 0.9584800063324658\n",
      "Generation 8645: M(n) = 862.6320056992192\n",
      "Generation 8646: p = 0.9584800063324658\n",
      "Generation 8646: M(n) = 862.6320056992192\n",
      "Generation 8647: p = 0.9584800063324658\n",
      "Generation 8647: M(n) = 862.6320056992192\n",
      "Generation 8648: p = 0.9584800063324658\n",
      "Generation 8648: M(n) = 862.6320056992192\n",
      "Generation 8649: p = 0.9584800063324658\n",
      "Generation 8649: M(n) = 862.6320056992192\n",
      "Generation 8650: p = 0.9584800063324658\n",
      "Generation 8650: M(n) = 862.6320056992192\n",
      "Generation 8651: p = 0.9584800063324658\n",
      "Generation 8651: M(n) = 862.6320056992192\n",
      "Generation 8652: p = 0.9584800063324658\n",
      "Generation 8652: M(n) = 862.6320056992192\n",
      "Generation 8653: p = 0.9584800063324658\n",
      "Generation 8653: M(n) = 862.6320056992192\n",
      "Generation 8654: p = 0.9584800063324658\n",
      "Generation 8654: M(n) = 862.6320056992192\n",
      "Generation 8655: p = 0.9584800063324658\n",
      "Generation 8655: M(n) = 862.6320056992192\n",
      "Generation 8656: p = 0.9584800063324658\n",
      "Generation 8656: M(n) = 862.6320056992192\n",
      "Generation 8657: p = 0.9584800063324658\n",
      "Generation 8657: M(n) = 862.6320056992192\n",
      "Generation 8658: p = 0.9584800063324658\n",
      "Generation 8658: M(n) = 862.6320056992192\n",
      "Generation 8659: p = 0.9584800063324658\n",
      "Generation 8659: M(n) = 862.6320056992192\n",
      "Generation 8660: p = 0.9584800063324658\n",
      "Generation 8660: M(n) = 862.6320056992192\n",
      "Generation 8661: p = 0.9584800063324658\n",
      "Generation 8661: M(n) = 862.6320056992192\n",
      "Generation 8662: p = 0.9584800063324658\n",
      "Generation 8662: M(n) = 862.6320056992192\n",
      "Generation 8663: p = 0.9584800063324658\n",
      "Generation 8663: M(n) = 862.6320056992192\n",
      "Generation 8664: p = 0.9584800063324658\n",
      "Generation 8664: M(n) = 862.6320056992192\n",
      "Generation 8665: p = 0.9584800063324658\n",
      "Generation 8665: M(n) = 862.6320056992192\n",
      "Generation 8666: p = 0.9584800063324658\n",
      "Generation 8666: M(n) = 862.6320056992192\n",
      "Generation 8667: p = 0.9584800063324658\n",
      "Generation 8667: M(n) = 862.6320056992192\n",
      "Generation 8668: p = 0.9584800063324658\n",
      "Generation 8668: M(n) = 862.6320056992192\n",
      "Generation 8669: p = 0.9584800063324658\n",
      "Generation 8669: M(n) = 862.6320056992192\n",
      "Generation 8670: p = 0.9584800063324658\n",
      "Generation 8670: M(n) = 862.6320056992192\n",
      "Generation 8671: p = 0.9584800063324658\n",
      "Generation 8671: M(n) = 862.6320056992192\n",
      "Generation 8672: p = 0.9584800063324658\n",
      "Generation 8672: M(n) = 862.6320056992192\n",
      "Generation 8673: p = 0.9584800063324658\n",
      "Generation 8673: M(n) = 862.6320056992192\n",
      "Generation 8674: p = 0.9584800063324658\n",
      "Generation 8674: M(n) = 862.6320056992192\n",
      "Generation 8675: p = 0.9584800063324658\n",
      "Generation 8675: M(n) = 862.6320056992192\n",
      "Generation 8676: p = 0.9584800063324658\n",
      "Generation 8676: M(n) = 862.6320056992192\n",
      "Generation 8677: p = 0.9584800063324658\n",
      "Generation 8677: M(n) = 862.6320056992192\n",
      "Generation 8678: p = 0.9584800063324658\n",
      "Generation 8678: M(n) = 862.6320056992192\n",
      "Generation 8679: p = 0.9584800063324658\n",
      "Generation 8679: M(n) = 862.6320056992192\n",
      "Generation 8680: p = 0.9584800063324658\n",
      "Generation 8680: M(n) = 862.6320056992192\n",
      "Generation 8681: p = 0.9584800063324658\n",
      "Generation 8681: M(n) = 862.6320056992192\n",
      "Generation 8682: p = 0.9584800063324658\n",
      "Generation 8682: M(n) = 862.6320056992192\n",
      "Generation 8683: p = 0.9584800063324658\n",
      "Generation 8683: M(n) = 862.6320056992192\n",
      "Generation 8684: p = 0.9584800063324658\n",
      "Generation 8684: M(n) = 862.6320056992192\n",
      "Generation 8685: p = 0.9584800063324658\n",
      "Generation 8685: M(n) = 862.6320056992192\n",
      "Generation 8686: p = 0.9584800063324658\n",
      "Generation 8686: M(n) = 862.6320056992192\n",
      "Generation 8687: p = 0.9584800063324658\n",
      "Generation 8687: M(n) = 862.6320056992192\n",
      "Generation 8688: p = 0.9584800063324658\n",
      "Generation 8688: M(n) = 862.6320056992192\n",
      "Generation 8689: p = 0.9584800063324658\n",
      "Generation 8689: M(n) = 862.6320056992192\n",
      "Generation 8690: p = 0.9584800063324658\n",
      "Generation 8690: M(n) = 862.6320056992192\n",
      "Generation 8691: p = 0.9584800063324658\n",
      "Generation 8691: M(n) = 862.6320056992192\n",
      "Generation 8692: p = 0.9584800063324658\n",
      "Generation 8692: M(n) = 862.6320056992192\n",
      "Generation 8693: p = 0.9584800063324658\n",
      "Generation 8693: M(n) = 862.6320056992192\n",
      "Generation 8694: p = 0.9584800063324658\n",
      "Generation 8694: M(n) = 862.6320056992192\n",
      "Generation 8695: p = 0.9584800063324658\n",
      "Generation 8695: M(n) = 862.6320056992192\n",
      "Generation 8696: p = 0.9584800063324658\n",
      "Generation 8696: M(n) = 862.6320056992192\n",
      "Generation 8697: p = 0.9584800063324658\n",
      "Generation 8697: M(n) = 862.6320056992192\n",
      "Generation 8698: p = 0.9584800063324658\n",
      "Generation 8698: M(n) = 862.6320056992192\n",
      "Generation 8699: p = 0.9584800063324658\n",
      "Generation 8699: M(n) = 862.6320056992192\n",
      "Generation 8700: p = 0.9584800063324658\n",
      "Generation 8700: M(n) = 862.6320056992192\n",
      "Generation 8701: p = 0.9584800063324658\n",
      "Generation 8701: M(n) = 862.6320056992192\n",
      "Generation 8702: p = 0.9584800063324658\n",
      "Generation 8702: M(n) = 862.6320056992192\n",
      "Generation 8703: p = 0.9584800063324658\n",
      "Generation 8703: M(n) = 862.6320056992192\n",
      "Generation 8704: p = 0.9584800063324658\n",
      "Generation 8704: M(n) = 862.6320056992192\n",
      "Generation 8705: p = 0.9584800063324658\n",
      "Generation 8705: M(n) = 862.6320056992192\n",
      "Generation 8706: p = 0.9584800063324658\n",
      "Generation 8706: M(n) = 862.6320056992192\n",
      "Generation 8707: p = 0.9584800063324658\n",
      "Generation 8707: M(n) = 862.6320056992192\n",
      "Generation 8708: p = 0.9584800063324658\n",
      "Generation 8708: M(n) = 862.6320056992192\n",
      "Generation 8709: p = 0.9584800063324658\n",
      "Generation 8709: M(n) = 862.6320056992192\n",
      "Generation 8710: p = 0.9584800063324658\n",
      "Generation 8710: M(n) = 862.6320056992192\n",
      "Generation 8711: p = 0.9584800063324658\n",
      "Generation 8711: M(n) = 862.6320056992192\n",
      "Generation 8712: p = 0.9584800063324658\n",
      "Generation 8712: M(n) = 862.6320056992192\n",
      "Generation 8713: p = 0.9584800063324658\n",
      "Generation 8713: M(n) = 862.6320056992192\n",
      "Generation 8714: p = 0.9584800063324658\n",
      "Generation 8714: M(n) = 862.6320056992192\n",
      "Generation 8715: p = 0.9584800063324658\n",
      "Generation 8715: M(n) = 862.6320056992192\n",
      "Generation 8716: p = 0.9584800063324658\n",
      "Generation 8716: M(n) = 862.6320056992192\n",
      "Generation 8717: p = 0.9584800063324658\n",
      "Generation 8717: M(n) = 862.6320056992192\n",
      "Generation 8718: p = 0.9584800063324658\n",
      "Generation 8718: M(n) = 862.6320056992192\n",
      "Generation 8719: p = 0.9584800063324658\n",
      "Generation 8719: M(n) = 862.6320056992192\n",
      "Generation 8720: p = 0.9584800063324658\n",
      "Generation 8720: M(n) = 862.6320056992192\n",
      "Generation 8721: p = 0.9584800063324658\n",
      "Generation 8721: M(n) = 862.6320056992192\n",
      "Generation 8722: p = 0.9584800063324658\n",
      "Generation 8722: M(n) = 862.6320056992192\n",
      "Generation 8723: p = 0.9584800063324658\n",
      "Generation 8723: M(n) = 862.6320056992192\n",
      "Generation 8724: p = 0.9584800063324658\n",
      "Generation 8724: M(n) = 862.6320056992192\n",
      "Generation 8725: p = 0.9584800063324658\n",
      "Generation 8725: M(n) = 862.6320056992192\n",
      "Generation 8726: p = 0.9584800063324658\n",
      "Generation 8726: M(n) = 862.6320056992192\n",
      "Generation 8727: p = 0.9584800063324658\n",
      "Generation 8727: M(n) = 862.6320056992192\n",
      "Generation 8728: p = 0.9584800063324658\n",
      "Generation 8728: M(n) = 862.6320056992192\n",
      "Generation 8729: p = 0.9584800063324658\n",
      "Generation 8729: M(n) = 862.6320056992192\n",
      "Generation 8730: p = 0.9584800063324658\n",
      "Generation 8730: M(n) = 862.6320056992192\n",
      "Generation 8731: p = 0.9584800063324658\n",
      "Generation 8731: M(n) = 862.6320056992192\n",
      "Generation 8732: p = 0.9584800063324658\n",
      "Generation 8732: M(n) = 862.6320056992192\n",
      "Generation 8733: p = 0.9584800063324658\n",
      "Generation 8733: M(n) = 862.6320056992192\n",
      "Generation 8734: p = 0.9584800063324658\n",
      "Generation 8734: M(n) = 862.6320056992192\n",
      "Generation 8735: p = 0.9584800063324658\n",
      "Generation 8735: M(n) = 862.6320056992192\n",
      "Generation 8736: p = 0.9584800063324658\n",
      "Generation 8736: M(n) = 862.6320056992192\n",
      "Generation 8737: p = 0.9584800063324658\n",
      "Generation 8737: M(n) = 862.6320056992192\n",
      "Generation 8738: p = 0.9584800063324658\n",
      "Generation 8738: M(n) = 862.6320056992192\n",
      "Generation 8739: p = 0.9584800063324658\n",
      "Generation 8739: M(n) = 862.6320056992192\n",
      "Generation 8740: p = 0.9584800063324658\n",
      "Generation 8740: M(n) = 862.6320056992192\n",
      "Generation 8741: p = 0.9584800063324658\n",
      "Generation 8741: M(n) = 862.6320056992192\n",
      "Generation 8742: p = 0.9584800063324658\n",
      "Generation 8742: M(n) = 862.6320056992192\n",
      "Generation 8743: p = 0.9584800063324658\n",
      "Generation 8743: M(n) = 862.6320056992192\n",
      "Generation 8744: p = 0.9584800063324658\n",
      "Generation 8744: M(n) = 862.6320056992192\n",
      "Generation 8745: p = 0.9584800063324658\n",
      "Generation 8745: M(n) = 862.6320056992192\n",
      "Generation 8746: p = 0.9584800063324658\n",
      "Generation 8746: M(n) = 862.6320056992192\n",
      "Generation 8747: p = 0.9584800063324658\n",
      "Generation 8747: M(n) = 862.6320056992192\n",
      "Generation 8748: p = 0.9584800063324658\n",
      "Generation 8748: M(n) = 862.6320056992192\n",
      "Generation 8749: p = 0.9584800063324658\n",
      "Generation 8749: M(n) = 862.6320056992192\n",
      "Generation 8750: p = 0.9584800063324658\n",
      "Generation 8750: M(n) = 862.6320056992192\n",
      "Generation 8751: p = 0.9584800063324658\n",
      "Generation 8751: M(n) = 862.6320056992192\n",
      "Generation 8752: p = 0.9584800063324658\n",
      "Generation 8752: M(n) = 862.6320056992192\n",
      "Generation 8753: p = 0.9584800063324658\n",
      "Generation 8753: M(n) = 862.6320056992192\n",
      "Generation 8754: p = 0.9584800063324658\n",
      "Generation 8754: M(n) = 862.6320056992192\n",
      "Generation 8755: p = 0.9584800063324658\n",
      "Generation 8755: M(n) = 862.6320056992192\n",
      "Generation 8756: p = 0.9584800063324658\n",
      "Generation 8756: M(n) = 862.6320056992192\n",
      "Generation 8757: p = 0.9584800063324658\n",
      "Generation 8757: M(n) = 862.6320056992192\n",
      "Generation 8758: p = 0.9584800063324658\n",
      "Generation 8758: M(n) = 862.6320056992192\n",
      "Generation 8759: p = 0.9584800063324658\n",
      "Generation 8759: M(n) = 862.6320056992192\n",
      "Generation 8760: p = 0.9584800063324658\n",
      "Generation 8760: M(n) = 862.6320056992192\n",
      "Generation 8761: p = 0.9584800063324658\n",
      "Generation 8761: M(n) = 862.6320056992192\n",
      "Generation 8762: p = 0.9584800063324658\n",
      "Generation 8762: M(n) = 862.6320056992192\n",
      "Generation 8763: p = 0.9584800063324658\n",
      "Generation 8763: M(n) = 862.6320056992192\n",
      "Generation 8764: p = 0.9584800063324658\n",
      "Generation 8764: M(n) = 862.6320056992192\n",
      "Generation 8765: p = 0.9584800063324658\n",
      "Generation 8765: M(n) = 862.6320056992192\n",
      "Generation 8766: p = 0.9584800063324658\n",
      "Generation 8766: M(n) = 862.6320056992192\n",
      "Generation 8767: p = 0.9584800063324658\n",
      "Generation 8767: M(n) = 862.6320056992192\n",
      "Generation 8768: p = 0.9584800063324658\n",
      "Generation 8768: M(n) = 862.6320056992192\n",
      "Generation 8769: p = 0.9584800063324658\n",
      "Generation 8769: M(n) = 862.6320056992192\n",
      "Generation 8770: p = 0.9584800063324658\n",
      "Generation 8770: M(n) = 862.6320056992192\n",
      "Generation 8771: p = 0.9584800063324658\n",
      "Generation 8771: M(n) = 862.6320056992192\n",
      "Generation 8772: p = 0.9584800063324658\n",
      "Generation 8772: M(n) = 862.6320056992192\n",
      "Generation 8773: p = 0.9584800063324658\n",
      "Generation 8773: M(n) = 862.6320056992192\n",
      "Generation 8774: p = 0.9584800063324658\n",
      "Generation 8774: M(n) = 862.6320056992192\n",
      "Generation 8775: p = 0.9584800063324658\n",
      "Generation 8775: M(n) = 862.6320056992192\n",
      "Generation 8776: p = 0.9584800063324658\n",
      "Generation 8776: M(n) = 862.6320056992192\n",
      "Generation 8777: p = 0.9584800063324658\n",
      "Generation 8777: M(n) = 862.6320056992192\n",
      "Generation 8778: p = 0.9584800063324658\n",
      "Generation 8778: M(n) = 862.6320056992192\n",
      "Generation 8779: p = 0.9584800063324658\n",
      "Generation 8779: M(n) = 862.6320056992192\n",
      "Generation 8780: p = 0.9584800063324658\n",
      "Generation 8780: M(n) = 862.6320056992192\n",
      "Generation 8781: p = 0.9584800063324658\n",
      "Generation 8781: M(n) = 862.6320056992192\n",
      "Generation 8782: p = 0.9584800063324658\n",
      "Generation 8782: M(n) = 862.6320056992192\n",
      "Generation 8783: p = 0.9584800063324658\n",
      "Generation 8783: M(n) = 862.6320056992192\n",
      "Generation 8784: p = 0.9584800063324658\n",
      "Generation 8784: M(n) = 862.6320056992192\n",
      "Generation 8785: p = 0.9584800063324658\n",
      "Generation 8785: M(n) = 862.6320056992192\n",
      "Generation 8786: p = 0.9584800063324658\n",
      "Generation 8786: M(n) = 862.6320056992192\n",
      "Generation 8787: p = 0.9584800063324658\n",
      "Generation 8787: M(n) = 862.6320056992192\n",
      "Generation 8788: p = 0.9584800063324658\n",
      "Generation 8788: M(n) = 862.6320056992192\n",
      "Generation 8789: p = 0.9584800063324658\n",
      "Generation 8789: M(n) = 862.6320056992192\n",
      "Generation 8790: p = 0.9584800063324658\n",
      "Generation 8790: M(n) = 862.6320056992192\n",
      "Generation 8791: p = 0.9584800063324658\n",
      "Generation 8791: M(n) = 862.6320056992192\n",
      "Generation 8792: p = 0.9584800063324658\n",
      "Generation 8792: M(n) = 862.6320056992192\n",
      "Generation 8793: p = 0.9584800063324658\n",
      "Generation 8793: M(n) = 862.6320056992192\n",
      "Generation 8794: p = 0.9584800063324658\n",
      "Generation 8794: M(n) = 862.6320056992192\n",
      "Generation 8795: p = 0.9584800063324658\n",
      "Generation 8795: M(n) = 862.6320056992192\n",
      "Generation 8796: p = 0.9584800063324658\n",
      "Generation 8796: M(n) = 862.6320056992192\n",
      "Generation 8797: p = 0.9584800063324658\n",
      "Generation 8797: M(n) = 862.6320056992192\n",
      "Generation 8798: p = 0.9584800063324658\n",
      "Generation 8798: M(n) = 862.6320056992192\n",
      "Generation 8799: p = 0.9584800063324658\n",
      "Generation 8799: M(n) = 862.6320056992192\n",
      "Generation 8800: p = 0.9584800063324658\n",
      "Generation 8800: M(n) = 862.6320056992192\n",
      "Generation 8801: p = 0.9584800063324658\n",
      "Generation 8801: M(n) = 862.6320056992192\n",
      "Generation 8802: p = 0.9584800063324658\n",
      "Generation 8802: M(n) = 862.6320056992192\n",
      "Generation 8803: p = 0.9584800063324658\n",
      "Generation 8803: M(n) = 862.6320056992192\n",
      "Generation 8804: p = 0.9584800063324658\n",
      "Generation 8804: M(n) = 862.6320056992192\n",
      "Generation 8805: p = 0.9584800063324658\n",
      "Generation 8805: M(n) = 862.6320056992192\n",
      "Generation 8806: p = 0.9584800063324658\n",
      "Generation 8806: M(n) = 862.6320056992192\n",
      "Generation 8807: p = 0.9584800063324658\n",
      "Generation 8807: M(n) = 862.6320056992192\n",
      "Generation 8808: p = 0.9584800063324658\n",
      "Generation 8808: M(n) = 862.6320056992192\n",
      "Generation 8809: p = 0.9584800063324658\n",
      "Generation 8809: M(n) = 862.6320056992192\n",
      "Generation 8810: p = 0.9584800063324658\n",
      "Generation 8810: M(n) = 862.6320056992192\n",
      "Generation 8811: p = 0.9584800063324658\n",
      "Generation 8811: M(n) = 862.6320056992192\n",
      "Generation 8812: p = 0.9584800063324658\n",
      "Generation 8812: M(n) = 862.6320056992192\n",
      "Generation 8813: p = 0.9584800063324658\n",
      "Generation 8813: M(n) = 862.6320056992192\n",
      "Generation 8814: p = 0.9584800063324658\n",
      "Generation 8814: M(n) = 862.6320056992192\n",
      "Generation 8815: p = 0.9584800063324658\n",
      "Generation 8815: M(n) = 862.6320056992192\n",
      "Generation 8816: p = 0.9584800063324658\n",
      "Generation 8816: M(n) = 862.6320056992192\n",
      "Generation 8817: p = 0.9584800063324658\n",
      "Generation 8817: M(n) = 862.6320056992192\n",
      "Generation 8818: p = 0.9584800063324658\n",
      "Generation 8818: M(n) = 862.6320056992192\n",
      "Generation 8819: p = 0.9584800063324658\n",
      "Generation 8819: M(n) = 862.6320056992192\n",
      "Generation 8820: p = 0.9584800063324658\n",
      "Generation 8820: M(n) = 862.6320056992192\n",
      "Generation 8821: p = 0.9584800063324658\n",
      "Generation 8821: M(n) = 862.6320056992192\n",
      "Generation 8822: p = 0.9584800063324658\n",
      "Generation 8822: M(n) = 862.6320056992192\n",
      "Generation 8823: p = 0.9584800063324658\n",
      "Generation 8823: M(n) = 862.6320056992192\n",
      "Generation 8824: p = 0.9584800063324658\n",
      "Generation 8824: M(n) = 862.6320056992192\n",
      "Generation 8825: p = 0.9584800063324658\n",
      "Generation 8825: M(n) = 862.6320056992192\n",
      "Generation 8826: p = 0.9584800063324658\n",
      "Generation 8826: M(n) = 862.6320056992192\n",
      "Generation 8827: p = 0.9584800063324658\n",
      "Generation 8827: M(n) = 862.6320056992192\n",
      "Generation 8828: p = 0.9584800063324658\n",
      "Generation 8828: M(n) = 862.6320056992192\n",
      "Generation 8829: p = 0.9584800063324658\n",
      "Generation 8829: M(n) = 862.6320056992192\n",
      "Generation 8830: p = 0.9584800063324658\n",
      "Generation 8830: M(n) = 862.6320056992192\n",
      "Generation 8831: p = 0.9584800063324658\n",
      "Generation 8831: M(n) = 862.6320056992192\n",
      "Generation 8832: p = 0.9584800063324658\n",
      "Generation 8832: M(n) = 862.6320056992192\n",
      "Generation 8833: p = 0.9584800063324658\n",
      "Generation 8833: M(n) = 862.6320056992192\n",
      "Generation 8834: p = 0.9584800063324658\n",
      "Generation 8834: M(n) = 862.6320056992192\n",
      "Generation 8835: p = 0.9584800063324658\n",
      "Generation 8835: M(n) = 862.6320056992192\n",
      "Generation 8836: p = 0.9584800063324658\n",
      "Generation 8836: M(n) = 862.6320056992192\n",
      "Generation 8837: p = 0.9584800063324658\n",
      "Generation 8837: M(n) = 862.6320056992192\n",
      "Generation 8838: p = 0.9584800063324658\n",
      "Generation 8838: M(n) = 862.6320056992192\n",
      "Generation 8839: p = 0.9584800063324658\n",
      "Generation 8839: M(n) = 862.6320056992192\n",
      "Generation 8840: p = 0.9584800063324658\n",
      "Generation 8840: M(n) = 862.6320056992192\n",
      "Generation 8841: p = 0.9584800063324658\n",
      "Generation 8841: M(n) = 862.6320056992192\n",
      "Generation 8842: p = 0.9584800063324658\n",
      "Generation 8842: M(n) = 862.6320056992192\n",
      "Generation 8843: p = 0.9584800063324658\n",
      "Generation 8843: M(n) = 862.6320056992192\n",
      "Generation 8844: p = 0.9584800063324658\n",
      "Generation 8844: M(n) = 862.6320056992192\n",
      "Generation 8845: p = 0.9584800063324658\n",
      "Generation 8845: M(n) = 862.6320056992192\n",
      "Generation 8846: p = 0.9584800063324658\n",
      "Generation 8846: M(n) = 862.6320056992192\n",
      "Generation 8847: p = 0.9584800063324658\n",
      "Generation 8847: M(n) = 862.6320056992192\n",
      "Generation 8848: p = 0.9584800063324658\n",
      "Generation 8848: M(n) = 862.6320056992192\n",
      "Generation 8849: p = 0.9584800063324658\n",
      "Generation 8849: M(n) = 862.6320056992192\n",
      "Generation 8850: p = 0.9584800063324658\n",
      "Generation 8850: M(n) = 862.6320056992192\n",
      "Generation 8851: p = 0.9584800063324658\n",
      "Generation 8851: M(n) = 862.6320056992192\n",
      "Generation 8852: p = 0.9584800063324658\n",
      "Generation 8852: M(n) = 862.6320056992192\n",
      "Generation 8853: p = 0.9584800063324658\n",
      "Generation 8853: M(n) = 862.6320056992192\n",
      "Generation 8854: p = 0.9584800063324658\n",
      "Generation 8854: M(n) = 862.6320056992192\n",
      "Generation 8855: p = 0.9584800063324658\n",
      "Generation 8855: M(n) = 862.6320056992192\n",
      "Generation 8856: p = 0.9584800063324658\n",
      "Generation 8856: M(n) = 862.6320056992192\n",
      "Generation 8857: p = 0.9584800063324658\n",
      "Generation 8857: M(n) = 862.6320056992192\n",
      "Generation 8858: p = 0.9584800063324658\n",
      "Generation 8858: M(n) = 862.6320056992192\n",
      "Generation 8859: p = 0.9584800063324658\n",
      "Generation 8859: M(n) = 862.6320056992192\n",
      "Generation 8860: p = 0.9584800063324658\n",
      "Generation 8860: M(n) = 862.6320056992192\n",
      "Generation 8861: p = 0.9584800063324658\n",
      "Generation 8861: M(n) = 862.6320056992192\n",
      "Generation 8862: p = 0.9584800063324658\n",
      "Generation 8862: M(n) = 862.6320056992192\n",
      "Generation 8863: p = 0.9584800063324658\n",
      "Generation 8863: M(n) = 862.6320056992192\n",
      "Generation 8864: p = 0.9584800063324658\n",
      "Generation 8864: M(n) = 862.6320056992192\n",
      "Generation 8865: p = 0.9584800063324658\n",
      "Generation 8865: M(n) = 862.6320056992192\n",
      "Generation 8866: p = 0.9584800063324658\n",
      "Generation 8866: M(n) = 862.6320056992192\n",
      "Generation 8867: p = 0.9584800063324658\n",
      "Generation 8867: M(n) = 862.6320056992192\n",
      "Generation 8868: p = 0.9584800063324658\n",
      "Generation 8868: M(n) = 862.6320056992192\n",
      "Generation 8869: p = 0.9584800063324658\n",
      "Generation 8869: M(n) = 862.6320056992192\n",
      "Generation 8870: p = 0.9584800063324658\n",
      "Generation 8870: M(n) = 862.6320056992192\n",
      "Generation 8871: p = 0.9584800063324658\n",
      "Generation 8871: M(n) = 862.6320056992192\n",
      "Generation 8872: p = 0.9584800063324658\n",
      "Generation 8872: M(n) = 862.6320056992192\n",
      "Generation 8873: p = 0.9584800063324658\n",
      "Generation 8873: M(n) = 862.6320056992192\n",
      "Generation 8874: p = 0.9584800063324658\n",
      "Generation 8874: M(n) = 862.6320056992192\n",
      "Generation 8875: p = 0.9584800063324658\n",
      "Generation 8875: M(n) = 862.6320056992192\n",
      "Generation 8876: p = 0.9584800063324658\n",
      "Generation 8876: M(n) = 862.6320056992192\n",
      "Generation 8877: p = 0.9584800063324658\n",
      "Generation 8877: M(n) = 862.6320056992192\n",
      "Generation 8878: p = 0.9584800063324658\n",
      "Generation 8878: M(n) = 862.6320056992192\n",
      "Generation 8879: p = 0.9584800063324658\n",
      "Generation 8879: M(n) = 862.6320056992192\n",
      "Generation 8880: p = 0.9584800063324658\n",
      "Generation 8880: M(n) = 862.6320056992192\n",
      "Generation 8881: p = 0.9584800063324658\n",
      "Generation 8881: M(n) = 862.6320056992192\n",
      "Generation 8882: p = 0.9584800063324658\n",
      "Generation 8882: M(n) = 862.6320056992192\n",
      "Generation 8883: p = 0.9584800063324658\n",
      "Generation 8883: M(n) = 862.6320056992192\n",
      "Generation 8884: p = 0.9584800063324658\n",
      "Generation 8884: M(n) = 862.6320056992192\n",
      "Generation 8885: p = 0.9584800063324658\n",
      "Generation 8885: M(n) = 862.6320056992192\n",
      "Generation 8886: p = 0.9584800063324658\n",
      "Generation 8886: M(n) = 862.6320056992192\n",
      "Generation 8887: p = 0.9584800063324658\n",
      "Generation 8887: M(n) = 862.6320056992192\n",
      "Generation 8888: p = 0.9584800063324658\n",
      "Generation 8888: M(n) = 862.6320056992192\n",
      "Generation 8889: p = 0.9584800063324658\n",
      "Generation 8889: M(n) = 862.6320056992192\n",
      "Generation 8890: p = 0.9584800063324658\n",
      "Generation 8890: M(n) = 862.6320056992192\n",
      "Generation 8891: p = 0.9584800063324658\n",
      "Generation 8891: M(n) = 862.6320056992192\n",
      "Generation 8892: p = 0.9584800063324658\n",
      "Generation 8892: M(n) = 862.6320056992192\n",
      "Generation 8893: p = 0.9584800063324658\n",
      "Generation 8893: M(n) = 862.6320056992192\n",
      "Generation 8894: p = 0.9584800063324658\n",
      "Generation 8894: M(n) = 862.6320056992192\n",
      "Generation 8895: p = 0.9584800063324658\n",
      "Generation 8895: M(n) = 862.6320056992192\n",
      "Generation 8896: p = 0.9584800063324658\n",
      "Generation 8896: M(n) = 862.6320056992192\n",
      "Generation 8897: p = 0.9584800063324658\n",
      "Generation 8897: M(n) = 862.6320056992192\n",
      "Generation 8898: p = 0.9584800063324658\n",
      "Generation 8898: M(n) = 862.6320056992192\n",
      "Generation 8899: p = 0.9584800063324658\n",
      "Generation 8899: M(n) = 862.6320056992192\n",
      "Generation 8900: p = 0.9584800063324658\n",
      "Generation 8900: M(n) = 862.6320056992192\n",
      "Generation 8901: p = 0.9584800063324658\n",
      "Generation 8901: M(n) = 862.6320056992192\n",
      "Generation 8902: p = 0.9584800063324658\n",
      "Generation 8902: M(n) = 862.6320056992192\n",
      "Generation 8903: p = 0.9584800063324658\n",
      "Generation 8903: M(n) = 862.6320056992192\n",
      "Generation 8904: p = 0.9584800063324658\n",
      "Generation 8904: M(n) = 862.6320056992192\n",
      "Generation 8905: p = 0.9584800063324658\n",
      "Generation 8905: M(n) = 862.6320056992192\n",
      "Generation 8906: p = 0.9584800063324658\n",
      "Generation 8906: M(n) = 862.6320056992192\n",
      "Generation 8907: p = 0.9584800063324658\n",
      "Generation 8907: M(n) = 862.6320056992192\n",
      "Generation 8908: p = 0.9584800063324658\n",
      "Generation 8908: M(n) = 862.6320056992192\n",
      "Generation 8909: p = 0.9584800063324658\n",
      "Generation 8909: M(n) = 862.6320056992192\n",
      "Generation 8910: p = 0.9584800063324658\n",
      "Generation 8910: M(n) = 862.6320056992192\n",
      "Generation 8911: p = 0.9584800063324658\n",
      "Generation 8911: M(n) = 862.6320056992192\n",
      "Generation 8912: p = 0.9584800063324658\n",
      "Generation 8912: M(n) = 862.6320056992192\n",
      "Generation 8913: p = 0.9584800063324658\n",
      "Generation 8913: M(n) = 862.6320056992192\n",
      "Generation 8914: p = 0.9584800063324658\n",
      "Generation 8914: M(n) = 862.6320056992192\n",
      "Generation 8915: p = 0.9584800063324658\n",
      "Generation 8915: M(n) = 862.6320056992192\n",
      "Generation 8916: p = 0.9584800063324658\n",
      "Generation 8916: M(n) = 862.6320056992192\n",
      "Generation 8917: p = 0.9584800063324658\n",
      "Generation 8917: M(n) = 862.6320056992192\n",
      "Generation 8918: p = 0.9584800063324658\n",
      "Generation 8918: M(n) = 862.6320056992192\n",
      "Generation 8919: p = 0.9584800063324658\n",
      "Generation 8919: M(n) = 862.6320056992192\n",
      "Generation 8920: p = 0.9584800063324658\n",
      "Generation 8920: M(n) = 862.6320056992192\n",
      "Generation 8921: p = 0.9584800063324658\n",
      "Generation 8921: M(n) = 862.6320056992192\n",
      "Generation 8922: p = 0.9584800063324658\n",
      "Generation 8922: M(n) = 862.6320056992192\n",
      "Generation 8923: p = 0.9584800063324658\n",
      "Generation 8923: M(n) = 862.6320056992192\n",
      "Generation 8924: p = 0.9584800063324658\n",
      "Generation 8924: M(n) = 862.6320056992192\n",
      "Generation 8925: p = 0.9584800063324658\n",
      "Generation 8925: M(n) = 862.6320056992192\n",
      "Generation 8926: p = 0.9584800063324658\n",
      "Generation 8926: M(n) = 862.6320056992192\n",
      "Generation 8927: p = 0.9584800063324658\n",
      "Generation 8927: M(n) = 862.6320056992192\n",
      "Generation 8928: p = 0.9584800063324658\n",
      "Generation 8928: M(n) = 862.6320056992192\n",
      "Generation 8929: p = 0.9584800063324658\n",
      "Generation 8929: M(n) = 862.6320056992192\n",
      "Generation 8930: p = 0.9584800063324658\n",
      "Generation 8930: M(n) = 862.6320056992192\n",
      "Generation 8931: p = 0.9584800063324658\n",
      "Generation 8931: M(n) = 862.6320056992192\n",
      "Generation 8932: p = 0.9584800063324658\n",
      "Generation 8932: M(n) = 862.6320056992192\n",
      "Generation 8933: p = 0.9584800063324658\n",
      "Generation 8933: M(n) = 862.6320056992192\n",
      "Generation 8934: p = 0.9584800063324658\n",
      "Generation 8934: M(n) = 862.6320056992192\n",
      "Generation 8935: p = 0.9584800063324658\n",
      "Generation 8935: M(n) = 862.6320056992192\n",
      "Generation 8936: p = 0.9584800063324658\n",
      "Generation 8936: M(n) = 862.6320056992192\n",
      "Generation 8937: p = 0.9584800063324658\n",
      "Generation 8937: M(n) = 862.6320056992192\n",
      "Generation 8938: p = 0.9584800063324658\n",
      "Generation 8938: M(n) = 862.6320056992192\n",
      "Generation 8939: p = 0.9584800063324658\n",
      "Generation 8939: M(n) = 862.6320056992192\n",
      "Generation 8940: p = 0.9584800063324658\n",
      "Generation 8940: M(n) = 862.6320056992192\n",
      "Generation 8941: p = 0.9584800063324658\n",
      "Generation 8941: M(n) = 862.6320056992192\n",
      "Generation 8942: p = 0.9584800063324658\n",
      "Generation 8942: M(n) = 862.6320056992192\n",
      "Generation 8943: p = 0.9584800063324658\n",
      "Generation 8943: M(n) = 862.6320056992192\n",
      "Generation 8944: p = 0.9584800063324658\n",
      "Generation 8944: M(n) = 862.6320056992192\n",
      "Generation 8945: p = 0.9584800063324658\n",
      "Generation 8945: M(n) = 862.6320056992192\n",
      "Generation 8946: p = 0.9584800063324658\n",
      "Generation 8946: M(n) = 862.6320056992192\n",
      "Generation 8947: p = 0.9584800063324658\n",
      "Generation 8947: M(n) = 862.6320056992192\n",
      "Generation 8948: p = 0.9584800063324658\n",
      "Generation 8948: M(n) = 862.6320056992192\n",
      "Generation 8949: p = 0.9584800063324658\n",
      "Generation 8949: M(n) = 862.6320056992192\n",
      "Generation 8950: p = 0.9584800063324658\n",
      "Generation 8950: M(n) = 862.6320056992192\n",
      "Generation 8951: p = 0.9584800063324658\n",
      "Generation 8951: M(n) = 862.6320056992192\n",
      "Generation 8952: p = 0.9584800063324658\n",
      "Generation 8952: M(n) = 862.6320056992192\n",
      "Generation 8953: p = 0.9584800063324658\n",
      "Generation 8953: M(n) = 862.6320056992192\n",
      "Generation 8954: p = 0.9584800063324658\n",
      "Generation 8954: M(n) = 862.6320056992192\n",
      "Generation 8955: p = 0.9584800063324658\n",
      "Generation 8955: M(n) = 862.6320056992192\n",
      "Generation 8956: p = 0.9584800063324658\n",
      "Generation 8956: M(n) = 862.6320056992192\n",
      "Generation 8957: p = 0.9584800063324658\n",
      "Generation 8957: M(n) = 862.6320056992192\n",
      "Generation 8958: p = 0.9584800063324658\n",
      "Generation 8958: M(n) = 862.6320056992192\n",
      "Generation 8959: p = 0.9584800063324658\n",
      "Generation 8959: M(n) = 862.6320056992192\n",
      "Generation 8960: p = 0.9584800063324658\n",
      "Generation 8960: M(n) = 862.6320056992192\n",
      "Generation 8961: p = 0.9584800063324658\n",
      "Generation 8961: M(n) = 862.6320056992192\n",
      "Generation 8962: p = 0.9584800063324658\n",
      "Generation 8962: M(n) = 862.6320056992192\n",
      "Generation 8963: p = 0.9584800063324658\n",
      "Generation 8963: M(n) = 862.6320056992192\n",
      "Generation 8964: p = 0.9584800063324658\n",
      "Generation 8964: M(n) = 862.6320056992192\n",
      "Generation 8965: p = 0.9584800063324658\n",
      "Generation 8965: M(n) = 862.6320056992192\n",
      "Generation 8966: p = 0.9584800063324658\n",
      "Generation 8966: M(n) = 862.6320056992192\n",
      "Generation 8967: p = 0.9584800063324658\n",
      "Generation 8967: M(n) = 862.6320056992192\n",
      "Generation 8968: p = 0.9584800063324658\n",
      "Generation 8968: M(n) = 862.6320056992192\n",
      "Generation 8969: p = 0.9584800063324658\n",
      "Generation 8969: M(n) = 862.6320056992192\n",
      "Generation 8970: p = 0.9584800063324658\n",
      "Generation 8970: M(n) = 862.6320056992192\n",
      "Generation 8971: p = 0.9584800063324658\n",
      "Generation 8971: M(n) = 862.6320056992192\n",
      "Generation 8972: p = 0.9584800063324658\n",
      "Generation 8972: M(n) = 862.6320056992192\n",
      "Generation 8973: p = 0.9584800063324658\n",
      "Generation 8973: M(n) = 862.6320056992192\n",
      "Generation 8974: p = 0.9584800063324658\n",
      "Generation 8974: M(n) = 862.6320056992192\n",
      "Generation 8975: p = 0.9584800063324658\n",
      "Generation 8975: M(n) = 862.6320056992192\n",
      "Generation 8976: p = 0.9584800063324658\n",
      "Generation 8976: M(n) = 862.6320056992192\n",
      "Generation 8977: p = 0.9584800063324658\n",
      "Generation 8977: M(n) = 862.6320056992192\n",
      "Generation 8978: p = 0.9584800063324658\n",
      "Generation 8978: M(n) = 862.6320056992192\n",
      "Generation 8979: p = 0.9584800063324658\n",
      "Generation 8979: M(n) = 862.6320056992192\n",
      "Generation 8980: p = 0.9584800063324658\n",
      "Generation 8980: M(n) = 862.6320056992192\n",
      "Generation 8981: p = 0.9584800063324658\n",
      "Generation 8981: M(n) = 862.6320056992192\n",
      "Generation 8982: p = 0.9584800063324658\n",
      "Generation 8982: M(n) = 862.6320056992192\n",
      "Generation 8983: p = 0.9584800063324658\n",
      "Generation 8983: M(n) = 862.6320056992192\n",
      "Generation 8984: p = 0.9584800063324658\n",
      "Generation 8984: M(n) = 862.6320056992192\n",
      "Generation 8985: p = 0.9584800063324658\n",
      "Generation 8985: M(n) = 862.6320056992192\n",
      "Generation 8986: p = 0.9584800063324658\n",
      "Generation 8986: M(n) = 862.6320056992192\n",
      "Generation 8987: p = 0.9584800063324658\n",
      "Generation 8987: M(n) = 862.6320056992192\n",
      "Generation 8988: p = 0.9584800063324658\n",
      "Generation 8988: M(n) = 862.6320056992192\n",
      "Generation 8989: p = 0.9584800063324658\n",
      "Generation 8989: M(n) = 862.6320056992192\n",
      "Generation 8990: p = 0.9584800063324658\n",
      "Generation 8990: M(n) = 862.6320056992192\n",
      "Generation 8991: p = 0.9584800063324658\n",
      "Generation 8991: M(n) = 862.6320056992192\n",
      "Generation 8992: p = 0.9584800063324658\n",
      "Generation 8992: M(n) = 862.6320056992192\n",
      "Generation 8993: p = 0.9584800063324658\n",
      "Generation 8993: M(n) = 862.6320056992192\n",
      "Generation 8994: p = 0.9584800063324658\n",
      "Generation 8994: M(n) = 862.6320056992192\n",
      "Generation 8995: p = 0.9584800063324658\n",
      "Generation 8995: M(n) = 862.6320056992192\n",
      "Generation 8996: p = 0.9584800063324658\n",
      "Generation 8996: M(n) = 862.6320056992192\n",
      "Generation 8997: p = 0.9584800063324658\n",
      "Generation 8997: M(n) = 862.6320056992192\n",
      "Generation 8998: p = 0.9584800063324658\n",
      "Generation 8998: M(n) = 862.6320056992192\n",
      "Generation 8999: p = 0.9584800063324658\n",
      "Generation 8999: M(n) = 862.6320056992192\n",
      "Generation 9000: p = 0.9584800063324658\n",
      "Generation 9000: M(n) = 862.6320056992192\n",
      "Generation 9001: p = 0.9584800063324658\n",
      "Generation 9001: M(n) = 862.6320056992192\n",
      "Generation 9002: p = 0.9584800063324658\n",
      "Generation 9002: M(n) = 862.6320056992192\n",
      "Generation 9003: p = 0.9584800063324658\n",
      "Generation 9003: M(n) = 862.6320056992192\n",
      "Generation 9004: p = 0.9584800063324658\n",
      "Generation 9004: M(n) = 862.6320056992192\n",
      "Generation 9005: p = 0.9584800063324658\n",
      "Generation 9005: M(n) = 862.6320056992192\n",
      "Generation 9006: p = 0.9584800063324658\n",
      "Generation 9006: M(n) = 862.6320056992192\n",
      "Generation 9007: p = 0.9584800063324658\n",
      "Generation 9007: M(n) = 862.6320056992192\n",
      "Generation 9008: p = 0.9584800063324658\n",
      "Generation 9008: M(n) = 862.6320056992192\n",
      "Generation 9009: p = 0.9584800063324658\n",
      "Generation 9009: M(n) = 862.6320056992192\n",
      "Generation 9010: p = 0.9584800063324658\n",
      "Generation 9010: M(n) = 862.6320056992192\n",
      "Generation 9011: p = 0.9584800063324658\n",
      "Generation 9011: M(n) = 862.6320056992192\n",
      "Generation 9012: p = 0.9584800063324658\n",
      "Generation 9012: M(n) = 862.6320056992192\n",
      "Generation 9013: p = 0.9584800063324658\n",
      "Generation 9013: M(n) = 862.6320056992192\n",
      "Generation 9014: p = 0.9584800063324658\n",
      "Generation 9014: M(n) = 862.6320056992192\n",
      "Generation 9015: p = 0.9584800063324658\n",
      "Generation 9015: M(n) = 862.6320056992192\n",
      "Generation 9016: p = 0.9584800063324658\n",
      "Generation 9016: M(n) = 862.6320056992192\n",
      "Generation 9017: p = 0.9584800063324658\n",
      "Generation 9017: M(n) = 862.6320056992192\n",
      "Generation 9018: p = 0.9584800063324658\n",
      "Generation 9018: M(n) = 862.6320056992192\n",
      "Generation 9019: p = 0.9584800063324658\n",
      "Generation 9019: M(n) = 862.6320056992192\n",
      "Generation 9020: p = 0.9584800063324658\n",
      "Generation 9020: M(n) = 862.6320056992192\n",
      "Generation 9021: p = 0.9584800063324658\n",
      "Generation 9021: M(n) = 862.6320056992192\n",
      "Generation 9022: p = 0.9584800063324658\n",
      "Generation 9022: M(n) = 862.6320056992192\n",
      "Generation 9023: p = 0.9584800063324658\n",
      "Generation 9023: M(n) = 862.6320056992192\n",
      "Generation 9024: p = 0.9584800063324658\n",
      "Generation 9024: M(n) = 862.6320056992192\n",
      "Generation 9025: p = 0.9584800063324658\n",
      "Generation 9025: M(n) = 862.6320056992192\n",
      "Generation 9026: p = 0.9584800063324658\n",
      "Generation 9026: M(n) = 862.6320056992192\n",
      "Generation 9027: p = 0.9584800063324658\n",
      "Generation 9027: M(n) = 862.6320056992192\n",
      "Generation 9028: p = 0.9584800063324658\n",
      "Generation 9028: M(n) = 862.6320056992192\n",
      "Generation 9029: p = 0.9584800063324658\n",
      "Generation 9029: M(n) = 862.6320056992192\n",
      "Generation 9030: p = 0.9584800063324658\n",
      "Generation 9030: M(n) = 862.6320056992192\n",
      "Generation 9031: p = 0.9584800063324658\n",
      "Generation 9031: M(n) = 862.6320056992192\n",
      "Generation 9032: p = 0.9584800063324658\n",
      "Generation 9032: M(n) = 862.6320056992192\n",
      "Generation 9033: p = 0.9584800063324658\n",
      "Generation 9033: M(n) = 862.6320056992192\n",
      "Generation 9034: p = 0.9584800063324658\n",
      "Generation 9034: M(n) = 862.6320056992192\n",
      "Generation 9035: p = 0.9584800063324658\n",
      "Generation 9035: M(n) = 862.6320056992192\n",
      "Generation 9036: p = 0.9584800063324658\n",
      "Generation 9036: M(n) = 862.6320056992192\n",
      "Generation 9037: p = 0.9584800063324658\n",
      "Generation 9037: M(n) = 862.6320056992192\n",
      "Generation 9038: p = 0.9584800063324658\n",
      "Generation 9038: M(n) = 862.6320056992192\n",
      "Generation 9039: p = 0.9584800063324658\n",
      "Generation 9039: M(n) = 862.6320056992192\n",
      "Generation 9040: p = 0.9584800063324658\n",
      "Generation 9040: M(n) = 862.6320056992192\n",
      "Generation 9041: p = 0.9584800063324658\n",
      "Generation 9041: M(n) = 862.6320056992192\n",
      "Generation 9042: p = 0.9584800063324658\n",
      "Generation 9042: M(n) = 862.6320056992192\n",
      "Generation 9043: p = 0.9584800063324658\n",
      "Generation 9043: M(n) = 862.6320056992192\n",
      "Generation 9044: p = 0.9584800063324658\n",
      "Generation 9044: M(n) = 862.6320056992192\n",
      "Generation 9045: p = 0.9584800063324658\n",
      "Generation 9045: M(n) = 862.6320056992192\n",
      "Generation 9046: p = 0.9584800063324658\n",
      "Generation 9046: M(n) = 862.6320056992192\n",
      "Generation 9047: p = 0.9584800063324658\n",
      "Generation 9047: M(n) = 862.6320056992192\n",
      "Generation 9048: p = 0.9584800063324658\n",
      "Generation 9048: M(n) = 862.6320056992192\n",
      "Generation 9049: p = 0.9584800063324658\n",
      "Generation 9049: M(n) = 862.6320056992192\n",
      "Generation 9050: p = 0.9584800063324658\n",
      "Generation 9050: M(n) = 862.6320056992192\n",
      "Generation 9051: p = 0.9584800063324658\n",
      "Generation 9051: M(n) = 862.6320056992192\n",
      "Generation 9052: p = 0.9584800063324658\n",
      "Generation 9052: M(n) = 862.6320056992192\n",
      "Generation 9053: p = 0.9584800063324658\n",
      "Generation 9053: M(n) = 862.6320056992192\n",
      "Generation 9054: p = 0.9584800063324658\n",
      "Generation 9054: M(n) = 862.6320056992192\n",
      "Generation 9055: p = 0.9584800063324658\n",
      "Generation 9055: M(n) = 862.6320056992192\n",
      "Generation 9056: p = 0.9584800063324658\n",
      "Generation 9056: M(n) = 862.6320056992192\n",
      "Generation 9057: p = 0.9584800063324658\n",
      "Generation 9057: M(n) = 862.6320056992192\n",
      "Generation 9058: p = 0.9584800063324658\n",
      "Generation 9058: M(n) = 862.6320056992192\n",
      "Generation 9059: p = 0.9584800063324658\n",
      "Generation 9059: M(n) = 862.6320056992192\n",
      "Generation 9060: p = 0.9584800063324658\n",
      "Generation 9060: M(n) = 862.6320056992192\n",
      "Generation 9061: p = 0.9584800063324658\n",
      "Generation 9061: M(n) = 862.6320056992192\n",
      "Generation 9062: p = 0.9584800063324658\n",
      "Generation 9062: M(n) = 862.6320056992192\n",
      "Generation 9063: p = 0.9584800063324658\n",
      "Generation 9063: M(n) = 862.6320056992192\n",
      "Generation 9064: p = 0.9584800063324658\n",
      "Generation 9064: M(n) = 862.6320056992192\n",
      "Generation 9065: p = 0.9584800063324658\n",
      "Generation 9065: M(n) = 862.6320056992192\n",
      "Generation 9066: p = 0.9584800063324658\n",
      "Generation 9066: M(n) = 862.6320056992192\n",
      "Generation 9067: p = 0.9584800063324658\n",
      "Generation 9067: M(n) = 862.6320056992192\n",
      "Generation 9068: p = 0.9584800063324658\n",
      "Generation 9068: M(n) = 862.6320056992192\n",
      "Generation 9069: p = 0.9584800063324658\n",
      "Generation 9069: M(n) = 862.6320056992192\n",
      "Generation 9070: p = 0.9584800063324658\n",
      "Generation 9070: M(n) = 862.6320056992192\n",
      "Generation 9071: p = 0.9584800063324658\n",
      "Generation 9071: M(n) = 862.6320056992192\n",
      "Generation 9072: p = 0.9584800063324658\n",
      "Generation 9072: M(n) = 862.6320056992192\n",
      "Generation 9073: p = 0.9584800063324658\n",
      "Generation 9073: M(n) = 862.6320056992192\n",
      "Generation 9074: p = 0.9584800063324658\n",
      "Generation 9074: M(n) = 862.6320056992192\n",
      "Generation 9075: p = 0.9584800063324658\n",
      "Generation 9075: M(n) = 862.6320056992192\n",
      "Generation 9076: p = 0.9584800063324658\n",
      "Generation 9076: M(n) = 862.6320056992192\n",
      "Generation 9077: p = 0.9584800063324658\n",
      "Generation 9077: M(n) = 862.6320056992192\n",
      "Generation 9078: p = 0.9584800063324658\n",
      "Generation 9078: M(n) = 862.6320056992192\n",
      "Generation 9079: p = 0.9584800063324658\n",
      "Generation 9079: M(n) = 862.6320056992192\n",
      "Generation 9080: p = 0.9584800063324658\n",
      "Generation 9080: M(n) = 862.6320056992192\n",
      "Generation 9081: p = 0.9584800063324658\n",
      "Generation 9081: M(n) = 862.6320056992192\n",
      "Generation 9082: p = 0.9584800063324658\n",
      "Generation 9082: M(n) = 862.6320056992192\n",
      "Generation 9083: p = 0.9584800063324658\n",
      "Generation 9083: M(n) = 862.6320056992192\n",
      "Generation 9084: p = 0.9584800063324658\n",
      "Generation 9084: M(n) = 862.6320056992192\n",
      "Generation 9085: p = 0.9584800063324658\n",
      "Generation 9085: M(n) = 862.6320056992192\n",
      "Generation 9086: p = 0.9584800063324658\n",
      "Generation 9086: M(n) = 862.6320056992192\n",
      "Generation 9087: p = 0.9584800063324658\n",
      "Generation 9087: M(n) = 862.6320056992192\n",
      "Generation 9088: p = 0.9584800063324658\n",
      "Generation 9088: M(n) = 862.6320056992192\n",
      "Generation 9089: p = 0.9584800063324658\n",
      "Generation 9089: M(n) = 862.6320056992192\n",
      "Generation 9090: p = 0.9584800063324658\n",
      "Generation 9090: M(n) = 862.6320056992192\n",
      "Generation 9091: p = 0.9584800063324658\n",
      "Generation 9091: M(n) = 862.6320056992192\n",
      "Generation 9092: p = 0.9584800063324658\n",
      "Generation 9092: M(n) = 862.6320056992192\n",
      "Generation 9093: p = 0.9584800063324658\n",
      "Generation 9093: M(n) = 862.6320056992192\n",
      "Generation 9094: p = 0.9584800063324658\n",
      "Generation 9094: M(n) = 862.6320056992192\n",
      "Generation 9095: p = 0.9584800063324658\n",
      "Generation 9095: M(n) = 862.6320056992192\n",
      "Generation 9096: p = 0.9584800063324658\n",
      "Generation 9096: M(n) = 862.6320056992192\n",
      "Generation 9097: p = 0.9584800063324658\n",
      "Generation 9097: M(n) = 862.6320056992192\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1000x600 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "## Program DuoMutationMax_VS_Simple_Math_Model.py\n",
    "# This program compares the maximum number of touched sites \n",
    "# in a generation according to a simulation\n",
    "# with the prediction of a simplified theoretical recursive model \n",
    "# of the number of matched sites at that generation.\n",
    "# The approximation implements the idea that \n",
    "# the fittest is not chosen at each step.\n",
    "# So, we take the values  kappa = 0 and k = constant = 1.5\n",
    "\n",
    "\n",
    "\n",
    "# SIMULATION\n",
    "\n",
    "# This part is based on the code of the program \n",
    "# Variability_in_the_number_of_touched_sites.py\n",
    "\n",
    "import datetime\n",
    "import random\n",
    "import matplotlib.pyplot as plt # Import matplotlib for plotting\n",
    "# target_sequence = 'Methinks it is like a weasel.'\n",
    "# alphabet = 'abcdefghijklmnopqrstuvwxyzABCDEFGHIJKLMNOPQRSTUVWXYZ .,'\n",
    "alphabet = '01' # Binary alphabet, binary strings\n",
    "length_of_target_sequence = 900\n",
    "target_sequence = '1'*length_of_target_sequence  #1111...1 (800 ones)\n",
    "population_size = 200\n",
    "include_clone_populationf5 = True\n",
    "include_mutate_allf5 = True\n",
    "include_crossover_allf5 = False\n",
    "mutation_rate = 0.01\n",
    "recombination_rate = 0\n",
    "# alphabet = 'abcdefghijklmnopqrstuvwxyzABCDEFGHIJKLMNOPQRSTUVWXYZ .,'\n",
    "# Boolean flag to print the generation, best chromosome and fitness.\n",
    "# This is the ancestral line of the solution.\n",
    "print_best_fitness = False\n",
    "\n",
    "\n",
    "\n",
    "\n",
    "def print_parametersf5():\n",
    "    print(f\"Lab: Simple Genetic Algorithm\")\n",
    "    print(f\"Purpose: solve an instance of the Shakespeare challenge\")\n",
    "    print(f\"Date of Experiment  = {datetime.datetime.now()}\")\n",
    "    print(f\"alphabet =  {alphabet}\")\n",
    "    print(f\"target_sequence = {target_sequence}\")\n",
    "    print(f\"length_of_target_sequence = {length_of_target_sequence}\")\n",
    "    print(f\"population_size = {population_size}\")\n",
    "    print(f\"include_clone_populationf5 = {include_clone_populationf5}\")\n",
    "    print(f\"include_mutate_allf5 = {include_mutate_allf5}\")\n",
    "    print(f\"include_crossover_allf5 = {include_crossover_allf5}\")\n",
    "    if include_mutate_allf5:\n",
    "        print(f\"mutation_rate = {mutation_rate}\")\n",
    "    if include_crossover_allf5:\n",
    "        print(f\"recombination_rate = {recombination_rate}\")\n",
    "    if include_clone_populationf5:\n",
    "        print(f\"print_best_fitness = {print_best_fitness}\")\n",
    "\n",
    "\n",
    "def create_populationf5(population_size, target_sequence, alphabet):\n",
    "    \"\"\"Creates a new population with random chromosomes.\"\"\"\n",
    "    # print(\"create_population8(population_size, target_sequence, alphabet)\")\n",
    "    population = []\n",
    "    for _ in range(population_size):\n",
    "        random_string = ''.join(random.choice(alphabet) for _ in range(len(target_sequence)))\n",
    "        population.append(random_string)\n",
    "    # print(\"initial population\")\n",
    "    # print(population)\n",
    "    return population\n",
    "\n",
    "def calculate_fitnessf5(chromosome, target_sequence):\n",
    "    \"\"\"Calculates the fitness of a chromosome based on its similarity to the target sequence.\"\"\"\n",
    "    #  print(\"\\n *calculate_fitness8(chromosome, target_sequence)\")\n",
    "    fitness = 0\n",
    "    for i in range(len(chromosome)):\n",
    "        if chromosome[i] == target_sequence[i]:\n",
    "            fitness += 1\n",
    "    # print(chromosome, \"  fitness: \", fitness)\n",
    "    return fitness\n",
    "\n",
    "def calculate_all_fitnessf5(population, target_sequence):\n",
    "    # print(\"\\n*calculate_all_fitness8(population, target_sequence)\")\n",
    "    \"\"\"Calculates the fitness of all chromosomes in the population.\"\"\"\n",
    "    fitness_scores = [calculate_fitnessf5(chromosome, target_sequence) for chromosome in population]\n",
    "    # print(\"fitness_scores: \", fitness_scores)\n",
    "    return fitness_scores\n",
    "\n",
    "def select_the_bestf5(population, target_sequence):\n",
    "    \"\"\"Selects the best chromosome for reproduction.\"\"\"\n",
    "    fitness_scores = calculate_all_fitnessf5(population, target_sequence)\n",
    "    best_fitness = max(fitness_scores)\n",
    "    best_chromosome_index = fitness_scores.index(best_fitness)\n",
    "    best_chromosome = population[best_chromosome_index]\n",
    "    # print(\"\\n*select_the_bestf5(population)\")\n",
    "    # print(\"best_fitness = \", best_fitness)\n",
    "    # print(\"The chro = \", best_chromosome )\n",
    "    return best_fitness, best_chromosome\n",
    "\n",
    "def clone_populationf5(best_chromosome, population_size):\n",
    "    \"\"\"Creates a new population by cloning the best chromosome.\"\"\"\n",
    "    return [best_chromosome] * population_size\n",
    "\n",
    "\n",
    "def mutatef5(chromosome, mutation_rate, alphabet):\n",
    "    \"\"\"Mutates a chromosome.\"\"\"\n",
    "    mutated_chromosome_list = list(chromosome)\n",
    "    for i in range(len(mutated_chromosome_list)):\n",
    "        if random.random() < mutation_rate:\n",
    "                mutated_chromosome_list[i] = random.choice(alphabet)\n",
    "    return \"\".join(mutated_chromosome_list)\n",
    "\n",
    "def mutate_allf5(population, mutation_rate, alphabet):\n",
    "    \"\"\"Mutates all chromosomes in the population.\"\"\"\n",
    "    mutated_population = []\n",
    "    for chromosome in population:\n",
    "        mutated_chromosome = mutatef5(chromosome, mutation_rate, alphabet)\n",
    "        mutated_population.append(mutated_chromosome)\n",
    "    return mutated_population\n",
    "\n",
    "def crossoverf5(parent1, parent2, target_sequence, recombination_rate):\n",
    "    \"\"\"Performs crossover between two parent chromosomes.\"\"\"\n",
    "    if random.random() < recombination_rate:\n",
    "        crossover_point = random.randint(0, len(target_sequence))\n",
    "        return parent1[:crossover_point] + parent2[crossover_point:]\n",
    "    else:\n",
    "        return parent1\n",
    "\n",
    "def crossover_allf5(population, target_sequence, recombination_rate):\n",
    "    \"\"\"Performs crossover on all chromosomes in the population.\"\"\"\n",
    "    recombinant_population = []\n",
    "    for i in range(len(population)):\n",
    "        parent1 =  population[i]\n",
    "        parent2 = random.choice(population)\n",
    "        child = crossoverf5(parent1, parent2, target_sequence, recombination_rate)\n",
    "        recombinant_population.append(child)\n",
    "    return recombinant_population\n",
    "\n",
    "\n",
    "\n",
    "def run_one_generationf5(population, target_sequence, mutation_rate, recombination_rate, alphabet):\n",
    "    \"\"\"Runs one generation of the genetic algorithm.\"\"\"\n",
    "    # Calculate fitness scores for the current population\n",
    "    best_fitness, best_chromosome  = select_the_bestf5(population, target_sequence)\n",
    "    # print(f\" best_chromosome {best_chromosome}, best_fitness {best_fitness}\")\n",
    "    # Clone the best to build the new population\n",
    "    new_population = []\n",
    "    if include_clone_populationf5:\n",
    "        new_population = clone_populationf5(best_chromosome, population_size)\n",
    "    if include_mutate_allf5:\n",
    "        new_population = mutate_allf5(new_population, mutation_rate, alphabet)\n",
    "    if include_crossover_allf5:\n",
    "        new_population = crossover_allf5(new_population, target_sequence, recombination_rate)\n",
    "    return best_fitness, best_chromosome, new_population\n",
    "\n",
    "\n",
    "\n",
    "\n",
    "\n",
    "def mainf5( target_sequence, mutation_rate, recombination_rate, alphabet):\n",
    "    print_parametersf5()\n",
    "    population = create_populationf5(population_size, target_sequence, alphabet)\n",
    "    # print(population)\n",
    "    best_fitness, best_chromosome = select_the_bestf5(population, target_sequence)\n",
    "    generation = 0\n",
    "    best_fitness_history = [] # List to store best fitness of each generation\n",
    "    best_fitness_history.append(best_fitness)\n",
    "    if print_best_fitness:\n",
    "        print(\"Generation, best_chromosome and best_fitness, M_t\")\n",
    "    while best_fitness < len(target_sequence):\n",
    "        generation += 1\n",
    "        best_fitness, best_chromosome, population = run_one_generationf5(population, target_sequence, mutation_rate, recombination_rate, alphabet)        \n",
    "        if print_best_fitness:\n",
    "            print(f\" {generation}  {best_chromosome} {best_fitness}\")\n",
    "        best_fitness_history.append(best_fitness)    \n",
    "    print(f\"\\nTarget sequence matched in generation {generation}\")\n",
    "    print(f\"Final chromosome: {best_chromosome}\")\n",
    "    totalCost = population_size * generation\n",
    "    print(f\"Total cost = population size * number of generations: {totalCost}\")\n",
    "    return generation, best_fitness_history\n",
    "\n",
    "generation, best_fitness_history =  mainf5( target_sequence, mutation_rate, recombination_rate, alphabet)\n",
    "\n",
    "############################\n",
    "\n",
    "# THEORETICAL MODEL\n",
    "\n",
    "# Program Theoretical_model.py\n",
    "# This program implements the theoretical model of the truncated evolution\n",
    "import numpy as np\n",
    "import matplotlib.pyplot as plt\n",
    "\n",
    "# Definition of parameters for the theoretical model\n",
    "\n",
    "n_generations = generation # number of generations to make predictions by the model\n",
    "\n",
    "#$c = 1.29$. \n",
    "c = 1.29\n",
    "#$k = 24.9 n^{-1.18} + 2.53$\n",
    "def k(length_of_target_sequence):\n",
    "    #return 24.9 * (length_of_target_sequence ** -1.18) + 2.53 #original definition of k\n",
    "    #return 2.53 # Simplified definition of k for large target sequence lengths\n",
    "    #return 10.3229 # Adjusted value of k for better fit with empirical data\n",
    "    return 1.5\n",
    "\n",
    "\n",
    "# $\\mu = $ mutation rate, constant\n",
    "mu = mutation_rate   # Example mutation rate\n",
    "#$H = $ length of the target string, total number of sites\n",
    "H = length_of_target_sequence \n",
    "#$m = $ number of monkeys or of binomial distributions.\n",
    "m = population_size\n",
    "#$M_t = $ number of solved sites at generation $t$\n",
    "#$M_o = I = $ initial number of matched sites\n",
    "#$ = \\frac{H}{2} +  \\sqrt{\\frac{H}{k}\\ln m  }  $\n",
    "I = H / 2 + ((H / k(H)) * np.log(m)) ** 0.5\n",
    "\n",
    "\n",
    "#$T= $ number of touched sites $ =  \\mu H +  \\sqrt{H \\mu (1 - \\mu) } \\sqrt{c \\ln (m)} $ \n",
    "def T(mu, H, c, m):\n",
    "    return mu * H + (H * mu * (1 - mu)) ** 0.5 * (c * np.log(m)) ** 0.5\n",
    "\n",
    "#  $ s = $ number of solved sites among touched $ =  \\frac{T}{2} +  \\sqrt{\\frac{T}{k}\\ln m  }  $\n",
    "def s(T, m):\n",
    "    return T / 2 + ((T / k(T)) * np.log(m)) ** 0.5\n",
    "\n",
    "# $ u = $ number of untouched sites $ = H-T$\n",
    "def u(H, T):\n",
    "    return H - T\n",
    "\n",
    "# $ r =  (H-T)p +  \\sqrt{(H-T)p(1-p)} \\sqrt{1.29 \\ln (m)} $.\n",
    "\n",
    "# $p = \\frac{M_t}{H}$\n",
    "\n",
    "def p(M_t, H):\n",
    "    return M_t / H\n",
    "\n",
    "#$ r = $ number of untouched sites that were right from start \n",
    "#$ = u p + \\sqrt{u p (1-p)} \\sqrt{c \\ln m} $\n",
    "def r(u_value, H, p_value, M_t):\n",
    "    return u_value * p_value  \n",
    "    #return u_value * p_value  + ((u_value * p_value  * (1 - p_value )) ** 0.5) * (kappa * np.log(m)) ** 0.5\n",
    "\n",
    "\n",
    "#$M_{t+1} =  s + r $, number of matched sites at generation $t+1$.\n",
    "def M(s, r):\n",
    "    return s + r\n",
    "\n",
    "print(\"Parameters of the theoretical model\")\n",
    "print(f\"c = {c}\")\n",
    "print(f\"k(H) = {k(H)}\")\n",
    "print(f\"I = {I}\")\n",
    "print(f\"mu = {mu}\")\n",
    "print(f\"H = {H}\")\n",
    "print(f\"m = {m}\")\n",
    "\n",
    "M_values = []\n",
    "m_value  = I\n",
    "n = 0\n",
    "T_value = T(mu, H, c, m)\n",
    "print(f\"Generation {n}: T = {T_value}\")\n",
    "s_value = s(T_value,  m)\n",
    "print(f\"Generation {n}: s = {s_value}\")\n",
    "u_value = u(H, T_value)\n",
    "print(f\"Generation {n}: u = {u_value}\")\n",
    "# Generate a range of generations\n",
    "for n in range(n_generations):\n",
    "    p_value = p(m_value, H)\n",
    "    print(f\"Generation {n}: p = {p_value}\")\n",
    "    r_value = r(u_value, H, p_value, m_value)\n",
    "    # print(f\"Generation {n}: r = {r_value}\")\n",
    "    m_value = M(s_value, r_value)\n",
    "    if m_value > H:\n",
    "        m_value = H\n",
    "    M_values.append(m_value)\n",
    "    print(f\"Generation {n}: M(n) = {m_value}\")\n",
    "\n",
    "###########\n",
    "\n",
    "# PLOT FUNCTIONS\n",
    "\n",
    "plt.figure(figsize=(10, 6))\n",
    "# Red line for the total number of sites (H)\n",
    "plt.axhline(y=H, color='red', linestyle='--', linewidth=2, label='Total number of sites (H)')\n",
    "plt.plot(best_fitness_history, label='Best Fitness in simulation', color='blue')\n",
    "plt.plot(M_values, label = 'Predicted number of matched sites by the theoretical model', color='green')\n",
    "plt.axhline(y=length_of_target_sequence, color='red', linestyle='--', linewidth=2)\n",
    "\n",
    "plt.xlabel('Generation (n)')\n",
    "plt.ylabel('Number of Matched Sites (M)')\n",
    "plt.title('Number of Matched Sites in GA, Simulation vs Theoretical Model')\n",
    "plt.grid(True)\n",
    "plt.legend()\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "1fcbf52a",
   "metadata": {},
   "source": [
    "*Comment.* The simplified model produces for a length of the target string $H$ = 400 a graph that is an upper bound for the results of the simulation. If $H=800$, the model upper bounds the simulation when the number of matched sites $M < 750$, i.e., the fitness is less than 0.9.  It is a lower bound afterward. For $H = 900$, after 4 minutes of work by Colab, the predicted graph is a lower bound of the observed. The fit looks good with an error of 5\\%. \n",
    "\n",
    "**Practical directive.** By mere casualty we have found that $kappa = 0$ produces a good approximation. The marvel is that with this value, all calculations get quite simple. So, we will explore what it gives of itself. \n",
    "\n",
    "**Exercise.** Practice thinking big: Design a project to carry out a full calculation of the aforementioned *simplified model*. Let the Scientific Method guide you. If predictions match observations, the model pass this test, and the model deserves credibility, but others test must be invented. If predictions contradict observations, or if the model is found to be void or self-contradictory, it is false, it has been falsified. In this case, a change must be done in the model to begin anew.\n",
    ">\n",
    "> *Answer.* The full calculation of the simplified model consists of:\n",
    ">\n",
    "> 1. Formulate the simplified math model proposed in the last example, in which $kappa = 0$. \n",
    "> 2. Extract a recurrence relation. \n",
    "> 3. Abstract it, i.e., replace cumbersome terms by a single letter. \n",
    "> 4. Solve it, i.e., find the formula for the general term as a function of the initial condition, and the parameters, and constants of the model. \n",
    "> 5. Prove your solution by induction. \n",
    "> 6. Replace abstract terms by concrete ones to find a solution for our specific problem. \n",
    "> 7. Compare graphically the evolution according to the proposed solution with that produced by the original recursion system. The two graphs must be undistinguishable. \n",
    "> 8. Test your specific solution, which is a prediction, comparing it with the observed. The predicted graph must be an upper bound of the observed one whenever the fitness is less than 90\\%, and a lower bound afterward. \n",
    "\n",
    "**Exercise.** Execute your project.\n",
    ">\n",
    ">*Answer.* Let us develop our research program step by step, 8 in all. \n",
    "\n",
    "- Step 1. Formulate the simplified math model proposed in the last example, in which $kappa = 0$. \n",
    "\n",
    "The parameter kappa does not appear in the simplified math model because it is equal to zero. The model is therefore the following:\n",
    "\n",
    "\n",
    ">**************\n",
    "> *Simplified Math Model*, without kappa, of the change in the number of matched sites $M$ in the winner chromosome of each generation:\n",
    ">*************\n",
    ">\n",
    "> $c = 1.29$. \n",
    ">\n",
    "> $n = $ length of a subsequence to be matched, depends on context. \n",
    "> \n",
    "> $k = 24.9 n^{-1.18} + 2.53$\n",
    ">\n",
    "> $\\mu = $ mutation rate, constant\n",
    ">\n",
    "> $H = $ length of the target string, total number of sites\n",
    ">\n",
    "> $m = $ number of monkeys or of binomial distributions.\n",
    "> \n",
    "> $M_t = $ number of solved sites at generation $t$\n",
    ">\n",
    "> $I = M_o = $ initial number of matched sites\n",
    "> $ = \\frac{H}{2} +  \\sqrt{\\frac{H}{k}\\ln m  }  $\n",
    ">\n",
    "> $T= $ number of touched sites $ =  \\mu H +  \\sqrt{H \\mu (1 - \\mu) } \\sqrt{c \\ln (m)} $ \n",
    ">\n",
    ">  $ s = $ number of solved sites among touched $ =  \\frac{T}{2} +  \\sqrt{\\frac{T}{k}\\ln m  }  $\n",
    "> \n",
    "> $H-T = $  number of untouched sites \n",
    ">\n",
    ">\n",
    "> $p_t = \\frac{M_t}{H}$ proportion of matched sites in the winner chromosome of present generation.\n",
    ">\n",
    ">  $ r = $ number of untouched sites that were right in the winning chromosome of generation $t$.\n",
    ">\n",
    "> $ r =  (H-T)p_t$.\n",
    ">\n",
    "> $M_{t+1} =  s + r = $ prediction for the winner of the next generation\n",
    "\n",
    "********\n",
    "\n",
    "Let us observe that $\\mu$, $c$, $k$, $H$, $m$,  $T$, $s$ are all constants:\n",
    ">\n",
    "> $\\mu = $ mutation rate\n",
    ">\n",
    "> $c = 1.29$\n",
    ">\n",
    "> $k = 1.5$\n",
    ">\n",
    "> $H$ is the length of the target string \n",
    "> \n",
    "> $m$ is the number of monkeys or of binomial distributions $Bi(H, \\mu)$\n",
    "> \n",
    ">  $ T= $ number of touched sites $ =  \\mu H +  \\sqrt{H \\mu (1 - \\mu) } \\sqrt{c \\ln (m)} $\n",
    ">\n",
    "> $ s = $ number of solved sites among touched $ =  \\frac{T}{2} +  \\sqrt{\\frac{T}{k}\\ln m  }  $\n",
    "> \n",
    "\n",
    "- Step 2. Extract a recurrence relation.\n",
    "  \n",
    "Taking into account that $s$ is a constant and that \n",
    ">\n",
    ">$p_t = \\frac{M_t}{H} = $ proportion of matched sites in the winner chromosome of present generation.\n",
    ">\n",
    ">$ r = $ number of untouched sites that were right in the winning chromosome of generation $t$.\n",
    ">\n",
    "> $ r = (H-T)p_t = (H-T)\\frac{M_t}{H}$\n",
    "> \n",
    "> $M_t = $ number of matched sites at generation $t$\n",
    ">\n",
    "> $M_{t+1} =  s + r  $\n",
    "\n",
    "we have a recurrence relation that is defined by\n",
    ">\n",
    "> $I = M_o = $ initial number of matched sites\n",
    ">\n",
    "> $M_{t+1} =  s +   (H-T)\\frac{M_t}{H} = s + \\frac{H-T}{H} M_t =   \\frac{H-T}{H} M_t + s$\n",
    "\n",
    "\n",
    "- Step 3. Formulate the recurrence relation in abstract terms:\n",
    ">\n",
    "> $M_o= I$, initial condition\n",
    ">\n",
    "> $M_{t+1} = a M_t + b$,  recurrence relation\n",
    ">\n",
    "> with\n",
    ">\n",
    "> $a = \\frac{H-T}{H} $\n",
    ">\n",
    "> $b = s$\n",
    "> \n",
    "\n",
    "- Step 4. Solve the abstract recurrence relation, i.e., find the formula for the general term as a function of the initial condition, and the parameters, and constants of the model. \n",
    "  \n",
    "We must solve the abstract equation\n",
    ">\n",
    "> $ M_{t+1} =  a M_t   + b$\n",
    "> \n",
    "> given that\n",
    ">\n",
    "> $M_o = I$.\n",
    ">\n",
    "> and $a$ and $b$ are constants. Our model is deterministic because we replaced the random variable MAX by its expected value.\n",
    "\n",
    "Let us iterate some terms to infere a general term: \n",
    " \n",
    "Let $M_o = (0) = I$. We have\n",
    "\n",
    "$ M_{1} =  a M_0   + b$\n",
    "\n",
    " $ M_{1} =  a I   + b$\n",
    "\n",
    " $ M_{2} =  a M_1   + b$\n",
    "\n",
    " $ M_{2} =  a (a I   + b)   + b = a^2I + ab + b$\n",
    "\n",
    " $ M_{3} =  a M_2   + b$\n",
    "\n",
    " $ M_{3} =  a (a^2I + ab + b)   + b $\n",
    "\n",
    " > $ = a^3I + a^2b + ab + b$\n",
    "\n",
    "$ M_{4} =  a M_3   + b$\n",
    ">\n",
    "> $  =  a ( a^3I + a^2b + ab + b)   + b$\n",
    ">\n",
    "> $   =  a^4I + a^3b + a^2 b + ab   + b$\n",
    ">\n",
    "> $    =  a^4I + (a^3 + a^2  + a   + 1) b$\n",
    ">\n",
    "> Our postulate for the general term is\n",
    ">\n",
    "> $M(n) = a^nI + (a^{n-1} + \\dots + a + 1) b$\n",
    "\n",
    "\n",
    "\n",
    "In our case, $a = \\frac{H-T}{H} $, so $a < 1$. We also have\n",
    "\n",
    " $a^{n-1} + \\dots + a + 1 = \\frac{1- a^n}{1-a}$\n",
    "\n",
    " This implies that the general term is\n",
    "\n",
    " $M(n) = a^nI + \\frac{1- a^n}{1-a} b$\n",
    "\n",
    "- Step 5. Prove the general formula by induction.  \n",
    "\n",
    "We use a proof by induction to argue that a formula is correct for every generation, from 0 to $\\infty$. The idea is: if the formula is correct for the first term, and if one can deduce that is also valid for the $k+1$-term assuming that it is valid for the $k$-term, then, the formula is valid for every term. Chaining everything, we get: the formula is valid for the initial condition, $k = 0$. Hence, it is valid for 1. Hence, it is valid for 2. Therefore, it is valid for 3. And so on. It is valid for every $k$ from 0 to $\\infty$. Let us proceed. \n",
    "\n",
    "Let us see that the formula reproduces the initial and second term:\n",
    "\n",
    "Replacing $n$ in the general formula by 0, we must get the initial condition. Is that true? Let us see:\n",
    ">\n",
    "> $M(n) = a^nI + \\frac{1- a^n}{1-a} b$\n",
    ">\n",
    ">> $  M_o = M(0) = a^0I + \\frac{1- a^0}{1-a} b$\n",
    ">\n",
    ">> $  =  I + \\frac{1- 1}{1-a} b$\n",
    ">\n",
    ">> $ = I$\n",
    "\n",
    "Replacing $n$ in the general formula by 2, we get\n",
    ">\n",
    "> $M(n) = a^nI + \\frac{1- a^n}{1-a} b$\n",
    ">\n",
    ">> $  M_2 = M(2) = a^2I + \\frac{1- a^2}{1-a} b$\n",
    ">\n",
    ">> $  = a^2I + \\frac{(1-a)(1+a))}{1-a} b$\n",
    ">\n",
    ">> $  = a^2I + (1+a)  b$\n",
    ">>\n",
    ">> $  = a^2I + ab + b$\n",
    ">>\n",
    ">> that is exactly the second term.\n",
    "\n",
    "We have verified that the formula reproduces the first and second term. Let us assume now that the formula is valid for $k$. From that, we must deduce the expression of the formula for $k+1$. Our assumption is:\n",
    ">\n",
    "> $M(k) = a^kI + \\frac{1- a^k}{1-a} b$\n",
    ">\n",
    "We must arrive at\n",
    ">\n",
    "> $M(k+1) = a^{k+1}I + \\frac{1- a^{k+1}}{1-a} b$\n",
    ">\n",
    "Let us proceed. Plugging the assumption\n",
    ">\n",
    "> $M(k) = a^kI + \\frac{1- a^k}{1-a} b$\n",
    ">\n",
    "> into the recurrence relation\n",
    ">\n",
    ">$ M_{t+1} =  a M_t   + b$\n",
    ">\n",
    "> we get\n",
    ">\n",
    "> $ M_{k+1} =  a M_k   + b$\n",
    ">\n",
    "> $ M_{k+1} =  a ( a^kI + \\frac{1- a^k}{1-a} b)   + b$\n",
    ">>\n",
    ">> $ = a^{k+1} I + a\\frac{1- a^k}{1-a} b   + b$\n",
    ">>\n",
    ">> $ = a^{k+1} I + (a\\frac{1- a^k}{1-a} + 1) b $\n",
    ">>\n",
    ">> $ = a^{k+1} I + (\\frac{a(1- a^k)}{1-a} + 1) b $\n",
    ">>\n",
    ">> $ = a^{k+1} I + (\\frac{a(1- a^k) + (1-a)}{1-a}) b $\n",
    ">>\n",
    ">> $ = a^{k+1} I + (\\frac{a- a^{k+1} + 1-a}{1-a}) b $\n",
    ">>\n",
    ">> $ = a^{k+1} I + (\\frac{1- a^{k+1}}{1-a}) b $\n",
    ">>\n",
    ">> which is the formula for the $k+1$-term. We see that if the formula is valid for $k$, it is also valid for $k+1$. We are done.\n",
    "\n",
    "-Step 6. Replace abstract terms by concrete ones to find a solution for our specific problem.\n",
    "\n",
    "Replacing $a = \\frac{H-T}{H} $ and $b = s$ in the general formula, \n",
    ">\n",
    "> $M(n) = a^nI + \\frac{1- a^n}{1-a} b$\n",
    ">\n",
    "we get\n",
    ">\n",
    "> $M(n) = (\\frac{H-T}{H} )^nI + \\frac{1- (\\frac{H-T}{H} )^n}{1-(\\frac{H-T}{H} )} s$\n",
    ">\n",
    "> with\n",
    ">\n",
    ">  $ s = $ number of solved sites among touched $ =  \\frac{T}{2} +  \\sqrt{\\frac{T}{k}\\ln m  }  $\n",
    ">\n",
    "For the purpose of programming, we prefer the system of equations:\n",
    ">\n",
    "> $\\mu = $ mutation rate\n",
    ">\n",
    "> $c = 1.29$\n",
    ">\n",
    "> $k = 1.5$\n",
    ">\n",
    "> $H$ is the length of the target string \n",
    "> \n",
    "> $m$ is the number of monkeys or of binomial distributions $Bi(H, \\mu)$\n",
    "> \n",
    ">  $ T= $ number of touched sites $ =  \\mu H +  \\sqrt{H \\mu (1 - \\mu) } \\sqrt{c \\ln (m)} $\n",
    ">\n",
    "> $ s = $ number of solved sites among touched $ =  \\frac{T}{2} +  \\sqrt{\\frac{T}{k}\\ln m  }  $\n",
    "> \n",
    "> $a = \\frac{H-T}{H} $\n",
    ">  \n",
    ">$b = s$ \n",
    ">\n",
    "> $M(n) = a^nI + \\frac{1- a^n}{1-a} b$\n",
    "\n",
    "-Step 7. Compare graphically the solution given by the last formula with that produced by the original recursion. The two graphs must be undistinguishable. \n",
    "\n",
    "The following code presents two graphs. The first is drawn by the recursion system of the difference equation, and the second by its solution formula. Do they overlap one another?\n",
    "\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "id": "aaaf2feb",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Parameters of the theoretical model\n",
      "c = 1.29\n",
      "k(H) = 1.5\n",
      "I = 822.7895416014419\n",
      "mu = 0.01\n",
      "H = 1500\n",
      "m = 200\n",
      "Generation 0: T = 25.074582702637237\n",
      "Generation 0: s = 21.94838753232849\n",
      "Generation 0: u = 1474.9254172973629\n",
      "Generation 0: p = 0.548526361067628\n",
      "Generation 0: M(n) = 830.9838595286036\n",
      "Generation 1: p = 0.5539892396857358\n",
      "Generation 1: M(n) = 839.0411980540612\n",
      "Generation 2: p = 0.5593607987027075\n",
      "Generation 2: M(n) = 846.9638469787055\n",
      "Generation 3: p = 0.5646425646524703\n",
      "Generation 3: M(n) = 854.7540578262265\n",
      "Generation 4: p = 0.5698360385508177\n",
      "Generation 4: M(n) = 862.4140444829694\n",
      "Generation 5: p = 0.5749426963219796\n",
      "Generation 5: M(n) = 869.9459838270952\n",
      "Generation 6: p = 0.5799639892180635\n",
      "Generation 6: M(n) = 877.3520163472241\n",
      "Generation 7: p = 0.5849013442314828\n",
      "Generation 7: M(n) = 884.6342467507367\n",
      "Generation 8: p = 0.5897561645004911\n",
      "Generation 8: M(n) = 891.7947445619075\n",
      "Generation 9: p = 0.5945298297079383\n",
      "Generation 9: M(n) = 898.8355447100396\n",
      "Generation 10: p = 0.5992236964733597\n",
      "Generation 10: M(n) = 905.7586481077669\n",
      "Generation 11: p = 0.6038390987385113\n",
      "Generation 11: M(n) = 912.5660222196908\n",
      "Generation 12: p = 0.6083773481464605\n",
      "Generation 12: M(n) = 919.2596016215098\n",
      "Generation 13: p = 0.6128397344143398\n",
      "Generation 13: M(n) = 925.8412885498037\n",
      "Generation 14: p = 0.6172275256998692\n",
      "Generation 14: M(n) = 932.3129534426268\n",
      "Generation 15: p = 0.6215419689617512\n",
      "Generation 15: M(n) = 938.6764354710639\n",
      "Generation 16: p = 0.6257842903140426\n",
      "Generation 16: M(n) = 944.9335430619019\n",
      "Generation 17: p = 0.6299556953746013\n",
      "Generation 17: M(n) = 951.0860544115627\n",
      "Generation 18: p = 0.6340573696077084\n",
      "Generation 18: M(n) = 957.1357179914461\n",
      "Generation 19: p = 0.638090478660964\n",
      "Generation 19: M(n) = 963.0842530448249\n",
      "Generation 20: p = 0.6420561686965499\n",
      "Generation 20: M(n) = 968.9333500754334\n",
      "Generation 21: p = 0.6459555667169556\n",
      "Generation 21: M(n) = 974.6846713278889\n",
      "Generation 22: p = 0.6497897808852592\n",
      "Generation 22: M(n) = 980.3398512600814\n",
      "Generation 23: p = 0.6535599008400543\n",
      "Generation 23: M(n) = 985.9004970076687\n",
      "Generation 24: p = 0.6572669980051125\n",
      "Generation 24: M(n) = 991.368188840804\n",
      "Generation 25: p = 0.6609121258938694\n",
      "Generation 25: M(n) = 996.7444806132311\n",
      "Generation 26: p = 0.6644963204088207\n",
      "Generation 26: M(n) = 1002.0309002038705\n",
      "Generation 27: p = 0.6680206001359137\n",
      "Generation 27: M(n) = 1007.2289499510258\n",
      "Generation 28: p = 0.6714859666340172\n",
      "Generation 28: M(n) = 1012.3401070793294\n",
      "Generation 29: p = 0.674893404719553\n",
      "Generation 29: M(n) = 1017.3658241195532\n",
      "Generation 30: p = 0.6782438827463688\n",
      "Generation 30: M(n) = 1022.3075293214002\n",
      "Generation 31: p = 0.6815383528809335\n",
      "Generation 31: M(n) = 1027.1666270593967\n",
      "Generation 32: p = 0.6847777513729311\n",
      "Generation 32: M(n) = 1031.9444982319985\n",
      "Generation 33: p = 0.6879629988213324\n",
      "Generation 33: M(n) = 1036.6425006540273\n",
      "Generation 34: p = 0.6910950004360182\n",
      "Generation 34: M(n) = 1041.261969442544\n",
      "Generation 35: p = 0.6941746462950292\n",
      "Generation 35: M(n) = 1045.8042173962738\n",
      "Generation 36: p = 0.6972028115975158\n",
      "Generation 36: M(n) = 1050.2705353686893\n",
      "Generation 37: p = 0.7001803569124595\n",
      "Generation 37: M(n) = 1054.6621926348544\n",
      "Generation 38: p = 0.7031081284232362\n",
      "Generation 38: M(n) = 1058.980437252138\n",
      "Generation 39: p = 0.705986958168092\n",
      "Generation 39: M(n) = 1063.2264964148974\n",
      "Generation 40: p = 0.7088176642765982\n",
      "Generation 40: M(n) = 1067.4015768032323\n",
      "Generation 41: p = 0.7116010512021549\n",
      "Generation 41: M(n) = 1071.506864925909\n",
      "Generation 42: p = 0.714337909950606\n",
      "Generation 42: M(n) = 1075.543527457552\n",
      "Generation 43: p = 0.7170290183050347\n",
      "Generation 43: M(n) = 1079.5127115702003\n",
      "Generation 44: p = 0.7196751410468002\n",
      "Generation 44: M(n) = 1083.4155452593188\n",
      "Generation 45: p = 0.7222770301728793\n",
      "Generation 45: M(n) = 1087.2531376643624\n",
      "Generation 46: p = 0.7248354251095749\n",
      "Generation 46: M(n) = 1091.0265793839797\n",
      "Generation 47: p = 0.7273510529226531\n",
      "Generation 47: M(n) = 1094.736942785949\n",
      "Generation 48: p = 0.729824628523966\n",
      "Generation 48: M(n) = 1098.3852823119319\n",
      "Generation 49: p = 0.7322568548746212\n",
      "Generation 49: M(n) = 1101.9726347771336\n",
      "Generation 50: p = 0.7346484231847558\n",
      "Generation 50: M(n) = 1105.500019664954\n",
      "Generation 51: p = 0.7370000131099693\n",
      "Generation 51: M(n) = 1108.9684394167118\n",
      "Generation 52: p = 0.7393122929444745\n",
      "Generation 52: M(n) = 1112.3788797165278\n",
      "Generation 53: p = 0.7415859198110185\n",
      "Generation 53: M(n) = 1115.7323097714436\n",
      "Generation 54: p = 0.7438215398476291\n",
      "Generation 54: M(n) = 1119.02968258686\n",
      "Generation 55: p = 0.74601978839124\n",
      "Generation 55: M(n) = 1122.2719352373683\n",
      "Generation 56: p = 0.7481812901582455\n",
      "Generation 56: M(n) = 1125.4599891330581\n",
      "Generation 57: p = 0.7503066594220388\n",
      "Generation 57: M(n) = 1128.5947502813694\n",
      "Generation 58: p = 0.7523965001875796\n",
      "Generation 58: M(n) = 1131.6771095445697\n",
      "Generation 59: p = 0.7544514063630464\n",
      "Generation 59: M(n) = 1134.7079428929271\n",
      "Generation 60: p = 0.7564719619286181\n",
      "Generation 60: M(n) = 1137.6881116536504\n",
      "Generation 61: p = 0.7584587411024336\n",
      "Generation 61: M(n) = 1140.618462755668\n",
      "Generation 62: p = 0.7604123085037786\n",
      "Generation 62: M(n) = 1143.4998289703153\n",
      "Generation 63: p = 0.7623332193135436\n",
      "Generation 63: M(n) = 1146.3330291479988\n",
      "Generation 64: p = 0.7642220194319992\n",
      "Generation 64: M(n) = 1149.1188684509032\n",
      "Generation 65: p = 0.7660792456339355\n",
      "Generation 65: M(n) = 1151.8581385818097\n",
      "Generation 66: p = 0.7679054257212065\n",
      "Generation 66: M(n) = 1154.551618009088\n",
      "Generation 67: p = 0.7697010786727254\n",
      "Generation 67: M(n) = 1157.2000721879283\n",
      "Generation 68: p = 0.7714667147919522\n",
      "Generation 68: M(n) = 1159.8042537778742\n",
      "Generation 69: p = 0.7732028358519162\n",
      "Generation 69: M(n) = 1162.3649028567204\n",
      "Generation 70: p = 0.7749099352378136\n",
      "Generation 70: M(n) = 1164.8827471308332\n",
      "Generation 71: p = 0.7765884980872221\n",
      "Generation 71: M(n) = 1167.358502141957\n",
      "Generation 72: p = 0.7782390014279713\n",
      "Generation 72: M(n) = 1169.792871470562\n",
      "Generation 73: p = 0.779861914313708\n",
      "Generation 73: M(n) = 1172.1865469357945\n",
      "Generation 74: p = 0.7814576979571963\n",
      "Generation 74: M(n) = 1174.540208792083\n",
      "Generation 75: p = 0.7830268058613886\n",
      "Generation 75: M(n) = 1176.8545259224584\n",
      "Generation 76: p = 0.7845696839483056\n",
      "Generation 76: M(n) = 1179.1301560286433\n",
      "Generation 77: p = 0.7860867706857623\n",
      "Generation 77: M(n) = 1181.3677458179627\n",
      "Generation 78: p = 0.7875784972119751\n",
      "Generation 78: M(n) = 1183.5679311871309\n",
      "Generation 79: p = 0.7890452874580872\n",
      "Generation 79: M(n) = 1185.7313374029654\n",
      "Generation 80: p = 0.7904875582686436\n",
      "Generation 80: M(n) = 1187.8585792800811\n",
      "Generation 81: p = 0.7919057195200541\n",
      "Generation 81: M(n) = 1189.9502613556126\n",
      "Generation 82: p = 0.7933001742370751\n",
      "Generation 82: M(n) = 1192.0069780610172\n",
      "Generation 83: p = 0.7946713187073448\n",
      "Generation 83: M(n) = 1194.0293138910047\n",
      "Generation 84: p = 0.7960195425940031\n",
      "Generation 84: M(n) = 1196.0178435696444\n",
      "Generation 85: p = 0.7973452290464296\n",
      "Generation 85: M(n) = 1197.973132213695\n",
      "Generation 86: p = 0.79864875480913\n",
      "Generation 86: M(n) = 1199.8957354932038\n",
      "Generation 87: p = 0.7999304903288025\n",
      "Generation 87: M(n) = 1201.7861997894215\n",
      "Generation 88: p = 0.8011907998596144\n",
      "Generation 88: M(n) = 1203.6450623500782\n",
      "Generation 89: p = 0.8024300415667188\n",
      "Generation 89: M(n) = 1205.4728514420615\n",
      "Generation 90: p = 0.803648567628041\n",
      "Generation 90: M(n) = 1207.270086501545\n",
      "Generation 91: p = 0.8048467243343633\n",
      "Generation 91: M(n) = 1209.0372782816048\n",
      "Generation 92: p = 0.8060248521877366\n",
      "Generation 92: M(n) = 1210.774928997371\n",
      "Generation 93: p = 0.8071832859982474\n",
      "Generation 93: M(n) = 1212.4835324687501\n",
      "Generation 94: p = 0.8083223549791667\n",
      "Generation 94: M(n) = 1214.163574260763\n",
      "Generation 95: p = 0.8094423828405086\n",
      "Generation 95: M(n) = 1215.8155318215374\n",
      "Generation 96: p = 0.8105436878810249\n",
      "Generation 96: M(n) = 1217.4398746179927\n",
      "Generation 97: p = 0.8116265830786618\n",
      "Generation 97: M(n) = 1219.0370642692565\n",
      "Generation 98: p = 0.8126913761795043\n",
      "Generation 98: M(n) = 1220.607554677852\n",
      "Generation 99: p = 0.8137383697852347\n",
      "Generation 99: M(n) = 1222.1517921586917\n",
      "Generation 100: p = 0.8147678614391278\n",
      "Generation 100: M(n) = 1223.670215565914\n",
      "Generation 101: p = 0.8157801437106094\n",
      "Generation 101: M(n) = 1225.1632564176016\n",
      "Generation 102: p = 0.8167755042784011\n",
      "Generation 102: M(n) = 1226.6313390184132\n",
      "Generation 103: p = 0.8177542260122754\n",
      "Generation 103: M(n) = 1228.0748805801659\n",
      "Generation 104: p = 0.818716587053444\n",
      "Generation 104: M(n) = 1229.494291340402\n",
      "Generation 105: p = 0.8196628608936013\n",
      "Generation 105: M(n) = 1230.8899746789737\n",
      "Generation 106: p = 0.8205933164526491\n",
      "Generation 106: M(n) = 1232.262327232679\n",
      "Generation 107: p = 0.8215082181551193\n",
      "Generation 107: M(n) = 1233.611739007981\n",
      "Generation 108: p = 0.8224078260053207\n",
      "Generation 108: M(n) = 1234.9385934918432\n",
      "Generation 109: p = 0.8232923956612288\n",
      "Generation 109: M(n) = 1236.243267760712\n",
      "Generation 110: p = 0.8241621785071412\n",
      "Generation 110: M(n) = 1237.5261325876775\n",
      "Generation 111: p = 0.8250174217251183\n",
      "Generation 111: M(n) = 1238.787552547843\n",
      "Generation 112: p = 0.8258583683652286\n",
      "Generation 112: M(n) = 1240.0278861219326\n",
      "Generation 113: p = 0.8266852574146217\n",
      "Generation 113: M(n) = 1241.2474857981674\n",
      "Generation 114: p = 0.827498323865445\n",
      "Generation 114: M(n) = 1242.4466981724383\n",
      "Generation 115: p = 0.8282977987816256\n",
      "Generation 115: M(n) = 1243.6258640468047\n",
      "Generation 116: p = 0.8290839093645365\n",
      "Generation 116: M(n) = 1244.7853185263464\n",
      "Generation 117: p = 0.8298568790175642\n",
      "Generation 117: M(n) = 1245.9253911143967\n",
      "Generation 118: p = 0.8306169274095978\n",
      "Generation 118: M(n) = 1247.046405806183\n",
      "Generation 119: p = 0.8313642705374553\n",
      "Generation 119: M(n) = 1248.1486811809025\n",
      "Generation 120: p = 0.8320991207872683\n",
      "Generation 120: M(n) = 1249.232530492259\n",
      "Generation 121: p = 0.8328216869948394\n",
      "Generation 121: M(n) = 1250.2982617574858\n",
      "Generation 122: p = 0.8335321745049905\n",
      "Generation 122: M(n) = 1251.34617784488\n",
      "Generation 123: p = 0.83423078522992\n",
      "Generation 123: M(n) = 1252.376576559875\n",
      "Generation 124: p = 0.8349177177065834\n",
      "Generation 124: M(n) = 1253.3897507296729\n",
      "Generation 125: p = 0.8355931671531153\n",
      "Generation 125: M(n) = 1254.3859882864622\n",
      "Generation 126: p = 0.8362573255243081\n",
      "Generation 126: M(n) = 1255.3655723492452\n",
      "Generation 127: p = 0.8369103815661635\n",
      "Generation 127: M(n) = 1256.3287813042973\n",
      "Generation 128: p = 0.8375525208695316\n",
      "Generation 128: M(n) = 1257.2758888842807\n",
      "Generation 129: p = 0.8381839259228537\n",
      "Generation 129: M(n) = 1258.2071642460355\n",
      "Generation 130: p = 0.8388047761640237\n",
      "Generation 130: M(n) = 1259.1228720470722\n",
      "Generation 131: p = 0.8394152480313815\n",
      "Generation 131: M(n) = 1260.0232725207832\n",
      "Generation 132: p = 0.8400155150138554\n",
      "Generation 132: M(n) = 1260.9086215503985\n",
      "Generation 133: p = 0.8406057477002656\n",
      "Generation 133: M(n) = 1261.7791707417045\n",
      "Generation 134: p = 0.8411861138278031\n",
      "Generation 134: M(n) = 1262.6351674945479\n",
      "Generation 135: p = 0.8417567783296986\n",
      "Generation 135: M(n) = 1263.476855073143\n",
      "Generation 136: p = 0.8423179033820953\n",
      "Generation 136: M(n) = 1264.3044726752053\n",
      "Generation 137: p = 0.8428696484501368\n",
      "Generation 137: M(n) = 1265.118255499928\n",
      "Generation 138: p = 0.8434121703332853\n",
      "Generation 138: M(n) = 1265.9184348148237\n",
      "Generation 139: p = 0.8439456232098825\n",
      "Generation 139: M(n) = 1266.7052380214475\n",
      "Generation 140: p = 0.844470158680965\n",
      "Generation 140: M(n) = 1267.4788887200211\n",
      "Generation 141: p = 0.8449859258133474\n",
      "Generation 141: M(n) = 1268.2396067729785\n",
      "Generation 142: p = 0.8454930711819857\n",
      "Generation 142: M(n) = 1268.9876083674476\n",
      "Generation 143: p = 0.8459917389116317\n",
      "Generation 143: M(n) = 1269.7231060766885\n",
      "Generation 144: p = 0.8464820707177924\n",
      "Generation 144: M(n) = 1270.4463089205042\n",
      "Generation 145: p = 0.8469642059470028\n",
      "Generation 145: M(n) = 1271.1574224246413\n",
      "Generation 146: p = 0.8474382816164275\n",
      "Generation 146: M(n) = 1271.856648679198\n",
      "Generation 147: p = 0.8479044324527987\n",
      "Generation 147: M(n) = 1272.5441863960561\n",
      "Generation 148: p = 0.8483627909307041\n",
      "Generation 148: M(n) = 1273.2202309653526\n",
      "Generation 149: p = 0.8488134873102351\n",
      "Generation 149: M(n) = 1273.884974511007\n",
      "Generation 150: p = 0.8492566496740046\n",
      "Generation 150: M(n) = 1274.5386059453201\n",
      "Generation 151: p = 0.8496924039635467\n",
      "Generation 151: M(n) = 1275.1813110226622\n",
      "Generation 152: p = 0.850120874015108\n",
      "Generation 152: M(n) = 1275.8132723922606\n",
      "Generation 153: p = 0.8505421815948404\n",
      "Generation 153: M(n) = 1276.434669650108\n",
      "Generation 154: p = 0.8509564464334053\n",
      "Generation 154: M(n) = 1277.0456793899998\n",
      "Generation 155: p = 0.8513637862599999\n",
      "Generation 155: M(n) = 1277.6464752537217\n",
      "Generation 156: p = 0.8517643168358146\n",
      "Generation 156: M(n) = 1278.2372279803956\n",
      "Generation 157: p = 0.8521581519869303\n",
      "Generation 157: M(n) = 1278.8181054550014\n",
      "Generation 158: p = 0.8525454036366676\n",
      "Generation 158: M(n) = 1279.3892727560892\n",
      "Generation 159: p = 0.8529261818373928\n",
      "Generation 159: M(n) = 1279.9508922026914\n",
      "Generation 160: p = 0.8533005948017943\n",
      "Generation 160: M(n) = 1280.503123400453\n",
      "Generation 161: p = 0.8536687489336353\n",
      "Generation 161: M(n) = 1281.0461232869882\n",
      "Generation 162: p = 0.8540307488579921\n",
      "Generation 162: M(n) = 1281.5800461764818\n",
      "Generation 163: p = 0.8543866974509878\n",
      "Generation 163: M(n) = 1282.1050438035425\n",
      "Generation 164: p = 0.8547366958690283\n",
      "Generation 164: M(n) = 1282.6212653663242\n",
      "Generation 165: p = 0.8550808435775494\n",
      "Generation 165: M(n) = 1283.1288575689266\n",
      "Generation 166: p = 0.8554192383792844\n",
      "Generation 166: M(n) = 1283.627964663087\n",
      "Generation 167: p = 0.8557519764420579\n",
      "Generation 167: M(n) = 1284.118728489174\n",
      "Generation 168: p = 0.856079152326116\n",
      "Generation 168: M(n) = 1284.6012885164978\n",
      "Generation 169: p = 0.8564008590109985\n",
      "Generation 169: M(n) = 1285.0757818829454\n",
      "Generation 170: p = 0.8567171879219636\n",
      "Generation 170: M(n) = 1285.5423434339539\n",
      "Generation 171: p = 0.8570282289559692\n",
      "Generation 171: M(n) = 1286.0011057608313\n",
      "Generation 172: p = 0.8573340705072209\n",
      "Generation 172: M(n) = 1286.452199238438\n",
      "Generation 173: p = 0.8576347994922919\n",
      "Generation 173: M(n) = 1286.8957520622373\n",
      "Generation 174: p = 0.8579305013748248\n",
      "Generation 174: M(n) = 1287.3318902847277\n",
      "Generation 175: p = 0.8582212601898185\n",
      "Generation 175: M(n) = 1287.7607378512653\n",
      "Generation 176: p = 0.8585071585675101\n",
      "Generation 176: M(n) = 1288.1824166352867\n",
      "Generation 177: p = 0.8587882777568578\n",
      "Generation 177: M(n) = 1288.5970464729457\n",
      "Generation 178: p = 0.8590646976486305\n",
      "Generation 178: M(n) = 1289.0047451971677\n",
      "Generation 179: p = 0.8593364967981119\n",
      "Generation 179: M(n) = 1289.4056286711375\n",
      "Generation 180: p = 0.859603752447425\n",
      "Generation 180: M(n) = 1289.799810821226\n",
      "Generation 181: p = 0.859866540547484\n",
      "Generation 181: M(n) = 1290.1874036693662\n",
      "Generation 182: p = 0.8601249357795775\n",
      "Generation 182: M(n) = 1290.5685173648892\n",
      "Generation 183: p = 0.8603790115765928\n",
      "Generation 183: M(n) = 1290.9432602158272\n",
      "Generation 184: p = 0.8606288401438847\n",
      "Generation 184: M(n) = 1291.311738719693\n",
      "Generation 185: p = 0.8608744924797953\n",
      "Generation 185: M(n) = 1291.674057593746\n",
      "Generation 186: p = 0.8611160383958307\n",
      "Generation 186: M(n) = 1292.0303198047511\n",
      "Generation 187: p = 0.8613535465365008\n",
      "Generation 187: M(n) = 1292.3806265982403\n",
      "Generation 188: p = 0.8615870843988268\n",
      "Generation 188: M(n) = 1292.7250775272864\n",
      "Generation 189: p = 0.8618167183515243\n",
      "Generation 189: M(n) = 1293.0637704807943\n",
      "Generation 190: p = 0.8620425136538629\n",
      "Generation 190: M(n) = 1293.3968017113198\n",
      "Generation 191: p = 0.8622645344742131\n",
      "Generation 191: M(n) = 1293.7242658624236\n",
      "Generation 192: p = 0.8624828439082824\n",
      "Generation 192: M(n) = 1294.0462559955683\n",
      "Generation 193: p = 0.8626975039970456\n",
      "Generation 193: M(n) = 1294.3628636165643\n",
      "Generation 194: p = 0.8629085757443762\n",
      "Generation 194: M(n) = 1294.6741787015756\n",
      "Generation 195: p = 0.8631161191343837\n",
      "Generation 195: M(n) = 1294.9802897226898\n",
      "Generation 196: p = 0.8633201931484599\n",
      "Generation 196: M(n) = 1295.2812836730607\n",
      "Generation 197: p = 0.8635208557820404\n",
      "Generation 197: M(n) = 1295.5772460916303\n",
      "Generation 198: p = 0.8637181640610868\n",
      "Generation 198: M(n) = 1295.8682610874391\n",
      "Generation 199: p = 0.8639121740582928\n",
      "Generation 199: M(n) = 1296.154411363528\n",
      "Generation 200: p = 0.8641029409090186\n",
      "Generation 200: M(n) = 1296.4357782404413\n",
      "Generation 201: p = 0.8642905188269608\n",
      "Generation 201: M(n) = 1296.712441679338\n",
      "Generation 202: p = 0.8644749611195587\n",
      "Generation 202: M(n) = 1296.9844803047151\n",
      "Generation 203: p = 0.8646563202031434\n",
      "Generation 203: M(n) = 1297.251971426752\n",
      "Generation 204: p = 0.8648346476178347\n",
      "Generation 204: M(n) = 1297.514991063281\n",
      "Generation 205: p = 0.8650099940421874\n",
      "Generation 205: M(n) = 1297.773613961391\n",
      "Generation 206: p = 0.865182409307594\n",
      "Generation 206: M(n) = 1298.0279136186696\n",
      "Generation 207: p = 0.8653519424124464\n",
      "Generation 207: M(n) = 1298.2779623040894\n",
      "Generation 208: p = 0.8655186415360596\n",
      "Generation 208: M(n) = 1298.5238310785478\n",
      "Generation 209: p = 0.8656825540523652\n",
      "Generation 209: M(n) = 1298.7655898150601\n",
      "Generation 210: p = 0.8658437265433734\n",
      "Generation 210: M(n) = 1299.0033072186172\n",
      "Generation 211: p = 0.8660022048124115\n",
      "Generation 211: M(n) = 1299.2370508457109\n",
      "Generation 212: p = 0.8661580338971406\n",
      "Generation 212: M(n) = 1299.466887123532\n",
      "Generation 213: p = 0.8663112580823547\n",
      "Generation 213: M(n) = 1299.692881368849\n",
      "Generation 214: p = 0.8664619209125659\n",
      "Generation 214: M(n) = 1299.9150978065695\n",
      "Generation 215: p = 0.8666100652043797\n",
      "Generation 215: M(n) = 1300.133599587993\n",
      "Generation 216: p = 0.866755733058662\n",
      "Generation 216: M(n) = 1300.3484488087572\n",
      "Generation 217: p = 0.8668989658725048\n",
      "Generation 217: M(n) = 1300.5597065264851\n",
      "Generation 218: p = 0.86703980435099\n",
      "Generation 218: M(n) = 1300.7674327781363\n",
      "Generation 219: p = 0.8671782885187576\n",
      "Generation 219: M(n) = 1300.97168659707\n",
      "Generation 220: p = 0.8673144577313799\n",
      "Generation 220: M(n) = 1301.1725260298201\n",
      "Generation 221: p = 0.8674483506865468\n",
      "Generation 221: M(n) = 1301.3700081525926\n",
      "Generation 222: p = 0.8675800054350618\n",
      "Generation 222: M(n) = 1301.5641890874854\n",
      "Generation 223: p = 0.8677094593916569\n",
      "Generation 223: M(n) = 1301.7551240184373\n",
      "Generation 224: p = 0.8678367493456248\n",
      "Generation 224: M(n) = 1301.9428672069112\n",
      "Generation 225: p = 0.8679619114712741\n",
      "Generation 225: M(n) = 1302.1274720073143\n",
      "Generation 226: p = 0.8680849813382095\n",
      "Generation 226: M(n) = 1302.3089908821607\n",
      "Generation 227: p = 0.8682059939214405\n",
      "Generation 227: M(n) = 1302.4874754169807\n",
      "Generation 228: p = 0.8683249836113205\n",
      "Generation 228: M(n) = 1302.662976334981\n",
      "Generation 229: p = 0.8684419842233208\n",
      "Generation 229: M(n) = 1302.8355435114597\n",
      "Generation 230: p = 0.8685570290076398\n",
      "Generation 230: M(n) = 1303.0052259879792\n",
      "Generation 231: p = 0.8686701506586528\n",
      "Generation 231: M(n) = 1303.1720719863051\n",
      "Generation 232: p = 0.8687813813242035\n",
      "Generation 232: M(n) = 1303.3361289221086\n",
      "Generation 233: p = 0.8688907526147391\n",
      "Generation 233: M(n) = 1303.4974434184423\n",
      "Generation 234: p = 0.8689982956122949\n",
      "Generation 234: M(n) = 1303.6560613189897\n",
      "Generation 235: p = 0.8691040408793265\n",
      "Generation 235: M(n) = 1303.8120277010935\n",
      "Generation 236: p = 0.8692080184673957\n",
      "Generation 236: M(n) = 1303.965386888566\n",
      "Generation 237: p = 0.8693102579257106\n",
      "Generation 237: M(n) = 1304.1161824642854\n",
      "Generation 238: p = 0.8694107883095237\n",
      "Generation 238: M(n) = 1304.264457282582\n",
      "Generation 239: p = 0.869509638188388\n",
      "Generation 239: M(n) = 1304.4102534814158\n",
      "Generation 240: p = 0.8696068356542772\n",
      "Generation 240: M(n) = 1304.5536124943526\n",
      "Generation 241: p = 0.8697024083295684\n",
      "Generation 241: M(n) = 1304.6945750623386\n",
      "Generation 242: p = 0.8697963833748924\n",
      "Generation 242: M(n) = 1304.8331812452786\n",
      "Generation 243: p = 0.8698887874968524\n",
      "Generation 243: M(n) = 1304.9694704334206\n",
      "Generation 244: p = 0.8699796469556137\n",
      "Generation 244: M(n) = 1305.1034813585495\n",
      "Generation 245: p = 0.8700689875723664\n",
      "Generation 245: M(n) = 1305.235252104995\n",
      "Generation 246: p = 0.8701568347366633\n",
      "Generation 246: M(n) = 1305.364820120454\n",
      "Generation 247: p = 0.870243213413636\n",
      "Generation 247: M(n) = 1305.4922222266337\n",
      "Generation 248: p = 0.870328148151089\n",
      "Generation 248: M(n) = 1305.6174946297147\n",
      "Generation 249: p = 0.8704116630864764\n",
      "Generation 249: M(n) = 1305.7406729306415\n",
      "Generation 250: p = 0.870493781953761\n",
      "Generation 250: M(n) = 1305.861792135239\n",
      "Generation 251: p = 0.8705745280901593\n",
      "Generation 251: M(n) = 1305.9808866641615\n",
      "Generation 252: p = 0.8706539244427743\n",
      "Generation 252: M(n) = 1306.0979903626742\n",
      "Generation 253: p = 0.8707319935751161\n",
      "Generation 253: M(n) = 1306.2131365102714\n",
      "Generation 254: p = 0.8708087576735143\n",
      "Generation 254: M(n) = 1306.3263578301346\n",
      "Generation 255: p = 0.8708842385534231\n",
      "Generation 255: M(n) = 1306.4376864984322\n",
      "Generation 256: p = 0.8709584576656214\n",
      "Generation 256: M(n) = 1306.5471541534628\n",
      "Generation 257: p = 0.8710314361023085\n",
      "Generation 257: M(n) = 1306.654791904647\n",
      "Generation 258: p = 0.871103194603098\n",
      "Generation 258: M(n) = 1306.7606303413688\n",
      "Generation 259: p = 0.8711737535609125\n",
      "Generation 259: M(n) = 1306.8646995416675\n",
      "Generation 260: p = 0.8712431330277783\n",
      "Generation 260: M(n) = 1306.9670290807862\n",
      "Generation 261: p = 0.8713113527205242\n",
      "Generation 261: M(n) = 1307.0676480395773\n",
      "Generation 262: p = 0.8713784320263849\n",
      "Generation 262: M(n) = 1307.166585012766\n",
      "Generation 263: p = 0.8714443900085107\n",
      "Generation 263: M(n) = 1307.263868117077\n",
      "Generation 264: p = 0.8715092454113846\n",
      "Generation 264: M(n) = 1307.3595249992247\n",
      "Generation 265: p = 0.8715730166661498\n",
      "Generation 265: M(n) = 1307.453582843771\n",
      "Generation 266: p = 0.8716357218958474\n",
      "Generation 266: M(n) = 1307.5460683808494\n",
      "Generation 267: p = 0.8716973789205663\n",
      "Generation 267: M(n) = 1307.6370078937623\n",
      "Generation 268: p = 0.8717580052625082\n",
      "Generation 268: M(n) = 1307.7264272264501\n",
      "Generation 269: p = 0.8718176181509668\n",
      "Generation 269: M(n) = 1307.814351790836\n",
      "Generation 270: p = 0.8718762345272241\n",
      "Generation 270: M(n) = 1307.900806574048\n",
      "Generation 271: p = 0.8719338710493653\n",
      "Generation 271: M(n) = 1307.9858161455186\n",
      "Generation 272: p = 0.8719905440970124\n",
      "Generation 272: M(n) = 1308.069404663969\n",
      "Generation 273: p = 0.8720462697759793\n",
      "Generation 273: M(n) = 1308.1515958842735\n",
      "Generation 274: p = 0.872101063922849\n",
      "Generation 274: M(n) = 1308.2324131642108\n",
      "Generation 275: p = 0.8721549421094739\n",
      "Generation 275: M(n) = 1308.3118794711015\n",
      "Generation 276: p = 0.872207919647401\n",
      "Generation 276: M(n) = 1308.3900173883362\n",
      "Generation 277: p = 0.8722600115922241\n",
      "Generation 277: M(n) = 1308.4668491217922\n",
      "Generation 278: p = 0.8723112327478615\n",
      "Generation 278: M(n) = 1308.5423965061452\n",
      "Generation 279: p = 0.8723615976707635\n",
      "Generation 279: M(n) = 1308.6166810110735\n",
      "Generation 280: p = 0.872411120674049\n",
      "Generation 280: M(n) = 1308.6897237473602\n",
      "Generation 281: p = 0.8724598158315735\n",
      "Generation 281: M(n) = 1308.7615454728925\n",
      "Generation 282: p = 0.8725076969819283\n",
      "Generation 282: M(n) = 1308.8321665985602\n",
      "Generation 283: p = 0.8725547777323734\n",
      "Generation 283: M(n) = 1308.901607194057\n",
      "Generation 284: p = 0.8726010714627047\n",
      "Generation 284: M(n) = 1308.9698869935842\n",
      "Generation 285: p = 0.8726465913290561\n",
      "Generation 285: M(n) = 1309.0370254014579\n",
      "Generation 286: p = 0.8726913502676386\n",
      "Generation 286: M(n) = 1309.1030414976244\n",
      "Generation 287: p = 0.8727353609984163\n",
      "Generation 287: M(n) = 1309.1679540430823\n",
      "Generation 288: p = 0.8727786360287215\n",
      "Generation 288: M(n) = 1309.2317814852138\n",
      "Generation 289: p = 0.8728211876568092\n",
      "Generation 289: M(n) = 1309.2945419630275\n",
      "Generation 290: p = 0.8728630279753516\n",
      "Generation 290: M(n) = 1309.3562533123138\n",
      "Generation 291: p = 0.8729041688748759\n",
      "Generation 291: M(n) = 1309.4169330707125\n",
      "Generation 292: p = 0.8729446220471416\n",
      "Generation 292: M(n) = 1309.4765984826977\n",
      "Generation 293: p = 0.8729843989884651\n",
      "Generation 293: M(n) = 1309.535266504478\n",
      "Generation 294: p = 0.8730235110029853\n",
      "Generation 294: M(n) = 1309.5929538088153\n",
      "Generation 295: p = 0.8730619692058769\n",
      "Generation 295: M(n) = 1309.6496767897638\n",
      "Generation 296: p = 0.8730997845265092\n",
      "Generation 296: M(n) = 1309.7054515673276\n",
      "Generation 297: p = 0.8731369677115517\n",
      "Generation 297: M(n) = 1309.760293992043\n",
      "Generation 298: p = 0.8731735293280286\n",
      "Generation 298: M(n) = 1309.8142196494823\n",
      "Generation 299: p = 0.8732094797663216\n",
      "Generation 299: M(n) = 1309.8672438646836\n",
      "Generation 300: p = 0.8732448292431224\n",
      "Generation 300: M(n) = 1309.9193817065052\n",
      "Generation 301: p = 0.8732795878043368\n",
      "Generation 301: M(n) = 1309.970647991909\n",
      "Generation 302: p = 0.8733137653279393\n",
      "Generation 302: M(n) = 1310.0210572901706\n",
      "Generation 303: p = 0.8733473715267804\n",
      "Generation 303: M(n) = 1310.07062392702\n",
      "Generation 304: p = 0.8733804159513467\n",
      "Generation 304: M(n) = 1310.119361988713\n",
      "Generation 305: p = 0.8734129079924754\n",
      "Generation 305: M(n) = 1310.1672853260334\n",
      "Generation 306: p = 0.8734448568840223\n",
      "Generation 306: M(n) = 1310.2144075582305\n",
      "Generation 307: p = 0.873476271705487\n",
      "Generation 307: M(n) = 1310.2607420768886\n",
      "Generation 308: p = 0.8735071613845924\n",
      "Generation 308: M(n) = 1310.3063020497334\n",
      "Generation 309: p = 0.8735375346998223\n",
      "Generation 309: M(n) = 1310.3511004243735\n",
      "Generation 310: p = 0.8735674002829157\n",
      "Generation 310: M(n) = 1310.3951499319803\n",
      "Generation 311: p = 0.8735967666213202\n",
      "Generation 311: M(n) = 1310.4384630909062\n",
      "Generation 312: p = 0.8736256420606041\n",
      "Generation 312: M(n) = 1310.4810522102416\n",
      "Generation 313: p = 0.8736540348068278\n",
      "Generation 313: M(n) = 1310.5229293933137\n",
      "Generation 314: p = 0.8736819529288757\n",
      "Generation 314: M(n) = 1310.5641065411255\n",
      "Generation 315: p = 0.8737094043607503\n",
      "Generation 315: M(n) = 1310.6045953557384\n",
      "Generation 316: p = 0.8737363969038257\n",
      "Generation 316: M(n) = 1310.6444073435978\n",
      "Generation 317: p = 0.8737629382290651\n",
      "Generation 317: M(n) = 1310.6835538188022\n",
      "Generation 318: p = 0.8737890358792015\n",
      "Generation 318: M(n) = 1310.7220459063203\n",
      "Generation 319: p = 0.8738146972708802\n",
      "Generation 319: M(n) = 1310.7598945451502\n",
      "Generation 320: p = 0.8738399296967668\n",
      "Generation 320: M(n) = 1310.7971104914307\n",
      "Generation 321: p = 0.8738647403276204\n",
      "Generation 321: M(n) = 1310.8337043214956\n",
      "Generation 322: p = 0.8738891362143304\n",
      "Generation 322: M(n) = 1310.8696864348817\n",
      "Generation 323: p = 0.8739131242899212\n",
      "Generation 323: M(n) = 1310.9050670572826\n",
      "Generation 324: p = 0.8739367113715217\n",
      "Generation 324: M(n) = 1310.939856243455\n",
      "Generation 325: p = 0.8739599041623034\n",
      "Generation 325: M(n) = 1310.9740638800772\n",
      "Generation 326: p = 0.8739827092533848\n",
      "Generation 326: M(n) = 1311.0076996885568\n",
      "Generation 327: p = 0.8740051331257046\n",
      "Generation 327: M(n) = 1311.0407732277956\n",
      "Generation 328: p = 0.8740271821518637\n",
      "Generation 328: M(n) = 1311.0732938969043\n",
      "Generation 329: p = 0.8740488625979361\n",
      "Generation 329: M(n) = 1311.1052709378748\n",
      "Generation 330: p = 0.8740701806252499\n",
      "Generation 330: M(n) = 1311.1367134382065\n",
      "Generation 331: p = 0.8740911422921377\n",
      "Generation 331: M(n) = 1311.1676303334882\n",
      "Generation 332: p = 0.8741117535556588\n",
      "Generation 332: M(n) = 1311.1980304099382\n",
      "Generation 333: p = 0.8741320202732921\n",
      "Generation 333: M(n) = 1311.2279223069006\n",
      "Generation 334: p = 0.8741519482046004\n",
      "Generation 334: M(n) = 1311.2573145193014\n",
      "Generation 335: p = 0.8741715430128676\n",
      "Generation 335: M(n) = 1311.2862154000618\n",
      "Generation 336: p = 0.8741908102667079\n",
      "Generation 336: M(n) = 1311.3146331624723\n",
      "Generation 337: p = 0.8742097554416483\n",
      "Generation 337: M(n) = 1311.3425758825272\n",
      "Generation 338: p = 0.8742283839216848\n",
      "Generation 338: M(n) = 1311.3700515012185\n",
      "Generation 339: p = 0.8742467010008124\n",
      "Generation 339: M(n) = 1311.3970678267945\n",
      "Generation 340: p = 0.8742647118845296\n",
      "Generation 340: M(n) = 1311.423632536977\n",
      "Generation 341: p = 0.874282421691318\n",
      "Generation 341: M(n) = 1311.4497531811446\n",
      "Generation 342: p = 0.8742998354540964\n",
      "Generation 342: M(n) = 1311.4754371824774\n",
      "Generation 343: p = 0.8743169581216517\n",
      "Generation 343: M(n) = 1311.5006918400666\n",
      "Generation 344: p = 0.8743337945600443\n",
      "Generation 344: M(n) = 1311.5255243309887\n",
      "Generation 345: p = 0.8743503495539925\n",
      "Generation 345: M(n) = 1311.549941712346\n",
      "Generation 346: p = 0.8743666278082307\n",
      "Generation 346: M(n) = 1311.5739509232712\n",
      "Generation 347: p = 0.8743826339488475\n",
      "Generation 347: M(n) = 1311.5975587868998\n",
      "Generation 348: p = 0.8743983725245998\n",
      "Generation 348: M(n) = 1311.6207720123089\n",
      "Generation 349: p = 0.8744138480082059\n",
      "Generation 349: M(n) = 1311.6435971964245\n",
      "Generation 350: p = 0.8744290647976163\n",
      "Generation 350: M(n) = 1311.6660408258954\n",
      "Generation 351: p = 0.8744440272172636\n",
      "Generation 351: M(n) = 1311.6881092789374\n",
      "Generation 352: p = 0.8744587395192917\n",
      "Generation 352: M(n) = 1311.7098088271457\n",
      "Generation 353: p = 0.8744732058847638\n",
      "Generation 353: M(n) = 1311.7311456372765\n",
      "Generation 354: p = 0.874487430424851\n",
      "Generation 354: M(n) = 1311.7521257730004\n",
      "Generation 355: p = 0.8745014171820003\n",
      "Generation 355: M(n) = 1311.7727551966254\n",
      "Generation 356: p = 0.8745151701310836\n",
      "Generation 356: M(n) = 1311.7930397707912\n",
      "Generation 357: p = 0.8745286931805275\n",
      "Generation 357: M(n) = 1311.8129852601355\n",
      "Generation 358: p = 0.8745419901734237\n",
      "Generation 358: M(n) = 1311.8325973329318\n",
      "Generation 359: p = 0.8745550648886212\n",
      "Generation 359: M(n) = 1311.8518815627003\n",
      "Generation 360: p = 0.8745679210418003\n",
      "Generation 360: M(n) = 1311.8708434297928\n",
      "Generation 361: p = 0.8745805622865285\n",
      "Generation 361: M(n) = 1311.8894883229489\n",
      "Generation 362: p = 0.8745929922152993\n",
      "Generation 362: M(n) = 1311.907821540828\n",
      "Generation 363: p = 0.874605214360552\n",
      "Generation 363: M(n) = 1311.9258482935152\n",
      "Generation 364: p = 0.8746172321956768\n",
      "Generation 364: M(n) = 1311.9435737040017\n",
      "Generation 365: p = 0.8746290491360011\n",
      "Generation 365: M(n) = 1311.9610028096406\n",
      "Generation 366: p = 0.8746406685397604\n",
      "Generation 366: M(n) = 1311.978140563579\n",
      "Generation 367: p = 0.8746520937090527\n",
      "Generation 367: M(n) = 1311.9949918361651\n",
      "Generation 368: p = 0.8746633278907767\n",
      "Generation 368: M(n) = 1312.0115614163326\n",
      "Generation 369: p = 0.874674374277555\n",
      "Generation 369: M(n) = 1312.0278540129611\n",
      "Generation 370: p = 0.8746852360086408\n",
      "Generation 370: M(n) = 1312.0438742562153\n",
      "Generation 371: p = 0.8746959161708102\n",
      "Generation 371: M(n) = 1312.0596266988598\n",
      "Generation 372: p = 0.8747064177992399\n",
      "Generation 372: M(n) = 1312.0751158175538\n",
      "Generation 373: p = 0.8747167438783692\n",
      "Generation 373: M(n) = 1312.0903460141226\n",
      "Generation 374: p = 0.8747268973427484\n",
      "Generation 374: M(n) = 1312.1053216168093\n",
      "Generation 375: p = 0.8747368810778728\n",
      "Generation 375: M(n) = 1312.1200468815039\n",
      "Generation 376: p = 0.8747466979210026\n",
      "Generation 376: M(n) = 1312.1345259929535\n",
      "Generation 377: p = 0.874756350661969\n",
      "Generation 377: M(n) = 1312.1487630659515\n",
      "Generation 378: p = 0.8747658420439677\n",
      "Generation 378: M(n) = 1312.1627621465066\n",
      "Generation 379: p = 0.8747751747643377\n",
      "Generation 379: M(n) = 1312.1765272129928\n",
      "Generation 380: p = 0.8747843514753285\n",
      "Generation 380: M(n) = 1312.1900621772804\n",
      "Generation 381: p = 0.8747933747848536\n",
      "Generation 381: M(n) = 1312.203370885847\n",
      "Generation 382: p = 0.8748022472572314\n",
      "Generation 382: M(n) = 1312.2164571208714\n",
      "Generation 383: p = 0.8748109714139143\n",
      "Generation 383: M(n) = 1312.2293246013073\n",
      "Generation 384: p = 0.8748195497342048\n",
      "Generation 384: M(n) = 1312.2419769839416\n",
      "Generation 385: p = 0.8748279846559611\n",
      "Generation 385: M(n) = 1312.254417864433\n",
      "Generation 386: p = 0.8748362785762887\n",
      "Generation 386: M(n) = 1312.266650778333\n",
      "Generation 387: p = 0.8748444338522221\n",
      "Generation 387: M(n) = 1312.2786792020925\n",
      "Generation 388: p = 0.874852452801395\n",
      "Generation 388: M(n) = 1312.2905065540474\n",
      "Generation 389: p = 0.8748603377026982\n",
      "Generation 389: M(n) = 1312.3021361953924\n",
      "Generation 390: p = 0.8748680907969283\n",
      "Generation 390: M(n) = 1312.3135714311352\n",
      "Generation 391: p = 0.8748757142874235\n",
      "Generation 391: M(n) = 1312.324815511035\n",
      "Generation 392: p = 0.87488321034069\n",
      "Generation 392: M(n) = 1312.3358716305272\n",
      "Generation 393: p = 0.8748905810870181\n",
      "Generation 393: M(n) = 1312.346742931631\n",
      "Generation 394: p = 0.8748978286210873\n",
      "Generation 394: M(n) = 1312.3574325038423\n",
      "Generation 395: p = 0.8749049550025616\n",
      "Generation 395: M(n) = 1312.3679433850123\n",
      "Generation 396: p = 0.8749119622566749\n",
      "Generation 396: M(n) = 1312.3782785622093\n",
      "Generation 397: p = 0.8749188523748062\n",
      "Generation 397: M(n) = 1312.3884409725692\n",
      "Generation 398: p = 0.8749256273150462\n",
      "Generation 398: M(n) = 1312.39843350413\n",
      "Generation 399: p = 0.8749322890027533\n",
      "Generation 399: M(n) = 1312.4082589966513\n",
      "Generation 400: p = 0.8749388393311008\n",
      "Generation 400: M(n) = 1312.4179202424227\n",
      "Generation 401: p = 0.8749452801616151\n",
      "Generation 401: M(n) = 1312.4274199870567\n",
      "Generation 402: p = 0.8749516133247045\n",
      "Generation 402: M(n) = 1312.4367609302692\n",
      "Generation 403: p = 0.8749578406201795\n",
      "Generation 403: M(n) = 1312.4459457266462\n",
      "Generation 404: p = 0.8749639638177641\n",
      "Generation 404: M(n) = 1312.4549769863988\n",
      "Generation 405: p = 0.8749699846575992\n",
      "Generation 405: M(n) = 1312.4638572761053\n",
      "Generation 406: p = 0.8749759048507368\n",
      "Generation 406: M(n) = 1312.4725891194391\n",
      "Generation 407: p = 0.8749817260796261\n",
      "Generation 407: M(n) = 1312.4811749978878\n",
      "Generation 408: p = 0.8749874499985919\n",
      "Generation 408: M(n) = 1312.4896173514571\n",
      "Generation 409: p = 0.8749930782343047\n",
      "Generation 409: M(n) = 1312.4979185793645\n",
      "Generation 410: p = 0.874998612386243\n",
      "Generation 410: M(n) = 1312.5060810407215\n",
      "Generation 411: p = 0.8750040540271476\n",
      "Generation 411: M(n) = 1312.5141070552036\n",
      "Generation 412: p = 0.875009404703469\n",
      "Generation 412: M(n) = 1312.5219989037096\n",
      "Generation 413: p = 0.8750146659358063\n",
      "Generation 413: M(n) = 1312.5297588290102\n",
      "Generation 414: p = 0.8750198392193401\n",
      "Generation 414: M(n) = 1312.537389036385\n",
      "Generation 415: p = 0.8750249260242567\n",
      "Generation 415: M(n) = 1312.5448916942494\n",
      "Generation 416: p = 0.8750299277961663\n",
      "Generation 416: M(n) = 1312.5522689347704\n",
      "Generation 417: p = 0.8750348459565136\n",
      "Generation 417: M(n) = 1312.559522854473\n",
      "Generation 418: p = 0.875039681902982\n",
      "Generation 418: M(n) = 1312.566655514836\n",
      "Generation 419: p = 0.8750444370098907\n",
      "Generation 419: M(n) = 1312.5736689428775\n",
      "Generation 420: p = 0.875049112628585\n",
      "Generation 420: M(n) = 1312.5805651317312\n",
      "Generation 421: p = 0.8750537100878208\n",
      "Generation 421: M(n) = 1312.5873460412133\n",
      "Generation 422: p = 0.8750582306941422\n",
      "Generation 422: M(n) = 1312.5940135983783\n",
      "Generation 423: p = 0.8750626757322522\n",
      "Generation 423: M(n) = 1312.6005696980674\n",
      "Generation 424: p = 0.8750670464653783\n",
      "Generation 424: M(n) = 1312.6070162034473\n",
      "Generation 425: p = 0.8750713441356315\n",
      "Generation 425: M(n) = 1312.613354946539\n",
      "Generation 426: p = 0.8750755699643593\n",
      "Generation 426: M(n) = 1312.619587728739\n",
      "Generation 427: p = 0.8750797251524925\n",
      "Generation 427: M(n) = 1312.6257163213302\n",
      "Generation 428: p = 0.8750838108808868\n",
      "Generation 428: M(n) = 1312.6317424659871\n",
      "Generation 429: p = 0.8750878283106581\n",
      "Generation 429: M(n) = 1312.637667875269\n",
      "Generation 430: p = 0.8750917785835127\n",
      "Generation 430: M(n) = 1312.6434942331075\n",
      "Generation 431: p = 0.8750956628220716\n",
      "Generation 431: M(n) = 1312.6492231952848\n",
      "Generation 432: p = 0.8750994821301898\n",
      "Generation 432: M(n) = 1312.6548563899048\n",
      "Generation 433: p = 0.8751032375932699\n",
      "Generation 433: M(n) = 1312.6603954178554\n",
      "Generation 434: p = 0.8751069302785702\n",
      "Generation 434: M(n) = 1312.665841853263\n",
      "Generation 435: p = 0.8751105612355086\n",
      "Generation 435: M(n) = 1312.6711972439405\n",
      "Generation 436: p = 0.8751141314959603\n",
      "Generation 436: M(n) = 1312.676463111827\n",
      "Generation 437: p = 0.8751176420745513\n",
      "Generation 437: M(n) = 1312.6816409534204\n",
      "Generation 438: p = 0.8751210939689469\n",
      "Generation 438: M(n) = 1312.6867322402022\n",
      "Generation 439: p = 0.8751244881601348\n",
      "Generation 439: M(n) = 1312.6917384190565\n",
      "Generation 440: p = 0.8751278256127043\n",
      "Generation 440: M(n) = 1312.6966609126803\n",
      "Generation 441: p = 0.8751311072751202\n",
      "Generation 441: M(n) = 1312.7015011199885\n",
      "Generation 442: p = 0.8751343340799923\n",
      "Generation 442: M(n) = 1312.706260416511\n",
      "Generation 443: p = 0.8751375069443407\n",
      "Generation 443: M(n) = 1312.7109401547839\n",
      "Generation 444: p = 0.8751406267698559\n",
      "Generation 444: M(n) = 1312.715541664734\n",
      "Generation 445: p = 0.875143694443156\n",
      "Generation 445: M(n) = 1312.720066254056\n",
      "Generation 446: p = 0.8751467108360373\n",
      "Generation 446: M(n) = 1312.7245152085854\n",
      "Generation 447: p = 0.8751496768057236\n",
      "Generation 447: M(n) = 1312.7288897926628\n",
      "Generation 448: p = 0.8751525931951085\n",
      "Generation 448: M(n) = 1312.7331912494933\n",
      "Generation 449: p = 0.8751554608329956\n",
      "Generation 449: M(n) = 1312.7374208015003\n",
      "Generation 450: p = 0.8751582805343335\n",
      "Generation 450: M(n) = 1312.741579650673\n",
      "Generation 451: p = 0.8751610531004487\n",
      "Generation 451: M(n) = 1312.7456689789074\n",
      "Generation 452: p = 0.8751637793192716\n",
      "Generation 452: M(n) = 1312.7496899483424\n",
      "Generation 453: p = 0.8751664599655616\n",
      "Generation 453: M(n) = 1312.7536437016904\n",
      "Generation 454: p = 0.8751690958011269\n",
      "Generation 454: M(n) = 1312.7575313625614\n",
      "Generation 455: p = 0.8751716875750409\n",
      "Generation 455: M(n) = 1312.7613540357831\n",
      "Generation 456: p = 0.8751742360238555\n",
      "Generation 456: M(n) = 1312.7651128077143\n",
      "Generation 457: p = 0.8751767418718096\n",
      "Generation 457: M(n) = 1312.7688087465538\n",
      "Generation 458: p = 0.8751792058310358\n",
      "Generation 458: M(n) = 1312.7724429026437\n",
      "Generation 459: p = 0.8751816286017624\n",
      "Generation 459: M(n) = 1312.7760163087685\n",
      "Generation 460: p = 0.8751840108725123\n",
      "Generation 460: M(n) = 1312.7795299804484\n",
      "Generation 461: p = 0.8751863533202989\n",
      "Generation 461: M(n) = 1312.7829849162276\n",
      "Generation 462: p = 0.8751886566108185\n",
      "Generation 462: M(n) = 1312.7863820979583\n",
      "Generation 463: p = 0.8751909213986389\n",
      "Generation 463: M(n) = 1312.7897224910794\n",
      "Generation 464: p = 0.8751931483273863\n",
      "Generation 464: M(n) = 1312.7930070448915\n",
      "Generation 465: p = 0.8751953380299277\n",
      "Generation 465: M(n) = 1312.7962366928261\n",
      "Generation 466: p = 0.8751974911285507\n",
      "Generation 466: M(n) = 1312.7994123527112\n",
      "Generation 467: p = 0.8751996082351408\n",
      "Generation 467: M(n) = 1312.802534927032\n",
      "Generation 468: p = 0.8752016899513546\n",
      "Generation 468: M(n) = 1312.8056053031873\n",
      "Generation 469: p = 0.8752037368687916\n",
      "Generation 469: M(n) = 1312.8086243537423\n",
      "Generation 470: p = 0.8752057495691615\n",
      "Generation 470: M(n) = 1312.8115929366754\n",
      "Generation 471: p = 0.8752077286244503\n",
      "Generation 471: M(n) = 1312.814511895623\n",
      "Generation 472: p = 0.875209674597082\n",
      "Generation 472: M(n) = 1312.817382060119\n",
      "Generation 473: p = 0.8752115880400793\n",
      "Generation 473: M(n) = 1312.8202042458302\n",
      "Generation 474: p = 0.8752134694972201\n",
      "Generation 474: M(n) = 1312.8229792547886\n",
      "Generation 475: p = 0.8752153195031924\n",
      "Generation 475: M(n) = 1312.8257078756194\n",
      "Generation 476: p = 0.8752171385837463\n",
      "Generation 476: M(n) = 1312.8283908837643\n",
      "Generation 477: p = 0.8752189272558428\n",
      "Generation 477: M(n) = 1312.8310290417028\n",
      "Generation 478: p = 0.8752206860278019\n",
      "Generation 478: M(n) = 1312.8336230991683\n",
      "Generation 479: p = 0.8752224153994456\n",
      "Generation 479: M(n) = 1312.8361737933617\n",
      "Generation 480: p = 0.8752241158622411\n",
      "Generation 480: M(n) = 1312.83868184916\n",
      "Generation 481: p = 0.8752257878994399\n",
      "Generation 481: M(n) = 1312.841147979323\n",
      "Generation 482: p = 0.8752274319862153\n",
      "Generation 482: M(n) = 1312.8435728846964\n",
      "Generation 483: p = 0.8752290485897977\n",
      "Generation 483: M(n) = 1312.8459572544098\n",
      "Generation 484: p = 0.8752306381696066\n",
      "Generation 484: M(n) = 1312.8483017660726\n",
      "Generation 485: p = 0.8752322011773818\n",
      "Generation 485: M(n) = 1312.8506070859678\n",
      "Generation 486: p = 0.8752337380573119\n",
      "Generation 486: M(n) = 1312.85287386924\n",
      "Generation 487: p = 0.87523524924616\n",
      "Generation 487: M(n) = 1312.8551027600824\n",
      "Generation 488: p = 0.8752367351733883\n",
      "Generation 488: M(n) = 1312.8572943919198\n",
      "Generation 489: p = 0.8752381962612799\n",
      "Generation 489: M(n) = 1312.8594493875878\n",
      "Generation 490: p = 0.8752396329250586\n",
      "Generation 490: M(n) = 1312.8615683595112\n",
      "Generation 491: p = 0.8752410455730075\n",
      "Generation 491: M(n) = 1312.8636519098768\n",
      "Generation 492: p = 0.8752424346065846\n",
      "Generation 492: M(n) = 1312.8657006308051\n",
      "Generation 493: p = 0.8752438004205367\n",
      "Generation 493: M(n) = 1312.8677151045185\n",
      "Generation 494: p = 0.8752451434030124\n",
      "Generation 494: M(n) = 1312.8696959035067\n",
      "Generation 495: p = 0.8752464639356711\n",
      "Generation 495: M(n) = 1312.8716435906895\n",
      "Generation 496: p = 0.875247762393793\n",
      "Generation 496: M(n) = 1312.8735587195767\n",
      "Generation 497: p = 0.8752490391463845\n",
      "Generation 497: M(n) = 1312.8754418344256\n",
      "Generation 498: p = 0.8752502945562838\n",
      "Generation 498: M(n) = 1312.8772934703952\n",
      "Generation 499: p = 0.8752515289802635\n",
      "Generation 499: M(n) = 1312.8791141536985\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1000x600 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Parameters of the theoretical model\n",
      "c = 1.29\n",
      "k = <function k at 0x7ae7ddad7060>\n",
      "I = 822.7895416014419\n",
      "mu = 0.01\n",
      "H = 1500\n",
      "m = 200\n",
      "Generation 0: T = 25.074582702637237\n",
      "Generation 0: s = 21.94838753232849\n",
      "Generation 0: u = 1474.9254172973629\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1000x600 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1000x600 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# ProgramRecursion_vs_solvedModel.py\n",
    "# This program presents two graphs. \n",
    "# The first is drawn by the recursion system of the difference equation, \n",
    "# and the second by its solution formula. \n",
    "# Do they overlap one another?\n",
    "\n",
    "# RECURSION MODEL\n",
    "\n",
    "# Program Theoretical_model.py\n",
    "# This program implements the theoretical model of the truncated evolution\n",
    "import numpy as np\n",
    "import matplotlib.pyplot as plt\n",
    "\n",
    "# Definition of parameters for the theoretical model\n",
    "\n",
    "n_generations = 500 # number of generations to make predictions by the model\n",
    "\n",
    "#$c = 1.29$. \n",
    "c = 1.29\n",
    "#$k = 24.9 n^{-1.18} + 2.53$\n",
    "def k(length_of_target_sequence):\n",
    "    #return 24.9 * (length_of_target_sequence ** -1.18) + 2.53 #original definition of k\n",
    "    #return 2.53 # Simplified definition of k for large target sequence lengths\n",
    "    #return 10.3229 # Adjusted value of k for better fit with empirical data\n",
    "    return 1.5\n",
    "\n",
    "mutation_rate = 0.01\n",
    "length_of_target_sequence = 1500\n",
    "population_size = 200\n",
    "\n",
    "# $\\mu = $ mutation rate, constant\n",
    "mu = mutation_rate   # Example mutation rate\n",
    "#$H = $ length of the target string, total number of sites\n",
    "H = length_of_target_sequence \n",
    "#$m = $ number of monkeys or of binomial distributions.\n",
    "m = population_size\n",
    "#$M_t = $ number of solved sites at generation $t$\n",
    "#$M_o = I = $ initial number of matched sites\n",
    "#$ = \\frac{H}{2} +  \\sqrt{\\frac{H}{k}\\ln m  }  $\n",
    "I = H / 2 + ((H / k(H)) * np.log(m)) ** 0.5\n",
    "\n",
    "\n",
    "#$T= $ number of touched sites $ =  \\mu H +  \\sqrt{H \\mu (1 - \\mu) } \\sqrt{c \\ln (m)} $ \n",
    "def T(mu, H, c, m):\n",
    "    return mu * H + (H * mu * (1 - mu)) ** 0.5 * (c * np.log(m)) ** 0.5\n",
    "\n",
    "#  $ s = $ number of solved sites among touched $ =  \\frac{T}{2} +  \\sqrt{\\frac{T}{k}\\ln m  }  $\n",
    "def s(T, m):\n",
    "    return T / 2 + ((T / k(T)) * np.log(m)) ** 0.5\n",
    "\n",
    "# $ u = $ number of untouched sites $ = H-T$\n",
    "def u(H, T):\n",
    "    return H - T\n",
    "\n",
    "# $ r =  (H-T)p +  \\sqrt{(H-T)p(1-p)} \\sqrt{1.29 \\ln (m)} $.\n",
    "\n",
    "# $p = \\frac{M_t}{H}$\n",
    "\n",
    "def p(M_t, H):\n",
    "    return M_t / H\n",
    "\n",
    "#$ r = $ number of untouched sites that were right from start \n",
    "#$ = u p + \\sqrt{u p (1-p)} \\sqrt{c \\ln m} $\n",
    "def r(u_value, H, p_value, M_t):\n",
    "    return u_value * p_value  \n",
    "    #return u_value * p_value  + ((u_value * p_value  * (1 - p_value )) ** 0.5) * (kappa * np.log(m)) ** 0.5\n",
    "\n",
    "\n",
    "#$M_{t+1} =  s + r $, number of matched sites at generation $t+1$.\n",
    "def M(s, r):\n",
    "    return s + r\n",
    "\n",
    "print(\"Parameters of the theoretical model\")\n",
    "print(f\"c = {c}\")\n",
    "print(f\"k(H) = {k(H)}\")\n",
    "print(f\"I = {I}\")\n",
    "print(f\"mu = {mu}\")\n",
    "print(f\"H = {H}\")\n",
    "print(f\"m = {m}\")\n",
    "\n",
    "# M_values according to recursion model, which will be plotted in the first graph\n",
    "M_values_R = []\n",
    "m_value  = I\n",
    "n = 0\n",
    "T_value = T(mu, H, c, m)\n",
    "print(f\"Generation {n}: T = {T_value}\")\n",
    "s_value = s(T_value,  m)\n",
    "print(f\"Generation {n}: s = {s_value}\")\n",
    "u_value = u(H, T_value)\n",
    "print(f\"Generation {n}: u = {u_value}\")\n",
    "# Here is the recursion system of the difference equation,\n",
    "# which is calculated for a range of generations\n",
    "for n in range(n_generations):\n",
    "    p_value = p(m_value, H)\n",
    "    print(f\"Generation {n}: p = {p_value}\")\n",
    "    r_value = r(u_value, H, p_value, m_value)\n",
    "    # print(f\"Generation {n}: r = {r_value}\")\n",
    "    m_value = M(s_value, r_value)\n",
    "    if m_value > H:\n",
    "        m_value = H\n",
    "    M_values_R.append(m_value)\n",
    "    print(f\"Generation {n}: M(n) = {m_value}\")\n",
    "\n",
    "###########\n",
    "\n",
    "# PLOT FUNCTION\n",
    "\n",
    "plt.figure(figsize=(10, 6))\n",
    "# Red line for the total number of sites (H)\n",
    "plt.axhline(y=H, color='red', linestyle='--', linewidth=2, label='Total number of sites (H)')\n",
    "plt.plot(M_values_R, label = 'Predicted number of matched sites by the recursion model', color='green')\n",
    "plt.axhline(y=length_of_target_sequence, color='red', linestyle='--', linewidth=2)\n",
    "\n",
    "plt.xlabel('Generation (n)')\n",
    "plt.ylabel('Number of Matched Sites (M)')\n",
    "plt.title('Number of Matched Sites in GA by the recursion model')\n",
    "plt.grid(True)\n",
    "plt.legend()\n",
    "plt.show()\n",
    "\n",
    "############################\n",
    "\n",
    "# SOLVED MODEL\n",
    "\n",
    "\n",
    "\n",
    "# $ u = $ number of untouched sites $ = H-T$\n",
    "def u(H, T):\n",
    "    return H - T\n",
    "\n",
    "# $ r =  (H-T)p +  \\sqrt{(H-T)p(1-p)} \\sqrt{1.29 \\ln (m)} $.\n",
    "\n",
    "# $p = \\frac{M_t}{H}$\n",
    "\n",
    "def p(M_t, H):\n",
    "    return M_t / H\n",
    "\n",
    "#$ r = $ number of untouched sites that were right from start \n",
    "#$ = u p + \\sqrt{u p (1-p)} \\sqrt{c \\ln m} $\n",
    "def r(u_value, H, p_value, M_t):\n",
    "    return u_value * p_value  \n",
    "    #return u_value * p_value  + ((u_value * p_value  * (1 - p_value )) ** 0.5) * (kappa * np.log(m)) ** 0.5\n",
    "\n",
    "\n",
    "#$M_{t+1} =  s + r $, number of matched sites at generation $t+1$.\n",
    "def M(s, r):\n",
    "    return s + r\n",
    "\n",
    "#$a = \\frac{H-T}{H} $\n",
    "a = (H - T(mu, H, c, m)) / H \n",
    "#$b = s$ \n",
    "b = s(T(mu, H, c, m), m)\n",
    "# M according to the solved model is given by the formula:\n",
    "#$M(n) = a^nI + \\frac{1- a^n}{1-a} b$\n",
    "def M_n(n, a, I, b):\n",
    "    if n == 0:\n",
    "        return I \n",
    "    else:\n",
    "        return (a ** n) * I + ((1 - a ** n) / (1 - a)) * b\n",
    "\n",
    "print(\"Parameters of the theoretical model\")\n",
    "print(f\"c = {c}\")\n",
    "print(f\"k = {k}\")\n",
    "print(f\"I = {I}\")\n",
    "print(f\"mu = {mu}\")\n",
    "print(f\"H = {H}\")\n",
    "print(f\"m = {m}\")\n",
    "\n",
    "# M_values according to solution formula\n",
    "M_values_S = []\n",
    "m_value  = I\n",
    "n = 0\n",
    "T_value = T(mu, H, c, m)\n",
    "print(f\"Generation {n}: T = {T_value}\")\n",
    "s_value = s(T_value,  m)\n",
    "print(f\"Generation {n}: s = {s_value}\")\n",
    "u_value = u(H, T_value)\n",
    "print(f\"Generation {n}: u = {u_value}\")\n",
    "# Generate a range of generations\n",
    "for n in range(n_generations):\n",
    "    m_value =  M_n(n, a, I, b)\n",
    "    #if m_value > H:\n",
    "    #    m_value = H\n",
    "    M_values_S.append(m_value)\n",
    "    #print(f\"Generation {n}: M(n) = {m_value}\")\n",
    "\n",
    "###########\n",
    "\n",
    "# PLOT FUNCTION\n",
    "\n",
    "plt.figure(figsize=(10, 6))\n",
    "# Red line for the total number of sites (H)\n",
    "plt.axhline(y=H, color='red', linestyle='--', linewidth=2, label='Total number of sites (H)')\n",
    "plt.plot(M_values, label = 'Predicted number of matched sites by the solved model', color='green')\n",
    "plt.axhline(y=length_of_target_sequence, color='red', linestyle='--', linewidth=2)\n",
    "\n",
    "plt.xlabel('Generation (n)')\n",
    "plt.ylabel('Number of Matched Sites (M)')\n",
    "plt.title('Number of Matched Sites in GA by Solved Model')\n",
    "plt.grid(True)\n",
    "plt.legend()\n",
    "plt.show()\n",
    "\n",
    "###########\n",
    "\n",
    "# PLOT FUNCTION\n",
    "\n",
    "plt.figure(figsize=(10, 6))\n",
    "# Red line for the total number of sites (H)\n",
    "plt.axhline(y=H, color='red', linestyle='--', linewidth=2, label='Total number of sites (H)')\n",
    "plt.plot(M_values_R, label = 'Predicted number of matched sites by the recursion model', color='green')\n",
    "plt.plot(M_values_S, label = 'Predicted number of matched sites by the solved model', color='blue')\n",
    "\n",
    "plt.axhline(y=length_of_target_sequence, color='red', linestyle='--', linewidth=2)\n",
    "\n",
    "plt.xlabel('Generation (n)')\n",
    "plt.ylabel('Number of Matched Sites (M)')\n",
    "plt.title('Number of Matched Sites in GA by Recursion and Solved Models')\n",
    "plt.grid(True)\n",
    "plt.legend()\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "d62dc1a1",
   "metadata": {},
   "source": [
    "*Comment.* The coincidence is perfect. This means that the solution formula is the correct solution to the recursion system. \n",
    "\n",
    "-Step 8. Test your specific solution, which is a prediction, comparing it with the observed. The predicted graph must be an upper bound of the observed one.\n",
    "\n",
    "The corresponding code follows."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "9523a9a6",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Lab: Simple Genetic Algorithm\n",
      "Purpose: solve an instance of the Shakespeare challenge\n",
      "Date of Experiment  = 2026-02-18 10:58:20.245883\n",
      "alphabet =  01\n",
      "target_sequence = 11111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111\n",
      "length_of_target_sequence = 800\n",
      "population_size = 200\n",
      "include_clone_populationf6 = True\n",
      "include_mutate_allf6 = True\n",
      "include_crossover_allf6 = False\n",
      "mutation_rate = 0.01\n",
      "print_best_fitness = False\n",
      "\n",
      "Target sequence matched in generation 568\n",
      "Final chromosome: 11111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111\n",
      "Total cost = population size * number of generations: 113600\n",
      "Parameters of the theoretical model\n",
      "c = 1.29\n",
      "k = 1.5\n",
      "I = 453.1579651807606\n",
      "mu = 0.01\n",
      "H = 800\n",
      "m = 200\n",
      "Generation 0: T = 15.357434938247703\n",
      "Generation 0: s = 15.04388613607459\n",
      "Generation 0: u = 784.6425650617523\n"
     ]
    },
    {
     "data": {
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",
      "text/plain": [
       "<Figure size 1000x600 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "## Program DuoMutationMax_VS_Solved_Simple_Math_Model.py\n",
    "# This program compares the maximum number of touched sites \n",
    "# in a generation according to a simulation\n",
    "# with the prediction of a solved simplified theoretical model \n",
    "# of the number of matched sites at that generation.\n",
    "# The approximation implements the idea that \n",
    "# the fittest is not chosen at each step.\n",
    "# So, we take the values  kappa = 0 and k = constant = 1.5\n",
    "\n",
    "\n",
    "\n",
    "# SIMULATION\n",
    "\n",
    "# This part is based on the code of the program \n",
    "# Variability_in_the_number_of_touched_sites.py\n",
    "\n",
    "import datetime\n",
    "import random\n",
    "import matplotlib.pyplot as plt # Import matplotlib for plotting\n",
    "# target_sequence = 'Methinks it is like a weasel.'\n",
    "# alphabet = 'abcdefghijklmnopqrstuvwxyzABCDEFGHIJKLMNOPQRSTUVWXYZ .,'\n",
    "alphabet = '01' # Binary alphabet, binary strings\n",
    "length_of_target_sequence = 800\n",
    "target_sequence = '1'*length_of_target_sequence  #1111...1 (800 ones)\n",
    "population_size = 200\n",
    "include_clone_populationf6 = True\n",
    "include_mutate_allf6 = True\n",
    "include_crossover_allf6 = False\n",
    "mutation_rate = 0.01\n",
    "recombination_rate = 0\n",
    "# alphabet = 'abcdefghijklmnopqrstuvwxyzABCDEFGHIJKLMNOPQRSTUVWXYZ .,'\n",
    "# Boolean flag to print the generation, best chromosome and fitness.\n",
    "# This is the ancestral line of the solution.\n",
    "print_best_fitness = False\n",
    "\n",
    "\n",
    "\n",
    "\n",
    "def print_parametersf6():\n",
    "    print(f\"Lab: Simple Genetic Algorithm\")\n",
    "    print(f\"Purpose: solve an instance of the Shakespeare challenge\")\n",
    "    print(f\"Date of Experiment  = {datetime.datetime.now()}\")\n",
    "    print(f\"alphabet =  {alphabet}\")\n",
    "    print(f\"target_sequence = {target_sequence}\")\n",
    "    print(f\"length_of_target_sequence = {length_of_target_sequence}\")\n",
    "    print(f\"population_size = {population_size}\")\n",
    "    print(f\"include_clone_populationf6 = {include_clone_populationf6}\")\n",
    "    print(f\"include_mutate_allf6 = {include_mutate_allf6}\")\n",
    "    print(f\"include_crossover_allf6 = {include_crossover_allf6}\")\n",
    "    if include_mutate_allf6:\n",
    "        print(f\"mutation_rate = {mutation_rate}\")\n",
    "    if include_crossover_allf6:\n",
    "        print(f\"recombination_rate = {recombination_rate}\")\n",
    "    if include_clone_populationf6:\n",
    "        print(f\"print_best_fitness = {print_best_fitness}\")\n",
    "\n",
    "\n",
    "def create_populationf6(population_size, target_sequence, alphabet):\n",
    "    \"\"\"Creates a new population with random chromosomes.\"\"\"\n",
    "    # print(\"create_population8(population_size, target_sequence, alphabet)\")\n",
    "    population = []\n",
    "    for _ in range(population_size):\n",
    "        random_string = ''.join(random.choice(alphabet) for _ in range(len(target_sequence)))\n",
    "        population.append(random_string)\n",
    "    # print(\"initial population\")\n",
    "    # print(population)\n",
    "    return population\n",
    "\n",
    "def calculate_fitnessf6(chromosome, target_sequence):\n",
    "    \"\"\"Calculates the fitness of a chromosome based on its similarity to the target sequence.\"\"\"\n",
    "    #  print(\"\\n *calculate_fitness8(chromosome, target_sequence)\")\n",
    "    fitness = 0\n",
    "    for i in range(len(chromosome)):\n",
    "        if chromosome[i] == target_sequence[i]:\n",
    "            fitness += 1\n",
    "    # print(chromosome, \"  fitness: \", fitness)\n",
    "    return fitness\n",
    "\n",
    "def calculate_all_fitnessf6(population, target_sequence):\n",
    "    # print(\"\\n*calculate_all_fitness8(population, target_sequence)\")\n",
    "    \"\"\"Calculates the fitness of all chromosomes in the population.\"\"\"\n",
    "    fitness_scores = [calculate_fitnessf6(chromosome, target_sequence) for chromosome in population]\n",
    "    # print(\"fitness_scores: \", fitness_scores)\n",
    "    return fitness_scores\n",
    "\n",
    "def select_the_bestf6(population, target_sequence):\n",
    "    \"\"\"Selects the best chromosome for reproduction.\"\"\"\n",
    "    fitness_scores = calculate_all_fitnessf6(population, target_sequence)\n",
    "    best_fitness = max(fitness_scores)\n",
    "    best_chromosome_index = fitness_scores.index(best_fitness)\n",
    "    best_chromosome = population[best_chromosome_index]\n",
    "    # print(\"\\n*select_the_bestf6(population)\")\n",
    "    # print(\"best_fitness = \", best_fitness)\n",
    "    # print(\"The chro = \", best_chromosome )\n",
    "    return best_fitness, best_chromosome\n",
    "\n",
    "def clone_populationf6(best_chromosome, population_size):\n",
    "    \"\"\"Creates a new population by cloning the best chromosome.\"\"\"\n",
    "    return [best_chromosome] * population_size\n",
    "\n",
    "\n",
    "def mutatef6(chromosome, mutation_rate, alphabet):\n",
    "    \"\"\"Mutates a chromosome.\"\"\"\n",
    "    mutated_chromosome_list = list(chromosome)\n",
    "    for i in range(len(mutated_chromosome_list)):\n",
    "        if random.random() < mutation_rate:\n",
    "                mutated_chromosome_list[i] = random.choice(alphabet)\n",
    "    return \"\".join(mutated_chromosome_list)\n",
    "\n",
    "def mutate_allf6(population, mutation_rate, alphabet):\n",
    "    \"\"\"Mutates all chromosomes in the population.\"\"\"\n",
    "    mutated_population = []\n",
    "    for chromosome in population:\n",
    "        mutated_chromosome = mutatef6(chromosome, mutation_rate, alphabet)\n",
    "        mutated_population.append(mutated_chromosome)\n",
    "    return mutated_population\n",
    "\n",
    "def crossoverf6(parent1, parent2, target_sequence, recombination_rate):\n",
    "    \"\"\"Performs crossover between two parent chromosomes.\"\"\"\n",
    "    if random.random() < recombination_rate:\n",
    "        crossover_point = random.randint(0, len(target_sequence))\n",
    "        return parent1[:crossover_point] + parent2[crossover_point:]\n",
    "    else:\n",
    "        return parent1\n",
    "\n",
    "def crossover_allf6(population, target_sequence, recombination_rate):\n",
    "    \"\"\"Performs crossover on all chromosomes in the population.\"\"\"\n",
    "    recombinant_population = []\n",
    "    for i in range(len(population)):\n",
    "        parent1 =  population[i]\n",
    "        parent2 = random.choice(population)\n",
    "        child = crossoverf6(parent1, parent2, target_sequence, recombination_rate)\n",
    "        recombinant_population.append(child)\n",
    "    return recombinant_population\n",
    "\n",
    "\n",
    "\n",
    "def run_one_generationf6(population, target_sequence, mutation_rate, recombination_rate, alphabet):\n",
    "    \"\"\"Runs one generation of the genetic algorithm.\"\"\"\n",
    "    # Calculate fitness scores for the current population\n",
    "    best_fitness, best_chromosome  = select_the_bestf6(population, target_sequence)\n",
    "    # print(f\" best_chromosome {best_chromosome}, best_fitness {best_fitness}\")\n",
    "    # Clone the best to build the new population\n",
    "    new_population = []\n",
    "    if include_clone_populationf6:\n",
    "        new_population = clone_populationf6(best_chromosome, population_size)\n",
    "    if include_mutate_allf6:\n",
    "        new_population = mutate_allf6(new_population, mutation_rate, alphabet)\n",
    "    if include_crossover_allf6:\n",
    "        new_population = crossover_allf6(new_population, target_sequence, recombination_rate)\n",
    "    return best_fitness, best_chromosome, new_population\n",
    "\n",
    "\n",
    "\n",
    "\n",
    "\n",
    "def mainf6( target_sequence, mutation_rate, recombination_rate, alphabet):\n",
    "    print_parametersf6()\n",
    "    population = create_populationf6(population_size, target_sequence, alphabet)\n",
    "    # print(population)\n",
    "    best_fitness, best_chromosome = select_the_bestf6(population, target_sequence)\n",
    "    generation = 0\n",
    "    best_fitness_history = [] # List to store best fitness of each generation\n",
    "    best_fitness_history.append(best_fitness)\n",
    "    if print_best_fitness:\n",
    "        print(\"Generation, best_chromosome and best_fitness, M_t\")\n",
    "    while best_fitness < len(target_sequence):\n",
    "        generation += 1\n",
    "        best_fitness, best_chromosome, population = run_one_generationf6(population, target_sequence, mutation_rate, recombination_rate, alphabet)        \n",
    "        if print_best_fitness:\n",
    "            print(f\" {generation}  {best_chromosome} {best_fitness}\")\n",
    "        best_fitness_history.append(best_fitness)    \n",
    "    print(f\"\\nTarget sequence matched in generation {generation}\")\n",
    "    print(f\"Final chromosome: {best_chromosome}\")\n",
    "    totalCost = population_size * generation\n",
    "    print(f\"Total cost = population size * number of generations: {totalCost}\")\n",
    "    return generation, best_fitness_history\n",
    "\n",
    "generation, best_fitness_history =  mainf6( target_sequence, mutation_rate, recombination_rate, alphabet)\n",
    "\n",
    "############################\n",
    "\n",
    "# THEORETICAL MODEL\n",
    "\n",
    "# Program Theoretical_model.py\n",
    "# This program implements the theoretical model of the truncated evolution\n",
    "import numpy as np\n",
    "import matplotlib.pyplot as plt\n",
    "\n",
    "# Definition of parameters for the theoretical model\n",
    "\n",
    "n_generations = generation # number of generations to make predictions by the model\n",
    "\n",
    "#$c = 1.29$. \n",
    "c = 1.29\n",
    "k = 1.5\n",
    "# $\\mu = $ mutation rate, constant\n",
    "mu = mutation_rate   # Example mutation rate\n",
    "#$H = $ length of the target string, total number of sites\n",
    "H = length_of_target_sequence \n",
    "#$m = $ number of monkeys or of binomial distributions.\n",
    "m = population_size\n",
    "#$M_t = $ number of solved sites at generation $t$\n",
    "#$M_o = I = $ initial number of matched sites\n",
    "#$ = \\frac{H}{2} +  \\sqrt{\\frac{H}{k}\\ln m  }  $\n",
    "I = H / 2 + ((H / k) * np.log(m)) ** 0.5\n",
    "\n",
    "\n",
    "#$T= $ number of touched sites $ =  \\mu H +  \\sqrt{H \\mu (1 - \\mu) } \\sqrt{c \\ln (m)} $ \n",
    "def T(mu, H, c, m):\n",
    "    return mu * H + (H * mu * (1 - mu)) ** 0.5 * (c * np.log(m)) ** 0.5\n",
    "\n",
    "#  $ s = $ number of solved sites among touched $ =  \\frac{T}{2} +  \\sqrt{\\frac{T}{k}\\ln m  }  $\n",
    "def s(T, m):\n",
    "    return T / 2 + ((T / k ) * np.log(m)) ** 0.5\n",
    "\n",
    "# $ u = $ number of untouched sites $ = H-T$\n",
    "def u(H, T):\n",
    "    return H - T\n",
    "\n",
    "# $ r =  (H-T)p +  \\sqrt{(H-T)p(1-p)} \\sqrt{1.29 \\ln (m)} $.\n",
    "\n",
    "# $p = \\frac{M_t}{H}$\n",
    "\n",
    "def p(M_t, H):\n",
    "    return M_t / H\n",
    "\n",
    "#$ r = $ number of untouched sites that were right from start \n",
    "#$ = u p + \\sqrt{u p (1-p)} \\sqrt{c \\ln m} $\n",
    "def r(u_value, H, p_value, M_t):\n",
    "    return u_value * p_value  \n",
    "    #return u_value * p_value  + ((u_value * p_value  * (1 - p_value )) ** 0.5) * (kappa * np.log(m)) ** 0.5\n",
    "\n",
    "\n",
    "#$M_{t+1} =  s + r $, number of matched sites at generation $t+1$.\n",
    "def M(s, r):\n",
    "    return s + r\n",
    "\n",
    "#$a = \\frac{H-T}{H} $\n",
    "a = (H - T(mu, H, c, m)) / H \n",
    "#$b = s$ \n",
    "b = s(T(mu, H, c, m), m)\n",
    "#$M(n) = a^nI + \\frac{1- a^n}{1-a} b$\n",
    "def M_n(n, a, I, b):\n",
    "    if n == 0:\n",
    "        return I \n",
    "    else:\n",
    "        return (a ** n) * I + ((1 - a ** n) / (1 - a)) * b\n",
    "\n",
    "print(\"Parameters of the theoretical model\")\n",
    "print(f\"c = {c}\")\n",
    "print(f\"k = {k}\")\n",
    "print(f\"I = {I}\")\n",
    "print(f\"mu = {mu}\")\n",
    "print(f\"H = {H}\")\n",
    "print(f\"m = {m}\")\n",
    "\n",
    "M_values = []\n",
    "m_value  = I\n",
    "n = 0\n",
    "T_value = T(mu, H, c, m)\n",
    "print(f\"Generation {n}: T = {T_value}\")\n",
    "s_value = s(T_value,  m)\n",
    "print(f\"Generation {n}: s = {s_value}\")\n",
    "u_value = u(H, T_value)\n",
    "print(f\"Generation {n}: u = {u_value}\")\n",
    "# Generate a range of generations\n",
    "for n in range(n_generations):\n",
    "    m_value =  M_n(n, a, I, b)\n",
    "    #if m_value > H:\n",
    "    #    m_value = H\n",
    "    M_values.append(m_value)\n",
    "    #print(f\"Generation {n}: M(n) = {m_value}\")\n",
    "\n",
    "###########\n",
    "\n",
    "# PLOT FUNCTIONS\n",
    "\n",
    "plt.figure(figsize=(10, 6))\n",
    "# Red line for the total number of sites (H)\n",
    "plt.axhline(y=H, color='red', linestyle='--', linewidth=2, label='Total number of sites (H)')\n",
    "plt.plot(best_fitness_history, label='Best Fitness in simulation', color='blue')\n",
    "plt.plot(M_values, label = 'Predicted number of matched sites by the theoretical model', color='green')\n",
    "plt.axhline(y=length_of_target_sequence, color='red', linestyle='--', linewidth=2)\n",
    "\n",
    "plt.xlabel('Generation (n)')\n",
    "plt.ylabel('Number of Matched Sites (M)')\n",
    "plt.title('Number of Matched Sites in GA, Simulation vs Solved Model')\n",
    "plt.grid(True)\n",
    "plt.legend()\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "bf14fda3",
   "metadata": {},
   "source": [
    "> *Our assessment.* The solved model produces a graph that exactly fulfills the demanded expectations. It is an upper bound for the observed process below a fitness of circa 90\\% and a lower bound afterward. The fit is not bad, and the error of the model is less than 3\\%.\n",
    "\n",
    "> *Practical directive.* We will use the solved model as an upper bound below 90\\% of the maximal fitness to make predictions that we must test.\n",
    "\n"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "2b3a0f0d",
   "metadata": {},
   "source": [
    "# THE COST OF EVOLUTION\n",
    "\n",
    "We work with a restraint mode of Evolution, which is composed of mutation + MAX, or selection of the fittest, + cloning of the fittest. Our simulations show us that it is a hard task for Evolution to solve the Shakespeare Challenge. This consists in matching a target binary string that we defined as a sequence of ones. Our task is to quantify that difficulty.\n",
    "\n",
    "**Exercise.** Use the solved simple math model that was developed in the previous section to predict the cost of Evolution. \n",
    ">\n",
    "> *Answer.* We found the following formula for the number of matched sites $M$ at generation $n$:\n",
    ">\n",
    "> $M(n) = a^n I + \\frac{1-a^n}{1-a} b$\n",
    ">\n",
    "where $a$ and $b$ are constants and $I$ is the initial condition, the initial number of matched sites. It is approximately the half of $H$, the length of the target binary string, but because population fluctuations that are harvested by MAX or the selection of the fittest, $I$ is above the half.\n",
    "\n",
    "Let us consider now that we give to Evolution the task of matching, say, 80\\% of a target binary string of length $H$. Thus, the task is to solve $rH$ sites, where $ 0 \\le r \\le 1$.  We need to know how many generations it takes to Evolution to do it. To know that, we solve the previous equation for $n$. That equation says how many sites $M$ has been solved until generation $n$:\n",
    "\n",
    "> $M(n) =  a^n I + \\frac{1-a^n}{1-a} b$\n",
    ">\n",
    "> We must equate the number of solved sites with that given by the task, and solve for $n$:\n",
    "> \n",
    ">$rH = a^n I + \\frac{1-a^n}{1-a} b$\n",
    ">\n",
    ">> $ = a^n I + \\frac{b-ba^n}{1-a}$\n",
    ">>\n",
    ">> $ = a^n I + \\frac{b }{1-a} - \\frac{ba^n}{1-a}$\n",
    ">>\n",
    ">> $ = a^n I + \\frac{b }{1-a} - \\frac{b}{1-a}a^n$\n",
    ">>\n",
    "> Naming \n",
    ">\n",
    "> $\\gamma = \\frac{b}{1-a}$\n",
    ">\n",
    "> we have\n",
    ">\n",
    "> $rH = a^n I + \\gamma - \\gamma a^n$\n",
    ">\n",
    "> $rH = a^n ( I - \\gamma)+ \\gamma$\n",
    ">\n",
    "> $rH - \\gamma  = a^n ( I - \\gamma)$\n",
    ">\n",
    ">  $ a^n = \\frac{rH - \\gamma }{ I - \\gamma} $\n",
    ">\n",
    "> Taking logarithms\n",
    ">\n",
    "> $\\ln a^n = \\ln (\\frac{rH - \\gamma }{ I - \\gamma})$\n",
    "> \n",
    "> \n",
    "> $n \\ln a = \\ln (\\frac{rH - \\gamma }{ I - \\gamma})$\n",
    ">\n",
    ">  Cost $ = n = \\frac{1}{ \\ln \\, a} \\ln (\\frac{rH - \\gamma }{ I - \\gamma})$\n",
    "\n",
    "**Interpretation.** If our model has something to do with Evolution, we interpret this equation as follows:\n",
    ">\n",
    "> Randomness, in one front or many, can solve every task but on an exponential cost. Our simulations also have shown us that complexity is a fierce enemy of our Mutation-MAX Duo. But here, the cost is dominated by a logarithm. This must be taken as a symbol of the great power of Evolution to battle complexity. But, then, what we do with our very long times of our simulations with our truly short inputs or tasks? Thus, we must continue our research to carefully compare predictions with observations.\n",
    "\n",
    "\n",
    "**Exercise.** Draw the Cost that is output by the previous simplified model. \n",
    "It must be a growing function in $H$ and with a tendency to be over-exponential.\n",
    ">\n",
    "> *Answer.* Let the task be to match a proportion $r$ of the sites of a target binary string of length $H$. The expected number of generations to fulfill the task by Evolution is, according to a simplified model, given by the following definitions:\n",
    "> \n",
    "> $\\mu = $ mutation rate\n",
    ">\n",
    "> $c = 1.29$\n",
    ">\n",
    "> $k = 1.5$\n",
    ">\n",
    "> $H = $  the length of the target string \n",
    ">\n",
    "> $ r = $ proportion of the task to be solved by evolution. \n",
    "> If $r = 1$, the whole task is solved.\n",
    "> \n",
    "> $r = 0.8$\n",
    "> \n",
    "> $m = $ the number of monkeys or of binomial distributions $Bi(H, \\mu)$\n",
    "> \n",
    "> $I = M_o = $ initial number of matched sites\n",
    "> $ = \\frac{H}{2} +  \\sqrt{\\frac{H}{k}\\ln m  }  $\n",
    ">\n",
    ">  $ T= $ number of touched sites $ =  \\mu H +  \\sqrt{H \\mu (1 - \\mu) } \\sqrt{c \\ln (m)} $\n",
    ">\n",
    "> $ s = $ number of solved sites among touched $ =  \\frac{T}{2} +  \\sqrt{\\frac{T}{k}\\ln m  }  $\n",
    "> \n",
    "> $a = \\frac{H-T}{H} $\n",
    ">  \n",
    ">$b = s$ \n",
    ">\n",
    "> $\\gamma = \\frac{b}{1-a}$\n",
    ">\n",
    "> $n = $ number of generations to solve a task $rH$.\n",
    "> \n",
    "> $n = \\frac{1}{ \\ln \\, a} \\ln (\\frac{rH - \\gamma }{ I - \\gamma})$\n",
    "\n",
    "The code follows."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "0fc2495a",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Parameters of the theoretical model\n",
      "c = 1.29\n",
      "mu = 0.01\n",
      "m = 200\n",
      "r = 0.8\n",
      "\n",
      "\n",
      "Calculations for H = 1\n",
      "I = 0.939497167630667\n",
      "a = 0.7298753931513111\n",
      "b = 0.3634844216085736\n",
      "gamma = 1.3456175868205167\n",
      "rH = 0.8\n",
      "Predicted cost of Evolution to solve a binary string of length H = 1 with a population of m = 200 monkeys: -187.54272238811072\n",
      "\n",
      "\n",
      "Calculations for H = 101\n",
      "I = 64.7442543065773\n",
      "a = 0.9641166342096802\n",
      "b = 4.510385563984058\n",
      "gamma = 125.69572180993168\n",
      "rH = 80.80000000000001\n",
      "Predicted cost of Evolution to solve a binary string of length H = 101 with a population of m = 200 monkeys: 1673.2912447237866\n",
      "\n",
      "\n",
      "Calculations for H = 201\n",
      "I = 120.82598793551509\n",
      "a = 0.9716522248982336\n",
      "b = 6.271196832109373\n",
      "gamma = 221.22359901601567\n",
      "rH = 160.8\n",
      "Predicted cost of Evolution to solve a binary string of length H = 201 with a population of m = 200 monkeys: 3531.333675994588\n",
      "\n",
      "\n",
      "Calculations for H = 301\n",
      "I = 175.46117525567092\n",
      "a = 0.9750066669203334\n",
      "b = 7.707678689726222\n",
      "gamma = 308.3893878882781\n",
      "rH = 240.8\n",
      "Predicted cost of Evolution to solve a binary string of length H = 301 with a population of m = 200 monkeys: 5344.388123225568\n",
      "\n",
      "\n",
      "Calculations for H = 401\n",
      "I = 229.35868747435467\n",
      "a = 0.9770099970255096\n",
      "b = 8.98518098519883\n",
      "gamma = 390.8299183418441\n",
      "rH = 320.8\n",
      "Predicted cost of Evolution to solve a binary string of length H = 401 with a population of m = 200 monkeys: 7183.680969543299\n",
      "\n",
      "\n",
      "Calculations for H = 501\n",
      "I = 282.7878258011128\n",
      "a = 0.9783784896347321\n",
      "b = 10.163872460514856\n",
      "gamma = 470.0815201532709\n",
      "rH = 400.8\n",
      "Predicted cost of Evolution to solve a binary string of length H = 501 with a population of m = 200 monkeys: 9099.357621209521\n",
      "\n",
      "\n",
      "Calculations for H = 601\n",
      "I = 335.8854621304663\n",
      "a = 0.9793892959667997\n",
      "b = 11.273605145150551\n",
      "gamma = 546.9781685764206\n",
      "rH = 480.8\n",
      "Predicted cost of Evolution to solve a binary string of length H = 601 with a population of m = 200 monkeys: 11139.373236393003\n",
      "\n",
      "\n",
      "Calculations for H = 701\n",
      "I = 388.7324768522725\n",
      "a = 0.9801752291944723\n",
      "b = 12.331732667409632\n",
      "gamma = 622.03658182879\n",
      "rH = 560.8000000000001\n",
      "Predicted cost of Evolution to solve a binary string of length H = 701 with a population of m = 200 monkeys: 13360.002980907811\n",
      "\n",
      "\n",
      "Calculations for H = 801\n",
      "I = 441.38138617454683\n",
      "a = 0.9808089489400967\n",
      "b = 13.349386700976348\n",
      "gamma = 695.6047722090548\n",
      "rH = 640.8000000000001\n",
      "Predicted cost of Evolution to solve a binary string of length H = 801 with a population of m = 200 monkeys: 15837.223319345267\n",
      "\n",
      "\n",
      "Calculations for H = 901\n",
      "I = 493.8685792897812\n",
      "a = 0.9813339928835041\n",
      "b = 14.334207482996165\n",
      "gamma = 767.9311056475727\n",
      "rH = 720.8000000000001\n",
      "Predicted cost of Evolution to solve a binary string of length H = 901 with a population of m = 200 monkeys: 18685.747157307454\n",
      "\n",
      "\n",
      "Calculations for H = 1001\n",
      "I = 546.2205032356276\n",
      "a = 0.9817782475180585\n",
      "b = 15.291705110410934\n",
      "gamma = 839.2005722592087\n",
      "rH = 800.8000000000001\n",
      "Predicted cost of Evolution to solve a binary string of length H = 1001 with a population of m = 200 monkeys: 22099.54158328778\n",
      "\n",
      "\n",
      "Calculations for H = 1101\n",
      "I = 598.4570957564717\n",
      "a = 0.982160510597906\n",
      "b = 16.226006899061332\n",
      "gamma = 909.5555670532091\n",
      "rH = 880.8000000000001\n",
      "Predicted cost of Evolution to solve a binary string of length H = 1101 with a population of m = 200 monkeys: 26457.86475419818\n",
      "\n",
      "\n",
      "Calculations for H = 1201\n",
      "I = 650.5938295415139\n",
      "a = 0.9824939762692477\n",
      "b = 17.14029842585346\n",
      "gamma = 979.1086022432178\n",
      "rH = 960.8000000000001\n",
      "Predicted cost of Evolution to solve a binary string of length H = 1201 with a population of m = 200 monkeys: 32695.769822539547\n",
      "\n",
      "\n",
      "Calculations for H = 1301\n",
      "I = 702.6429983099631\n",
      "a = 0.9827882147072642\n",
      "b = 18.037098886985582\n",
      "gamma = 1047.9504932354744\n",
      "rH = 1040.8\n",
      "Predicted cost of Evolution to solve a binary string of length H = 1301 with a population of m = 200 monkeys: 44664.630931434775\n",
      "\n",
      "\n",
      "Calculations for H = 1401\n",
      "I = 754.6145624835488\n",
      "a = 0.9830503590237395\n",
      "b = 18.918440972740697\n",
      "gamma = 1116.1558524595107\n",
      "rH = 1120.8\n",
      "Predicted cost of Evolution to solve a binary string of length H = 1401 with a population of m = 200 monkeys: nan\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/tmp/ipykernel_8896/3804532735.py:82: RuntimeWarning: invalid value encountered in log\n",
      "  n = (1 / np.log(a)) * np.log((r*H - gamma) / (I - gamma))\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1000x600 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Program Cost_of_DuoMutationMax_by_Solved_Simple_Math_Model.py\n",
    "# The predicted cost of Evolution to solve \n",
    "# a binary string of varying length H with a population of m monkeys\n",
    "# according to a simplified model.\n",
    "# The cost is the total number of chromosomes or evaluations \n",
    "# of the fitness function, \n",
    "# which is the population size multiplied by the number of generations.\n",
    "\n",
    "# Program Theoretical_model.py\n",
    "# This program implements the theoretical model of the truncated evolution\n",
    "import numpy as np\n",
    "import matplotlib.pyplot as plt\n",
    "\n",
    "# Definition of parameters for the theoretical model\n",
    "\n",
    "# r = proportion of the task solved at the end of the evolution. \n",
    "# If r = 1, the whole task is solved.\n",
    "r = 0.8\n",
    "mutation_rate = 0.01\n",
    "population_size = 200\n",
    "\n",
    "#$c = 1.29$. \n",
    "c = 1.29\n",
    "# k = 1.5\n",
    "def k(length_of_target_sequence):\n",
    "    return 24.9 * (length_of_target_sequence ** -1.18) + 2.53 #original definition of k\n",
    "    #return 2.53 # Simplified definition of k for large target sequence lengths\n",
    "    #return 10.3229 # Adjusted value of k for better fit with empirical data\n",
    "    #return 1.5 # recommended value of k for better fit with empirical data\n",
    "    #return 2.1\n",
    "\n",
    "# $\\mu = $ mutation rate, constant\n",
    "mu = mutation_rate   # Example mutation rate\n",
    "#H = varying  length of the target string, total number of sites\n",
    "#$m = $ number of monkeys or of binomial distributions.\n",
    "m = population_size\n",
    "\n",
    "#$T= $ number of touched sites $ =  \\mu H +  \\sqrt{H \\mu (1 - \\mu) } \\sqrt{c \\ln (m)} $ \n",
    "def T(mu, H, c, m):\n",
    "    return mu * H + (H * mu * (1 - mu)) ** 0.5 * (c * np.log(m)) ** 0.5\n",
    "\n",
    "#  $ s = $ number of solved sites among touched $ =  \\frac{T}{2} +  \\sqrt{\\frac{T}{k}\\ln m  }  $\n",
    "def s(H,T, m):\n",
    "    return T / 2 + ((T / k(H)) * np.log(m)) ** 0.5\n",
    "\n",
    "\n",
    "\n",
    "print(\"Parameters of the theoretical model\")\n",
    "print(f\"c = {c}\")\n",
    "print(f\"mu = {mu}\")\n",
    "print(f\"m = {m}\")\n",
    "print(f\"r = {r}\")\n",
    "\n",
    "\n",
    "\n",
    "\n",
    "H_values = []\n",
    "Costs = []\n",
    "# Generate a range of H values\n",
    "for H in range(1, 1500, 100):\n",
    "        print()\n",
    "        print(f\"\\nCalculations for H = {H}\")\n",
    "        H_values.append(H)\n",
    "        k_value = k(H)\n",
    "        #$M_o = I = $ initial number of matched sites\n",
    "        #$ = \\frac{H}{2} +  \\sqrt{\\frac{H}{k}\\ln m  }  $\n",
    "        I = H / 2 + ((H / k_value) * np.log(m)) ** 0.5\n",
    "        #$a = \\frac{H-T}{H} $\n",
    "        T_value = T(mu, H, c, m)\n",
    "        a = (H - T_value) / H \n",
    "        #$b = s$ \n",
    "        b = s(H, T_value, m)\n",
    "        # $\\gamma = \\frac{b}{1-a}$\n",
    "        gamma = b / (1 - a)\n",
    "        print(f\"I = {I}\")\n",
    "        print(f\"a = {a}\")\n",
    "        print(f\"b = {b}\")\n",
    "        print(f\"gamma = {gamma}\")\n",
    "        print(f\"rH = {r*H}\")\n",
    "        #$n = $ number of generations to solve a task $rH$.\n",
    "        # $n = \\frac{1}{ \\ln \\, a} \\ln (\\frac{rH - \\gamma }{ I - \\gamma})$\n",
    "        n = (1 / np.log(a)) * np.log((r*H - gamma) / (I - gamma))\n",
    "        cost_value = population_size * n\n",
    "        Costs.append(cost_value)\n",
    "        print(f\"Predicted cost of Evolution to solve a binary string of length H = {H} with a population of m = {m} monkeys: {cost_value}\")\n",
    "\n",
    "\n",
    "###########\n",
    "\n",
    "# PLOT FUNCTIONS\n",
    "\n",
    "plt.figure(figsize=(10, 6))\n",
    "plt.plot(H_values, Costs, label='Predicted cost of Evolution as a function of length of target string H', color='blue')\n",
    "plt.xlabel('H = length_of_target_sequence')\n",
    "plt.ylabel('Cost')\n",
    "plt.title('Cost of Evolution as a function of length of target string H. After the solved model.')\n",
    "plt.grid(True)\n",
    "plt.legend()\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "6fb5b5b8",
   "metadata": {},
   "source": [
    "*Comments.* The graph of the cost is not a complex function that is concave at the start, and it is not defined for all values, i.e., beyond 1300 the cost is reported as nan (not a number). The simplified model is void.\n",
    "\n",
    "\n",
    "\n",
    "# THE SIMPLIFIED MODEL IS FALSE\n",
    "\n",
    "Pursuing a comparison of predicted with observed, we have unveiled that our simplified model is void because it does not output predictions of the cost of Evolution for all values of the independent variable $H =$ the length of the target binary string. \n",
    "\n",
    "Let us see why this void implies a strong violation against the Scientific Method. \n",
    "\n",
    "The cost $C$ is the number of generations to solve a task $n$ multiplied by the population size $m$, the number of monkeys, $C = mn$.  To know the cost, we must put a task to Evolution. It is given by a binary string of length $H$, and see how long it takes to solve the string. This is the observation. \n",
    "\n",
    "The prediction comes from our simplified model that outputs the number of matched sites $M$ that are expected to be solved after a number of generations $n$. This defines a function $n \\rightarrow M$. If we put $M = rH$, where $rH$ is a fraction of $H$, and solve for $n$, the cost is $C = nm$.\n",
    "\n",
    "The immediate cause of the void is that the number of matched sites $M$ in terms of the number of generations $n$ as predicted by our simplified model is not an invertible function.  This contradicts the logical expectation because we know that Evolution works and therefore, $M$ must be an increasing function, the more generations are run, the greater is the number of solved sites. Hence, $M$ must be invertible. \n",
    "\n",
    "Additionally, the cost function must be an increasing function of the complexity of the binary string to be solved. Therefore, it must be invertible. Or, since the cost and the inverse of $M(n)$ are related by a factor, both must be invertible. \n",
    "\n",
    "The mandatory invertibility has not been ratified. We have no other choice but to accept that the Scientific Method have falsified our simple model. This means that we failed, we have not been able as yet to produce a model with a full set of predictions that fit observations.\n",
    "\n",
    "## In hindsight\n",
    "\n",
    "Until now, Evolution has included only *mutation + MAX or selection of the fittest + reproduction by cloning of the fittest*. Our simulations say that Evolution works. And, we asked: Why and how? We firmly believe that Evolution is moved by the fluctuations created by mutation, which are deviation off the expected value. We used the mathematical theory of MAX, which is an abstraction of the selection of the fittest, to formulate a natural and accurate model that was next simplified. After working out the simplified model thoroughly, we asked it to predict the cost of solving a string of length $H$. We witnessed that it does not produce predictions for all possible values of $H$. Thus, the model is void. It is false, it has been falsified. This is the second time that the Scientific Method liberates us from believing our own lies.\n",
    "\n",
    "We failed again, but this is not a capitulation. The war continues.\n",
    "\n",
    "# WHAT TO DO?\n",
    "\n",
    "Since our simple model is false, we must make a change to begin anew.\n",
    "\n",
    "Can we make an intelligent change, one that puts us in the path of a robust model, capable of resisting our tests? \n",
    "\n",
    "We must try. In consequence, we must examine our work and detect what is possibly wrong.\n",
    "\n",
    "\n",
    "## Possible sources of troubles\n",
    "\n",
    "Various causes might explain why we have a non-invertible $M$ function: \n",
    "\n",
    "- 1. Numerical artifacts plague the proposed reasoning.\n",
    "- 2. Evolution requires fine-tuning of parameters.\n",
    "- 3. Evolution cannot solve complex problems.\n",
    "- 4. The model failed because our concepts are wrong.\n",
    "\n",
    "> *Clarification showing the reasonability of each point.*\n",
    ">\n",
    "- 1: Numerical artifacts plague the proposed reasoning. A numerical artifact is an error caused by the operative procedure and that does not concern the evolutionary process.\n",
    "  \n",
    "We use a semi-empirical approach. This means that mathematics showed us a family of functions that possible solves a problem, but a parameter must be fine-tuned to make a good fit with observations.  This calibration task may cause numerical artifacts that can be at the root of our problems. But, Where?\n",
    "\n",
    "The immediate cause of the indefiniteness of the cost function, as the inverse of the function $n \\rightarrow M$, is that the number of matched sites $M$, as predicted by the simplified model, is a growing function that tends to a horizontal asymptote that might be quite below $H$, so, a horizontal line $M = H$ does not cut the graph of the function of $M(n)$. Hence, there is no inverse value for $H$. This deficiency can be remedied varying the parameter $k$, at least for $H = 800$. But we have assumed that for other values the remedy is also valid. Seemingly not. We must, therefore, revise how helpful is a perturbation of the operative parameters, which are not related to Evolution. \n",
    "\n",
    "The simplified model uses only three operative parameters that at last come from the same abstract parameter. The first is $c$ and is related to the initial condition.  The second is $k$, which is variable as function of $H$. And the third is kappa that was nullified together with its multiplicative companions. Thus, let us investigate $k$. \n",
    "\n",
    "**Exercise.** Play with the value of $k$ to see the effect on the range of definition of the cost function.  \n",
    ">\n",
    "> *Answer.* To ease the research, let us put here a copy of the program that calculates the cost of solving a string $H$ bits long according to the solved model, which output nan beyond $H = 1300$. The aim is to enlarge the range of definition of $H$ in the domain. The program follows:\n",
    ">\n",
    "> \n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 41,
   "id": "f195095e",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Parameters of the theoretical model\n",
      "c = 1.29\n",
      "mu = 0.01\n",
      "m = 200\n",
      "r = 0.8\n",
      "\n",
      "\n",
      "Calculations for H = 1\n",
      "I = 0.939497167630667\n",
      "a = 0.7298753931513111\n",
      "b = 0.3634844216085736\n",
      "gamma = 1.3456175868205167\n",
      "rH = 0.8\n",
      "-187.54272238811072 = Predicted cost of Evolution to solve a binary string of length H = 1 with a population of m = 200 monkeys\n",
      "\n",
      "\n",
      "Calculations for H = 101\n",
      "I = 64.7442543065773\n",
      "a = 0.9641166342096802\n",
      "b = 4.510385563984058\n",
      "gamma = 125.69572180993168\n",
      "rH = 80.80000000000001\n",
      "1673.2912447237866 = Predicted cost of Evolution to solve a binary string of length H = 101 with a population of m = 200 monkeys\n",
      "\n",
      "\n",
      "Calculations for H = 201\n",
      "I = 120.82598793551509\n",
      "a = 0.9716522248982336\n",
      "b = 6.271196832109373\n",
      "gamma = 221.22359901601567\n",
      "rH = 160.8\n",
      "3531.333675994588 = Predicted cost of Evolution to solve a binary string of length H = 201 with a population of m = 200 monkeys\n",
      "\n",
      "\n",
      "Calculations for H = 301\n",
      "I = 175.46117525567092\n",
      "a = 0.9750066669203334\n",
      "b = 7.707678689726222\n",
      "gamma = 308.3893878882781\n",
      "rH = 240.8\n",
      "5344.388123225568 = Predicted cost of Evolution to solve a binary string of length H = 301 with a population of m = 200 monkeys\n",
      "\n",
      "\n",
      "Calculations for H = 401\n",
      "I = 229.35868747435467\n",
      "a = 0.9770099970255096\n",
      "b = 8.98518098519883\n",
      "gamma = 390.8299183418441\n",
      "rH = 320.8\n",
      "7183.680969543299 = Predicted cost of Evolution to solve a binary string of length H = 401 with a population of m = 200 monkeys\n",
      "\n",
      "\n",
      "Calculations for H = 501\n",
      "I = 282.7878258011128\n",
      "a = 0.9783784896347321\n",
      "b = 10.163872460514856\n",
      "gamma = 470.0815201532709\n",
      "rH = 400.8\n",
      "9099.357621209521 = Predicted cost of Evolution to solve a binary string of length H = 501 with a population of m = 200 monkeys\n",
      "\n",
      "\n",
      "Calculations for H = 601\n",
      "I = 335.8854621304663\n",
      "a = 0.9793892959667997\n",
      "b = 11.273605145150551\n",
      "gamma = 546.9781685764206\n",
      "rH = 480.8\n",
      "11139.373236393003 = Predicted cost of Evolution to solve a binary string of length H = 601 with a population of m = 200 monkeys\n",
      "\n",
      "\n",
      "Calculations for H = 701\n",
      "I = 388.7324768522725\n",
      "a = 0.9801752291944723\n",
      "b = 12.331732667409632\n",
      "gamma = 622.03658182879\n",
      "rH = 560.8000000000001\n",
      "13360.002980907811 = Predicted cost of Evolution to solve a binary string of length H = 701 with a population of m = 200 monkeys\n",
      "\n",
      "\n",
      "Calculations for H = 801\n",
      "I = 441.38138617454683\n",
      "a = 0.9808089489400967\n",
      "b = 13.349386700976348\n",
      "gamma = 695.6047722090548\n",
      "rH = 640.8000000000001\n",
      "15837.223319345267 = Predicted cost of Evolution to solve a binary string of length H = 801 with a population of m = 200 monkeys\n",
      "\n",
      "\n",
      "Calculations for H = 901\n",
      "I = 493.8685792897812\n",
      "a = 0.9813339928835041\n",
      "b = 14.334207482996165\n",
      "gamma = 767.9311056475727\n",
      "rH = 720.8000000000001\n",
      "18685.747157307454 = Predicted cost of Evolution to solve a binary string of length H = 901 with a population of m = 200 monkeys\n",
      "\n",
      "\n",
      "Calculations for H = 1001\n",
      "I = 546.2205032356276\n",
      "a = 0.9817782475180585\n",
      "b = 15.291705110410934\n",
      "gamma = 839.2005722592087\n",
      "rH = 800.8000000000001\n",
      "22099.54158328778 = Predicted cost of Evolution to solve a binary string of length H = 1001 with a population of m = 200 monkeys\n",
      "\n",
      "\n",
      "Calculations for H = 1101\n",
      "I = 598.4570957564717\n",
      "a = 0.982160510597906\n",
      "b = 16.226006899061332\n",
      "gamma = 909.5555670532091\n",
      "rH = 880.8000000000001\n",
      "26457.86475419818 = Predicted cost of Evolution to solve a binary string of length H = 1101 with a population of m = 200 monkeys\n",
      "\n",
      "\n",
      "Calculations for H = 1201\n",
      "I = 650.5938295415139\n",
      "a = 0.9824939762692477\n",
      "b = 17.14029842585346\n",
      "gamma = 979.1086022432178\n",
      "rH = 960.8000000000001\n",
      "32695.769822539547 = Predicted cost of Evolution to solve a binary string of length H = 1201 with a population of m = 200 monkeys\n",
      "\n",
      "\n",
      "Calculations for H = 1301\n",
      "I = 702.6429983099631\n",
      "a = 0.9827882147072642\n",
      "b = 18.037098886985582\n",
      "gamma = 1047.9504932354744\n",
      "rH = 1040.8\n",
      "44664.630931434775 = Predicted cost of Evolution to solve a binary string of length H = 1301 with a population of m = 200 monkeys\n",
      "\n",
      "\n",
      "Calculations for H = 1401\n",
      "I = 754.6145624835488\n",
      "a = 0.9830503590237395\n",
      "b = 18.918440972740697\n",
      "gamma = 1116.1558524595107\n",
      "rH = 1120.8\n",
      "nan = Predicted cost of Evolution to solve a binary string of length H = 1401 with a population of m = 200 monkeys\n",
      "\n",
      "\n",
      "Calculations for H = 1501\n",
      "I = 806.5167258582738\n",
      "a = 0.9832858492089547\n",
      "b = 19.785992821951915\n",
      "gamma = 1183.786904241186\n",
      "rH = 1200.8\n",
      "nan = Predicted cost of Evolution to solve a binary string of length H = 1501 with a population of m = 200 monkeys\n",
      "\n",
      "\n",
      "Calculations for H = 1601\n",
      "I = 858.3563410108117\n",
      "a = 0.9834989161001648\n",
      "b = 20.641143322360143\n",
      "gamma = 1250.8962106765798\n",
      "rH = 1280.8000000000002\n",
      "nan = Predicted cost of Evolution to solve a binary string of length H = 1601 with a population of m = 200 monkeys\n",
      "\n",
      "\n",
      "Calculations for H = 1701\n",
      "I = 910.139201788853\n",
      "a = 0.9836929063438903\n",
      "b = 21.485063373983188\n",
      "gamma = 1317.528667405026\n",
      "rH = 1360.8000000000002\n",
      "nan = Predicted cost of Evolution to solve a binary string of length H = 1701 with a population of m = 200 monkeys\n",
      "\n",
      "\n",
      "Calculations for H = 1801\n",
      "I = 961.8702591011497\n",
      "a = 0.9838705066187655\n",
      "b = 22.318750903138344\n",
      "gamma = 1383.7229958570565\n",
      "rH = 1440.8000000000002\n",
      "nan = Predicted cost of Evolution to solve a binary string of length H = 1801 with a population of m = 200 monkeys\n",
      "\n",
      "\n",
      "Calculations for H = 1901\n",
      "I = 1013.553783246538\n",
      "a = 0.9840339020614469\n",
      "b = 23.143064599462893\n",
      "gamma = 1449.512879636026\n",
      "rH = 1520.8000000000002\n",
      "nan = Predicted cost of Evolution to solve a binary string of length H = 1901 with a population of m = 200 monkeys\n",
      "\n",
      "\n",
      "Calculations for H = 2001\n",
      "I = 1065.193488131264\n",
      "a = 0.9841848905603424\n",
      "b = 23.95874964529854\n",
      "gamma = 1514.9278439528318\n",
      "rH = 1600.8000000000002\n",
      "nan = Predicted cost of Evolution to solve a binary string of length H = 2001 with a population of m = 200 monkeys\n",
      "\n",
      "\n",
      "Calculations for H = 2101\n",
      "I = 1116.7926277723616\n",
      "a = 0.984324966747076\n",
      "b = 24.76645764302843\n",
      "gamma = 1579.9939460038202\n",
      "rH = 1680.8000000000002\n",
      "nan = Predicted cost of Evolution to solve a binary string of length H = 2101 with a population of m = 200 monkeys\n",
      "\n",
      "\n",
      "Calculations for H = 2201\n",
      "I = 1168.3540722897399\n",
      "a = 0.9844553847444795\n",
      "b = 25.566762262450503\n",
      "gamma = 1644.7343238920432\n",
      "rH = 1760.8000000000002\n",
      "nan = Predicted cost of Evolution to solve a binary string of length H = 2201 with a population of m = 200 monkeys\n",
      "\n",
      "\n",
      "Calculations for H = 2301\n",
      "I = 1219.8803684765694\n",
      "a = 0.9845772057423187\n",
      "b = 26.360171680001656\n",
      "gamma = 1709.169638107112\n",
      "rH = 1840.8000000000002\n",
      "nan = Predicted cost of Evolution to solve a binary string of length H = 2301 with a population of m = 200 monkeys\n",
      "\n",
      "\n",
      "Calculations for H = 2401\n",
      "I = 1271.3737886090694\n",
      "a = 0.9846913345541084\n",
      "b = 27.147138578349477\n",
      "gamma = 1773.3184302904065\n",
      "rH = 1920.8000000000002\n",
      "nan = Predicted cost of Evolution to solve a binary string of length H = 2401 with a population of m = 200 monkeys\n",
      "\n",
      "\n",
      "Calculations for H = 2501\n",
      "I = 1322.8363701718813\n",
      "a = 0.9847985480494081\n",
      "b = 27.928068266447347\n",
      "gamma = 1837.197417537473\n",
      "rH = 2000.8000000000002\n",
      "nan = Predicted cost of Evolution to solve a binary string of length H = 2501 with a population of m = 200 monkeys\n",
      "\n",
      "\n",
      "Calculations for H = 2601\n",
      "I = 1374.2699484839482\n",
      "a = 0.9848995175127707\n",
      "b = 28.703325334321306\n",
      "gamma = 1900.821735901231\n",
      "rH = 2080.8\n",
      "nan = Predicted cost of Evolution to solve a binary string of length H = 2601 with a population of m = 200 monkeys\n",
      "\n",
      "\n",
      "Calculations for H = 2701\n",
      "I = 1425.676183716733\n",
      "a = 0.9849948264052943\n",
      "b = 29.47323915314015\n",
      "gamma = 1964.2051434539435\n",
      "rH = 2160.8\n",
      "nan = Predicted cost of Evolution to solve a binary string of length H = 2701 with a population of m = 200 monkeys\n",
      "\n",
      "\n",
      "Calculations for H = 2801\n",
      "I = 1477.0565834396996\n",
      "a = 0.9850849846057552\n",
      "b = 30.238108456247573\n",
      "gamma = 2027.3601908527348\n",
      "rH = 2240.8\n",
      "nan = Predicted cost of Evolution to solve a binary string of length H = 2801 with a population of m = 200 monkeys\n",
      "\n",
      "\n",
      "Calculations for H = 2901\n",
      "I = 1528.4125215660988\n",
      "a = 0.9851704399273065\n",
      "b = 30.998205182040216\n",
      "gamma = 2090.2983655677604\n",
      "rH = 2320.8\n",
      "nan = Predicted cost of Evolution to solve a binary string of length H = 2901 with a population of m = 200 monkeys\n",
      "\n",
      "\n",
      "Calculations for H = 3001\n",
      "I = 1579.7452543775821\n",
      "a = 0.9852515875050369\n",
      "b = 31.75377771896953\n",
      "gamma = 2153.0302145952464\n",
      "rH = 2400.8\n",
      "nan = Predicted cost of Evolution to solve a binary string of length H = 3001 with a population of m = 200 monkeys\n",
      "\n",
      "\n",
      "Calculations for H = 3101\n",
      "I = 1631.05593415999\n",
      "a = 0.9853287775044676\n",
      "b = 32.505053662503045\n",
      "gamma = 2215.5654494641626\n",
      "rH = 2480.8\n",
      "nan = Predicted cost of Evolution to solve a binary string of length H = 3101 with a population of m = 200 monkeys\n",
      "\n",
      "\n",
      "Calculations for H = 3201\n",
      "I = 1682.3456208716743\n",
      "a = 0.9854023214947464\n",
      "b = 33.25224217081333\n",
      "gamma = 2277.9130365726332\n",
      "rH = 2560.8\n",
      "nan = Predicted cost of Evolution to solve a binary string of length H = 3201 with a population of m = 200 monkeys\n",
      "\n",
      "\n",
      "Calculations for H = 3301\n",
      "I = 1733.6152921805922\n",
      "a = 0.9854724977515668\n",
      "b = 33.995535988308504\n",
      "gamma = 2340.0812752911356\n",
      "rH = 2640.8\n",
      "nan = Predicted cost of Evolution to solve a binary string of length H = 3301 with a population of m = 200 monkeys\n",
      "\n",
      "\n",
      "Calculations for H = 3401\n",
      "I = 1784.8658521405368\n",
      "a = 0.9855395556959372\n",
      "b = 34.73511319248207\n",
      "gamma = 2402.0778658040904\n",
      "rH = 2720.8\n",
      "nan = Predicted cost of Evolution to solve a binary string of length H = 3401 with a population of m = 200 monkeys\n",
      "\n",
      "\n",
      "Calculations for H = 3501\n",
      "I = 1836.0981387254526\n",
      "a = 0.9856037196304442\n",
      "b = 35.47113870893561\n",
      "gamma = 2463.909968296219\n",
      "rH = 2800.8\n",
      "nan = Predicted cost of Evolution to solve a binary string of length H = 3501 with a population of m = 200 monkeys\n",
      "\n",
      "\n",
      "Calculations for H = 3601\n",
      "I = 1887.3129304003285\n",
      "a = 0.985665191900732\n",
      "b = 36.203765631083215\n",
      "gamma = 2525.58425479947\n",
      "rH = 2880.8\n",
      "nan = Predicted cost of Evolution to solve a binary string of length H = 3601 with a population of m = 200 monkeys\n",
      "\n",
      "\n",
      "Calculations for H = 3701\n",
      "I = 1938.510951875103\n",
      "a = 0.9857241555838637\n",
      "b = 36.933136374443336\n",
      "gamma = 2587.1069547870015\n",
      "rH = 2960.8\n",
      "nan = Predicted cost of Evolution to solve a binary string of length H = 3701 with a population of m = 200 monkeys\n",
      "\n",
      "\n",
      "Calculations for H = 3801\n",
      "I = 1989.6928791624052\n",
      "a = 0.9857807767850228\n",
      "b = 37.65938369016037\n",
      "gamma = 2648.483895413754\n",
      "rH = 3040.8\n",
      "nan = Predicted cost of Evolution to solve a binary string of length H = 3801 with a population of m = 200 monkeys\n",
      "\n",
      "\n",
      "Calculations for H = 3901\n",
      "I = 2040.8593440393993\n",
      "a = 0.9858352066082522\n",
      "b = 38.382631558175866\n",
      "gamma = 2709.7205371549576\n",
      "rH = 3120.8\n",
      "nan = Predicted cost of Evolution to solve a binary string of length H = 3901 with a population of m = 200 monkeys\n",
      "\n",
      "\n",
      "Calculations for H = 4001\n",
      "I = 2092.010937997358\n",
      "a = 0.9858875828545305\n",
      "b = 39.10299597705952\n",
      "gamma = 2770.8220054714507\n",
      "rH = 3200.8\n",
      "nan = Predicted cost of Evolution to solve a binary string of length H = 4001 with a population of m = 200 monkeys\n",
      "\n",
      "\n",
      "Calculations for H = 4101\n",
      "I = 2143.1482157490723\n",
      "a = 0.9859380314906766\n",
      "b = 39.82058566474098\n",
      "gamma = 2831.793119031596\n",
      "rH = 3280.8\n",
      "nan = Predicted cost of Evolution to solve a binary string of length H = 4101 with a population of m = 200 monkeys\n",
      "\n",
      "\n",
      "Calculations for H = 4201\n",
      "I = 2194.2716983531363\n",
      "a = 0.9859866679247599\n",
      "b = 40.53550268212161\n",
      "gamma = 2892.638414937939\n",
      "rH = 3360.8\n",
      "nan = Predicted cost of Evolution to solve a binary string of length H = 4201 with a population of m = 200 monkeys\n",
      "\n",
      "\n",
      "Calculations for H = 4301\n",
      "I = 2245.381876005045\n",
      "a = 0.9860335981174342\n",
      "b = 41.24784298968798\n",
      "gamma = 2953.362171339022\n",
      "rH = 3440.8\n",
      "nan = Predicted cost of Evolution to solve a binary string of length H = 4301 with a population of m = 200 monkeys\n",
      "\n",
      "\n",
      "Calculations for H = 4401\n",
      "I = 2296.4792105375377\n",
      "a = 0.9860789195535739\n",
      "b = 41.957696945715966\n",
      "gamma = 3013.968427751414\n",
      "rH = 3520.8\n",
      "nan = Predicted cost of Evolution to solve a binary string of length H = 4401 with a population of m = 200 monkeys\n",
      "\n",
      "\n",
      "Calculations for H = 4501\n",
      "I = 2347.5641376663734\n",
      "a = 0.9861227220944978\n",
      "b = 42.66514975338309\n",
      "gamma = 3074.46100336917\n",
      "rH = 3600.8\n",
      "nan = Predicted cost of Evolution to solve a binary string of length H = 4501 with a population of m = 200 monkeys\n",
      "\n",
      "\n",
      "Calculations for H = 4601\n",
      "I = 2398.6370690125077\n",
      "a = 0.9861650887277504\n",
      "b = 43.370281863047786\n",
      "gamma = 3134.8435136003413\n",
      "rH = 3680.8\n",
      "nan = Predicted cost of Evolution to solve a binary string of length H = 4601 with a population of m = 200 monkeys\n",
      "\n",
      "\n",
      "Calculations for H = 4701\n",
      "I = 2449.6983939273096\n",
      "a = 0.9862060962286804\n",
      "b = 44.073169335068286\n",
      "gamma = 3195.119385036275\n",
      "rH = 3760.8\n",
      "nan = Predicted cost of Evolution to solve a binary string of length H = 4701 with a population of m = 200 monkeys\n",
      "\n",
      "\n",
      "Calculations for H = 4801\n",
      "I = 2500.7484811437557\n",
      "a = 0.9862458157458208\n",
      "b = 44.773884167789205\n",
      "gamma = 3255.2918690314004\n",
      "rH = 3840.8\n",
      "nan = Predicted cost of Evolution to solve a binary string of length H = 4801 with a population of m = 200 monkeys\n",
      "\n",
      "\n",
      "Calculations for H = 4901\n",
      "I = 2551.787680273471\n",
      "a = 0.9862843133202354\n",
      "b = 45.472494594696116\n",
      "gamma = 3315.36405404942\n",
      "rH = 3920.8\n",
      "nan = Predicted cost of Evolution to solve a binary string of length H = 4901 with a population of m = 200 monkeys\n",
      "\n",
      "\n",
      "Calculations for H = 5001\n",
      "I = 2602.8163231668464\n",
      "a = 0.9863216503474516\n",
      "b = 46.16906535420675\n",
      "gamma = 3375.338876909387\n",
      "rH = 4000.8\n",
      "nan = Predicted cost of Evolution to solve a binary string of length H = 5001 with a population of m = 200 monkeys\n",
      "\n",
      "\n",
      "Calculations for H = 5101\n",
      "I = 2653.8347251512364\n",
      "a = 0.986357883989337\n",
      "b = 46.863657935115526\n",
      "gamma = 3435.21913304987\n",
      "rH = 4080.8\n",
      "nan = Predicted cost of Evolution to solve a binary string of length H = 5101 with a population of m = 200 monkeys\n",
      "\n",
      "\n",
      "Calculations for H = 5201\n",
      "I = 2704.843186160334\n",
      "a = 0.9863930675422067\n",
      "b = 47.556330800323096\n",
      "gamma = 3495.0074859146807\n",
      "rH = 4160.8\n",
      "nan = Predicted cost of Evolution to solve a binary string of length H = 5201 with a population of m = 200 monkeys\n",
      "\n",
      "\n",
      "Calculations for H = 5301\n",
      "I = 2755.8419917661868\n",
      "a = 0.9864272507665506\n",
      "b = 48.24713959115275\n",
      "gamma = 3554.706475549543\n",
      "rH = 4240.8\n",
      "nan = Predicted cost of Evolution to solve a binary string of length H = 5301 with a population of m = 200 monkeys\n",
      "\n",
      "\n",
      "Calculations for H = 5401\n",
      "I = 2806.831414123927\n",
      "a = 0.9864604801830262\n",
      "b = 48.936137314273026\n",
      "gamma = 3614.3185264904614\n",
      "rH = 4320.8\n",
      "nan = Predicted cost of Evolution to solve a binary string of length H = 5401 with a population of m = 200 monkeys\n",
      "\n",
      "\n",
      "Calculations for H = 5501\n",
      "I = 2857.8117128380645\n",
      "a = 0.9864927993387188\n",
      "b = 49.62337451300183\n",
      "gamma = 3673.84595501337\n",
      "rH = 4400.8\n",
      "nan = Predicted cost of Evolution to solve a binary string of length H = 5501 with a population of m = 200 monkeys\n",
      "\n",
      "\n",
      "Calculations for H = 5601\n",
      "I = 2908.783135758165\n",
      "a = 0.9865242490471354\n",
      "b = 50.308899424557694\n",
      "gamma = 3733.2909758074306\n",
      "rH = 4480.8\n",
      "nan = Predicted cost of Evolution to solve a binary string of length H = 5601 with a population of m = 200 monkeys\n",
      "\n",
      "\n",
      "Calculations for H = 5701\n",
      "I = 2959.7459197108187\n",
      "a = 0.9865548676049435\n",
      "b = 50.99275812464143\n",
      "gamma = 3792.655708127528\n",
      "rH = 4560.8\n",
      "nan = Predicted cost of Evolution to solve a binary string of length H = 5701 with a population of m = 200 monkeys\n",
      "\n",
      "\n",
      "Calculations for H = 5801\n",
      "I = 3010.7002911740306\n",
      "a = 0.9865846909880672\n",
      "b = 51.67499466057326\n",
      "gamma = 3851.9421814740836\n",
      "rH = 4640.8\n",
      "nan = Predicted cost of Evolution to solve a binary string of length H = 5801 with a population of m = 200 monkeys\n",
      "\n",
      "\n",
      "Calculations for H = 5901\n",
      "I = 3061.646466899469\n",
      "a = 0.9866137530294289\n",
      "b = 52.35565117407335\n",
      "gamma = 3911.152340844615\n",
      "rH = 4720.8\n",
      "nan = Predicted cost of Evolution to solve a binary string of length H = 5901 with a population of m = 200 monkeys\n",
      "\n",
      "\n",
      "Calculations for H = 6001\n",
      "I = 3112.5846544874203\n",
      "a = 0.9866420855803308\n",
      "b = 53.034768014653224\n",
      "gamma = 3970.2880515959137\n",
      "rH = 4800.8\n",
      "nan = Predicted cost of Evolution to solve a binary string of length H = 6001 with a population of m = 200 monkeys\n",
      "\n",
      "\n",
      "Calculations for H = 6101\n",
      "I = 3163.5150529187667\n",
      "a = 0.9866697186572263\n",
      "b = 53.7123838444807\n",
      "gamma = 4029.351103950856\n",
      "rH = 4880.8\n",
      "nan = Predicted cost of Evolution to solve a binary string of length H = 6101 with a population of m = 200 monkeys\n",
      "\n",
      "\n",
      "Calculations for H = 6201\n",
      "I = 3214.4378530478534\n",
      "a = 0.986696680575421\n",
      "b = 54.388535735488816\n",
      "gamma = 4088.3432171824406\n",
      "rH = 4960.8\n",
      "nan = Predicted cost of Evolution to solve a binary string of length H = 6201 with a population of m = 200 monkeys\n",
      "\n",
      "\n",
      "Calculations for H = 6301\n",
      "I = 3265.3532380597\n",
      "a = 0.9867229980710551\n",
      "b = 55.06325925941832\n",
      "gamma = 4147.2660435016\n",
      "rH = 5040.8\n",
      "nan = Predicted cost of Evolution to solve a binary string of length H = 6301 with a population of m = 200 monkeys\n",
      "\n",
      "\n",
      "Calculations for H = 6401\n",
      "I = 3316.2613838946604\n",
      "a = 0.9867486964125627\n",
      "b = 55.73658857141207\n",
      "gamma = 4206.121171674933\n",
      "rH = 5120.8\n",
      "nan = Predicted cost of Evolution to solve a binary string of length H = 6401 with a population of m = 200 monkeys\n",
      "\n",
      "\n",
      "Calculations for H = 6501\n",
      "I = 3367.1624596433217\n",
      "a = 0.9867737995026649\n",
      "b = 56.408556487716574\n",
      "gamma = 4264.910130394739\n",
      "rH = 5200.8\n",
      "nan = Predicted cost of Evolution to solve a binary string of length H = 6501 with a population of m = 200 monkeys\n",
      "\n",
      "\n",
      "Calculations for H = 6601\n",
      "I = 3418.056627914148\n",
      "a = 0.986798329971831\n",
      "b = 57.07919455799052\n",
      "gamma = 4323.634391421556\n",
      "rH = 5280.8\n",
      "nan = Predicted cost of Evolution to solve a binary string of length H = 6601 with a population of m = 200 monkeys\n",
      "\n",
      "\n",
      "Calculations for H = 6701\n",
      "I = 3468.944045176136\n",
      "a = 0.9868223092640412\n",
      "b = 57.74853313267066\n",
      "gamma = 4382.295372518401\n",
      "rH = 5360.8\n",
      "nan = Predicted cost of Evolution to solve a binary string of length H = 6701 with a population of m = 200 monkeys\n",
      "\n",
      "\n",
      "Calculations for H = 6801\n",
      "I = 3519.8248620785303\n",
      "a = 0.9868457577155847\n",
      "b = 58.41660142580166\n",
      "gamma = 4440.894440192244\n",
      "rH = 5440.8\n",
      "nan = Predicted cost of Evolution to solve a binary string of length H = 6801 with a population of m = 200 monkeys\n",
      "\n",
      "\n",
      "Calculations for H = 6901\n",
      "I = 3570.6992237494405\n",
      "a = 0.9868686946275578\n",
      "b = 59.08342757369759\n",
      "gamma = 4499.43291225958\n",
      "rH = 5520.8\n",
      "nan = Predicted cost of Evolution to solve a binary string of length H = 6901 with a population of m = 200 monkeys\n",
      "\n",
      "\n",
      "Calculations for H = 7001\n",
      "I = 3621.567270075047\n",
      "a = 0.9868911383326434\n",
      "b = 59.7490386897682\n",
      "gamma = 4557.912060248069\n",
      "rH = 5600.8\n",
      "nan = Predicted cost of Evolution to solve a binary string of length H = 7001 with a population of m = 200 monkeys\n",
      "\n",
      "\n",
      "Calculations for H = 7101\n",
      "I = 3672.429135960907\n",
      "a = 0.9869131062567003\n",
      "b = 60.41346091581166\n",
      "gamma = 4616.333111647848\n",
      "rH = 5680.8\n",
      "nan = Predicted cost of Evolution to solve a binary string of length H = 7101 with a population of m = 200 monkeys\n",
      "\n",
      "\n",
      "Calculations for H = 7201\n",
      "I = 3723.2849515767493\n",
      "a = 0.9869346149756326\n",
      "b = 61.07671947004847\n",
      "gamma = 4674.69725202421\n",
      "rH = 5760.8\n",
      "nan = Predicted cost of Evolution to solve a binary string of length H = 7201 with a population of m = 200 monkeys\n",
      "\n",
      "\n",
      "Calculations for H = 7301\n",
      "I = 3774.134842586012\n",
      "a = 0.9869556802679583\n",
      "b = 61.73883869214562\n",
      "gamma = 4733.005627000402\n",
      "rH = 5840.8\n",
      "nan = Predicted cost of Evolution to solve a binary string of length H = 7301 with a population of m = 200 monkeys\n",
      "\n",
      "\n",
      "Calculations for H = 7401\n",
      "I = 3824.9789303612733\n",
      "a = 0.9869763171634602\n",
      "b = 62.39984208545869\n",
      "gamma = 4791.259344122479\n",
      "rH = 5920.8\n",
      "nan = Predicted cost of Evolution to solve a binary string of length H = 7401 with a population of m = 200 monkeys\n",
      "\n",
      "\n",
      "Calculations for H = 7501\n",
      "I = 3875.8173321866166\n",
      "a = 0.9869965399882548\n",
      "b = 63.05975235669862\n",
      "gamma = 4849.459474612185\n",
      "rH = 6000.8\n",
      "nan = Predicted cost of Evolution to solve a binary string of length H = 7501 with a population of m = 200 monkeys\n",
      "\n",
      "\n",
      "Calculations for H = 7601\n",
      "I = 3926.650161447887\n",
      "a = 0.9870163624065913\n",
      "b = 63.718591453212866\n",
      "gamma = 4907.607055018261\n",
      "rH = 6080.8\n",
      "nan = Predicted cost of Evolution to solve a binary string of length H = 7601 with a population of m = 200 monkeys\n",
      "\n",
      "\n",
      "Calculations for H = 7701\n",
      "I = 3977.477527811717\n",
      "a = 0.9870357974596542\n",
      "b = 64.37638059805363\n",
      "gamma = 4965.703088771434\n",
      "rH = 6160.8\n",
      "nan = Predicted cost of Evolution to solve a binary string of length H = 7701 with a population of m = 200 monkeys\n",
      "\n",
      "\n",
      "Calculations for H = 7801\n",
      "I = 4028.299537394114\n",
      "a = 0.9870548576016221\n",
      "b = 65.03314032299173\n",
      "gamma = 5023.748547651434\n",
      "rH = 6240.8\n",
      "nan = Predicted cost of Evolution to solve a binary string of length H = 7801 with a population of m = 200 monkeys\n",
      "\n",
      "\n",
      "Calculations for H = 7901\n",
      "I = 4079.116292919348\n",
      "a = 0.9870735547332079\n",
      "b = 65.68889049962125\n",
      "gamma = 5081.7443731708145\n",
      "rH = 6320.8\n",
      "nan = Predicted cost of Evolution to solve a binary string of length H = 7901 with a population of m = 200 monkeys\n",
      "\n",
      "\n",
      "Calculations for H = 8001\n",
      "I = 4129.927893869818\n",
      "a = 0.9870919002328855\n",
      "b = 66.34365036868815\n",
      "gamma = 5139.691477881936\n",
      "rH = 6400.8\n",
      "nan = Predicted cost of Evolution to solve a binary string of length H = 8001 with a population of m = 200 monkeys\n",
      "\n",
      "\n",
      "Calculations for H = 8101\n",
      "I = 4180.734436627504\n",
      "a = 0.987109904985991\n",
      "b = 66.99743856776517\n",
      "gamma = 5197.590746612215\n",
      "rH = 6480.8\n",
      "nan = Predicted cost of Evolution to solve a binary string of length H = 8101 with a population of m = 200 monkeys\n",
      "\n",
      "\n",
      "Calculations for H = 8201\n",
      "I = 4231.536014607582\n",
      "a = 0.9871275794118652\n",
      "b = 67.65027315738561\n",
      "gamma = 5255.443037632154\n",
      "rH = 6560.8\n",
      "nan = Predicted cost of Evolution to solve a binary string of length H = 8201 with a population of m = 200 monkeys\n",
      "\n",
      "\n",
      "Calculations for H = 8301\n",
      "I = 4282.3327183847305\n",
      "a = 0.9871449334891927\n",
      "b = 68.30217164573956\n",
      "gamma = 5313.249183760964\n",
      "rH = 6640.8\n",
      "nan = Predicted cost of Evolution to solve a binary string of length H = 8301 with a population of m = 200 monkeys\n",
      "\n",
      "\n",
      "Calculations for H = 8401\n",
      "I = 4333.1246358126\n",
      "a = 0.9871619767796769\n",
      "b = 68.953151012028\n",
      "gamma = 5371.0099934133395\n",
      "rH = 6720.8\n",
      "nan = Predicted cost of Evolution to solve a binary string of length H = 8401 with a population of m = 200 monkeys\n",
      "\n",
      "\n",
      "Calculations for H = 8501\n",
      "I = 4383.911852136901\n",
      "a = 0.9871787184501782\n",
      "b = 69.60322772856286\n",
      "gamma = 5428.726251591477\n",
      "rH = 6800.8\n",
      "nan = Predicted cost of Evolution to solve a binary string of length H = 8501 with a population of m = 200 monkeys\n",
      "\n",
      "\n",
      "Calculations for H = 8601\n",
      "I = 4434.694450102523\n",
      "a = 0.987195167293434\n",
      "b = 70.25241778169435\n",
      "gamma = 5486.398720825995\n",
      "rH = 6880.8\n",
      "nan = Predicted cost of Evolution to solve a binary string of length H = 8601 with a population of m = 200 monkeys\n",
      "\n",
      "\n",
      "Calculations for H = 8701\n",
      "I = 4485.472510055053\n",
      "a = 0.9872113317474629\n",
      "b = 70.9007366916407\n",
      "gamma = 5544.028142068266\n",
      "rH = 6960.8\n",
      "nan = Predicted cost of Evolution to solve a binary string of length H = 8701 with a population of m = 200 monkeys\n",
      "\n",
      "\n",
      "Calculations for H = 8801\n",
      "I = 4536.246110037068\n",
      "a = 0.9872272199137546\n",
      "b = 71.54819953128987\n",
      "gamma = 5601.615235538106\n",
      "rH = 7040.8\n",
      "nan = Predicted cost of Evolution to solve a binary string of length H = 8801 with a population of m = 200 monkeys\n",
      "\n",
      "\n",
      "Calculations for H = 8901\n",
      "I = 4587.015325879505\n",
      "a = 0.9872428395743312\n",
      "b = 72.19482094403756\n",
      "gamma = 5659.160701528365\n",
      "rH = 7120.8\n",
      "nan = Predicted cost of Evolution to solve a binary string of length H = 8901 with a population of m = 200 monkeys\n",
      "\n",
      "\n",
      "Calculations for H = 9001\n",
      "I = 4637.78023128843\n",
      "a = 0.9872581982077653\n",
      "b = 72.8406151607213\n",
      "gamma = 5716.665221170903\n",
      "rH = 7200.8\n",
      "nan = Predicted cost of Evolution to solve a binary string of length H = 9001 with a population of m = 200 monkeys\n",
      "\n",
      "\n",
      "Calculations for H = 9101\n",
      "I = 4688.540897927468\n",
      "a = 0.9872733030042232\n",
      "b = 73.4855960157058\n",
      "gamma = 5774.129457163256\n",
      "rH = 7280.8\n",
      "nan = Predicted cost of Evolution to solve a binary string of length H = 9101 with a population of m = 200 monkeys\n",
      "\n",
      "\n",
      "Calculations for H = 9201\n",
      "I = 4739.297395496181\n",
      "a = 0.987288160879612\n",
      "b = 74.12977696217114\n",
      "gamma = 5831.554054462311\n",
      "rH = 7360.8\n",
      "nan = Predicted cost of Evolution to solve a binary string of length H = 9201 with a population of m = 200 monkeys\n",
      "\n",
      "\n",
      "Calculations for H = 9301\n",
      "I = 4790.049791804609\n",
      "a = 0.9873027784888828\n",
      "b = 74.77317108665147\n",
      "gamma = 5888.9396409429455\n",
      "rH = 7440.8\n",
      "nan = Predicted cost of Evolution to solve a binary string of length H = 9301 with a population of m = 200 monkeys\n",
      "\n",
      "\n",
      "Calculations for H = 9401\n",
      "I = 4840.79815284422\n",
      "a = 0.9873171622385565\n",
      "b = 75.41579112286858\n",
      "gamma = 5946.286828026489\n",
      "rH = 7520.8\n",
      "nan = Predicted cost of Evolution to solve a binary string of length H = 9401 with a population of m = 200 monkeys\n",
      "\n",
      "\n",
      "Calculations for H = 9501\n",
      "I = 4891.542542855461\n",
      "a = 0.9873313182985215\n",
      "b = 76.05764946490186\n",
      "gamma = 6003.596211279468\n",
      "rH = 7600.8\n",
      "nan = Predicted cost of Evolution to solve a binary string of length H = 9501 with a population of m = 200 monkeys\n",
      "\n",
      "\n",
      "Calculations for H = 9601\n",
      "I = 4942.283024392132\n",
      "a = 0.9873452526131534\n",
      "b = 76.69875817973288\n",
      "gamma = 6060.868370984161\n",
      "rH = 7680.8\n",
      "nan = Predicted cost of Evolution to solve a binary string of length H = 9601 with a population of m = 200 monkeys\n",
      "\n",
      "\n",
      "Calculations for H = 9701\n",
      "I = 4993.019658382734\n",
      "a = 0.9873589709118045\n",
      "b = 77.33912901920071\n",
      "gamma = 6118.1038726840425\n",
      "rH = 7760.8\n",
      "nan = Predicted cost of Evolution to solve a binary string of length H = 9701 with a population of m = 200 monkeys\n",
      "\n",
      "\n",
      "Calculations for H = 9801\n",
      "I = 5043.752504188986\n",
      "a = 0.9873724787187002\n",
      "b = 77.97877343140145\n",
      "gamma = 6175.303267703105\n",
      "rH = 7840.8\n",
      "nan = Predicted cost of Evolution to solve a binary string of length H = 9801 with a population of m = 200 monkeys\n",
      "\n",
      "\n",
      "Calculations for H = 9901\n",
      "I = 5094.4816196616575\n",
      "a = 0.9873857813622866\n",
      "b = 78.61770257156302\n",
      "gamma = 6232.467093642688\n",
      "rH = 7920.8\n",
      "nan = Predicted cost of Evolution to solve a binary string of length H = 9901 with a population of m = 200 monkeys\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/tmp/ipykernel_11136/3199623982.py:87: RuntimeWarning: invalid value encountered in log\n",
      "  n = (1 / np.log(a)) * np.log((r*H - gamma) / (I - gamma))\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1000x600 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Program Cost_of_DuoMutationMax_by_Solved_Simple_Math_Model.py\n",
    "# The predicted cost of Evolution to solve \n",
    "# a binary string of varying length H with a population of m monkeys\n",
    "# according to a simplified model.\n",
    "# The cost is the total number of chromosomes or evaluations \n",
    "# of the fitness function, \n",
    "# which is the population size multiplied by the number of generations.\n",
    "\n",
    "# Program Theoretical_model.py\n",
    "# This program implements the theoretical model of the truncated evolution\n",
    "import numpy as np\n",
    "import matplotlib.pyplot as plt\n",
    "\n",
    "# Definition of parameters for the graph\n",
    "stepH = 100 # Step size for H values\n",
    "finalH = 100 * stepH # Final value of H to consider in the graph\n",
    "\n",
    "\n",
    "# Definition of parameters for the theoretical model\n",
    "\n",
    "# r = proportion of the task solved at the end of the evolution. \n",
    "# If r = 1, the whole task is solved.\n",
    "r = 0.8\n",
    "mutation_rate = 0.01\n",
    "population_size = 200\n",
    "\n",
    "#$c = 1.29$. \n",
    "c = 1.29\n",
    "# k = 1.5\n",
    "def k(length_of_target_sequence):\n",
    "    return 24.9 * (length_of_target_sequence ** -1.18) + 2.53 #original definition of k\n",
    "    #return 24.9 * (length_of_target_sequence ** -1.18) + 1.5 #original definition of k\n",
    "    #return 2.53 # Simplified definition of k for large target sequence lengths\n",
    "    #return 10.3229 # Adjusted value of k for better fit with empirical data\n",
    "    #return 0.1 # produces negative values of cost for low H\n",
    "    #return 0.001\n",
    "\n",
    "# $\\mu = $ mutation rate, constant\n",
    "mu = mutation_rate   # Example mutation rate\n",
    "#H = varying  length of the target string, total number of sites\n",
    "#$m = $ number of monkeys or of binomial distributions.\n",
    "m = population_size\n",
    "\n",
    "#$T= $ number of touched sites $ =  \\mu H +  \\sqrt{H \\mu (1 - \\mu) } \\sqrt{c \\ln (m)} $ \n",
    "def T(mu, H, c, m):\n",
    "    return mu * H + (H * mu * (1 - mu)) ** 0.5 * (c * np.log(m)) ** 0.5\n",
    "\n",
    "#  $ s = $ number of solved sites among touched $ =  \\frac{T}{2} +  \\sqrt{\\frac{T}{k}\\ln m  }  $\n",
    "def s(H,T, m):\n",
    "    return T / 2 + ((T / k(H)) * np.log(m)) ** 0.5\n",
    "\n",
    "\n",
    "\n",
    "print(\"Parameters of the theoretical model\")\n",
    "print(f\"c = {c}\")\n",
    "print(f\"mu = {mu}\")\n",
    "print(f\"m = {m}\")\n",
    "print(f\"r = {r}\")\n",
    "\n",
    "\n",
    "\n",
    "H_values = []\n",
    "Costs = []\n",
    "# Generate a range of H values\n",
    "for H in range(1, finalH, stepH):\n",
    "        print()\n",
    "        print(f\"\\nCalculations for H = {H}\")\n",
    "        H_values.append(H)\n",
    "        k_value = k(H)\n",
    "        #$M_o = I = $ initial number of matched sites\n",
    "        #$ = \\frac{H}{2} +  \\sqrt{\\frac{H}{k}\\ln m  }  $\n",
    "        I = H / 2 + ((H / k_value) * np.log(m)) ** 0.5\n",
    "        #$a = \\frac{H-T}{H} $\n",
    "        T_value = T(mu, H, c, m)\n",
    "        a = (H - T_value) / H \n",
    "        #$b = s$ \n",
    "        b = s(H, T_value, m)\n",
    "        # $\\gamma = \\frac{b}{1-a}$\n",
    "        gamma = b / (1 - a)\n",
    "        print(f\"I = {I}\")\n",
    "        print(f\"a = {a}\")\n",
    "        print(f\"b = {b}\")\n",
    "        print(f\"gamma = {gamma}\")\n",
    "        print(f\"rH = {r*H}\")\n",
    "        #$n = $ number of generations to solve a task $rH$.\n",
    "        # $n = \\frac{1}{ \\ln \\, a} \\ln (\\frac{rH - \\gamma }{ I - \\gamma})$\n",
    "        n = (1 / np.log(a)) * np.log((r*H - gamma) / (I - gamma))\n",
    "        cost_value = population_size * n\n",
    "        Costs.append(cost_value)\n",
    "        print(f\"{cost_value} = Predicted cost of Evolution to solve a binary string of length H = {H} with a population of m = {m} monkeys\")\n",
    "\n",
    "\n",
    "###########\n",
    "\n",
    "# PLOT FUNCTIONS\n",
    "\n",
    "plt.figure(figsize=(10, 6))\n",
    "plt.plot(H_values, Costs, label='Cost as a function of length of target string H', color='blue')\n",
    "plt.xlabel('H = length_of_target_sequence')\n",
    "plt.ylabel('Cost')\n",
    "plt.title('Cost of Evolution as a function of length of target string H. After the solved model.')\n",
    "plt.grid(True)\n",
    "plt.legend()\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "af600730",
   "metadata": {},
   "source": [
    "Some experiments with the deformation of $k$ follow. \n",
    "\n",
    "The native definition of $k$ was\n",
    "\n",
    "$k(H) =  24.9 * (H ** -1.18) + 2.53$\n",
    "\n",
    "where $H$ is the length of the target string. One star is multiplication, two is exponentiation.\n",
    "\n",
    "The range of definition of the cost is the interval [0, 1300]. With this and most values, the cost for $H = 1$ is negative. We vary only one of the three coefficients. The others two remain in its original setting.\n",
    "\n",
    "The range of definition of the cost function of the program was insensitive to the changes in the first coefficient, but for some values, the cost can be negative. The exponent equated to $-0.18$ shrinks the range of definition of the cost to the interval [0, 100] and for initial values, the cost is negative. If the exponent was $-2.18$ or $-20.18$ or $-200.18$, the interval of definition was the original one $[0, 1300]$. A constant value of $1.5$ rendered [1, 2500]. For the constant value $0.5$, the range was [1, 9200]. A constant value of $0.1$ produced a function that was defined in the interval [1, 50000] but with very negative values at the vicinity of $H= 1$. For $k = 0.001$, the cost is negative everywhere. If $k = 50$, the cost for $H= 1$ was negative or nan. \n",
    "\n",
    "\n",
    "\n",
    "*Practical decision.* Deforming the value of the coefficients of $k$ one at a time, does not solve the problem of the indefiniteness of the cost function that the simplified model gives.  The next challenge is to play with changes in the diverse coefficients at the same time. \n",
    "\n",
    "**Challenge.** Play with deformation of the operative parameter $c$ to see whether a change resolves the problem of the indefiniteness of the cost function.\n",
    "\n",
    "**Challenge.** Play with deformation of the operative parameter $kappa$ to see whether a change resolves the problem of the indefiniteness of the cost function. This parameter was nullified, but you can resurrect and vary it to see what happens. \n",
    "\n",
    "- 2. Evolution requires fine-tuning of parameters.\n",
    "\n",
    "Evolution might be as a bike, whose functioning demands very precise formalities in the relative location of parts. The control parameter that capture our attention and has evolutionary origin is mutation. \n",
    "\n",
    "*Intrigue.* Is it in vain that mutation in living beings is so low, of the order of 1 event in $10^{8}$ bases per generation? \n",
    "\n",
    "**Example.** One cannot give to mutation whatever value comes to the mind. To show this, we set a high mutation rate in the following program, which must solve a really humble task.\n",
    "\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "9ea189aa",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Lab: Simple Genetic Algorithm\n",
      "Purpose: solve an instance of the Shakespeare challenge\n",
      "Date of Experiment  = 2026-02-23 11:22:54.930214\n",
      "alphabet =  01\n",
      "target_sequence = 1111111111111111111111111\n",
      "length_of_target_sequence = 25\n",
      "population_size = 200\n",
      "include_clone_populationf7 = True\n",
      "include_mutate_allf7 = True\n",
      "include_crossover_allf7 = False\n",
      "mutation_rate = 0.9\n",
      "print_best_fitness = False\n",
      "Time limit of 3 seconds exceeded. Terminating program.\n"
     ]
    }
   ],
   "source": [
    "## Program High_Mutation_rate_vs_humble_task.py\n",
    "## This program reports the performance of a high mutation rate \n",
    "## on a simple task, which is to evolve a binary string of 25 bits, \n",
    "# with a population of 200 monkeys.\n",
    "\n",
    "import datetime\n",
    "import random\n",
    "import matplotlib.pyplot as plt # Import matplotlib for plotting\n",
    "# target_sequence = 'Methinks it is like a weasel.'\n",
    "# alphabet = 'abcdefghijklmnopqrstuvwxyzABCDEFGHIJKLMNOPQRSTUVWXYZ .,'\n",
    "alphabet = '01' # Binary alphabet, binary strings\n",
    "length_of_target_sequence = 25\n",
    "target_sequence = '1'*length_of_target_sequence  #1111...1 (800 ones)\n",
    "population_size = 200\n",
    "include_clone_populationf7 = True\n",
    "include_mutate_allf7 = True\n",
    "include_crossover_allf7 = False\n",
    "# Default parameter for the genetic algorithm.\n",
    "# mutation_rate = 0.01 # Mutation rate of 1% means that \n",
    "# each site has a 1% chance of being mutated in each generation.\n",
    "mutation_rate = 0.9\n",
    "recombination_rate = 0\n",
    "# alphabet = 'abcdefghijklmnopqrstuvwxyzABCDEFGHIJKLMNOPQRSTUVWXYZ .,'\n",
    "# Boolean flag to print the generation, best chromosome and fitness.\n",
    "# This is the ancestral line of the solution.\n",
    "print_best_fitness = False\n",
    "show_graph = True\n",
    "\n",
    "\n",
    "def print_parametersf7():\n",
    "    print(f\"Lab: Simple Genetic Algorithm\")\n",
    "    print(f\"Purpose: study the performance of a high mutation rate\")\n",
    "    print(f\"Date of Experiment  = {datetime.datetime.now()}\")\n",
    "    print(f\"alphabet =  {alphabet}\")\n",
    "    print(f\"target_sequence = {target_sequence}\")\n",
    "    print(f\"length_of_target_sequence = {length_of_target_sequence}\")\n",
    "    print(f\"population_size = {population_size}\")\n",
    "    print(f\"include_clone_populationf7 = {include_clone_populationf7}\")\n",
    "    print(f\"include_mutate_allf7 = {include_mutate_allf7}\")\n",
    "    print(f\"include_crossover_allf7 = {include_crossover_allf7}\")\n",
    "    if include_mutate_allf7:\n",
    "        print(f\"mutation_rate = {mutation_rate}\")\n",
    "    if include_crossover_allf7:\n",
    "        print(f\"recombination_rate = {recombination_rate}\")\n",
    "    if include_clone_populationf7:\n",
    "        print(f\"print_best_fitness = {print_best_fitness}\")\n",
    "\n",
    "\n",
    "def create_populationf7(population_size, target_sequence, alphabet):\n",
    "    \"\"\"Creates a new population with random chromosomes.\"\"\"\n",
    "    # print(\"create_population8(population_size, target_sequence, alphabet)\")\n",
    "    population = []\n",
    "    for _ in range(population_size):\n",
    "        random_string = ''.join(random.choice(alphabet) for _ in range(len(target_sequence)))\n",
    "        population.append(random_string)\n",
    "    # print(\"initial population\")\n",
    "    # print(population)\n",
    "    return population\n",
    "\n",
    "def calculate_fitnessf7(chromosome, target_sequence):\n",
    "    \"\"\"Calculates the fitness of a chromosome based on its similarity to the target sequence.\"\"\"\n",
    "    #  print(\"\\n *calculate_fitness8(chromosome, target_sequence)\")\n",
    "    fitness = 0\n",
    "    for i in range(len(chromosome)):\n",
    "        if chromosome[i] == target_sequence[i]:\n",
    "            fitness += 1\n",
    "    # print(chromosome, \"  fitness: \", fitness)\n",
    "    return fitness\n",
    "\n",
    "def calculate_all_fitnessf7(population, target_sequence):\n",
    "    # print(\"\\n*calculate_all_fitness8(population, target_sequence)\")\n",
    "    \"\"\"Calculates the fitness of all chromosomes in the population.\"\"\"\n",
    "    fitness_scores = [calculate_fitnessf7(chromosome, target_sequence) for chromosome in population]\n",
    "    # print(\"fitness_scores: \", fitness_scores)\n",
    "    return fitness_scores\n",
    "\n",
    "def select_the_bestf7(population, target_sequence):\n",
    "    \"\"\"Selects the best chromosome for reproduction.\"\"\"\n",
    "    fitness_scores = calculate_all_fitnessf7(population, target_sequence)\n",
    "    best_fitness = max(fitness_scores)\n",
    "    best_chromosome_index = fitness_scores.index(best_fitness)\n",
    "    best_chromosome = population[best_chromosome_index]\n",
    "    # print(\"\\n*select_the_bestf7(population)\")\n",
    "    # print(\"best_fitness = \", best_fitness)\n",
    "    # print(\"The chro = \", best_chromosome )\n",
    "    return best_fitness, best_chromosome\n",
    "\n",
    "def clone_populationf7(best_chromosome, population_size):\n",
    "    \"\"\"Creates a new population by cloning the best chromosome.\"\"\"\n",
    "    return [best_chromosome] * population_size\n",
    "\n",
    "\n",
    "def mutatef7(chromosome, mutation_rate, alphabet):\n",
    "    \"\"\"Mutates a chromosome.\"\"\"\n",
    "    mutated_chromosome_list = list(chromosome)\n",
    "    for i in range(len(mutated_chromosome_list)):\n",
    "        if random.random() < mutation_rate:\n",
    "                mutated_chromosome_list[i] = random.choice(alphabet)\n",
    "    return \"\".join(mutated_chromosome_list)\n",
    "\n",
    "def mutate_allf7(population, mutation_rate, alphabet):\n",
    "    \"\"\"Mutates all chromosomes in the population.\"\"\"\n",
    "    mutated_population = []\n",
    "    for chromosome in population:\n",
    "        mutated_chromosome = mutatef7(chromosome, mutation_rate, alphabet)\n",
    "        mutated_population.append(mutated_chromosome)\n",
    "    return mutated_population\n",
    "\n",
    "def crossoverf7(parent1, parent2, target_sequence, recombination_rate):\n",
    "    \"\"\"Performs crossover between two parent chromosomes.\"\"\"\n",
    "    if random.random() < recombination_rate:\n",
    "        crossover_point = random.randint(0, len(target_sequence))\n",
    "        return parent1[:crossover_point] + parent2[crossover_point:]\n",
    "    else:\n",
    "        return parent1\n",
    "\n",
    "def crossover_allf7(population, target_sequence, recombination_rate):\n",
    "    \"\"\"Performs crossover on all chromosomes in the population.\"\"\"\n",
    "    recombinant_population = []\n",
    "    for i in range(len(population)):\n",
    "        parent1 =  population[i]\n",
    "        parent2 = random.choice(population)\n",
    "        child = crossoverf7(parent1, parent2, target_sequence, recombination_rate)\n",
    "        recombinant_population.append(child)\n",
    "    return recombinant_population\n",
    "\n",
    "\n",
    "\n",
    "def run_one_generationf7(population, target_sequence, mutation_rate, recombination_rate, alphabet):\n",
    "    \"\"\"Runs one generation of the genetic algorithm.\"\"\"\n",
    "    # Calculate fitness scores for the current population\n",
    "    best_fitness, best_chromosome  = select_the_bestf7(population, target_sequence)\n",
    "    # print(f\" best_chromosome {best_chromosome}, best_fitness {best_fitness}\")\n",
    "    # Clone the best to build the new population\n",
    "    new_population = []\n",
    "    if include_clone_populationf7:\n",
    "        new_population = clone_populationf7(best_chromosome, population_size)\n",
    "    if include_mutate_allf7:\n",
    "        new_population = mutate_allf7(new_population, mutation_rate, alphabet)\n",
    "    if include_crossover_allf7:\n",
    "        new_population = crossover_allf7(new_population, target_sequence, recombination_rate)\n",
    "    return best_fitness, best_chromosome, new_population\n",
    "\n",
    "\n",
    "\n",
    "def plot_Best_Fitnessf7(best_fitness_history ):\n",
    "    # Plot the fitness history\n",
    "    plt.plot(best_fitness_history, label='Best Fitness in simulation', color='blue')\n",
    "    plt.axhline(y=length_of_target_sequence, color='red', linestyle='--', linewidth=2)\n",
    "    plt.xlabel('Generation')\n",
    "    plt.ylabel('Best Fitness')  \n",
    "    plt.title('Genetic Algorithm - Fitness over Generations')\n",
    "    plt.grid(True)\n",
    "    plt.legend()\n",
    "    plt.show()\n",
    "\n",
    "\n",
    "def mainf7( target_sequence, mutation_rate, recombination_rate, alphabet):\n",
    "    print_parametersf7()\n",
    "    population = create_populationf7(population_size, target_sequence, alphabet)\n",
    "    # print(population)\n",
    "    best_fitness, best_chromosome = select_the_bestf7(population, target_sequence)\n",
    "    generation = 0\n",
    "    best_fitness_history = [] # List to store best fitness of each generation\n",
    "    M_t = best_fitness # Initial number of solved sites according to simulation results, M_t starts at the best fitness of the initial population\n",
    "    best_fitness_history.append(best_fitness)\n",
    "    if print_best_fitness:\n",
    "        print(\"Generation, best_chromosome and best_fitness, M_t\")\n",
    "    while best_fitness < len(target_sequence):\n",
    "        generation += 1\n",
    "        best_fitness, best_chromosome, population = run_one_generationf7(population, target_sequence, mutation_rate, recombination_rate, alphabet)\n",
    "        \n",
    "        if print_best_fitness:\n",
    "            print(f\" {generation}  {best_chromosome} {best_fitness} {M_t}\")\n",
    "        best_fitness_history.append(best_fitness)\n",
    "\n",
    "    print(f\"\\nTarget sequence matched in generation {generation}\")\n",
    "    print(f\"Final chromosome: {best_chromosome}\")\n",
    "    totalCost = population_size * generation\n",
    "    print(f\"Total cost = population size * number of generations: {totalCost}\")\n",
    "    if show_graph:\n",
    "        plot_Best_Fitnessf7(best_fitness_history)\n",
    "    return best_fitness_history\n",
    "\n",
    "#mainf7( target_sequence, mutation_rate, recombination_rate, alphabet)\n",
    "\n",
    "\n",
    "import time\n",
    "from multiprocessing import Process\n",
    "\n",
    "\n",
    "def long_running_process():\n",
    "    try:\n",
    "        mainf7( target_sequence, mutation_rate, recombination_rate, alphabet)\n",
    "    except KeyboardInterrupt:\n",
    "        print(\"\\nExecution was interrupted!\")\n",
    "    finally:\n",
    "        print(\"Cleaning up resources...\")\n",
    "\n",
    "# Call the long_running_process function\n",
    "\n",
    "\n",
    "def stop_after_timeout(target_function, timeout_seconds):\n",
    "    p = Process(target=target_function)\n",
    "    p.start()\n",
    "    # The main process waits for the child process for 'timeout_seconds'\n",
    "    p.join(timeout_seconds) \n",
    "\n",
    "    if p.is_alive():\n",
    "        print(f\"Time limit of {timeout_seconds} seconds exceeded. Terminating program.\")\n",
    "        p.terminate() # Forcefully stop the process\n",
    "        p.join() # Wait for termination to complete\n",
    "    else:\n",
    "        print(\"Program finished within the time limit.\")\n",
    "\n",
    "#if __name__ == '__main__':\n",
    "    # Run the long_running_task with a 60-second limit\n",
    "infinite_time = 3 \n",
    "stop_after_timeout(long_running_process, infinite_time )"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "b6cd62cb",
   "metadata": {},
   "source": [
    "**Exercise.** Run the previous program with various high values of the mutation rate. Verify or reject the following expectancy: high mutation rates create chaos that Evolution cannot overcome. The program has defined $infinite\\_time = 3$ seconds. You can redefine this value in the pre-last line of code. \n",
    ">\n",
    "> *Answer.* A humble task that must be solved instantaneously needs some few seconds to be executed when the mutation rate is 0.9.\n",
    "\n",
    "**Exercise.** In the previous program, give consecutively diminishing values to mutation and see whether the span of defined values of the cost function augments.\n",
    ">\n",
    "> *Answer.* When mutation consecutively takes on diminishing values, the range of definition of the cost function grows. For a value of $\\mu = 10^{-13}$ the function is defined until $1.5 \\times 10^{13}$ sites. But the cost is not realistic, in fact, the graph of the cost does not look like as an exponential function. \n",
    " \n",
    "- 3. Evolution cannot solve complex problems. \n",
    "  \n",
    "This is contrary to our expectation. Nevertheless, the reality is rather crude: we have simple unconcluded tasks because of lack of time. So, only tested math models can convincingly say that Evolution can solve all problems -if enough time is given. \n",
    "  \n",
    "- 4. The model failed because our concepts are wrong.  \n",
    "\n",
    "Precisely, we have a point to examine. It refers to the negative role of mutation. \n",
    "\n",
    "Mutation is a progressive force when the number of matched sites $M$ is less than mediocrity, but it turns to be retrograde when $M$ is above it. Since our initial condition is always above mediocrity, and Evolution works, then the mutation is always a retrograde force. Now, we ask: Is this detrimental role of mutation compatible with our algorithm in which we always have defined the best as the one with more good points?\n",
    "\n",
    "**Example.** Mutation produces fluctuations, i.e., variability of touched and matched sites. We have assumed that the selection of the fittest implies that Max must pick the best at each step. Let us test this belief with the following cases. \n",
    ">\n",
    "> The initial condition in two chromosomes is 70% of the sites are correct and 30% are wrong. In the first chromosome, fluctuations in mutation affect 10\\% of the sites, and in the second 5\\%. According to our prior conception, the fittest is the first because more sites have been touched, hence more have the opportunity to become right. Let us check this out. Why do we need to carry a test? It is because we know that mutation is a detrimental force above mediocrity.\n",
    ">\n",
    "> *Development.*\n",
    "> \n",
    "> First chromosome: 70\\% of sites were right. 10\\% of 70\\% are touched among those that were right, this is 7\\%. From these, the half become right, 3.5\\%.  Untouched are the 63\\%, and they were all right.  The wrong sites were the 30\\%, from which the 10% will be touched, i.e., 3. The half on them become right, this is 1.5.  \n",
    "> \n",
    "> Adding the percentage of all right sites, we get 3.5 + 63 + 1.5 = 68%. This is less than the original percentage of right sites. The detrimental role of mutation shows its action.\n",
    ">\n",
    "> Second chromosome. 70\\% of sites were right. 5\\% of 70\\% are touched among those that were right, this is 3.5\\%. From these, the half become right, 1.75%.  Untouched are the 66.5\\%, and they were all right.  The wrong sites were the 30\\%, from which the 5% will be touched, i.e., 1.5\\%. The half on them become right, this is 0.75.  \n",
    "> \n",
    "> Adding the percentage of all right sites, we get 1.75 + 66.5 + 0.75 = 69%. This is less than the original percentage of right sites.\n",
    ">\n",
    "> We conclude that the fittest is not that with the greater number of touched sites, but that with the less. This contradicts our previous assumptions.\n",
    "\n",
    "**Exercise.** Decide which chromosome is the fittest when in both chromosome the proportion of right sites is 30\\% and of wrong 70\\%. In the first chromosome, fluctuations in mutation have affected 10\\% of the sites, and in the second 5\\%. \n",
    ">\n",
    "> *Answer.* \n",
    "> \n",
    "> First chromosome: 30\\% of sites were right. 10\\% of 30\\% are touched among those that were right, this 3\\%. From these, the half become right, 1.5\\%.  Untouched are the 27\\%, and they were all right.  The wrong sites were the 70\\%, from which the 10% will be touched, i.e., 7. The half on them become right, this is 3.5.  \n",
    "> \n",
    "> Adding the percentage of all right sites after mutation, we get 1.5 + 27 + 3.5  = 32%. This is greater than the original percentage of right sites.\n",
    ">\n",
    "> Second chromosome. 30\\% of sites were right. 5\\% of 30\\% are touched among those that were right, this is 1.5\\%. From these, the half become right, 0.75%.  Untouched are the 28.5\\%, and they were all right.  The wrong sites were the 70\\%, from which the 5% will be touched, i.e., 3.5\\%. The half on them become right, this is 1.75.  \n",
    "> \n",
    "> Adding the percentage of all right sites, we get 0.75 + 28.5 + 1.75 = 31%. This is greater than the original percentage of right sites.\n",
    ">\n",
    "> We conclude that the fittest is that with the greater number of touched sites.   \n",
    "\n",
    "**Challenge.** An ultrasophisticated biochemical machinery keeps the mutation rate low in present populations of living organisms. Do you consider that this is compatible with our results, that say that Evolution rewards a large mutation rate below mediocrity and a low one above mediocrity? \n",
    "\n",
    "**Practical directive.** We will manage the fluctuations as follows: the number of touched sites will be represented not by the winner but by the underdog, a chromosome with the less number of touched sites. But the number of solved sites will be represented by the winner, that with the maximal number of solved sites. \n",
    "\n",
    "**Exercise.** Convert the previous directive into an easily solvable math model.\n",
    ">\n",
    "> *Answer.* \n",
    "> \n",
    "> We had in the complete model:\n",
    ">>\n",
    ">> $c = 1.29$\n",
    ">>\n",
    ">> $T= $ number of touched sites $ =  \\mu H +  \\sqrt{H \\mu (1 - \\mu) } \\sqrt{c \\ln (m)} $ \n",
    ">>\n",
    ">> We see in $T$ the expected value together with the contribution of MAX\n",
    ">>\n",
    ">> $\\kappa = 1.29$\n",
    ">>\n",
    ">> $p_t = \\frac{M_t}{H}$\n",
    ">> \n",
    ">>  $ r = $ number of untouched sites that were right in the winning chromosome of generation $t$.\n",
    ">>\n",
    ">> $ r =  (H-T)p_t +  \\sqrt{(H-T)p_t(1-p_t)} \\sqrt{\\kappa \\times \\ln (m)} $.\n",
    ">>\n",
    ">> The second term represents the contribution of MAX. \n",
    ">\n",
    "> A direct implementation of the directive results in the *Underdog Model*:\n",
    ">>\n",
    ">> The number of touched sites must be changed, but the number of solved sites among those touched remains equal as before.  \n",
    ">\n",
    ">> $T= $ number of touched sites $ =  \\mu H +  \\lambda_T \\sqrt{H \\mu (1 - \\mu) } \\sqrt{ \\ln (m)} $ \n",
    ">>\n",
    ">> where $\\lambda_T$ is the square root of $c$, but $\\lambda_T$ can take on whatever value, including negatives. In that way, $T$ could represent a number of touched sites less than the expected value, and with less space to be hurt by mutation.\n",
    ">>\n",
    ">> $ r =  (H-T)p_t +  \\lambda_r \\sqrt{(H-T)p_t(1-p_t)} \\sqrt{ \\ln (m)} $.\n",
    ">>\n",
    ">> where $\\lambda_r$ is the square root of $\\kappa$, but $\\lambda_r$ can also be less than 0. \n",
    ">\n",
    "> The problem is that the resultant model is convoluted. To get a flavor of its behavior, we can propose a *Simplified Underdog Model* that we can specify for a fixed concrete number of monkeys:\n",
    ">>\n",
    ">> $T= $ number of touched sites $ =  \\mu H +  \\lambda_T \\sqrt{H \\mu (1 - \\mu) } \\sqrt{ \\ln (m)} $ \n",
    ">>\n",
    "> $T$ is a constant, it adds no trouble to our computing machinery. \n",
    ">\n",
    ">   $ r = $ number of untouched sites that were right in the winning chromosome of generation $t$.\n",
    ">\n",
    "> $ r =  \\epsilon (H-T)p_t $\n",
    "> \n",
    "> Parameters $\\lambda_t$ and $\\epsilon$ can be positive, negative but not zero. The parameter $\\epsilon$ must be preferably less than 1 and positive. If it is negative, Evolution would not work. \n",
    "\n",
    "**Exercise.** Make a full listing of the conditions that define the simplified underdog model, solve and test it, adjust the value of $\\epsilon$ to decide if the model is useful and if the underdog theory is in the right track.\n",
    ">\n",
    "*Answer.* \n",
    "> \n",
    "> The following conditions define the model:\n",
    "> \n",
    ">**************\n",
    "> *Simplified Underdog Model* of the change in the number of matched sites $M$ in the winner chromosome of each generation:\n",
    ">*************\n",
    ">\n",
    "> $c = 1.29$. \n",
    ">\n",
    "> $n = $ length of a subsequence to be matched, depends on context. \n",
    "> \n",
    "> $k = 24.9 n^{-1.18} + 2.53$\n",
    ">\n",
    "> $\\mu = $ mutation rate, constant\n",
    ">\n",
    "> $H = $ length of the target string, total number of sites\n",
    ">\n",
    "> $m = $ number of monkeys or of binomial distributions.\n",
    "> \n",
    "> $M_t = $ number of solved sites at generation $t$\n",
    ">\n",
    "> $I = M_o = $ initial number of matched sites\n",
    "> $ = \\frac{H}{2} +  \\sqrt{\\frac{H}{k}\\ln m  }  $\n",
    ">\n",
    "> $T= $ number of touched sites $ =  \\mu H +  \\lambda_T \\sqrt{H \\mu (1 - \\mu) } \\sqrt{ \\ln (m)} $ \n",
    ">\n",
    ">  $ s = $ number of solved sites among touched $ =  \\frac{T}{2} +  \\sqrt{\\frac{T}{k}\\ln m  }  $. It is a constant.\n",
    "> \n",
    "> $H-T = $  number of untouched sites \n",
    ">\n",
    ">\n",
    "> $p_t = \\frac{M_t}{H}$ proportion of matched sites in the winner chromosome of present generation.\n",
    "> \n",
    ">  $ r = $ number of untouched sites that were right in the winning chromosome of generation $t$.\n",
    ">\n",
    "> $ r =  \\epsilon (H-T)p_t$. The parameter $\\epsilon$ can be greater than 1 (winner) or less than 1 (underdog).\n",
    ">\n",
    "> $M_{t+1} =  s + r = $ prediction for the winner of the next generation\n",
    "\n",
    "********\n",
    "\n",
    "This leads to a recurrence relation that is defined by\n",
    ">\n",
    "> $I = M_o = $ initial number of matched sites\n",
    ">\n",
    ">  $ s = $ number of solved sites among touched $ =  \\frac{T}{2} +  \\sqrt{\\frac{T}{k}\\ln m  }  $. It is a constant.\n",
    "> \n",
    "> $M_{t+1} = r+s =    \\epsilon (H-T)\\frac{M_t}{H} + s=     \\epsilon  \\frac{H-T}{H} M_t + s$\n",
    ">\n",
    "> This relation can be reformulated in abstract terms:\n",
    ">\n",
    "> $M_o= I$, initial condition\n",
    ">\n",
    "> $M_{t+1} = a M_t + b$,  recurrence relation\n",
    ">\n",
    "> with\n",
    ">\n",
    "> $a = \\epsilon \\frac{H-T}{H} $\n",
    ">\n",
    "> $b = s$\n",
    ">\n",
    "> The general term is\n",
    ">\n",
    "> $M(n) = a^nI + (a^{n-1} + \\dots + a + 1) b$\n",
    "\n",
    "\n",
    "In our case, $a =  \\epsilon\\frac{H-T}{H} $. We cannot guarantee this time that $a < 1$. Thus,  limits of $M$ when $n$ grows must be carefully studied. Anyway, \n",
    "\n",
    "$a^{n-1} + \\dots + a + 1 = \\frac{1- a^n}{1-a}$\n",
    "\n",
    "This implies that\n",
    "\n",
    "$M(n) = a^nI + \\frac{1- a^n}{1-a} b$\n",
    "\n",
    "\n",
    "Replacing $a = \\epsilon \\frac{H-T}{H} $ and $b = s$ in the general formula, \n",
    ">\n",
    "> $M(n) = a^nI + \\frac{1- a^n}{1-a} b$\n",
    ">\n",
    "we get\n",
    ">\n",
    "> $M(n) = (\\epsilon \\frac{H-T}{H} )^nI + \\frac{1- (\\epsilon \\frac{H-T}{H} )^n}{1-(\\epsilon \\frac{H-T}{H} )} s$\n",
    ">\n",
    "> with\n",
    ">\n",
    ">  $ s = $ number of solved sites among touched $ =  \\frac{T}{2} +  \\sqrt{\\frac{T}{k}\\ln m  }  $\n",
    ">\n",
    "For the purpose of programming, a system of equations is suitable:\n",
    ">\n",
    "> $\\mu = $ mutation rate\n",
    ">\n",
    "> $c = 1.29$\n",
    ">\n",
    "> $k = 1.5$\n",
    ">\n",
    "> $H$ is the length of the target string \n",
    "> \n",
    "> $m$ is the number of monkeys or of binomial distributions $Bi(H, \\mu)$\n",
    "> \n",
    "> $I = M_o = $ initial number of matched sites\n",
    "> $ = \\frac{H}{2} +  \\sqrt{\\frac{H}{k}\\ln m  }  $\n",
    "> \n",
    ">  $ T= $ number of touched sites $ =  \\mu H +  \\lambda_T \\sqrt{H \\mu (1 - \\mu) } \\sqrt{\\ln (m)} $\n",
    ">\n",
    "> $ s = $ number of solved sites among touched $ =  \\frac{T}{2} +  \\sqrt{\\frac{T}{k}\\ln m  }  $\n",
    "> \n",
    "> $a = \\epsilon  \\frac{H-T}{H} $\n",
    ">  \n",
    ">$b = s$ \n",
    ">\n",
    "> $M(n) = a^nI + \\frac{1- a^n}{1-a} b$\n",
    "\n",
    "To test our simplified underdog model, we can now compare graphically the solution to the last system of equations with a simulation. This is done in the following code.\n",
    "\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "1fea2f35",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Lab: Simple Genetic Algorithm\n",
      "Purpose: solve an instance of the Shakespeare challenge\n",
      "Date of Experiment  = 2026-02-26 10:59:08.830545\n",
      "alphabet =  01\n",
      "target_sequence = 11111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111\n",
      "length_of_target_sequence = 800\n",
      "population_size = 200\n",
      "include_clone_populationf8 = True\n",
      "include_mutate_allf8 = True\n",
      "include_crossover_allf8 = False\n",
      "mutation_rate = 0.01\n",
      "print_best_fitness = False\n",
      "\n",
      "Target sequence matched in generation 422\n",
      "Final chromosome: 11111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111\n",
      "Total cost = population size * number of generations: 84400\n",
      "Parameters of the theoretical model\n",
      "c = 1.29\n",
      "k = 1.5\n",
      "epsilon = 0.99833\n",
      "lambda_T = 0\n",
      "I = 453.1579651807606\n",
      "mu = 0.01\n",
      "H = 800\n",
      "m = 200\n",
      "Generation 0: T = 8.0\n",
      "Generation 0: s = 9.315796518076056\n"
     ]
    },
    {
     "data": {
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",
      "text/plain": [
       "<Figure size 1000x600 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "## Program DuoMutationMax_VS_Solved_Underdog_Model.py\n",
    "# This program compares the maximum number of solved sites \n",
    "# in a generation according to a simulation\n",
    "# with the prediction of a solved underdog model \n",
    "# of the number of matched sites at that generation.\n",
    "# The approximation implements the idea that \n",
    "# the fittest is not chosen at each step. Instead, \n",
    "# a chromosome with a low number of touched sites might do it better.\n",
    "# So, MAX is allowed to play a negative role in the evolution, \n",
    "# by not always choosing the best chromosome,\n",
    "# but a chromosome with a lower number of touched sites, \n",
    "# which might be more efficient in the long run.\n",
    "\n",
    "\n",
    "\n",
    "# SIMULATION\n",
    "\n",
    "# This part is based on the code of the program \n",
    "# Variability_in_the_number_of_touched_sites.py\n",
    "\n",
    "import datetime\n",
    "import random\n",
    "import matplotlib.pyplot as plt # Import matplotlib for plotting\n",
    "# target_sequence = 'Methinks it is like a weasel.'\n",
    "# alphabet = 'abcdefghijklmnopqrstuvwxyzABCDEFGHIJKLMNOPQRSTUVWXYZ .,'\n",
    "alphabet = '01' # Binary alphabet, binary strings\n",
    "length_of_target_sequence = 800\n",
    "target_sequence = '1'*length_of_target_sequence  #1111...1 (800 ones)\n",
    "population_size = 200\n",
    "include_clone_populationf8 = True\n",
    "include_mutate_allf8 = True\n",
    "include_crossover_allf8 = False\n",
    "mutation_rate = 0.01\n",
    "recombination_rate = 0\n",
    "# alphabet = 'abcdefghijklmnopqrstuvwxyzABCDEFGHIJKLMNOPQRSTUVWXYZ .,'\n",
    "# Boolean flag to print the generation, best chromosome and fitness.\n",
    "# This is the ancestral line of the solution.\n",
    "print_best_fitness = False\n",
    "\n",
    "\n",
    "\n",
    "\n",
    "def print_parametersf8():\n",
    "    print(f\"Lab: Simple Genetic Algorithm\")\n",
    "    print(f\"Purpose: solve an instance of the Shakespeare challenge\")\n",
    "    print(f\"Date of Experiment  = {datetime.datetime.now()}\")\n",
    "    print(f\"alphabet =  {alphabet}\")\n",
    "    print(f\"target_sequence = {target_sequence}\")\n",
    "    print(f\"length_of_target_sequence = {length_of_target_sequence}\")\n",
    "    print(f\"population_size = {population_size}\")\n",
    "    print(f\"include_clone_populationf8 = {include_clone_populationf8}\")\n",
    "    print(f\"include_mutate_allf8 = {include_mutate_allf8}\")\n",
    "    print(f\"include_crossover_allf8 = {include_crossover_allf8}\")\n",
    "    if include_mutate_allf8:\n",
    "        print(f\"mutation_rate = {mutation_rate}\")\n",
    "    if include_crossover_allf8:\n",
    "        print(f\"recombination_rate = {recombination_rate}\")\n",
    "    if include_clone_populationf8:\n",
    "        print(f\"print_best_fitness = {print_best_fitness}\")\n",
    "\n",
    "\n",
    "def create_populationf8(population_size, target_sequence, alphabet):\n",
    "    \"\"\"Creates a new population with random chromosomes.\"\"\"\n",
    "    # print(\"create_population8(population_size, target_sequence, alphabet)\")\n",
    "    population = []\n",
    "    for _ in range(population_size):\n",
    "        random_string = ''.join(random.choice(alphabet) for _ in range(len(target_sequence)))\n",
    "        population.append(random_string)\n",
    "    # print(\"initial population\")\n",
    "    # print(population)\n",
    "    return population\n",
    "\n",
    "def calculate_fitnessf8(chromosome, target_sequence):\n",
    "    \"\"\"Calculates the fitness of a chromosome based on its similarity to the target sequence.\"\"\"\n",
    "    #  print(\"\\n *calculate_fitness8(chromosome, target_sequence)\")\n",
    "    fitness = 0\n",
    "    for i in range(len(chromosome)):\n",
    "        if chromosome[i] == target_sequence[i]:\n",
    "            fitness += 1\n",
    "    # print(chromosome, \"  fitness: \", fitness)\n",
    "    return fitness\n",
    "\n",
    "def calculate_all_fitnessf8(population, target_sequence):\n",
    "    # print(\"\\n*calculate_all_fitness8(population, target_sequence)\")\n",
    "    \"\"\"Calculates the fitness of all chromosomes in the population.\"\"\"\n",
    "    fitness_scores = [calculate_fitnessf8(chromosome, target_sequence) for chromosome in population]\n",
    "    # print(\"fitness_scores: \", fitness_scores)\n",
    "    return fitness_scores\n",
    "\n",
    "def select_the_bestf8(population, target_sequence):\n",
    "    \"\"\"Selects the best chromosome for reproduction.\"\"\"\n",
    "    fitness_scores = calculate_all_fitnessf8(population, target_sequence)\n",
    "    best_fitness = max(fitness_scores)\n",
    "    best_chromosome_index = fitness_scores.index(best_fitness)\n",
    "    best_chromosome = population[best_chromosome_index]\n",
    "    # print(\"\\n*select_the_bestf8(population)\")\n",
    "    # print(\"best_fitness = \", best_fitness)\n",
    "    # print(\"The chro = \", best_chromosome )\n",
    "    return best_fitness, best_chromosome\n",
    "\n",
    "def clone_populationf8(best_chromosome, population_size):\n",
    "    \"\"\"Creates a new population by cloning the best chromosome.\"\"\"\n",
    "    return [best_chromosome] * population_size\n",
    "\n",
    "\n",
    "def mutatef8(chromosome, mutation_rate, alphabet):\n",
    "    \"\"\"Mutates a chromosome.\"\"\"\n",
    "    mutated_chromosome_list = list(chromosome)\n",
    "    for i in range(len(mutated_chromosome_list)):\n",
    "        if random.random() < mutation_rate:\n",
    "                mutated_chromosome_list[i] = random.choice(alphabet)\n",
    "    return \"\".join(mutated_chromosome_list)\n",
    "\n",
    "def mutate_allf8(population, mutation_rate, alphabet):\n",
    "    \"\"\"Mutates all chromosomes in the population.\"\"\"\n",
    "    mutated_population = []\n",
    "    for chromosome in population:\n",
    "        mutated_chromosome = mutatef8(chromosome, mutation_rate, alphabet)\n",
    "        mutated_population.append(mutated_chromosome)\n",
    "    return mutated_population\n",
    "\n",
    "def crossoverf8(parent1, parent2, target_sequence, recombination_rate):\n",
    "    \"\"\"Performs crossover between two parent chromosomes.\"\"\"\n",
    "    if random.random() < recombination_rate:\n",
    "        crossover_point = random.randint(0, len(target_sequence))\n",
    "        return parent1[:crossover_point] + parent2[crossover_point:]\n",
    "    else:\n",
    "        return parent1\n",
    "\n",
    "def crossover_allf8(population, target_sequence, recombination_rate):\n",
    "    \"\"\"Performs crossover on all chromosomes in the population.\"\"\"\n",
    "    recombinant_population = []\n",
    "    for i in range(len(population)):\n",
    "        parent1 =  population[i]\n",
    "        parent2 = random.choice(population)\n",
    "        child = crossoverf8(parent1, parent2, target_sequence, recombination_rate)\n",
    "        recombinant_population.append(child)\n",
    "    return recombinant_population\n",
    "\n",
    "\n",
    "\n",
    "def run_one_generationf8(population, target_sequence, mutation_rate, recombination_rate, alphabet):\n",
    "    \"\"\"Runs one generation of the genetic algorithm.\"\"\"\n",
    "    # Calculate fitness scores for the current population\n",
    "    best_fitness, best_chromosome  = select_the_bestf8(population, target_sequence)\n",
    "    # print(f\" best_chromosome {best_chromosome}, best_fitness {best_fitness}\")\n",
    "    # Clone the best to build the new population\n",
    "    new_population = []\n",
    "    if include_clone_populationf8:\n",
    "        new_population = clone_populationf8(best_chromosome, population_size)\n",
    "    if include_mutate_allf8:\n",
    "        new_population = mutate_allf8(new_population, mutation_rate, alphabet)\n",
    "    if include_crossover_allf8:\n",
    "        new_population = crossover_allf8(new_population, target_sequence, recombination_rate)\n",
    "    return best_fitness, best_chromosome, new_population\n",
    "\n",
    "\n",
    "\n",
    "\n",
    "\n",
    "def mainf8( target_sequence, mutation_rate, recombination_rate, alphabet):\n",
    "    print_parametersf8()\n",
    "    population = create_populationf8(population_size, target_sequence, alphabet)\n",
    "    # print(population)\n",
    "    best_fitness, best_chromosome = select_the_bestf8(population, target_sequence)\n",
    "    generation = 0\n",
    "    best_fitness_history = [] # List to store best fitness of each generation\n",
    "    best_fitness_history.append(best_fitness)\n",
    "    if print_best_fitness:\n",
    "        print(\"Generation, best_chromosome and best_fitness, M_t\")\n",
    "    while best_fitness < 1.0 * len(target_sequence):\n",
    "        generation += 1\n",
    "        best_fitness, best_chromosome, population = run_one_generationf8(population, target_sequence, mutation_rate, recombination_rate, alphabet)        \n",
    "        if print_best_fitness:\n",
    "            print(f\" {generation}  {best_chromosome} {best_fitness}\")\n",
    "        best_fitness_history.append(best_fitness)    \n",
    "    print(f\"\\nTarget sequence matched in generation {generation}\")\n",
    "    print(f\"Final chromosome: {best_chromosome}\")\n",
    "    totalCost = population_size * generation\n",
    "    print(f\"Total cost = population size * number of generations: {totalCost}\")\n",
    "    return generation, best_fitness_history\n",
    "\n",
    "generation, best_fitness_history =  mainf8( target_sequence, mutation_rate, recombination_rate, alphabet)\n",
    "\n",
    "############################\n",
    "\n",
    "# UNDERDOG MODEL\n",
    "\n",
    "# Program Theoretical_model.py\n",
    "# This program implements the theoretical underdog model,\n",
    "# in which MAX plays a negative role in some steps of the evolution,\n",
    "# and positive on others, by not always choosing the best chromosome.\n",
    "\n",
    "\n",
    "\n",
    "import numpy as np\n",
    "import matplotlib.pyplot as plt\n",
    "\n",
    "# Definition of parameters for the underdog model\n",
    "\n",
    "n_generations = int(3*generation) # number of generations to make predictions by the model\n",
    "\n",
    "#$c = 1.29$. \n",
    "c = 1.29\n",
    "k = 1.5\n",
    "# $\\mu = $ mutation rate, constant\n",
    "mu = mutation_rate   # Example mutation rate\n",
    "#$H = $ length of the target string, total number of sites\n",
    "H = length_of_target_sequence \n",
    "#$m = $ number of monkeys or of binomial distributions.\n",
    "m = population_size\n",
    "#$M_t = $ number of solved sites at generation $t$\n",
    "#$M_o = I = $ initial number of matched sites\n",
    "#$ = \\frac{H}{2} +  \\sqrt{\\frac{H}{k}\\ln m  }  $\n",
    "I = H / 2 + ((H / k) * np.log(m)) ** 0.5\n",
    "\n",
    "\n",
    "lambda_T = 0 # This parameter allows to adjust the number of touched sites T, by multiplying the second term of the formula of T, which is the variability in the number of touched sites.\n",
    "epsilon = 0.99833 # This parameter allows to adjust the value of a, by multiplying\n",
    "###\n",
    "#$T= $ number of touched sites $ =  \\mu H +  \\sqrt{H \\mu (1 - \\mu) } \\sqrt{c \\ln (m)} $ \n",
    "def T(mu, H, c, m):\n",
    "    return mu * H + lambda_T *(H * mu * (1 - mu)) ** 0.5 * ( np.log(m)) ** 0.5\n",
    "\n",
    "#  $ s = $ number of solved sites among touched $ =  \\frac{T}{2} +  \\sqrt{\\frac{T}{k}\\ln m  }  $\n",
    "def s(T, m):\n",
    "    return T / 2 + ((T / k ) * np.log(m)) ** 0.5\n",
    "\n",
    "#$a = \\epsilon  \\frac{H-T}{H} $\n",
    "a = epsilon* (H - T(mu, H, c, m)) / H \n",
    "#$b = s$ \n",
    "b = s(T(mu, H, c, m), m)\n",
    "#$M(n) = a^nI + \\frac{1- a^n}{1-a} b$\n",
    "def M_n(n, a, I, b):\n",
    "    if n == 0:\n",
    "        return I \n",
    "    else:\n",
    "        return (a ** n) * I + ((1 - a ** n) / (1 - a)) * b\n",
    "\n",
    "print(\"Parameters of the theoretical model\")\n",
    "print(f\"c = {c}\")\n",
    "print(f\"k = {k}\")\n",
    "print(f\"epsilon = {epsilon}\")\n",
    "print(f\"lambda_T = {lambda_T}\")\n",
    "print(f\"I = {I}\")\n",
    "print(f\"mu = {mu}\")\n",
    "print(f\"H = {H}\")\n",
    "print(f\"m = {m}\")\n",
    "\n",
    "M_values = []\n",
    "m_value  = I\n",
    "n = 0\n",
    "T_value = T(mu, H, c, m)\n",
    "print(f\"Generation {n}: T = {T_value}\")\n",
    "s_value = s(T_value,  m)\n",
    "print(f\"Generation {n}: s = {s_value}\")\n",
    "# Generate a range of generations\n",
    "for n in range(n_generations):\n",
    "    m_value =  M_n(n, a, I, b)\n",
    "    #if m_value > H:\n",
    "    #    m_value = H\n",
    "    M_values.append(m_value)\n",
    "    #print(f\"Generation {n}: M(n) = {m_value}\")\n",
    "\n",
    "###########\n",
    "\n",
    "# PLOT FUNCTIONS\n",
    "\n",
    "plt.figure(figsize=(10, 6))\n",
    "# Red line for the total number of sites (H)\n",
    "plt.axhline(y=H, color='red', linestyle='--', linewidth=2, label=f'Total number of sites {H}')\n",
    "plt.plot(best_fitness_history, label='Best Fitness in simulation', color='blue')\n",
    "plt.plot(M_values, label = 'Predicted number of matched sites by the underdog model', color='green')\n",
    "plt.axhline(y=length_of_target_sequence, color='red', linestyle='--', linewidth=2)\n",
    "\n",
    "plt.xlabel('Generation (n)')\n",
    "plt.ylabel('Number of Matched Sites (M)')\n",
    "plt.title('Number of Matched Sites in GA, Simulation vs Solved Model')\n",
    "plt.grid(True)\n",
    "plt.legend()\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "56156160",
   "metadata": {},
   "source": [
    "*Comments.* For a task given by $H= $ length_of_target_sequence = 800, the following parameters produced a fitting that was good with an error of the 5\\% for 90% of the task. After that, the graph overgrows:\n",
    ">\n",
    "> c = 1.29\n",
    "> \n",
    "> k = 1.5\n",
    "> \n",
    "> epsilon = 0.99833\n",
    "> \n",
    "> lambda\\_T = 0\n",
    "\n",
    "> The same setting of parameters produced a good fit for $H=400$ but the number of solved sites did not converge to $H$ but overflowed.  For $H= 1000$ the fitting was regular, with an error of 7\\% until 90\\% of the task.\n",
    ">\n",
    "> The fact that $\\epsilon$ is less than 1 and that $\\lambda_T$ is zero is compatible with the insinuation that Evolution is not fueled by the best but by a populational combination that includes the ordinary and the underdog. \n",
    "\n",
    "*Generalization.* We believe that one can fit with constant parameters the behavior of Evolution for specific tasks. But, to fit a general task, it is mandatory to use variable parameters and success is not guaranteed.\n",
    "\n",
    "*Criticism.* Our semi-empirical approach needs so many operative parameters that it is similar to an old patient that cannot walk alone, so it uses a cane, and two after a year. Later, he requires external provision of oxygen, plus nursing care.\n",
    "\n",
    "*ADMINISTRATIVE DIRECTION.* This game with fine-tuning of parameters is a never ending adventure. It forces us to carry out a separate study that includes the search for a better conceptualization that sheds more light over our path. In that way, we might formulate more intuitive and natural models.\n",
    "\n",
    "# CONCLUSION\n",
    "\n",
    "We are lost in the jungle. Not far away, you can hear the monkeys clattering. We imagined that MAX, which encodes the selection of the fittest, will rapidly solve all of our troubles. But, this is false. In fact, we ended considering the possibility that the solution to our conundrum of why Evolution works does not come from the best but from the underdog. We do not know what really happens. We are very intrigued. Anyway, one of our problems is that Evolution demands too much time to solve rather simple tasks. So, we do not see that Evolution could solve the MAX-Rocket challenge, which consists in skyrocketing the capabilities of MAX to battle complexity. \n",
    "\n",
    "\n"
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