{
 "cells": [
  {
   "cell_type": "markdown",
   "id": "70fbceca",
   "metadata": {},
   "source": [
    ">> LA Evolución TODOPODEROSA\n",
    ">>>>\n",
    ">>> José Rodríguez\n",
    ">>>>\n",
    ">>> jose@ejristos.com\n",
    ">>>>\n",
    ">>> 9 Mayo 2026.\n",
    ">>>>\n",
    ">>> Bogotá, Colombia.\n",
    "\n",
    "**Resumen**\n",
    "\n",
    "Según la Ciencia, somos un producto de la Evolución. La Ciencia consiste en poner a prueba lo que creemos. En la presente contribución, probamos esta afirmación de la siguiente manera: si la Evolución es la causa de nuestra existencia, resolviendo innumerables problemas matemáticos terribles, pero sin dejar rastro de su batalla contra la complejidad, entonces el Método Científico tiene tres predicciones. En primer lugar, podemos construir un mundo virtual, en el que los organismos son cadenas de caracteres que codifican para soluciones provisionales a un problema matemático. Segundo: la Evolución conducirá  a una solución perfecta. Tercero: los recursos utilizados serán mínimos. En nuestros términos, el Método Científico predice que la Evolución puede usarse como un oráculo todopoderoso. Aquí, la Evolución se compone de MAX (selección del más apto y posterior clonación), mutación y recombinación. También se consideran algunas variantes. \n",
    " "
   ]
  },
  {
   "cell_type": "markdown",
   "id": "e272a950",
   "metadata": {},
   "source": [
    "# INTRODUCCIÓN\n",
    "\n",
    "Según la Ciencia, somos un producto de la Evolución. \n",
    "\n",
    "Las afirmaciones científicas deben ser probadas -si tan solo es posible.\n",
    "\n",
    "En la presente contribución, ponemos a prueba  de la siguiente manera la afirmación de que la Evolución es nuestro creador:\n",
    ">\n",
    "> Si la Evolución es la causa de nuestra existencia, resolviendo innumerables problemas matemáticos terribles pero sin dejar rastro de su batalla contra la complejidad, entonces podemos modelarla para resolver perfecta y fácilmente problemas matemáticos tan complejos como queramos. En resumen, el Método Científico predice que la Evolución puede ser utilizada como un oráculo todopoderoso.\n",
    "\n",
    "**Ejercicio.** Resuelve la siguiente objeción a la afirmación mencionada:\n",
    ">\n",
    "> La Evolución ha dejado claramente infinidad de huellas en su batalla contra la complejidad. Por ejemplo, antes del hombre, tenemos toda una cadena de organismos más simples. Comencemos con el mono, y antes del mono tenemos cuádrupedos, antes de ellos peces, antes de ellos microorganismos con mitocondrias, y antes que eso, bacterias simples. Así, la Evolución puede resolver problemas pero deja una clara y amplia huella de su batalla contra la complejidad. \n",
    ">\n",
    "> *Respuesta.* Véase más abajo. \n",
    "\n",
    "\n",
    "Hemos estado estudiando la Evolución sin recombinación, pero para usarla como un oráculo, necesitamos la Evolución con todo su poder, que consiste en ciclos de *selección del más apto + reproducción + mutación + recombinación*. Este modelo se llama Algoritmo Genético (AG). Tiene muchas variantes. Hemos utilizado solo una de ellas, en el que sólo lo más adecuado se reproduce para crear la próxima generación, pero aquí, cada sujeto puede reproducirse según su desempeño. Esta nueva variante es autoconsistente, en el sentido de que no mata la variabilidad existente para comenzar de nuevo a construirla. Creemos que esta variante es muy adecuada para tareas muy complejas. \n",
    "\n",
    "Para probar la Evolución como un Oráculo, debemos darle un problema. Nuestro problema es encontrar la línea que mejor represente un conjunto de puntos en el plano. Esta es la línea de regresión, en la terminología matemática. Si la Evolución puede resolver este problema, la desafiamos con el polinomio de regresión del quinto grado de un conjunto de 6 puntos (estos deben ser cuidadosamente elegidos).  \n",
    "\n",
    "Nuestra motivación para estudiar este problema es que necesitamos especificar los valores óptimos para un grupo de parámetros de un modelo matemático. Ya tenemos una asignación que hemos logrado mediante Evolución rudimentaria. Pero, dado que la Evolución es un maestro en la Evolución, debemos investigar lo buena que es como oráculo.  Nuestro modelo matemático que tiene los parámetros a especificar captura el comportamiento del  Dúo Mutación-MAX, que consiste en ciclos de *selección del más apto + reproducción del más apto + mutación*.  \n"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "73954b7b",
   "metadata": {},
   "source": [
    "# EL ORÁCULO\n",
    "\n",
    "Vamos a especificar algunos detalles del AG, nuestro oráculo, con el que trabajaremos. \n",
    "\n",
    "Nuestro problema es especificar los parámetros de una línea o de un polinomio. Entonces, generamos una población de vectores, conjuntos numerados, de dos números reales, un número para cada parámetro. Para medir la idoneidad del vector, conectamos los dos números al modelo y lo ejecutamos, medimos el error de la predicción subsiguiente con respecto a lo observado, y el mejor vector es aquel con menos error. Para un problema de regresión, el error mínimo esperado es cero. Por lo tanto, la aptitud es el error, que se debe minimizar. Debemos resolver una desventaja menor: \n",
    "\n",
    "**Ejercicio.** Resuelve el siguiente problema: \n",
    ">\n",
    "> Nosotros, junto con nuestros AGs, estamos acostumbrados a asociar lo mejor con la puntuación más alta que debe maximizarse, y no con la menor que debe minimizarse.  ¿Qué hacer con el error?\n",
    ">\n",
    "> *Respuesta.* Podemos redefinir el fitness o aptitud como $f = k - error$, donde $k$ se elige de tal manera que $f$ nunca sea negativa. Por lo tanto, cuando el error es cero, $f = k$ y si el error crece, la aptitud $f$ disminuye. Se puede tomar la constante $k$ como el error máximo posible. O, simplemente, seguimos con el error para minimizarlo. \n",
    "\n",
    "Otro problema técnico es el siguiente: \n",
    "\n",
    "**Ejercicio.** La Evolución funciona con cadenas de caracteres, pero el error debe darse en números.  ¿Cómo se debe implementar la comunicación y la comprensión entre estos dos tipos de datos? \n",
    ">\n",
    "> *Respuesta.* Para convertir un AG en el oráculo necesario, necesitamos diseñar una interfaz que relacione cadenas con números, al derecho y al revés. El paso de números a cadenas se realiza mediante un codificador, y de vuelta por un decodificador.\n",
    "\n",
    "Necesitamos desarrollar un codificador y un decodificador para nuestro problema actual. \n",
    "\n",
    "**Ejemplo.**  Pensemos qué debemos hacer para obtener el número codificado por la cadena $\"34,765\"$. Una cadena está compuesta de caracteres, no de números. Los caracteres se pueden concatenar, no añadir. A su vez, se pueden añadir números, no concatenar.\n",
    ">\n",
    "> Cada carácter representa un dígito, y para transformar un carácter en un dígito, se puede invocar una función apropiada de Python. Los números vienen en base diez.\n",
    "> \n",
    "> Por lo tanto, si ya hemos transformado todos los caracteres en números, el número asociado a $\"34.765\"$ es \n",
    ">\n",
    "> $3 \\times 10 + 4 + 7 \\times 0.1 + 6 \\times 0.01 + 5 \\times 0.001 = 30 + 4 + 0.7 + 0.06 + 0.005 = 34.765$ \n",
    "\n",
    "**Ejercicio.** Desarrollar o investigar el código de Python para un decodificador general que produzca el número codificado por una cadena de dígitos con un punto en cualquier lugar. \n",
    ">\n",
    "> *Respuesta.* El código de Python para un decodificador es sorprendentemente simple:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "18c91737",
   "metadata": {},
   "outputs": [],
   "source": [
    "#program decoder.py\n",
    "\n",
    "number_as_string = \"12.3456789\"\n",
    "\n",
    "def decoder(s):\n",
    "    ''' The input is a number as string, outputs the number as a float. '''\n",
    "    return float(s)\n",
    "\n",
    "r = decoder(number_as_string)\n",
    "\n",
    "print(\"The string is \" + number_as_string)\n",
    "print(\"The number is \", r)\n",
    "\n",
    "print(\"Proof that we have a number:\")\n",
    "print(\"number + 87.654321 is \",  r + 87.654321)\n",
    "print(\"The expected answer is 99.999999\")"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "fff7ef69",
   "metadata": {},
   "source": [
    "**Ejercicio.** Ejecuta el programa anterior y verifica que recupera un número del número escrito como cadena. \n",
    ">\n",
    "> *Respuesta.* Está bien.\n",
    "\n",
    "*Comentario.* Los números reales o flotantes de Python son un poco complicados. Esto significa que se definen como un pequeño error. Es por eso que todos los procedimientos matemáticos deben ser tolerables y estables ante errores minúsculos. Esa es una razón por la cual no se permite la división por cero.\n",
    "\n",
    "**Ejercicio.** Desarrollar el código para un codificador de números en cadenas.\n",
    ">\n",
    "> *Respuesta.* El siguiente programa prueba un codificador"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "a3c5f2ac",
   "metadata": {},
   "outputs": [],
   "source": [
    "#program encoder.py\n",
    "\n",
    "float_num = 12.3456789\n",
    "\n",
    "def numberTostring(r):\n",
    "    ''' The input is a number as a float. It outputs the number as a string. '''\n",
    "    return str(r)\n",
    "\n",
    "s = numberTostring(float_num)\n",
    "print(\"The string is \", s)\n",
    "print(\"Proof that we have a string\")\n",
    "print(\"s + isString = \", s+ \"isString\")\n",
    "print(\"The expected output is 12.3456789isString\")"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "66a118ab",
   "metadata": {},
   "source": [
    "**Ejercicio.** Ejecuta el programa anterior y verifica que convierte un número en una cadena.\n",
    "\n",
    "*Respuesta.* Está bien.\n",
    "\n",
    "*Observación.* El operador $+$ entre cadenas produce concatenación, pero entre números produce adición. \n",
    "\n",
    "Ahora, debemos enfrentar un problema terrible. \n",
    "\n",
    "**Ejercicio.** Demuestra que un AG que utiliza los codificadores y decodificadores mencionados está condenado a fallar. Propón una solución.\n",
    ">\n",
    "> *Respuesta.* Usamos recombinación, y esta produce cadenas que no se pueden interpretar como números. Ejemplo: consideremos las dos cadenas\n",
    "> \n",
    "> 1.2345  \n",
    "> 678.90\n",
    "> \n",
    "> Un producto de la recombinación podría ser\n",
    ">\n",
    "> 1.2.90\n",
    ">\n",
    "> No hay ningún número directamente asociado a esta cadena. Nuestra solución para este error es la siguiente.\n",
    "\n",
    "## Nuestra codificación\n",
    "\n",
    "Necesitamos total libertad para trabajar con números flotantes. Estos tienen un signo, varios dígitos con un punto que flota en cualquier lugar. Consideraremos un número con la misma estructura, digamos, $ \\pm 12,34567890$. \n",
    "\n",
    "En nuestra cadena de codificación, el primer carácter está reservado para el signo. Si el dígito codificado es par, el signo es más; si es impar, el signo es menos. El segundo carácter codifica un dígito que debe interpretarse como el espacio reservado para la posición del punto. El subconjunto con el resto de letras es el número sin signo ni punto. Si el segundo carácter, interpretado como un número es $r$, multiplicamos el número por $10^{-r}$.\n",
    "\n",
    "**Ejemplo.** La cadena \"32567\" codifica para un número. El primer carácter es 3, que, interpretado como número, es impar, por lo que el signo del número es menos. El segundo carácter es 2, que codifica la posición del punto. El resto de los caracteres representa el número 567. Así, el número codificado es \n",
    ">\n",
    "> $-567 \\times 10 {-2} = -5,67$.\n",
    ">\n",
    "> Veamos si hemos resuelto el problema con la recombinación. Los números \n",
    "> \n",
    "> 1.2345\n",
    "> \n",
    "> -678,90\n",
    "> \n",
    "> están codificados como las cadenas\n",
    "> \n",
    "> 2412345\n",
    "> \n",
    "> 1267890\n",
    ">\n",
    "> \n",
    "> Los productos de la recombinación y los números asociados pueden ser\n",
    ">\n",
    "> 2417890 $ \\rightarrow $ 1,7890 \n",
    "> \n",
    "> 2267890 $\\rightarrow $ 678.90\n",
    "> \n",
    "> 1412345 $ \\rightarrow $ -1.2345\n",
    ">\n",
    "> Perfecto. La recombinación que tenemos en mente es demasiado simple como para causar problemas. Lo que queda por hacer es desarrollar nuestro propio decodificador:\n",
    "\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "77605319",
   "metadata": {},
   "outputs": [],
   "source": [
    "#Program ourDecoder.py\n",
    "\n",
    "def decoder(s):\n",
    "    ''' The input is a number as string, outputs the number as a float. '''\n",
    "    \n",
    "    l = len(s)\n",
    "    # The first char encodes for the sign, \n",
    "    sign = 1\n",
    "    if  float(s[0]) % 2 == 1:\n",
    "        sign = -1\n",
    "    # The second char encodes for the position of the decimal point,\n",
    "    d = float(s[1])\n",
    "    # The remaining chars encode for the number itself, \n",
    "    # without the decimal point nor sign.\n",
    "    n = float(s[2:l])\n",
    "    return sign * (n * (10**-d))\n",
    "\n",
    "# Tests\n",
    "\n",
    "number_as_string = \"2417890\"\n",
    "print(\"String = \" + number_as_string)\n",
    "r = decoder(number_as_string)\n",
    "print(\"Number = \" , r )\n",
    "print(\"The expected answer is 1.789\")\n",
    "print()\n",
    "\n",
    "number_as_string = \"2267890\"\n",
    "print(\"String = \" + number_as_string)\n",
    "r = decoder(number_as_string)\n",
    "print(\"Number = \" , r )\n",
    "print(\"The expected answer is 678.90\")\n",
    "print()\n",
    "\n",
    "number_as_string = \"1412345\"\n",
    "print(\"String = \" + number_as_string)\n",
    "r = decoder(number_as_string)\n",
    "print(\"Number = \" , r )\n",
    "print(\"The expected answer is -1.2345\")\n",
    "print()\n",
    "\n",
    "\n",
    "number_as_string = \"123456789\"\n",
    "print(\"String = \" + number_as_string)\n",
    "r = decoder(number_as_string)\n",
    "print(\"Number = \" , r )\n",
    "print(\"The expected answer is -34567.89\")\n",
    "print()\n"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "84b9eeeb",
   "metadata": {},
   "source": [
    "**Ejercicio.** Ejecuta el programa anterior y verifica que decodifica correctamente las cadenas en números.\n",
    ">\n",
    "> *Respuesta.* Está bien.\n",
    "\n",
    "**Desafío.** Prueba si el decodificador propuesto en el programa anterior es compatible con la recombinación.\n",
    "\n",
    "**Ejercicio.** Desarrollar el codificador correspondiente al decodificador recién desarrollado. La entrada debe ser un número, la salida una cadena, y debe deshacer el trabajo del decodificador.\n",
    ">\n",
    "> *Respuesta.* Nuestro codificador está dentro de un programa a continuación. \n",
    "\n",
    "**Ejemplo.** Veamos un programa completo que utiliza la Evolución para especificar un parámetro, la pendiente de una línea en el plano que pasa por el origen. La línea debe minimizar el error cuadrático total generado por un conjunto de puntos. Elegimos los puntos para hacer que la línea resultante esté cerca de la producida por la regresión lineal."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "1d3a16c3",
   "metadata": {},
   "outputs": [],
   "source": [
    "# Program lineOfMinimalError.py\n",
    "# This program uses a genetic algorithm to find the line \n",
    "# that best fits a set of points.\n",
    "# The line passes through the origin\n",
    "# and its slope is represented by a chromosome, \n",
    "# which is a string of digits.\n",
    "# The error of a chromosome is the sum of the vertical quadratic distances \n",
    "# of the points to the line it encodes.\n",
    "# The fitness of a chromosome is K - error, \n",
    "# where K is a constant that is larger than the maximum possible error.\n",
    "# The Genetic algorithm must maximize the fitness, \n",
    "# which is equivalent to minimizing the error.\n",
    "# Developed with the assistance of the AI of Visual Studio Code.\n",
    "# An old version of a GA developed with the help of Gemini was reused and updated.\n",
    "\n",
    "from datetime import datetime, timedelta\n",
    "import time\n",
    "import random\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",
    "percentageOfTask = 1.0\n",
    "\n",
    "xArray = [1, 2, 3, 4, 5, 6]\n",
    "yArray = [2, 1, 4, 3, 6, 5]\n",
    "\n",
    "alphabet = '0123456789'\n",
    "length_of_chromosomes = 7\n",
    "population_size = 200\n",
    "# Include cloning of the fittest\n",
    "include_clone_populationj1 = True\n",
    "# Include mutation\n",
    "include_mutate_allj1 = True\n",
    "# Include recombination\n",
    "include_crossover_allj1 = True\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",
    "def print_parametersj1():\n",
    "    print(f\"Lab: la Evolución finds the line of minimal error\")\n",
    "    print(f\"Purpose: To find the slope of a line that best fits a set of points using a genetic algorithm.\")\n",
    "    print(f\"Date of Experiment  = {datetime.datetime.now()}\")\n",
    "    print(f\"alphabet =  {alphabet}\")\n",
    "    print(f\"population_size = {population_size}\")\n",
    "    print(f\"include_clone_populationj1 = {include_clone_populationj1}\")\n",
    "    print(f\"include_mutate_allj1 = {include_mutate_allj1}\")\n",
    "    print(f\"include_crossover_allj1 = {include_crossover_allj1}\")\n",
    "    if include_mutate_allj1:\n",
    "        print(f\"mutation_rate = {mutation_rate}\")\n",
    "    if include_crossover_allj1:\n",
    "        print(f\"recombination_rate = {recombination_rate}\")\n",
    "    if include_clone_populationj1:\n",
    "        print(f\"print_best_fitness = {print_best_fitness}\")\n",
    "\n",
    "\n",
    "def create_populationj1(population_size, length_of_chromosomes, alphabet):\n",
    "    \"\"\"Creates a new population with random chromosomes.\"\"\"\n",
    "    # print(\"create_populationj1(population_size, target_sequence, alphabet)\")\n",
    "    population = []\n",
    "    for _ in range(population_size):\n",
    "        random_string = ''.join(random.choice(alphabet) for _ in range(length_of_chromosomes))\n",
    "        population.append(random_string)\n",
    "    # print(\"initial population\")\n",
    "    # print(population)\n",
    "    return population\n",
    "\n",
    "\n",
    "def decoder(s):\n",
    "    ''' The input is a number as string, outputs the number as a float. '''\n",
    "    \n",
    "    l = len(s)\n",
    "    # The first char encodes for the sign, \n",
    "    sign = 1\n",
    "    if  float(s[0]) % 2 == 1:\n",
    "        sign = -1\n",
    "    # The second char encodes for the position of the decimal point,\n",
    "    d = float(s[1])\n",
    "    # The remaining chars encode for the number itself, \n",
    "    # without the decimal point nor sign.\n",
    "    n = float(s[2:l])\n",
    "    return sign * (n * (10**-d))\n",
    "\n",
    "\n",
    "def calculate_fitnessj1(chromosome, xArray, yArray):\n",
    "    \"\"\"Calculates the fitness of a chromosome.\n",
    "        A chromosome encodes for the slope of a line that passes though zero.\n",
    "        The error of a chromosome is the sum of \n",
    "        the vertical distances of the points to the line it encodes.\n",
    "        The fitness of a chromosome is the similarity of the line it encodes\n",
    "        to the target sequence.\n",
    "    \"\"\"\n",
    "    #  print(\"\\n *calculate_fitnessj1(chromosome, target_sequence)\")\n",
    "    fitness = 0\n",
    "    for i in range(len(xArray)):\n",
    "        x = xArray[i]\n",
    "        y = yArray[i]\n",
    "        slope = decoder(chromosome)\n",
    "        # Calculate the predicted y value based on the line's slope\n",
    "        predicted_y = slope * x\n",
    "        # Calculate the error as the quadratic difference \n",
    "        # between predicted and y value\n",
    "        error = (predicted_y - y)**2\n",
    "        # Update fitness based on the error (the smaller the error, the higher the fitness)\n",
    "        fitness +=  100 - error  # Fitness is between 0 and 1\n",
    "    # print(chromosome, \"  fitness: \", fitness)\n",
    "    return fitness\n",
    "\n",
    "def calculate_all_fitnessj1(population, xArray, yArray):\n",
    "    # print(\"\\n*calculate_all_fitnessj1(population, target_sequence)\")\n",
    "    \"\"\"Calculates the fitness of all chromosomes in the population.\"\"\"\n",
    "    fitness_scores = [calculate_fitnessj1(chromosome, xArray, yArray) for chromosome in population]\n",
    "    # print(\"fitness_scores: \", fitness_scores)\n",
    "    return fitness_scores\n",
    "\n",
    "def select_the_bestj1(population, xArray, yArray):\n",
    "    \"\"\"Selects the best chromosome for reproduction.\"\"\"\n",
    "    fitness_scores = calculate_all_fitnessj1(population, xArray, yArray)\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_bestj1(population)\")\n",
    "    # print(\"best_fitness = \", best_fitness)\n",
    "    # print(\"The chro = \", best_chromosome )\n",
    "    return best_fitness, best_chromosome\n",
    "\n",
    "def clone_populationj1(best_chromosome, population_size):\n",
    "    \"\"\"Creates a new population by cloning the best chromosome.\"\"\"\n",
    "    return [best_chromosome] * population_size\n",
    "\n",
    "\n",
    "def mutatej1(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_allj1(population, mutation_rate, alphabet):\n",
    "    \"\"\"Mutates all chromosomes in the population.\"\"\"\n",
    "    mutated_population = []\n",
    "    for chromosome in population:\n",
    "        mutated_chromosome = mutatej1(chromosome, mutation_rate, alphabet)\n",
    "        mutated_population.append(mutated_chromosome)\n",
    "    return mutated_population\n",
    "\n",
    "def crossoverj1(parent1, parent2, length_of_chromosomes, recombination_rate):\n",
    "    \"\"\"Performs crossover between two parent chromosomes.\"\"\"\n",
    "    if random.random() < recombination_rate:\n",
    "        crossover_point = random.randint(0, length_of_chromosomes)\n",
    "        return parent1[:crossover_point] + parent2[crossover_point:]\n",
    "    else:\n",
    "        return parent1\n",
    "\n",
    "def crossover_allj1(population, length_of_chromosomes, 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 = crossoverj1(parent1, parent2, length_of_chromosomes, recombination_rate)\n",
    "        recombinant_population.append(child)\n",
    "    return recombinant_population\n",
    "\n",
    "\n",
    "\n",
    "def run_one_generationj1(population, xArray, yArray, 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_bestj1(population, xArray, yArray)\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_populationj1:\n",
    "        new_population = clone_populationj1(best_chromosome, population_size)\n",
    "    if include_mutate_allj1:\n",
    "        new_population = mutate_allj1(new_population, mutation_rate, alphabet)\n",
    "    if include_crossover_allj1:\n",
    "        new_population = crossover_allj1(new_population, length_of_chromosomes, recombination_rate)\n",
    "    return best_fitness, best_chromosome, new_population\n",
    "\n",
    "\n",
    "\n",
    "def plot_functionj1(g_values, 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_taskj1( xArray, yArray, mutation_rate, recombination_rate, alphabet, percentageOfTask):\n",
    "    \n",
    "    population = create_populationj1(population_size, length_of_chromosomes, 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 generation < 50:\n",
    "        generation += 1\n",
    "        best_fitness, best_chromosome, population = run_one_generationj1(population, xArray,yArray, 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",
    "    \n",
    "    \n",
    "    return  best_chromosome, totalCost, best_fitness_history\n",
    "\n",
    "def main():\n",
    "    print_parametersj1()\n",
    "    print(\"Total cost = population size * number of generations\")\n",
    "    best_chromosome, totalCost, best_fitness_history = truncated_taskj1(xArray, yArray, mutation_rate, recombination_rate, alphabet, length_of_chromosomes)\n",
    "    print(f\" Total cost =  {totalCost} chromosomes\")\n",
    "    our_slope = decoder(best_chromosome)\n",
    "    print(f\" The best chromosome is {best_chromosome} and it encodes for the slope {our_slope}\")\n",
    "\n",
    "    # Plot the fitness history    \n",
    "    g_values = list(range(1, len(best_fitness_history) + 1))\n",
    "    plot_functionj1(g_values, best_fitness_history, xlabel='Generation', ylabel='Best Fitness', title='Best Fitness Over Generations')\n",
    "    # Perform linear regression\n",
    "    # Fit a polynomial of degree 1 (linear)\n",
    "    slope, intercept = np.polyfit(xArray, yArray, 1)\n",
    "    # Create the regression line\n",
    "    regression_line = slope * np.array(xArray) + intercept\n",
    "\n",
    "# Plot the original data, the regression line, and the equation of our_line\n",
    "    our_line = our_slope * np.array(xArray)   # Line corresponding to the slope found by\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.plot(xArray,        our_line, color='green', label=f'Our Line: y = {our_slope:.2f}x (Intercept = 0) ')\n",
    "    plt.xlabel('Independent variable (x)')\n",
    "    plt.ylabel('Dependent variable (y)')\n",
    "    plt.title('Linear Regression and la Evolución minimize the error of the line with respect to the data points')\n",
    "    plt.legend()\n",
    "    plt.grid(True)\n",
    "    plt.show()\n",
    "\n",
    "\n",
    "    end_time = time.time()\n",
    "    # Calculate the difference in seconds\n",
    "    elapsed_time = end_time - start_time\n",
    "    elapsed_time = timedelta(seconds=elapsed_time)\n",
    "    print(f\"Elapsed time: {elapsed_time}\")\n",
    "\n",
    "main()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "8dd6b0f3",
   "metadata": {},
   "source": [
    "**Ejercicio.** Ejecuta el programa anterior y verifica que la línea encontrada pasa por el origen y, dada esa restricción, representa más o menos equitativamente los puntos dados. \n",
    ">\n",
    "> *Respuesta.* La línea que pasa por el origen es, en este caso, una buena aproximación a la línea de regresión. \n",
    "\n",
    "**Ejercicio.** En el programa anterior, asumimos que la línea pasa por el origen. Por lo tanto, la Evolución debió especificar solo su pendiente. Ahora no haga ninguna suposición, y haga que la Evolución especifique ambos parámetros, pendiente e intersección. Test: la línea resultante debe coincidir con la dada por la regresión lineal. Explica el resultado. \n",
    ">\n",
    "> *Respuesta.* Para codificar dos parámetros, usamos un cromosoma con una longitud igual al doble de la utilizada para codificar un parámetro. La función de descodificación debe dividir el cromosoma en dos partes y descodificar cada parte por separado. El código sigue."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "731be06d",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Lab: Evolution finds the line of minimal error\n",
      "Purpose: To find the intercept and slope of a line that best fits a set of points using a genetic algorithm.\n",
      "Date of Experiment  = 2026-05-04 13:07:06.751363\n",
      "alphabet =  0123456789\n",
      "percentageOfTask = 1.0\n",
      "population_size = 200\n",
      "include_clone_populationj2 = True\n",
      "include_mutate_allj2 = True\n",
      "include_crossover_allj2 = True\n",
      "mutation_rate = 0.01\n",
      "recombination_rate = 0.01\n",
      "print_best_fitness = False\n",
      "Total cost = population size * number of generations\n",
      "Number of generations: 50000, best_chromosome: 65599972582858, best_fitness: 594.5142857129999\n",
      " Total cost =  10000000 chromosomes\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": [
      " The best chromosome is 65599972582858\n",
      "Encoded: Intercept 0.59997, slope 0.8285800000000001,\n",
      "Linear regression: Intercept 0.6000000000000014, slope 0.8285714285714285,\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": [
      "Elapsed time: 0:02:02.066374\n"
     ]
    }
   ],
   "source": [
    "# Program lineOfMinimalError2.py\n",
    "# This program uses a genetic algorithm to find the line \n",
    "# that best fits a set of points.\n",
    "# The slope and the intercept are represented by a chromosome, \n",
    "# which is a string of digits.\n",
    "# The decoding function must divide the chromosome into two parts, \n",
    "# and decode each one apart.\n",
    "# The error of a chromosome is the sum of the vertical quadratic distances \n",
    "# of the points to the line it encodes.\n",
    "# The fitness of a chromosome is K - error, \n",
    "# where K is a constant that is larger than the maximum possible error.\n",
    "# The Genetic algorithm must maximize the fitness, \n",
    "# which is equivalent to minimizing the error.\n",
    "# Developed with the assistance of the AI of Visual Studio Code.\n",
    "# An old version of a GA developed with the help of Gemini was reused and updated.\n",
    "\n",
    "from datetime import datetime, timedelta\n",
    "import time\n",
    "import random\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 generations to run the GA\n",
    "numberOfGenerations = 50000\n",
    "percentageOfTask = 1.0\n",
    "\n",
    "xArray = [1, 2, 3, 4, 5, 6]\n",
    "yArray = [2, 1, 4, 3, 6, 5]\n",
    "\n",
    "alphabet = '0123456789'\n",
    "length_of_chromosomes = 7\n",
    "population_size = 200\n",
    "# Include cloning of the fittest\n",
    "include_clone_populationj2 = True\n",
    "# Include mutation\n",
    "include_mutate_allj2 = True\n",
    "# Include recombination\n",
    "include_crossover_allj2 = True\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",
    "def print_parametersj2():\n",
    "    print(f\"Lab: la Evolución finds the line of minimal error\")\n",
    "    print(f\"Purpose: To find the intercept and slope of a line that best fits a set of points using a genetic algorithm.\")\n",
    "    print(f\"Date of Experiment  = {datetime.datetime.now()}\")\n",
    "    print(f\"alphabet =  {alphabet}\")\n",
    "    print(f\"percentageOfTask = {percentageOfTask}\")\n",
    "    print(f\"population_size = {population_size}\")\n",
    "    print(f\"include_clone_populationj2 = {include_clone_populationj2}\")\n",
    "    print(f\"include_mutate_allj2 = {include_mutate_allj2}\")\n",
    "    print(f\"include_crossover_allj2 = {include_crossover_allj2}\")\n",
    "    if include_mutate_allj2:\n",
    "        print(f\"mutation_rate = {mutation_rate}\")\n",
    "    if include_crossover_allj2:\n",
    "        print(f\"recombination_rate = {recombination_rate}\")\n",
    "    if include_clone_populationj2:\n",
    "        print(f\"print_best_fitness = {print_best_fitness}\")\n",
    "\n",
    "\n",
    "def create_populationj2(population_size, length_of_chromosomes, alphabet):\n",
    "    \"\"\"Creates a new population with random chromosomes.\"\"\"\n",
    "    # print(\"create_populationj2(population_size, target_sequence, alphabet)\")\n",
    "    population = []\n",
    "    for _ in range(population_size):\n",
    "        random_string1 = ''.join(random.choice(alphabet) for _ in range(length_of_chromosomes))\n",
    "        random_string2 = ''.join(random.choice(alphabet) for _ in range(length_of_chromosomes))\n",
    "        random_string = random_string1 + random_string2\n",
    "        population.append(random_string)\n",
    "    # print(\"initial population\")\n",
    "    # print(population)\n",
    "    return population\n",
    "\n",
    "\n",
    "def decoder(s):\n",
    "    ''' The input is a number as string, outputs the number as a float. '''\n",
    "    \n",
    "    l = len(s)\n",
    "    # The first char encodes for the sign, \n",
    "    sign = 1\n",
    "    if  float(s[0]) % 2 == 1:\n",
    "        sign = -1\n",
    "    # The second char encodes for the position of the decimal point,\n",
    "    d = float(s[1])\n",
    "    # The remaining chars encode for the number itself, \n",
    "    # without the decimal point nor sign.\n",
    "    n = float(s[2:l])\n",
    "    return sign * (n * (10**-d))\n",
    "\n",
    "def calculate_fitnessj2(chromosome, xArray, yArray):\n",
    "    \"\"\"Calculates the fitness of a chromosome.\n",
    "        A chromosome encodes for the slope of a line that passes though zero.\n",
    "        The error of a chromosome is the sum of \n",
    "        the vertical distances of the points to the line it encodes.\n",
    "        The fitness of a chromosome is the similarity of the line it encodes\n",
    "        to the target sequence.\n",
    "    \"\"\"\n",
    "    #  print(\"\\n *calculate_fitnessj2(chromosome, target_sequence)\")\n",
    "    fitness = 0\n",
    "    for i in range(len(xArray)):\n",
    "        x = xArray[i]\n",
    "        y = yArray[i]\n",
    "        #The chromosome is divided in two parts and decoded\n",
    "        chro1 = chromosome[0:length_of_chromosomes]\n",
    "        chro2 = chromosome[length_of_chromosomes:2*length_of_chromosomes]\n",
    "        intercept = decoder(chro1)\n",
    "        slope = decoder(chro2)\n",
    "        # Calculate the predicted y value based on the line's slope\n",
    "        predicted_y = slope * x + intercept\n",
    "        # Calculate the error as the quadratic difference \n",
    "        # between predicted and y value\n",
    "        error = (predicted_y - y)**2\n",
    "        # Update fitness based on the error (the smaller the error, the higher the fitness)\n",
    "        fitness +=  100 - error  # Fitness is between 0 and 1\n",
    "    # print(chromosome, \"  fitness: \", fitness)\n",
    "    return fitness\n",
    "\n",
    "def calculate_all_fitnessj2(population, xArray, yArray):\n",
    "    # print(\"\\n*calculate_all_fitnessj2(population, target_sequence)\")\n",
    "    \"\"\"Calculates the fitness of all chromosomes in the population.\"\"\"\n",
    "    fitness_scores = [calculate_fitnessj2(chromosome, xArray, yArray) for chromosome in population]\n",
    "    # print(\"fitness_scores: \", fitness_scores)\n",
    "    return fitness_scores\n",
    "\n",
    "def select_the_bestj2(population, xArray, yArray):\n",
    "    \"\"\"Selects the best chromosome for reproduction.\"\"\"\n",
    "    fitness_scores = calculate_all_fitnessj2(population, xArray, yArray)\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_bestj2(population)\")\n",
    "    # print(\"best_fitness = \", best_fitness)\n",
    "    # print(\"The chro = \", best_chromosome )\n",
    "    return best_fitness, best_chromosome\n",
    "\n",
    "def clone_populationj2(best_chromosome, population_size):\n",
    "    \"\"\"Creates a new population by cloning the best chromosome.\"\"\"\n",
    "    return [best_chromosome] * population_size\n",
    "\n",
    "\n",
    "def mutatej2(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_allj2(population, mutation_rate, alphabet):\n",
    "    \"\"\"Mutates all chromosomes in the population.\"\"\"\n",
    "    mutated_population = []\n",
    "    for chromosome in population:\n",
    "        mutated_chromosome = mutatej2(chromosome, mutation_rate, alphabet)\n",
    "        mutated_population.append(mutated_chromosome)\n",
    "    return mutated_population\n",
    "\n",
    "def crossoverj2(parent1, parent2, length_of_chromosomes, recombination_rate):\n",
    "    \"\"\"Performs crossover between two parent chromosomes.\"\"\"\n",
    "    if random.random() < recombination_rate:\n",
    "        crossover_point = random.randint(0, length_of_chromosomes)\n",
    "        return parent1[:crossover_point] + parent2[crossover_point:]\n",
    "    else:\n",
    "        return parent1\n",
    "\n",
    "def crossover_allj2(population, length_of_chromosomes, 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 = crossoverj2(parent1, parent2, length_of_chromosomes, recombination_rate)\n",
    "        recombinant_population.append(child)\n",
    "    return recombinant_population\n",
    "\n",
    "\n",
    "\n",
    "def run_one_generationj2(population, xArray, yArray, 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_bestj2(population, xArray, yArray)\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_populationj2:\n",
    "        new_population = clone_populationj2(best_chromosome, population_size)\n",
    "    if include_mutate_allj2:\n",
    "        new_population = mutate_allj2(new_population, mutation_rate, alphabet)\n",
    "    if include_crossover_allj2:\n",
    "        new_population = crossover_allj2(new_population, length_of_chromosomes, recombination_rate)\n",
    "    return best_fitness, best_chromosome, new_population\n",
    "\n",
    "\n",
    "\n",
    "def plot_functionj2(g_values, 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_taskj2( xArray, yArray, mutation_rate, recombination_rate, alphabet, percentageOfTask):\n",
    "    \n",
    "    population = create_populationj2(population_size, length_of_chromosomes, 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 generation < numberOfGenerations:\n",
    "        generation += 1\n",
    "        best_fitness, best_chromosome, population = run_one_generationj2(population, xArray,yArray, 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\"Number of generations: {generation}, best_chromosome: {best_chromosome}, best_fitness: {best_fitness}\")\n",
    "\n",
    "\n",
    "    return  best_chromosome, totalCost, best_fitness_history\n",
    "\n",
    "def main(xArray, yArray, mutation_rate, recombination_rate, alphabet, length_of_chromosomes):\n",
    "    print_parametersj2()\n",
    "    print(\"Total cost = population size * number of generations\")\n",
    "    best_chromosome, totalCost, best_fitness_history = truncated_taskj2(xArray, yArray, mutation_rate, recombination_rate, alphabet, length_of_chromosomes)\n",
    "    print(f\" Total cost =  {totalCost} chromosomes\")\n",
    "\n",
    "    # Plot the fitness history    \n",
    "    g_values = list(range(1, len(best_fitness_history) + 1))\n",
    "    plot_functionj2(g_values, best_fitness_history, xlabel='Generation', ylabel='Best Fitness', title='Best Fitness Over Generations')\n",
    "\n",
    "    # The best chromosome encodes for the slope and intercept of the line that best fits the data points\"\n",
    "    chro1 = best_chromosome[0:length_of_chromosomes]\n",
    "    chro2 = best_chromosome[length_of_chromosomes:2*length_of_chromosomes]\n",
    "    our_intercept = decoder(chro1)\n",
    "    our_slope = decoder(chro2)\n",
    "    our_line = our_slope * np.array(xArray) + our_intercept\n",
    "    print(f\" The best chromosome is {best_chromosome}\" )\n",
    "    print(f\"Encoded: Intercept {our_intercept}, slope {our_slope},\")\n",
    "    # Perform linear regression\n",
    "    # Fit a polynomial of degree 1 (linear)\n",
    "    slope, intercept = np.polyfit(xArray, yArray, 1)\n",
    "    print(f\"Linear regression: Intercept {intercept}, slope {slope},\")\n",
    "    # Create the regression line\n",
    "    regression_line = slope * np.array(xArray) + intercept\n",
    "\n",
    "    # Plot the original data, the regression line, and the equation of our_line\n",
    "    our_line = our_slope * np.array(xArray) + our_intercept  # Line corresponding to the slope found by\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.plot(xArray,        our_line, color='green', label=f'Our Line: y = {our_slope:.2f}x + {our_intercept:.2f}')\n",
    "    plt.xlabel('Independent variable')\n",
    "    plt.ylabel('Dependent variable (y)')\n",
    "    plt.title('Linear Regression and la Evolución minimize the error of the line with respect to the data points')\n",
    "    plt.legend()\n",
    "    plt.grid(True)\n",
    "    plt.show()\n",
    "\n",
    "\n",
    "    end_time = time.time()\n",
    "    # Calculate the difference in seconds\n",
    "    elapsed_time = end_time - start_time\n",
    "    elapsed_time = timedelta(seconds=elapsed_time)\n",
    "    print(f\"Elapsed time: {elapsed_time}\")\n",
    "    #return best_chromosome, totalCost, best_fitness_history\n",
    "\n",
    "# Call the main function with the defined parameters\n",
    "main(xArray, yArray, mutation_rate, recombination_rate, alphabet, length_of_chromosomes)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "16f590a8",
   "metadata": {},
   "source": [
    "**Ejercicio.** Ejecuta el programa anterior y ejecútalo con suficientes generaciones para generar la línea de regresión.\n",
    ">\n",
    "> *Respuesta.* La Evolución produce el mismo resultado de las matemáticas, pero hay que pagar un precio. Mientras que una buena aproximación puede aparecer en las primeras generaciones, la alta precisión se obtiene después de, tal vez, 50000 generaciones con un tamaño poblacional de 200 y un tiempo de CPU de dos minutos.\n",
    "\n",
    "Hemos sido testigos de que la Evolución puede resolver perfectamente un problema ligeramente complejo. Y, a veces eso se hace muy rápido. Esto significa que tenemos la licencia para emprender una tarea más compleja.\n",
    "\n",
    "**Ejercicio.** Investiga el código para encontrar el polinomio de regresión que mejor se ajuste a un conjunto de puntos. Redacta tus observaciones.\n",
    ">\n",
    "> *Respuesta.* El siguiente programa fue propuesto por Google con el prompt:\n",
    "> > \n",
    "> Ejemplo de una regresión polinomial con numpy. \n",
    "> \n",
    "> Se emplean seis puntos para un polinomio de grado 3. Por lo tanto, el ajuste no puede ser perfecto. Numpy significa Python Numérico, es la biblioteca de Python para trabajar con números. \n",
    "\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "id": "82668dd9",
   "metadata": {},
   "outputs": [
    {
     "data": {
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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Program polynomialRegressionDegree3ByNumpy.py\n",
    "# This program uses numpy to find the polynomial of minimal error \n",
    "# that best fits a set of points.\n",
    "# Observe that arrays are not standard Python lists, \n",
    "# instead they are numpy objects.\n",
    "# This example was proposed by Google with the prompt:\n",
    "# Example of a polynomial regression with numpy\n",
    "\n",
    "import numpy as np\n",
    "import matplotlib.pyplot as plt\n",
    "from numpy.polynomial import Polynomial\n",
    "\n",
    "# 1. Generate sample non-linear data\n",
    "# x-coordinates of six points\n",
    "xArray = np.array([-2, -1, 0, 1, 2, 3])\n",
    "# y-coordinates of six points\n",
    "yArray = np.array([5,   1, 4, 0, 6, 3])\n",
    "\n",
    "# 2. Fit a 3rd-degree (cubic) polynomial\n",
    "# .fit() returns a Polynomial instance\n",
    "p_fitted = Polynomial.fit(xArray, yArray, deg=3)\n",
    "\n",
    "# 3. Predict values for visualization\n",
    "x_new = np.linspace(-2, 3, 100)\n",
    "y_new = p_fitted(x_new)\n",
    "\n",
    "# 4. Plot results\n",
    "plt.scatter(xArray, yArray, label='Data Points')\n",
    "plt.plot(x_new, y_new, label='Cubic Fit', color='green')\n",
    "plt.legend()\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "d29c80f7",
   "metadata": {},
   "source": [
    "\n",
    "> *Nuestra observación. * El polinomio de regresión de grado 3 sobre un conjunto de 6 puntos tiene sentido.\n",
    "\n",
    "**Ejercicio.** Prueba el programa anterior en tu propio conjunto de puntos en el plano. Reporta tus observaciones. \n",
    ">\n",
    "> *Respuesta.* Tarea: Hallar por regresión matemática el polinomio de quinto grado que mejor representa un conjunto de seis puntos. Test: el ajuste debe ser perfecto (los puntos se eligen cuidadosamente, por ejemplo, no debe haber dos puntos en la misma línea vertical). ¿Es eso cierto?"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "2540d2a4",
   "metadata": {},
   "outputs": [],
   "source": [
    "# Program Polynomial_5_MinimalErrorWithNumpy.py\n",
    "# This program uses numpy to find the polynomial of minimal error \n",
    "# that best fits a set of 6 points points.\n",
    "\n",
    "\n",
    "import numpy as np\n",
    "import matplotlib.pyplot as plt\n",
    "# Documentation: https://numpy.org/devdocs/reference/routines.polynomials.html\n",
    "from numpy.polynomial import Polynomial\n",
    "\n",
    "\n",
    "# 1. Generate sample non-linear data\n",
    "# x-coordinates of six points\n",
    "xArray = np.array([-2, -1, 0, 1, 2, 3])\n",
    "# y-coordinates of six points\n",
    "yArray = np.array([5,   1, 4, 0, 6, 3])\n",
    "\n",
    "# print(f\"Points = {list(zip(x, y))}\")\n",
    "print(f\"Points = {list(zip(xArray, yArray))}\")\n",
    "\n",
    "# 2. Fit a 3rd-degree (cubic) polynomial\n",
    "# .fit() returns a Polynomial instance\n",
    "p_fitted = Polynomial.fit(xArray, yArray, deg=5)\n",
    "print(f\"Fitted polynomial coefficients: {p_fitted.convert().coef}\")\n",
    "\n",
    "# 3. Predict values for visualization\n",
    "x_new = np.linspace(-2,3, 100) # Generate 100 points between -2 and 3 for a smooth curve\n",
    "y_new = p_fitted(x_new)\n",
    "\n",
    "# 4. Plot results\n",
    "plt.scatter(xArray, yArray, label='Data Points')\n",
    "plt.xlabel('x')\n",
    "plt.ylabel('y')\n",
    "plt.plot(x_new, y_new, label='Quintic Fit', color='green')\n",
    "plt.legend()\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "38a4835b",
   "metadata": {},
   "source": [
    "*Observación.* Como era de esperar, el ajuste por la regresión polinomial es perfecto. Así, incorporaremos este fragmento de código en nuestros programas como referente para juzgar la precisión de nuestras soluciones evolutivas. Según los coeficientes reportados, el polinomio es:\n",
    "\n",
    " $ p(x) = 4 - 2,983333x - 4,791667x 2 + 3,041667x 3 + 1,291667x 4 - 0,558333x 5 $\n",
    "\n",
    "Test: El gráfico debe pasar por $(0,4)$, así que $p(0)$ debe ser $4$. ¿Es eso cierto? Sí, lo es.  \n",
    "\n"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "96bb6061",
   "metadata": {},
   "source": [
    "\n",
    "## Regresión evolutiva\n",
    "\n",
    "Le daremos a la Evolución la tarea de encontrar el polinomio que mejor encaje en un conjunto de puntos. \n",
    "\n",
    "**Test.** Debido a que la regresión matemática y la Evolución usan la misma función de error, las dos respuestas deben coincidir. \n",
    "\n",
    "*Experimentos tempranos.* Experimentamos un fracaso en los experimentos iniciales. Entonces, tomamos dos decisiones:\n",
    "\n",
    "1. El problema matemático es minimizar un error, pero el evolutivo es maximizar la aptitud. Descubrimos que para este problema, el truco para cambiar un min por un max debe ser cuidadosamente preparado, y esto implica mucho trabajo. Así, cambiamos el objetivo de optimización al problema natural de minimizar el error. \n",
    "\n",
    "2. Después de sufrir mucho con experimentos diversos, llegamos a la conclusión de que la codificación es la principal causa de fracaso. De hecho, se podrían explorar regiones inútiles mientras que algunos valores nunca aparecerían. Guiados por la solución de la regresión matemática, seleccionamos una longitud de cromosomas igual a 9, y esto implica que los números pueden tomar valores enormes y también bajar al nivel centesimal.\n",
    "\n",
    "**Desafío.** Encuentra e implementa una solución a prueba de agua para nuestro problema de convertir un error en una función de fitness. \n",
    "\n",
    "***Ejemplo.**  El siguiente programa permite a la Evolución especificar los seis coeficientes de un polinomio de quinto grado que mejor se adapta a un conjunto de 6 pares de datos inventados. Se puede comparar la solución de regresión polinomial encontrada matemáticamente con la de la Evolución. Nuestro AG consiste en MAX (selección y clonación del más apto), mutación y recombinación. Este GA se corrió durante un millón de generaciones con una población de 200 habitantes."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "1ff6b7c2",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Lab: Evolution finds the polynomial of minimal error\n",
      "Purpose: Use a Genetic Algorithm (MAX or selection of the fittest, mutation, recombination) to find the coefficients of a polynomial that best fits a set of points.\n",
      "Date of Experiment  = 2026-04-20 14:41:12.705556\n",
      "number_of_generations = 1000000\n",
      "length_of_chromosomes = 9\n",
      "alphabet =  0123456789\n",
      "Points = [(-2, 5), (-1, 1), (0, 4), (1, 0), (2, 6), (3, 3)]\n",
      "population_size = 200\n",
      "include_clone_populationj3 = True\n",
      "include_mutate_allj3 = True\n",
      "include_crossover_allj3 = True\n",
      "mutation_rate = 0.02\n",
      "recombination_rate = 0.03\n",
      "print_best_fitness = False\n",
      "Total cost = population size * number of generations\n",
      " The best chromosome is 861660469976381016674157784075871000089999999789999999\n",
      " Encoded coefficients: Intercept 1.660469, slope -0.6381015999999999, quadratic 0.4157784, cubic 0.5871, quartic 0.09999999, quintic -0.09999999\n",
      " Total cost =  200000000 chromosomes\n",
      " Final error =  12.17682606507979 \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": [
      "Polynomial regression coefficients: Intercept 4.0, slope -2.983333333333327, quadratic -4.791666666666659, cubic 3.041666666666663, quartic 1.2916666666666643, quintic -0.5583333333333323\n",
      "Encoded coefficients: Intercept 1.660469, slope -0.6381015999999999, quadratic 0.4157784, cubic 0.5871, quartic 0.09999999, quintic -0.09999999\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"
    },
    {
     "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": [
      "Elapsed time: 0:37:13.966612\n"
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    }
   ],
   "source": [
    "# Program PolynomialMinimalErrorByGA_WithMAX.py\n",
    "# This program uses a genetic algorithm with MAX to find \n",
    "# the fifth degree polinomial that best fits a set of 6 points.\n",
    "# The coefficients are represented by a chromosome, \n",
    "# which is a string of digits.\n",
    "# The decoding function must divide the chromosome into parts, \n",
    "# and decode each one apart as one coefficient.\n",
    "# The error of a chromosome is the sum of the vertical quadratic distances \n",
    "# of the points to the polynomial it encodes.\n",
    "# The Genetic algorithm must minimize the error, \n",
    "# (which is equivalent to maximizing the fitness).\n",
    "# We use MAX (selection of the best and cloning),  mutation and recombination.\n",
    "# Developed with the assistance of the AI of Visual Studio Code.\n",
    "# An old version of a GA developed with the help of Gemini was reused and updated.\n",
    "\n",
    "from datetime import datetime, timedelta\n",
    "import time\n",
    "import random\n",
    "import numpy as np\n",
    "# Documentation: https://numpy.org/devdocs/reference/routines.polynomials.html\n",
    "from numpy.polynomial import Polynomial\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",
    "#Task to be done\n",
    "number_of_generations = 1000000\n",
    "\n",
    "xArray = [-2, -1, 0, 1, 2, 3]\n",
    "yArray = [5,   1, 4, 0, 6, 3]\n",
    "\n",
    "alphabet = '0123456789'\n",
    "length_of_chromosomes = 9\n",
    "population_size = 200\n",
    "# Include cloning of the fittest\n",
    "include_clone_populationj3 = True\n",
    "# Include mutation\n",
    "include_mutate_allj3 = True\n",
    "# Include recombination\n",
    "include_crossover_allj3 = True\n",
    "mutation_rate = 0.02\n",
    "recombination_rate = 0.03\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",
    "def print_parametersj3():\n",
    "    print(f\"Lab: la Evolución finds the polynomial of minimal error\")\n",
    "    print(f\"Purpose: Use a Genetic Algorithm (MAX or selection of the fittest, mutation, recombination) to find the coefficients of a polynomial that best fits a set of points.\")\n",
    "    print(f\"Date of Experiment  = {datetime.datetime.now()}\")\n",
    "    print(f\"number_of_generations = {number_of_generations}\")\n",
    "    print(f\"length_of_chromosomes = {length_of_chromosomes}\")\n",
    "    print(f\"alphabet =  {alphabet}\")\n",
    "    print(f\"Points = {list(zip(xArray, yArray))}\")\n",
    "    print(f\"population_size = {population_size}\")\n",
    "    print(f\"include_clone_populationj3 = {include_clone_populationj3}\")\n",
    "    print(f\"include_mutate_allj3 = {include_mutate_allj3}\")\n",
    "    print(f\"include_crossover_allj3 = {include_crossover_allj3}\")\n",
    "    if include_mutate_allj3:\n",
    "        print(f\"mutation_rate = {mutation_rate}\")\n",
    "    if include_crossover_allj3:\n",
    "        print(f\"recombination_rate = {recombination_rate}\")\n",
    "    if include_clone_populationj3:\n",
    "        print(f\"print_best_fitness = {print_best_fitness}\")\n",
    "\n",
    "\n",
    "def create_populationj3(population_size, length_of_chromosomes, alphabet):\n",
    "    \"\"\"Creates a new population with random chromosomes.\"\"\"\n",
    "    # print(\"create_populationj3(population_size, target_sequence, alphabet)\")\n",
    "    population = []\n",
    "    for _ in range(population_size):\n",
    "        random_string1 = ''.join(random.choice(alphabet) for _ in range(length_of_chromosomes))\n",
    "        random_string2 = ''.join(random.choice(alphabet) for _ in range(length_of_chromosomes))\n",
    "        random_string3 = ''.join(random.choice(alphabet) for _ in range(length_of_chromosomes))\n",
    "        random_string4 = ''.join(random.choice(alphabet) for _ in range(length_of_chromosomes))\n",
    "        random_string5 = ''.join(random.choice(alphabet) for _ in range(length_of_chromosomes))\n",
    "        random_string6 = ''.join(random.choice(alphabet) for _ in range(length_of_chromosomes))\n",
    "        random_string = random_string1 + random_string2 + random_string3 + random_string4 + random_string5 + random_string6\n",
    "        population.append(random_string)\n",
    "    # print(\"initial population\")\n",
    "    # print(population)\n",
    "    return population\n",
    "\n",
    "# Decode a part of the chromosome into a coefficient of the polynomial.\n",
    "def decoderj3(s):\n",
    "    ''' The input is a number as string, outputs the number as a float. '''\n",
    "    \n",
    "    l = len(s)\n",
    "    # The first char encodes for the sign, \n",
    "    sign = 1\n",
    "    if  float(s[0]) % 2 == 1:\n",
    "        sign = -1\n",
    "    # The second char encodes for the position of the decimal point,\n",
    "    d = float(s[1])\n",
    "    # The remaining chars encode for the number itself, \n",
    "    # without the decimal point nor sign.\n",
    "    n = float(s[2:l])\n",
    "    return sign * (n * (10**-d))\n",
    "\n",
    "def decodeFullCromosomej3(chromosome, length_of_chromosomes):\n",
    "    \"\"\"Decodes the full chromosome into the coefficients of the polynomial.\"\"\"\n",
    "    \"\"\"The chromosome is divided into 5 parts, \n",
    "        each one encoding for a coefficient of the polynomial.\"\"\"\n",
    "    chro0 = chromosome[0:length_of_chromosomes]\n",
    "    chro1 = chromosome[length_of_chromosomes:2*length_of_chromosomes]\n",
    "    chro2 = chromosome[2*length_of_chromosomes:3*length_of_chromosomes]\n",
    "    chro3 = chromosome[3*length_of_chromosomes:4*length_of_chromosomes]\n",
    "    chro4 = chromosome[4*length_of_chromosomes:5*length_of_chromosomes]\n",
    "    chro5 = chromosome[5*length_of_chromosomes:6*length_of_chromosomes]\n",
    "    a_0 = decoderj3(chro0)\n",
    "    a_1 = decoderj3(chro1)\n",
    "    a_2 = decoderj3(chro2)\n",
    "    a_3 = decoderj3(chro3)\n",
    "    a_4 = decoderj3(chro4)\n",
    "    a_5 = decoderj3(chro5)\n",
    "    return a_0, a_1, a_2, a_3, a_4, a_5\n",
    "\n",
    " \n",
    "\n",
    "def calculate_errorj3(chromosome, xArray, yArray):\n",
    "    \"\"\"Calculates the error of a chromosome.\n",
    "        A chromosome encodes for the coefficients of a polynomial of fith degree.\n",
    "        The error of a chromosome is the sum of \n",
    "        the vertical distances of the points to the polynomial it encodes.\n",
    "    \"\"\"\n",
    "    #  print(\"\\n calculate_errorj3(chromosome, xArray, yArray)\")\n",
    "    a_0, a_1, a_2, a_3, a_4, a_5 = decodeFullCromosomej3(chromosome, length_of_chromosomes) \n",
    "    error = 0\n",
    "    for i in range(len(xArray)):\n",
    "        x = xArray[i]\n",
    "        y = yArray[i]\n",
    "        # Calculate the predicted y value based on the coefficients of the polynomial\n",
    "        predicted_y = a_0 + a_1 * x + a_2 * x**2 + a_3 * x**3 + a_4 * x**4 + a_5 * x**5\n",
    "        # Calculate the error as the quadratic difference \n",
    "        # between predicted and y value\n",
    "        error += (predicted_y - y)**2\n",
    "    return error\n",
    "\n",
    "def calculate_all_errorsj3(population, xArray, yArray):\n",
    "    # print(\"\\n*calculate_all_errorsj3(population, target_sequence)\")\n",
    "    \"\"\"Calculates the error of all chromosomes in the population.\"\"\"\n",
    "    errors = [calculate_errorj3(chromosome, xArray, yArray) for chromosome in population]\n",
    "    # print(\"errors: \", errors)\n",
    "    return errors\n",
    "\n",
    "def select_the_least_errorj3(population, xArray, yArray):\n",
    "    \"\"\"Selects the best chromosome with minimal error for reproduction.\"\"\"\n",
    "    errors = calculate_all_errorsj3(population, xArray, yArray)\n",
    "    smallest_error = min(errors)\n",
    "    best_chromosome_index = errors.index(smallest_error)\n",
    "    best_chromosome = population[best_chromosome_index]\n",
    "    # print(\"\\n*select_the_least_errorj3(population)\")\n",
    "    # print(\"smallest_error = \", smallest_error)\n",
    "    # print(\"The chro = \", best_chromosome )\n",
    "    return smallest_error, best_chromosome\n",
    "\n",
    "def clone_populationj3(best_chromosome, population_size):\n",
    "    \"\"\"Creates a new population by cloning the best chromosome.\"\"\"\n",
    "    return [best_chromosome] * population_size\n",
    "\n",
    "\n",
    "def mutatej3(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_allj3(population, mutation_rate, alphabet):\n",
    "    \"\"\"Mutates all chromosomes in the population.\"\"\"\n",
    "    mutated_population = []\n",
    "    for chromosome in population:\n",
    "        mutated_chromosome = mutatej3(chromosome, mutation_rate, alphabet)\n",
    "        mutated_population.append(mutated_chromosome)\n",
    "    return mutated_population\n",
    "\n",
    "def crossoverj3(parent1, parent2, length_of_chromosomes, recombination_rate):\n",
    "    \"\"\"Performs crossover between two parent chromosomes.\"\"\"\n",
    "    if random.random() < recombination_rate:\n",
    "        crossover_point = random.randint(0, length_of_chromosomes)\n",
    "        return parent1[:crossover_point] + parent2[crossover_point:]\n",
    "    else:\n",
    "        return parent1\n",
    "\n",
    "def crossover_allj3(population, length_of_chromosomes, 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 = crossoverj3(parent1, parent2, length_of_chromosomes, recombination_rate)\n",
    "        recombinant_population.append(child)\n",
    "    return recombinant_population\n",
    "\n",
    "\n",
    "\n",
    "def run_one_generationj3(population, xArray, yArray, mutation_rate, recombination_rate, alphabet):\n",
    "    \"\"\"Runs one generation of the genetic algorithm.\"\"\"\n",
    "    # Calculate fitness scores for the current population\n",
    "    smallest_error, best_chromosome  = select_the_least_errorj3(population, xArray, yArray)\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_populationj3:\n",
    "        new_population = clone_populationj3(best_chromosome, population_size)\n",
    "    if include_mutate_allj3:\n",
    "        new_population = mutate_allj3(new_population, mutation_rate, alphabet)\n",
    "    if include_crossover_allj3:\n",
    "        new_population = crossover_allj3(new_population, length_of_chromosomes, recombination_rate)\n",
    "    return smallest_error, best_chromosome, new_population\n",
    "\n",
    "\n",
    "\n",
    "def plot_functionj3(g_values, 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 taskj3( xArray, yArray, mutation_rate, recombination_rate, alphabet, percentageOfTask):\n",
    "    \n",
    "    population = create_populationj3(population_size, length_of_chromosomes, alphabet)\n",
    "    # print(population)\n",
    "    generation = 0\n",
    "    best_chromosome = ''\n",
    "    best_fitness = 0\n",
    "    start_time = time.time()\n",
    "    smallest_error_history = [] # List to store best fitness of each generation\n",
    "    if print_best_fitness:\n",
    "        print(\"Generation, best_chromosome and best_fitness\")\n",
    "    while generation < number_of_generations:\n",
    "        generation += 1\n",
    "        smallest_error, best_chromosome, population = run_one_generationj3(population, xArray,yArray, mutation_rate, recombination_rate, alphabet)\n",
    "        if print_best_fitness:\n",
    "            print(f\" {generation}  {best_chromosome} {smallest_error}\")\n",
    "        smallest_error_history.append(smallest_error)\n",
    "    # print(f\"\\nTarget sequence matched in generation {generation}\")\n",
    "    # print(f\"Final chromosome: {best_chromosome}\")\n",
    "    totalCost = population_size * generation\n",
    "    \n",
    "    return  best_chromosome, totalCost, smallest_error_history\n",
    "\n",
    "def main(xArray, yArray, mutation_rate, recombination_rate, alphabet, length_of_chromosomes):\n",
    "    print_parametersj3()\n",
    "    print(\"Total cost = population size * number of generations\")\n",
    "    best_chromosome, totalCost, smallest_error_history = taskj3(xArray, yArray, mutation_rate, recombination_rate, alphabet, length_of_chromosomes)\n",
    "    final_error = smallest_error_history[-1]\n",
    "    print(f\" The best chromosome is {best_chromosome}\" )\n",
    "    coefficients = decodeFullCromosomej3(best_chromosome, length_of_chromosomes)\n",
    "    print(f\" Encoded coefficients: Intercept {coefficients[0]}, slope {coefficients[1]}, quadratic {coefficients[2]}, cubic {coefficients[3]}, quartic {coefficients[4]}, quintic {coefficients[5]}\")\n",
    "    print(f\" Total cost =  {totalCost} chromosomes\")\n",
    "    print(f\" Final error =  {final_error} \")\n",
    "\n",
    "    # Plot the fitness history    \n",
    "    g_values = list(range(1, len(smallest_error_history) + 1))\n",
    "    plot_functionj3(g_values, smallest_error_history, xlabel='Generation', ylabel='SmallestError', title='Smallest Error Over Generations')\n",
    "\n",
    "\n",
    "    # Perform polynomial regression\n",
    "    # Fit a polynomial of degree 5 (polynomial regression)\n",
    "    p_fitted = Polynomial.fit(xArray, yArray, deg=5)\n",
    "    a_0, a_1, a_2, a_3, a_4, a5 = p_fitted.convert().coef\n",
    "    print(f\"Polynomial regression coefficients: Intercept {a_0}, slope {a_1}, quadratic {a_2}, cubic {a_3}, quartic {a_4}, quintic {a5}\")\n",
    "    # Create the regression graph\n",
    "    x_new = np.linspace(-2,3, 100) # Generate 100 points between -2 and 3 for a smooth curve\n",
    "    y_new = p_fitted(x_new)\n",
    "\n",
    "    # The best chromosome encodes for the coefficients of the polynomial that best fits the data points\"\n",
    "    b_0, b_1, b_2, b_3, b_4, b5 = decodeFullCromosomej3(best_chromosome, length_of_chromosomes)\n",
    "    print(f\"Encoded coefficients: Intercept {b_0}, slope {b_1}, quadratic {b_2}, cubic {b_3}, quartic {b_4}, quintic {b5}\")\n",
    "    # Calculate the predicted y value based on the coefficients of the polynomial\n",
    "    our_polynomial = b_0 + b_1 * np.array(x_new ) + b_2 * np.array(x_new )**2 + b_3 * np.array(x_new )**3 + b_4 * np.array(x_new )**4 + b5 * np.array(x_new )**5\n",
    "    \n",
    "\n",
    "\n",
    "    # Plot the original data, the regression polynomial, and our polynomial\n",
    "    plt.figure(figsize=(10, 6))\n",
    "    plt.scatter(xArray, yArray, label='Observed Data')\n",
    "    plt.plot(x_new, y_new, color='red', label=f'Polynomial Regression: y = {a_0:.2f} + {a_1:.2f}x + {a_2:.2f}x^2 + {a_3:.2f}x^3 + {a_4:.2f}x^4 + {a5:.2f}x^5')\n",
    "    plt.plot(x_new,        our_polynomial, color='green', label=f'Our polynomial: y = {b_0:.2f} + {b_1:.2f}x + {b_2:.2f}x^2 + {b_3:.2f}x^3 + {b_4:.2f}x^4 + {b5:.2f}x^5')\n",
    "    plt.xlabel('Independent variable (x)')\n",
    "    plt.ylabel('Dependent variable (y)')\n",
    "    plt.title('Linear Regression and la Evolución minimize the error of the line with respect to the data points')\n",
    "    plt.legend()\n",
    "    plt.grid(True)\n",
    "    plt.show()\n",
    "\n",
    "    # Plot the original data and the regression polynomial\n",
    "    plt.figure(figsize=(10, 6))\n",
    "    plt.scatter(xArray, yArray, label='Observed Data')\n",
    "    plt.plot(x_new, y_new, color='red', label=f'Polynomial Regression: y = {a_0:.2f} + {a_1:.2f}x + {a_2:.2f}x^2 + {a_3:.2f}x^3 + {a_4:.2f}x^4 + {a5:.2f}x^5')\n",
    "    plt.xlabel('Independent variable (x)')\n",
    "    plt.ylabel('Dependent variable (y)')\n",
    "    plt.title('Linear Regression minimizes the error of the line with respect to the data points')\n",
    "    plt.legend()\n",
    "    plt.grid(True)\n",
    "    plt.show()\n",
    "\n",
    "    # Plot  our polynomial\n",
    "    plt.figure(figsize=(10, 6))\n",
    "    plt.scatter(xArray, yArray, label='Observed Data')\n",
    "    #plt.plot(xArray, regression_polynomial, color='red', label=f'Polynomial Regression: y = {a_0:.2f} + {a_1:.2f}x + {a_2:.2f}x^2 + {a_3:.2f}x^3 + {a_4:.2f}x^4 + {a5:.2f}x^5')\n",
    "    plt.plot(x_new,        our_polynomial, color='green', label=f'Our polynomial: y = {b_0:.2f} + {b_1:.2f}x + {b_2:.2f}x^2 + {b_3:.2f}x^3 + {b_4:.2f}x^4 + {b5:.2f}x^5')\n",
    "    plt.xlabel('Independent variable (x)')\n",
    "    plt.ylabel('Dependent variable (y)')\n",
    "    plt.title('la Evoluciónary Regression minimizes the error of the line with respect to the data points')\n",
    "    plt.legend()\n",
    "    plt.grid(True)\n",
    "    plt.show()\n",
    "\n",
    "\n",
    "    end_time = time.time()\n",
    "    # Calculate the difference in seconds\n",
    "    elapsed_time = end_time - start_time\n",
    "    elapsed_time = timedelta(seconds=elapsed_time)\n",
    "    print(f\"Elapsed time: {elapsed_time}\")\n",
    "    #return best_chromosome, totalCost, best_fitness_history\n",
    "\n",
    "# Call the main function with the defined parameters\n",
    "main(xArray, yArray, mutation_rate, recombination_rate, alphabet, length_of_chromosomes)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "7d8766e5",
   "metadata": {},
   "source": [
    "\n",
    "\n",
    "*Nuestras observaciones. * \n",
    "\n",
    "- Para 1000 generaciones, el error final fue 18.13, 15.99, 14.8, 16.8. \n",
    "- Para 10000 generaciones, el error final fue 74.9, 20.81\n",
    "- Para 100000 generaciones, el error final fue 151.2, 17.29\n",
    "- Para 300000 generaciones, el error final fue 11.75, 2.7, 15.4, 12.6 \n",
    "- Para 1000000 generaciones, el error final fue 12.1\n",
    "- No hemos podido encontrar un ajuste perfecto. En lugar de ser cero, el error mínimo encontrado fue 2.7, era muy caro y no era reproducible. \n",
    "  \n",
    "*Nuestro diagnóstico* \n",
    ">\n",
    "> No hemos sido capaces de encontrar la solución perfecta. Puede ser porque hemos probado un enfoque muy particular, no el más general, o porque la perfección puede ser muy cara, o porque nos hemos quedado atrapados en un extremo local, o porque la Evolución no es tan poderosa. \n",
    "\n",
    " ¿Qué haremos?\n",
    "\n",
    "## Valorar la variabilidad\n",
    "\n",
    "Recurramos a una solución multifuncional: crear y conservar la variabilidad. Los efectos esperados son:\n",
    ">\n",
    "> Se requiere un enfoque más general. Hemos estado utilizando MAX, seleccionando el más adecuado y clonándolo para crear la próxima generación. Esta es una contradicción semántica porque la clonación mata la variabilidad de entre la cual la selección del más apto elige el mejor. Pero, si la variabilidad se mata de manera recurrente, ¿qué podemos esperar? La solución es conservar la variabilidad, reproducir no sólo al campeón sino también a otros individuos. Y no despreciar al perdedor porque, aparte de nuestros propios resultados anteriores, en cada cultura hay una leyenda sobre un perdedor épico.\n",
    ">\n",
    "> ¿Y qué tal quedar atrapado en un óptimo local?  La Evolución maximiza la función de fitness. Aunque, en nuestro problema actual, minimiza la función de error. Los valores mínimo y máximo son extremos. Si dibujamos el gráfico de, por ejemplo, la aptitud de los cromosomas, tenemos un paisaje parecido a una montaña, con algunos picos más altos que otros. El propósito de la Evolución es ascender al pico más alto. Pero sucede que una selección subóptima podría tener una gran cuenca de atracción, y por lo tanto, la posibilidad de saltar por mutación o recombinación a la aptitud más alta es baja. Podríamos estar experimentando esa situación aquí. En la jerga oficial se dice: estamos atrapados en un extremo local o máximo o mínimo, y la sabiduría consiste en dejarlo para un futuro mejor. Por eso necesitamos más variabilidad.\n",
    ">\n",
    "> Si la variabilidad aumenta, la solución se puede encontrar más rápido y el costo disminuye. \n",
    ">\n",
    "> Existen dos soluciones inmediatas:\n",
    "> \n",
    ">> 1. Conservar la variabilidad. Un camino habitual es asignar a cada cromosoma una probabilidad de reproducción que sea proporcional a la aptitud. Esto se implementa en el próximo programa, aunque de alguna manera conspicua.\n",
    ">>>\n",
    ">> 2. Crear más variabilidad. Uno puede aumentar las tasas de mutación y recombinación. \n",
    "\n",
    "Implementemos ahora la conservación de la variabilidad.\n",
    "\n",
    "\n",
    "**Desafío.** Prueba al revés. Primero optimizar los parámetros de mutación y recombinación y luego ejecutar la Evolución conservando la variabilidad. \n",
    "\n",
    "\n",
    "\n",
    "### Conservación de la variabilidad\n",
    "\n",
    "Debemos hacer algunos cambios para conservar la variabilidad.\n",
    "\n",
    "**Ejemplo.** El siguiente código encuentra un ajuste polinomial a un conjunto de puntos. Conserva la variabilidad:\n",
    ">\n",
    " > Incorporamos un algoritmo de renombre, Tournament Selection, para crear la próxima generación que no mate la variabilidad. En lugar de tomar el MAX de la población total, tomamos el MAX de una muestra reducida, que luego se convierte en un padre de la siguiente generación. Se encuentra un compañero para ese progenitor para el cruce por el mismo procedimiento, y la pareja es sometida a recombinación, y el resultado a mutación. La implementación se tomó del programa `Program FastLabSimpleGeneticAlgorithm.py`, que fue desarrollado por Gemini para una contribución previa (MUTATION AND THE MAX-ROCKET CHALLENGE). \n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "249da0a5",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Lab: Evolution finds the polynomial of minimal error\n",
      "Purpose: Use a Genetic Algorithm (tournament selection, mutation, recombination) to find the coefficients of a polynomial that best fits a set of points.\n",
      "Date of Experiment  = 2026-04-20 13:01:41.405727\n",
      "number_of_generations = 100000\n",
      "length_of_chromosomes = 9\n",
      "alphabet =  0123456789\n",
      "Points = [(-2, 5), (-1, 1), (0, 4), (1, 0), (2, 6), (3, 3)]\n",
      "population_size = 200\n",
      "include_clone_populationj4 = True\n",
      "include_mutate_allj4 = True\n",
      "include_crossover_allj4 = True\n",
      "mutation_rate = 0.01\n",
      "recombination_rate = 0.01\n",
      "print_best_fitness = False\n",
      "Total cost = population size * number of generations\n",
      " The best chromosome is 679999999473332966878587912189999999999999999199999999\n",
      " Encoded coefficients: Intercept 0.9999998999999999, slope 0.3332966, quadratic 0.8587912, cubic -0.09999999, quartic  -0.009999999, quintic -0.009999999\n",
      " Total cost =  20000000 chromosomes\n",
      " Final error =  19.12574152100582 \n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Decoded coefficients: Intercept 0.9999998999999999, slope 0.3332966, quadratic 0.8587912, cubic -0.09999999, quartic -0.009999999, quintic -0.009999999\n",
      "Polynomial regression coefficients: Intercept 4.0, slope -2.983333333333327, quadratic -4.791666666666659, cubic 3.041666666666663, quartic 1.2916666666666643, quintic -0.5583333333333323\n",
      "Encoded coefficients: Intercept 0.9999998999999999, slope 0.3332966, quadratic 0.8587912, cubic -0.09999999, quartic -0.009999999, quintic -0.009999999\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"
    },
    {
     "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": [
      "Elapsed time: 0:11:33.188854\n"
     ]
    }
   ],
   "source": [
    "# Program PolynomialMinimalErrorTournamentSelection.py\n",
    "# This program uses a genetic algorithm to find the polynomial \n",
    "# of fifth degree that best fits a set of 6 points.\n",
    "# The coefficients are represented by a chromosome, \n",
    "# which is a string of digits.\n",
    "# The decoding function must divide the chromosome into parts, \n",
    "# and decode each one apart as one coefficient.\n",
    "# The error of a chromosome is the sum of the vertical quadratic distances \n",
    "# of the points to the polynomial it encodes.\n",
    "# The Genetic algorithm must minimize the error, \n",
    "# (which is equivalent to maximizing the fitness).\n",
    "# We use tournament selection, mutation and recombination to evolve the population of chromosomes.\n",
    "# The algorithm of tournament selection is as follows:\n",
    "# 1. Randomly select a group of chromosomes from the population (the tournament).\n",
    "# 2. Evaluate the fitness of each chromosome in the tournament.\n",
    "# 3. Select the chromosome with the best fitness as the parent for the next generation. \n",
    "# 4. Find a partner for the parent by repeating steps 1-3.\n",
    "# 5. Perform crossover between the parent and the partner to create a child chromosome.\n",
    "# 6. Mutate the child chromosome with a certain mutation rate.\n",
    "# 7. Add the child chromosome to the new population.\n",
    "# 8. Repeat steps 1-7 until the new population is complete.\n",
    "# Developed with the assistance of the AI of Visual Studio Code.\n",
    "# An old version of a GA developed with the help of Gemini was reused and updated.\n",
    "\n",
    "\n",
    "from datetime import datetime, timedelta\n",
    "import time\n",
    "import random\n",
    "import numpy as np\n",
    "from numpy.polynomial import Polynomial\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",
    "#Task to be done\n",
    "number_of_generations = 100000\n",
    "\n",
    "xArray =  [-2, -1, 0, 1, 2, 3]\n",
    "yArray =  [5,   1, 4, 0, 6, 3]\n",
    "\n",
    "alphabet = '0123456789'\n",
    "length_of_chromosomes = 9\n",
    "population_size = 200\n",
    "# Include cloning of the fittest\n",
    "include_clone_populationj4 = True\n",
    "# Include mutation\n",
    "include_mutate_allj4 = True\n",
    "# Include recombination\n",
    "include_crossover_allj4 = True\n",
    "mutation_rate = 0.01\n",
    "recombination_rate = 0.01\n",
    "# Size of the sampled groups from which the best \n",
    "# is chosen as a parent for the next generation.\n",
    "tournament_size = 5\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",
    "def print_parametersj4():\n",
    "    print(f\"Lab: la Evolución finds the polynomial of minimal error\")\n",
    "    print(\"Purpose: Use a Genetic Algorithm (tournament selection, mutation, recombination) to find the coefficients of a polynomial that best fits a set of points.\")\n",
    "    print(f\"Date of Experiment  = {datetime.datetime.now()}\")\n",
    "    print(f\"number_of_generations = {number_of_generations}\")\n",
    "    print(f\"length_of_chromosomes = {length_of_chromosomes}\")\n",
    "    print(f\"alphabet =  {alphabet}\")\n",
    "    print(f\"Points = {list(zip(xArray, yArray))}\")\n",
    "    print(f\"population_size = {population_size}\")\n",
    "    print(f\"include_clone_populationj4 = {include_clone_populationj4}\")\n",
    "    print(f\"include_mutate_allj4 = {include_mutate_allj4}\")\n",
    "    print(f\"include_crossover_allj4 = {include_crossover_allj4}\")\n",
    "    if include_mutate_allj4:\n",
    "        print(f\"mutation_rate = {mutation_rate}\")\n",
    "    if include_crossover_allj4:\n",
    "        print(f\"recombination_rate = {recombination_rate}\")\n",
    "    if include_clone_populationj4:\n",
    "        print(f\"print_best_fitness = {print_best_fitness}\")\n",
    "\n",
    "def draw_points_and_polynomialj4(xNumpyArray, yNumpyArray):\n",
    "    \"\"\"Draws the original data points, finds and draws the \n",
    "    regression polynomial defined by the coefficients.\"\"\"\n",
    "    \n",
    "    # 2. Fit a 5th-degree (quintic) polynomial\n",
    "    # .fit() returns a Polynomial instance\n",
    "    p_fitted = Polynomial.fit(xNumpyArray, yNumpyArray, deg=5)\n",
    "\n",
    "    # 3. Predict values for visualization\n",
    "    x_new = np.linspace(-2,3, 100) # Generate 100 points between 0 and 6 for a smooth curve\n",
    "    y_new = p_fitted(x_new)\n",
    "    b_0, b_1, b_2, b_3, b_4, b5 = p_fitted.coef\n",
    "\n",
    "    # 4. Plot results\n",
    "    plt.scatter(xNumpyArray, yNumpyArray, label='Data Points')\n",
    "    plt.xlabel('x')\n",
    "    plt.ylabel('y')\n",
    "    plt.plot(x_new, y_new, label=f'Quintic Fit: y = {b_0:.2f} + {b_1:.2f}x + {b_2:.2f}x^2 + {b_3:.2f}x^3 + {b_4:.2f}x^4 + {b5:.2f}x^5', color='green')\n",
    "    plt.title(' Data Points and Quintic Fit by numpy')\n",
    "    plt.legend()\n",
    "    plt.show()\n",
    "    return p_fitted.coef\n",
    "\n",
    "\n",
    "def create_populationj4(population_size, length_of_chromosomes, alphabet):\n",
    "    \"\"\"Creates a new population with random chromosomes.\"\"\"\n",
    "    # print(\"create_populationj4(population_size, target_sequence, alphabet)\")\n",
    "    population = []\n",
    "    for _ in range(population_size):\n",
    "        random_string1 = ''.join(random.choice(alphabet) for _ in range(length_of_chromosomes))\n",
    "        random_string2 = ''.join(random.choice(alphabet) for _ in range(length_of_chromosomes))\n",
    "        random_string3 = ''.join(random.choice(alphabet) for _ in range(length_of_chromosomes))\n",
    "        random_string4 = ''.join(random.choice(alphabet) for _ in range(length_of_chromosomes))\n",
    "        random_string5 = ''.join(random.choice(alphabet) for _ in range(length_of_chromosomes))\n",
    "        random_string6 = ''.join(random.choice(alphabet) for _ in range(length_of_chromosomes))\n",
    "        random_string = random_string1 + random_string2 + random_string3 + random_string4 + random_string5 + random_string6\n",
    "        population.append(random_string)\n",
    "    # print(\"initial population\")\n",
    "    # print(population)\n",
    "    return population\n",
    "\n",
    "# Decode a part of the chromosome into a coefficient of the polynomial.\n",
    "def decoderj4(s):\n",
    "    ''' The input is a number as string, outputs the number as a float. '''\n",
    "    \n",
    "    l = len(s)\n",
    "    # The first char encodes for the sign, \n",
    "    sign = 1\n",
    "    if  float(s[0]) % 2 == 1:\n",
    "        sign = -1\n",
    "    # The second char encodes for the position of the decimal point,\n",
    "    d = float(s[1])\n",
    "    # The remaining chars encode for the number itself, \n",
    "    # without the decimal point nor sign.\n",
    "    n = float(s[2:l])\n",
    "    return sign * (n * (10**-d))\n",
    "\n",
    "def decodeFullCromosomej4(chromosome, length_of_chromosomes):\n",
    "    \"\"\"Decodes the full chromosome into the coefficients of the polynomial.\"\"\"\n",
    "    \"\"\"The chromosome is divided into 5 parts, \n",
    "        each one encoding for a coefficient of the polynomial.\"\"\"\n",
    "    chro0 = chromosome[0:length_of_chromosomes]\n",
    "    chro1 = chromosome[length_of_chromosomes:2*length_of_chromosomes]\n",
    "    chro2 = chromosome[2*length_of_chromosomes:3*length_of_chromosomes]\n",
    "    chro3 = chromosome[3*length_of_chromosomes:4*length_of_chromosomes]\n",
    "    chro4 = chromosome[4*length_of_chromosomes:5*length_of_chromosomes]\n",
    "    chro5 = chromosome[5*length_of_chromosomes:6*length_of_chromosomes]\n",
    "    a_0 = decoderj4(chro0)\n",
    "    a_1 = decoderj4(chro1)\n",
    "    a_2 = decoderj4(chro2)\n",
    "    a_3 = decoderj4(chro3)\n",
    "    a_4 = decoderj4(chro4)\n",
    "    a_5 = decoderj4(chro5)\n",
    "    return a_0, a_1, a_2, a_3, a_4, a_5\n",
    "\n",
    "\n",
    "def calculate_errorj4(chromosome, xArray, yArray, length_of_chromosomes):\n",
    "    \"\"\"Calculates the error of a chromosome.\n",
    "        A chromosome encodes for the coefficients of a polynomial of fith degree.\n",
    "        The error of a chromosome is the sum of \n",
    "        the vertical distances of the points to the polynomial it encodes.\n",
    "    \"\"\"\n",
    "    #  print(\"\\n calculate_errorj4(chromosome, xArray, yArray)\")\n",
    "    a_0, a_1, a_2, a_3, a_4, a_5 = decodeFullCromosomej4(chromosome, length_of_chromosomes) \n",
    "    error = 0\n",
    "    for i in range(len(xArray)):\n",
    "        x = xArray[i]\n",
    "        y = yArray[i]\n",
    "        # Calculate the predicted y value based on the coefficients of the polynomial\n",
    "        predicted_y = a_0 + a_1 * x + a_2 * x**2 + a_3 * x**3 + a_4 * x**4 + a_5 * x**5\n",
    "        # Calculate the error as the quadratic difference \n",
    "        # between predicted and y value\n",
    "        error += (predicted_y - y)**2\n",
    "    return error\n",
    "\n",
    "def calculate_all_errorsj4(population, xArray, yArray,   length_of_chromosomes):\n",
    "    # print(\"\\n*calculate_all_errorsj4(population, target_sequence)\")\n",
    "    \"\"\"Calculates the error of all chromosomes in the population.\"\"\"\n",
    "    errors = [calculate_errorj4(chromosome, xArray, yArray, length_of_chromosomes) for chromosome in population]\n",
    "    # print(\"errors: \", errors)\n",
    "    return errors\n",
    "\n",
    "def select_the_least_errorj4(population, xArray, yArray, length_of_chromosomes):\n",
    "    \"\"\"Selects the best chromosome with minimal error for reproduction.\"\"\"\n",
    "    errors = calculate_all_errorsj4(population, xArray, yArray, length_of_chromosomes)\n",
    "    smallest_error = min(errors)\n",
    "    best_chromosome_index = errors.index(smallest_error)\n",
    "    best_chromosome = population[best_chromosome_index]\n",
    "    # print(\"\\n*select_the_least_errorj4(population)\")\n",
    "    # print(\"smallest_error = \", smallest_error)\n",
    "    # print(\"The chro = \", best_chromosome )\n",
    "    return smallest_error, best_chromosome\n",
    "\n",
    "def mutatej4(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",
    "##########\n",
    "\n",
    "# Define a more efficient reproduction function using tournament selection \n",
    "# and single-point crossover\n",
    "# To conserve variability, instead of taking the best chromosome \n",
    "# from the complete population and cloning it,\n",
    "# we can use tournament selection.\n",
    "# In it, parents for reproduction are chosen as the best of a small sample. \n",
    "# and then apply single-point crossover to create offspring, followed by mutation.\n",
    "def tournament_selectionOldj4(population, fitness_scores, tournament_size):\n",
    "    \"\"\"Selects a parent chromosome using tournament selection.\"\"\"\n",
    "    selected_indices = random.sample(range(len(population)), tournament_size)\n",
    "    best_index = selected_indices[0]\n",
    "    for index in selected_indices:\n",
    "        if fitness_scores[index] > fitness_scores[best_index]:\n",
    "            best_index = index\n",
    "    return population[best_index]\n",
    "\n",
    "def tournament_selectionj4(population, errors, tournament_size):\n",
    "    \"\"\"Selects a parent chromosome using tournament selection.\"\"\"\n",
    "    selected_indices = random.sample(range(len(population)), tournament_size)\n",
    "    best_index = selected_indices[0]\n",
    "    for index in selected_indices:\n",
    "        if errors[index] < errors[best_index]:\n",
    "            best_index = index\n",
    "    return population[best_index]\n",
    "\n",
    "def single_point_crossoverj4(parent1, parent2):\n",
    "    \"\"\"Performs single-point crossover between two parent chromosomes.\"\"\"\n",
    "    crossover_point = random.randint(0, len(parent1))\n",
    "    return parent1[:crossover_point] + parent2[crossover_point:]\n",
    "\n",
    "def reproduce_efficientj4(population, fitness_scores, mutation_rate, recombination_rate, alphabet, tournament_size):\n",
    "    \"\"\"Creates a new population through reproduction with tournament selection, single-point crossover, and mutation.\"\"\"\n",
    "    new_population = []\n",
    "    for _ in range(len(population)):\n",
    "        parent1 = tournament_selectionj4(population, fitness_scores, tournament_size)\n",
    "        parent2 = tournament_selectionj4(population, fitness_scores, tournament_size)\n",
    "        if random.random() < recombination_rate:\n",
    "            child = single_point_crossoverj4(parent1, parent2)\n",
    "        else:\n",
    "            child = random.choice([parent1, parent2]) # Choose one parent if no crossover\n",
    "        mutated_child = mutatej4(child, mutation_rate, alphabet)\n",
    "        new_population.append(mutated_child)\n",
    "    return new_population\n",
    "\n",
    "\n",
    "\n",
    "def run_one_generationj4(population, xArray, yArray, mutation_rate, recombination_rate, alphabet, length_of_chromosomes, tournament_size):\n",
    "    \"\"\"Runs one generation of the genetic algorithm.\"\"\"\n",
    "    # Calculate error scores for the current population\n",
    "    errors = calculate_all_errorsj4(population, xArray, yArray, length_of_chromosomes)\n",
    "    new_population =  reproduce_efficientj4(population, errors, mutation_rate, recombination_rate, alphabet, tournament_size)\n",
    "    smallest_error, best_chromosome  = select_the_least_errorj4(population, xArray, yArray, length_of_chromosomes)\n",
    "    return smallest_error, best_chromosome, new_population\n",
    "\n",
    "\n",
    "\n",
    "def plot_functionj4(g_values, 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 taskj4( xArray, yArray, mutation_rate, recombination_rate, alphabet, length_of_chromosomes, tournament_size):\n",
    "    \n",
    "    population = create_populationj4(population_size, length_of_chromosomes, alphabet)\n",
    "    # print(population)\n",
    "    generation = 0\n",
    "    best_chromosome = ''\n",
    "    best_fitness = 0\n",
    "    start_time = time.time()\n",
    "    smallest_error_history = [] # List to store best fitness of each generation\n",
    "    if print_best_fitness:\n",
    "        print(\"Generation, best_chromosome and best_fitness\")\n",
    "    while generation < number_of_generations:\n",
    "        generation += 1\n",
    "        smallest_error, best_chromosome, population = run_one_generationj4(population, xArray,yArray, mutation_rate, recombination_rate, alphabet, length_of_chromosomes, tournament_size)\n",
    "        if print_best_fitness:\n",
    "            print(f\" {generation}  {best_chromosome} {smallest_error}\")\n",
    "        smallest_error_history.append(smallest_error)\n",
    "    # print(f\"\\nTarget sequence matched in generation {generation}\")\n",
    "    # print(f\"Final chromosome: {best_chromosome}\")\n",
    "    totalCost = population_size * generation\n",
    "    \n",
    "    return  best_chromosome, totalCost, smallest_error_history\n",
    "\n",
    "def mainj4(xArray, yArray, mutation_rate, recombination_rate, alphabet, length_of_chromosomes, tournament_size):\n",
    "    print_parametersj4()\n",
    "    print(\"Total cost = population size * number of generations\")\n",
    "    best_chromosome, totalCost, smallest_error_history = taskj4(xArray, yArray, mutation_rate, recombination_rate, alphabet, length_of_chromosomes, tournament_size)\n",
    "    final_error = smallest_error_history[-1]\n",
    "    print(f\" The best chromosome is {best_chromosome}\" )\n",
    "    coefficients = decodeFullCromosomej4(best_chromosome, length_of_chromosomes)\n",
    "    print(f\" Encoded coefficients: Intercept {coefficients[0]}, slope {coefficients[1]}, quadratic {coefficients[2]}, cubic {coefficients[3]}, quartic  {coefficients[4]}, quintic {coefficients[5]}\")\n",
    "    print(f\" Total cost =  {totalCost} chromosomes\")\n",
    "    print(f\" Final error =  {final_error} \")\n",
    "\n",
    "    # Plot the fitness history    \n",
    "    g_values = list(range(1, len(smallest_error_history) + 1))\n",
    "    plot_functionj4(g_values, smallest_error_history, xlabel='Generation', ylabel='SmallestError', title='Smallest Error Over Generations')\n",
    "    # The best chromosome encodes for the coefficients of the polynomial that best fits the data points\"\n",
    "    b_0, b_1, b_2, b_3, b_4, b5 = decodeFullCromosomej4(best_chromosome, length_of_chromosomes)\n",
    "    print(f\"Decoded coefficients: Intercept {b_0}, slope {b_1}, quadratic {b_2}, cubic {b_3}, quartic {b_4}, quintic {b5}\")\n",
    "    # Calculate the predicted y value based on the coefficients of the polynomial\n",
    "    our_polynomial = b_0 + b_1 * np.array(xArray) + b_2 * np.array(xArray)**2 + b_3 * np.array(xArray)**3 + b_4 * np.array(xArray)**4 + b5 * np.array(xArray)**5\n",
    "    \n",
    "\n",
    "    # Perform polynomial regression\n",
    "    # Fit a polynomial of degree 5 (polynomial regression)\n",
    "    p_fitted = Polynomial.fit(xArray, yArray, deg=5)\n",
    "    a_0, a_1, a_2, a_3, a_4, a5 = p_fitted.convert().coef\n",
    "    print(f\"Polynomial regression coefficients: Intercept {a_0}, slope {a_1}, quadratic {a_2}, cubic {a_3}, quartic {a_4}, quintic {a5}\")\n",
    "    # Create the regression graph\n",
    "    x_new = np.linspace(-2,3, 100) # Generate 100 points between -2 and 3 for a smooth curve\n",
    "    y_new = p_fitted(x_new)\n",
    "\n",
    "    # The best chromosome encodes for the coefficients of the polynomial that best fits the data points\"\n",
    "    b_0, b_1, b_2, b_3, b_4, b5 = decodeFullCromosomej4(best_chromosome, length_of_chromosomes)\n",
    "    print(f\"Encoded coefficients: Intercept {b_0}, slope {b_1}, quadratic {b_2}, cubic {b_3}, quartic {b_4}, quintic {b5}\")\n",
    "    # Calculate the predicted y value based on the coefficients of the polynomial\n",
    "    our_polynomial = b_0 + b_1 * np.array(x_new ) + b_2 * np.array(x_new )**2 + b_3 * np.array(x_new )**3 + b_4 * np.array(x_new )**4 + b5 * np.array(x_new )**5\n",
    "    \n",
    "\n",
    "\n",
    "    # Plot the original data, the regression polynomial, and our polynomial\n",
    "    plt.figure(figsize=(10, 6))\n",
    "    plt.scatter(xArray, yArray, label='Observed Data')\n",
    "    plt.plot(x_new, y_new, color='red', label=f'Polynomial Regression: y = {a_0:.2f} + {a_1:.2f}x + {a_2:.2f}x^2 + {a_3:.2f}x^3 + {a_4:.2f}x^4 + {a5:.2f}x^5')\n",
    "    plt.plot(x_new,        our_polynomial, color='green', label=f'Our polynomial: y = {b_0:.2f} + {b_1:.2f}x + {b_2:.2f}x^2 + {b_3:.2f}x^3 + {b_4:.2f}x^4 + {b5:.2f}x^5')\n",
    "    plt.xlabel('Independent variable (x)')\n",
    "    plt.ylabel('Dependent variable (y)')\n",
    "    plt.title('Linear Regression and la Evolución minimize the error of the line with respect to the data points')\n",
    "    plt.legend()\n",
    "    plt.grid(True)\n",
    "    plt.show()\n",
    "\n",
    "    # Plot the original data and the regression polynomial\n",
    "    plt.figure(figsize=(10, 6))\n",
    "    plt.scatter(xArray, yArray, label='Observed Data')\n",
    "    plt.plot(x_new, y_new, color='red', label=f'Polynomial Regression: y = {a_0:.2f} + {a_1:.2f}x + {a_2:.2f}x^2 + {a_3:.2f}x^3 + {a_4:.2f}x^4 + {a5:.2f}x^5')\n",
    "    plt.xlabel('Independent variable (x)')\n",
    "    plt.ylabel('Dependent variable (y)')\n",
    "    plt.title('Linear Regression minimizes the error of the line with respect to the data points')\n",
    "    plt.legend()\n",
    "    plt.grid(True)\n",
    "    plt.show()\n",
    "\n",
    "    # Plot  our polynomial\n",
    "    plt.figure(figsize=(10, 6))\n",
    "    plt.scatter(xArray, yArray, label='Observed Data')\n",
    "    #plt.plot(xArray, regression_polynomial, color='red', label=f'Polynomial Regression: y = {a_0:.2f} + {a_1:.2f}x + {a_2:.2f}x^2 + {a_3:.2f}x^3 + {a_4:.2f}x^4 + {a5:.2f}x^5')\n",
    "    plt.plot(x_new,        our_polynomial, color='green', label=f'Our polynomial: y = {b_0:.2f} + {b_1:.2f}x + {b_2:.2f}x^2 + {b_3:.2f}x^3 + {b_4:.2f}x^4 + {b5:.2f}x^5')\n",
    "    plt.xlabel('Independent variable (x)')\n",
    "    plt.ylabel('Dependent variable (y)')\n",
    "    plt.title('la Evoluciónary Regression minimizes the error of the line with respect to the data points')\n",
    "    plt.legend()\n",
    "    plt.grid(True)\n",
    "    plt.show()\n",
    "\n",
    "    \n",
    "\n",
    "    end_time = time.time()\n",
    "    # Calculate the difference in seconds\n",
    "    elapsed_time = end_time - start_time\n",
    "    elapsed_time = timedelta(seconds=elapsed_time)\n",
    "    print(f\"Elapsed time: {elapsed_time}\")\n",
    "    #return best_chromosome, totalCost, best_fitness_history\n",
    "\n",
    "# Call the main function with the defined parameters\n",
    "mainj4(xArray, yArray, mutation_rate, recombination_rate, alphabet, length_of_chromosomes, tournament_size)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "d6d73329",
   "metadata": {},
   "source": [
    "**Ejercicio.** Ejecuta el programa durante un número apropiado de generaciones y reporta tus observaciones.\n",
    "\n",
    "*Nuestras observaciones.* El AG anterior que conserva la variabilidad se corrió para obtener los siguientes resultados:\n",
    "\n",
    "- Para 1000 generaciones, el error final fue 18.68, 23.4, \n",
    "- Para 10000 generaciones, el error final fue 25.22, 15.4\n",
    "- para 100000 generaciones, el error final fue 18.13, 12.48, 9.4, 19.12\n",
    "- Para 300000 generaciones, el error final fue 15,4, 15,44\n",
    "- No hemos podido encontrar un ajuste perfecto. En lugar de cero, el error mínimo encontrado fue 9,4, era muy caro y no era reproducible. Parece que las únicas generaciones importantes fuesen las primeras 100. \n",
    "  \n",
    "\n",
    "*Evaluación.* Este nuevo algoritmo de selección por torneos, tomando el MÁXIMO de pequeñas muestras, no se ve mejor que el original basado en tomar el MÁXIMO de toda la población. Para el problema dado, esto es más lento y produce mayores errores. \n",
    "\n",
    "Necesitamos más ideas.\n",
    "\n",
    "**Ejercicio.**  Basado en el polinomio reportado por la solución matemática, los coeficientes tienen un valor absoluto que es inferior a 9. Ponga a prueba una codificación adecuada.\n",
    ">\n",
    "> *Respuesta.* Intentaremos con dos decimales, por ejemplo $-95,23$ o $0,03$. El código sigue.\n",
    "\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "ba3a6a8e",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Lab: Evolution finds the polynomial of minimal error\n",
      "Purpose: Use a Genetic Algorithm (MAX = selection of the fittest, mutation and recombination) to find the coefficients of a polynomial that best fits a set of points.\n",
      "Hint to be tested: consider only numbers of the form 93.24 with a sign that could be positive or negative, and a decimal point in the middle of the encoding chromosome.\n",
      "Date of Experiment  = 2026-04-23 07:52:16.437091\n",
      "number_of_generations = 300000\n",
      "length_of_chromosomes = 11\n",
      "alphabet =  0123456789\n",
      "Points = [(-2, 5), (-1, 1), (0, 4), (1, 0), (2, 6), (3, 3)]\n",
      "population_size = 200\n",
      "include_clone_populationj5 = True\n",
      "include_mutate_allj5 = True\n",
      "include_crossover_allj5 = True\n",
      "mutation_rate = 0.1\n",
      "recombination_rate = 1e-05\n",
      "print_best_fitness = False\n",
      "Total cost = population size * number of generations\n",
      " The best chromosome is 504001012700038681739941316773697904999999761028436830340100000000\n",
      " Encoded coefficientes: (-4.0010127, 3.86817399, 13.16773697, -4.99999976, -2.84368303, 1.0) \n",
      " Total cost =  60000000 chromosomes\n",
      " Final error =  144.71802061047606 \n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Decoded coefficients: Intercept -4.0010127, slope 3.86817399, quadratic 13.16773697, cubic -4.99999976, quartic -2.84368303, quintic 1.0\n",
      "Polynomial regression coefficients: Intercept 4.0, slope -2.983333333333327, quadratic -4.791666666666659, cubic 3.041666666666663, quartic 1.2916666666666643, quintic -0.5583333333333323\n",
      "Encoded coefficients: Intercept -4.0010127, slope 3.86817399, quadratic 13.16773697, cubic -4.99999976, quartic -2.84368303, quintic 1.0\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"
    },
    {
     "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": [
      "Elapsed time: 0:18:25.708908\n"
     ]
    }
   ],
   "source": [
    "# Program PolynomialMinimalEncoding.py\n",
    "# This program uses a genetic algorithm to find the polynomial \n",
    "# of fifth degree that best fits a set of 6 points.\n",
    "# The coefficients are represented by a chromosome, \n",
    "# which is a string of digits.\n",
    "# The decoding function must divide the chromosome into parts, \n",
    "# and decode each one apart as one coefficient.\n",
    "# We consider numbers of the form 93.24 \n",
    "# with a sign that could be positive or negative, \n",
    "# and a decimal point in the middle of the encoding chromosome.\n",
    "# The error of a chromosome is the sum of the vertical quadratic distances \n",
    "# of the points to the polynomial it encodes.\n",
    "# The Genetic algorithm must minimize the error, \n",
    "# (which is equivalent to maximizing the fitness).\n",
    "# Developed with the assistance of the AI of Visual Studio Code.\n",
    "# An old version of a GA developed with the help of Gemini was reused and updated.\n",
    "\n",
    "\n",
    "#from datetime import datetime, timedelta\n",
    "import datetime\n",
    "import time\n",
    "import random\n",
    "import numpy as np\n",
    "from numpy.polynomial import Polynomial\n",
    "import matplotlib.pyplot as plt # Import matplotlib for plotting\n",
    "\n",
    "\n",
    "start_time = time.time() # Record the start time\n",
    "\n",
    "#Task to be done\n",
    "number_of_generations = 10000\n",
    "\n",
    "xArray =  [-2, -1, 0, 1, 2, 3]\n",
    "yArray =  [5,   1, 4, 0, 6, 3]\n",
    "\n",
    "alphabet = '0123456789'\n",
    "# Chromosome encoding for one of 6 coefficients, \n",
    "# each one with a length of 5 chars.\n",
    "# Encoding number as -93.24 with a sign and a decimal point.\n",
    "length_of_chromosomes = 5\n",
    "population_size = 200\n",
    "# Include cloning of the fittest\n",
    "include_clone_populationj5 = True\n",
    "# Include mutation\n",
    "include_mutate_allj5 = True\n",
    "# Include recombination\n",
    "include_crossover_allj5 = True\n",
    "mutation_rate = 0.01\n",
    "recombination_rate = 0.01\n",
    "# Size of the sampled groups from which the best \n",
    "# is chosen as a parent for the next generation.\n",
    "tournament_size = 5\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",
    "def print_parametersj5():\n",
    "    print(f\"Lab: la Evolución finds the polynomial of minimal error\")\n",
    "    print(f\"Purpose: Use a Genetic Algorithm (MAX = selection of the fittest, mutation and recombination) to find the coefficients of a polynomial that best fits a set of points.\")\n",
    "    print(\"Hint to be tested: consider only numbers of the form 93.24 with a sign that could be positive or negative, and a decimal point in the middle of the encoding chromosome.\")\n",
    "    print(f\"Date of Experiment  = {datetime.datetime.now()}\")\n",
    "    print(f\"number_of_generations = {number_of_generations}\")\n",
    "    print(f\"length_of_chromosomes = {length_of_chromosomes}\")\n",
    "    print(f\"alphabet =  {alphabet}\")\n",
    "    print(f\"Points = {list(zip(xArray, yArray))}\")\n",
    "    print(f\"population_size = {population_size}\")\n",
    "    print(f\"include_clone_populationj5 = {include_clone_populationj5}\")\n",
    "    print(f\"include_mutate_allj5 = {include_mutate_allj5}\")\n",
    "    print(f\"include_crossover_allj5 = {include_crossover_allj5}\")\n",
    "    if include_mutate_allj5:\n",
    "        print(f\"mutation_rate = {mutation_rate}\")\n",
    "    if include_crossover_allj5:\n",
    "        print(f\"recombination_rate = {recombination_rate}\")\n",
    "    if include_clone_populationj5:\n",
    "        print(f\"print_best_fitness = {print_best_fitness}\")\n",
    "\n",
    "def draw_points_and_polynomialj5(xNumpyArray, yNumpyArray):\n",
    "    \"\"\"Draws the original data points, finds and draws the \n",
    "    regression polynomial defined by the coefficients.\"\"\"\n",
    "    \n",
    "    # 2. Fit a 5th-degree (quintic) polynomial\n",
    "    # .fit() returns a Polynomial instance\n",
    "    p_fitted = Polynomial.fit(xNumpyArray, yNumpyArray, deg=5)\n",
    "\n",
    "    # 3. Predict values for visualization\n",
    "    x_new = np.linspace(-2,3, 100) # Generate 100 points between 0 and 6 for a smooth curve\n",
    "    y_new = p_fitted(x_new)\n",
    "    b_0, b_1, b_2, b_3, b_4, b5 = p_fitted.coef\n",
    "\n",
    "    # 4. Plot results\n",
    "    plt.scatter(xNumpyArray, yNumpyArray, label='Data Points')\n",
    "    plt.xlabel('x')\n",
    "    plt.ylabel('y')\n",
    "    plt.plot(x_new, y_new, label=f'Quintic Fit: y = {b_0:.2f} + {b_1:.2f}x + {b_2:.2f}x^2 + {b_3:.2f}x^3 + {b_4:.2f}x^4 + {b5:.2f}x^5', color='green')\n",
    "    plt.title(' Data Points and Quintic Fit by numpy.polynomial.Polynomial.fit()')\n",
    "    plt.legend()\n",
    "    plt.show()\n",
    "    return p_fitted.coef\n",
    "\n",
    "\n",
    "\n",
    "def create_populationj5(population_size, length_of_chromosomes, alphabet):\n",
    "    \"\"\"Creates a new population with random chromosomes.\"\"\"\n",
    "    # print(\"create_populationj5(population_size, target_sequence, alphabet)\")\n",
    "    population = []\n",
    "    for _ in range(population_size):\n",
    "        random_string1 = ''.join(random.choice(alphabet) for _ in range(length_of_chromosomes))\n",
    "        random_string2 = ''.join(random.choice(alphabet) for _ in range(length_of_chromosomes))\n",
    "        random_string3 = ''.join(random.choice(alphabet) for _ in range(length_of_chromosomes))\n",
    "        random_string4 = ''.join(random.choice(alphabet) for _ in range(length_of_chromosomes))\n",
    "        random_string5 = ''.join(random.choice(alphabet) for _ in range(length_of_chromosomes))\n",
    "        random_string6 = ''.join(random.choice(alphabet) for _ in range(length_of_chromosomes))\n",
    "        random_string = random_string1 + random_string2 + random_string3 + random_string4 + random_string5 + random_string6\n",
    "        population.append(random_string)\n",
    "    # print(\"initial population\")\n",
    "    # print(population)\n",
    "    return population\n",
    "\n",
    "# Decode a part of the chromosome into a coefficient of the polynomial.\n",
    "def decoderj5(s):\n",
    "    ''' The input is a number as string, outputs the number as a float. \n",
    "        We consider numbers of the form 93.24 with a sign that could be positive or negative,\n",
    "    '''\n",
    "    \n",
    "    l = len(s)\n",
    "    if (l != 5):\n",
    "        print(f\"Error in decoder: the input string must have a length of 5 chars, but it has {l} chars. The input string is {s}.\")\n",
    "        return 0.0\n",
    "    # The first char encodes for the sign, \n",
    "    sign = 1\n",
    "    if  float(s[0]) % 2 == 1:\n",
    "        sign = -1\n",
    "    # The remaining chars encode for the number itself, \n",
    "    # without the decimal point nor sign.\n",
    "    sn = s[1:l]\n",
    "    # The point is inserted in the middle of the encoding string\n",
    "    sn = sn[:2] + \".\" + sn[2:]\n",
    "    # Convert the string to a number\n",
    "    n = float(sn)\n",
    "    return sign * n\n",
    "\n",
    "def decodeFullCromosomej5(chromosome, length_of_chromosomes):\n",
    "    \"\"\"Decodes the full chromosome into the coefficients of the polynomial.\"\"\"\n",
    "    \"\"\"The chromosome is divided into 5 parts, \n",
    "        each one encoding for a coefficient of the polynomial.\"\"\"\n",
    "    chro0 = chromosome[0:length_of_chromosomes]\n",
    "    chro1 = chromosome[length_of_chromosomes:2*length_of_chromosomes]\n",
    "    chro2 = chromosome[2*length_of_chromosomes:3*length_of_chromosomes]\n",
    "    chro3 = chromosome[3*length_of_chromosomes:4*length_of_chromosomes]\n",
    "    chro4 = chromosome[4*length_of_chromosomes:5*length_of_chromosomes]\n",
    "    chro5 = chromosome[5*length_of_chromosomes:6*length_of_chromosomes]\n",
    "    a_0 = decoderj5(chro0)\n",
    "    a_1 = decoderj5(chro1)\n",
    "    a_2 = decoderj5(chro2)\n",
    "    a_3 = decoderj5(chro3)\n",
    "    a_4 = decoderj5(chro4)\n",
    "    a_5 = decoderj5(chro5)\n",
    "    # print(f\"Chromosome: {chromosome}\")\n",
    "    # print(f\"Coefficients: Intercept {a_0}, slope {a_1}, quadratic {a_2}, cubic {a_3}, quartic {a_4}, quintic {a_5}\")\n",
    "    # print()\n",
    "    return a_0, a_1, a_2, a_3, a_4, a_5\n",
    "\n",
    "\n",
    "\n",
    "def calculate_errorj5(chromosome, xArray, yArray, length_of_chromosomes):\n",
    "    \"\"\"Calculates the error of a chromosome.\n",
    "        A chromosome encodes for the coefficients of a polynomial of fith degree.\n",
    "        The error of a chromosome is the sum of \n",
    "        the vertical distances of the points to the polynomial it encodes.\n",
    "    \"\"\"\n",
    "    #  print(\"\\n calculate_errorj5(chromosome, xArray, yArray)\")\n",
    "    a_0, a_1, a_2, a_3, a_4, a_5 = decodeFullCromosomej5(chromosome, length_of_chromosomes)  \n",
    "    error = 0\n",
    "    for i in range(len(xArray)):\n",
    "        x = xArray[i]\n",
    "        y = yArray[i]\n",
    "        # Calculate the predicted y value based on the coefficients of the polynomial\n",
    "        predicted_y = a_0 + a_1 * x + a_2 * x**2 + a_3 * x**3 + a_4 * x**4 + a_5 * x**5\n",
    "        # Calculate the error as the quadratic difference \n",
    "        # between predicted and y value\n",
    "        error += (predicted_y - y)**2\n",
    "    return error\n",
    "\n",
    "def calculate_all_errorsj5(population, xArray, yArray, length_of_chromosomes):\n",
    "    # print(\"\\n*calculate_all_errorsj5(population, target_sequence)\")\n",
    "    \"\"\"Calculates the error of all chromosomes in the population.\"\"\"\n",
    "    errors = [calculate_errorj5(chromosome, xArray, yArray, length_of_chromosomes) for chromosome in population]\n",
    "    # print(\"errors: \", errors)\n",
    "    return errors\n",
    "\n",
    "def select_the_least_errorj5(population, xArray, yArray, length_of_chromosomes):\n",
    "    \"\"\"Selects the best chromosome with minimal error for reproduction.\"\"\"\n",
    "    errors = calculate_all_errorsj5(population, xArray, yArray, length_of_chromosomes)\n",
    "    smallest_error = min(errors)\n",
    "    best_chromosome_index = errors.index(smallest_error)\n",
    "    best_chromosome = population[best_chromosome_index]\n",
    "    # print(\"\\n*select_the_least_errorj5(population)\")\n",
    "    # print(\"smallest_error = \", smallest_error)\n",
    "    # print(\"The chro = \", best_chromosome )\n",
    "    return smallest_error, best_chromosome\n",
    "\n",
    "def clone_populationj5(best_chromosome, population_size):\n",
    "    \"\"\"Creates a new population by cloning the best chromosome.\"\"\"\n",
    "    return [best_chromosome] * population_size\n",
    "\n",
    "\n",
    "def mutatej5(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_allj5(population, mutation_rate, alphabet):\n",
    "    \"\"\"Mutates all chromosomes in the population.\"\"\"\n",
    "    mutated_population = []\n",
    "    for chromosome in population:\n",
    "        mutated_chromosome = mutatej5(chromosome, mutation_rate, alphabet)\n",
    "        mutated_population.append(mutated_chromosome)\n",
    "    return mutated_population\n",
    "\n",
    "def crossoverj5(parent1, parent2, length_of_chromosomes, recombination_rate):\n",
    "    \"\"\"Performs crossover between two parent chromosomes.\"\"\"\n",
    "    if random.random() < recombination_rate:\n",
    "        crossover_point = random.randint(0, length_of_chromosomes)\n",
    "        return parent1[:crossover_point] + parent2[crossover_point:]\n",
    "    else:\n",
    "        return parent1\n",
    "\n",
    "def crossover_allj5(population, length_of_chromosomes, 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 = crossoverj5(parent1, parent2, length_of_chromosomes, recombination_rate)\n",
    "        recombinant_population.append(child)\n",
    "    return recombinant_population\n",
    "\n",
    "\n",
    "\n",
    "def run_one_generationj5(population, xArray, yArray, mutation_rate, recombination_rate, alphabet, length_of_chromosomes):\n",
    "    \"\"\"Runs one generation of the genetic algorithm.\"\"\"\n",
    "    # Calculate fitness scores for the current population\n",
    "    smallest_error, best_chromosome  = select_the_least_errorj5(population, xArray, yArray, length_of_chromosomes)\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_populationj5:\n",
    "        new_population = clone_populationj5(best_chromosome, population_size)\n",
    "    if include_mutate_allj5:\n",
    "        new_population = mutate_allj5(new_population, mutation_rate, alphabet)\n",
    "    if include_crossover_allj5:\n",
    "        new_population = crossover_allj5(new_population, length_of_chromosomes, recombination_rate)\n",
    "    return smallest_error, best_chromosome, new_population\n",
    "\n",
    "\n",
    "\n",
    "def plot_functionj5(g_values, 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 taskj5( xArray, yArray, mutation_rate, recombination_rate, alphabet,  length_of_chromosomes):\n",
    "    population = create_populationj5(population_size, length_of_chromosomes, alphabet)\n",
    "    # print(population)\n",
    "    generation = 0\n",
    "    best_chromosome = ''\n",
    "    best_fitness = 0\n",
    "    start_time = time.time()\n",
    "    smallest_error_history = [] # List to store best fitness of each generation\n",
    "    if print_best_fitness:\n",
    "        print(\"Generation, best_chromosome and best_fitness\")\n",
    "    while generation < number_of_generations:\n",
    "        generation += 1\n",
    "        smallest_error, best_chromosome, population = run_one_generationj5(population, xArray,yArray, mutation_rate, recombination_rate, alphabet, length_of_chromosomes)\n",
    "        if print_best_fitness:\n",
    "            print(f\" {generation}  {best_chromosome} {smallest_error}\")\n",
    "        smallest_error_history.append(smallest_error)\n",
    "    # print(f\"\\nTarget sequence matched in generation {generation}\")\n",
    "    # print(f\"Final chromosome: {best_chromosome}\")\n",
    "    totalCost = population_size * generation\n",
    "    return  best_chromosome, totalCost, smallest_error_history\n",
    "\n",
    "def mainj5(xArray, yArray, mutation_rate, recombination_rate, alphabet, length_of_chromosomes):\n",
    "    print_parametersj5()\n",
    "    print(\"Total cost = population size * number of generations\")\n",
    "    best_chromosome, totalCost, smallest_error_history = taskj5(xArray, yArray, mutation_rate, recombination_rate, alphabet, length_of_chromosomes)\n",
    "    final_error = smallest_error_history[-1]\n",
    "    print(f\" The best chromosome is {best_chromosome}\" )\n",
    "    coefficients = decodeFullCromosomej5(best_chromosome, length_of_chromosomes)\n",
    "    print(f\" Encoded coefficientes: {coefficients} \" )\n",
    "    print(f\" Total cost =  {totalCost} chromosomes\")\n",
    "    print(f\" Final error =  {final_error} \")\n",
    "\n",
    "    # Plot the fitness history    \n",
    "    g_values = list(range(1, len(smallest_error_history) + 1))\n",
    "    plot_functionj5(g_values, smallest_error_history, xlabel='Generation', ylabel='SmallestError', title='Smallest Error Over Generations')\n",
    "    # The best chromosome encodes for the coefficients of the polynomial that best fits the data points\"\n",
    "    b_0, b_1, b_2, b_3, b_4, b5 = decodeFullCromosomej5(best_chromosome, length_of_chromosomes)\n",
    "    print(f\"Decoded coefficients: Intercept {b_0}, slope {b_1}, quadratic {b_2}, cubic {b_3}, quartic {b_4}, quintic {b5}\")\n",
    "    # Calculate the predicted y value based on the coefficients of the polynomial\n",
    "    our_polynomial = b_0 + b_1 * np.array(xArray) + b_2 * np.array(xArray)**2 + b_3 * np.array(xArray)**3 + b_4 * np.array(xArray)**4 + b5 * np.array(xArray)**5\n",
    "    \n",
    "\n",
    "    # Perform polynomial regression\n",
    "    # Fit a polynomial of degree 5 (polynomial regression)\n",
    "    p_fitted = Polynomial.fit(xArray, yArray, deg=5)\n",
    "    a_0, a_1, a_2, a_3, a_4, a5 = p_fitted.convert().coef\n",
    "    print(f\"Polynomial regression coefficients: Intercept {a_0}, slope {a_1}, quadratic {a_2}, cubic {a_3}, quartic {a_4}, quintic {a5}\")\n",
    "    # Create the regression graph\n",
    "    x_new = np.linspace(-2,3, 100) # Generate 100 points between -2 and 3 for a smooth curve\n",
    "    y_new = p_fitted(x_new)\n",
    "\n",
    "    # The best chromosome encodes for the coefficients of the polynomial that best fits the data points\"\n",
    "    b_0, b_1, b_2, b_3, b_4, b5 = decodeFullCromosomej5(best_chromosome, length_of_chromosomes)\n",
    "    print(f\"Encoded coefficients: Intercept {b_0}, slope {b_1}, quadratic {b_2}, cubic {b_3}, quartic {b_4}, quintic {b5}\")\n",
    "    # Calculate the predicted y value based on the coefficients of the polynomial\n",
    "    our_polynomial = b_0 + b_1 * np.array(x_new ) + b_2 * np.array(x_new )**2 + b_3 * np.array(x_new )**3 + b_4 * np.array(x_new )**4 + b5 * np.array(x_new )**5\n",
    "    \n",
    "\n",
    "\n",
    "    # Plot the original data, the regression polynomial, and our polynomial\n",
    "    plt.figure(figsize=(10, 6))\n",
    "    plt.scatter(xArray, yArray, label='Observed Data')\n",
    "    plt.plot(x_new, y_new, color='red', label=f'Polynomial Regression: y = {a_0:.2f} + {a_1:.2f}x + {a_2:.2f}x^2 + {a_3:.2f}x^3 + {a_4:.2f}x^4 + {a5:.2f}x^5')\n",
    "    plt.plot(x_new,        our_polynomial, color='green', label=f'Our polynomial: y = {b_0:.2f} + {b_1:.2f}x + {b_2:.2f}x^2 + {b_3:.2f}x^3 + {b_4:.2f}x^4 + {b5:.2f}x^5')\n",
    "    plt.xlabel('Independent variable (x)')\n",
    "    plt.ylabel('Dependent variable (y)')\n",
    "    plt.title('Linear Regression and la Evolución minimize the error of the line with respect to the data points')\n",
    "    plt.legend()\n",
    "    plt.grid(True)\n",
    "    plt.show()\n",
    "\n",
    "    # Plot the original data and the regression polynomial\n",
    "    plt.figure(figsize=(10, 6))\n",
    "    plt.scatter(xArray, yArray, label='Observed Data')\n",
    "    plt.plot(x_new, y_new, color='red', label=f'Polynomial Regression: y = {a_0:.2f} + {a_1:.2f}x + {a_2:.2f}x^2 + {a_3:.2f}x^3 + {a_4:.2f}x^4 + {a5:.2f}x^5')\n",
    "    plt.xlabel('Independent variable (x)')\n",
    "    plt.ylabel('Dependent variable (y)')\n",
    "    plt.title('Linear Regression minimizes the error of the line with respect to the data points')\n",
    "    plt.legend()\n",
    "    plt.grid(True)\n",
    "    plt.show()\n",
    "\n",
    "    # Plot  our polynomial\n",
    "    plt.figure(figsize=(10, 6))\n",
    "    plt.scatter(xArray, yArray, label='Observed Data')\n",
    "    #plt.plot(xArray, regression_polynomial, color='red', label=f'Polynomial Regression: y = {a_0:.2f} + {a_1:.2f}x + {a_2:.2f}x^2 + {a_3:.2f}x^3 + {a_4:.2f}x^4 + {a5:.2f}x^5')\n",
    "    plt.plot(x_new,        our_polynomial, color='green', label=f'Our polynomial: y = {b_0:.2f} + {b_1:.2f}x + {b_2:.2f}x^2 + {b_3:.2f}x^3 + {b_4:.2f}x^4 + {b5:.2f}x^5')\n",
    "    plt.xlabel('Independent variable (x)')\n",
    "    plt.ylabel('Dependent variable (y)')\n",
    "    plt.title('la Evoluciónary Regression minimizes the error of the line with respect to the data points')\n",
    "    plt.legend()\n",
    "    plt.grid(True)\n",
    "    plt.show()\n",
    "\n",
    "\n",
    "\n",
    "    end_time = time.time()\n",
    "    # Calculate the duration of the run in seconds\n",
    "    elapsed_time = end_time - start_time\n",
    "    elapsed_time = timedelta(seconds=elapsed_time)\n",
    "    print(f\"Elapsed time: {elapsed_time}\")\n",
    "    #return best_chromosome, totalCost, best_fitness_history\n",
    "\n",
    "# Call the main function with the defined parameters\n",
    "mainj5(xArray, yArray, mutation_rate, recombination_rate, alphabet, length_of_chromosomes)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "9da1007a",
   "metadata": {},
   "source": [
    "**Ejercicio.** Ejecuta el programa anterior y reporta tu experiencia.\n",
    ">\n",
    "> *Respuesta.* El AG anterior que funciona con números de la forma -23.45 se ejecutó para obtener los siguientes resultados:\n",
    "\n",
    "- Para 1000 generaciones, el error final fue 7887, 1144.5\n",
    "- Para 10000 generaciones, el error final fue 15162, 35.12, 225\n",
    "- para 100000 generaciones, el error final fue 20.3, 2727.6, 7861.7\n",
    "- Para 300000 generaciones, el error final fue 5410, 5222\n",
    "\n",
    "\n",
    "*Un experimento largo. * El siguiente resultado fue el reporte de un experimento que duró medio millón de generaciones:\n",
    ">\n",
    "> Lab: Evolution finds the polynomial of minimal error \n",
    "\n",
    "> Purpose: To find the coefficients of a polynomial that best fits a set of points using a genetic algorithm.\n",
    ">\n",
    "> Date of Experiment = 2026-04-13 14:16:06.797449\n",
    ">\n",
    "> number_of_generations = 500000\n",
    "> \n",
    "> length_of_chromosomes = 5\n",
    "> \n",
    "> alphabet = 0123456789\n",
    "> \n",
    "> Points = [(-2, 5), (-1, 1), (0, 4), (1, 0), (2, 6), (3, 3)]\n",
    "> \n",
    "> population_size = 200\n",
    "> \n",
    "> include_clone_populationj5 = True\n",
    "> \n",
    "> include_mutate_allj5 = True\n",
    "> \n",
    "> include_crossover_allj5 = True\n",
    "> \n",
    "> mutation_rate = 0.01\n",
    "> \n",
    "> recombination_rate = 0.01\n",
    "> \n",
    "> print_best_fitness = False\n",
    "> \n",
    "> Total cost = population size * number of generations\n",
    "> \n",
    "> initial population\n",
    "> \n",
    "> ['170993425944533283113246872169', '422669086587863984637430988959', ...]\n",
    "> \n",
    "> The best chromosome is 229767866917999264874199931000\n",
    "> \n",
    "> Total cost = 100000000 chromosomes\n",
    "> \n",
    "> Final error = 7096.1012 \n",
    "\n",
    "*Nuestras observaciones.* Este programa ha producido el mayor error. Por lo general se logra en las primeras 200 generaciones, y rara vez puede reducirse a un valor que de todas formas es gigantesco. Este resultado contradice fuertemente nuestra mentalidad porque estábamos seguros de que la codificación utilizada funcionaría como una poderosa ayuda para que la Evolución pudiera encontrar fácilmente la perfección. De hecho, especificar 4 números es mucho más fácil que 9. Pero esto está muy lejos de la realidad. Nuestra comprensión de la Evolución es muy pobre. O, la Evolución trabaja en conjunto con la complejidad para enredar las cosas. Complejidad significa aquí que debemos especificar 6 parámetros, cada uno con 4 dígitos y un signo. Esto equivale a una cadena binaria de 150 bits de largo porque un dígito necesita 4 bits para ser codificado. Pero los chars son más caros. \n",
    "\n",
    "**Desafío.** Hacer algo a favor de la idea de dar una pista a la Evolución. Lo intentamos en el programa anterior, pero el resultado fue una gran frustración. Se puede, por ejemplo, modificar el valor de las tasas de mutación y recombinación, el número de generaciones, la longitud de los cromosomas, la codificación. \n",
    "\n",
    "**Ejercicio.* Dale más tiempo a Evolución para ver qué sucede.\n",
    ">\n",
    "> *Respuesta.* Llevamos a cabo durante un millón de generaciones nuestros dos programas preferidos, Evolución con selección por torneos y MAX o selección del más apto.\n",
    "\n",
    "El resultado del experimento con la selección por torneos, programa `PolynomialMinimalErrorTournamentSelection.py`,  fue:\n",
    "\n",
    "> Lab: Evolution finds the polynomial of minimal error\n",
    "> \n",
    "> Purpose: Use a Genetic Algorithm (tournament selection, mutation, recombination) to find the coefficients of a polynomial that best fits a set of points.\n",
    "> \n",
    "> Date of Experiment = 2026-04-14 09:15:53.102603\n",
    "> \n",
    "> number_of_generations = 1000000\n",
    "> \n",
    "> length_of_chromosomes = 9\n",
    "> \n",
    "> alphabet = 0123456789\n",
    ">\n",
    "> Points = [(-2, 5), (-1, 1), (0, 4), (1, 0), (2, 6), (3, 3)]\n",
    "> \n",
    "> population_size = 200\n",
    "> \n",
    "> include_clone_populationj4 = True\n",
    "> \n",
    "> include_mutate_allj4 = True\n",
    "> \n",
    "> include_crossover_allj4 = True\n",
    "> \n",
    "> mutation_rate = 0.01\n",
    "> \n",
    "> recombination_rate = 0.01\n",
    "> \n",
    "> print_best_fitness = False\n",
    "> \n",
    "> Total cost = population size * number of generations\n",
    "> \n",
    "> The best chromosome is 451367833068602172752000000079999999264300000179480515\n",
    "> \n",
    "> Encoded coefficients: Intercept 13.67833, slope 8.602172, quadratic -20.0, cubic 0.9999998999999999, quartic 4.3, quintic -0.9480514999999999\n",
    "> \n",
    "> Total cost = 200000000 chromosomes\n",
    "> \n",
    "> Final error = 357.69616648820784 \n",
    "\n",
    "Vemos que más tiempo (aquí, una hora y media) es muy bueno para la Evolución. Pero, aparentemente, la Evolución no tiene prisa.\n",
    "\n",
    "También ejecutamos MAX, como se implementó en el programa `PolynomialMinimalErrorByGA_WithMAX.py durante un millón de generaciones. Los resultados fueron:\n",
    ">\n",
    ">\n",
    "Lab: la Evolución finds the polynomial of minimal error  \n",
    "Purpose: Use a Genetic Algorithm (MAX or selection and cloning of the fittest, mutation, recombination) to find the coefficients of a polynomial that best fits a set of points.   \n",
    "Date of Experiment = 2026-04-20 14:41:12.705556\n",
    "number_of_generations = 1000000    \n",
    "length_of_chromosomes = 9  \n",
    "alphabet = 0123456789  \n",
    "Points = [(-2, 5), (-1, 1), (0, 4), (1, 0), (2, 6), (3, 3)]  \n",
    "population_size = 200  \n",
    "include_clone_populationj3 = True  \n",
    "include_mutate_allj3 = True  \n",
    "include_crossover_allj3 = True  \n",
    "mutation_rate = 0.02  \n",
    "recombination_rate = 0.03  \n",
    "print_best_fitness = False  \n",
    "Total cost = population size * number of generations  \n",
    " The best chromosome is 861660469976381016674157784075871000089999999789999999  \n",
    " Encoded coefficients: Intercept 1.660469, slope -0.6381015999999999, quadratic 0.4157784, cubic 0.5871, quartic 0.09999999, quintic -0.09999999  \n",
    " Total cost = 200000000 chromosomes  \n",
    " Final error = 12.17682606507979   \n",
    "\n",
    "Nuestras conclusiones con respecto al problema de encontrar un polinomio de quinto grado que se ajuste a un conjunto de seis puntos son:\n",
    ">\n",
    "> 1. MAX es mejor que Selección de torneo porque produce un error final menor.\n",
    ">\n",
    "> 2. La Evolución es buena para encontrar a bajo costo una solución aproximada que, desde el punto de vista de las matemáticas, sea muy primitiva, sin uno o más extremos. \n",
    ">\n",
    "> 3. Una aproximación fina que sea aceptable, con todos los mínimos y máximos de la solución perfecta, es muy cara y ocurre al azar. \n",
    "> \n",
    "> 4. Hasta este momento, no sabemos cómo usar la Evolución para encontrar una optimización perfecta que genere un error en la proximidad de cero, y que represente una solución interesante para un humano.\n"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "8550df0f",
   "metadata": {},
   "source": [
    "## Optimización de parámetros\n",
    "\n",
    "Hemos concluido que MAX es mejor que Tournament Selection y que ambos son buenos para encontrar aproximaciones rudimentarias, sin tocar la perfección. Una conclusión justa sería: En algunos experimentos en los que se ha utilizado la Evolución para resolver la tarea de ajustar un polinomio de quinto grado a un conjunto de 6 puntos en el plano, MAX ha producido un error final menor que la selección del torneo, con un tamaño poblacional de 200 y una tasa de mutación igual a 0,02, tasa de recombinación igual a 0,03, y máximo un millón de generaciones. Pero, con estos valores de parámetros, ninguno ha alcanzado la perfección.  \n",
    "\n",
    "Si alguien siente que este desequilibrio entre nuestras afirmaciones y su evidencia experimental es demasiado grande para ser apoyado, él o ella está bajo un poderoso desafío de su conCiencia que le extiende una invitación a hacer algo mejor. \n",
    "\n",
    "Exploremos ahora algunos valores de mutación y recombinación para ver su efecto en el error final. \n",
    "\n",
    "**Ejercicio.** En el contexto de nuestros valores habituales de parámetros, explora el papel de la tasa de mutación en el error final. Redacta tus observaciones.\n",
    ">\n",
    "> *Respuesta.* El siguiente programa dibuja el comportamiento del error del mejor cromosoma durante 1000 generaciones para diversos valores de tasa de mutación. El ajuste inicial de los parámetros es: MAX, un tamaño poblacional de 200, tasa de recombinación igual a 0,03. Los números reales están codificados en cromosomas de 9 enteros. \n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "ef9c7997",
   "metadata": {},
   "outputs": [],
   "source": [
    "# Program EffectOfMutationOverFinalError.py\n",
    "# This program uses a genetic algorithm with MAX to find \n",
    "# the fifth degree polinomial that best fits a set of 6 points.\n",
    "# THis is a variation of the previous program, but now we test the effect of mutation over the final error.\n",
    "# The coefficients are represented by a chromosome, \n",
    "# which is a string of digits.\n",
    "# The decoding function must divide the chromosome into parts, \n",
    "# and decode each one apart as one coefficient.\n",
    "# The error of a chromosome is the sum of the vertical quadratic distances \n",
    "# of the points to the polynomial it encodes.\n",
    "# The Genetic algorithm must minimize the error, \n",
    "# (which is equivalent to maximizing the fitness).\n",
    "# We use MAX (selection of the best and cloning),  mutation and recombination.\n",
    "# Developed with the assistance of the AI of Visual Studio Code.\n",
    "# An old version of a GA developed with the help of Gemini was reused and updated.\n",
    "\n",
    "from datetime import datetime, timedelta\n",
    "import time\n",
    "import random\n",
    "import numpy as np\n",
    "# Documentation: https://numpy.org/devdocs/reference/routines.polynomials.html\n",
    "from numpy.polynomial import Polynomial\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",
    "#Task to be done\n",
    "number_of_generations = 1000\n",
    "\n",
    "xArray = [-2, -1, 0, 1, 2, 3]\n",
    "yArray = [5,   1, 4, 0, 6, 3]\n",
    "\n",
    "alphabet = '0123456789'\n",
    "length_of_chromosomes = 9\n",
    "population_size = 200\n",
    "# Include cloning of the fittest\n",
    "include_clone_populationj6 = True\n",
    "# Include mutation\n",
    "include_mutate_allj6 = True\n",
    "# Include recombination\n",
    "include_crossover_allj6 = True\n",
    "mutation_rates = [0.00001, 0.0001, 0.001, 0.01, 0.05, 0.1, 0.15, 0.2, 0.3, 0.4, 0.5] # Different mutation rates to test\n",
    "best_mutation_rate = 0.01 # This will be updated with the best mutation rate found  \n",
    "recombination_rate = 0.03\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",
    "def print_parametersj6():\n",
    "    print(f\"Lab: la Evolución finds the polynomial of minimal error\")\n",
    "    print(f\"Purpose: Use a Genetic Algorithm (MAX or selection of the fittest, mutation, recombination) to find the coefficients of a polynomial that best fits a set of points.\")\n",
    "    print(f\"Date of Experiment  = {datetime.datetime.now()}\")\n",
    "    print(f\"number_of_generations = {number_of_generations}\")\n",
    "    print(f\"length_of_chromosomes = {length_of_chromosomes}\")\n",
    "    print(f\"alphabet =  {alphabet}\")\n",
    "    print(f\"Points = {list(zip(xArray, yArray))}\")\n",
    "    print(f\"population_size = {population_size}\")\n",
    "    print(f\"include_clone_populationj6 = {include_clone_populationj6}\")\n",
    "    print(f\"include_mutate_allj6 = {include_mutate_allj6}\")\n",
    "    print(f\"include_crossover_allj6 = {include_crossover_allj6}\")\n",
    "    if include_mutate_allj6:\n",
    "        print(f\"mutation_rates = {mutation_rates}\")\n",
    "    if include_crossover_allj6:\n",
    "        print(f\"recombination_rate = {recombination_rate}\")\n",
    "    if include_clone_populationj6:\n",
    "        print(f\"print_best_fitness = {print_best_fitness}\")\n",
    "\n",
    "\n",
    "def create_populationj6(population_size, length_of_chromosomes, alphabet):\n",
    "    \"\"\"Creates a new population with random chromosomes.\"\"\"\n",
    "    # print(\"create_populationj6(population_size, target_sequence, alphabet)\")\n",
    "    population = []\n",
    "    for _ in range(population_size):\n",
    "        random_string1 = ''.join(random.choice(alphabet) for _ in range(length_of_chromosomes))\n",
    "        random_string2 = ''.join(random.choice(alphabet) for _ in range(length_of_chromosomes))\n",
    "        random_string3 = ''.join(random.choice(alphabet) for _ in range(length_of_chromosomes))\n",
    "        random_string4 = ''.join(random.choice(alphabet) for _ in range(length_of_chromosomes))\n",
    "        random_string5 = ''.join(random.choice(alphabet) for _ in range(length_of_chromosomes))\n",
    "        random_string6 = ''.join(random.choice(alphabet) for _ in range(length_of_chromosomes))\n",
    "        random_string = random_string1 + random_string2 + random_string3 + random_string4 + random_string5 + random_string6\n",
    "        population.append(random_string)\n",
    "    # print(\"initial population\")\n",
    "    # print(population)\n",
    "    return population\n",
    "\n",
    "# Decode a part of the chromosome into a coefficient of the polynomial.\n",
    "def decoderj6(s):\n",
    "    ''' The input is a number as string, outputs the number as a float. '''\n",
    "    \n",
    "    l = len(s)\n",
    "    # The first char encodes for the sign, \n",
    "    sign = 1\n",
    "    if  float(s[0]) % 2 == 1:\n",
    "        sign = -1\n",
    "    # The second char encodes for the position of the decimal point,\n",
    "    d = float(s[1])\n",
    "    # The remaining chars encode for the number itself, \n",
    "    # without the decimal point nor sign.\n",
    "    n = float(s[2:l])\n",
    "    return sign * (n * (10**-d))\n",
    "\n",
    "def decodeFullCromosomej6(chromosome, length_of_chromosomes):\n",
    "    \"\"\"Decodes the full chromosome into the coefficients of the polynomial.\"\"\"\n",
    "    \"\"\"The chromosome is divided into 5 parts, \n",
    "        each one encoding for a coefficient of the polynomial.\"\"\"\n",
    "    chro0 = chromosome[0:length_of_chromosomes]\n",
    "    chro1 = chromosome[length_of_chromosomes:2*length_of_chromosomes]\n",
    "    chro2 = chromosome[2*length_of_chromosomes:3*length_of_chromosomes]\n",
    "    chro3 = chromosome[3*length_of_chromosomes:4*length_of_chromosomes]\n",
    "    chro4 = chromosome[4*length_of_chromosomes:5*length_of_chromosomes]\n",
    "    chro5 = chromosome[5*length_of_chromosomes:6*length_of_chromosomes]\n",
    "    a_0 = decoderj6(chro0)\n",
    "    a_1 = decoderj6(chro1)\n",
    "    a_2 = decoderj6(chro2)\n",
    "    a_3 = decoderj6(chro3)\n",
    "    a_4 = decoderj6(chro4)\n",
    "    a_5 = decoderj6(chro5)\n",
    "    return a_0, a_1, a_2, a_3, a_4, a_5\n",
    "\n",
    " \n",
    "\n",
    "def calculate_errorj6(chromosome, xArray, yArray):\n",
    "    \"\"\"Calculates the error of a chromosome.\n",
    "        A chromosome encodes for the coefficients of a polynomial of fith degree.\n",
    "        The error of a chromosome is the sum of \n",
    "        the vertical distances of the points to the polynomial it encodes.\n",
    "    \"\"\"\n",
    "    #  print(\"\\n calculate_errorj6(chromosome, xArray, yArray)\")\n",
    "    a_0, a_1, a_2, a_3, a_4, a_5 = decodeFullCromosomej6(chromosome, length_of_chromosomes) \n",
    "    error = 0\n",
    "    for i in range(len(xArray)):\n",
    "        x = xArray[i]\n",
    "        y = yArray[i]\n",
    "        # Calculate the predicted y value based on the coefficients of the polynomial\n",
    "        predicted_y = a_0 + a_1 * x + a_2 * x**2 + a_3 * x**3 + a_4 * x**4 + a_5 * x**5\n",
    "        # Calculate the error as the quadratic difference \n",
    "        # between predicted and y value\n",
    "        error += (predicted_y - y)**2\n",
    "    return error\n",
    "\n",
    "def calculate_all_errorsj6(population, xArray, yArray):\n",
    "    # print(\"\\n*calculate_all_errorsj6(population, target_sequence)\")\n",
    "    \"\"\"Calculates the error of all chromosomes in the population.\"\"\"\n",
    "    errors = [calculate_errorj6(chromosome, xArray, yArray) for chromosome in population]\n",
    "    # print(\"errors: \", errors)\n",
    "    return errors\n",
    "\n",
    "def select_the_least_errorj6(population, xArray, yArray):\n",
    "    \"\"\"Selects the best chromosome with minimal error for reproduction.\"\"\"\n",
    "    errors = calculate_all_errorsj6(population, xArray, yArray)\n",
    "    smallest_error = min(errors)\n",
    "    best_chromosome_index = errors.index(smallest_error)\n",
    "    best_chromosome = population[best_chromosome_index]\n",
    "    # print(\"\\n*select_the_least_errorj6(population)\")\n",
    "    # print(\"smallest_error = \", smallest_error)\n",
    "    # print(\"The chro = \", best_chromosome )\n",
    "    return smallest_error, best_chromosome\n",
    "\n",
    "def clone_populationj6(best_chromosome, population_size):\n",
    "    \"\"\"Creates a new population by cloning the best chromosome.\"\"\"\n",
    "    return [best_chromosome] * population_size\n",
    "\n",
    "\n",
    "def mutatej6(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_allj6(population, mutation_rate, alphabet):\n",
    "    \"\"\"Mutates all chromosomes in the population.\"\"\"\n",
    "    mutated_population = []\n",
    "    for chromosome in population:\n",
    "        mutated_chromosome = mutatej6(chromosome, mutation_rate, alphabet)\n",
    "        mutated_population.append(mutated_chromosome)\n",
    "    return mutated_population\n",
    "\n",
    "def crossoverj6(parent1, parent2, length_of_chromosomes, recombination_rate):\n",
    "    \"\"\"Performs crossover between two parent chromosomes.\"\"\"\n",
    "    if random.random() < recombination_rate:\n",
    "        crossover_point = random.randint(0, length_of_chromosomes)\n",
    "        return parent1[:crossover_point] + parent2[crossover_point:]\n",
    "    else:\n",
    "        return parent1\n",
    "\n",
    "def crossover_allj6(population, length_of_chromosomes, 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 = crossoverj6(parent1, parent2, length_of_chromosomes, recombination_rate)\n",
    "        recombinant_population.append(child)\n",
    "    return recombinant_population\n",
    "\n",
    "\n",
    "\n",
    "def run_one_generationj6(population, xArray, yArray, mutation_rate, recombination_rate, alphabet):\n",
    "    \"\"\"Runs one generation of the genetic algorithm.\"\"\"\n",
    "    # Calculate fitness scores for the current population\n",
    "    smallest_error, best_chromosome  = select_the_least_errorj6(population, xArray, yArray)\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_populationj6:\n",
    "        new_population = clone_populationj6(best_chromosome, population_size)\n",
    "    if include_mutate_allj6:\n",
    "        new_population = mutate_allj6(new_population, mutation_rate, alphabet)\n",
    "    if include_crossover_allj6:\n",
    "        new_population = crossover_allj6(new_population, length_of_chromosomes, recombination_rate)\n",
    "    return smallest_error, best_chromosome, new_population\n",
    "\n",
    "\n",
    "\n",
    "def plot_functionj6(g_values, 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",
    "def plot_polynomialj6(xArray, yArray, coefficients, best_mutation_rate, title=f'Polynomial for Best Mutation Rate {best_mutation_rate}'):\n",
    "    '''This function plots the polynomial defined by the best coefficients over the data points.\n",
    "    Developed by the AI of Visual Studio Code. '''\n",
    "    # Plot the polynomial\n",
    "    plt.figure(figsize=(10, 6))\n",
    "    plt.scatter(xArray, yArray, label='Data Points')\n",
    "    x_plot = np.linspace(min(xArray), max(xArray), 100)\n",
    "    y_plot = coefficients[0] + coefficients[1] * x_plot + coefficients[2] * x_plot**2 + coefficients[3] * x_plot**3 + coefficients[4] * x_plot**4 + coefficients[5] * x_plot**5\n",
    "    plt.plot(x_plot, y_plot, label='Fitted Polynomial')\n",
    "    plt.xlabel('x')\n",
    "    plt.ylabel('y')\n",
    "    plt.title(title)\n",
    "    plt.legend()\n",
    "    plt.grid(True)\n",
    "    plt.show()\n",
    "\n",
    "\n",
    "def taskj6( xArray, yArray, mutation_rate, recombination_rate, alphabet, percentageOfTask):\n",
    "    population = create_populationj6(population_size, length_of_chromosomes, alphabet)\n",
    "    # print(population)\n",
    "    generation = 0\n",
    "    best_chromosome = ''\n",
    "    best_fitness = 0\n",
    "    start_time = time.time()\n",
    "    smallest_error_history = [] # List to store best fitness of each generation\n",
    "    if print_best_fitness:\n",
    "        print(\"Generation, best_chromosome and best_fitness\")\n",
    "    while generation < number_of_generations:\n",
    "        generation += 1\n",
    "        smallest_error, best_chromosome, population = run_one_generationj6(population, xArray,yArray, mutation_rate, recombination_rate, alphabet)\n",
    "        if print_best_fitness:\n",
    "            print(f\" {generation}  {best_chromosome} {smallest_error}\")\n",
    "        smallest_error_history.append(smallest_error)\n",
    "    # print(f\"\\nTarget sequence matched in generation {generation}\")\n",
    "    # print(f\"Final chromosome: {best_chromosome}\")\n",
    "    totalCost = population_size * generation\n",
    "    \n",
    "    return  best_chromosome, totalCost, smallest_error_history\n",
    "\n",
    "\n",
    "\n",
    "def main(xArray, yArray, mutation_rates, recombination_rate, alphabet, length_of_chromosomes):\n",
    "    '''# We test the effect of mutation over the final error by running the main function with different mutation rates.\n",
    "    The best mutation rate is the one that gives the lowest final error.\n",
    "    We run the main function for each mutation rate,\n",
    "    and we keep the best chromosome and the final error history for each mutation rate.\n",
    "    Finally, we plot the final error history for each mutation rate, \n",
    "    and we compare them to find the best mutation rate.\n",
    "    With the assistance of the AI of Visual Studio Code. '''\n",
    "\n",
    "    print_parametersj6()\n",
    "    # print(\"Total cost = population size * number of generations\")\n",
    "\n",
    "    # Array to keep the best chromosmes for each mutation rate    \n",
    "    best_chromosomes = []\n",
    "    # Array to keep the final error history for each mutation rate\n",
    "    final_error_histories = []\n",
    "    #Loop over the mutation rates to test their effect over the final error.\n",
    "    for mutation_rate in mutation_rates:   \n",
    "        best_chromosome, totalCost, smallest_error_history = taskj6(xArray, yArray, mutation_rate, recombination_rate, alphabet, length_of_chromosomes)\n",
    "        final_error = smallest_error_history[-1]\n",
    "        # print(f\" The best chromosome is {best_chromosome}\" )\n",
    "        # coefficients = decodeFullCromosomej6(best_chromosome, length_of_chromosomes)\n",
    "        # print(f\" Encoded coefficients: Intercept {coefficients[0]}, slope {coefficients[1]}, quadratic {coefficients[2]}, cubic {coefficients[3]}, quartic {coefficients[4]}, quintic {coefficients[5]}\")\n",
    "        # print(f\" Total cost =  {totalCost} chromosomes\")\n",
    "        print(f\" Mutation rate {mutation_rate}: Final error =  {final_error} \")\n",
    "        final_error_histories.append(smallest_error_history)\n",
    "        best_chromosomes.append(best_chromosome)\n",
    "\n",
    "    best_mutation_rate_index = np.argmin([final_error_history[-1] for final_error_history in final_error_histories])\n",
    "    best_mutation_rate = mutation_rates[best_mutation_rate_index]\n",
    "    least_error = final_error_histories[best_mutation_rate_index][-1]\n",
    "    print(f\"\\nBest mutation rate: {best_mutation_rate} with final error {least_error}\")\n",
    "    best_chromosome = best_chromosomes[best_mutation_rate_index]\n",
    "    best_coefficients = decodeFullCromosomej6(best_chromosome, length_of_chromosomes)\n",
    "\n",
    "    # Plot the final_error_histories for each mutation rate\n",
    "    for i, mutation_rate in enumerate(mutation_rates):\n",
    "        g_values = list(range(1, len(final_error_histories[i]) + 1))\n",
    "        plot_functionj6(g_values, final_error_histories[i], xlabel='Generation', ylabel='SmallestError', title=f'Smallest Error Over Generations for Mutation Rate {mutation_rate}')   \n",
    "    \n",
    "    # Plot all final_error_histories for all mutation rates in the same graph\n",
    "    plt.figure(figsize=(10, 6))\n",
    "    for i, mutation_rate in enumerate(mutation_rates):\n",
    "        plt.plot(final_error_histories[i], label=f'Mutation Rate {mutation_rate}')\n",
    "    plt.xlabel('Generation')\n",
    "    plt.ylabel('Smallest Error')\n",
    "    plt.title('Smallest Error Over Generations for Different Mutation Rates')\n",
    "    plt.legend()\n",
    "    plt.grid(True)\n",
    "    plt.show()\n",
    "\n",
    "    # Plot again the graph of the best error history for the best mutation rate (the one with the lowest final error)\n",
    "    g_values = list(range(1, len(final_error_histories[best_mutation_rate_index]) + 1))\n",
    "    plot_functionj6(g_values, final_error_histories[best_mutation_rate_index], xlabel='Generation', ylabel='SmallestError', title=f'Smallest Error Over Generations for the Best Mutation Rate {best_mutation_rate}')\n",
    "\n",
    "    # Plot the polynomial given by the coefficients of the best chromosome for the best mutation rate\n",
    "    plot_polynomialj6(xArray, yArray, best_coefficients, best_mutation_rate, title=f'Polynomial for Best Mutation Rate {best_mutation_rate}, least error = {least_error:.2f}')\n",
    "\n",
    "    end_time = time.time()\n",
    "    # Calculate the difference in seconds\n",
    "    elapsed_time = end_time - start_time\n",
    "    elapsed_time = timedelta(seconds=elapsed_time)\n",
    "    print(f\"Elapsed time: {elapsed_time}\")\n",
    "    #return best_chromosome, totalCost, best_fitness_history\n",
    "\n",
    "# Call the main function with the defined parameters\n",
    "main(xArray, yArray, mutation_rates, recombination_rate, alphabet, length_of_chromosomes)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "d81475f8",
   "metadata": {},
   "source": [
    "*Nuestras observaciones.* Para 1000 generaciones, nuestras conclusiones con respecto al papel de la tasa de mutación sobre el error final son:\n",
    "\n",
    "- El intervalo más habitual en el que cae la mejor tasa de mutación es [0,1, 0,2]. Nuestros valores preferidos son 0,1 y 0,15. Adoptaremos 0,1 para futuros trabajos. \n",
    "- En nuestra opinión, la variación en el error final debido a un cambio en la tasa de mutación no es tan significativa porque hay una brecha insuperable de 12 entre el error mínimo observado y la perfección. Por esa razón, el mejor ajuste parece ser rudimentario porque carece de 1 mínimo y 1 máximo. \n",
    "- Los valores más bajos de la tasa de mutación son intrigantes porque parecen dar más de sí mismos si se le concede más tiempo a la Evoluicón. \n",
    "  \n",
    "**Desafío.** Concede más tiempo a la Evolución dando valores muy bajos a la tasa de mutación. Informa tus hallazgos. \n",
    "\n",
    "**Ejercicio.* En el contexto de nuestros valores usuales de parámetros, explore el papel de la tasa de recombinación en el error final. Redacte sus observaciones.\n",
    ">\n",
    "> *Respuesta.* El siguiente programa dibuja el comportamiento del error del mejor cromosoma durante 1000 generaciones para diversos valores de la tasa de recombinación. El ajuste inicial de los parámetros es: MAX, tamaño de la población 200, tasa de mutación igual a 0,1. Los números reales están codificados en cromosomas de 9 enteros. \n",
    "\n",
    "\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "e7f1cc7d",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Lab: Evolution finds the polynomial of minimal error\n",
      "Purpose: Use a Genetic Algorithm (MAX or selection of the fittest, mutation, recombination) to find the coefficients of a polynomial that best fits a set of points.\n",
      "Date of Experiment  = 2026-05-04 14:12:54.800626\n",
      "number_of_generations = 1000\n",
      "length_of_chromosomes = 9\n",
      "alphabet =  0123456789\n",
      "Points = [(-2, 5), (-1, 1), (0, 4), (1, 0), (2, 6), (3, 3)]\n",
      "population_size = 200\n",
      "include_clone_populationj7 = True\n",
      "include_mutate_allj7 = True\n",
      "include_crossover_allj7 = True\n",
      "mutation_rate = 0.01\n",
      "recombination_rates = [1e-05, 0.0001, 0.001, 0.01, 0.05, 0.1, 0.15, 0.2, 0.3, 0.4, 0.5]\n",
      "print_best_fitness = False\n",
      " Recombination rate 1e-05: Final error =  19.709831653066395 \n",
      " Recombination rate 0.0001: Final error =  42.614441828695206 \n",
      " Recombination rate 0.001: Final error =  15.355621918213524 \n",
      " Recombination rate 0.01: Final error =  127.48808625152579 \n",
      " Recombination rate 0.05: Final error =  279.4251192445161 \n",
      " Recombination rate 0.1: Final error =  26.28720158440021 \n",
      " Recombination rate 0.15: Final error =  34.73404302935795 \n",
      " Recombination rate 0.2: Final error =  23.39733734770162 \n",
      " Recombination rate 0.3: Final error =  19.13977827208429 \n",
      " Recombination rate 0.4: Final error =  8379.423160160037 \n",
      " Recombination rate 0.5: Final error =  33.93777856188312 \n",
      "\n",
      "Best recombination rate: 0.001 with final error 15.355621918213524\n"
     ]
    },
    {
     "data": {
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nmvLy8oSnp6do06aNtEzzOVnxGBkzZoxwcHDQ+t3Qp7LHgaF9LS4uFg0aNBATJ06Ulj/s1FujRo1ESEiIzjSH7t27Cx8fnypNW3lYUIqKihJ16tTR+YfquHHjhIODwyM/Y+bMmaP1u/2gyMhI8cwzz0iPjx8/LiZMmCC2b98uvv/+e7Fq1SrRuHFjYWtrq/fz92Gq3ak3d3d3HDp0CEePHsXcuXPx0ksv4cKFC5g+fTqCg4N1riZq3rw5ateuLT1u3LgxgPtDvA9OANYsf/C0Wn5+PqZOnYqnn34adnZ2sLOzg7OzM+7evYtffvmlSv3+9ttvUVpaiiFDhqC0tFT6cXBwQHh4uDT8W6tWLQQGBuKjjz7C/PnzceLECZ1TKsZq164djh49qvMzcuRInbYvv/yy3nU0bdpU5zTYvn370KlTJ9StW1dr+bBhw3Dv3j2dYWtD6zaG+O8pIM0VhsHBwQgNDcXq1aulNr/88guOHDmCESNGSMt2796NoKAgNG/eXOv9iIqK0jsc/+KLL8LNzc3ofp48eRJKpVLrR3Os7t69GwqFAq+99ppWX7y9vdGsWTOdvnh7e+P555/XWta0aVOtY9dU+7dv3z507twZrq6usLW1hVKpxPvvv49bt27hxo0bVa7D3bt38dNPP6Fv375aE6dtbW0xePBgXL16FefPn9d6Tc+ePXX2Ffj7d7V58+awt7fHqFGjsHbtWp3TlVWlmWBbcWL6K6+8AicnJ51TSPp+Jx7m7t270jHg4eGBN998E6+++irmzJkjtans58WFCxfw+++/Y+TIkXBwcDC4varWvHv37lqPNZ+P3bp101mubypCnz59tPrj4uKCHj164Pvvv0dZWdlD61OZ4xsAtmzZgrZt28LZ2Rl2dnZQKpVYuXJllT+bNc6fP4/r169j8ODBWqeanJ2d8fLLL+PHH3/UOZWr79gsLCys1O9GZY4DACgtLUVcXByaNGkCe3t72NnZwd7eHr/++mul9vW3337DuXPnMGjQIGl9mp+uXbsiMzNT5/03RmFhIb777jv07t0bjo6OOtspLCyUrkYrKyvTer7i3zhDV4w/uDwkJAQLFy5Er1690L59ewwfPhwpKSnw8fHBlClTqtT3aheUNMLCwjB16lRs2bIF169fx8SJE/HHH38gISFBq12tWrW0Htvb2z90eWFhobRs4MCBWLx4MV5//XV8++23OHLkCI4ePYqnnnoKBQUFVeqv5pzzc889p/MHc/PmzdIfTYVCge+++w5RUVFISEhAixYt8NRTT+Gtt95CXl5elbZZkaurK8LCwnR+9F11YuhKFH3Lb926pXe5r6+v9Hxl1l1RvXr1AAAZGRkG22jmNzwY0kaMGIHU1FScO3cOALB69WqoVCqtOUN//vknTp06pfNeuLi4QAihE7ir2ueKH+oNGzaUgmnF+Ul//vknhBDw8vLS6c+PP/6o0xd3d3ed7apUKq1j0hT7d+TIEURGRgIAvvjiC/zwww84evQoZsyYAQBV/h0AgOzsbAghqnS8VNxflUqltf3AwEDs3bsXnp6eGDt2LAIDAxEYGIhPP/20yv3TbN/Ozg5PPfWU1nKFQgFvb2+jj2cNtVotHQu7du1Chw4dsGnTJsydO1dqU9nPi7/++gsAUKdOHYPbM6bmVfncfPAzU8Pb21vvsuLiYp3LvCuqzPG9bds29OvXD7Vr18aGDRuQmpqKo0ePYsSIEXr7UxmaGhiqU3l5ObKzsx/a14rH5sNU5jgAgEmTJuG9995Dr169sGvXLvz00084evQomjVrVqntaI6lyZMn6xxLY8aMAQCT3K7k1q1bKC0txaJFi3S207VrV63tBAYGaj0/e/ZsAH/Xs+LxCAC3b9/WOf4qqlmzJrp3745Tp05V6fOp2t0eQB+lUomZM2diwYIFSE9PN8k6c3JysHv3bsycORPTpk2TlhcVFeH27dtVXp+HhwcA4KuvvoKfn99D2/r5+WHlypUA7v+L8d///jdiY2NRXFyMZcuWVXnbxqhMotdwd3dHZmamznLNhFvNvj9q3RVFRERg+fLl2LFjh9Z78KAdO3bAzs5O615QAwYMwKRJk7BmzRrMmTMH69evR69evbRGTDw8PKBWq7Fq1Sq96zW2zx06dICdnR127tyJUaNGScvVarU0UVNzMcGD21IoFDh06JD0QfsgfcsexRT7l5iYCKVSid27d2uNDui7J01lubm5wcbGpkrHS2W0b98e7du3R1lZGY4dO4ZFixYhOjoaXl5e6N+/f5XW5e7ujtLSUvz1119aYUkIgaysLGnSrEZV75dmY2MjHQvA/eM8NDQUs2bNwqBBg1C3bt1Kf15o+nf16lWDbcxV84fJysrSu8ze3t4kt2DYsGEDAgICsHnzZq36FxUVGb1OzR9pQ3WysbF5rFHliipzHAD393XIkCGIi4vTev3NmzdRs2bNR25H895Onz4dffr00dumYcOGRu7F39zc3KRRyrFjx+ptExAQAADYtWuX1nulCezBwcEAgNOnT2vdtqG0tBTnzp0zeIHMgyqeZaiMajeipO8gBiANQWoK/rgUCgWEEDp/pFasWPHIoWN9oqKiYGdnh99//13vqM6DvzAPeuaZZ/Duu+8iODgYx48fl5ZX/BeWNXXq1An79u3TuRJp3bp1cHR0RKtWrYxab+/evdGkSRPMnTsXFy5c0Hl+8+bNSEpKwuuvv671L1g3Nzf06tUL69atw+7du5GVlaV12g24f2rh999/h7u7u973wtirCH18fDBixAh8/fXXSExMrNRrunfvDiEErl27prcvmg+PqjDF/ikUCtjZ2cHW1lZaVlBQgPXr1+u0rezx6OTkhJYtW2Lbtm1a7TU36KxTp06VTmNVZGtri5YtW0pX2Tz4O1NZnTp1AnD/D9SDtm7dirt370rPm4pKpcJnn32GwsJCfPjhhwAq/3nxzDPPIDAwEKtWrTIYEsxdc322bdumNbKTl5eHXbt2oX379lrHk7E0N2l88I9hVlaWzlVvQOWPzYYNG6J27drYuHGj1lWdd+/exdatW6Ur4cxF33EA3N/Xin+Hvv76a1y7dk3n9YDuaFbDhg3RoEED/PzzzwaPJRcXl8fuv6OjIzp27IgTJ06gadOmerejCaPBwcFayzV/t1u2bAkfHx+dq2S/+uor5OfnGwx6GtnZ2di9e7d0s8rKqnYjSlFRUahTpw569OiBRo0aoby8HCdPnsQnn3wCZ2dnTJgwwSTbqVGjBl544QV89NFH8PDwgL+/Pw4ePIiVK1dWKsVX5O/vj9mzZ2PGjBm4ePEiunTpAjc3N/z55584cuQInJycMGvWLJw6dQrjxo3DK6+8ggYNGsDe3h779u3DqVOntEZVgoODkZiYiM2bN6N+/fpwcHB45B/UO3fu6L1jqUqlQkhISJX3SWPmzJnYvXs3OnbsiPfffx+1atXCl19+ia+//hoJCQlwdXU1ar22trbYunUrIiIipDuvt27dGkVFRdi1axeWL1+O8PBwvTcZHTFiBDZv3oxx48ahTp066Ny5s9bz0dHR2Lp1K1544QVMnDgRTZs2RXl5OS5fvoykpCTExMSgZcuWRvV74cKFyMjIwKBBg7Bz50689NJL8PX1xb1793Du3DkkJibCwcEBSqUSwP0bgY4aNQrDhw/HsWPH8MILL8DJyQmZmZk4fPgwgoOD8eabb1apD6bYv27dumH+/PkYOHAgRo0ahVu3buHjjz/WO8JVleMxPj4eERER6NixIyZPngx7e3ssWbIE6enp2LRpU5VHaJYtW4Z9+/ahW7duqFevHgoLC6WRtIrve2VEREQgKioKU6dORW5uLtq2bYtTp05h5syZCAkJ0Xv7iccVHh6Orl27YvXq1Zg2bRoCAgIq9XkBAJ999hl69OiBVq1aYeLEiahXrx4uX76Mb7/9Fl9++SUA09f8UWxtbREREYFJkyahvLwc8+bNQ25urlG3TtBHc0uGMWPGoG/fvrhy5Qo++OAD+Pj44Ndff9VqGxwcjAMHDmDXrl3w8fGBi4uL3hEUGxsbJCQkYNCgQejevTtGjx6NoqIifPTRR7hz547OKTFz0HccdO/eHWvWrEGjRo3QtGlTpKWl4aOPPtI53RoYGAi1Wo0vv/wSjRs3hrOzM3x9feHr64vPP/8c//jHPxAVFYVhw4ahdu3auH37Nn755RccP34cW7ZseWi/zp49i7NnzwK4H0jv3buHr776CgDQpEkTafTn008/Rbt27dC+fXu8+eab8Pf3R15eHn777Tfs2rVLmv9niK2tLRISEjB48GCMHj0aAwYMwK+//oopU6YgIiICXbp0kdoOHDgQ9erVQ1hYGDw8PPDrr7/ik08+wZ9//ln1bwKo0tRvGdi8ebMYOHCgaNCggXB2dhZKpVLUq1dPDB48WJw9e1arraGbLAIQY8eO1Vqm70ZpV69eFS+//LJwc3MTLi4uokuXLiI9PV34+flpXUVRlRtO7tixQ3Ts2FHUqFFDqFQq4efnJ/r27Sv27t0rhBDizz//FMOGDRONGjUSTk5OwtnZWTRt2lQsWLBAlJaWSuv5448/RGRkpHBxcZEu53+Yh131Vrt2bZ1+P3j7g0fVUwghTp8+LXr06CFcXV2Fvb29aNasmc7VF8beIOzmzZti2rRpolGjRsLBwUE4OzuL559/XixevNjg7SHKyspE3bp1BQAxY8YMvW3y8/PFu+++Kxo2bCjs7e2ly1onTpyodUm+vuPlUcrKysS6detERESE8PDwEHZ2dsLV1VU8//zz4r333tO6ElNj1apVomXLlsLJyUmo1WoRGBgohgwZIo4dOya1CQ8PF88++6zOa4cOHapzDJhi/1atWiUaNmwoVCqVqF+/voiPjxcrV67UuVrJ0PGo76o3IYQ4dOiQePHFF6V9bdWqldi1a5dWG81VURWv3Kv4+5aamip69+4t/Pz8hEqlEu7u7iI8PPyhV7A+WDd9l2kXFBSIqVOnCj8/P6FUKoWPj4948803dW43UNUbuRranhD3f4dsbGy0Li9/1OeFRmpqqvjHP/4hXF1dhUqlEoGBgVpXRAnxeDU39LlQcX807/e8efPErFmzRJ06dYS9vb0ICQkR3377rd5tVbzqrbLH99y5c4W/v79QqVSicePG4osvvtD7uXvy5EnRtm1b4ejoKABIV2fq+9wW4n7NW7ZsKRwcHISTk5Po1KmT+OGHHypVD337pE9VjoPs7GwxcuRI4enpKRwdHUW7du3EoUOHRHh4uM6Vpps2bRKNGjUSSqVSABAzZ86Unvv5559Fv379hKenp1AqlcLb21u8+OKLYtmyZQ/t64P7q+/nwW0Icf8YGDFihKhdu7ZQKpXiqaeeEm3atBEffvjhI7ejsXHjRtG0aVNhb28vvL29xVtvvaVzVXt8fLxo3ry5cHV1Fba2tuKpp54SvXv3fujtOQxRCPHAGCIRERERSardHCUiIiIiU2FQIiIiIjKAQYmIiIjIAAYlIiIiIgMYlIiIiIgMYFAiIiIiMqDa3XDSGOXl5bh+/TpcXFxMfmM1IiIiMg8hBPLy8uDr66v1ZcWmxKCE+9/TU/Gb7YmIiEgerly58tAvf34cDEqA9D02V65cQY0aNUy23pKSEiQlJSEyMlL6OgoyD9baMlhny2CdLYe1tgxz1Tk3Nxd169Y1yffRGcKghL+/RbhGjRomD0qOjo6oUaMGfwHNjLW2DNbZMlhny2GtLcPcdTbntBlO5iYiIiIygEGJiIiIyAAGJSIiIiIDGJSIiIiIDGBQIiIiIjKAQYmIiIjIAAYlIiIiIgMYlIiIiIgMYFAiIiIiMoBBiYiIiMgABiUiIiIiAxiUiIiIiAxgUDKj7HvFuF0E5BaUWLsrREREZAQGJTOav/c3zDpuh3U/XrZ2V4iIiMgIDEpEREREBjAoWYCwdgeIiIjIKAxKZqSwdgeIiIjosTAoERERERnAoGQJPPdGREQkSwxKZqTguTciIiJZY1CyAMEhJSIiIlliUDIjBadzExERyRqDEhEREZEBDEoWIHjmjYiISJYYlMyIk7mJiIjkjUHJAjigREREJE8MSmbEASUiIiJ5Y1AiIiIiMoBByQI4mZuIiEieGJTMibO5iYiIZI1ByQJ4Z24iIiJ5smpQKi0txbvvvouAgACo1WrUr18fs2fPRnl5udRGCIHY2Fj4+vpCrVajQ4cOOHPmjNZ6ioqKMH78eHh4eMDJyQk9e/bE1atXLb07OjieREREJG9WDUrz5s3DsmXLsHjxYvzyyy9ISEjARx99hEWLFkltEhISMH/+fCxevBhHjx6Ft7c3IiIikJeXJ7WJjo7G9u3bkZiYiMOHDyM/Px/du3dHWVmZNXaLiIiIqgk7a248NTUVL730Erp16wYA8Pf3x6ZNm3Ds2DEA90eTFi5ciBkzZqBPnz4AgLVr18LLywsbN27E6NGjkZOTg5UrV2L9+vXo3LkzAGDDhg2oW7cu9u7di6ioKOvs3IN45o2IiEiWrBqU2rVrh2XLluHChQt45pln8PPPP+Pw4cNYuHAhACAjIwNZWVmIjIyUXqNSqRAeHo6UlBSMHj0aaWlpKCkp0Wrj6+uLoKAgpKSk6A1KRUVFKCoqkh7n5uYCAEpKSlBSUmKy/RPi/inEsvJyk66XdGnqyzqbF+tsGayz5bDWlmGuOlvifbNqUJo6dSpycnLQqFEj2NraoqysDHPmzMGAAQMAAFlZWQAALy8vrdd5eXnh0qVLUht7e3u4ubnptNG8vqL4+HjMmjVLZ3lSUhIcHR0fe780Ll+yAWCDjIwM7Nnzu8nWS4YlJydbuwv/E1hny2CdLYe1tgxT1/nevXsmXZ8+Vg1KmzdvxoYNG7Bx40Y8++yzOHnyJKKjo+Hr64uhQ4dK7RQVLrMXQugsq+hhbaZPn45JkyZJj3Nzc1G3bl1ERkaiRo0aj7FH2o7tPgtkXYW/vz+6dmlksvWSrpKSEiQnJyMiIgJKpdLa3am2WGfLYJ0th7W2DHPVWXNGyJysGpTefvttTJs2Df379wcABAcH49KlS4iPj8fQoUPh7e0N4P6okY+Pj/S6GzduSKNM3t7eKC4uRnZ2ttao0o0bN9CmTRu921WpVFCpVDrLlUqlSd9AW5v7c+VtbW35C2ghpn4PST/W2TJYZ8thrS3D1HW2xHtm1ave7t27Bxsb7S7Y2tpKtwcICAiAt7e31lBdcXExDh48KIWg0NBQKJVKrTaZmZlIT083GJQsjXfmJiIikierjij16NEDc+bMQb169fDss8/ixIkTmD9/PkaMGAHg/im36OhoxMXFoUGDBmjQoAHi4uLg6OiIgQMHAgBcXV0xcuRIxMTEwN3dHbVq1cLkyZMRHBwsXQVnLY86PUhERERPNqsGpUWLFuG9997DmDFjcOPGDfj6+mL06NF4//33pTZTpkxBQUEBxowZg+zsbLRs2RJJSUlwcXGR2ixYsAB2dnbo168fCgoK0KlTJ6xZswa2trbW2C0iIiKqJqwalFxcXLBw4ULpdgD6KBQKxMbGIjY21mAbBwcHLFq0SOtGlU8SfoUJERGRPPG73syIJ96IiIjkjUHJAjiZm4iISJ4YlMyIc7mJiIjkjUGJiIiIyAAGJQvgmTciIiJ5YlAiIiIiMoBBiYiIiMgABiULELzsjYiISJYYlMyIX2FCREQkbwxKRERERAYwKJkRx5OIiIjkjUGJiIiIyAAGJQvgXG4iIiJ5YlAyI87lJiIikjcGJQvggBIREZE8MSiZkYLTuYmIiGSNQYmIiIjIAAYlC+CduYmIiOSJQcmMOJmbiIhI3hiULIDjSURERPLEoERERERkAIOSGfHMGxERkbwxKFkA53ITERHJE4OSOXFIiYiISNYYlIiIiIgMYFCyAJ55IyIikicGJTPiV5gQERHJG4OSJXA2NxERkSwxKJkR78xNREQkbwxKRERERAYwKFkAT7wRERHJE4OSGfHMGxERkbwxKFkA53ITERHJE4OSGXEyNxERkbwxKBEREREZwKBkAYLTuYmIiGSJQcmMeGduIiIieWNQIiIiIjKAQckCeNUbERGRPDEomRPPvBEREckag5IFcECJiIhInhiUzIgDSkRERPLGoERERERkAIOSBXAyNxERkTwxKJmRgt9hQkREJGsMShbBISUiIiI5YlAyI44nERERyRuDEhEREZEBDEoWwMncRERE8sSgZEacy01ERCRvDEpEREREBjAoWQDPvBEREckTg5IZ8cwbERGRvDEoWQAncxMREckTg5IZ8c7cRERE8sagRERERGQAg5IFCE7nJiIikiUGJSIiIiIDGJQsgJO5iYiI5IlByYw4l5uIiEjeGJSIiIiIDGBQsgCeeSMiIpInBiUz4qk3IiIieWNQsgTO5iYiIpIlBiUzUvDb3oiIiGSNQYmIiIjIAAYlC+CZNyIiInliUDIjTuYmIiKSNwYlIiIiIgOsHpSuXbuG1157De7u7nB0dETz5s2RlpYmPS+EQGxsLHx9faFWq9GhQwecOXNGax1FRUUYP348PDw84OTkhJ49e+Lq1auW3hWDeOaNiIhInqwalLKzs9G2bVsolUr85z//wdmzZ/HJJ5+gZs2aUpuEhATMnz8fixcvxtGjR+Ht7Y2IiAjk5eVJbaKjo7F9+3YkJibi8OHDyM/PR/fu3VFWVmaFvfobz7wRERHJm501Nz5v3jzUrVsXq1evlpb5+/tL/y+EwMKFCzFjxgz06dMHALB27Vp4eXlh48aNGD16NHJycrBy5UqsX78enTt3BgBs2LABdevWxd69exEVFWXRfdKHk7mJiIjkyaojSjt37kRYWBheeeUVeHp6IiQkBF988YX0fEZGBrKyshAZGSktU6lUCA8PR0pKCgAgLS0NJSUlWm18fX0RFBQktbEWBWdzExERyZpVR5QuXryIpUuXYtKkSXjnnXdw5MgRvPXWW1CpVBgyZAiysrIAAF5eXlqv8/LywqVLlwAAWVlZsLe3h5ubm04bzesrKioqQlFRkfQ4NzcXAFBSUoKSkhKT7Z/m1F+5KDfpekmXpr6ss3mxzpbBOlsOa20Z5qqzJd43qwal8vJyhIWFIS4uDgAQEhKCM2fOYOnSpRgyZIjUruLIjBDikaM1D2sTHx+PWbNm6SxPSkqCo6NjVXfDoPPXFQBskZmZiT17rplsvWRYcnKytbvwP4F1tgzW2XJYa8swdZ3v3btn0vXpY9Wg5OPjgyZNmmgta9y4MbZu3QoA8Pb2BnB/1MjHx0dqc+PGDWmUydvbG8XFxcjOztYaVbpx4wbatGmjd7vTp0/HpEmTpMe5ubmoW7cuIiMjUaNGDdPsHIDMQxeBS7/B29sHXbs2M9l6SVdJSQmSk5MREREBpVJp7e5UW6yzZbDOlsNaW4a56qw5I2ROVg1Kbdu2xfnz57WWXbhwAX5+fgCAgIAAeHt7Izk5GSEhIQCA4uJiHDx4EPPmzQMAhIaGQqlUIjk5Gf369QMAZGZmIj09HQkJCXq3q1KpoFKpdJYrlUqTvoE2trYA7o+I8RfQMkz9HpJ+rLNlsM6Ww1pbhqnrbIn3zKpBaeLEiWjTpg3i4uLQr18/HDlyBMuXL8fy5csB3A8Y0dHRiIuLQ4MGDdCgQQPExcXB0dERAwcOBAC4urpi5MiRiImJgbu7O2rVqoXJkycjODhYugrOWjiXm4iISN6sGpSee+45bN++HdOnT8fs2bMREBCAhQsXYtCgQVKbKVOmoKCgAGPGjEF2djZatmyJpKQkuLi4SG0WLFgAOzs79OvXDwUFBejUqRPWrFkD2/+O6BAREREZw6pBCQC6d++O7t27G3xeoVAgNjYWsbGxBts4ODhg0aJFWLRokRl6+Ph4GyUiIiJ5svpXmFRnPPNGREQkbwxKRERERAYwKFkCz70RERHJEoOSGfErTIiIiOSNQckCBIeUiIiIZIlByYw4nkRERCRvDEpEREREBjAoWYDgmTciIiJZYlAyI87lJiIikjcGJQvggBIREZE8MSiZEQeUiIiI5I1BiYiIiMgABiULEJzNTUREJEsMSubE2dxERESyxqBkARxPIiIikqcqB6WSkhJ07NgRFy5cMEd/qhWOJxEREclblYOSUqlEeno6v/CViIiIqj2jTr0NGTIEK1euNHVfqi3O5SYiIpInO2NeVFxcjBUrViA5ORlhYWFwcnLSen7+/Pkm6ZzccdCNiIhI3owKSunp6WjRogUA6MxV4ik5IiIiqi6MCkr79+83dT+IiIiInjiPfXuAq1ev4tq1a6boS7Wj4HVvREREsmZUUCovL8fs2bPh6uoKPz8/1KtXDzVr1sQHH3yA8vJyU/dR9nhnbiIiInky6tTbjBkzsHLlSsydOxdt27aFEAI//PADYmNjUVhYiDlz5pi6n7LE6VpERETyZlRQWrt2LVasWIGePXtKy5o1a4batWtjzJgxDEpERERULRh16u327dto1KiRzvJGjRrh9u3bj92p6oYn3oiIiOTJqKDUrFkzLF68WGf54sWL0axZs8fuVHXBM29ERETyZtSpt4SEBHTr1g179+5F69atoVAokJKSgitXrmDPnj2m7qPscS43ERGRPBk1ohQeHo4LFy6gd+/euHPnDm7fvo0+ffrg/PnzaN++van7KFuczE1ERCRvVR5RKikpQWRkJD7//HNO2iYiIqJqrcojSkqlEunp6fyqkioQnM5NREQkS0adehsyZAhWrlxp6r5UQwyTREREcmbUZO7i4mKsWLECycnJCAsLg5OTk9bz8+fPN0nniIiIiKzJqKCUnp6OFi1aAAAuXLig9RxPyeniVW9ERETyVOWgVFZWhtjYWAQHB6NWrVrm6FO1wcxIREQkb1Weo2Rra4uoqCjk5OSYoz/VEgeUiIiI5MmoydzBwcG4ePGiqftS7XBAiYiISN6MCkpz5szB5MmTsXv3bmRmZiI3N1frh4iIiKg6MGoyd5cuXQAAPXv21Jq8LYSAQqFAWVmZaXpXXfDcGxERkSwZFZT2799v6n5US5zMTUREJG9GBaXw8HBT96Na4525iYiI5KlKc5QSEhJQUFAgPf7+++9RVFQkPc7Ly8OYMWNM1zuZU3A6NxERkaxVKShNnz4deXl50uPu3bvj2rVr0uN79+7h888/N13viIiIiKyoSkFJVLjFdMXHpB/LREREJE9G3R6AKoeTuYmIiOSNQckCOKBEREQkT1W+6m3FihVwdnYGAJSWlmLNmjXw8PAAAK35S8Q7cxMREcldlYJSvXr18MUXX0iPvb29sX79ep02RERERNVBlYLSH3/8YaZuVG+czE1ERCRPRs1RWrdundb9kzSKi4uxbt26x+5UtcHZ3ERERLJmVFAaPnw4cnJydJbn5eVh+PDhj90pIiIioieBUUFJ8+W3FV29ehWurq6P3anqhl9hQkREJE9VmqMUEhIChUIBhUKBTp06wc7u75eXlZUhIyMDXbp0MXkn5Yon3oiIiOStSkGpV69eAICTJ08iKipKuk0AANjb28Pf3x8vv/yySTtYLXBAiYiISJaqFJRmzpwJAPD390f//v2hUqnM0qnqgnO5iYiI5M2oOUovvvgi/vrrL+nxkSNHEB0djeXLl5usY0RERETWZlRQGjhwIPbv3w8AyMrKQufOnXHkyBG88847mD17tkk7WB3wzBsREZE8GRWU0tPT8fzzzwMA/v3vfyM4OBgpKSnYuHEj1qxZY8r+yRrPvBEREcmbUUGppKREmp+0d+9e9OzZEwDQqFEjZGZmmq531YTgrbmJiIhkyaig9Oyzz2LZsmU4dOgQkpOTpVsCXL9+He7u7ibtoJzpu9cUERERyYdRQWnevHn4/PPP0aFDBwwYMADNmjUDAOzcuVM6JUdEREQkd1W6PYBGhw4dcPPmTeTm5sLNzU1aPmrUKDg6Opqsc9UFT7wRERHJk1EjSsD9eTdpaWn4/PPPkZeXB+D+TScZlP7GE29ERETyZtSI0qVLl9ClSxdcvnwZRUVFiIiIgIuLCxISElBYWIhly5aZup9EREREFmfUiNKECRMQFhaG7OxsqNVqaXnv3r3x3Xffmaxz1QUveiMiIpIno0aUDh8+jB9++AH29vZay/38/HDt2jWTdKw64EVvRERE8mbUiFJ5eTnKysp0ll+9ehUuLi6P3anqhgNKRERE8mRUUIqIiMDChQulxwqFAvn5+Zg5cya6du1qqr4RERERWZVRp94WLFiAjh07okmTJigsLMTAgQPx66+/wsPDA5s2bTJ1H4mIiIiswqig5Ovri5MnT2LTpk04fvw4ysvLMXLkSAwaNEhrcjfdx68wISIikiej76OkVqsxYsQILF68GEuWLMHrr7/+WCEpPj4eCoUC0dHR0jIhBGJjY+Hr6wu1Wo0OHTrgzJkzWq8rKirC+PHj4eHhAScnJ/Ts2RNXr141uh+mxK8wISIikrdKjyjt3Lmz0ivVfEluZR09ehTLly9H06ZNtZYnJCRg/vz5WLNmDZ555hl8+OGHiIiIwPnz56VJ49HR0di1axcSExPh7u6OmJgYdO/eHWlpabC1ta1SP4iIiIgeVOmg1KtXr0q1UygUeq+IMyQ/Px+DBg3CF198gQ8//FBaLoTAwoULMWPGDPTp0wcAsHbtWnh5eWHjxo0YPXo0cnJysHLlSqxfvx6dO3cGAGzYsAF169bF3r17ERUVVel+mAPHk4iIiOSt0kGpvLzcLB0YO3YsunXrhs6dO2sFpYyMDGRlZSEyMlJaplKpEB4ejpSUFIwePRppaWkoKSnRauPr64ugoCCkpKQYDEpFRUUoKiqSHufm5gIASkpKUFJSYrJ90wTG8nJh0vWSLk19WWfzYp0tg3W2HNbaMsxVZ0u8b0ZN5jaVxMREHD9+HEePHtV5LisrCwDg5eWltdzLywuXLl2S2tjb22t9Ma+mjeb1+sTHx2PWrFk6y5OSkkz6XXU/31IAsEX2nTvYs2ePydZLhiUnJ1u7C/8TWGfLYJ0th7W2DFPX+d69eyZdnz6VDkr/+te/Kr3St95665Ftrly5ggkTJiApKQkODg4G21WcEC2EeOQk6Ue1mT59OiZNmiQ9zs3NRd26dREZGYkaNWo8su+VpTh9HbiQDreaNdG1a0uTrZd0lZSUIDk5GREREVAqldbuTrXFOlsG62w5rLVlmKvOmjNC5lTpoLRgwYJKtVMoFJUKSmlpabhx4wZCQ0OlZWVlZfj++++xePFinD9/HsD9USMfHx+pzY0bN6RRJm9vbxQXFyM7O1trVOnGjRto06aNwW2rVCqoVCqd5Uql0qRvoDSZXKHgL6CFmPo9JP1YZ8tgnS2HtbYMU9fZEu9ZpYNSRkaGSTfcqVMnnD59WmvZ8OHD0ahRI0ydOhX169eHt7c3kpOTERISAgAoLi7GwYMHMW/ePABAaGgolEolkpOT0a9fPwBAZmYm0tPTkZCQYNL+EhER0f8eq81RcnFxQVBQkNYyJycnuLu7S8ujo6MRFxeHBg0aoEGDBoiLi4OjoyMGDhwIAHB1dcXIkSMRExMDd3d31KpVC5MnT0ZwcLB0FZw1KXjdGxERkawZHZSuXr2KnTt34vLlyyguLtZ6bv78+Y/dMQCYMmUKCgoKMGbMGGRnZ6Nly5ZISkrS+uLdBQsWwM7ODv369UNBQQE6deqENWvWPFH3UOKduYmIiOTJqKD03XffoWfPnggICMD58+cRFBSEP/74A0IItGjRwujOHDhwQOuxQqFAbGwsYmNjDb7GwcEBixYtwqJFi4zerrnwxtxERETyZtRXmEyfPh0xMTFIT0+Hg4MDtm7diitXriA8PByvvPKKqftIREREZBVGBaVffvkFQ4cOBQDY2dmhoKAAzs7OmD17tjTRmv7GE29ERETyZFRQcnJyku5s7evri99//1167ubNm6bpWTXAM29ERETyZtQcpVatWuGHH35AkyZN0K1bN8TExOD06dPYtm0bWrVqZeo+yh7nchMREcmTUUFp/vz5yM/PBwDExsYiPz8fmzdvxtNPP13pG1P+T+CQEhERkawZFZTq168v/b+joyOWLFlisg4RERERPSke+4aT+fn5KC8v11pmyu9Lqw4Ep3MTERHJklGTuTMyMtCtWzc4OTnB1dUVbm5ucHNzQ82aNbW+c+1/3aO+vJeIiIiebEaNKA0aNAgAsGrVKnh5eTEQPAoHlIiIiGTJqKB06tQppKWloWHDhqbuT7XC+EhERCRvRp16e+6553DlyhVT94WIiIjoiWLUiNKKFSvwxhtv4Nq1awgKCoJSqdR6vmnTpibpXHXBM29ERETyZFRQ+uuvv/D7779j+PDh0jKFQgEhBBQKBcrKykzWQTnj1C0iIiJ5MyoojRgxAiEhIdi0aRMncxMREVG1ZVRQunTpEnbu3Imnn37a1P2plvgVJkRERPJk1GTuF198ET///LOp+1LtcJyNiIhI3owaUerRowcmTpyI06dPIzg4WGcyd8+ePU3SueqCd+YmIiKSJ6OC0htvvAEAmD17ts5znMz9N87dIiIikjejglLF73YjIiIiqo6qNEfpp59+wn/+8x+tZevWrUNAQAA8PT0xatQoFBUVmbSD1QEncxMREclTlYJSbGwsTp06JT0+ffo0Ro4cic6dO2PatGnYtWsX4uPjTd5JueKJNyIiInmrUlA6efIkOnXqJD1OTExEy5Yt8cUXX2DSpEn417/+hX//+98m76TccUSJiIhInqoUlLKzs+Hl5SU9PnjwILp06SI95nfAVcAhJSIiIlmrUlDy8vJCRkYGAKC4uBjHjx9H69atpefz8vJ0bhVAREREJFdVCkpdunTBtGnTcOjQIUyfPh2Ojo5o37699PypU6cQGBho8k7KHc+8ERERyVOVbg/w4Ycfok+fPggPD4ezszPWrl0Le3t76flVq1YhMjLS5J2UKwXPvREREclalYLSU089hUOHDiEnJwfOzs6wtbXVen7Lli1wdnY2aQeJiIiIrMWoG066urrqXV6rVq3H6ky1xcveiIiIZMmoL8WlyuE3mBAREckbg5IFcDyJiIhInhiUzIgDSkRERPLGoERERERkAIOSBXAuNxERkTwxKJkRJ3MTERHJG4OSBQhO5yYiIpIlBiUz4p25iYiI5I1BiYiIiMgABiUL4GRuIiIieWJQMiNO5iYiIpI3BiUL4IASERGRPDEoERERERnAoERERERkAIOSBXAyNxERkTwxKJkRJ3MTERHJG4MSERERkQEMShbBc29ERERyxKBkRvwKEyIiInljULIATuYmIiKSJwYlM+JkbiIiInljUCIiIiIygEHJAnjmjYiISJ4YlMyIZ96IiIjkjUHJAjiZm4iISJ4YlMxIwdncREREssagRERERGQAg5IFCE7nJiIikiUGJTPiiTciIiJ5Y1AiIiIiMoBByQJ41RsREZE8MSiZE8+9ERERyRqDkgVwQImIiEieGJTMiANKRERE8sagRERERGQAg5IlcDY3ERGRLDEomRG/woSIiEjeGJQsgONJRERE8sSgZEYcTyIiIpI3BiUiIiIiAxiULIBzuYmIiOSJQcmMOJebiIhI3qwalOLj4/Hcc8/BxcUFnp6e6NWrF86fP6/VRgiB2NhY+Pr6Qq1Wo0OHDjhz5oxWm6KiIowfPx4eHh5wcnJCz549cfXqVUvuykNxQImIiEierBqUDh48iLFjx+LHH39EcnIySktLERkZibt370ptEhISMH/+fCxevBhHjx6Ft7c3IiIikJeXJ7WJjo7G9u3bkZiYiMOHDyM/Px/du3dHWVmZNXZLouB0biIiIlmzs+bGv/nmG63Hq1evhqenJ9LS0vDCCy9ACIGFCxdixowZ6NOnDwBg7dq18PLywsaNGzF69Gjk5ORg5cqVWL9+PTp37gwA2LBhA+rWrYu9e/ciKirK4vtFRERE1YNVg1JFOTk5AIBatWoBADIyMpCVlYXIyEipjUqlQnh4OFJSUjB69GikpaWhpKREq42vry+CgoKQkpKiNygVFRWhqKhIepybmwsAKCkpQUlJicn2p7S0FMD904emXC/p0tSXdTYv1tkyWGfLYa0tw1x1tsT79sQEJSEEJk2ahHbt2iEoKAgAkJWVBQDw8vLSauvl5YVLly5Jbezt7eHm5qbTRvP6iuLj4zFr1iyd5UlJSXB0dHzsfdG4kg8AdigsLMSePXtMtl4yLDk52dpd+J/AOlsG62w5rLVlmLrO9+7dM+n69HligtK4ceNw6tQpHD58WOe5il8FIoR45NeDPKzN9OnTMWnSJOlxbm4u6tati8jISNSoUcOI3uv38+XbwOljcHBwQNeu4SZbL+kqKSlBcnIyIiIioFQqrd2daot1tgzW2XJYa8swV501Z4TM6YkISuPHj8fOnTvx/fffo06dOtJyb29vAPdHjXx8fKTlN27ckEaZvL29UVxcjOzsbK1RpRs3bqBNmzZ6t6dSqaBSqXSWK5VKk76Bdnb3yyv+u24yP1O/h6Qf62wZrLPlsNaWYeo6W+I9s+pVb0IIjBs3Dtu2bcO+ffsQEBCg9XxAQAC8vb21huqKi4tx8OBBKQSFhoZCqVRqtcnMzER6errBoERERERUGVYdURo7diw2btyI//u//4OLi4s0p8jV1RVqtRoKhQLR0dGIi4tDgwYN0KBBA8TFxcHR0REDBw6U2o4cORIxMTFwd3dHrVq1MHnyZAQHB0tXwVkdb6REREQkS1YNSkuXLgUAdOjQQWv56tWrMWzYMADAlClTUFBQgDFjxiA7OxstW7ZEUlISXFxcpPYLFiyAnZ0d+vXrh4KCAnTq1Alr1qyBra2tpXZFL96Zm4iISN6sGpREJb4ETaFQIDY2FrGxsQbbODg4YNGiRVi0aJEJe0dERET/6/hdbxbAM29ERETyxKBkRvwKEyIiInljULKAypxiJCIioicPg5IZcTI3ERGRvDEoERERERnAoGQBPPFGREQkTwxKZsQzb0RERPLGoERERERkAIOSBfCiNyIiInliUDIjXvVGREQkbwxKFiA4nZuIiEiWGJTMiHfmJiIikjcGJSIiIiIDGJQsgJO5iYiI5IlByZx45o2IiEjWGJSIiIiIDGBQMiMOKBEREckbgxIRERGRAQxKFsDJ3ERERPLEoGRGCt6am4iISNYYlCyAd+YmIiKSJwYlIiIiIgMYlMyIJ96IiIjkjUHJAjiZm4iISJ4YlMyIc7mJiIjkjUGJiIiIyAAGJQvgmTciIiJ5YlAyI556IyIikjcGJQvgZG4iIiJ5YlAyI6Xt/fKWlJVbuSdERERkDAYlM1LZ3S9vUWk5BIeViIiIZIdByYw0QQkAijmqREREJDsMSmZkb2cr/X9RKYMSERGR3DAomZG97d+XvRWVMCgRERHJDYOSGSkUCigV9+cmFZWWWbk3REREVFUMSmammabEU29ERETyw6BkZkpNUOKpNyIiItlhUDKzv0eUeOqNiIhIbhiUzEzJU29ERESyxaBkZnb/vfCNQYmIiEh+GJTM7O85Sjz1RkREJDcMSmZmZ6O5PQBHlIiIiOSGQcnMOEeJiIhIvhiUzEz9328xuZVfZN2OEBERUZUxKJnZU+r7//3j1l3rdoSIiIiqjEHJzDwd7s9RuvgXgxIREZHcMCiZmZf6flA6m5mLsnJh5d4QERFRVTAomZmvE+Bkb4u8wlKcvZ5r7e4QERFRFTAomZmtAmj3tDsAYPUPGVbuDREREVUFg5IFvNyiNgDgDEeUiIiIZIVByQLq1XIEAFzPKbByT4iIiKgqGJQswMdVBQDIKyxFXmGJlXtDRERElcWgZAGO9nao6agEAGTmFFq5N0RERFRZDEoW4uN6/86T1+7w9BsREZFcMChZSO2aDgCAzDscUSIiIpILBiUL0YwoXeeIEhERkWwwKFmIb837QSmD3/lGREQkGwxKFvKcvxsA4MC5G/grr8jKvSEiIqLKYFCykBb13BDg4YS7xWXoveQHZN8ttnaXiIiI6BEYlCzExkaBFUPDULumGlezC/BW4gnk8p5KRERETzQGJQsKfMoZ8X2CAQCHfr2J/p//iJKyciv3ioiIiAxhULKwF555Ch+/0gwqOxuczczF1K9OWbtLREREZACDkhX0Da2DyZENAQDbTlzDicvZVu4RERER6cOgZCXD2vrDx/X+TShXHMqAEMLKPSIiIqKK7Kzdgf9VSlsbfNo/BP2Xp+Lr05n4bWE+3uwQCD93R9goFFAoAAXu/xeA1mOt///vc9B6rJCWV1xHdVVaWorbRfe/IsbOjpPkzYV1tgzW2XJYa8soLS1FYZm1e2EcheBQBnJzc+Hq6oqcnBzUqFHDZOstKSnBnj170LVrVyiVSr1tNv50Ge9sP22ybRIRET2JXq1fhg+H/8Pg30NjmOvv94M4omRlA1vWQ8v6tbD6hwz8kpmHrJz73wUnhIAAIARQ/sD/AwJC4L+P/16u+X/oe+6/r6nuysvKYGNra+1uVHuss2WwzpbDWluGAvIcUmJQegIEPuWMD3sFW7sbsvb36F2USf+1QtpYZ8tgnS2HtbYMTZ3liJO5iYiIiAxgUCIiIiIyoNoEpSVLliAgIAAODg4IDQ3FoUOHrN0lIiIikrlqEZQ2b96M6OhozJgxAydOnED79u3xj3/8A5cvX7Z214iIiEjGqkVQmj9/PkaOHInXX38djRs3xsKFC1G3bl0sXbrU2l0jIiIiGZP9VW/FxcVIS0vDtGnTtJZHRkYiJSVF72uKiopQVFQkPc7NzQVwf1Z+SYnpbjimWZcp10n6sdaWwTpbButsOay1ZZirzpZ432QflG7evImysjJ4eXlpLffy8kJWVpbe18THx2PWrFk6y5OSkuDo6GjyPiYnJ5t8naQfa20ZrLNlsM6Ww1pbhqnrfO/ePZOuTx/ZByUNRYXv5xBC6CzTmD59OiZNmiQ9zs3NRd26dREZGWnyO3MnJycjIiKC9+cwM9baMlhny2CdLYe1tgxz1VlzRsicZB+UPDw8YGtrqzN6dOPGDZ1RJg2VSgWVSqWzXKlUmuUXxVzrJV2stWWwzpbBOlsOa20Zpq6zJd4z2U/mtre3R2hoqM5wXnJyMtq0aWOlXhEREVF1IPsRJQCYNGkSBg8ejLCwMLRu3RrLly/H5cuX8cYbb1i7a0RERCRj1SIovfrqq7h16xZmz56NzMxMBAUFYc+ePfDz87N214iIiEjGqkVQAoAxY8ZgzJgx1u4GERERVSOyn6NEREREZC7VZkTpcQghAJj+MsOSkhLcu3cPubm5vJrCzFhry2CdLYN1thzW2jLMVWfN323N33FzYFACkJeXBwCoW7eulXtCREREVZWXlwdXV1ezrFshzBnDZKK8vBzXr1+Hi4uLwZtUGkNzI8srV66Y9EaWpIu1tgzW2TJYZ8thrS3DXHUWQiAvLw++vr6wsTHPbCKOKAGwsbFBnTp1zLb+GjVq8BfQQlhry2CdLYN1thzW2jLMUWdzjSRpcDI3ERERkQEMSkREREQGMCiZkUqlwsyZM/V+rxyZFmttGayzZbDOlsNaW4ac68zJ3EREREQGcESJiIiIyAAGJSIiIiIDGJSIiIiIDGBQIiIiIjKAQcmMlixZgoCAADg4OCA0NBSHDh2ydpdkIz4+Hs899xxcXFzg6emJXr164fz581pthBCIjY2Fr68v1Go1OnTogDNnzmi1KSoqwvjx4+Hh4QEnJyf07NkTV69eteSuyEp8fDwUCgWio6OlZayz6Vy7dg2vvfYa3N3d4ejoiObNmyMtLU16nrV+fKWlpXj33XcREBAAtVqN+vXrY/bs2SgvL5fasM7G+f7779GjRw/4+vpCoVBgx44dWs+bqq7Z2dkYPHgwXF1d4erqisGDB+POnTtm3ruHEGQWiYmJQqlUii+++EKcPXtWTJgwQTg5OYlLly5Zu2uyEBUVJVavXi3S09PFyZMnRbdu3US9evVEfn6+1Gbu3LnCxcVFbN26VZw+fVq8+uqrwsfHR+Tm5kpt3njjDVG7dm2RnJwsjh8/Ljp27CiaNWsmSktLrbFbT7QjR44If39/0bRpUzFhwgRpOetsGrdv3xZ+fn5i2LBh4qeffhIZGRli79694rfffpPasNaP78MPPxTu7u5i9+7dIiMjQ2zZskU4OzuLhQsXSm1YZ+Ps2bNHzJgxQ2zdulUAENu3b9d63lR17dKliwgKChIpKSkiJSVFBAUFie7du1tqN3UwKJnJ888/L9544w2tZY0aNRLTpk2zUo/k7caNGwKAOHjwoBBCiPLycuHt7S3mzp0rtSksLBSurq5i2bJlQggh7ty5I5RKpUhMTJTaXLt2TdjY2IhvvvnGsjvwhMvLyxMNGjQQycnJIjw8XApKrLPpTJ06VbRr187g86y1aXTr1k2MGDFCa1mfPn3Ea6+9JoRgnU2lYlAyVV3Pnj0rAIgff/xRapOamioAiHPnzpl5r/TjqTczKC4uRlpaGiIjI7WWR0ZGIiUlxUq9krecnBwAQK1atQAAGRkZyMrK0qqxSqVCeHi4VOO0tDSUlJRotfH19UVQUBDfhwrGjh2Lbt26oXPnzlrLWWfT2blzJ8LCwvDKK6/A09MTISEh+OKLL6TnWWvTaNeuHb777jtcuHABAPDzzz/j8OHD6Nq1KwDW2VxMVdfU1FS4urqiZcuWUptWrVrB1dXVarXnl+Kawc2bN1FWVgYvLy+t5V5eXsjKyrJSr+RLCIFJkyahXbt2CAoKAgCpjvpqfOnSJamNvb093NzcdNrwffhbYmIijh8/jqNHj+o8xzqbzsWLF7F06VJMmjQJ77zzDo4cOYK33noLKpUKQ4YMYa1NZOrUqcjJyUGjRo1ga2uLsrIyzJkzBwMGDADAY9pcTFXXrKwseHp66qzf09PTarVnUDIjhUKh9VgIobOMHm3cuHE4deoUDh8+rPOcMTXm+/C3K1euYMKECUhKSoKDg4PBdqzz4ysvL0dYWBji4uIAACEhIThz5gyWLl2KIUOGSO1Y68ezefNmbNiwARs3bsSzzz6LkydPIjo6Gr6+vhg6dKjUjnU2D1PUVV97a9aep97MwMPDA7a2tjrp98aNGzppmx5u/Pjx2LlzJ/bv3486depIy729vQHgoTX29vZGcXExsrOzDbb5X5eWloYbN24gNDQUdnZ2sLOzw8GDB/Gvf/0LdnZ2Up1Y58fn4+ODJk2aaC1r3LgxLl++DIDHtKm8/fbbmDZtGvr374/g4GAMHjwYEydORHx8PADW2VxMVVdvb2/8+eefOuv/66+/rFZ7BiUzsLe3R2hoKJKTk7WWJycno02bNlbqlbwIITBu3Dhs27YN+/btQ0BAgNbzAQEB8Pb21qpxcXExDh48KNU4NDQUSqVSq01mZibS09P5PvxXp06dcPr0aZw8eVL6CQsLw6BBg3Dy5EnUr1+fdTaRtm3b6tzi4sKFC/Dz8wPAY9pU7t27Bxsb7T9ttra20u0BWGfzMFVdW7dujZycHBw5ckRq89NPPyEnJ8d6tbfGDPL/BZrbA6xcuVKcPXtWREdHCycnJ/HHH39Yu2uy8OabbwpXV1dx4MABkZmZKf3cu3dPajN37lzh6uoqtm3bJk6fPi0GDBig91LUOnXqiL1794rjx4+LF1988X/+Et9HefCqNyFYZ1M5cuSIsLOzE3PmzBG//vqr+PLLL4Wjo6PYsGGD1Ia1fnxDhw4VtWvXlm4PsG3bNuHh4SGmTJkitWGdjZOXlydOnDghTpw4IQCI+fPnixMnTki3vTFVXbt06SKaNm0qUlNTRWpqqggODubtAaqrzz77TPj5+Ql7e3vRokUL6dJ2ejQAen9Wr14ttSkvLxczZ84U3t7eQqVSiRdeeEGcPn1aaz0FBQVi3LhxolatWkKtVovu3buLy5cvW3hv5KViUGKdTWfXrl0iKChIqFQq0ahRI7F8+XKt51nrx5ebmysmTJgg6tWrJxwcHET9+vXFjBkzRFFRkdSGdTbO/v379X4uDx06VAhhurreunVLDBo0SLi4uAgXFxcxaNAgkZ2dbaG91KUQQgjrjGURERERPdk4R4mIiIjIAAYlIiIiIgMYlIiIiIgMYFAiIiIiMoBBiYiIiMgABiUiIiIiAxiUiIiIiAxgUCIiqqQ1a9agZs2a1u4GEVkQgxIRmVxWVhYmTJiAp59+Gg4ODvDy8kK7du2wbNky3Lt3z9rdqxR/f38sXLhQa9mrr76KCxcuWKdDRGQVdtbuABFVLxcvXkTbtm1Rs2ZNxMXFITg4GKWlpbhw4QJWrVoFX19f9OzZ0yp9E0KgrKwMdnbGffSp1Wqo1WoT94qInmQcUSIikxozZgzs7Oxw7Ngx9OvXD40bN0ZwcDBefvllfP311+jRowcAICcnB6NGjYKnpydq1KiBF198ET///LO0ntjYWDRv3hzr16+Hv78/XF1d0b9/f+Tl5UlthBBISEhA/fr1oVar0axZM3z11VfS8wcOHIBCocC3336LsLAwqFQqHDp0CL///jteeukleHl5wdnZGc899xz27t0rva5Dhw64dOkSJk6cCIVCAYVCAUD/qbelS5ciMDAQ9vb2aNiwIdavX6/1vEKhwIoVK9C7d284OjqiQYMG2Llzp8nqTUTmxaBERCZz69YtJCUlYezYsXByctLbRqFQQAiBbt26ISsrC3v27EFaWhpatGiBTp064fbt21Lb33//HTt27MDu3buxe/duHDx4EHPnzpWef/fdd7F69WosXboUZ86cwcSJE/Haa6/h4MGDWtucMmUK4uPj8csvv6Bp06bIz89H165dsXfvXpw4cQJRUVHo0aMHLl++DADYtm0b6tSpg9mzZyMzMxOZmZl692X79u2YMGECYmJikJ6ejtGjR2P48OHYv3+/VrtZs2ahX79+OHXqFLp27YpBgwZp7ScRPcGs9nW8RFTt/PjjjwKA2LZtm9Zyd3d34eTkJJycnMSUKVPEd999J2rUqCEKCwu12gUGBorPP/9cCCHEzJkzhaOjo8jNzZWef/vtt0XLli2FEELk5+cLBwcHkZKSorWOkSNHigEDBggh/v628x07djyy702aNBGLFi2SHvv5+YkFCxZotVm9erVwdXWVHrdp00b885//1GrzyiuviK5du0qPAYh3331Xepyfny8UCoX4z3/+88g+EZH1cY4SEZmc5lSVxpEjR1BeXo5BgwahqKgIaWlpyM/Ph7u7u1a7goIC/P7779Jjf39/uLi4SI99fHxw48YNAMDZs2dRWFiIiIgIrXUUFxcjJCREa1lYWJjW47t372LWrFnYvXs3rl+/jtLSUhQUFEgjSpX1yy+/YNSoUVrL2rZti08//VRrWdOmTaX/d3JygouLi7QfRPRkY1AiIpN5+umnoVAocO7cOa3l9evXBwBpInR5eTl8fHxw4MABnXU8OAdIqVRqPadQKFBeXi6tAwC+/vpr1K5dW6udSqXSelzxNODbb7+Nb7/9Fh9//DGefvppqNVq9O3bF8XFxZXcU+0+PUgIobPsYftBRE82BiUiMhl3d3dERERg8eLFGD9+vMF5Si1atEBWVhbs7Ozg7+9v1LaaNGkClUqFy5cvIzw8vEqvPXToEIYNG4bevXsDAPLz8/HHH39otbG3t0dZWdlD19O4cWMcPnwYQ4YMkZalpKSgcePGVeoPET25GJSIyKSWLFmCtm3bIiwsDLGxsWjatClsbGxw9OhRnDt3DqGhoejcuTNat26NXr16Yd68eWjYsCGuX7+OPXv2oFevXjqnyvRxcXHB5MmTMXHiRJSXl6Ndu3bIzc1FSkoKnJ2dMXToUIOvffrpp7Ft2zb06NEDCoUC7733ns4Ij7+/P77//nv0798fKpUKHh4eOut5++230a9fP2ki+q5du7Bt2zatK+iISN4YlIjIpAIDA3HixAnExcVh+vTpuHr1KlQqFZo0aYLJkydjzJgxUCgU2LNnD2bMmIERI0bgr7/+gre3N1544QV4eXlVelsffPABPD09ER8fj4sXL6JmzZpo0aIF3nnnnYe+bsGCBRgxYgTatGkDDw8PTJ06Fbm5uVptZs+ejdGjRyMwMBBFRUUQQuisp1evXvj000/x0Ucf4a233kJAQABWr16NDh06VHofiOjJphD6fvuJiIiIiPdRIiIiIjKEQYmIiIjIAAYlIiIiIgMYlIiIiIgMYFAiIiIiMoBBiYiIiMgABiUiIiIiAxiUiIiIiAxgUCIiIiIygEGJiIiIyAAGJSIiIiIDGJSIiIiIDPh/NQxOrkXAY2gAAAAASUVORK5CYII=",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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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 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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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 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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SjB8/XiqvaiqwVatWIjAw0GTZRVRUlPD29q5yGc306dNlv293i4iIEI888kiV/b1XVX+7/ve//4kpU6aILVu2iD179ohFixaJRo0aCUdHxxr/fnMqsAbc3Nywd+9eHDp0CLNmzcLTTz+NM2fOYPLkyQgICDC526pdu3Zo2LCh9NjPzw/AnSHnuxc8l5ffPc1XUFCASZMm4eGHH4aNjQ1sbGzQoEED3Lx5E6dOnapRv7/66iuUlJRgyJAhKCkpkX7s7OwQGhoqDUe7urqiRYsWmDt3LubNm4ejR4+aTPHUVpcuXXDo0CGTnxEjRpjU/fvf/15hG23atDGZltu5cye6desGHx8fWfmwYcNw69Ytk2H0ytquDfH7lFT5HZgBAQEICgrCihUrpDqnTp3CwYMHMXz4cKls69at8Pf3R7t27WTvR2RkZIXTA0899RRcXFxq3c+MjAxotVrZT/m1unXrVmg0Grzwwguyvnh5eaFt27YmffHy8sLjjz8uK2vTpo3s2lXq/Hbu3Inu3btDr9fD2toaWq0Wb7/9Nn777Tfk5OTUOA43b97EgQMH8Mwzz8gWiltbWyMmJgaXLl3C6dOnZc+Jjo42OVfgj9/Vdu3awdbWFqNGjcKqVatMpk9rqnxB8b0L8Z999lk4OjqaTGlV9DtRlZs3b0rXgLu7O/75z3/iueeew/Tp06U61f28OHPmDM6ePYsRI0bAzs6u0teracyjoqJkj8s/H3v37m1SXtHSiP79+8v64+TkhD59+uCbb75BaWlplfGpzvUNAF988QU6d+6MBg0awMbGBlqtFsuXL6/xZ3O506dP4/Lly4iJiZFNXTVo0AB///vfsX//fpOp5Yquzdu3b1frd6M61wEAlJSUYMaMGWjdujVsbW1hY2MDW1tb/PDDD9U61x9//BHff/89Bg8eLLVX/tOrVy9kZWWZvP8VqewudyXvfu/Rowfee+89REVF4cknn8TLL7+MvXv3QqPR4O23365RW0ysaqFDhw6YNGkSvvjiC1y+fBnjx4/Hzz//jDlz5sjqubq6yh7b2tpWWX779m2pbNCgQVi0aBH+8Y9/4KuvvsLBgwdx6NAh/O1vf0NhYWGN+ls+Z/7YY4+Z/IFdt26d9EdWo9Hg66+/RmRkJObMmYP27dvjb3/7G8aNG4cbN27U6DXvpdfr0aFDB5Ofiu7KqexOnYrKf/vttwrLDQaDdLw6bd+rcePGAIBz585VWqd8fcbdSd3w4cORlpaG77//HsCdO0x0Op1szdOVK1dw7Ngxk/fCyckJQgiTBL2mfb73j4Cvr6+UyN67vurKlSsQQsDT09OkP/v37zfpS0V3x+h0Otk1qcT5HTx4EBEREQCApUuX4ttvv8WhQ4cwZcoUAKjx7wAA5ObmQghRo+vl3vPV6XSy12/RogV27NgBDw8PvPzyy2jRogVatGiBDz/8sMb9K399Gxsb/O1vf5OVazQaeHl51fp6Lmdvby9dC1u2bEFYWBg+//xzzJo1S6pT3c+Lq1evAgAaNWpU6evVJuY1+dy8+zOznJeXV4VlxcXF971FvzrX94YNGzBgwAA0bNgQCQkJSEtLw6FDhzB8+PAK+1Md5TGoLE5lZWXIzc2tsq/3XptVqc51AAATJkzAW2+9hb59+2LLli04cOAADh06hLZt21brdcqvpYkTJ5pcS2PGjAGAKrd/KT/He68RALh27ZrJNaG0pk2bokuXLti/f3+NnsftFh6QVqvF1KlTMX/+fGRmZirSZl5eHrZu3YqpU6fijTfekMqLiopw7dq1Grfn7u4OAPjyyy/RpEmTKus2adIEy5cvB3DnX6T//e9/ER8fj+LiYixevLjGr10bNfnXiZubG7KyskzKyxcYl5/7/dq+V3h4OD755BNs2rRJ9h7cbdOmTbCxsZHti/L8889jwoQJWLlyJaZPn47Vq1ejb9++shEZd3d32Nvb49NPP62w3dr2OSwsDDY2Nti8eTNGjRolldvb20sLU8tvnrj7tTQaDfbu3St9MN+torL7UeL8EhMTodVqsXXrVtnoQ0V7AlWXi4sLrKysanS9VMcTTzyBJ554AqWlpTh8+DAWLlyI2NhYeHp6YuDAgTVqy83NDSUlJbh69aosuRJCIDs7W1okXK6m/2K3srKSrgXgznUeFBSEadOmYfDgwfDx8an250V5/y5dulRpnbqKeVUq2nMoOzsbtra2imxpkZCQgGbNmmHdunWy+BcVFdW6zfIEorI4WVlZPdCo9b2qcx0Ad851yJAhmDFjhuz5v/76Kx566KH7vk75ezt58mT079+/wjq+vr6VPj8gIAAAcPz4cdnWFCUlJfj+++8rvUlHSUKIGi+A54hVDVR00QOQhkTL/wX2oDQaDYQQJn/Uli1bdt+h7IpERkbCxsYGZ8+erXDU6O5fsLs98sgjePPNNxEQEIAjR45I5ff+C64+devWDTt37jS5U+uzzz6Dg4MDOnbsWKt2+/Xrh9atW2PWrFk4c+aMyfF169YhOTkZ//jHP2T/QnZxcUHfvn3x2WefYevWrcjOzpZNAwJ3pjrOnj0LNze3Ct+L2t5l6e3tjeHDh2Pbtm1ITEys1nOioqIghMAvv/xSYV/KP9hqQonz02g0sLGxgbW1tVRWWFiI1atXm9St7vXo6OiI4OBgbNiwQVa/fEPVRo0a1Wha7V7W1tYIDg7Gf/7zHwCQ/c5UV7du3QDc+YN2t/Xr1+PmzZvScaXodDr85z//we3bt/Hee+8BqP7nxSOPPIIWLVrg008/rTSpqOuYV2TDhg2ykaMbN25gy5YteOKJJ2TXU22Vb6p5d1KVnZ1tclcgUP1r09fXFw0bNsTatWtld73evHkT69evl+4UrCsVXQfAnXO99+/Qtm3b8Msvv5g8HzAdLfP19UXLli3x3XffVXotOTk5Vdqv4OBgeHt7m9zZ++WXX6KgoKDSZE0p586dw7ffflvjvyMcsaqByMhINGrUCH369EGrVq1QVlaGjIwMfPDBB2jQoAFeffVVRV7H2dkZTz75JObOnQt3d3c0bdoUe/bswfLly6v1r4R7NW3aFO+88w6mTJmCn376CT169ICLiwuuXLmCgwcPwtHREdOmTcOxY8fwyiuv4Nlnn0XLli1ha2uLnTt34tixY7JRm4CAACQmJmLdunVo3rw57Ozs7vsH+Pr16xUOp+p0OgQGBtb4nMpNnToVW7duRdeuXfH222/D1dUVa9aswbZt2zBnzhzo9fpatWttbY3169cjPDxc2lk/JCQERUVF2LJlCz755BOEhoZWuCns8OHDsW7dOrzyyito1KgRunfvLjseGxuL9evX48knn8T48ePRpk0blJWV4cKFC0hOTkZcXByCg4Nr1e8FCxbg3LlzGDx4MDZv3oynn34aBoMBt27dwvfff4/ExETY2dlBq9UCuLNx66hRo/Diiy/i8OHDePLJJ+Ho6IisrCzs27cPAQEB+Oc//1mjPihxfr1798a8efMwaNAgjBo1Cr/99hvef//9CkfQanI9zpw5E+Hh4ejatSsmTpwIW1tbfPTRR8jMzMTnn39e4xGgxYsXY+fOnejduzcaN26M27dvSyN1977v1REeHo7IyEhMmjQJ+fn56Ny5M44dO4apU6ciMDCwwu08HlRoaCh69eqFFStW4I033kCzZs2q9XkBAP/5z3/Qp08fdOzYEePHj0fjxo1x4cIFfPXVV1izZg0A5WN+P9bW1ggPD8eECRNQVlaG2bNnIz8/v1ZbUVSkfIuLMWPG4JlnnsHFixfx7rvvwtvbGz/88IOsbkBAAHbv3o0tW7bA29sbTk5OFY7QWFlZYc6cORg8eDCioqIwevRoFBUVYe7cubh+/brJFF1dqOg6iIqKwsqVK9GqVSu0adMG6enpmDt3rsn0b4sWLWBvb481a9bAz88PDRo0gMFggMFgwJIlS9CzZ09ERkZi2LBhaNiwIa5du4ZTp07hyJEj+OKLLyrtk7W1NebMmYOYmBiMHj0azz//PH744Qe8/vrrCA8PR48ePaS6e/bsQbdu3fD222/L1kQdPnxYWraRn58PIQS+/PJLAHemu8tHZbt3744nn3wSbdq0gbOzM44fP445c+ZAo9Hg3XffrVkwa7TU/S9u3bp1YtCgQaJly5aiQYMGQqvVisaNG4uYmBhx8uRJWd3KNsUEIF5++WVZWUUb2126dEn8/e9/Fy4uLsLJyUn06NFDZGZmiiZNmsjuMqnJBqGbNm0SXbt2Fc7OzkKn04kmTZqIZ555RuzYsUMIIcSVK1fEsGHDRKtWrYSjo6No0KCBaNOmjZg/f74oKSmR2vn5559FRESEcHJykrZHqEpVdwU2bNjQpN93bydxv3gKIcTx48dFnz59hF6vF7a2tqJt27Ymd6eUx+mLL76osq/3+vXXX8Ubb7whWrVqJezs7ESDBg3E448/LhYtWlTpdhulpaXCx8dHABBTpkypsE5BQYF48803ha+vr7C1tRV6vV4EBASI8ePHy7Y4qOh6uZ/S0lLx2WefifDwcOHu7i5sbGyEXq8Xjz/+uHjrrbdkd6qW+/TTT0VwcLBwdHQU9vb2okWLFmLIkCHi8OHDUp3Q0FDx6KOPmjx36NChJteAEuf36aefCl9fX6HT6UTz5s3FzJkzxfLly03u5qrseqzorkAhhNi7d6946qmnpHPt2LGj2LJli6xOZZsF3vv7lpaWJvr16yeaNGkidDqdcHNzE6GhoVXe4Xt33Cq67b2wsFBMmjRJNGnSRGi1WuHt7S3++c9/mmzfUNONdyt7PSHu/A5ZWVnJbte/3+dFubS0NNGzZ0+h1+uFTqcTLVq0kN0xJsSDxbyyz4V7z6f8/Z49e7aYNm2aaNSokbC1tRWBgYHiq6++qvC17r0rsLrX96xZs0TTpk2FTqcTfn5+YunSpRV+7mZkZIjOnTsLBwcHAUC6I62iz20h7sQ8ODhY2NnZCUdHR9GtWzfx7bffViseFZ1TRWpyHeTm5ooRI0YIDw8P4eDgILp06SL27t0rQkNDTe6u+/zzz0WrVq2EVqsVAMTUqVOlY999950YMGCA8PDwEFqtVnh5eYmnnnpKLF68uMq+llu7dq1o06aNsLW1FV5eXmLcuHEmd+KXx/Tu1y0/38r+/tz92RAbGytat24tnJychI2NjTAYDOKFF16o9l23d9MIcde4IxERERHVGtdYERERESmEiRURERGRQphYERERESmEiRURERGRQphYERERESmEiRURERGRQrhBqILKyspw+fJlODk5Kb7pHREREdUNIQRu3LgBg8FQ46+wuRcTKwVdvnxZ9oW8REREpB4XL16s8ovFq4OJlYLKv/Po4sWLcHZ2Vqxdo9GI5ORkRERESF9FQspjnM2HsTYPxtk8GGfzqatY5+fnw8fHp8rvLqwuJlYKKp/+c3Z2VjyxcnBwgLOzM39p6xDjbD6MtXkwzubBOJtPXcdaiWU8XLxOREREpJB6Tay++eYb9OnTBwaDARqNBps2bTKpc+rUKURHR0Ov18PJyQkdO3bEhQsXpONFRUUYO3Ys3N3d4ejoiOjoaFy6dEnWRm5uLmJiYqDX66HX6xETE4Pr16/L6ly4cAF9+vSBo6Mj3N3dMW7cOBQXF9fFaRMREdGfVL0mVjdv3kTbtm2xaNGiCo+fPXsWXbp0QatWrbB792589913eOutt2BnZyfViY2NxcaNG5GYmIh9+/ahoKAAUVFRKC0tleoMGjQIGRkZSEpKQlJSEjIyMhATEyMdLy0tRe/evXHz5k3s27cPiYmJWL9+PeLi4uru5ImIiOhPp17XWPXs2RM9e/as9PiUKVPQq1cvzJkzRypr3ry59P95eXlYvnw5Vq9eje7duwMAEhIS4OPjgx07diAyMhKnTp1CUlIS9u/fj+DgYADA0qVLERISgtOnT8PX1xfJyck4efIkLl68CIPBAAD44IMPMGzYMEyfPl3R9VJERET052Wxi9fLysqwbds2vP7664iMjMTRo0fRrFkzTJ48GX379gUApKenw2g0IiIiQnqewWCAv78/UlNTERkZibS0NOj1eimpAoCOHTtCr9cjNTUVvr6+SEtLg7+/v5RUAUBkZCSKioqQnp6Orl27VtjHoqIiFBUVSY/z8/MB3FlcZzQaFYtFeVtKtkmmGGfzYazNg3E2D8bZfOoq1kq2Z7GJVU5ODgoKCjBr1iy89957mD17NpKSktC/f3/s2rULoaGhyM7Ohq2tLVxcXGTP9fT0RHZ2NgAgOzsbHh4eJu17eHjI6nh6esqOu7i4wNbWVqpTkZkzZ2LatGkm5cnJyXBwcKjxOd9PSkqK4m2SKcbZfBhr82CczYNxNh+lY33r1i3F2rLYxKqsrAwA8PTTT2P8+PEAgHbt2iE1NRWLFy9GaGhopc8VQshumazo9sna1LnX5MmTMWHCBOlx+T4YERERim+3kJKSgvDwcN7KW4cYZ/NhrM2DcTYPxtl86irW5TNOSrDYxMrd3R02NjZo3bq1rNzPzw/79u0DAHh5eaG4uBi5ubmyUaucnBx06tRJqnPlyhWT9q9evSqNUnl5eeHAgQOy47m5uTAajSYjWXfT6XTQ6XQm5Vqttk5+ueqqXZJjnM2HsTYPxtk8GGfzUTrWSrZlsftY2dra4rHHHsPp06dl5WfOnEGTJk0AAEFBQdBqtbIhwaysLGRmZkqJVUhICPLy8nDw4EGpzoEDB5CXlyerk5mZiaysLKlOcnIydDodgoKC6uwciYiI6M+lXkesCgoK8OOPP0qPz507h4yMDLi6uqJx48Z47bXX8Nxzz+HJJ59E165dkZSUhC1btmD37t0AAL1ejxEjRiAuLg5ubm5wdXXFxIkTERAQIN0l6Ofnhx49emDkyJFYsmQJAGDUqFGIioqCr68vACAiIgKtW7dGTEwM5s6di2vXrmHixIkYOXIk7wgkIiKiaqvXEavDhw8jMDAQgYGBAIAJEyYgMDAQb7/9NgCgX79+WLx4MebMmYOAgAAsW7YM69evR5cuXaQ25s+fj759+2LAgAHo3LkzHBwcsGXLFlhbW0t11qxZg4CAAERERCAiIgJt2rTB6tWrpePW1tbYtm0b7Ozs0LlzZwwYMAB9+/bF+++/b6ZIEBER0Z9BvY5YhYWFQQhRZZ3hw4dj+PDhlR63s7PDwoULsXDhwkrruLq6IiEhocrXady4MbZu3Vp1h4mIiIiqYLFrrOgPV/Jv41oRUGQsvX9lIiIiqjcWe1cg/WHIisP46Vcb+Abmo1NLu/s/gYiIiOoFR6yIiIiIFMLESkUEql6PRkRERPWLiZUqVL77OxEREVkOJlYqcp8bKImIiKieMbFSgSq+rpCIiIgsCBMrIiIiIoUwsVIBDlgRERGpAxMrIiIiIoUwsVIRLl4nIiKybEysVICL14mIiNSBiZWKcINQIiIiy8bESgU0XL5ORESkCkysVIRrrIiIiCwbEysV4BorIiIidWBiRURERKQQJlYqwplAIiIiy8bESgU4E0hERKQOTKxUhIvXiYiILBsTKzXg6nUiIiJVYGKlItwglIiIyLIxsVIBjlcRERGpAxMrIiIiIoUwsVITzgQSERFZNCZWKsC160REROrAxEpFOGBFRERk2ZhYqQBHrIiIiNSBiZWKCO4QSkREZNGYWBEREREphImVCmi4kxUREZEqMLFSEU4EEhERWbZ6Tay++eYb9OnTBwaDARqNBps2baq07ujRo6HRaLBgwQJZeVFREcaOHQt3d3c4OjoiOjoaly5dktXJzc1FTEwM9Ho99Ho9YmJicP36dVmdCxcuoE+fPnB0dIS7uzvGjRuH4uJihc70wXDxOhERkTrUa2J18+ZNtG3bFosWLaqy3qZNm3DgwAEYDAaTY7Gxsdi4cSMSExOxb98+FBQUICoqCqWlpVKdQYMGISMjA0lJSUhKSkJGRgZiYmKk46Wlpejduzdu3ryJffv2ITExEevXr0dcXJxyJ6sArl0nIiKybDb1+eI9e/ZEz549q6zzyy+/4JVXXsFXX32F3r17y47l5eVh+fLlWL16Nbp37w4ASEhIgI+PD3bs2IHIyEicOnUKSUlJ2L9/P4KDgwEAS5cuRUhICE6fPg1fX18kJyfj5MmTuHjxopS8ffDBBxg2bBimT58OZ2fnOjj76uOAFRERkTpY9BqrsrIyxMTE4LXXXsOjjz5qcjw9PR1GoxERERFSmcFggL+/P1JTUwEAaWlp0Ov1UlIFAB07doRer5fV8ff3l42IRUZGoqioCOnp6XV1ekRERPQnU68jVvcze/Zs2NjYYNy4cRUez87Ohq2tLVxcXGTlnp6eyM7Olup4eHiYPNfDw0NWx9PTU3bcxcUFtra2Up2KFBUVoaioSHqcn58PADAajTAajdU4w+op37+qpKRE0XZJrjy2jHHdY6zNg3E2D8bZfOoq1kq2Z7GJVXp6Oj788EMcOXIEmhqu3hZCyJ5T0fNrU+deM2fOxLRp00zKk5OT4eDgUKM+VyU/3xqABkczMmA8f1SxdqliKSkp9d2FvwzG2jwYZ/NgnM1H6VjfunVLsbYsNrHau3cvcnJy0LhxY6mstLQUcXFxWLBgAX7++Wd4eXmhuLgYubm5slGrnJwcdOrUCQDg5eWFK1eumLR/9epVaZTKy8sLBw4ckB3Pzc2F0Wg0Gcm62+TJkzFhwgTpcX5+Pnx8fBAREaHouqxl59OAghto17YdIvy9FWuX5IxGI1JSUhAeHg6tVlvf3flTY6zNg3E2D8bZfOoq1uUzTkqw2MQqJiZGWpBeLjIyEjExMXjxxRcBAEFBQdBqtUhJScGAAQMAAFlZWcjMzMScOXMAACEhIcjLy8PBgwfx+OOPAwAOHDiAvLw8KfkKCQnB9OnTkZWVBW/vO4lLcnIydDodgoKCKu2jTqeDTqczKddqtYq+4VZWd5bCWdtY85fWDJR+/6hyjLV5MM7mwTibj9KxVrKtek2sCgoK8OOPP0qPz507h4yMDLi6uqJx48Zwc3OT1ddqtfDy8oKvry8AQK/XY8SIEYiLi4ObmxtcXV0xceJEBAQESEmZn58fevTogZEjR2LJkiUAgFGjRiEqKkpqJyIiAq1bt0ZMTAzmzp2La9euYeLEiRg5cmS93xEow+0WiIiILFq93hV4+PBhBAYGIjAwEAAwYcIEBAYG4u233652G/Pnz0ffvn0xYMAAdO7cGQ4ODtiyZQusra2lOmvWrEFAQAAiIiIQERGBNm3aYPXq1dJxa2trbNu2DXZ2dujcuTMGDBiAvn374v3331fuZB8ANwglIiJSh3odsQoLC5PueKuOn3/+2aTMzs4OCxcuxMKFCyt9nqurKxISEqpsu3Hjxti6dWu1+0JERER0L4vex4rkOBNIRERk2ZhYqQBnAomIiNSBiZWK8LsCiYiILBsTKxWo6QapREREVD+YWKmI4CorIiIii8bESgU4XkVERKQOTKyIiIiIFMLESkW4eJ2IiMiyMbFSAa5dJyIiUgcmVirCASsiIiLLxsSKiIiISCFMrFSkJt+rSERERObHxEoFuEEoERGROjCxIiIiIlIIEysiIiIihTCxUgFOBBIREakDEysV4dp1IiIiy8bESgW4dp2IiEgdmFipCAesiIiILBsTKxXggBUREZE6MLEiIiIiUggTKxXhzutERESWjYmVCnDndSIiInVgYqUiHK8iIiKybEysVIDjVUREROrAxEpFuMSKiIjIsjGxUgMOWREREakCEysiIiIihTCxUhHOBBIREVk2JlYqoOFcIBERkSowsVITrl4nIiKyaEysVID7gxIREalDvSZW33zzDfr06QODwQCNRoNNmzZJx4xGIyZNmoSAgAA4OjrCYDBgyJAhuHz5sqyNoqIijB07Fu7u7nB0dER0dDQuXbokq5Obm4uYmBjo9Xro9XrExMTg+vXrsjoXLlxAnz594OjoCHd3d4wbNw7FxcV1deq1wvEqIiIiy1avidXNmzfRtm1bLFq0yOTYrVu3cOTIEbz11ls4cuQINmzYgDNnziA6OlpWLzY2Fhs3bkRiYiL27duHgoICREVFobS0VKozaNAgZGRkICkpCUlJScjIyEBMTIx0vLS0FL1798bNmzexb98+JCYmYv369YiLi6u7k68BDlgRERGpg019vnjPnj3Rs2fPCo/p9XqkpKTIyhYuXIjHH38cFy5cQOPGjZGXl4fly5dj9erV6N69OwAgISEBPj4+2LFjByIjI3Hq1CkkJSVh//79CA4OBgAsXboUISEhOH36NHx9fZGcnIyTJ0/i4sWLMBgMAIAPPvgAw4YNw/Tp0+Hs7FyHUSAiIqI/C1WtscrLy4NGo8FDDz0EAEhPT4fRaERERIRUx2AwwN/fH6mpqQCAtLQ06PV6KakCgI4dO0Kv18vq+Pv7S0kVAERGRqKoqAjp6elmOLPq4dp1IiIiy1avI1Y1cfv2bbzxxhsYNGiQNIKUnZ0NW1tbuLi4yOp6enoiOztbquPh4WHSnoeHh6yOp6en7LiLiwtsbW2lOhUpKipCUVGR9Dg/Px/AnfVhRqOxFmdZMfF7RlVaWqpouyRXHlvGuO4x1ubBOJsH42w+dRVrJdtTRWJlNBoxcOBAlJWV4aOPPrpvfSEENHfdSqep4La62tS518yZMzFt2jST8uTkZDg4ONy3n9X1229WAKyQmZkJh5zjirVLFbt3CprqDmNtHoyzeTDO5qN0rG/duqVYWxafWBmNRgwYMADnzp3Dzp07ZeudvLy8UFxcjNzcXNmoVU5ODjp16iTVuXLlikm7V69elUapvLy8cODAAdnx3NxcGI1Gk5Gsu02ePBkTJkyQHufn58PHxwcRERGKrsv68uph4Po1POr/KHp1aKxYuyRnNBqRkpKC8PBwaLXa+u7OnxpjbR6Ms3kwzuZTV7Eun3FSgkUnVuVJ1Q8//IBdu3bBzc1NdjwoKAharRYpKSkYMGAAACArKwuZmZmYM2cOACAkJAR5eXk4ePAgHn/8cQDAgQMHkJeXJyVfISEhmD59OrKysuDt7Q3gzqiTTqdDUFBQpf3T6XTQ6XQm5VqtVtE33EpzZymclZU1f2nNQOn3jyrHWJsH42wejLP5KB1rJduq18SqoKAAP/74o/T43LlzyMjIgKurKwwGA5555hkcOXIEW7duRWlpqbTeydXVFba2ttDr9RgxYgTi4uLg5uYGV1dXTJw4EQEBAdJdgn5+fujRowdGjhyJJUuWAABGjRqFqKgo+Pr6AgAiIiLQunVrxMTEYO7cubh27RomTpyIkSNHWsYdgdxvgYiISBXqNbE6fPgwunbtKj0un1YbOnQo4uPjsXnzZgBAu3btZM/btWsXwsLCAADz58+HjY0NBgwYgMLCQnTr1g0rV66EtbW1VH/NmjUYN26cdPdgdHS0bO8sa2trbNu2DWPGjEHnzp1hb2+PQYMG4f3336+L0yYiIqI/qXpNrMLCwqQ73ipS1bFydnZ2WLhwIRYuXFhpHVdXVyQkJFTZTuPGjbF169b7vl594m4LRERElk1V+1j9VXEmkIiISB2YWKkINwglIiKybEysVKCKrbSIiIjIgjCxUhUOWREREVkyJlYqoOEqKyIiIlVgYkVERESkECZWKsLF60RERJaNiZUKcPE6ERGROjCxUhEOWBEREVk2JlYqwAErIiIidWBipSJcY0VERGTZmFipgIaLrIiIiFSBiRURERGRQphYqYjg8nUiIiKLxsSKiIiISCFMrFSEi9eJiIgsGxMrFeDadSIiInVgYqUiHLAiIiKybEysVIADVkREROrAxIqIiIhIIUys1ISr14mIiCwaEysV4M7rRERE6sDESkU4XkVERGTZmFipAMeriIiI1IGJFREREZFCmFipCNeuExERWTYmVirAtetERETqwMRKRThgRUREZNmYWKmAhsvXiYiIVIGJlYoILrIiIiKyaEys1IADVkRERKrAxIqIiIhIIUysVIQTgURERJatXhOrb775Bn369IHBYIBGo8GmTZtkx4UQiI+Ph8FggL29PcLCwnDixAlZnaKiIowdOxbu7u5wdHREdHQ0Ll26JKuTm5uLmJgY6PV66PV6xMTE4Pr167I6Fy5cQJ8+feDo6Ah3d3eMGzcOxcXFdXHaNcaZQCIiInWo18Tq5s2baNu2LRYtWlTh8Tlz5mDevHlYtGgRDh06BC8vL4SHh+PGjRtSndjYWGzcuBGJiYnYt28fCgoKEBUVhdLSUqnOoEGDkJGRgaSkJCQlJSEjIwMxMTHS8dLSUvTu3Rs3b97Evn37kJiYiPXr1yMuLq7uTr4WuHadiIjIstnU54v37NkTPXv2rPCYEAILFizAlClT0L9/fwDAqlWr4OnpibVr12L06NHIy8vD8uXLsXr1anTv3h0AkJCQAB8fH+zYsQORkZE4deoUkpKSsH//fgQHBwMAli5dipCQEJw+fRq+vr5ITk7GyZMncfHiRRgMBgDABx98gGHDhmH69OlwdnY2QzQqxw1CiYiI1KFeE6uqnDt3DtnZ2YiIiJDKdDodQkNDkZqaitGjRyM9PR1Go1FWx2AwwN/fH6mpqYiMjERaWhr0er2UVAFAx44dodfrkZqaCl9fX6SlpcHf319KqgAgMjISRUVFSE9PR9euXSvsY1FREYqKiqTH+fn5AACj0Qij0ahYLMrK7gxVlZaWKtouyZXHljGue4y1eTDO5sE4m09dxVrJ9iw2scrOzgYAeHp6yso9PT1x/vx5qY6trS1cXFxM6pQ/Pzs7Gx4eHibte3h4yOrc+zouLi6wtbWV6lRk5syZmDZtmkl5cnIyHBwc7neK1ZadbQXACqdPn8b2G98r1i5VLCUlpb678JfBWJsH42wejLP5KB3rW7duKdaWxSZW5TT3zIMJIUzK7nVvnYrq16bOvSZPnowJEyZIj/Pz8+Hj44OIiAhFpw9T/vsd8OsV+Pr6otcTzRVrl+SMRiNSUlIQHh4OrVZb3935U2OszYNxNg/G2XzqKtblM05KqHFiVT71tmTJEjzyyCOKdeReXl5eAO6MJnl7e0vlOTk50uiSl5cXiouLkZubKxu1ysnJQadOnaQ6V65cMWn/6tWrsnYOHDggO56bmwuj0WgyknU3nU4HnU5nUq7VahV9w600d+4xsLKy4i+tGSj9/lHlGGvzYJzNg3E2H6Vjrejf7Nq8eGZm5n1HjR5Us2bN4OXlJRvuKy4uxp49e6SkKSgoCFqtVlYnKysLmZmZUp2QkBDk5eXh4MGDUp0DBw4gLy9PViczMxNZWVlSneTkZOh0OgQFBdXpeVYHF68TERGpQ622WxgyZAiWL1/+wC9eUFCAjIwMZGRkALizYD0jIwMXLlyARqNBbGwsZsyYgY0bNyIzMxPDhg2Dg4MDBg0aBADQ6/UYMWIE4uLi8PXXX+Po0aN44YUXEBAQIN0l6Ofnhx49emDkyJHYv38/9u/fj5EjRyIqKgq+vr4AgIiICLRu3RoxMTE4evQovv76a0ycOBEjR46s9zsC78bdFoiIiCxbrdZYFRcXY9myZUhJSUGHDh3g6OgoOz5v3rxqtXP48GHZHXfl65WGDh2KlStX4vXXX0dhYSHGjBmD3NxcBAcHIzk5GU5OTtJz5s+fDxsbGwwYMACFhYXo1q0bVq5cCWtra6nOmjVrMG7cOOnuwejoaNneWdbW1ti2bRvGjBmDzp07w97eHoMGDcL7779f8+DUAQ5YERERqUOtEqvMzEy0b98eAHDmzBnZsZpMEYaFhUFUseulRqNBfHw84uPjK61jZ2eHhQsXYuHChZXWcXV1RUJCQpV9ady4MbZu3XrfPtcnbhBKRERk2WqVWO3atUvpflAVuMaKiIhIHR74K20uXbqEX375RYm+EBEREalarRKrsrIyvPPOO9Dr9WjSpAkaN26Mhx56CO+++y7KysqU7iP9TnD5OhERkUWr1VTglClTsHz5csyaNQudO3eGEALffvst4uPjcfv2bUyfPl3pfv61cS6QiIhIFWqVWK1atQrLli1DdHS0VNa2bVs0bNgQY8aMYWJVR7h4nYiIyLLVairw2rVraNWqlUl5q1atcO3atQfuFMlxvIqIiEgdapVYtW3bVrYPVLlFixahbdu2D9wpqhhHrIiIiCxbraYC58yZg969e2PHjh0ICQmBRqNBamoqLl68iO3btyvdx788LrEiIiJSh1qNWIWGhuLMmTPo168frl+/jmvXrqF///44ffo0nnjiCaX7SERERKQKNR6xMhqNiIiIwJIlS7hInYiIiOguNR6x0mq1yMzMrNFX19CD0XD5OhERkSrUaipwyJAhWL58udJ9ofuo6nsViYiIqP7VavF6cXExli1bhpSUFHTo0AGOjo6y4/PmzVOkc3QHBweJiIjUoVaJVWZmJtq3bw8AOHPmjOwYpwjrDseriIiILFuNE6vS0lLEx8cjICAArq6uddEnugdTVSIiInWo8Rora2trREZGIi8vry76Q0RERKRatVq8HhAQgJ9++knpvtB9cO06ERGRZatVYjV9+nRMnDgRW7duRVZWFvLz82U/pCwuWyMiIlKHWi1e79GjBwAgOjpatlhdCAGNRoPS0lJlekcyHLAiIiKybLVKrHbt2qV0P6hKHLIiIiJSg1olVqGhoUr3g6qBG4QSERFZthqtsZozZw4KCwulx9988w2Kioqkxzdu3MCYMWOU6x0B4BorIiIitahRYjV58mTcuHFDehwVFYVffvlFenzr1i0sWbJEud4RERERqUiNEqt7p6I4NWVejDYREZFlq9V2C2RenAkkIiJSByZWasIhKyIiIotW47sCly1bhgYNGgAASkpKsHLlSri7uwOAbP0VKYeL14mIiNShRolV48aNsXTpUumxl5cXVq9ebVKH6obgkBUREZFFq1Fi9fPPP9dRN6gqGq6yIiIiUoVarbH67LPPZPtXlSsuLsZnn332wJ0iIiIiUqNaJVYvvvgi8vLyTMpv3LiBF1988YE7RRXj7hZERESWrVaJVfmXLd/r0qVL0Ov1D9wpkuPidSIiInWoUWIVGBiI9u3bQ6PRoFu3bmjfvr3007ZtWzzxxBPo3r27Yp0rKSnBm2++iWbNmsHe3h7NmzfHO++8g7KyMqmOEALx8fEwGAywt7dHWFgYTpw4IWunqKgIY8eOhbu7OxwdHREdHY1Lly7J6uTm5iImJgZ6vR56vR4xMTG4fv26YueiBA5YERERWbYaLV7v27cvACAjIwORkZHStgsAYGtri6ZNm+Lvf/+7Yp2bPXs2Fi9ejFWrVuHRRx/F4cOH8eKLL0Kv1+PVV18FcOf7C+fNm4eVK1fikUcewXvvvYfw8HCcPn0aTk5OAIDY2Fhs2bIFiYmJcHNzQ1xcHKKiopCeng5ra2sAwKBBg3Dp0iUkJSUBAEaNGoWYmBhs2bJFsfOpLQ5YERERqUONEqupU6cCAJo2bYqBAwdCp9PVSafKpaWl4emnn0bv3r2l1/38889x+PBhAHdGqxYsWIApU6agf//+AIBVq1bB09MTa9euxejRo5GXl4fly5dj9erV0mhaQkICfHx8sGPHDkRGRuLUqVNISkrC/v37ERwcDABYunQpQkJCcPr0afj6+tbpeVYX11gRERFZthpvEAoATz31FK5evYpGjRoBAA4ePIi1a9eidevWGDVqlGKd69KlCxYvXowzZ87gkUcewXfffYd9+/ZhwYIFAIBz584hOzsbERER0nN0Oh1CQ0ORmpqK0aNHIz09HUajUVbHYDDA398fqampiIyMRFpaGvR6vZRUAUDHjh2h1+uRmppaaWJVVFQkuzsyPz8fAGA0GmE0GhWLQ5m4M/VZVlaqaLskVx5bxrjuMdbmwTibB+NsPnUVayXbq1ViNWjQIGmqLDs7G927d4e/vz8SEhKQnZ2Nt99+W5HOTZo0CXl5eWjVqhWsra1RWlqK6dOn4/nnnwcAZGdnAwA8PT1lz/P09MT58+elOra2tnBxcTGpU/787OxseHh4mLy+h4eHVKciM2fOxLRp00zKk5OT4eDgUIMzrdrFC1YArPDTT+ewfftZxdqliqWkpNR3F/4yGGvzYJzNg3E2H6VjfevWLcXaqlVilZmZiccffxwA8N///hcBAQH49ttvkZycjJdeekmxxGrdunVISEjA2rVr8eijjyIjIwOxsbEwGAwYOnSoVO/eOxQru2uxqjoV1b9fO5MnT8aECROkx/n5+fDx8UFERAScnZ3ve37VdXDLCSD7FzRr1gy9Ii1jWvLPyGg0IiUlBeHh4dBqtfXdnT81xto8GGfzYJzNp65iXT7jpIRaJVZGo1FaX7Vjxw5ER0cDAFq1aoWsrCzFOvfaa6/hjTfewMCBAwEAAQEBOH/+PGbOnImhQ4fCy8sLwJ0RJ29vb+l5OTk50iiWl5cXiouLkZubKxu1ysnJQadOnaQ6V65cMXn9q1evmoyG3U2n01W4zkyr1Sr6hltb3Vlgb2VtxV9aM1D6/aPKMdbmwTibB+NsPkrHWsm2arWP1aOPPorFixdj7969SElJQY8ePQAAly9fhpubm2Kdu3XrFqys5F20traWtlto1qwZvLy8ZEOCxcXF2LNnj5Q0BQUFQavVyupkZWUhMzNTqhMSEoK8vDwcPHhQqnPgwAHk5eVJdSwCF68TERFZtFqNWM2ePRv9+vXD3LlzMXToULRt2xYAsHnzZmmKUAl9+vTB9OnT0bhxYzz66KM4evQo5s2bh+HDhwO4M30XGxuLGTNmoGXLlmjZsiVmzJgBBwcHDBo0CACg1+sxYsQIxMXFwc3NDa6urpg4cSICAgKkuwT9/PzQo0cPjBw5EkuWLAFwZ7uFqKgoi7gjkBuEEhERqUOtEquwsDD8+uuvyM/Pl02vjRo1StFF2wsXLsRbb72FMWPGICcnBwaDAaNHj5at4Xr99ddRWFiIMWPGIDc3F8HBwUhOTpb2sAKA+fPnw8bGBgMGDEBhYSG6deuGlStXSntYAcCaNWswbtw46e7B6OhoLFq0SLFzUQIHrIiIiCxbrRIr4M7C7vT0dJw9exaDBg2Ck5MTbG1tFU2snJycsGDBAml7hYpoNBrEx8cjPj6+0jp2dnZYuHAhFi5cWGkdV1dXJCQkPEBv6w4HrIiIiNShVonV+fPn0aNHD1y4cAFFRUUIDw+Hk5MT5syZg9u3b2Px4sVK95OIiIjI4tVq8fqrr76KDh06IDc3F/b29lJ5v3798PXXXyvWOZLjzutERESWrVYjVvv27cO3334LW1tbWXmTJk3wyy+/KNIx+sP99uQiIiIiy1CrEauysjKUlpaalF+6dEm2aJyUJbh8nYiIyKLVKrEKDw+XLSjXaDQoKCjA1KlT0atXL6X6Rr/jeBUREZE61GoqcP78+ejatStat26N27dvY9CgQfjhhx/g7u6Ozz//XOk+0u+4xoqIiMiy1SqxMhgMyMjIwOeff44jR46grKwMI0aMwODBg2WL2UkZXGJFRESkDrXex8re3h7Dhw+XdkEnIiIi+qurdmK1efPmajda/qXMpCzOBBIREVm2aidWffv2rVY9jUZT4R2DRERERH921U6sysrK6rIfVA2Cq9eJiIgsWq22WyDz4gahRERE6lDtEat///vf1W503LhxteoMERERkZpVO7GaP39+teppNBomVgrjeBUREZE6VDuxOnfuXF32g4iIiEj1uMZKRbh2nYiIyLLVeoPQS5cuYfPmzbhw4QKKi4tlx+bNm/fAHaM/cO06ERGROtQqsfr6668RHR2NZs2a4fTp0/D398fPP/8MIQTat2+vdB/pdxywIiIismy1mgqcPHky4uLikJmZCTs7O6xfvx4XL15EaGgonn32WaX7+Jen4fJ1IiIiVahVYnXq1CkMHToUAGBjY4PCwkI0aNAA77zzDmbPnq1oB4mIiIjUolaJlaOjI4qKigAABoMBZ8+elY79+uuvyvSMTHDndSIiIstWqzVWHTt2xLfffovWrVujd+/eiIuLw/Hjx7FhwwZ07NhR6T7+5XHxOhERkTrUKrGaN28eCgoKAADx8fEoKCjAunXr8PDDD1d7I1GqOY5XERERWbZaJVbNmzeX/t/BwQEfffSRYh0iUxywIiIiUoda72NVrqCgAGVlZbIyZ2fnB22WKsAlVkRERJatVovXz507h969e8PR0RF6vR4uLi5wcXHBQw89BBcXF6X7SByyIiIiUoVajVgNHjwYAPDpp5/C09MTGq6uJiIiIqpdYnXs2DGkp6fD19dX6f5QFTgTSEREZNlqNRX42GOP4eLFi0r3hSrBndeJiIjUoVYjVsuWLcNLL72EX375Bf7+/tBqtbLjbdq0UaRzdA+uXiciIrJotUqsrl69irNnz+LFF1+UyjQaDYQQ0Gg0KC0tVayDxA1CiYiI1KJWidXw4cMRGBiIzz//nIvXzYjjVURERJatVmuszp8/j9mzZyM4OBhNmzZFkyZNZD9K+uWXX/DCCy/Azc0NDg4OaNeuHdLT06XjQgjEx8fDYDDA3t4eYWFhOHHihKyNoqIijB07Fu7u7nB0dER0dDQuXbokq5Obm4uYmBjo9Xro9XrExMTg+vXrip5LbTFtJSIiUodaJVZPPfUUvvvuO6X7YiI3NxedO3eGVqvF//73P5w8eRIffPABHnroIanOnDlzMG/ePCxatAiHDh2Cl5cXwsPDcePGDalObGwsNm7ciMTEROzbtw8FBQWIioqSTVkOGjQIGRkZSEpKQlJSEjIyMhATE1Pn50hERER/HrWaCuzTpw/Gjx+P48ePIyAgwGTxenR0tCKdmz17Nnx8fLBixQqprGnTptL/CyGwYMECTJkyBf379wcArFq1Cp6enli7di1Gjx6NvLw8LF++HKtXr0b37t0BAAkJCfDx8cGOHTsQGRmJU6dOISkpCfv370dwcDAAYOnSpQgJCcHp06ctZlsJrl0nIiKybLVKrF566SUAwDvvvGNyTMnF65s3b0ZkZCSeffZZ7NmzBw0bNsSYMWMwcuRIAHd2gM/OzkZERIT0HJ1Oh9DQUKSmpmL06NFIT0+H0WiU1TEYDPD390dqaioiIyORlpYGvV4vJVUA0LFjR+j1eqSmplaaWBUVFaGoqEh6nJ+fDwAwGo0wGo2KxACA9JVBZWVlirZLcuWxZYzrHmNtHoyzeTDO5lNXsVayvVolVvd+N2Bd+emnn/Dxxx9jwoQJ+Ne//oWDBw9i3Lhx0Ol0GDJkCLKzswEAnp6esud5enri/PnzAIDs7GzY2tqafNWOp6en9Pzs7Gx4eHiYvL6Hh4dUpyIzZ87EtGnTTMqTk5Ph4OBQs5Otwk8XrQBY4cLFi9i+/bxi7VLFUlJS6rsLfxmMtXkwzubBOJuP0rG+deuWYm3VKLE6cOAArl27hp49e0pln332GaZOnYqbN2+ib9++WLhwIXQ6nSKdKysrQ4cOHTBjxgwAQGBgIE6cOIGPP/4YQ4YMkerde1di+bYPVbm3TkX179fO5MmTMWHCBOlxfn4+fHx8EBERoegXUZ/ZcQa49DN8fBqhVy9/xdolOaPRiJSUFISHh5tMb5OyGGvzYJzNg3E2n7qKdfmMkxJqlFjFx8cjLCxMSqyOHz+OESNGYNiwYfDz88PcuXNhMBgQHx+vSOe8vb3RunVrWZmfnx/Wr18PAPDy8gJwZ8TJ29tbqpOTkyONYnl5eaG4uBi5ubmyUaucnBx06tRJqnPlyhWT17969arJaNjddDpdhUmkVqtV9A23trIGAGg0VvylNQOl3z+qHGNtHoyzeTDO5qN0rJVsq0Z3BWZkZKBbt27S48TERAQHB2Pp0qWYMGEC/v3vf+O///2vYp3r3LkzTp8+LSs7c+aMtKVDs2bN4OXlJRsSLC4uxp49e6SkKSgoCFqtVlYnKysLmZmZUp2QkBDk5eXh4MGDUp0DBw4gLy9PqlOvuN8CERGRKtRoxCo3N1c2grNnzx706NFDeqz0dwiOHz8enTp1wowZMzBgwAAcPHgQn3zyCT755BMAd6bvYmNjMWPGDLRs2RItW7bEjBkz4ODggEGDBgEA9Ho9RowYgbi4OLi5ucHV1RUTJ05EQECAdJegn58fevTogZEjR2LJkiUAgFGjRiEqKspi7ggkIiIiy1ejEStPT0+cO3cOwJ2RoSNHjiAkJEQ6fuPGDUWH0x577DFs3LgRn3/+Ofz9/fHuu+9iwYIFGDx4sFTn9ddfR2xsLMaMGYMOHTrgl19+QXJyMpycnKQ68+fPR9++fTFgwAB07twZDg4O2LJlC6ytraU6a9asQUBAACIiIhAREYE2bdpg9erVip2LErjbAhERkWWr0YhVjx498MYbb2D27NnYtGkTHBwc8MQTT0jHjx07hhYtWijawaioKERFRVV6XKPRID4+vsp1XXZ2dli4cCEWLlxYaR1XV1ckJCQ8SFfrDGcCiYiI1KFGidV7772H/v37IzQ0FA0aNMCqVatga2srHf/0009l+0WRsrhBKBERkWWrUWL1t7/9DXv37kVeXh4aNGggm0oDgC+++AINGjRQtINU8VYQREREZHlqtUGoXq+vsNzV1fWBOkP3wyErIiIiS1arL2Em8+J4FRERkTowsSIiIiJSCBMrFeHidSIiIsvGxEoFuHadiIhIHZhYqQgHrIiIiCwbEysV4IAVERGROjCxUhGusSIiIrJsTKxUgBuEEhERqQMTKyIiIiKFMLFSEcHl60RERBaNiRURERGRQphYqQgXrxMREVk2JlYqwLXrRERE6sDESkU4YEVERGTZmFipAEesiIiI1IGJFREREZFCmFipCVevExERWTQmViqg4bcFEhERqQITKxXhgBUREZFlY2KlAly8TkREpA5MrFSEA1ZERESWjYmVCnDAioiISB2YWBEREREphImVinDxOhERkWVjYqUCGq5eJyIiUgUmVioiuHydiIjIojGxIiIiIlIIEysV4RorIiIiy8bESgW4xIqIiEgdVJVYzZw5ExqNBrGxsVKZEALx8fEwGAywt7dHWFgYTpw4IXteUVERxo4dC3d3dzg6OiI6OhqXLl2S1cnNzUVMTAz0ej30ej1iYmJw/fp1M5wVERER/VmoJrE6dOgQPvnkE7Rp00ZWPmfOHMybNw+LFi3CoUOH4OXlhfDwcNy4cUOqExsbi40bNyIxMRH79u1DQUEBoqKiUFpaKtUZNGgQMjIykJSUhKSkJGRkZCAmJsZs51cdnAkkIiKybKpIrAoKCjB48GAsXboULi4uUrkQAgsWLMCUKVPQv39/+Pv7Y9WqVbh16xbWrl0LAMjLy8Py5cvxwQcfoHv37ggMDERCQgKOHz+OHTt2AABOnTqFpKQkLFu2DCEhIQgJCcHSpUuxdetWnD59ul7O+W6cCSQiIlIHm/ruQHW8/PLL6N27N7p374733ntPKj937hyys7MREREhlel0OoSGhiI1NRWjR49Geno6jEajrI7BYIC/vz9SU1MRGRmJtLQ06PV6BAcHS3U6duwIvV6P1NRU+Pr6VtivoqIiFBUVSY/z8/MBAEajEUajUbHzLy0tAwCUlZUp2i7JlceWMa57jLV5MM7mwTibT13FWsn2LD6xSkxMxJEjR3Do0CGTY9nZ2QAAT09PWbmnpyfOnz8v1bG1tZWNdJXXKX9+dnY2PDw8TNr38PCQ6lRk5syZmDZtmkl5cnIyHBwc7nNm1XcmSwPAGtnZ2di+fbti7VLFUlJS6rsLfxmMtXkwzubBOJuP0rG+deuWYm1ZdGJ18eJFvPrqq0hOToadnV2l9e7dmVwIcd/dyu+tU1H9+7UzefJkTJgwQXqcn58PHx8fREREwNnZucrXr4kr354Dfv4Bnp5e6NWrnWLtkpzRaERKSgrCw8Oh1Wrruzt/aoy1eTDO5sE4m09dxbp8xkkJFp1YpaenIycnB0FBQVJZaWkpvvnmGyxatEha/5SdnQ1vb2+pTk5OjjSK5eXlheLiYuTm5spGrXJyctCpUyepzpUrV0xe/+rVqyajYXfT6XTQ6XQm5VqtVtE33MbaGgBgZaXhL60ZKP3+UeUYa/NgnM2DcTYfpWOtZFsWvXi9W7duOH78ODIyMqSfDh06YPDgwcjIyEDz5s3h5eUlGxIsLi7Gnj17pKQpKCgIWq1WVicrKwuZmZlSnZCQEOTl5eHgwYNSnQMHDiAvL0+qQ0RERHQ/Fj1i5eTkBH9/f1mZo6Mj3NzcpPLY2FjMmDEDLVu2RMuWLTFjxgw4ODhg0KBBAAC9Xo8RI0YgLi4Obm5ucHV1xcSJExEQEIDu3bsDAPz8/NCjRw+MHDkSS5YsAQCMGjUKUVFRlS5crw/ceZ2IiMiyWXRiVR2vv/46CgsLMWbMGOTm5iI4OBjJyclwcnKS6syfPx82NjYYMGAACgsL0a1bN6xcuRLWv0+xAcCaNWswbtw46e7B6OhoLFq0yOznUxHuvE5ERKQOqkusdu/eLXus0WgQHx+P+Pj4Sp9jZ2eHhQsXYuHChZXWcXV1RUJCgkK9rBscsCIiIrJsFr3Giu7ggBUREZE6MLFSEcFFVkRERBaNiZUacJEVERGRKjCxIiIiIlIIEysV4UQgERGRZWNipQKcCCQiIlIHJlYqwrXrRERElo2JlQpw7ToREZE6MLEiIiIiUggTKyIiIiKFMLFSAQ2XrxMREakCEysV4c7rRERElo2JlQpw8ToREZE6MLFSEY5XERERWTYmVipg9fuQVWkZUysiIiJLxsRKBWys7iRWZVxjRUREZNGYWKmA1e+JVQlHrIiIiCwaEysVKB+x4lQgERGRZWNipQLWTKyIiIhUgYmVClhz8ToREZEqMLFSAWvr3xMrLl4nIiKyaEysVIBrrIiIiNSBiZUKSPtYlTKxIiIismRMrFRAGrHiVCAREZFFY2KlAla/v0ucCiQiIrJsTKxUwOb3zIobhBIREVk2JlYqUL6PVRkTKyIiIovGxEoFyvex4ogVERGRZWNipQLSiBXzKiIiIovGxEoFbKQvYS6r554QERFRVZhYqYAVNwglIiJSBSZWKvDHzuv13BEiIiKqkkUnVjNnzsRjjz0GJycneHh4oG/fvjh9+rSsjhAC8fHxMBgMsLe3R1hYGE6cOCGrU1RUhLFjx8Ld3R2Ojo6Ijo7GpUuXZHVyc3MRExMDvV4PvV6PmJgYXL9+va5PsVr+2MeKmRUREZEls+jEas+ePXj55Zexf/9+pKSkoKSkBBEREbh586ZUZ86cOZg3bx4WLVqEQ4cOwcvLC+Hh4bhx44ZUJzY2Fhs3bkRiYiL27duHgoICREVFobS0VKozaNAgZGRkICkpCUlJScjIyEBMTIxZz7cy5ftY8RttiIiILJtNfXegKklJSbLHK1asgIeHB9LT0/Hkk09CCIEFCxZgypQp6N+/PwBg1apV8PT0xNq1azF69Gjk5eVh+fLlWL16Nbp37w4ASEhIgI+PD3bs2IHIyEicOnUKSUlJ2L9/P4KDgwEAS5cuRUhICE6fPg1fX1/znvg9rLnGioiISBUsesTqXnl5eQAAV1dXAMC5c+eQnZ2NiIgIqY5Op0NoaChSU1MBAOnp6TAajbI6BoMB/v7+Up20tDTo9XopqQKAjh07Qq/XS3Xqk/WdvAqlZQKC3xdIRERksSx6xOpuQghMmDABXbp0gb+/PwAgOzsbAODp6Smr6+npifPnz0t1bG1t4eLiYlKn/PnZ2dnw8PAweU0PDw+pTkWKiopQVFQkPc7PzwcAGI1GGI3Gmp5ipcrK/piyLCo2SiNYpKzy90zJ944qxlibB+NsHoyz+dRVrJVsTzWJ1SuvvIJjx45h3759Jsc0GnmiIYQwKbvXvXUqqn+/dmbOnIlp06aZlCcnJ8PBwaHK16+JwhKg/K3atv1/sFHVOKP6pKSk1HcX/jIYa/NgnM2DcTYfpWN969YtxdpSRWI1duxYbN68Gd988w0aNWoklXt5eQG4M+Lk7e0tlefk5EijWF5eXiguLkZubq5s1ConJwedOnWS6ly5csXkda9evWoyGna3yZMnY8KECdLj/Px8+Pj4ICIiAs7OzrU8W1N5N28Dh74BAHSPiICDrSreNtUxGo1ISUlBeHg4tFptfXfnT42xNg/G2TwYZ/Opq1iXzzgpwaL/QgshMHbsWGzcuBG7d+9Gs2bNZMebNWsGLy8vpKSkIDAwEABQXFyMPXv2YPbs2QCAoKAgaLVapKSkYMCAAQCArKwsZGZmYs6cOQCAkJAQ5OXl4eDBg3j88ccBAAcOHEBeXp6UfFVEp9NBp9OZlGu1WkXfcDvdH9ssWFnb8Be3jin9/lHlGGvzYJzNg3E2H6VjrWRbFp1Yvfzyy1i7di3+7//+D05OTtJ6J71eD3t7e2g0GsTGxmLGjBlo2bIlWrZsiRkzZsDBwQGDBg2S6o4YMQJxcXFwc3ODq6srJk6ciICAAOkuQT8/P/To0QMjR47EkiVLAACjRo1CVFRUvd8RCPyxeB3gnYFERESWzKITq48//hgAEBYWJitfsWIFhg0bBgB4/fXXUVhYiDFjxiA3NxfBwcFITk6Gk5OTVH/+/PmwsbHBgAEDUFhYiG7dumHlypWwtraW6qxZswbjxo2T7h6Mjo7GokWL6vYEq+nuxepMrIiIiCyXRSdW1dlaQKPRID4+HvHx8ZXWsbOzw8KFC7Fw4cJK67i6uiIhIaE23axzGo0GVhAog4aJFRERkQXj/WUqUX5zYgkTKyIiIovFxEol7t4klIiIiCwTEyuVsOKIFRERkcVjYqUSNr8nVsUlZVVXJCIionrDxEolyndbLyoprboiERER1RsmViqhlRIrjlgRERFZKiZWKlE+YsWpQCIiIsvFxEoltL+vseJUIBERkeViYqUS0horI0esiIiILBUTK5WwsbqzzQLXWBEREVkuJlYqoeVdgURERBaPiZVK/LHGiiNWREREloqJlUrwrkAiIiLLx8RKJWy4jxUREZHFY2KlEtJUoJFrrIiIiCwVEyuV4IgVERGR5WNipRL8ShsiIiLLx8RKJbS/72N1s6iknntCRERElWFipRINtHf+e+1mcf12hIiIiCrFxEolHG3u/Pc3JlZEREQWi4mVSjhp70wFcsSKiIjIcjGxUglOBRIREVk+JlYqUZ5YFRSV8PsCiYiILBQTK5WwswY0v28Sml/IOwOJiIgsERMrlbDSAA10d1aw59821nNviIiIqCJMrFTE2e73xKqQiRUREZElYmKlIk6/j1jduM2pQCIiIkvExEpFnOzvrGDnVCAREZFlYmKlIhyxIiIismxMrFSEa6yIiIgsGxMrFXF30gEALuUW1nNPiIiIqCJMrFTEz8sJAHDicl4994SIiIgqwsTqHh999BGaNWsGOzs7BAUFYe/evfXdJUlAQ2cAwJEL1/Fl+iWUlYl67hERERHdjYnVXdatW4fY2FhMmTIFR48exRNPPIGePXviwoUL9d01AEBTNwd0auEGAJj4xXfo93Eq8m4ZIQQTLCIiIkugEfyrLAkODkb79u3x8ccfS2V+fn7o27cvZs6ced/n5+fnQ6/XIy8vD87Ozor1y2g0Yvv27ejVqxdulQDzU85gZerP0nEbKw3sba1ha20FG2sNbKysYG2lgbWVBhrFevE7xRu0IEKgoOAmGjRw/OP7g35nZ2ONhz0awMb6j/K7o3t39XtDJD9WyXNkT5K3oPkTxrysrAwXLlxA48aNYWXFf9/VFcZZWY1dHdDdzxM6G3ksjSVG7N61G2Fdw6C10dZP5/4iSkpKcPTbXegT1QtarXKxVvLvt41CfVK94uJipKen44033pCVR0REIDU1tZ56ZUpvr0V89KNo4dEAH+/6EZfzbqOkTHALBsVokHP7VoVHTmblm7kvf3ZWSL1yqb478RfAOCtp1v++r+SIDd45us+sffmrmtKuvntQNSZWv/v1119RWloKT09PWbmnpyeys7MrfE5RURGKioqkx/n5d/7wGo1GGI3KbYlQ3tbdbQ4MMuC59t64cbsEt4ylKCwuhbG0DCVlAqVlQvpvdVR3zFLgzz24WVpSikOHD+GxDo/B2sZaduz6LSMuXPvjbsy7Y1Eev8riePegsJCVo5Lyiuv/mZSVluLs2bNo0aIFrKyt7/8EqhXGWTnG0jLsPv0rzl8z/YeXEEBpaQmsrW3qfIS5vieZ6v0z6fcOKPk3Vun2mFjdQ3PPb4UQwqSs3MyZMzFt2jST8uTkZDg4OCjet5SUFMXbJLmHnYHcM4cqPGYwc1/+7Fr6ACj+sb678afHOCunVTMAzaqqUWqmnpDSfw9v3ap4pqI2mFj9zt3dHdbW1iajUzk5OSajWOUmT56MCRMmSI/z8/Ph4+ODiIgIxddYpaSkIDw8XNE5ZZJjnM2HsTYPxtk8GGfzqatYl884KYGJ1e9sbW0RFBSElJQU9OvXTypPSUnB008/XeFzdDoddDqdSblWq62TX666apfkGGfzYazNg3E2D8bZfJSOtZJtMbG6y4QJExATE4MOHTogJCQEn3zyCS5cuICXXnqpvrtGREREKsDE6i7PPfccfvvtN7zzzjvIysqCv78/tm/fjiZNmtR314iIiEgFmFjdY8yYMRgzZkx9d4OIiIhUiDvGERERESmEiRURERGRQphYERERESmEiRURERGRQphYERERESmEiRURERGRQphYERERESmEiRURERGRQphYERERESmEO68rSAgBQNlvyQbufJv3rVu3kJ+fzy/4rEOMs/kw1ubBOJsH42w+dRXr8r/b5X/HHwQTKwXduHEDAODj41PPPSEiIqKaunHjBvR6/QO1oRFKpGcEACgrK8Ply5fh5OQEjUajWLv5+fnw8fHBxYsX4ezsrFi7JMc4mw9jbR6Ms3kwzuZTV7EWQuDGjRswGAywsnqwVVIcsVKQlZUVGjVqVGftOzs785fWDBhn82GszYNxNg/G2XzqItYPOlJVjovXiYiIiBTCxIqIiIhIIUysVECn02Hq1KnQ6XT13ZU/NcbZfBhr82CczYNxNh81xJqL14mIiIgUwhErIiIiIoUwsSIiIiJSCBMrIiIiIoUwsSIiIiJSCBMrFfjoo4/QrFkz2NnZISgoCHv37q3vLqnGzJkz8dhjj8HJyQkeHh7o27cvTp8+LasjhEB8fDwMBgPs7e0RFhaGEydOyOoUFRVh7NixcHd3h6OjI6Kjo3Hp0iVznoqqzJw5ExqNBrGxsVIZ46ycX375BS+88ALc3Nzg4OCAdu3aIT09XTrOWD+4kpISvPnmm2jWrBns7e3RvHlzvPPOOygrK5PqMM41980336BPnz4wGAzQaDTYtGmT7LhSMc3NzUVMTAz0ej30ej1iYmJw/fr1Oj67P06CLFhiYqLQarVi6dKl4uTJk+LVV18Vjo6O4vz58/XdNVWIjIwUK1asEJmZmSIjI0P07t1bNG7cWBQUFEh1Zs2aJZycnMT69evF8ePHxXPPPSe8vb1Ffn6+VOell14SDRs2FCkpKeLIkSOia9euom3btqKkpKQ+TsuiHTx4UDRt2lS0adNGvPrqq1I546yMa9euiSZNmohhw4aJAwcOiHPnzokdO3aIH3/8UarDWD+49957T7i5uYmtW7eKc+fOiS+++EI0aNBALFiwQKrDONfc9u3bxZQpU8T69esFALFx40bZcaVi2qNHD+Hv7y9SU1NFamqq8Pf3F1FRUWY5RyZWFu7xxx8XL730kqysVatW4o033qinHqlbTk6OACD27NkjhBCirKxMeHl5iVmzZkl1bt++LfR6vVi8eLEQQojr168LrVYrEhMTpTq//PKLsLKyEklJSeY9AQt348YN0bJlS5GSkiJCQ0OlxIpxVs6kSZNEly5dKj3OWCujd+/eYvjw4bKy/v37ixdeeEEIwTgr4d7ESqmYnjx5UgAQ+/fvl+qkpaUJAOL777+v47MSglOBFqy4uBjp6emIiIiQlUdERCA1NbWeeqVueXl5AABXV1cAwLlz55CdnS2LsU6nQ2hoqBTj9PR0GI1GWR2DwQB/f3++D/d4+eWX0bt3b3Tv3l1WzjgrZ/PmzejQoQOeffZZeHh4IDAwEEuXLpWOM9bK6NKlC77++mucOXMGAPDdd99h37596NWrFwDGuS4oFdO0tDTo9XoEBwdLdTp27Ai9Xm+WuPNLmC3Yr7/+itLSUnh6esrKPT09kZ2dXU+9Ui8hBCZMmIAuXbrA398fAKQ4VhTj8+fPS3VsbW3h4uJiUofvwx8SExNx5MgRHDp0yOQY46ycn376CR9//DEmTJiAf/3rXzh48CDGjRsHnU6HIUOGMNYKmTRpEvLy8tCqVStYW1ujtLQU06dPx/PPPw+A13RdUCqm2dnZ8PDwMGnfw8PDLHFnYqUCGo1G9lgIYVJG9/fKK6/g2LFj2Ldvn8mx2sSY78MfLl68iFdffRXJycmws7OrtB7j/ODKysrQoUMHzJgxAwAQGBiIEydO4OOPP8aQIUOkeoz1g1m3bh0SEhKwdu1aPProo8jIyEBsbCwMBgOGDh0q1WOcladETCuqb664cyrQgrm7u8Pa2tokw87JyTHJ6KlqY8eOxebNm7Fr1y40atRIKvfy8gKAKmPs5eWF4uJi5ObmVlrnry49PR05OTkICgqCjY0NbGxssGfPHvz73/+GjY2NFCfG+cF5e3ujdevWsjI/Pz9cuHABAK9ppbz22mt44403MHDgQAQEBCAmJgbjx4/HzJkzATDOdUGpmHp5eeHKlSsm7V+9etUscWdiZcFsbW0RFBSElJQUWXlKSgo6depUT71SFyEEXnnlFWzYsAE7d+5Es2bNZMebNWsGLy8vWYyLi4uxZ88eKcZBQUHQarWyOllZWcjMzOT78Ltu3brh+PHjyMjIkH46dOiAwYMHIyMjA82bN2ecFdK5c2eTLUPOnDmDJk2aAOA1rZRbt27Bykr+J9La2lraboFxVp5SMQ0JCUFeXh4OHjwo1Tlw4ADy8vLME/c6Xx5PD6R8u4Xly5eLkydPitjYWOHo6Ch+/vnn+u6aKvzzn/8Uer1e7N69W2RlZUk/t27dkurMmjVL6PV6sWHDBnH8+HHx/PPPV3h7b6NGjcSOHTvEkSNHxFNPPfWXvmW6Ou6+K1AIxlkpBw8eFDY2NmL69Onihx9+EGvWrBEODg4iISFBqsNYP7ihQ4eKhg0bStstbNiwQbi7u4vXX39dqsM419yNGzfE0aNHxdGjRwUAMW/ePHH06FFpCyGlYtqjRw/Rpk0bkZaWJtLS0kRAQAC3W6A//Oc//xFNmjQRtra2on379tJWAXR/ACr8WbFihVSnrKxMTJ06VXh5eQmdTieefPJJcfz4cVk7hYWF4pVXXhGurq7C3t5eREVFiQsXLpj5bNTl3sSKcVbOli1bhL+/v9DpdKJVq1bik08+kR1nrB9cfn6+ePXVV0Xjxo2FnZ2daN68uZgyZYooKiqS6jDONbdr164KP5OHDh0qhFAupr/99psYPHiwcHJyEk5OTmLw4MEiNzfXLOeoEUKIuh8XIyIiIvrz4xorIiIiIoUwsSIiIiJSCBMrIiIiIoUwsSIiIiJSCBMrIiIiIoUwsSIiIiJSCBMrIiIiIoUwsSIiMrOVK1fioYcequ9uEFEdYGJFRBYrOzsbr776Kh5++GHY2dnB09MTXbp0weLFi3Hr1q367l61NG3aFAsWLJCVPffcczhz5kz9dIiI6pRNfXeAiKgiP/30Ezp37oyHHnoIM2bMQEBAAEpKSnDmzBl8+umnMBgMiI6Orpe+CSFQWloKG5vafYTa29vD3t5e4V4RkSXgiBURWaQxY8bAxsYGhw8fxoABA+Dn54eAgAD8/e9/x7Zt29CnTx8AQF5eHkaNGgUPDw84OzvjqaeewnfffSe1Ex8fj3bt2mH16tVo2rQp9Ho9Bg4ciBs3bkh1hBCYM2cOmjdvDnt7e7Rt2xZffvmldHz37t3QaDT46quv0KFDB+h0Ouzduxdnz57F008/DU9PTzRo0ACPPfYYduzYIT0vLCwM58+fx/jx46HRaKDRaABUPBX48ccfo0WLFrC1tYWvry9Wr14tO67RaLBs2TL069cPDg4OaNmyJTZv3qxYvIlIGUysiMji/Pbbb0hOTsbLL78MR0fHCutoNBoIIdC7d29kZ2dj+/btSE9PR/v27dGtWzdcu3ZNqnv27Fls2rQJW7duxdatW7Fnzx7MmjVLOv7mm29ixYoV+Pjjj3HixAmMHz8eL7zwAvbs2SN7zddffx0zZ87EqVOn0KZNGxQUFKBXr17YsWMHjh49isjISPTp0wcXLlwAAGzYsAGNGjXCO++8g6ysLGRlZVV4Lhs3bsSrr76KuLg4ZGZmYvTo0XjxxRexa9cuWb1p06ZhwIABOHbsGHr16oXBgwfLzpOILIBZvuqZiKgG9u/fLwCIDRs2yMrd3NyEo6OjcHR0FK+//rr4+uuvhbOzs7h9+7asXosWLcSSJUuEEEJMnTpVODg4iPz8fOn4a6+9JoKDg4UQQhQUFAg7OzuRmpoqa2PEiBHi+eefF0IIsWvXLgFAbNq06b59b926tVi4cKH0uEmTJmL+/PmyOitWrBB6vV563KlTJzFy5EhZnWeffVb06tVLegxAvPnmm9LjgoICodFoxP/+97/79omIzIdrrIjIYpVPnZU7ePAgysrKMHjwYBQVFSE9PR0FBQVwc3OT1SssLMTZs2elx02bNoWTk5P02NvbGzk5OQCAkydP4vbt2wgPD5e1UVxcjMDAQFlZhw4dZI9v3ryJadOmYevWrbh8+TJKSkpQWFgojVhV16lTpzBq1ChZWefOnfHhhx/Kytq0aSP9v6OjI5ycnKTzICLLwMSKiCzOww8/DI1Gg++//15W3rx5cwCQFn6XlZXB29sbu3fvNmnj7jVMWq1Wdkyj0aCsrExqAwC2bduGhg0byurpdDrZ43unJV977TV89dVXeP/99/Hwww/D3t4ezzzzDIqLi6t5pvI+3U0IYVJW1XkQkWVgYkVEFsfNzQ3h4eFYtGgRxo4dW+k6q/bt2yM7Oxs2NjZo2rRprV6rdevW0Ol0uHDhAkJDQ2v03L1792LYsGHo168fAKCgoAA///yzrI6trS1KS0urbMfPzw/79u3DkCFDpLLU1FT4+fnVqD9EVP+YWBGRRfroo4/QuXNndOjQAfHx8WjTpg2srKxw6NAhfP/99wgKCkL37t0REhKCvn37Yvbs2fD19cXly5exfft29O3b12TqriJOTk6YOHEixo8fj7KyMnTp0gX5+flITU1FgwYNMHTo0Eqf+/DDD2PDhg3o06cPNBoN3nrrLZMRpKZNm+Kbb77BwIEDodPp4O7ubtLOa6+9hgEDBkgL77ds2YINGzbI7jAkInVgYkVEFqlFixY4evQoZsyYgcmTJ+PSpUvQ6XRo3bo1Jk6ciDFjxkCj0WD79u2YMmUKhg8fjqtXr8LLywtPPvkkPD09q/1a7777Ljw8PDBz5kz89NNPeOihh9C+fXv861//qvJ58+fPx/Dhw9GpUye4u7tj0qRJyM/Pl9V55513MHr0aLRo0QJFRUUQQpi007dvX3z44YeYO3cuxo0bh2bNmmHFihUICwur9jkQkWXQiIp+y4mIiIioxriPFREREZFCmFgRERERKYSJFREREZFCmFgRERERKYSJFREREZFCmFgRERERKYSJFREREZFCmFgRERERKYSJFREREZFCmFgRERERKYSJFREREZFCmFgRERERKeT/AZXH/RaZw8dzAAAAAElFTkSuQmCC",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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2reXl5cLf319MmTJFWn63Q2xt2rQRnTt3NpjOEBkZKby8vO46PeW9997T+327U3h4uHj44Yfv2t+arFy5UgDQ+ztaFzzEdg9ubm7Yv38/MjMzMW/ePDz11FM4c+YMZs2ahYCAAIOzgzp16oSmTZtKj9u2bQvg1lDunRN7dcvvPHxWUlKCmTNn4qGHHoKNjQ1sbGzg5OSE69ev4+TJk/Xq9zfffIOKigqMGDECFRUV0o+dnR1CQkKkYV5XV1f4+fnh/fffx4IFC/DDDz8YHDoxVu/evZGZmWnwM3bsWIO2zzzzTI3r6NChg8Hhrj179qBPnz7w8fHRWz5q1CjcuHHDYHi6tnUbQ/x1qEc3hBsQEIDAwECsWbNGanPy5ElkZGRgzJgx0rKdO3eiffv26NSpk97nERERUeOw+xNPPIEmTZoY3c+srCwolUq9H92+unPnTigUCrz44ot6fdFoNOjYsaNBXzQaDbp37663rEOHDnr7rqm2b8+ePejbty/UajWsra2hVCrx1ltv4erVq8jPz693Ha5fv45Dhw7h2Wef1ZsQbW1tjejoaFy4cAGnT5/We01UVJTBtgK3f1c7deoEW1tbjB8/HuvWrTM4LFlfuomz1SecP/fcc3B0dDQ4VFTT78TdXL9+XdoH3N3d8fLLL+P555/He++9J7Wp6/fFmTNn8Ouvv2Ls2LGws7Or9f3qW/PIyEi9x7rvxwEDBhgsr2nKweDBg/X64+zsjIEDB+K7775DZWXlXetTl/0bAD7//HP06tULTk5OsLGxgVKpxKpVq+r93axz+vRpXLx4EdHR0XrTNZycnPDMM8/g4MGDBodsa9o3b968WaffjbrsBwBQUVGBuLg4tGvXDra2trCxsYGtrS1+/vnnOm3rL7/8glOnTmH48OHS+nQ//fv3R25ursHnX5Pazsqu79naX3/9NV555RU8++yzmDRpUr1ey4BUR127dsXMmTPx+eef4+LFi5gyZQp+//13JCQk6LVzdXXVe2xra3vX5Tdv3pSWDRs2DEuWLME//vEPfPPNN8jIyEBmZiYefPBBlJaW1qu/umPK3bp1M/hDuXnzZumPpUKhwLfffouIiAgkJCSgS5cuePDBBzF58mQUFxfX6z2rU6vV6Nq1q8FPTWeR1HZmSU3Lr169WuNyb29v6fm6rLu65s2bAwBycnJqbaObv3BnOBszZgzS09Nx6tQpAMCaNWugUqn05gRdunQJx44dM/gsnJ2dIYQwCNr17XP1L/PWrVtLgbT6/KNLly5BCAFPT0+D/hw8eNCgL25ubgbvq1Kp9PZJU2xfRkYGwsPDAQArV67E999/j8zMTMyePRsA6v07AAAFBQUQQtRrf6m+vSqVSu/9/fz8sHv3bnh4eOCVV16Bn58f/Pz88NFHH9W7f7r3t7GxwYMPPqi3XKFQQKPRGL0/69jb20v7wpdffonQ0FB89tlnmDdvntSmrt8Xly9fBgA0a9as1vczpub1+d688ztTR6PR1LisvLz8nqeG12X/3rp1K4YMGYKmTZtiw4YNSE9PR2ZmJsaMGVNjf+pCV4Pa6lRVVYWCgoK79rX6vnk3ddkPAGDq1Kn417/+hUGDBuHLL7/EoUOHkJmZiY4dO9bpfXT70vTp0w32pYkTJwLAXS87otvG6vsIAPz5558G+8TdfPPNNxg8eDDCwsKwcePGeocrnuZvBKVSiTlz5mDhwoXIzs42yToLCwuxc+dOzJkzB6+//rq0vKysrH6Tyv7i7u4OAPjiiy/g6+t717a+vr5YtWoVgFv/Qvzvf/+L2NhYlJeXY/ny5fV+b2PU518Lbm5uyM3NNVium0ir2/Z7rbu6sLAwfPzxx9i+fbveZ3Cn7du3w8bGRu9aTkOHDsXUqVOxdu1avPfee1i/fj0GDRqkN0Li7u4Oe3t7rF69usb1Gtvn0NBQ2NjYYMeOHRg/fry03N7eXpqAqTtJ4M73UigU2L9/v/QFe6ealt2LKbYvMTERSqUSO3fu1BsNqOmaMnXVpEkTWFlZ1Wt/qYtHH30Ujz76KCorK3H48GEsXrwYMTEx8PT0xAsvvFCvdbm5uaGiogKXL1/WC0lCCOTl5UmTYXXq+yVvZWUl7QvArf08MDAQc+fOxfDhw+Hj41Pn7wtd/y5cuFBrm4aq+d3k5eXVuMzW1tYkl1LYsGEDWrZsic2bN+vVv6yszOh16oJAbXWysrK6r1Hk6uqyHwC3tnXEiBGIi4vTe/2VK1fwwAMP3PN9dJ/trFmzMHjw4BrbtG7dutbXBwQEAACOHz+ud0mEiooKnDp1qtaTUar75ptvMGjQIISEhGDLli1S6K4PjiDdQ007LwBpqFH3L6L7pVAoIIQw+OP0ySef3HOIuCYRERGwsbHBr7/+WuMozp2/KHd6+OGH8eabbyIgIABHjx6Vllf/F5Ul9enTB3v27DE4s+jTTz+Fg4MDevToYdR6n376abRr1w7z5s3DmTNnDJ7fvHkzkpOT8Y9//EPvX6xNmjTBoEGD8Omnn2Lnzp3Iy8vTO7wG3DqE8Ouvv8LNza3Gz8LYswK9vLwwZswYfPXVV0hMTKzTayIjIyGEwB9//FFjX3RfUPVhiu1TKBSwsbGBtbW1tKy0tBTr1683aFvX/dHR0RFBQUHYunWrXnvdhTWbNWtWr8NV1VlbWyMoKAj/+c9/AEDvd6au+vTpA+DWH6Y7bdmyBdevX5eeNxWVSoX//Oc/uHnzJt59910Adf++ePjhh+Hn54fVq1fXGg4auuY12bp1q95ITnFxMb788ks8+uijevuTsXQXV7wzHOXl5RmcxQbUfd9s3bo1mjZtik2bNumdpXn9+nVs2bJFOrOtodS0HwC3trX636GvvvoKf/zxh8HrAcPRq9atW8Pf3x8//vhjrfuSs7Nzrf0KCgqCl5eXwZmoX3zxBUpKSmoNXXdKTk7GoEGD0Lt3b2zfvt2of/QBHEG6p4iICDRr1gwDBw5EmzZtUFVVhaysLHz44YdwcnLCa6+9ZpL3cXFxwWOPPYb3338f7u7uaNGiBVJTU7Fq1ao6pfbqWrRogbfffhuzZ8/Gb7/9hn79+qFJkya4dOkSMjIy4OjoiLlz5+LYsWN49dVX8dxzz8Hf3x+2trbYs2cPjh07pjeKEhAQgMTERGzevBmtWrWCnZ3dPf+QXrt2DQcPHjRYrlKp0Llz53pvk86cOXOwc+dOPP7443jrrbfg6uqKjRs34quvvkJCQgLUarVR67W2tsaWLVsQFhYmXSk9ODgYZWVl+PLLL/Hxxx8jJCSkxouDjhkzBps3b8arr76KZs2aoW/fvnrPx8TEYMuWLXjssccwZcoUdOjQAVVVVTh37hySk5Mxbdo0BAUFGdXvRYsWIScnB8OHD8eOHTvw1FNPwdvbGzdu3MCpU6eQmJgIOzs7KJVKALcu4Dl+/HiMHj0ahw8fxmOPPQZHR0fk5ubiwIEDCAgIwMsvv1yvPphi+wYMGIAFCxZg2LBhGD9+PK5evYoPPvigxi+3+uyP8fHxCAsLw+OPP47p06fD1tYWS5cuRXZ2Nj777LN6j8gsX74ce/bswYABA9C8eXPcvHlTGjmr/rnXRVhYGCIiIjBz5kwUFRWhV69eOHbsGObMmYPOnTvXeBmJ+xUSEoL+/ftjzZo1eP3119GyZcs6fV8AwH/+8x8MHDgQPXr0wJQpU9C8eXOcO3cO33zzDTZu3AjA9DW/F2tra4SFhWHq1KmoqqrC/PnzUVRUZNQlEGqiu7TCxIkT8eyzz+L8+fN455134OXlhZ9//lmvbUBAAPbt24cvv/wSXl5ecHZ2rnHExMrKCgkJCRg+fDgiIyMxYcIElJWV4f3338e1a9cMDn01hJr2g8jISKxduxZt2rRBhw4dcOTIEbz//vsGh1X9/Pxgb2+PjRs3om3btnBycoK3tze8vb2xYsUKPPnkk4iIiMCoUaPQtGlT/Pnnnzh58iSOHj2Kzz//vNY+WVtbIyEhAdHR0ZgwYQKGDh2Kn3/+GTNmzEBYWBj69esntU1NTUWfPn3w1ltvSReAPHDgAAYNGgSNRoM33njD4Erf7dq1q/vFius9HbyR2bx5sxg2bJjw9/cXTk5OQqlUiubNm4vo6Gjx008/6bWt7eKIAMQrr7yit6ymC5xduHBBPPPMM6JJkybC2dlZ9OvXT2RnZwtfX1+9syLqc6HI7du3i8cff1y4uLgIlUolfH19xbPPPit2794thBDi0qVLYtSoUaJNmzbC0dFRODk5iQ4dOoiFCxfqnQ75+++/i/DwcOHs7Cydln83dzuLrWnTpgb9vvMyBveqpxBCHD9+XAwcOFCo1Wpha2srOnbsaHA2ha5On3/++V37Wt2VK1fE66+/Ltq0aSPs7OyEk5OT6N69u1iyZEmtl3morKwUPj4+AoCYPXt2jW1KSkrEm2++KVq3bi1sbW2FWq0WAQEBYsqUKXqn1te0v9xLZWWl+PTTT0VYWJhwd3cXNjY2Qq1Wi+7du4t//etfemdW6qxevVoEBQUJR0dHYW9vL/z8/MSIESPE4cOHpTYhISHikUceMXjtyJEjDfYBU2zf6tWrRevWrYVKpRKtWrUS8fHxYtWqVQZnH9W2P9Z0FpsQQuzfv1888cQT0rb26NFDfPnll3ptdGc5VT8Tr/rvW3p6unj66aeFr6+vUKlUws3NTYSEhNz1jNQ761bT6dalpaVi5syZwtfXVyiVSuHl5SVefvllg8sG1PcCrLW9nxC3foesrKz0ThO/1/eFTnp6unjyySeFWq0WKpVK+Pn56Z3hJMT91by274Xq26P7vOfPny/mzp0rmjVrJmxtbUXnzp3FN998U+N7VT+Lra7797x580SLFi2ESqUSbdu2FStXrqzxezcrK0v06tVLODg4CADS2ZY1fW8LcavmQUFBws7OTjg6Ooo+ffqI77//vk71qGmbalKf/aCgoECMHTtWeHh4CAcHB9G7d2+xf/9+ERISYnDm6GeffSbatGkjlEqlACDmzJkjPffjjz+KIUOGCA8PD6FUKoVGoxFPPPGEWL58+V37qrNp0ybRoUMHYWtrKzQajZg8ebLBmeO6mt75vrpa1fZTvf53oxDijrE9IiIiIuIcJCIiIqLqGJCIiIiIqmFAIiIiIqqGAYmIiIioGgYkIiIiomoYkIiIiIiq4YUi66iqqgoXL16Es7OzyS9yRkRERA1DCIHi4mJ4e3vr3Rj4XhiQ6ujixYsGd48nIiKi/w3nz5+/642Wq2NAqiPdvWPOnz9f98uU14FWq0VycjLCw8OlW0FQw2CtzYN1Ng/W2TxYZ/NpqFoXFRXBx8fnrveAqwkDUh3pDqu5uLiYPCA5ODjAxcWFv3wNjLU2D9bZPFhn82Cdzaeha13f6TGcpE1ERERUDQMSERERUTUMSERERETVMCARERERVcOARERERFQNAxIRERFRNQxIRERERNUwIBERERFVw4BEREREVI1FA1KLFi2gUCgMfl555RUAt24wFxsbC29vb9jb2yM0NBQnTpzQW0dZWRkmTZoEd3d3ODo6IioqChcuXNBrU1BQgOjoaKjVaqjVakRHR+PatWvm2kwiIiL6H2PRgJSZmYnc3FzpJyUlBQDw3HPPAQASEhKwYMECLFmyBJmZmdBoNAgLC0NxcbG0jpiYGGzbtg2JiYk4cOAASkpKEBkZicrKSqnNsGHDkJWVhaSkJCQlJSErKwvR0dHm3VgiIiL6n2HRe7E9+OCDeo/nzZsHPz8/hISEQAiBRYsWYfbs2Rg8eDAAYN26dfD09MSmTZswYcIEFBYWYtWqVVi/fj369u0LANiwYQN8fHywe/duRERE4OTJk0hKSsLBgwcRFBQEAFi5ciWCg4Nx+vRptG7d2rwbTURERLInmzlI5eXl2LBhA8aMGQOFQoGcnBzk5eUhPDxcaqNSqRASEoK0tDQAwJEjR6DVavXaeHt7o3379lKb9PR0qNVqKRwBQI8ePaBWq6U2lnS1pAxXbwLXyyos3RUiIiL6i0VHkO60fft2XLt2DaNGjQIA5OXlAQA8PT312nl6euLs2bNSG1tbWzRp0sSgje71eXl58PDwMHg/Dw8PqU1NysrKUFZWJj0uKioCcOtuw1qttp5bV7upnx9D2m82cPDNxTOBPiZbLxnSfW6m/PzIEOtsHqyzebDO5tNQtTZ2fbIJSKtWrcKTTz4Jb29vveUKhULvsRDCYFl11dvU1P5e64mPj8fcuXMNlicnJ8PBweGu718ff161AmCF49nZsL903GTrpdrp5rpRw2KdzYN1Ng/W2XxMXesbN24Y9TpZBKSzZ89i9+7d2Lp1q7RMo9EAuDUC5OXlJS3Pz8+XRpU0Gg3Ky8tRUFCgN4qUn5+Pnj17Sm0uXbpk8J6XL182GJ2606xZszB16lTpcVFREXx8fBAeHg4XFxcjt9TQF5cP41Thn2jX7hH079bcZOslQ1qtFikpKQgLC4NSqbR0d/62WGfzYJ3Ng3U2n4aqte4IUH3JIiCtWbMGHh4eGDBggLSsZcuW0Gg0SElJQefOnQHcmqeUmpqK+fPnAwACAwOhVCqRkpKCIUOGAAByc3ORnZ2NhIQEAEBwcDAKCwuRkZGB7t27AwAOHTqEwsJCKUTVRKVSQaVSGSxXKpUm/eCsrG5NA1NYWfOXz0xM/RlSzVhn82CdzYN1Nh9T19rYdVk8IFVVVWHNmjUYOXIkbGxud0ehUCAmJgZxcXHw9/eHv78/4uLi4ODggGHDhgEA1Go1xo4di2nTpsHNzQ2urq6YPn06AgICpLPa2rZti379+mHcuHFYsWIFAGD8+PGIjIyUxRlsVtJRPmHJbhAREdEdLB6Qdu/ejXPnzmHMmDEGz82YMQOlpaWYOHEiCgoKEBQUhOTkZDg7O0ttFi5cCBsbGwwZMgSlpaXo06cP1q5dC2tra6nNxo0bMXnyZOlst6ioKCxZsqThN64OFLiVkKqYj4iIiGTD4gEpPDwcQtScDhQKBWJjYxEbG1vr6+3s7LB48WIsXry41jaurq7YsGHD/Xa1QehGkGopAREREVmAbK6D1FjpzqSrYkIiIiKSDQYkC1NII0gMSERERHLBgGRhVn8lJMYjIiIi+WBAsjDdSWycpE1ERCQfDEgWJo0g8RAbERGRbDAgWZhuDhJHkIiIiOSDAcnCOEmbiIhIfhiQLIyTtImIiOSHAcnCrKRDbIxIREREcsGAZGm6C0VWWbgfREREJGFAsrDbN6slIiIiuWBAsrDbN6vlITYiIiK5YECyMN6sloiISH4YkCyMN6slIiKSHwYkC1NwBImIiEh2GJAsTDrExishERERyQYDkoXdnqRt4Y4QERGRhAHJwjhJm4iISH4YkCxMN0mb92IjIiKSDwYkC1NItxqxbD+IiIjoNgYkC7t9s1omJCIiIrlgQLIwK44gERERyQ4DkkxwDhIREZF8MCBZmHSIjfmIiIhINhiQLOz2JG0mJCIiIrlgQLKw25O0iYiISC4YkCyMp/kTERHJDwOSheluNcJJ2kRERPLBgGRhvNUIERGR/DAgWRgnaRMREckPA5KFKThJm4iISHYYkCzMijerJSIikh0GJAv76wgbz2IjIiKSEQYkC+MkbSIiIvlhQLIw3RwkTtImIiKSDwYkC1NII0gMSERERHLBgGRhvFktERGR/DAgWRhvNUJERCQ/Fg9If/zxB1588UW4ubnBwcEBnTp1wpEjR6TnhRCIjY2Ft7c37O3tERoaihMnTuito6ysDJMmTYK7uzscHR0RFRWFCxcu6LUpKChAdHQ01Go11Go1oqOjce3aNXNs4l3dvlktExIREZFcWDQgFRQUoFevXlAqlfj666/x008/4cMPP8QDDzwgtUlISMCCBQuwZMkSZGZmQqPRICwsDMXFxVKbmJgYbNu2DYmJiThw4ABKSkoQGRmJyspKqc2wYcOQlZWFpKQkJCUlISsrC9HR0ebc3BpxBImIiEh+bCz55vPnz4ePjw/WrFkjLWvRooX030IILFq0CLNnz8bgwYMBAOvWrYOnpyc2bdqECRMmoLCwEKtWrcL69evRt29fAMCGDRvg4+OD3bt3IyIiAidPnkRSUhIOHjyIoKAgAMDKlSsRHByM06dPo3Xr1ubb6Gp010HiJG0iIiL5sGhA2rFjByIiIvDcc88hNTUVTZs2xcSJEzFu3DgAQE5ODvLy8hAeHi69RqVSISQkBGlpaZgwYQKOHDkCrVar18bb2xvt27dHWloaIiIikJ6eDrVaLYUjAOjRowfUajXS0tJqDEhlZWUoKyuTHhcVFQEAtFottFqtyWogqqoAAJVVVSZdLxnS1Zd1bliss3mwzubBOptPQ9Xa2PVZNCD99ttvWLZsGaZOnYo33ngDGRkZmDx5MlQqFUaMGIG8vDwAgKenp97rPD09cfbsWQBAXl4ebG1t0aRJE4M2utfn5eXBw8PD4P09PDykNtXFx8dj7ty5BsuTk5Ph4OBQ/42txek8BQBr5OVdwq5du0y2XqpdSkqKpbvQKLDO5sE6mwfrbD6mrvWNGzeMep1FA1JVVRW6du2KuLg4AEDnzp1x4sQJLFu2DCNGjJDa6S6mqCOEMFhWXfU2NbW/23pmzZqFqVOnSo+Liorg4+OD8PBwuLi43Hvj6uhq+u9Azhl4eHiif//OJlsvGdJqtUhJSUFYWBiUSqWlu/O3xTqbB+tsHqyz+TRUrXVHgOrLogHJy8sL7dq101vWtm1bbNmyBQCg0WgA3BoB8vLyktrk5+dLo0oajQbl5eUoKCjQG0XKz89Hz549pTaXLl0yeP/Lly8bjE7pqFQqqFQqg+VKpdKkH5yNjfWt/1Ao+MtnJqb+DKlmrLN5sM7mwTqbj6lrbey6LHoWW69evXD69Gm9ZWfOnIGvry8AoGXLltBoNHrDbeXl5UhNTZXCT2BgIJRKpV6b3NxcZGdnS22Cg4NRWFiIjIwMqc2hQ4dQWFgotbEUBXirESIiIrmx6AjSlClT0LNnT8TFxWHIkCHIyMjAxx9/jI8//hjArcNiMTExiIuLg7+/P/z9/REXFwcHBwcMGzYMAKBWqzF27FhMmzYNbm5ucHV1xfTp0xEQECCd1da2bVv069cP48aNw4oVKwAA48ePR2RkpEXPYAN4s1oiIiI5smhA6tatG7Zt24ZZs2bh7bffRsuWLbFo0SIMHz5cajNjxgyUlpZi4sSJKCgoQFBQEJKTk+Hs7Cy1WbhwIWxsbDBkyBCUlpaiT58+WLt2LaytraU2GzduxOTJk6Wz3aKiorBkyRLzbWwteLNaIiIi+bFoQAKAyMhIREZG1vq8QqFAbGwsYmNja21jZ2eHxYsXY/HixbW2cXV1xYYNG+6nqw1CwREkIiIi2bH4rUYaO+kQG281QkREJBsMSBZ2e5K2hTtCREREEgYkC+MkbSIiIvlhQLIw3SRt3ouNiIhIPhiQLEw3SZtnsREREckHA5KFWelGkCzcDyIiIrqNAcnCdHeC4yRtIiIi+WBAsrDb10FiQiIiIpILBiQLkw6xMR8RERHJBgOShXGSNhERkfwwIFkYJ2kTERHJDwOShXEEiYiISH4YkCxMwTlIREREssOAZGG81QgREZH8MCBZ2O3rIDEhERERyQUDkoXxNH8iIiL5YUCyMN6sloiISH4YkCzs9llslu0HERER3caAZGHSJG1eCYmIiEg2GJAsTPHXNG2OIBEREckHA5KFKXiaPxERkewwIFmYFSdpExERyQ4DkoVxkjYREZH8MCBZ2O2b1TIhERERyQUDkoVxBImIiEh+GJAsTHerEc5BIiIikg8GJAvjrUaIiIjkhwHJwm4fYmNCIiIikgsGJAu7PUmbiIiI5IIBycJ4oUgiIiL5YUCysNu3GmFCIiIikgsGJAuz4ggSERGR7DAgWRgnaRMREckPA5KFKXQJiYiIiGSDAcnCdGexcQSJiIhIPhiQLEw3fsRbjRAREckHA5KFWf31CXAAiYiISD4sGpBiY2OhUCj0fjQajfS8EAKxsbHw9vaGvb09QkNDceLECb11lJWVYdKkSXB3d4ejoyOioqJw4cIFvTYFBQWIjo6GWq2GWq1GdHQ0rl27Zo5NvCeFdKsRJiQiIiK5sPgI0iOPPILc3Fzp5/jx49JzCQkJWLBgAZYsWYLMzExoNBqEhYWhuLhYahMTE4Nt27YhMTERBw4cQElJCSIjI1FZWSm1GTZsGLKyspCUlISkpCRkZWUhOjrarNtZm9uH2BiQiIiI5MLG4h2wsdEbNdIRQmDRokWYPXs2Bg8eDABYt24dPD09sWnTJkyYMAGFhYVYtWoV1q9fj759+wIANmzYAB8fH+zevRsRERE4efIkkpKScPDgQQQFBQEAVq5cieDgYJw+fRqtW7c238bWgLcaISIikh+LB6Sff/4Z3t7eUKlUCAoKQlxcHFq1aoWcnBzk5eUhPDxcaqtSqRASEoK0tDRMmDABR44cgVar1Wvj7e2N9u3bIy0tDREREUhPT4darZbCEQD06NEDarUaaWlptQaksrIylJWVSY+LiooAAFqtFlqt1mTbX1FRAQCoqoJJ10uGdPVlnRsW62werLN5sM7m01C1NnZ9Fg1IQUFB+PTTT/Hwww/j0qVLePfdd9GzZ0+cOHECeXl5AABPT0+913h6euLs2bMAgLy8PNja2qJJkyYGbXSvz8vLg4eHh8F7e3h4SG1qEh8fj7lz5xosT05OhoODQ/029C4KygDABpVVldi1a5fJ1ku1S0lJsXQXGgXW2TxYZ/Ngnc3H1LW+ceOGUa+zaEB68sknpf8OCAhAcHAw/Pz8sG7dOvTo0QOA4YUUhRD3vLhi9TY1tb/XembNmoWpU6dKj4uKiuDj44Pw8HC4uLjcfcPq4cLVEuBoGhQKK/TvH2Gy9ZIhrVaLlJQUhIWFQalUWro7f1uss3mwzubBOptPQ9VadwSovix+iO1Ojo6OCAgIwM8//4xBgwYBuDUC5OXlJbXJz8+XRpU0Gg3Ky8tRUFCgN4qUn5+Pnj17Sm0uXbpk8F6XL182GJ26k0qlgkqlMliuVCpN+sEplbc+gioh+MtnJqb+DKlmrLN5sM7mwTqbj+n/zhq3LoufxXansrIynDx5El5eXmjZsiU0Go3eUFt5eTlSU1Ol8BMYGAilUqnXJjc3F9nZ2VKb4OBgFBYWIiMjQ2pz6NAhFBYWSm0siZO0iYiI5MeiI0jTp0/HwIED0bx5c+Tn5+Pdd99FUVERRo4cCYVCgZiYGMTFxcHf3x/+/v6Ii4uDg4MDhg0bBgBQq9UYO3Yspk2bBjc3N7i6umL69OkICAiQzmpr27Yt+vXrh3HjxmHFihUAgPHjxyMyMtLiZ7ABt29Wy7P8iYiI5MOiAenChQsYOnQorly5ggcffBA9evTAwYMH4evrCwCYMWMGSktLMXHiRBQUFCAoKAjJyclwdnaW1rFw4ULY2NhgyJAhKC0tRZ8+fbB27VpYW1tLbTZu3IjJkydLZ7tFRUVhyZIl5t3YWtw5D6ou86uIiIio4Vk0ICUmJt71eYVCgdjYWMTGxtbaxs7ODosXL8bixYtrbePq6ooNGzYY280GZXVHHqoSgDXzERERkcXJag5SY6TA7UTEq2kTERHJAwOShd05gsR8REREJA8MSBZ255wjjiARERHJAwOShSk4gkRERCQ7DEgWpneIjVdDIiIikgUGJAvTn6RtwY4QERGRhAHJwvQnaTMhERERyQEDkoXpT9K2YEeIiIhIwoBkYQqOIBEREckOA5KFWendasSCHSEiIiIJA5KF3XlnEV4HiYiISB4YkCxM7xCb5bpBREREd2BAsjCFQgHFX9GII0hERETywIAkI8xHRERE8sCAJAO6w2wMSERERPLAgCQDumlIPMRGREQkDwxIMsCAREREJC8MSDLAQ2xERETywoAkA7oRJAYkIiIieWBAkgEpIPFKSERERLJQ74Ck1Wrx+OOP48yZMw3Rn0ZJd4iNN6slIiKSh3oHJKVSiezsbL270NP94SRtIiIieTHqENuIESOwatUqU/el0eIcJCIiInmxMeZF5eXl+OSTT5CSkoKuXbvC0dFR7/kFCxaYpHONhnQWGxMSERGRHBgVkLKzs9GlSxcAMJiLxENv9Xd7kjYRERHJgVEBae/evabuR6N2e5I2IxIREZEc3Pdp/hcuXMAff/xhir40WtIk7SqLdoOIiIj+YlRAqqqqwttvvw21Wg1fX180b94cDzzwAN555x1U8a98vfE6SERERPJi1CG22bNnY9WqVZg3bx569eoFIQS+//57xMbG4ubNm3jvvfdM3c+/Nd5qhIiISF6MCkjr1q3DJ598gqioKGlZx44d0bRpU0ycOJEBqZ54HSQiIiJ5MeoQ259//ok2bdoYLG/Tpg3+/PPP++5UY8PrIBEREcmLUQGpY8eOWLJkicHyJUuWoGPHjvfdqcaGZ7ERERHJi1GH2BISEjBgwADs3r0bwcHBUCgUSEtLw/nz57Fr1y5T9/Fvj9dBIiIikhejRpBCQkJw5swZPP3007h27Rr+/PNPDB48GKdPn8ajjz5q6j7+7d0+xMaIREREJAf1HkHSarUIDw/HihUrOBnbVKRDbJbtBhEREd1S7xEkpVKJ7Oxs3lLEhHQfAgeQiIiI5MGoQ2wjRozAqlWrTN2XRo+TtImIiOTBqIBUXl6OZcuWITAwEBMmTMDUqVP1fowRHx8PhUKBmJgYaZkQArGxsfD29oa9vT1CQ0Nx4sQJvdeVlZVh0qRJcHd3h6OjI6KionDhwgW9NgUFBYiOjoZarYZarUZ0dDSuXbtmVD8bAi8USUREJC9GBaTs7Gx06dIFLi4uOHPmDH744QfpJysrq97ry8zMxMcff4wOHTroLU9ISMCCBQuwZMkSZGZmQqPRICwsDMXFxVKbmJgYbNu2DYmJiThw4ABKSkoQGRmJyspKqc2wYcOQlZWFpKQkJCUlISsrC9HR0cZseoPgJG0iIiJ5qfck7crKSsTGxiIgIACurq733YGSkhIMHz4cK1euxLvvvistF0Jg0aJFmD17NgYPHgzg1hW8PT09sWnTJkyYMAGFhYVYtWoV1q9fj759+wIANmzYAB8fH+zevRsRERE4efIkkpKScPDgQQQFBQEAVq5cieDgYJw+fRqtW7e+7224X7evpG3RbhAREdFf6h2QrK2tpeBhioD0yiuvYMCAAejbt69eQMrJyUFeXh7Cw8OlZSqVCiEhIUhLS8OECRNw5MgR6aw6HW9vb7Rv3x5paWmIiIhAeno61Gq1FI4AoEePHlCr1UhLS6s1IJWVlaGsrEx6XFRUBODWWXxarfa+t1tHq9VKCUlbUWHSdZM+XW1Z44bFOpsH62werLP5NFStjV2fUReKDAgIwG+//YaWLVsa9aY6iYmJOHr0KDIzMw2ey8vLAwB4enrqLff09MTZs2elNra2tmjSpIlBG93r8/Ly4OHhYbB+Dw8PqU1N4uPjMXfuXIPlycnJcHBwuMeW1Y8C1gCAjIwMFJ3hMFJDS0lJsXQXGgXW2TxYZ/Ngnc3H1LW+ceOGUa8zKiC99957mD59Ot555x0EBgbC0dFR73kXF5d7ruP8+fN47bXXkJycDDs7u1rbVb+cgBDinpcYqN6mpvb3Ws+sWbP0JpwXFRXBx8cH4eHhddq+utJqtUj4cQ8AoFu3bnjU391k6yZ9Wq0WKSkpCAsLg1KptHR3/rZYZ/Ngnc2DdTafhqq17ghQfRkVkPr16wcAiIqK0gsZutBx5wTp2hw5cgT5+fkIDAyUllVWVuK7777DkiVLcPr0aQC3RoC8vLykNvn5+dKokkajQXl5OQoKCvRGkfLz89GzZ0+pzaVLlwze//LlywajU3dSqVRQqVQGy5VKZYP9klhZW/MX0Awa8jOk21hn82CdzYN1Nh9T19rYdRkVkPbu3WvUm92pT58+OH78uN6y0aNHo02bNpg5cyZatWoFjUaDlJQUdO7cGcCtywukpqZi/vz5AIDAwEAolUqkpKRgyJAhAIDc3FxkZ2cjISEBABAcHIzCwkJkZGSge/fuAIBDhw6hsLBQClGWxmtuEhERyYtRASkkJOS+39jZ2Rnt27fXW+bo6Ag3NzdpeUxMDOLi4uDv7w9/f3/ExcXBwcEBw4YNAwCo1WqMHTsW06ZNg5ubG1xdXTF9+nQEBARIZ7W1bdsW/fr1w7hx47BixQoAwPjx4xEZGSmLM9juxNlHRERE8lCv6yAlJCSgtLRUevzdd9/pnelVXFyMiRMnmqxzM2bMQExMDCZOnIiuXbvijz/+QHJyMpydnaU2CxcuxKBBgzBkyBD06tULDg4O+PLLL2FtbS212bhxIwICAhAeHo7w8HB06NAB69evN1k/TYYJiYiISBbqNYI0a9YsjBo1Cvb29gCAyMhIZGVloVWrVgBuzRRfsWIFli5dalRn9u3bp/dYoVAgNjYWsbGxtb7Gzs4OixcvxuLFi2tt4+rqig0bNhjVJ3OQLhTJhERERCQL9RpBqn6lZ1752bRYTiIiInkw6lYjZFqco01ERCQvDEgywJvVEhERyUu9z2L75JNP4OTkBACoqKjA2rVr4e5+6+KGd95EluqP+YiIiEge6hWQmjdvjpUrV0qPNRqNwdlgzZs3N03PGiHO6SIiIpKHegWk33//vYG60bjdPouNiIiI5MCoOUiffvqp3vWPdMrLy/Hpp5/ed6eIiIiILMmogDR69GgUFhYaLC8uLsbo0aPvu1ONDSdpExERyYtRAUl3U9rqLly4ALVafd+daryYkIiIiOSgXnOQOnfuDIVCAYVCgT59+sDG5vbLKysrkZOTg379+pm8k40FR5CIiIjkoV4BadCgQQCArKwsRERESKf7A4CtrS1atGiBZ555xqQdbAw4SZuIiEhe6hWQ5syZAwBo0aIFXnjhBahUqgbpVGMjBSQmJCIiIlkwag7SE088gcuXL0uPMzIyEBMTg48//thkHSMiIiKyFKMC0rBhw7B3714AQF5eHvr27YuMjAy88cYbePvtt03awcZE8CAbERGRLBgVkLKzs9G9e3cAwH//+18EBAQgLS0NmzZtwtq1a03Zv0aBp/kTERHJi1EBSavVSvOPdu/ejaioKABAmzZtkJuba7reNRrijv8lIiIiSzMqID3yyCNYvnw59u/fj5SUFOnU/osXL8LNzc2kHWwMbk/SZkQiIiKSA6MC0vz587FixQqEhoZi6NCh6NixIwBgx44d0qE3IiIiov9V9TrNXyc0NBRXrlxBUVERmjRpIi0fP348HBwcTNa5xqKGi5ITERGRBRk1ggTcOhx05MgRrFixAsXFxQBuXSySAcl4PMJGREQkD0aNIJ09exb9+vXDuXPnUFZWhrCwMDg7OyMhIQE3b97E8uXLTd3PRoGn+RMREcmDUSNIr732Grp27YqCggLY29tLy59++ml8++23JutcY8EraRMREcmLUSNIBw4cwPfffw9bW1u95b6+vvjjjz9M0rHGhFOQiIiI5MWoEaSqqipUVlYaLL9w4QKcnZ3vu1ONFUeQiIiI5MGogBQWFoZFixZJjxUKBUpKSjBnzhz079/fVH1rdJiPiIiI5MGoQ2wLFy7E448/jnbt2uHmzZsYNmwYfv75Z7i7u+Ozzz4zdR//9m7faoQRiYiISA6MCkje3t7IysrCZ599hqNHj6Kqqgpjx47F8OHD9SZtU/0wHhEREcmDUQEJAOzt7TFmzBiMGTPGlP1plDhJm4iISF7qHJB27NhR55Xqbl5L9cQhJCIiIlmoc0AaNGhQndopFIoaz3Cje+OFIomIiOShzgGpqqqqIfvRqN2epG3ZfhAREdEtRt+LjUxHupK2RXtBREREOnUeQfr3v/9d55VOnjzZqM4QERERyUGdA9LChQvr1E6hUDAg1RPvxUZERCQvdQ5IOTk5DdkPAidpExERyQXnIMkIR5CIiIjkwegLRV64cAE7duzAuXPnUF5ervfcggUL7rtjjYl0Fptlu0FERER/MWoE6dtvv0Xr1q2xdOlSfPjhh9i7dy/WrFmD1atXIysrq87rWbZsGTp06AAXFxe4uLggODgYX3/9tfS8EAKxsbHw9vaGvb09QkNDceLECb11lJWVYdKkSXB3d4ejoyOioqJw4cIFvTYFBQWIjo6GWq2GWq1GdHQ0rl27ZsymExERUSNgVECaNWsWpk2bhuzsbNjZ2WHLli04f/48QkJC8Nxzz9V5Pc2aNcO8efNw+PBhHD58GE888QSeeuopKQQlJCRgwYIFWLJkCTIzM6HRaBAWFobi4mJpHTExMdi2bRsSExNx4MABlJSUIDIyUu9ilcOGDUNWVhaSkpKQlJSErKwsREdHG7PpDUK61QiPsREREcmDMIKTk5P45ZdfhBBCPPDAAyI7O1sIIURWVpbw9fU1ZpWSJk2aiE8++URUVVUJjUYj5s2bJz138+ZNoVarxfLly4UQQly7dk0olUqRmJgotfnjjz+ElZWVSEpKEkII8dNPPwkA4uDBg1Kb9PR0AUCcOnWqzv0qLCwUAERhYeF9bV915eXl4qn5O4TvzJ1iXVqOSddN+srLy8X27dtFeXm5pbvyt8Y6mwfrbB6ss/k0VK2N/ftt1AiSo6MjysrKAADe3t749ddfpeeuXLliVFCrrKxEYmIirl+/juDgYOTk5CAvLw/h4eFSG5VKhZCQEKSlpQEAjhw5Aq1Wq9fG29sb7du3l9qkp6dDrVYjKChIatOjRw+o1WqpjVxwAImIiEgejJqk3aNHD3z//fdo164dBgwYgGnTpuH48ePYunUrevToUa91HT9+HMHBwbh58yacnJywbds2tGvXTgovnp6eeu09PT1x9uxZAEBeXh5sbW3RpEkTgzZ5eXlSGw8PD4P39fDwkNrUpKysTAqBAFBUVAQA0Gq10Gq19drGu9FqtdIxtorKSpOum/TpassaNyzW2TxYZ/Ngnc2noWpt7PqMCkgLFixASUkJACA2NhYlJSXYvHkzHnrooTpfUFKndevWyMrKwrVr17BlyxaMHDkSqamp0vMKhUKvvRDCYFl11dvU1P5e64mPj8fcuXMNlicnJ8PBweGu719fir+mgv104gR2/Zlt0nWToZSUFEt3oVFgnc2DdTYP1tl8TF3rGzduGPU6owJSq1atpP92cHDA0qVLjXpzALC1tcVDDz0EAOjatSsyMzPx0UcfYebMmQBujQB5eXlJ7fPz86VRJY1Gg/LychQUFOiNIuXn56Nnz55Sm0uXLhm87+XLlw1Gp+40a9YsTJ06VXpcVFQEHx8fhIeHw8XFxejtrU6r1WLtmW8BAG3btUP/YF+TrZv0abVapKSkICwsDEql0tLd+dtinc2DdTYP1tl8GqrWuiNA9WX0dZB0SkpKUFVVpbfsfgKEEAJlZWVo2bIlNBoNUlJS0LlzZwBAeXk5UlNTMX/+fABAYGAglEolUlJSMGTIEABAbm4usrOzkZCQAAAIDg5GYWEhMjIy0L17dwDAoUOHUFhYKIWomqhUKqhUKoPlSqXS5L8kunEsKytr/gKaQUN8hmSIdTYP1tk8WGfzMXWtjV2XUQEpJycHr776Kvbt24ebN29Ky3WHre48xf5u3njjDTz55JPw8fFBcXExEhMTsW/fPiQlJUGhUCAmJgZxcXHw9/eHv78/4uLi4ODggGHDhgEA1Go1xo4di2nTpsHNzQ2urq6YPn06AgIC0LdvXwBA27Zt0a9fP4wbNw4rVqwAAIwfPx6RkZFo3bq1MZvfYDhHm4iISB6MCkjDhw8HAKxevRqenp73nBNUm0uXLiE6Ohq5ublQq9Xo0KEDkpKSEBYWBgCYMWMGSktLMXHiRBQUFCAoKAjJyclwdnaW1rFw4ULY2NhgyJAhKC0tRZ8+fbB27VpYW1tLbTZu3IjJkydLZ7tFRUVhyZIlRvW5IQmexkZERCQLRgWkY8eO4ciRI/c9ArNq1aq7Pq9QKBAbG4vY2Nha29jZ2WHx4sVYvHhxrW1cXV2xYcMGY7vZ4IzMl0RERNRAjLoOUrdu3XD+/HlT94WIiIhIFowaQfrkk0/w0ksv4Y8//kD79u0NJkB16NDBJJ1rLHQDSDzCRkREJA9GBaTLly/j119/xejRo6VlCoWi3pO06RYpIHGaNhERkSwYFZDGjBmDzp0747PPPruvSdqkjyNIRERE8mBUQDp79ix27NghXeCR7tNf+ZL5iIiISB6MmqT9xBNP4McffzR1Xxotjr8RERHJi1EjSAMHDsSUKVNw/PhxBAQEGEzSjoqKMknnGhseYiMiIpIHowLSSy+9BAB4++23DZ7jJO364yRtIiIieTEqIFW/9xqZBkeQiIiI5KFec5AOHTqEr7/+Wm/Zp59+ipYtW8LDwwPjx49HWVmZSTtIREREZG71CkixsbE4duyY9Pj48eMYO3Ys+vbti9dffx1ffvkl4uPjTd7JvzteJYGIiEhe6hWQsrKy0KdPH+lxYmIigoKCsHLlSkydOhX//ve/8d///tfknfy7u30lbR5jIyIikoN6BaSCggJ4enpKj1NTU9GvXz/pMe/Rdn+Yj4iIiOShXgHJ09MTOTk5AIDy8nIcPXoUwcHB0vPFxcUGp/xT3TEfERERyUO9AlK/fv3w+uuvY//+/Zg1axYcHBzw6KOPSs8fO3YMfn5+Ju/k3x1vVktERCQv9TrN/91338XgwYMREhICJycnrFu3Dra2ttLzq1evRnh4uMk7+bfHSdpERESyUq+A9OCDD2L//v0oLCyEk5MTrK2t9Z7//PPP4eTkZNIONga8UCQREZG8GHWhSLVaXeNyV1fX++pMY8dDbERERPJg1M1qybRujyARERGRHDAgyQmHkIiIiGSBAUkGOEebiIhIXhiQ5OCvhMTxIyIiInlgQJIBXgeJiIhIXhiQZISn+RMREckDA5KMcASJiIhIHhiQZICTtImIiOSFAUkOOEmbiIhIVhiQZICTtImIiOSFAUlGOEmbiIhIHhiQ5IT5iIiISBYYkGSAk7SJiIjkhQFJBnizWiIiInlhQJID3VlsnKVNREQkCwxIMsCz2IiIiOSFAUlGmI+IiIjkgQFJRjiCREREJA8MSDLAs9iIiIjkxaIBKT4+Ht26dYOzszM8PDwwaNAgnD59Wq+NEAKxsbHw9vaGvb09QkNDceLECb02ZWVlmDRpEtzd3eHo6IioqChcuHBBr01BQQGio6OhVquhVqsRHR2Na9euNfQm1o10qxEOIREREcmBRQNSamoqXnnlFRw8eBApKSmoqKhAeHg4rl+/LrVJSEjAggULsGTJEmRmZkKj0SAsLAzFxcVSm5iYGGzbtg2JiYk4cOAASkpKEBkZicrKSqnNsGHDkJWVhaSkJCQlJSErKwvR0dFm3d7acJI2ERGRvNhY8s2TkpL0Hq9ZswYeHh44cuQIHnvsMQghsGjRIsyePRuDBw8GAKxbtw6enp7YtGkTJkyYgMLCQqxatQrr169H3759AQAbNmyAj48Pdu/ejYiICJw8eRJJSUk4ePAggoKCAAArV65EcHAwTp8+jdatW5t3w6vhITYiIiJ5kdUcpMLCQgCAq6srACAnJwd5eXkIDw+X2qhUKoSEhCAtLQ0AcOTIEWi1Wr023t7eaN++vdQmPT0darVaCkcA0KNHD6jVaqmNHPA6SERERPJg0RGkOwkhMHXqVPTu3Rvt27cHAOTl5QEAPD099dp6enri7NmzUhtbW1s0adLEoI3u9Xl5efDw8DB4Tw8PD6lNdWVlZSgrK5MeFxUVAQC0Wi20Wq0xm1ijO9dVVVVl0nWTPl1tWeOGxTqbB+tsHqyz+TRUrY1dn2wC0quvvopjx47hwIEDBs8pFPoHoYQQBsuqq96mpvZ3W098fDzmzp1rsDw5ORkODg53fe/6Uvw1kPf772exa1eOSddNhlJSUizdhUaBdTYP1tk8WGfzMXWtb9y4YdTrZBGQJk2ahB07duC7775Ds2bNpOUajQbArREgLy8vaXl+fr40qqTRaFBeXo6CggK9UaT8/Hz07NlTanPp0iWD9718+bLB6JTOrFmzMHXqVOlxUVERfHx8EB4eDhcXl/vYWn1arRa7Vn8LAGju64v+/duabN2kT6vVIiUlBWFhYVAqlZbuzt8W62werLN5sM7m01C11h0Bqi+LBiQhBCZNmoRt27Zh3759aNmypd7zLVu2hEajQUpKCjp37gwAKC8vR2pqKubPnw8ACAwMhFKpREpKCoYMGQIAyM3NRXZ2NhISEgAAwcHBKCwsREZGBrp37w4AOHToEAoLC6UQVZ1KpYJKpTJYrlQqTf5LohvDUlgp+AtoBg3xGZIh1tk8WGfzYJ3Nx9S1NnZdFg1Ir7zyCjZt2oT/+7//g7OzszQfSK1Ww97eHgqFAjExMYiLi4O/vz/8/f0RFxcHBwcHDBs2TGo7duxYTJs2DW5ubnB1dcX06dMREBAgndXWtm1b9OvXD+PGjcOKFSsAAOPHj0dkZKTFz2C7E+doExERyYNFA9KyZcsAAKGhoXrL16xZg1GjRgEAZsyYgdLSUkycOBEFBQUICgpCcnIynJ2dpfYLFy6EjY0NhgwZgtLSUvTp0wdr166FtbW11Gbjxo2YPHmydLZbVFQUlixZ0rAbWGdMRkRERHJi8UNs96JQKBAbG4vY2Nha29jZ2WHx4sVYvHhxrW1cXV2xYcMGY7rZ4KQLRVq0F0RERKQjq+sgNVa6E+l4iI2IiEgeGJBkhQmJiIhIDhiQZID3YiMiIpIXBiQiIiKiahiQZIQjSERERPLAgCQD0iRtzkEiIiKSBQYkGeEIEhERkTwwIMkAr4NEREQkLwxIRERERNUwIMkAT/MnIiKSFwYkGeEkbSIiInlgQJIBBSchERERyQoDkowwHxEREckDAxIRERFRNQxIMnB7kjbHkIiIiOSAAUlGGI+IiIjkgQFJBqRbjTAhERERyQIDkowwHxEREckDA5IMKO7dhIiIiMyIAUlGOEmbiIhIHhiQZIDXiSQiIpIXBiQ5YUIiIiKSBQYkGZDOYmNCIiIikgUGJBnhFCQiIiJ5YEAiIiIiqoYBSQZu32rEot0gIiKivzAgyQjnIBEREckDA5IM8FYjRERE8sKAJAO8DhIREZG8MCARERERVcOAJCM8xEZERCQPDEgycPtmtUxIREREcsCAJCMcQSIiIpIHBiQZuH2rESIiIpIDBiQiIiKiahiQZETwGBsREZEsMCDJAK+DREREJC8MSDLAe7ERERHJi0UD0nfffYeBAwfC29sbCoUC27dv13teCIHY2Fh4e3vD3t4eoaGhOHHihF6bsrIyTJo0Ce7u7nB0dERUVBQuXLig16agoADR0dFQq9VQq9WIjo7GtWvXGnjr6oGTtImIiGTFogHp+vXr6NixI5YsWVLj8wkJCViwYAGWLFmCzMxMaDQahIWFobi4WGoTExODbdu2ITExEQcOHEBJSQkiIyNRWVkptRk2bBiysrKQlJSEpKQkZGVlITo6usG3r65ujyAxIhEREcmBjSXf/Mknn8STTz5Z43NCCCxatAizZ8/G4MGDAQDr1q2Dp6cnNm3ahAkTJqCwsBCrVq3C+vXr0bdvXwDAhg0b4OPjg927dyMiIgInT55EUlISDh48iKCgIADAypUrERwcjNOnT6N169bm2di70AWkKgYkIiIiWbBoQLqbnJwc5OXlITw8XFqmUqkQEhKCtLQ0TJgwAUeOHIFWq9Vr4+3tjfbt2yMtLQ0RERFIT0+HWq2WwhEA9OjRA2q1GmlpabUGpLKyMpSVlUmPi4qKAABarRZardZk26nVamH1V0KqrKwy6bpJn662rHHDYp3Ng3U2D9bZfBqq1sauT7YBKS8vDwDg6empt9zT0xNnz56V2tja2qJJkyYGbXSvz8vLg4eHh8H6PTw8pDY1iY+Px9y5cw2WJycnw8HBoX4bcw+Kv64UefnKn9i1a5dJ102GUlJSLN2FRoF1Ng/W2TxYZ/Mxda1v3Lhh1OtkG5B0dOFBRwhhsKy66m1qan+v9cyaNQtTp06VHhcVFcHHxwfh4eFwcXGpa/fvSavVIitxNwCgiWsT9O/f3WTrJn1arRYpKSkICwuDUqm0dHf+tlhn82CdzYN1Np+GqrXuCFB9yTYgaTQaALdGgLy8vKTl+fn50qiSRqNBeXk5CgoK9EaR8vPz0bNnT6nNpUuXDNZ/+fJlg9GpO6lUKqhUKoPlSqXS5L8kukNsVQL8BTSDhvgMyRDrbB6ss3mwzuZj6lobuy7ZXgepZcuW0Gg0ekNt5eXlSE1NlcJPYGAglEqlXpvc3FxkZ2dLbYKDg1FYWIiMjAypzaFDh1BYWCi1sbTbk7Qt2g0iIiL6i0VHkEpKSvDLL79Ij3NycpCVlQVXV1c0b94cMTExiIuLg7+/P/z9/REXFwcHBwcMGzYMAKBWqzF27FhMmzYNbm5ucHV1xfTp0xEQECCd1da2bVv069cP48aNw4oVKwAA48ePR2RkpCzOYANujyDxNH8iIiJ5sGhAOnz4MB5//HHpsW7Oz8iRI7F27VrMmDEDpaWlmDhxIgoKChAUFITk5GQ4OztLr1m4cCFsbGwwZMgQlJaWok+fPli7di2sra2lNhs3bsTkyZOls92ioqJqvfaSJehGkCoZkIiIiGTBogEpNDT0rqMmCoUCsbGxiI2NrbWNnZ0dFi9ejMWLF9faxtXVFRs2bLifrjYoaQ5SlWX7QURERLfIdg5SY8ILRRIREckLA5IM3D6LjQGJiIhIDhiQZEDx121qK3kaGxERkSwwIMmAQjqLzbL9ICIiolsYkGRAuhcbExIREZEsMCDJACdpExERyQsDkgwoeJo/ERGRrDAgyYDuQ+AIEhERkTwwIMmAbgSJZ7ERERHJAwOSDPBmtURERPLCgCQDvFktERGRvDAgyQBvVktERCQvDEgycPssNgYkIiIiOWBAkoHbZ7FZtBtERET0FwYkGVDwZrVERESywoAkA1Y8zZ+IiEhWGJBkQDdJmwNIRERE8sCAJAO8WS0REZG8MCDJAG9WS0REJC8MSDJw+0KRvFgkERGRHDAgyYDijv/mPG0iIiLLY0CSAcUdCYlnshEREVkeA5IM3PkhcB4SERGR5TEgycCdI0jMR0RERJbHgCQDd85B4qn+RERElseAJANWdyQkHmIjIiKyPAYkGbjzEFsVJ2kTERFZHAOSDPA0fyIiInlhQJIBvTlITEhEREQWx4AkAwrFnVfTZkAiIiKyNAYkmbD6ayISz2IjIiKyPAYkmbD6awiJR9iIiIgsjwFJJnSH2HgWGxERkeUxIMmEtUI3gsSAREREZGkMSDKh0M1B4ggSERGRxTEgyYT1X58E8xEREZHl2Vi6A3SL7iy2lzccQa+H3NHO2wVRHb1hp7S2cM+IiIgan0YVkJYuXYr3338fubm5eOSRR7Bo0SI8+uijlu4WAKBjMzX2nbmCn/NL8HN+CQBg/tenMLpXC9jaWEFpbQVbGyt4OtvhIQ8nWFspYGWlgI2VAmp7JWytORh4L1VVAlXir///mw3VKRS3D9MSEdH9azQBafPmzYiJicHSpUvRq1cvrFixAk8++SR++uknNG/e3NLdw7JhnXD4fBFyrlzH2as3sDbtd1y9Xo4Pks9Yumt/MzaYcjDF0p0wOSeVDSY+7ofwdhrYWClgpVDAUnlJW6HF1ZvA+YIbUNooLdOJRoB1No+KigpcvQlcKCiFjY3W0t35W6uoqEB5paV7cZtCNJJLNwcFBaFLly5YtmyZtKxt27YYNGgQ4uPj7/n6oqIiqNVqFBYWwsXFxWT90mq12LVrF/r37w+l8vaXXNovV/B1dh60lVUor6hCeWUVSssrkX2xECU3K1ApBKqqgIqqKs5bIiKiv4WX21Zi6rAn9f4e3i9j/343ihGk8vJyHDlyBK+//rre8vDwcKSlpdX4mrKyMpSVlUmPi4qKANwKNFqt6f4VoVtX9XV281Wjm6/6nq8XQqDoZgXPfquDigot9u1LRWhoCGz+Zv/i/u/hC9iUeQE3yitQIYNDiJWVlbC25vy5hmaJOje6bxoBVFZVwtrKWv/GmWR6AlCg0qR/YwHDv6911SgC0pUrV1BZWQlPT0+95Z6ensjLy6vxNfHx8Zg7d67B8uTkZDg4OJi8jykpf7/DPnLkpAQOf59q6W6YXHMAr7ezdC+qk9FY+d8a62werLO5mPrv4Y0bN4x6XaMISDrVJ7EKIWqd2Dpr1ixMnTpVelxUVAQfHx+Eh4eb/BBbSkoKwsLCTDqkSIZYa/Ngnc2DdTYP1tl8GqrWuiNA9dUoApK7uzusra0NRovy8/MNRpV0VCoVVCqVwXKlUtkgvyQNtV4yxFqbB+tsHqyzebDO5mPqWhu7rkZxbritrS0CAwMNhu1SUlLQs2dPC/WKiIiI5KpRjCABwNSpUxEdHY2uXbsiODgYH3/8Mc6dO4eXXnrJ0l0jIiIimWk0Aen555/H1atX8fbbbyM3Nxft27fHrl274Ovra+muERERkcw0moAEABMnTsTEiRMt3Q0iIiKSuUYxB4mIiIioPhiQiIiIiKphQCIiIiKqhgGJiIiIqBoGJCIiIqJqGJCIiIiIqmFAIiIiIqqGAYmIiIiomkZ1ocj7IYQAYPxdgWuj1Wpx48YNFBUV8UaIDYy1Ng/W2TxYZ/Ngnc2noWqt+7ut+zteVwxIdVRcXAwA8PHxsXBPiIiIqL6Ki4uhVqvr3F4h6hupGqmqqipcvHgRzs7OUCgUJltvUVERfHx8cP78ebi4uJhsvWSItTYP1tk8WGfzYJ3Np6FqLYRAcXExvL29YWVV95lFHEGqIysrKzRr1qzB1u/i4sJfPjNhrc2DdTYP1tk8WGfzaYha12fkSIeTtImIiIiqYUAiIiIiqoYBycJUKhXmzJkDlUpl6a787bHW5sE6mwfrbB6ss/nIrdacpE1ERERUDUeQiIiIiKphQCIiIiKqhgGJiIiIqBoGJCIiIqJqGJAsbOnSpWjZsiXs7OwQGBiI/fv3W7pL/zPi4+PRrVs3ODs7w8PDA4MGDcLp06f12gghEBsbC29vb9jb2yM0NBQnTpzQa1NWVoZJkybB3d0djo6OiIqKwoULF8y5Kf9T4uPjoVAoEBMTIy1jnU3njz/+wIsvvgg3Nzc4ODigU6dOOHLkiPQ8a33/Kioq8Oabb6Jly5awt7dHq1at8Pbbb6OqqkpqwzrX33fffYeBAwfC29sbCoUC27dv13veVDUtKChAdHQ01Go11Go1oqOjce3aNdNvkCCLSUxMFEqlUqxcuVL89NNP4rXXXhOOjo7i7Nmzlu7a/4SIiAixZs0akZ2dLbKyssSAAQNE8+bNRUlJidRm3rx5wtnZWWzZskUcP35cPP/888LLy0sUFRVJbV566SXRtGlTkZKSIo4ePSoef/xx0bFjR1FRUWGJzZK1jIwM0aJFC9GhQwfx2muvSctZZ9P4888/ha+vrxg1apQ4dOiQyMnJEbt37xa//PKL1Ia1vn/vvvuucHNzEzt37hQ5OTni888/F05OTmLRokVSG9a5/nbt2iVmz54ttmzZIgCIbdu26T1vqpr269dPtG/fXqSlpYm0tDTRvn17ERkZafLtYUCyoO7du4uXXnpJb1mbNm3E66+/bqEe/W/Lz88XAERqaqoQQoiqqiqh0WjEvHnzpDY3b94UarVaLF++XAghxLVr14RSqRSJiYlSmz/++ENYWVmJpKQk826AzBUXFwt/f3+RkpIiQkJCpIDEOpvOzJkzRe/evWt9nrU2jQEDBogxY8boLRs8eLB48cUXhRCssylUD0imqulPP/0kAIiDBw9KbdLT0wUAcerUKZNuAw+xWUh5eTmOHDmC8PBwveXh4eFIS0uzUK/+txUWFgIAXF1dAQA5OTnIy8vTq7FKpUJISIhU4yNHjkCr1eq18fb2Rvv27fk5VPPKK69gwIAB6Nu3r95y1tl0duzYga5du+K5556Dh4cHOnfujJUrV0rPs9am0bt3b3z77bc4c+YMAODHH3/EgQMH0L9/fwCsc0MwVU3T09OhVqsRFBQktenRowfUarXJ686b1VrIlStXUFlZCU9PT73lnp6eyMvLs1Cv/ncJITB16lT07t0b7du3BwCpjjXV+OzZs1IbW1tbNGnSxKANP4fbEhMTcfToUWRmZho8xzqbzm+//YZly5Zh6tSpeOONN5CRkYHJkydDpVJhxIgRrLWJzJw5E4WFhWjTpg2sra1RWVmJ9957D0OHDgXAfbohmKqmeXl58PDwMFi/h4eHyevOgGRhCoVC77EQwmAZ3durr76KY8eO4cCBAwbPGVNjfg63nT9/Hq+99hqSk5NhZ2dXazvW+f5VVVWha9euiIuLAwB07twZJ06cwLJlyzBixAipHWt9fzZv3owNGzZg06ZNeOSRR5CVlYWYmBh4e3tj5MiRUjvW2fRMUdOa2jdE3XmIzULc3d1hbW1tkHjz8/MNEjbd3aRJk7Bjxw7s3bsXzZo1k5ZrNBoAuGuNNRoNysvLUVBQUGubxu7IkSPIz89HYGAgbGxsYGNjg9TUVPz73/+GjY2NVCfW+f55eXmhXbt2esvatm2Lc+fOAeA+bSr//Oc/8frrr+OFF15AQEAAoqOjMWXKFMTHxwNgnRuCqWqq0Whw6dIlg/VfvnzZ5HVnQLIQW1tbBAYGIiUlRW95SkoKevbsaaFe/W8RQuDVV1/F1q1bsWfPHrRs2VLv+ZYtW0Kj0ejVuLy8HKmpqVKNAwMDoVQq9drk5uYiOzubn8Nf+vTpg+PHjyMrK0v66dq1K4YPH46srCy0atWKdTaRXr16GVyq4syZM/D19QXAfdpUbty4ASsr/T9/1tbW0mn+rLPpmaqmwcHBKCwsREZGhtTm0KFDKCwsNH3dTTrlm+pFd5r/qlWrxE8//SRiYmKEo6Oj+P333y3dtf8JL7/8slCr1WLfvn0iNzdX+rlx44bUZt68eUKtVoutW7eK48ePi6FDh9Z4WmmzZs3E7t27xdGjR8UTTzzRqE/VrYs7z2ITgnU2lYyMDGFjYyPee+898fPPP4uNGzcKBwcHsWHDBqkNa33/Ro4cKZo2bSqd5r9161bh7u4uZsyYIbVhneuvuLhY/PDDD+KHH34QAMSCBQvEDz/8IF26xlQ17devn+jQoYNIT08X6enpIiAggKf5/x395z//Eb6+vsLW1lZ06dJFOkWd7g1AjT9r1qyR2lRVVYk5c+YIjUYjVCqVeOyxx8Tx48f11lNaWipeffVV4erqKuzt7UVkZKQ4d+6cmbfmf0v1gMQ6m86XX34p2rdvL1QqlWjTpo34+OOP9Z5nre9fUVGReO2110Tz5s2FnZ2daNWqlZg9e7YoKyuT2rDO9bd3794av5NHjhwphDBdTa9evSqGDx8unJ2dhbOzsxg+fLgoKCgw+fYohBDCtGNSRERERP/bOAeJiIiIqBoGJCIiIqJqGJCIiIiIqmFAIiIiIqqGAYmIiIioGgYkIiIiomoYkIiIiIiqYUAiIjKhtWvX4oEHHrB0N4joPjEgEZFF5OXl4bXXXsNDDz0EOzs7eHp6onfv3li+fDlu3Lhh6e7VSYsWLbBo0SK9Zc8//zzOnDljmQ4RkcnYWLoDRNT4/Pbbb+jVqxceeOABxMXFISAgABUVFThz5gxWr14Nb29vREVFWaRvQghUVlbCxsa4r0d7e3vY29ubuFdEZG4cQSIis5s4cSJsbGxw+PBhDBkyBG3btkVAQACeeeYZfPXVVxg4cCAAoLCwEOPHj4eHhwdcXFzwxBNP4Mcff5TWExsbi06dOmH9+vVo0aIF1Go1XnjhBRQXF0tthBBISEhAq1atYG9vj44dO+KLL76Qnt+3bx8UCgW++eYbdO3aFSqVCvv378evv/6Kp556Cp6ennByckK3bt2we/du6XWhoaE4e/YspkyZAoVCAYVCAaDmQ2zLli2Dn58fbG1t0bp1a6xfv17veYVCgU8++QRPP/00HBwc4O/vjx07dpis3kRUfwxIRGRWV69eRXJyMl555RU4OjrW2EahUEAIgQEDBiAvLw+7du3CkSNH0KVLF/Tp0wd//vmn1PbXX3/F9u3bsXPnTuzcuROpqamYN2+e9Pybb76JNWvWYNmyZThx4gSmTJmCF198EampqXrvOWPGDMTHx+PkyZPo0KEDSkpK0L9/f+zevRs//PADIiIiMHDgQJw7dw4AsHXrVjRr1gxvv/02cnNzkZubW+O2bNu2Da+99hqmTZuG7OxsTJgwAaNHj8bevXv12s2dOxdDhgzBsWPH0L9/fwwfPlxvO4nIzEx++1siors4ePCgACC2bt2qt9zNzU04OjoKR0dHMWPGDPHtt98KFxcXcfPmTb12fn5+YsWKFUIIIebMmSMcHBxEUVGR9Pw///lPERQUJIQQoqSkRNjZ2Ym0tDS9dYwdO1YMHTpUCHH7DuTbt2+/Z9/btWsnFi9eLD329fUVCxcu1GuzZs0aoVarpcc9e/YU48aN02vz3HPPif79+0uPAYg333xTelxSUiIUCoX4+uuv79knImoYnINERBahOySlk5GRgaqqKgwfPhxlZWU4cuQISkpK4ObmpteutLQUv/76q/S4RYsWcHZ2lh57eXkhPz8fAPDTTz/h5s2bCAsL01tHeXk5OnfurLesa9eueo+vX7+OuXPnYufOnbh48SIqKipQWloqjSDV1cmTJzF+/Hi9Zb169cJHH32kt6xDhw7Sfzs6OsLZ2VnaDiIyPwYkIjKrhx56CAqFAqdOndJb3qpVKwCQJjhXVVXBy8sL+/btM1jHnXN8lEql3nMKhQJVVVXSOgDgq6++QtOmTfXaqVQqvcfVD/f985//xDfffIMPPvgADz30EOzt7fHss8+ivLy8jluq36c7CSEMlt1tO4jI/BiQiMis3NzcEBYWhiVLlmDSpEm1zkPq0qUL8vLyYGNjgxYtWhj1Xu3atYNKpcK5c+cQEhJSr9fu378fo0aNwtNPPw0AKCkpwe+//67XxtbWFpWVlXddT9u2bXHgwAGMGDFCWpaWloa2bdvWqz9EZF4MSERkdkuXLkWvXr3QtWtXxMbGokOHDrCyskJmZiZOnTqFwMBA9O3bF8HBwRg0aBDmz5+P1q1b4+LFi9i1axcGDRpkcEisJs7Ozpg+fTqmTJmCqqoq9O7dG0VFRUhLS4OTkxNGjhxZ62sfeughbN26FQMHDoRCocC//vUvgxGdFi1a4LvvvsMLL7wAlUoFd3d3g/X885//xJAhQ6QJ5l9++SW2bt2qd0YcEckPAxIRmZ2fnx9++OEHxMXFYdasWbhw4QJUKhXatWuH6dOnY+LEiVAoFNi1axdmz56NMWPG4PLly9BoNHjsscfg6elZ5/d655134OHhgfj4ePz222944IEH0KVLF7zxxht3fd3ChQsxZswY9OzZE+7u7pg5cyaKior02rz99tuYMGEC/Pz8UFZWBiGEwXoGDRqEjz76CO+//z4mT56Mli1bYs2aNQgNDa3zNhCR+SlETb/RRERERI0Yr4NEREREVA0DEhEREVE1DEhERERE1TAgEREREVXDgERERERUDQMSERERUTUMSERERETVMCARERERVcOARERERFQNAxIRERFRNQxIRERERNUwIBERERFV8/9qq/3/QI04KAAAAABJRU5ErkJggg==",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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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 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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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 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"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Elapsed time: 0:00:27.562947\n"
     ]
    }
   ],
   "source": [
    "# Program EffectOfRecombinationOverFinalError.py\n",
    "# This program uses a genetic algorithm with MAX to find \n",
    "# the fifth degree polinomial that best fits a set of 6 points.\n",
    "# THis is a variation of the previous program, but now we test the effect of recombination over the final error.\n",
    "# The coefficients are represented by a chromosome, \n",
    "# which is a string of digits.\n",
    "# The decoding function must divide the chromosome into parts, \n",
    "# and decode each one apart as one coefficient.\n",
    "# The error of a chromosome is the sum of the vertical quadratic distances \n",
    "# of the points to the polynomial it encodes.\n",
    "# The Genetic algorithm must minimize the error, \n",
    "# (which is equivalent to maximizing the fitness).\n",
    "# We use MAX (selection of the best and cloning),  mutation and recombination.\n",
    "# Developed with the assistance of the AI of Visual Studio Code.\n",
    "# An old version of a GA developed with the help of Gemini was reused and updated.\n",
    "\n",
    "from datetime import datetime, timedelta\n",
    "import time\n",
    "import random\n",
    "import numpy as np\n",
    "# Documentation: https://numpy.org/devdocs/reference/routines.polynomials.html\n",
    "from numpy.polynomial import Polynomial\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",
    "#Task to be done\n",
    "number_of_generations = 1000\n",
    "\n",
    "xArray = [-2, -1, 0, 1, 2, 3]\n",
    "yArray = [5,   1, 4, 0, 6, 3]\n",
    "\n",
    "alphabet = '0123456789'\n",
    "length_of_chromosomes = 9\n",
    "population_size = 200\n",
    "# Include cloning of the fittest\n",
    "include_clone_populationj7 = True\n",
    "# Include mutation\n",
    "include_mutate_allj7 = True\n",
    "# Include recombination\n",
    "include_crossover_allj7 = True\n",
    "mutation_rate = 0.01 # \n",
    "recombination_rates = [0.00001, 0.0001, 0.001, 0.01, 0.05, 0.1, 0.15, 0.2, 0.3, 0.4, 0.5] # Different recombination rates to test\n",
    "best_recombination_rate = 0.03 # This will be updated with the best recombination rate found\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",
    "def print_parametersj7():\n",
    "    print(f\"Lab: la Evolución finds the polynomial of minimal error\")\n",
    "    print(f\"Purpose: Use a Genetic Algorithm (MAX or selection of the fittest, mutation, recombination) to find the coefficients of a polynomial that best fits a set of points.\")\n",
    "    print(f\"Date of Experiment  = {datetime.datetime.now()}\")\n",
    "    print(f\"number_of_generations = {number_of_generations}\")\n",
    "    print(f\"length_of_chromosomes = {length_of_chromosomes}\")\n",
    "    print(f\"alphabet =  {alphabet}\")\n",
    "    print(f\"Points = {list(zip(xArray, yArray))}\")\n",
    "    print(f\"population_size = {population_size}\")\n",
    "    print(f\"include_clone_populationj7 = {include_clone_populationj7}\")\n",
    "    print(f\"include_mutate_allj7 = {include_mutate_allj7}\")\n",
    "    print(f\"include_crossover_allj7 = {include_crossover_allj7}\")\n",
    "    if include_mutate_allj7:\n",
    "        print(f\"mutation_rate = {mutation_rate}\")\n",
    "    if include_crossover_allj7:\n",
    "        print(f\"recombination_rates = {recombination_rates}\")\n",
    "    if include_clone_populationj7:\n",
    "        print(f\"print_best_fitness = {print_best_fitness}\")\n",
    "\n",
    "\n",
    "def create_populationj7(population_size, length_of_chromosomes, alphabet):\n",
    "    \"\"\"Creates a new population with random chromosomes.\"\"\"\n",
    "    # print(\"create_populationj7(population_size, target_sequence, alphabet)\")\n",
    "    population = []\n",
    "    for _ in range(population_size):\n",
    "        random_string1 = ''.join(random.choice(alphabet) for _ in range(length_of_chromosomes))\n",
    "        random_string2 = ''.join(random.choice(alphabet) for _ in range(length_of_chromosomes))\n",
    "        random_string3 = ''.join(random.choice(alphabet) for _ in range(length_of_chromosomes))\n",
    "        random_string4 = ''.join(random.choice(alphabet) for _ in range(length_of_chromosomes))\n",
    "        random_string5 = ''.join(random.choice(alphabet) for _ in range(length_of_chromosomes))\n",
    "        random_string6 = ''.join(random.choice(alphabet) for _ in range(length_of_chromosomes))\n",
    "        random_string = random_string1 + random_string2 + random_string3 + random_string4 + random_string5 + random_string6\n",
    "        population.append(random_string)\n",
    "    # print(\"initial population\")\n",
    "    # print(population)\n",
    "    return population\n",
    "\n",
    "# Decode a part of the chromosome into a coefficient of the polynomial.\n",
    "def decoderj7(s):\n",
    "    ''' The input is a number as string, outputs the number as a float. '''\n",
    "    \n",
    "    l = len(s)\n",
    "    # The first char encodes for the sign, \n",
    "    sign = 1\n",
    "    if  float(s[0]) % 2 == 1:\n",
    "        sign = -1\n",
    "    # The second char encodes for the position of the decimal point,\n",
    "    d = float(s[1])\n",
    "    # The remaining chars encode for the number itself, \n",
    "    # without the decimal point nor sign.\n",
    "    n = float(s[2:l])\n",
    "    return sign * (n * (10**-d))\n",
    "\n",
    "def decodeFullCromosomej7(chromosome, length_of_chromosomes):\n",
    "    \"\"\"Decodes the full chromosome into the coefficients of the polynomial.\"\"\"\n",
    "    \"\"\"The chromosome is divided into 5 parts, \n",
    "        each one encoding for a coefficient of the polynomial.\"\"\"\n",
    "    chro0 = chromosome[0:length_of_chromosomes]\n",
    "    chro1 = chromosome[length_of_chromosomes:2*length_of_chromosomes]\n",
    "    chro2 = chromosome[2*length_of_chromosomes:3*length_of_chromosomes]\n",
    "    chro3 = chromosome[3*length_of_chromosomes:4*length_of_chromosomes]\n",
    "    chro4 = chromosome[4*length_of_chromosomes:5*length_of_chromosomes]\n",
    "    chro5 = chromosome[5*length_of_chromosomes:6*length_of_chromosomes]\n",
    "    a_0 = decoderj7(chro0)\n",
    "    a_1 = decoderj7(chro1)\n",
    "    a_2 = decoderj7(chro2)\n",
    "    a_3 = decoderj7(chro3)\n",
    "    a_4 = decoderj7(chro4)\n",
    "    a_5 = decoderj7(chro5)\n",
    "    return a_0, a_1, a_2, a_3, a_4, a_5\n",
    "\n",
    " \n",
    "\n",
    "def calculate_errorj7(chromosome, xArray, yArray):\n",
    "    \"\"\"Calculates the error of a chromosome.\n",
    "        A chromosome encodes for the coefficients of a polynomial of fith degree.\n",
    "        The error of a chromosome is the sum of \n",
    "        the vertical distances of the points to the polynomial it encodes.\n",
    "    \"\"\"\n",
    "    #  print(\"\\n calculate_errorj7(chromosome, xArray, yArray)\")\n",
    "    a_0, a_1, a_2, a_3, a_4, a_5 = decodeFullCromosomej7(chromosome, length_of_chromosomes) \n",
    "    error = 0\n",
    "    for i in range(len(xArray)):\n",
    "        x = xArray[i]\n",
    "        y = yArray[i]\n",
    "        # Calculate the predicted y value based on the coefficients of the polynomial\n",
    "        predicted_y = a_0 + a_1 * x + a_2 * x**2 + a_3 * x**3 + a_4 * x**4 + a_5 * x**5\n",
    "        # Calculate the error as the quadratic difference \n",
    "        # between predicted and y value\n",
    "        error += (predicted_y - y)**2\n",
    "    return error\n",
    "\n",
    "def calculate_all_errorsj7(population, xArray, yArray):\n",
    "    # print(\"\\n*calculate_all_errorsj7(population, target_sequence)\")\n",
    "    \"\"\"Calculates the error of all chromosomes in the population.\"\"\"\n",
    "    errors = [calculate_errorj7(chromosome, xArray, yArray) for chromosome in population]\n",
    "    # print(\"errors: \", errors)\n",
    "    return errors\n",
    "\n",
    "def select_the_least_errorj7(population, xArray, yArray):\n",
    "    \"\"\"Selects the best chromosome with minimal error for reproduction.\"\"\"\n",
    "    errors = calculate_all_errorsj7(population, xArray, yArray)\n",
    "    smallest_error = min(errors)\n",
    "    best_chromosome_index = errors.index(smallest_error)\n",
    "    best_chromosome = population[best_chromosome_index]\n",
    "    # print(\"\\n*select_the_least_errorj7(population)\")\n",
    "    # print(\"smallest_error = \", smallest_error)\n",
    "    # print(\"The chro = \", best_chromosome )\n",
    "    return smallest_error, best_chromosome\n",
    "\n",
    "def clone_populationj7(best_chromosome, population_size):\n",
    "    \"\"\"Creates a new population by cloning the best chromosome.\"\"\"\n",
    "    return [best_chromosome] * population_size\n",
    "\n",
    "\n",
    "def mutatej7(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_allj7(population, mutation_rate, alphabet):\n",
    "    \"\"\"Mutates all chromosomes in the population.\"\"\"\n",
    "    mutated_population = []\n",
    "    for chromosome in population:\n",
    "        mutated_chromosome = mutatej7(chromosome, mutation_rate, alphabet)\n",
    "        mutated_population.append(mutated_chromosome)\n",
    "    return mutated_population\n",
    "\n",
    "def crossoverj7(parent1, parent2, length_of_chromosomes, recombination_rate):\n",
    "    \"\"\"Performs crossover between two parent chromosomes.\"\"\"\n",
    "    if random.random() < recombination_rate:\n",
    "        crossover_point = random.randint(0, length_of_chromosomes)\n",
    "        return parent1[:crossover_point] + parent2[crossover_point:]\n",
    "    else:\n",
    "        return parent1\n",
    "\n",
    "def crossover_allj7(population, length_of_chromosomes, 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 = crossoverj7(parent1, parent2, length_of_chromosomes, recombination_rate)\n",
    "        recombinant_population.append(child)\n",
    "    return recombinant_population\n",
    "\n",
    "\n",
    "\n",
    "def run_one_generationj7(population, xArray, yArray, mutation_rate, recombination_rate, alphabet):\n",
    "    \"\"\"Runs one generation of the genetic algorithm.\"\"\"\n",
    "    # Calculate fitness scores for the current population\n",
    "    smallest_error, best_chromosome  = select_the_least_errorj7(population, xArray, yArray)\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_populationj7:\n",
    "        new_population = clone_populationj7(best_chromosome, population_size)\n",
    "    if include_mutate_allj7:\n",
    "        new_population = mutate_allj7(new_population, mutation_rate, alphabet)\n",
    "    if include_crossover_allj7:\n",
    "        new_population = crossover_allj7(new_population, length_of_chromosomes, recombination_rate)\n",
    "    return smallest_error, best_chromosome, new_population\n",
    "\n",
    "\n",
    "\n",
    "def plot_functionj7(g_values, 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",
    "def plot_polynomialj7(xArray, yArray, coefficients, best_mutation_rate, title=f'Polynomial for Best Mutation Rate {best_mutation_rate}'):\n",
    "    '''This function plots the polynomial defined by the best coefficients over the data points.\n",
    "    Developed by the AI of Visual Studio Code. '''\n",
    "    # Plot the polynomial\n",
    "    plt.figure(figsize=(10, 6))\n",
    "    plt.scatter(xArray, yArray, label='Data Points')\n",
    "    x_plot = np.linspace(min(xArray), max(xArray), 100)\n",
    "    y_plot = coefficients[0] + coefficients[1] * x_plot + coefficients[2] * x_plot**2 + coefficients[3] * x_plot**3 + coefficients[4] * x_plot**4 + coefficients[5] * x_plot**5\n",
    "    plt.plot(x_plot, y_plot, label='Fitted Polynomial')\n",
    "    plt.xlabel('x')\n",
    "    plt.ylabel('y')\n",
    "    plt.title(title)\n",
    "    plt.legend()\n",
    "    plt.grid(True)\n",
    "    plt.show()\n",
    "\n",
    "\n",
    "def taskj7( xArray, yArray, mutation_rate, recombination_rate, alphabet, percentageOfTask):\n",
    "    population = create_populationj7(population_size, length_of_chromosomes, alphabet)\n",
    "    # print(population)\n",
    "    generation = 0\n",
    "    best_chromosome = ''\n",
    "    best_fitness = 0\n",
    "    start_time = time.time()\n",
    "    smallest_error_history = [] # List to store best fitness of each generation\n",
    "    if print_best_fitness:\n",
    "        print(\"Generation, best_chromosome and best_fitness\")\n",
    "    while generation < number_of_generations:\n",
    "        generation += 1\n",
    "        smallest_error, best_chromosome, population = run_one_generationj7(population, xArray,yArray, mutation_rate, recombination_rate, alphabet)\n",
    "        if print_best_fitness:\n",
    "            print(f\" {generation}  {best_chromosome} {smallest_error}\")\n",
    "        smallest_error_history.append(smallest_error)\n",
    "    # print(f\"\\nTarget sequence matched in generation {generation}\")\n",
    "    # print(f\"Final chromosome: {best_chromosome}\")\n",
    "    totalCost = population_size * generation\n",
    "    \n",
    "    return  best_chromosome, totalCost, smallest_error_history\n",
    "\n",
    "\n",
    "\n",
    "def main(xArray, yArray, mutation_rates, recombination_rates, alphabet, length_of_chromosomes):\n",
    "    '''# We test the effect of recombination over the final error by running the main function with different recombination rates.\n",
    "    The best recombination rate is the one that gives the lowest final error.\n",
    "    We run the main function for each recombination rate,\n",
    "    and we keep the best chromosome and the final error history for each recombination rate.\n",
    "    Finally, we plot the final error history for each recombination rate, \n",
    "    and we compare them to find the best recombination rate.\n",
    "    Developed with the assistance of the AI of Visual Studio Code. '''\n",
    "\n",
    "    print_parametersj7()\n",
    "    # print(\"Total cost = population size * number of generations\")\n",
    "\n",
    "    # Array to keep the best chromosmes for each mutation rate    \n",
    "    best_chromosomes = []\n",
    "    # Array to keep the final error history for each mutation rate\n",
    "    final_error_histories = []\n",
    "    #Loop over the recombination rates to test their effect over the final error.\n",
    "    for recombination_rate in recombination_rates:   \n",
    "        best_chromosome, totalCost, smallest_error_history = taskj7(xArray, yArray, mutation_rate, recombination_rate, alphabet, length_of_chromosomes)\n",
    "        final_error = smallest_error_history[-1]\n",
    "        # print(f\" The best chromosome is {best_chromosome}\" )\n",
    "        # coefficients = decodeFullCromosomej7(best_chromosome, length_of_chromosomes)\n",
    "        # print(f\" Encoded coefficients: Intercept {coefficients[0]}, slope {coefficients[1]}, quadratic {coefficients[2]}, cubic {coefficients[3]}, quartic {coefficients[4]}, quintic {coefficients[5]}\")\n",
    "        # print(f\" Total cost =  {totalCost} chromosomes\")\n",
    "        print(f\" Recombination rate {recombination_rate}: Final error =  {final_error} \")\n",
    "        final_error_histories.append(smallest_error_history)\n",
    "        best_chromosomes.append(best_chromosome)\n",
    "\n",
    "    best_recombination_rate_index = np.argmin([final_error_history[-1] for final_error_history in final_error_histories])\n",
    "    best_recombination_rate = recombination_rates[best_recombination_rate_index]\n",
    "    least_error = final_error_histories[best_recombination_rate_index][-1]\n",
    "    print(f\"\\nBest recombination rate: {best_recombination_rate} with final error {least_error}\")\n",
    "    best_chromosome = best_chromosomes[best_recombination_rate_index]\n",
    "    best_coefficients = decodeFullCromosomej7(best_chromosome, length_of_chromosomes)\n",
    "\n",
    "    # Plot the final_error_histories for each recombination rate\n",
    "    for i, recombination_rate in enumerate(recombination_rates):\n",
    "        g_values = list(range(1, len(final_error_histories[i]) + 1))\n",
    "        plot_functionj7(g_values, final_error_histories[i], xlabel='Generation', ylabel='SmallestError', title=f'Smallest Error Over Generations for Recombination Rate {recombination_rate}')   \n",
    "    \n",
    "    # Plot all final_error_histories for all recombination rates in the same graph\n",
    "    plt.figure(figsize=(10, 6))\n",
    "    for i, recombination_rate in enumerate(recombination_rates):\n",
    "        plt.plot(final_error_histories[i], label=f'Recombination Rate {recombination_rate}')\n",
    "    plt.xlabel('Generation')\n",
    "    plt.ylabel('Smallest Error')\n",
    "    plt.title('Smallest Error Over Generations for Different Recombination Rates')\n",
    "    plt.legend()\n",
    "    plt.grid(True)\n",
    "    plt.show()\n",
    "\n",
    "    # Plot again the graph of the best error history for the best recombination rate (the one with the lowest final error)\n",
    "    g_values = list(range(1, len(final_error_histories[best_recombination_rate_index]) + 1))\n",
    "    plot_functionj7(g_values, final_error_histories[best_recombination_rate_index], xlabel='Generation', ylabel='SmallestError', title=f'Smallest Error Over Generations for the Best Recombination Rate {best_recombination_rate}')\n",
    "\n",
    "    # Plot the polynomial given by the coefficients of the best chromosome for the best recombination rate\n",
    "    plot_polynomialj7(xArray, yArray, best_coefficients, best_recombination_rate, title=f'Polynomial for Best Recombination Rate {best_recombination_rate}, least error = {least_error:.2f}')\n",
    "\n",
    "    end_time = time.time()\n",
    "    # Calculate the difference in seconds\n",
    "    elapsed_time = end_time - start_time\n",
    "    elapsed_time = timedelta(seconds=elapsed_time)\n",
    "    print(f\"Elapsed time: {elapsed_time}\")\n",
    "    #return best_chromosome, totalCost, best_fitness_history\n",
    "\n",
    "# Call the main function with the defined parameters\n",
    "main(xArray, yArray, mutation_rates, recombination_rates, alphabet, length_of_chromosomes)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "4c3d1e8a",
   "metadata": {},
   "source": [
    "*Nuestras observaciones.* Para 1000 generaciones, nuestras conclusiones con respecto al papel de la tasa de recombinación sobre el error final son:\n",
    "\n",
    "- El mejor valor de la tasa de recombinación es casi siempre 1E-5, pero otras veces cae en el intervalo [0,01, 0,1]. Nuestro valor preferido es 0,1. Adoptaremos este valor para futuros trabajos. \n",
    "- En nuestra opinión, la variación en el error final debido a un cambio en la tasa de recombinación no es tan significativa porque hay una brecha insuperable de 12 entre el error mínimo observado y la perfección. Por esa razón, el mejor ajuste parece ser rudimentario porque carece de 1 mínimo y 1 máximo. \n",
    "\n",
    "  \n",
    "**Desafío.** Concede más tiempo a la Evolución para valores muy bajos de la tasa de recombinación. Reporta tus hallazgos. "
   ]
  },
  {
   "cell_type": "markdown",
   "id": "28663152",
   "metadata": {},
   "source": [
    "\n",
    "\n",
    "# ¿Por qué existe la recombinación?\n",
    "\n",
    "Para inaugurar esta pregunta importante, resuelve el siguiente ejercicio.\n",
    "\n",
    "**Ejercicio.** Ejecuta el programa `EffectOfMutationOverFinalError.py` para una tasa de recombinación de cero. O, desactiva la recombinación. Comparar y decidir: ¿La recombinación energiza el proceso evolutivo permitiendo alcanzar la perfección? \n",
    ">\n",
    "> *Respuesta.* A nosotros nos parece que con respecto a alcanzar la perfección, la recombinación es un estropeador porque sin ella, el mínimo error podría ser 10,8 en lugar de 12. Esto implica que la recombinación no existe para favorecer el ritmo de la Evolución a alcanzar la perfección. El papel natural de la recombinación sería crear variabilidad dentro de un clan. \n",
    ">\n",
    "> \n",
    "La recombinación está ligada al sexo, que es omnipresente en todos los niveles del reino viviente. Pero, si bien el tamaño de la población podría ser extremadamente grande, por ejemplo, en cuanto a bacterias, insectos y seres humanos, la capacidad para aparearse está restringida. Por lo tanto, el tamaño de la población que debemos insertar en nuestros modelos será generalmente pequeño cuando consideremos la recombinación o el crossover. O bien, podremos considerar muestras pequeñas, como en la selección de torneos. \n",
    "\n",
    "**Ejercicio.** Seleccione valores adecuados para la mutación y la recombinación, y explore el papel de pequeños números de tamaño poblacional. Activar y desactivar la recombinación y comparar.\n",
    ">\n",
    "> *Respuesta.* Para tasas de mutación y recombinación de 0,1, preguntamos sobre el error final después de 1000 generaciones para diversos valores de tamaño poblacional, especialmente los pequeños:\n",
    ">\n",
    "> Tamaño de la población $\\rightarrow$ error final con recombinación activada, desactivada\n",
    ">\n",
    "> 2 $\\rightarrow$ 3E9 + fuertes fluctuaciones, de 345 a 1E11\n",
    ">\n",
    "> 3 $\\rightarrow$ de 84 a E10, de 50 a 1E11\n",
    ">\n",
    "> 4 $\\rightarrow$ de 50 a 10000 y raras fluctuaciones fuertes, de 40 a 27 millones y fluctuaciones.\n",
    ">\n",
    "> 5 $\\rightarrow$ de 25 a 1E11 con fluctuaciones, de 50 a 2500 y sin fluctuaciones \n",
    ">\n",
    "> 6 $\\rightarrow$ de 16 a 2500, pero raras veces valores muy grandes, de 16 a 200 la mayoría de las corridas.\n",
    "> \n",
    "> 10 $\\rightarrow$ de 19 a 240, de 16 a 80\n",
    ">\n",
    "> 15 $\\rightarrow$ de 16 a generalmente menos de 100, valores superiores a menos de 45000, 13 a 4000.\n",
    "> \n",
    "> 20 $\\rightarrow$ de 13 a 50 con algunas excepciones por debajo de 5000, de 12 a 38.\n",
    ">\n",
    "> 25 $\\rightarrow$ de 14 a 13000, de 14 a 40.\n",
    ">\n",
    "> 100 $\\rightarrow$ de 11,8 a 3400, de 14,5 a 364\n",
    ">\n",
    "> 1000 $\\rightarrow $ de 10,2 a 17, de 12,06 a 17,5\n",
    ">\n",
    "> 10 000 $\\rightarrow$ de  7.11 a 17.12, de 17.12 a 17.12\n",
    ">\n",
    "> 100 000 $\\rightarrow$ 12.17\n",
    ">\n",
    "> 1 000 000 $ \\rightarrow$ 12,17 obtenido con recombinación en generación 10 y mantenido hasta que el programa se detuvo en generación 100. El error inicial fue 27. Sin recombinación: el error mínimo fue de 7,25 obtenido en la generación 80 y se mantuvo hasta que el programa se detuvo en la generación 100. El error inicial fue 28.\n",
    "> \n",
    "> 10 000 000 $ \\rightarrow$ 12,17 obtenido con recombinación en la generación 10 y mantenido hasta que el programa se detuvo en la generación 50. El error inicial fue 16.3. Sin recombinación: casi la misma historia. \n",
    "> \n",
    "> Comparación: Consideramos que estos resultados dicen que la recombinación es un descarrilador con esta tasa de 0,1 y para este problema. Esto significa que el propósito de la recombinación no parece ser desarrollar mejores productos. Podría ser crear variabilidad dentro del mismo clan, un poder que es apreciado por todos en la tierra. \n",
    "\n",
    "\n",
    "**Ejercicio.** Prueba diversos valores de la tasa de cruce para un tamaño de población de 2 y una tasa de mutación de 0,1.\n",
    ">\n",
    "> Tasa de recombinación $\\rightarrow$ error mínimo.\n",
    "> \n",
    "> 0.1 $\\rightarrow$ de 260 a 1E11 para 1000 generaciones. De 187 a 1 E13 para 100000 generaciones.\n",
    ">\n",
    "> 0,01 $\\rightarrow$ de 3000 a 1E11 para 1000 generaciones.\n",
    ">\n",
    "> 0,001 $\\rightarrow$ de 490000 a 3E9 para 1000 generaciones. De 162000 a 6E12 para 100000 generaciones.\n",
    "> \n",
    "> 0,0001 $\\rightarrow$ de 18000 a 3E12 para 1000 generaciones.\n",
    ">\n",
    "> 0,00001 $\\rightarrow$ de 3600 a 4E11 para 1000 generaciones.\n",
    ">\n",
    "> 0,000001 $\\rightarrow$ de 309 a 1E12 para 1000 generaciones. De 171 a 1 E10 para 100000 generaciones.\n",
    ">\n",
    "> 0.0000001 $ \\rightarrow$ de 2920 a 1E14 en 1000 generaciones. De 128 para 100000 generaciones. \n",
    ">\n",
    "> 0 $ \\rightarrow$ de 444 a 7E12 para 1000 generaciones. De 848 a 1E14 para 100000 generaciones.\n",
    "\n",
    "> En nuestra opinión, cuando el tamaño de la población es 2, una tasa de recombinación igual a 0,1 o 1E-7 hace posible la aparición de valores con un error menor que sin ella. De todos modos, el error es demasiado alto en comparación con un tamaño de población de 20. Advertencia: la tarea planteada es especificar un conjunto de 6 números reales con unos 10 dígitos, un signo y un lugar para el punto decimal. Esto equivale a alrededor de 66 dígitos o 280 bits. Un valor de complejidad tan bajo no aparece en la naturaleza en referencia al origen de la vida o de las especies, donde se cuenta con una complejidad en el rango de unos pocos millones a miles de millones.  \n",
    "\n",
    "**Ejercicio.** Desarrollar un programa que nos ayude a decidir si el estado de equilibrio observado es resultado de una dinámica interna de la Evolución o de la complejidad del problema planteado que crea un óptimo local con un error de 12,17 que atrapa a la Evolución impidiéndole reducir el error.\n",
    ">\n",
    "> *Respuesta.* Para conocer el efecto de la dinámica interna de la Evolución, tomamos un  cromosoma perfecto, y miramos hacia dónde tiende. Si se conserva la perfección, ésta puede ser alcanzada por las dinámicas internas. De lo contrario, la perfección es degradada por la dinámica interna a un estado de equilibrio estable debajo de ella. El código sigue. Perfección significa aquí que el conjunto elegido de coeficientes produce un polinomio de quinto grado que pasa a través de todos los 6 puntos dados. Según los programas anteriores, se da por [[ 4, -2.98333333, -4.79166667, 3.04166667, 1.29166667, -0.55833333]], el primer número es la intersección del gráfico con el eje vertical, el último, el coeficiente de $x^5$. Este array es codificado y luego se evoluciona. "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "c3a98804",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Lab: Evolution finds the polynomial of minimal error\n",
      "Purpose: Use a Genetic Algorithm (MAX or selection of the fittest, mutation, recombination) to find the coefficients of a polynomial that best fits a set of points.\n",
      "Date of Experiment  = 2026-04-23 08:29:06.841464\n",
      "number_of_generations = 10000\n",
      "length_of_chromosomes = 9\n",
      "alphabet =  0123456789\n",
      "Points = [(-2, 5), (-1, 1), (0, 4), (1, 0), (2, 6), (3, 3)]\n",
      "population_size = 200\n",
      "include_clone_populationj8 = True\n",
      "include_mutate_allj8 = True\n",
      "include_crossover_allj8 = True\n",
      "mutation_rate = 0.02\n",
      "recombination_rate = 0.03\n",
      "print_best_fitness = False\n",
      "Total cost = population size * number of generations\n",
      "Points that must be regressed: [(-2, 5), (-1, 1), (0, 4), (1, 0), (2, 6), (3, 3)]\n",
      "type of xNumpyArray: <class 'numpy.ndarray'>, type of yNumpyArray: <class 'numpy.ndarray'>\n",
      "Polynomial.fit.convert().coef: Intercept 4.0, slope -2.983333333333327, quadratic -4.791666666666659, cubic 3.041666666666663, quartic 1.2916666666666643, quintic -0.5583333333333323\n",
      "x points: [-2.         -1.94949495 -1.8989899  -1.84848485 -1.7979798  -1.74747475\n",
      " -1.6969697  -1.64646465 -1.5959596  -1.54545455 -1.49494949 -1.44444444\n",
      " -1.39393939 -1.34343434 -1.29292929 -1.24242424 -1.19191919 -1.14141414\n",
      " -1.09090909 -1.04040404 -0.98989899 -0.93939394 -0.88888889 -0.83838384\n",
      " -0.78787879 -0.73737374 -0.68686869 -0.63636364 -0.58585859 -0.53535354\n",
      " -0.48484848 -0.43434343 -0.38383838 -0.33333333 -0.28282828 -0.23232323\n",
      " -0.18181818 -0.13131313 -0.08080808 -0.03030303  0.02020202  0.07070707\n",
      "  0.12121212  0.17171717  0.22222222  0.27272727  0.32323232  0.37373737\n",
      "  0.42424242  0.47474747  0.52525253  0.57575758  0.62626263  0.67676768\n",
      "  0.72727273  0.77777778  0.82828283  0.87878788  0.92929293  0.97979798\n",
      "  1.03030303  1.08080808  1.13131313  1.18181818  1.23232323  1.28282828\n",
      "  1.33333333  1.38383838  1.43434343  1.48484848  1.53535354  1.58585859\n",
      "  1.63636364  1.68686869  1.73737374  1.78787879  1.83838384  1.88888889\n",
      "  1.93939394  1.98989899  2.04040404  2.09090909  2.14141414  2.19191919\n",
      "  2.24242424  2.29292929  2.34343434  2.39393939  2.44444444  2.49494949\n",
      "  2.54545455  2.5959596   2.64646465  2.6969697   2.74747475  2.7979798\n",
      "  2.84848485  2.8989899   2.94949495  3.        ]\n",
      "Fitted polynomial values: [ 5.          3.44780189  2.14179315  1.06065771  0.18410904 -0.50713191\n",
      " -1.03135868 -1.40590137 -1.6471486  -1.77056957 -1.79073605 -1.72134442\n",
      " -1.57523765 -1.36442737 -1.10011583 -0.79271795 -0.45188333 -0.08651828\n",
      "  0.29519221  0.68576238  1.07838376  1.4669031   1.84580038  2.21016678\n",
      "  2.55568267  2.87859559  3.17569824  3.44430646  3.68223721  3.88778654\n",
      "  4.05970762  4.19718868  4.29983099  4.36762689  4.40093771  4.40047181\n",
      "  4.36726254  4.30264622  4.20824011  4.08592044  3.93780035  3.76620788\n",
      "  3.57366396  3.36286043  3.13663793  2.897964    2.64991096  2.39563396\n",
      "  2.13834894  1.88131062  1.62779046  1.38105468  1.14434222  0.92084273\n",
      "  0.71367455  0.5258627   0.36031686  0.21980935  0.10695312  0.02417972\n",
      " -0.02628269 -0.04243138 -0.02251107  0.03496408  0.13118843  0.26704285\n",
      "  0.4430727   0.65946584  0.91603056  1.21217361  1.54687818  1.91868185\n",
      "  2.32565461  2.76537682  3.2349172   3.73081084  4.24903712  4.78499777\n",
      "  5.33349479  5.88870847  6.44417536  6.99276627  7.52666421  8.03734243\n",
      "  8.51554237  8.95125165  9.33368205  9.6512475   9.89154205 10.04131789\n",
      " 10.08646329 10.0119806   9.80196424  9.43957868  8.90703641  8.18557594\n",
      "  7.25543979  6.09585246  4.68499839  3.        ]\n",
      "Original Points = [(-2, 5), (-1, 1), (0, 4), (1, 0), (2, 6), (3, 3)] \n",
      "Interpolated fitted polynomial points: [(-2.0, 4.999999999999969), (-1.9494949494949494, 3.4478018886507784), (-1.898989898989899, 2.141793145975416), (-1.8484848484848484, 1.0606577103578034), (-1.797979797979798, 0.18410903936559309), (-1.7474747474747474, -0.5071319067786817), (-1.696969696969697, -1.0313586817266334), (-1.6464646464646464, -1.405901369533007), (-1.595959595959596, -1.6471486011846799), (-1.5454545454545454, -1.7705695711296472), (-1.4949494949494948, -1.7907360538059693), (-1.4444444444444444, -1.7213444201708175), (-1.393939393939394, -1.575237654229424), (-1.3434343434343434, -1.3644273695640745), (-1.2929292929292928, -1.1001158258631039), (-1.2424242424242424, -0.7927179454498714), (-1.191919191919192, -0.45188332981176504), (-1.1414141414141414, -0.0865182761291603), (-1.0909090909090908, 0.29519220619555386), (-1.0404040404040404, 0.6857623790090248), (-0.9898989898989898, 1.0783837588779246), (-0.9393939393939394, 1.4669031005599797), (-0.8888888888888888, 1.845800380474973), (-0.8383838383838385, 2.210166780175757), (-0.7878787878787878, 2.555682669819277), (-0.7373737373737375, 2.878595591637569), (-0.6868686868686869, 3.175698243408789), (-0.6363636363636365, 3.4443064619282073), (-0.5858585858585859, 3.6822372064792432), (-0.5353535353535355, 3.887786542304458), (-0.48484848484848486, 4.059707624076581), (-0.4343434343434345, 4.197188679369516), (-0.38383838383838387, 4.299830992129358), (-0.33333333333333326, 4.367626886145404), (-0.2828282828282829, 4.4009377085211625), (-0.23232323232323226, 4.400471813145376), (-0.18181818181818188, 4.367262544163028), (-0.13131313131313127, 4.302646219446352), (-0.08080808080808088, 4.208240114065852), (-0.030303030303030276, 4.085920443761312), (0.020202020202020332, 3.9378003484128072), (0.0707070707070705, 3.7662078755117245), (0.1212121212121211, 3.5736639636317626), (0.1717171717171717, 3.362860425899956), (0.22222222222222232, 3.1366379334676866), (0.2727272727272725, 2.8979639989816923), (0.3232323232323231, 2.649910960055079), (0.3737373737373737, 2.395633962738341), (0.4242424242424243, 2.1383489449903688), (0.4747474747474749, 1.8813106201494616), (0.5252525252525251, 1.627790460404345), (0.5757575757575757, 1.3810546802651729), (0.6262626262626263, 1.1443422200345557), (0.6767676767676769, 0.920842729278562), (0.7272727272727271, 0.7136745502977393), (0.7777777777777777, 0.525862701598115), (0.8282828282828283, 0.3603168613622252), (0.8787878787878789, 0.21980935092011555), (0.9292929292929291, 0.10695311822036091), (0.9797979797979797, 0.02417972130107282), (1.0303030303030303, -0.026282688239082752), (1.0808080808080809, -0.042431381769873155), (1.131313131313131, -0.022511070158489632), (1.1818181818181817, 0.03496407970147031), (1.2323232323232323, 0.1311884283610134), (1.2828282828282829, 0.26704284728676275), (1.3333333333333335, 0.44307270233197227), (1.3838383838383836, 0.6594658372075373), (1.4343434343434343, 0.9160305569530187), (1.4848484848484849, 1.2121736114076351), (1.5353535353535355, 1.5468781786812924), (1.5858585858585856, 1.9186818486255912), (1.6363636363636362, 2.3256546063048447), (1.6868686868686869, 2.765376815467081), (1.7373737373737375, 3.2349172020150654), (1.7878787878787876, 3.7308108374773106), (1.8383838383838382, 4.249037122479088), (1.8888888888888888, 4.784997770213449), (1.9393939393939394, 5.333494789912223), (1.9898989898989896, 5.888708470317025), (2.0404040404040407, 6.444175363150327), (2.090909090909091, 6.992766266586372), (2.141414141414141, 7.526664208722271), (2.191919191919192, 8.037342431049007), (2.242424242424242, 8.515542371922361), (2.2929292929292933, 8.951251650034056), (2.3434343434343434, 9.333682047882672), (2.3939393939393936, 9.651247495244705), (2.4444444444444446, 9.891542052645555), (2.494949494949495, 10.041317894830563), (2.545454545454545, 10.086463294236005), (2.595959595959596, 10.011980604460106), (2.646464646464646, 9.80196424373408), (2.6969696969696972, 9.43957867839309), (2.7474747474747474, 8.907036406347322), (2.7979797979797976, 8.185575940552962), (2.8484848484848486, 7.255439792483188), (2.898989898989899, 6.095852455599262), (2.94949494949495, 4.684998388821405), (3.0, 3.000000000000031)] \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": [
      "Numpy fitted polynomial coefficients: 4.0, -2.983333333333327, -4.791666666666659, 3.041666666666663, 1.2916666666666643, -0.5583333333333323\n",
      "Perfect chromosome: 064000000162983333164791666063041666061291666175583333\n",
      "Decoded perfect chromosome: (4.0, -2.983333, -4.791666, 3.0416659999999998, 1.291666, -0.5583332999999999)\n",
      "Error of perfect chromosome: 3.3917100005296273e-09\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      " The final best chromosome is 464000001162983334764791665663041666261291666175583331\n",
      " Encoded coefficients: Intercept 4.000001, slope -2.9833339999999997, quadratic -4.791665, cubic 3.0416659999999998, quartic 1.291666, quintic -0.5583331\n",
      " Total cost =  2000000 chromosomes\n",
      " Final error =  3.2390000030228983e-11 \n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Polynomial regression coefficients: Intercept 4.0, slope -2.983333333333327, quadratic -4.791666666666659, cubic 3.041666666666663, quartic 1.2916666666666643, quintic -0.5583333333333323\n",
      "Encoded coefficients: Intercept 4.000001, slope -2.9833339999999997, quadratic -4.791665, cubic 3.0416659999999998, quartic 1.291666, quintic -0.5583331\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": [
      "Elapsed time: 0:02:22.595479\n"
     ]
    }
   ],
   "source": [
    "# Program PolynomialPerfectChromosome.py\n",
    "# This program uses a genetic algorithm with MAX to find \n",
    "# the fifth degree polinomial that best fits a set of 6 points.\n",
    "# The coefficients are represented by a chromosome, \n",
    "# which is a string of digits.\n",
    "# The decoding function must divide the chromosome into parts, \n",
    "# and decode each one apart as one coefficient.\n",
    "# The error of a chromosome is the sum of the vertical quadratic distances \n",
    "# of the points to the polynomial it encodes.\n",
    "# The Genetic algorithm must minimize the error, \n",
    "# (which is equivalent to maximizing the fitness).\n",
    "# We use MAX (selection of the best and cloning),  mutation and recombination.\n",
    "# Developed with the assistance of the AI of Visual Studio Code.\n",
    "# An old version of a GA developed with the help of Gemini was reused and updated.\n",
    "\n",
    "from datetime import datetime, timedelta\n",
    "import time\n",
    "import random\n",
    "import numpy as np\n",
    "# Documentation: https://numpy.org/devdocs/reference/routines.polynomials.html\n",
    "from numpy.polynomial import Polynomial\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",
    "#Task to be done\n",
    "number_of_generations = 1000\n",
    "\n",
    "xArray = np.array([-2, -1, 0, 1, 2, 3])\n",
    "yArray = np.array([5,   1, 4, 0, 6, 3])\n",
    "\n",
    "alphabet = '0123456789'\n",
    "length_of_chromosomes = 9\n",
    "population_size = 200\n",
    "# Include cloning of the fittest\n",
    "include_clone_populationj8 = True\n",
    "# Include mutation\n",
    "include_mutate_allj8 = True\n",
    "# Include recombination\n",
    "include_crossover_allj8 = True\n",
    "mutation_rate = 0.02\n",
    "recombination_rate = 0.03\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",
    "def print_parametersj8():\n",
    "    print(f\"Lab: la Evolución finds the polynomial of minimal error\")\n",
    "    print(f\"Purpose: Use a Genetic Algorithm (MAX or selection of the fittest, mutation, recombination) to find the coefficients of a polynomial that best fits a set of points.\")\n",
    "    print(f\"Date of Experiment  = {datetime.datetime.now()}\")\n",
    "    print(f\"number_of_generations = {number_of_generations}\")\n",
    "    print(f\"length_of_chromosomes = {length_of_chromosomes}\")\n",
    "    print(f\"alphabet =  {alphabet}\")\n",
    "    print(f\"Points = {list(zip(xArray, yArray))}\")\n",
    "    print(f\"population_size = {population_size}\")\n",
    "    print(f\"include_clone_populationj8 = {include_clone_populationj8}\")\n",
    "    print(f\"include_mutate_allj8 = {include_mutate_allj8}\")\n",
    "    print(f\"include_crossover_allj8 = {include_crossover_allj8}\")\n",
    "    if include_mutate_allj8:\n",
    "        print(f\"mutation_rate = {mutation_rate}\")\n",
    "    if include_crossover_allj8:\n",
    "        print(f\"recombination_rate = {recombination_rate}\")\n",
    "    if include_clone_populationj8:\n",
    "        print(f\"print_best_fitness = {print_best_fitness}\")\n",
    "\n",
    "def draw_points_and_polynomialj8(xNumpyArray, yNumpyArray):\n",
    "    \"\"\"Draws the original data points, finds and draws the \n",
    "    regression polynomial defined by the coefficients.\"\"\"\n",
    "    \n",
    "    # 2. Fit a 5th-degree (quintic) polynomial\n",
    "    # .fit() returns a Polynomial instance\n",
    "    p_fitted = Polynomial.fit(xNumpyArray, yNumpyArray, deg=5)\n",
    "    coefficients = p_fitted. convert().coef\n",
    "    b_0, b_1, b_2, b_3, b_4, b5 = coefficients\n",
    "    print(f\"Polynomial.fit.convert().coef: Intercept {b_0}, slope {b_1}, quadratic {b_2}, cubic {b_3}, quartic {b_4}, quintic {b5}\")\n",
    "\n",
    "    # 3. Predict values for visualization\n",
    "    x_new = np.linspace(-2,3, 100) # Generate 100 points between -2 and 3for a smooth curve\n",
    "    y_new = p_fitted(x_new)\n",
    "    print(f\"x points: {x_new}\")\n",
    "    print(f\"Fitted polynomial values: {y_new}\")\n",
    "    print(f\"Original Points = {list(zip(xNumpyArray, yNumpyArray))} \")\n",
    "    print(f\"Interpolated fitted polynomial points: {list(zip(x_new, y_new))} \")\n",
    "\n",
    "\n",
    "    # 4. Plot results\n",
    "    plt.scatter(xNumpyArray, yNumpyArray, label='Data Points')\n",
    "    plt.xlabel('x')\n",
    "    plt.ylabel('y')\n",
    "    plt.plot(x_new, y_new, label=f'Quintic Fit: y = {b_0:.2f} + {b_1:.2f}x + {b_2:.2f}x^2 + {b_3:.2f}x^3 + {b_4:.2f}x^4 + {b5:.2f}x^5', color='green')\n",
    "    plt.title(' Data Points and Quintic Fit by numpy.polynomial.Polynomial.fit()')\n",
    "    plt.legend()\n",
    "    plt.show()\n",
    "    return  coefficients\n",
    "\n",
    "def create_populationj8(population_size, length_of_chromosomes, alphabet):\n",
    "    \"\"\"Creates a new population with random chromosomes.\"\"\"\n",
    "    # print(\"create_populationj8(population_size, target_sequence, alphabet)\")\n",
    "    population = []\n",
    "    for _ in range(population_size):\n",
    "        random_string1 = ''.join(random.choice(alphabet) for _ in range(length_of_chromosomes))\n",
    "        random_string2 = ''.join(random.choice(alphabet) for _ in range(length_of_chromosomes))\n",
    "        random_string3 = ''.join(random.choice(alphabet) for _ in range(length_of_chromosomes))\n",
    "        random_string4 = ''.join(random.choice(alphabet) for _ in range(length_of_chromosomes))\n",
    "        random_string5 = ''.join(random.choice(alphabet) for _ in range(length_of_chromosomes))\n",
    "        random_string6 = ''.join(random.choice(alphabet) for _ in range(length_of_chromosomes))\n",
    "        random_string = random_string1 + random_string2 + random_string3 + random_string4 + random_string5 + random_string6\n",
    "        population.append(random_string)\n",
    "    # print(\"initial population\")\n",
    "    # print(population)\n",
    "    return population\n",
    "\n",
    "# Decode a part of the chromosome into a coefficient of the polynomial.\n",
    "def decoderj8(s):\n",
    "    ''' The input is a number as string, outputs the number as a float. '''\n",
    "    \n",
    "    l = len(s)\n",
    "    # The first char encodes for the sign, \n",
    "    sign = 1\n",
    "    if  float(s[0]) % 2 == 1:\n",
    "        sign = -1\n",
    "    # The second char encodes for the position of the decimal point,\n",
    "    d = float(s[1])\n",
    "    # The remaining chars encode for the number itself, \n",
    "    # without the decimal point nor sign.\n",
    "    n = float(s[2:l])\n",
    "    return sign * (n * (10**-d))\n",
    "\n",
    "def decodeFullCromosomej8(chromosome, length_of_chromosomes):\n",
    "    \"\"\"Decodes the full chromosome into the coefficients of the polynomial.\"\"\"\n",
    "    \"\"\"The chromosome is divided into 5 parts, \n",
    "        each one encoding for a coefficient of the polynomial.\"\"\"\n",
    "    chro0 = chromosome[0:length_of_chromosomes]\n",
    "    chro1 = chromosome[length_of_chromosomes:2*length_of_chromosomes]\n",
    "    chro2 = chromosome[2*length_of_chromosomes:3*length_of_chromosomes]\n",
    "    chro3 = chromosome[3*length_of_chromosomes:4*length_of_chromosomes]\n",
    "    chro4 = chromosome[4*length_of_chromosomes:5*length_of_chromosomes]\n",
    "    chro5 = chromosome[5*length_of_chromosomes:6*length_of_chromosomes]\n",
    "    a_0 = decoderj8(chro0)\n",
    "    a_1 = decoderj8(chro1)\n",
    "    a_2 = decoderj8(chro2)\n",
    "    a_3 = decoderj8(chro3)\n",
    "    a_4 = decoderj8(chro4)\n",
    "    a_5 = decoderj8(chro5)\n",
    "    return a_0, a_1, a_2, a_3, a_4, a_5\n",
    "\n",
    "def encodeFullCromosomej8(a_0, a_1, a_2, a_3, a_4, a_5, length_of_chromosomes):\n",
    "    \"\"\"Encodes the coefficients of the polynomial into a chromosome.\n",
    "        The chromosome is divided into 5 parts,\n",
    "        each one encoding for a coefficient of the polynomial.\n",
    "        The encoding of a coefficient is as follows:\n",
    "        The first char encodes for the sign,\n",
    "        The second char encodes for the position of the decimal point,\n",
    "        The remaining chars encode for the number itself,\n",
    "        without the decimal point nor sign.\n",
    "        Developed by the AI of Visual Studio Code, based on the decoder function.\"\"\"\n",
    "    def encoderj8(coefficient, length_of_chromosomes):\n",
    "        ''' The input is a coefficient as a float, outputs a string of digits. '''\n",
    "        # Determine the sign\n",
    "        sign = 0 if coefficient >= 0 else 1\n",
    "        # Determine the position of the decimal point\n",
    "        if coefficient == 0:\n",
    "            d = 0\n",
    "        else:\n",
    "            d = int(np.floor(np.log10(abs(coefficient)))) +1\n",
    "        d = length_of_chromosomes - d - 2 # -2 for the sign and decimal point chars\n",
    "        #print(f\"Coefficient: {coefficient}, sign: {sign}, decimal point position: {d}\")\n",
    "        # Determine the number itself without the decimal point and sign\n",
    "        n = int(abs(coefficient) * (10**d))\n",
    "        # Create the string representation of the coefficient, \n",
    "        # first the sign, then the position of the decimal point, then the number itself\n",
    "        # The string is trimmed to fit the length of the chromosome part.\n",
    "        n_str = str(n)\n",
    "        if len(n_str) > length_of_chromosomes - 2:\n",
    "            n_str = str(n)[:length_of_chromosomes - 2]\n",
    "        return str(sign) + str(d) + n_str\n",
    "    \n",
    "    #coef = -123.456789123456789\n",
    "    #print(f\"Encoding coefficient: {coef}, encoded as: {encoder(coef, length_of_chromosomes)}, decoded as: {decoder(encoder(coef, length_of_chromosomes))}\")\n",
    "\n",
    "    chro0 = encoderj8(a_0, length_of_chromosomes)\n",
    "    chro1 = encoderj8(a_1, length_of_chromosomes)\n",
    "    chro2 = encoderj8(a_2, length_of_chromosomes)\n",
    "    chro3 = encoderj8(a_3, length_of_chromosomes)\n",
    "    chro4 = encoderj8(a_4, length_of_chromosomes)\n",
    "    chro5 = encoderj8(a_5, length_of_chromosomes)\n",
    "    return chro0 + chro1 + chro2 + chro3 + chro4 + chro5\n",
    "\n",
    "def createPerfectPopulationj8(a_0, a_1, a_2, a_3, a_4, a_5, length_of_chromosomes, population_size):\n",
    "    \"\"\"Creates a new population with the perfect chromosome.\n",
    "    By the AI of Visual Studio Code, based on the encodeFullCromosome function.\"\"\"\n",
    "    perfect_chromosome = encodeFullCromosomej8(a_0, a_1, a_2, a_3, a_4, a_5, length_of_chromosomes)\n",
    "    return [perfect_chromosome] * population_size\n",
    "\n",
    "def calculate_errorj8(chromosome, xArray, yArray):\n",
    "    \"\"\"Calculates the error of a chromosome.\n",
    "        A chromosome encodes for the coefficients of a polynomial of fith degree.\n",
    "        The error of a chromosome is the sum of \n",
    "        the vertical distances of the points to the polynomial it encodes.\n",
    "    \"\"\"\n",
    "    #  print(\"\\n calculate_errorj8(chromosome, xArray, yArray)\")\n",
    "    a_0, a_1, a_2, a_3, a_4, a_5 = decodeFullCromosomej8(chromosome, length_of_chromosomes) \n",
    "    error = 0\n",
    "    for i in range(len(xArray)):\n",
    "        x = xArray[i]\n",
    "        y = yArray[i]\n",
    "        # Calculate the predicted y value based on the coefficients of the polynomial\n",
    "        predicted_y = a_0 + a_1 * x + a_2 * x**2 + a_3 * x**3 + a_4 * x**4 + a_5 * x**5\n",
    "        # Calculate the error as the quadratic difference \n",
    "        # between predicted and y value\n",
    "        error += (predicted_y - y)**2\n",
    "    return error\n",
    "\n",
    "def calculate_all_errorsj8(population, xArray, yArray):\n",
    "    # print(\"\\n*calculate_all_errorsj8(population, target_sequence)\")\n",
    "    \"\"\"Calculates the error of all chromosomes in the population.\"\"\"\n",
    "    errors = [calculate_errorj8(chromosome, xArray, yArray) for chromosome in population]\n",
    "    # print(\"errors: \", errors)\n",
    "    return errors\n",
    "\n",
    "def select_the_least_errorj8(population, xArray, yArray):\n",
    "    \"\"\"Selects the best chromosome with minimal error for reproduction.\"\"\"\n",
    "    errors = calculate_all_errorsj8(population, xArray, yArray)\n",
    "    smallest_error = min(errors)\n",
    "    best_chromosome_index = errors.index(smallest_error)\n",
    "    best_chromosome = population[best_chromosome_index]\n",
    "    # print(\"\\n*select_the_least_errorj8(population)\")\n",
    "    # print(\"smallest_error = \", smallest_error)\n",
    "    # print(\"The chro = \", best_chromosome )\n",
    "    return smallest_error, best_chromosome\n",
    "\n",
    "def clone_populationj8(best_chromosome, population_size):\n",
    "    \"\"\"Creates a new population by cloning the best chromosome.\"\"\"\n",
    "    return [best_chromosome] * population_size\n",
    "\n",
    "\n",
    "def mutatej8(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_allj8(population, mutation_rate, alphabet):\n",
    "    \"\"\"Mutates all chromosomes in the population.\"\"\"\n",
    "    mutated_population = []\n",
    "    for chromosome in population:\n",
    "        mutated_chromosome = mutatej8(chromosome, mutation_rate, alphabet)\n",
    "        mutated_population.append(mutated_chromosome)\n",
    "    return mutated_population\n",
    "\n",
    "def crossoverj8(parent1, parent2, length_of_chromosomes, recombination_rate):\n",
    "    \"\"\"Performs crossover between two parent chromosomes.\"\"\"\n",
    "    if random.random() < recombination_rate:\n",
    "        crossover_point = random.randint(0, length_of_chromosomes)\n",
    "        return parent1[:crossover_point] + parent2[crossover_point:]\n",
    "    else:\n",
    "        return parent1\n",
    "\n",
    "def crossover_allj8(population, length_of_chromosomes, 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 = crossoverj8(parent1, parent2, length_of_chromosomes, recombination_rate)\n",
    "        recombinant_population.append(child)\n",
    "    return recombinant_population\n",
    "\n",
    "\n",
    "\n",
    "def run_one_generationj8(population, xArray, yArray, mutation_rate, recombination_rate, alphabet):\n",
    "    \"\"\"Runs one generation of the genetic algorithm.\"\"\"\n",
    "    # Calculate fitness scores for the current population\n",
    "    smallest_error, best_chromosome  = select_the_least_errorj8(population, xArray, yArray)\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_populationj8:\n",
    "        new_population = clone_populationj8(best_chromosome, population_size)\n",
    "    if include_mutate_allj8:\n",
    "        new_population = mutate_allj8(new_population, mutation_rate, alphabet)\n",
    "    if include_crossover_allj8:\n",
    "        new_population = crossover_allj8(new_population, length_of_chromosomes, recombination_rate)\n",
    "    return smallest_error, best_chromosome, new_population\n",
    "\n",
    "\n",
    "\n",
    "def plot_functionj8(g_values, 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 draw_perfect_polynomialj8(coefficients, xArray, yArray):\n",
    "    \"\"\"Draws the original data points, finds and draws the \n",
    "    regression polynomial defined by the coefficients.\n",
    "    By the AI of Visual Studio Code, based on the draw_points_and_polynomialj5 function.\"\"\"\n",
    "    \n",
    "    a_0, a_1, a_2, a_3, a_4, a5 = coefficients\n",
    "    x_new = np.linspace(-2,3, 100) # Generate 100 points between -2 and 3for a smooth curve\n",
    "    # Plot polynomial defined by the coefficients\n",
    "    plt.scatter(xArray, yArray, label='Data Points')\n",
    "    plt.xlabel('x')\n",
    "    plt.ylabel('y')\n",
    "    plt.plot(x_new, a_0 + a_1 * np.array(x_new) + a_2 * np.array(x_new)**2 + a_3 * np.array(x_new)**3 + a_4 * np.array(x_new)**4 + a5 * np.array(x_new)**5, label=f'Perfect polynomial: y = {a_0:.2f} + {a_1:.2f}x + {a_2:.2f}x^2 + {a_3:.2f}x^3 + {a_4:.2f}x^4 + {a5:.2f}x^5', color='red')\n",
    "    plt.title(' Data Points, and Polynomial defined by the perfect chromosome')\n",
    "    plt.legend()\n",
    "    plt.show()\n",
    "\n",
    "\n",
    "def draw_polynomialsj8( xArray, yArray):\n",
    "    # Perform polynomial least squares regression\n",
    "    # Fit a polynomial of degree 5 (numpy polynomial regression)\n",
    "    # Arrays to np.arrays\n",
    "    # xNumpyArray = np.array(xArray)\n",
    "    # yNumpyArray = np.array(yArray)\n",
    "    print(f\"Points that must be regressed: {list(zip(xArray, yArray))}\")\n",
    "    #print type of xNumpyArray and yNumpyArray\n",
    "    print(f\"type of xNumpyArray: {type(xArray)}, type of yNumpyArray: {type(yArray)}\")\n",
    "    coefficients = draw_points_and_polynomialj8(xArray, yArray)\n",
    "    print(f\"Numpy fitted polynomial coefficients: {coefficients[0]}, {coefficients[1]}, {coefficients[2]}, {coefficients[3]}, {coefficients[4]}, {coefficients[5]}\")\n",
    "    perfect_chromosome = encodeFullCromosomej8(coefficients[0], coefficients[1], coefficients[2], coefficients[3], coefficients[4], coefficients[5], length_of_chromosomes)\n",
    "    print(f\"Perfect chromosome: {perfect_chromosome}\")\n",
    "    print(f\"Decoded perfect chromosome: {decodeFullCromosomej8(perfect_chromosome, length_of_chromosomes)}\")\n",
    "    print(f\"Error of perfect chromosome: {calculate_errorj8(perfect_chromosome, xArray, yArray)}\")\n",
    "    draw_perfect_polynomialj8(coefficients, xArray, yArray)\n",
    "    print\n",
    "    return coefficients\n",
    "\n",
    "\n",
    "def taskj8( xArray, yArray, mutation_rate, recombination_rate, alphabet, length_of_chromosomes):\n",
    "\n",
    "    # First, we draw the original data points, find and draw the regression polynomial defined by the points.\n",
    "    # We will use this polynomial to create a perfect chromosome, that is decoded into a polynomial that is next drawn.\n",
    "    # Test: the two polynomials should be the same, and the error of the perfect chromosome should be zero (or very close to zero due to rounding errors).\n",
    "    coefficients = draw_polynomialsj8( xArray, yArray)\n",
    "    # Population of chromosomes at random, each chromosome encodes for the coefficients of a polynomial of fifth degree.\n",
    "    #population = create_populationj8(population_size, length_of_chromosomes, alphabet)\n",
    "\n",
    "    # Create a perfect population with the chromosome that encodes for the coefficients of the polynomial that best fits the data points.\n",
    "    population = createPerfectPopulationj8(coefficients[0], coefficients[1], coefficients[2], coefficients[3], coefficients[4], coefficients[5], length_of_chromosomes, population_size)\n",
    "\n",
    "    # print(population)\n",
    "    #population = create_populationj8(population_size, length_of_chromosomes, alphabet)\n",
    "    # print(population)\n",
    "    generation = 0\n",
    "    best_chromosome = ''\n",
    "    best_fitness = 0\n",
    "    start_time = time.time()\n",
    "    smallest_error_history = [] # List to store best fitness of each generation\n",
    "    if print_best_fitness:\n",
    "        print(\"Generation, best_chromosome and best_fitness\")\n",
    "    while generation < number_of_generations:\n",
    "        generation += 1\n",
    "        smallest_error, best_chromosome, population = run_one_generationj8(population, xArray,yArray, mutation_rate, recombination_rate, alphabet)\n",
    "        if print_best_fitness:\n",
    "            print(f\" {generation}  {best_chromosome} {smallest_error}\")\n",
    "        smallest_error_history.append(smallest_error)\n",
    "    # print(f\"\\nTarget sequence matched in generation {generation}\")\n",
    "    # print(f\"Final chromosome: {best_chromosome}\")\n",
    "    totalCost = population_size * generation\n",
    "    \n",
    "    return  best_chromosome, totalCost, smallest_error_history\n",
    "\n",
    "def main(xArray, yArray, mutation_rate, recombination_rate, alphabet, length_of_chromosomes):\n",
    "    print_parametersj8()\n",
    "    print(\"Total cost = population size * number of generations\")\n",
    "    best_chromosome, totalCost, smallest_error_history = taskj8(xArray, yArray, mutation_rate, recombination_rate, alphabet, length_of_chromosomes)\n",
    "    final_error = smallest_error_history[-1]\n",
    "    print(f\" The final best chromosome is {best_chromosome}\" )\n",
    "    coefficients = decodeFullCromosomej8(best_chromosome, length_of_chromosomes)\n",
    "    print(f\" Encoded coefficients: Intercept {coefficients[0]}, slope {coefficients[1]}, quadratic {coefficients[2]}, cubic {coefficients[3]}, quartic {coefficients[4]}, quintic {coefficients[5]}\")\n",
    "    print(f\" Total cost =  {totalCost} chromosomes\")\n",
    "    print(f\" Final error =  {final_error} \")\n",
    "\n",
    "    # Plot the fitness history    \n",
    "    g_values = list(range(1, len(smallest_error_history) + 1))\n",
    "    plot_functionj8(g_values, smallest_error_history, xlabel='Generation', ylabel='SmallestError', title='Smallest Error Over Generations')\n",
    "\n",
    "\n",
    "    # Perform polynomial regression\n",
    "    # Fit a polynomial of degree 5 (polynomial regression)\n",
    "    p_fitted = Polynomial.fit(xArray, yArray, deg=5)\n",
    "    a_0, a_1, a_2, a_3, a_4, a5 = p_fitted.convert().coef\n",
    "    print(f\"Polynomial regression coefficients: Intercept {a_0}, slope {a_1}, quadratic {a_2}, cubic {a_3}, quartic {a_4}, quintic {a5}\")\n",
    "    # Create the regression graph\n",
    "    x_new = np.linspace(-2,3, 100) # Generate 100 points between -2 and 3 for a smooth curve\n",
    "    y_new = p_fitted(x_new)\n",
    "\n",
    "    # The best chromosome encodes for the coefficients of the polynomial that best fits the data points\"\n",
    "    b_0, b_1, b_2, b_3, b_4, b5 = decodeFullCromosomej8(best_chromosome, length_of_chromosomes)\n",
    "    print(f\"Encoded coefficients: Intercept {b_0}, slope {b_1}, quadratic {b_2}, cubic {b_3}, quartic {b_4}, quintic {b5}\")\n",
    "    # Calculate the predicted y value based on the coefficients of the polynomial\n",
    "    our_polynomial = b_0 + b_1 * np.array(x_new ) + b_2 * np.array(x_new )**2 + b_3 * np.array(x_new )**3 + b_4 * np.array(x_new )**4 + b5 * np.array(x_new )**5\n",
    "    \n",
    "\n",
    "    # Plot  our polynomial\n",
    "    plt.figure(figsize=(10, 6))\n",
    "    plt.scatter(xArray, yArray, label='Observed Data')\n",
    "    #plt.plot(xArray, regression_polynomial, color='red', label=f'Polynomial Regression: y = {a_0:.2f} + {a_1:.2f}x + {a_2:.2f}x^2 + {a_3:.2f}x^3 + {a_4:.2f}x^4 + {a5:.2f}x^5')\n",
    "    plt.plot(x_new,        our_polynomial, color='green', label=f'Our best evolved polynomial: y = {b_0:.2f} + {b_1:.2f}x + {b_2:.2f}x^2 + {b_3:.2f}x^3 + {b_4:.2f}x^4 + {b5:.2f}x^5')\n",
    "    plt.xlabel('Independent variable (x)')\n",
    "    plt.ylabel('Dependent variable (y)')\n",
    "    plt.title('la Evoluciónary Regression minimizes the error of the line with respect to the data points')\n",
    "    plt.legend()\n",
    "    plt.grid(True)\n",
    "    plt.show()\n",
    "\n",
    "\n",
    "    end_time = time.time()\n",
    "    # Calculate the difference in seconds\n",
    "    elapsed_time = end_time - start_time\n",
    "    elapsed_time = timedelta(seconds=elapsed_time)\n",
    "    print(f\"Elapsed time: {elapsed_time}\")\n",
    "    #return best_chromosome, totalCost, best_fitness_history\n",
    "\n",
    "# Call the main function with the defined parameters\n",
    "main(xArray, yArray, mutation_rate, recombination_rate, alphabet, length_of_chromosomes)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "f6a6bc18",
   "metadata": {},
   "source": [
    "\n",
    "\n",
    "*Nuestras observaciones. * \n",
    "\n",
    "- El procedimiento de codificación y decodificación son perfectos porque la solución matemática coincide con la que se da por la decodificación de su codificación. \n",
    "- La solución matemática, cuyos coeficientes se han recortado a seis decimales causa un pequeño error, del orden de 1E-9. La población de cromosomas que representa esa solución evoluciona, y el error se reduce unas 5 veces. Este comportamiento muestra claramente que la meseta observada cerca de 12 no es el estado estacionario final de la Evolución. Además, la Evolución puede mantener la perfección, de modo que el nivel dado por la dinámica es la perfección misma. Entonces, ¿por qué estamos atrapados en una solución con un error de casi 12? Podría ser un óptimo local de la función a optimizar, o también podría ser el comportamiento normal de la Evolución cerca de la perfección: es barato obtener una aproximación pero muy caro conseguir una buena y extremadamente caro alcanzar la perfección. Nos inclinamos a pensar que estamos tratando con un óptimo local porque esa barrera se ha encontrado en muchos experimentos, con algunas pocas excepciones. El error final de 12 no es pequeño. Es enorme porque el polinomio asociado no pasa por ninguno de los cinco puntos y la silueta del grafo está lejos de la de la solución matemática. \n",
    "\n",
    "\n",
    "\n",
    "# S.O.S.\n",
    "\n",
    "Hemos trabajado mucho para terminar con soluciones aproximadas que podrían ser peores que las hechas por un niño. La frustración se debe al hecho de que nuestras aproximaciones no cruzan ninguno de los seis puntos dados, y los números de máximos y mínimos no coinciden con el del polinomio dado por las matemáticas, es decir, por la regresión polinomial. \n",
    "\n",
    "Necesitamos ayuda.\n",
    "\n",
    "Para ayudarnos a nosotros mismos, probemos dos estrategias: mejorar los detalles y probar nuevos caminos. Nuestro propósito es mostrar cómo convertir ideas simples en código, es decir, en programas de investigación. Pero la experimentación es en cualquier caso extremadamente limitada.  \n",
    "\n",
    "## Mejorando los detalles\n",
    "\n",
    "El siguiente programa pretende mejorar un código anterior que no funcionaba, pero que merece una nueva oportunidad. \n",
    "\n",
    "**Ejemplo.** Tenemos dos cambios:\n",
    "\n",
    "1. Hemos trabajado con números de la forma $ \\pm 12,34$. Ahora, trabajaremos con números de la forma $ \\pm 1,234567$. Usar más decimales aumenta el gradualismo y así hace posible una Evolución más rápida. No estamos usando cifras en el orden de diez con el objetivo de facilitar la Evolución. Es una ayuda.\n",
    "2. La función de error era la suma sobre todos los puntos del cuadrado de la diferencia vertical entre el punto y el polinomio codificado por el cromosoma dado. La función cuadrada es casi costante cerca de cero, y esto puede hacer que el concepto de elegir lo mejor carezca de significado. En lugar de las distancias cuadradas, usamos las distancias. Esta no es plana cerca de cero, y por lo tanto, encontrar la perfección podría ser más fácil. El código sigue:\n",
    "\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "d52669ba",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Lab: Evolution finds the polynomial of minimal error\n",
      "Purpose: Use a Genetic Algorithm (MAX = selection of the fittest, mutation and recombination) to find the coefficients of a polynomial that best fits a set of points.\n",
      "Hint to be tested: consider only numbers of the form -3.244025 with a sign that could be positive or negative, and a decimal point in the second place of the encoding chromosome.\n",
      "Date of Experiment  = 2026-04-25 07:58:53.978847\n",
      "number_of_generations = 10000\n",
      "length_of_chromosomes = 8\n",
      "alphabet =  0123456789\n",
      "Points = [(-2, 5), (-1, 1), (0, 4), (1, 0), (2, 6), (3, 3)]\n",
      "population_size = 12800\n",
      "include_clone_populationj9 = True\n",
      "include_mutate_allj9 = True\n",
      "include_crossover_allj9 = False\n",
      "mutation_rate = 0.1\n",
      "print_best_fitness = False\n",
      "Total cost = population size * number of generations\n",
      " The best chromosome is 840600007279994715000016629775984132999270558784\n",
      " Encoded coefficientes: (4.06, -2.799947, -5.000016, 2.977598, 1.329992, -0.558784) \n",
      " Total cost =  128000000 chromosomes\n",
      " Final error =  0.618131000000024 \n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Decoded coefficients: Intercept 4.06, slope -2.799947, quadratic -5.000016, cubic 2.977598, quartic 1.329992, quintic -0.558784\n",
      "Polynomial regression coefficients: Intercept 4.0, slope -2.983333333333327, quadratic -4.791666666666659, cubic 3.041666666666663, quartic 1.2916666666666643, quintic -0.5583333333333323\n",
      "Encoded coefficients: Intercept 4.06, slope -2.799947, quadratic -5.000016, cubic 2.977598, quartic 1.329992, quintic -0.558784\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"
    },
    {
     "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": [
      "Elapsed time: 0:29:13.677371\n"
     ]
    }
   ],
   "source": [
    "# Program PolynomialMinimalEncoding2.py\n",
    "# This program uses a genetic algorithm to find the polynomial \n",
    "# of fifth degree that best fits a set of 6 points.\n",
    "# The coefficients are represented by a chromosome, \n",
    "# which is a string of digits.\n",
    "# The decoding function must divide the chromosome into parts, \n",
    "# and decode each one apart as one coefficient.\n",
    "# We consider numbers of the form -3.244025\n",
    "# with a sign that could be positive or negative, \n",
    "# and a decimal point in the second place of the encoding chromosome.\n",
    "# The error of a chromosome is the sum of the vertical distances \n",
    "# of the points to the polynomial it encodes.\n",
    "# The Genetic algorithm must minimize the error, \n",
    "# (which is equivalent to maximizing the fitness).\n",
    "# Developed with the assistance of the AI of Visual Studio Code.\n",
    "# An old version of a GA developed with the help of Gemini was reused and updated.\n",
    "\n",
    "\n",
    "from datetime import datetime, timedelta\n",
    "import datetime\n",
    "import time\n",
    "import random\n",
    "import numpy as np\n",
    "from numpy.polynomial import Polynomial\n",
    "import matplotlib.pyplot as plt # Import matplotlib for plotting\n",
    "\n",
    "\n",
    "start_time = time.time() # Record the start time\n",
    "\n",
    "#Task to be done\n",
    "number_of_generations = 10000\n",
    "\n",
    "xArray =  [-2, -1, 0, 1, 2, 3]\n",
    "yArray =  [5,   1, 4, 0, 6, 3]\n",
    "\n",
    "alphabet = '0123456789'\n",
    "# Chromosome encoding for one of 6 coefficients, \n",
    "# each one with a length of 5 chars.\n",
    "# Encoding number as -93.24 with a sign and a decimal point.\n",
    "length_of_chromosomes = 8\n",
    "population_size = 12800\n",
    "# Include cloning of the fittest\n",
    "include_clone_populationj9 = True\n",
    "# Include mutation\n",
    "include_mutate_allj9 = True\n",
    "# Include recombination\n",
    "include_crossover_allj9 = False\n",
    "mutation_rate = 0.1\n",
    "recombination_rate = 0.0\n",
    "# Size of the sampled groups from which the best \n",
    "# is chosen as a parent for the next generation.\n",
    "tournament_size = 5\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",
    "def print_parametersj9():\n",
    "    print(f\"Lab: la Evolución finds the polynomial of minimal error\")\n",
    "    print(f\"Purpose: Use a Genetic Algorithm (MAX = selection of the fittest, mutation and recombination) to find the coefficients of a polynomial that best fits a set of points.\")\n",
    "    print(\"Hint to be tested: consider only numbers of the form -3.244025 with a sign that could be positive or negative, and a decimal point in the second place of the encoding chromosome.\")\n",
    "    print(f\"Date of Experiment  = {datetime.datetime.now()}\")\n",
    "    print(f\"number_of_generations = {number_of_generations}\")\n",
    "    print(f\"length_of_chromosomes = {length_of_chromosomes}\")\n",
    "    print(f\"alphabet =  {alphabet}\")\n",
    "    print(f\"Points = {list(zip(xArray, yArray))}\")\n",
    "    print(f\"population_size = {population_size}\")\n",
    "    print(f\"include_clone_populationj9 = {include_clone_populationj9}\")\n",
    "    print(f\"include_mutate_allj9 = {include_mutate_allj9}\")\n",
    "    print(f\"include_crossover_allj9 = {include_crossover_allj9}\")\n",
    "    if include_mutate_allj9:\n",
    "        print(f\"mutation_rate = {mutation_rate}\")\n",
    "    if include_crossover_allj9:\n",
    "        print(f\"recombination_rate = {recombination_rate}\")\n",
    "    if include_clone_populationj9:\n",
    "        print(f\"print_best_fitness = {print_best_fitness}\")\n",
    "\n",
    "def draw_points_and_polynomialj9(xNumpyArray, yNumpyArray):\n",
    "    \"\"\"Draws the original data points, finds and draws the \n",
    "    regression polynomial defined by the coefficients.\"\"\"\n",
    "    \n",
    "    # 2. Fit a 5th-degree (quintic) polynomial\n",
    "    # .fit() returns a Polynomial instance\n",
    "    p_fitted = Polynomial.fit(xNumpyArray, yNumpyArray, deg=5)\n",
    "\n",
    "    # 3. Predict values for visualization\n",
    "    x_new = np.linspace(-2,3, 100) # Generate 100 points between 0 and 6 for a smooth curve\n",
    "    y_new = p_fitted(x_new)\n",
    "    b_0, b_1, b_2, b_3, b_4, b5 = p_fitted.coef\n",
    "\n",
    "    # 4. Plot results\n",
    "    plt.scatter(xNumpyArray, yNumpyArray, label='Data Points')\n",
    "    plt.xlabel('x')\n",
    "    plt.ylabel('y')\n",
    "    plt.plot(x_new, y_new, label=f'Quintic Fit: y = {b_0:.2f} + {b_1:.2f}x + {b_2:.2f}x^2 + {b_3:.2f}x^3 + {b_4:.2f}x^4 + {b5:.2f}x^5', color='green')\n",
    "    plt.title(' Data Points and Quintic Fit by numpy.polynomial.Polynomial.fit()')\n",
    "    plt.legend()\n",
    "    plt.show()\n",
    "    return p_fitted.coef\n",
    "\n",
    "\n",
    "\n",
    "def create_populationj9(population_size, length_of_chromosomes, alphabet):\n",
    "    \"\"\"Creates a new population with random chromosomes.\"\"\"\n",
    "    # print(\"create_populationj9(population_size, target_sequence, alphabet)\")\n",
    "    population = []\n",
    "    for _ in range(population_size):\n",
    "        random_string1 = ''.join(random.choice(alphabet) for _ in range(length_of_chromosomes))\n",
    "        random_string2 = ''.join(random.choice(alphabet) for _ in range(length_of_chromosomes))\n",
    "        random_string3 = ''.join(random.choice(alphabet) for _ in range(length_of_chromosomes))\n",
    "        random_string4 = ''.join(random.choice(alphabet) for _ in range(length_of_chromosomes))\n",
    "        random_string5 = ''.join(random.choice(alphabet) for _ in range(length_of_chromosomes))\n",
    "        random_string6 = ''.join(random.choice(alphabet) for _ in range(length_of_chromosomes))\n",
    "        random_string = random_string1 + random_string2 + random_string3 + random_string4 + random_string5 + random_string6\n",
    "        population.append(random_string)\n",
    "    # print(\"initial population\")\n",
    "    # print(population)\n",
    "    return population\n",
    "\n",
    "# Decode a part of the chromosome into a coefficient of the polynomial.\n",
    "def decoderOldj9(s):\n",
    "    ''' The input is a number as string, outputs the number as a float. \n",
    "        We consider numbers of the form 93.24 with a sign that could be positive or negative,\n",
    "    '''\n",
    "    l = len(s) \n",
    "    # The first char encodes for the sign, \n",
    "    sign = 1\n",
    "    if  float(s[0]) % 2 == 1:\n",
    "        sign = -1\n",
    "    # The remaining chars encode for the number itself, \n",
    "    # without the decimal point nor sign.\n",
    "    sn = s[1:l]\n",
    "    # The point is inserted after the second char, so that we have numbers of the form 93.24\n",
    "    sn = sn[:2] + \".\" + sn[2:]\n",
    "    # Convert the string to a number\n",
    "    n = float(sn)\n",
    "    return sign * n\n",
    "\n",
    "# Decode a part of the chromosome into a coefficient of the polynomial.\n",
    "def decoderj9(s):\n",
    "    ''' The input is a number as string, outputs the number as a float. \n",
    "        We consider numbers of the form 93.24 with a sign that could be positive or negative,\n",
    "    '''\n",
    "    l = len(s) \n",
    "    # The first char encodes for the sign, \n",
    "    sign = 1\n",
    "    if  float(s[0]) % 2 == 1:\n",
    "        sign = -1\n",
    "    # The remaining chars encode for the number itself, \n",
    "    # without the decimal point nor sign.\n",
    "    sn = s[1:l]\n",
    "    # The point is inserted after the first char, so that we have numbers of the form -3.24\n",
    "    sn = sn[:1] + \".\" + sn[1:]\n",
    "    # Convert the string to a number\n",
    "    n = float(sn)\n",
    "    return sign * n\n",
    "\n",
    "\n",
    "def decodeFullCromosomej9(chromosome, length_of_chromosomes):\n",
    "    \"\"\"Decodes the full chromosome into the coefficients of the polynomial.\"\"\"\n",
    "    \"\"\"The chromosome is divided into 5 parts, \n",
    "        each one encoding for a coefficient of the polynomial.\"\"\"\n",
    "    chro0 = chromosome[0:length_of_chromosomes]\n",
    "    chro1 = chromosome[length_of_chromosomes:2*length_of_chromosomes]\n",
    "    chro2 = chromosome[2*length_of_chromosomes:3*length_of_chromosomes]\n",
    "    chro3 = chromosome[3*length_of_chromosomes:4*length_of_chromosomes]\n",
    "    chro4 = chromosome[4*length_of_chromosomes:5*length_of_chromosomes]\n",
    "    chro5 = chromosome[5*length_of_chromosomes:6*length_of_chromosomes]\n",
    "    a_0 = decoderj9(chro0)\n",
    "    a_1 = decoderj9(chro1)\n",
    "    a_2 = decoderj9(chro2)\n",
    "    a_3 = decoderj9(chro3)\n",
    "    a_4 = decoderj9(chro4)\n",
    "    a_5 = decoderj9(chro5)\n",
    "    # print(f\"Chromosome: {chromosome}\")\n",
    "    # print(f\"Coefficients: Intercept {a_0}, slope {a_1}, quadratic {a_2}, cubic {a_3}, quartic {a_4}, quintic {a_5}\")\n",
    "    # print()\n",
    "    return a_0, a_1, a_2, a_3, a_4, a_5\n",
    "\n",
    "\n",
    "\n",
    "def calculate_errorj9(chromosome, xArray, yArray, length_of_chromosomes):\n",
    "    \"\"\"Calculates the error of a chromosome.\n",
    "        A chromosome encodes for the coefficients of a polynomial of fith degree.\n",
    "        The error of a chromosome is the sum of \n",
    "        the vertical distances of the points to the polynomial it encodes.\n",
    "    \"\"\"\n",
    "    #  print(\"\\n calculate_errorj9(chromosome, xArray, yArray)\")\n",
    "    a_0, a_1, a_2, a_3, a_4, a_5 = decodeFullCromosomej9(chromosome, length_of_chromosomes)  \n",
    "    error = 0\n",
    "    for i in range(len(xArray)):\n",
    "        x = xArray[i]\n",
    "        y = yArray[i]\n",
    "        # Calculate the predicted y value based on the coefficients of the polynomial\n",
    "        predicted_y = a_0 + a_1 * x + a_2 * x**2 + a_3 * x**3 + a_4 * x**4 + a_5 * x**5\n",
    "        # Calculate the error as the quadratic difference \n",
    "        # between predicted and y value\n",
    "        # error += (predicted_y - y)**2\n",
    "        # Calculate the error as the distance between predicted and y value\n",
    "        error += abs(predicted_y - y)\n",
    "    return error\n",
    "\n",
    "def calculate_all_errorsj9(population, xArray, yArray, length_of_chromosomes):\n",
    "    # print(\"\\n*calculate_all_errorsj9(population, target_sequence)\")\n",
    "    \"\"\"Calculates the error of all chromosomes in the population.\"\"\"\n",
    "    errors = [calculate_errorj9(chromosome, xArray, yArray, length_of_chromosomes) for chromosome in population]\n",
    "    # print(\"errors: \", errors)\n",
    "    return errors\n",
    "\n",
    "def select_the_least_errorj9(population, xArray, yArray, length_of_chromosomes):\n",
    "    \"\"\"Selects the best chromosome with minimal error for reproduction.\"\"\"\n",
    "    errors = calculate_all_errorsj9(population, xArray, yArray, length_of_chromosomes)\n",
    "    smallest_error = min(errors)\n",
    "    best_chromosome_index = errors.index(smallest_error)\n",
    "    best_chromosome = population[best_chromosome_index]\n",
    "    # print(\"\\n*select_the_least_errorj9(population)\")\n",
    "    # print(\"smallest_error = \", smallest_error)\n",
    "    # print(\"The chro = \", best_chromosome )\n",
    "    return smallest_error, best_chromosome\n",
    "\n",
    "def clone_populationj9(best_chromosome, population_size):\n",
    "    \"\"\"Creates a new population by cloning the best chromosome.\"\"\"\n",
    "    return [best_chromosome] * population_size\n",
    "\n",
    "\n",
    "def mutatej9(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_allj9(population, mutation_rate, alphabet):\n",
    "    \"\"\"Mutates all chromosomes in the population.\"\"\"\n",
    "    mutated_population = []\n",
    "    for chromosome in population:\n",
    "        mutated_chromosome = mutatej9(chromosome, mutation_rate, alphabet)\n",
    "        mutated_population.append(mutated_chromosome)\n",
    "    return mutated_population\n",
    "\n",
    "def crossoverj9(parent1, parent2, length_of_chromosomes, recombination_rate):\n",
    "    \"\"\"Performs crossover between two parent chromosomes.\"\"\"\n",
    "    if random.random() < recombination_rate:\n",
    "        crossover_point = random.randint(0, length_of_chromosomes)\n",
    "        return parent1[:crossover_point] + parent2[crossover_point:]\n",
    "    else:\n",
    "        return parent1\n",
    "\n",
    "def crossover_allj9(population, length_of_chromosomes, 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 = crossoverj9(parent1, parent2, length_of_chromosomes, recombination_rate)\n",
    "        recombinant_population.append(child)\n",
    "    return recombinant_population\n",
    "\n",
    "\n",
    "\n",
    "def run_one_generationj9(population, xArray, yArray, mutation_rate, recombination_rate, alphabet, length_of_chromosomes):\n",
    "    \"\"\"Runs one generation of the genetic algorithm.\"\"\"\n",
    "    # Calculate fitness scores for the current population\n",
    "    smallest_error, best_chromosome  = select_the_least_errorj9(population, xArray, yArray, length_of_chromosomes)\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_populationj9:\n",
    "        new_population = clone_populationj9(best_chromosome, population_size)\n",
    "    if include_mutate_allj9:\n",
    "        new_population = mutate_allj9(new_population, mutation_rate, alphabet)\n",
    "    if include_crossover_allj9:\n",
    "        new_population = crossover_allj9(new_population, length_of_chromosomes, recombination_rate)\n",
    "    return smallest_error, best_chromosome, new_population\n",
    "\n",
    "\n",
    "\n",
    "def plot_functionj9(g_values, 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 taskj9( xArray, yArray, mutation_rate, recombination_rate, alphabet,  length_of_chromosomes):\n",
    "    population = create_populationj9(population_size, length_of_chromosomes, alphabet)\n",
    "    # print(population)\n",
    "    generation = 0\n",
    "    best_chromosome = ''\n",
    "    best_fitness = 0\n",
    "    start_time = time.time()\n",
    "    smallest_error_history = [] # List to store best fitness of each generation\n",
    "    if print_best_fitness:\n",
    "        print(\"Generation, best_chromosome and best_fitness\")\n",
    "    while generation < number_of_generations:\n",
    "        generation += 1\n",
    "        smallest_error, best_chromosome, population = run_one_generationj9(population, xArray,yArray, mutation_rate, recombination_rate, alphabet, length_of_chromosomes)\n",
    "        if print_best_fitness:\n",
    "            print(f\" {generation}  {best_chromosome} {smallest_error}\")\n",
    "        smallest_error_history.append(smallest_error)\n",
    "    # print(f\"\\nTarget sequence matched in generation {generation}\")\n",
    "    # print(f\"Final chromosome: {best_chromosome}\")\n",
    "    totalCost = population_size * generation\n",
    "    return  best_chromosome, totalCost, smallest_error_history\n",
    "\n",
    "def mainj9(xArray, yArray, mutation_rate, recombination_rate, alphabet, length_of_chromosomes):\n",
    "    print_parametersj9()\n",
    "    print(\"Total cost = population size * number of generations\")\n",
    "    best_chromosome, totalCost, smallest_error_history = taskj9(xArray, yArray, mutation_rate, recombination_rate, alphabet, length_of_chromosomes)\n",
    "    final_error = smallest_error_history[-1]\n",
    "    print(f\" The best chromosome is {best_chromosome}\" )\n",
    "    coefficients = decodeFullCromosomej9(best_chromosome, length_of_chromosomes)\n",
    "    print(f\" Encoded coefficientes: {coefficients} \" )\n",
    "    print(f\" Total cost =  {totalCost} chromosomes\")\n",
    "    print(f\" Final error =  {final_error} \")\n",
    "\n",
    "    # Plot the fitness history    \n",
    "    g_values = list(range(1, len(smallest_error_history) + 1))\n",
    "    plot_functionj9(g_values, smallest_error_history, xlabel='Generation', ylabel='SmallestError', title='Smallest Error Over Generations')\n",
    "    # The best chromosome encodes for the coefficients of the polynomial that best fits the data points\"\n",
    "    b_0, b_1, b_2, b_3, b_4, b5 = decodeFullCromosomej9(best_chromosome, length_of_chromosomes)\n",
    "    print(f\"Decoded coefficients: Intercept {b_0}, slope {b_1}, quadratic {b_2}, cubic {b_3}, quartic {b_4}, quintic {b5}\")\n",
    "    # Calculate the predicted y value based on the coefficients of the polynomial\n",
    "    our_polynomial = b_0 + b_1 * np.array(xArray) + b_2 * np.array(xArray)**2 + b_3 * np.array(xArray)**3 + b_4 * np.array(xArray)**4 + b5 * np.array(xArray)**5\n",
    "    \n",
    "\n",
    "    # Perform polynomial regression\n",
    "    # Fit a polynomial of degree 5 (polynomial regression)\n",
    "    p_fitted = Polynomial.fit(xArray, yArray, deg=5)\n",
    "    a_0, a_1, a_2, a_3, a_4, a5 = p_fitted.convert().coef\n",
    "    print(f\"Polynomial regression coefficients: Intercept {a_0}, slope {a_1}, quadratic {a_2}, cubic {a_3}, quartic {a_4}, quintic {a5}\")\n",
    "    # Create the regression graph\n",
    "    x_new = np.linspace(-2,3, 100) # Generate 100 points between -2 and 3 for a smooth curve\n",
    "    y_new = p_fitted(x_new)\n",
    "\n",
    "    # The best chromosome encodes for the coefficients of the polynomial that best fits the data points\"\n",
    "    b_0, b_1, b_2, b_3, b_4, b5 = decodeFullCromosomej9(best_chromosome, length_of_chromosomes)\n",
    "    print(f\"Encoded coefficients: Intercept {b_0}, slope {b_1}, quadratic {b_2}, cubic {b_3}, quartic {b_4}, quintic {b5}\")\n",
    "    # Calculate the predicted y value based on the coefficients of the polynomial\n",
    "    our_polynomial = b_0 + b_1 * np.array(x_new ) + b_2 * np.array(x_new )**2 + b_3 * np.array(x_new )**3 + b_4 * np.array(x_new )**4 + b5 * np.array(x_new )**5\n",
    "    \n",
    "\n",
    "\n",
    "    # Plot the original data, the regression polynomial, and our polynomial\n",
    "    plt.figure(figsize=(10, 6))\n",
    "    plt.scatter(xArray, yArray, label='Observed Data')\n",
    "    plt.plot(x_new, y_new, color='red', label=f'Polynomial Regression: y = {a_0:.2f} + {a_1:.2f}x + {a_2:.2f}x^2 + {a_3:.2f}x^3 + {a_4:.2f}x^4 + {a5:.2f}x^5')\n",
    "    plt.plot(x_new,        our_polynomial, color='green', label=f'Our polynomial: y = {b_0:.2f} + {b_1:.2f}x + {b_2:.2f}x^2 + {b_3:.2f}x^3 + {b_4:.2f}x^4 + {b5:.2f}x^5')\n",
    "    plt.xlabel('Independent variable (x)')\n",
    "    plt.ylabel('Dependent variable (y)')\n",
    "    plt.title('Linear Regression and la Evolución minimize the error of the line with respect to the data points')\n",
    "    plt.legend()\n",
    "    plt.grid(True)\n",
    "    plt.show()\n",
    "\n",
    "    # Plot the original data and the regression polynomial\n",
    "    plt.figure(figsize=(10, 6))\n",
    "    plt.scatter(xArray, yArray, label='Observed Data')\n",
    "    plt.plot(x_new, y_new, color='red', label=f'Polynomial Regression: y = {a_0:.2f} + {a_1:.2f}x + {a_2:.2f}x^2 + {a_3:.2f}x^3 + {a_4:.2f}x^4 + {a5:.2f}x^5')\n",
    "    plt.xlabel('Independent variable (x)')\n",
    "    plt.ylabel('Dependent variable (y)')\n",
    "    plt.title('Linear Regression minimizes the error of the line with respect to the data points')\n",
    "    plt.legend()\n",
    "    plt.grid(True)\n",
    "    plt.show()\n",
    "\n",
    "    # Plot  our polynomial\n",
    "    plt.figure(figsize=(10, 6))\n",
    "    plt.scatter(xArray, yArray, label='Observed Data')\n",
    "    #plt.plot(xArray, regression_polynomial, color='red', label=f'Polynomial Regression: y = {a_0:.2f} + {a_1:.2f}x + {a_2:.2f}x^2 + {a_3:.2f}x^3 + {a_4:.2f}x^4 + {a5:.2f}x^5')\n",
    "    plt.plot(x_new,        our_polynomial, color='green', label=f'Our polynomial: y = {b_0:.2f} + {b_1:.2f}x + {b_2:.2f}x^2 + {b_3:.2f}x^3 + {b_4:.2f}x^4 + {b5:.2f}x^5')\n",
    "    plt.xlabel('Independent variable (x)')\n",
    "    plt.ylabel('Dependent variable (y)')\n",
    "    plt.title('la Evoluciónary Regression minimizes the error of the line with respect to the data points')\n",
    "    plt.legend()\n",
    "    plt.grid(True)\n",
    "    plt.show()\n",
    "\n",
    "\n",
    "\n",
    "    end_time = time.time()\n",
    "    # Calculate the duration of the run in seconds\n",
    "    elapsed_time = end_time - start_time\n",
    "    elapsed_time = timedelta(seconds=elapsed_time)\n",
    "    print(f\"Elapsed time: {elapsed_time}\")\n",
    "    #return best_chromosome, totalCost, best_fitness_history\n",
    "\n",
    "# Call the main function with the defined parameters\n",
    "mainj9(xArray, yArray, mutation_rate, recombination_rate, alphabet, length_of_chromosomes)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "73ab96f5",
   "metadata": {},
   "source": [
    "**Evaluación.** Este programa es muy bueno: hemos superado la barrera de 12, y ahora, con una frecuencia relativamente alta, vemos errores de un dígito. Esto se acompaña de la agradable aparición de una silueta que se ajusta a la dada por las matemáticas, y el polinomio encontrado pasa por 3 puntos de cinco. Pero la perfección no se encuentra. ¿Es la cuasi-perfección endémica de la Evolución?\n",
    "\n",
    "**Desafío.** Experimenta con más decimales para ver el efecto en el error final. \n",
    "\n",
    "**Misterio.** Hay un problema que no sabemos cómo atacar: la codificación de los números no es gradualista, así que tiene saltos de cada medida, digamos, para pasar en base 10 del 99 al siguiente número, 100, necesitamos 3 cambios coordinados, lo cual es absurdo. Los saltos significan que la obtención de pequeños avances puede perderse en cualquier momento. El resultado es que no hay Evolución hacia la perfección. Para remediar de alguna manera nuestro fracaso, estamos obligados a usar una alta tasa de mutación, 0,1. Pero esto podría afectar la permanencia en la población de la perfección o de una solución mejorada. "
   ]
  },
  {
   "cell_type": "markdown",
   "id": "705e1775",
   "metadata": {},
   "source": [
    "## Caminos alternativos\n",
    "\n",
    "Veamos otras implementaciones de la Evolución, cuyo objetivo es conservar la variabilidad. \n",
    "\n",
    "- *El Error como probabilidad de muerte.* Los errores se normalizan y transforman en una probabilidad de muerte antes de la reproducción. Los cromosomas que sobreviven pueden reproducirse al azar. En este caso, seguimos la directiva de que la Evolución no es la selección del mejor sino la muerte del peor. O, que la Evolución es una cuestión de sobrevivir bajo el trasfondo de mutación que siempre crea variabilidad. \n",
    "- *La aptitud como probabilidad de reproducción.* La probabilidad de reproducción de cada cromosoma está determinada por su aptitud. En nuestro caso, los errores se normalizan y se transforman en probabilidades de muerte. El complemento es la probabilidad de sobrevivir y de ser clonado al azar. \n",
    "- *La aleatoriedad como una fuente directa de variabilidad* Se usa para obtener una solución plausible más allá de los callejones sin salida. Es tentador pensar que nada podría ser mejor que la pura aleatoriedad para crear variabilidad. La solución aproximada encontrada es entonces sometida a la Evolución para alcanzar cuasi-perfección, o tal vez, perfección. \n",
    "\n",
    "Implementemos cada alternativa.\n",
    "\n",
    "### El error como probabilidad de muerte\n",
    "\n",
    "Los errores significan defectos. En la naturaleza, algunos defectos hacen que los individuos sean más frágiles y propensos a morir. El mensaje es que el progreso en la Evolución no se debe a la selección del más apto sino a la muerte del peor. \n",
    "\n",
    "**Ejemplo.** En el siguiente programa, los errores se normalizan y transforman en probabilidades de muerte. Los individuos que permanecen vivos se reproducen al azar. \n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "f4d28a7e",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Lab: Evolution finds the polynomial of minimal error\n",
      "Purpose: Use a Genetic Algorithm (MAX = selection of the fittest, mutation and recombination) to find the coefficients of a polynomial that best fits a set of points.\n",
      "Hint to be tested: consider only numbers of the form -3.244025 with a sign that could be positive or negative, and a decimal point in the second place of the encoding chromosome.\n",
      "Date of Experiment  = 2026-04-24 13:14:44.248280\n",
      "number_of_generations = 1000\n",
      "length_of_chromosomes = 8\n",
      "alphabet =  0123456789\n",
      "Points = [(-2, 5), (-1, 1), (0, 4), (1, 0), (2, 6), (3, 3)]\n",
      "population_size = 200\n",
      "include_reproduce_populationj10 = True\n",
      "include_mutate_allj10 = True\n",
      "include_crossover_allj10 = True\n",
      "mutation_rate = 0.1\n",
      "recombination_rate = 0.1\n",
      "Reproduce = True\n",
      "Total cost = population size * number of generations\n",
      " The best chromosome is 142683985787880203612506639483038066176010655206\n",
      " Encoded coefficientes: (-4.268398, -7.878802, 3.612506, 3.948303, 0.66176, -0.655206) \n",
      " Total cost =  200000 chromosomes\n",
      " Final error =  49.57881300000002 \n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Decoded coefficients: Intercept -4.268398, slope -7.878802, quadratic 3.612506, cubic 3.948303, quartic 0.66176, quintic -0.655206\n",
      "Polynomial regression coefficients: Intercept 4.0, slope -2.983333333333327, quadratic -4.791666666666659, cubic 3.041666666666663, quartic 1.2916666666666643, quintic -0.5583333333333323\n",
      "Encoded coefficients: Intercept -4.268398, slope -7.878802, quadratic 3.612506, cubic 3.948303, quartic 0.66176, quintic -0.655206\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"
    },
    {
     "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": [
      "Elapsed time: 0:00:04.392720\n"
     ]
    }
   ],
   "source": [
    "# Program PolynomialErrorIsDeath.py\n",
    "# This program uses a genetic algorithm to find the polynomial \n",
    "# of fifth degree that best fits a set of 6 points.\n",
    "# The coefficients are represented by a chromosome, \n",
    "# which is a string of digits.\n",
    "# The decoding function must divide the chromosome into parts, \n",
    "# and decode each one apart as one coefficient.\n",
    "# We consider numbers of the form -3.244025\n",
    "# with a sign that could be positive or negative, \n",
    "# and a decimal point in the second place of the encoding chromosome.\n",
    "# The error of a chromosome is the sum of the vertical distances \n",
    "# of the points to the polynomial it encodes.\n",
    "# The Genetic algorithm must minimize the error, \n",
    "# (which is equivalent to maximizing the fitness).\n",
    "# The GA consists of \n",
    "# 1. Evaluation of the error caused by each chromosome,\n",
    "# 2. Probability of death in proportion to the error,\n",
    "# 3. Cloning at random,\n",
    "# 4. Mutation  and recombination at random, \n",
    "# Developed with the assistance of the AI of Visual Studio Code.\n",
    "# An old version of a GA developed with the help of Gemini was reused and updated.\n",
    "\n",
    "\n",
    "from datetime import datetime, timedelta\n",
    "import datetime\n",
    "import time\n",
    "import random\n",
    "import numpy as np\n",
    "from numpy.polynomial import Polynomial\n",
    "import matplotlib.pyplot as plt # Import matplotlib for plotting\n",
    "\n",
    "\n",
    "start_time = time.time() # Record the start time\n",
    "\n",
    "#Task to be done\n",
    "number_of_generations = 1000\n",
    "\n",
    "xArray =  [-2, -1, 0, 1, 2, 3]\n",
    "yArray =  [5,   1, 4, 0, 6, 3]\n",
    "\n",
    "alphabet = '0123456789'\n",
    "# Chromosome encoding for one of 6 coefficients, \n",
    "# each one with a length of 5 chars.\n",
    "# Encoding number as -93.24 with a sign and a decimal point.\n",
    "length_of_chromosomes = 8\n",
    "population_size = 200\n",
    "# Include cloning of the fittest\n",
    "include_reproduce_populationj10 = True\n",
    "# Include mutation\n",
    "include_mutate_allj10 = True\n",
    "# Include recombination\n",
    "include_crossover_allj10 = True\n",
    "mutation_rate = 0.1\n",
    "recombination_rate = 0.1\n",
    "# Boolean flag to print the generation, best chromosome and fitness.\n",
    "# This is the ancestral line of the solution.\n",
    "print_task = False\n",
    "print_decimation = False\n",
    "print_parameters = True\n",
    "show_graph = True\n",
    "    \n",
    "\n",
    "def print_parametersj10():\n",
    "    print(f\"Lab: la Evolución finds the polynomial of minimal error\")\n",
    "    print(f\"Purpose: Use a Genetic Algorithm (error as a probability of death, mutation and recombination) to find the coefficients of a polynomial that best fits a set of points.\")\n",
    "    print(\"Hint to be tested: consider only numbers of the form -3.244025 with a sign that could be positive or negative, and a decimal point in the second place of the encoding chromosome.\")\n",
    "    print(f\"Date of Experiment  = {datetime.datetime.now()}\")\n",
    "    print(f\"number_of_generations = {number_of_generations}\")\n",
    "    print(f\"length_of_chromosomes = {length_of_chromosomes}\")\n",
    "    print(f\"alphabet =  {alphabet}\")\n",
    "    print(f\"Points = {list(zip(xArray, yArray))}\")\n",
    "    print(f\"population_size = {population_size}\")\n",
    "    print(f\"include_reproduce_populationj10 = {include_reproduce_populationj10}\")\n",
    "    print(f\"include_mutate_allj10 = {include_mutate_allj10}\")\n",
    "    print(f\"include_crossover_allj10 = {include_crossover_allj10}\")\n",
    "    if include_mutate_allj10:\n",
    "        print(f\"mutation_rate = {mutation_rate}\")\n",
    "    if include_crossover_allj10:\n",
    "        print(f\"recombination_rate = {recombination_rate}\")\n",
    "    if include_reproduce_populationj10:\n",
    "        print(f\"Reproduce = {include_reproduce_populationj10:}\")\n",
    "\n",
    "def draw_points_and_polynomialj10(xNumpyArray, yNumpyArray):\n",
    "    \"\"\"Draws the original data points, finds and draws the \n",
    "    regression polynomial defined by the coefficients.\"\"\"\n",
    "    \n",
    "    # 2. Fit a 5th-degree (quintic) polynomial\n",
    "    # .fit() returns a Polynomial instance\n",
    "    p_fitted = Polynomial.fit(xNumpyArray, yNumpyArray, deg=5)\n",
    "\n",
    "    # 3. Predict values for visualization\n",
    "    x_new = np.linspace(-2,3, 100) # Generate 100 points between 0 and 6 for a smooth curve\n",
    "    y_new = p_fitted(x_new)\n",
    "    b_0, b_1, b_2, b_3, b_4, b5 = p_fitted.coef\n",
    "\n",
    "    # 4. Plot results\n",
    "    plt.scatter(xNumpyArray, yNumpyArray, label='Data Points')\n",
    "    plt.xlabel('x')\n",
    "    plt.ylabel('y')\n",
    "    plt.plot(x_new, y_new, label=f'Quintic Fit: y = {b_0:.2f} + {b_1:.2f}x + {b_2:.2f}x^2 + {b_3:.2f}x^3 + {b_4:.2f}x^4 + {b5:.2f}x^5', color='green')\n",
    "    plt.title(' Data Points and Quintic Fit by numpy.polynomial.Polynomial.fit()')\n",
    "    plt.legend()\n",
    "    plt.show()\n",
    "    return p_fitted.coef\n",
    "\n",
    "\n",
    "\n",
    "def create_populationj10(population_size, length_of_chromosomes, alphabet):\n",
    "    \"\"\"Creates a new population with random chromosomes.\"\"\"\n",
    "    # print(\"create_populationj10(population_size, target_sequence, alphabet)\")\n",
    "    population = []\n",
    "    for _ in range(population_size):\n",
    "        random_string1 = ''.join(random.choice(alphabet) for _ in range(length_of_chromosomes))\n",
    "        random_string2 = ''.join(random.choice(alphabet) for _ in range(length_of_chromosomes))\n",
    "        random_string3 = ''.join(random.choice(alphabet) for _ in range(length_of_chromosomes))\n",
    "        random_string4 = ''.join(random.choice(alphabet) for _ in range(length_of_chromosomes))\n",
    "        random_string5 = ''.join(random.choice(alphabet) for _ in range(length_of_chromosomes))\n",
    "        random_string6 = ''.join(random.choice(alphabet) for _ in range(length_of_chromosomes))\n",
    "        random_string = random_string1 + random_string2 + random_string3 + random_string4 + random_string5 + random_string6\n",
    "        population.append(random_string)\n",
    "    # print(\"initial population\")\n",
    "    # print(population)\n",
    "    return population\n",
    "\n",
    "# Decode a part of the chromosome into a coefficient of the polynomial.\n",
    "def decoderOldj10(s):\n",
    "    ''' The input is a number as string, outputs the number as a float. \n",
    "        We consider numbers of the form 93.24 with a sign that could be positive or negative,\n",
    "    '''\n",
    "    l = len(s) \n",
    "    # The first char encodes for the sign, \n",
    "    sign = 1\n",
    "    if  float(s[0]) % 2 == 1:\n",
    "        sign = -1\n",
    "    # The remaining chars encode for the number itself, \n",
    "    # without the decimal point nor sign.\n",
    "    sn = s[1:l]\n",
    "    # The point is inserted after the second char, so that we have numbers of the form 93.24\n",
    "    sn = sn[:2] + \".\" + sn[2:]\n",
    "    # Convert the string to a number\n",
    "    n = float(sn)\n",
    "    return sign * n\n",
    "\n",
    "# Decode a part of the chromosome into a coefficient of the polynomial.\n",
    "def decoderj10(s):\n",
    "    ''' The input is a number as string, outputs the number as a float. \n",
    "        We consider numbers of the form 93.24 with a sign that could be positive or negative,\n",
    "    '''\n",
    "    l = len(s) \n",
    "    # The first char encodes for the sign, \n",
    "    sign = 1\n",
    "    if  float(s[0]) % 2 == 1:\n",
    "        sign = -1\n",
    "    # The remaining chars encode for the number itself, \n",
    "    # without the decimal point nor sign.\n",
    "    sn = s[1:l]\n",
    "    # The point is inserted after the first char, so that we have numbers of the form -3.24\n",
    "    sn = sn[:1] + \".\" + sn[1:]\n",
    "    # Convert the string to a number\n",
    "    n = float(sn)\n",
    "    return sign * n\n",
    "\n",
    "\n",
    "def decodeFullCromosomej10(chromosome, length_of_chromosomes):\n",
    "    \"\"\"Decodes the full chromosome into the coefficients of the polynomial.\"\"\"\n",
    "    \"\"\"The chromosome is divided into 5 parts, \n",
    "        each one encoding for a coefficient of the polynomial.\"\"\"\n",
    "    chro0 = chromosome[0:length_of_chromosomes]\n",
    "    chro1 = chromosome[length_of_chromosomes:2*length_of_chromosomes]\n",
    "    chro2 = chromosome[2*length_of_chromosomes:3*length_of_chromosomes]\n",
    "    chro3 = chromosome[3*length_of_chromosomes:4*length_of_chromosomes]\n",
    "    chro4 = chromosome[4*length_of_chromosomes:5*length_of_chromosomes]\n",
    "    chro5 = chromosome[5*length_of_chromosomes:6*length_of_chromosomes]\n",
    "    a_0 = decoderj10(chro0)\n",
    "    a_1 = decoderj10(chro1)\n",
    "    a_2 = decoderj10(chro2)\n",
    "    a_3 = decoderj10(chro3)\n",
    "    a_4 = decoderj10(chro4)\n",
    "    a_5 = decoderj10(chro5)\n",
    "    # print(f\"Chromosome: {chromosome}\")\n",
    "    # print(f\"Coefficients: Intercept {a_0}, slope {a_1}, quadratic {a_2}, cubic {a_3}, quartic {a_4}, quintic {a_5}\")\n",
    "    # print()\n",
    "    return a_0, a_1, a_2, a_3, a_4, a_5\n",
    "\n",
    "\n",
    "\n",
    "def calculate_errorj10(chromosome, xArray, yArray, length_of_chromosomes):\n",
    "    \"\"\"Calculates the error of a chromosome.\n",
    "        A chromosome encodes for the coefficients of a polynomial of fith degree.\n",
    "        The error of a chromosome is the sum of \n",
    "        the vertical distances of the points to the polynomial it encodes.\n",
    "    \"\"\"\n",
    "    #  print(\"\\n calculate_errorj10(chromosome, xArray, yArray)\")\n",
    "    a_0, a_1, a_2, a_3, a_4, a_5 = decodeFullCromosomej10(chromosome, length_of_chromosomes)  \n",
    "    error = 0\n",
    "    for i in range(len(xArray)):\n",
    "        x = xArray[i]\n",
    "        y = yArray[i]\n",
    "        # Calculate the predicted y value based on the coefficients of the polynomial\n",
    "        predicted_y = a_0 + a_1 * x + a_2 * x**2 + a_3 * x**3 + a_4 * x**4 + a_5 * x**5\n",
    "        # Calculate the error as the quadratic difference \n",
    "        # between predicted and y value\n",
    "        # error += (predicted_y - y)**2\n",
    "        # Calculate the error as the distance between predicted and y value\n",
    "        error += abs(predicted_y - y)\n",
    "    return error\n",
    "\n",
    "def calculate_all_errorsj10(population, xArray, yArray, length_of_chromosomes):\n",
    "    # print(\"\\n*calculate_all_errorsj10(population, target_sequence)\")\n",
    "    \"\"\"Calculates the error of all chromosomes in the population.\"\"\"\n",
    "    errors = [calculate_errorj10(chromosome, xArray, yArray, length_of_chromosomes) for chromosome in population]\n",
    "    # print(\"errors: \", errors)\n",
    "    return errors\n",
    "\n",
    "def normalize_errorsj10(population, xArray, yArray, length_of_chromosomes):\n",
    "    \"\"\"Selects the best chromosome with minimal error for reproduction.\"\"\"\n",
    "    errors = calculate_all_errorsj10(population, xArray, yArray, length_of_chromosomes)\n",
    "    greatest_error = max(errors)\n",
    "    smallest_error = min(errors)\n",
    "    best_chromosome_index = errors.index(smallest_error)\n",
    "    best_chromosome = population[best_chromosome_index]\n",
    "    if greatest_error == 0:\n",
    "        # print(\"Greatest error is zero, the population is perfect.\")\n",
    "        return\n",
    "    normalized_errors = [error/greatest_error for error in errors]\n",
    "    # print(\"normalized_errors: \", normalized_errors)\n",
    "    return   normalized_errors, smallest_error, best_chromosome\n",
    "\n",
    "def decimation(population, normalized_errors):\n",
    "    \"\"\"Population is decimated in proportion to the normalized error, with a probability of death proportional to the error.\"\"\"\n",
    "    new_population = []\n",
    "    for i in range(len(population)):\n",
    "        if random.random() > normalized_errors[i]:\n",
    "            new_population.append(population[i]) # surviving\n",
    "            if print_decimation:\n",
    "                print(f\"Survived: i: {i}, chromosome: {population[i]} with normalized error {normalized_errors[i]:.4f}\")\n",
    "        if len(new_population) >= 3*len(population) // 4:  # Keep only half of the population\n",
    "            return new_population\n",
    "    if print_decimation:\n",
    "        print(f\"Decimation complete. New population size: {len(new_population)}\")            \n",
    "        print(\"new_population: \", new_population)\n",
    "    return new_population\n",
    "\n",
    "def reproduce_populationj10(population, population_size):\n",
    "    \"\"\"Creates a new population by cloning at random.\"\"\"\n",
    "    new_population = []\n",
    "    for i in range(population_size):\n",
    "        j = random.randint(0, len(population)-1)\n",
    "        new_population.append(population[j])\n",
    "    # print(f\"Reproduction complete. New population size: {len(new_population)}\")\n",
    "    return new_population\n",
    "\n",
    "\n",
    "def mutatej10(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_allj10(population, mutation_rate, alphabet):\n",
    "    \"\"\"Mutates all chromosomes in the population.\"\"\"\n",
    "    mutated_population = []\n",
    "    for chromosome in population:\n",
    "        mutated_chromosome = mutatej10(chromosome, mutation_rate, alphabet)\n",
    "        mutated_population.append(mutated_chromosome)\n",
    "    return mutated_population\n",
    "\n",
    "def crossoverj10(parent1, parent2, length_of_chromosomes, recombination_rate):\n",
    "    \"\"\"Performs crossover between two parent chromosomes.\"\"\"\n",
    "    if random.random() < recombination_rate:\n",
    "        crossover_point = random.randint(0, length_of_chromosomes)\n",
    "        return parent1[:crossover_point] + parent2[crossover_point:]\n",
    "    else:\n",
    "        return parent1\n",
    "\n",
    "def crossover_allj10(population, length_of_chromosomes, 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 = crossoverj10(parent1, parent2, length_of_chromosomes, recombination_rate)\n",
    "        recombinant_population.append(child)\n",
    "    return recombinant_population\n",
    "\n",
    "\n",
    "\n",
    "def run_one_generationj10(population, xArray, yArray, mutation_rate, recombination_rate, alphabet, length_of_chromosomes):\n",
    "    \"\"\"Runs one generation of the genetic algorithm.\"\"\"\n",
    "    \n",
    "    # errors are calculated for all the population, and normalized to be between 0 and 1.\n",
    "    normalized_errors, smallest_error, best_chromosome = normalize_errorsj10(population, xArray, yArray, length_of_chromosomes)\n",
    "    # print(\"normalized_errors: \", normalized_errors)\n",
    "    # Population is decimated in proportion to the normalized error, with a probability of death proportional to the error.\n",
    "    new_population = decimation(population, normalized_errors)\n",
    "    if include_reproduce_populationj10:\n",
    "        new_population = reproduce_populationj10(new_population, population_size)\n",
    "    if include_crossover_allj10:\n",
    "        new_population = crossover_allj10(new_population, length_of_chromosomes, recombination_rate)\n",
    "    if include_mutate_allj10:\n",
    "        new_population = mutate_allj10(new_population, mutation_rate, alphabet)\n",
    "    \n",
    "    return smallest_error, best_chromosome, new_population\n",
    "\n",
    "\n",
    "\n",
    "def plot_functionj10(g_values, 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 taskj10( xArray, yArray, mutation_rate, recombination_rate, alphabet,  length_of_chromosomes):\n",
    "    population = create_populationj10(population_size, length_of_chromosomes, alphabet)\n",
    "    # print(population)\n",
    "    generation = 0\n",
    "    best_chromosome = ''\n",
    "    best_fitness = 0\n",
    "    start_time = time.time()\n",
    "    smallest_error_history = [] # List to store best fitness of each generation\n",
    "    if print_task:\n",
    "        print(\"Generation, best_chromosome and best_fitness\")\n",
    "    while generation < number_of_generations:\n",
    "        generation += 1\n",
    "        smallest_error, best_chromosome, population = run_one_generationj10(population, xArray,yArray, mutation_rate, recombination_rate, alphabet, length_of_chromosomes)\n",
    "        if print_task:\n",
    "            print(f\" generation: {generation}  {best_chromosome} {smallest_error}\")\n",
    "        smallest_error_history.append(smallest_error)\n",
    "    # print(f\"\\nTarget sequence matched in generation {generation}\")\n",
    "    # print(f\"Final chromosome: {best_chromosome}\")\n",
    "    totalCost = population_size * generation\n",
    "    return  best_chromosome, totalCost, smallest_error_history\n",
    "\n",
    "def mainj10(xArray, yArray, mutation_rate, recombination_rate, alphabet, length_of_chromosomes):\n",
    "    print_parametersj10()\n",
    "    print(\"Total cost = population size * number of generations\")\n",
    "    best_chromosome, totalCost, smallest_error_history = taskj10(xArray, yArray, mutation_rate, recombination_rate, alphabet, length_of_chromosomes)\n",
    "    final_error = smallest_error_history[-1]\n",
    "    print(f\" The best chromosome is {best_chromosome}\" )\n",
    "    coefficients = decodeFullCromosomej10(best_chromosome, length_of_chromosomes)\n",
    "    print(f\" Encoded coefficientes: {coefficients} \" )\n",
    "    print(f\" Total cost =  {totalCost} chromosomes\")\n",
    "    print(f\" Final error =  {final_error} \")\n",
    "\n",
    "    # Plot the fitness history    \n",
    "    g_values = list(range(1, len(smallest_error_history) + 1))\n",
    "    plot_functionj10(g_values, smallest_error_history, xlabel='Generation', ylabel='SmallestError', title='Smallest Error Over Generations')\n",
    "    # The best chromosome encodes for the coefficients of the polynomial that best fits the data points\"\n",
    "    b_0, b_1, b_2, b_3, b_4, b5 = decodeFullCromosomej10(best_chromosome, length_of_chromosomes)\n",
    "    print(f\"Decoded coefficients: Intercept {b_0}, slope {b_1}, quadratic {b_2}, cubic {b_3}, quartic {b_4}, quintic {b5}\")\n",
    "    # Calculate the predicted y value based on the coefficients of the polynomial\n",
    "    our_polynomial = b_0 + b_1 * np.array(xArray) + b_2 * np.array(xArray)**2 + b_3 * np.array(xArray)**3 + b_4 * np.array(xArray)**4 + b5 * np.array(xArray)**5\n",
    "    \n",
    "\n",
    "    # Perform polynomial regression\n",
    "    # Fit a polynomial of degree 5 (polynomial regression)\n",
    "    p_fitted = Polynomial.fit(xArray, yArray, deg=5)\n",
    "    a_0, a_1, a_2, a_3, a_4, a5 = p_fitted.convert().coef\n",
    "    print(f\"Polynomial regression coefficients: Intercept {a_0}, slope {a_1}, quadratic {a_2}, cubic {a_3}, quartic {a_4}, quintic {a5}\")\n",
    "    # Create the regression graph\n",
    "    x_new = np.linspace(-2,3, 100) # Generate 100 points between -2 and 3 for a smooth curve\n",
    "    y_new = p_fitted(x_new)\n",
    "\n",
    "    # The best chromosome encodes for the coefficients of the polynomial that best fits the data points\"\n",
    "    b_0, b_1, b_2, b_3, b_4, b5 = decodeFullCromosomej10(best_chromosome, length_of_chromosomes)\n",
    "    print(f\"Encoded coefficients: Intercept {b_0}, slope {b_1}, quadratic {b_2}, cubic {b_3}, quartic {b_4}, quintic {b5}\")\n",
    "    # Calculate the predicted y value based on the coefficients of the polynomial\n",
    "    our_polynomial = b_0 + b_1 * np.array(x_new ) + b_2 * np.array(x_new )**2 + b_3 * np.array(x_new )**3 + b_4 * np.array(x_new )**4 + b5 * np.array(x_new )**5\n",
    "    \n",
    "\n",
    "\n",
    "    # Plot the original data, the regression polynomial, and our polynomial\n",
    "    plt.figure(figsize=(10, 6))\n",
    "    plt.scatter(xArray, yArray, label='Observed Data')\n",
    "    plt.plot(x_new, y_new, color='red', label=f'Polynomial Regression: y = {a_0:.2f} + {a_1:.2f}x + {a_2:.2f}x^2 + {a_3:.2f}x^3 + {a_4:.2f}x^4 + {a5:.2f}x^5')\n",
    "    plt.plot(x_new,        our_polynomial, color='green', label=f'Our polynomial: y = {b_0:.2f} + {b_1:.2f}x + {b_2:.2f}x^2 + {b_3:.2f}x^3 + {b_4:.2f}x^4 + {b5:.2f}x^5')\n",
    "    plt.xlabel('Independent variable (x)')\n",
    "    plt.ylabel('Dependent variable (y)')\n",
    "    plt.title('Linear Regression and la Evolución minimize the error of the line with respect to the data points')\n",
    "    plt.legend()\n",
    "    plt.grid(True)\n",
    "    plt.show()\n",
    "\n",
    "    # Plot the original data and the regression polynomial\n",
    "    plt.figure(figsize=(10, 6))\n",
    "    plt.scatter(xArray, yArray, label='Observed Data')\n",
    "    plt.plot(x_new, y_new, color='red', label=f'Polynomial Regression: y = {a_0:.2f} + {a_1:.2f}x + {a_2:.2f}x^2 + {a_3:.2f}x^3 + {a_4:.2f}x^4 + {a5:.2f}x^5')\n",
    "    plt.xlabel('Independent variable (x)')\n",
    "    plt.ylabel('Dependent variable (y)')\n",
    "    plt.title('Linear Regression minimizes the error of the line with respect to the data points')\n",
    "    plt.legend()\n",
    "    plt.grid(True)\n",
    "    plt.show()\n",
    "\n",
    "    # Plot  our polynomial\n",
    "    plt.figure(figsize=(10, 6))\n",
    "    plt.scatter(xArray, yArray, label='Observed Data')\n",
    "    #plt.plot(xArray, regression_polynomial, color='red', label=f'Polynomial Regression: y = {a_0:.2f} + {a_1:.2f}x + {a_2:.2f}x^2 + {a_3:.2f}x^3 + {a_4:.2f}x^4 + {a5:.2f}x^5')\n",
    "    plt.plot(x_new,        our_polynomial, color='green', label=f'Our polynomial: y = {b_0:.2f} + {b_1:.2f}x + {b_2:.2f}x^2 + {b_3:.2f}x^3 + {b_4:.2f}x^4 + {b5:.2f}x^5')\n",
    "    plt.xlabel('Independent variable (x)')\n",
    "    plt.ylabel('Dependent variable (y)')\n",
    "    plt.title('la Evoluciónary Regression minimizes the error of the line with respect to the data points')\n",
    "    plt.legend()\n",
    "    plt.grid(True)\n",
    "    plt.show()\n",
    "\n",
    "\n",
    "\n",
    "    end_time = time.time()\n",
    "    # Calculate the duration of the run in seconds\n",
    "    elapsed_time = end_time - start_time\n",
    "    elapsed_time = timedelta(seconds=elapsed_time)\n",
    "    print(f\"Elapsed time: {elapsed_time}\")\n",
    "    #return best_chromosome, totalCost, best_fitness_history\n",
    "\n",
    "# Call the main function with the defined parameters\n",
    "mainj10(xArray, yArray, mutation_rate, recombination_rate, alphabet, length_of_chromosomes)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "2204716f",
   "metadata": {},
   "source": [
    "**Evaluación.** Errático. A veces el rendimiento es regular, otras muy malo.\n",
    "\n",
    "### La aptitud como probabilidad de reproducción\n",
    "\n",
    "Nuestras simulaciones han demostrado que seleccionar el MAX y clonarlo es una estrategia muy buena. Pero este procedimiento elimina la variabilidad, que es el combustible de la Evolución. Hemos visto que la variabilidad se puede mantener si el MAX se selecciona en grupos pequeños, pero nos parece que esta solución no es mejor que el MAX. Aquí, implementamos en otra forma la idea de que el fitness significa éxito reproductivo. \n",
    "\n",
    "**Ejercicio.** Reutiliza nuestro programa anterior para calcular la aptitud a partir del error normalizado, y úsalo como probabilidad de reproducción.\n",
    ">\n",
    "> *Respuesta. * En el siguiente programa, el error se normaliza, el complemento módulo 1 se toma e interpreta como una probabilidad de reproducción. El código sigue:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "7b0c7d50",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Lab: Evolution finds the polynomial of minimal error\n",
      "Purpose: Use a Genetic Algorithm (fitness as a probability of reproduction, mutation and recombination) to find the coefficients of a polynomial that best fits a set of points.\n",
      "Date of Experiment  = 2026-04-25 07:18:16.481839\n",
      "number_of_generations = 10000\n",
      "length_of_chromosomes = 8\n",
      "alphabet =  0123456789\n",
      "Points = [(-2, 5), (-1, 1), (0, 4), (1, 0), (2, 6), (3, 3)]\n",
      "population_size = 200\n",
      "include_reproduce_populationj11 = True\n",
      "include_mutate_allj11 = True\n",
      "include_crossover_allj11 = True\n",
      "mutation_rate = 0.2\n",
      "recombination_rate = 0.1\n",
      "Reproduce = True\n",
      "Total cost = population size * number of generations\n",
      " The best chromosome is 777683735449507040459382958831609008564320723630\n",
      " Encoded coefficientes: (-7.768373, -4.49507, 0.459382, -5.88316, -0.085643, 0.72363) \n",
      " Total cost =  2000000 chromosomes\n",
      " Final error =  106.93555100000003 \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": [
      "Decoded coefficients: Intercept -7.768373, slope -4.49507, quadratic 0.459382, cubic -5.88316, quartic -0.085643, quintic 0.72363\n",
      "Polynomial regression coefficients: Intercept 4.0, slope -2.983333333333327, quadratic -4.791666666666659, cubic 3.041666666666663, quartic 1.2916666666666643, quintic -0.5583333333333323\n",
      "Encoded coefficients: Intercept -7.768373, slope -4.49507, quadratic 0.459382, cubic -5.88316, quartic -0.085643, quintic 0.72363\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"
    },
    {
     "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": [
      "Elapsed time: 0:00:48.991810\n"
     ]
    }
   ],
   "source": [
    "# Program PolynomialFitnessIsReproduction.py\n",
    "# This program uses a genetic algorithm to find the polynomial \n",
    "# of fifth degree that best fits a set of 6 points.\n",
    "# The coefficients are represented by a chromosome, \n",
    "# which is a string of digits.\n",
    "# The decoding function must divide the chromosome into parts, \n",
    "# and decode each one apart as one coefficient.\n",
    "# We consider numbers of the form -3.244025\n",
    "# with a sign that could be positive or negative, \n",
    "# and a decimal point in the second place of the encoding chromosome.\n",
    "# The error of a chromosome is the sum of the vertical distances \n",
    "# of the points to the polynomial it encodes.\n",
    "# The Genetic algorithm must minimize the error, \n",
    "# (which is equivalent to maximizing the fitness).\n",
    "# The GA consists of \n",
    "# 1. Evaluation of the error caused by each chromosome,\n",
    "# 2. Normalization of the error to be between 0 and 1. \n",
    "# 3. The complement modulo 1 is the fitness, \n",
    "#    a number between 0 and 1, which is the probability of reproduction, \n",
    "# 4. Mutation  and recombination at random. \n",
    "# \n",
    "# Developed with the assistance of the AI of Visual Studio Code.\n",
    "# An old version of a GA developed with the help of Gemini was reused and updated.\n",
    "\n",
    "\n",
    "from datetime import datetime, timedelta\n",
    "import datetime\n",
    "import time\n",
    "import random\n",
    "import numpy as np\n",
    "from numpy.polynomial import Polynomial\n",
    "import matplotlib.pyplot as plt # Import matplotlib for plotting\n",
    "\n",
    "\n",
    "start_time = time.time() # Record the start time\n",
    "\n",
    "#Task to be done\n",
    "number_of_generations = 10000\n",
    "\n",
    "xArray =  [-2, -1, 0, 1, 2, 3]\n",
    "yArray =  [5,   1, 4, 0, 6, 3]\n",
    "\n",
    "alphabet = '0123456789'\n",
    "# Chromosome encoding for one of 6 coefficients, \n",
    "# each one with a length of 5 chars.\n",
    "# Encoding number as -93.24 with a sign and a decimal point.\n",
    "length_of_chromosomes = 8\n",
    "population_size = 200\n",
    "# Include cloning of the fittest\n",
    "include_reproduce_populationj11 = True\n",
    "# Include mutation\n",
    "include_mutate_allj11 = True\n",
    "# Include recombination\n",
    "include_crossover_allj11 = True\n",
    "mutation_ratej11 = 0.2\n",
    "recombination_ratej11 = 0.1\n",
    "# Boolean flag to print the generation, best chromosome and fitness.\n",
    "# This is the ancestral line of the solution.\n",
    "print_taskj11 = False\n",
    "print_decimationj11 = False\n",
    "print_parametersj11 = True\n",
    "show_graph = True\n",
    "    \n",
    "\n",
    "def print_parametersj11():\n",
    "    print(f\"Lab: la Evolución finds the polynomial of minimal error\")\n",
    "    print(f\"Purpose: Use a Genetic Algorithm (fitness as a probability of reproduction, mutation and recombination) to find the coefficients of a polynomial that best fits a set of points.\")\n",
    "    print(f\"Date of Experiment  = {datetime.datetime.now()}\")\n",
    "    print(f\"number_of_generations = {number_of_generations}\")\n",
    "    print(f\"length_of_chromosomes = {length_of_chromosomes}\")\n",
    "    print(f\"alphabet =  {alphabet}\")\n",
    "    print(f\"Points = {list(zip(xArray, yArray))}\")\n",
    "    print(f\"population_size = {population_size}\")\n",
    "    print(f\"include_reproduce_populationj11 = {include_reproduce_populationj11}\")\n",
    "    print(f\"include_mutate_allj11 = {include_mutate_allj11}\")\n",
    "    print(f\"include_crossover_allj11 = {include_crossover_allj11}\")\n",
    "    if include_mutate_allj11:\n",
    "        print(f\"mutation_rate = {mutation_ratej11}\")\n",
    "    if include_crossover_allj11:\n",
    "        print(f\"recombination_rate = {recombination_ratej11}\")\n",
    "    if include_reproduce_populationj11:\n",
    "        print(f\"Reproduce = {include_reproduce_populationj11:}\")\n",
    "\n",
    "def draw_points_and_polynomialj11(xNumpyArray, yNumpyArray):\n",
    "    \"\"\"Draws the original data points, finds and draws the \n",
    "    regression polynomial defined by the coefficients.\"\"\"\n",
    "    \n",
    "    # 2. Fit a 5th-degree (quintic) polynomial\n",
    "    # .fit() returns a Polynomial instance\n",
    "    p_fitted = Polynomial.fit(xNumpyArray, yNumpyArray, deg=5)\n",
    "\n",
    "    # 3. Predict values for visualization\n",
    "    x_new = np.linspace(-2,3, 100) # Generate 100 points between 0 and 6 for a smooth curve\n",
    "    y_new = p_fitted(x_new)\n",
    "    b_0, b_1, b_2, b_3, b_4, b5 = p_fitted.coef\n",
    "\n",
    "    # 4. Plot results\n",
    "    plt.scatter(xNumpyArray, yNumpyArray, label='Data Points')\n",
    "    plt.xlabel('x')\n",
    "    plt.ylabel('y')\n",
    "    plt.plot(x_new, y_new, label=f'Quintic Fit: y = {b_0:.2f} + {b_1:.2f}x + {b_2:.2f}x^2 + {b_3:.2f}x^3 + {b_4:.2f}x^4 + {b5:.2f}x^5', color='green')\n",
    "    plt.title(' Data Points and Quintic Fit by numpy.polynomial.Polynomial.fit()')\n",
    "    plt.legend()\n",
    "    plt.show()\n",
    "    return p_fitted.coef\n",
    "\n",
    "\n",
    "\n",
    "def create_populationj11(population_size, length_of_chromosomes, alphabet):\n",
    "    \"\"\"Creates a new population with random chromosomes.\"\"\"\n",
    "    # print(\"create_populationj11(population_size, target_sequence, alphabet)\")\n",
    "    population = []\n",
    "    for _ in range(population_size):\n",
    "        random_string1 = ''.join(random.choice(alphabet) for _ in range(length_of_chromosomes))\n",
    "        random_string2 = ''.join(random.choice(alphabet) for _ in range(length_of_chromosomes))\n",
    "        random_string3 = ''.join(random.choice(alphabet) for _ in range(length_of_chromosomes))\n",
    "        random_string4 = ''.join(random.choice(alphabet) for _ in range(length_of_chromosomes))\n",
    "        random_string5 = ''.join(random.choice(alphabet) for _ in range(length_of_chromosomes))\n",
    "        random_string6 = ''.join(random.choice(alphabet) for _ in range(length_of_chromosomes))\n",
    "        random_string = random_string1 + random_string2 + random_string3 + random_string4 + random_string5 + random_string6\n",
    "        population.append(random_string)\n",
    "    # print(\"initial population\")\n",
    "    # print(population)\n",
    "    return population\n",
    "\n",
    "# Decode a part of the chromosome into a coefficient of the polynomial.\n",
    "def decoderOldj11(s):\n",
    "    ''' The input is a number as string, outputs the number as a float. \n",
    "        We consider numbers of the form 93.24 with a sign that could be positive or negative,\n",
    "    '''\n",
    "    l = len(s) \n",
    "    # The first char encodes for the sign, \n",
    "    sign = 1\n",
    "    if  float(s[0]) % 2 == 1:\n",
    "        sign = -1\n",
    "    # The remaining chars encode for the number itself, \n",
    "    # without the decimal point nor sign.\n",
    "    sn = s[1:l]\n",
    "    # The point is inserted after the second char, so that we have numbers of the form 93.24\n",
    "    sn = sn[:2] + \".\" + sn[2:]\n",
    "    # Convert the string to a number\n",
    "    n = float(sn)\n",
    "    return sign * n\n",
    "\n",
    "# Decode a part of the chromosome into a coefficient of the polynomial.\n",
    "def decoderj11(s):\n",
    "    ''' The input is a number as string, outputs the number as a float. \n",
    "        We consider numbers of the form 93.24 with a sign that could be positive or negative,\n",
    "    '''\n",
    "    l = len(s) \n",
    "    # The first char encodes for the sign, \n",
    "    sign = 1\n",
    "    if  float(s[0]) % 2 == 1:\n",
    "        sign = -1\n",
    "    # The remaining chars encode for the number itself, \n",
    "    # without the decimal point nor sign.\n",
    "    sn = s[1:l]\n",
    "    # The point is inserted after the first char, so that we have numbers of the form -3.24\n",
    "    sn = sn[:1] + \".\" + sn[1:]\n",
    "    # Convert the string to a number\n",
    "    n = float(sn)\n",
    "    return sign * n\n",
    "\n",
    "\n",
    "def decodeFullCromosomej11(chromosome, length_of_chromosomes):\n",
    "    \"\"\"Decodes the full chromosome into the coefficients of the polynomial.\"\"\"\n",
    "    \"\"\"The chromosome is divided into 5 parts, \n",
    "        each one encoding for a coefficient of the polynomial.\"\"\"\n",
    "    chro0 = chromosome[0:length_of_chromosomes]\n",
    "    chro1 = chromosome[length_of_chromosomes:2*length_of_chromosomes]\n",
    "    chro2 = chromosome[2*length_of_chromosomes:3*length_of_chromosomes]\n",
    "    chro3 = chromosome[3*length_of_chromosomes:4*length_of_chromosomes]\n",
    "    chro4 = chromosome[4*length_of_chromosomes:5*length_of_chromosomes]\n",
    "    chro5 = chromosome[5*length_of_chromosomes:6*length_of_chromosomes]\n",
    "    a_0 = decoderj11(chro0)\n",
    "    a_1 = decoderj11(chro1)\n",
    "    a_2 = decoderj11(chro2)\n",
    "    a_3 = decoderj11(chro3)\n",
    "    a_4 = decoderj11(chro4)\n",
    "    a_5 = decoderj11(chro5)\n",
    "    # print(f\"Chromosome: {chromosome}\")\n",
    "    # print(f\"Coefficients: Intercept {a_0}, slope {a_1}, quadratic {a_2}, cubic {a_3}, quartic {a_4}, quintic {a_5}\")\n",
    "    # print()\n",
    "    return a_0, a_1, a_2, a_3, a_4, a_5\n",
    "\n",
    "\n",
    "\n",
    "def calculate_errorj11(chromosome, xArray, yArray, length_of_chromosomes):\n",
    "    \"\"\"Calculates the error of a chromosome.\n",
    "        A chromosome encodes for the coefficients of a polynomial of fith degree.\n",
    "        The error of a chromosome is the sum of \n",
    "        the vertical distances of the points to the polynomial it encodes.\n",
    "    \"\"\"\n",
    "    #  print(\"\\n calculate_errorj11(chromosome, xArray, yArray)\")\n",
    "    a_0, a_1, a_2, a_3, a_4, a_5 = decodeFullCromosomej11(chromosome, length_of_chromosomes)  \n",
    "    error = 0\n",
    "    for i in range(len(xArray)):\n",
    "        x = xArray[i]\n",
    "        y = yArray[i]\n",
    "        # Calculate the predicted y value based on the coefficients of the polynomial\n",
    "        predicted_y = a_0 + a_1 * x + a_2 * x**2 + a_3 * x**3 + a_4 * x**4 + a_5 * x**5\n",
    "        # Calculate the error as the quadratic difference \n",
    "        # between predicted and y value\n",
    "        # error += (predicted_y - y)**2\n",
    "        # Calculate the error as the distance between predicted and y value\n",
    "        error += abs(predicted_y - y)\n",
    "    return error\n",
    "\n",
    "def calculate_all_errorsj11(population, xArray, yArray, length_of_chromosomes):\n",
    "    # print(\"\\n*calculate_all_errorsj11(population, target_sequence)\")\n",
    "    \"\"\"Calculates the error of all chromosomes in the population.\"\"\"\n",
    "    errors = [calculate_errorj11(chromosome, xArray, yArray, length_of_chromosomes) for chromosome in population]\n",
    "    # print(\"errors: \", errors)\n",
    "    return errors\n",
    "\n",
    "def normalize_errorsj11(population, xArray, yArray, length_of_chromosomes):\n",
    "    \"\"\"Selects the best chromosome with minimal error for reproduction.\"\"\"\n",
    "    errors = calculate_all_errorsj11(population, xArray, yArray, length_of_chromosomes)\n",
    "    greatest_error = max(errors)\n",
    "    smallest_error = min(errors)\n",
    "    best_chromosome_index = errors.index(smallest_error)\n",
    "    best_chromosome = population[best_chromosome_index]\n",
    "    if greatest_error == 0:\n",
    "        # print(\"Greatest error is zero, the population is perfect.\")\n",
    "        return\n",
    "    normalized_errors = [error/greatest_error for error in errors]\n",
    "    # print(\"normalized_errors: \", normalized_errors)\n",
    "    return   normalized_errors, smallest_error, best_chromosome\n",
    "\n",
    "def decimation(population, normalized_errors):\n",
    "    \"\"\"Population is decimated in proportion to the normalized error, with a probability of death proportional to the error.\"\"\"\n",
    "    new_population = []\n",
    "    for i in range(len(population)):\n",
    "        if random.random() > normalized_errors[i]:\n",
    "            new_population.append(population[i]) # surviving\n",
    "            if print_decimationj11:\n",
    "                print(f\"Survived: i: {i}, chromosome: {population[i]} with normalized error {normalized_errors[i]:.4f}\")\n",
    "        if len(new_population) >= 3*len(population) // 4:  # Keep only half of the population\n",
    "            return new_population\n",
    "    if print_decimationj11:\n",
    "        print(f\"Decimation complete. New population size: {len(new_population)}\")            \n",
    "        print(\"new_population: \", new_population)\n",
    "    return new_population\n",
    "\n",
    "def reproduce_populationj11(population, population_size, fitness_probabilities):\n",
    "    \"\"\"Creates a new population by cloning at random.\"\"\"\n",
    "    new_population = []\n",
    "    for i in range(population_size):\n",
    "        j = random.choices(range(len(population)), weights=fitness_probabilities)[0]\n",
    "        new_population.append(population[j])\n",
    "    # print(f\"Reproduction complete. New population size: {len(new_population)}\")\n",
    "    return new_population\n",
    "\n",
    "\n",
    "def mutatej11(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_allj11(population, mutation_rate, alphabet):\n",
    "    \"\"\"Mutates all chromosomes in the population.\"\"\"\n",
    "    mutated_population = []\n",
    "    for chromosome in population:\n",
    "        mutated_chromosome = mutatej11(chromosome, mutation_rate, alphabet)\n",
    "        mutated_population.append(mutated_chromosome)\n",
    "    return mutated_population\n",
    "\n",
    "def crossoverj11(parent1, parent2, length_of_chromosomes, recombination_rate):\n",
    "    \"\"\"Performs crossover between two parent chromosomes.\"\"\"\n",
    "    if random.random() < recombination_rate:\n",
    "        crossover_point = random.randint(0, length_of_chromosomes)\n",
    "        return parent1[:crossover_point] + parent2[crossover_point:]\n",
    "    else:\n",
    "        return parent1\n",
    "\n",
    "def crossover_allj11(population, length_of_chromosomes, 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 = crossoverj11(parent1, parent2, length_of_chromosomes, recombination_rate)\n",
    "        recombinant_population.append(child)\n",
    "    return recombinant_population\n",
    "\n",
    "\n",
    "\n",
    "def run_one_generationj11(population, xArray, yArray, mutation_rate, recombination_rate, alphabet, length_of_chromosomes):\n",
    "    \"\"\"Runs one generation of the genetic algorithm.\"\"\"\n",
    "    \n",
    "    # errors are calculated for all the population, and normalized to be between 0 and 1.\n",
    "    normalized_errors, smallest_error, best_chromosome = normalize_errorsj11(population, xArray, yArray, length_of_chromosomes)\n",
    "    # print(\"normalized_errors: \", normalized_errors)\n",
    "    # Fitness as a probability is defined as 1 - normalized_error, so that the best chromosome has a fitness of 1 and the worst has a fitness of 0.\n",
    "    fitness_probabilities = [1 - error for error in normalized_errors]\n",
    "    # Population is reproduced in proportion to the fitness.\n",
    "    if include_reproduce_populationj11:\n",
    "        new_population = reproduce_populationj11(population, population_size, fitness_probabilities)\n",
    "    if include_crossover_allj11:\n",
    "        new_population = crossover_allj11(new_population, length_of_chromosomes, recombination_rate)\n",
    "    if include_mutate_allj11:\n",
    "        new_population = mutate_allj11(new_population, mutation_rate, alphabet)\n",
    "    \n",
    "    return smallest_error, best_chromosome, new_population\n",
    "\n",
    "\n",
    "\n",
    "def plot_functionj11(g_values, 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 taskj11( xArray, yArray, mutation_rate, recombination_rate, alphabet,  length_of_chromosomes):\n",
    "    population = create_populationj11(population_size, length_of_chromosomes, alphabet)\n",
    "    # print(population)\n",
    "    generation = 0\n",
    "    best_chromosome = ''\n",
    "    best_fitness = 0\n",
    "    start_time = time.time()\n",
    "    smallest_error_history = [] # List to store best fitness of each generation\n",
    "    if print_taskj11:\n",
    "        print(\"Generation, best_chromosome and best_fitness\")\n",
    "    while generation < number_of_generations:\n",
    "        generation += 1\n",
    "        smallest_error, best_chromosome, population = run_one_generationj11(population, xArray,yArray, mutation_rate, recombination_rate, alphabet, length_of_chromosomes)\n",
    "        if print_taskj11:\n",
    "            print(f\" generation: {generation}  {best_chromosome} {smallest_error}\")\n",
    "        smallest_error_history.append(smallest_error)\n",
    "    # print(f\"\\nTarget sequence matched in generation {generation}\")\n",
    "    # print(f\"Final chromosome: {best_chromosome}\")\n",
    "    totalCost = population_size * generation\n",
    "    return  best_chromosome, totalCost, smallest_error_history\n",
    "\n",
    "def mainj11(xArray, yArray, mutation_rate, recombination_rate, alphabet, length_of_chromosomes):\n",
    "    print_parametersj11()\n",
    "    print(\"Total cost = population size * number of generations\")\n",
    "    best_chromosome, totalCost, smallest_error_history = taskj11(xArray, yArray, mutation_rate, recombination_rate, alphabet, length_of_chromosomes)\n",
    "    final_error = smallest_error_history[-1]\n",
    "    print(f\" The best chromosome is {best_chromosome}\" )\n",
    "    coefficients = decodeFullCromosomej11(best_chromosome, length_of_chromosomes)\n",
    "    print(f\" Encoded coefficientes: {coefficients} \" )\n",
    "    print(f\" Total cost =  {totalCost} chromosomes\")\n",
    "    print(f\" Final error =  {final_error} \")\n",
    "\n",
    "    # Plot the fitness history    \n",
    "    g_values = list(range(1, len(smallest_error_history) + 1))\n",
    "    plot_functionj11(g_values, smallest_error_history, xlabel='Generation', ylabel='SmallestError', title='Smallest Error Over Generations')\n",
    "    # The best chromosome encodes for the coefficients of the polynomial that best fits the data points\"\n",
    "    b_0, b_1, b_2, b_3, b_4, b5 = decodeFullCromosomej11(best_chromosome, length_of_chromosomes)\n",
    "    print(f\"Decoded coefficients: Intercept {b_0}, slope {b_1}, quadratic {b_2}, cubic {b_3}, quartic {b_4}, quintic {b5}\")\n",
    "    # Calculate the predicted y value based on the coefficients of the polynomial\n",
    "    our_polynomial = b_0 + b_1 * np.array(xArray) + b_2 * np.array(xArray)**2 + b_3 * np.array(xArray)**3 + b_4 * np.array(xArray)**4 + b5 * np.array(xArray)**5\n",
    "    \n",
    "\n",
    "    # Perform polynomial regression\n",
    "    # Fit a polynomial of degree 5 (polynomial regression)\n",
    "    p_fitted = Polynomial.fit(xArray, yArray, deg=5)\n",
    "    a_0, a_1, a_2, a_3, a_4, a5 = p_fitted.convert().coef\n",
    "    print(f\"Polynomial regression coefficients: Intercept {a_0}, slope {a_1}, quadratic {a_2}, cubic {a_3}, quartic {a_4}, quintic {a5}\")\n",
    "    # Create the regression graph\n",
    "    x_new = np.linspace(-2,3, 100) # Generate 100 points between -2 and 3 for a smooth curve\n",
    "    y_new = p_fitted(x_new)\n",
    "\n",
    "    # The best chromosome encodes for the coefficients of the polynomial that best fits the data points\"\n",
    "    b_0, b_1, b_2, b_3, b_4, b5 = decodeFullCromosomej11(best_chromosome, length_of_chromosomes)\n",
    "    print(f\"Encoded coefficients: Intercept {b_0}, slope {b_1}, quadratic {b_2}, cubic {b_3}, quartic {b_4}, quintic {b5}\")\n",
    "    # Calculate the predicted y value based on the coefficients of the polynomial\n",
    "    our_polynomial = b_0 + b_1 * np.array(x_new ) + b_2 * np.array(x_new )**2 + b_3 * np.array(x_new )**3 + b_4 * np.array(x_new )**4 + b5 * np.array(x_new )**5\n",
    "    \n",
    "\n",
    "\n",
    "    # Plot the original data, the regression polynomial, and our polynomial\n",
    "    plt.figure(figsize=(10, 6))\n",
    "    plt.scatter(xArray, yArray, label='Observed Data')\n",
    "    plt.plot(x_new, y_new, color='red', label=f'Polynomial Regression: y = {a_0:.2f} + {a_1:.2f}x + {a_2:.2f}x^2 + {a_3:.2f}x^3 + {a_4:.2f}x^4 + {a5:.2f}x^5')\n",
    "    plt.plot(x_new,        our_polynomial, color='green', label=f'Our polynomial: y = {b_0:.2f} + {b_1:.2f}x + {b_2:.2f}x^2 + {b_3:.2f}x^3 + {b_4:.2f}x^4 + {b5:.2f}x^5')\n",
    "    plt.xlabel('Independent variable (x)')\n",
    "    plt.ylabel('Dependent variable (y)')\n",
    "    plt.title('Linear Regression and la Evolución minimize the error of the line with respect to the data points')\n",
    "    plt.legend()\n",
    "    plt.grid(True)\n",
    "    plt.show()\n",
    "\n",
    "    # Plot the original data and the regression polynomial\n",
    "    plt.figure(figsize=(10, 6))\n",
    "    plt.scatter(xArray, yArray, label='Observed Data')\n",
    "    plt.plot(x_new, y_new, color='red', label=f'Polynomial Regression: y = {a_0:.2f} + {a_1:.2f}x + {a_2:.2f}x^2 + {a_3:.2f}x^3 + {a_4:.2f}x^4 + {a5:.2f}x^5')\n",
    "    plt.xlabel('Independent variable (x)')\n",
    "    plt.ylabel('Dependent variable (y)')\n",
    "    plt.title('Linear Regression minimizes the error of the line with respect to the data points')\n",
    "    plt.legend()\n",
    "    plt.grid(True)\n",
    "    plt.show()\n",
    "\n",
    "    # Plot  our polynomial\n",
    "    plt.figure(figsize=(10, 6))\n",
    "    plt.scatter(xArray, yArray, label='Observed Data')\n",
    "    #plt.plot(xArray, regression_polynomial, color='red', label=f'Polynomial Regression: y = {a_0:.2f} + {a_1:.2f}x + {a_2:.2f}x^2 + {a_3:.2f}x^3 + {a_4:.2f}x^4 + {a5:.2f}x^5')\n",
    "    plt.plot(x_new,        our_polynomial, color='green', label=f'Our polynomial: y = {b_0:.2f} + {b_1:.2f}x + {b_2:.2f}x^2 + {b_3:.2f}x^3 + {b_4:.2f}x^4 + {b5:.2f}x^5')\n",
    "    plt.xlabel('Independent variable (x)')\n",
    "    plt.ylabel('Dependent variable (y)')\n",
    "    plt.title('la Evoluciónary Regression minimizes the error of the line with respect to the data points')\n",
    "    plt.legend()\n",
    "    plt.grid(True)\n",
    "    plt.show()\n",
    "\n",
    "\n",
    "\n",
    "    end_time = time.time()\n",
    "    # Calculate the duration of the run in seconds\n",
    "    elapsed_time = end_time - start_time\n",
    "    elapsed_time = timedelta(seconds=elapsed_time)\n",
    "    print(f\"Elapsed time: {elapsed_time}\")\n",
    "    #return best_chromosome, totalCost, best_fitness_history\n",
    "\n",
    "# Call the main function with the defined parameters\n",
    "mainj11(xArray, yArray, mutation_ratej11, recombination_ratej11, alphabet, length_of_chromosomes)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "c75c91a6",
   "metadata": {},
   "source": [
    "*Nuestras observaciones.* El programa produce a veces un resultado aceptable. \n"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "71c258f3",
   "metadata": {},
   "source": [
    "### El poder de la riqueza\n",
    "\n",
    "Hemos hecho todo lo que consideramos inteligente para encontrar la perfección. Hasta ahora, no hemos tenido éxito. Pero, ciertamente, hemos encontrado buenas aproximaciones alentadoras. Así que continuamos nuestra búsqueda.\n",
    "\n",
    "**Ejercicio.** Demuestra que la Evolución puede resolver el problema planteado y una solución perfecta puede evolucionarse. Consejo: Aplica el proverbio que dice: la sabiduría es una bendición tanto como la riqueza.\n",
    ">\n",
    "> *Respuesta.* La Evolución siempre puede recurrir a un banco donde reside un capital infinito: el tamaño de la población. Este es un recurso que funciona como el poder de una máquina para subir una colina. Si no tienes potencia, sin importar cuánto lo intentes, no puedes tener éxito. Pero, si tienes suficiente potencia, tendrás éxito, muy seguramente después de algún tiempo y pruebas. Así que elegimos un programa prometedor, con una implementación adecuada de la Evolución, y comenzando con 200, duplicamos el tamaño de la población para cada nueva ronda hasta que tuvimos éxito. El programa y los resultados siguen."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "c55c4bb5",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Lab: Evolution finds the polynomial of minimal error\n",
      "Purpose: Use a Genetic Algorithm (MAX = selection of the fittest, mutation and recombination) to find the coefficients of a polynomial that best fits a set of points.\n",
      "Hint to be tested: consider only numbers of the form -3.244025 with a sign that could be positive or negative, and a decimal point in the second place of the encoding chromosome.\n",
      "Date of Experiment  = 2026-04-25 11:49:02.946052\n",
      "number_of_generations = 1000\n",
      "length_of_chromosomes = 8\n",
      "alphabet =  0123456789\n",
      "Points = [(-2, 5), (-1, 1), (0, 4), (1, 0), (2, 6), (3, 3)]\n",
      "population_size = 102400\n",
      "include_clone_populationj12 = True\n",
      "include_mutate_allj12 = True\n",
      "include_crossover_allj12 = False\n",
      "mutation_rate = 0.05\n",
      "print_best_fitness = False\n",
      "Total cost = population size * number of generations\n",
      " The best chromosome is 239999965949131218975999068000186233999551090050\n",
      " Encoded coefficientes: (3.999996, -9.491312, -8.975999, 6.800018, 2.339995, -1.09005) \n",
      " Total cost =  102400000 chromosomes\n",
      " Final error =  6.634532000000011 \n"
     ]
    },
    {
     "data": {
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yZGZm4r333kOdOnUwZcoUq7yPp6cnunfvjnfeeQe+vr4ICQlBWloali9fjrp161a7v5CQEMydOxezZs3C77//jl69eqFevXr4448/sG/fPri7u2POnDk4cuQIJk2ahGeeeQbNmjWDs7Mztm3bhiNHjhjNgoSFhSExMRFr1qxBkyZN4OLigrCwsErHcO3aNezZs8fkuFarRXh4eLXPyWD27NnYtGkTevTogTfeeAPe3t74+uuvsXnzZixYsABeXl4W9evo6Ii1a9ciKipK/qbvzp07o7i4GN9++y0++eQTREREmP3yy/Hjx2PNmjWYNGkSGjRogCeffNLo+alTp2Lt2rXo3r07pk2bhpYtW6K8vBzZ2dnYunUrZsyYgY4dO1o07vj4eGRlZWHUqFHYuHEjBgwYgKCgIBQWFuLXX39FYmIiXFxcoNFoANz8gsoJEybg2WefxYEDB9C9e3e4u7sjJycHu3btQlhYGP75z39WawzWOL++ffti4cKFGDlyJCZMmIDLly/j3XffNTsjVZ3fx7i4OERFRaFHjx548cUX4ezsjKVLl+LYsWNYvXp1tb9BfdmyZdi2bRv69u2LRo0aoaioSJ75uvNzp1pOzR3YRDVtzZo1YuTIkaJZs2aiTp06QqPRiEaNGonRo0eLn3/+2ahtcHCw6Nu3r0kfAMTEiRONjhmuVnnnnXfkY+fOnRNPP/20qFevnvDw8BC9evUSx44dE8HBwWLs2LFyu6peBi/EzavNevToITw9PYVWqxXBwcFiyJAhIiUlRQghxB9//CHGjRsnmjdvLtzd3UWdOnVEy5YtxaJFi0Rpaancz+nTp0V0dLTw8PCQL1uvTGVXgdWvX99k3Ldf5n+3egohxNGjR0W/fv2El5eXcHZ2Fq1atTK68uf2On3zzTeVjvVOly5dEq+88opo3ry5cHFxEXXq1BEdOnQQS5YsqfBrEMrKykTDhg0FADFr1iyzbQoKCsRrr70mHn74YeHs7Cy8vLxEWFiYmDZtmtGl5+Z+X+6mrKxMfPHFFyIqKkr4+voKJycn4eXlJTp06CBef/11oysTDVasWCE6duwo3N3dhaurq2jatKkYM2aMOHDggNwmIiJCPProoyavHTt2rMnvgDXOb8WKFeLhhx8WWq1WNGnSRMTFxYnly5cLACIrK0tuV9Hvo7mrwIQQYufOneLxxx+Xz7VTp07i22+/NWpjuArszivZ7vx7S09PF4MGDRLBwcFCq9UKHx8fERERUekVnVQ7SULc9g1VRERERHaAV4ERERGR3WEAIiIiIrvDAERERER2hwGIiIiI7A4DEBEREdkdBiAiIiKyO/wiRDPKy8tx4cIFeHh4VPtLtoiIiEgdQgjk5+cjKCgIDg6Vz/EwAJlx4cIFkztVExER0f3h7NmzaNCgQaVtGIDM8PDwAHCzgJ6enlbtW6/XY+vWrYiOjpa/2p6sj3VWBuusHNZaGayzMmqqzjqdDg0bNpT/Ha8MA5AZhmUvT0/PGglAbm5u8PT05B9XDWKdlcE6K4e1VgbrrIyarnNVtq9wEzQRERHZHQYgIiIisjsMQERERGR3GICIiIjI7jAAERERkd1hACIiIiK7wwBEREREdocBiIiIiOwOAxARERHZHQYgIiIisjsMQERERGR3GICIiIjI7vBmqAoqLi1DzrUbuFas9kiIiIjsG2eAFHTsvA6R7+3E4p8c1R4KERGRXWMAIiIiIrvDAKQgSbr5f4W6wyAiIrJ7DEAKktQeABEREQFgAFKUJDECERER2QIGIBUIroERERGpigFIQYb5H+YfIiIidTEAKYgrYERERLaBAYiIiIjsDgOQgqS/FsG4BEZERKQuBiAFSdwEREREZBMYgIiIiMjuMACpgBNARERE6mIAUhCvAiMiIrINDEAKkngzDCIiIpvAAKQg3gyViIjINjAAqYABiIiISF0MQAriZfBERES2gQFIQdwDREREZBsYgFTACSAiIiJ1MQApiJfBExER2QZVA1BcXBzat28PDw8P+Pn5YeDAgTh+/LhRm3HjxkGSJKOfTp063bXvtWvXIjQ0FFqtFqGhoVi3bl1NnUaVcQsQERGRbVA1AKWlpWHixInYs2cPkpOTUVpaiujoaFy/ft2oXa9evZCTkyP/bNmypdJ+09PTMWzYMIwePRqHDx/G6NGjMXToUOzdu7cmT+euOANERERkG5zUfPPvvvvO6HFCQgL8/Pxw8OBBdO/eXT6u1WoREBBQ5X7j4+MRFRWFmJgYAEBMTAzS0tIQHx+P1atXW2fw94JTQERERKpSNQDdKS8vDwDg7e1tdDw1NRV+fn6oW7cuIiIi8NZbb8HPz6/CftLT0zFt2jSjYz179kR8fLzZ9sXFxSguLpYf63Q6AIBer4der7fkVMwqLS0DcDP/WLNfMmWoL+tcs1hn5bDWymCdlVFTda5Of5IQwibmI4QQGDBgAK5evYqdO3fKx9esWYM6deogODgYWVlZeP3111FaWoqDBw9Cq9Wa7cvZ2RkrV67EyJEj5WOrVq3Cs88+axR0DGJjYzFnzhyT46tWrYKbm5sVzu6mP24Ab2c6wdVRYF6HMqv1S0REREBhYSFGjhyJvLw8eHp6VtrWZmaAJk2ahCNHjmDXrl1Gx4cNGyb/d4sWLdCuXTsEBwdj8+bNGDx4cIX9SXdsuBFCmBwziImJwfTp0+XHOp0ODRs2RHR09F0LWB1Zl67j7cwfAQBRUVHQaDRW65uM6fV6JCcns841jHVWDmutDNZZGTVVZ8MKTlXYRACaPHkyNm7ciB07dqBBgwaVtg0MDERwcDBOnjxZYZuAgADk5uYaHbt48SL8/f3NttdqtWZnkzQajVU/GCenm+UWNdA3mcc6K4N1Vg5rrQzWWRnWrnN1+lL1KjAhBCZNmoSkpCRs27YNjRs3vutrLl++jLNnzyIwMLDCNp07d0ZycrLRsa1bt6JLly73POZ7YZiBsok1RyIiIjum6gzQxIkTsWrVKmzYsAEeHh7yrI2XlxdcXV1RUFCA2NhYPP300wgMDMTp06fx6quvwtfXF4MGDZL7GTNmDOrXr4+4uDgAwJQpU9C9e3fMnz8fAwYMwIYNG5CSkmKyvKY0XgVPRERkG1SdAfroo4+Ql5eHyMhIBAYGyj9r1qwBADg6OuLo0aMYMGAAHnroIYwdOxYPPfQQ0tPT4eHhIfeTnZ2NnJwc+XGXLl2QmJiIhIQEtGzZEitXrsSaNWvQsWNHxc/xdrwZKhERkW1QdQbobhegubq64vvvv79rP6mpqSbHhgwZgiFDhlg6tBrF/ENERKQu3gtMQbwbPBERkW1gAFIQb4VBRERkGxiAVMAlMCIiInUxAKmBCYiIiEhVDEAK4hIYERGRbWAAUhC/CJGIiMg2MACpgAGIiIhIXQxACuIKGBERkW1gAFIQ9wARERHZBgYgBRm+CJFLYEREROpiAFIDExAREZGqGIAUxCUwIiIi28AApCDeDJ6IiMg2MAARERGR3WEAUtJfU0CCF8QTERGpigFIQRKDDxERkU1gAFIQN0ETERHZBgYglQjBrdBERERqYQBS0O0TQMw/RERE6mEAUpDENTAiIiKbwACkIKMZINVGQURERAxAKuEeICIiIvUwACmIK2BERES2gQFIQbd/DxDnf4iIiNTDAKSk22aAuAJGRESkHgYglTD/EBERqYcBSEHcA0RERGQbGIAUZJR/uAZGRESkGgYglTD+EBERqYcBSEG3fxM0J4CIiIjUwwCkIG4BIiIisg2qBqC4uDi0b98eHh4e8PPzw8CBA3H8+HH5eb1ej5dffhlhYWFwd3dHUFAQxowZgwsXLlTa78qVKyFJkslPUVFRTZ9SpW7fBC24CEZERKQaVQNQWloaJk6ciD179iA5ORmlpaWIjo7G9evXAQCFhYXIyMjA66+/joyMDCQlJeHEiRPo37//Xfv29PRETk6O0Y+Li0tNn1KVcQmMiIhIPU5qvvl3331n9DghIQF+fn44ePAgunfvDi8vLyQnJxu1+eCDD9ChQwdkZ2ejUaNGFfYtSRICAgJqZNyWkrgIRkREZBNUDUB3ysvLAwB4e3tX2kaSJNStW7fSvgoKChAcHIyysjK0bt0ab775JsLDw822LS4uRnFxsfxYp9MBuLkEp9frq3kWFSstLZP/+2bfNlX+WsXwuVnz8yNTrLNyWGtlsM7KqKk6V6c/SdjIbcmFEBgwYACuXr2KnTt3mm1TVFSEbt26oXnz5vjqq68q7GvPnj04deoUwsLCoNPp8P7772PLli04fPgwmjVrZtI+NjYWc+bMMTm+atUquLm5WX5Sd9CXAy/uvRl65rcvhQvzDxERkdUUFhZi5MiRyMvLg6enZ6VtbSYATZw4EZs3b8auXbvQoEEDk+f1ej2eeeYZZGdnIzU19a4ndrvy8nK0adMG3bt3x+LFi02eNzcD1LBhQ1y6dKla73M3xfoytJj7AwBg78zH4O3harW+yZher0dycjKioqKg0WjUHk6txTorh7VWBuusjJqqs06ng6+vb5UCkE3MQUyePBkbN27Ejh07Kgw/Q4cORVZWFrZt21btUOLg4ID27dvj5MmTZp/XarXQarUmxzUajVU/mHLp1p5zjcaJf1wKsPZnSOaxzsphrZXBOivD2nWuTl+qXgUmhMCkSZOQlJSEbdu2oXHjxiZtDOHn5MmTSElJgY+Pj0Xvk5mZicDAQGsM22K3b4K2jXk3IiIi+6TqDNDEiROxatUqbNiwAR4eHsjNzQUAeHl5wdXVFaWlpRgyZAgyMjKwadMmlJWVyW28vb3h7OwMABgzZgzq16+PuLg4AMCcOXPQqVMnNGvWDDqdDosXL0ZmZiY+/PBDdU7UDOYfIiIi9agagD766CMAQGRkpNHxhIQEjBs3DufOncPGjRsBAK1btzZqs337dvl12dnZcHC4NZl17do1TJgwAbm5ufDy8kJ4eDh27NiBDh061Ni5VAXvBk9ERGQbVA1Ad9t/HRISctc2AJCammr0eNGiRVi0aNG9DK1G3J5/uARGRESkHt4LTEFGN0PlIhgREZFqGIBUwhkgIiIi9TAAKYhbgIiIiGwDA5CCjO8GT0RERGphAFKQZJSAGIGIiIjUwgCkEsYfIiIi9TAAERERkd1hAFKYYRWMK2BERETqYQBSmGEXEPMPERGRehiAiIiIyO4wACnMcCVYVW7xQURERDWDAUhhXAIjIiJSHwOQSjgBREREpB4GIIVJvB8GERGR6hiAiIiIyO4wACmMm6CJiIjUxwCkEsYfIiIi9TAAKYxbgIiIiNTHAKQw3gqDiIhIfQxACrv1PUBMQERERGphACIiIiK7wwCksFtXgak8ECIiIjvGAKQw3gqDiIhIfQxAamECIiIiUg0DkNJ4HTwREZHqGIAUJv2VgHgVGBERkXoYgBTG7wEiIiJSHwMQERER2R0GIIXJV4FxBoiIiEg1DEAKk5fA1B0GERGRXWMAUpi8CZpTQERERKphACIiIiK7o2oAiouLQ/v27eHh4QE/Pz8MHDgQx48fN2ojhEBsbCyCgoLg6uqKyMhI/PTTT3fte+3atQgNDYVWq0VoaCjWrVtXU6dRLVwCIyIiUp+qASgtLQ0TJ07Enj17kJycjNLSUkRHR+P69etymwULFmDhwoVYsmQJ9u/fj4CAAERFRSE/P7/CftPT0zFs2DCMHj0ahw8fxujRozF06FDs3btXidOqGiYgIiIi1Tip+ebfffed0eOEhAT4+fnh4MGD6N69O4QQiI+Px6xZszB48GAAwOeffw5/f3+sWrUK//jHP8z2Gx8fj6ioKMTExAAAYmJikJaWhvj4eKxevbpmT+oubs0AMQERERGpRdUAdKe8vDwAgLe3NwAgKysLubm5iI6OlttotVpERERg9+7dFQag9PR0TJs2zehYz549ER8fb7Z9cXExiouL5cc6nQ4AoNfrodfrLT4fs/7KPaWlpdbvm2SG2rLGNYt1Vg5rrQzWWRk1Vefq9GczAUgIgenTp6Nbt25o0aIFACA3NxcA4O/vb9TW398fZ86cqbCv3Nxcs68x9HenuLg4zJkzx+T41q1b4ebmVq3zuJsSvSMACbt3p+O0u1W7JjOSk5PVHoJdYJ2Vw1org3VWhrXrXFhYWOW2NhOAJk2ahCNHjmDXrl0mz0mS8R1EhRAmx+7lNTExMZg+fbr8WKfToWHDhoiOjoanp2dVT6FK5h5JRYG+BJ06d0aLBvWs2jfdotfrkZycjKioKGg0GrWHU2uxzsphrZXBOiujpupsWMGpCpsIQJMnT8bGjRuxY8cONGjQQD4eEBAA4OaMTmBgoHz84sWLJjM8twsICDCZ7ansNVqtFlqt1uS4RqOx+h+AIYM5OTnxj0sBNfEZkinWWTmstTJYZ2VYu87V6UvVq8CEEJg0aRKSkpKwbds2NG7c2Oj5xo0bIyAgwGiKrKSkBGlpaejSpUuF/Xbu3NlkWm3r1q2VvkYpvBUGERGR+lSdAZo4cSJWrVqFDRs2wMPDQ5618fLygqurKyRJwtSpU/H222+jWbNmaNasGd5++224ublh5MiRcj9jxoxB/fr1ERcXBwCYMmUKunfvjvnz52PAgAHYsGEDUlJSzC6vKc2wDMerwIiIiNSjagD66KOPAACRkZFGxxMSEjBu3DgAwMyZM3Hjxg288MILuHr1Kjp27IitW7fCw8NDbp+dnQ0Hh1uTWV26dEFiYiJee+01vP7662jatCnWrFmDjh071vg53Q1ngIiIiNSnagCqyv2wJElCbGwsYmNjK2yTmppqcmzIkCEYMmTIPYyOiIiIaiveC0xplV+8RkRERApgAFIYl8CIiIjUxwCkMG6CJiIiUh8DEBEREdkdBiCFcQmMiIhIfQxACrt1N3giIiJSCwMQERER2Z1qByC9Xo8ePXrgxIkTNTGeWu/WEhjngIiIiNRS7QCk0Whw7Nixu96NnSogXwVGREREarFoCWzMmDFYvny5tcdiF+TYyARERESkGotuhVFSUoLPPvsMycnJaNeuHdzd3Y2eX7hwoVUGR0RERFQTLApAx44dQ5s2bQDAZC8Ql8Yqx6vAiIiI1GdRANq+fbu1x2E3pL8WwbgJmoiISD33fBn8uXPncP78eWuMxS5wBoiIiEh9FgWg8vJyzJ07F15eXggODkajRo1Qt25dvPnmmygvL7f2GImIiIisyqIlsFmzZmH58uWYN28eunbtCiEEfvzxR8TGxqKoqAhvvfWWtcdZa/BWGEREROqzKAB9/vnn+Oyzz9C/f3/5WKtWrVC/fn288MILDECVuLUExgRERESkFouWwK5cuYLmzZubHG/evDmuXLlyz4Oq3XiVHBERkdosCkCtWrXCkiVLTI4vWbIErVq1uudB2QMugREREanHoiWwBQsWoG/fvkhJSUHnzp0hSRJ2796Ns2fPYsuWLdYeY63Cr0kiIiJSn0UzQBEREThx4gQGDRqEa9eu4cqVKxg8eDCOHz+Oxx57zNpjrFW4CZqIiEh91Z4B0uv1iI6Oxscff8zNzkRERHRf4t3gFcarwIiIiNTHu8Er7NatMFQeCBERkR3j3eAVxokzIiIi9fFu8CrhBBAREZF6qh2AysrKEBsbi7CwMHh7e9fEmGo1XgVGRESkvmrvAXJ0dETPnj2Rl5dXE+Op/f6aIeMmaCIiIvVYtAk6LCwMv//+u7XHYhe4QEhERKQ+iwLQW2+9hRdffBGbNm1CTk4OdDqd0Q9VASeAiIiIVGPRJuhevXoBAPr372+06VkIAUmSUFZWZp3R1UK3vgeIiIiI1GJRANq+fbtV3nzHjh145513cPDgQeTk5GDdunUYOHCg/HxFV5QtWLAAL730ktnnVq5ciWeffdbk+I0bN+Di4mKVcd8LOQBxFzQREZFqLApAERERVnnz69evo1WrVnj22Wfx9NNPmzyfk5Nj9Ph///sfnnvuObNtb+fp6Ynjx48bHbOF8ENERES2oVp7gBYsWIAbN27Ij3fs2IHi4mL5cX5+Pl544YUq99e7d2/8+9//xuDBg80+HxAQYPSzYcMG9OjRA02aNKm0X0mSTF5rK+RvglZ5HERERPasWjNAMTExGDduHFxdXQEATz31FDIzM+VAUlhYiI8//hhLly61+kD/+OMPbN68GZ9//vld2xYUFCA4OBhlZWVo3bo13nzzTYSHh1fYvri42CjIGTZy6/V66PX6ex+8kZvRp1RfWgN9k4GhtqxxzWKdlcNaK4N1VkZN1bk6/VUrAN25b0XJfSyff/45PDw8KpwtMmjevDlWrlyJsLAw6HQ6vP/+++jatSsOHz6MZs2amX1NXFwc5syZY3J869atcHNzs8r4DXR5jgAkHMrMRMmZQ1btm0wlJyerPQS7wDorh7VWBuusDGvXubCwsMptLdoDpIYVK1Zg1KhRd93L06lTJ3Tq1El+3LVrV7Rp0wYffPABFi9ebPY1MTExmD59uvxYp9OhYcOGiI6Ohqenp3VO4C+fnUkHruejdevWiHo00Kp90y16vR7JycmIioqCRqNRezi1FuusHNZaGayzMmqqztX5Kp77IgDt3LkTx48fx5o1a6r9WgcHB7Rv3x4nT56ssI1Wq4VWqzU5rtForP4HIDnc3APk4OjIPy4F1MRnSKZYZ+Ww1spgnZVh7TpXp69qB6DPPvsMderUAQCUlpZi5cqV8PX1BXBzE3RNWL58Odq2bYtWrVpV+7VCCGRmZiIsLKwGRlZ9hk3Q3AVNRESknmoFoEaNGuHTTz+VHwcEBODLL780aVNVBQUFOHXqlPw4KysLmZmZ8Pb2lvvR6XT45ptv8N5775ntY8yYMahfvz7i4uIAAHPmzEGnTp3QrFkz6HQ6LF68GJmZmfjwww+rPK6aVMFXGxEREZGCqhWATp8+bdU3P3DgAHr06CE/NuzDGTt2LFauXAkASExMhBACI0aMMNtHdnY2HBxuXc1/7do1TJgwAbm5ufDy8kJ4eDh27NiBDh06WHXs94oTQEREROqxaA/QF198gWHDhpnsmykpKUFiYiLGjBlTpX4iIyPveiXZhAkTMGHChAqfT01NNXq8aNEiLFq0qErvrwbDBBC/CJqIiEg9Ft0M9dlnn0VeXp7J8fz8fLO3oaBbDLf3EJwDIiIiUo1FAchw09M7nTt3Dl5eXvc8qNrMQb4XmLrjICIismfVWgILDw+HJEmQJAlPPPEEnJxuvbysrAxZWVnyneLJPENwLGcCIiIiUk21ApDhTu2ZmZno2bOnfDk8ADg7OyMkJOSuNyq1d5wBIiIiUl+1AtDs2bMBACEhIRg+fLjZLw+kyjlwBoiIiEh1Fu0Bevzxx/Hnn3/Kj/ft24epU6fik08+sdrAaivD1qly5h8iIiLVWBSARo4cie3btwMAcnNz8eSTT2Lfvn149dVXMXfuXKsOsLbhDBAREZH6LApAx44dk79Y8D//+Q/CwsKwe/durFq1Sv4CQzLPkQGIiIhIdRYFIL1eL+//SUlJQf/+/QEAzZs3R05OjvVGVwtxCYyIiEh9FgWgRx99FMuWLcPOnTuRnJwsX/p+4cIF+Pj4WHWAtY1hCexu34BNRERENceiADR//nx8/PHHiIyMxIgRI+S7tG/cuNHm7rllaxw4A0RERKQ6i+4FFhkZiUuXLkGn06FevXry8QkTJsDNzc1qg6uN+EWIRERE6rNoBgi4uYRz8OBBfPzxx8jPzwdw88sQGYAqJ88AcQqIiIhINRbNAJ05cwa9evVCdnY2iouLERUVBQ8PDyxYsABFRUVYtmyZtcdZazg6GGaAVB4IERGRHbNoBmjKlClo164drl69CldXV/n4oEGD8MMPP1htcLURl8CIiIjUZ9EM0K5du/Djjz/C2dnZ6HhwcDDOnz9vlYHVVtwETUREpD6LZoDKy8tRVlZmcvzcuXPw8PC450HVZrwMnoiISH0WBaCoqCjEx8fLjyVJQkFBAWbPno0+ffpYa2y1EmeAiIiI1GfREtiiRYvQo0cPhIaGoqioCCNHjsTJkyfh6+uL1atXW3uMtYphD1AZExAREZFqLApAQUFByMzMxOrVq5GRkYHy8nI899xzGDVqlNGmaDJluAqMS2BERETqsSgAAYCrqyvGjx+P8ePHW3M8tR6XwIiIiNRX5QC0cePGKndquDkqmeJl8EREROqrcgAaOHBgldpJkmT2CjG6yTADxPxDRESknioHoPLy8poch91w4AwQERGR6iy+FxhZRr4KjAGIiIhINVWeAVq8eHGVO/3Xv/5l0WDsAZfAiIiI1FflALRo0aIqtZMkiQGoEo5cAiMiIlJdlQNQVlZWTY7Dbki8DJ6IiEh13AOkMN4LjIiISH0WfxHiuXPnsHHjRmRnZ6OkpMTouYULF97zwGqrW1eBqTwQIiIiO2ZRAPrhhx/Qv39/NG7cGMePH0eLFi1w+vRpCCHQpk0ba4+xVjFsgua9wIiIiNRj0RJYTEwMZsyYgWPHjsHFxQVr167F2bNnERERgWeeecbaY6xVJC6BERERqc6iAPTLL79g7NixAAAnJyfcuHEDderUwdy5czF//vwq97Njxw7069cPQUFBkCQJ69evN3p+3LhxkCTJ6KdTp0537Xft2rUIDQ2FVqtFaGgo1q1bV63zq0mOf1WcE0BERETqsSgAubu7o7i4GMDNO8P/9ttv8nOXLl2qcj/Xr19Hq1atsGTJkgrb9OrVCzk5OfLPli1bKu0zPT0dw4YNw+jRo3H48GGMHj0aQ4cOxd69e6s8rprEe4ERERGpz6I9QJ06dcKPP/6I0NBQ9O3bFzNmzMDRo0eRlJRUpRkag969e6N3796VttFqtQgICKhyn/Hx8YiKikJMTAyAm8t1aWlpiI+Px+rVq6vcT03hJmgiIiL1WRSAFi5ciIKCAgBAbGwsCgoKsGbNGjz44INV/sLEqkpNTYWfnx/q1q2LiIgIvPXWW/Dz86uwfXp6OqZNm2Z0rGfPnoiPj6/wNcXFxfKMFgDodDoAgF6vh16vv7cTuIMov3mj2LKyMqv3TbcYassa1yzWWTmstTJYZ2XUVJ2r059FAahJkybyf7u5uWHp0qWWdHNXvXv3xjPPPIPg4GBkZWXh9ddfx+OPP46DBw9Cq9WafU1ubi78/f2Njvn7+yM3N7fC94mLi8OcOXNMjm/duhVubm73dhJ3+O28BMARZ8+dx5YtZ63aN5lKTk5Wewh2gXVWDmutDNZZGdauc2FhYZXbWvw9QAYFBQUmd4r39PS8124BAMOGDZP/u0WLFmjXrh2Cg4OxefNmDB48uMLXGfbZGAghTI7dLiYmBtOnT5cf63Q6NGzYENHR0VY7F4Ps1FPYlP07AoOC0KdPS6v2Tbfo9XokJycjKioKGo1G7eHUWqyzclhrZbDOyqipOhtWcKrCogCUlZWFSZMmITU1FUVFRfJxQ9AoKyuzpNu7CgwMRHBwME6ePFlhm4CAAJPZnosXL5rMCt1Oq9WanVHSaDRW/wPQaAwll/jHpYCa+AzJFOusHNZaGayzMqxd5+r0ZVEAGjVqFABgxYoV8Pf3r3R2xZouX76Ms2fPIjAwsMI2nTt3RnJystE+oK1bt6JLly5KDPGuuAmaiIhIfRYFoCNHjuDgwYN4+OGH7+nNCwoKcOrUKflxVlYWMjMz4e3tDW9vb8TGxuLpp59GYGAgTp8+jVdffRW+vr4YNGiQ/JoxY8agfv36iIuLAwBMmTIF3bt3x/z58zFgwABs2LABKSkp2LVr1z2N1Vpu3QyVCYiIiEgtFn0PUPv27XH27L1v4D1w4ADCw8MRHh4OAJg+fTrCw8PxxhtvwNHREUePHsWAAQPw0EMPYezYsXjooYeQnp4ODw8PuY/s7Gzk5OTIj7t06YLExEQkJCSgZcuWWLlyJdasWYOOHTve83it4dbNUFUeCBERkR2zaAbos88+w/PPP4/z58+jRYsWJmtuLVtWbXNvZGRkpbeE+P777+/aR2pqqsmxIUOGYMiQIVUag9Lke4ExAREREanGogD0559/4rfffsOzzz4rH5MkqcY3QdcG/CZoIiIi9VkUgMaPH4/w8HCsXr1a0U3QtYEjl8CIiIhUZ1EAOnPmDDZu3IgHH3zQ2uOp9Ry4CZqIiEh1Fm2Cfvzxx3H48GFrj8UucAmMiIhIfRbNAPXr1w/Tpk3D0aNHERYWZrIJun///lYZXG0kzwCVV96OiIiIao5FAej5558HAMydO9fkOW6CrpwDZ4CIiIhUZ1EAuvPeX1R1t/YAqTsOIiIie1atPUB79+7F//73P6NjX3zxBRo3bgw/Pz9MmDABxcXFVh1gbePgYLgKjAmIiIhILdUKQLGxsThy5Ij8+OjRo3juuefw5JNP4pVXXsG3334r35KCzOMSGBERkfqqFYAyMzPxxBNPyI8TExPRsWNHfPrpp5g+fToWL16M//znP1YfZG3CJTAiIiL1VSsAXb16Ff7+/vLjtLQ09OrVS35srXuE1Wa8DJ6IiEh91QpA/v7+yMrKAgCUlJQgIyMDnTt3lp/Pz883uSSejHm53tx3/md+icojISIisl/VCkC9evXCK6+8gp07dyImJgZubm547LHH5OePHDmCpk2bWn2QtclD/jfvZJ99tRDXi0tVHg0REZF9qlYA+ve//w1HR0dERETg008/xaeffgpnZ2f5+RUrViA6Otrqg6xNfNyd4akREALYfvyi2sMhIiKyS9X6HqAHHngAO3fuRF5eHurUqQNHR0ej57/55hvUqVPHqgOsjdo/IPDDBQnrD13AUy2D1B4OERGR3bHoXmBeXl4m4QcAvL29jWaEyLyHvG5ugD59+brKIyEiIrJPFgUgujcPuNwMQKcuFuD8tRsqj4aIiMj+MACpoJ4WcHe+OYPWdd42JP/8h8ojIiIisi8MQCpwkIC3Bj4qPz52Pk/F0RAREdkfBiCV9A0LwP91awwAKCotU3k0RERE9oUBSEUumpvLYEUlDEBERERKYgBSketf+4CK9OUqj4SIiMi+MACpSOt0s/xcAiMiIlIWA5CKDDNAN7gERkREpCgGIBW5OP21BFbKJTAiIiIlMQCpiJugiYiI1MEApCJXZ+4BIiIiUgMDkIrkJTA9AxAREZGSGIBU5GLYBM0AREREpCgGIBXdmgHiJmgiIiIlMQCpSKu5Wf5izgAREREpStUAtGPHDvTr1w9BQUGQJAnr16+Xn9Pr9Xj55ZcRFhYGd3d3BAUFYcyYMbhw4UKlfa5cuRKSJJn8FBUV1fDZVJ+jJAEAyoXKAyEiIrIzqgag69evo1WrVliyZInJc4WFhcjIyMDrr7+OjIwMJCUl4cSJE+jfv/9d+/X09EROTo7Rj4uLS02cwj1xdLgZgMqYgIiIiBTlpOab9+7dG7179zb7nJeXF5KTk42OffDBB+jQoQOys7PRqFGjCvuVJAkBAQFWHWtNcHJkACIiIlKDqgGouvLy8iBJEurWrVtpu4KCAgQHB6OsrAytW7fGm2++ifDw8ArbFxcXo7i4WH6s0+kA3FyG0+v1Vhm7gaE/vV6P8rKbm59Ly8ut/j727vY6U81hnZXDWiuDdVZGTdW5Ov1JQgibmH6QJAnr1q3DwIEDzT5fVFSEbt26oXnz5vjqq68q7GfPnj04deoUwsLCoNPp8P7772PLli04fPgwmjVrZvY1sbGxmDNnjsnxVatWwc3NzaLzqYoCPTDrwM0MGt+pFH9tCSIiIiILFBYWYuTIkcjLy4Onp2elbe+LAKTX6/HMM88gOzsbqampdz2p25WXl6NNmzbo3r07Fi9ebLaNuRmghg0b4tKlS9V6r6rQ6/VITk5GVFQUruuB9nHbAQC/xD4JJ0delGctt9dZo9GoPZxai3VWDmutDNZZGTVVZ51OB19f3yoFIJtfAtPr9Rg6dCiysrKwbdu2agcSBwcHtG/fHidPnqywjVarhVarNTmu0Whq7A9Ao9HA5ba8Izk6QfPXvcHIemryM6RbWGflsNbKYJ2VYe06V6cvm55yMISfkydPIiUlBT4+PtXuQwiBzMxMBAYG1sAI742Tw63yl9vGRBwREZFdUHUGqKCgAKdOnZIfZ2VlITMzE97e3ggKCsKQIUOQkZGBTZs2oaysDLm5uQAAb29vODs7AwDGjBmD+vXrIy4uDgAwZ84cdOrUCc2aNYNOp8PixYuRmZmJDz/8UPkTvIvb8g9KeSUYERGRYlQNQAcOHECPHj3kx9OnTwcAjB07FrGxsdi4cSMAoHXr1kav2759OyIjIwEA2dnZcLgtSVy7dg0TJkxAbm4uvLy8EB4ejh07dqBDhw41ezIWuH0GqKyMAYiIiEgpqgagyMhIVLYHuyr7s1NTU40eL1q0CIsWLbrXoSnC4barvsq4BEZERKQYm94DVNtJksRvgyYiIlIBA5DKDAGIe4CIiIiUwwCkMqe/AlA5AxAREZFiGIBUZrgjPGeAiIiIlMMApDJH+Yao5SqPhIiIyH4wAKnMSd4ErfJAiIiI7AgDkMoc5CUwJiAiIiKlMACp7NYmaJUHQkREZEcYgFRm2APEGSAiIiLlMACpzHAVGL8IkYiISDkMQCrjN0ETEREpjwFIZQxAREREymMAUpnjX3eE5xchEhERKYcBSGXy9wDxbvBERESKYQBSmYMhAJUxABERESmFAUhlTrwbPBERkeIYgFRm2ARdziUwIiIixTAAqYx3gyciIlIeA5DKnHg3eCIiIsUxAKnMsARWyk3QREREimEAUpmrxhEAcENfpvJIiIiI7AcDkMq8XDUAgLxCvcojISIish8MQCrz/CsA6YoYgIiIiJTCAKQyeQboBgMQERGRUhiAVObp4gQA0N0oVXkkRERE9oMBSGWenAEiIiJSHAOQygxLYNcYgIiIiBTDAKSyAC8XAMCFazdUHgkREZH9YABSWbC3O4CbS2BXr5eoPBoiIiL7wACkMldnRwR43pwF2v3bZZTznmBEREQ1jgHIBrQLqQcAmLgqA9HxO3CjhN8KTUREVJNUDUA7duxAv379EBQUBEmSsH79eqPnhRCIjY1FUFAQXF1dERkZiZ9++umu/a5duxahoaHQarUIDQ3FunXraugMrGNa1ENo5O0GADh1sQD/+OogFiafwMLkE9h8JEfl0REREdU+qgag69evo1WrVliyZInZ5xcsWICFCxdiyZIl2L9/PwICAhAVFYX8/PwK+0xPT8ewYcMwevRoHD58GKNHj8bQoUOxd+/emjqNe9b0gTrYMbMH3n2mFQBgx4k/sfiHk1j8w0lMXJWB3/4sUHmEREREtYuTmm/eu3dv9O7d2+xzQgjEx8dj1qxZGDx4MADg888/h7+/P1atWoV//OMfZl8XHx+PqKgoxMTEAABiYmKQlpaG+Ph4rF69umZOxEqGtG2Aem4a7Pn9Mor05Ug9cRFnr9zA/qwraPpAHbWHR0REVGvY7B6grKws5ObmIjo6Wj6m1WoRERGB3bt3V/i69PR0o9cAQM+ePSt9jS154hF/zOobijcHtsBTLYMAAMcu5Kk8KiIiotpF1RmgyuTm5gIA/P39jY77+/vjzJkzlb7O3GsM/ZlTXFyM4uJi+bFOpwMA6PV66PXW/YJCQ39V6beuiyMAIP+G9cdR21WnzmQ51lk5rLUyWGdl1FSdq9OfzQYgA0mSjB4LIUyO3etr4uLiMGfOHJPjW7duhZubWzVGW3XJycl3bXMqVwLgiKyz57Fly9kaGUdtV5U6071jnZXDWiuDdVaGtetcWFhY5bY2G4ACAgIA3JzRCQwMlI9fvHjRZIbnztfdOdtzt9fExMRg+vTp8mOdToeGDRsiOjoanp6elp6CWXq9HsnJyYiKioJGo6m0bfGhC/gm6xjq+jyAPn3aWnUctV116kyWY52Vw1org3VWRk3V2bCCUxU2G4AaN26MgIAAJCcnIzw8HABQUlKCtLQ0zJ8/v8LXde7cGcnJyZg2bZp8bOvWrejSpUuFr9FqtdBqtSbHNRpNjf0BVKXvOq7OAICiUsE/RAvV5GdIt7DOymGtlcE6K8Pada5OX6oGoIKCApw6dUp+nJWVhczMTHh7e6NRo0aYOnUq3n77bTRr1gzNmjXD22+/DTc3N4wcOVJ+zZgxY1C/fn3ExcUBAKZMmYLu3btj/vz5GDBgADZs2ICUlBTs2rVL8fO7V66am3uAivT8YkQiIiJrUjUAHThwAD169JAfG5ahxo4di5UrV2LmzJm4ceMGXnjhBVy9ehUdO3bE1q1b4eHhIb8mOzsbDg63Lmbr0qULEhMT8dprr+H1119H06ZNsWbNGnTs2FG5E7MSl78CEL8ZmoiIyLpUDUCRkZEQouJ7X0mShNjYWMTGxlbYJjU11eTYkCFDMGTIECuMUF2uzn8FIM4AERERWZXNfg8QcQmMiIiopjAA2TBDACrkEhgREZFVMQDZMBfnmx/PDX1ZpUuFREREVD0MQDbMMAMkBFBcWq7yaIiIiGoPBiAbpnG89fGUlDEAERERWQsDkA1zdLh1+47yci6BERERWQsDkA1zvO3+ZWUMQERERFbDAGTDHG6bASrjJmgiIiKrYQCycYZlsHJuASIiIrIaBiAbZ1gG4wwQERGR9TAA2TjDbc64CZqIiMh6GIBsnDwDxABERERkNQxANs6wEZpLYERERNbDAGTjDJugeSsMIiIi62EAsnG3lsBUHggREVEtwgBk4+QlMO4BIiIishoGIBtnmAEq5xIYERGR1TAA2ThHzgARERFZHQOQjTN8DxCvAiMiIrIeBiAbJy+BcQaIiIjIahiAbBw3QRMREVkfA5CN473AiIiIrI8ByMbxbvBERETWxwBk4xw4A0RERGR1DEA27tYMEAMQERGRtTAA2ThugiYiIrI+BiAb53gz/3AJjIiIyIoYgGwcl8CIiIisjwHIxnETNBERkfUxANk43guMiIjI+hiAbJy8BMYZICIiIqthALJx8hIYvwiRiIjIamw+AIWEhECSJJOfiRMnmm2fmppqtv2vv/6q8Mitg5ugiYiIrM9J7QHczf79+1FWViY/PnbsGKKiovDMM89U+rrjx4/D09NTfvzAAw/U2BhrEjdBExERWZ/NB6A7g8u8efPQtGlTREREVPo6Pz8/1K1btwZHpgzHv+bouAmaiIjIemw+AN2upKQEX331FaZPnw7pr5mRioSHh6OoqAihoaF47bXX0KNHjwrbFhcXo7i4WH6s0+kAAHq9Hnq93jqD/4uhv6r2azhLfWmp1cdSm1W3zmQZ1lk5rLUyWGdl1FSdq9OfJMT9s7byn//8ByNHjkR2djaCgoLMtjl+/Dh27NiBtm3bori4GF9++SWWLVuG1NRUdO/e3exrYmNjMWfOHJPjq1atgpubm1XPobpWnnDAocsOGBxShojA++ajIiIiUlxhYSFGjhyJvLw8o20w5txXAahnz55wdnbGt99+W63X9evXD5IkYePGjWafNzcD1LBhQ1y6dOmuBawuvV6P5ORkREVFQaPR3LX99G+O4NsjuXi198N4tkuwVcdSm1W3zmQZ1lk5rLUyWGdl1FSddTodfH19qxSA7pslsDNnziAlJQVJSUnVfm2nTp3w1VdfVfi8VquFVqs1Oa7RaGrsD6CqfWscHW/+hyTxj9ECNfkZ0i2ss3JYa2Wwzsqwdp2r05fNXwZvkJCQAD8/P/Tt27farz106BACAwNrYFQ179bd4FUeCBERUS1yX8wAlZeXIyEhAWPHjoWTk/GQY2JicP78eXzxxRcAgPj4eISEhODRRx+VN02vXbsWa9euVWPo98xR4jdBExERWdt9EYBSUlKQnZ2N8ePHmzyXk5OD7Oxs+XFJSQlefPFFnD9/Hq6urnj00UexefNm9OnTR8khW40D7wVGRERkdfdFAIqOjkZFe7VXrlxp9HjmzJmYOXOmAqNShrPjzQCku8FLMomIiKzlvghA9qxNcD18nn4Gn+3Kwqk/C+AgSZAA3P41SA3quWFijwfxgIfpRm4iIiIyxQBk4x5v7odALxfk5BUh9fifFbZbvS8bzQM94eQgwaHy74i0aRKsM/hyUY6rVxzx5YV9cJAU2Ot/X9fcckIIXLniiK9z9t/1y0mtydFBQnSoP8Z2CVH0fYmo9mAAsnEeLhpsmtwNu05dQklpOYQABG4tBxaXliNx31n8nKPD4bPX1BuoTZKA/GtqD8IOSIDuquLvuvu3y6jn7oz+rYIYgoio2hiA7gM+dbQY0Lp+hc8Pb98IB05fwfWSMpSV3wxJ9ubOUy4tLcWhQ4cQHh5ucuVgbaL2Z11WVoqMQ4fQJjwcjo7K1XnbrxexNuMcpiRmYkpiptlZT3Oh6M4j5nKT2VlIqdKHVe7LfJs7+zE/bgGgtNQRszK23XxNlcZkpi9LX3eXfirqrWrvZ66nymsn4eZFIo4O5ueNOzb2wbynwxiOqUK1918GO+Ls5IAuD/qqPQybotfrIbIFercI4JeZ1SC16vxkqB9O/JGPo+fzAABmL5K0OB3a8v+CkICyUrUHcV84fbkQ06IeQoCXi9pDIRvFAERE9x2tkyM2TOyK/KJS6MvLTb8ny0yGufOQuXwkzLywCl2bvUq1KvnLtO+K+yktLUVqaioiIyPheMesptn3r8L7mWtlvi5VaVOF2ln4OnPKhUBZuTD7HWkTvz6EXF0Rzl0tZACiCjEAEdF9ycFBgpeb/czu6fV6POAKBPu4cVbzLkJ83ZCrK0L6b5erHYBKS0txpRg4f+0GnJz49SM1pbS0FLoSdcfAAERERLVKg3puAK7gveQTeC/5hAU9OGFOxk5rD4vuEFLHEcNVfH8GICIiqlWGt2+IvVmXcVFXbNHry8vK4GC4ETXVGCeHMnXfX9V3JyIisrJ2Id7YOfNxi16r1+uxZcsW9OnTk0uNNchQZzXdN3eDJyIiIrIWBiAiIiKyOwxAREREZHcYgIiIiMjuMAARERGR3WEAIiIiIrvDAERERER2hwGIiIiI7A4DEBEREdkdBiAiIiKyOwxAREREZHcYgIiIiMjuMAARERGR3WEAIiIiIrvjpPYAbJEQAgCg0+ms3rder0dhYSF0Oh00Go3V+6ebWGdlsM7KYa2VwToro6bqbPh32/DveGUYgMzIz88HADRs2FDlkRAREVF15efnw8vLq9I2kqhKTLIz5eXluHDhAjw8PCBJklX71ul0aNiwIc6ePQtPT0+r9k23sM7KYJ2Vw1org3VWRk3VWQiB/Px8BAUFwcGh8l0+nAEyw8HBAQ0aNKjR9/D09OQflwJYZ2WwzsphrZXBOiujJup8t5kfA26CJiIiIrvDAERERER2hwFIYVqtFrNnz4ZWq1V7KLUa66wM1lk5rLUyWGdl2EKduQmaiIiI7A5ngIiIiMjuMAARERGR3WEAIiIiIrvDAERERER2hwFIQUuXLkXjxo3h4uKCtm3bYufOnWoP6b4SFxeH9u3bw8PDA35+fhg4cCCOHz9u1EYIgdjYWAQFBcHV1RWRkZH46aefjNoUFxdj8uTJ8PX1hbu7O/r3749z584peSr3lbi4OEiShKlTp8rHWGfrOH/+PP72t7/Bx8cHbm5uaN26NQ4ePCg/zzpbR2lpKV577TU0btwYrq6uaNKkCebOnYvy8nK5DWtdfTt27EC/fv0QFBQESZKwfv16o+etVdOrV69i9OjR8PLygpeXF0aPHo1r167d+wkIUkRiYqLQaDTi008/FT///LOYMmWKcHd3F2fOnFF7aPeNnj17ioSEBHHs2DGRmZkp+vbtKxo1aiQKCgrkNvPmzRMeHh5i7dq14ujRo2LYsGEiMDBQ6HQ6uc3zzz8v6tevL5KTk0VGRobo0aOHaNWqlSgtLVXjtGzavn37REhIiGjZsqWYMmWKfJx1vndXrlwRwcHBYty4cWLv3r0iKytLpKSkiFOnTsltWGfr+Pe//y18fHzEpk2bRFZWlvjmm29EnTp1RHx8vNyGta6+LVu2iFmzZom1a9cKAGLdunVGz1urpr169RItWrQQu3fvFrt37xYtWrQQTz311D2PnwFIIR06dBDPP/+80bHmzZuLV155RaUR3f8uXrwoAIi0tDQhhBDl5eUiICBAzJs3T25TVFQkvLy8xLJly4QQQly7dk1oNBqRmJgotzl//rxwcHAQ3333nbInYOPy8/NFs2bNRHJysoiIiJADEOtsHS+//LLo1q1bhc+zztbTt29fMX78eKNjgwcPFn/729+EEKy1NdwZgKxV059//lkAEHv27JHbpKenCwDi119/vacxcwlMASUlJTh48CCio6ONjkdHR2P37t0qjer+l5eXBwDw9vYGAGRlZSE3N9eozlqtFhEREXKdDx48CL1eb9QmKCgILVq04Gdxh4kTJ6Jv37548sknjY6zztaxceNGtGvXDs888wz8/PwQHh6OTz/9VH6edbaebt264YcffsCJEycAAIcPH8auXbvQp08fAKx1TbBWTdPT0+Hl5YWOHTvKbTp16gQvL697rjtvhqqAS5cuoaysDP7+/kbH/f39kZubq9Ko7m9CCEyfPh3dunVDixYtAECupbk6nzlzRm7j7OyMevXqmbThZ3FLYmIiMjIysH//fpPnWGfr+P333/HRRx9h+vTpePXVV7Fv3z7861//glarxZgxY1hnK3r55ZeRl5eH5s2bw9HREWVlZXjrrbcwYsQIAPydrgnWqmlubi78/PxM+vfz87vnujMAKUiSJKPHQgiTY1Q1kyZNwpEjR7Br1y6T5yypMz+LW86ePYspU6Zg69atcHFxqbAd63xvysvL0a5dO7z99tsAgPDwcPz000/46KOPMGbMGLkd63zv1qxZg6+++gqrVq3Co48+iszMTEydOhVBQUEYO3as3I61tj5r1NRce2vUnUtgCvD19YWjo6NJWr148aJJOqa7mzx5MjZu3Ijt27ejQYMG8vGAgAAAqLTOAQEBKCkpwdWrVytsY+8OHjyIixcvom3btnBycoKTkxPS0tKwePFiODk5yXVine9NYGAgQkNDjY498sgjyM7OBsDfZ2t66aWX8Morr2D48OEICwvD6NGjMW3aNMTFxQFgrWuCtWoaEBCAP/74w6T/P//8857rzgCkAGdnZ7Rt2xbJyclGx5OTk9GlSxeVRnX/EUJg0qRJSEpKwrZt29C4cWOj5xs3boyAgACjOpeUlCAtLU2uc9u2baHRaIza5OTk4NixY/ws/vLEE0/g6NGjyMzMlH/atWuHUaNGITMzE02aNGGdraBr164mX+Nw4sQJBAcHA+DvszUVFhbCwcH4nztHR0f5MnjW2vqsVdPOnTsjLy8P+/btk9vs3bsXeXl59173e9pCTVVmuAx++fLl4ueffxZTp04V7u7u4vTp02oP7b7xz3/+U3h5eYnU1FSRk5Mj/xQWFspt5s2bJ7y8vERSUpI4evSoGDFihNnLLhs0aCBSUlJERkaGePzxx+36UtaquP0qMCFYZ2vYt2+fcHJyEm+99ZY4efKk+Prrr4Wbm5v46quv5Dass3WMHTtW1K9fX74MPikpSfj6+oqZM2fKbVjr6svPzxeHDh0Shw4dEgDEwoULxaFDh+Svd7FWTXv16iVatmwp0tPTRXp6uggLC+Nl8PebDz/8UAQHBwtnZ2fRpk0b+fJtqhoAZn8SEhLkNuXl5WL27NkiICBAaLVa0b17d3H06FGjfm7cuCEmTZokvL29haurq3jqqadEdna2wmdzf7kzALHO1vHtt9+KFi1aCK1WK5o3by4++eQTo+dZZ+vQ6XRiypQpolGjRsLFxUU0adJEzJo1SxQXF8ttWOvq2759u9n/nzx27FghhPVqevnyZTFq1Cjh4eEhPDw8xKhRo8TVq1fvefySEELc2xwSERER0f2Fe4CIiIjI7jAAERERkd1hACIiIiK7wwBEREREdocBiIiIiOwOAxARERHZHQYgIiIisjsMQEREFlq5ciXq1q2r9jCIyAIMQERU43JzczFlyhQ8+OCDcHFxgb+/P7p164Zly5ahsLBQ7eFVSUhICOLj442ODRs2DCdOnFBnQER0T5zUHgAR1W6///47unbtirp16+Ltt99GWFgYSktLceLECaxYsQJBQUHo37+/KmMTQqCsrAxOTpb9v0JXV1e4urpaeVREpATOABFRjXrhhRfg5OSEAwcOYOjQoXjkkUcQFhaGp59+Gps3b0a/fv0AAHl5eZgwYQL8/Pzg6emJxx9/HIcPH5b7iY2NRevWrfHll18iJCQEXl5eGD58OPLz8+U2QggsWLAATZo0gaurK1q1aoX//ve/8vOpqamQJAnff/892rVrB61Wi507d+K3337DgAED4O/vjzp16qB9+/ZISUmRXxcZGYkzZ85g2rRpkCQJkiQBML8E9tFHH6Fp06ZwdnbGww8/jC+//NLoeUmS8Nlnn2HQoEFwc3NDs2bNsHHjRqvVm4iqhgGIiGrM5cuXsXXrVkycOBHu7u5m20iSBCEE+vbti9zcXGzZsgUHDx5EmzZt8MQTT+DKlSty299++w3r16/Hpk2bsGnTJqSlpWHevHny86+99hoSEhLw0Ucf4aeffsK0adPwt7/9DWlpaUbvOXPmTMTFxeGXX35By5YtUVBQgD59+iAlJQWHDh1Cz5490a9fP2RnZwMAkpKS0KBBA8ydOxc5OTnIyckxey7r1q3DlClTMGPGDBw7dgz/+Mc/8Oyzz2L79u1G7ebMmYOhQ4fiyJEj6NOnD0aNGmV0nkSkgHu+nSoRUQX27NkjAIikpCSj4z4+PsLd3V24u7uLmTNnih9++EF4enqKoqIio3ZNmzYVH3/8sRBCiNmzZws3Nzeh0+nk51966SXRsWNHIYQQBQUFwsXFRezevduoj+eee06MGDFCCHHr7tXr16+/69hDQ0PFBx98ID8ODg4WixYtMmqTkJAgvLy85MddunQRf//7343aPPPMM6JPnz7yYwDitddekx8XFBQISZLE//73v7uOiYish3uAiKjGGZaMDPbt24fy8nKMGjUKxcXFOHjwIAoKCuDj42PU7saNG/jtt9/kxyEhIfDw8JAfBwYG4uLFiwCAn3/+GUVFRYiKijLqo6SkBOHh4UbH2rVrZ/T4+vXrmDNnDjZt2oQLFy6gtLQUN27ckGeAquqXX37BhAkTjI517doV77//vtGxli1byv/t7u4ODw8P+TyISBkMQERUYx588EFIkoRff/3V6HiTJk0AQN5AXF5ejsDAQKSmppr0cfseG41GY/ScJEkoLy+X+wCAzZs3o379+kbttFqt0eM7l+NeeuklfP/993j33Xfx4IMPwtXVFUOGDEFJSUkVz9R4TLcTQpgcq+w8iEgZDEBEVGN8fHwQFRWFJUuWYPLkyRXuA2rTpg1yc3Ph5OSEkJAQi94rNDQUWq0W2dnZiIiIqNZrd+7ciXHjxmHQoEEAgIKCApw+fdqojbOzM8rKyirt55FHHsGuXbswZswY+dju3bvxyCOPVGs8RFTzGICIqEYtXboUXbt2Rbt27RAbG4uWLVvCwcEB+/fvx6+//oq2bdviySefROfOnTFw4EDMnz8fDz/8MC5cuIAtW7Zg4MCBJktW5nh4eODFF1/EtGnTUF5ejm7dukGn02H37t2oU6cOxo4dW+FrH3zwQSQlJaFfv36QJAmvv/66yYxMSEgIduzYgeHDh0Or1cLX19ekn5deeglDhw6VN3B/++23SEpKMrqijIhsAwMQEdWopk2b4tChQ3j77bcRExODc+fOQavVIjQ0FC+++CJeeOEFSJKELVu2YNasWRg/fjz+/PNPBAQEoHv37vD396/ye7355pvw8/NDXFwcfv/9d9StWxdt2rTBq6++WunrFi1ahPHjx6NLly7w9fXFyy+/DJ1OZ9Rm7ty5+Mc//oGmTZuiuLgYQgiTfgYOHIj3338f77zzDv71r3+hcePGSEhIQGRkZJXPgYiUIQlzf8VEREREtRi/B4iIiIjsDgMQERER2R0GICIiIrI7DEBERERkdxiAiIiIyO4wABEREZHdYQAiIiIiu8MARERERHaHAYiIiIjsDgMQERER2R0GICIiIrI7DEBERERkd/4fsqEj+8A5ulEAAAAASUVORK5CYII=",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Decoded coefficients: Intercept 3.999996, slope -9.491312, quadratic -8.975999, cubic 6.800018, quartic 2.339995, quintic -1.09005\n",
      "Polynomial regression coefficients: Intercept 4.0, slope -2.983333333333327, quadratic -4.791666666666659, cubic 3.041666666666663, quartic 1.2916666666666643, quintic -0.5583333333333323\n",
      "Encoded coefficients: Intercept 3.999996, slope -9.491312, quadratic -8.975999, cubic 6.800018, quartic 2.339995, quintic -1.09005\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"
    },
    {
     "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": [
      "Elapsed time: 0:19:17.727746\n"
     ]
    }
   ],
   "source": [
    "# Program PolynomialThePowerOfRichness.py\n",
    "# This program uses a genetic algorithm to find the polynomial \n",
    "# of fifth degree that best fits a set of 6 points.\n",
    "# The coefficients are represented by a chromosome, \n",
    "# which is a string of digits.\n",
    "# The decoding function must divide the chromosome into parts, \n",
    "# and decode each one apart as one coefficient.\n",
    "# We consider numbers of the form -3.244025\n",
    "# with a sign that could be positive or negative, \n",
    "# and a decimal point in the second place of the encoding chromosome.\n",
    "# The error of a chromosome is the sum of the vertical distances \n",
    "# of the points to the polynomial it encodes.\n",
    "# The Genetic algorithm must minimize the error, \n",
    "# (which is equivalent to maximizing the fitness).\n",
    "# In this program, it is explored the power of the population size\n",
    "# to find a good solution. \n",
    "# To that aim, we double the population size for each run, \n",
    "# to see whther perfection is found.\n",
    "# Developed with the assistance of the AI of Visual Studio Code.\n",
    "# An old version of a GA developed with the help of Gemini was reused and updated.\n",
    "\n",
    "\n",
    "from datetime import datetime, timedelta\n",
    "import datetime\n",
    "import time\n",
    "import random\n",
    "import numpy as np\n",
    "from numpy.polynomial import Polynomial\n",
    "import matplotlib.pyplot as plt # Import matplotlib for plotting\n",
    "\n",
    "\n",
    "start_time = time.time() # Record the start time\n",
    "\n",
    "#Task to be done\n",
    "number_of_generations = 1000\n",
    "\n",
    "xArray =  [-2, -1, 0, 1, 2, 3]\n",
    "yArray =  [5,   1, 4, 0, 6, 3]\n",
    "\n",
    "alphabet = '0123456789'\n",
    "# Chromosome encoding for one of 6 coefficients, \n",
    "# each one with a length of 5 chars.\n",
    "# Encoding number as -93.24 with a sign and a decimal point.\n",
    "length_of_chromosomes = 8\n",
    "population_size = 102400\n",
    "# Include cloning of the fittest\n",
    "include_clone_populationj12 = True\n",
    "# Include mutation\n",
    "include_mutate_allj12 = True\n",
    "# Include recombination\n",
    "include_crossover_allj12 = False\n",
    "mutation_rate = 0.05\n",
    "recombination_rate = 0.0\n",
    "# Size of the sampled groups from which the best \n",
    "# is chosen as a parent for the next generation.\n",
    "tournament_size = 5\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",
    "def print_parametersj12():\n",
    "    print(f\"Lab: la Evolución finds the polynomial of minimal error\")\n",
    "    print(f\"Purpose: Use a Genetic Algorithm (MAX = selection of the fittest, mutation and recombination) to find the coefficients of a polynomial that best fits a set of points.\")\n",
    "    print(\"Hint to be tested: consider only numbers of the form -3.244025 with a sign that could be positive or negative, and a decimal point in the second place of the encoding chromosome.\")\n",
    "    print(f\"Date of Experiment  = {datetime.datetime.now()}\")\n",
    "    print(f\"number_of_generations = {number_of_generations}\")\n",
    "    print(f\"length_of_chromosomes = {length_of_chromosomes}\")\n",
    "    print(f\"alphabet =  {alphabet}\")\n",
    "    print(f\"Points = {list(zip(xArray, yArray))}\")\n",
    "    print(f\"population_size = {population_size}\")\n",
    "    print(f\"include_clone_populationj12 = {include_clone_populationj12}\")\n",
    "    print(f\"include_mutate_allj12 = {include_mutate_allj12}\")\n",
    "    print(f\"include_crossover_allj12 = {include_crossover_allj12}\")\n",
    "    if include_mutate_allj12:\n",
    "        print(f\"mutation_rate = {mutation_rate}\")\n",
    "    if include_crossover_allj12:\n",
    "        print(f\"recombination_rate = {recombination_rate}\")\n",
    "    if include_clone_populationj12:\n",
    "        print(f\"print_best_fitness = {print_best_fitness}\")\n",
    "\n",
    "def draw_points_and_polynomialj12(xNumpyArray, yNumpyArray):\n",
    "    \"\"\"Draws the original data points, finds and draws the \n",
    "    regression polynomial defined by the coefficients.\"\"\"\n",
    "    \n",
    "    # 2. Fit a 5th-degree (quintic) polynomial\n",
    "    # .fit() returns a Polynomial instance\n",
    "    p_fitted = Polynomial.fit(xNumpyArray, yNumpyArray, deg=5)\n",
    "\n",
    "    # 3. Predict values for visualization\n",
    "    x_new = np.linspace(-2,3, 100) # Generate 100 points between 0 and 6 for a smooth curve\n",
    "    y_new = p_fitted(x_new)\n",
    "    b_0, b_1, b_2, b_3, b_4, b5 = p_fitted.coef\n",
    "\n",
    "    # 4. Plot results\n",
    "    plt.scatter(xNumpyArray, yNumpyArray, label='Data Points')\n",
    "    plt.xlabel('x')\n",
    "    plt.ylabel('y')\n",
    "    plt.plot(x_new, y_new, label=f'Quintic Fit: y = {b_0:.2f} + {b_1:.2f}x + {b_2:.2f}x^2 + {b_3:.2f}x^3 + {b_4:.2f}x^4 + {b5:.2f}x^5', color='green')\n",
    "    plt.title(' Data Points and Quintic Fit by numpy.polynomial.Polynomial.fit()')\n",
    "    plt.legend()\n",
    "    plt.show()\n",
    "    return p_fitted.coef\n",
    "\n",
    "\n",
    "\n",
    "def create_populationj12(population_size, length_of_chromosomes, alphabet):\n",
    "    \"\"\"Creates a new population with random chromosomes.\"\"\"\n",
    "    # print(\"create_populationj12(population_size, target_sequence, alphabet)\")\n",
    "    population = []\n",
    "    for _ in range(population_size):\n",
    "        random_string1 = ''.join(random.choice(alphabet) for _ in range(length_of_chromosomes))\n",
    "        random_string2 = ''.join(random.choice(alphabet) for _ in range(length_of_chromosomes))\n",
    "        random_string3 = ''.join(random.choice(alphabet) for _ in range(length_of_chromosomes))\n",
    "        random_string4 = ''.join(random.choice(alphabet) for _ in range(length_of_chromosomes))\n",
    "        random_string5 = ''.join(random.choice(alphabet) for _ in range(length_of_chromosomes))\n",
    "        random_string6 = ''.join(random.choice(alphabet) for _ in range(length_of_chromosomes))\n",
    "        random_string = random_string1 + random_string2 + random_string3 + random_string4 + random_string5 + random_string6\n",
    "        population.append(random_string)\n",
    "    # print(\"initial population\")\n",
    "    # print(population)\n",
    "    return population\n",
    "\n",
    "# Decode a part of the chromosome into a coefficient of the polynomial.\n",
    "def decoderOldj12(s):\n",
    "    ''' The input is a number as string, outputs the number as a float. \n",
    "        We consider numbers of the form 93.24 with a sign that could be positive or negative,\n",
    "    '''\n",
    "    l = len(s) \n",
    "    # The first char encodes for the sign, \n",
    "    sign = 1\n",
    "    if  float(s[0]) % 2 == 1:\n",
    "        sign = -1\n",
    "    # The remaining chars encode for the number itself, \n",
    "    # without the decimal point nor sign.\n",
    "    sn = s[1:l]\n",
    "    # The point is inserted after the second char, so that we have numbers of the form 93.24\n",
    "    sn = sn[:2] + \".\" + sn[2:]\n",
    "    # Convert the string to a number\n",
    "    n = float(sn)\n",
    "    return sign * n\n",
    "\n",
    "# Decode a part of the chromosome into a coefficient of the polynomial.\n",
    "def decoderj12(s):\n",
    "    ''' The input is a number as string, outputs the number as a float. \n",
    "        We consider numbers of the form 93.24 with a sign that could be positive or negative,\n",
    "    '''\n",
    "    l = len(s) \n",
    "    # The first char encodes for the sign, \n",
    "    sign = 1\n",
    "    if  float(s[0]) % 2 == 1:\n",
    "        sign = -1\n",
    "    # The remaining chars encode for the number itself, \n",
    "    # without the decimal point nor sign.\n",
    "    sn = s[1:l]\n",
    "    # The point is inserted after the first char, so that we have numbers of the form -3.24\n",
    "    sn = sn[:1] + \".\" + sn[1:]\n",
    "    # Convert the string to a number\n",
    "    n = float(sn)\n",
    "    return sign * n\n",
    "\n",
    "\n",
    "def decodeFullCromosomej12(chromosome, length_of_chromosomes):\n",
    "    \"\"\"Decodes the full chromosome into the coefficients of the polynomial.\"\"\"\n",
    "    \"\"\"The chromosome is divided into 5 parts, \n",
    "        each one encoding for a coefficient of the polynomial.\"\"\"\n",
    "    chro0 = chromosome[0:length_of_chromosomes]\n",
    "    chro1 = chromosome[length_of_chromosomes:2*length_of_chromosomes]\n",
    "    chro2 = chromosome[2*length_of_chromosomes:3*length_of_chromosomes]\n",
    "    chro3 = chromosome[3*length_of_chromosomes:4*length_of_chromosomes]\n",
    "    chro4 = chromosome[4*length_of_chromosomes:5*length_of_chromosomes]\n",
    "    chro5 = chromosome[5*length_of_chromosomes:6*length_of_chromosomes]\n",
    "    a_0 = decoderj12(chro0)\n",
    "    a_1 = decoderj12(chro1)\n",
    "    a_2 = decoderj12(chro2)\n",
    "    a_3 = decoderj12(chro3)\n",
    "    a_4 = decoderj12(chro4)\n",
    "    a_5 = decoderj12(chro5)\n",
    "    # print(f\"Chromosome: {chromosome}\")\n",
    "    # print(f\"Coefficients: Intercept {a_0}, slope {a_1}, quadratic {a_2}, cubic {a_3}, quartic {a_4}, quintic {a_5}\")\n",
    "    # print()\n",
    "    return a_0, a_1, a_2, a_3, a_4, a_5\n",
    "\n",
    "\n",
    "\n",
    "def calculate_errorj12(chromosome, xArray, yArray, length_of_chromosomes):\n",
    "    \"\"\"Calculates the error of a chromosome.\n",
    "        A chromosome encodes for the coefficients of a polynomial of fith degree.\n",
    "        The error of a chromosome is the sum of \n",
    "        the vertical distances of the points to the polynomial it encodes.\n",
    "    \"\"\"\n",
    "    #  print(\"\\n calculate_errorj12(chromosome, xArray, yArray)\")\n",
    "    a_0, a_1, a_2, a_3, a_4, a_5 = decodeFullCromosomej12(chromosome, length_of_chromosomes)  \n",
    "    error = 0\n",
    "    for i in range(len(xArray)):\n",
    "        x = xArray[i]\n",
    "        y = yArray[i]\n",
    "        # Calculate the predicted y value based on the coefficients of the polynomial\n",
    "        predicted_y = a_0 + a_1 * x + a_2 * x**2 + a_3 * x**3 + a_4 * x**4 + a_5 * x**5\n",
    "        # Calculate the error as the quadratic difference \n",
    "        # between predicted and y value\n",
    "        # error += (predicted_y - y)**2\n",
    "        # Calculate the error as the distance between predicted and y value\n",
    "        error += abs(predicted_y - y)\n",
    "    return error\n",
    "\n",
    "def calculate_all_errorsj12(population, xArray, yArray, length_of_chromosomes):\n",
    "    # print(\"\\n*calculate_all_errorsj12(population, target_sequence)\")\n",
    "    \"\"\"Calculates the error of all chromosomes in the population.\"\"\"\n",
    "    errors = [calculate_errorj12(chromosome, xArray, yArray, length_of_chromosomes) for chromosome in population]\n",
    "    # print(\"errors: \", errors)\n",
    "    return errors\n",
    "\n",
    "def select_the_least_errorj12(population, xArray, yArray, length_of_chromosomes):\n",
    "    \"\"\"Selects the best chromosome with minimal error for reproduction.\"\"\"\n",
    "    errors = calculate_all_errorsj12(population, xArray, yArray, length_of_chromosomes)\n",
    "    smallest_error = min(errors)\n",
    "    best_chromosome_index = errors.index(smallest_error)\n",
    "    best_chromosome = population[best_chromosome_index]\n",
    "    # print(\"\\n*select_the_least_errorj12(population)\")\n",
    "    # print(\"smallest_error = \", smallest_error)\n",
    "    # print(\"The chro = \", best_chromosome )\n",
    "    return smallest_error, best_chromosome\n",
    "\n",
    "def clone_populationj12(best_chromosome, population_size):\n",
    "    \"\"\"Creates a new population by cloning the best chromosome.\"\"\"\n",
    "    return [best_chromosome] * population_size\n",
    "\n",
    "\n",
    "def mutatej12(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_allj12(population, mutation_rate, alphabet):\n",
    "    \"\"\"Mutates all chromosomes in the population.\"\"\"\n",
    "    mutated_population = []\n",
    "    for chromosome in population:\n",
    "        mutated_chromosome = mutatej12(chromosome, mutation_rate, alphabet)\n",
    "        mutated_population.append(mutated_chromosome)\n",
    "    return mutated_population\n",
    "\n",
    "def crossoverj12(parent1, parent2, length_of_chromosomes, recombination_rate):\n",
    "    \"\"\"Performs crossover between two parent chromosomes.\"\"\"\n",
    "    if random.random() < recombination_rate:\n",
    "        crossover_point = random.randint(0, length_of_chromosomes)\n",
    "        return parent1[:crossover_point] + parent2[crossover_point:]\n",
    "    else:\n",
    "        return parent1\n",
    "\n",
    "def crossover_allj12(population, length_of_chromosomes, 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 = crossoverj12(parent1, parent2, length_of_chromosomes, recombination_rate)\n",
    "        recombinant_population.append(child)\n",
    "    return recombinant_population\n",
    "\n",
    "\n",
    "\n",
    "def run_one_generationj12(population, xArray, yArray, mutation_rate, recombination_rate, alphabet, length_of_chromosomes):\n",
    "    \"\"\"Runs one generation of the genetic algorithm.\"\"\"\n",
    "    # Calculate fitness scores for the current population\n",
    "    smallest_error, best_chromosome  = select_the_least_errorj12(population, xArray, yArray, length_of_chromosomes)\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_populationj12:\n",
    "        new_population = clone_populationj12(best_chromosome, population_size)\n",
    "    if include_mutate_allj12:\n",
    "        new_population = mutate_allj12(new_population, mutation_rate, alphabet)\n",
    "    if include_crossover_allj12:\n",
    "        new_population = crossover_allj12(new_population, length_of_chromosomes, recombination_rate)\n",
    "    return smallest_error, best_chromosome, new_population\n",
    "\n",
    "\n",
    "\n",
    "def plot_functionj12(g_values, 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 taskj12( xArray, yArray, mutation_rate, recombination_rate, alphabet,  length_of_chromosomes):\n",
    "    population = create_populationj12(population_size, length_of_chromosomes, alphabet)\n",
    "    # print(population)\n",
    "    generation = 0\n",
    "    best_chromosome = ''\n",
    "    best_fitness = 0\n",
    "    start_time = time.time()\n",
    "    smallest_error_history = [] # List to store best fitness of each generation\n",
    "    if print_best_fitness:\n",
    "        print(\"Generation, best_chromosome and best_fitness\")\n",
    "    while generation < number_of_generations:\n",
    "        generation += 1\n",
    "        smallest_error, best_chromosome, population = run_one_generationj12(population, xArray,yArray, mutation_rate, recombination_rate, alphabet, length_of_chromosomes)\n",
    "        if print_best_fitness:\n",
    "            print(f\" {generation}  {best_chromosome} {smallest_error}\")\n",
    "        smallest_error_history.append(smallest_error)\n",
    "    # print(f\"\\nTarget sequence matched in generation {generation}\")\n",
    "    # print(f\"Final chromosome: {best_chromosome}\")\n",
    "    totalCost = population_size * generation\n",
    "    return  best_chromosome, totalCost, smallest_error_history\n",
    "\n",
    "def mainj12(xArray, yArray, mutation_rate, recombination_rate, alphabet, length_of_chromosomes):\n",
    "    print_parametersj12()\n",
    "    print(\"Total cost = population size * number of generations\")\n",
    "    best_chromosome, totalCost, smallest_error_history = taskj12(xArray, yArray, mutation_rate, recombination_rate, alphabet, length_of_chromosomes)\n",
    "    final_error = smallest_error_history[-1]\n",
    "    print(f\" The best chromosome is {best_chromosome}\" )\n",
    "    coefficients = decodeFullCromosomej12(best_chromosome, length_of_chromosomes)\n",
    "    print(f\" Encoded coefficientes: {coefficients} \" )\n",
    "    print(f\" Total cost =  {totalCost} chromosomes\")\n",
    "    print(f\" Final error =  {final_error} \")\n",
    "\n",
    "    # Plot the fitness history    \n",
    "    g_values = list(range(1, len(smallest_error_history) + 1))\n",
    "    plot_functionj12(g_values, smallest_error_history, xlabel='Generation', ylabel='SmallestError', title='Smallest Error Over Generations')\n",
    "    # The best chromosome encodes for the coefficients of the polynomial that best fits the data points\"\n",
    "    b_0, b_1, b_2, b_3, b_4, b5 = decodeFullCromosomej12(best_chromosome, length_of_chromosomes)\n",
    "    print(f\"Decoded coefficients: Intercept {b_0}, slope {b_1}, quadratic {b_2}, cubic {b_3}, quartic {b_4}, quintic {b5}\")\n",
    "    # Calculate the predicted y value based on the coefficients of the polynomial\n",
    "    our_polynomial = b_0 + b_1 * np.array(xArray) + b_2 * np.array(xArray)**2 + b_3 * np.array(xArray)**3 + b_4 * np.array(xArray)**4 + b5 * np.array(xArray)**5\n",
    "    \n",
    "\n",
    "    # Perform polynomial regression\n",
    "    # Fit a polynomial of degree 5 (polynomial regression)\n",
    "    p_fitted = Polynomial.fit(xArray, yArray, deg=5)\n",
    "    a_0, a_1, a_2, a_3, a_4, a5 = p_fitted.convert().coef\n",
    "    print(f\"Polynomial regression coefficients: Intercept {a_0}, slope {a_1}, quadratic {a_2}, cubic {a_3}, quartic {a_4}, quintic {a5}\")\n",
    "    # Create the regression graph\n",
    "    x_new = np.linspace(-2,3, 100) # Generate 100 points between -2 and 3 for a smooth curve\n",
    "    y_new = p_fitted(x_new)\n",
    "\n",
    "    # The best chromosome encodes for the coefficients of the polynomial that best fits the data points\"\n",
    "    b_0, b_1, b_2, b_3, b_4, b5 = decodeFullCromosomej12(best_chromosome, length_of_chromosomes)\n",
    "    print(f\"Encoded coefficients: Intercept {b_0}, slope {b_1}, quadratic {b_2}, cubic {b_3}, quartic {b_4}, quintic {b5}\")\n",
    "    # Calculate the predicted y value based on the coefficients of the polynomial\n",
    "    our_polynomial = b_0 + b_1 * np.array(x_new ) + b_2 * np.array(x_new )**2 + b_3 * np.array(x_new )**3 + b_4 * np.array(x_new )**4 + b5 * np.array(x_new )**5\n",
    "    \n",
    "\n",
    "\n",
    "    # Plot the original data, the regression polynomial, and our polynomial\n",
    "    plt.figure(figsize=(10, 6))\n",
    "    plt.scatter(xArray, yArray, label='Observed Data')\n",
    "    plt.plot(x_new, y_new, color='red', label=f'Polynomial Regression: y = {a_0:.2f} + {a_1:.2f}x + {a_2:.2f}x^2 + {a_3:.2f}x^3 + {a_4:.2f}x^4 + {a5:.2f}x^5')\n",
    "    plt.plot(x_new,        our_polynomial, color='green', label=f'Our polynomial: y = {b_0:.2f} + {b_1:.2f}x + {b_2:.2f}x^2 + {b_3:.2f}x^3 + {b_4:.2f}x^4 + {b5:.2f}x^5')\n",
    "    plt.xlabel('Independent variable (x)')\n",
    "    plt.ylabel('Dependent variable (y)')\n",
    "    plt.title('Linear Regression and la Evolución minimize the error of the line with respect to the data points')\n",
    "    plt.legend()\n",
    "    plt.grid(True)\n",
    "    plt.show()\n",
    "\n",
    "    # Plot the original data and the regression polynomial\n",
    "    plt.figure(figsize=(10, 6))\n",
    "    plt.scatter(xArray, yArray, label='Observed Data')\n",
    "    plt.plot(x_new, y_new, color='red', label=f'Polynomial Regression: y = {a_0:.2f} + {a_1:.2f}x + {a_2:.2f}x^2 + {a_3:.2f}x^3 + {a_4:.2f}x^4 + {a5:.2f}x^5')\n",
    "    plt.xlabel('Independent variable (x)')\n",
    "    plt.ylabel('Dependent variable (y)')\n",
    "    plt.title('Linear Regression minimizes the error of the line with respect to the data points')\n",
    "    plt.legend()\n",
    "    plt.grid(True)\n",
    "    plt.show()\n",
    "\n",
    "    # Plot  our polynomial\n",
    "    plt.figure(figsize=(10, 6))\n",
    "    plt.scatter(xArray, yArray, label='Observed Data')\n",
    "    #plt.plot(xArray, regression_polynomial, color='red', label=f'Polynomial Regression: y = {a_0:.2f} + {a_1:.2f}x + {a_2:.2f}x^2 + {a_3:.2f}x^3 + {a_4:.2f}x^4 + {a5:.2f}x^5')\n",
    "    plt.plot(x_new,        our_polynomial, color='green', label=f'Our polynomial: y = {b_0:.2f} + {b_1:.2f}x + {b_2:.2f}x^2 + {b_3:.2f}x^3 + {b_4:.2f}x^4 + {b5:.2f}x^5')\n",
    "    plt.xlabel('Independent variable (x)')\n",
    "    plt.ylabel('Dependent variable (y)')\n",
    "    plt.title('la Evoluciónary Regression minimizes the error of the line with respect to the data points')\n",
    "    plt.legend()\n",
    "    plt.grid(True)\n",
    "    plt.show()\n",
    "\n",
    "\n",
    "\n",
    "    end_time = time.time()\n",
    "    # Calculate the duration of the run in seconds\n",
    "    elapsed_time = end_time - start_time\n",
    "    elapsed_time = timedelta(seconds=elapsed_time)\n",
    "    print(f\"Elapsed time: {elapsed_time}\")\n",
    "    #return best_chromosome, totalCost, best_fitness_history\n",
    "\n",
    "# Call the main function with the defined parameters\n",
    "mainj12(xArray, yArray, mutation_rate, recombination_rate, alphabet, length_of_chromosomes)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "8617e606",
   "metadata": {},
   "source": [
    "*Nuestras observaciones.* Con un tamaño poblacional de más de 100000, y después de 1000 generaciones, el error final fue 6 y la forma final era muy parecida a la perfecta. La curva pasa a través de cinco de seis puntos y el error se debe al mal ajuste de solo uno de ellos. Esto muestra que la riqueza es en verdad una bendición, pero no la panacea, porque no se encontró la perfección.\n",
    "\n",
    "\n"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "e1ba7331",
   "metadata": {},
   "source": [
    "\n",
    "### La aleatoriedad como única herramienta\n",
    "\n",
    "Hemos considerado que la falta de variabilidad es la causa de todos nuestros problemas. ¿Qué podría ser mejor para crear variabilidad que la aleatoriedad?\n",
    "\n",
    "**Ejercicio.** Explora el poder de la aleatoriedad para curar nuestra enfermedad de imperfección crónica. \n",
    ">\n",
    "> *Respuesta.* La población inicial de toda nuestra implementación de la Evolución consiste en cromosomas generados aleatoriamente. Por lo tanto, es per se una exploración del poder de la aleatoriedad. Por ello, ejecutamos el programa anterior para una población de un millón durante 100 generaciones para ver qué sucede. El código se muestra nuevamente.\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "a018fdc0",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Lab: Evolution finds the polynomial of minimal error\n",
      "Purpose: Use a Genetic Algorithm (MAX = selection of the fittest, mutation and recombination) to find the coefficients of a polynomial that best fits a set of points.\n",
      "Hint to be tested: consider only numbers of the form -3.244025 with a sign that could be positive or negative, and a decimal point in the second place of the encoding chromosome.\n",
      "Date of Experiment  = 2026-04-27 10:38:43.274857\n",
      "number_of_generations = 100\n",
      "length_of_chromosomes = 8\n",
      "alphabet =  0123456789\n",
      "Points = [(-2, 5), (-1, 1), (0, 4), (1, 0), (2, 6), (3, 3)]\n",
      "population_size = 20000000\n",
      "include_clone_populationj13 = True\n",
      "include_mutate_allj13 = True\n",
      "include_crossover_allj13 = False\n",
      "mutation_rate = 0.05\n",
      "print_best_fitness = False\n",
      "Total cost = population size * number of generations\n",
      " The best chromosome is 227507125310000012510000824734352079930090408999\n",
      " Encoded coefficientes: (2.750712, -3.1, -2.51, 2.473435, 0.7993, -0.408999) \n",
      " Total cost =  2000000000 chromosomes\n",
      " Final error =  2.330288 \n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Decoded coefficients: Intercept 2.750712, slope -3.1, quadratic -2.51, cubic 2.473435, quartic 0.7993, quintic -0.408999\n",
      "Polynomial regression coefficients: Intercept 4.0, slope -2.983333333333327, quadratic -4.791666666666659, cubic 3.041666666666663, quartic 1.2916666666666643, quintic -0.5583333333333323\n",
      "Encoded coefficients: Intercept 2.750712, slope -3.1, quadratic -2.51, cubic 2.473435, quartic 0.7993, quintic -0.408999\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"
    },
    {
     "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": [
      "Elapsed time: 6:27:11.751361\n",
      "\u0007\n"
     ]
    }
   ],
   "source": [
    "# Program PolynomialThePowerOfRandomness.py\n",
    "# This program uses a genetic algorithm to find the polynomial \n",
    "# of fifth degree that best fits a set of 6 points.\n",
    "# The coefficients are represented by a chromosome, \n",
    "# which is a string of digits.\n",
    "# The decoding function must divide the chromosome into parts, \n",
    "# and decode each one apart as one coefficient.\n",
    "# We consider numbers of the form -3.244025\n",
    "# with a sign that could be positive or negative, \n",
    "# and a decimal point in the second place of the encoding chromosome.\n",
    "# The error of a chromosome is the sum of the vertical distances \n",
    "# of the points to the polynomial it encodes.\n",
    "# The Genetic algorithm must minimize the error, \n",
    "# (which is equivalent to maximizing the fitness).\n",
    "# In this program, it is explored the power of randomness\n",
    "# to find a good solution. \n",
    "# To that aim, we take a population size of one million, and we run the algorithm for ten generations,\n",
    "# to see whther perfection is found.\n",
    "# Developed with the assistance of the AI of Visual Studio Code.\n",
    "# An old version of a GA developed with the help of Gemini was reused and updated.\n",
    "\n",
    "\n",
    "from datetime import datetime, timedelta\n",
    "import datetime\n",
    "import time\n",
    "import random\n",
    "import numpy as np\n",
    "from numpy.polynomial import Polynomial\n",
    "import matplotlib.pyplot as plt # Import matplotlib for plotting\n",
    "\n",
    "\n",
    "start_time = time.time() # Record the start time\n",
    "\n",
    "#Task to be done\n",
    "number_of_generations = 100\n",
    "\n",
    "xArray =  [-2, -1, 0, 1, 2, 3]\n",
    "yArray =  [5,   1, 4, 0, 6, 3]\n",
    "\n",
    "alphabet = '0123456789'\n",
    "# Chromosome encoding for one of 6 coefficients, \n",
    "# each one with a length of 5 chars.\n",
    "# Encoding number as -93.24 with a sign and a decimal point.\n",
    "length_of_chromosomes = 8\n",
    "population_size = 20000000\n",
    "# Include cloning of the fittest\n",
    "include_clone_populationj13 = True\n",
    "# Include mutation\n",
    "include_mutate_allj13 = True\n",
    "# Include recombination\n",
    "include_crossover_allj13 = False\n",
    "mutation_rate = 0.05\n",
    "recombination_rate = 0.0\n",
    "# Size of the sampled groups from which the best \n",
    "# is chosen as a parent for the next generation.\n",
    "tournament_size = 5\n",
    "# Boolean flag to print the generation, best chromosome and fitness.\n",
    "# This is the ancestral line of the solution.\n",
    "print_best_fitness = True\n",
    "print_parameters = True\n",
    "show_graph = True\n",
    "    \n",
    "\n",
    "def print_parametersj13():\n",
    "    print(f\"Lab: la Evolución finds the polynomial of minimal error\")\n",
    "    print(f\"Purpose: Use a Genetic Algorithm (MAX = selection of the fittest, mutation and recombination) to find the coefficients of a polynomial that best fits a set of points.\")\n",
    "    print(\"Hint to be tested: consider only numbers of the form -3.244025 with a sign that could be positive or negative, and a decimal point in the second place of the encoding chromosome.\")\n",
    "    print(f\"Date of Experiment  = {datetime.datetime.now()}\")\n",
    "    print(f\"number_of_generations = {number_of_generations}\")\n",
    "    print(f\"length_of_chromosomes = {length_of_chromosomes}\")\n",
    "    print(f\"alphabet =  {alphabet}\")\n",
    "    print(f\"Points = {list(zip(xArray, yArray))}\")\n",
    "    print(f\"population_size = {population_size}\")\n",
    "    print(f\"include_clone_populationj13 = {include_clone_populationj13}\")\n",
    "    print(f\"include_mutate_allj13 = {include_mutate_allj13}\")\n",
    "    print(f\"include_crossover_allj13 = {include_crossover_allj13}\")\n",
    "    if include_mutate_allj13:\n",
    "        print(f\"mutation_rate = {mutation_rate}\")\n",
    "    if include_crossover_allj13:\n",
    "        print(f\"recombination_rate = {recombination_rate}\")\n",
    "    if include_clone_populationj13:\n",
    "        print(f\"print_best_fitness = {print_best_fitness}\")\n",
    "\n",
    "def draw_points_and_polynomialj13(xNumpyArray, yNumpyArray):\n",
    "    \"\"\"Draws the original data points, finds and draws the \n",
    "    regression polynomial defined by the coefficients.\"\"\"\n",
    "    \n",
    "    # 2. Fit a 5th-degree (quintic) polynomial\n",
    "    # .fit() returns a Polynomial instance\n",
    "    p_fitted = Polynomial.fit(xNumpyArray, yNumpyArray, deg=5)\n",
    "\n",
    "    # 3. Predict values for visualization\n",
    "    x_new = np.linspace(-2,3, 100) # Generate 100 points between 0 and 6 for a smooth curve\n",
    "    y_new = p_fitted(x_new)\n",
    "    b_0, b_1, b_2, b_3, b_4, b5 = p_fitted.coef\n",
    "\n",
    "    # 4. Plot results\n",
    "    plt.scatter(xNumpyArray, yNumpyArray, label='Data Points')\n",
    "    plt.xlabel('x')\n",
    "    plt.ylabel('y')\n",
    "    plt.plot(x_new, y_new, label=f'Quintic Fit: y = {b_0:.2f} + {b_1:.2f}x + {b_2:.2f}x^2 + {b_3:.2f}x^3 + {b_4:.2f}x^4 + {b5:.2f}x^5', color='green')\n",
    "    plt.title(' Data Points and Quintic Fit by numpy.polynomial.Polynomial.fit()')\n",
    "    plt.legend()\n",
    "    plt.show()\n",
    "    return p_fitted.coef\n",
    "\n",
    "\n",
    "\n",
    "def create_populationj13(population_size, length_of_chromosomes, alphabet):\n",
    "    \"\"\"Creates a new population with random chromosomes.\"\"\"\n",
    "    # print(\"create_populationj13(population_size, target_sequence, alphabet)\")\n",
    "    population = []\n",
    "    for _ in range(population_size):\n",
    "        random_string1 = ''.join(random.choice(alphabet) for _ in range(length_of_chromosomes))\n",
    "        random_string2 = ''.join(random.choice(alphabet) for _ in range(length_of_chromosomes))\n",
    "        random_string3 = ''.join(random.choice(alphabet) for _ in range(length_of_chromosomes))\n",
    "        random_string4 = ''.join(random.choice(alphabet) for _ in range(length_of_chromosomes))\n",
    "        random_string5 = ''.join(random.choice(alphabet) for _ in range(length_of_chromosomes))\n",
    "        random_string6 = ''.join(random.choice(alphabet) for _ in range(length_of_chromosomes))\n",
    "        random_string = random_string1 + random_string2 + random_string3 + random_string4 + random_string5 + random_string6\n",
    "        population.append(random_string)\n",
    "    # print(\"initial population\")\n",
    "    # print(population)\n",
    "    return population\n",
    "\n",
    "# Decode a part of the chromosome into a coefficient of the polynomial.\n",
    "def decoderOldj13(s):\n",
    "    ''' The input is a number as string, outputs the number as a float. \n",
    "        We consider numbers of the form 93.24 with a sign that could be positive or negative,\n",
    "    '''\n",
    "    l = len(s) \n",
    "    # The first char encodes for the sign, \n",
    "    sign = 1\n",
    "    if  float(s[0]) % 2 == 1:\n",
    "        sign = -1\n",
    "    # The remaining chars encode for the number itself, \n",
    "    # without the decimal point nor sign.\n",
    "    sn = s[1:l]\n",
    "    # The point is inserted after the second char, so that we have numbers of the form 93.24\n",
    "    sn = sn[:2] + \".\" + sn[2:]\n",
    "    # Convert the string to a number\n",
    "    n = float(sn)\n",
    "    return sign * n\n",
    "\n",
    "# Decode a part of the chromosome into a coefficient of the polynomial.\n",
    "def decoderj13(s):\n",
    "    ''' The input is a number as string, outputs the number as a float. \n",
    "        We consider numbers of the form 93.24 with a sign that could be positive or negative,\n",
    "    '''\n",
    "    l = len(s) \n",
    "    # The first char encodes for the sign, \n",
    "    sign = 1\n",
    "    if  float(s[0]) % 2 == 1:\n",
    "        sign = -1\n",
    "    # The remaining chars encode for the number itself, \n",
    "    # without the decimal point nor sign.\n",
    "    sn = s[1:l]\n",
    "    # The point is inserted after the first char, so that we have numbers of the form -3.24\n",
    "    sn = sn[:1] + \".\" + sn[1:]\n",
    "    # Convert the string to a number\n",
    "    n = float(sn)\n",
    "    return sign * n\n",
    "\n",
    "\n",
    "def decodeFullCromosomej13(chromosome, length_of_chromosomes):\n",
    "    \"\"\"Decodes the full chromosome into the coefficients of the polynomial.\"\"\"\n",
    "    \"\"\"The chromosome is divided into 5 parts, \n",
    "        each one encoding for a coefficient of the polynomial.\"\"\"\n",
    "    chro0 = chromosome[0:length_of_chromosomes]\n",
    "    chro1 = chromosome[length_of_chromosomes:2*length_of_chromosomes]\n",
    "    chro2 = chromosome[2*length_of_chromosomes:3*length_of_chromosomes]\n",
    "    chro3 = chromosome[3*length_of_chromosomes:4*length_of_chromosomes]\n",
    "    chro4 = chromosome[4*length_of_chromosomes:5*length_of_chromosomes]\n",
    "    chro5 = chromosome[5*length_of_chromosomes:6*length_of_chromosomes]\n",
    "    a_0 = decoderj13(chro0)\n",
    "    a_1 = decoderj13(chro1)\n",
    "    a_2 = decoderj13(chro2)\n",
    "    a_3 = decoderj13(chro3)\n",
    "    a_4 = decoderj13(chro4)\n",
    "    a_5 = decoderj13(chro5)\n",
    "    # print(f\"Chromosome: {chromosome}\")\n",
    "    # print(f\"Coefficients: Intercept {a_0}, slope {a_1}, quadratic {a_2}, cubic {a_3}, quartic {a_4}, quintic {a_5}\")\n",
    "    # print()\n",
    "    return a_0, a_1, a_2, a_3, a_4, a_5\n",
    "\n",
    "\n",
    "\n",
    "def calculate_errorj13(chromosome, xArray, yArray, length_of_chromosomes):\n",
    "    \"\"\"Calculates the error of a chromosome.\n",
    "        A chromosome encodes for the coefficients of a polynomial of fith degree.\n",
    "        The error of a chromosome is the sum of \n",
    "        the vertical distances of the points to the polynomial it encodes.\n",
    "    \"\"\"\n",
    "    #  print(\"\\n calculate_errorj13(chromosome, xArray, yArray)\")\n",
    "    a_0, a_1, a_2, a_3, a_4, a_5 = decodeFullCromosomej13(chromosome, length_of_chromosomes)  \n",
    "    error = 0\n",
    "    for i in range(len(xArray)):\n",
    "        x = xArray[i]\n",
    "        y = yArray[i]\n",
    "        # Calculate the predicted y value based on the coefficients of the polynomial\n",
    "        predicted_y = a_0 + a_1 * x + a_2 * x**2 + a_3 * x**3 + a_4 * x**4 + a_5 * x**5\n",
    "        # Calculate the error as the quadratic difference \n",
    "        # between predicted and y value\n",
    "        # error += (predicted_y - y)**2\n",
    "        # Calculate the error as the distance between predicted and y value\n",
    "        error += abs(predicted_y - y)\n",
    "    return error\n",
    "\n",
    "def calculate_all_errorsj13(population, xArray, yArray, length_of_chromosomes):\n",
    "    # print(\"\\n*calculate_all_errorsj13(population, target_sequence)\")\n",
    "    \"\"\"Calculates the error of all chromosomes in the population.\"\"\"\n",
    "    errors = [calculate_errorj13(chromosome, xArray, yArray, length_of_chromosomes) for chromosome in population]\n",
    "    # print(\"errors: \", errors)\n",
    "    return errors\n",
    "\n",
    "def select_the_least_errorj13(population, xArray, yArray, length_of_chromosomes):\n",
    "    \"\"\"Selects the best chromosome with minimal error for reproduction.\"\"\"\n",
    "    errors = calculate_all_errorsj13(population, xArray, yArray, length_of_chromosomes)\n",
    "    smallest_error = min(errors)\n",
    "    best_chromosome_index = errors.index(smallest_error)\n",
    "    best_chromosome = population[best_chromosome_index]\n",
    "    # print(\"\\n*select_the_least_errorj13(population)\")\n",
    "    # print(\"smallest_error = \", smallest_error)\n",
    "    # print(\"The chro = \", best_chromosome )\n",
    "    return smallest_error, best_chromosome\n",
    "\n",
    "def clone_populationj13(best_chromosome, population_size):\n",
    "    \"\"\"Creates a new population by cloning the best chromosome.\"\"\"\n",
    "    return [best_chromosome] * population_size\n",
    "\n",
    "\n",
    "def mutatej13(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_allj13(population, mutation_rate, alphabet):\n",
    "    \"\"\"Mutates all chromosomes in the population.\"\"\"\n",
    "    mutated_population = []\n",
    "    for chromosome in population:\n",
    "        mutated_chromosome = mutatej13(chromosome, mutation_rate, alphabet)\n",
    "        mutated_population.append(mutated_chromosome)\n",
    "    return mutated_population\n",
    "\n",
    "def crossoverj13(parent1, parent2, length_of_chromosomes, recombination_rate):\n",
    "    \"\"\"Performs crossover between two parent chromosomes.\"\"\"\n",
    "    if random.random() < recombination_rate:\n",
    "        crossover_point = random.randint(0, length_of_chromosomes)\n",
    "        return parent1[:crossover_point] + parent2[crossover_point:]\n",
    "    else:\n",
    "        return parent1\n",
    "\n",
    "def crossover_allj13(population, length_of_chromosomes, 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 = crossoverj13(parent1, parent2, length_of_chromosomes, recombination_rate)\n",
    "        recombinant_population.append(child)\n",
    "    return recombinant_population\n",
    "\n",
    "\n",
    "\n",
    "def run_one_generationj13(population, xArray, yArray, mutation_rate, recombination_rate, alphabet, length_of_chromosomes):\n",
    "    \"\"\"Runs one generation of the genetic algorithm.\"\"\"\n",
    "    # Calculate fitness scores for the current population\n",
    "    smallest_error, best_chromosome  = select_the_least_errorj13(population, xArray, yArray, length_of_chromosomes)\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_populationj13:\n",
    "        new_population = clone_populationj13(best_chromosome, population_size)\n",
    "    if include_mutate_allj13:\n",
    "        new_population = mutate_allj13(new_population, mutation_rate, alphabet)\n",
    "    if include_crossover_allj13:\n",
    "        new_population = crossover_allj13(new_population, length_of_chromosomes, recombination_rate)\n",
    "    return smallest_error, best_chromosome, new_population\n",
    "\n",
    "\n",
    "\n",
    "def plot_functionj13(g_values, 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 taskj13( xArray, yArray, mutation_rate, recombination_rate, alphabet,  length_of_chromosomes):\n",
    "    population = create_populationj13(population_size, length_of_chromosomes, alphabet)\n",
    "    # print(population)\n",
    "    generation = 0\n",
    "    best_chromosome = ''\n",
    "    best_fitness = 0\n",
    "    start_time = time.time()\n",
    "    smallest_error_history = [] # List to store best fitness of each generation\n",
    "    if print_best_fitness:\n",
    "        print(\"Generation, best_chromosome and best_fitness\")\n",
    "    while generation < number_of_generations:\n",
    "        generation += 1\n",
    "        smallest_error, best_chromosome, population = run_one_generationj13(population, xArray,yArray, mutation_rate, recombination_rate, alphabet, length_of_chromosomes)\n",
    "        if print_best_fitness:\n",
    "            print(f\" {generation}  {best_chromosome} {smallest_error}\")\n",
    "        smallest_error_history.append(smallest_error)\n",
    "    # print(f\"\\nTarget sequence matched in generation {generation}\")\n",
    "    # print(f\"Final chromosome: {best_chromosome}\")\n",
    "    totalCost = population_size * generation\n",
    "    return  best_chromosome, totalCost, smallest_error_history\n",
    "\n",
    "def mainj13(xArray, yArray, mutation_rate, recombination_rate, alphabet, length_of_chromosomes):\n",
    "    print_parametersj13()\n",
    "    print(\"Total cost = population size * number of generations\")\n",
    "    best_chromosome, totalCost, smallest_error_history = taskj13(xArray, yArray, mutation_rate, recombination_rate, alphabet, length_of_chromosomes)\n",
    "    final_error = smallest_error_history[-1]\n",
    "    print(f\" The best chromosome is {best_chromosome}\" )\n",
    "    coefficients = decodeFullCromosomej13(best_chromosome, length_of_chromosomes)\n",
    "    print(f\" Encoded coefficientes: {coefficients} \" )\n",
    "    print(f\" Total cost =  {totalCost} chromosomes\")\n",
    "    print(f\" Final error =  {final_error} \")\n",
    "\n",
    "    # Plot the fitness history    \n",
    "    g_values = list(range(1, len(smallest_error_history) + 1))\n",
    "    plot_functionj13(g_values, smallest_error_history, xlabel='Generation', ylabel='SmallestError', title='Smallest Error Over Generations')\n",
    "    # The best chromosome encodes for the coefficients of the polynomial that best fits the data points\"\n",
    "    b_0, b_1, b_2, b_3, b_4, b5 = decodeFullCromosomej13(best_chromosome, length_of_chromosomes)\n",
    "    print(f\"Decoded coefficients: Intercept {b_0}, slope {b_1}, quadratic {b_2}, cubic {b_3}, quartic {b_4}, quintic {b5}\")\n",
    "    # Calculate the predicted y value based on the coefficients of the polynomial\n",
    "    our_polynomial = b_0 + b_1 * np.array(xArray) + b_2 * np.array(xArray)**2 + b_3 * np.array(xArray)**3 + b_4 * np.array(xArray)**4 + b5 * np.array(xArray)**5\n",
    "    \n",
    "\n",
    "    # Perform polynomial regression\n",
    "    # Fit a polynomial of degree 5 (polynomial regression)\n",
    "    p_fitted = Polynomial.fit(xArray, yArray, deg=5)\n",
    "    a_0, a_1, a_2, a_3, a_4, a5 = p_fitted.convert().coef\n",
    "    print(f\"Polynomial regression coefficients: Intercept {a_0}, slope {a_1}, quadratic {a_2}, cubic {a_3}, quartic {a_4}, quintic {a5}\")\n",
    "    # Create the regression graph\n",
    "    x_new = np.linspace(-2,3, 100) # Generate 100 points between -2 and 3 for a smooth curve\n",
    "    y_new = p_fitted(x_new)\n",
    "\n",
    "    # The best chromosome encodes for the coefficients of the polynomial that best fits the data points\"\n",
    "    b_0, b_1, b_2, b_3, b_4, b5 = decodeFullCromosomej13(best_chromosome, length_of_chromosomes)\n",
    "    print(f\"Encoded coefficients: Intercept {b_0}, slope {b_1}, quadratic {b_2}, cubic {b_3}, quartic {b_4}, quintic {b5}\")\n",
    "    # Calculate the predicted y value based on the coefficients of the polynomial\n",
    "    our_polynomial = b_0 + b_1 * np.array(x_new ) + b_2 * np.array(x_new )**2 + b_3 * np.array(x_new )**3 + b_4 * np.array(x_new )**4 + b5 * np.array(x_new )**5\n",
    "    \n",
    "\n",
    "\n",
    "    # Plot the original data, the regression polynomial, and our polynomial\n",
    "    plt.figure(figsize=(10, 6))\n",
    "    plt.scatter(xArray, yArray, label='Observed Data')\n",
    "    plt.plot(x_new, y_new, color='red', label=f'Polynomial Regression: y = {a_0:.2f} + {a_1:.2f}x + {a_2:.2f}x^2 + {a_3:.2f}x^3 + {a_4:.2f}x^4 + {a5:.2f}x^5')\n",
    "    plt.plot(x_new,        our_polynomial, color='green', label=f'Our polynomial: y = {b_0:.2f} + {b_1:.2f}x + {b_2:.2f}x^2 + {b_3:.2f}x^3 + {b_4:.2f}x^4 + {b5:.2f}x^5')\n",
    "    plt.xlabel('Independent variable (x)')\n",
    "    plt.ylabel('Dependent variable (y)')\n",
    "    plt.title('Linear Regression and la Evolución minimize the error of the line with respect to the data points')\n",
    "    plt.legend()\n",
    "    plt.grid(True)\n",
    "    plt.show()\n",
    "\n",
    "    # Plot the original data and the regression polynomial\n",
    "    plt.figure(figsize=(10, 6))\n",
    "    plt.scatter(xArray, yArray, label='Observed Data')\n",
    "    plt.plot(x_new, y_new, color='red', label=f'Polynomial Regression: y = {a_0:.2f} + {a_1:.2f}x + {a_2:.2f}x^2 + {a_3:.2f}x^3 + {a_4:.2f}x^4 + {a5:.2f}x^5')\n",
    "    plt.xlabel('Independent variable (x)')\n",
    "    plt.ylabel('Dependent variable (y)')\n",
    "    plt.title('Linear Regression minimizes the error of the line with respect to the data points')\n",
    "    plt.legend()\n",
    "    plt.grid(True)\n",
    "    plt.show()\n",
    "\n",
    "    # Plot  our polynomial\n",
    "    plt.figure(figsize=(10, 6))\n",
    "    plt.scatter(xArray, yArray, label='Observed Data')\n",
    "    #plt.plot(xArray, regression_polynomial, color='red', label=f'Polynomial Regression: y = {a_0:.2f} + {a_1:.2f}x + {a_2:.2f}x^2 + {a_3:.2f}x^3 + {a_4:.2f}x^4 + {a5:.2f}x^5')\n",
    "    plt.plot(x_new,        our_polynomial, color='green', label=f'Our polynomial: y = {b_0:.2f} + {b_1:.2f}x + {b_2:.2f}x^2 + {b_3:.2f}x^3 + {b_4:.2f}x^4 + {b5:.2f}x^5')\n",
    "    plt.xlabel('Independent variable (x)')\n",
    "    plt.ylabel('Dependent variable (y)')\n",
    "    plt.title('la Evoluciónary Regression minimizes the error of the line with respect to the data points')\n",
    "    plt.legend()\n",
    "    plt.grid(True)\n",
    "    plt.show()\n",
    "\n",
    "\n",
    "\n",
    "    end_time = time.time()\n",
    "    # Calculate the duration of the run in seconds\n",
    "    elapsed_time = end_time - start_time\n",
    "    elapsed_time = timedelta(seconds=elapsed_time)\n",
    "    print(f\"Elapsed time: {elapsed_time}\")\n",
    "    #return best_chromosome, totalCost, best_fitness_history\n",
    "\n",
    "    print(\"\\a\") # Alert sound to indicate the end of the run.  \n",
    "\n",
    "# Call the main function with the defined parameters\n",
    "mainj13(xArray, yArray, mutation_rate, recombination_rate, alphabet, length_of_chromosomes)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "a4909272",
   "metadata": {},
   "source": []
  },
  {
   "cell_type": "markdown",
   "id": "09b2b52e",
   "metadata": {},
   "source": [
    "*Nuestras observaciones.* \n",
    "\n",
    "- Con un millón de cromosomas como tamaño poblacional, el error comenzó con 16 y después de diez generaciones, se redujo a la mitad, que fue el error final. La curva pasa por 4 de 6 puntos, pero la silueta era imperfecta. \n",
    "- Con un tamaño de población de 10 millones, el error comenzó con 16 y el error final fue 3.8 después de 10 generaciones, la curva pasa por 4 de 6 puntos y la curva pasa cerca de otro. La silueta es pobre. \n",
    "- Con 20 millones de habitantes y 10 generaciones, el error comenzó con 11 y terminó con 1,31. Todo era casi perfecto, la silueta y el ajuste.  \n",
    "- Con 30 millones y 10 generaciones, el error comenzó con 10 y descendió a 4,2. La silueta era perfecta, se ajustaban 4 puntos, los otros dos casi se solucionan.\n",
    "- Una repetición con 20 millones dio un error final de 2,3 y una buena aproximación de la silueta. Se ajustaron cuatro puntos de seis. \n",
    "\n",
    "Nuestra conclusión: la quasiperfección es factible a un alto costo. La perfección total sigue ausente."
   ]
  },
  {
   "cell_type": "markdown",
   "id": "7a0ad3c1",
   "metadata": {},
   "source": [
    "### Las firmas m y d\n",
    "\n",
    "Hemos estado permanentemente hablando mal de la Evolución y a espaldas de ella porque estamos insatisfechos con las siluetas de las curvas que ella ha producido. Esto es muy deshonesto. Aquí hacemos un intento de decirle a la Evolución que la silueta esperada de las curvas es importante para nosotros y que debe tener una forma predefinida.  ¿Cómo se puede hacer eso? Debe hacerse de la misma manera que le hemos dicho a la Evolución que el error era muy importante y que debe ser minimizado. Por lo tanto, modificamos o actualizamos la función de error que determina quién se reproduce. \n",
    "\n",
    "Nuestra implementación es la siguiente:\n",
    "\n",
    "1. La silueta esperada es la que da la teoría matemática de la regresión y también la del sentido común. Se inyecta, como una preconcepción que afecta a la función de error. La silueta esperada está codificada como una cadena de caracteres, la m-signature o m-firma. Para nuestro conjunto de seis puntos, es mMmM, donde m significa mínimo y M, máximo, y la firma debe leerse de izquierda a derecha. Entonces, la firma comienza con un mínimo, luego un máximo, otro mínimo y termina con un máximo. Dado que el primero es un mínimo, la curva debe tomar el valor $ \\infty$ en $-\\infty$. Debe divergir a $-\\infty$ porque el último extremo es un máximo. \n",
    "2. Para determinar los extremos, calculamos la derivada en cada punto. No hay puntos de inflexión, y un cambio de signo de la derivada implica ya sea un máximo o un mínimo. Es un máximo si pasamos de + a -, y un mínimo si el cambio es de - a +. Cuando se detecta un máximo, se añade una M a la firma. Cuando se detecta un min, se le añade m. \n",
    "3. La derivada tiene el mismo signo que el cambio delta, por lo que es todo lo que debemos tener en cuenta. El cambio delta determina la d-firma.\n",
    "4. La función de error actualizada será de la forma *error = error geométrico + $ \\alpha$ error de firma*. Esta ecuación es la *espec* o *especificación de la función para optimizar*, ya sea la función de fitness, idoneidad o de error. El error de firma mide la diferencia entre las cadenas debido a una diferencia en la firma del polinomio evolucionado con respecto al deseado. El parámetro $ \\alpha$ determina la importancia relativa de cada factor. Esto debe ser determinado por la experimentación para producir los mejores resultados, el error mínimo. \n",
    "\n",
    "El código sigue."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "1cba2b1f",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Lab: Evolution finds the polynomial of minimal error\n",
      "Purpose: Use a Genetic Algorithm (MAX = selection of the fittest, mutation and recombination) to find the coefficients of a polynomial that best fits a set of points.\n",
      "Hint 1 to be tested: consider only numbers of the form -3.244025 with a sign that could be positive or negative, and a decimal point in the second place of the encoding chromosome.\n",
      "Hint 2: the error of a chromosome is the sum of the vertical distances of the points to the polynomial it encodes, plus a penalty if the d_signature of the polynomial it encodes does not match the d_signature of the expected curve.\n",
      "Date of Experiment  = 2026-04-29 07:52:25.224692\n",
      "expected_d_signature = -+-+-\n",
      "d_signature_error_weight = 500\n",
      "number_of_generations = 20\n",
      "length_of_chromosomes = 8\n",
      "alphabet =  0123456789\n",
      "Points = [(-2, 5), (-1, 1), (0, 4), (1, 0), (2, 6), (3, 3)]\n",
      "population_size = 200\n",
      "include_clone_populationj14 = True\n",
      "include_mutate_allj14 = True\n",
      "include_crossover_allj14 = False\n",
      "mutation_rate = 0.05\n",
      "print_best_fitness = False\n",
      "Total cost = population size * number of generations\n",
      "Expected d_signature: -+-+-\n",
      "Generation, best_d_signature and best_fitness\n",
      " 1  ---+- 664.624587\n",
      " 2  ---+- 585.868556\n",
      " 3  ---+- 559.743894\n",
      " 4  ---+- 544.746314\n",
      " 5  ---+- 541.8443139999999\n",
      " 6  ---+- 540.9743139999999\n",
      " 7  ---+- 540.956936\n",
      " 8  ---+- 540.9552510000001\n",
      " 9  ---+- 540.9546710000001\n",
      " 10  -+-+- 35.09853700000002\n",
      " 11  -+-+- 32.09853700000002\n",
      " 12  -+-+- 26.998537\n",
      " 13  -+-+- 23.42845600000002\n",
      " 14  -+-+- 23.04641999999999\n",
      " 15  -+-+- 22.745669999999983\n",
      " 16  -+-+- 21.077796000000014\n",
      " 17  -+-+- 19.844878000000016\n",
      " 18  -+-+- 19.462878000000035\n",
      " 19  -+-+- 19.437923000000012\n",
      " 20  -+-+- 19.437427000000007\n",
      " The best chromosome is 221371071517040873393924859825932158841831001122\n",
      " Encoded coefficientes: (2.137107, -5.170408, -3.393924, 5.982593, 1.588418, -1.001122) \n",
      " Total cost =  4000 chromosomes\n",
      " Final error =  19.437427000000007 \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": [
      "Decoded coefficients: Intercept 2.137107, slope -5.170408, quadratic -3.393924, cubic 5.982593, quartic 1.588418, quintic -1.001122\n",
      "Polynomial regression coefficients: Intercept 4.0, slope -2.983333333333327, quadratic -4.791666666666659, cubic 3.041666666666663, quartic 1.2916666666666643, quintic -0.5583333333333323\n",
      "Encoded coefficients: Intercept 2.137107, slope -5.170408, quadratic -3.393924, cubic 5.982593, quartic 1.588418, quintic -1.001122\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"
    },
    {
     "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": [
      "Elapsed time: 0:00:01.213270\n"
     ]
    }
   ],
   "source": [
    "# Program Polynomial_The_m_signature.py\n",
    "# This program uses pretends to give to la Evolución a hint to find perfection.\n",
    "# It is a genetic algorithm to find the polynomial \n",
    "# of fifth degree that best fits a set of 6 points.\n",
    "# The coefficients are represented by a chromosome, \n",
    "# which is a string of digits.\n",
    "# The decoding function must divide the chromosome into parts, \n",
    "# and decode each one apart as one coefficient.\n",
    "# We consider numbers of the form -3.244025\n",
    "# with a sign that could be positive or negative, \n",
    "# and a decimal point in the second place of the encoding chromosome.\n",
    "# The error of a chromosome is the sum of the vertical distances \n",
    "# of the points to the polynomial it encodes.\n",
    "# The Genetic algorithm must minimize the error, \n",
    "# (which is equivalent to maximizing the fitness).\n",
    "# In this program, the error has two components. \n",
    "# The first one is the sum of the vertical distances of the points to the polynomial it encodes.\n",
    "# The second one comes from the m-signature of the expected curve,\n",
    "# which is the sequence of the signs of the m-th derivatives of the curve at the points.\n",
    "# If the derivative changes from + to -, \n",
    "# we have a maximum, and if it changes from - to +, we have a minimum. \n",
    "# Our set of points is [(-2, 5), (-1, 1), (0, 4), (1, 0), (2, 6), (3, 3)].\n",
    "# The expected curve is a polynomial of fifth degree that best fits the points,\n",
    "# and has the same m-signature at the points: \n",
    "# it decreases from x=-2 to x=-1, the derivative is -\n",
    "# increases from x=-1 to x=0, the derivative is +,\n",
    "# decreases from x=0 to x=1, the derivative is -\n",
    "# increases from x=1 to x=2, the derivative is +, and\n",
    "# decreases from x=2 to x=3, the derivative is -.\n",
    "# The d_signature is the pattern of the derivative of the expected curve.\n",
    "# It is - + - + -.\n",
    "# Since a polynomial is continuous and derivable, \n",
    "# the m-signature of the expected curve is mMmM,\n",
    "# where m stands for a minimum and M for a maximum. \n",
    "# This says that\n",
    "# the curve has a minimum in within the interval (-2, -0), m is added to the signature,\n",
    "# a maximum in within the interval (-1, 1), M is added to the signature,\n",
    "# a minimum in within the interval (0, 2), m is added to the signature,\n",
    "# a maximum in within the interval (1, 3), M is added to the signature.\n",
    "# The signature is mMmM, and the expected curve must have the same signature.\n",
    "# The error of a chromosome is the sum of the vertical distances \n",
    "# of the points to the polynomial it encodes, \n",
    "# plus a penalty if the d_signature\n",
    "# of the polynomial it encodes does not match the d_signature of the expected curve.\n",
    "# The purpose of the second component is to give a hint to la Evolución to find perfection.\n",
    "# We propose here to rely on the d_signature using only the given points, and not the whole curve.\n",
    "# Developed with the assistance of the AI of Visual Studio Code.\n",
    "# An old version of a GA developed with the help of Gemini was reused and updated.\n",
    "\n",
    "\n",
    "from datetime import datetime, timedelta\n",
    "import datetime\n",
    "import time\n",
    "import random\n",
    "import numpy as np\n",
    "from numpy.polynomial import Polynomial\n",
    "import matplotlib.pyplot as plt # Import matplotlib for plotting\n",
    "\n",
    "\n",
    "start_time = time.time() # Record the start time\n",
    "# The d_signature of the expected curve, which is the pattern of the derivative of the expected curve.\n",
    "expected_d_signature = \"-+-+-\"\n",
    "# The weight of the m-signature error in the total error.\n",
    "d_signature_error_weight = 500 \n",
    "#Task to be done\n",
    "number_of_generations = 20\n",
    "\n",
    "xArray =  [-2, -1, 0, 1, 2, 3]\n",
    "yArray =  [5,   1, 4, 0, 6, 3]\n",
    "\n",
    "alphabet = '0123456789'\n",
    "# Chromosome encoding for one of 6 coefficients, \n",
    "# each one with a length of 5 chars.\n",
    "# Encoding number as -93.24 with a sign and a decimal point.\n",
    "length_of_chromosomes = 8\n",
    "population_size = 200\n",
    "# Include cloning of the fittest\n",
    "include_clone_populationj14 = True\n",
    "# Include mutation\n",
    "include_mutate_allj14 = True\n",
    "# Include recombination\n",
    "include_crossover_allj14 = False\n",
    "mutation_rate = 0.05\n",
    "recombination_rate = 0.0\n",
    "# Size of the sampled groups from which the best \n",
    "# is chosen as a parent for the next generation.\n",
    "tournament_size = 5\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_generation = True\n",
    "print_parameters = True\n",
    "print_d_signature = False\n",
    "show_graph = True\n",
    "    \n",
    "\n",
    "def print_parametersj14():\n",
    "    print(f\"Lab: la Evolución finds the polynomial of minimal error\")\n",
    "    print(f\"Purpose: Use a Genetic Algorithm (MAX = selection of the fittest, mutation and recombination) to find the coefficients of a polynomial that best fits a set of points.\")\n",
    "    print(\"Hint 1 to be tested: consider only numbers of the form -3.244025 with a sign that could be positive or negative, and a decimal point in the second place of the encoding chromosome.\")\n",
    "    print(\"Hint 2: the error of a chromosome is the sum of the vertical distances of the points to the polynomial it encodes, plus a penalty if the d_signature of the polynomial it encodes does not match the d_signature of the expected curve.\")\n",
    "    print(f\"Date of Experiment  = {datetime.datetime.now()}\")\n",
    "    print(f\"expected_d_signature = {expected_d_signature}\")\n",
    "    print(f\"d_signature_error_weight = {d_signature_error_weight}\")\n",
    "    print(f\"number_of_generations = {number_of_generations}\")\n",
    "    print(f\"length_of_chromosomes = {length_of_chromosomes}\")\n",
    "    print(f\"alphabet =  {alphabet}\")\n",
    "    print(f\"Points = {list(zip(xArray, yArray))}\")\n",
    "    print(f\"population_size = {population_size}\")\n",
    "    print(f\"include_clone_populationj14 = {include_clone_populationj14}\")\n",
    "    print(f\"include_mutate_allj14 = {include_mutate_allj14}\")\n",
    "    print(f\"include_crossover_allj14 = {include_crossover_allj14}\")\n",
    "    if include_mutate_allj14:\n",
    "        print(f\"mutation_rate = {mutation_rate}\")\n",
    "    if include_crossover_allj14:\n",
    "        print(f\"recombination_rate = {recombination_rate}\")\n",
    "    if include_clone_populationj14:\n",
    "        print(f\"print_best_fitness = {print_best_fitness}\")\n",
    "\n",
    "def draw_points_and_polynomialj14(xNumpyArray, yNumpyArray):\n",
    "    \"\"\"Draws the original data points, finds and draws the \n",
    "    regression polynomial defined by the coefficients.\"\"\"\n",
    "    \n",
    "    # 2. Fit a 5th-degree (quintic) polynomial\n",
    "    # .fit() returns a Polynomial instance\n",
    "    p_fitted = Polynomial.fit(xNumpyArray, yNumpyArray, deg=5)\n",
    "\n",
    "    # 3. Predict values for visualization\n",
    "    x_new = np.linspace(-2,3, 100) # Generate 100 points between 0 and 6 for a smooth curve\n",
    "    y_new = p_fitted(x_new)\n",
    "    b_0, b_1, b_2, b_3, b_4, b5 = p_fitted.coef\n",
    "\n",
    "    # 4. Plot results\n",
    "    plt.scatter(xNumpyArray, yNumpyArray, label='Data Points')\n",
    "    plt.xlabel('x')\n",
    "    plt.ylabel('y')\n",
    "    plt.plot(x_new, y_new, label=f'Quintic Fit: y = {b_0:.2f} + {b_1:.2f}x + {b_2:.2f}x^2 + {b_3:.2f}x^3 + {b_4:.2f}x^4 + {b5:.2f}x^5', color='green')\n",
    "    plt.title(' Data Points and Quintic Fit by numpy.polynomial.Polynomial.fit()')\n",
    "    plt.legend()\n",
    "    plt.show()\n",
    "    return p_fitted.coef\n",
    "\n",
    "\n",
    "\n",
    "def create_populationj14(population_size, length_of_chromosomes, alphabet):\n",
    "    \"\"\"Creates a new population with random chromosomes.\"\"\"\n",
    "    # print(\"create_populationj14(population_size, target_sequence, alphabet)\")\n",
    "    population = []\n",
    "    for _ in range(population_size):\n",
    "        random_string1 = ''.join(random.choice(alphabet) for _ in range(length_of_chromosomes))\n",
    "        random_string2 = ''.join(random.choice(alphabet) for _ in range(length_of_chromosomes))\n",
    "        random_string3 = ''.join(random.choice(alphabet) for _ in range(length_of_chromosomes))\n",
    "        random_string4 = ''.join(random.choice(alphabet) for _ in range(length_of_chromosomes))\n",
    "        random_string5 = ''.join(random.choice(alphabet) for _ in range(length_of_chromosomes))\n",
    "        random_string6 = ''.join(random.choice(alphabet) for _ in range(length_of_chromosomes))\n",
    "        random_string = random_string1 + random_string2 + random_string3 + random_string4 + random_string5 + random_string6\n",
    "        population.append(random_string)\n",
    "    # print(\"initial population\")\n",
    "    # print(population)\n",
    "    return population\n",
    "\n",
    "# Decode a part of the chromosome into a coefficient of the polynomial.\n",
    "def decoderOldj14(s):\n",
    "    ''' The input is a number as string, outputs the number as a float. \n",
    "        We consider numbers of the form 93.24 with a sign that could be positive or negative,\n",
    "    '''\n",
    "    l = len(s) \n",
    "    # The first char encodes for the sign, \n",
    "    sign = 1\n",
    "    if  float(s[0]) % 2 == 1:\n",
    "        sign = -1\n",
    "    # The remaining chars encode for the number itself, \n",
    "    # without the decimal point nor sign.\n",
    "    sn = s[1:l]\n",
    "    # The point is inserted after the second char, so that we have numbers of the form 93.24\n",
    "    sn = sn[:2] + \".\" + sn[2:]\n",
    "    # Convert the string to a number\n",
    "    n = float(sn)\n",
    "    return sign * n\n",
    "\n",
    "# Decode a part of the chromosome into a coefficient of the polynomial.\n",
    "def decoderj14(s):\n",
    "    ''' The input is a number as string, outputs the number as a float. \n",
    "        We consider numbers of the form 93.24 with a sign that could be positive or negative,\n",
    "    '''\n",
    "    l = len(s) \n",
    "    # The first char encodes for the sign, \n",
    "    sign = 1\n",
    "    if  float(s[0]) % 2 == 1:\n",
    "        sign = -1\n",
    "    # The remaining chars encode for the number itself, \n",
    "    # without the decimal point nor sign.\n",
    "    sn = s[1:l]\n",
    "    # The point is inserted after the first char, so that we have numbers of the form -3.24\n",
    "    sn = sn[:1] + \".\" + sn[1:]\n",
    "    # Convert the string to a number\n",
    "    n = float(sn)\n",
    "    return sign * n\n",
    "\n",
    "\n",
    "def decodeFullCromosomej14(chromosome, length_of_chromosomes):\n",
    "    \"\"\"Decodes the full chromosome into the coefficients of the polynomial.\"\"\"\n",
    "    \"\"\"The chromosome is divided into 5 parts, \n",
    "        each one encoding for a coefficient of the polynomial.\"\"\"\n",
    "    chro0 = chromosome[0:length_of_chromosomes]\n",
    "    chro1 = chromosome[length_of_chromosomes:2*length_of_chromosomes]\n",
    "    chro2 = chromosome[2*length_of_chromosomes:3*length_of_chromosomes]\n",
    "    chro3 = chromosome[3*length_of_chromosomes:4*length_of_chromosomes]\n",
    "    chro4 = chromosome[4*length_of_chromosomes:5*length_of_chromosomes]\n",
    "    chro5 = chromosome[5*length_of_chromosomes:6*length_of_chromosomes]\n",
    "    a_0 = decoderj14(chro0)\n",
    "    a_1 = decoderj14(chro1)\n",
    "    a_2 = decoderj14(chro2)\n",
    "    a_3 = decoderj14(chro3)\n",
    "    a_4 = decoderj14(chro4)\n",
    "    a_5 = decoderj14(chro5)\n",
    "    # print(f\"Chromosome: {chromosome}\")\n",
    "    # print(f\"Coefficients: Intercept {a_0}, slope {a_1}, quadratic {a_2}, cubic {a_3}, quartic {a_4}, quintic {a_5}\")\n",
    "    # print()\n",
    "    return a_0, a_1, a_2, a_3, a_4, a_5\n",
    "\n",
    "\n",
    "\n",
    "def calculate_geometrical_errorj14(chromosome, xArray, yArray, length_of_chromosomes):\n",
    "    \"\"\"Calculates the error of a chromosome.\n",
    "        A chromosome encodes for the coefficients of a polynomial of fith degree.\n",
    "        The error of a chromosome is the sum of \n",
    "        the vertical distances of the points to the polynomial it encodes.\n",
    "    \"\"\"\n",
    "    #  print(\"\\n calculate_geometrical_errorj14(chromosome, xArray, yArray)\")\n",
    "    a_0, a_1, a_2, a_3, a_4, a_5 = decodeFullCromosomej14(chromosome, length_of_chromosomes) \n",
    "    error = 0\n",
    "    for i in range(len(xArray)):\n",
    "        x = xArray[i]\n",
    "        y = yArray[i]\n",
    "        # Calculate the predicted y value based on the coefficients of the polynomial\n",
    "        predicted_y = a_0 + a_1 * x + a_2 * x**2 + a_3 * x**3 + a_4 * x**4 + a_5 * x**5\n",
    "        # Calculate the error as the quadratic difference \n",
    "        # between predicted and y value\n",
    "        # error += (predicted_y - y)**2\n",
    "        # Calculate the error as the distance between predicted and y value\n",
    "        error += abs(predicted_y - y)\n",
    "    return error\n",
    "\n",
    "def calculate_d_signaturej14(chromosome, xArray, yArray, length_of_chromosomes):\n",
    "    \"\"\"Calculates the d-signature of the polynomial encoded by the chromosome.\n",
    "        The d-signature of a curve is the sequence of the signs of the derivative of the curve at the points.\n",
    "        If the derivative changes from + to -, we have a maximum, and if it changes from - to +, we have a minimum. \n",
    "        Our set of points is [(-2, 5), (-1, 1), (0, 4), (1, 0), (2, 6), (3, 3)].\n",
    "        The expected curve is a polynomial of fifth degree that best fits the points,\n",
    "        and has the same m-signature at the points: \n",
    "        it decreases from x=-2 to x=-1, the derivative is -\n",
    "        increases from x=-1 to x=0, the derivative is +,\n",
    "        decreases from x=0 to x=1, the derivative is -\n",
    "        increases from x=1 to x=2, the derivative is +, and\n",
    "        decreases from x=2 to x=3, the derivative is -.\n",
    "        The pattern of the derivative of the expected curve is - + - + -.\n",
    "        Since a polynomial is continuous and derivable, \n",
    "        the m-signature of the expected curve is mMmM,\n",
    "        where m stands for a minimum and M for a maximum. \n",
    "    \"\"\"\n",
    "    # This function can be implemented by calculating if the expected function is increasing or decreasing at each point. \n",
    "    # Then we can compare it with the expected m-signature and calculate an error based on how many signs are different.\n",
    "    a_0, a_1, a_2, a_3, a_4, a_5 = decodeFullCromosomej14(chromosome, length_of_chromosomes) \n",
    "    # Calculate the predicted y value at each x-coordinate based on the coefficients of the polynomial\n",
    "    predicted_y = a_0 + a_1 * np.array(xArray) + a_2 * np.array(xArray)**2 + a_3 * np.array(xArray)**3 + a_4 * np.array(xArray)**4 + a_5 * np.array(xArray)**5\n",
    "    # Calculate the sign of the first derivative at each point\n",
    "    d_signature = \"\"\n",
    "    for i in range(len(xArray)-1):\n",
    "        x1 = xArray[i]\n",
    "        x2 = xArray[i+1]\n",
    "        y1 = predicted_y[i]\n",
    "        y2 = predicted_y[i+1]\n",
    "        if y2 > y1:\n",
    "            sign = '+'\n",
    "        elif y2 < y1:\n",
    "            sign = '-'\n",
    "        else:\n",
    "            sign = '0'\n",
    "        d_signature += sign\n",
    "        # print(f\"At x={x1} to x={x2}, the predicted function is {'increasing' if sign == '+' else 'decreasing' if sign == '-' else 'constant'}\")\n",
    "    if print_d_signature:\n",
    "        print(f\"d_signature = {d_signature}\")\n",
    "    \n",
    "    return d_signature\n",
    "\n",
    "def calculate_d_signature_errorj14(chromosome, xArray, yArray, length_of_chromosomes):\n",
    "    \"\"\"Calculates the error of the d-signature error of the polynomial encoded by the chromosome.\n",
    "        The d-signature of a curve is the sequence of the signs of the derivative of the curve at the points.\n",
    "        If the derivative changes from + to -, we have a maximum, and if it changes from - to +, we have a minimum. \n",
    "        Our set of points is [(-2, 5), (-1, 1), (0, 4), (1, 0), (2, 6), (3, 3)].\n",
    "        The expected curve is a polynomial of fifth degree that best fits the points,\n",
    "        and has the same m-signature at the points: \n",
    "        it decreases from x=-2 to x=-1, the derivative is -\n",
    "        increases from x=-1 to x=0, the derivative is +,\n",
    "        decreases from x=0 to x=1, the derivative is -\n",
    "        increases from x=1 to x=2, the derivative is +, and\n",
    "        decreases from x=2 to x=3, the derivative is -.\n",
    "        The pattern of the derivative of the expected curve is - + - + -.\n",
    "        Since a polynomial is continuous and derivable, \n",
    "        the m-signature of the expected curve is mMmM,\n",
    "        where m stands for a minimum and M for a maximum. \n",
    "    \"\"\"\n",
    "    d_signature = calculate_d_signaturej14(chromosome, xArray, yArray, length_of_chromosomes)\n",
    "    # The d-signature error is the number of signs that are different from the expected d_signature.\n",
    "    d_signature_error = sum(1 for a, b in zip(d_signature, expected_d_signature) if a != b)\n",
    "\n",
    "    return d_signature_error\n",
    "\n",
    "\n",
    "def calculate_all_errorsj14(population, xArray, yArray, length_of_chromosomes,  d_signature_error_weight):\n",
    "    # print(\"\\n*calculate_all_errorsj14(population, target_sequence)\")\n",
    "    \"\"\"Calculates the error of all chromosomes in the population.\n",
    "        The error of a chromosome is the sum of the geometrical error and the m-signature error,\n",
    "        with a weight for the m-signature error to give it more or less importance.\n",
    "        Developed almost entirely by the AI of Visual Studio Code.\"\"\"\n",
    "    g_errors = [calculate_geometrical_errorj14(chromosome, xArray, yArray, length_of_chromosomes) for chromosome in population]\n",
    "    d_signature_errors = [calculate_d_signature_errorj14(chromosome, xArray, yArray, length_of_chromosomes) for chromosome in population]\n",
    "    # The total error is the sum of the geometrical error and the d-signature error, with a weight for the d-signature error to give it more or less importance.\n",
    "    errors = [g + d_signature_error_weight * d for g, d in zip(g_errors, d_signature_errors)]\n",
    "    # print(\"errors: \", errors)\n",
    "    return errors\n",
    "\n",
    "def select_the_least_errorj14(population, xArray, yArray, length_of_chromosomes, d_signature_error_weight):\n",
    "    \"\"\"Selects the best chromosome with minimal error for reproduction.\"\"\"\n",
    "    errors = calculate_all_errorsj14(population, xArray, yArray, length_of_chromosomes, d_signature_error_weight)\n",
    "    smallest_error = min(errors)\n",
    "    best_chromosome_index = errors.index(smallest_error)\n",
    "    best_chromosome = population[best_chromosome_index]\n",
    "    # print(\"\\n*select_the_least_errorj14(population)\")\n",
    "    # print(\"smallest_error = \", smallest_error)\n",
    "    # print(\"The chro = \", best_chromosome )\n",
    "    return smallest_error, best_chromosome\n",
    "\n",
    "def clone_populationj14(best_chromosome, population_size):\n",
    "    \"\"\"Creates a new population by cloning the best chromosome.\"\"\"\n",
    "    return [best_chromosome] * population_size\n",
    "\n",
    "\n",
    "def mutatej14(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_allj14(population, mutation_rate, alphabet):\n",
    "    \"\"\"Mutates all chromosomes in the population.\"\"\"\n",
    "    mutated_population = []\n",
    "    for chromosome in population:\n",
    "        mutated_chromosome = mutatej14(chromosome, mutation_rate, alphabet)\n",
    "        mutated_population.append(mutated_chromosome)\n",
    "    return mutated_population\n",
    "\n",
    "def crossoverj14(parent1, parent2, length_of_chromosomes, recombination_rate):\n",
    "    \"\"\"Performs crossover between two parent chromosomes.\"\"\"\n",
    "    if random.random() < recombination_rate:\n",
    "        crossover_point = random.randint(0, length_of_chromosomes)\n",
    "        return parent1[:crossover_point] + parent2[crossover_point:]\n",
    "    else:\n",
    "        return parent1\n",
    "\n",
    "def crossover_allj14(population, length_of_chromosomes, 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 = crossoverj14(parent1, parent2, length_of_chromosomes, recombination_rate)\n",
    "        recombinant_population.append(child)\n",
    "    return recombinant_population\n",
    "\n",
    "\n",
    "\n",
    "def run_one_generationj14(population, xArray, yArray, mutation_rate, recombination_rate, alphabet, length_of_chromosomes, m_signature_error_weight):\n",
    "    \"\"\"Runs one generation of the genetic algorithm.\"\"\"\n",
    "    # Calculate fitness scores for the current population\n",
    "    smallest_error, best_chromosome  = select_the_least_errorj14(population, xArray, yArray, length_of_chromosomes, m_signature_error_weight)\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_populationj14:\n",
    "        new_population = clone_populationj14(best_chromosome, population_size)\n",
    "    if include_mutate_allj14:\n",
    "        new_population = mutate_allj14(new_population, mutation_rate, alphabet)\n",
    "    if include_crossover_allj14:\n",
    "        new_population = crossover_allj14(new_population, length_of_chromosomes, recombination_rate)\n",
    "    return smallest_error, best_chromosome, new_population\n",
    "\n",
    "\n",
    "\n",
    "def plot_functionj14(g_values, 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 taskj14( xArray, yArray, mutation_rate, recombination_rate, alphabet,  length_of_chromosomes, d_signature_error_weight):\n",
    "    population = create_populationj14(population_size, length_of_chromosomes, alphabet)\n",
    "    # print(population)\n",
    "    generation = 0\n",
    "    best_chromosome = ''\n",
    "    best_fitness = 0\n",
    "    start_time = time.time()\n",
    "    smallest_error_history = [] # List to store best fitness of each generation\n",
    "    if print_generation:\n",
    "        print(f\"Expected d_signature: {expected_d_signature}\")\n",
    "        print(\"Generation, best_d_signature and best_fitness\")\n",
    "    while generation < number_of_generations:\n",
    "        generation += 1\n",
    "        smallest_error, best_chromosome, population = run_one_generationj14(population, xArray,yArray, mutation_rate, recombination_rate, alphabet, length_of_chromosomes, d_signature_error_weight)\n",
    "        best_d_signature = calculate_d_signaturej14(best_chromosome, xArray, yArray, length_of_chromosomes)\n",
    "        if print_generation:\n",
    "            print(f\" {generation}  {best_d_signature} {smallest_error}\")\n",
    "        smallest_error_history.append(smallest_error)\n",
    "    # print(f\"\\nTarget sequence matched in generation {generation}\")\n",
    "    # print(f\"Final chromosome: {best_chromosome}\")\n",
    "    totalCost = population_size * generation\n",
    "    return  best_chromosome, totalCost, smallest_error_history\n",
    "\n",
    "def mainj14(xArray, yArray, mutation_rate, recombination_rate, alphabet, length_of_chromosomes):\n",
    "    print_parametersj14()\n",
    "    print(\"Total cost = population size * number of generations\")\n",
    "    best_chromosome, totalCost, smallest_error_history = taskj14(xArray, yArray, mutation_rate, recombination_rate, alphabet, length_of_chromosomes, d_signature_error_weight)\n",
    "    final_error = smallest_error_history[-1]\n",
    "    print(f\" The best chromosome is {best_chromosome}\" )\n",
    "    coefficients = decodeFullCromosomej14(best_chromosome, length_of_chromosomes)\n",
    "    print(f\" Encoded coefficientes: {coefficients} \" )\n",
    "    print(f\" Total cost =  {totalCost} chromosomes\")\n",
    "    print(f\" Final error =  {final_error} \")\n",
    "\n",
    "    # Plot the fitness history \n",
    "    g_values = list(range(1, len(smallest_error_history) + 1))\n",
    "    plot_functionj14(g_values, smallest_error_history, xlabel='Generation', ylabel='SmallestError', title='Smallest Error Over Generations')\n",
    "    # The best chromosome encodes for the coefficients of the polynomial that best fits the data points\"\n",
    "    b_0, b_1, b_2, b_3, b_4, b5 = decodeFullCromosomej14(best_chromosome, length_of_chromosomes)\n",
    "    print(f\"Decoded coefficients: Intercept {b_0}, slope {b_1}, quadratic {b_2}, cubic {b_3}, quartic {b_4}, quintic {b5}\")\n",
    "    # Calculate the predicted y value based on the coefficients of the polynomial\n",
    "    our_polynomial = b_0 + b_1 * np.array(xArray) + b_2 * np.array(xArray)**2 + b_3 * np.array(xArray)**3 + b_4 * np.array(xArray)**4 + b5 * np.array(xArray)**5\n",
    "    \n",
    "\n",
    "    # Perform polynomial regression\n",
    "    # Fit a polynomial of degree 5 (polynomial regression)\n",
    "    p_fitted = Polynomial.fit(xArray, yArray, deg=5)\n",
    "    a_0, a_1, a_2, a_3, a_4, a5 = p_fitted.convert().coef\n",
    "    print(f\"Polynomial regression coefficients: Intercept {a_0}, slope {a_1}, quadratic {a_2}, cubic {a_3}, quartic {a_4}, quintic {a5}\")\n",
    "    # Create the regression graph\n",
    "    x_new = np.linspace(-2,3, 100) # Generate 100 points between -2 and 3 for a smooth curve\n",
    "    y_new = p_fitted(x_new)\n",
    "\n",
    "    # The best chromosome encodes for the coefficients of the polynomial that best fits the data points\"\n",
    "    b_0, b_1, b_2, b_3, b_4, b5 = decodeFullCromosomej14(best_chromosome, length_of_chromosomes)\n",
    "    print(f\"Encoded coefficients: Intercept {b_0}, slope {b_1}, quadratic {b_2}, cubic {b_3}, quartic {b_4}, quintic {b5}\")\n",
    "    # Calculate the predicted y value based on the coefficients of the polynomial\n",
    "    our_polynomial = b_0 + b_1 * np.array(x_new ) + b_2 * np.array(x_new )**2 + b_3 * np.array(x_new )**3 + b_4 * np.array(x_new )**4 + b5 * np.array(x_new )**5\n",
    "    \n",
    "\n",
    "\n",
    "    # Plot the original data, the regression polynomial, and our polynomial\n",
    "    plt.figure(figsize=(10, 6))\n",
    "    plt.scatter(xArray, yArray, label='Observed Data')\n",
    "    plt.plot(x_new, y_new, color='red', label=f'Polynomial Regression: y = {a_0:.2f} + {a_1:.2f}x + {a_2:.2f}x^2 + {a_3:.2f}x^3 + {a_4:.2f}x^4 + {a5:.2f}x^5')\n",
    "    plt.plot(x_new,        our_polynomial, color='green', label=f'Our polynomial: y = {b_0:.2f} + {b_1:.2f}x + {b_2:.2f}x^2 + {b_3:.2f}x^3 + {b_4:.2f}x^4 + {b5:.2f}x^5')\n",
    "    plt.xlabel('Independent variable (x)')\n",
    "    plt.ylabel('Dependent variable (y)')\n",
    "    plt.title('Linear Regression and la Evolución minimize the error of the line with respect to the data points')\n",
    "    plt.legend()\n",
    "    plt.grid(True)\n",
    "    plt.show()\n",
    "\n",
    "    # Plot the original data and the regression polynomial\n",
    "    plt.figure(figsize=(10, 6))\n",
    "    plt.scatter(xArray, yArray, label='Observed Data')\n",
    "    plt.plot(x_new, y_new, color='red', label=f'Polynomial Regression: y = {a_0:.2f} + {a_1:.2f}x + {a_2:.2f}x^2 + {a_3:.2f}x^3 + {a_4:.2f}x^4 + {a5:.2f}x^5')\n",
    "    plt.xlabel('Independent variable (x)')\n",
    "    plt.ylabel('Dependent variable (y)')\n",
    "    plt.title('Linear Regression minimizes the error of the line with respect to the data points')\n",
    "    plt.legend()\n",
    "    plt.grid(True)\n",
    "    plt.show()\n",
    "\n",
    "    # Plot  our polynomial\n",
    "    plt.figure(figsize=(10, 6))\n",
    "    plt.scatter(xArray, yArray, label='Observed Data')\n",
    "    #plt.plot(xArray, regression_polynomial, color='red', label=f'Polynomial Regression: y = {a_0:.2f} + {a_1:.2f}x + {a_2:.2f}x^2 + {a_3:.2f}x^3 + {a_4:.2f}x^4 + {a5:.2f}x^5')\n",
    "    plt.plot(x_new,        our_polynomial, color='green', label=f'Our polynomial: y = {b_0:.2f} + {b_1:.2f}x + {b_2:.2f}x^2 + {b_3:.2f}x^3 + {b_4:.2f}x^4 + {b5:.2f}x^5')\n",
    "    plt.xlabel('Independent variable (x)')\n",
    "    plt.ylabel('Dependent variable (y)')\n",
    "    plt.title('la Evoluciónary Regression minimizes the error of the line with respect to the data points')\n",
    "    plt.legend()\n",
    "    plt.grid(True)\n",
    "    plt.show()\n",
    "\n",
    "\n",
    "\n",
    "    end_time = time.time()\n",
    "    # Calculate the duration of the run in seconds\n",
    "    elapsed_time = end_time - start_time\n",
    "    elapsed_time = timedelta(seconds=elapsed_time)\n",
    "    print(f\"Elapsed time: {elapsed_time}\")\n",
    "    #return best_chromosome, totalCost, best_fitness_history\n",
    " \n",
    "# Call the main function with the defined parameters\n",
    "mainj14(xArray, yArray, mutation_rate, recombination_rate, alphabet, length_of_chromosomes)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "87eec5e3",
   "metadata": {},
   "source": [
    "   \n",
    "**Ejercicio.** Juega con el programa anterior y reporta tus observaciones. Decide si la ayuda dada por la d-firma ayuda a la Evolución. \n",
    "\n",
    "*Nuestras observaciones.* Ejecutamos el programa con un tamaño de población de 200: \n",
    "\n",
    "1. La población original ya tiene un exponente con la firma correcta.\n",
    "2. El proceso evolutivo intercalan saltos en medio de períodos de éxtasis. \n",
    "3. Con frecuencia, 10 generaciones son suficientes para definir correctamente la d-firma. Por lo tanto, la pista resuelve correctamente el problema de silueta que nos pareció tan preocupante. \n",
    "4. A veces 20 generaciones son suficientes para lograr un error con un dígito.  Este comportamiento también se observa cuando el peso de la d-firma se establece en cero, cuando la pista se silencia. \n",
    "5. Los errores altos son menos frecuentes con la d-firma  que sin ella. Por lo tanto, la d-firma hace que las conclusiones sean más confiables. \n"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "10cc3fe0",
   "metadata": {},
   "source": [
    "\n",
    "# OBSERVANDO EL PROCESO EVOLUTIVO\n",
    "\n",
    "Observemos cómo evoluciona la silueta del polinomio.\n",
    "\n",
    "**Ejercicio.** Añada al programa anterior la posibilidad de ver el progreso de la forma del polinomio en Evolución. Reporte sus observaciones.\n",
    ">\n",
    "> *Respuesta.* Ordenamos al programa anterior, que incluye la d-signature como una pista, que dibuje el mejor polinomio para aquellas generaciones en las que el error disminuye en una o más unidades."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "ccddf13f",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Lab: Evolution finds the polynomial of minimal error\n",
      "Purpose: Use a Genetic Algorithm (MAX = selection of the fittest, mutation and recombination) to find the coefficients of a polynomial that best fits a set of points.\n",
      "Hint 1 to be tested: consider only numbers of the form -3.244025 with a sign that could be positive or negative, and a decimal point in the second place of the encoding chromosome.\n",
      "Hint 2: the error of a chromosome is the sum of the vertical distances of the points to the polynomial it encodes, plus a penalty if the d_signature of the polynomial it encodes does not match the d_signature of the expected curve.\n",
      "Date of Experiment  = 2026-05-05 06:42:58.935508\n",
      "expected_d_signature = -+-+-\n",
      "d_signature_error_weight = 500\n",
      "number_of_generations = 200\n",
      "length_of_chromosomes = 8\n",
      "alphabet =  0123456789\n",
      "Points = [(-2, 5), (-1, 1), (0, 4), (1, 0), (2, 6), (3, 3)]\n",
      "population_size = 200\n",
      "include_clone_populationj15 = True\n",
      "include_mutate_allj15 = True\n",
      "include_crossover_allj15 = False\n",
      "mutation_rate = 0.05\n",
      "print_best_fitness = False\n",
      "Total cost = population size * number of generations\n",
      "Expected d_signature: -+-+-\n",
      "Generation, best_d_signature and best_fitness\n",
      " 1  -+++- 753.174052\n",
      "Generation 1: Error decreased to 753.174052. Best chromosome: 476800708487934896693309898350476281393012617256\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": [
      " 2  -+-+- 263.85724400000004\n",
      "Generation 2: Error decreased to 263.85724400000004. Best chromosome: 476800709487934896693309898350476281393012617256\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      " 3  -+-+- 59.90012200000004\n",
      "Generation 3: Error decreased to 59.90012200000004. Best chromosome: 476800709487934896693303898350476261393011617256\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      " 4  -+-+- 46.192251999999996\n",
      "Generation 4: Error decreased to 46.192251999999996. Best chromosome: 476800709487934896693303898350476261394011677256\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      " 5  -+-+- 41.23328600000002\n",
      "Generation 5: Error decreased to 41.23328600000002. Best chromosome: 446800709487934896693509898350476261394011677256\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      " 6  -+-+- 38.803286\n",
      "Generation 6: Error decreased to 38.803286. Best chromosome: 446800709487934896693509898350476264394011677256\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      " 7  -+-+- 38.215198\n",
      " 8  -+-+- 37.90958599999996\n",
      " 9  -+-+- 36.650901999999896\n",
      "Generation 9: Error decreased to 36.650901999999896. Best chromosome: 442800769887934896393509898350476264396011612216\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      " 10  -+-+- 28.00249000000005\n",
      "Generation 10: Error decreased to 28.00249000000005. Best chromosome: 442800779887954896993509898350476264390011612216\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      " 11  -+-+- 27.675546000000004\n",
      " 12  -+-+- 27.58674600000002\n",
      " 13  -+-+- 27.55674599999997\n",
      " 14  -+-+- 27.517745999999974\n",
      " 15  -+-+- 27.51697\n",
      " 16  -+-+- 27.516069999999964\n",
      " 17  -+-+- 27.51449599999998\n",
      " 18  -+-+- 27.514030000000005\n",
      " 19  -+-+- 27.49456299999997\n",
      " 20  -+-+- 27.49426299999995\n",
      " 21  -+-+- 27.43425699999998\n",
      " 22  -+-+- 26.945857000000046\n",
      "Generation 22: Error decreased to 26.945857000000046. Best chromosome: 442000577887214696999159898951486262312011610206\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      " 23  -+-+- 26.907570999999976\n",
      " 24  -+-+- 26.896516000000013\n",
      " 25  -+-+- 26.89489600000001\n",
      " 26  -+-+- 26.89343800000001\n",
      " 27  -+-+- 26.89272399999995\n",
      " 28  -+-+- 26.892705999999997\n",
      " 29  -+-+- 26.892682999999998\n",
      " 30  -+-+- 26.891658999999986\n",
      " 31  -+-+- 26.831402999999995\n",
      " 32  -+-+- 26.785159000000014\n",
      " 33  -+-+- 26.771659000000003\n",
      " 34  -+-+- 26.624659000000044\n",
      " 35  -+-+- 26.618658999999997\n",
      " 36  -+-+- 26.618658999999997\n",
      " 37  -+-+- 26.61836999999993\n",
      " 38  -+-+- 26.61830999999996\n",
      " 39  -+-+- 26.618194000000067\n",
      " 40  -+-+- 26.618169999999942\n",
      " 41  -+-+- 26.618134000000055\n",
      " 42  -+-+- 26.618113000000065\n",
      " 43  -+-+- 26.61811300000003\n",
      " 44  -+-+- 26.618110000000048\n",
      " 45  -+-+- 26.618110000000016\n",
      " 46  -+-+- 26.618095000000025\n",
      " 47  -+-+- 26.61806500000006\n",
      " 48  -+-+- 26.618065000000048\n",
      " 49  -+-+- 26.618065000000023\n",
      " 50  -+-+- 26.618065000000023\n",
      " 51  -+-+- 26.618065000000023\n",
      " 52  -+-+- 26.618065000000023\n",
      " 53  -+-+- 26.618065000000023\n",
      " 54  -+-+- 26.618065000000023\n",
      " 55  -+-+- 26.618065000000023\n",
      " 56  -+-+- 26.618065000000023\n",
      " 57  -+-+- 26.618065000000023\n",
      " 58  -+-+- 26.618065000000023\n",
      " 59  -+-+- 26.618065000000023\n",
      " 60  -+-+- 26.618065000000023\n",
      " 61  -+-+- 26.618065000000023\n",
      " 62  -+-+- 26.618065000000023\n",
      " 63  -+-+- 26.618065000000023\n",
      " 64  -+-+- 26.618065000000023\n",
      " 65  -+-+- 26.618065000000023\n",
      " 66  -+-+- 26.618065000000023\n",
      " 67  -+-+- 26.618065000000023\n",
      " 68  -+-+- 26.61658000000004\n",
      " 69  -+-+- 26.61523000000004\n",
      " 70  -+-+- 26.612830000000073\n",
      " 71  -+-+- 26.612650000000055\n",
      " 72  -+-+- 26.61235000000004\n",
      " 73  -+-+- 26.611992999999995\n",
      " 74  -+-+- 26.61199299999999\n",
      " 75  -+-+- 26.61199299999999\n",
      " 76  -+-+- 26.61199299999999\n",
      " 77  -+-+- 26.611981000000043\n",
      " 78  -+-+- 26.611978000000054\n",
      " 79  -+-+- 26.611977999999997\n",
      " 80  -+-+- 26.611977999999997\n",
      " 81  -+-+- 26.611977999999997\n",
      " 82  -+-+- 26.611977999999997\n",
      " 83  -+-+- 26.611977999999997\n",
      " 84  -+-+- 26.611977999999997\n",
      " 85  -+-+- 26.611977999999997\n",
      " 86  -+-+- 26.611977999999997\n",
      " 87  -+-+- 26.611977999999997\n",
      " 88  -+-+- 26.611977999999997\n",
      " 89  -+-+- 26.611977999999997\n",
      " 90  -+-+- 26.611977999999997\n",
      " 91  -+-+- 26.611977999999997\n",
      " 92  -+-+- 26.611977999999997\n",
      " 93  -+-+- 26.611977999999997\n",
      " 94  -+-+- 26.611977999999997\n",
      " 95  -+-+- 26.611977999999997\n",
      " 96  -+-+- 26.611977999999997\n",
      " 97  -+-+- 26.611977999999997\n",
      " 98  -+-+- 26.611977999999997\n",
      " 99  -+-+- 26.611977999999997\n",
      " 100  -+-+- 26.611977999999997\n",
      " 101  -+-+- 26.611977999999997\n",
      " 102  -+-+- 26.611977999999997\n",
      " 103  -+-+- 26.611977999999997\n",
      " 104  -+-+- 26.611977999999997\n",
      " 105  -+-+- 26.611977999999997\n",
      " 106  -+-+- 26.611977999999997\n",
      " 107  -+-+- 26.611977999999997\n",
      " 108  -+-+- 26.611977999999997\n",
      " 109  -+-+- 26.611977999999997\n",
      " 110  -+-+- 26.611977999999997\n",
      " 111  -+-+- 26.611977999999997\n",
      " 112  -+-+- 26.189813999999963\n",
      " 113  -+-+- 26.086614000000004\n",
      " 114  -+-+- 26.025714\n",
      " 115  -+-+- 26.012214000000036\n",
      " 116  -+-+- 26.01077799999998\n",
      " 117  -+-+- 26.010777999999974\n",
      " 118  -+-+- 26.009877999999972\n",
      " 119  -+-+- 26.009877999999958\n",
      " 120  -+-+- 26.00927800000001\n",
      " 121  -+-+- 25.37383899999999\n",
      "Generation 121: Error decreased to 25.37383899999999. Best chromosome: 640014233819200777399200098994796263609991610400\n"
     ]
    },
    {
     "data": {
      "image/png": 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Lj4+PvPnmmyIi8ujRIwEg8+bNy/Sxc1KyMmLECAEg165dy9b82nV/1KhRetNnz54tACQ0NFQ3zd/fXywtLeX69et687711ltia2srd+/e1Zverl07cXBw0CUI2g+2Tp066c03ZswYASAffPCB3vSuXbuKu7u77u9du3al+1pv2LBBAMjixYtFROS3334TAHL+/PkMn/ePP/4oAOTXX3/Vmz5r1iwBIHv27NFNAyA+Pj56Px1v3bpVAEj16tX1EoN58+YJALl48aKIKD+bu7u7p3nOycnJUq1aNalTp06GMYpkvt4FBgaKSNrELrclK926ddObfvToUQEgX375pW7awIEDxcvLS+Lj43XTZs2aJRYWFhIcHJzhY/z9998CQCZOnJjmfy8nL9rxzMnYZXc7cPz4cQEg3377rd589+7dE3t7exk/frxuWtOmTQVAhqVfWtrt08GDB9MkSZmVrLz8uk2cOFEAyIkTJ/TmGzlypGg0Gt37TrtOVKlSRW+7c/LkSQEg69atyzTel+UkIY+KipIKFSqIn5+fREdHZzifIRPyjNb/1CUz2tf/s88+S3cZhthuNWnSxCBxp75k9bmTngsXLoi9vX2a9+v9+/dl2LBh8uuvv8rhw4dlzZo1Uq9ePQEgP//8c7aXP3z4cF18NjY2snDhwizvU7duXSlUqJDExsbm+PmwZIVyTET0/n727BkmTJiA0qVLw8rKClZWVnByckJMTEyacpCMhIeHY8SIEfDz84OVlRWsra3h7+8PANlexoQJE2BtbQ07OzvUqlULd+/exU8//aTrthIbG5vmZ1E/Pz+0aNEiWz+ZV69eXa+8wc7ODmXLltUriclI6dKl4ebmhgkTJuDHH39EUFBQtp4TkPOx6dy5s97fVatWRVxcnK5Dzv79+wEAffv21Zvv5YNfsjJ69GicOnUKp06dwv79+zFjxgz8+uuv6N27t26e3bt3IykpCQMGDEBSUpLuYmdnh6ZNm+LAgQMAAHd3d5QqVQpff/015syZg3Pnzun9NG1K6Y0fgDSvc9WqVVG2bFm9afv27UPLli3h5+enN33QoEF4/vx5mgOAOnbsqPd3hQoVAAAdOnRIMz0iIkJXtrJv3z7dclPr2bMnHB0ddetz9erVYWNjg3feeQcrV65MU4qgXZajoyN69OiRJmYAad4bzZs31/vpWBtzu3bt9MovtNO143bs2DFERERg4MCBeutCSkoK2rZti1OnTumVOWQk9XqnvdStWzfL++XEy++NBg0awN/fX/fe0cYRHh6OjRs3AgBSUlKwaNEidOjQIdcHdHt4eMDa2lp32bRpE4DcjV1W24EdO3ZAo9GgX79+esv08fFBtWrVdO9NLTc3t3RLv27fvo0+ffrAx8cHlpaWsLa2RtOmTQFkf9v9sn379qFixYq6cgStQYMGQUR0679Whw4d9Mp7MnrPGkpcXBy6d++OO3fuYOPGjbqDio2tUaNGadb9U6dOYciQIWnmfeONN9JdhiG2WxktOz3bt29PN+aXL++88062lwko5UodO3aEn58flixZovc/X19fLF68GD179kSjRo3Qp08fHDp0CDVq1MDEiRORlJSUrcf4+OOPcerUKfzxxx8YPHgw3nvvvXQPqtW6cuUKTpw4gb59+8LOzi5HzwdglxXKoZiYGDx+/BhVqlTRTevTpw/27t2LTz/9FK+99hpcXFyg0WjQvn17xMbGZrnMlJQUtG7dGvfv38enn36KKlWqwNHRESkpKahXr162lgEoH5D9+vWDhYUFChUqhBIlSugShMePHwNQ3qgvK1KkCAIDA7NcvoeHR5pptra22YrP1dUVBw8exPTp0/Hxxx8jMjISvr6+GDZsGD755JN0666B3I3Ny3Ha2toCgG7ex48fw8rKKs18Pj4+WT6P1IoVK6ZrNwcodaYajQaTJk3C7t270aZNGzx48AAAdLW8L9PWWmo0Guzduxeff/45Zs+ejXHjxsHd3R19+/bF9OnT4ezsnKPYAOi+PAUHB6NcuXLZvl9W46eV3rr0+PHjDNcx7f9Tc3d31/vbxsYm0+lxcXFwcnLSvYaFCxfWm0+j0cDHx0f3OKVKlcJff/2F2bNn491330VMTAxKliyJDz74AKNHj9bF5OPjk6aW2cvLC1ZWVgaJGYBuXXg58U8tIiIi3TrR1F5e74whvfdC6nEFgBo1aqBx48b44Ycf0LdvX+zYsQMhISF6x9ekR5v0pJcsHjhwAElJSThz5gxGjBihm56bsctqPX7w4AFERK87SGolS5bU+zu99frZs2do3Lgx7Ozs8OWXX6Js2bJwcHDAvXv30L1792xvu1/2+PHjdL/UZPQ+yu571hDi4+PRrVs3HDlyBDt27DD4l8HMuLq6ZnvdT+/1ymh6TrdbGS07PRUrVkyzEy89Oam7v3PnDpo3bw4rKyvs3bs3zbYnPdbW1ujVqxcmTpyImzdv6nYYZKZ48eK6z5H27dsDACZNmoSBAwem2fYCwNKlSwEondpygwk55cgff/yB5ORkXd/Tp0+fYseOHZgyZQomTpyomy8+Ph4RERHZWubly5dx4cIFrFixAgMHDtRNz+mBIpl9UGs32On1jL1//z48PT1z9Fi5UaVKFaxfvx4igosXL2LFihX4/PPPYW9vrzd2qRlqbFLz8PBAUlISHj9+rPdBFhYWlutlamn3TF24cAFt2rTRjetvv/2m26ufEX9/f90G7caNG/j1118xdepUJCQk4Mcff8xxLG3atMHHH3+MrVu35rqNZWbSOxjPw8Mjw3UMgMHWM+1r+PDhQ70PBhFBWFiY3hegxo0bo3HjxkhOTsbp06cxf/58jBkzBt7e3njrrbfg4eGBEydOQET0nlN4eDiSkpIMFrN2OfPnz9cdcP2yjJJDU0vvvRAWFpbmIK0PPvgAPXv2xNmzZ7FgwQKULVsWrVq1ynTZRYoUQaVKlRAYGIi4uDi9PWna1owvH8BrjLHz9PSERqPB4cOHdQlsai9PS29937dvH+7fv48DBw7o9ooDSHNgcU6Z6n2UU/Hx8ejatSv279+va5tqrjI6l4Yhtls5OU9HqVKlsvVLxZQpU7J1wPWdO3fQrFkziAgOHDiAYsWKZTsW7ReD3B50W6dOHfz444+4fft2moQ8ISEBq1evRq1atXLdYpUlK5Rtd+/exUcffQRXV1cMHz4cgPLGFJE0G+8lS5akOUFMRnsttG/ul5eR1Z6mnKhfvz7s7e3TNPb/999/dT/XGUJ29sxoNBpUq1YNc+fORaFChXD27NlM5029XK1XGZvmzZsDANasWaM3fe3atbleppa2I4q2I0GbNm1gZWWFW7duoXbt2ule0lO2bFl88sknqFKlit74ZPcXCQCoWbMm2rVrh6VLl6b5iVvr9OnTuHv3bg6eYeZatmypS1JSW7VqFRwcHDJMpnLzOADSrM+bNm1CTExMuuuzpaUl6tatq+t2oR3Xli1b4tmzZ9i6dWuamFM/1qtq2LAhChUqhKCgoAzXBe1edUPJ7Z7Sl98bx44d0yUCqXXr1g3FixfHuHHj8Ndff2HUqFHZSlYmT56MR48eYezYsdnae2iMsevYsSNEBP/991+6y0v9K2hGcrJ9yslr0bJlSwQFBaXZNq5atQoajUa3DTMl7Z7xffv2YdOmTWjTpo3JYzAWY263DFmycvfuXTRr1gzJycnYt29fljt5UktMTMSGDRvg6emZ8+4n/2///v2wsLBI8+sRAGzbtg2PHj1Kt3wou7iHnNJ1+fJlXU1heHg4Dh8+jOXLl8PS0hJbtmzRfTt0cXFBkyZN8PXXX8PT0xMBAQE4ePAgli5dikKFCukts3LlygCAxYsXw9nZGXZ2dihRogTKly+PUqVKYeLEiRARuLu7Y/v27dkqI8muQoUK4dNPP8XHH3+MAQMGoHfv3nj8+DGmTZsGOzs7TJkyxSCPk9FzPH78OBYuXIiuXbuiZMmSEBFs3rwZT548yXSPmjHGpnXr1mjSpAnGjx+PmJgY1K5dG0ePHsXq1atztJy7d+/qWovFxMTg+PHjmDlzJvz9/dG9e3cASputzz//HJMnT8bt27fRtm1buLm54cGDBzh58iQcHR0xbdo0XLx4Ee+99x569uyJMmXKwMbGBvv27cPFixf1fj3Q/sqwYcMGlCxZEnZ2dpkmDqtWrULbtm3Rrl07DB48GO3atYObmxtCQ0Oxfft2rFu3DmfOnEnT+jC3pkyZgh07dqB58+b47LPP4O7ujjVr1uCPP/7A7Nmz4erqapDHadWqFdq0aYMJEyYgKioKDRs2xMWLFzFlyhTUqFED/fv3BwD8+OOP2Ldvn+6sc3FxcbpWndqTew0YMAA//PADBg4ciJCQEFSpUgVHjhzBjBkz0L59+1ydBCw9Tk5OmD9/PgYOHIiIiAj06NEDXl5eePjwIS5cuICHDx9i0aJFBnksrVKlSsHe3h5r1qxBhQoV4OTkhCJFiuh+is/I6dOnMXToUPTs2RP37t3D5MmTUbRoUYwaNUpvPktLS7z77ruYMGECHB0ds33Cqt69e+PKlSuYPn06Lly4gEGDBqFMmTJISUnBvXv3dO9FbamWMcauYcOGeOedd/D222/j9OnTaNKkCRwdHREaGoojR46gSpUqGDlyZKbLaNCgAdzc3DBixAhMmTIF1tbWWLNmDS5cuJBmXu37dNasWWjXrh0sLS1RtWrVdL9IfPjhh1i1ahU6dOiAzz//HP7+/vjjjz+wcOFCjBw5Mk0N9Ks4ePAgHj58CABITk7GnTt38NtvvwEAmjZtqvus69GjB3bu3InJkyfDw8NDr62ii4sLKlasqPs7KChId5xQWFgYnj9/rltmxYoVdfMePHgQLVu2xGeffYbPPvssy1ifPHmSbjtHW1vbHJ387mXG3G5l54tddoSHh6N58+YIDQ3F0qVLER4ernfm8GLFiun2lo8dOxaJiYlo2LAhfHx8cO/ePcyfPx/nz5/X5TFan3/+OT7//HPs3btX9yvPO++8AxcXF9SpUwfe3t549OgRNm7ciA0bNuB///tfhuUq9vb2OT4WS0+ODwOlfE3bZQCpjiz28vKSpk2byowZM3RtClP7999/5Y033hA3NzdxdnaWtm3byuXLl9McOS+idF4oUaKEWFpa6nU/CAoKklatWomzs7O4ublJz5495e7duznq+pGdkwAsWbJEqlatKjY2NuLq6ipdunTRa70nknGXlfROytC0adM0XT/Se47Xrl2T3r17S6lSpcTe3l5cXV2lTp06smLFiixjzu7YaOPWtprU0r6mqTs/PHnyRAYPHiyFChUSBwcHadWqlVy7di3XXVbs7OykbNmyMmbMGL1uJFpbt26V5s2bi4uLi9ja2oq/v7/06NFD167twYMHMmjQIClfvrw4OjqKk5OTVK1aVebOnavXPSEkJERat24tzs7OutZeWYmNjZXvv/9e6tevLy4uLmJlZSVFihSR7t27yx9//JFmnF7uMKTtLJC6c05mJ+m4dOmSdOrUSVxdXcXGxkaqVauWpsuHdpkbN27Um55RDOm9trGxsTJhwgTx9/cXa2tr8fX1lZEjR+pa84konTS6desm/v7+YmtrKx4eHtK0aVPZtm2b3vIfP34sI0aMEF9fX7GyshJ/f3+ZNGmSri2dFgB599139aZl9P7L6DkePHhQOnToIO7u7mJtbS1FixaVDh06pJnvZdl5n6e3zVm3bp2UL19erK2ts1y/teO/Z88e6d+/vxQqVEjXnSmjk3yEhIQIoJzkJ6cOHTokvXr1kmLFiom1tbU4ODhIxYoVZeTIkXL69Ok082dn7HKyHRARWbZsmdStW1ccHR3F3t5eSpUqJQMGDNB7/KZNm0qlSpXSfQ7Hjh2T+vXri4ODgxQuXFiGDh0qZ8+eTdPdJj4+XoYOHSqFCxcWjUajF0t6r9udO3ekT58+utZ15cqVk6+//lqvPV5m60R2tmXa5/by9kx7Sf2ez2geAGk+A7SvQXqX1DFp3yPZiTOzbiVFixZN89gvv/7aZRhju2UK2sfOzrguXbpU6tSpI+7u7mJlZSVubm7Spk0b2b17d5rlascr9Wu9bNkyady4sXh6eoqVlZUUKlRImjZtKqtXr043trt374qFhYUMGDDglZ6jRiQbv5cRERFRGvPnz8cHH3yAy5cvo1KlSmqHQ0R5FBNyIiKiHDp37hyCg4MxfPhwNGzYME0NPhFRTjAhJyIiyqGAgACEhYWhcePGWL16dY7bhhIRpcaEnIiIiIhIRWx7SERERESkIibkREREREQqYkJOqpo5cyY0Gg3GjBmjmyYimDp1KooUKQJ7e3s0a9YMV65cUS9IIiIiIiPiiYFINadOncLixYt1p1vXmj17NubMmYMVK1agbNmy+PLLL9GqVStcv35dd6KMrKSkpOD+/ftwdnbO0Wl+iYiISD0igujoaBQpUiTXp7nPi5iQkyqePXuGvn374ueff8aXX36pmy4imDdvHiZPnqw72+PKlSvh7e2NtWvXYvjw4dla/v379+Hn52eU2ImIiMi47t27pzv7ZkHAhJxU8e6776JDhw54/fXX9RLy4OBghIWFoXXr1rpptra2aNq0KY4dO5ZhQh4fH4/4+Hjd39rmQcHBwdneq55diYmJ2L9/P5o3bw5ra2uDLpte4DibBsfZNDjOpsFxNh1jjXV0dDRKlChh8M9uc8eEnExu/fr1OHv2LE6dOpXmf2FhYQAAb29vvene3t64c+dOhsucOXMmpk2blmb68ePH4eDg8IoRp+Xg4IATJ04YfLmkj+NsGhxn0+A4mwbH2XSMMdbPnz8HgAJXbsqEnEzq3r17GD16NPbs2QM7O7sM53v5jSgimb45J02ahLFjx+r+joqKgp+fH1q3bg0XF5dXDzyVxMREBAYGolWrVtwDY0QcZ9PgOJsGx9k0OM6mY6yxjoqKMtiy8hIm5GRSZ86cQXh4OGrVqqWblpycjEOHDmHBggW4fv06AGVPua+vr26e8PDwNHvNU7O1tYWtrW2a6dbW1kbbKBtz2fQCx9k0OM6mwXE2DY6z6Rh6rAvq61ZwDl8ls9CyZUtcunQJ58+f111q166Nvn374vz58yhZsiR8fHwQGBiou09CQgIOHjyIBg0aqBg5ERERkXFwDzmZlLOzMypXrqw3zdHRER4eHrrpY8aMwYwZM1CmTBmUKVMGM2bMgIODA/r06aNGyERERERGxYSczM748eMRGxuLUaNGITIyEnXr1sWePXsK3BHXREREVDAwISfVHThwQO9vjUaDqVOnYurUqarEQ0RERGRKrCEnIiIiIlIRE3IiIiIiIhUxISciIiIiUhETciIiIiIiFTEhJyIiIiJSERNyIiIiIiIVMSEnIiIiMoGUFODJE7WjIHPEhJyIiIjISEJCgKVLgd69AV9fwM0NqFED+Ppr4N49taMjc8ETAxEREREZ2JUrQL9+wPnzaf93/rxyGT8eaNIE+OAD4I03TBwgmRXuISciIiIyoK1bgXr1lKTb0hJo0AD49FPg4EHg/n3gxx+VRBwADh0CevRQplHBxYSciIiIyABSUoApU4Bu3YBnz4DmzZUE/OhR4PPPlSTc1xcYPlxJzu/eBUaNUu47ciSwcqW68ZN6mJATERERvaKoKCUR//xz5e/Ro4HduwEvr4zv4+cHLFiglKwAwODBwK+/Gj9WMj+sISciIiJ6BYmJQMeOwOHDgK0t8NNPwMCB2buvRgPMnQs8fw4sWQL07QvY2wOdOhk3ZjIv3ENORERE9ArGj1eScRcXpSY8u8m4loWFUkPety+QlKTUlB86ZJxYyTwxISciIiLKpfXrgXnzlNurVgF16uRuOZaWwIoVQPfuQEKCUmeelGSoKMncMSEnIiIiyoUrV4AhQ5TbkyYBXbq82vKsrIBlywAPD+DaNaV/ORUMTMiJiIiIcujpU2Vv9vPnwOuvA198YZjluroCn32m3J4yBYiONsxyybwxISciIiLKARHg7beBGzeUTilr1yolJ4YyYgRQujTw4AHwzTeGWy6ZLybkRERERDmwYgWwZQtgYwNs2gQULmzY5dvYADNnKre/+UbpZU75GxNyIiIiomx68gSYOFG5/eWXwGuvGedx3ngDqF9fKYmZMsU4j0Hmgwk5ERERUTZNnQqEhwPlyysn/zEWjQb4+mvl9rJlygGklH8xISciIiLKhsuXlTNrAsD33yulJcbUsKFy9s+UFKXXOeVfTMiJiIiIsiACvP8+kJysdFdp1co0j/vVV0o7xD//BM6fN81jkukxISciIiLKwsaNwIEDgJ0d8O23pnvcsmWBrl2V2ytXmu5xybSYkBMRERFlIiYGGDdOuT1pEhAQYNrHHzRIuV6zBkhMNO1jk2kwISciIiLKxIwZwL//Kon4//5n+sdv0wbw9gYePgR27jT945PxMSEnIiIiykB4ODB3rnJ77lzA3t70MVhZAf36KbdXrDD945PxMSEnIiIiysC33wKxsUCdOkCXLurFMXCgcr1jB/DokXpxkHEwISciIiJKx6NHwA8/KLc//VTpDa6WKlWAmjWVGvJ169SLg4yDCTkRERFROubNUw7orFED6NBB7WheHNzJspX8hwk5ERER0UsiI4H585Xbau8d1+rdG7C2Bs6eBS5eVDsaMiQm5EREREQv+f57ICpKKRVRs3Y8NU9PoFMn5TZ7kucvTMiJiIiIUomKUspVAOCTTwALM8qWtAd3sid5/mJGqxgRERGR+hYsAJ48ASpUAN54Q+1o9LVrBxQuDDx4AOzerXY0ZChMyImIiIj+37NnwJw5yu3JkwFLS3XjeZm19Yue5L/8om4sZDhMyImIiIj+35IlwOPHQJkyQK9eakeTvh49lOs9e4DkZHVjIcNgQk5EREQEJbnVdlYZO1Y5Q6Y5qlMHcHVVOsGcOaN2NGQITMiJiIiIAOzcCdy+DRQqBPTvr3Y0GbOyAlq2VG6zjjx/YEJOREREBKXVIQAMHQo4OqobS1batFGumZDnD0zIiYiIqMC7ehUIDFRaHL77rtrRZK11a+X677+Bp0/VjYVeHRNyIiIiKvAWLFCuO3cGAgJUDSVbAgKAsmWVuvd9+9SOhl4VE3IiIiIq0J48eXHmy/ffVzWUHGHZSv7BhJyIiIgKtOXLgZgYoFIloHlztaPJvtQJuYi6sdCrYUJOREREBVZy8otylQ8+ADQadePJiaZNlRMFhYQA//yjdjT0KpiQExERUYH1559Kq0M3N6BvX7WjyRknJ6BRI+U2y1byNibkREREVGDlpVaH6dGWrezZo24c9GqYkBMREVGBdOsW8NdfSpnKqFFqR5M72vaH+/cDCQnqxkK5x4SciIiICqRly5Tr1q3zRqvD9FSrBnh5Ac+eAceOqR0N5RYTciIiIipwkpKU7iqAUq6SV1lYvNhLzrKVvIsJORERERU4u3YBoaGAp6dyMqC8TJuQ88DOvIsJORERERU4S5Yo1wMGADY26sbyqrQJ+dmzQHi4urFQ7jAhJyIiogIlLAzYsUO5PWSIurEYgrc3ULWqcvvIEXVjodxhQk5EREQFysqVygmB6tcHKlZUOxrDqFdPuT5xQt04KHeYkBMREVGBIQIsXarczssHc76sbl3lmgl53sSEnIiIiAqMw4eBmzeVs1y++aba0RiONiE/fVrZ+095CxNyIiIiKjC0e8ffektJyvOL8uWV5xMTA1y5onY0lFNMyImIiKhAePoU2LhRuZ2fylUAwNISeO015fbJk+rGQjnHhJyIiIgKhHXrgNhYoFIloE4dtaMxPNaR511MyImIiKhAWLVKuR48GNBo1I3FGJiQ511MyImIiCjfu3ULOH5cOdV8795qR2Mc2oT8yhXg2TN1Y6GcYUJORERE+d4vvyjXrVoBvr7qxmIsvr6Anx+QkqJ0W6G8gwk5mdyiRYtQtWpVuLi4wMXFBfXr18fOnTt1/xcRTJ06FUWKFIG9vT2aNWuGKzxknIiIckkEWL1aud2vn7qxGBvLVvImJuRkcsWKFcNXX32F06dP4/Tp02jRogW6dOmiS7pnz56NOXPmYMGCBTh16hR8fHzQqlUrREdHqxw5ERHlRX//rZSsODoC3bqpHY1xaQ9WZUKetzAhJ5Pr1KkT2rdvj7Jly6Js2bKYPn06nJyc8Pfff0NEMG/ePEyePBndu3dH5cqVsXLlSjx//hxr165VO3QiIsqDtOUq3bsrSXl+xj3keRMTclJVcnIy1q9fj5iYGNSvXx/BwcEICwtD69atdfPY2tqiadOmOHbsmIqREhFRXpSQAKxfr9zO7+UqAFCrltKT/P594L//1I6GsstK7QCoYLp06RLq16+PuLg4ODk5YcuWLahYsaIu6fb29tab39vbG3fu3MlwefHx8YiPj9f9HRUVBQBITExEYmKiQWPXLs/QyyV9HGfT4DibBsfZNNIb5+3bNYiIsIKvr6BJkyTk95fAxgaoVMkKFy9qcPRoErp1E6M8jrHW6YL6HmFCTqooV64czp8/jydPnmDTpk0YOHAgDh48qPu/5qUGsSKSZlpqM2fOxLRp09JM37NnDxwcHAwXeCqBgYFGWS7p4zibBsfZNDjOppF6nOfMqQ2gKOrUuYXduwtGgwAfn2q4eDEA69cHw9Y2yKiPZeh1+vnz5wZdXl6hERHjfHUiyoHXX38dpUqVwoQJE1CqVCmcPXsWNWrU0P2/S5cuKFSoEFauXJnu/dPbQ+7n54dHjx7BxcXFoLEmJiYiMDAQrVq1grW1tUGXTS9wnE2D42waHGfTeHmcnzwB/PysEB+vwcmTiaheXe0ITWPFCg3eeccKTZqk4K+/ko3yGMZap6OiouDp6YmnT58a/PPbnHEPOZkFEUF8fDxKlCgBHx8fBAYG6hLyhIQEHDx4ELNmzcrw/ra2trC1tU0z3dra2mgffsZcNr3AcTYNjrNpcJxNQzvOW7cC8fFA5cpA7drW+fLsnOmpX1+5PnPGAhYWFrC0NN5jGXqdLqjvDybkZHIff/wx2rVrBz8/P0RHR2P9+vU4cOAAdu3aBY1GgzFjxmDGjBkoU6YMypQpgxkzZsDBwQF9+vRRO3QiIspDtL3H+/dHgUnGAaBCBcDJSTlb55UrQNWqakdEWWFCTib34MED9O/fH6GhoXB1dUXVqlWxa9cutGrVCgAwfvx4xMbGYtSoUYiMjETdunWxZ88eODs7qxw5ERHlFXfvAocPK4l4QdufY2kJvPYasH+/0v6QCbn5Y0JOJrd06dJM/6/RaDB16lRMnTrVNAEREVG+s2GDct20KVCsmLqxqKFuXSUhP3kSGDZM7WgoK+xDTkRERPmOtvf4W2+pG4datGfsPHVK3Tgoe5iQExERUb5y4wZw9qxSuvHGG2pHo45q1ZTrq1eBpCR1Y6GsMSEnIiKifGXjRiW9adUK8PRUORiVBAQADg7KmUr/+UftaCgrTMiJiIgo3xABNmxQ0puCWq4CABYWQKVKyu3Ll9WNhbLGhJyIiIjyjTt3nHHtmgY2NkDXrmpHo67KlZVrJuTmjwk5ERER5RtHjigtVdq3B1xdVQ5GZVWqKNdMyM0fE3IiIiLKF0SAw4eLAijY5Spa3EOedzAhJyIionzhzBkNHjxwhIODoGNHtaNRnzYhv3kTiItTNxbKHBNyIiIiyhd+/VUDAOjYUeDoqHIwZsDHB3B3B1JSgGvX1I6GMsOEnIiIiPK8lJQX7Q7ffDNF5WjMg0bDspW8ggk5ERER5XlHjwL//aeBg0Mi2rQRtcMxG0zI8wYm5ERERJTnrV+vXNevfx+2turGYk60CfmlS+rGQZljQk5ERER5WnIysGmTcrthw/vqBmNmuIc8b2BCTkRERHna4cPAgweAm5ugatWHaodjVrRn67x7F4iKUjcWyhgTciIiIsrTNm5Urjt3FlhZsX48NXd3oEgR5faVK+rGQhljQk5ERER5VupylTfeYHeV9LBsxfwxISciIqI868gRpVylUCGgRQvuHU9PlSrKNRNy88WEnIiIiPIsbblK166AjY2qoZgt7iE3f0zIiYiIKE9KXa7Ss6e6sZgzJuTmjwk5ERER5UlHjgBhYUq5yuuvqx2N+apQQTlrZ3i4ciHzw4SciIiI8iRtuUqXLixXyYyjI1CypHKbnVbMExNyIiIiynNSl6u8+aa6seQFLFsxb0zIiYiIKM85epTlKjnBhNy8MSEnIiKiPIflKjmjTcgvXVI3DkofE3IiIiLKU1JS2F0lp1LvIRe2azc7TMiJiIgoTzl2DAgNBVxdWa6SXWXLAlZWQHQ0cO+e2tHQy5iQExERUZ7y22/KdefOgK2turHkFTY2QLlyym3WkZsfJuRERESUZ4gAmzcrt994Q91Y8poKFZTrGzfUjYPSYkJOREREecapU0rJhaMj0Lq12tHkLWXKKNc3b6obB6XFhJyIiIjyDG25SseOgL29urHkNaVLK9f//KNuHJQWE3IiIiLKE0RedFdhuUrOMSE3X0zIiYiIKE+4cAG4fVvZM96undrR5D3ahDwkBEhIUDUUegkTciIiIsoTtOUqbdsCTk7qxpIX+foCDg5KH/eQELWjodSYkBMREVGewHKVV6PRsGzFXDEhJyIiIrMXFARcu6b00+7YUe1o8i4m5OaJCTkRERGZPW25SqtWyhk6KXe0CTlbH5oXJuRERERk9liuYhjaXuTcQ25emJATERGRWfvnH+DiRcDKCujSRe1o8jaWrJgnJuRERERk1rR7x5s3B9zd1Y0lr0vd+jAxUdVQKBUm5ERERGTWWK5iOEWKKH3ck5KAO3fUjoa0mJATERGR2bp7Fzh1SmnZ17Wr2tHkfRYWQKlSym2WrZgPJuRERERktjZvVq4bNwa8vdWNJb9gHbn5YUJOREREZkubkHfvrm4c+QkTcvPDhJyIiIjMUlgYcOSIcpsJueFoWx+yF7n5YEJOREREZun33wER4LXXAD8/taPJP7iH3PwwISciIiKzxO4qxqFNyIODlW4rpD4m5ERERGR2IiKA/fuV2yxXMaxixQBbW6UP+d27akdDABNyIiIiMkPbtyt7b6tUeVHzTIbB1ofmhwk5ERERmR1tdxWWqxgH68jNCxNyIiIiMivR0cDu3cptlqsYBxNy88KEnIiIiMzKzp1AfLxSqlK5strR5E9sfWhemJATERGRWdF2V+neHdBo1I0lv+IecvPChJyIiIjMRmws8Mcfym3WjxuPNiG/fRtITlY3FmJCTkRERGYkMBCIiVFOBFS7ttrR5F9+foCNDZCQANy7p3Y0xISciIiIzAbLVUzD0hIoWVK5zbIV9TEhJyIiIrOQkABs26bcZrmK8bGO3HwwISciIiKzcOAA8OQJ4O0NNGigdjT5HxNy88GEnIiIiMyCtlyla1elpIKMi60PzQcTciIiIlJdcjKwdatym+UqpqHdQ86EXH1MyImIiEh1R48C4eGAmxvQrJna0RQM2oM6Q0IAEVVDKfCYkBMREZHqtOUqnTsD1tbqxlJQ+Pkp17GxwOPH6sZS0DEhJyIiIlWlpACbNyu3Wa5iOra2gI+PcvvOHXVjKeiYkJPJzZw5E6+99hqcnZ3h5eWFrl274vr163rziAimTp2KIkWKwN7eHs2aNcOVK1dUipiIiIzp1Cng338BJyegVSu1oylY/P2V67t31Y2joGNCTiZ38OBBvPvuu/j7778RGBiIpKQktG7dGjExMbp5Zs+ejTlz5mDBggU4deoUfHx80KpVK0RHR6sYORERGYN273iHDoCdnbqxFDTFiyvX3EOuLiu1A6CCZ9euXXp/L1++HF5eXjhz5gyaNGkCEcG8efMwefJkdO/eHQCwcuVKeHt7Y+3atRg+fLgaYRMRkRGIvKgfZ7mK6WkTcu4hVxcTclLd06dPAQDu7u4AgODgYISFhaF169a6eWxtbdG0aVMcO3Ys3YQ8Pj4e8fHxur+joqIAAImJiUhMTDRovNrlGXq5pI/jbBocZ9PgOGfswgXg1i1r2NkJXn89Ca8yRBznnCtWzAKAJUJCUpCYmJzt+xlrrAvqa8eEnFQlIhg7diwaNWqEypUrAwDCwsIAAN7e3nrzent7404Gv6nNnDkT06ZNSzN9z549cHBwMHDUisDAQKMsl/RxnE2D42waHOe01q0rB6A8qlYNw6FDJw2yTI5z9oWH+wCoi0uXnuLPPw/l+P6GHuvnz58bdHl5BRNyUtV7772Hixcv4siRI2n+p9Fo9P4WkTTTtCZNmoSxY8fq/o6KioKfnx9at24NFxcXg8acmJiIwMBAtGrVCtbszWU0HGfT4DibBsc5Yx9/rKQiI0YURvv27V9pWRznnCtSBJg5E4iKKpSj8TfWWGt/4S5omJCTat5//31s27YNhw4dQrFixXTTff6/B1NYWBh8fX1108PDw9PsNdeytbWFra1tmunW1tZG2ygbc9n0AsfZNDjOpsFx1nftGhAUpPQd79bNymD9xznO2VeqlHIdHq5BUpI17O1zdn9Dj3VBfd3YZYVMTkTw3nvvYfPmzdi3bx9KlCih9/8SJUrAx8dH72ewhIQEHDx4EA0aNDB1uEREZCTagzlffx0oVEjVUAosNzel3SQA3LunbiwFGRNyMrl3330Xv/zyC9auXQtnZ2eEhYUhLCwMsbGxAJRSlTFjxmDGjBnYsmULLl++jEGDBsHBwQF9+vRROXoiIjKU335Trnv0UDeOgkyjYacVc8CSFTK5RYsWAQCaNWumN3358uUYNGgQAGD8+PGIjY3FqFGjEBkZibp162LPnj1wdnY2cbRERGQMt24B588DlpZAly5qR1OwFS+ulA6xF7l6mJCTyYlIlvNoNBpMnToVU6dONX5ARERkctpylebNAQ8PdWMp6Hi2TvWxZIWIiIhMTluuwpMBqY9n61QfE3IiIiIyqTt3gFOnlPrlbt3Ujoa4h1x9TMiJiIjIpDZvVq6bNAEy6GZLJsQ95OpjQk5EREQmxXIV86JNyO/dA1JS1I2loGJCTkRERCbz33/AsWPK7e7d1Y2FFEWLAhYWQGIi8OCB2tEUTEzIiYiIyGS2bFGu69dXEkFSn5XVi9eCZSvqYEJOREREJsOTAZknHtiprhz3IU9OTkZiYqIxYiEymISEBPj7+yMhIQFxcXEGXXZiYiKsrKwQFxeH5ORkgy6bXuA4mwbH2TQ4zopHj5Q9sP7+ysmADLx55ji/gmrVlBryhw+z97rkdqytra1haWn5CpHmTxrJzllaoJzMJSwsDE+ePDFySESvLiUlBffu3YOfnx8sLAz7Q5CIIDY2Fvb29tBoNAZdNr3AcTYNjrNpcJwV0dFARARgYwP4+hp++Rzn3IuMBKKiAGdnwN096/lfZawLFSoEHx+fdO8XFRUFV1dXPH36FC4uLjlabl6W7T3k2mTcy8sLDg4OXNHJrCUnJyM2NhYBAQEG/yaekpKCZ8+ewcnJyeDJPr3AcTYNjrNpcJwVwcHKwYPe3kDhwoZfPsc591xcgNBQJSHXlq9kJjdjLSJ4/vw5wsPDAQC+xvhWlkdlKyFPTk7WJeMePL8t5QHan8/s7OyMkpAnJCTAzs6OG3wj4jibBsfZNDjOSgePmBjltpcXYGtr+MfgOOeek5NynZQE2NllPX9ux9re3h4AEB4eDi8vL5av/L9sjaC2ZtzBwcGowRAREVH+FBmpXDs4GCcZp1djY6NcJyQY/7G0+SSPSXwhR18fWaZCREREuaFNyLNTn0ymp03Ik5OVizExn0yLv+cQERGRUSUmKgd0AoCbm7qxUPosLZULYJq95KSPCXketGLFChQqVEjtMIiIiLJF26CN5SrmzZRlK6QvXyfkgwYNgkajgUajgbW1Nby9vdGqVSssW7YMKSkpOVqWIZPgZs2a6eKytbVF2bJlMWPGjGz38ezVqxdu3LiR48ccM2ZMLqIlIiJ6NRERyjXLVcyb9stSfLy6cRREJk3Ik1MEx289xu/n/8PxW4+RnJKtFuivpG3btggNDUVISAh27tyJ5s2bY/To0ejYsSOSkpKM/vgZGTZsGEJDQ3H9+nV88MEH+OSTT/DNN99k67729vbw8vIycoRERESvjuUqeQf3kKvHZAn5rsuhaDRrH3r//DdGrz+P3j//jUaz9mHX5VCjPq6trS18fHxQtGhR1KxZEx9//DF+//137Ny5EytWrNDNN2fOHFSpUgWOjo7w8/PDqFGj8OzZMwDAgQMH8Pbbb+Pp06e6PdtTp04FAPzyyy+oXbs2nJ2d4ePjgz59+uj6a2bGwcEBPj4+CAgIwHvvvYeWLVti69atAIDIyEgMGDAAbm5ucHBwQLt27XDz5k3dfV/eWz916lRUr14dq1evRkBAAFxdXfHWW28h+v+3gIMGDcLBgwfx3Xff6eIPCQlBZGQk+vbti8KFC8Pe3h5lypTB8uXLX23AiYiIUmG5St7BhFw9JknId10OxchfziL0qf65WMOexmHkL2eNnpS/rEWLFqhWrRo2b96sm2ZhYYHvv/8ely9fxsqVK7Fv3z6MHz8eANCgQQPMmzcPLi4uCA0NRWhoKD766CMAyinav/jiC1y4cAFbt25FcHAwBg0alOOY7O3tde1/Bg0ahNOnT2Pbtm04fvw4RATt27fPtD3QrVu3sHXrVuzYsQM7duzAwYMH8dVXXwEAvvvuO9SvX1+3Vz40NBR+fn749NNPERQUhJ07d+Lq1atYtGgRPD09cxw7ERFRRliukncwIVdPts/UmVvJKYJp24OQXnGKANAAmLY9CK0q+sDSwnRtcMqXL4+LFy/q/k5dX12iRAl88cUXGDlyJBYuXAgbGxu4urpCo9HAx8dHbzmDBw/W3S5ZsiS+//571KlTR3f2qqykpKRgz5492L17N8aMGYObN29i27ZtOHr0KBo0aAAAWLNmDfz8/LB161b07Nkzw+WsWLECzs7OAID+/ftj7969mD59OlxdXWFjY6PbK6919+5d1KhRA7Vr1wYABAQEZBkvERFRdrFcJW9hQq4eo+8hPxkckWbPeGoCIPRpHE4GRxg7FP3HFdHrg7l//360atUKRYsWhbOzMwYMGIDHjx8jRntasQycO3cOXbp0gb+/P5ydndGsWTMASrKbmYULF8LJyQl2dnbo3Lkz+vXrhylTpuDq1auwsrJC3bp1dfN6eHigXLlyuHr1aobLCwgI0CXjgHI62qxKZ0aOHIn169ejevXqGD9+PI4dO5bp/ERERDnBcpW8JXVCLsY/zI9SMXpCHh6dcTKem/kM5erVqyhRogQA4M6dO2jfvj0qV66MTZs24cyZM/jhhx8AZH4WqZiYGLRu3RpOTk745ZdfcOrUKWzZsgWAUsqSmb59++L8+fO4desWYmNjsXTpUjg4OEAyeAe8/AXiZdbW1np/azSaLDvJtGvXDnfu3MGYMWNw//59tGzZUleKQ0RE9KpYrpK3WFsD2lSDe8lNy+gJuZeznUHnM4R9+/bh0qVLeOONNwAAp0+fRlJSEr799lvUq1cPZcuWxf379/XuY2Njk6Yt4bVr1/Do0SN89dVXaNy4McqXL5+tAzoBwNXVFaVLl4afnx8stZ34AVSsWBFJSUk4ceKEbtrjx49x48YNVKhQIbdPOd34AaBw4cIYNGgQfvnlF8ybNw+LFy/O9WMQERFpsVwl79FoWLaiFqMn5HVKuMPX1Q4Z7dvVAPB1tUOdEsb5+hwfH4+wsDD8999/OHv2LGbMmIEuXbqgY8eOGDBgAACgVKlSSEpKwvz583H79m2sXr0aP/74o95yAgIC8OzZM+zduxePHj3C8+fPUbx4cdjY2Ojut23bNnzxxRevFG+ZMmXQpUsXDBs2DEeOHMGFCxfQr18/FC1aFF26dMn1cgMCAnDixAmEhITg0aNHSElJwWeffYbff/8d//zzD65cuYIdO3a8UtJPRESkFRmpXDs6slwlL2FCrg6jJ+SWFhpM6VQRANIk5dq/p3SqaLQDOnft2gVfX18EBASgbdu22L9/P77//nv8/vvvuj3T1atXx5w5czBr1ixUrlwZa9aswcyZM/WW06BBA4wYMQK9evVC4cKFMXv2bBQuXBgrVqzAxo0bUbFiRXz11VfZ7iWemeXLl6NWrVro2LEj6tevDxHBn3/+maYsJSc++ugjWFpaomLFiihcuDDu3r0LGxsbTJo0CVWrVkWTJk1gaWmJ9evXv3L8RERELFfJm5iQq0MjGRUtpxIXF4fg4GCUKFECdna5Ky3ZdTkU07YH6R3g6etqhymdKqJtZd9cLZMoI8nJyTh37hxq1KihVxJkCCkpKYiKioKLiwssLPL1yW5VxXE2DY6zaRS0cU5IALSNzKpWfZHkGVtBG2dj+PdfICwM8PICihfPeL5XGevM8sqoqCi4urri6dOncHFxyc1TyJOM3vZQq21lX7Sq6IOTwREIj46Dl7NSpmLKVodERERkfNq9405OpkvGyTC0r1cmPS3ICEyWkANK+Ur9Uh6mfEgiIiIyMW39OMtV8h5tdSxLVkyLv+cUYMHBwYjWHgJPRERkAPHxgPYUHuyukvdoE3LuITctk+4hJ/OSnJyMGzduwMbGBp6envDw8IANf1skIqJXoC1XcXF5kdxR3pE6IRd50ZecjIsJeQFWunRpJCUl4fHjx3j8+DHu378PZ2dneHp6olChQjwghoiIckybkHPveN6kTchFgKQkfqkyFSbkBZyVlRW8vb3h7e2N58+f49GjRwgODoalpSU8PDxQuHDhXHfWISKigiU2VrloNEzI8yoLC8DKSknGExOZkJsKd4ESACAhIQFPnz5FVFQUNBoNXF1dERsbiytXruDBgwdqh0dERHmA9mBOFxclqaO8iXXkpse3SwGWkpKCp0+f4tGjR4iKioK9vT28vLzg4eGh690dERGBO3fuwNvbW+VoiYjInInwZED5hY2N8ksHE3LTYUJegF28eBEiAnd3d1SoUAEODg5p5nFxcTH4iXWIiCj/iY0F4uKUcpVChdSOhl4FWx+aHktWzExAQADmzZtnksfy8/NDtWrV4O/vn24yDig15lWrVjVJPGoJCQmBRqPB+fPn1Q6FKE/bsmULrKysULZsWYSHh6sdTp5z8+ZNeHt7w8HBAUePHlU7nBzT7h13dQXU2I8TGxuLJk2awM3NzWSfo/mVNiGPj09Bz549odFoMHr0aHWDyufydUI+aNAgaDQa3cXDwwNt27bFRe35fA1g6tSpqF69erbmjYqKwuTJk1G+fHnY2dnBx8cHr7/+OjZv3gwRMVhM2eXh4VGgOqmkXhe0l0aNGsHPzw+hoaGoXLkyAODAgQPQaDR48uSJugHnkIigXbt20Gg02Lp1a5bzL1y4UHfa4lq1auHw4cNpljd16lQUKVIE9vb2aNasGa5cuWKk6DM3b948lCtXDvb29vDz88OHH36IuLi4DOePi4vDoEGDUKVKFVhZWaFr167pzvfDDz+gQoUKsLe3R7ly5bBq1SojPYPc035hTO+ycePGbC1j5syZ0Gg0GDNmjN50EcG0adNQoUIFODo6vtJrvH//fvTp0wdTpkyBl5cX2rZti6ioqDTPZciQIShRogTs7e1RqlQpTJkyBQlG3g0XHR2NMWPGwN/fH/b29mjQoAFOnTqV5f2ys35s2rQJFStWhK2tLSpWrIgtW7bkKsb79++jdevWaNSoEYYMGYKOHTvi0qVLaeabOnUqypcvD0dHR7i5ueH111/HiRMncvWY2bV582a0atUKhQsXhouLC+rXr4/du3frzZO6XMUj1fn/VqxYgapVq+o+89577710H+Off/6Bs7MzCuVy13pSUhJ69OiBR48eYdasWZg0aVKW7+f169dDo9FkuH0wpuxuo9Lzxx9/oG7durC3t4enpye6d++u9//Ro0ejVq1asLW1zXZ+8jJtQj5p0kgcOXIEP/30E5YtW4Yvvvgizbzaz8yXL9euXcvVYxdYkg2xsbESFBQksbGx2ZndbAwcOFDatm0roaGhEhoaKufOnZMOHTqIn5+fwR5jypQpUq1atSzni4yMlEqVKkmxYsVkxYoVcuXKFbl+/bosXrxYSpUqJZGRkSIi4u/vL3Pnzs1RDAkJCTkPPJ9LSkqSU6dOSVJSkm4aAFm+fLlufQgNDZXHjx+nue/+/fsFgO41eVlycrJERkZKcnKyscLPlTlz5ki7du0EgGzZsiXTedevXy/W1tby888/S1BQkIwePVocHR3lzp07unm++uorcXZ2lk2bNsmlS5ekV69e4uvrK1FRUdmOaeDAgTJlypRcPR/tOK9atUpsbW1lzZo1EhwcLLt37xZfX18ZM2ZMhvd99uyZjBgxQhYvXixt2rSRLl26pJln4cKF4uzsLOvXr5dbt27JunXrxMnJSbZt25areDMCQIKDg3N9/6SkJL11NjQ0VKZNmyaOjo4SHR2d5f1PnjwpAQEBUrVqVRk9erTe/7Sv8apVq+TChQu5eo1FRE6fPi2urq6ycOFCEVHGv2XLltK0aVO9z42dO3fKoEGDZPfu3XLr1i35/fffxcvLS8aNG5ejx/P395f9+/dne/4333xTKlasKAcPHpSbN2/KlClTxMXFRf79998M75Od9ePYsWNiaWkpM2bMkKtXr8qMGTPEyspK/v777zTLy2y7ERERIZUqVZJ+/frptlmTJk0SX19fuXXrlt68a9askcDAQLl165ZcvnxZhgwZIi4uLhIeHp7t8cjp+3L06NEya9YsOXnypNy4cUMmTZok1tbWcvbsWd08UVEip06JnD0ron2K3377rRQpUkTWrFkj//zzj1y+fDnd91dCQoLUrl1b2rVrJ66urtmOSyslJUX69u0r1apVk9DQUImMjJQtW7aIo6Njhu/nkJAQKVq0qDRu3Djd7UNmli9fLk2bNs1xnKllZxuVnt9++03c3Nxk0aJFcv36dbl27Zps3LhRb573339fFixYIP37989WfpKeyEiRgQMniq9vcblx44aIiBw/flzc3Nx073PtOr13714BINevX9fbTqX+/H1ZZnnl06dPBYA8ffo0V7HnVfk+IX95JT906JAA0Nt4/fvvv/Lmm29KoUKFxN3dXTp37qz3Abp//3557bXXxMHBQVxdXaVBgwYSEhIiy5cvFwB6l+XLl6cby8iRI8XR0VH++++/NP+Ljo6WxMREEVE+aKZPny5vv/22ODk5iZ+fn/z000+6eYODgwWAbNiwQZo2bSq2traybNkySU5OlmnTpknRokXFxsZGqlWrJjt37kz3fo0aNRI7OzupXbu2XL9+XU6ePCm1atUSR0dHadOmjd7YZLXc+Ph4effdd8XHx0dsbW3F399fZsyYofv/nTt3pHPnzuLo6CjOzs7Ss2dPCQsL0/1f+4Vm6dKl4ufnJ46OjjJixAhJSkqSWbNmibe3txQuXFi+/PJLvTF78uSJDBs2TAoXLizOzs7SvHlzOX/+vO7/GSXk6SWq2rE5d+6c7nbqy8CBA/Xmz+iDdeXKleLu7i5xcXF607t37y79+/dP87iGdP78eSlWrJiEhoZmKyGvU6eOjBgxQm9a+fLlZeLEiSKifMD5+PjIV199pft/XFycuLq6yo8//pjtuAyRkI8aNUpatGih97+xY8dKo0aNsh1Deh929evXl48++khv2ujRo6Vhw4Yiomz3KlasKMOGDdP9//bt2+Li4iKLFy/O9vN41YQ8PdWrV5fBgwdnOV90dLSUKVNGAgMDpWnTpnoJufY1njlzpm59fvk13r9/v1hbW8uhQ4d09/vmm2/Ew8ND7t+/LyIi165dEx8fH1m5cqXeY8fFxUmnTp2kc+fOuu1bembPni0lSpTIydPPUUL+/PlzsbS0lB07duhNr1atmkyePDnD+2W1fogoiX7btm315mnTpo289dZbIiISHh4u3t7eMn36dN36fOzYMbG2tpbdu3eLiEhMTIzUq1dPhg8fnmab8uWXX0qpUqUkNDQ0wzi1yctff/2VySjoe5X3pVbFihVl2rRpur+Dg5WEXLuqR0REiL29fbbiGj9+vPTr10+WL1+ul5CnpKRIy5YtpU2bNpKSkiIiys4tPz8/+fjjj3Xzvf/++1KnTh2JiIjQ2z7v2bNHPDw85ODBg3qPl5SUJA0bNpQlS5ZkuH3IjCES8tSyG0NiYqIULVpUlixZkq3lZrTD8O2335YqVaroPqsSEhKkZs2a0qdPH908X301R/z8SsuuXXf07nvu3Dnx9vaWdevWpUnIM9qJlR4m5GnlOiFPSRF59sz0l/9/T2bLyyt5dHS0DB8+XEqXLq3b8MXExEiZMmVk8ODBcvHiRQkKCpI+ffpIuXLlJD4+XhITE8XV1VU++ugj+eeffyQoKEhWrFghd+7ckefPn8u4ceOkUqVKum+Ez58/TxNHcnKyuLm5yTvvvJNlzP7+/uLu7i4//PCD3Lx5U2bOnCkWFhZy9epVEXmRPAYEBMimTZvk9u3b8t9//8mcOXPExcVF1q1bJ9euXZPx48eLtbW17put9n7ly5eXXbt2SVBQkNSrV09q1qwpzZo1kyNHjsjZs2eldOnSeolaVsv9+uuvxc/PTw4dOiQhISFy+PBhWbt27f+vIylSo0YNadSokZw+fVr+/vtvqVmzpt6GbMqUKeLk5CQ9evSQK1euyLZt28TGxkbatGkj77//vly7dk2WLVsmAOT48eO65TZs2FA6deokp06dkhs3bsi4cePEw8NDt8c7twl5UlKSbNq0Se/b/pMnT0REdF/AMkrInz9/Lq6urvLrr7/qpj18+FBsbGxk3759Gb7mFStWFEdHxwwvFStWzHSdiYmJkQoVKsjWrVszfZ5a8fHxYmlpKZs3b9ab/sEHH0iTJk1EROTWrVsCQG8PmIhI586dZcCAAZnGk5ohEvI1a9aIq6urnDhxQhdb+fLlZebMmdmOIb0Pu5o1a8onn3yiN23ixIlibW2t+9Xp3LlzYmNjI1u2bNF9iOf0w9vQCfnp06cFgBw9ejTLeQcMGKD7JeHlhFz7Gp8+fVpvfX75Nf7f//4n/v7+8uTJEzl//rzY2tqmWXdexeTJk6VWrVo5uk9OEvKoqKh0E9Z69eplmlRlZ/3w8/OTOXPm6M0zZ84cKV68uO7vP/74Q6ytreXEiRNy7949KV26dJpfKnIrPj5evv76a3F1dZWHDx9m+36vmpAnJyeLn5+fzJ8/////VvaMnzolos2hNmzYILa2trJy5UopX768FC1aVHr27Cl3797VW9bevXulRIkS8vTp0zQJuYiyw8zNzU3mzZsnIiK9evWS2rVrZ/jLcHZ+wfzss8+ka9euIpL9ZDg1tRLyEydOCABZtmyZVK9eXXx8fKRt27Zy+fLldOfPKCGPjo6WkiVL6rYNEyZMkOLFi+s+60RE4uOV1/PUqYzzrpcT8oCAAPHx8ZEWLVpk+pknwoQ8PblOyJ89E1Gqxkx7efYs+09u4MCBYmlpqUtsAIivr6+cOXNGN8/SpUulXLlyum/fIspGzt7eXnbv3i2PHz8WAHLgwIF0HyM7JSsPHjwQAGk23Onx9/eXfv366f5OSUkRLy8vWbRokYi8SB61GyetIkWKyPTp0/WmvfbaazJq1Ci9+6X+Zr1u3ToBIHv37tVNmzlzppQrVy7by33//felRYsWeuOntWfPHrG0tNTbAF+5ckUAyMmTJ0VEGT8HBwe9n8jbtGkjAQEBehvUcuXK6RKwvXv3iouLS5o90aVKldL9mpBRQm5nZ6eX7G7ZskUvIRfJuGRl8+bNUq5cuUw3+CNHjpR27drp/p43b56ULFky3fHRCgkJkZs3b2Z4CQkJyfC+IiLvvPOODBkyRO95ZpaQ//fff+kmdNOnT5eyZcuKiMjRo0cFQJpfdIYNGyatW7fONJ7UDJGQJycny/fffy/W1tZiZWUlAGTkyJE5iiG9D7tJkyaJj4+PnD59WlJSUuTUqVPi5eUlAHR7f0WUPbienp7y/vvvi4+PT44SHxHDJ+QjR46UChUqZDnfunXrpHLlyrrt9ssJufY1vnfvnt76/PJrHB8fLzVq1JA333xTKlWqJEOHDjXYc/nnn3/ExcVFfv755xzdL6clK/Xr15emTZvKf//9J0lJSbJ69WrRaDS69T092Vk/rK2tZc2aNXr3W7NmjdjY2OhNGzVqlJQtW1Z69uyp95rk1vbt28XR0VE0Go0UKVJEtz3NrldNyGfPni3u7u7y4MEDERGJiFASt/PnXyRvM2fOFGtraylXrpzs2rVLjh8/Li1bttTt7BIRefTokfj5+en2YKeXkIuI/Prrr2JrayuTJk0SBwcHuX79eoaxZZWQHzlyRIoWLap7H+elhFz7mV28eHH57bff5PTp09K7d2+9nVGpZZafaH+p+fTTT8XKyirNrwgpKS8S8oyqYrVjHRQUJIsXL5YzZ87IsWPHZOTIkaLRaNIsMzUm5Gnl+yP6mjdvjvPnz+P8+fM4ceIEWrdujXbt2uHOnTsAgDNnzugOJnFycoKTkxPc3d0RFxeHW7duwd3dHYMGDUKbNm3QqVMnfPfddwgNDc1RDPL/B2xqNJpszZ+6q4lGo4GPj0+ajgW1a9fW3Y6KisL9+/fRsGFDvXkaNmyIq1evZrhsbW/xKlWq6E3TPlZ2ljto0CCcP38e5cqVwwcffIA9e/bo5rt69Sr8/Pzg5+enm1axYkUUKlRIL66AgAA4OzvrxVCxYkW9A05Tx3XmzBk8e/YMHh4eutfMyckJwcHBuHXrFjIzd+5c3fpw/vx5tGrVKtP5U+vWrVuWB6kMGzYMe/bswX///QcAWL58ue7g4oz4+/ujdOnSGV78/f0zvO+2bduwb9++XHUUeDkmEUkzLTvzpLZmzRq912TNmjWYMWNGmmnpuXv3rt58M2fOBKAcMDR9+nQsXLgQZ8+exebNm7Fjx450Dy7KiU8//RTt2rVDvXr1YG1tjS5dumDQoEEAoNfqc9y4cShXrhzmz5+P5cuXw9PTM9PltmvXTu95AEClSpXSTEvPy2N19+5dvf/HxsZi7dq1GDJkSKYx3Lt3D6NHj8Yvv/yS5Zl2s3qNbWxs8Msvv2DTpk2IjY01WPeK+/fvo23btujZsyeGDh2a6bwjRoxIMy4vj/PLY5Xa6tWrISIoWrQobG1t8f3336NPnz6ZtnTN7vqRnffIN998g6SkJGzduhWrV69+5bMfaz/Xjh07hrZt2+LNN9/MtKvNq7wvX7Zu3TpMnToVGzZsgJeXFwD93uPap56SkoLExER8//33aNOmDerVq4d169bh5s2b2L9/PwBle9mnTx80adIk08fs2bMnunfvjpkzZ+Lbb79F2bJlsxXry6Kjo9GvXz/8/PPPWb6PU3t52zRixAgcPnw4zbSMpH7/t2vXLlexA8qYAsDkyZPxxhtvoFatWli+fHmODvDWql+/Pj766CN88cUXGDduXJrXQKPJ/smBypUrh2HDhqFmzZqoX78+Fi5ciA4dOuCbb77JUUwFXa77kDs4AM+eGTKU7D9uTjg6OqJ06dK6v2vVqgVXV1f8/PPP+PLLL5GSkoJatWqluzEqXLgwACWp+uCDD7Br1y5s2LABn3zyCQIDA1GvXr1sxVC4cGG4ubmlSY4zYv3SeWo1Go3ujZj6eb0sOx8MqZet/d/L015+rMyWW7NmTQQHB2Pnzp3466+/8Oabb+L111/Hb7/9lmHy9vL09J5vZmOQkpICX19fHDhwIM2yszpC38fHR299AICHDx9mep+cqFGjBqpVq4ZVq1ahTZs2uHTpErZv357pfSpVqqT7gpgef3//DDtf7Nu3D7du3UrzvN944w00btw43THy9PSEpaUlwsLC9KaHh4frvqT5+PgAAMLCwuDr65vuPOnp3Lkz6tatq/t7woQJKFq0KD744APdtIzuX6RIEb3Wk9rnNGXKFPTv31+XtFWpUgUxMTF45513MHny5Fx3CrK3t8eyZcvw008/4cGDB/D19cXixYvh7Oys92EdHh6O69evw9LSEjdv3kTbtm0zXe6SJUsQGxur+7tMmTL4888/UbRo0SxjGjFiBN58803d30WKFNH7/2+//Ybnz59jwIABmS7nzJkzCA8PR61atXTTkpOTcejQISxYsADx8fF6r3GpUqX0nu/Lr9GxY8cAKCcKi4iISHf7kxP3799H8+bNUb9+fSxevDjL+T///HN89NFHur+bNWuGWbNm6a1rL49VaqVKlcLBgwcRExODqKgo+Pr6olevXihRokSG98nO+uHj45Pp+0jr9u3buH//PlJSUnDnzp1cd77Q0n6ulS5dGvXq1UOZMmWwdOlSTJo0Kd35X+V9mdqGDRswZMgQbNy4Ea+//joA5fTq2oZUqburaLcbFStW1E0rXLgwPD09dV+e9u3bh23btukSNxFBSkoKrKyssHjxYgwePBgA8Pz5c5w5c0b3HsytW7duISQkBJ06ddJN036uWFlZ4fr163rvBa2Xt02bN2/Gpk2b9PIGFxeXDB/3zz//ROL/Z7X29va5jj+9MbW1tUXJkiUz/UKanpSUFBw9ejTTMbW2VpLxhISc51716tXDL7/8krM7FXC5Tsg1GuAVt8mq0Gg0sLCw0H1g1qxZU/dNP7M3VI0aNVCjRg1MmjQJ9evXx9q1a1GvXj3Y2NggOTk508e0sLBAr169sHr1akyZMiXNB0dMTAxsbW1hlcvzDLu4uKBIkSI4cuSI3rfcY8eOoU6dOrlaZk6W6+Ligl69eqFXr17o0aMH2rZti4iICFSsWBF3797FvXv3dHvJg4KC8PTpU1SoUCHXcdWsWRNhYWGwsrJCQEBArpeTERsbGwDI8nXNyNChQzF37lz8999/eP311/V+IUhP6o11el7+cpLaxIkT0+xdrFKlCubOnav3oZOajY0NatWqhcDAQHTr1k03PTAwEF26dAEAlChRAj4+PggMDESNGjUAAAkJCTh48CBmzZqVYTzOzs56v3Y4OzvD3d09zZeg9FhZWenNl5KSgqioKDx//jxN0m1paQlRSu6yXG5WrK2tUaxYMQBKG7SOHTvqPd7gwYNRuXJlDBs2DEOGDEHLli31PhBfll7i7e/vn6111d3dHe6ZnOJw6dKl6Ny5s25nQUZatmyZpmXe22+/jfLly2PChAmwtLTUvcZ//fWXLglJ7zW+desWPvzwQ/z888/49ddfMWDAAOzduzfXX4T+++8/NG/eXLd3LzvL8fLy0u2NBZR1pWjRotlar1JzdHSEo6MjIiMjsXv3bsyePTvL+2S2ftSvXx+BgYH48MMPdfPv2bMHDRo00P2dkJCAvn374s0330RAQACGDRuGevXqGfTsxyKC+Pj4DP//Ku9LrXXr1mHw4MFYt24dOnTooJv+5IlSUGpnB6TONbW/rF6/fl03fhEREXj06JHuV7/jx4/rbWd///13zJo1C8eOHdN7H40bNw4WFhbYuXMn2rdvjw4dOqBFixbZjl2rfPnyad4Xn3zyCaKjo/Hdd99luK1+edvk5eUFe3v7bI9fZr9y5oS2leH169fRqFEjAEBiYiJCQkJy/Bhff/01rl69ioMHD6JNmzZYvnw53n77bb15sruHPD3nzp3T25lD2ZCdupa83GUlddvDoKAgGTVqlGg0Gl39ofagzmbNmsmhQ4fk9u3bcuDAAfnggw/k3r17cvv2bZk4caIcO3ZMQkJCZPfu3eLu7q5r+7NmzRpxdHSUc+fOycOHD9PUNWtFRERI+fLlpVixYrJy5Uq5cuWK3LhxQ5YuXSqlS5fOtO1htWrVdPV+L9c7a82dO1dcXFxk/fr1cu3aNZkwYUK6B3Wmvl96tdIv1/Bltdw5c+bIunXr5OrVq3L9+nUZMmSI+Pj4SHJysu6gzsaNG8uZM2fkxIkTUqtWrTQHdb5c45ZePV3q+teUlBRp1KiRVKtWTXbt2iXBwcFy9OhRmTx5spw6dUpEcn9Qp4hyEJFGo5EVK1ZIeHi4rrVcdmrIRZT6NwcHB7GxsZH169enO48xpfc8W7RooTsAS+RF28OlS5dKUFCQjBkzRhwdHfXq1b/66itxdXWVzZs3y6VLl6R3796qtD387LPPxNnZWdatWye3b9+WPXv2SKlSpeTNN9/UzTt//vw0nViuXLki586dk06dOkmzZs3k3Llzeuv/9evXZfXq1XLjxg05ceKE9OrVS9zd3fXqvRcsWCCFChXSHQfRr18/qV69uq4GNjtgoBrymzdvikaj0etylNrLr/HLXq4hF3nxGq9evVouXLiQ5jVOSkqS+vXrS/fu3UVEJDQ0VDw9PWX27Nm5eg7//feflC5dWlq0aCH//vuvXou0nMhpDfmuXbtk586duvWnWrVqUqdOHb0DAydOnKjXDSk768fRo0fF0tJSvvrqK7l69ap89dVXadoefvTRRxIQECCRkZHy+PFjadKkiXTo0CFHz1fr2bNnMmnSJDl+/LiEhITImTNnZMiQIWJra5vhgX3pyen7cu3atWJlZSU//PCD3mv25MkTuXZNqTNeunSz3vFHIiJdunSRSpUqydGjR+XSpUvSsWNHqVixYoYHZKZXQ75jxw6xsbHRHfv1ySefSLFixSQiIiLdZeS0La2aNeRZbaNOnDgh5cqV02vPOXr0aClatKjs3r1brl27JkOGDBEvLy+98bh586acO3dOhg8fLmXLltUtV7vd0h6srm0JuWTJEnF2dk7TYjMkRHlt02kOJyIvxnrOnDmyZcsWuXHjhly+fFkmTpwoAGTTpk0ZPnfWkKeV7xNypGpf5+zsLK+99pr89ttvevOFhobKgAEDxNPTU2xtbaVkyZIybNgwefr0qYSFhUnXrl3F19dXbGxsxN/fXz777DPdmz0uLk7eeOMNKVSoUKZtD0WUVn0TJ06UMmXKiI2NjXh7e8vrr78uW7Zs0R30l9uEPHV7Qmtr6wzbHuY0Ic9quYsXL5bq1auLo6OjuLi4SMuWLfU6c2S37WFqWSXkIkrnhPfff1+KFCki1tbW4ufnJ3379tUlTq+SkIuIfP755+Lj4yMajUbX9jCrLiup9e/fP90WiKaQ3vP09/dP8wH8ww8/iL+/v9jY2EjNmjXTOagnRaZMmaJradmkSRO5dOlSjmIxREIeHx8vU6dOlVKlSomdnZ34+fnJqFGj9NbbKVOmiL+/v979/f3907SwTL0PIigoSKpXry729vbi4uIiXbp0kWvXrun+f/XqVbG3t9d1DRJRPigCAgJk/Pjx2X4ehkrIJ02aJMWKFctwvUvvNU4tvYQ8JSVFPvvsM/H29k73NZ42bZr4+vrKo0ePdNO2bt0qNjY2abZB2ZFeq9iXX5fsyGlCvmHDBilZsqTY2NiIj4+PvPvuu3odJUSUdTV1kpXV+qG1ceNGKVeunFhbW0v58uX1kpD9+/eLlZWVHD58WLc+BwcH6/Vsz4nY2Fjp1q2bFClSRGxsbMTX11c6d+5s9IM6mzZtmu5r1r//QN2Bf4sXL0/zOj59+lQGDx6sayncrVu3NF1WUnv580fbNjJ1K93ExESpU6eO3hfy1PJSQp7VNkr7GZ16+5GQkCDjxo0TLy8vcXZ2ltdffz3Nl7GMXq/g4GBdO9eXu75169ZNGjRooPeZ+d9/ymubUV8B7Vh/9dVXuu2zm5ubNGrUSP74449MnzsT8rQ0Iln/5hsXF4fg4GDdWf2IzF1ycjLOnTuHGjVqZHrgVm5oSylcXFwy/Lm9VatWqFChAr7//nuDPnZBkp1xplfHcTaN/DjOYWHAv/8CTk5A+fJqR6PIj+OslocPgTt3AFdXoEyZtP9/lbHOLK+MioqCq6srnj59mmkpcX6T6xpyIkorIiICe/bswb59+7BgwQK1wyEiMprU3VUo/3mVGnLKOSbkRAZUs2ZNREZGYtasWShXrpza4RARGUVsLPD8udLgwc1N7WjIGJiQmxYTciIDCgkJUTsEIiKje/xYuXZ1fZG4Uf7y/w3HkJiodNLJ5qlUKJdYYEVERETZJvIiIU/de5zyl9SdmLmX3PhylJBn4/hPIiIiyseiopQEzcpK2UNO+VNOztaZU8wn08pWQq49Mcnz58+NGgwRERGZt0ePlGt3d4CNTPK31GUrhqTNJzM78V1Bk60acktLSxQqVAjh4eEAAAcHh3RPiU5kLrRnf4uLizNK28OEhATExcWxrZYRcZxNg+NsGvllnJOSlLNzAkq7w7g4VcNJI7+Ms7nQDmFMjHI21tRyM9YigufPnyM8PByFChUy+OdzXpbtgzp9fHwAQJeUE5mzlJQUPHr0CCEhIQbfKIsIYmNjYW9vzy+mRsRxNg2Os2nkl3GOjlbaHVpbAw8eqB1NWvllnM3F48fAs2fKHvKoKP3/vcpYFypUSJdXkiLbCblGo4Gvry+8vLyQyOp+MnPPnj1Dhw4dcPr0aTg5ORl02YmJiTh06BCaNGnCn9uMiONsGhxn08gv49y7N3DuHDB+PNCwodrRpJVfxtlc7NoFfPcd0KMH8OWX+v/L7VhbW1tzz3g6ctz20NLSkgNJZi8hIQF37tyBjY2Nwc8ua2lpiaSkJNjZ2XGDb0QcZ9PgOJtGfhjn69eBrVuVMoZu3dKWMJiD/DDO5sTFRTlbZ1BQ2tebY21YLLAiIiKiLK1apVy3aQP4+qobC5lGkSLKdWiounEUBEzIiYiIKFMpKcDq1crtQYNUDYVMSJuQ37+vbhwFARNyIiIiytT+/cC9e0ChQkDnzmpHQ6aiTcjDw3lyIGNjQk5ERESZWr5cue7Vyzxrx8k4PDxenBwoLEzdWPI7JuRERESUoYgI4LfflNuDB6sbC5mWhcWL4wVYtmJcTMjJ5A4dOoROnTqhSJEi0Gg02Lp1q97/RQRTp05FkSJFYG9vj2bNmuHKlSvqBEtEVMCtWQPExwNVqwKvvaZ2NGRqrCM3DSbkZHIxMTGoVq0aFixYkO7/Z8+ejTlz5mDBggU4deoUfHx80KpVK0RHR5s4UiKigk0E+Pln5fbQoQDPtVPwMCE3jRz3ISd6Ve3atUO7du3S/Z+IYN68eZg8eTK6d+8OAFi5ciW8vb2xdu1aDB8+3JShEhEVaKdOAZcuAba2QL9+akdDamBCbhpMyMmsBAcHIywsDK1bt9ZNs7W1RdOmTXHs2LEME/L4+HjEx8fr/o76/3P8JiYmGvzMstrl8Yy1xsVxNg2Os2nk1XH+6SdLABbo3j0FTk7JZt9pI6+Osznz9rYAYIl//01BYmKybrqxxrqgvnZMyMmshP3/Ydze3t560729vXHnzp0M7zdz5kxMmzYtzfQ9e/bAwcHBsEH+v8DAQKMsl/RxnE2D42waeWmcY2OtsHZtGwAWqFTpGP7887HaIWVbXhpnc/fwoR+Amrh48RH+/PN4mv8beqyfP39u0OXlFUzIySxpXipUFJE001KbNGkSxo4dq/s7KioKfn5+aN26NVxcXAwaW2JiIgIDA9GqVSueLtiIOM6mwXE2jbw4zsuWaRAXZ4XSpQX/+1/dPFE/nhfH2dxZW2vw/fdAYmJhtG/fXjfdWGOt/YW7oGFCTmbFx8cHgLKn3DfVuZnDw8PT7DVPzdbWFra2tmmmW1tbG22jbMxl0wscZ9PgOJtGXhpnbe/xYcM0sLHJGzFr5aVxNnfFiyvXYWGadMfU0GNdUF83dlkhs1KiRAn4+Pjo/QSWkJCAgwcPokGDBipGRkRUcFy6BJw4AVhZAQMHqh0NqUm7b+zxY6X9JRkH95CTyT179gz//POP7u/g4GCcP38e7u7uKF68OMaMGYMZM2agTJkyKFOmDGbMmAEHBwf06dNHxaiJiAqOJUuU686dgUx+nKQCwM1N+WKWlAQ8fAgUK6Z2RPkTE3IyudOnT6N58+a6v7W13wMHDsSKFSswfvx4xMbGYtSoUYiMjETdunWxZ88eODs7qxUyEVGBERcHrF6t3B46VN1YSH0WFoCXl9L2MDycCbmxMCEnk2vWrBlEJMP/azQaTJ06FVOnTjVdUEREBADYsAGIjAT8/IBUHWipANMm5A8eqB1J/sUaciIiItJZuFC5HjECsLRUNxYyD15eynV4uLpx5GdMyImIiAgAcPo0cPIkYGPDchV6QXscARNy42FCTkRERACAH35Qrnv2fLFXlEi7LrBkxXiYkBMREREePwbWr1duv/uuurGQeWHJivExISciIiIsW6Z0WKlRA6hXT+1oyJywZMX4mJATEREVcMnJwKJFyu133wU0GnXjIfPCkhXjY0JORERUwO3aBQQHKyeB6d1b7WjI3LBkxfiYkBMRERVw2laHb78NODioGwuZn9QlK5mcRoReARNyIiKiAuz2bWDnTuX2yJHqxkLmqXBh5TopCXjyRNVQ8i0m5ERERAXYokXKXs+2bYHSpdWOhsyRrS3g6qrcZh25cTAhJyIiKqCio4Gff1Zus9UhZYZ15MbFhJyIiKiAWrYMePoUKFcOaN9e7WjInLH1oXExISciIiqAkpKAefOU2x9+CFgwI6BMsPWhcfHtR0REVABt2QKEhACensCAAWpHQ+aOJSvGxYSciIiogBEBvv1WuT1qFGBvr248ZP5YsmJcTMiJiIgKmGPHgBMnlO4Zo0apHQ3lBSxZMS4m5ERERAXMnDnKdb9+L/Z8EmWGJSvGxYSciIioALl1S6kfB4CxY9WNxZCSUwQngyMAACeDI5CcwlNKGhJLVoyLCTkREVEBMm+eUkPerh1QsaLa0RjGrsuhaDRrHwavPAUAGLzyFBrN2oddl0NVjiz/YMmKcTEhJyIiKiAiIpTe4wAwbpy6sRjKrsuhGPnLWYQ+jdObHvY0DiN/Ocuk3EC0CXlUFBAXl/m8lHNMyImIiAqI+fOB58+BatWAFi3UjubVJacIpm0PQnrFKdpp07YHsXzFAAoVAqytldsPH6oaSr7EhJyIiKgAiIoCvvtOuf3xx4BGo248hnAyOCLNnvHUBEDo0zhdbTnlnkbDAzuNiQk5ERFRAbBwIRAZCZQrB7zxhtrRGEZ4dPZqJ7I7H2WOdeTGY6V2AEREBZGIcury+HjlkpAAODgALi75Y88lmZeYmBcnApo8GbC0VDceQ/FytjPofJQ5dloxHibkRDnwcluteqW9YGnB7IkylpAA/P03cOkScP26crlxA7h7F0hJSTu/vT3g4wP4+gJFiwLVqwN16gC1ays1nES5sXgx8OgRULIk0Lu32tEYTp0S7vB1tUPY07h068g1AHxc7VCnhLupQ8uXWLJiPEzIibJp1+VQTNsehIfhSZhc1Q7jV56Cu5M9pnSqiLaVfdUOj8xISAiwa5dy2bsXePYs6/toNMpe89hYIDhYuQDAxo0v5ilXDmjcGOjWDWjZUjnLIlFW4uKAr79Wbk+aBFjlo09+SwsNpnSqiJG/nMXLu0a0f0/pVJE7TgyEJSvGk4/elkTGo22rFXmsNJ4eLodf2wYDNa/o2mot6leTSXkBFxsLbNig1OmeOqX/Py8voG5dJaHWXkqWVEpUbG0BGxslSYqJAcLClEtoqJLYnzmjnOI8OPjFHvYlSwBnZ6BDByU579RJ2bNOlJ5ly5T1yc8PGDBA7WgMr21lXyzqVxPTtgch4lmsbrqPqx13mBgY95AbDxNyoiykbqtlXeg5ACA42BWoqRzBr4HSVqtVRR/uhSmA/vkH+PFHJemJjFSmWVoCDRoAbdsql+rVAYtsHELv6AiUKqVcXvbwIXDyJLBzp3KWxfv3gfXrlYu7OzB4MDBypJLoE2klJACzZim3J0xQvvzlR20r+6JVRR/8/U84Hl39G8sGvsaSQiNgDbnxsMsKURZSt9Wy8YoCANy54wL5/4JFttUqmP79F3j7baBsWeVguchIwN8fmDlTSZYPHVJay9Wsmb1kPCuFCyt7xBcsAO7dU+rSx49XHjMiAvjmG6B0aWWeXbugWz+pYFu9WjlewcdH+dKWn1laaHS14nVKuDMZNwKWrBgPE3KiLKRul2XlHgONVTLi4qyQGOmY4XyUfz19qtThlikDrFjx4hTkO3YAt24BEye++NAyFgsLpQRm1izlMbdtA9q0UWL5808lnnr1gN27mZgXZAkJwPTpyu3//Y9lTfTqWLJiPEzIibKQul2WxkJgUzgaABD/wCXD+Sj/SUkBFi1Sykm++ko5UK5xY2VP9Z9/Knum1WglZ2mp1JDv2qV0bxkzRqlNP3lSKZdp1Eg5sJSJecGzeLFy7IGPDzB8uNrRUH6gLVl5+DD9LlGUe0zIibKgbaul/fHT1lspW9Em5BoAvmyrla/duQO0agWMGgU8fgxUqKDslT54UNlTbS7KlAHmzgVu3wbGjgXs7IBjx4DXXwdatwaCgvTnf7mNJ08vnn88ewZ88YVy+7PPlOMTiF5V4cLKdVIS8OSJqqHkO0zIibKgbasFKMm3nddTAEB8uAvbauVzIkpHkypVgH37lJ/8v/sOuHhR2Sttrifw8fZW6tpv3wY++EA5kO+vv4CqVYEPP1Q+SHddDkWjWfsweKXSEmbwylNoNGsfdl0OVTd4Moh585SyglKlgKFD1Y6G8gsbmxfnQ2AduWExISfKBm1bLR9XO7095D6udmx5mE89eKCUoQwbBkRHK11TLlxQEty80sfZ11f5AnH1KtC1K5CcrCRqAaWS0e9/D3H/if5xD9o2nkzK87ZHj4DZs5XbX34JWFurGw/lLy/KVsx0j0QexYScKJvaVvbFkQktsGRMGQBAUrQ9fh/agsl4PnT6tHJmzJ07lT7hX3+tdE0pU0btyHKnZEmlVeLu3UD58oKnEZZ4vKsqHqyrh4QIB9182oKVaduDWL6Sh82cqXyJrFEDePNNtaOh/IYHdhoHE3KiHLC00KB5FTd4e8cAAC5f4h6C/Gb1auVgzX//VU7gc+YM8NFH6hywaWitWwOLt0TArXkQNNZJiL/ngTtLmmLr1lKQ/z9Ai20887a7d5XWmICSmBui5SZRai8Scn7+GRLfqkS5UKKEUkd+/ry6cZDhJCUpB0IOGKB0UOnYUTlDZqVKakdmWBFxcXCpEwzfwYdg5/8IkmSJFSsq496qhkh46KSbj20886apU5V2h82bK1/AiAyNJwcyDibkRLmgTcgvXFA5EDKI6GigfXulQwkAfPIJ8PvvgKurunEZg7Y9p3WhWHj1OgHv9hfg4JCIuPtuCF3ZCFFnAiDCNp550ZUrwMqVyu2ZM833oGPK27R7yB8+VDeO/IYJOVEulCihHNjJPeR53+PHQMuWQGCg0hrut9+UdnH59af+1G08NRrAtfo9zJ+/Dw6lwoFkS0T+VQlPt9ZFcXu28cxLRIDRo5Xe0N27m1c7TspfXpytk9/4DCmffuQQGVdAgLKH/OpV5edhypv+/VepFz91CvDwAA4cAN54Q+2ojOvlNp4A4OERh6JvnoT765ehsUrG0xueqF5Ng+3b1YuTcmbzZuUEUNqDkImMRZuQB99LAsBzGBgKE3KiXChcOBaFCgkSE9OebIXyhps3lbNYXr0KFC0KHD6sdFYpCFK38dTSaICyLR5g0cYIVK2qtM7r3FnZ6xofr2KwlKXnz5XjHwBg/Hilqw6RsQTHPAIAXAtJBMBzGBgKE3KiXNBogKpVlT0CrCPPey5eVJLxO3eUVoZHjypn3yxItG08lw18DQCwbOBrODKhBYZ3LYyTJ18keN9/r4zV7dsqBkuZmjVL6a5SvDgwcaLa0VB+tutyKOYduQwASI6x0U3nOQxeHRNyolyqVk1JyFlHnrdcvaqcSj48HKheHThyBPD3VzsqdVhaaFCnhFIrXqeEu+5ss7a2ypk+t28H3N2Vvuw1ayplEWRebt9WEnJAec0cHDKfnyi3klME07YHwcJB+cksJcEa8fFKGslzGLw6JuREucQ95HnPrVtKMv7woZJg7t//oh6S0urYETh3DqhfH3j6VKmvHzOGx02Yk7FjlZKili3z//EPpK6TwREIfRoHjW0SYJkMAIiKstX9n+cweDVMyIlySZuQnz+vdDgg83bvnpK03L+v9BbfvRsoVEjtqMxf8eLAwYPA//6n/P3dd0CLFso4krp27VLac1pZKaVFbHNIxqQ9N4FGA1g6KN/Knz61zXA+yhkm5ES5VLGi8kEYGakke2S+wsKUZFxbM/7XX4Cnp9pR5R3W1sDs2Ury5+Ki1NzXrAkcOqR2ZAVXbCzwwQfK7fffV7ZHRMaU+twE2oT8yZO0CTnPYZA7TMiJcsnW9sWBgCxbMV9PngCtWildVfz9ldZwPj5qR5U3de6s1JNXqQI8eKDsKZ87l78QqeHTT5V12tcXmDJF7WioIEh9DgMLR6WOPPUecg0AX1c73XEplDNMyIleQbVqyjUP7DRPCQnKSVIuX1YSl717AT8/taPK28qUAY4fB/r2BZKTlRrm3r2BmBi1Iys4jh0D5sxRbv/8c/48oyyZn9TnMLB00CbkSqcVbbXUlE4VdQeHU84wISd6BdWrK9fcQ25+RIChQ5UDN52dgZ07gVKl1I4qf3B0BFavBhYsUMq2NmxQDvy8dUvtyPK/2Fhg8GBl/R4wAOjQQe2IqCDRnsPAxS0FwIuSFR9XOyzqVxNtK/uqGV6eZqV2AER5GfeQm6+pU5Wk0dIS2LjxxWtFhqHRAO++q4xrjx7ApUvKiZXWrQPatlU7uvzrs8+A69eVX3zmzVM7GiqI2lb2xcwhgoUSjyJFYjB+4GuoV9qLe8ZfEfeQE70CbZJ36xYQHa1uLPTCihXA558rt3/8EWjTRtVw8rVGjYAzZ4B69ZR6/fbtgRkzWFduDMePvyhV+eknwM1N3Xio4Bo4UIMj+yzQtm2I3jkMKPeYkBO9gsKFldOuA0q/ZlLf3r3AsGHK7Y8/VspWyLiKFgUOHFDGXQSYPBno2ZNfUg0pNhZ4+20gJQXo3x/o1EntiIjIkJiQE72iunWV67//VjcOUs5a2LMnkJSkHGj4xRdqR1Rw2NoCixcre26trYFNm5S95jdvqh1Z/jB+/ItSle++UzsaIjI0JuREr6h+feX62DF148hPklNEd7a3k8ER2ToVc0wM0LWr0he+Th1g2TLAgls4k3vnHeVEQr6+QFAQ8NprwB9/qB1V3vbrr8oBtACwZAlLVYjyI35cEb2iBg2U6+PHWTdrCLsuh6LRrH0YvPIUAGDwylNoNGsfdl0OzfA+IkrniUuXAG9vYPNmwI7nplBN/fpKXXmDBsDTp0p5xRdfKOUWlDM3brwou5o4UanRJ6L8hwk50SuqWVP5iT48XCmZoNzbdTkUI385i9Cn+qdeDnsah5G/nM0wKZ89W9mLqC2V0Nb1k3p8fZWWkyNGKF+YPvsM6NJFOfCTsuf5c6WDTXQ00KQJS7CI8jMm5ESvyM4OqFVLuX38uLqx5GXJKYJp24OQ3o8M2mnTtgelKV/ZtQuYNEm5/f33QMOGRg2TcsDGBli0SCkfsrUFduxQWiNevKh2ZHnD++8rv/p4eQHr1ys934kof2JCTmQA2jpyJuS5dzI4Is2e8dQEQOjTOF1tOQAEBysHb4ooHT6GDzdBoJRjb78NHD0K+PsrLULr1QPWrlU7KvO2YoXyRUajUXq7+/J8K0T5GhNyIgPQ1pHzwM7cC4/OOBlPb774eKWjypMnSoI3f76SvJB5qlVLqStv3Vpp4de3LzBqFBCXvZe9QDl2DBg5Urk9bRrQooW68RCR8TEhJzIA7R7yixeBZ8/UjSWv8nLO3lGY2vk++khJ8NzdlfpxW1tjRkeG4OEB/Pkn8Mknyt+LFiklRjz24oXr15WDYOPigI4dlZ7uRJT/MSEnMoCiRQE/P6WLxMmTakeTN9Up4Q5fVztktJNbA8DX1Q51Srhj48YXbeBWr1bGnvIGS0vl4MSdO5UE/exZ5cDorVvVjsx4stvGMywMaNsWiIhQWneuX8/WnUQFBd/qZLYWLlyIEiVKwM7ODrVq1cLhw4fVDilTqdsfUs5ZWmgwpVNFAEiTlGv/ntKpIm7f0mDIEOXvCRPYBi6vattWObuttjVit27AmDH5r4Qlu208o6OVdTkkBChVCti+HXB0VCFgIlIFE3IySxs2bMCYMWMwefJknDt3Do0bN0a7du1w9+5dtUPLEE8Q9OraVvbFon414eOqX77i42qHRf1qollpX7z5ppK8NGoEfPmlSoGSQfj5AQcOKOVHgHIGyrp1gStXVA3LYLLbxjMxUTke4tw5oHBhpXOQl5caERORWpiQk1maM2cOhgwZgqFDh6JChQqYN28e/Pz8sGjRIrVDy5B2D/nff/MEQa+ibWVfHJnQAssGvgYAWDbwNRyZ0AJtK/ti7Fjg/HnA05Nt4PILa2vg66+Vs3kWLqwch1G7tlJfnpffR9lt4xkbJ+jbF9i9G3BwUFpDli5tykiJyBzw44zMTkJCAs6cOYOJEyfqTW/dujWOZbD7OT4+HvHx8bq/o6KiAACJiYlITEw0aHza5b283IoVATs7K0REaHDlSiLKlTPowxY4NYo5I/Cqcp2SnIQtmzVYtEjZZK1YkQQvL4GBX9oCKaP12dRatVIO0h02zBK7d1tg1Cjgzz9TsGhRMry9VQ0tV04GRyDiWSxsLZW/bS1E7xoAHkXGo0WbBPx9yBY2NoJ165JRowbX61dhLutzQWCssS6or51GJC/vg6D86P79+yhatCiOHj2KBtrdzgBmzJiBlStX4vr162nuM3XqVEybNi3N9LVr18LBwcGo8ab28ccNERTkifffP4eWLc23vCavefzYDmPGNEd0tA26dr2JQYOC1A6JjCQlBdixoyRWraqIpCRLODsnYOjQS2jS5N981dYyJsYK06fXRVCQJ2xtkzBp0klUr/5Q7bCIVPf8+XP06dMHT58+hYuLi9rhmAz3kJPZ0rz06SsiaaZpTZo0CWPHjtX9HRUVBT8/P7Ru3drgb+jExEQEBgaiVatWsLa21vvf4cMWCAoCnj+vhvbtKxv0cQsa7Ti3aNEKnTvbITraAjVqCH75JQA2NgFqh5dvZLY+q6VjR2DUqBQMHWqB8+dtMHduLdy8WQM//JCcZ06QczI4QncgJ6DsGf+idgo+PW2B589s8O/6uogPKwQn5xTs2A40aPCaitHmH+a4PudXxhpr7S/cBQ0TcjI7np6esLS0RFhYmN708PBweGfw27WtrS1s02lEbW1tbbSNcnrLbtwY+PZb4O+/LWBtzUM0DGH+fFscOGABBwdg/XoNHB35IWsMxnyv5EatWkoL0VmzgM8/B3bssMCRIxb45hvlzJ/m3g6wXmkvuDvZI+xpnF4defRDJ/y78TUkRTjByjEB+/dbo3YtfhQbmrmtz/mZoce6oL5uZr5Jo4LIxsYGtWrVQmBgoN70wMBAvRIWc6TttBIUpLRyo1dz82YhTJmibKbmzwfKllU5IDIpa2vlJEJnzigJ+pMnwNChyvvs1Kks766q9Np4Hj5cFHeWN0ZShBMsnWOxcO0T1K6Vj+pwiCjXmJCTWRo7diyWLFmCZcuW4erVq/jwww9x9+5djBgxQu3QMuXlpfQQFgFOnFA7mrwtOhqYM6cWkpI06NlT2StKBVOVKkr3om++AZyclD3ndesCw4YBD8247FrbxtPL0R4PdlXGt9/WhiRYwblEJFb9HoVhndnbkIgUTMjJLPXq1Qvz5s3D559/jurVq+PQoUP4888/4e/vr3ZoWWI/csP43/8sERrqBD8/wU8/IV8d0Ec5Z2UFjBsH3LgB9O+vfOldskT51WTGDOULnDkqbeeL5N+b4+nZAABA/xHP8PBaIfRpngdbxxCR0TAhJ7M1atQohISEID4+HmfOnEGTJk3UDilbtFU1R4+qG0detm0bsGyZBTQawbJlyXBzUzsiMhe+vsCqVcCRI0D16koZy+TJQMmSSj/zmBi1I1Q8ewZ8/DFQqRJw5owG7u6CTz89jqXf28LWht8uiUgfE3IiA2vaVLk+cgSIjVU3lrwoPFypEwaALl3+QdOm7MxKaTVsCJw+DaxZA5QpAzx6BIwfryTms2Ypf6tBBPjlF6BcOWDmTCAhAWjdGjh1Kgm1aoWrExQRmT0m5EQGVqECUKwYEBcHHDqkdjR5i8iLuuDKlQV9+15TOyQyY5aWQJ8+ykHUK1YoyXh4ODBxovIe7N8fOH7cNGf8TEgAfv1VKVnr3x+4f1+J5/ffgV27AD8/48dARHkXE3IiA9NogDZtlNt79qgbS16zbJlSrmJjo5yN09o6Re2QKA+wsgIGDgSuXQOWL1c6ssTHK3uqGzQAatRQ6swvXzZ8cn7vHvDpp4C/P9Crl3Iwt6Oj8nhXrgCdO/P4ByLKGhNyIiNo3Vq53r1b3Tjyklu3gNGjldtffglUrapuPJT3WFsDgwYppSwnTyq37eyACxeUOvMqVZS91qNHAzt2KMl0ThP0uDjgwAFg6lSgWTMgIEBZX8PCAB8fJTm/eROYNEl5bCKi7ODZCIiM4PXXlROXXLkC/Puv8vM5ZSw5WdnDGRMDNGkCjB2rnEKdKLdee03ZW/7tt8DGjcD27cBffwEhIcD33ysXAHBzU778Va4MeHoCzs5Ka0UnJ2W9DAsDQkOV67t3lZ7o8fH6j9W8OTByJNC1q/KlgIgop5iQExmBu7uSEJw4oZStDB6sdkTm7dtvla40zs7AypVKbTATcjIEd3dg+HDlEhOjJOXbtyvvzWvXgMhI4OBB5ZJdvr7K3vFmzYCWLZVzDxARvQom5ERG0qaN8qG/ezcT8sxcuqT8zA8A8+YpJQBExuDoCHTpolwAZU/31avAxYsvzq777JlyiY5War99fZVSFO11rVpKVxfWhRORITEhJzKSNm2Azz8HAgOVn74tLdWOyPwkJAADBijXHTvybJxkWra2Si/z6tXVjoSICjoe1ElkJHXqAK6uyk/iZ86oHY15+vxz4Px5wMMD+Pln7nUkIqKCiQk5kZFYWSn1pQC7raTnxAnlxCkAsGiRUg5ARERUEDEhJzIibT9yJuT6nj9XSlVSUpQTu/TsqXZERERE6mFCTmRE2oT877+VA8ZIMWkScOMGUKQIsGCB2tEQERGpiwk5kRH5+wPlyikHde7dq3Y05mHfvhc9oJcuVfpAExERFWRMyImMjGUrLzx9+qKTyvDhQNu26sZDRERkDpiQExlZ69bK9e7dOT9Nd37z4YfK2Q5LlgS++UbtaIiIiMwDE3IiI2vWDLCxAe7cUeqmC6rt25VTmWs0wIoVyqnJiYiIiAk5kdE5OgJNmii3t25VNRTVPHoEDBum3B43DmjcWN14iIiIzAkTciIT6NVLuV67Vt041CACjBwJPHgAVKoEfPGF2hERERGZFybkRCbwxhuAtTVw8SJw+bLa0ZjWmjXAb78pJ0pauRKws1M7IiIiIvPChJzIBNzcgHbtlNvr1qkbiyndvQu8+65ye8oUoFYtdeMhIiIyR0zIiUykTx/let26gtFtJSUFGDgQiIoC6tUDJk5UOyIiIiLzxIScyEQ6dVIO8AwOBk6cUDsa45s7FzhwQHnOq1crJStERESUFhNyIhNxcAC6dlVu5/eDOy9dAj7+WLk9dy5QurS68RAREZkzJuREJqQtW9mwAUhKUjcWY4mPB/r2BRISgI4dgaFD1Y6IiIjIvDEhJzKhVq0ADw8gPBzYv1/taIxj8mRlD3nhwsCSJcqJgIiIiChjTMiJTMjaGnjzTeV2fixb2b0b+PZb5faSJYC3t7rxEBER5QVMyIlMrHdv5XrTJiA2Vt1YDOnBA2DAAOX2u+8CnTurGw8REVFewYScyMQaNgT8/IDoaODPP9WOxjC0LQ7Dw4HKlYGvv1Y7IiIioryDCTmRiVlYvNhLnl/KVubOVcpV7OyA9esBe3u1IyIiIso7mJATqaBvX+V62zblbJZ52ZkzwKRJyu1584BKlVQNh4iIKM9hQk6kgqpVgebNldaH8+apHU3uRUUpe/sTE4Hu3YF33lE7IiIioryHCTmRSsaPV64XLwYiI9WNJTdEgLffBm7eBIoVA37+mS0OiYiIcoMJOZFK2rQBqlQBYmKARYvUjibn5swBNm9WWjn+9hvg7q52RERERHkTE3IilWg0L/aSf/cdEBenbjw5cegQMGGCcnvePKBuXVXDISIiytOYkBOpqFcvpQVieDiwapXa0WRPaKhycqPkZKBfP2DkSLUjIiIiytuYkBOpyNoaGDtWuf3NN0qSa84SE5Vk/MEDpd/4jz+ybpyIiOhVMSEnUtnQoYCbm3Jw5O+/qx1N5saNA44cAVxclPpxR0e1IyIiIsr7mJATqczJCRg1Srk9a5bSvcQcff89MH++cnvFCqBMGVXDISIiyjeYkBOZgfffB2xtgZMngf371Y4mre3bgQ8/VG5/9RXQrZu68RAREeUnTMiJzIC3NzBkiHL7vfeA+Hh140nt7FngrbeAlBSlvEbbGYaIiIgMgwk5kZn44gslMb96FZg5U+1oFPfuAR07As+fA61aAQsX8iBOIiIiQ2NCTmQm3N1f1GjPmAFcuaJuPJGRSjIeGgpUqgRs3Kh0hSEiIiLDYkJOZEZ69AA6d1baCw4dql4bxMhIoHVr4OJFZa/9H38Arq7qxEJERJTfMSEnMiMaDfDDD4CzM/D330qJiKlFRirlKadPA56ewJ49gL+/6eMgIiIqKJiQE5mZYsWU9ocAMGkScPeu6R5bm4yfOaMk4/v2AVWrmu7xiYiICiIm5ERmaPhwoFEjICZGKV1JSjL+Y0ZGAq+/rp+MV6li/MclIiIq6JiQE5khCwvg55+V3uSBgUD//sZNyq9fBxo2VFocMhknIiIyLSbkRGaqfPkXnU3Wrwfefts4B3n+/jtQp47SbrFIEeXEREzGiYiITIcJOZEZ69QJ2LABsLQEfvlFKV9JSTHMspOTgU8/Bbp2BaKigMaNlXKVypUNs3wiIiLKHibkRGauWzdg3TolKV+xQqkvf9WkPCRE6TH+5ZfK36NHA3v3Aj4+rxotERER5RQTcqI8oGdPZQ+5hQWwZImyN/vo0Zwv5+FDYMwYoFw5YNcuwN5eWe68eTzpDxERkVqYkBPlEW+9BaxerSTRx44pXVi6dlVqv7MSGQlMmwaULAl89x2QkAC0bAmcOAH07Wv00ImIiCgTVmoHQETZ16cP0LQpMHUqsGyZckDm9u1Aly7KQaABAUCJEsrZNS9dUvaiHz2q3BZRllGrFvDVV0qLQyIiIlIfE3KiPKZoUaUl4tixyomDfv8d2LIl6/tVqgR89hnQo4dS+kJERETmgQk5UR5VoQKwdStw8iRw+LByoGZwsHK5fx8oW1bpLa698IBNIiIi88SEnCiPq1NHuRAREVHexB+uiYiIiIhUxISciIiIiEhFTMiJiIiIiFTEhJyIiIiISEVMyImIiIiIVMSEnIiIiIhIRUzIyaSmT5+OBg0awMHBAYUKFUp3nrt376JTp05wdHSEp6cnPvjgAyQkJJg2UCIiIiITYR9yMqmEhAT07NkT9evXx9KlS9P8Pzk5GR06dEDhwoVx5MgRPH78GAMHDoSIYP78+SpETERERGRcTMjJpKZNmwYAWLFiRbr/37NnD4KCgnDv3j0UKVIEAPDtt99i0KBBmD59OlxcXEwVKhEREZFJMCEns3L8+HFUrlxZl4wDQJs2bRAfH48zZ86gefPm6d4vPj4e8fHxur+joqIAAImJiUhMTDRojNrlGXq5pI/jbBocZ9PgOJsGx9l0jDXWBfW1Y0JOZiUsLAze3t5609zc3GBjY4OwsLAM7zdz5kzd3vfU9uzZAwcHB4PHCQCBgYFGWS7p4zibBsfZNDjOpsFxNh1Dj/Xz588Nury8ggk5vbKpU6emmwyndurUKdSuXTtby9NoNGmmiUi607UmTZqEsWPH6v6OioqCn58fWrdubfAyl8TERAQGBqJVq1awtrY26LLpBY6zaXCcTYPjbBocZ9Mx1lhrf+EuaJiQ0yt777338NZbb2U6T0BAQLaW5ePjgxMnTuhNi4yMRGJiYpo956nZ2trC1tY2zXRra2ujbZSNuWx6geNsGhxn0+A4mwbH2XQMPdYF9XVjQk6vzNPTE56engZZVv369TF9+nSEhobC19cXgFJ2Ymtri1q1ahnkMYiIiIjMCRNyMqm7d+8iIiICd+/eRXJyMs6fPw8AKF26NJycnNC6dWtUrFgR/fv3x9dff42IiAh89NFHGDZsWI5KT0QEgHF++kpMTMTz588RFRVVYL/JmwLH2TQ4zqbBcTYNjrPpGGustZ/b2s/xgkIjBe0Z0/+1d38hUa17GMefsYNp+CdEVEQlSchC7I9aGBUaJEmEdiFEEBp2kakgQgR2YTdlpKVRaHajIpRBYEVUZKVZiKGRJkZBWWmNkRGJSTWksy8ORyj37ux0nLdZfT8gOO/MyMMPHJ55Z601RuXk5KihoWHaemtrq1JSUiT9t7Tv3btXt2/flq+vr3bs2KGKioq/PSTln7x+/VqRkZGuig0AANxoaGhIERERpmO4DYUcljQ5OSm73S5/f/+fngw6E/87YXRoaIjros8h5uwezNk9mLN7MGf3matZO51OjY2NKTw8XF5ef84XynPICizJy8trzt9ZBwQE8ILvBszZPZizezBn92DO7jMXsw4MDHTp3/MEf85bDwAAAOA3RCEHAAAADKKQA79o/vz5Ki0t/aWTTPHrmLN7MGf3YM7uwZzdh1m7Fid1AgAAAAaxQw4AAAAYRCEHAAAADKKQAwAAAAZRyAEAAACDKOTADL18+VK5ubmKjo6Wr6+vFi9erNLSUjkcDtPRLOfQoUNau3atFixYoIULF5qOYxnV1dWKjo6Wj4+PEhISdPfuXdORLKe9vV1bt25VeHi4bDabLl68aDqSJZWVlSkpKUn+/v4KCQlRZmamnj59ajqW5dTU1Cg+Pn7qy4CSk5N17do107EsgUIOzNCTJ080OTmp2tpa9ff3q7KyUqdPn1ZJSYnpaJbjcDiUlZWlvLw801Es4/z58yoqKtKBAwf08OFDrV+/Xunp6RocHDQdzVLGx8e1fPlynTp1ynQUS7tz547y8/PV2dmplpYWffv2TWlpaRofHzcdzVIiIiJ05MgRdXd3q7u7Wxs3blRGRob6+/tNR/N4XPYQcKHy8nLV1NRoYGDAdBRLqq+vV1FRkT5+/Gg6isdbs2aNVq1apZqamqm1pUuXKjMzU2VlZQaTWZfNZlNzc7MyMzNNR7G8kZERhYSE6M6dO9qwYYPpOJYWFBSk8vJy5ebmmo7i0dghB1xodHRUQUFBpmMAP+VwOPTgwQOlpaV9t56WlqaOjg5DqQDXGR0dlSRej+fQxMSEmpqaND4+ruTkZNNxPN5/TAcArOL58+c6efKkjh07ZjoK8FPv37/XxMSEQkNDv1sPDQ3V27dvDaUCXMPpdKq4uFjr1q1TXFyc6TiW09fXp+TkZH358kV+fn5qbm7WsmXLTMfyeOyQAz84ePCgbDbbT3+6u7u/e47dbtfmzZuVlZWl3bt3G0ruWWYyZ7iWzWb77rbT6Zy2BniagoICPXr0SOfOnTMdxZKWLFminp4edXZ2Ki8vT9nZ2Xr8+LHpWB6PHXLgBwUFBdq+fftPH7No0aKp3+12u1JTU5WcnKwzZ87McTrr+NU5w3WCg4M1b968abvh7969m7ZrDniSwsJCXb58We3t7YqIiDAdx5K8vb0VExMjSUpMTFRXV5dOnDih2tpaw8k8G4Uc+EFwcLCCg4P/1WPfvHmj1NRUJSQkqK6uTl5efOj0b/3KnOFa3t7eSkhIUEtLi7Zt2za13tLSooyMDIPJgJlxOp0qLCxUc3Oz2traFB0dbTrSH8PpdOrr16+mY3g8CjkwQ3a7XSkpKYqKilJFRYVGRkam7gsLCzOYzHoGBwf14cMHDQ4OamJiQj09PZKkmJgY+fn5mQ3noYqLi7Vz504lJiZOfbozODioPXv2mI5mKZ8+fdKzZ8+mbr948UI9PT0KCgpSVFSUwWTWkp+fr7Nnz+rSpUvy9/ef+vQnMDBQvr6+htNZR0lJidLT0xUZGamxsTE1NTWpra1N169fNx3N43HZQ2CG6uvrtWvXrr+9j38r18rJyVFDQ8O09dbWVqWkpLg/kEVUV1fr6NGjGh4eVlxcnCorK7lEnIu1tbUpNTV12np2drbq6+vdH8ii/unch7q6OuXk5Lg3jIXl5ubq1q1bGh4eVmBgoOLj47V//35t2rTJdDSPRyEHAAAADOKAVwAAAMAgCjkAAABgEIUcAAAAMIhCDgAAABhEIQcAAAAMopADAAAABlHIAQAAAIMo5AAAAIBBFHIAAADAIAo5AAAAYBCFHADw2xsZGVFYWJgOHz48tXb//n15e3vrxo0bBpMBwOzZnE6n03QIAAD+n6tXryozM1MdHR2KjY3VypUrtWXLFlVVVZmOBgCzQiEHAHiM/Px83bx5U0lJSert7VVXV5d8fHxMxwKAWaGQAwA8xufPnxUXF6ehoSF1d3crPj7edCQAmDWOIQcAeIyBgQHZ7XZNTk7q1atXpuMAgEuwQw4A8AgOh0OrV6/WihUrFBsbq+PHj6uvr0+hoaGmowHArFDIAQAeYd++fbpw4YJ6e3vl5+en1NRU+fv768qVK6ajAcCscMgKAOC319bWpqqqKjU2NiogIEBeXl5qbGzUvXv3VFNTYzoeAMwKO+QAAACAQeyQAwAAAAZRyAEAAACDKOQAAACAQRRyAAAAwCAKOQAAAGAQhRwAAAAwiEIOAAAAGEQhBwAAAAyikAMAAAAGUcgBAAAAgyjkAAAAgEEUcgAAAMCgvwCsuGjkaMi1TAAAAABJRU5ErkJggg==",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      " 122  -+-+- 25.07383900000003\n",
      " 123  -+-+- 24.907939000000006\n",
      " 124  -+-+- 24.78874900000006\n",
      " 125  -+-+- 24.77304900000002\n",
      " 126  -+-+- 24.75823900000003\n",
      " 127  -+-+- 24.755359000000027\n",
      " 128  -+-+- 24.754819000000083\n",
      " 129  -+-+- 24.754729000000083\n",
      " 130  -+-+- 24.754714000000064\n",
      " 131  -+-+- 24.754714000000046\n",
      " 132  -+-+- 24.754714000000046\n",
      " 133  -+-+- 24.754714000000046\n",
      " 134  -+-+- 24.754714000000046\n",
      " 135  -+-+- 24.754283999999963\n",
      " 136  -+-+- 24.75411400000013\n",
      " 137  -+-+- 24.754084000000077\n",
      " 138  -+-+- 24.75408400000006\n",
      " 139  -+-+- 24.754078000000074\n",
      " 140  -+-+- 24.754078000000074\n",
      " 141  -+-+- 24.752764000000017\n",
      " 142  -+-+- 24.752564000000028\n",
      " 143  -+-+- 24.751751999999925\n",
      " 144  -+-+- 24.751672000000056\n",
      " 145  -+-+- 24.751666000000046\n",
      " 146  -+-+- 24.751666000000046\n",
      " 147  -+-+- 24.751666000000046\n",
      " 148  -+-+- 24.751666000000046\n",
      " 149  -+-+- 24.751666000000046\n",
      " 150  -+-+- 24.751666000000046\n",
      " 151  -+-+- 24.751666000000046\n",
      " 152  -+-+- 24.75166600000003\n",
      " 153  -+-+- 24.751663000000047\n",
      " 154  -+-+- 24.751663000000047\n",
      " 155  -+-+- 24.751663000000047\n",
      " 156  -+-+- 24.751663000000047\n",
      " 157  -+-+- 24.751663000000047\n",
      " 158  -+-+- 24.751663000000047\n",
      " 159  -+-+- 24.751663000000015\n",
      " 160  -+-+- 24.751663000000015\n",
      " 161  -+-+- 24.751663000000015\n",
      " 162  -+-+- 24.751663000000015\n",
      " 163  -+-+- 24.751663000000015\n",
      " 164  -+-+- 24.751663000000015\n",
      " 165  -+-+- 24.751663000000015\n",
      " 166  -+-+- 24.751660000000044\n",
      " 167  -+-+- 24.751660000000044\n",
      " 168  -+-+- 24.751660000000044\n",
      " 169  -+-+- 24.751660000000044\n",
      " 170  -+-+- 24.751660000000044\n",
      " 171  -+-+- 24.751660000000044\n",
      " 172  -+-+- 24.751651000000102\n",
      " 173  -+-+- 24.75165099999993\n",
      " 174  -+-+- 24.75164399999992\n",
      " 175  -+-+- 24.75164399999992\n",
      " 176  -+-+- 24.751636000000083\n",
      " 177  -+-+- 24.751636000000026\n",
      " 178  -+-+- 24.751636000000026\n",
      " 179  -+-+- 24.751636000000026\n",
      " 180  -+-+- 24.751636000000026\n",
      " 181  -+-+- 24.751636000000026\n",
      " 182  -+-+- 24.75163600000002\n",
      " 183  -+-+- 24.75163600000002\n",
      " 184  -+-+- 24.75163600000002\n",
      " 185  -+-+- 24.75163400000004\n",
      " 186  -+-+- 24.75163400000004\n",
      " 187  -+-+- 24.75163400000004\n",
      " 188  -+-+- 24.751630000000045\n",
      " 189  -+-+- 24.751630000000045\n",
      " 190  -+-+- 24.751630000000045\n",
      " 191  -+-+- 24.751630000000045\n",
      " 192  -+-+- 24.751630000000045\n",
      " 193  -+-+- 24.751630000000045\n",
      " 194  -+-+- 24.751630000000045\n",
      " 195  -+-+- 24.751630000000045\n",
      " 196  -+-+- 24.751630000000045\n",
      " 197  -+-+- 24.751630000000045\n",
      " 198  -+-+- 24.751630000000045\n",
      " 199  -+-+- 24.751630000000045\n",
      " 200  -+-+- 24.751630000000045\n",
      " The best chromosome is 440303141802186317395104498998996263639811610100\n",
      " Encoded coefficientes: (4.030314, -8.021863, -7.395104, 9.899899, 2.636398, -1.6101) \n",
      " Total cost =  40000 chromosomes\n",
      " Final error =  24.751630000000045 \n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Decoded coefficients: Intercept 4.030314, slope -8.021863, quadratic -7.395104, cubic 9.899899, quartic 2.636398, quintic -1.6101\n",
      "Polynomial regression coefficients: Intercept 3.9999999999999973, slope -2.98333333333332, quadratic -4.79166666666666, cubic 3.04166666666666, quartic 1.2916666666666654, quintic -0.5583333333333326\n",
      "Encoded coefficients: Intercept 4.030314, slope -8.021863, quadratic -7.395104, cubic 9.899899, quartic 2.636398, quintic -1.6101\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"
    },
    {
     "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": [
      "Elapsed time: 0:00:04.283227\n"
     ]
    }
   ],
   "source": [
    "# Program Polynomial_The_m_signature2.py\n",
    "# This program uses pretends to give to la Evolución a hint to find perfection.\n",
    "# It is a genetic algorithm to find the polynomial \n",
    "# of fifth degree that best fits a set of 6 points.\n",
    "# The coefficients are represented by a chromosome, \n",
    "# which is a string of digits.\n",
    "# The decoding function must divide the chromosome into parts, \n",
    "# and decode each one apart as one coefficient.\n",
    "# We consider numbers of the form -3.244025\n",
    "# with a sign that could be positive or negative, \n",
    "# and a decimal point in the second place of the encoding chromosome.\n",
    "# The error of a chromosome is the sum of the vertical distances \n",
    "# of the points to the polynomial it encodes.\n",
    "# The Genetic algorithm must minimize the error, \n",
    "# (which is equivalent to maximizing the fitness).\n",
    "# In this program, the error has two components. \n",
    "# The first one is the sum of the vertical distances of the points to the polynomial it encodes.\n",
    "# The second one comes from the m-signature of the expected curve,\n",
    "# which is the sequence of the signs of the m-th derivatives of the curve at the points.\n",
    "# If the derivative changes from + to -, \n",
    "# we have a maximum, and if it changes from - to +, we have a minimum. \n",
    "# Our set of points is [(-2, 5), (-1, 1), (0, 4), (1, 0), (2, 6), (3, 3)].\n",
    "# The expected curve is a polynomial of fifth degree that best fits the points,\n",
    "# and has the same m-signature at the points: \n",
    "# it decreases from x=-2 to x=-1, the derivative is -\n",
    "# increases from x=-1 to x=0, the derivative is +,\n",
    "# decreases from x=0 to x=1, the derivative is -\n",
    "# increases from x=1 to x=2, the derivative is +, and\n",
    "# decreases from x=2 to x=3, the derivative is -.\n",
    "# The d_signature is the pattern of the derivative of the expected curve.\n",
    "# It is - + - + -.\n",
    "# Since a polynomial is continuous and derivable, \n",
    "# the m-signature of the expected curve is mMmM,\n",
    "# where m stands for a minimum and M for a maximum. \n",
    "# This says that\n",
    "# the curve has a minimum in within the interval (-2, -0), m is added to the signature,\n",
    "# a maximum in within the interval (-1, 1), M is added to the signature,\n",
    "# a minimum in within the interval (0, 2), m is added to the signature,\n",
    "# a maximum in within the interval (1, 3), M is added to the signature.\n",
    "# The signature is mMmM, and the expected curve must have the same signature.\n",
    "# The error of a chromosome is the sum of the vertical distances \n",
    "# of the points to the polynomial it encodes, \n",
    "# plus a penalty if the d_signature\n",
    "# of the polynomial it encodes does not match the d_signature of the expected curve.\n",
    "# The purpose of the second component is to give a hint to la Evolución to find perfection.\n",
    "# We propose here to rely on the d_signature using only the given points, and not the whole curve.\n",
    "# We observe here the la Evolución of the shape of the evolving polynomial.\n",
    "# Developed with the assistance of the AI of Visual Studio Code.\n",
    "# An old version of a GA developed with the help of Gemini was reused and updated.\n",
    "\n",
    "\n",
    "from datetime import datetime, timedelta\n",
    "import datetime\n",
    "import time\n",
    "import random\n",
    "import numpy as np\n",
    "from numpy.polynomial import Polynomial\n",
    "import matplotlib.pyplot as plt # Import matplotlib for plotting\n",
    "\n",
    "\n",
    "start_time = time.time() # Record the start time\n",
    "# The d_signature of the expected curve, which is the pattern of the derivative of the expected curve.\n",
    "expected_d_signature = \"-+-+-\"\n",
    "# The weight of the m-signature error in the total error.\n",
    "d_signature_error_weight = 500 \n",
    "#Task to be done\n",
    "number_of_generations = 200\n",
    "\n",
    "xArray =  [-2, -1, 0, 1, 2, 3]\n",
    "yArray =  [5,   1, 4, 0, 6, 3]\n",
    "\n",
    "alphabet = '0123456789'\n",
    "# Chromosome encoding for one of 6 coefficients, \n",
    "# each one with a length of 5 chars.\n",
    "# Encoding number as -93.24 with a sign and a decimal point.\n",
    "length_of_chromosomes = 8\n",
    "population_size = 200\n",
    "# Include cloning of the fittest\n",
    "include_clone_populationj15 = True\n",
    "# Include mutation\n",
    "include_mutate_allj15 = True\n",
    "# Include recombination\n",
    "include_crossover_allj15 = False\n",
    "mutation_rate = 0.05\n",
    "recombination_rate = 0.0\n",
    "# Size of the sampled groups from which the best \n",
    "# is chosen as a parent for the next generation.\n",
    "tournament_size = 5\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_generation = True\n",
    "print_parameters = True\n",
    "print_d_signature = False\n",
    "show_graph = True\n",
    "    \n",
    "\n",
    "def print_parametersj15():\n",
    "    print(f\"Lab: la Evolución finds the polynomial of minimal error\")\n",
    "    print(f\"Purpose: Use a Genetic Algorithm (MAX = selection of the fittest, mutation and recombination) to find the coefficients of a polynomial that best fits a set of points.\")\n",
    "    print(\"Hint 1 to be tested: consider only numbers of the form -3.244025 with a sign that could be positive or negative, and a decimal point in the second place of the encoding chromosome.\")\n",
    "    print(\"Hint 2: the error of a chromosome is the sum of the vertical distances of the points to the polynomial it encodes, plus a penalty if the d_signature of the polynomial it encodes does not match the d_signature of the expected curve.\")\n",
    "    print(f\"Date of Experiment  = {datetime.datetime.now()}\")\n",
    "    print(f\"expected_d_signature = {expected_d_signature}\")\n",
    "    print(f\"d_signature_error_weight = {d_signature_error_weight}\")\n",
    "    print(f\"number_of_generations = {number_of_generations}\")\n",
    "    print(f\"length_of_chromosomes = {length_of_chromosomes}\")\n",
    "    print(f\"alphabet =  {alphabet}\")\n",
    "    print(f\"Points = {list(zip(xArray, yArray))}\")\n",
    "    print(f\"population_size = {population_size}\")\n",
    "    print(f\"include_clone_populationj15 = {include_clone_populationj15}\")\n",
    "    print(f\"include_mutate_allj15 = {include_mutate_allj15}\")\n",
    "    print(f\"include_crossover_allj15 = {include_crossover_allj15}\")\n",
    "    if include_mutate_allj15:\n",
    "        print(f\"mutation_rate = {mutation_rate}\")\n",
    "    if include_crossover_allj15:\n",
    "        print(f\"recombination_rate = {recombination_rate}\")\n",
    "    if include_clone_populationj15:\n",
    "        print(f\"print_best_fitness = {print_best_fitness}\")\n",
    "\n",
    "def draw_points_and_polynomialj15(xNumpyArray, yNumpyArray):\n",
    "    \"\"\"Draws the original data points, finds and draws the \n",
    "    regression polynomial defined by the coefficients.\"\"\"\n",
    "    \n",
    "    # 2. Fit a 5th-degree (quintic) polynomial\n",
    "    # .fit() returns a Polynomial instance\n",
    "    p_fitted = Polynomial.fit(xNumpyArray, yNumpyArray, deg=5)\n",
    "\n",
    "    # 3. Predict values for visualization\n",
    "    x_new = np.linspace(-2,3, 100) # Generate 100 points between 0 and 6 for a smooth curve\n",
    "    y_new = p_fitted(x_new)\n",
    "    b_0, b_1, b_2, b_3, b_4, b5 = p_fitted.coef\n",
    "\n",
    "    # 4. Plot results\n",
    "    plt.scatter(xNumpyArray, yNumpyArray, label='Data Points')\n",
    "    plt.xlabel('x')\n",
    "    plt.ylabel('y')\n",
    "    plt.plot(x_new, y_new, label=f'Quintic Fit: y = {b_0:.2f} + {b_1:.2f}x + {b_2:.2f}x^2 + {b_3:.2f}x^3 + {b_4:.2f}x^4 + {b5:.2f}x^5', color='green')\n",
    "    plt.title(' Data Points and Quintic Fit by numpy.polynomial.Polynomial.fit()')\n",
    "    plt.legend()\n",
    "    plt.show()\n",
    "    return p_fitted.coef\n",
    "\n",
    "\n",
    "\n",
    "def create_populationj15(population_size, length_of_chromosomes, alphabet):\n",
    "    \"\"\"Creates a new population with random chromosomes.\"\"\"\n",
    "    # print(\"create_populationj15(population_size, target_sequence, alphabet)\")\n",
    "    population = []\n",
    "    for _ in range(population_size):\n",
    "        random_string1 = ''.join(random.choice(alphabet) for _ in range(length_of_chromosomes))\n",
    "        random_string2 = ''.join(random.choice(alphabet) for _ in range(length_of_chromosomes))\n",
    "        random_string3 = ''.join(random.choice(alphabet) for _ in range(length_of_chromosomes))\n",
    "        random_string4 = ''.join(random.choice(alphabet) for _ in range(length_of_chromosomes))\n",
    "        random_string5 = ''.join(random.choice(alphabet) for _ in range(length_of_chromosomes))\n",
    "        random_string6 = ''.join(random.choice(alphabet) for _ in range(length_of_chromosomes))\n",
    "        random_string = random_string1 + random_string2 + random_string3 + random_string4 + random_string5 + random_string6\n",
    "        population.append(random_string)\n",
    "    # print(\"initial population\")\n",
    "    # print(population)\n",
    "    return population\n",
    "\n",
    "# Decode a part of the chromosome into a coefficient of the polynomial.\n",
    "def decoderOldj15(s):\n",
    "    ''' The input is a number as string, outputs the number as a float. \n",
    "        We consider numbers of the form 93.24 with a sign that could be positive or negative,\n",
    "    '''\n",
    "    l = len(s) \n",
    "    # The first char encodes for the sign, \n",
    "    sign = 1\n",
    "    if  float(s[0]) % 2 == 1:\n",
    "        sign = -1\n",
    "    # The remaining chars encode for the number itself, \n",
    "    # without the decimal point nor sign.\n",
    "    sn = s[1:l]\n",
    "    # The point is inserted after the second char, so that we have numbers of the form 93.24\n",
    "    sn = sn[:2] + \".\" + sn[2:]\n",
    "    # Convert the string to a number\n",
    "    n = float(sn)\n",
    "    return sign * n\n",
    "\n",
    "# Decode a part of the chromosome into a coefficient of the polynomial.\n",
    "def decoderj15(s):\n",
    "    ''' The input is a number as string, outputs the number as a float. \n",
    "        We consider numbers of the form 93.24 with a sign that could be positive or negative,\n",
    "    '''\n",
    "    l = len(s) \n",
    "    # The first char encodes for the sign, \n",
    "    sign = 1\n",
    "    if  float(s[0]) % 2 == 1:\n",
    "        sign = -1\n",
    "    # The remaining chars encode for the number itself, \n",
    "    # without the decimal point nor sign.\n",
    "    sn = s[1:l]\n",
    "    # The point is inserted after the first char, so that we have numbers of the form -3.24\n",
    "    sn = sn[:1] + \".\" + sn[1:]\n",
    "    # Convert the string to a number\n",
    "    n = float(sn)\n",
    "    return sign * n\n",
    "\n",
    "\n",
    "def decodeFullCromosomej15(chromosome, length_of_chromosomes):\n",
    "    \"\"\"Decodes the full chromosome into the coefficients of the polynomial.\"\"\"\n",
    "    \"\"\"The chromosome is divided into 5 parts, \n",
    "        each one encoding for a coefficient of the polynomial.\"\"\"\n",
    "    chro0 = chromosome[0:length_of_chromosomes]\n",
    "    chro1 = chromosome[length_of_chromosomes:2*length_of_chromosomes]\n",
    "    chro2 = chromosome[2*length_of_chromosomes:3*length_of_chromosomes]\n",
    "    chro3 = chromosome[3*length_of_chromosomes:4*length_of_chromosomes]\n",
    "    chro4 = chromosome[4*length_of_chromosomes:5*length_of_chromosomes]\n",
    "    chro5 = chromosome[5*length_of_chromosomes:6*length_of_chromosomes]\n",
    "    a_0 = decoderj15(chro0)\n",
    "    a_1 = decoderj15(chro1)\n",
    "    a_2 = decoderj15(chro2)\n",
    "    a_3 = decoderj15(chro3)\n",
    "    a_4 = decoderj15(chro4)\n",
    "    a_5 = decoderj15(chro5)\n",
    "    # print(f\"Chromosome: {chromosome}\")\n",
    "    # print(f\"Coefficients: Intercept {a_0}, slope {a_1}, quadratic {a_2}, cubic {a_3}, quartic {a_4}, quintic {a_5}\")\n",
    "    # print()\n",
    "    return a_0, a_1, a_2, a_3, a_4, a_5\n",
    "\n",
    "\n",
    "\n",
    "def calculate_geometrical_errorj15(chromosome, xArray, yArray, length_of_chromosomes):\n",
    "    \"\"\"Calculates the error of a chromosome.\n",
    "        A chromosome encodes for the coefficients of a polynomial of fith degree.\n",
    "        The error of a chromosome is the sum of \n",
    "        the vertical distances of the points to the polynomial it encodes.\n",
    "    \"\"\"\n",
    "    #  print(\"\\n calculate_geometrical_errorj15(chromosome, xArray, yArray)\")\n",
    "    a_0, a_1, a_2, a_3, a_4, a_5 = decodeFullCromosomej15(chromosome, length_of_chromosomes) \n",
    "    error = 0\n",
    "    for i in range(len(xArray)):\n",
    "        x = xArray[i]\n",
    "        y = yArray[i]\n",
    "        # Calculate the predicted y value based on the coefficients of the polynomial\n",
    "        predicted_y = a_0 + a_1 * x + a_2 * x**2 + a_3 * x**3 + a_4 * x**4 + a_5 * x**5\n",
    "        # Calculate the error as the quadratic difference \n",
    "        # between predicted and y value\n",
    "        # error += (predicted_y - y)**2\n",
    "        # Calculate the error as the distance between predicted and y value\n",
    "        error += abs(predicted_y - y)\n",
    "    return error\n",
    "\n",
    "def calculate_d_signaturej15(chromosome, xArray, yArray, length_of_chromosomes):\n",
    "    \"\"\"Calculates the d-signature of the polynomial encoded by the chromosome.\n",
    "        The d-signature of a curve is the sequence of the signs of the derivative of the curve at the points.\n",
    "        If the derivative changes from + to -, we have a maximum, and if it changes from - to +, we have a minimum. \n",
    "        Our set of points is [(-2, 5), (-1, 1), (0, 4), (1, 0), (2, 6), (3, 3)].\n",
    "        The expected curve is a polynomial of fifth degree that best fits the points,\n",
    "        and has the same m-signature at the points: \n",
    "        it decreases from x=-2 to x=-1, the derivative is -\n",
    "        increases from x=-1 to x=0, the derivative is +,\n",
    "        decreases from x=0 to x=1, the derivative is -\n",
    "        increases from x=1 to x=2, the derivative is +, and\n",
    "        decreases from x=2 to x=3, the derivative is -.\n",
    "        The pattern of the derivative of the expected curve is - + - + -.\n",
    "        Since a polynomial is continuous and derivable, \n",
    "        the m-signature of the expected curve is mMmM,\n",
    "        where m stands for a minimum and M for a maximum. \n",
    "    \"\"\"\n",
    "    # This function can be implemented by calculating if the expected function is increasing or decreasing at each point. \n",
    "    # Then we can compare it with the expected m-signature and calculate an error based on how many signs are different.\n",
    "    a_0, a_1, a_2, a_3, a_4, a_5 = decodeFullCromosomej15(chromosome, length_of_chromosomes) \n",
    "    # Calculate the predicted y value at each x-coordinate based on the coefficients of the polynomial\n",
    "    predicted_y = a_0 + a_1 * np.array(xArray) + a_2 * np.array(xArray)**2 + a_3 * np.array(xArray)**3 + a_4 * np.array(xArray)**4 + a_5 * np.array(xArray)**5\n",
    "    # Calculate the sign of the first derivative at each point\n",
    "    d_signature = \"\"\n",
    "    for i in range(len(xArray)-1):\n",
    "        x1 = xArray[i]\n",
    "        x2 = xArray[i+1]\n",
    "        y1 = predicted_y[i]\n",
    "        y2 = predicted_y[i+1]\n",
    "        if y2 > y1:\n",
    "            sign = '+'\n",
    "        elif y2 < y1:\n",
    "            sign = '-'\n",
    "        else:\n",
    "            sign = '0'\n",
    "        d_signature += sign\n",
    "        # print(f\"At x={x1} to x={x2}, the predicted function is {'increasing' if sign == '+' else 'decreasing' if sign == '-' else 'constant'}\")\n",
    "    if print_d_signature:\n",
    "        print(f\"d_signature = {d_signature}\")\n",
    "    \n",
    "    return d_signature\n",
    "\n",
    "def calculate_d_signature_errorj15(chromosome, xArray, yArray, length_of_chromosomes):\n",
    "    \"\"\"Calculates the error of the d-signature error of the polynomial encoded by the chromosome.\n",
    "        The d-signature of a curve is the sequence of the signs of the derivative of the curve at the points.\n",
    "        If the derivative changes from + to -, we have a maximum, and if it changes from - to +, we have a minimum. \n",
    "        Our set of points is [(-2, 5), (-1, 1), (0, 4), (1, 0), (2, 6), (3, 3)].\n",
    "        The expected curve is a polynomial of fifth degree that best fits the points,\n",
    "        and has the same m-signature at the points: \n",
    "        it decreases from x=-2 to x=-1, the derivative is -\n",
    "        increases from x=-1 to x=0, the derivative is +,\n",
    "        decreases from x=0 to x=1, the derivative is -\n",
    "        increases from x=1 to x=2, the derivative is +, and\n",
    "        decreases from x=2 to x=3, the derivative is -.\n",
    "        The pattern of the derivative of the expected curve is - + - + -.\n",
    "        Since a polynomial is continuous and derivable, \n",
    "        the m-signature of the expected curve is mMmM,\n",
    "        where m stands for a minimum and M for a maximum. \n",
    "    \"\"\"\n",
    "    d_signature = calculate_d_signaturej15(chromosome, xArray, yArray, length_of_chromosomes)\n",
    "    # The d-signature error is the number of signs that are different from the expected d_signature.\n",
    "    d_signature_error = sum(1 for a, b in zip(d_signature, expected_d_signature) if a != b)\n",
    "\n",
    "    return d_signature_error\n",
    "\n",
    "\n",
    "def calculate_all_errorsj15(population, xArray, yArray, length_of_chromosomes,  d_signature_error_weight):\n",
    "    # print(\"\\n*calculate_all_errorsj15(population, target_sequence)\")\n",
    "    \"\"\"Calculates the error of all chromosomes in the population.\n",
    "        The error of a chromosome is the sum of the geometrical error and the m-signature error,\n",
    "        with a weight for the m-signature error to give it more or less importance.\n",
    "        Developed almost entirely by the AI of Visual Studio Code.\"\"\"\n",
    "    g_errors = [calculate_geometrical_errorj15(chromosome, xArray, yArray, length_of_chromosomes) for chromosome in population]\n",
    "    d_signature_errors = [calculate_d_signature_errorj15(chromosome, xArray, yArray, length_of_chromosomes) for chromosome in population]\n",
    "    # The total error is the sum of the geometrical error and the d-signature error, with a weight for the d-signature error to give it more or less importance.\n",
    "    errors = [g + d_signature_error_weight * d for g, d in zip(g_errors, d_signature_errors)]\n",
    "    # print(\"errors: \", errors)\n",
    "    return errors\n",
    "\n",
    "def select_the_least_errorj15(population, xArray, yArray, length_of_chromosomes, d_signature_error_weight):\n",
    "    \"\"\"Selects the best chromosome with minimal error for reproduction.\"\"\"\n",
    "    errors = calculate_all_errorsj15(population, xArray, yArray, length_of_chromosomes, d_signature_error_weight)\n",
    "    smallest_error = min(errors)\n",
    "    best_chromosome_index = errors.index(smallest_error)\n",
    "    best_chromosome = population[best_chromosome_index]\n",
    "    # print(\"\\n*select_the_least_errorj15(population)\")\n",
    "    # print(\"smallest_error = \", smallest_error)\n",
    "    # print(\"The chro = \", best_chromosome )\n",
    "    return smallest_error, best_chromosome\n",
    "\n",
    "def clone_populationj15(best_chromosome, population_size):\n",
    "    \"\"\"Creates a new population by cloning the best chromosome.\"\"\"\n",
    "    return [best_chromosome] * population_size\n",
    "\n",
    "\n",
    "def mutatej15(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_allj15(population, mutation_rate, alphabet):\n",
    "    \"\"\"Mutates all chromosomes in the population.\"\"\"\n",
    "    mutated_population = []\n",
    "    for chromosome in population:\n",
    "        mutated_chromosome = mutatej15(chromosome, mutation_rate, alphabet)\n",
    "        mutated_population.append(mutated_chromosome)\n",
    "    return mutated_population\n",
    "\n",
    "def crossoverj15(parent1, parent2, length_of_chromosomes, recombination_rate):\n",
    "    \"\"\"Performs crossover between two parent chromosomes.\"\"\"\n",
    "    if random.random() < recombination_rate:\n",
    "        crossover_point = random.randint(0, length_of_chromosomes)\n",
    "        return parent1[:crossover_point] + parent2[crossover_point:]\n",
    "    else:\n",
    "        return parent1\n",
    "\n",
    "def crossover_allj15(population, length_of_chromosomes, 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 = crossoverj15(parent1, parent2, length_of_chromosomes, recombination_rate)\n",
    "        recombinant_population.append(child)\n",
    "    return recombinant_population\n",
    "\n",
    "\n",
    "\n",
    "def run_one_generationj15(population, xArray, yArray, mutation_rate, recombination_rate, alphabet, length_of_chromosomes, m_signature_error_weight):\n",
    "    \"\"\"Runs one generation of the genetic algorithm.\"\"\"\n",
    "    # Calculate fitness scores for the current population\n",
    "    smallest_error, best_chromosome  = select_the_least_errorj15(population, xArray, yArray, length_of_chromosomes, m_signature_error_weight)\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_populationj15:\n",
    "        new_population = clone_populationj15(best_chromosome, population_size)\n",
    "    if include_mutate_allj15:\n",
    "        new_population = mutate_allj15(new_population, mutation_rate, alphabet)\n",
    "    if include_crossover_allj15:\n",
    "        new_population = crossover_allj15(new_population, length_of_chromosomes, recombination_rate)\n",
    "    return smallest_error, best_chromosome, new_population\n",
    "\n",
    "\n",
    "\n",
    "def plot_functionj15(g_values, 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",
    "def plot_graphsj15(xArray, yArray, best_chromosome, length_of_chromosomes, generation, new_best_error):\n",
    "    # Plot the original data and the polynomial defined by the best chromosome.\n",
    "    a_0, a_1, a_2, a_3, a_4, a_5 = decodeFullCromosomej15(best_chromosome, length_of_chromosomes)  \n",
    "    x_new = np.linspace(-2,3, 100) # Generate 100 points between -2 and 3 for a smooth curve\n",
    "    predicted_y = a_0 + a_1 * x_new + a_2 * x_new**2 + a_3 * x_new**3 + a_4 * x_new**4 + a_5 * x_new**5\n",
    "    plt.scatter(xArray, yArray, label='Data Points')\n",
    "    plt.plot(x_new, predicted_y, label=f'Best Chromosome Fit: y = {a_0:.2f} + {a_1:.2f}x + {a_2:.2f}x^2 + {a_3:.2f}x^3 + {a_4:.2f}x^4 + {a_5:.2f}x^5', color='blue')\n",
    "    plt.xlabel('x')\n",
    "    plt.ylabel('y')\n",
    "    plt.title(f'Data Points and Best Chromosome Fit by Generation {generation}. Error = {new_best_error:.2f}')\n",
    "    plt.legend()\n",
    "    plt.grid(True)\n",
    "    plt.show()\n",
    "\n",
    "def taskj15( xArray, yArray, mutation_rate, recombination_rate, alphabet,  length_of_chromosomes, d_signature_error_weight):\n",
    "    population = create_populationj15(population_size, length_of_chromosomes, alphabet)\n",
    "    # print(population)\n",
    "    generation = 0\n",
    "    best_chromosome = ''\n",
    "    best_fitness = 0\n",
    "    start_time = time.time()\n",
    "    smallest_error_history = [] # List to store best fitness of each generation\n",
    "    old_best_error = float('inf') # Store the best error from the previous generation\n",
    "    new_best_error = float('inf') # Store the best error from the current generation\n",
    "    if print_generation:\n",
    "        print(f\"Expected d_signature: {expected_d_signature}\")\n",
    "        print(\"Generation, best_d_signature and best_fitness\")\n",
    "    while generation < number_of_generations:\n",
    "        generation += 1\n",
    "        smallest_error, best_chromosome, population = run_one_generationj15(population, xArray,yArray, mutation_rate, recombination_rate, alphabet, length_of_chromosomes, d_signature_error_weight)\n",
    "        best_d_signature = calculate_d_signaturej15(best_chromosome, xArray, yArray, length_of_chromosomes)\n",
    "        if print_generation:\n",
    "            print(f\" {generation}  {best_d_signature} {smallest_error}\")\n",
    "        smallest_error_history.append(smallest_error)\n",
    "        new_best_error = smallest_error\n",
    "        if new_best_error + 1 < old_best_error:\n",
    "            old_best_error = new_best_error\n",
    "            print(f\"Generation {generation}: Error decreased to {new_best_error}. Best chromosome: {best_chromosome}\")\n",
    "            plot_graphsj15(xArray, yArray, best_chromosome, length_of_chromosomes, generation, new_best_error)\n",
    "    # print(f\"\\nTarget sequence matched in generation {generation}\")\n",
    "    # print(f\"Final chromosome: {best_chromosome}\")\n",
    "    totalCost = population_size * generation\n",
    "    return  best_chromosome, totalCost, smallest_error_history\n",
    "\n",
    "def mainj15(xArray, yArray, mutation_rate, recombination_rate, alphabet, length_of_chromosomes):\n",
    "    print_parametersj15()\n",
    "    print(\"Total cost = population size * number of generations\")\n",
    "    best_chromosome, totalCost, smallest_error_history = taskj15(xArray, yArray, mutation_rate, recombination_rate, alphabet, length_of_chromosomes, d_signature_error_weight)\n",
    "    final_error = smallest_error_history[-1]\n",
    "    print(f\" The best chromosome is {best_chromosome}\" )\n",
    "    coefficients = decodeFullCromosomej15(best_chromosome, length_of_chromosomes)\n",
    "    print(f\" Encoded coefficientes: {coefficients} \" )\n",
    "    print(f\" Total cost =  {totalCost} chromosomes\")\n",
    "    print(f\" Final error =  {final_error} \")\n",
    "\n",
    "    # Plot the fitness history \n",
    "    g_values = list(range(1, len(smallest_error_history) + 1))\n",
    "    plot_functionj15(g_values, smallest_error_history, xlabel='Generation', ylabel='SmallestError', title='Smallest Error Over Generations')\n",
    "    # The best chromosome encodes for the coefficients of the polynomial that best fits the data points\"\n",
    "    b_0, b_1, b_2, b_3, b_4, b5 = decodeFullCromosomej15(best_chromosome, length_of_chromosomes)\n",
    "    print(f\"Decoded coefficients: Intercept {b_0}, slope {b_1}, quadratic {b_2}, cubic {b_3}, quartic {b_4}, quintic {b5}\")\n",
    "    # Calculate the predicted y value based on the coefficients of the polynomial\n",
    "    our_polynomial = b_0 + b_1 * np.array(xArray) + b_2 * np.array(xArray)**2 + b_3 * np.array(xArray)**3 + b_4 * np.array(xArray)**4 + b5 * np.array(xArray)**5\n",
    "    \n",
    "\n",
    "    # Perform polynomial regression\n",
    "    # Fit a polynomial of degree 5 (polynomial regression)\n",
    "    p_fitted = Polynomial.fit(xArray, yArray, deg=5)\n",
    "    a_0, a_1, a_2, a_3, a_4, a5 = p_fitted.convert().coef\n",
    "    print(f\"Polynomial regression coefficients: Intercept {a_0}, slope {a_1}, quadratic {a_2}, cubic {a_3}, quartic {a_4}, quintic {a5}\")\n",
    "    # Create the regression graph\n",
    "    x_new = np.linspace(-2,3, 100) # Generate 100 points between -2 and 3 for a smooth curve\n",
    "    y_new = p_fitted(x_new)\n",
    "\n",
    "    # The best chromosome encodes for the coefficients of the polynomial that best fits the data points\"\n",
    "    b_0, b_1, b_2, b_3, b_4, b5 = decodeFullCromosomej15(best_chromosome, length_of_chromosomes)\n",
    "    print(f\"Encoded coefficients: Intercept {b_0}, slope {b_1}, quadratic {b_2}, cubic {b_3}, quartic {b_4}, quintic {b5}\")\n",
    "    # Calculate the predicted y value based on the coefficients of the polynomial\n",
    "    our_polynomial = b_0 + b_1 * np.array(x_new ) + b_2 * np.array(x_new )**2 + b_3 * np.array(x_new )**3 + b_4 * np.array(x_new )**4 + b5 * np.array(x_new )**5\n",
    "    \n",
    "\n",
    "\n",
    "    # Plot the original data, the regression polynomial, and our polynomial\n",
    "    plt.figure(figsize=(10, 6))\n",
    "    plt.scatter(xArray, yArray, label='Observed Data')\n",
    "    plt.plot(x_new, y_new, color='red', label=f'Polynomial Regression: y = {a_0:.2f} + {a_1:.2f}x + {a_2:.2f}x^2 + {a_3:.2f}x^3 + {a_4:.2f}x^4 + {a5:.2f}x^5')\n",
    "    plt.plot(x_new,        our_polynomial, color='green', label=f'Our polynomial: y = {b_0:.2f} + {b_1:.2f}x + {b_2:.2f}x^2 + {b_3:.2f}x^3 + {b_4:.2f}x^4 + {b5:.2f}x^5')\n",
    "    plt.xlabel('Independent variable (x)')\n",
    "    plt.ylabel('Dependent variable (y)')\n",
    "    plt.title('Linear Regression and la Evolución minimize the error of the line with respect to the data points')\n",
    "    plt.legend()\n",
    "    plt.grid(True)\n",
    "    plt.show()\n",
    "\n",
    "    # Plot the original data and the regression polynomial\n",
    "    plt.figure(figsize=(10, 6))\n",
    "    plt.scatter(xArray, yArray, label='Observed Data')\n",
    "    plt.plot(x_new, y_new, color='red', label=f'Polynomial Regression: y = {a_0:.2f} + {a_1:.2f}x + {a_2:.2f}x^2 + {a_3:.2f}x^3 + {a_4:.2f}x^4 + {a5:.2f}x^5')\n",
    "    plt.xlabel('Independent variable (x)')\n",
    "    plt.ylabel('Dependent variable (y)')\n",
    "    plt.title('Linear Regression minimizes the error of the line with respect to the data points')\n",
    "    plt.legend()\n",
    "    plt.grid(True)\n",
    "    plt.show()\n",
    "\n",
    "    # Plot  our polynomial\n",
    "    plt.figure(figsize=(10, 6))\n",
    "    plt.scatter(xArray, yArray, label='Observed Data')\n",
    "    #plt.plot(xArray, regression_polynomial, color='red', label=f'Polynomial Regression: y = {a_0:.2f} + {a_1:.2f}x + {a_2:.2f}x^2 + {a_3:.2f}x^3 + {a_4:.2f}x^4 + {a5:.2f}x^5')\n",
    "    plt.plot(x_new,        our_polynomial, color='green', label=f'Our polynomial: y = {b_0:.2f} + {b_1:.2f}x + {b_2:.2f}x^2 + {b_3:.2f}x^3 + {b_4:.2f}x^4 + {b5:.2f}x^5')\n",
    "    plt.xlabel('Independent variable (x)')\n",
    "    plt.ylabel('Dependent variable (y)')\n",
    "    plt.title('la Evoluciónary Regression minimizes the error of the line with respect to the data points')\n",
    "    plt.legend()\n",
    "    plt.grid(True)\n",
    "    plt.show()\n",
    "\n",
    "\n",
    "\n",
    "    end_time = time.time()\n",
    "    # Calculate the duration of the run in seconds\n",
    "    elapsed_time = end_time - start_time\n",
    "    elapsed_time = timedelta(seconds=elapsed_time)\n",
    "    print(f\"Elapsed time: {elapsed_time}\")\n",
    "    #return best_chromosome, totalCost, best_fitness_history\n",
    " \n",
    "# Call the main function with the defined parameters\n",
    "mainj15(xArray, yArray, mutation_rate, recombination_rate, alphabet, length_of_chromosomes)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "f607af76",
   "metadata": {},
   "source": [
    "*Nuestras observaciones.*\n",
    "\n",
    "1. La población original ya tiene un exponente con la firma correcta.\n",
    "2. El proceso evolutivo intercalan saltos en medio de períodos de éxtasis. \n",
    "\n",
    "\n",
    "**Ejercicio.** Selecciona un programa sin la d-signature como pista, y añade la posibilidad de ver el progreso de la forma del polinomio en Evolución. Reporta tus observaciones. ¿Percibes una diferencia en el proceso evolutivo con la d-firma como una ayuda y sin ella?\n",
    ">\n",
    "> *Respuesta.* Seleccionamos un programa en el que los números están restringidos a la forma -1,234567. Le ordenamos que dibujara el mejor polinomio para aquellas generaciones en las que el error disminuye en una o más unidades. El código y los resultados siguen:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "51c890c7",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Lab: Evolution finds the polynomial of minimal error\n",
      "Purpose: Use a Genetic Algorithm (MAX = selection of the fittest, mutation and recombination) to find the coefficients of a polynomial that best fits a set of points.\n",
      "Hint to be tested: consider only numbers of the form -3.244025 with a sign that could be positive or negative, and a decimal point in the second place of the encoding chromosome.\n",
      "Date of Experiment  = 2026-05-05 06:50:44.797078\n",
      "number_of_generations = 200\n",
      "length_of_chromosomes = 8\n",
      "alphabet =  0123456789\n",
      "Points = [(-2, 5), (-1, 1), (0, 4), (1, 0), (2, 6), (3, 3)]\n",
      "population_size = 200\n",
      "include_clone_populationj16 = True\n",
      "include_mutate_allj16 = True\n",
      "include_crossover_allj16 = False\n",
      "mutation_rate = 0.1\n",
      "print_best_fitness = False\n",
      "Polynomial regression coefficients: Intercept 3.9999999999999973, slope -2.98333333333332, quadratic -4.79166666666666, cubic 3.04166666666666, quartic 1.2916666666666654, quintic -0.5583333333333326\n",
      "Total cost = population size * number of generations\n",
      "Generation 1: Error decreased to 152.506209. Best chromosome: 763420967275764174612789502077388028086840453523\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": [
      "Generation 2: Error decreased to 85.977631. Best chromosome: 863420967275764174612789502075385028086840453523\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Generation 3: Error decreased to 61.87812299999999. Best chromosome: 863420967275763974612789502075385028085840353523\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Generation 4: Error decreased to 48.00368400000001. Best chromosome: 863420967279763974612780512675385008085840353523\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Generation 5: Error decreased to 28.340493000000006. Best chromosome: 863890967279763971612789512675385008085040253523\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Generation 6: Error decreased to 24.572887. Best chromosome: 853890967279763971612789512675385008085040253523\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Generation 9: Error decreased to 23.559363. Best chromosome: 853890917261763971612759512675385008085000250163\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Generation 24: Error decreased to 21.865966. Best chromosome: 853254764211514671612319519682681002070100250640\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Generation 30: Error decreased to 20.829629999999987. Best chromosome: 450253414211504611206310519682681007070700250665\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Generation 31: Error decreased to 18.80061. Best chromosome: 655253414211504611106512519682681002070700230015\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Generation 34: Error decreased to 17.420802000000002. Best chromosome: 841263414232504611106515519588681002070400232055\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Generation 76: Error decreased to 16.262553. Best chromosome: 440001256205902291001734319520094000205440222480\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Generation 114: Error decreased to 15.188798999999992. Best chromosome: 240004256202924771001714919137742002785660211344\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      " The best chromosome is 240000226200401231001247519139782002873640211322\n",
      " Encoded coefficientes: (4.000022, 2.004012, -1.001247, -1.913978, 0.028736, 0.211322) \n",
      " Total cost =  40000 chromosomes\n",
      " Final error =  15.147715000000007 \n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Decoded coefficients: Intercept 4.000022, slope 2.004012, quadratic -1.001247, cubic -1.913978, quartic 0.028736, quintic 0.211322\n",
      "Encoded coefficients: Intercept 4.000022, slope 2.004012, quadratic -1.001247, cubic -1.913978, quartic 0.028736, quintic 0.211322\n"
     ]
    },
    {
     "data": {
      "image/png": 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/f7W0ZM8zROrX3e3bt6lt27YEgKKjo4U/VdweHh7UtWtXYf2EhARydXUle3t7WrJkCe3Zs4cGDhxIAKhfv35q2/H09KQmTZpQZGQkRUZGUqVKlcja2pr++++/XI+lKl+VKFGChg8fTvv27aOwsDAyNDSkjh07UvXq1WnKlCkUFRVFo0ePVrvmiIgAUEhIiFqcJUuWpEGDBtHevXtp+fLlZG1trZZnch5P1f54eHhQy5YtaefOnbRu3TpydHSksmXLUnBwMPXo0YN2795NS5YsIXNzc2rZsmWucd6+fVt0zKOjo6lz585CHiIina9nTWJjY8nX15ecnJxE29D3/Bw8eJBkMhn5+fnRxo0bac+ePdStWzedromsrCxq0qQJmZmZ0cSJEykqKoqWL19Orq6uVL58eXr79q0Q1sPDg5ydnalkyZK0cuVKOnToEJ0+fVrIy66urtS2bVvavn077dy5k16+fKlXWSOVSsnT05OmT59OBw4coL1792pN9+HDh0kqlVKNGjVo48aNFBkZSY0bNyaJREIbNmwgIqJHjx7R1q1bCQANGjSIoqOj6fz58xrje/36tZD/JkyYIJyLR48eCenTpYzS53hqorrPZactrxd23hgzZgyZm5sL9+H4+HgCQHK5nKZOnSqE69evHzk6Ogqfc95zCiqfa6LalqurK/Xp04d2795NmzdvpszMTJo6dSpJJBLq0aMH7dy5k7Zu3Uo+Pj5kZmZGsbGxQhxeXl5UunRpWrt2LR05coS2bNlCw4cPF5XNHh4e5OrqSsWLF6eVK1fSrl27qFOnTgSAZs2aJYTTpzwIDg4miURCvXr1or///pt2795NU6dOpfnz5xMR0fnz56lkyZJUrVo14Zhpy79ERNHR0SSXy6lZs2ZCeNV+Xr9+nSwsLKhUqVK0Zs0a+ueff6hjx44EgMLCwnI9xrnFq0+Zrev50CQ2NpZMTU2pfPnytH79evr7778pMDBQuPdnr9/oUu/I6746bNgwWrx4Me3Zs4cOHjxIc+fOJTs7O7V6ribZ66ojR46kvXv30pw5c4R6QfZ6bZ8+fQgADRw4kPbs2UNLliwhe3t7cnd3p+fPnwvhunbtSh4eHqLtqK6bWrVq0aZNm2jXrl1Uv359MjIyojt37hCRsgwcNGgQAaCtW7cK+/n69Wu6d+8emZiYUEBAAEVGRtLhw4cpIiKCgoOD6dWrV3nuZ3ZPnjwRynl9rF27liQSCX377be0detW2rFjB7Vo0YIMDQ1p//79ase0IJ89tNXRiQomD32IupkqbPbt6OPOnTtkYGBAw4YNE5bt2bOHANA///yjFr5t27bk7OwsfO7QoQPZ29urhUtOTiYANHbsWL3TpNqnsLCwXOvpRNrPoSoOV1dXatCgAW3evJn27dtH9+7do4iICAJAjRs3psjISNq4cSPVqFGDZDIZ/fvvv0Lc+j5z6lLGJiQkUHR0NAGgtm3biu6FmqSmplLlypXJzMyMZs+eTfv27aOff/6ZjIyMqFmzZmrHTNM9PWc9W9/9UpXx7u7uQh36jz/+IAcHB3J3dxeVFbrW93LWcy5evEgAaNmyZaJtx8bGEgD6/fffRfuTV7lHpFsdMfv+FeSzzPXr16lfv360YcMGOnz4MO3cuZN69uxJBgYGas98OdclUpYdOct7XZiZmWktC1TH3MnJiQwMDMjBwYGCg4PpwYMHem9n1qxZavfd7ACQtbU1mZiYkEwmo+rVq9PKlSv13s4HbdiaOXOmKGz//v3JxMREqLSpLtycJ//Ro0ckl8tp1KhRGrepUCgoIyODHjx4QADo77//Vtv2L7/8otM+5mzEePv2LR0/fpy8vLyofPnyoosxMDCQ3Nzc6PXr16I4Bg4cSCYmJpSYmEhERCNHjiSJRKJWCQsMDNTYsAWADhw4IAo7ffp0MjAwUDv2mzdvJgC0a9cuIiKaPXs2Aci1Yt+iRQuqWrVqrsch50PGq1evhEpqdg8fPiRjY2MKCgoSlnXt2pUA0KZNm0RhmzVrRl5eXrluNyfVuT1y5AgBoIsXL+q9ncWLF6vlCyJlRUafhi1tf6qH2IyMDHJ0dBQdCyKiUaNGkUwmoxcvXhDR/yoAOa+HjRs3EgD6448/hGX5bdgiIhowYIDaw65KzsrTmDFjCACdOnVKFK5fv34kkUjoxo0bou1UqlSJMjMzhXCnT58mALR+/XqN21NR5atBgwaJln/77bcEgObMmSNaXrVqVapevbpombaGrf79+4vCzZw5kwDQ06dPhWXaHvarVKlCWVlZwvJ58+YRAGrVqpUozqFDhxIA0TWfM86cNm3aRBKJhMaNGycs0/V61qZ58+Yab2D6nB9vb2+qVq2aWqWvRYsW5OzsLDoeOa1fv54A0JYtW0TLz5w5QwBo0aJFwjIPDw8yNDQU8pCKKi/Xq1dPtDw/ZY2uN786deqQg4MDvXnzRliWmZlJFStWJDc3N+FepDqO2RsftFHts6ZyRNcySp/jqYk+DVuFnTf2799PAOjo0aNERLRu3TqysLCg/v37ix7wypQpIzqXmn5MKYh8rolqW126dBEtf/jwIRkZGamVT2/evCEnJydq3749ERG9ePGCANC8efNy3Y6HhwdJJBK6cOGCaHlAQABZWlpSSkoKEeleHhw9epQA0Pjx43PdboUKFXItk3LSVrHt0KEDGRsb08OHD0XLmzZtSqampnk2IGqLV9cyW9fzoc0PP/xAcrlc1DCRmZlJ3t7euVawc6t35HZfzS4rK4syMjJozZo1ZGhoKNQHtVFdw9kbC4hIeKBet24dEf3vh7Kcx+7UqVMEQHSf0daw5ejoSElJScKy+Ph4MjAwoOnTpwvLtD2EqPJkzjydHydPniQANGbMGLXvMjMzRQ0TqrI5JSWFbGxs1H5gysrKoipVqlCtWrWEZYXx7KGtjp5TfvPQh6ib3b9/nwwNDalHjx657oMmGRkZVL9+fbK0tBSVC6p8qqnBpU+fPiSTyYTPAQEBWp8FZDIZ9enTR+90qfZf21/2xidt51AVR6lSpUQNyVlZWeTi4kKVKlUS3fvevHlDDg4OVLduXWGZvs+c+pSxAGjAgAF5xrlkyRKN9Y6wsDACQPv27RPtrz4NW7rul6qMb9OmjWj58ePHCQBNmTKFiPSr72mr5+R8nu3Xrx9ZWlqK6nm6lnu61hEL41kmJ1UZ2KhRI7XjqGndUqVKUalSpbTGp01uDVtr1qyhqVOnCh1lZsyYQTY2NuTo6EiPHz/Wazt5NWwFBQVRREQEHT16lDZv3kxNmzYlQPmjsT4+aB+xVq1aiT5XrlwZaWlpwqs9O3fuhEQiQefOnZGZmSn8OTk5oUqVKqLXrxISEvDjjz/C3d0dRkZGkEql8PDwAACN3Re///57vdL6ww8/QCqVCl2ck5KS8M8//wiDaKalpeHAgQNo06YNTE1NRelt1qwZ0tLShO6/R44cQcWKFdXGPOnYsaPGbVtbW6Nhw4aiZTt37kTFihVRtWpV0bYCAwNFXcRVr8W0b98emzZtwpMnT9Tir1WrFi5evIj+/ftj7969SEpKyvN4REdHIzU1Va2LtLu7Oxo2bKjWBVwikaBly5aiZZUrV8aDBw/y3Nbdu3cRFBQEJycnGBoaQiqVwt/fH4D6udVlO4cOHYKFhYVa/tM0wGRuwsLCcObMGbU/R0dHAICRkRE6d+6MrVu3Ct3cs7KysHbtWrRu3Rq2trYAlN34Aagdy3bt2sHMzEztWH4IBw8eRPny5VGrVi3R8m7duoGIhDSrNG/eXPRqQOXKlQFAp/MLAC1atBB9LleunBBvzuW6xqmpfNE1Tc2aNRN1mc0tPYDy1QBdHDlyBMHBwejcuTOmTp0qLNf1es6vvM7P7du3cf36dXTq1AkA1Mqvp0+f4saNG1rj37lzJ4oVK4aWLVuK1q1atSqcnJzU0l+5cmWULVtWY1w5y2Z9yxpNcWiSkpKCU6dOoW3btqKZCg0NDREcHIzHjx/nus/5pUsZpe/xfB+FnTdUr33t378fgHLYgPr166NJkyY4ceIE3r59i0ePHuHWrVv45ptvCnVf8pIz3+zduxeZmZno0qWLaL9NTEzg7+8vnAcbGxuUKlUKs2bNwpw5cxATE6PxFXQAqFChAqpUqSJaFhQUhKSkJJw/fx6A7uXB7t27AQADBgzQaf/e18GDB9GoUSO4u7uLlnfr1g1v375Vew1HX3mV2bqeD20OHTqERo0aCfdoQHm9//DDD2ph9al3aBMTE4NWrVrB1tZWiKNLly7IysrCzZs3dYpDdd2ptG/fHkZGRsLrUKp/c5aPtWrVQrly5XSqPzRo0AAWFhbCZ0dHRzg4OOh03VStWhUymQx9+vTB6tWrNb5WVBBsbW0hlUqFvy1btgBQDmqfmJiIrl27ivKEQqFAkyZNcObMGbXXdwvy2QPQXEcHCiYP5VQYdTMPDw9kZmZixYoVeqWFiNCzZ0/8+++/WLNmjVq5AEDrK3I5l+f2Kt37jHM4ZMgQjfX0nBO7aDuHgDK/SKVS4fONGzcQFxeH4OBgUT3R3Nwc33//PU6ePKn2Opyuz5yFUcYePHgQZmZmaNu2rVqcAN7rGUPfZ+mc5VndunXh4eEhlGP5qe9lN2TIEFy4cAHHjx8HoHylf+3atejatavajNR5lXv5qSMW9LPMkiVLUL16dZiYmAhtGwcOHNCp/Lh9+7YwlEdBCQ4Oxrhx49C0aVM0aNAAo0ePxu7du/H8+XPMnDmzQLcVERGBoKAg+Pn54fvvv8euXbvQokULzJgxQ68hOT5ow5bqwV5FNRhfamoqAOX4VUQER0dH0Q1NKpXi5MmTwvhZCoUCjRs3xtatWzFq1CgcOHAAp0+fFhqSVPFlp+/sfqpGjCNHjmD8+PF49uwZvv32W+H95JcvXyIzMxMLFy5US2uzZs0AQEjvy5cvRRUrFU3LtKX12bNnuHTpktq2LCwsQETCturVq4fIyEihMujm5oaKFSti/fr1Qlxjx47F7NmzcfLkSTRt2hS2trbCrCXavHz5UmvaXFxchO9VTE1N1aYDNTY2RlpamtZtAEBycjL8/Pxw6tQpTJkyBYcPH8aZM2ewdetWAOrnVpftaDv+Tk5OuaYlp5IlS6JmzZpqf9lvgD169EBaWho2bNgAQFkxf/r0qWgsgZcvX8LIyEhtoGSJRAInJye1Y/khvHz5Uuu5VX2fXV7Xcl5yDgwqk8m0Ls8rzxREmvRJDwCd0hQbG4tvv/0Wfn5+ahVIXa/n/NKlrAWAESNGqKWhf//+AJBrGp49e4b//vsPMplMbf34+Hi1dXMrf3N+l5+yRpdZpF69egUi0iufFwRdyih9j+f7KOy8YWJiAl9fX6Fh68CBAwgICED9+vWRlZWFf//9F1FRUQDw3g1b71sO5cwLqn3/6quv1PZ948aNwn5LJBIcOHAAgYGBmDlzJqpXrw57e3sMHjwYb968EcWp6T6jWqbKb7qWB8+fP4ehoaHe96780ve+oC9d82Je5yO39Od2/FX0rXdo8vDhQ/j5+eHJkyeYP38+/v33X5w5c0YYT0nXPJkzbUZGRrC1tRWOtb7loyY5jzugPPa6pLFUqVLYv38/HBwcMGDAAJQqVQqlSpUSjdGqK9XDvKYHPtU5WLJkiWi5Kk+0bdtWLU+EhYWBiJCYmChap6CePVQ0HfuCyEOafOi6mTZEhF69emHdunVYtWoVWrdurXG7mvJfYmKiqC6VPT9nl5KSgvT09HwPHA8oZz/UVE/P2chRkHUShUKBV69e6Rx/zrgLuoxVlXs5GwgdHBxgZGT0XuW2vs/S2srfgirPWrduDU9PT6GcXbVqFVJSUjT++JNXuZefOmJBPsvMmTMH/fr1Q+3atbFlyxacPHkSZ86cQZMmTd77+i1ItWrVQtmyZd9r7D5dqX5syK19IqcCnxXxfdjZ2UEikeDff//VOAOFatmVK1dw8eJFrFq1Cl27dhW+z62lUt9fAFSNGICysUgul2PChAlYuHAhRowYAWtra6EVV9uvpyVKlACgvJhyDjoPQOvg5ZrSamdnB7lcrnVazuyzFbRu3RqtW7fGu3fvcPLkSUyfPh1BQUHw9PSEj48PjIyM8NNPP+Gnn37Cf//9h/3792PcuHEIDAzEo0ePNM5yoSoQnj59qvZdXFxcvmZL0OTgwYOIi4vD4cOHhV+6AOQ5qHpubG1tcfr0abXlBT14PADhl7Xw8HD07dsX4eHhcHFxQePGjUXpyczMxPPnz0WNW0SE+Ph4odedJqoH5JwDTxdEQ4i2cwugwM7vl+Lx48do0qQJihcvji1btogaPwH9rufCoIp/7Nix+O677zSG8fLyynV9W1tbrYO8Zv9VDNDv11l9yxpdy3Zra2sYGBh8lPlc3+NZ2GkB8p83AKBRo0b45ZdfcPr0aTx+/BgBAQGwsLDAV199haioKMTFxaFs2bIaf/H/kHLmHdW+b968WegBro2Hh4fQYH3z5k1s2rQJoaGhSE9PFz2Ma7rPqJap8rqu5YG9vT2ysrIQHx+v9wNGfhT1fUGf86GJra1trsdfpSDqHZGRkUhJScHWrVtFac0+mYAu4uPj4erqKnzOzMzEy5cvhbySvXzMOVV8QdbFcuPn5wc/Pz9kZWXh7NmzWLhwIYYOHQpHR0d06NBB53hcXFxQoUIFREVFIS0tTfQDgKqHTXJysmgd1f4tXLhQ6+xZ2n401kbXZw8VTfecwqi7AkV/DQL/a9QKDw/HihUr0LlzZ7UwFStWBABcvnxZ+HFf5fLly8L3gHIykQ0bNiA+Pl7U8KGaSCR72MJSkHUSAwMDWFtb6xx/zrgL+vza2tri1KlTICJROhISEpCZmSnEqe15IrfGJH2fpbWVv6VLlxbSCuT/2dLAwAADBgzAuHHj8Ouvv2LRokVo1KhRnnUUTYq6jrhu3TrUr18fixcvFi3P+WPZx4CIPsjA8EQEQL9B6ItguHrtWrRoASLCkydPNLa4V6pUCcD/LqycN5ulS5cWWtpGjRqF0qVLY8aMGXjz5g1MTU3RoEEDxMTEoHLlyhrTq7pg/f39ceXKFVy9elUUp6pXjy5atGiBO3fuwNbWVuO2NM16ZGxsDH9/f4SFhQGAxlmEihUrhrZt22LAgAFITExUmwVRxcfHB3K5HOvWrRMtf/z4sdCVtiAUxrlt0KAB3rx5I8wapfLnn3/mO87cdO/eHadOncKxY8ewY8cOdO3aVdQ1XHWsch7LLVu2ICUlJddjqTrPly5dEi3PuW+Afr/UNWrUCFevXhVejVFZs2YNJBIJGjRokGccTOn169do2rQpJBIJdu3apbE3UX6u5+x0/XVdGy8vL5QpUwYXL17UuP2aNWvm2pjSokULvHz5EllZWRrXzU+lQqWwyhozMzPUrl0bW7duFR07hUKBdevWwc3NTevrkrkpiF/EC/N46ut98wag7ImVmZmJn3/+GW5ubvD29haW79+/HwcPHtSpt9b75nN9BQYGwsjICHfu3NG675qULVsWEyZMQKVKldTK0NjYWFy8eFG07M8//4SFhYUwU66u5YFqmvecFd+c9D1u2sI3atRIeGDPbs2aNTA1Nc1zWu73PX/5PR8qDRo0wIEDB0Q/LGZlZWHjxo2icPrUO7Rd75riICIsW7Ysr90UiYiIEH3etGkTMjMzhRklVa9P5Swfz5w5g2vXrhVYXUyXcs3Q0BC1a9cWekvkzPu6GD9+PF68eIGffvpJeIjJja+vL4oVK4arV69qzROqXhO60vXZIzcFkYc0Keq6GRGhd+/eCA8Px9KlS9VmMlRxdXVFrVq1sG7dOmRlZQnLT548iRs3boh+JGndujUkEona7KqrVq2CXC5HkyZNCmdn8snLywuurq74888/RXk0JSUFW7ZsEWZKzI/3LWO1xZmcnIzIyEi1OFXfA8oGYBMTE7Xnib///lvvbWqTszw7ceIEHjx4IJRnBVHf69WrF2QyGTp16oQbN25g4MCB+UprYdURdSWRSNTKj0uXLr33K/8F7eTJk7h161a+8qa+1q5dC6lUiho1aui8Tr56bB08eFBjA0jOVnp9+fr6ok+fPujevTvOnj2LevXqwczMDE+fPsWxY8dQqVIl9OvXD97e3ihVqhTGjBkDIoKNjQ127NghvN5QGKRSKaZNm4b27dtj/vz5mDBhAubPn4+vv/4afn5+6NevHzw9PfHmzRvcvn0bO3bsEN59Hzp0KFauXImmTZti0qRJcHR0xJ9//onr168D0K0lcujQodiyZQvq1auHYcOGoXLlylAoFHj48CH27duH4cOHo3bt2vjll1/w+PFjNGrUCG5ubvjvv/8wf/580bv+LVu2RMWKFVGzZk3Y29vjwYMHmDdvHjw8PFCmTBmN2y9WrBh+/vlnjBs3Dl26dEHHjh3x8uVLTJw4ESYmJggJCSmQ41y3bl1YW1vjxx9/REhICKRSKSIiItQeDPTRpUsXzJ07F126dMHUqVNRpkwZ7Nq1C3v37tUrnlu3bmnseunm5ib65bRjx4746aef0LFjR7x7907t3fGAgAAEBgZi9OjRSEpKgq+vLy5duoSQkBBUq1YNwcHBWtPg5OSEb775BtOnT4e1tTU8PDxw4MABobt7dqrKWFhYGJo2bQpDQ0NUrlxZY6Vv2LBhWLNmDZo3b45JkybBw8MD//zzDxYtWoR+/foVamH+uQkKCsLVq1fxxx9/4NGjR6IpsVV5RdfrWZtKlSph69atWLx4MWrUqAEDA4M8H/JyWrp0KZo2bYrAwEB069YNrq6uSExMxLVr13D+/Hn89ddfWtft0KEDIiIi0KxZMwwZMgS1atWCVCrF48ePcejQIbRu3Rpt2rTRKz0qhVnWTJ8+HQEBAWjQoAFGjBgBmUyGRYsW4cqVK1i/fn2+xvYoVaoU5HI5IiIiUK5cOZibm8PFxUXouq6Lwjye+fE+eQMAatSoAWtra+zbt0/0IPTNN99g8uTJwv/zUhD5XB+enp6YNGkSxo8fj7t376JJkyawtrbGs2fPcPr0aZiZmWHixIm4dOkSBg4ciHbt2qFMmTKQyWQ4ePAgLl26hDFjxojidHFxQatWrRAaGgpnZ2esW7cOUVFRCAsLEx6GdC0P/Pz8EBwcjClTpuDZs2do0aIFjI2NERMTA1NTUwwaNEg4bhs2bMDGjRtRsmRJmJiY5PpwXqlSJRw+fBg7duyAs7MzLCws4OXlhZCQEOzcuRMNGjTAL7/8AhsbG0REROCff/7BzJkzYWVllevx1BZvQZ8PbSZMmIDt27ejYcOG+OWXX2Bqaorff/9dbQwmfeod2u6rAQEBkMlk6NixI0aNGoW0tDQsXrxY7RWlvGzduhVGRkYICAhAbGwsfv75Z1SpUgXt27cHoHzI7tOnDxYuXAgDAwM0bdoU9+/fx88//wx3d3cMGzZMr+1po9rP+fPno2vXrpBKpfDy8kJERAQOHjyI5s2bo3jx4khLSxN6Gma/plU9MvIa86Vjx46IjY3F1KlTcfHiRXTr1g1lypSBQqHAo0ePsHbtWgD/67Vqbm6OhQsXomvXrkhMTETbtm3h4OCA58+f4+LFi3j+/HmeDb856frskZuCyEMfqm724MEDlCpVCl27ds1znK3BgwdjxYoV6NGjBypVqiSqAxsbG6NatWrC57CwMAQEBKBdu3bo378/EhISMGbMGFSsWFF0H6hQoQJ69uyJkJAQGBoa4quvvsK+ffvwxx9/YMqUKaLXuCZNmoRJkybhwIEDop5w2jx8+FBjPd3e3h6lSpXKc31NDAwMMHPmTHTq1AktWrRA37598e7dO8yaNQv//fcfZsyYka94Abx3GatJly5d8Pvvv6Nr1664f/8+KlWqhGPHjmHatGlo1qyZcJ2qxpVbuXIlSpUqhSpVquD06dMF+qP/2bNn0atXL7Rr1w6PHj3C+PHj4erqKgxrUBD1vWLFiqFLly5YvHgxPDw81MY01Udh1BF11aJFC0yePBkhISHw9/fHjRs3MGnSJJQoUQKZmZl5rq9rmQsox/9VjVuVlZWFBw8eYPPmzQCUnXFUbxNVqVIFnTt3Rrly5WBiYoLTp09j1qxZcHJywqhRo/Lc/vPnz3HkyBEA/+uRuXv3btjb28Pe3l64pmfNmoWrV68KbRcJCQlYsWIF9u3bh9DQUP16yukz0rxqFgBtf/fu3ct1VsTs0xBnjy/nCPkrV66k2rVrk5mZGcnlcipVqhR16dKFzp49K4S5evUqBQQEkIWFBVlbW1O7du3o4cOHWmdyyLltbVQzdf31118av69du7Zo6tx79+5Rjx49yNXVlaRSKdnb21PdunWFGR9Urly5Qt988w2ZmJiQjY0N9ezZk1avXq02W4q/vz9VqFBB47aTk5NpwoQJ5OXlRTKZjKysrKhSpUo0bNgwYdafnTt3UtOmTcnV1ZVkMhk5ODhQs2bNRDOC/Prrr1S3bl2ys7MjmUxGxYsXp549e9L9+/eFMNrOzfLly6ly5crC9lu3bq0222PXrl3JzMxMLf2aZrTQ5MSJE+Tj40OmpqZkb29PvXr1ovPnz6vlK3228/jxY/r+++/J3NycLCws6Pvvv6cTJ05onREku7xmRdQ0Q1VQUBABIF9fX41xpqam0ujRo8nDw4OkUik5OztTv3791KbL1jTj3tOnT6lt27ZkY2NDVlZW1LlzZzp79qzavrx794569epF9vb2JJFIROcz58w7REQPHjygoKAgsrW1JalUSl5eXjRr1izRLDC5zRaX89rTRNvMqtquU03nOOd2tMWpaQZJbTPF5dwfbeWApm3ljNPDw0NrXsmebl2uZ20SExOpbdu2VKxYMeHc5rY/mo4bkXK65Pbt25ODgwNJpVJycnKihg0b0pIlS3LdPpFydqTZs2dTlSpVyMTEhMzNzcnb25v69u1Lt27dEh2P5s2bq62fV1n7PmVNbv79919q2LChcH+pU6cO7dixQxRGn1kRiZSzGnp7e5NUKhUdZ33KKF2Ppyb6zIr4IfIGEVGbNm0IAEVERAjL0tPTyczMjAwMDNTKOk33nILK5znlNcNzZGQkNWjQgCwtLcnY2Jg8PDyobdu2tH//fiIievbsGXXr1o28vb3JzMyMzM3NqXLlyjR37lzRjGSqvL9582aqUKECyWQy8vT0VJsxiUj38iArK4vmzp1LFStWFML5+PiI8vD9+/epcePGZGFhQQDynAL8woUL5OvrS6ampgRAlG8uX75MLVu2JCsrK5LJZFSlSpU875l5xatPmU2U9/nIzfHjx6lOnTpkbGxMTk5ONHLkSPrjjz/U8pqu9Y7c7qs7duwQrl9XV1caOXIk7d69W+M+5aS6hs+dO0ctW7YU6iodO3akZ8+eicJmZWVRWFgYlS1blqRSKdnZ2VHnzp2FGZpVtM2KqGlmNU11grFjx5KLiwsZGBgI+xAdHU1t2rQhDw8PMjY2JltbW/L396ft27erxafP1PNHjx6lH374gdzc3EgqlZKpqSmVL1+e+vXrJ6r7qxw5coSaN29ONjY2JJVKydXVlZo3by66nxTGs0dudfSCyEMfom6mCqttJrTscqvPaDq/+/btozp16gjPOl26dFHLv0TKe0FISAgVL16cZDIZlS1blhYsWKAWTnUO87p+8poVsVOnTkJYbecwr/t+ZGQk1a5dm0xMTMjMzIwaNWpEx48f15heXZ85iXQvY7Vdu5q8fPmSfvzxR3J2diYjIyPy8PCgsWPHUlpamijc69evqVevXuTo6EhmZmbUsmVLun///ns/S6uusX379lFwcDAVK1ZMmP1QU31Gl/pebs+Qhw8fJgA0Y8YMjd/rU+7pUkcsjGeZd+/e0YgRI8jV1ZVMTEyoevXqFBkZqbUcz1nP0afMVc0Mqukv+7XWoUMHKl26NJmZmZFUKiUPDw/68ccfKS4uTi1OTdvP7fk5ez1j+/bt9PXXX5O9vT0ZGRmRhYUF+fn55TnDtSYSIh36/rJC0adPH6xfvx4vX77Uu+s0Y4wxxj5enp6eqFixInbu3FnUSWEfudDQUEycOBHPnz/nMS0ZY5+0VatWoXv37jhz5kyh9rJWGT58OBYvXoxHjx5pHCSefTk+qsHjP2eTJk2Ci4sLSpYsieTkZOzcuRPLly/HhAkTuFGLMcYYY4wxxhjTwcmTJ3Hz5k0sWrQIffv25UYtxg1bH4pUKsWsWbPw+PFjZGZmokyZMpgzZw6GDBlS1EljjDHGGGOMMcY+CaqB+1u0aIEpU6YUdXLYR4BfRWSMMcYYY4wxxhhjn6S8p+NjjDHGGGOMMcYYY+wjxA1bjDHGGGOMMcYYY+yTxA1bjDHGGGOMMcYYY+yTxIPHM1ZIFAoF4uLiYGFhAYlEUtTJYYwxxhhjjBURIsKbN2/g4uICAwPuX8JYQeKGLcYKSVxcHNzd3Ys6GYwxxhhjjLGPxKNHj+Dm5lbUyWDss8INW4wVEgsLCwDKm5elpWWRpiUjIwP79u1D48aNIZVKizQt7NPAeYbpi/MM0xfnGaYvzjNMXx9TnklKSoK7u7vwjMAYKzjcsMVYIVG9fmhpaflRNGyZmprC0tKyyG/q7NPAeYbpi/MM0xfnGaYvzjNMXx9jnuEhShgrePxyL2OMMcYYY4wxxhj7JHHDFmOMMcYYY4wxxhj7JHHDFmOMMcYYY4wxxhj7JPEYW4wVISJCZmYmsrKyCnU7GRkZMDIyQlpaWqFvi30eOM8wfXGeYfriPMP0xXlGf4aGhjAyMuJxnRhjnzVu2GKsiKSnp+Pp06d4+/ZtoW+LiODk5IRHjx5xxYbphPMM0xfnGaYvzjNMX5xn8sfU1BTOzs6QyWRFnRTGGCsU3LDFWBFQKBS4d+8eDA0N4eLiAplMVqgVNIVCgeTkZJibm8PAgN9AZnnjPMP0xXmG6YvzDNMX5xn9EBHS09Px/Plz3Lt3D2XKlOHjxhj7LHHDFmNFID09HQqFAu7u7jA1NS307SkUCqSnp8PExIQrNEwnnGeYvjjPMH1xnmH64jyjP7lcDqlUigcPHgjHjjHGPjd8R2CsCHGljDHGGGOMFSaubzLGPndcyjHGGGOMMcYYY4yxTxI3bDHGGGOMMcYYY4yxTxI3bDHGCoWnpyfmzZtX1MkoMJ/b/jDGGGOMMcbY54Abthhjenn06BF69uwpzObo4eGBIUOG4OXLl0WdtCIVGhoKiUQCiUQCIyMj2NnZoV69epg3bx7evXunV1yHDx+GRCLBf//9VziJZYwxxhhjjLHPBDdsMfYJy1IQou+8xN8XniD6zktkKahQt3f37l3UrFkTN2/exPr163H79m0sWbIEBw4cgI+PDxITEwt1+7nJysqCQqEosu0DQIUKFfD06VM8fPgQhw4dQrt27TB9+nTUrVsXb968KdK0McYYY4wxxtjniBu2GPtE7bnyFF+HHUTHZScxZMMFdFx2El+HHcSeK08LbZsDBgyATCbDvn374O/vj+LFi6Np06bYv38/njx5gvHjx4vCv3nzBkFBQTA3N4eLiwsWLlwo+j40NBTFixeHsbExXFxcMHjwYOG79PR0jBo1Cq6urjAzM0Pt2rVx+PBh4ftVq1ahWLFi2LlzJ8qXLw9jY2MsW7YMJiYmaj2dBg8eDH9/f+HziRMnUK9ePcjlcri7u2Pw4MFISUkRvk9ISEDLli0hl8tRokQJRERE6HR8jIyM4OTkBBcXF1SqVAmDBg3CkSNHcOXKFYSFhQnh1q1bh5o1a8LCwgJOTk4ICgpCQkICAOD+/fto0KABAMDa2hoSiQTdunUDAOzZswdff/01ihUrBltbW7Ro0QJ37tzRKW2MMcYYY4wx9jnihi3GPkF7rjxFv3Xn8fR1mmh5/Os09Ft3vlAatxITE7F37170798fcrlc9J2TkxM6deqEjRs3guh/vcZmzZqFypUr4/z58xg7diyGDRuGqKgoAMDmzZsxd+5cLF26FLdu3UJkZCQqVaokrNu9e3ccP34cGzZswKVLl9CuXTs0adIEt27dEsK8ffsW06dPx/LlyxEbG4vOnTujWLFi2LJlixAmKysLmzZtQqdOnQAAly9fRmBgIL777jtcunQJGzduxLFjxzBw4EBhnW7duuH+/fs4ePAgNm/ejEWLFgkNT/ry9vZG06ZNsXXrVmFZeno6Jk+ejIsXLyIyMhL37t0TGq/c3d2F9N+4cQNPnz7F/PnzAQApKSn46aefcObMGRw4cAAGBgZo06ZNkfdUY4wxxhhjjLGiYlTUCWCM6SdLQZi44yo0vXRIACQAJu64ioDyTjA0kBTYdm/dugUiQrly5TR+X65cObx69QrPnz+Hg4MDAMDX1xdjxowBAJQtWxbHjx/H3LlzERAQgIcPH8LJyQnffPMNpFIpihcvjlq1agEA7ty5g/Xr1+Px48dwcXEBAIwYMQJ79uxBeHg4pk2bBgDIyMjAokWLUKVKFSEdP/zwA/7880/07NkTAHDgwAG8evUK7dq1A6BsbAsKCsLQoUMBAGXKlMGCBQvg7++PxYsX4+HDh9i9ezdOnjyJ2rVrAwBWrFihdb914e3tjX379gmfe/ToIfy/ZMmSWLBgAWrVqoXk5GSYm5vDxsYGAODg4IBixYoJYb///ntRvCtWrICDgwOuXr2KihUr5jt9jDHGGGOMMfap4h5b7It09OhRtGzZEi4uLpBIJIiMjBR9T0QIDQ2Fi4sL5HI56tevj9jY2KJJbA6n7yWq9dTKjgA8fZ2G0/c+7HhXqp5aEsn/GtN8fHxEYXx8fHDt2jUAQLt27ZCamoqSJUuid+/e2LZtGzIzMwEA58+fBxGhbNmyMDc3F/6OHDkievVOJpOhcuXKom106tQJhw8fRlxcHAAgIiICzZo1g7W1NQDg3LlzWLVqlSjewMBAKBQK3Lt3D9euXYORkRFq1qwpxOnt7S1qYMrPscl+XGJiYtC6dWt4eHjAwsIC9evXBwA8fPgw13ju3LmDoKAglCxZEpaWlihRooRO6zHGGGPsC0MEpKUBr18D6elFnRrGGCtU3GOLfZFSUlJQpUoVdO/eXa0XDADMnDkTc+bMwapVq1C2bFlMmTIFAQEBuHHjBiwsLIogxf+T8EZ7o1Z+wumqdOnSkEgkuHr1Kr799lu1769fvw5ra2vY2dnlGo+qgcfd3R03btxAVFQU9u/fj/79+2PWrFk4cuQIFAoFDA0Nce7cORgaGorWNzc3F/4vl8tFDUYAUKtWLZQqVQobNmxAv379sG3bNoSHhwvfKxQK9O3bVzSel0rx4sVx48YNUToLwrVr14RGqJSUFDRu3BiNGzfGunXrYG9vj4cPHyIwMBDpeVQ8W7ZsCXd3dyxbtgwuLi5QKBSoWLFinusxxhhj7DOWng68fatsyEpNVf6lpQHZhyr47z8gIgKoWxfw9wfMzIosuYwxVtC4YYt9kZo2bYqmTZtq/I6IMG/ePIwfPx7fffcdAGD16tVwdHTEn3/+ib59+37IpKpxsDAp0HC6srW1RUBAABYtWoRhw4aJxtmKj49HREQEunTpImoQOnnypCiOkydPwtvbW/gsl8vRqlUrtGrVCgMGDIC3tzcuX76MatWqISsrCwkJCfDz89M7rUFBQYiIiICbmxsMDAzQvHlz4bvq1asjNjYWpUuX1rhuuXLlkJmZibNnzwqvRt64cUNtQHpdXb9+HXv27MHYsWOFzy9evMCMGTPg7u4OADh79qxoHZlMBkA5PpjKy5cvce3aNSxdulQ4JseOHctXmhhjjDH2GUhLAx4/VjZaaSKRAMbGynCZmcC6dcDUqYBMBtSrBwQGAp06Ac7OHzTZjDFW0Lhhi7Ec7t27h/j4eDRu3FhYZmxsDH9/f5w4cUJrw9a7d+/w7t074XNSUhIA5ThQGRkZorAZGRkgIigUCr0H/q7pUQxOliZ4lpSmcZwtCQAnKxPU9CgmxK16TVC1zfxasGABvv76awQGBmLSpEkoUaIEYmNjMXr0aLi6umLy5Mmi+I8fP46wsDC0bt0a+/fvx19//YUdO3ZAoVBg1apVyMrKQu3atWFqaoo1a9YIsxTa2toiKCgIXbp0waxZs1CtWjW8ePEChw4dQsWKFdGsWTNhO5r2p2PHjpg4cSKmTp2K77//HjKZTAg3cuRI1K1bF/3790evXr1gZmaGa9euYf/+/ViwYAHKlCmDwMBA9O7dG0uWLIGRkRF++uknyOXyXI8fESEzMxNxcXFQKBR4+fIljhw5gqlTp6Jq1aoYPnw4FAoF3NzcIJPJsGDBAvTt2xdXrlzB5MmThX1RKBRwd3eHRCLB9u3b0axZM8jlclhZWcHW1hZLly6Fo6MjHj58iHHjxonWK0gFlWfYl4PzDNMX5xmmL84z/y8rC5KnT4HnzyEhUtYH5XLAxET4l+RyZaMWAEVKCghAVrt2oE2bIHn4ENi/H9i/HzR9OrLWrQN9801R7lGhUdXBc9bFi8LHkAbGPlfcsMVYDvHx8QAAR0dH0XJHR0c8ePBA63rTp0/HxIkT1Zbv27cPpqamomVGRkZwcnJCcnJyvl4jG9nIEyO2XYcEEDVuqfpKjWjoiZTkN2rrvXmjvkwfjo6OOHDgAMLCwtChQwckJibCwcEBzZs3x+jRo2FkZCQ06CkUCgwYMACnTp3CpEmTYG5ujilTpsDHxwdJSUkwNjbGvHnzhAaf8uXLY/369ZBKpUhKSsK8efMwe/ZsDB8+HE+fPoWNjQ2++uor+Pn5ISkpCWlpaSAiYXs501m9enWcP38eU6ZMEYXx9PTEzp07MWXKFPj7+4OI4OnpiTZt2gjh5s+fj8GDB6NBgwawt7fH+PHj8eDBA6SlpWncHqBs2IyNjYWrqysMDQ1haWkJLy8vDB06FD169IBCoRD2+/fff8fkyZOxcOFCVK5cGaGhoQgKCkJKSgqSkpJgYWGBsWPHYuzYsejZsyc6dOiARYsWYfny5RgzZgwqV66M0qVLIywsDC1atEBqaqrWdL2v980z7MvDeYbpi/MM09cXm2cUCsiSkmCSmAjJ/zfsZZiaItXWFor/b8QSvHun/INyNuZUiQSH69dHpq8vzJ88gcP58yh+8CCs7t+HYYsWuNapE259952yl9dnSDUrd1F6+/ZtUSeBsc+WhFQ/fTD2hZJIJNi2bZswbtSJEyfg6+uLuLg4OGfrmt27d288evQIe/bs0RiPph5b7u7uePHiBSwtLUVh09LS8OjRI3h6esLEJH+vDO65Eo9JO68hPul/Y2k5W5ng5+bl0KSikygsEeHNmzewsLAo0LGj2OeL8wzTF+cZpi/OM0xfX3Kekfz3H/DkCST/X9ckuRxwcwPpMPZrWloa7t+/D3d3d3G9My0NhkOGwOD/xyJVtG6NrBUrgBz11k9ZRkYGoqKiEBAQAKlUWqRpSUpKgp2dHV6/fq32bMAYez/cY4uxHJyclI1C8fHxooathIQEtV5c2RkbG8M4569lAKRSqdqNNCsrCxKJBAYGBjAwyN/kpM0quyCwojNO30tEwps0OFiYoFYJGxgaqFf0VN31VdtkLC+cZ5i+OM8wfXGeYfr6IvOMQgE8eAC8fKn8LJUCLi6Q2NkBEgl0ad4zMDCARCJRr5NKpcDKlYCPDzBwIAz+/hsG168D27YB5coVyu4UFU318aJIA2OscHwhdwTGdFeiRAk4OTmJuiynp6fjyJEjqFu3bhGmTJ2hgQQ+pWzRuqorfErZamzUYowxxhhjn6CsLOD2bWWjlkSiHOS9YkXA3r5gXxns3Rs4ehRwdQVu3ABq1QK2bCm4+BljrJBxwxb7IiUnJ+PChQu4cOECAOWA8RcuXMDDhw8hkUgwdOhQTJs2Ddu2bcOVK1fQrVs3mJqaIigoqGgTzhhjjDHGPn8ZGcpGpqQkwMAAKF1a2fBkaFg426tdGzh3DvD3B5KTgbZtAQ1jxzLG2MeIX0VkX6SzZ8+iQYMGwueffvoJANC1a1esWrUKo0aNQmpqKvr3749Xr16hdu3a2LdvHyx0GMeAMcYYY4yxfHv3Drh5U/mvkRFQpgxgZlb423V0VM6WOHo0MGcOEBqq7CH2/feFv23GGHsP3LDFvkj169dHbvMmSCQShIaGIjQ09MMlijHGGGOMfdnevgVu3VL22JLJgLJlgXxONJQvRkbAr78q/505E+jZE6hRA/D0/HBpYIwxPfGriIwxxhhjjDFW1JKSgOvXlY1acjng7f1hG7WymzJF+Xri69dAUJAyTYwx9pHihi3GGGOMMcYYK0qvXil7aikUgIUF4OWl7LFVVKRSYP16wMoKiI4GQkKKLi2MMZYHbthijDHGGGOMsaKSnAzcvQsQAdbWyjG1jD6CEWNKlACWLVP+f8YMINuM4Ywx9jHhhi3GGGOMMcYYKwrv3gF37igbtaysgJIllbMgfizatQP69lWmr3NnID6+qFPEGGNqPqJSkzH2uTt8+DAkEgn++++/ok5KnlatWoVixYrptY6npyfmzZtXKOn52H3J+85YUdm2bRuMjIxQtmxZJCQkFHVyPjm3bt2Co6MjTE1Ncfz48aJOzicnNTUVX3/9NSQSCebOnVvUyfk0ZWUBt28LY2opPD3Rrn17SCQSDBkypKhT9z9z5ypnR0xIALp0Ub4uyRhjHxFu2GKM6axbt26QSCSQSCSQSqUoWbIkRowYgZSUlKJOWoH74YcfcPPmzQKNMzQ0VDh+BgYGcHFxQadOnfDo0aMC3U5ROHPmDPr06VPUyfigiAhNmzaFRCJBZGRknuEXLVqEEiVKwMTEBDVq1MC///6rFl9oaChcXFwgl8tRv359xMbGFlLqtVu2bBn8/PxgbW0Na2trfPPNNzh9+nSe623atAl+fn4wNzeHh4cHZs2apRYmIiICVapUgampKZydndG9e3e8fPmyMHajQOhzjj09PYXrO/vfgAEDhDDPnj1Dt27d4OLiAlNTUzRp0gS3bt3KV9oOHTqEoKAghISEwMHBAU2aNEFSUpIozP3799GzZ0+UKFECcrkcpUqVQkhICNLT0/O1TV0tXrwYlStXhqWlJSwtLeHj44Pdu3fnud6RI0dQo0YNmJiYoGTJkliyZInWsBs2bIBEIsG3336brzTGxcWhcePG+Prrr9GzZ0+0aNECly9fVgsXGhoKb29vmJmZCdfDqVOn8rVNXT19+hRBQUHw8vKCgYEBhg4dmuc6Fy9eRMeOHeHu7g65XI5y5cph/vz5auE2bdqEqlWrwtTUVOt1qovMzEy0bdsWL168wIIFCzBmzBisWbMm13Xe95y9r8uXL8Pf3x9yuRyurq6YNGlSrjNkA5qv6zFjxqiFW7VqFSpXrgwTExM4OTlh4MCBeSeISPn6YWqqcjyr0qXRb+BAHDt2DEuXLsXKlSsxefJktdVUPxLm/Lt+/brOx0JvcjmwcaPy36goIJ/5hjHGCg0xxgrF69evCQC9fv1a7bvU1FS6evUqpaamfpC0ZGVl0atXrygrK+u94unatSs1adKEnj59Sg8fPqSIiAiSy+X0448/6rT+oUOHCAC9evXqvdLxsfLw8KC5c+dq/T4kJIQqVKhAT58+pSdPntDRo0epUqVKVKdOnUJPW3p6ul7hCyrPfM7mzJlDTZs2JQC0bdu2XMNu2LCBpFIpLVu2jK5evUpDhgwhMzMzevDggRBmxowZZGFhQVu2bKHLly/TDz/8QM7OzpSUlKRzmrp27UohISH53COloKAg+v333ykmJoauXbtG3bt3JysrK3r8+LHWdXbt2kVGRkb066+/0q1bt2jnzp3k5ORECxcuFML8+++/ZGBgQPPnz6e7d+/Sv//+SxUqVKBvv/32vdKbEwC6d+9egcSlzzlOSEigp0+fCn9RUVEEgA4dOkRERAqFgurUqUN+fn50+vRpun79OvXp04eKFy9OycnJeqXr7NmzZGVlRYsWLSIiouTkZGrUqBH5+/uL7iu7d++mbt260d69e+nOnTv0999/k4ODAw0fPlyv7Xl4eAj7oYvt27fTP//8Qzdu3KAbN27QuHHjSCqV0pUrV0Thspczd+/eJVNTUxoyZAhdvXqVli1bRlKplDZv3qwW//3798nV1ZX8/PyodevWeu0LEVFiYiJVqFCBOnfuTJmZmURENHbsWHJ2dqY7d+6IwkZERFBUVBTduXOHrly5Qj179iRLS0tKSEjQeXv6Xpf37t2jwYMH0+rVq6lq1ao0ZMiQPNdZsWIFDRo0iA4fPkx37tyhtWvXklwuF12Dqut08eLFdOfOHY3XqS4UCgV16tSJqlSpQs+ePSMior///pvMzMxo+/btGtd5n3MWHh5O/v7+RJT/e9Pr16/J0dGROnToQJcvX6YtW7aQhYUFzZ49O9f1PDw8aNKkSaJr+82bN6Iwv/76K7m4uFBERATdvn2brly5ovU4iDx6RHTmDNHZs0Rv3tCYMWOoePHidPPmTSIiio6OJmtra+E6V1HVpW7cuCFKlyova1Jg9c7ly4kAIkNDohMn3i+uDyQ9PZ0iIyP1rgcVhtyeDRhj74cbthgrJHo1bCkURMnJhfaXlZRErx4/pqykJPXvFQqd96lr165qFdJevXqRk5MTERGlpaXRoEGDyN7enoyNjcnX15dOnz4thM3esJWcnEwWFhb0119/ieLbvn07mZqaUlJSEt27d48A0JYtW6h+/fokl8upcuXKdCJHZWrz5s1Uvnx5kslk5OHhoVZR9fDwoMmTJ1NwcDCZmZlR8eLFKTIykhISEqhVq1ZkZmZGFStWpDNnzgjrhIeHk5WVlfD59u3b1KpVK3JwcCAzMzOqWbMmRUVFqW0nr4atKlWqiJYtWLBALZ9s376dqlevTsbGxlSiRAkKDQ2ljIwM4ftr166Rr68vGRsbU7ly5YQHaNWDt+q4bdy4kfz9/cnY2JhWrlxJREQrV64kb29vMjY2Ji8vL/r999+FeN+9e0cDBgwgJycnMjY2Jnd3d5o6daoo/e7u7iSTycjZ2ZkGDRqkdd8fPHggHFsLCwtq164dxcfHqx2LNWvWkIeHB1laWtIPP/ygVyPO6tWrycbGhtLS0kTLv/vuOwoODtY5nvy4cOECubm50dOnT3Vq9KhVq5ZaA7C3tzeNGTOGiJQPik5OTjRjxgzh+7S0NLKysqIlS5bonK6CaNjKKTMzkywsLGj16tVaw3Ts2JG+//570QPn3Llzyc3NjRT/X8bMmjWLSpYsKVpvwYIF5ObmRkTKcrF8+fLUu3dv4fu7d++SpaUl/fHHHzqnt6AatvQ9xzkNGTKESpUqJez/jRs3CICocSczM5NsbGxo2bJlRKQsI6VSKR09elQIM3v2bLK1taW4uDgiIrp+/To5OTmpnY+0tDRq2bIltWrVSlRe5DRz5kwqUaKEXvuib8OWJtbW1rR8+XLRsuyNFKNGjSJvb2/R93379lVr+M/MzCRfX19avny52j0pISGBHB0dReXWyZMnSSqV0t69e4mIKCUlherUqUN9+/ZVaxyZMmUKlSpVip4+fap1P1T39v379+u87+9zXfr7++vUsKVJ//79qUGDBsLnjh07Utu2bUVhsl+nCoWCGjVqRIGBgUK+ffXqFbm7u9O4ceOEdQYNGkS1atWixMREUVz79u0jW1tbOnLkiGh5budMFwXRsLVo0SKysrIS3S+mT59OLi4uwr5qktd9PTExkeRyea75oXv37lSpUiVh2+np6VS9cmUKCgxUNmy9eEFz5syh0qVLi37sICKKiYkhR0dHWr9+vbAsPz8SFljDlkJB1KGDsnHL05PoA/1A+z64YYuxLwO/isjYx+DtW8DcvND+DCwtUczNDQaWlurfv337XkmXy+XIyMgAAIwaNQpbtmzB6tWrcf78eZQuXRqBgYFITExUW8/MzAwdOnRAeHi4aHl4eDjatm0LCwsLYdn48eMxYsQIXLhwAWXLlkXHjh2RmZkJADh37hzat2+PDh064PLlywgNDcXPP/+MVatWieKdO3cufH19ERMTg+bNmyM4OBhdunRB586dhbR26dJF62sJycnJaNasGfbv34+YmBgEBgaiZcuWePjwYb6PXXx8PLZu3QpDQ0MYGhoCAPbu3YvOnTtj8ODBuHr1KpYuXYpVq1Zh6tSpAACFQoFvv/0WpqamOHXqFP744w+MHz9eY/yjR4/G4MGDce3aNQQGBmLZsmUYP348pk6dimvXrmHatGn4+eefsXr1agDAggULsH37dmzatAnXrl3D0qVL4eHhAQDYvHkz5s6di6VLl+LWrVuIjIxEpUqVNG6XiPDtt98iMTERR44cQVRUFO7cuYMffvhBFO7OnTuIjIzEzp07sXPnThw5cgQzZswQvl+1ahUkEonW49euXTtkZWVh+/btwrIXL15g586d6N69u9b1KlSoAHNzc61/FSpU0LouALx9+xYdO3bEb7/9Bicnp1zDAkB6ejrOnTuHxo0bi5Y3btwYJ06cAADcu3cP8fHxojDGxsbw9/cXwhSVt2/fIiMjAzY2NlrDvHv3DiYmJqJlcrkcjx8/xoMHDwAAdevWxePHj7Fr1y4QEZ49e4bNmzejefPmAAATExNERERg9erViIyMRFZWFoKDg9GgQQP07t278HZQA33PcU7p6elYt24devToIeThd+/eAYDoOBkaGkImk+HYsWMAgPr162Po0KEIDg7G69evcfHiRYwfPx7Lli2Ds7MzAMDLywtPnz5Fly5dRNs0NjbG9u3b8ffff8Mol9nUXr9+neu5LGhZWVnYsGEDUlJS4OPjozVcdHS02jUSGBiIs2fPCvcYAJg0aRLs7e3Rs2dPtTjs7e2xcuVKhIaG4uzZs0hOTkbnzp3Rv39/IW5TU1NER0djyZIlMMgxQPf48eNx+/Ztrec8PT0df/zxB6ysrFClShWdj0FRyXmu87pOJRIJVq9ejdOnT2PBggUAgB9//BGOjo4IDQ0V1lmwYAFOnToFa2trUVwBAQF48eIF6tWrJ1qe2zn7UKKjo+Hv7w9jY2NhWWBgIOLi4nD//v1c1w0LC4OtrS2qVq2KqVOnil7ljYqKgkKhwJMnT1CuXDm4ubmhffv2oiEGFixYgJSUFOEVxp9Hj8aLhAQsGjMGcHYGbG0xbNgw3Lp1C8WLFxdtu2rVqoiPj0eHDh3U0lWtWjU4OzujUaNGOHToUH4Oi/4kEmDpUsDNDbh//38zJjLGWFEr4oY1xj5bevXYSk5W/vpVFH96vAKT85fWU6dOka2tLbVv356Sk5NJKpVSRESE8H16ejq5uLjQzJkziUj9V8ZTp06RoaEhPXnyhIiInj9/TlKplA4fPkxE/+t5lP1X/tjYWAJA165dIyLla1MBAQGidI4cOZLKly8vfPbw8KDOnTsLn1U9MH7++WdhWXR0NAEQfqnP2WNLk/Lly4te4dClx5aBgQGZmZmRXC4nAASABg8eLITx8/OjadOmidZbu3YtOTs7E5Hy1SIjIyNRjwJtPbbmzZsnisfd3Z3+/PNP0bLJkyeTj48PESl/hW/YsCEpFAq1X8V//fVXKlu2rNZfPLPv+759+8jQ0JAePnwofK86b6oefCEhIULPPJWRI0dS7dq1hc9bt24lLy8vLUdTqV+/ftS0aVPh87x586hkyZK5/gJ///59unXrlta/+/fv57rNPn36UM+ePYXP2Y+9Jk+ePCEAdPz4cdHyqVOnUtmyZYmI6Pjx4wRAuBZUevfuTY0bN841PdkVRo+t/v37U6lSpXL9pX/p0qVkampKkZGRlJGRQTdu3CBvb28CIOph+ddff5G5uTkZGRkRAGrVqpVanpo5cybZ2dnRoEGDyMnJiZ4/f65XelEAPbb0Pcc5bdy4UVS2ESnLQw8PD2rXrh0lJibSu3fvaPr06QRAdI7fvXtH1apVo/bt21OFChWoV69e77Uv2d2+fZssLS2FHmK6yk+PrUuXLpGZmRkZGhqSlZUV/fPPP2phspczZcqUEfW0IvrfdaHqrXbs2DFydXUV8oS23j/9+/ensmXLUqdOnahixYrv3Utlx44dZGZmRhKJhFxcXEQ9kXVRFD22Tpw4QVKplPbt2ycsU12n+/fvp6ysLK3X6aZNm8jY2JjGjh1LpqamdOPGjXylnUj3c5abguixFRAQIOoNSvS/sjlnL/Ds5syZQ4cPH6aLFy/SsmXLyM7OTlQ2TJ8+naRSKXl5edGePXsoOjqaGjVqRF5eXvTu3TshnOp8/Dx2LBkZGdGRpUuJbt/Wq9e8yvXr1+mPP/6gc+fO0YkTJ6hfv34kkUjUesplV+BDYCxerKxDOjt/9L22uMcWY18GbthirJB8rq8iGhoakpmZGRkbG5OBgQG1adOGnj17RhcvXiQAao0C3377LXXv3p2INHefr1y5Mk2fPp2IlBXI7K/uqBposj9EJCYmEgChAletWjUKDQ0VbTMyMpKkUqkw3oSHh4fQuKY83AoCQJs2bRKW3b17lwDQxYsXiUi9YSs5OZlGjhxJ5cqVIysrKzIzMyMDAwMaOXKkEEaXhq1y5crRrVu36MqVKzR16lSqWrWqaLwOU1NTMjExITMzM+HPxMSEAFBKSgrNmzdP7TUiVV7L2bB17NgxIUxCQgIBILlcLorb2NiYHBwciIjo3LlzZGNjQ2XKlKGBAwfSli1bhIeHhw8fkru7O7m5uVGvXr1o69atotedsu/7/PnzydPTU23/ixUrJrw+FRISImp8JFKef31fkTp//jwZGhoK4z9VqVKFJk2apFcc+vj777+pdOnSonOma8NWzoenKVOmCA13OR/gVXr16kWBgYFa4163bp3ofBoZGZFUKhUtW7duncZ1Hzx4IAqXs1GBiCgsLIysra2F60IbhUJBI0eOJBMTEzI0NCRra2sKDQ0lAHTq1CkiUjZuOjs708yZM+nixYu0Z88eqlSpEvXo0UMUV1ZWFvn6+hIA2r17d67bJSJq0qSJaD8AkKmpqWiZNlOnThWFe/DgQb7OcU6NGzemFi1aqC0/e/YsValShQCQoaEhBQYGUtOmTUWNs0TKY2VoaEglS5bUe/wtbZ48eUKlS5cWPZRr07dvX9FxkUgkauVSzlemcnr37h3dunWLzpw5Q2PGjCE7OzuKjY0VhcnZsJWzUf/YsWPCDw5JSUnk6elJu3btEr7X1kjy9u1bKlmyJEml0jzzri6Sk5Pp1q1bFB0dTT169CBPT09hbClN3ue6zCk/DVtXrlwhe3t7mjx5smi5QqGgUaNG5XqdqnTs2JEA0OLFi/Xadnb6nLPscpZNqvpG9mV9+vTRun758uWFcE2aNCEiZcNWznUeP35MACg6Olrnfdq8eTMBoBcvXhCRsgwBILzqSqS83xoYGNCePXtE644dM4YA0OguXYhiY4lyGRNLXy1atKCWLVtq/b7AG7bS0ojc3ZWNWwsWFEychYQbthj7Mmjvq84Y+3AkEsDMrPDiVyiUU0qbmQEG7/cGcoMGDbB48WJIpVK4uLhAKpUCUM7iBEDt1TEiyvV1sl69euG3337DmDFjEB4eju7du6uFV20je/yK/59qWlP8pOF1Qk1x5BZvTiNHjsTevXsxe/ZslC5dGnK5HG3bttV7djGZTIbSpUsDUL4Sd+vWLfTr1w9r164Vtj9x4kR89913auuamJjkeTyzM8uWp1T7tWzZMtSuXVsUTvUaZPXq1XHv3j3s3r0bUVFR6N69OyIiIrBlyxa4u7vjxo0biIqKwv79+9G/f3/MmjULR44cER1HQPs5z7k853oSiUTr8demWrVqqFKlCtasWYPAwEBcvnwZO3bsyHWdChUqCK/HaeLh4aF1NsKDBw/izp07KFasmGj5999/Dz8/Pxw+fFhtHTs7OxgaGiI+Pl60PCEhAY6OjgAgvPoUHx8vvHKWM4wmrVq1Ep3P0aNHw9XVFYMHDxaWaVvfxcUFFy5cED7nfD1t9uzZmDZtGvbv34/KlStrTQOgPHczZszA6NGj8fbtWzg6OuLAgQMAlLOKAcD06dPh6+uLkSNHAgAqV64MMzMz+Pn5YcqUKcJ+JyQk4MaNGzA0NMStW7fQpEmTXLe9fPlypKamCp/LlCmDXbt2wdXVNdf1AOVrVu3btxc+u7i4YM6cOXqf4+wePHiA/fv3Y+vWrWrf1ahRAxcuXMDr16+Rnp4Oe3t71K5dGzVr1hSFU71+mpiYiMTERNG1nB9xcXFo0KABfHx88Mcff+QZftKkSRgxYoTwuX79+ggLCxPlNRcXl1zjyF7W1axZE2fOnMH8+fOxdOlSjeGdnJw0XiNGRkawtbVFbGws7t+/j5YtWwrfq8oLIyMj3LhxA6VKlQIA3L17F3FxcVAoFHjw4EGe+TcvZmZmKF26NEqXLo06deqgTJkyWLFiBcaOHasx/Ptcl+/r6tWraNiwIXr37o0JEyaIvpNIJAgLC8O0adMQHx8Pe3t7tesUUL6Ke+7cOeEazK87d+7ofM6yy1k2bd26FVu2bEFERAQUCgWSk5NzzX+7du0SXl+Vy+UAtOcvQL9zUadOHQDA7du3YWtrK5Rb5cuXF8LY29vDzs5ONFSBQqHA8UOHlMf08WOgdGng/++9BaFOnTpYt25dgcWXJ2NjYNw4oF8/YPp0oHdvIMdrrowx9iFxwxZjTC+qCn5OpUuXFsaKCQoKAgBkZGTg7NmzuU5V3rlzZ4waNQoLFixAbGwsunbtqld6ypcvL4xPo3LixAmULVtWaLApCP/++y+6deuGNm3aAFCOuZXXuBy6+Pnnn1G2bFkMGzYM1atXR/Xq1XHjxg2NxxgAvL298fDhQzx79kyojJ85cybP7Tg6OsLV1RV3795Fp06dtIaztLTEDz/8gHbt2qFp06Zo27YtEhMTYWNjA7lcjlatWqFVq1YYMGAAvL29cfnyZVSvXl0UR/ny5fHw4UM8evQI7u7uAJQPW69fv0a5cuV0PTQ669WrF+bOnYsnT57gm2++EbapTfaHHk1yNrhlN2bMGPTq1Uu0rFKlSpg7d67o4S07mUyGGjVqICoqSsg/gHJsltatWwMASpQoAScnJ0RFRaFatWoAlOP5HDlyBGFhYVrTY2FhIRqPzsLCAjY2NlrzT3ZGRkZaw82aNQtTpkzB3r171RpdcmNoaAhXV1cYGBhg/fr18PHxgYODAwDlw3LOsZ9U12j2xugePXqgYsWK6N27N3r27IlGjRqJHhpz0tSA5eHhIXpQ18bGxkatQS8/5zi78PBwODg4CGOHaWJlZQUAuHXrFs6ePYvJkycL3925cwfDhg3DsmXLsGnTJnTp0gUHDhxQGw9KV0+ePEGDBg1Qo0YNhIeH6xSPg4ODcN4AZV5xdXXVKV9pQ0TCOGOa+Pj4qDVK79u3DzVr1oRUKhXKm+wmTJiAN2/eYP78+cJ1n56ejk6dOuGHH36At7c3evbsicuXLxdoQ1Je+/I+1+X7iI2NRcOGDdG1a1dhXEZNVNcpALXrFACGDx8OAwMD7N69G82aNUPz5s3RsGFDvdOj6znLKWfZ5ODgALlcjtKlS0OhUCApKQmWlpZat6saGzI7Hx8fjBs3Dunp6ZDJZACU+cvFxUWnskIlJiYGAIQGLV9fXwDAjRs34ObmBkDZIP3ixQtROmZNnoxrN2/iyNKlCBwyBOEREbmOBamvmJgY0Y8iH0T37sC0acCjR8qxtgYN+rDbZ4yx7Iqsrxhjnzm9XkUsZPkdkyKnvF4hGDJkCLm4uNDu3bspNjaWunbtStbW1sLMSdpm8gkKCiKZTCa8MqCieqUuJiZGWPbq1SsCIIz3cu7cOTIwMKBJkybRjRs3aNWqVSSXyyk8PFxYR9MrgsjxalHObeV8FfHbb7+lqlWrUkxMDF24cIFatmxJFhYWoldE8jMrIpFyFr/mzZsTEdGePXvIyMiIQkJC6MqVK3T16lXasGEDjR8/noiUs0t5eXlRYGAgXbx4kY4dO0a1a9cmABQZGan1uBERLVu2jORyOc2bN49u3LhBly5dopUrV9Kvv/5KRMpXAdevX0/Xrl2ja9euUXBwMDk5OVFWVhaFh4fT8uXL6fLly3Tnzh0aP348yeVy4XWM7PuuUCioWrVq5OfnR+fOnaNTp05RjRo1hDFStB2LuXPnkoeHh/BZlzG2iJTXmqmpKclkMtqwYUOe4QtazrxERNSwYUPR+GsbNmwgqVRKK1asoKtXr9LQoUPJzMxM9OrujBkzyMrKirZu3UqXL1+mjh07krOzs14zRRbEGFthYWEkk8lo8+bNWqe4X7hwITVs2FD4/Pz5c/r999/p1KlTdO7cORo8eDCZmJiIXm8KDw8nIyMjWrRoEd25c4eOHTtGNWvWpFq1aglhfvvtNypWrJgwPlvnzp2patWqorFq8oICmhUxZ5x5nWMiZVlbvHhxGj16tMZ4Nm3aRIcOHaI7d+5QZGQkeXh40HfffSd8n5mZST4+PsKyp0+fkp2dnehVan2oXj9s2LAhPX78WHQ+9aHvGFtjx46lo0eP0r179+jSpUs0btw4MjAwEI33NGbMGOrcubNwb7p79y6ZmprSsGHD6OrVq7RixQqSSqW0efNmrdvRdE8aMWIEeXp60uvXrykrK4vq1asnlK/6Sk5OprFjx1J0dDTdv3+fzp07Rz179iRjY2PR7JZ5yc91GRMTQzExMVSjRg0KCgqimJgY0aucOctH1euHnTp1Ep3nhIQEIczz589p8eLFdO3aNYqJidF4ne7cuZNkMhmdO3eOiIgmTJhAbm5uajMg5ldRjbH133//kaOjI3Xs2JEuX75MW7duJUtLS9EsyqdOnSIvLy/h1fYTJ07QnDlzKCYmhu7evUsbN24kFxcXatWqlSju1q1bU4UKFej48eN0+fJlatGiBZUvX1549S3mzBmSSaW0/ddfie7do+XLl5OFhQXduXNHr31QmTt3Lm3bto1u3rxJV65coTH//4rjli1btK5TaPXOT2CsLX4VkbEvAzdsMVZIvsSGrdTUVBo0aBDZ2dmRsbEx+fr6isbH0tawdeDAAbUxr4h0a9giUo55Ub58eZJKpVS8eHGaNWuWKJ6CaNi6d+8eNWjQgORyObm7u9Nvv/2mNvZJfhu2VOMrnTx5koiUjVt169YluVxOlpaWVKtWLfrjjz+E8NeuXSNfX1+SyWTk7e1NO3bsIADCeB7aGraIiCIiIqhq1aokk8nI2tqa6tWrR1u3biUioj/++IOqVq1KZmZmZGlpSf7+/nT27FkiItq2bRvVrl2bLC0tyczMjOrUqSOa3jznvj948IBatWpFZmZmZGFhQe3ataP4+Phcj0XOhq3w8HDS9feX4OBgsrGxEU3l/qFoavTw8PBQe5D9/fffycPDg2QyGVWvXl1toF+FQkEhISHk5ORExsbGVK9ePbp8+bJeaSmIhi0PDw9hYoPsf9njDQkJEZ2r58+fU506dcjMzIxMTU2pUaNGQn7ObsGCBVS+fHmSy+Xk7OxMnTp1Eh4ir127RnK5XDTBwevXr8nT05NGjRqlc/o/VMOWpnO8d+9eAqB1sO358+eTm5ubUFZNmDBB1Gg3ceJEcnZ2FhqMiZRjBspkMo3Xc15U15CmP33o27DVo0cPIa/b29tTo0aNRI1aRMq86u/vL7o3HT58mKpVq0YymYw8PT3zHN8p5z3p0KFDZGRkRP/++6+w7MGDB2RlZUWLFi3SOf0qqamp1KZNG3JxcSGZTEbOzs7UqlWrDzJ4vKZzllv5GBISkuc6eV2nCQkJ5OjoKBrrLCMjg2rVqkXt27fXK/3aFFXDFpFyQgM/Pz8yNjYmJycnCg0NFU00oqqjqMqPc+fOUe3atcnKyopMTEzIy8uLQkJCKCUlRRTv69evqUePHlSsWDGysbGhNm3aCI3zqampVL5MGerTpg3RpUvCuFpt2rShunXrCmOB6iMsLIxKlSpFJiYmZG1tTV9//bXGyRmyK7R65ycw1hY3bDH2ZZAQaZnbnjH2XpKSkmBlZYXXr1+rdZlPS0vDvXv3UKJECbWptwtD9q77+X2dpTBFRERgyJAhiIuLE14RYLo7fvw4vv76a9y+fVvjeCX58bHnmZwCAgJQrlw5YYp69uF9anmGFT3OM0xfn1yeSUwE7t5V/t/bGzA3L5JkFGq9c8kS5Vhbzs7Kff3IxtrKyMjArl270KxZs1yHGvgQcns2YIy9n0/gjsAY+1y9ffsWsbGxmD59Ovr27cuNWjratm0boqKicP/+fezfvx99+vSBr69vgTVqfUoSExOxYcMGHDx4EAMGDCjq5DDGGGNK6emAaqISZ+cia9QqdD16AO7uwNOnyrG2GGOsCHDDFmOsyMycORNVq1aFo6Oj1tmlmLo3b96gf//+8Pb2Rrdu3fDVV1/h77//LupkFYnq1aujb9++CAsLg5eXV1EnhzHGGAOIgPv3lTNSm5oqG7Y+VzIZMH688v/TpwPZZqlljLEPhWdFZIwVmdDQUISGhhZ1Mj45Xbp0QZcuXYo6GR+FgpiZkjHGGCtQCQlAUhJgYACUKKH893PWvTswder/ZkgcPLioU8QY+8J85qUsY4wxxhhjjH0gqanA48fK/7u5AXJ50abnQ8jea2vGDO61xRj74LhhizHGGGOMMcbeFxFw757yX0tLwN6+qFP04XTvzmNtMcaKDDdsMcYYY4wxxtj7SkgA3r4FDA0BT09AIinqFH04OXttpaUVbXoYY18UbthijDHGGGOMsfeRng7ExSn/7+ambOj50nTvrtz3p0+BL3RSG8ZY0eCGLcYYY4wxxhh7H48fK2dBNDMD7OyKOjVFQyYDunZV/n/16qJNC2Psi8INW4wxxhhjjDGWX0lJQGKi8v/Fi39ZryDmFBys/HfvXiA+vmjTwhj7YnDDFmPsi9CtWzd8++23RZ0MndSvXx9Dhw7VOfzhw4chkUjw33//FVqaGPtUpaam4uuvv4ZEIsHcuXOLOjmfBYVCgXbt2kEikWDIkCFFnZxP0oIFCyCRSFC3bl28ffu2qJPzyYmOjoaZmRkcHBxw8+bNok2MQgE8fKj8v4ODssfWl8zLC6hTR3lcIiKKOjWMsS8EN2wxxvTy6NEj9OzZEy4uLpDJZPDw8MCQIUPw8uXLok7aZ2Pr1q2YPHlyUSejUG3YsAESiUSnxsbLly/D398fcrkcrq6umDRpEohIFObIkSOoUaMGTExMULJkSSxZsqSQUq50//599OzZEyVKlIBcLkepUqUQEhKC9PT0XNcjIoSGhsLFxQVyuRz169dHbGysKMy7d+8waNAg2NnZwczMDK1atcJj1dTxH5GnT58iKCgIXl5eMDAwwLBhw3Ra7+HDh2jZsiXMzMxgZ2eHwYMHqx03Xc65LjIzM9G2bVu8ePECCxYswJgxY7BmzRq1cMuWLYOfnx+sra1hbW2Nb775BqdPn9Z7e+8rLS0N3bp1Q6VKlWBkZKRzY/z58+cREBCAYsWKwdbWFn369EFycrIozJAhQ1CjRg0YGxujatWq75XOfv364dixY1i6dClWrlypsbw6duwYfH19YWtrC7lcDm9v7w/SsPjq1SsEBwfDysoKVlZWCA4OzrPRX5frsm/fvihVqhTkcjns7e3RunVrXL9+PV9pjIiIwMiRI7FgwQIkJibi+++/R0ZGhtbwL1++hJub2wf5AUOXY5GTLtfP0aNH0bJlS7i4uEAikSAyMjLfabx69SpatmyJHj16wM/PDwEBARrLyPr160MikYj+OnTokO/tahUfrxwoXSoFXFwKPv5Pkep1RA3lLWOMFQZu2GKM6ezu3buoWbMmbt68ifXr1+P27dtYsmQJDhw4AB8fHySquuHnU24V+y+JjY0NLCwsijoZhebBgwcYMWIE/Pz88gyblJSEgIAAuLi44MyZM1i4cCFmz56NOXPmCGHu3buHZs2awc/PDzExMRg3bhwGDx6MLVu26Jymw4cPw9PTU+fw169fh0KhwNKlSxEbG4u5c+diyZIlGDduXK7rzZw5E3PmzMFvv/2GM2fOwMnJCQEBAXjz5o0QZujQodi2bRs2bNiAY8eOITk5GS1atEBWVpbO6ctLaGgounXr9l5xvHv3Dvb29hg/fjyqVKmi0zpZWVlo3rw5UlJScOzYMWzYsAFbtmzB8OHDhTC6nHNdEBG6deuGJ0+e4OjRoxg0aBD++usv9O/fHzt27BCFPXz4MDp27IhDhw4hOjoaxYsXR+PGjfHkyROdt7dq1SrUr19frzTmlJWVBblcjsGDB+Obb77RaZ24uDh88803KF26NE6dOoU9e/YgNjZW7fwSEXr06IEffvjhvdI4duxY7NmzB0ePHkWfPn0QFRWFuXPnYvHixaJwZmZmGDhwII4ePYpr165hwoQJmDBhAv744w+dt6XvdQkAQUFBuHDhAvbs2YM9e/bgwoULCFa9GqWFLtdljRo1EB4ejmvXrmHv3r0gIjRu3Fjv63LXrl348ccf8ddff2HQoEE4evQo4uLi0KVLFygUCo3r9OzZE5UrV9ZrOyoSiQT379/XObwuxyInXa6flJQUVKlSBb/99lu+9kPl/v37aNu2Lfr27YuFCxdi06ZNqFevHho3bqzxB7bevXvj6dOnwt/SpUvfa/tq3r1TDpQOAO7ugJFRwcb/qWrfXjne1qVLwIULRZ0axtiXgBhjheL169cEgF6/fq32XWpqKl29epVSU1OJiEihUFDyu+RC+0tKTaLHCY8pKTVJ7TuFQqHzPjVp0oTc3Nzo7du3ouVPnz4lU1NT+vHHH4VlAGjbtm2icFZWVhQeHk5ERPfu3SMAtHHjRvL39ydjY2NauXKlxu0CoEWLFlGTJk3IxMSEPD09adOmTaIwly5dogYNGpCJiQnZ2NhQ79696c2bN8L3Xbt2pdatWxMR0erVq8nGxobS0tJEcXz33XcUHBxMREQhISFUpUoVWrNmDXl4eJClpSX98MMPlJSUJIRPS0ujQYMGkb29PRkbG5Ovry+dPn1a+P7QoUMEgPbs2UNVq1YlExMTatCgAT179ox27dpF3t7eZGFhQR06dKCUlBRhPX9/fxoyZIjwee3atVSjRg0yNzcnR0dH6tixIz179kxtO69evdJ4/HJKTk4mCwsL+uuvv0TLt2/fTqamppSUlERZWVn06tUrysrK0ilOXWVmZpKvry8tX75cdE60WbRoEVlZWYnO1fTp08nFxUXIu6NGjSJvb2/Ren379qU6deronK5Dhw6Rh4eHzuE1mTlzJpUoUULr9wqFgpycnGjGjBnCsrS0NLKysqIlS5YQEdF///1HUqmUNmzYIIR58uQJGRgY0J49e4hImX/NzMzo5s2bQpiBAwdSmTJlKDk5Wae0hoSEUNeuXfXZvVz5+/vT4MGD88wzu3btIgMDA3ry5ImwbP369WRsbCyUlXmdc4VCQY0aNaLAwEAhD7x69Yrc3d1p3LhxwjqDBg2iWrVqUWJioigN+/btI1tbWzpy5IjWdGZmZpKFhQWtXr1a52MQHh5O/v7+OofPiy7XBxHR0qVLycHBQXTcY2JiCADdunVLLbyqbMupe/fuVKlSJeG4p6enU/Xq1SkoKEgIM2fOHCpdujQ9ePBAtG5MTAw5OjrS+vXrc01rmzZtqHPnzsLnvMoZfa/Lq1evEgA6efKksCw6OpoA0PXr1zWuo8t1qcnFixcJAN2+fZuIdLsujx07RnZ2drRv3z5RXImJiVSrVi3q37+/2nYWLVpE/v7+dODAAb3KeRUAdO/ePZ3C5vdY5JTX9aOpfnDt2jWSy+UUEREhLNuyZQsZGxvTpUuXiIjo2bNnVKZMGRo/frwoz2RlZVHfvn2pVq1aovt+zntpgVMoiG7eJDpzhuj6deXnj1TOeucH0bYtEUA0dOiH26YG6enpFBkZSenp6UWaDqLcnw0YY++He2wx9hF4m/EW5tPNC+3PMswSbovcYBlmqfbd2wzdxvZITEzE3r170b9/f8jlctF3Tk5O6NSpEzZu3Kj360KjR4/G4MGDce3aNQQGBmoN9/PPP+P777/HxYsX0blzZ3Ts2BHXrl1THr+3b9GkSRNYW1vjzJkz+Ouvv7B//34MHDhQY1zt2rVDVlYWtm/fLix78eIFdu7cie7duwvL7ty5g8jISOzcuRM7d+7EkSNHMGPGDOH7UaNGYcuWLVi9ejXOnz+P0qVLIzAwUK3nWmhoKH777TecOHECjx49Qvv27TFv3jz8+eef+OeffxAVFYWFCxdq3ff09HRMnjwZFy9eRGRkJO7du5dnbxuJRIJVq1Zp/M7MzAwdOnRAeHi4aHl4eDjatm2rtbfYtGnTYG5unuvfv//+m2u6Jk2aBHt7e/Ts2TPXcCrR0dHw9/eHsbGxsCwwMBBxcXFCL4To6Gg0btxYtF5gYCDOnj37QXsBvn79GjY2Nlq/v3fvHuLj40VpNTY2hr+/P06cOAEAOHfuHDIyMkRhXFxcULFiRSFMly5d0KxZM3Tq1AmZmZnYs2cPli5dioiICJh95GO7REdHo2LFinDJ9rpOYGAg3r17h3PnzglhcjvnEokEq1evxunTp7FgwQIAwI8//ghHR0eEhoYK6yxYsACnTp2CtbW1KA0BAQF48eIF6tWrpzWdb9++RUZGRq7n82Px7t07yGQyGBj8r0qnKqOPHTumczwLFixASkoKxowZA0BZ5r548QKLFi0SwgwbNgy3bt1C8eLFRetWrVoV8fHxub7mFRMTgxMnTsDf31/nNOkrOjoaVlZWqF27trCsTp06sLKyEq6fnHS5LnNKSUlBeHg4SpQoAXd3dwC6XZe+vr54/vw5AgICRPFZW1vj1KlT+P3330XLr169ikmTJmHNmjWi81tY8nMsNMnP9ePt7Y3Zs2ejf//+ePDgAeLi4tC7d2/MmDEDlSpVAgA4ODjg+vXrGDFihGhdAwMDLFmyBKdOnYK5ubnou4iICNjZ2aFChQoYMWJErj3P9Pbff8Dr18qB4j08vuwB4zXp0kX5759/AtwjnzFWyLi/LGNMJ7du3QIRoVy5chq/L1euHF69eoXnz5/DwcFB53iHDh2K7777Ls9w7dq1Q69evQAAkydPFhqDFi1ahIiICKSmpmLNmjXCA8Rvv/2Gli1bIiwsDI6OjqK45HI5goKCEB4ejnbt2gFQVn7d3NxErxIpFAqsWrVKaOgJDg7GgQMHMHXqVKSkpGDx4sVYtWoVmjZtCkA5zkhUVBRWrFiBkSNHCvFMmTIFvr6+AJSvlIwdOxZ37txByZIlAQBt27bFoUOHMHr0aI373qNHD+H/JUuWxIIFC1CrVi0kJyerVeJVvLy8YGVlpfV49urVC3Xr1kVcXBxcXFyEhr2oqCit6/z4449o37691u8BwNXVVet3x48fx4oVK3BBj9cS4uPj1V5FUp3P+Ph4lChRAvHx8Wrn2NHREZmZmXjx4gWcnZ113l5+3blzBwsXLsSvv/6qNUz8/88OpSmtDx48EMLIZDK1xhhHR0dhfQBYunQpKleujMGDB2Pr1q0ICQnBV199VVC7U2g0nStra2vIZDJh/3Q5566urli6dCmCg4Px7Nkz7NixAzExMZBKpQWSzjFjxsDV1VXn1wGLUsOGDfHTTz9h1qxZGDJkCFJSUoRXYp+qXpHSgbm5OdatWwd/f39YWFjg119/xYEDB3ItR3Th5uaG58+fIzMzE6GhoUI5Xhji4+M13n8cHBxE10/OdYDcr0uVRYsWYdSoUUhJSYG3tzeioqIgk8mE7wvyunz37h06duyIWbNmoXjx4rh7926+4tGHPsciN/m9fvr3749du3YhODgYMpkMNWrUeK/JCTp16oQSJUrAyckJV65cwdixY3Hx4sVc73M6y8oCHj1S/t/JCTAxef84PzdNmgD29kBCgnKGxBYtijpFjLHPGDdsMfYRMJWaInlsct4B80mhUCDpTRIsLSzVfvU1lZoWyDZUPbUkev5iWbNmTZ3C+fj4qH1WNZBcu3YNVapUEfVW8fX1hUKhwI0bN9Qq6YBy3I2vvvoKT548gaurK8LDw9GtWzdR+j09PUW9l5ydnZGQkABA2ZCRkZEhNFgBgFQqRa1atYSeZCrZx0ZxdHSEqamp0KilWpbbQNUxMTEIDQ3FhQsXkJiYKIzD8vDhQ5QvX17jOnkNalyrVi1UqFABa9aswZgxY7B27VoUL148114sNjY2+e7B8ubNG3Tu3BnLli2DnZ2dXuvmzFOa8pouYXLK3iiYlZWFd+/eiZb5+flh9+7deaYvLi4OTZo0ETW+5kZTWvO6bnKGsba2xooVKxAYGIi6desKvWy0+ffff4UGWEDZC5CIsHnzZmHZuHHjtI4Rlv24dO7c+b0G59e0rzn3T5fz2a5dO2zbtg3Tp0/H4sWLUbZs2XynKbuZM2di/fr1OHz4MExyeVjNef1lZmYiIyND52NVoUIFobFA17ymLZ7Vq1fjp59+wtixY2FoaIjBgwfD0dERhoaGesXl4+ODESNGYPLkyRg9enSu5YGu/v33XyQnJ+PkyZMYM2YMSpcujY4dO2oN/77XpS75S5f1NK3TqVMnBAQE4OnTp5g9ezbat2+P48ePC/lE3+syN2PHjkW5cuXQuXNnvdZr2rSpWs/ZChUqiPYl58QCOeWnjFLR9frRZuXKlShbtiwMDAxw5coVvesU2fXu3Vv4f8WKFVGmTBnUrFkT58+fR/Xq1fMdLwAgLg5ITweMjYEP8OPJJ0kqBTp1AubNUw4izw1bjLFCxA1bjH0EJBIJzGSF9wqRQqFAljQLZjKzfL/OULp0aUgkEly9elXjTF3Xr1+HtbW10GghkUjUXkvU9FrY+7w6parw5lbp1ra8WrVqqFKlCtasWYPAwEBcvnxZbUDpnL0/JBKJ0KikreFEU1qyxyORSHKNN6eUlBQ0btwYjRs3xrp162Bvb4+HDx8iMDAwzxn48tKrVy/89ttvGDNmDMLDw9G9e/dcHyKmTZuGadOm5Rrn7t27NQ4Kf+fOHdy/fx8tW7YUlqn22cjICDdu3ECpUqXU1nNyclLraaFqXFQ1WGoLY2RkBFtbW61pzd5z7NSpUxg9ejQOHz4sLMv5yq0mcXFxaNCgAXx8fPIcFNvJyQmAsldE9l5kCQkJon1JT0/Hq1evRL22EhISULduXVF8R48ehaGhIeLi4pCSkgJLS0ut265Zs6ZofxcsWIAnT54gLCxMWJZbo2X2dXPbTl6cnJxw6tQp0bJXr14hIyMjz/MJiHuSvH37FufOnYOhoSFu3bqV7zRlN3v2bEybNg379+/Pc7BuFxcX0XHZunUrtmzZgohs09vndqx27dollIm65LXcBAUFISgoCM+ePYOZmRkkEgnmzJmDEiVK6BWPQqHA8ePHC/SYqtJQqVIlPHv2DKGhobk2bL3Pdenk5IRnz56pLX/+/LnGHzhU6wC5X5cqqpkWy5Qpgzp16sDa2hrbtm0T7Y8+12VuDh48iMuXLwuNz6p7jp2dHcaPH4+JEydqXG/58uVITU0VPpcpUwa7du3KtTetij7HQhN9rh9tLl68iJSUFBgYGCA+Pl702vL7ql69OqRSKW7duvV+DVupqYAqnxUvDnyA10Q/WV26KBu2/v4bePUKyNEbmTHGCgqXxIwxndja2iIgIACLFi0SVZoBZSU4IiICP/zwg9AwYm9vL3oN5tatW3j7VrfxvDQ5efKk2mdvb28AQPny5XHhwgWkpKQI3x8/fhwGBga59uLo1asXwsPDsXLlSnzzzTfCWCm6KF26NGQymWgMm4yMDJw9e1br65r5cf36dbx48QIzZsyAn58fvL29hYf899W5c2c8fPgQCxYsQGxsLLqqpufW4scff8SFCxdy/dPWA8/b2xuXL18WhW3VqhUaNGiACxcuaD32Pj4+OHr0qKgRb9++fXBxcRFeV/Px8VF7tWTfvn2oWbNmrq+mlS5dWvhzdXWFkZGR2rLcPHnyBPXr10f16tURHh6eZ6Ox6pWY7GlNT0/HkSNHhEarGjVqQCqVisI8ffoUV65cETVsnThxAjNnzsSOHTtgaWmJQYMG5bptuVwu2jfVzJs5l+lyrPR51TgnHx8fXLlyRVQ27Nu3D8bGxqhRo4YQJq9zDgDDhw+HgYEBdu/ejQULFuDgwYP5ThcAzJo1C5MnT8aePXt06kmaM784ODioHefcjpWHh4fOeU1Xjo6OMDc3x8aNG2FiYqI2llNeZs2ahWvXruHIkSPYu3ev2jh874uI8O7du1zDvM916ePjg9evX4t6wJ46dQqvX79WaxhW0eW61HV/9L0uc7NlyxZcvHhRKC+XL18OQNkDbsCAAVrXc3V1FR0vQJzXVMs0eZ9joe/1o0liYiK6deuG8ePHo3v37ujUqZNafeN9xMbGIiMj4/1fT3/8WPmvlZXyj2lXtSpQqZKyd9umTUWdGsbY5+zDjlXP2JdDn1kRC1tBzXB38+ZNsrOzIz8/Pzpy5Ag9fPiQdu/eTRUrVqQyZcrQy5cvhbAdOnSgcuXK0blz5+jMmTPUsGFDkkqlarMixsTE5LldAGRnZ0crVqygGzdu0C+//EIGBgYUGxtLREQpKSnk7OxM33//PV2+fJkOHjxIJUuWFM36pmmGsdevX5OpqSnJZDLRLHREmmcOmzt3rmiGriFDhpCLiwvt3r2bYmNjqWvXrmRtbS3MwqZptsLw8HCysrLKdVvZZ3JKSEggmUxGI0eOpDt37tDff/9NZcuWFR07Tdvx8vKirVu35npciYiCgoJIJpNRkyZNRMsLa1bE7DSdk4ULF1LDhg2Fz//9958wE+Tly5dp69atZGlpSbNnzxbC3L17l0xNTWnYsGF09epVWrFiBUmlUtq8ebPOadF39rUnT55Q6dKlqWHDhvT48WN6+vSp8JddzvMwY8YMsrKyoq1bt9Lly5epY8eO5OzsLJpt88cffyQ3Nzfav38/nT9/nho2bEhVqlShzMxMIiJKSkqikiVL0k8//URERFeuXCETExO1mUJzU1CzIsbExFBMTAzVqFGDOnbsSEePHqXLly8L32/dupW8vLyEz5mZmVSxYkVq1KgRnT9/nvbv309ubm40cOBAIYwu53znzp0kk8no3LlzREQ0YcIEcnNzU5sBUVdhYWEkk8lo8+bNonOZfYa1vBTUrIixsbEUExNDLVu2pPr16wvHWOXUqVPk5eVFjx8/FpYtXLiQzp07Rzdu3KDffvuN5HI5zZ8/XxTvrVu3KCYmhvr27Utly5YV4n337h0RKc+lTCaj7du3ExHR8uXLycLCgu7cuZOv/fjtt99o+/btdPPmTbp58yatXLmSLC0tafz48UKYgp4VkUg5e2/lypUpOjqaoqOjqVKlStSiRQtRGH2vyzt37tC0adPo7Nmz9ODBAzpx4gS1bt2abGxshBlqC+K6zI2+s9+qQI9ZEYl0K6OCg4NpzJgxwmddrp83b94IeQ4AzZkzh2JiYkQzbLZr145q165NGRkZlJKSQl5eXmozRep6b7p9+zZNnDiRzpw5Q/fu3aN//vmHvL29qVq1akJZmi+vXytnQTxzhuhDzjD4nopkVkSVWbOUsyP6+Hz4bRPPisjYl4IbthgrJJ9jwxYR0f3796lbt27k5OREUqmU3N3dadCgQfTixQtRuCdPnlDjxo3JzMyMypQpQ7t27SIrK6t8N2z9/vvvFBAQQMbGxuTh4aE2rfylS5eoQYMGZGJiQjY2NtS7d29RpVpTIwqRsoJuY2MjTHGvokvDVmpqKg0aNIjs7OzI2NiYfH196fTp08L3BdGwRUT0559/kqenJxkbG5OPjw9t3749z4YtAMKxzo1qCvmcD19F1bAVEhKi9iB76dIl8vPzI2NjY3JycqLQ0FBS5JhW/fDhw1StWjWSyWTk6elJixcv1ist+j5Ah4eHEwCNf9nlPA8KhYJCQkLIycmJjI2NqV69eqKGICJlvho4cCDZ2NiQXC6nFi1a0MOHD4Xvu3fvTpUqVRLl2fnz55ONjY2osSM3BdWwpWn/sx9H1XHK7sGDB9S8eXOSy+VkY2NDAwcOVLv+cjvnCQkJ5OjoSNOmTRPCZ2RkUK1atah9+/b52g8PDw+N+xISEqJzHAXVsKUtLSqq6z17Y4WqHJPJZFS5cmVas2aNWrz+/v4a47137x6lpqZS+fLlqU+fPqJ12rRpQ3Xr1s1XQ8CCBQuoQoUKZGpqSpaWllStWjVatGiRqEwpjIatly9fUqdOncjCwoIsLCyoU6dOao1B+l6XT548oaZNm5KDgwNJpVJyc3OjoKAgun79uhCmIK7L3Hyohi1dyih/f39R+aHL9aNKf84/VTyrV68mMzMzunnzprDO2bNnSSaT0T///CMs0/Xe9PDhQ6pXr55wXZQqVYoGDx4s+gFObwoFUWysslErW4Pcp6BIG7bi4ogMDJSNW9nO74fCDVuMfRkkRDkGwWGMFYikpCRYWVnh9evXamNspKWl4d69eyhRokS+BlfVl0KhQFJSEiwt1QeP/xRIJBJs27ZN49he7ysgIADlypXDggULCjzuT0FERASGDBmCuLg40exen3qeYR8e5xmmL84zTF9FmmdevADu3wcMDYGKFZWDo38iPnS9U02zZsDu3cCECcDkyR900xkZGdi1axeaNWtWYDPn5lduzwaMsffDtQjG2BcpMTERGzZswMGDB3Mdr+Rz9fbtW8TGxmL69Ono27evqFGLMcYYY9lkZSlnQgQAJ6dPqlHro9Cli/LftWsBLZPlMMbY++CGLcbYF6l69ero27cvwsLC4OXlVdTJ+eBmzpyJqlWrwtHREWPHji3q5DDGGGMfr4QE5QDoMhmgwwyRLIfWrQFLS+DBA+Do0aJODWPsM2RU1AlgjLG8FMYb0/fv3y/wOD8loaGhCA0NLepkMMYYYx+3jAxANZOrqyvAr83qTy4H2rcHli8H1qwB6tcv6hQxxj4zXDIzxhhjjDHGmCZxccrX58zMABubok7Np6trV+W/f/0FpKQUbVoYY58dbthirAjx3A2MMcYYYx+p1FTg+XPl/93cAImkaNOTTx9FfdPXFyhZEkhOBnbtKurUMMY+M9ywxVgRUM3K8vbt2yJOCWOMMcYY0+jxY+W/xYoBFhZFmpT3oapvFumsgBIJoJrdevfuoksHY+yzxGNsMaZBZmYmQkNDERERgfj4eDg7O6Nbt26YMGFCgUwvbWhoiGLFiiEhIQEAYGpqCkkh/gqoUCiQnp6OtLQ0nlKd6YTzDNMX5xmmL84zTF8fNM8kJwOvXysbZOztgbS0wt1eISAivH37FgkJCShWrBgMDQ2LNkFNmwJz5igbtog+2R5wjLGPDzdsMaZBWFgYlixZgtWrV6NChQo4e/YsunfvDisrKwwZMqRAtuHk5AQAQuNWYSIipKamQi6XF2oDGvt8cJ5h+uI8w/TFeYbp64PlGSLlgPEZGcqeWnFxhbetD6BYsWJCvbNI+fkpxyqLjwcuXACqVSvqFDHGPhPcsMWYBtHR0WjdujWaN28OAPD09MT69etx9uxZreu8e/cO7969Ez4nJSUBADIyMpCRkaFxHTs7O1hbWyMzM7NQxz/IzMzEiRMnULduXRgZ8WXP8sZ5humL8wzTF+cZpq8PlWckO3bAaNw4kIUFMnftUr6K+AmSSCQwMjKCoaEhMjMzizo5gIEBDBs0gMHOncjauROKihULfZOqOri2uviH9DGkgbHPFdciGNPg66+/xpIlS3Dz5k2ULVsWFy9exLFjxzBv3jyt60yfPh0TJ05UW75v3z6YmpoWYmp1d/To0aJOAvvEcJ5h+uI8w/TFeYbpqzDzjCQjA41++gkmz57hanAwbp0/X2jb+hJ5urmhCoD/1q/HscqVP9h2o6KiPti2tOGxdRkrPBL6KKbJYOzjQkQYN24cwsLCYGhoiKysLEydOhVjx47Vuo6mHlvu7u548eIFLC0tP0SytcrIyEBUVBQCAgKKduBQ9sngPMP0xXmG6YvzDNPXh8gzBn/8AcOBA0GOjsi8fl356hwrOA8eQFqmDMjAAJlPnwLW1oW6uY+pnElKSoKdnR1ev35d5M8GjH1uuMcWYxps3LgR69atw59//okKFSrgwoULGDp0KFxcXNC1a1eN6xgbG8PY2FhtuVQqLfIbqcrHlBb2aeA8w/TFeYbpi/MM01eh5ZnUVGDaNACAZPx4SD/RVxA/aqVLA+XLQ3L1KqSHDwPt23+QzX4M5UxRb5+xzxlPQcOYBiNHjsSYMWPQoUMHVKpUCcHBwRg2bBimT59e1EljjDHGGGOFYdEi5UDxxYsDffoUdWo+X02bKv/dvbto08EY+2xwwxZjGrx9+1ZtGmlDQ0MoFIoiShFjjDHGGCs0SUmA6gfMkBBAQy98VkCyN2xx3ZoxVgD4VUTGNGjZsiWmTp2K4sWLo0KFCoiJicGcOXPQo0ePok4aY4wxxhgraPPmAS9fAmXLAl26FHVqPm9ffw2YmwPPngEXLgDVqxd1ihhjnzjuscWYBgsXLkTbtm3Rv39/lCtXDiNGjEDfvn0xefLkok4aY4wxxhgrSC9fArNnK/8/aRJgxL/9FypjY6BRI+X/+XVExlgB4IYtxjSwsLDAvHnz8ODBA6SmpuLOnTuYMmUKZDJZUSeNMcYYY4wVpJkzgTdvgCpVgHbtijo1XwbV64i7dhVtOhhjnwVu2GKMMcYYY4x9mZ4+BRYuVP5/6lTAgB+PPghVw9bJk0BiYtGmhTH2yeOSmzHGGGOMMfZlmjoVSE0FfHyAZs2KOjVfjuLFgQoVlIPH79tX1KlhjH3iuGGLMcYYY4wx9uW5dw/44w/l/6dNAySSok3Plyb77IiMMfYeuGGLMcYYY4wx9uWZOBHIyAC++QaoX7+oU/PlUfWQ27NH2XOLMcbyiRu2GGOMMcYYY1+W69eBtWuV/586tWjT8qXy9QXMzYGEBOD8+aJODWPsE8YNW4wxxhhjjLEvy+TJyl5CrVoBtWoVdWq+TDKZsrccwK8jMsbeCzdsMcYYY4wxxr4c168D69cr/x8aWqRJ+eKpXkfkhi3G2Hvghi3GGGOMMcbYl2PyZIAIaN0aqFatqFPzZVMNIH/yJPDyZdGmhTH2yeKGLcYYY4wxxtiXIXtvrZCQok0LA9zcgIoVlQ2N+/YVdWoYY58obthijDHGGGOMfRm4t9bHR/U64q5dRZsOxtgnixu2GGOMMcYYY5+/69eBDRuU/+feWh8P1euIe/cqB/RnjDE9ccMWY4wxxhhj7PM3Zcr/ZkLk3lofD19fwMICeP4cOHeuqFPDGPsEccMWY4wxxhhj7PPGY2t9vKRSoFEj5f/37y/atDDGPkncsMUYY4wxxhj7vGXvrVW9+v+xd9fxVZZvHMc/Zz1gwAaM7u7uLukUFQFpEAlB4KcoUgooCAqodEsICCjdpXRJd3cNNnIszu+Pxw0VUMBt9znb9/16ndd5dhbPd/h4tnPtuq/bdBr5u3LlrPstW8zmEBGnpMKWiIiIiIjEXseOqVvL0ZUqZd1v2aI5WyLy0lTYEhERERGR2CuiW6tOHXVrOaqCBcHLCwICrEKkiMhLUGFLRERERERip2PHYNYs61jdWo7LwwOKFbOON282m0VEnI4KWyIiIiIiEjv9uVurcGHTaeSflC5t3WvOloi8JBW2REREREQk9jl+XN1aziSisKWOLRF5SSpsiYiIiIhI7DN4sNWtVbu2urWcQcmS1v3x43DjhtksIuJUVNgSEREREZHY5fRpmDHDOu7Tx2wWeTF+fpAzp3Ws5Ygi8hJU2BIRERERkdhlyBAIC4PXXnsylFwcn5YjisgrUGFLRERERERijwsXYMoU61jdWs5FA+RF5BWosCUiIiIiIrHHV19BSAiULw9lyphOIy8jorC1axcEB5vNIiJOQ4UtERERERGJHa5ehQkTrONPPzWbRV5eliyQLJlV1Nq923QaEXESKmyJiIiIiEjsMHw4PHoEJUpA5cqm08jLstk0Z0tEXpoKWyIiIiIi4vxu3oQxY6zjTz+1iiTifEqVsu5V2BKRF6TCloiIiIiIOL8RI+D+fShYEGrWNJ1GXtWfB8jb7WaziIhTUGFLRERERESc25078O231rG6tZxb4cLg6Qk3bsDJk6bTiIgTUGFLRERERESc23ffQVAQ5M4N9eubTiP/hacnFCliHWs5ooi8ABW2RERERETEed29C998Yx337g0ueonj9DRAXkRegp71RURERETEeY0dCwEBkDUrvPmm6TQSFVTYEpGXoMKWiIiIiIg4p4cPYdgw6/jjj8HV1WweiRolS1r3R45YRUsRkX+gwpaIiIiIiDinCRPg+nVInx6aNTOdRqJKsmSQLZt1vHWr2Swi4vBU2BIREREREefz+DF89ZV1/NFH4O5uNo9ELS1HFJEXpMKWiIiIiIg4n+nT4eJFSJkSWrUynUaimgpbIvKCVNgSERERERHnEhoKX35pHffoAV5eZvNI1IsobO3YYXXniYg8hwpbIiIiIiLiXObNg1OnwM8P3n3XdBqJDtmzW/99Hz2CvXtNpxERB6bCloiIiIiIOI/wcBg82Dru1g0SJDAaR6KJzQalSlnHW7aYzSIiDk2FLRERERERcRq2JUvg4EHw8YHOnU3HkeikOVsi8gJU2BIREREREedgt+MSMVurUyfw9TWbR6LXnwtbdrvZLCLisFTYEhERERERhxYWbmfHmQCS7d+Py65d2L294YMPTMeS6FakCLi7w9WrcOaM6TQi4qBU2BJ5jkuXLtGsWTOSJElCvHjxKFCgALt37zYdS0RERCROWXHwCmWGrKP1tJ1knTcPgLkFqrPiepjhZBLtvL2hcGHrWMsRReQ5VNgSeYbbt29TunRp3N3dWb58OYcPH2b48OEkTpzYdDQRERGROGPFwSu8N2MPVwIfUfDiEZIdPMhjFzdGFqjLezP2sOLgFdMRJbpFDJDfscNsDhFxWG6mA4g4oiFDhpA2bVqmTJkS+ViGDBnMBRIRERGJY8LC7QxYfJiIyUodNs8F4Je8FbmcMBk2YMDiw1TNlQJXF5uxnBLNCha07n//3WgMEXFcKmyJPMOiRYuoVq0ab7zxBhs3biR16tR07NiRdu3aPfdzgoODCQ4Ojnw7KCgIgJCQEEJCQqI98z+JOL/pHOI8dM3Iy9I1Iy9L14z8mx1nAgi49xBPV8hx7TQVTu3C7uLC1NKv4+lqlbsC7j1k28nrFMvoZzitRJs8eXAH7L//TmhwMLi8+KIjR3qecYQMIrGVzW7X9hIif+fl5QVA9+7deeONN9ixYwfdunVj3LhxNG/e/Jmf079/fwYMGPDU47NmzSJevHjRmldEREQkNisydCipt2zhYtmy7O7Rw3QciUG2sDBqNW6Ma0gIa8aM4X7KlKYjvZIHDx7QpEkTAgMDSZgwoek4IrGKClsiz+Dh4UGRIkXYsmVL5GPvv/8+O3fuZOvWrc/8nGd1bKVNm5abN28a/+EVEhLC6tWrqVq1Ku7u7kaziHPQNSMvS9eMvCxdM/JvdpwJoPW0nWS6eYGl4zvhgp11I0fS7UZGgsOfLD2c3KKoOrZiOdeSJXHZvZvQ2bOxv/76C3+eIz3PBAUFkTRpUhW2RKKBliKKPEPKlCnJlSvXXx7LmTMn8+fPf+7neHp64unp+dTj7u7uxn+QRnCkLOIcdM3Iy9I1Iy9L14w8T4ks/vgl8KbNovm4YGdNtuLcT5+e4Gs2gsNs2IAUibwokcVfM7Ziu0KFYPdu3A4cgMaNX/rTHeF5xvT5RWIz7Yoo8gylS5fm2LFjf3ns+PHjpE+f3lAiERERkbjF1cXGl4V8qH9oPQBjS70Z+b6IMla/OrlU1IoLChSw7jVAXkSeQYUtkWf44IMP2LZtG4MHD+bkyZPMmjWL8ePH06lTJ9PRREREROKM8oum4WYPZ0eWQhxIlS3y8RSJvBjTrBDV8zjnvCV5SSpsicg/0FJEkWcoWrQoCxcu5OOPP+azzz4jY8aMjBgxgqZNm5qOJiIiIhI3XLkCkyYBUHjcMCanycXNI9uY3KKolh/GNfnygc0Gly/D9evg7286kYg4EBW2RJ6jdu3a1K5d23QMERERkbjp668hOBhKlcK1YgWKhYay7AgUy+inolZckyABZM0Kx49bXVuvvWY6kYg4EC1FFBERERERx3LrFowZYx337m1160jcFrEcce9eozFExPGosCUiIiIiIo5l1Ci4f98qZtSoYTqNOIKCBa17zdkSkb9RYUtERERERBxHUJBV2AL45BN1a4lFA+RF5DlU2BIREREREccxZgzcuQPZs0PDhqbTiKOIKGwdO2Z184mI/EGFLRERERERcQwPH1pD4wE+/hhcXc3mEceRIoV1s9vhwAHTaUTEgaiwJSIiIiIijmHSJLh+HTJkgCZNTKcRR6PliCLyDCpsiYiIiIiIeY8fw9Ch1vGHH4K7u9k84ngiBshrZ0QR+RMVtkRERERExLwZM+DCBUiZElq1Mp1GHJE6tkTkGVTYEhERERERs8LC4MsvreMePcDLy2wecUwRha39+yE01GgUEXEcKmyJiIiIiIhZ8+bBiRPg5wfvvms6jTiqLFkgfnx49AiOHzedRkQchApbIiIiIiJiTng4DB5sHXftCgkSmM0jjsvFBfLnt461HFFE/qDCloiIiIiImLN4MRw4AD4+0KWL6TTi6CKWI2qAvIj8QYUtERERERExw26HgQOt486dwdfXbB5xfBE7I6pjS0T+oMKWiIiIiIiYsXIl7NoF8eLBBx+YTiPO4M87I9rtJpOIiINQYUtERERERGKe3Q6ff24dd+gAyZKZzSPOIU8ecHWFmzfh0iXTaUTEAaiwJU4jODjYdASnFBZuZ8eZAAB2nAkgLFx/2RIREREHsGEDbNkCnp7Qs6fpNOIsvLwgZ07rWMsRRQQVtsSBrVy5kpYtW5I5c2bc3d2JFy8ePj4+lC9fnkGDBnH58mXTER3eioNXKDNkHa2n7QSg9bSdlBmyjhUHrxhOJiIiInFexGyttm0hZUqzWcS5/Hk5oojEeSpsicP5+eefyZ49Oy1atMDFxYX//e9/LFiwgJUrVzJp0iTKly/PmjVryJQpEx06dODGjRumIzukFQev8N6MPVwJfPSXx68GPuK9GXtU3BIRERFztmyBdevA3R0+/NB0GnE22hlRRP7EzXQAkb8bPHgww4YNo1atWri4PF17ffPNNwG4dOkSI0eOZPr06fTo0SOmYzq0sHA7AxYfxg7Y7OFku/gt5y4G4J68PcEuqbEBAxYfpmquFLi62EzHFRERkbgmolurRQtIl85sFnE+2hlRRP5EhS1xODt27Hihj0udOjVDhw6N5jTOaceZgMhOLbvNhf1+a1mSOBx4F7fwFHiG5yboXi7m/R6ftwoWx2ZTcUtERERiyO7dsHy5NQC8Vy/TacQZ5c9v3Z8+DYGBkCiR2TwiYpSWIopD27Bhg+kITun63SfLD+2EUuyyHwWuAHYIdbnKfbe1BHh8y9uLS5J8WHIazW3EjP0zCHwUaC60iIiIxA2DBln3TZpA5sxms4hzSpIE0qa1jvftM5tFRIxTYUscWvXq1cmcOTMDBw7kwoULpuM4DX8fr8hjG27UPlOKvePgu9U18Q8eQMKQt/AMy4OHiyc3Htxg/pH5vLPwHfyH+VNndh2m/T6N2w9vG/wOREREJFY6cAAWLgSbDT7+2HQacWZajigif1BhSxza5cuX6dq1KwsWLCBjxoxUq1aNuXPn8vjxY9PRHFqxjH6kTORFxALD48ms2RX5rlzBO7wwfqHvUNB7BLc/usPm1pvpU64POZLm4HHYY5YcX0LLX1riP8yfGjNrMGnPJO4G3zX3zYiIiEjsMXiwdd+oEeTMaTaLODcNkBeRP6iwJQ7Nz8+P999/nz179rBr1y6yZ89Op06dSJkyJe+//z771Hr8TK4uNvrVyQWADTiRLD0A2W6ciyx29auTi3geXpRKW4rPKn7GkU5HONTxEAMqDCCvf15Cw0NZcXIFbRe3JeXwlLy7+F32XNlj5hsSERER53fsGMyZYx1/+qnZLOL8Igpb6tgSifNU2BKnUaBAAXr16kWnTp24f/8+kydPpnDhwpQtW5ZDhw6ZjudwqudJyZhmhUiRyIuTSa2OreT3Asjm/pgxzQpRPU/Kpz4nV7Jc9C3fl/3v7edop6MMqjSI7Emycz/kPuP3jKfw+MIUm1CMSXsmcf/x/Zj+lkRERMSZffEF2O1Qty7ky2c6jTi7iKWIhw6BVnOIxGkqbInDCwkJ4aeffqJmzZqkT5+elStX8t1333Ht2jXOnDlD2rRpeeONN0zHdEjV86Tkt48q8W378jxIlgyAZVWSPLOo9XfZk2bnk7KfcKTTETa02EDjPI1xd3Fn5+WdtF3cllRfp6Lzss4cv3U8ur8NERERcXanTsGMGdaxurUkKqRPb+2GGBIChw+bTiMiBqmwJQ6tS5cupEyZkg4dOpAtWzb27t3L1q1badu2LfHjxydt2rR8+eWXHD161HRUh+XqYqNYRj+C0lvLEV0Pv1x3m81mo3yG8sx+fTaXul9iaJWhZPHLQlBwEN/v/J4c3+Xg9bmvs+PSjuiILyIiIrHBoEEQFgY1akDRoqbTSGxgs2k5oogAKmyJgzt8+DDffvstly9fZsSIEeTJk+epj0mVKhXr1683kM653E1nLUfk4MFX/hrJ4ifjf6X/x7HOx1j9zmrqZKuDHTsLjiyg+MTiVJxWkRUnV2C326MotYiIiDi906dh+nTruF8/s1kkdolYjqgB8iJxmpvpACL/ZO3atf/6MW5ubpQvXz4G0ji3oCgobEVwsblQJVMVqmSqwuEbh/lqy1fM2D+DDWc3sOHsBvInz8+HpT/kzdxv4uaipxkREZE4bfBgq1urenUoXtx0GolN8ua17rUUUSROU8eWOJytW7e+8Mfev39fg+Nf0F8KW1HYUZUrWS6m1JvCma5n6F6iOwk8ErDv2j6aLmhKzu9zMmP/DMLCw6LsfCIiIuJEzpyBadOsY3VrSVTLmdO6P3LEbA4RMUqFLXE4zZs3p2rVqsydO5d79+4982MOHz7MJ598QpYsWdizZ08MJ3RO99Kkwe7iAgEBcPVqlH/9NAnTMLzacM53O8/AigNJGi8pJwNO8s7Cd8g7Ji9zD80l3B4e5ecVERERBzZ4MISGwmuvQYkSptNIbJMjh3V/6RLcvWs2i4gYozVC4nAOHz7MuHHj6Nu3L02bNiVbtmykSpUKLy8vbt++zdGjR7l//z4NGzZk9erVz5y7JU8L9/CALFng+HGrayvlv++M+Cp8vX3pXa43XUt05bsd3zF081CO3DzCWz+9RV7/vAyoMID6Oepjs9mi5fwiIq/Kbrdz59Edzgee51zgOS4EXiDgYQCBwYHceXQn8hYYHEjgo0BCw0Of+7XiucfD19sXP28/fL18rdsfb6dIkILMvpnJ7JeZhJ4JY/A7FIlhZ8/C1KnWsbq1JDr4+kLy5HDtGhw9qo0JROIoFbbE4bi7u9O5c2c6d+7Mnj17+PXXXzl79iwPHz4kf/78fPDBB1SsWBE/Pz/TUZ2OPXdubBGFrapVo/VcCTwS0KtMLzoW7ciIbSMYvnU4B64foOHchhRMUZCBlQZSI0sNFbhEJMbdfHCTg9cPcvD6QY7cOMLZwLOcu3OO84Hnufs4Zv/inzRe0sgiV2bfzORImoNiqYuR2Teznh/F+X3xhdWtVbUqlCplOo3EVjlyqLAlEsepsCUOrVChQhQqVMh0jFjDnjs3LFwYJQPkX1RCz4T0Ld+XLsW6MHzrcEZuH8neq3upNasWFTJUYGiVoRRNrV9CRCTqhYaHcvD6QXZd3hVZyDp4/SDX7l/7x89LFi8Z6RKlI12idCSNl5TEXolJ5JmIxF6JrWOvRCTyTIS7q/szP99ut3M/5D63H97m9qPbf7kPeBTApaBLnAw4yY0HN7j54CY3H9xk+6Xtf/kavl6+FE1dlGKpilEsdTGKpi5KigQpouzfRiTanTsHkydbx+rWkuiUMyds3Kg5WyJxmApbInGIPXdu6yAGC1sRfL19GVhpIN1KdOPL377kux3fseHsBopNLMabud9kcKXBZPbLHOO5RBzagwfWi8OzZ61bQMCT90V080Tce3lBunSQIYN18/N78r444vr962y7uI1tF7ex9eJWdl7ayf2Q+8/82Ey+mcjjn4dcSXORyTcT6ROnJ32i9KRNlJZ47vFiJG9QcBCnb5/mVMApTt0+xcmAkxy4foC9V/Zy+9FtVp1axapTqyI/PkPiDFTLXI2aWWtSKWMlEngkiJGcIq8kolurcmUoXdp0GonNIuZsHT1qNoeIGKPClkgcYs+Vyzo4dAjCw8El5vePSBovKcNeG0aXYl3ou6EvP+z7gbmH5rLgyAI6FO5An/J98I/vH+O5RIwKDobt22HDBuv/z4hC1vXrr/41EyR4UuTKnNlaBlS2bLTN1zPhyt0rrDuzjjVn1rDp3CZO3z791Mf4ePhQLHUx8ifPTx7/POTxz0POZDkdoiiU0DMhBVIUoECKAn95/HHYYw5cO8COSzvYeXknOy7t4PCNw5y9c5Zxu8cxbvc4PFw9KJe+HDWz1KRG1hpkT5JdSxfFcZw/r24tiTnaGVEkzlNhSyQuyZIFPDzg/n2rCyRjRmNR0idOz7T60+heojsfrfmIladW8t3O75i6byoflf6IHiV74O3ubSyfSLQKCYGdO2H9euu2ZQs8fPjsj02Y0Pp/NUMGSJbM6sKy2633RdwD3Lv3pLvr6lXr7YMHn3Rojhxp3WfNCuXKPbmlT+80nV2BjwLZeG4ja0+vZc2ZNRy+cfgv77dhI1eyXJRIU4ISaUpQMk1JciTNgauLq6HEr8bD1YPCqQpTOFVh3uM9AO4G3+XX87+y7MQylp1Yxpk7Z1hzeg1rTq+h+6ruZPLNRJM8TXgn/ztkS5LN8Hcgcd4XX1jPc5UqWQV1kegU0bF18qR13bk/e5m4iMReKmyJxCXu7tYP//37rRe7BgtbEfKnyM+KZitYe3otH675kD1X9tBnfR/G7x7PF5W/4O28b+Nii/nOMpEo9/gxLFli7RC2bp1VYP4zf3+oWBGKFYNMmZ50WyVO/PLnevTI6piI6Pw6dAh+/RV+/x1OnLBukyZZH5s2LTRsCE2bQpEiDlXkstvtHLl5hCXHl7D4+GK2XthKmD0s8v02bBRKWYjKGStTKWMlSqQpQSKvRAYTRx8fTx9qZq1Jzaw1sdvtHL913CpynVwW2a028NeBDPx1ICXSlKB5vua8lect/Ly10YrEsAsXnjy/qFtLYkKaNBA/vvVz9dSpJ4UuEYkzVNgSp/Ho0SO8vLxMx3B+efI8KWzVqWM6TaTKmSqzs91Ofjz4I73W9OJC0AWaLWzGqB2j+Pq1rymdTvM5xEkdPmy9yPvhB7hx48njSZJAhQpWMatiRWspRVQVlby8IFs26/Znd+5Y3WGbNlm3nTutF6EjR1q3rFmtAleTJtaxASFhIWw6t4nFxxez+Pjip5YXZvXLSpVMVaicsTIVM1aMk4Ubm81G9qTZyZ40Ox+U/IB7j++x5PgSftj/AytProycM9Z1RVdqZ6tN8/zNqZ2tNm4u+rVPYsCXX1pdMxUqWF2hItHNxQWyZ4c9e6w5WypsicQ5+g1HHFp4eDiDBg1i7NixXLt2jePHj5MpUyb69OlDhgwZaNOmjemIzidPHuv+0CGzOZ7BxeZCk7xNaJCjAd9s+4YvfvuCHZd2UGZKGd7M/SZfVv6SjL7mu8xE/lVQEMyZY82Y2bbtyeMpU0KLFtC4MeTNG/Nz7hInhpo1rRtYf91etw5mzYJffrE6ufr3t25Fi1pFrnfesQbRR6OHIQ9ZcXIF8w7PY+mJpQQFB0W+z8PVg0oZK1EnWx1qZa1F+sTpozWLM0rgkYDGeRrTOE9jrt67yuwDs5m+fzq/X/2dhUcXsvDoQtIlSkfX4l1pW6gtCT0Tmo4ssdX58zBxonWsbi2JSTlzWoWtI0egfn3TaUQkhml9jzi0gQMHMnXqVIYOHYqHh0fk43nz5mVixC9O8nIiClsGdkZ8Ud7u3nxS9hNOdDlB24JtsWFj7qG55Pw+J73W9OJu8F3TEUWe7fZt+PRTSJ0a2re3ilpubtYv2YsXWy/6vvgC8uc3snnDU+LHtzo3Z8+2BtX/8ANUrw6urlY3V7du1k6LXbtaSxqj0MOQhyw8spAm85vgP8yfhnMbMvvgbIKCg0gWLxmtCrRiwZsLuPXhLZY3XU7Hoh1V1HoBKRKk4IOSH7D33b3s67CPniV7kjReUs4HnqfHqh6k/SYtPVf15HzgedNRJTYaONBadl2hgnUTiSnaGVEkTnOA36pFnm/69OmMHz+epk2b4ur6ZPhvvnz5OKofXK8morB15Ii1DbcDS5EgBRPqTmDvu3upnLEywWHBDNk8hKzfZmXy3smE28NNRxSx3L1rvaDLmBEGDbIGt+fIAV99BRcvwsKFULu2VeRyVAkSQLNmsHw5XL4M334LBQpYXV2jRlmbTzRpAnv3PvWpYeF2dpwJAGDHmQDCwu1PfQxAcGgwPx/9+ali1r3H90iXKB3dS3Rnc+vNXOlxhcn1JtMgZwOH2L3QWeVLno+vXvuK893OM772eHIkzUFQcBDDtw4n08hMNJnfhF2Xd5mOKbHFqVMwZYp1PHCg2SwS90TsjKjXByJxkgpb4tAuXbpElixZnno8PDyckJCQGMvxxRdfYLPZ6NatW4ydM9qkT291aTx+bO0e4wTyp8jP6ndWs6jxIrL6ZeXa/Wu0WdSGohOK8uu5X03Hk7js4UMYNswqaPXpA4GBkDs3LFhgzdbq2ROSJzed8uX5+0PnztayjtWroWpVCAuzOrsKFbLeXrUK7HZWHLxCmSHraD1tJwCtp+2kzJB1rDh4BYBwezi/nf+NDks6kHJ4ShrMafCXYlaPkj3Y1mYbZ7ueZXi14ZRKW8rpdjF0dN7u3rQr3I5DHQ+x5O0lVMxQkTB7GLMPzqbohKLUmFmD36/+bjqmOLvPPrP+YFa9OpTWXEyJYREdW0eO/HXHYBGJE1TYEoeWO3dufv316cLFvHnzKFiwYIxk2LlzJ+PHjydfvnwxcr5o5+JivfAGh16O+Hc2m4062etwsONBhr82nISeCdlzZQ/lppbjrZ/e4tydc6YjSlwSGgrffw+ZM8P//ge3blnD1mfNgn37oEEDh9pd8JXZbFClilXE2rPH6thydYU1a6BaNe4UKMLEL2dwJfDRXz7tauAj2sz8hbfndCPzqMyUnVKWcbvHcfvRbVL5pKJ7ie6Rxaxhrw2jeJri2GLDv5eDc7G5UCtbLda1WMee9ntolq8Zbi5urDi5goLjCtJkfhNOBjjHHzzEwRw9CjNmWMeff242i8RNWbJYP5/u3oUrV0ynEZEYpsKWOLR+/frRuXNnhgwZQnh4OAsWLKBdu3YMHjyYvn37Rvv57927R9OmTZkwYQK+vr7Rfr4Y4wRztp7Hw9WD7iW7c6LLCdoXao+LzYW5h+aS4/sc9FnXh/uP75uOKLHdnj1QrJjV0XTlitUFOXmy1aH19tvWL9axUcGCMHOmtdyoa1fs8eKReP8efpr5IaMXDiZdwGXuhd7jjstSLnt+wGWv9/jx6EjO3jmLj4cPLQu0ZM07azjf7TzDqw1XMcuwgikL8kODHzjS6Qhv53kbgNkHZ5Pz+5x0XNqRq/euGk4oTqV/fwgPh3r1oEgR02kkLvL0hEyZrOMjR8xmEZEY58DDPkSgTp06zJkzh8GDB2Oz2ejbty+FChVi8eLFVK1aNdrP36lTJ2rVqkWVKlUY+C/zIoKDgwkODo58OyjI2tUrJCQkRpdNPkvE+SPuXXLmxBUI37+fMMPZXpWvhy/fVf+OdgXb0XN1Tzae38jAXwcyee9kBlYcSJM8TXCxqXb/qv5+zQjw8CEun3+OyzffYAsLw+7rS/iAAYS3bg0eHtbSh7jw75UqFXz1FXsbteZMlw9puG8V7qFb8Lu5ldb7bTx2+2P2nd2F+PZCfFimLV1LNyaeezwAwsPCCQ/TfDxHkd4nPdPqTqNbsW703dCXladXMmbXGKbtm0aXol3oWaInibwSRcu59TwTS+zfj/ucOQCE9OkTrc+Dumbkn7hmz47LiROEHTpEeLlygGNdM46QQSS2stntWoQs8iw//vgjgwYNYufOnXh5eVGhQgUKFCjAiBEjnvnx/fv3Z8CAAU89PmvWLOLFixfNaV9Ost9/p1T//txNnZp1339vOs5/Zrfb2Ra4jamXp3Lt8TUAssbLStvUbckeP7vhdBIbJDl4kAKjR5Pg8mUALpUqxYH27QlOnNhsMIOuBV9jXcA61t9YxfXw25GP57lho6ZrUfKUbE9C76QGE8qrOHD3ADOuzODYg2MA+Lr50jp1a8okLqMOO3mmYoMHk3LHDi6WKcPunj1Nx5E4LNe0aWRduJDTNWtyoH1703Ge8uDBA5o0aUJgYCAJEyY0HUckVlFhS+QZLly4QJEiRVi1ahX58+cH+NfC1rM6ttKmTcvNmzeN//AKCQlh9erVVK1aFXd3d7hyBff06bG7uBB65w54eRnNF1UehT7i253f8sXmL7j3+B4AjXM3ZnDFwaRJmMZwOufy1DUTVwUG4vLJJ7hOmACAPVUqwkaNwl63ruFgZjwOe8yi44uYtHcSa8+ujXzcxR6fHHdyMfrXC5TbcxUbcMYvNZ/W7EzHPq0oltHPXGh5aXa7nUXHF/HJ+k84EXACgCoZqzCy2kiy+mWNsvPoecb52Xbvxq1kSev3id9/fzLAO5rompF/Yps+Hbe2bQmvVImwFSsAx7pmgoKCSJo0qQpbItFASxHF4fj6+r7wX4UDAgKiJcPu3bu5fv06hQsXjnwsLCyMTZs28d133xEcHIzr3+boeHp64unp+dTXcnd3N/6DNEJklrRpwc8PW0AA7qdOQYECpqNFCXd3dz4p9wmtC7Wm99reTPl9Cj8e+pFfjv3CR6U/4n+l/xe5HEpejCNdvzFu3Tpo3hwuXbLebt8e29ChuCWKnmVZjuzErRNM2DOBqb9P5caDGwDYsJHQVgj34ErECytJaHx37vR+TO/JG+m24QcyBlxi5oyPCY9/FpchQyAO/rs5s0Z5GlEnRx2Gbh7KoF8HsebMGgpNKMQnZT/ho9If4en29M+7VxWnn2ec3R+d6rZmzXDPmzfGTqtrRp7pj82RXI4exeVv14cjXDOmzy8Sm6mwJQ7neR1RMaly5cocOHDgL4+1atWKHDly8NFHHz1V1HI6Nps1QH7TJmuAfCwpbEVIkSAFk+pNomPRjnRb2Y3fzv9G/439mbh3Il9U/oImeTV/S/5BeDh8+SX06WMdZ8kCEyZAhQqmk8Wo4NBgFh5dyPjd41l/dn3k4ykTpKRNwTa0KdSGoxc9eW/Gnj/eYwdXV+bnr8qSLKX4eMMU3t63Epdx42DJEhg9GuJop5uz8nTzpE/5Pryd9206LevEqlOr6LehHzMPzGR0zdFUzlTZdEQxafNmWLEC3NwgBjb0EflXER2Dly9DUBCoK0okzlBhSxxOixYtTEfAx8eHPBE7B/4hfvz4JEmS5KnHndafC1uxVOFUhdnUchPzDs/jw9Ufci7wHO8sfIdR20fxdbWvKZOujOmI4mhu37a6tJYssd5u1Qq++w4cbE5edDp9+zTjdo1j8u+TufngJmB1Z9XMWpN2hdpRK1st3FysXx8yJIYxzQoxYPFhAu49jPwa8ZMnxXfGFLhxFNq3h5Mnrd3S3nwTRo2C5MlNfGvyirL4ZWFF0xXMPTSXbiu7cfzWcar8UIXm+ZszqvqoaBsuLw6uTx/rvlUryJzZbBYRgMSJIUUKuHoVjh61djAWkThBhS1xeGFhYSxcuJAjR45gs9nImTMn9erVw81Nl+9/ElGgi8WFLQCbzcabud+kbva6jNg2gsG/Dmbn5Z2UnVKWN3K9wZAqQ8jom9F0THEEe/ZAo0Zw5oy1bfj330ObNqZTxYjQ8FCWHF/C2F1jWXlqZeTjqX1S07ZQW1oXbE26ROme+bnV86Skaq4UbDt5nZtHtjG5RVFKZPHH1cUGpIT9+63lSsOGwdy5sHo1jBwJzZpZ3aPiFGw2G2/leYvqWarTZ30fvtvxHdP3TWfj2Y380OAHyqYvazqixKR162D9emtH2E8/NZ1G5ImcOVXYEomDtBZHHNrBgwfJli0bLVq0YOHChSxYsIAWLVqQNWvWp5YKRrcNGzY4xDLJKBNHClsRvNy86FWmFye6nKB9ofa42FyYd3geOb7PwUerPyLwUaDpiGLSpElQqpRV1MqYEbZujRNFrUtBlxiwYQAZRmSgwZwGkUWtapmrsfCthZztdpb+Ffo/t6gVwdXFFjkgvlhGvz+KWn/w9raWdu7YAQULPumKa9IEAvX/nbNJ5JWIUTVG8Vvr38iYOCPnAs9Rfmp5Pln7CY/DHpuOJzHBbn/SrfXuu5Dun58fRGJUxHLEI0fM5hCRGKXClji0tm3bkjt3bi5evMiePXvYs2cPFy5cIF++fLR3wG18ncofAzY5d86aQxBHJE+QnHF1xvH7u79TJVMVHoc9ZuiWoWQelZmR20bqhVlc8/AhtG4NbdtCcDDUqQO7d1sFmFjKbrez9vRaGs1tRPoR6em/sT+X7l4iabykfFjqQ052OcmKZiuon6N+5JLDKFGokFXcGjgQXF3hxx+t+X5bt0bdOSTGlEpbin0d9tGqQCvs2Pnity8oOakkR28eNR1NotvSpbBli7Wj8scfm04j8lc5c1r3R/VcJBKXqLAlDm3fvn188cUX+Pr6Rj7m6+vLoEGD+P33380Fiw38/CBVKuv48GGzWQzImzwvq5qtYsnbS8iZNCe3Ht6i28pu5Pw+J3MOzsFut5uOKNHt5k2oVAmmTAEXFxg8GH7+Gf70fBOb3H54mxHbRpDz+5xU+aEK84/MJ8weRpl0ZZjVcBYXP7jIkKpDyOwXjbNy3Nygd2/47TerM+7sWShb1ip2hYVF33klWvh4+jC53mR+euMn/Lz92HNlD4XGFWL0ztF6Do2twsKgVy/ruGtXSJnSbB6Rv1PHlkicpMKWOLTs2bNz7dq1px6/fv06WbJkMZAololjyxH/zmazUStbLfa/t5/xtceTIkEKTt8+TeP5jSk+sTgbz240HVGiy5kzULo0bNtmFbJWr7Y6D1xi34/F3Zd303ZRW1J/nZoPVn7AsVvHSOCRgI5FOrK/w35+bfUrb+d9G083z5gLVaIE7N1rLUcMC7OWNVWuDBcuxFwGiTKv53qdA+8doGqmqjwMfUinZZ2oM7sOtx/eNh1NotqMGXDokPW8+dFHptOIPC2iY+vUKQgJMZtFRGJM7PsNXpxeUFBQ5G3w4MG8//77/PTTT1y8eJGLFy/y008/0a1bN4YMGWI6qvOL44WtCG4ubrQr3I6TXU7yWYXPSOCRgJ2Xd1JhWgXqzK7DgWsxO89NotnevdY8rePHrdkwmzdbnVuxyIOQB0zZO4ViE4pRZEIRJu2dxMPQh+T1z8uYWmO43P0y39f6nrzJ85oLmSgRzJwJ06dDggSwcSPkzw8LF5rLJK8slU8qVjRbwcjqI/F09WTpiaUUmVCE/df2m44mUeXRoyeztT7+ONZ2t4qTS53a+pkSGmrtyCsicYK2lROHkzhxYmx/2inLbrfz5ptvRj4WsbyhTp06hGnpyn8TUdg6dMhsDgcR3yM+fcr3oX3h9ny28TPG7R7HkuNLWHp8KU3yNqF/hf5k8VOnoFNbswYaNoS7dyFfPli+/MmS3Fjg+K3jjN01lqm/T+X2I6tbxt3FnUa5GtGxaEdKpy39l+dXh/DOO1CypNW9tXOn9d/nww9h0CBr6aI4DRebC+8Xf5+y6crScG5DTt8+TYmJJZhYdyJN8jYxHU/+q++/t7oq06SBzp1NpxF5NpvNWo64a5c1Z0srPETiBP3GKA5n/fr1piPEHRED5ON4x9bfJU+QnO9rfU/XEl35dN2nzDs8j5kHZjLn0BxaF2hNn/J9SJMwjemY8rJmzoSWLa2/4lasaHUGJUpkOtV/FhIWwuLjixmzawxrTq+JfDxD4gy8W/hdWhdsjX98f4MJX0CWLNbcrU8+geHDYehQa4j/jz9C0qSm08lLKpiyILva7aLpgqasPLWSpguasuPSDr6q+hXuru6m48mruHPHmkMIMGCAtdupiKOKKGwdOQK1a5tOIyIxQIUtcTjly5c3HSHuyJXLur961RqkrReQf5EtSTbmvjGXvVf28un6T1l2Yhnj94xn2r5pdCraiV5lepEsfjLTMeXf2O3w1VdP5sE0bgxTp4JnDM6UigbnA88zcc9EJu6ZyJV7VwCwYaNm1pp0LNqRapmr4eriajjlS/DwgGHDoHhxaNUK1q6FwoVhwQLrXpxKknhJWNpkKf029GPQr4MYuX0ke6/uZU6jOaRIkMJ0PHlZQ4dCQID1e0Pz5qbTiPwz7YwoEudoxpY4hQcPHnD06FH279//l5v8RwkSWDuTgbq2/kHBlAVZ2mQpv7b6lbLpyhIcFszX274m06hM9F7bm5sPbpqOKM9jt1vL2iKKWt27W51bTlrUCgsPY9mJZdSdXZeMIzPy+abPuXLvCv7x/elVuhenu55mSZMl1Mxa07mKWn/2xhuwfTtkzQrnz1tD/qdONZ1KXoGriysDKw1k4VsL8fHwYdO5TRQeX5itF7aajiYv4/JlGDHCOh48WEuExfFpZ0SROEeFLXFoN27coHbt2vj4+JA7d24KFiz4l5tEgfz5rfu9e83mcAJl0pVhY8uNrGi6gkIpC3Hv8T0G/zaYDCMy8NHqj7h+/7rpiPJndjv8739WFxBYS9yGD3fKnQ8vBV1i4KaBZB6VmVqzarH4+GLC7eFUyliJOY3mcOGDC3xR5QsyJM5gOmrUyJ0bduywlpAEB1sdXJ06wePHppPJK6ifoz472+0kZ9KcXL57mQrTKvDjwR9Nx5IXNWAAPHxobbpRt67pNCL/LqKwdfSo9buAiMR6zvfbvcQp3bp14/bt22zbtg1vb29WrFjBtGnTyJo1K4sWLTIdL3YoUsS637XLbA4nYbPZqJalGrva7WLBmwsomKIg90PuM3TLUDKMyECPlT24eu+q6Zhit1tdWsOHW2+PHWt1azmR0PBQFh9bTN3ZdUk3Ih191vfhXOA5fL186V6iO0c7HWVt87W8mftNPFw9TMeNeokTwy+/WC+qbTYYPdqajXbtmulk8gqyJ83O9rbbqZ+jPo/DHvP2/Lf5autXkRvCiIM6dgwmTbKOhwyx/l8UcXRZsoCrK9y7B5cumU4jIjFAhS1xaOvWreObb76haNGiuLi4kD59epo1a8bQoUP54osvTMeLHVTYeiU2m40GORuwu/1uFr+9mKKpivIw9CFfb/uajCMz0nV5Vy4GXTQdM26y262t6L/6ynp79Gh4912zmV7C2Ttn6bOuD+lHpKfuj3Uju7PKpivLtPrTuNT9EsOrDSd70uymo0Y/Fxfo2xcWL7YG/W/ZYs3g0tJpp+Tj6cNPb/xEt+LdAOi9vjfjLo4jNDzUbDB5vt69ISwM6tSBMmVMpxF5MR4ekDkzALZjxwyHEZGYoMKWOLT79+/j72/t5uXn58eNGzcAyJs3L3v27DEZLfaIGMp8/Li165G8FJvNRu1stdnedjvLmy6nRJoSPAp9xKgdo8g4MiPNFzZn/zXNg4sxdrv1QmzIEOvt776D994zm+kFPAx5yOwDs3nth9fINDITA38dyOW7l0kaLyk9SvbgSKcjbGq1ieb5m+PtHgd3I6tVy1qamDUrnDtnLYlascJ0KnkFri6ufFP9G0ZUG4ENGyturaDRT4249/ie6Wjyd9u3w/z5VpdWxI6IIs7ijwHyNg2QF4kTVNgSh5Y9e3aO/fGXlgIFCjBu3DguXbrE2LFjSZkypeF0sUTSpE8GyKtY+MpsNhvVs1RnS+strH5nNeXTlyc0PJQf9v9A/rH5qT6jOmtOr9Gym+hkt0OfPhDRzTlqlDWXyUHZ7Xa2X9zOe0veI+XwlDRZ0ITVp1djx06VTFWY02gOFz+4yLDXhpEjaQ7Tcc3Llg22boXy5eHuXavY9f33plPJK+paoitzXp+Dh82DZSeXUWFqBS3jdiQRy7kBWrSAPHnM5hF5WRFzttSxJRInqLAlDq1bt25cuWJtY9+vXz9WrFhBunTpGDVqFIP118Ooo+WIUcZms1ElUxU2tNzAjrY7eDP3m7jYXFh5aiVVf6hK4fGFmXVgFiFhIaajxi52u7VkbdAg6+0RI6BLF6ORnufqvat8tfkr8ozJQ4lJJRi7eyyBwYGkS5SOPuX6cOr9U6x+ZzVv5n4TTzfn3L0x2iRJAqtWQcuWEB4OnTtD167WUilxOvWz1+fzLJ+T1Dspu6/spsTEEhy5oV3MHMKyZbBxo7WD7IABptOIvDx1bInEKdqvVxxa06ZNI48LFizI2bNnOXr0KOnSpSNp0qQGk8UyRYrAvHkqbEWxoqmLMqfRHE7fPs03W79h8u+T2Xt1L00XNOXD1R/SvnB72hVqR0ofdR/+Z59/DgMHWsdff20VOxzI3eC7LDy6kJkHZrLm9BrC7eEAeLl58XrO12lVoBUVM1bExaa/N/0rDw+YPBmyZ7dmqY0aBSdPwo8/go+P6XTykrLHz86mFpuoO7cuJwNOUmpyqchl3WJISAj06GEdv/8+pEtnNo/Iq/ijY0sztkTiBv0GLU4lXrx4FCpUSEWtqBbRsbVzp9kcsVQm30x8W/Nbznc7z+cVP8c/vj+X7l6i34Z+pBuRjrd+eouNZzdqmeKrGjsW+vWzjocPhw8+MJvnDyFhISw9vpS3579N8mHJafFzC1adWkW4PZwSaUowrvY4rva4yoyGM6icqbKKWi/DZoNeveCnn8Db2+ouKV0aLlwwnUxeQRa/LGxts5USaUpw59Edqv5QlY1nN5qOFXeNGWMt30qWzJpZKOKMIgpbV67gdv8+O84EEBau37NEYit1bInD6d69O59//jnx48ene/fu//ixX3/9dQyliuUiBsifPQs3b1pztyTKJYmXhE/Lfcr/Sv2P+UfmM3rnaDZf2MzcQ3OZe2guuZLlomORjryT/x0SeiY0Hdc5/Pzzkzla/frBvzxnRLew8DB+O/+b9d/08FxuPrgZ+b5sSbLRNG9TmuRtQha/LAZTxiKvv251k9StCwcOPBkqnzu36WTykpLGS8qad9ZQ98e6rDuzjhoza7DwrYVUy1LNdLS4JSAA+ve3jj//3NqNVMQJrbjwgMI+SUh29xY+ly7R+tBO/BJ4069OLqrnUae8SGyjwpY4nL179xISYs0f2rNnDzab7Zkf97zH5RUkSmQNZj5+HHbvhmp6IRGdPN08aZK3CU3yNmHf1X2M2TWGGftncPjGYTov78z/Vv+Phjkb0iJ/CyplrISri6vpyI7pt9/g7betWUvt2j3p2ophYeFhbDq3iXmH57HgyAKu3b8W+b7k8ZPTOE9jmuZtSpFURfS8FR2KFrV2b6teHY4cgTJlYNEiKFvWdDJ5SfE94rPk7SU0mteIZSeWUffHusxtNJd6OeqZjhZ3fPYZ3L5tDYtv08Z0GpFXsuLgFd6bsYcZfqlJdvcWCS5cAJ+cXA18xHsz9jCmWSEVt0RiGRW2xOGsX78+8njDhg3mgsQ1RYpYha1du1TYikH5U+RnbO2xDKkyhOn7pjNm1xiO3DzCzAMzmXlgJql9UtMsXzNa5G9BzmQ5Tcd1HIcOQZ068OiRdT96tLU8LYaEhIWw6dwmfjr8EwuOLuD6/euR7/P18qV+jvq8lfstKmeqjJuLftRGu3TprEJnnTqwZQtUrQqzZkHDhqaTyUvydvdm4VsLaTK/CfOPzOf1ua8zs+FM3srzlulosd+xY092Gv36a3DTc5c4n7BwOwMWH8YOHEqWkgSP9uNx+TxkBztgAwYsPkzVXClwddEfm0RiCw30EIcVGhqKm5sbBw8eNB0lbtCcLaMSeSWiS/EuHOp4iG1tttGxSEd8vXy5dPcSQzYPIdfoXBSbUIxR20dxMeii6bhmXbxodefcuQMlS1pDw2PgBVjAwwBm7p9J458ak+yrZFT5oQpjd4/l+v3r+Hn70aZgG1Y0XcG1nteYXG8y1bJUU1ErJvn5wZo1UK8eBAdDo0ZWwVOcjoerBz82+pFm+ZoRZg+jyYImTP19qulYsV/PnhAaCrVrW8VhESe040wAVwIfAbAxgysF3oNGGVZFvt8OXAl8xI4zAYYSikh00G/c4rDc3NxInz49YdrGPWYULWrda2dEo2w2G8XTFKd4muJ8Xe1rlhxfwvT901l2Yhk7L+9k5+WddF3RleKpi9MwZ0Nez/k6mf0ym44dc27fhho1rOJWjhyweDHEixctp7Lb7Ry/dZzFxxez+PhiNp/fTJj9yfNRsnjJqJe9Hm/kfoOKGSri7uoeLTnkJXh7WwPlO3eGceOs+WuXLlk7ZmoZqFNxc3FjWv1peLt5M2HPBFr90ooHIQ/oWLSj6Wix05o1sGSJ9UeCYcNMpxF5ZdfvPoo8PpLM2oE4x203jqR4/seJiPNTYUsc2qeffsrHH3/MjBkz8PPzMx0nditQAFxcrBeBV65ASs0eMM3TzZPXc73O67le5/r968w+MJt5h+ex5cIWtl/azvZL2/lozUfkS56P13O+Tv0c9cnrnzf2znF69Mjqxjl40Lo+V6yAJEmi9BTX719n3Zl1rD61mjVn1nA+8Pxf3p/HPw91stWhTrY6FEtdTPPPHJGbm7WrW+rU0LcvDB5sPaeNGwfuKj46ExebC+NqjyOeezxGbh9Jp2WdsNvtdCrWyXS02CUs7MnGGx07QvbsZvOI/Af+Pl6Rx6f8HgMQr1htOP/8jxMR56fClji0UaNGcfLkSVKlSkX69OmJHz/+X96/Z88eQ8lioQQJIGdOa3bR7t3WUgRxGP7x/elaoitdS3Tlyt0r/Hz0ZxYcXcD6M+vZf20/+6/tp9+GfqRMkJKqmatSNVNVqmSqQooEKf79izuD8HBo1gx+/RUSJrSKWunT/+cvezf4LpsvbGbN6TWsOb2Gfdf2/eX97i7uVMhQwSpmZa9DhsQZ/vM5JQbYbNCnj1UA7dABpkyxdnydM8fq6hKnYbPZ+KbaN3i7efPl5i/pvLwz8dzj0apgK9PRYo9Jk6xdRX19jW3CIRJVimX0I2UiL64GPuKR6wUA0nqlZfcf77cBKRJ5USyj/mAuEpuosCUOrX79+qYjxC1FiliFrZ07VdhyYCl9UvJe0fd4r+h73Hpwi8XHFzP/yHzWnl7LlXtXmL5vOtP3TQcgX/J8vJbpNapkqkKJNCVI5OWkW7f36wfz54OHB/z8M+TL99Jfwm63cy7wHJvPb2bLhS1svrCZA9cPEG4P/8vH5U+enyqZqlA1U1XKpCtDfI/4z/mK4vDatoUUKeCNN6xlqzVqWDsmJkxoOpm8BJvNxuDKg3kU+ogR20fQZlEbvN29aZynselozi8wED791Dru39+aVSfixFxdbPSrk4sOM3YRYrMKW+m9rD+ERfSz96uTS4PjRWIZFbbEofXTXw5jVtGiMG2a5mw5kSTxktCyQEtaFmjJo9BHbD6/mdWnV7Pq1Cr2Xt0b2c01bOswbNjImSwnJVKXoGTakpRIU4KcSXM6/nK6OXOsGUkA48dDxYov9GlX711l39V9/H71d3Zd2cWWC1u4fPfyUx+XIXEGKmWoRNXMVamUsRL+8f2jMr2YVrs2rFxp7Zi4cSNUqgTLl0OyZKaTyUuw2Wx8Xe1rHoY+ZNzucTRb0AwvNy/q56hvOppzGzwYbtywlh++957pNCJRonqelPRv4E+rFY+w2d1I4Wl1r6dI5EW/OrmonkfjNkRiGxW2ROSJiJ0Rd+0Cu13Dlp2Ml5sXlTNVpnKmynxZ5Utu3L/B2jNrWXVqFRvObuDMnTMcvnGYwzcOM/n3yQD4ePhQNHVR8iTLQ27/3OROlptcyXKRwC2B4e/mD7t3Q8uW1nGPHtCixVMfcu/xPU4GnOTIjSP8fvV39l2zilnX7l976mPdXNwolLIQpdOWplTaUpRKW4pUPqmi+ZsQ48qVg/Xrrd00d++23l61CtKmNZ1MXoLNZmN0rdE8CHnAD/t/4K2f3uKXxr9QPUt109Gc0+nTMGKEdTxsmGbQSayS1PcGAJl9s+Nqc2Vyi6KUyOKvTi2RWEqFLXFoYWFhfPPNN8ydO5fz58/z+PHjv7w/IEBb9UapfPmswcvXr1u7zulFn1NLFj8ZjfM0jlyuc/3+dbZf3M7Wi1vZdnEbOy7t4O7ju6w7s451Z9b95XNTJkiJP/6sXrWaTH6ZSJswLWkTpSVtwrSkSJAiZrq8rlyBevUIDnnEtXoVuPJ+Q84fmseJgBOcDDjJyYCTnAg4wdV7V5/56TZsZE+anfzJ81MwRUFKpi1J0VRF8XbXjKU4qVAha0Zb1apw9CiUKQOrV0O2bKaTyUtwsbkwud5kHoU+Yt7heTSY04DlTZdTIUMF09Gci90O778Pjx9DlSpQq5bpRCJR6uD1gwAUSZ0XsGZvqaglEnupsCUObcCAAUycOJHu3bvTp08fevfuzdmzZ/n555/p27ev6Xixj7c35MkDv/9udW2psBWr+Mf3p052awg6QFh4GIduHGLX5V0cun6IQzcOcfjGYS4EXeDKvStc4Qr7du176uu42lxJ5ZOKtInS4uftR2KvxCTyTEQiz0TWsZd17OHqgc1mw8XmgovNBRtPjoPDgrn3+B73H9+37kPuR7596+EtrgZd5urh7Vxt9ojb3gAbYErp535vSbyTkC1JNgqkKED+5PkpkKIAefzzaD6W/FX27PDbb1Zx6/hxKFvWWqZYoIDpZPIS3FzcmNFwBg9DH7Lk+BJqz6rN6ndWUzJtSdPRnMeiRbB0qdWl9e236tCWWCeisJU7WW64YzaLiEQ/FbbEoc2cOZMJEyZQq1YtBgwYwNtvv03mzJnJly8f27Zt4/333zcdMfYpWtQqbO3cCQ0amE4j0cjVxZV8yfORL/lfB7EHBQex/8p+flz3I56pPLl07xIXgi5wIfACl+9eJsweZr0ddCF6A/5pNaS7izspEqQgTcI0ZPHLQla/rGTxyxJ58/X2jd4sEnukS2d1blWvDnv3Qvny1gv8MmVMJ5OX4OHqwbw35lFndh3WnF5DjZk12NByAwVSFDAdzfE9eABdu1rHPXpAjhxm84hEg0M3DgGQK2kuFbZE4gAVtsShXb16lbx5rRbiBAkSEBgYCEDt2rXp06ePyWixV5EiMGGCBsjHYQk9E1I8dXFuJblFzco1cf/T3JWw8DCu3LvCxaCLXAy6yO2HtwkMDiTwUSCBwYHceXQn8u3Q8FDC7eHYsRNuD7eO7daxh6sHCTwSEN8jPvHd41vH7vGJ7xEf362/k3LOUlI8cCHFNxNIUaU+vl6+2NRRIFHF39+auVW3LmzaBNWqwS+/WEuyxGl4uXnx81s/U31mdX47/xs1ZtZga5utZEicwXQ0xzZoEJw7ZxV5I3ZEFIlFwsLDOHLjCGB1bB09edRwIhGJbipsiUNLkyYNV65cIV26dGTJkoVVq1ZRqFAhdu7ciaenp+l4sZMGyMs/cHVxJU3CNKRJmCZ6TrBkCfQZDHbgu1FQp3X0nEckUSJYsQJef93aJbFWLfjpJ2v3RHEa8T3is/jtxZSbUo4D1w9QfUZ1NrfeTJJ4SUxHc0zHjsFXX1nHI0dCfC3Xltjn1O1TBIcFE889HhkSZ+AoKmyJxHYupgOI/JMGDRqwdu1aALp27UqfPn3ImjUrzZs3p3VrveCNFnnygIcH3L4NZ86YTiNxyfHj0KSJVVB9913o2NF0IontvL1h4UJo2NAaot2wIcyZYzqVvKTEXolZ3nQ5aROm5ditY9SZXYeHIQ9Nx3I8djt07gwhIVCzJtSrZzqRSLSImK+VK1kuXGx6uSsSF6hjSxzal19+GXncqFEj0qZNy+bNm8mSJQt169Y1mCwW8/CwBinv2GHN2cqUyXQiiQvu37c6Z+7ehXLlNMxYYo6np1XMatUKZsywiqsPHlhvi9NInTA1y5sup8yUMmy9uJW357/N/Dfnx8wOrs5i3jxYs8a65keN0nOsxFqHrlvztfL45zGcRERiikrY4tAePHjwl7eLFy9O9+7dVdSKbn9ejigS3ex26NABDh6EFCmsIsOf5nqJRDs3N5g2Ddq3h/BwaN0avvvOdCp5Sbn9c7Oo8SI8XT355dgvdFneBbvdbjqWY7h7Fz74wDr++GPInNlsHpFodPDGn3ZEFJE4QYUtcWj+/v40a9aMlStXEh4ebjpO3KHClsSkceOsThlXV6uolSKF6UQSF7m4wNixT178d+kCQ4aYzSQvrWz6ssxsOBMbNsbsGsMXv31hOpJj6N8fLl+2CloffWQ6jUi0UseWSNyjwpY4tOnTpxMcHEyDBg1IlSoVXbt2ZefOnaZjxX4Rha3du63uBZHosnPnk23nv/zSWoYoYorNBsOHQ8Suu716Qd++VlehOI3Xc73OqBqjAOi9rjdTf59qNpBpBw5Yg+LBWubt5WU2j0g0ehz2mGO3jgHq2BKJS1TYEofWsGFD5s2bx7Vr1/jiiy84cuQIpUqVIlu2bHz22Wem48VeOXNaQ5Xv3rUGeotEh1u3oFEja2h3gwbQo4fpRCJWceuzz6xCK8Dnn8OHH6q45WQ6F+vMR6WtzqS2i9qy6tQqw4kMsduhUycIC7M2R6hRw3QikWh1/NZxQsNDSeiZMPp2cBYRh6PCljgFHx8fWrVqxapVq9i3bx/x48dnwIABpmPFXm5uUKiQdazliBIdwsOhWTM4fx6yZIEpUzTIWBzLRx9ZA7YBhg2zliaqg9WpDK48mGb5mhFmD+PNeW9y9OZR05Fi3rRp8OuvEC8ejBhhOo1ItItYhpg7WW5s+r1CJM5QYUucwqNHj5g7dy7169enUKFC3Lp1i549e5qOFbtpzpZEp4EDYcUKqzNw/nxIlMh0IpGndekC48dbRdfvv7eGy4eFmU4lL8jF5sLEOhMpk64MgcGB1J5Vm1sPbpmOFXOuXHkyM65fP0ib1mwekRhw8Lo1OF7ztUTiFhW2xKGtWrWKFi1akDx5cjp06IC/vz8rV67k/PnzDNFQ3+ilwpZEl1WrrEHGYA3rzpfPaByRf9SundX14uICkyZBixYQGmo6lbwgTzdPFry5gAyJM3Dq9ikazWtESFiI6VjRz26Hjh3hzh0oXBi6dzedSCRGHLrxpGNLROIOFbbEodWvX58HDx4wbdo0rl27xvjx4ylfvrzpWHFDRGFrzx69iJOoc/EiNG1qvehq3x6aNzedSOTfvfMOzJ5tLdOeORPeftuaDSdOIVn8ZCx+ezEJPBKw4ewGuizvgj22z0ybNw9+/tm6ZidPtu5F4gB1bInETSpsiUO7evUq8+bNo379+ri7u5uOE7dkywY+PvDwIRw5YjqNxAZhYdZcrZs3rRluEbt0iTiDN9+En34CDw/rvlEjePTIdCp5QXn88zD79dnYsDFu9zi+2/Gd6UjR5+ZN6NzZOv7kE3XFSpzxMOQhp26fAlTYEolrVNgSh5YwYULTEeIuFxdr+QLAzp1ms0jsMGgQbNwICRLAnDnacl6cT716sGiRde0uXmy9/eCB6VTygmpnq83QqkMB6LayGytPrjScKJp07Qo3bkCePNC7t+k0IjHm6M2jhNvDSeKdBP/4/qbjiEgMUmFL5Bm++OILihYtio+PD/7+/tSvX59jx46ZjhXzSpSw7n/91WwOcX6bNkHETqZjx1o7IYo4o2rVYNkyiB/fmhdXsybcvWs6lbygHiV70KpAK8Lt4bz101uxb6fExYth1izrj1OTJ1sdhiJxRMR8rTz+ebQjokgco8KWyDNs3LiRTp06sW3bNlavXk1oaCivvfYa9+/fNx0tZkXMM9u40WwOcW63bllztcLDrcHbTZuaTiTy31SsCCtXWsu1N260il137phOJS/AZrMxptaYyJ0S68yuQ8DDANOxosadO9Chg3XcowcULWo0jkhMi5ivpcHxInGPClsiz7BixQpatmxJ7ty5yZ8/P1OmTOH8+fPs3r3bdLSYVbo0uLrCmTNw4YLpNOKM7HZo08YaGp8tG3wXi+faSNxSujSsXQu+vrB1K1SubBVxxeH9eafEkwEneeuntwgLDzMd67/r2RMuX4asWZ90yIrEIX/u2BKRuEVbpIhDa926NSNHjsTHx+cvj9+/f58uXbowefLkGMkRGBgIgJ+f33M/Jjg4mODg4Mi3g4KCAAgJCSEkxOzW4hHnf+kcXl64FiyIy65dhK5di12dNnHGK18zf+MyejSuv/yC3cOD0B9+AE9PMPz/g0SPqLpmnEqBArBqFW41a2Lbswd7hQqELl8OyZObTuYUTF4ziT0SM7/RfMpOK8ua02v4eM3HDKo4KMZzRBXbmjW4TZoEQOi4cdjd3GLlc22cfJ6RF3bwmtWxld0v+1PXiiNcM46QQSS2stlj/X7H4sxcXV25cuUK/v5/HQB58+ZNUqRIQWhoaLRnsNvt1KtXj9u3b/PrP8ya6t+/PwOe8RfSWbNmES9evOiMGK1yTZ1K1p9/5mzVquzr1Ml0HHEiCc+codyHH+IaEsKBNm04XaeO6Ugi0cLnwgVK9e2L1+3b3E2dmi2ffcajJElMx5IX8Nvt3xh2bhgAvTL0okTiEoYTvTzXhw+p9P77xLtxg9M1a3KgfXvTkURi3MOwh7x94G0ApueZTkI3x9uA6sGDBzRp0oTAwEBtkCUSxVTYEocUFBSE3W7H19eXEydOkCxZssj3hYWFsXjxYnr16sXly5ejPUunTp1YunQpv/32G2nSpHnuxz2rYytt2rTcvHnT+A+vkJAQVq9eTdWqVXF3d3+pz7UtXYpbgwbYs2Qh9PDhaEoojua/XDMA3L+PW/Hi2I4fJ7xmTcIWLgQNco3V/vM14+xOnsStWjVsFy5gz5SJ0JUrIX1606kcmqNcM/9b8z9G7hiJj4cPW1ptIXuS7MayvAqXzp1xHT8ee/r0hO7da+08G0s5yjUjjmfn5Z2UnlqaFPFTcL7r+cjHHemaCQoKImnSpCpsiUQDLUUUh5Q4cWJsNhs2m41s2bI99X6bzfbM7qio1qVLFxYtWsSmTZv+sagF4Onpiaen51OPu7u7G/9BGuGVslSoAC4u2E6exP3mTUiZMlqyiWN65eu3Rw84fhxSpcJl2jRctDNXnOFIz3kxKmdOa/fPypWxnT6Ne6VK1gyurFlNJ3N4pq+Zr177ir3X9rLp3CbeWvAW29tuJ4GHkxSHfvkFxo8HwDZpEu6+voYDxQzT14w4nqMB1g6neZLneea14QjXjOnzi8RmKmyJQ1q/fj12u51KlSoxf/78v8y28vDwIH369KRKlSrazm+32+nSpQsLFy5kw4YNZMyYMdrO5fASJ7bmyOzZY+3+1bix6UTi6ObOtbaZt9lgxgxImtR0IpGYkSFDZHGLY8egbFlYswbyaJCxI3N3dWduo7kUGl+IwzcO0/qX1sxpNAebo3eZXr5sbc4B1h8TKlc2m0fEoEPX/xgcn0zPtyJxkQpb4pDKly8PwJkzZ0ibNi0uLjG7gWenTp2YNWsWv/zyCz4+Ply9ehWARIkS4e3tHaNZHEL58lZha8MGFbbkn128CO++ax1/8glUrGg2j0hMS53aKm699hrs22c9f65cCUWKmE4m/yB5guT89MZPlJ9annmH51F8a3F6lOphOtbzhYdD8+bWTpwFC8Ig5x18LxIVDt6wBsfn9s9tOImImKDClji09OnTc+fOHXbs2MH169cJDw//y/ubN28eLecdM2YMABUqVPjL41OmTKFly5bRck6HVr48fPON1bEl8jzh4dCiBdy5A0WLQr9+phOJmOHvD+vXQ40asH07VKoEy5ZBmTKmk8k/KJm2JCOqj6DTsk58tOYjCqcqTIUMFUzHerbhw62lrt7eMGuWteOsSBwW2bHlr44tkbhIhS1xaIsXL6Zp06bcv38fHx+fvywLsNls0VbY0p4Kf1O2rLWs7OhRuHZNW9nLs40YAevWQbx41hJEzZKQuMzXF1avhrp1rW7X116z5iFVrWo6mfyD94q8x7aL2/hh/w+8Oe9N9ry7hzQJ/3nGZozbvRt697aOR46EHDnM5hEx7M6jO1y6ewmAXMlyGU4jIibE7PoukZfUo0cPWrduzd27d7lz5w63b9+OvAUEBJiOF3f4+UHevNbxpk1ms4hj2r8fPv7YOv7mG3jGpg8icY6Pj9WpVaMGPHwItWtbxS1xWDabjbG1x5I/eX5uPLjBG/PeICQsxHSsJ+7fhyZNICQEGjSAtm1NJxIxLqJbK12idCT01G6DInGRClvi0C5dusT7779PvHjxTEeRP+aeaTmiPOXRI2jaFB4/hjp1oF0704lEHIe3N/z8M7z+uvX/yOuvw+zZplPJP4jnHo8Fby0gkWcitl3cxqfrPjUd6Ylu3awdZ1OnhgkTrG5qkTju4PU/5msl03wtkbhKhS1xaNWqVWPXrl2mYwiosCXP98kncPCgNVdo4kS90BL5Ow8P+PFHa9h3WJhVCP5jlqM4pky+mZhcbzIAQ7cMZdmJZYYTAfPnP3mO/eEHSJLEdCIRhxBR2NJ8LZG4SzO2xKHVqlWL//3vfxw+fJi8efPi/reZPXXr1jWULA4qV866P3gQbt6EpEnN5hHHsGaNtfQQYPJkq7glIk9zc4MpUyBBAhg9Gjp2hIAAqzCsYrBDapizIZ2Ldua7nd/RfGFzfu/wu7l5WxcuPOmG/egj7Tgr8ieHblhLEdWxJRJ3qbAlDq3dH7/EffbZZ0+9z2azERYWFtOR4q5kySBXLjh8GH791ZrtIXFbQIC1CyLAe+9BrVpm84g4OhcX+O47q9Pm88/h00/h1i0YNsx6nzicYa8NY8vFLey5socm85uwrsU63Fxi+Nfnx4/h7bfh9m0oUgQGDIjZ84s4OHVsiYh+ixKHFh4e/tybiloGVKhg3Ws5otjt8O67cPkyZM9uvTAXkX9ns8Fnnz3pdPzmG2jdGkJDzeaSZ/J082ROozn4ePjw6/lfGbDBQFGpe3fYvBkSJoRZs6ylrSICwPX717nx4AY2bORMltN0HBExRIUtcRqPHj0yHUEi5mxt2GA0hjiAGTPgp5+s5VUzZoA2eBB5Od26wbRp4Opq3TdqZG3EIA4ni18WxtcZD8CgXwex5vSamDv5lCnw/ffW8cyZkDVrzJ1bxAlE7IiYyTcT8dz1u4hIXKXClji0sLAwPv/8c1KnTk2CBAk4ffo0AH369GHSpEmG08VBEXO29u+3lkRI3HThAnTubB33728tjRGRl9e8OSxYAJ6e8MsvUL06BAWZTiXP0DhPY9oXao8dO00XNOXqvavRf9Jdu6xl3mA919auHf3nFHEykTsi+mu+lkhcpsKWOLRBgwYxdepUhg4disefWu/z5s3LxIkTDSaLo1KksJad2e3WnC2Je8LDoVUr68V3iRLWEGMReXV168LKleDjYy3zrlgRrl0znUqeYUT1EeT1z8v1+9dpuqApYeHROBLh+nVo2BCCg6FOHejTJ/rOJeLE9l7dC0CB5AXMBhERo1TYEoc2ffp0xo8fT9OmTXF1dY18PF++fBw9etRgsjgsYjmi5mzFTaNHw9q14O0N06dbSxFF5L8pX95a4p0sGezZAyVLwvHjplPJ33i7ezP3jbnEd4/PujPrGPTroOg5UUgIvPmm1R2bLRv88IM2FxB5jojCVsGUBQ0nERGT9FNSHNqlS5fIkiXLU4+Hh4cTEhJiIJGosBWHHT8OH35oHX/1lWa9iESlQoWsAeGZMsGZM1CqFGzbZjqV/E2OpDkYU2sMAAM2DmDLhS1Rf5IPP7R+xiZIAD//DIkSRf05RGKB4NDgyKWIhVIWMpxGRExSYUscWu7cufn1GUve5s2bR8GC+suMERGFrb17ITDQbBaJOaGh1jyghw+hSpUnc19EJOpkzQpbtlhz627dgkqVYPFi06nkb97J/w7N8jUj3B5OswXNCAqOwrloM2bAiBHW8fTpkFO7vIk8z8HrBwkNDyWJdxLSJkxrOo6IGKTClji0fv360blzZ4YMGUJ4eDgLFiygXbt2DB48mL59+5qOFzelTg2ZM1uzljZvNp1GYsqQIbB9u9U5MHmylsWIRJfkyWH9eqhRwyok168P48aZTiV/812N78iQOANn7pyhy/IuUfNF9+6F9u2t4969oUGDqPm6IrHUn5ch2mw2w2lExCS9MhGHVqdOHebMmcOyZcuw2Wz07duXI0eOsHjxYqpWrWo6Xtyl5Yhxy9691o5cAN99B2n1V1GRaJUggbVLYuvW1h8ROnSwhofb7aaTyR8SeSViRoMZuNhcmL5vOj8e/PG/fcGLF62NBB4+tIqaAwZETVCRWGzPlT0AFEqhZYgicZ0KW+LwqlWrxsaNG7l37x4PHjzgt99+47XXXjMdK25TYStWCwu3s+NMAAA7j17G3ry5tRSxYUNo2tRwOpE4wt0dJk6EiO7kgQOtQtfjx2ZzSaTS6UrzadlPAeiwpAPnA8+/2he6fRuqV7eKWzlywMyZ8KcNc0Tk2SILW5qvJRLnqbAlIi8vorC1axfcu2c2i0SpFQevUGbIOlpP2wnA4fbdsR08SLBfUhg7FtTqLxJzbDarc2f8eGv579SpUK0aBASYTiZ/6FO+DyXSlCAwOJB3Fr5DWHjYy32Bhw+tTq1DhyBVKli5Enx9oyesSCwSGh7K/mv7Ae2IKCIqbIkD8vX1xc/P74VuYkj69JAhA4SFac5WLLLi4BXem7GHK4GPAPA7fJjW2xYC0LnCe6y4Fmoynkjc1a4dLFpkLVHcsAGKF4djx0ynEsDNxY0ZDWaQwCMBm85tYujmoS/+yaGh0KQJ/PabNb9wxQpIly76worEIsduHuNh6EMSeCQgi9/TO6iLSNziZjqAyN+NiNgNCLh16xYDBw6kWrVqlCxZEoCtW7eycuVK+vTpYyihAFbX1tmz1pDjatVMp5H/KCzczoDFh4mY4BPv8UMKjRyJC3bm5anCmqzFObj4MFVzpcDVRV1bIjGuVi1rx8Q6deDkSShRAubNs3YpFaMy+2Xmuxrf0fKXlvTd0JeqmatSJFWRf/4kux06dYKffwZPT6twmTdvjOQViQ0iliEWTFEQF5t6NUTiOj0LiMNp0aJF5G3z5s189tlnzJ49m/fff5/333+f2bNn89lnn7FR853MiphztnSp2RwSJXacCYjs1ALouW4q8a9d43LCpHxWpR124Ergo8jZWyJiQN68sGMHlCoFd+5Yc5nGjjWdSoDm+ZvzZu43CQ0Ppcn8Jtx/fP+fP+Gzz6wlpjYbzJoF5crFTFCRWCJyR8QUWoYoIipsiYNbuXIl1atXf+rxatWqsWbNGgOJJFKNGtZw24MH4fRp02nkP7p+90lRq8yZvTTdswyAT2p15a5n/Gd+nIgY4O8Pa9dCs2bWcvD33oOuXa1lbWKMzWZjbK2xpEmYhhMBJ+i2otvzP3j8+Cc7zX7/vbUxh4i8FA2OF5E/U2FLHFqSJElYuHDhU4///PPPJEmSxEAiieTr++QvzIsXm80i/5m/jxcAPsH3Gbp8JACna9Zka8YCz/w4ETHIywumT4fBg623R42C2rWtLi4xxtfblx8a/IANGxP3TmTxsWf8bPz5Z6sYCfDpp0+OReSFhdvDIzu2VNgSEVBhSxzcgAED6NWrF7Vq1WLgwIEMHDiQ2rVr8/HHHzNgwADT8aROHet+0SKzOeQ/K5bRj5SJvOi7ZgKp7t7knG9KDjdvHvl+G5AykRfFMmrTBhGHYLPBxx/D/PkQL561m16RIrBvn+lkcVqFDBXoUbIHAO0Wt+Pmg5tP3vnLL/DWWxAeDm3aWMsRReSlnbl9hqDgIDxdPcmRNIfpOCLiAFTYEofWsmVLtmzZQuLEiVmwYAHz588nUaJEbN68mZYtW5qOJ3XrWvebNqlTwMm5utj4zucibxxcQzg2etXuRpiX1Z0VMSq+X51cGhwv4mgaNrR21cuQAU6dsobKT59uOlWc9nmlz8mVLBfX7l+j07JO1oNz5kCjRvD4sXU/dqxVnBSRlxaxDDFf8ny4u7obTiMijkCFLXF4xYsXZ+bMmezZs4e9e/cyc+ZMihcvbjqWAGTODLlyWbNdVqwwnUb+i1u3KDzwIwBml23EnrS5It+VIpEXY5oVonqelKbSicg/KVgQdu+2Zh8+egQtWlhL3IKDTSeLk7zcvJhefzpuLm7MPTSXH79/D5o0sX5WNmsGs2eDmzYmF3lVmq8lIn+nwpY4vPDwcI4fP85vv/3Gpk2b/nITBxDRtaXliM6tUye4dg1y5qTximlMblEUgMktivLbR5VU1BJxdH5+sGSJNZTcZrM6gsqVg/PnTSeLkwqnKsynZT8FoOOFsVyOHw7t2sG0aSpqifxH2hFRRP5OhS1xaNu2bSNLlizkzJmTcuXKUaFChchbxYoVTccTeDJna9kyCAkxm0Vezdy51jIZV1eYPh3XeN6Rs7SKZfTT8kMRZ+HiAv36Wc/Hfn6wYwcUKgSrV5tOFid9sjcBhS/DbW9o2yU99rFjrf9GIvLK7Ha7OrZE5Cn66SoOrUOHDhQpUoSDBw8SEBDA7du3I28BAQGm4wlA8eKQLBkEBsKvv5pOIy/r6lXo2NE67t3bGj4tIs6tenVraWLhwnDrFlSrBn366I8PMemLL3Dv3pPpC8HT7spyj3NM3DvJdCoRp3fp7iVuPLiBq82VvMnzmo4jIg5ChS1xaCdOnGDw4MHkzJmTxIkTkyhRor/cxAG4ulrbzIOWIzobux3at7de+BYoYBW2RCR2yJDBGirftq31//rAgVC6NBw/bjpZ7Ga3w6efwiefAJCrU38GvfYlAN1XdefM7TMm04k4vb1XrGWIuZLlwsvNy3AaEXEUKmyJQytevDgnT540HUP+zZ/nbNntZrPIi5s2DRYvBg8Paxc1Dw/TiUQkKnl5wYQJ1lJjX1/YudMaND9+vJ6ro8P9+9C4MQwaZL09ZAj060e3Eh9QNl1Z7j2+R8tfWhJuDzebU8SJaRmiiDyLClvi0Lp06UKPHj2YOnUqu3fvZv/+/X+5iYOoWhU8PeHMGTh82HQaeRHnz0PXrtbxZ59BXrXzi8Rab74J+/dDpUrw4AG8+y7Urw83bphOFnucPWt1xM2dC+7uVkHxww8BcHVxZWr9qcR3j8+mc5sYuW2k2awiTmzPVRW2RORpKmyJQ3v99dc5cuQIrVu3pmjRohQoUICCBQtG3ouDiB8fKle2jrUc0fGFh0OrVhAUBCVLQs+ephOJSHRLk8YaIj9smNWduWiRVdBevtx0Mue3cSMULQr79oG/P6xbZy0B/ZNMvpkY/tpwAD5e+zFHbx41kVTE6UV0bGlHRBH5MxW2xKGdOXPmqdvp06cj78WB/Hk5oji20aOtF17x4lnLEV1dTScSkZjg4gI9eli7JebODdeuQc2aVhFGG7K8PLvdej6tUgVu3rSG9e/aBWXKPPPD2xduT7XM1QgOC6b1L60JCw+L4cAizu3G/RtcDLoIQIEUBcyGERGHosKWOLT06dP/400cSMQA+e3brZ32xDEdPx65PIahQyFrVrN5RCTm5c9vzduKWI48aRJkz27N2tPsrRcTHGxtvtGpE4SGQpMm1s7AadM+91NsNhvj64zHx8OHrRe3Mmr7qBgMLOL89l61BsdnS5INH08fw2lExJGosCUO74cffqB06dKkSpWKc+fOATBixAh++eUXw8nkL1KnhiJFrBdFS5eaTiPPEhoKLVrAw4fW0tH33jOdSERM8faGESOsYkzu3FbHUYsWVvfRsWOm0zm2U6egYkWYOBFsNuuPBDNmWP+m/yJdonR8VfUrAHqv683JAG2QI/KitAxRRJ5HhS1xaGPGjKF79+7UrFmTO3fuEBZmte0nTpyYESNGmA0nT9NyRMc2bBhs2wYJE8KUKdayJBGJ28qUgT17YPBgaxfFdesgXz7o3x8ePTKdzrGEh8PIkda/z9atkCgRLFsG//ufVeB6Qe0Lt6dSxko8DH1Im0VttEuiyAuK6NjS4HgR+Tu9qhGH9u233zJhwgR69+6N65/mABUpUoQDBw4YTCbPVKeOdb96tdUVJI5j/37o29c6HjXqH5fLiEgc4+EBH38Mhw5B9erw+DEMGGAVcJYt0/JEsJZxlysH3bpZO0tWrGgVBKtXf+kvZbPZmFhnYuQuiWN2jon6vCKxUETHlgpbIvJ3KmyJQztz5swzdz/09PTk/v37BhLJP8qf3yqYPHwIa9eaTiMRHj+G5s0hJMTqqmve3HQiEXFEmTJZhaw5cyBFCjhxAmrVgvLlYfNm0+nMCAuzul3z57f+DRIkgDFjYM0a69/rFWX0zciXVb4E4KM1H3Hm9pmoSiwSKwU+CoxcuquliCLydypsiUPLmDEjv//++1OPL1++nFy5csV8IPlnNpuWIzqiAQOsbeiTJoXx419qyYyIxDE2G7z5Jhw9au2g6OlpzeEqU8baJGTfPtMJY87hw1C6tLXU8NEjqFoVDh6EDh2iZCl3x6IdKZe+HPdD7tNucTvs6owTea5916znnnSJ0pEkXhLDaUTE0aiwJQ7tf//7H506dWLOnDnY7XZ27NjBoEGD+OSTT/jf//5nOp48S0Rha/Fiax6JmLVlC3xpdQUwZgwkT242j4g4h0SJrE6lkyehXTtwdbU2BilQwNoB8GQsHnp+6RJ07mx9r9u3W3MJJ06ElSshCndkdrG5MKnuJLzdvFl7Zi0T9kyIsq8tEttoGaKI/BMVtsShtWrVin79+vHhhx/y4MEDmjRpwtixYxk5ciSNGzc2HU+epXx58PGBq1dh1y7TaeK2u3fhnXesAuM770CjRqYTiYizSZPG6vQ8fBgifu7Ong05c0KrVtacqdji2jX44APInBm+/95avl2zpjV7rE2baOl2zeKXhUGVBgHQc1VPzgeej/JziMQG2hFRRP6JClvi8Nq1a8e5c+e4fv06V69e5cKFC7Rp08Z0LHkeT0+oVs061nJEsz74AE6ftjoMvv3WdBoRcWbZslkFrb17rWJPaChMnQqFC1vL9WbPtub5OaObN+Gjj6yZWSNGQHCw9T2tW2d1qaVJE62nf7/4+5RMU5K7j+/SfnF7LUkUeQbtiCgi/0SFLXEK169f58iRIxw/fpwbN26YjiP/pn59637WLC1HNOXnn2HSJKvDYNo0a1mRiMh/VaCAVezZts1akujubi15btLEKqL37w+XL//rlwkLt7PjTAAAO84EEBZuoJhz7hz07g0ZM8LQodZuh8WLw6pV1lyxihVjJIariyuT603G09WTladWMn3f9Bg5r4izeBDygMM3DgMqbInIs6mwJQ4tKCiId955h1SpUlG+fHnKlStHqlSpaNasGYGBgdF+/tGjR5MxY0a8vLwoXLgwv/76a7SfM1Zo0MCaSXLmDGzYYDpN3HPtmjUTB6BnT2t5qIhIVCpeHGbOhPPnrQ0qUqa0lqAPGGAVuBo0gOnT4datpz51xcErlBmyjtbTdgLQetpOygxZx4qDV6I/95071rysChUgQwYYPBju3bM6z5Yuha1brSHxMbzJRo6kOehfoT8A3Vd15/r96zF6fhFHduDaAcLt4fjH9ydlgpSm44iIA1JhSxxa27Zt2b59O0uXLuXOnTsEBgayZMkSdu3aRbuIF+7RZM6cOXTr1o3evXuzd+9eypYtS40aNTh/XvMv/lW8ePD229bxpElms8Q1drs1C+bmTWt7+s8/N51IRGKzFCmgb1+r++nHH63dE0NDra7RFi2sDSsqVrSW+J05w4qDV3hvxh6uBD76y5e5GviI92bsiZ7i1uPH8Msv8MYbVt527WDjRqt4VbEiLFwIO3daSywN7hrbo2QPCqQoQMDDALqu6Gosh4ij+fMyRJt2dhaRZ1BhSxza0qVLmTx5MtWqVSNhwoT4+PhQrVo1JkyYwNKlS6P13F9//TVt2rShbdu25MyZkxEjRpA2bVrGjBkTreeNNSLmoM2fD7dvm80Sl4wfb3UdeHjAjBnWzDMRkejm7g5vvWUt4du/3yp25c8PYWFW5+4HH0CmTGSuWoaPNkyh9pFNZLx1MXK5esRCxAGLD//3ZYlBQbB2rdWNVa+eVcyqXx9++sman5UnDwwZYnWbrVtnvc8BXiy7u7ozsc5EXGwu/HjwR5YcX2I6kohD2HnJ6u7U4HgReR430wFE/kmSJElI9IzZQIkSJcLX1zfazvv48WN2795Nr169/vL4a6+9xpYtW575OcHBwQQHB0e+HRQUBEBISAghISHRlvVFRJw/RnPkz49b7tzYDh0ibMYMwjt0iLlzx1UnTuDWvTs2IGzgQMKzZ7d29XoFRq4ZcWq6ZiRSjhzw6afW7cwZXJYswbZoEbbffiPr1dNkvXo68kNDp3mRPmkGDvln4kjyTJxOkob9y1zJkysdJE4MCRI8XXQKD4fAQLh1C1tAgHV/8SK2nTux7dgBR45g+9sAdnvKlIS//Tbhb78N+fI9+ZoOdr3mS5aPbsW68fX2r3lvyXuUal8KH08f07Echp5n4qYtF6zfvYukKPLS/+0d6ZpxhAwisZXNrq1XxIGNHz+eefPmMX36dFKmtNbUX716lRYtWtCwYUPefffdaDnv5cuXSZ06NZs3b6ZUqVKRjw8ePJhp06Zx7Nixpz6nf//+DBgw4KnHZ82aRbx48aIlp6PLtGgReSdP5k6mTGz8+mvTcWI1W1gYZT7+GL/jx7mRNy9bBgwAFzXliojjcA8KIsXu3fgeO0ai06dJePYsbv+yk6LdxYWQePEIiRePcHd3PO7dw/3uXVz+ZWOS+/7+3M6W7ckta1ZwdY3KbyfaBIcH8/7R97n2+Bo1k9akfZr2piOJGHMv9B7NDjYDYFqeaSRyc97NcB48eECTJk0IDAwkYcKEpuOIxCoqbIlDK1iwICdPniQ4OJh06dIBcP78eTw9PcmaNetfPnbPnj1Rdt6IwtaWLVsoWbJk5OODBg3ihx9+4OjRo099zrM6ttKmTcvNmzeN//AKCQlh9erVVK1aFXd395g78c2buKVPjy0khJAdO6zdtCRauHz+Oa6ff449USJC9+yBtGn/09czds2I09I1I/9mx5mAyIHxAN6EMjzlRVatPUvWq2fIefU0aQKvkYpg3O4GYQsN/cevZ48fH5IkAT8/7MmTYy9QAHuxYtiLFbNmezmxdWfWUX12dWzY2NB8AyXTlPz3T4oD9DwT96w8tZI6c+qQxTcLh987/NKf70jXTFBQEEmTJlVhSyQaaCmiOLT69esbOW/SpElxdXXl6tWrf3n8+vXrJH/OL8uenp54PmOekbu7u/EfpBFiPEvKlNbsknnzcP/hByhaNObOHZds3mzNkgFso0fjnilTlH1pR7p+xTnompHnKZHFH78E3lwNfGTN1HJ1417atPycKwPB2StiA1Ik8uK3jypZKwUfPrSWHN65Y92Cg8HPzypmJUmCzcsr8mubn5AVtaplq0arAq2Y8vsUOizrwN539+LpppmJEfQ8E3fsvGIVw0umLfmf/ps7wjVj+vwisZkKW+LQ+vXrZ+S8Hh4eFC5cmNWrV9OgQYPIx1evXk29evWMZHJarVvDvHnWIPOhQ+FPL0QkCty+DU2aWAOamzWzjkVEHJCri41+dXLx3ow9TxWiIt7uVycXri5/vBUvnnX7YxRBXDPstWEsO7GMIzeP8MVvX9C/Qn/TkURi3NaLWwHUtSgi/0gDWMTh3blzh4kTJ/Lxxx8TEBAAWMsOL126FK3n7d69OxMnTmTy5MkcOXKEDz74gPPnz9NBQ9BfTtWq1rK427et7dYl6tjt0LattbNXliwwerTpRCIi/6h6npSMaVaIFIn++keOFIm8GNOsENXzxM0i1rP4efvxbY1vARj862AOXT9kOJFIzAoLD2P7pe2A1bElIvI86tgSh7Z//36qVKlCokSJOHv2LO3atcPPz4+FCxdy7tw5pk+fHm3nfuutt7h16xafffYZV65cIU+ePCxbtoz06dNH2zljJVdXaNkSPv8cJk2ytoOXqDF+PCxYAO7uMHs2+GjnLBFxfNXzpKRqrhRsO3mdm0e2MblFUUpk8X/SqSWRGuVqRN3sdVl0bBFtFrVhc+vNuLo4xxB8kf/q8I3DBAUHEd89Pnn885iOIyIOTB1b4tC6d+9Oy5YtOXHiBF5/WsJWo0YNNm3aFO3n79ixI2fPniU4OJjdu3dTrly5aD9nrNSqlXW/Zg2cO2c2S2xx8CB062Ydf/EFFCliNI6IyMtwdbFRLKMfAMUy+qmo9Rw2m43va36Pj4cP2y9tZ8yuMaYjicSYiGWIxVIXw81F/Rgi8nwqbIlD27lzJ+++++5Tj6dOnfqpwe7iwDJmhEqVrKVzU6eaTuP8HjyAxo3h0SOoXh0++MB0IhERiSZpEqbhyypfAvDJ2k+4FBS9oxhEHEVEYatU2lKGk4iIo1NhSxyal5cXQUFBTz1+7NgxkiVLZiCRvLI2baz7KVMgPNxsFmfXvTscOmRtZz91KrjoqVxEJDbrUKQDJdKU4O7ju3RZ3sV0HJEYsfWCBseLyIvRqyFxaPXq1eOzzz4jJCQEsFryz58/T69evXj99dcNp5OX0qABJE5sLUVcu9Z0Guc1fz6MG2cd//CDVdwSEZFYzcXmwvja43FzcWPh0YX8clSbsUjsFvAwgGO3jgFQIk0Jw2lExNGpsCUObdiwYdy4cQN/f38ePnxI+fLlyZIlCz4+PgwaNMh0PHkZ3t7QpIl1PHmy2SzO6tw5axdEgI8+snacFBGROCFv8rz0LNkTgM7LO3M3+K7hRCLRZ9vFbQBkS5KNJPGSGE4jIo5OhS1xaAkTJuS3335j/vz5fPnll3Tu3Jlly5axceNG4sePbzqevKyI5YgLF0JAgNksziYkxCoM3rkDxYpZu0yKiEic0rd8XzL5ZuJi0EX6rO9jOo5ItNlyYQugZYgi8mJU2BKnUKlSJXr27MmHH35IlSpVTMeRV1WoEBQoAMHBMHOm6TTO5cMPYcsWSJgQZs8Gd3fTiUREJIZ5u3szttZYAL7d8S27Lu8ynEgkekQMjldhS0RehApb4rDCw8OZPHkytWvXJk+ePOTNm5e6desyffp07Ha76XjyqiK6tkaPhrAws1mcxezZMGKEdTx9OmTKZDSOiIiYUzVzVZrmbUq4PZx2i9sRGh5qOpJIlAoLD2PHpR0AlEyrwpaI/DsVtsQh2e126tatS9u2bbl06RJ58+Yld+7cnDt3jpYtW9KgQQPTEeVVNW8Ovr5w9CjMmWM6jeM7ePDJXK2PP4Z69czmERER476u9jW+Xr78fvV3Rm4baTqOSJQ6eP0g9x7fw8fDh9zJcpuOIyJOQIUtcUhTp05l06ZNrF27lr179zJ79mx+/PFH9u3bx5o1a1i3bh3Tp083HVNeRcKE0NMafkv//hCqvzQ/V2AgNGwIDx5AlSqaqyUiIgD4x/fnq6pfAdB3Q1/O3jlrNpBIFIpYhlg8TXFcXVwNpxERZ6DCljik2bNn88knn1CxYsWn3lepUiV69erFTM1ocl5dukDSpHDihGZtPU94OLRoYf0bpU0Ls2aBq365ExERS+uCrSmXvhwPQh7QaVknjWmQWEPztUTkZamwJQ5p//79VK9e/bnvr1GjBvv27YvBRBKlfHysYegAn31m7fgnfzV0KPzyC3h4wPz5kCyZ6UQiIuJAbDYb42qPw8PVg2UnlvHT4Z9MRxKJEtoRUURelgpb4pACAgJInjz5c9+fPHlybt++HYOJJMp17Aj+/nD6tDUQXZ5YswZ697aOv/sOihY1m0dERBxSjqQ5+LjMxwB0XdGVoOAgw4lE/psb929wMuAkACXSlDCcRkSchQpb4pDCwsJwc3N77vtdXV0J1Wwm5xY/PvTqZR1//jk8fmw2j6M4fx7efttaiti69ZPB8SIiIs/Qq0wvsvpl5cq9K3y67lPTcUT+k20XtwFW0dbX29dwGhFxFs+vHIgYZLfbadmyJZ6ens98f3BwcAwnkmjRoYO15O7cOZgyBd5913Qisx4+hEaN4OZNKFTI6tay2UynEhERB+bl5sXoWqOp+kNVvt/5Pc3zN6dIqiKmY4m8Es3XEpFXoY4tcUgtWrTA39+fRIkSPfPm7+9P8+bNTceU/8rbGz75xDoeOBDicsEyPByaN4edO8HPz5qr5e1tOpWIiDiBKpmq0DRvU8Lt4XRY0oGw8DDTkUReSURhq1TaUoaTiIgzUceWOKQpU6aYjiAxpV07q2vr4kWYMAE6dzadyIxeveCnn8DdHRYsgAwZTCcSEREnMvy14Sw9sZTdV3YzeudouhTvYjqSyEsJDQ9lx6UdgDq2ROTlqGNLRMzy8noyKH3wYGs5XlwzZgx89ZV1PGUKlC9vNo+IiDid5AmS82XlLwHova43l4IuGU4k8nIOXDvAg5AHJPJMRM5kOU3HEREnosKWiJjXujWkSwdXrsC4cabTxKxly550qX3+OTRtajaPiIg4rXaF21EiTQnuPr7LBys/MB1H5KVsubAFgOJpiuNi08tUEXlxesYQEfM8PKBPH+v4i8+vPaoAADTFSURBVC/g/n2zeWLK3r3w5pvWfK1WrZ50romIiLwCF5sLY2uNxdXmyrzD81h+YrnpSCIvTIPjReRVqbAlIo6hRQvImBGuX7eW5sV2Fy5ArVpWEa9KFatTTTsgiojIf5Q/RX66legGQKdlnXgQ8sBsIJEXpMKWiLwqFbZExDG4u0PfvtbxwIFw/rzZPNEpKMgqal25ArlzPxkaLyIiEgX6V+hP2oRpOXPnDAM3DTQdR+RfXb9/ndO3TwPWUkQRkZehwpaIOI5mzaBYMQgMhObNISwWblf++DG88QYcOAApUlgzthIlMp1KRERikQQeCfi2xrcAfLXlKw5dP2Q4kcg/23rB6tbKnSw3ib0Smw0jIk5HhS0RcRxubjBzJsSPDxs3PtkpMLaIKGqtWmV9j0uXWkPzRUREoli9HPWom70uoeGhdFzWEbvdbjqSyHNpGaKI/BcqbImIY8mSBb61/spMnz6wa5fZPFElOBgaNYJFi8DLCxYsgEKFTKcSEZFY7Nsa3xLPPR6bzm1i+r7ppuOIPNemc5sAKJW2lOEkIuKMVNgSEcfTsqVVBAoNhSZNnH+XxOBgeP11WLzYKmotWgSvvWY6lYiIxHLpEqWjX/l+APRc3ZNbD24ZTiTytLvBd9lxaQcAFTNWNJxGRJyRClsi4nhsNmuXwDRp4MQJ+OAD04le3aNH0KCBtezQ2xuWLIGqVU2nEhGROOKDEh+QO1lubj64ycdrPzYdR+Qpm85tIsweRibfTGRInMF0HBFxQipsiYhj8vOD6dOtIteECbBwoelEL+/RI6hfH5Yvf1LUqlzZdCoREYlD3F3dGVNrDAAT9kyIHNIt4ijWnVkHQKUMlQwnERFnpcKWiDiuihXhww+t47Zt4dIls3lexsOHUK8erFwJ8eJZux9W0i9sIiIS88qmL0urAq0AeG/pe4SGhxpOJPLE2jNrAaicSX/8E5FXo8KWiDi2zz6zhqwHBECLFhAebjrRv7t/3ypqRex+uHw5VKhgOpWIiMRhQ6sOxc/bj33X9vHt9m9NxxEB4OaDm+y7tg+Aihk0X0tEXo0KWyLi2Dw8YNYsaynf2rXw9demE/2zkyehRAlYvfpJUatcOdOpREQkjksaLylDqgwBoO+GvlwMumg4kQisP7MegDz+eUieILnhNCLirFTYEhHHlz07jBhhHX/0EYwfbzTOcy1dCkWKwMGDkCKFVdwqW9Z0KhEREQBaF2xNyTQluff4Ht1WdDMdR0TztUQkSqiwJSLOoV07aN/eWor47rvw+edgt5tOZQkPt5ZM1qkDgYFQqhTs3g0lS5pOJiIiEsnF5sLY2mNxtbky/8h8lp9YbjqSxHGaryUiUUGFLRFxDjYbjB0LvXtbb/ftC507Q1iY2VyBgdbOh/36WYW2jh1h/XpIlcpsLhERkWfIlzwfXYt3BaDz8s48DHloOJHEVRcCL3Ai4AQuNhfKpdfYBhF5dSpsiYjzsNlg4ED49lvrePRoaNwYHj0yk+fQIShaFBYvBk9PmDIFvv/emgsmIiLioPpX6E9qn9Scvn2aQb8OMh1H4qiIZYhFUhUhsVdis2FExKmpsCUizqdzZ/jxR6uA9NNPUKOG1TkVU4KDrSH2xYvDiROQLh1s3gwtW8ZcBhERkVfk4+nDyOojARi6eShHbx41nEjionVnrcJW5Yxahigi/40KWyLinN5809px0McHNmyAChXg6tXoPWd4uLVDY44c0KMH3L8PlSrBrl1QuHD0nltERCQKNczZkJpZaxISHkLHpR2xO8rcSokT7HY7a09b87UqZdTgeBH5b1TYEhHnVakSbNwIyZPD779bOxJ+/z08eBD151q/HooVg6ZN4exZa4bWpEmwahUkSxb15xMREYlGNpuNb2t8i5ebF+vPrmfWgVmmI0kcciLgBJfuXsLD1YPSaUubjiMiTk6FLRFxbgULwpYtkCULXLpkLVNMn97apfDWrf/+9Q8ehFq1rCLa7t1Wh9igQdYSxNatwdX1v59DRETEgEy+mfi07KcAdF/VnTuP7pgNJHFGRLdWqbSl8Hb3NpxGRJydClsi4vwyZYJ9++C77yBjRrh509qlMF066NoVzp178a8VHGwtbezTB0qVgvz5YdkycHOzimYnT8Inn0C8eNH27YiIiMSUnqV6kj1Jdq7fv07vtb1Nx5E4QvO1RCQquZkOICISJeLFg06d4N13rYHyQ4fC3r0wapS1PLFmTauTK0kSSJrUuo84fvzYKmatXQu//fb0Louvvw6DB0O2bEa+NRERkeji6ebJ6FqjqTy9MmN2jaFlgZYUTV3UdCyJxcLt4aw/sx7QfC0RiRoqbIlI7OLmBo0bw1tvwZo1MGSIVbBavPjFv0aKFNbSw8qVrfsMGaItroiIiGmVMlaiad6mzDwwk/eWvsf2tttxddFSe4ke+6/t59bDWyTwSEDRVCqiish/p8KWiMRONhtUrWrd9uyxhszfumUtU7x166/HISFQuvSTYlbOnNbni4iIxBHDXxvOkuNL2H1lN2N2jaFzsc6mI0ksFTFfq1z6cri7uhtOIyKxgQpbIhL7FSpk3UREROSZkidIzuDKg+m0rBO91/Xm9Zyvk9InpelYEgtpvpaIRDUNjxf5m7Nnz9KmTRsyZsyIt7c3mTNnpl+/fjx+/Nh0NBEREZFo827hdymSqghBwUH0WNXDdByJhULCQth0bhOg+VoiEnVU2BL5m6NHjxIeHs64ceM4dOgQ33zzDWPHjuWTTz4xHU1EREQk2ri6uDK21lhcbC7MPjibNafXmI4ksczOyzu59/geSbyTkC95PtNxRCSWUGFL5G+qV6/OlClTeO2118iUKRN169alZ8+eLFiwwHQ0ERERkWhVOFVhOhXtBEDHpR15FProXz5D5MVFzNeqmLEiLja9FBWRqKEZWyIvIDAwED8/v3/8mODgYIKDgyPfDgoKAiAkJISQkJBozfdvIs5vOoc4D10z8rJ0zcjL0jXjuPqW6ctPh3/iRMAJBm8aTJ+yfUxHAnTNxAYRha0K6SrEyH9HR7pmHCGDSGxls9vtdtMhRBzZqVOnKFSoEMOHD6dt27bP/bj+/fszYMCApx6fNWsW8eLFi86IIiIiIlHqt9u/MezcMNxsbozKMYpUnqlMRxInFxweTNMDTQm1h/J9ju9J7ZXadKQY9eDBA5o0aUJgYCAJEyY0HUckVlFhS+KM5xWe/mznzp0UKVIk8u3Lly9Tvnx5ypcvz8SJE//xc5/VsZU2bVpu3rxp/IdXSEgIq1evpmrVqri7a1tl+Xe6ZuRl6ZqRl6VrxrHZ7XbqzKnDqtOrqJShEsvfXo7NZjOaSdeMc1t7Zi01ZtcgjU8aTnU+FSPXkyNdM0FBQSRNmlSFLZFooKWIEmd07tyZxo0b/+PHZMiQIfL48uXLVKxYkZIlSzJ+/Ph//fqenp54eno+9bi7u7vxH6QRHCmLOAddM/KydM3Iy9I147hG1xpNnjF5WHd2HT8d+4kmeZuYjgTomnFWG89vBKBypsp4eHjE6Lkd4ZoxfX6R2EyFLYkzkiZNStKkSV/oYy9dukTFihUpXLgwU6ZMwcVFwy1FREQkbsnsl5lPy37Kp+s/5YOVH1AjSw18vX1NxxInteaMtctmpYyVDCcRkdhGr9ZF/uby5ctUqFCBtGnTMmzYMG7cuMHVq1e5evWq6WgiIiIiMapnqZ7kSJqD6/ev88naT0zHESd1+e5ldl3ehQ0b1TJXMx1HRGIZFbZE/mbVqlWcPHmSdevWkSZNGlKmTBl5ExEREYlLPN08GVNrDADjdo9j28VthhOJM1p8bDEAxdMUJ3mC5IbTiEhso8KWyN+0bNkSu93+zJuIiIhIXFMhQwVa5G+BHTsdlnQgNDzUdCRxMr8c+wWAetnrGU4iIrGRClsiIiIiIvKPvqr6Fb5evuy7to9R20eZjiNO5N7je6w9sxaAutnrGk4jIrGRClsiIiIiIvKPksVPxtCqQwHou74vFwIvGE4kzmLlyZU8DntMFr8s5Eya03QcEYmFVNgSEREREZF/1bpga0qnLc39kPu8v+J903HESSw6vgiAutnqYrPZDKcRkdhIhS0REREREflXLjYXxtYei5uLGz8f/Zlfjv5iOpI4uNDwUJYeXwpAvRyaryUi0UOFLREREREReSF5/PPQs2RPADov78zd4LuGE4kj23JhC7ce3sLP249SaUuZjiMisZQKWyIiIiIi8sL6lu9LJt9MXAy6yKfrPjUdRxzYomPWMsTa2Wrj5uJmOI2IxFYqbImIiIiIyAvzdvdmbK2xAHy741t2XtppOJE4Irvdzi/HrOWqdbNpN0QRiT4qbImIiIiIyEupmrkqTfM2xY6d9kvaExoeajqSOJijN49yMuAkHq4eVMtSzXQcEYnFVNgSEREREZGX9nW1r/H18uX3q78zcttI03HEwUR0a1XOWJkEHgkMpxGR2EyFLREREREReWn+8f35qupXAPTd0Jezd86aDSQOJWK+Vt3sWoYoItFLhS0REREREXklrQu2plz6cjwIeUCnZZ2w2+2mI4kDuHbvGtsubgOgTrY6htOISGynwpaIiIiIiLwSm83GuNrj8HD1YNmJZcw7PM90JHEAS44vwY6dIqmKkDphatNxRCSWU2FLREREREReWY6kOfi4zMcAdF3RlTuP7pgNJMYtOm4tQ6yXvZ7hJCISF6iwJSIiIiIi/8nHZT4me5LsXL13lV5repmOIwY9CHnA6lOrAc3XEpGYocKWiIiIiIj8J55unoyrPQ6AcbvH8eu5Xw0nElPWnF7Dw9CHZEicgbz+eU3HEZE4QIUtERERERH5z8pnKE+bgm0AaLu4LY9CHxlOJCb8cvQXAOpmq4vNZjOcRkTiAhW2REREREQkSnxV9StSJEjB8VvH+Xzj56bjSAwLCw9j8fHFANTLoflaIhIzVNgSEREREZEo4evty+iaowEYumUo+67uM5xIYtL2S9u58eAGib0SUzZdWdNxRCSOUGFLRERERESiTIOcDXg95+uEhofSZlEbQsNDTUeSGLLomLUbYs2sNXF3dTecRkTiChW2REREREQkSn1X8zsSeyVm95XdfLP1G9NxJAbY7XZ+PvozYM3XEhGJKSpsiYiIiIhIlEqRIAXDXxsOQN8NfTkZcNJwIolue67s4ditY3i5eVEjaw3TcUQkDlFhS0REREREolyrAq2onLEyj0If0X5xe+x2u+lIEo2m75sOQIMcDUjomdBwGhGJS1TYEhERERGRKGez2RhfZzzebt6sP7ueSXsnmY4k0eRx2GNmHZwFQPP8zQ2nEZG4RoUtERERERGJFpl8MzGw0kAAeq7qyeW7lw0nkuiw4uQKbj64SYoEKaiSqYrpOCISx6iwJSIiIiIi0aZr8a4UTVWUwOBAOi3rpCWJsVDEMsSmeZvi5uJmOI2IxDUqbImIiIiISLRxdXFlYt2JuLm48fPRn5l7aK7pSBKFAh4GsPj4YkDLEEXEDBW2REREREQkWuVLno/eZXsD0GlZJ/7f3p2H53Qmbhy/3yyySII0pEiIpbZBaIImVVsnthmlpmpJLRWUSkd1XDXDtImiWmvRomuS2tMFbVVJbdGFiqIEoYqo0JKWBElkOb8/jPfXiJCoOHmT7+e6el3OOc97zp3jacLd55z+cvEXkxPhTolNjNWV3Cvy9/ZXc+/mZscBUA5RbAEAAAAocRMemiB/b3+lZqRq1NpRPJJYRlx7DJHVWgDMQrEFAAAAoMRVsK+gmF4xcrBz0KpDq7R8/3KzI+FPOpJ6RN/+/K3sLHYa0GyA2XEAlFMUWwAAAADuCv97/fVCuxckSeGfh+t0+mmTE+HPWPzDYklSl3pddK/bvSanAVBeUWwBAAAAuGv+0/Y/anlvS/2e+btGrh3JI4k2Ks/IsxZbPIYIwEwUWwAAAADuGkd7R8X0ipGjnaM+SfpES/ctNTsSbsO2E9t0/PxxeTh5qGfDnmbHAVCOUWwBAAAAuKuaeTdTRPsISdIz655RSnqKyYlQXNdeGv94k8fl4uhichoA5RnFFgAAAIC7bnzb8QqoHqDzmef11GdP8UiiDbmcfVkfHPhAEo8hAjAfxRYAAACAu87BzkExvWJUwb6CPjv8mXUFEEq/NYfWKP1KuupUrqMHaz1odhwA5RzFFgAAAABT/KXaXzSpwyRJ0pgvxujntJ9NToSieP+HqyXkwOYDZWfhr5QAzMV3IQAAAACmGRc8Tq1rttaFrAsavHqw8ow8syPhJk6nn9aGoxskSQP9B5qcBgAotgAAAACYyMHOQYsfXSxXR1dtOrZJc76dY3Yk3MSyfcuUZ+Qp2DdY9T3rmx0HACi2AAAAAJirwT0NNKfL1UJrwqYJ2ntmr8mJcCOGYShmb4wkaVBzXhoPoHSg2AIAAABguuH3D9cjDR/RldwrCv04VBnZGWZHwnW+Sv5K+37dJyd7Jz3+l8fNjgMAkii2AAAAAJQCFotF7/R4R94VvZV4NlH//vLfZkfCdWZ9O0uSNNh/sKq4VDE5DQBcRbEFAAAAoFSoWrGqonpGSZLmfTdP639cb3IiXHM49bA+SfpEkjQ2aKzJaQDg/1FsATeRlZWlFi1ayGKxaM+ePWbHAQAAKPO63ddNo1uNliQNWTNE5y6fMzkRJGnOt3NkyFCPBj3UyKuR2XEAwIpiC7iJ559/XjVq1DA7BgAAQLkyI2SGGns11pmLZzT80+EyDMPsSOXa2UtnFb03WpL0r6B/mRsGAK5DsQUUYt26ddqwYYNmzpxpdhQAAIByxcXRRUt7L5WjnaNWH1qt93a/Z3akcm1hwkJl5mQqoHqA2tVuZ3YcAMjHwewAQGn0yy+/aPjw4Vq9erVcXV2L9JmsrCxlZWVZt9PS0iRJ2dnZys7OLpGcRXXt+mbngO1gzqC4mDMoLuYMbqWpV1NNaj9JEzZP0JgvxqiVdytJzJm7LTMnU69/97ok6dnWzyonJ8fkREVXmr7PlIYMQFllMVjXC+RjGIa6d++uBx98UP/97391/Phx1alTR7t371aLFi0K/VxkZKQmTZpUYP+yZcuKXI4BAADg/+UauYo4GqH9F/erjksdvXLfK3KyczI7VrmyIXWDFpxcoKqOVbWoySLZW+zNjmSTLl++rAEDBujChQvy8PAwOw5QplBsodworHj6o507d+qbb77RypUrFR8fL3t7+yIXWzdaseXr66tz586Z/sMrOztbcXFxCgkJkaOjo6lZYBuYMygu5gyKizmDojqVfkqt322ts5fPqvM9nbVq6CrmzF2SZ+TJ/y1/JaUmacZfZ2hM6zFmRyqW0vR9Ji0tTV5eXhRbQAngUUSUG+Hh4erXr99Nx/j5+WnKlCnavn27nJzy/9fAwMBAhYaGKiYm5oafdXJyKvAZSXJ0dDT9B+k1pSkLbANzBsXFnEFxMWdwK36eflrSe4m6LumqDakb9EHSBxrccrDZscqFzw5/pqTUJHk4eWhE4Aib/Xe1NHyfMfv6QFlGsYVyw8vLS15eXrccN2/ePE2ZMsW6nZKSoi5dumjlypVq06ZNSUYEAADADXSu11n/efA/evnrlzV63Wi18W2jRl6NzI5V5s36dpYkacT9I+ThxCojAKUTxRZwnVq1auXbdnNzkyTVq1dPPj4+ZkQCAAAo91546AV9uvdT7bu4T4/FPqbvhn8nV0feY1pSdqXs0pbjW+Rg56B/tvmn2XEAoFB2ZgcAAAAAgFuxt7PXc7Wfk3dFbyWeTdToz0ebHalMu7Zaq+9f+sq3kq/JaQCgcBRbwC34+fnJMIybvjgeAAAAJa+KYxUt7rlYdhY7Re+JVtTuKLMjlUnJF5IVmxgrSfpX0L9MTgMAN0exBQAAAMBmdPDroEkdrv6frkd/Plr7ftlncqKyZ96Oeco1ctWpTie1rN7S7DgAcFMUWwAAAABsyoSHJqhLvS7KyMlQnw/6KD0r3exIZcbvGb/rrV1vSZLGBY0zOQ0A3BrFFgAAAACbYmex0+JHF6ume00lpSZpyJohyjPyzI5VJry09SWlX0lXs2rN1LV+V7PjAMAtUWwBAAAAsDlVK1ZVbJ9YOdo56uODH2vSlklmR7J5SeeS9PrO1yVJMzvPlMViMTkRANwaxRYAAAAAmxTsG6y3elx9bO6l+Je0cv9KkxPZtnFx45STl6O/3fc3da7X2ew4AFAkFFsAAAAAbNaQFkP03APPXf31miHalbLL5ES2Ke5onD47/Jkc7Bw0s/NMs+MAQJFRbAEAAACwadNDpqtr/a7KzMlUzxU9dTr9tNmRbEpOXo6e23C1HBzdarQaeTUyOREAFB3FFgAAAACbZm9nrxX/WKFGXo10Kv2Ueq3spYzsDLNj2Yx3vn9H+3/dL08XT73Y/kWz4wBAsVBsAQAAALB5lZwr6dP+n6qKcxV9d+o7Df90uAzDMDtWqXc+87xe2PyCJGlSh0nydPE0OREAFA/FFgAAAIAyob5nfX34+Ieyt9hr6b6levXrV82OVOpNiZ+ic5fPqbFXYz0V8JTZcQCg2Ci2AAAAAJQZnep00vxu8yVJEzZO0KqDq0xOVHodST2ieTvmSZJmdZ4lR3tHkxMBQPFRbAEAAAAoU0a1GqVRgaNkyFD/j/pry/EtZkcqlZ7/8nll52Wra/2u6nZfN7PjAMBtodgCAAAAUObM7TpXjzR8RFm5WXpk+SNKSEkwO1KpsunYJq0+tFr2FnvN6jzL7DgAcNsotgAAAACUOY72jlr52Ep19Ouo9Cvp6rqkqw6ePWh2rFIhNy9XY9ePlSSNChylJlWbmJwIAG4fxRYAAACAMsnZwVlr+q1RYI1ApWakKmRxiE6cP2F2LNNN3TZVP/zygyo7V1Zkh0iz4wDAn0KxBQAAAKDMcndy17rQdWrs1Vin0k8pZHGIfrn4i9mxTLPp2CZFbomUdPVxzXtc7zE3EAD8SRRbAAAAAMo0L1cvbRi4QbUr1daR346oy5IuOp953uxYd92Zi2c04KMBMmRoaIuhGuQ/yOxIAPCnUWwBAAAAKPN8PHz05aAv5V3RW3t/2au/L/u7LmdfNjvWXZObl6vQj0P1y6Vf1LRaU83vPt/sSABwR1BsAQAAACgX6nvW1/on1quyc2V9ffJr9VjeQ+lZ6WbHuismx0/WpmObVNGxoj7o84FcHV3NjgQAdwTFFgAAAIByw/9ef60dsFZuFdy06dgmdXq/k85eOmt2rBK18aeNemnrS5KkN//+php5NTI5EQDcORRbAAAAAMqVYN9gbRq0SV6uXkpISVDbqLZl9v+WeDr9tAZ8fPW9WsNaDlNo81CzIwHAHUWxBQAAAKDcaVWzlb568ivVqlRLh1MPK/i9YCX+mmh2rDsqNy9XAz4eoF8v/apm1ZppXrd5ZkcCgDuOYgsAAABAudTQq6G+Hvq1mlRtopT0FD0U9ZC+OfmN2bHumElbJ2nL8S1yq+CmD/p8IBdHF7MjAcAdR7EFAAAAoNzy8fDRtie3KcgnSL9n/q6/vv9XfX7kc7Nj/Wkr96/UlPgpkqS3/v6WGno1NDkRAJQMii0AAAAA5Zqni6fiBsapW/1uysjJ0CPLH1HU7iizY922t3e9rf4f9ZchQ6MCR6l/s/5mRwKAEkOxBQAAAKDcq1ihotb0W6PQZqHKNXI19JOhenLNk7p05ZLZ0Ypl1jezNOKzETJkaGTASM3vNt/sSABQoii2AAAAAECSo72j3n/0fUW0j5CdxU7Re6IV8FaA9p7Za3a0WzIMQy9uflHj4sZJkp4Pfl4L/rZA9nb2JicDgJJFsQUAAAAA/2NnsVNkh0htHLRRNdxrKCk1SW3eaaM3vntDhmGYHe+G8ow8jflijCbHT5YkTXt4ml4NeVUWi8XkZABQ8ii2AAAAAOA6Hfw6aO/Ivfp7g78rKzdL4evC1Tu2t37L+M3saPnk5OUo7JMwzf/u6iOHb3R/Q/9u+2+TUwHA3UOxBQAAAAA34OXqpU/6faLXurwmRztHrT60Wi0WtVD8iXizo0mSMnMy1e/DforeEy17i70WP7pYT7d62uxYAHBXUWwBAAAAQCEsFovGPDBG34Z9q/qe9XUy7aTaR7dXrxW9tP/X/aZkMgxDqw+tVpM3muijgx+pgn0Fffj4h3qi+ROm5AEAM1FsAQAAAMAtBNQI0PcjvteI+0fIzmKnNUlr1Hxhcw1cNVA//f7TXctx4OwBdV7SWY+ufFTHzh9TTfeaWhe6Tr0a9bprGQCgNKHYAgAAAIAicHdy15s93lTi04l6rMljMmRoyQ9L1Oj1Rhq9drROp58usWufzzyvsV+MVfOFzfXlT1+qgn0FTXxoog6FH1KnOp1K7LoAUNpRbAEAAABAMTTyaqQP+nyghOEJ6lKvi7LzsrUgYYHqzaunZ794VluPb1V2bvYdudaV3Ct65/t31GB+A7224zXlGrnq2bCnDjx9QFM6TZFbBbc7ch0AsFUOZgcAAAAAAFsUUCNAXzzxhbYe36r/bPyPvv35W83dMVdzd8xVJadK6lK/i/5239/UtX5XVatYrUjnzDPytPfMXm08tlEbj23UthPbdCn7kqSrhdrcrnPVuV7nkvyyAMCmUGwBAAAAwJ/Q3q+9vh76tdb9uE7L9y/XuiPrlJqRqtjEWMUmxsoii1rVbKWHaj0ktwpucnZwtv7jZO8kZwdn/Z75uzYf36zNxzYrNSM13/m9K3pr/IPjFd46XI72jiZ9lQBQOlFsAQAAAMCfZLFY1P2+7up+X3fl5uVqZ8pOrT28VmuPrNXuM7v13anv9N2p74p0LrcKbmpfu70ervOwHq77sJpWayo7C2+RAYAbodgCAAAAgDvI3s5eD/g8oAd8HtDkTpOVkp6iz498rgNnDygzJ1OZOZnKys2y/jozJ1OOdo560PdBPVz3YbWq0YqVWQBQRBRbAAAAAFCCarjX0LD7h5kdAwDKJNazAgAAAAAAwCZRbAEAAAAAAMAmUWwBAAAAAADAJlFsAYVYu3at2rRpIxcXF3l5eal3795mRwIAAAAAAH/Ay+OBG/joo480fPhwvfzyy+rUqZMMw9C+ffvMjgUAAAAAAP6AYgu4Tk5OjsaMGaMZM2YoLCzMur9hw4YmpgIAAAAAANej2AKu8/333+vUqVOys7NTy5YtdebMGbVo0UIzZ87UX/7yl0I/l5WVpaysLOt2WlqaJCk7O1vZ2dklnvtmrl3f7BywHcwZFBdzBsXFnEFxMWdQXKVpzpSGDEBZZTEMwzA7BFCarFixQv3791etWrU0e/Zs+fn5adasWdqwYYMOHz4sT0/PG34uMjJSkyZNKrB/2bJlcnV1LenYAAAAAEqpy5cva8CAAbpw4YI8PDzMjgOUKRRbKDcKK57+aOfOnTp8+LBCQ0P15ptvasSIEZKursby8fHRlClT9NRTT93wszdaseXr66tz586Z/sMrOztbcXFxCgkJkaOjo6lZYBuYMygu5gyKizmD4mLOoLhK05xJS0uTl5cXxRZQAngUEeVGeHi4+vXrd9Mxfn5+Sk9PlyQ1adLEut/JyUl169ZVcnJyoZ91cnKSk5NTgf2Ojo6m/yC9pjRlgW1gzqC4mDMoLuYMios5g+IqDXPG7OsDZRnFFsoNLy8veXl53XJcQECAnJyclJSUpLZt20q6+l97jh8/rtq1a5d0TAAAAAAAUEQUW8B1PDw8NHLkSEVERMjX11e1a9fWjBkzJEl9+vQxOR0AAAAAALiGYgu4gRkzZsjBwUEDBw5URkaG2rRpo02bNqlKlSpmRwMAAAAAAP9DsQXcgKOjo2bOnKmZM2eaHQUAAAAAABTCzuwAAAAAAAAAwO2g2AIAAAAAAIBNotgCAAAAAACATaLYAgAAAAAAgE3i5fFACTEMQ5KUlpZmchIpOztbly9fVlpamhwdHc2OAxvAnEFxMWdQXMwZFBdzBsVVmubMtb8TXPs7AoA7h2ILKCHp6emSJF9fX5OTAAAAACgN0tPTValSJbNjAGWKxaAyBkpEXl6eUlJS5O7uLovFYmqWtLQ0+fr66uTJk/Lw8DA1C2wDcwbFxZxBcTFnUFzMGRRXaZozhmEoPT1dNWrUkJ0dbwQC7iRWbAElxM7OTj4+PmbHyMfDw8P0H+qwLcwZFBdzBsXFnEFxMWdQXKVlzrBSCygZVMUAAAAAAACwSRRbAAAAAAAAsEkUW0A54OTkpIiICDk5OZkdBTaCOYPiYs6guJgzKC7mDIqLOQOUD7w8HgAAAAAAADaJFVsAAAAAAACwSRRbAAAAAAAAsEkUWwAAAAAAALBJFFsAAAAAAACwSRRbQDly/PhxhYWFqU6dOnJxcVG9evUUERGhK1eumB0NpdjUqVMVHBwsV1dXVa5c2ew4KIUWLFigOnXqyNnZWQEBAdq2bZvZkVCKxcfHq0ePHqpRo4YsFotWr15tdiSUYtOmTVOrVq3k7u6uatWqqVevXkpKSjI7FkqxhQsXqnnz5vLw8JCHh4eCgoK0bt06s2MBKEEUW0A5cujQIeXl5enNN99UYmKi5syZo0WLFmnChAlmR0MpduXKFfXp00ejRo0yOwpKoZUrV+rZZ5/VxIkTtXv3bj300EPq1q2bkpOTzY6GUurSpUvy9/fX66+/bnYU2ICtW7dq9OjR2r59u+Li4pSTk6POnTvr0qVLZkdDKeXj46NXXnlFCQkJSkhIUKdOndSzZ08lJiaaHQ1ACbEYhmGYHQKAeWbMmKGFCxfqp59+MjsKSrno6Gg9++yzOn/+vNlRUIq0adNG999/vxYuXGjd17hxY/Xq1UvTpk0zMRlsgcVi0apVq9SrVy+zo8BGnD17VtWqVdPWrVvVrl07s+PARnh6emrGjBkKCwszOwqAEsCKLaCcu3Dhgjw9Pc2OAcAGXblyRbt27VLnzp3z7e/cubO++eYbk1IBKMsuXLggSfzZBUWSm5urFStW6NKlSwoKCjI7DoAS4mB2AADmOXr0qObPn69Zs2aZHQWADTp37pxyc3Pl7e2db7+3t7fOnDljUioAZZVhGHruuefUtm1bNW3a1Ow4KMX27dunoKAgZWZmys3NTatWrVKTJk3MjgWghLBiCygDIiMjZbFYbvpPQkJCvs+kpKSoa9eu6tOnj4YNG2ZScpjlduYMUBiLxZJv2zCMAvsA4M8KDw/XDz/8oOXLl5sdBaVcw4YNtWfPHm3fvl2jRo3S4MGDdeDAAbNjASghrNgCyoDw8HD169fvpmP8/Pysv05JSVHHjh0VFBSkt956q4TToTQq7pwBbsTLy0v29vYFVmf9+uuvBVZxAcCf8cwzz+iTTz5RfHy8fHx8zI6DUq5ChQqqX7++JCkwMFA7d+7U3Llz9eabb5qcDEBJoNgCygAvLy95eXkVaeypU6fUsWNHBQQEKCoqSnZ2LNwsj4ozZ4DCVKhQQQEBAYqLi9Ojjz5q3R8XF6eePXuamAxAWWEYhp555hmtWrVKW7ZsUZ06dcyOBBtkGIaysrLMjgGghFBsAeVISkqKOnTooFq1amnmzJk6e/as9di9995rYjKUZsnJyfrtt9+UnJys3Nxc7dmzR5JUv359ubm5mRsOpnvuuec0cOBABQYGWleBJicna+TIkWZHQyl18eJF/fjjj9btY8eOac+ePfL09FStWrVMTIbSaPTo0Vq2bJnWrFkjd3d36wrRSpUqycXFxeR0KI0mTJigbt26ydfXV+np6VqxYoW2bNmiL774wuxoAEqIxTAMw+wQAO6O6OhoPfnkkzc8xrcCFGbIkCGKiYkpsH/z5s3q0KHD3Q+EUmfBggWaPn26Tp8+raZNm2rOnDlq166d2bFQSm3ZskUdO3YssH/w4MGKjo6++4FQqhX2vr6oqCgNGTLk7oaBTQgLC9PGjRt1+vRpVapUSc2bN9f48eMVEhJidjQAJYRiCwAAAAAAADaJl+sAAAAAAADAJlFsAQAAAAAAwCZRbAEAAAAAAMAmUWwBAAAAAADAJlFsAQAAAAAAwCZRbAEAAAAAAMAmUWwBAAAAAADAJlFsAQAAAAAAwCZRbAEAgDvOYrFo9erVZscoksjISLVo0cLsGHecn5+fXnvttSKPj46OVuXKlW865k7dq9TUVFWrVk3Hjx8v0visrCzVqlVLu3bt+tPXBgAAZQvFFgAAsBoyZIh69epldgybV5SSqKTt3LlTI0aMMDVDYaZNm6YePXrIz8+vSOOdnJw0btw4jR8/vmSDAQAAm0OxBQAAUIZcuXJFklS1alW5urqanKagjIwMvfvuuxo2bFixPhcaGqpt27bp4MGDJZQMAADYIootAABQqA4dOuif//ynnn/+eXl6euree+9VZGRkvjFHjhxRu3bt5OzsrCZNmiguLq7AeU6dOqW+ffuqSpUquueee9SzZ898j6FdWyk2adIkVatWTR4eHnrqqaesJY0kGYah6dOnq27dunJxcZG/v78+/PBD6/EtW7bIYrFo48aNCgwMlKurq4KDg5WUlJQvyyuvvCJvb2+5u7srLCxMmZmZBfJGRUWpcePGcnZ2VqNGjbRgwQLrsePHj8tisejjjz9Wx44d5erqKn9/f3377bfWHE8++aQuXLggi8Uii8VS4J5JUlJSkiwWiw4dOpRv/+zZs+Xn5yfDMJSbm6uwsDDVqVNHLi4uatiwoebOnZtv/LV7N23aNNWoUUMNGjSQVPBRxNmzZ6tZs2aqWLGifH199fTTT+vixYsFcq1evVoNGjSQs7OzQkJCdPLkyQJjinqvbmTdunVycHBQUFCQdd9LL72kGjVqKDU11brvkUceUbt27ZSXlydJuueeexQcHKzly5ff9PwAAKB8odgCAAA3FRMTo4oVK2rHjh2aPn26XnrpJWt5lZeXp969e8ve3l7bt2/XokWLCjwudvnyZXXs2FFubm6Kj4/XV199JTc3N3Xt2jVfcbVx40YdPHhQmzdv1vLly7Vq1SpNmjTJevy///2voqKitHDhQiUmJmrs2LF64okntHXr1nzXmzhxombNmqWEhAQ5ODho6NCh1mOxsbGKiIjQ1KlTlZCQoOrVqxcoYt5++21NnDhRU6dO1cGDB/Xyyy/rhRdeUExMTIHrjBs3Tnv27FGDBg3Uv39/5eTkKDg4WK+99po8PDx0+vRpnT59WuPGjStwXxs2bKiAgAAtXbo03/5ly5ZpwIABslgsysvLk4+Pj2JjY3XgwAG9+OKLmjBhgmJjY/N95tq9i4uL02effXbD30c7OzvNmzdP+/fvV0xMjDZt2qTnn3++wO/V1KlTFRMTo6+//lppaWnq16/fDc9XnHv1R/Hx8QoMDCxwL/38/KyruBYtWqT4+HgtXrxYdnb//8fV1q1ba9u2bYWeGwAAlEMGAADA/wwePNjo2bOndbt9+/ZG27Zt841p1aqVMX78eMMwDGP9+vWGvb29cfLkSevxdevWGZKMVatWGYZhGO+++67RsGFDIy8vzzomKyvLcHFxMdavX2+9rqenp3Hp0iXrmIULFxpubm5Gbm6ucfHiRcPZ2dn45ptv8mUJCwsz+vfvbxiGYWzevNmQZHz55ZfW42vXrjUkGRkZGYZhGEZQUJAxcuTIfOdo06aN4e/vb9329fU1li1blm/M5MmTjaCgIMMwDOPYsWOGJOOdd96xHk9MTDQkGQcPHjQMwzCioqKMSpUqGbcye/Zso27dutbtpKQkQ5KRmJhY6Geefvpp4x//+Id1e/DgwYa3t7eRlZWVb1zt2rWNOXPmFHqe2NhY45577rFuR0VFGZKM7du3W/cdPHjQkGTs2LHDMAzDiIiIKNa9upGePXsaQ4cOLbD/6NGjhru7uzF+/HjD1dXVWLJkSYExc+fONfz8/Ao9NwAAKH9YsQUAAG6qefPm+barV6+uX3/9VZJ08OBB1apVSz4+Ptbjf3zETJJ27dqlH3/8Ue7u7nJzc5Obm5s8PT2VmZmpo0ePWsf5+/vneydUUFCQLl68qJMnT+rAgQPKzMxUSEiI9Rxubm56//33853j+rzVq1eXpHx5r8/3x+2zZ8/q5MmTCgsLy3edKVOmFOs6RdWvXz+dOHFC27dvlyQtXbpULVq0UJMmTaxjFi1apMDAQFWtWlVubm56++23lZycnO88zZo1U4UKFW56rc2bNyskJEQ1a9aUu7u7Bg0apNTUVF26dMk6xsHBId9qqkaNGqly5co3fK9Vce7VH2VkZMjZ2bnA/rp162rmzJl69dVX1aNHD4WGhhYY4+LiosuXL9/06wQAAOWLg9kBAABA6ebo6Jhv+9ojctLV915dz2Kx5NvOy8u74SN30tUXnN/KH6+3du1a1axZM99xJyenQvNey3Lt87dybdzbb7+tNm3a5Dtmb29/x65zTfXq1dWxY0ctW7ZMDzzwgJYvX66nnnrKejw2NlZjx47VrFmzFBQUJHd3d82YMUM7duzId56KFSve9DonTpxQ9+7dNXLkSE2ePFmenp766quvFBYWpuzs7Hxjr//9K2xfce7VH3l5een333+/4bH4+HjZ29vr+PHjysnJkYND/j+q/vbbb0WaMwAAoPyg2AIAALetSZMmSk5OVkpKimrUqCFJ1peoX3P//fdr5cqV1pfCF2bv3r3KyMiQi4uLJGn79u1yc3OTj4+PqlSpIicnJyUnJ6t9+/a3nbdx48bavn27Bg0aZN13bbWUJHl7e6tmzZr66aefbrhiqKgqVKig3NzcIo0NDQ3V+PHj1b9/fx09ejTfO622bdum4OBgPf3009Z9N1sNVZiEhATl5ORo1qxZ1ndWXf+eLknKyclRQkKCWrduLenqC+7Pnz+vRo0aFRh7u/eqZcuWWrJkSYH9K1eu1Mcff6wtW7aob9++mjx5cr53rEnS/v371bJlyyJfCwAAlH08iggAAG7bX//6VzVs2FCDBg3S3r17tW3bNk2cODHfmNDQUHl5ealnz57atm2bjh07pq1bt2rMmDH6+eefreOuXLmisLAwHThwQOvWrVNERITCw8NlZ2cnd3d3jRs3TmPHjlVMTIyOHj2q3bt364033rjpi8qvN2bMGL333nt67733dPjwYUVERCgxMTHfmMjISE2bNk1z587V4cOHtW/fPkVFRWn27NlFvo6fn58uXryojRs36ty5czd9fK53795KS0vTqFGj1LFjx3wr0urXr6+EhAStX79ehw8f1gsvvKCdO3cWOcc19erVU05OjubPn6+ffvpJixcv1qJFiwqMc3R01DPPPKMdO3bo+++/15NPPqkHHnjAWnRd73buVZcuXZSYmJhv1dbPP/+sUaNG6dVXX1Xbtm0VHR2tadOm5SsdpatFX+fOnYv99QMAgLKLYgsAANw2Ozs7rVq1SllZWWrdurWGDRumqVOn5hvj6uqq+Ph41apVS71791bjxo01dOhQZWRk5FvB9fDDD+u+++5Tu3bt9Pjjj6tHjx6KjIy0Hp88ebJefPFFTZs2TY0bN1aXLl306aefqk6dOkXO27dvX7344osaP368AgICdOLECY0aNSrfmGHDhumdd95RdHS0mjVrpvbt2ys6OrpY1wkODtbIkSPVt29fVa1aVdOnTy90rIeHh3r06KG9e/cWWPk0cuRI9e7dW3379lWbNm2Umpqab/VWUbVo0UKzZ8/Wq6++qqZNm2rp0qWaNm1agXGurq4aP368BgwYoKCgILm4uGjFihWFnvd27lWzZs0UGBhoXTFmGIaGDBmi1q1bKzw8XJIUEhKi8PBwPfHEE7p48aKkqysBL1y4oMcee6zYXz8AACi7LMaNXo4BAABwFw0ZMkTnz5/X6tWrzY6Cu+Dzzz/XuHHjtH//fuujkbfSp08ftWzZUhMmTCjhdAAAwJbwji0AAADcVd27d9eRI0d06tQp+fr63nJ8VlaW/P39NXbs2LuQDgAA2BJWbAEAANOxYgsAAAC3g2ILAAAAAAAANomXxwMAAAAAAMAmUWwBAAAAAADAJlFsAQAAAAAAwCZRbAEAAAAAAMAmUWwBAAAAAADAJlFsAQAAAAAAwCZRbAEAAAAAAMAmUWwBAAAAAADAJv0fGDu5ebFewFIAAAAASUVORK5CYII=",
      "text/plain": [
       "<Figure size 1000x600 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Elapsed time: 0:00:03.385478\n"
     ]
    }
   ],
   "source": [
    "# Program Polynomialla EvoluciónOfShape.py\n",
    "# We use a genetic algorithm to find the polynomial of fifth degree that best fits a set of 6 points.\n",
    "# It consists of mutation and selection of the fittest, but no recombination.\n",
    "# The coefficients of the polynomial are represented by a chromosome, \n",
    "# which is a string of digits.\n",
    "# The decoding function must divide the chromosome into parts, \n",
    "# and decode each one apart as one coefficient.\n",
    "# We consider numbers of the form -3.244025\n",
    "# with a sign that could be positive or negative, \n",
    "# and a decimal point in the second place of the encoding chromosome.\n",
    "# The error of a chromosome is the sum of the vertical distances \n",
    "# of the points to the polynomial it encodes.\n",
    "# The Genetic algorithm must minimize the error, \n",
    "# (which is equivalent to maximizing the fitness).\n",
    "# The program reports and draws a polynomial for those generations in which the error decreases.\n",
    "# Developed with the assistance of the AI of Visual Studio Code.\n",
    "# An old version of a GA developed with the help of Gemini was reused and updated.\n",
    "\n",
    "\n",
    "from datetime import datetime, timedelta\n",
    "import datetime\n",
    "import time\n",
    "import random\n",
    "import numpy as np\n",
    "from numpy.polynomial import Polynomial\n",
    "import matplotlib.pyplot as plt # Import matplotlib for plotting\n",
    "\n",
    "\n",
    "start_time = time.time() # Record the start time\n",
    "\n",
    "#Task to be done\n",
    "number_of_generations = 200\n",
    "\n",
    "xArray =  [-2, -1, 0, 1, 2, 3]\n",
    "yArray =  [5,   1, 4, 0, 6, 3]\n",
    "\n",
    "alphabet = '0123456789'\n",
    "# Chromosome encoding for one of 6 coefficients, \n",
    "# each one with a length of 5 chars.\n",
    "# Encoding number as -93.24 with a sign and a decimal point.\n",
    "length_of_chromosomes = 8\n",
    "population_size = 200\n",
    "# Include cloning of the fittest\n",
    "include_clone_populationj16 = True\n",
    "# Include mutation\n",
    "include_mutate_allj16 = True\n",
    "# Include recombination\n",
    "include_crossover_allj16 = False\n",
    "mutation_rate = 0.1\n",
    "recombination_rate = 0.0\n",
    "# Size of the sampled groups from which the best \n",
    "# is chosen as a parent for the next generation.\n",
    "tournament_size = 5\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",
    "def print_parametersj16():\n",
    "    print(f\"Lab: la Evolución finds the polynomial of minimal error\")\n",
    "    print(f\"Purpose: Use a Genetic Algorithm (MAX = selection of the fittest, mutation and recombination) to find the coefficients of a polynomial that best fits a set of points.\")\n",
    "    print(\"Hint to be tested: consider only numbers of the form -3.244025 with a sign that could be positive or negative, and a decimal point in the second place of the encoding chromosome.\")\n",
    "    print(f\"Date of Experiment  = {datetime.datetime.now()}\")\n",
    "    print(f\"number_of_generations = {number_of_generations}\")\n",
    "    print(f\"length_of_chromosomes = {length_of_chromosomes}\")\n",
    "    print(f\"alphabet =  {alphabet}\")\n",
    "    print(f\"Points = {list(zip(xArray, yArray))}\")\n",
    "    print(f\"population_size = {population_size}\")\n",
    "    print(f\"include_clone_populationj16 = {include_clone_populationj16}\")\n",
    "    print(f\"include_mutate_allj16 = {include_mutate_allj16}\")\n",
    "    print(f\"include_crossover_allj16 = {include_crossover_allj16}\")\n",
    "    if include_mutate_allj16:\n",
    "        print(f\"mutation_rate = {mutation_rate}\")\n",
    "    if include_crossover_allj16:\n",
    "        print(f\"recombination_rate = {recombination_rate}\")\n",
    "    if include_clone_populationj16:\n",
    "        print(f\"print_best_fitness = {print_best_fitness}\")\n",
    "\n",
    "def draw_points_and_polynomialj16(xNumpyArray, yNumpyArray):\n",
    "    \"\"\"Draws the original data points, finds and draws the \n",
    "    regression polynomial defined by the coefficients.\"\"\"\n",
    "    \n",
    "    # 2. Fit a 5th-degree (quintic) polynomial\n",
    "    # .fit() returns a Polynomial instance\n",
    "    p_fitted = Polynomial.fit(xNumpyArray, yNumpyArray, deg=5)\n",
    "\n",
    "    # 3. Predict values for visualization\n",
    "    x_new = np.linspace(-2,3, 100) # Generate 100 points between 0 and 6 for a smooth curve\n",
    "    y_new = p_fitted(x_new)\n",
    "    b_0, b_1, b_2, b_3, b_4, b5 = p_fitted.coef\n",
    "\n",
    "    # 4. Plot results\n",
    "    plt.scatter(xNumpyArray, yNumpyArray, label='Data Points')\n",
    "    plt.xlabel('x')\n",
    "    plt.ylabel('y')\n",
    "    plt.plot(x_new, y_new, label=f'Quintic Fit: y = {b_0:.2f} + {b_1:.2f}x + {b_2:.2f}x^2 + {b_3:.2f}x^3 + {b_4:.2f}x^4 + {b5:.2f}x^5', color='green')\n",
    "    plt.title(' Data Points and Quintic Fit by numpy.polynomial.Polynomial.fit()')\n",
    "    plt.legend()\n",
    "    plt.show()\n",
    "    return p_fitted.coef\n",
    "\n",
    "\n",
    "\n",
    "def create_populationj16(population_size, length_of_chromosomes, alphabet):\n",
    "    \"\"\"Creates a new population with random chromosomes.\"\"\"\n",
    "    # print(\"create_populationj16(population_size, target_sequence, alphabet)\")\n",
    "    population = []\n",
    "    for _ in range(population_size):\n",
    "        random_string1 = ''.join(random.choice(alphabet) for _ in range(length_of_chromosomes))\n",
    "        random_string2 = ''.join(random.choice(alphabet) for _ in range(length_of_chromosomes))\n",
    "        random_string3 = ''.join(random.choice(alphabet) for _ in range(length_of_chromosomes))\n",
    "        random_string4 = ''.join(random.choice(alphabet) for _ in range(length_of_chromosomes))\n",
    "        random_string5 = ''.join(random.choice(alphabet) for _ in range(length_of_chromosomes))\n",
    "        random_string6 = ''.join(random.choice(alphabet) for _ in range(length_of_chromosomes))\n",
    "        random_string = random_string1 + random_string2 + random_string3 + random_string4 + random_string5 + random_string6\n",
    "        population.append(random_string)\n",
    "    # print(\"initial population\")\n",
    "    # print(population)\n",
    "    return population\n",
    "\n",
    "# Decode a part of the chromosome into a coefficient of the polynomial.\n",
    "def decoderOldj16(s):\n",
    "    ''' The input is a number as string, outputs the number as a float. \n",
    "        We consider numbers of the form 93.24 with a sign that could be positive or negative,\n",
    "    '''\n",
    "    l = len(s) \n",
    "    # The first char encodes for the sign, \n",
    "    sign = 1\n",
    "    if  float(s[0]) % 2 == 1:\n",
    "        sign = -1\n",
    "    # The remaining chars encode for the number itself, \n",
    "    # without the decimal point nor sign.\n",
    "    sn = s[1:l]\n",
    "    # The point is inserted after the second char, so that we have numbers of the form 93.24\n",
    "    sn = sn[:2] + \".\" + sn[2:]\n",
    "    # Convert the string to a number\n",
    "    n = float(sn)\n",
    "    return sign * n\n",
    "\n",
    "# Decode a part of the chromosome into a coefficient of the polynomial.\n",
    "def decoderj16(s):\n",
    "    ''' The input is a number as string, outputs the number as a float. \n",
    "        We consider numbers of the form 93.24 with a sign that could be positive or negative,\n",
    "    '''\n",
    "    l = len(s) \n",
    "    # The first char encodes for the sign, \n",
    "    sign = 1\n",
    "    if  float(s[0]) % 2 == 1:\n",
    "        sign = -1\n",
    "    # The remaining chars encode for the number itself, \n",
    "    # without the decimal point nor sign.\n",
    "    sn = s[1:l]\n",
    "    # The point is inserted after the first char, so that we have numbers of the form -3.24\n",
    "    sn = sn[:1] + \".\" + sn[1:]\n",
    "    # Convert the string to a number\n",
    "    n = float(sn)\n",
    "    return sign * n\n",
    "\n",
    "\n",
    "def decodeFullCromosomej16(chromosome, length_of_chromosomes):\n",
    "    \"\"\"Decodes the full chromosome into the coefficients of the polynomial.\"\"\"\n",
    "    \"\"\"The chromosome is divided into 5 parts, \n",
    "        each one encoding for a coefficient of the polynomial.\"\"\"\n",
    "    chro0 = chromosome[0:length_of_chromosomes]\n",
    "    chro1 = chromosome[length_of_chromosomes:2*length_of_chromosomes]\n",
    "    chro2 = chromosome[2*length_of_chromosomes:3*length_of_chromosomes]\n",
    "    chro3 = chromosome[3*length_of_chromosomes:4*length_of_chromosomes]\n",
    "    chro4 = chromosome[4*length_of_chromosomes:5*length_of_chromosomes]\n",
    "    chro5 = chromosome[5*length_of_chromosomes:6*length_of_chromosomes]\n",
    "    a_0 = decoderj16(chro0)\n",
    "    a_1 = decoderj16(chro1)\n",
    "    a_2 = decoderj16(chro2)\n",
    "    a_3 = decoderj16(chro3)\n",
    "    a_4 = decoderj16(chro4)\n",
    "    a_5 = decoderj16(chro5)\n",
    "    # print(f\"Chromosome: {chromosome}\")\n",
    "    # print(f\"Coefficients: Intercept {a_0}, slope {a_1}, quadratic {a_2}, cubic {a_3}, quartic {a_4}, quintic {a_5}\")\n",
    "    # print()\n",
    "    return a_0, a_1, a_2, a_3, a_4, a_5\n",
    "\n",
    "\n",
    "\n",
    "def calculate_errorj16(chromosome, xArray, yArray, length_of_chromosomes):\n",
    "    \"\"\"Calculates the error of a chromosome.\n",
    "        A chromosome encodes for the coefficients of a polynomial of fith degree.\n",
    "        The error of a chromosome is the sum of \n",
    "        the vertical distances of the points to the polynomial it encodes.\n",
    "    \"\"\"\n",
    "    #  print(\"\\n calculate_errorj16(chromosome, xArray, yArray)\")\n",
    "    a_0, a_1, a_2, a_3, a_4, a_5 = decodeFullCromosomej16(chromosome, length_of_chromosomes)  \n",
    "    error = 0\n",
    "    for i in range(len(xArray)):\n",
    "        x = xArray[i]\n",
    "        y = yArray[i]\n",
    "        # Calculate the predicted y value based on the coefficients of the polynomial\n",
    "        predicted_y = a_0 + a_1 * x + a_2 * x**2 + a_3 * x**3 + a_4 * x**4 + a_5 * x**5\n",
    "        # Calculate the error as the quadratic difference \n",
    "        # between predicted and y value\n",
    "        # error += (predicted_y - y)**2\n",
    "        # Calculate the error as the distance between predicted and y value\n",
    "        error += abs(predicted_y - y)\n",
    "    return error\n",
    "\n",
    "def calculate_all_errorsj16(population, xArray, yArray, length_of_chromosomes):\n",
    "    # print(\"\\n*calculate_all_errorsj16(population, target_sequence)\")\n",
    "    \"\"\"Calculates the error of all chromosomes in the population.\"\"\"\n",
    "    errors = [calculate_errorj16(chromosome, xArray, yArray, length_of_chromosomes) for chromosome in population]\n",
    "    # print(\"errors: \", errors)\n",
    "    return errors\n",
    "\n",
    "def select_the_least_errorj16(population, xArray, yArray, length_of_chromosomes):\n",
    "    \"\"\"Selects the best chromosome with minimal error for reproduction.\"\"\"\n",
    "    errors = calculate_all_errorsj16(population, xArray, yArray, length_of_chromosomes)\n",
    "    smallest_error = min(errors)\n",
    "    best_chromosome_index = errors.index(smallest_error)\n",
    "    best_chromosome = population[best_chromosome_index]\n",
    "    # print(\"\\n*select_the_least_errorj16(population)\")\n",
    "    # print(\"smallest_error = \", smallest_error)\n",
    "    # print(\"The chro = \", best_chromosome )\n",
    "    return smallest_error, best_chromosome\n",
    "\n",
    "def clone_populationj16(best_chromosome, population_size):\n",
    "    \"\"\"Creates a new population by cloning the best chromosome.\"\"\"\n",
    "    return [best_chromosome] * population_size\n",
    "\n",
    "\n",
    "def mutatej16(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_allj16(population, mutation_rate, alphabet):\n",
    "    \"\"\"Mutates all chromosomes in the population.\"\"\"\n",
    "    mutated_population = []\n",
    "    for chromosome in population:\n",
    "        mutated_chromosome = mutatej16(chromosome, mutation_rate, alphabet)\n",
    "        mutated_population.append(mutated_chromosome)\n",
    "    return mutated_population\n",
    "\n",
    "def crossoverj16(parent1, parent2, length_of_chromosomes, recombination_rate):\n",
    "    \"\"\"Performs crossover between two parent chromosomes.\"\"\"\n",
    "    if random.random() < recombination_rate:\n",
    "        crossover_point = random.randint(0, length_of_chromosomes)\n",
    "        return parent1[:crossover_point] + parent2[crossover_point:]\n",
    "    else:\n",
    "        return parent1\n",
    "\n",
    "def crossover_allj16(population, length_of_chromosomes, 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 = crossoverj16(parent1, parent2, length_of_chromosomes, recombination_rate)\n",
    "        recombinant_population.append(child)\n",
    "    return recombinant_population\n",
    "\n",
    "\n",
    "\n",
    "def run_one_generationj16(population, xArray, yArray, mutation_rate, recombination_rate, alphabet, length_of_chromosomes):\n",
    "    \"\"\"Runs one generation of the genetic algorithm.\"\"\"\n",
    "    # Calculate fitness scores for the current population\n",
    "    smallest_error, best_chromosome  = select_the_least_errorj16(population, xArray, yArray, length_of_chromosomes)\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_populationj16:\n",
    "        new_population = clone_populationj16(best_chromosome, population_size)\n",
    "    if include_mutate_allj16:\n",
    "        new_population = mutate_allj16(new_population, mutation_rate, alphabet)\n",
    "    if include_crossover_allj16:\n",
    "        new_population = crossover_allj16(new_population, length_of_chromosomes, recombination_rate)\n",
    "    return smallest_error, best_chromosome, new_population\n",
    "\n",
    "\n",
    "\n",
    "def plot_functionj16(g_values, 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",
    "def plot_graphsj16(xArray, yArray, best_chromosome, length_of_chromosomes, generation, new_best_error):\n",
    "    # Plot the original data and the polynomial defined by the best chromosome.\n",
    "    a_0, a_1, a_2, a_3, a_4, a_5 = decodeFullCromosomej16(best_chromosome, length_of_chromosomes)  \n",
    "    x_new = np.linspace(-2,3, 100) # Generate 100 points between -2 and 3 for a smooth curve\n",
    "    predicted_y = a_0 + a_1 * x_new + a_2 * x_new**2 + a_3 * x_new**3 + a_4 * x_new**4 + a_5 * x_new**5\n",
    "    plt.scatter(xArray, yArray, label='Data Points')\n",
    "    plt.plot(x_new, predicted_y, label=f'Best Chromosome Fit: y = {a_0:.2f} + {a_1:.2f}x + {a_2:.2f}x^2 + {a_3:.2f}x^3 + {a_4:.2f}x^4 + {a_5:.2f}x^5', color='blue')\n",
    "    plt.xlabel('x')\n",
    "    plt.ylabel('y')\n",
    "    plt.title(f'Data Points and Best Chromosome Fit by Generation {generation}. Error = {new_best_error:.2f}')\n",
    "    plt.legend()\n",
    "    plt.grid(True)\n",
    "    plt.show()\n",
    "\n",
    "def taskj16( xArray, yArray, mutation_rate, recombination_rate, alphabet,  length_of_chromosomes):\n",
    "    population = create_populationj16(population_size, length_of_chromosomes, alphabet)\n",
    "    # print(population)\n",
    "    generation = 0\n",
    "    best_chromosome = ''\n",
    "    best_fitness = 0\n",
    "    start_time = time.time()\n",
    "    smallest_error_history = [] # List to store best fitness of each generation\n",
    "    old_best_error = float('inf') # Store the best error from the previous generation\n",
    "    new_best_error = float('inf') # Store the best error from the current generation\n",
    "    if print_best_fitness:\n",
    "        print(\"Generation, best_chromosome and best_fitness\")\n",
    "    while generation < number_of_generations:\n",
    "        generation += 1\n",
    "        smallest_error, best_chromosome, population = run_one_generationj16(population, xArray,yArray, mutation_rate, recombination_rate, alphabet, length_of_chromosomes)\n",
    "        if print_best_fitness:\n",
    "            print(f\" {generation}  {best_chromosome} {smallest_error}\")\n",
    "        smallest_error_history.append(smallest_error)\n",
    "        new_best_error = smallest_error\n",
    "        if new_best_error + 1 < old_best_error:\n",
    "            old_best_error = new_best_error\n",
    "            print(f\"Generation {generation}: Error decreased to {new_best_error}. Best chromosome: {best_chromosome}\")\n",
    "            plot_graphsj16(xArray, yArray, best_chromosome, length_of_chromosomes, generation, new_best_error)\n",
    "    # print(f\"\\nTarget sequence matched in generation {generation}\")\n",
    "    # print(f\"Final chromosome: {best_chromosome}\")\n",
    "    totalCost = population_size * generation\n",
    "    return  best_chromosome, totalCost, smallest_error_history\n",
    "\n",
    "def mainj16(xArray, yArray, mutation_rate, recombination_rate, alphabet, length_of_chromosomes):\n",
    "    print_parametersj16()\n",
    "\n",
    "    # Perform polynomial regression\n",
    "    # Fit a polynomial of degree 5 (polynomial regression)\n",
    "    p_fitted = Polynomial.fit(xArray, yArray, deg=5)\n",
    "    a_0, a_1, a_2, a_3, a_4, a5 = p_fitted.convert().coef\n",
    "    print(f\"Polynomial regression coefficients: Intercept {a_0}, slope {a_1}, quadratic {a_2}, cubic {a_3}, quartic {a_4}, quintic {a5}\")\n",
    "    # Create the regression graph\n",
    "    x_new = np.linspace(-2,3, 100) # Generate 100 points between -2 and 3 for a smooth curve\n",
    "    y_new = p_fitted(x_new)\n",
    "\n",
    "    # Run la Evolución to find the coefficients of the polynomial that best fits the data points.\n",
    "    print(\"Total cost = population size * number of generations\")\n",
    "    best_chromosome, totalCost, smallest_error_history = taskj16(xArray, yArray, mutation_rate, recombination_rate, alphabet, length_of_chromosomes)\n",
    "    final_error = smallest_error_history[-1]\n",
    "    print(f\" The best chromosome is {best_chromosome}\" )\n",
    "    coefficients = decodeFullCromosomej16(best_chromosome, length_of_chromosomes)\n",
    "    print(f\" Encoded coefficientes: {coefficients} \" )\n",
    "    print(f\" Total cost =  {totalCost} chromosomes\")\n",
    "    print(f\" Final error =  {final_error} \")\n",
    "\n",
    "    # Plot the fitness history    \n",
    "    g_values = list(range(1, len(smallest_error_history) + 1))\n",
    "    plot_functionj16(g_values, smallest_error_history, xlabel='Generation', ylabel='SmallestError', title='Smallest Error Over Generations')\n",
    "    # The best chromosome encodes for the coefficients of the polynomial that best fits the data points\"\n",
    "    b_0, b_1, b_2, b_3, b_4, b5 = decodeFullCromosomej16(best_chromosome, length_of_chromosomes)\n",
    "    print(f\"Decoded coefficients: Intercept {b_0}, slope {b_1}, quadratic {b_2}, cubic {b_3}, quartic {b_4}, quintic {b5}\")\n",
    "    # Calculate the predicted y value based on the coefficients of the polynomial\n",
    "    our_polynomial = b_0 + b_1 * np.array(xArray) + b_2 * np.array(xArray)**2 + b_3 * np.array(xArray)**3 + b_4 * np.array(xArray)**4 + b5 * np.array(xArray)**5\n",
    "    \n",
    "\n",
    "\n",
    "\n",
    "    # The best chromosome encodes for the coefficients of the polynomial that best fits the data points\"\n",
    "    b_0, b_1, b_2, b_3, b_4, b5 = decodeFullCromosomej16(best_chromosome, length_of_chromosomes)\n",
    "    print(f\"Encoded coefficients: Intercept {b_0}, slope {b_1}, quadratic {b_2}, cubic {b_3}, quartic {b_4}, quintic {b5}\")\n",
    "    # Calculate the predicted y value based on the coefficients of the polynomial\n",
    "    our_polynomial = b_0 + b_1 * np.array(x_new ) + b_2 * np.array(x_new )**2 + b_3 * np.array(x_new )**3 + b_4 * np.array(x_new )**4 + b5 * np.array(x_new )**5\n",
    "    \n",
    "\n",
    "    # Plot the original data, the regression polynomial, and our polynomial\n",
    "    plt.figure(figsize=(10, 6))\n",
    "    plt.scatter(xArray, yArray, label='Observed Data')\n",
    "    plt.plot(x_new, y_new, color='red', label=f'Polynomial Regression: y = {a_0:.2f} + {a_1:.2f}x + {a_2:.2f}x^2 + {a_3:.2f}x^3 + {a_4:.2f}x^4 + {a5:.2f}x^5')\n",
    "    plt.plot(x_new,        our_polynomial, color='green', label=f'Our polynomial: y = {b_0:.2f} + {b_1:.2f}x + {b_2:.2f}x^2 + {b_3:.2f}x^3 + {b_4:.2f}x^4 + {b5:.2f}x^5')\n",
    "    plt.xlabel('Independent variable (x)')\n",
    "    plt.ylabel('Dependent variable (y)')\n",
    "    plt.title(f'Linear Regression and la Evolución minimize the error of the line with respect to the data points. Generation: {number_of_generations}. Error of our polynomial: {final_error:.2f}')\n",
    "    plt.legend()\n",
    "    plt.grid(True)\n",
    "    plt.show()\n",
    "\n",
    "    end_time = time.time()\n",
    "    # Calculate the duration of the run in seconds\n",
    "    elapsed_time = end_time - start_time\n",
    "    elapsed_time = timedelta(seconds=elapsed_time)\n",
    "    print(f\"Elapsed time: {elapsed_time}\")\n",
    "    #return best_chromosome, totalCost, best_fitness_history\n",
    "\n",
    "# Call the main function with the defined parameters\n",
    "mainj16(xArray, yArray, mutation_rate, recombination_rate, alphabet, length_of_chromosomes)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "7977bcd1",
   "metadata": {},
   "source": [
    "*Nuestras observaciones.* \n",
    "\n",
    "Cuando el d-hint está ausente:\n",
    "\n",
    "1.  La silueta correcta puede no aparecer en el tiempo establecido, 200 generaciones.\n",
    "2. El error disminuye, pero en la clase de formas insatisfactorias.\n",
    "\n",
    "Observamos en ambos procesos que la perfección es muy diferente de las buenas aproximaciones y que no se encuentra. \n"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "46ec8215",
   "metadata": {},
   "source": [
    "\n",
    "# SOLO POR DIVERSIÓN: EL ANCESTRO COMÚN DE UN GATO Y UN PERRO\n",
    "\n",
    "Hace mucho tiempo hicimos un ejercicio divertido para considerar la Evolución del perro en un gato y determinar el antepasado común. Observamos que el antepasado común tiene subcadenas que parecen aleatorias. Tenemos aquí una ocasión para dar otra vuelta a este problema. La idea es imitar al gato y al perro con polinomios y estudiar la Evolución de uno en el otro. Un antepasado común está en algún lugar en medio del camino evolutivo. \n",
    "\n",
    "**Ejercicio.** Seleccione uno de nuestros programas anteriores para estudiar la Evolución de una solución de un problema simple a uno más complejo. Concretamente: Da un conjunto de seis puntos en el plano.  La población inicial no es un conjunto de cromosomas sintetizados al azar, sino que cada uno de ellos codifica los coeficientes del polinomio de segundo grado que se ajusta a un subconjunto de tres puntos. Este polinomio debe evolucionarse a una solución de un conjunto de cuatro, cinco o seis puntos. Reporte sus observaciones.\n",
    ">\n",
    "> *Respuesta.* Todo lo que necesitamos es codificar en los cromosomas iniciales el polinomio de regresión que corresponde a un subconjunto de tres puntos. Esta solución inicial debe evolucionarse en un polinomio que se ajuste al conjunto completo de seis puntos. Reutilizamos el programa que crea una población inicial de cromosomas perfectos, es decir, que codifica el polinomio de regresión generado por el conjunto inicial de seis puntos.  El código sigue:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "8aa3df3b",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "c912d2f8",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Lab: Evolution finds the polynomial of minimal error\n",
      "Purpose: Use a Genetic Algorithm (MAX or selection of the fittest, mutation, recombination) to find the coefficients of a polynomial that best fits a set of points.\n",
      "Date of Experiment  = 2026-05-05 07:29:00.888708\n",
      "number_of_generations = 100000\n",
      "length_of_chromosomes = 9\n",
      "alphabet =  0123456789\n",
      "Points = [(np.int64(-2), np.int64(5)), (np.int64(-1), np.int64(1)), (np.int64(0), np.int64(4)), (np.int64(1), np.int64(0)), (np.int64(2), np.int64(6)), (np.int64(3), np.int64(3))]\n",
      "population_size = 200\n",
      "include_clone_populationj17 = True\n",
      "include_mutate_allj17 = True\n",
      "include_crossover_allj17 = True\n",
      "mutation_rate = 0.1\n",
      "recombination_rate = 0.1\n",
      "print_best_fitness = False\n",
      "Total cost = population size * number of generations\n",
      "Polynomial.fit.convert().coef: Intercept 4.000000000000001, slope 0.24999999999999964, quadratic 0.3750000000000003, cubic 0.0, quartic 0.0, quintic 0.0\n",
      "x points: [-2.         -1.94949495 -1.8989899  -1.84848485 -1.7979798  -1.74747475\n",
      " -1.6969697  -1.64646465 -1.5959596  -1.54545455 -1.49494949 -1.44444444\n",
      " -1.39393939 -1.34343434 -1.29292929 -1.24242424 -1.19191919 -1.14141414\n",
      " -1.09090909 -1.04040404 -0.98989899 -0.93939394 -0.88888889 -0.83838384\n",
      " -0.78787879 -0.73737374 -0.68686869 -0.63636364 -0.58585859 -0.53535354\n",
      " -0.48484848 -0.43434343 -0.38383838 -0.33333333 -0.28282828 -0.23232323\n",
      " -0.18181818 -0.13131313 -0.08080808 -0.03030303  0.02020202  0.07070707\n",
      "  0.12121212  0.17171717  0.22222222  0.27272727  0.32323232  0.37373737\n",
      "  0.42424242  0.47474747  0.52525253  0.57575758  0.62626263  0.67676768\n",
      "  0.72727273  0.77777778  0.82828283  0.87878788  0.92929293  0.97979798\n",
      "  1.03030303  1.08080808  1.13131313  1.18181818  1.23232323  1.28282828\n",
      "  1.33333333  1.38383838  1.43434343  1.48484848  1.53535354  1.58585859\n",
      "  1.63636364  1.68686869  1.73737374  1.78787879  1.83838384  1.88888889\n",
      "  1.93939394  1.98989899  2.04040404  2.09090909  2.14141414  2.19191919\n",
      "  2.24242424  2.29292929  2.34343434  2.39393939  2.44444444  2.49494949\n",
      "  2.54545455  2.5959596   2.64646465  2.6969697   2.74747475  2.7979798\n",
      "  2.84848485  2.8989899   2.94949495  3.        ]\n",
      "Fitted polynomial values: [5.         4.93782522 4.87756351 4.81921488 4.76277931 4.70825681\n",
      " 4.65564738 4.60495103 4.55616774 4.50929752 4.46434037 4.4212963\n",
      " 4.38016529 4.34094735 4.30364249 4.26825069 4.23477196 4.20320631\n",
      " 4.17355372 4.1458142  4.11998776 4.09607438 4.07407407 4.05398684\n",
      " 4.03581267 4.01955158 4.00520355 3.9927686  3.98224671 3.97363789\n",
      " 3.96694215 3.96215947 3.95928987 3.95833333 3.95928987 3.96215947\n",
      " 3.96694215 3.97363789 3.98224671 3.9927686  4.00520355 4.01955158\n",
      " 4.03581267 4.05398684 4.07407407 4.09607438 4.11998776 4.1458142\n",
      " 4.17355372 4.20320631 4.23477196 4.26825069 4.30364249 4.34094735\n",
      " 4.38016529 4.4212963  4.46434037 4.50929752 4.55616774 4.60495103\n",
      " 4.65564738 4.70825681 4.76277931 4.81921488 4.87756351 4.93782522\n",
      " 5.         5.06408785 5.13008877 5.19800275 5.26782981 5.33956994\n",
      " 5.41322314 5.48878941 5.56626875 5.64566116 5.72696664 5.81018519\n",
      " 5.8953168  5.98236149 6.07131925 6.16219008 6.25497398 6.34967095\n",
      " 6.44628099 6.5448041  6.64524028 6.74758953 6.85185185 6.95802724\n",
      " 7.0661157  7.17611723 7.28803183 7.4018595  7.51760024 7.63525406\n",
      " 7.75482094 7.87630089 7.99969391 8.125     ]\n",
      "Original Points = [(np.int64(-2), np.int64(5)), (np.int64(0), np.int64(4)), (np.int64(2), np.int64(6))] \n",
      "Interpolated fitted polynomial points: [(np.float64(-2.0), np.float64(5.000000000000003)), (np.float64(-1.9494949494949494), np.float64(4.937825221916134)), (np.float64(-1.898989898989899), np.float64(4.877563513927153)), (np.float64(-1.8484848484848484), np.float64(4.81921487603306)), (np.float64(-1.797979797979798), np.float64(4.762779308233856)), (np.float64(-1.7474747474747474), np.float64(4.70825681052954)), (np.float64(-1.696969696969697), np.float64(4.655647382920113)), (np.float64(-1.6464646464646464), np.float64(4.6049510254055726)), (np.float64(-1.595959595959596), np.float64(4.556167737985922)), (np.float64(-1.5454545454545454), np.float64(4.509297520661159)), (np.float64(-1.4949494949494948), np.float64(4.464340373431284)), (np.float64(-1.4444444444444444), np.float64(4.4212962962962985)), (np.float64(-1.393939393939394), np.float64(4.3801652892562)), (np.float64(-1.3434343434343434), np.float64(4.34094735231099)), (np.float64(-1.2929292929292928), np.float64(4.303642485460669)), (np.float64(-1.2424242424242424), np.float64(4.268250688705236)), (np.float64(-1.191919191919192), np.float64(4.234771962044691)), (np.float64(-1.1414141414141414), np.float64(4.203206305479035)), (np.float64(-1.0909090909090908), np.float64(4.173553719008266)), (np.float64(-1.0404040404040404), np.float64(4.145814202632386)), (np.float64(-0.9898989898989898), np.float64(4.119987756351394)), (np.float64(-0.9393939393939394), np.float64(4.096074380165291)), (np.float64(-0.8888888888888888), np.float64(4.074074074074075)), (np.float64(-0.8383838383838385), np.float64(4.053986838077749)), (np.float64(-0.7878787878787878), np.float64(4.03581267217631)), (np.float64(-0.7373737373737375), np.float64(4.01955157636976)), (np.float64(-0.6868686868686869), np.float64(4.005203550658098)), (np.float64(-0.6363636363636365), np.float64(3.9927685950413236)), (np.float64(-0.5858585858585859), np.float64(3.982246709519438)), (np.float64(-0.5353535353535355), np.float64(3.9736378940924406)), (np.float64(-0.48484848484848486), np.float64(3.9669421487603316)), (np.float64(-0.4343434343434345), np.float64(3.962159473523111)), (np.float64(-0.38383838383838387), np.float64(3.9592898683807785)), (np.float64(-0.33333333333333326), np.float64(3.9583333333333344)), (np.float64(-0.2828282828282829), np.float64(3.9592898683807785)), (np.float64(-0.23232323232323226), np.float64(3.9621594735231107)), (np.float64(-0.18181818181818188), np.float64(3.9669421487603316)), (np.float64(-0.13131313131313127), np.float64(3.9736378940924406)), (np.float64(-0.08080808080808088), np.float64(3.982246709519438)), (np.float64(-0.030303030303030276), np.float64(3.992768595041323)), (np.float64(0.020202020202020332), np.float64(4.005203550658097)), (np.float64(0.0707070707070705), np.float64(4.019551576369759)), (np.float64(0.1212121212121211), np.float64(4.035812672176309)), (np.float64(0.1717171717171717), np.float64(4.053986838077748)), (np.float64(0.22222222222222232), np.float64(4.074074074074075)), (np.float64(0.2727272727272725), np.float64(4.09607438016529)), (np.float64(0.3232323232323231), np.float64(4.119987756351393)), (np.float64(0.3737373737373737), np.float64(4.145814202632385)), (np.float64(0.4242424242424243), np.float64(4.173553719008265)), (np.float64(0.4747474747474749), np.float64(4.203206305479034)), (np.float64(0.5252525252525251), np.float64(4.2347719620446895)), (np.float64(0.5757575757575757), np.float64(4.268250688705235)), (np.float64(0.6262626262626263), np.float64(4.303642485460668)), (np.float64(0.6767676767676769), np.float64(4.340947352310989)), (np.float64(0.7272727272727271), np.float64(4.380165289256199)), (np.float64(0.7777777777777777), np.float64(4.421296296296297)), (np.float64(0.8282828282828283), np.float64(4.464340373431283)), (np.float64(0.8787878787878789), np.float64(4.509297520661158)), (np.float64(0.9292929292929291), np.float64(4.556167737985921)), (np.float64(0.9797979797979797), np.float64(4.604951025405572)), (np.float64(1.0303030303030303), np.float64(4.655647382920111)), (np.float64(1.0808080808080809), np.float64(4.708256810529539)), (np.float64(1.131313131313131), np.float64(4.7627793082338545)), (np.float64(1.1818181818181817), np.float64(4.819214876033058)), (np.float64(1.2323232323232323), np.float64(4.877563513927151)), (np.float64(1.2828282828282829), np.float64(4.937825221916132)), (np.float64(1.3333333333333335), np.float64(5.000000000000001)), (np.float64(1.3838383838383836), np.float64(5.064087848178758)), (np.float64(1.4343434343434343), np.float64(5.1300887664524035)), (np.float64(1.4848484848484849), np.float64(5.198002754820937)), (np.float64(1.5353535353535355), np.float64(5.26782981328436)), (np.float64(1.5858585858585856), np.float64(5.33956994184267)), (np.float64(1.6363636363636362), np.float64(5.413223140495869)), (np.float64(1.6868686868686869), np.float64(5.488789409243956)), (np.float64(1.7373737373737375), np.float64(5.566268748086931)), (np.float64(1.7878787878787876), np.float64(5.645661157024794)), (np.float64(1.8383838383838382), np.float64(5.726966636057546)), (np.float64(1.8888888888888888), np.float64(5.810185185185186)), (np.float64(1.9393939393939394), np.float64(5.895316804407715)), (np.float64(1.9898989898989896), np.float64(5.982361493725131)), (np.float64(2.0404040404040407), np.float64(6.071319253137437)), (np.float64(2.090909090909091), np.float64(6.16219008264463)), (np.float64(2.141414141414141), np.float64(6.25497398224671)), (np.float64(2.191919191919192), np.float64(6.349670951943681)), (np.float64(2.242424242424242), np.float64(6.446280991735538)), (np.float64(2.2929292929292933), np.float64(6.544804101622286)), (np.float64(2.3434343434343434), np.float64(6.64524028160392)), (np.float64(2.3939393939393936), np.float64(6.7475895316804415)), (np.float64(2.4444444444444446), np.float64(6.851851851851854)), (np.float64(2.494949494949495), np.float64(6.958027242118153)), (np.float64(2.545454545454545), np.float64(7.066115702479339)), (np.float64(2.595959595959596), np.float64(7.176117232935416)), (np.float64(2.646464646464646), np.float64(7.2880318334863805)), (np.float64(2.6969696969696972), np.float64(7.401859504132234)), (np.float64(2.7474747474747474), np.float64(7.517600244872973)), (np.float64(2.7979797979797976), np.float64(7.635254055708602)), (np.float64(2.8484848484848486), np.float64(7.7548209366391205)), (np.float64(2.898989898989899), np.float64(7.8763008876645255)), (np.float64(2.94949494949495), np.float64(7.9996939087848205)), (np.float64(3.0), np.float64(8.125000000000004))] \n"
     ]
    },
    {
     "data": {
      "image/png": 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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 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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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 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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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 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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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 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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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 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      " The final best chromosome is 679999998077888253679999999370169699099999238370399927\n",
      " Encoded coefficients: Intercept 0.9999998, slope 0.7888253, quadratic 0.9999998999999999, cubic -0.0169699, quartic 0.009999238, quintic -0.0399927\n",
      " Total cost =  20000000 chromosomes\n",
      " Final error =  6.700023981999999 \n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Polynomial regression coefficients: Intercept 3.9999999999999973, slope -2.98333333333332, quadratic -4.79166666666666, cubic 3.04166666666666, quartic 1.2916666666666654, quintic -0.5583333333333326\n",
      "Encoded coefficients: Intercept 0.9999998, slope 0.7888253, quadratic 0.9999998999999999, cubic -0.0169699, quartic 0.009999238, quintic -0.0399927\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": [
      "Elapsed time: 0:20:33.763124\n"
     ]
    }
   ],
   "source": [
    "# Program PolynomialDogIntoCatla Evolución.py\n",
    "# The la Evoluciónary Theory claims that \n",
    "# the dog and the cat have a common ancestor, \n",
    "# which was neither a dog nor a cat.\n",
    "# We mimic here these mammals as polynomials,\n",
    "# and give a glance into the la Evolución of one into the other. \n",
    "# We would like to say something about the supposed common ancestor. \n",
    "# The dog is represented by a polynomial of second degree,\n",
    "# and the cat is represented by a polynomial of fifth degree.\n",
    "#\n",
    "# We study la Evoluciónary regression.\n",
    "# A set of six points is given.\n",
    "# A subset of three points is chosen, and \n",
    "# math regression is invoked to produce \n",
    "# the second degree polynomial that fits that subset.\n",
    "# The coefficients of this polynomial are represented by a chromosome, \n",
    "# which is a string of digits.\n",
    "# This perfect solution is next cloned to fill the initial population.\n",
    "# The population is then evolved into a solution of the problem of \n",
    "# finding the fifth degree polynomial \n",
    "# that best fits the whole set of six points.\n",
    "# The decoding function must divide the chromosome into parts, \n",
    "# and decode each one apart as one coefficient.\n",
    "# The error of a chromosome is the sum of the vertical distances \n",
    "# of the points to the polynomial it encodes.\n",
    "# The Genetic algorithm must minimize the error, \n",
    "# (which is equivalent to maximizing the fitness).\n",
    "# We use MAX (selection of the best and cloning),  mutation and recombination.\n",
    "# Developed with the assistance of the AI of Visual Studio Code.\n",
    "# An old version of a GA developed with the help of Gemini was reused and updated.\n",
    "\n",
    "from datetime import datetime, timedelta\n",
    "import time\n",
    "import random\n",
    "import numpy as np\n",
    "# Documentation: https://numpy.org/devdocs/reference/routines.polynomials.html\n",
    "from numpy.polynomial import Polynomial\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",
    "#Task to be done\n",
    "number_of_generations = 100000\n",
    "\n",
    "# Initial data points that define the initial polynomial of second degree, which is the  dog.\n",
    "xArrayInitial = np.array([-2, 0,  2])\n",
    "yArrayInitial = np.array([ 5, 4,  6])\n",
    "# Final data points that define the target polynomial of fifth degree, which is the  cat.\n",
    "xArray = np.array([-2, -1, 0, 1, 2, 3])\n",
    "yArray = np.array([5,   1, 4, 0, 6, 3])\n",
    "\n",
    "alphabet = '0123456789'\n",
    "length_of_chromosomes = 9\n",
    "population_size = 200\n",
    "# Include cloning of the fittest\n",
    "include_clone_populationj17 = True\n",
    "# Include mutation\n",
    "include_mutate_allj17 = True\n",
    "# Include recombination\n",
    "include_crossover_allj17 = True\n",
    "mutation_rate = 0.1\n",
    "recombination_rate = 0.1\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",
    "def print_parametersj17():\n",
    "    print(f\"Lab: la Evolución finds the polynomial of minimal error\")\n",
    "    print(f\"Purpose: Use a Genetic Algorithm (MAX or selection of the fittest, mutation, recombination) to find the coefficients of a polynomial that best fits a set of points.\")\n",
    "    print(f\"Date of Experiment  = {datetime.datetime.now()}\")\n",
    "    print(f\"number_of_generations = {number_of_generations}\")\n",
    "    print(f\"length_of_chromosomes = {length_of_chromosomes}\")\n",
    "    print(f\"alphabet =  {alphabet}\")\n",
    "    print(f\"Points = {list(zip(xArray, yArray))}\")\n",
    "    print(f\"population_size = {population_size}\")\n",
    "    print(f\"include_clone_populationj17 = {include_clone_populationj17}\")\n",
    "    print(f\"include_mutate_allj17 = {include_mutate_allj17}\")\n",
    "    print(f\"include_crossover_allj17 = {include_crossover_allj17}\")\n",
    "    if include_mutate_allj17:\n",
    "        print(f\"mutation_rate = {mutation_rate}\")\n",
    "    if include_crossover_allj17:\n",
    "        print(f\"recombination_rate = {recombination_rate}\")\n",
    "    if include_clone_populationj17:\n",
    "        print(f\"print_best_fitness = {print_best_fitness}\")\n",
    "\n",
    "def draw_initial_points_and_polynomialj17(xNumpyArray, yNumpyArray):\n",
    "    \"\"\"Draws the initial data points, finds and draws the \n",
    "    regression polynomial defined by the coefficients.\"\"\"\n",
    "    \n",
    "    # 2. Fit a 5th-degree (quintic) polynomial\n",
    "    # .fit() returns a Polynomial instance\n",
    "    degree = len(xArrayInitial) - 1 # Degree of the polynomial is one less than the number of points\n",
    "    p_fitted = Polynomial.fit(xNumpyArray, yNumpyArray, deg=degree)\n",
    "    coefficients = p_fitted. convert().coef\n",
    "    coefficients = np.append(coefficients, [0.0] * (6 - len(coefficients))) # Pad with zeros to have 6 coefficients for the quintic polynomial\n",
    "    b_0, b_1, b_2, b_3, b_4, b_5 = coefficients\n",
    "    print(f\"Polynomial.fit.convert().coef: Intercept {b_0}, slope {b_1}, quadratic {b_2}, cubic {b_3}, quartic {b_4}, quintic {b_5}\")\n",
    "\n",
    "    # 3. Predict values for visualization\n",
    "    x_new = np.linspace(-2,3, 100) # Generate 100 points between -2 and 3for a smooth curve\n",
    "    y_new = p_fitted(x_new)\n",
    "    print(f\"x points: {x_new}\")\n",
    "    print(f\"Fitted polynomial values: {y_new}\")\n",
    "    print(f\"Original Points = {list(zip(xNumpyArray, yNumpyArray))} \")\n",
    "    print(f\"Interpolated fitted polynomial points: {list(zip(x_new, y_new))} \")\n",
    "\n",
    "\n",
    "    # 4. Plot results\n",
    "    plt.scatter(xNumpyArray, yNumpyArray, label='Data Points')\n",
    "    plt.xlabel('x')\n",
    "    plt.ylabel('y')\n",
    "    plt.plot(x_new, y_new, label=f'Parabolic Fit: y = {b_0:.2f} + {b_1:.2f}x + {b_2:.2f}x^2 + {b_3:.2f}x^3 + {b_4:.2f}x^4 + {b_5:.2f}x^5', color='green')\n",
    "    plt.title(' Data Points and parabolic Fit by numpy.polynomial.Polynomial.fit()')\n",
    "    plt.legend()\n",
    "    plt.show()\n",
    "    return  coefficients\n",
    "\n",
    "\n",
    "\n",
    "def plot_functionj17(g_values, 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 draw_polynomial_from_coefficientsj17(coefficients, xArray, yArray, generation, error):\n",
    "    \"\"\"Draws the original data points and the \n",
    "    polynomial defined by the coefficients.\n",
    "    By the AI of Visual Studio Code, based on the draw_points_and_polynomialj5 function.\"\"\"\n",
    "    \n",
    "    a_0, a_1, a_2, a_3, a_4, a5 = coefficients\n",
    "    x_new = np.linspace(-2,3, 100) # Generate 100 points between -2 and 3for a smooth curve\n",
    "    # Plot polynomial defined by the coefficients\n",
    "    plt.scatter(xArray, yArray, label='Data Points')\n",
    "    plt.xlabel('x')\n",
    "    plt.ylabel('y')\n",
    "    plt.plot(x_new, a_0 + a_1 * np.array(x_new) + a_2 * np.array(x_new)**2 + a_3 * np.array(x_new)**3 + a_4 * np.array(x_new)**4 + a5 * np.array(x_new)**5, label=f'Perfect polynomial: y = {a_0:.2f} + {a_1:.2f}x + {a_2:.2f}x^2 + {a_3:.2f}x^3 + {a_4:.2f}x^4 + {a5:.2f}x^5', color='red')\n",
    "    plt.title(f'Data points and best polynomial by generation {generation}. Error = {error:.2f}')\n",
    "    plt.legend()\n",
    "    plt.show()\n",
    "\n",
    "\n",
    "def draw_polynomialsj17( xArray, yArray, generation):\n",
    "    # Perform polynomial least squares regression\n",
    "    # Fit a polynomial of degree 5 (numpy polynomial regression)\n",
    "    # Arrays to np.arrays\n",
    "    # xNumpyArray = np.array(xArray)\n",
    "    # yNumpyArray = np.array(yArray)\n",
    "    print(f\"Points that must be regressed: {list(zip(xArray, yArray))}\")\n",
    "    #print type of xNumpyArray and yNumpyArray\n",
    "    print(f\"type of xNumpyArray: {type(xArray)}, type of yNumpyArray: {type(yArray)}\")\n",
    "    coefficients = draw_initial_points_and_polynomialj17(xArray, yArray)\n",
    "    print(f\"Numpy fitted polynomial coefficients: {coefficients[0]}, {coefficients[1]}, {coefficients[2]}, {coefficients[3]}, {coefficients[4]}, {coefficients[5]}\")\n",
    "    perfect_chromosome = encodeFullCromosomej17(coefficients[0], coefficients[1], coefficients[2], coefficients[3], coefficients[4], coefficients[5], length_of_chromosomes)\n",
    "    print(f\"Perfect chromosome: {perfect_chromosome}\")\n",
    "    print(f\"Decoded perfect chromosome: {decodeFullCromosomej17(perfect_chromosome, length_of_chromosomes)}\")\n",
    "    print(f\"Error of perfect chromosome: {calculate_errorj17(perfect_chromosome, xArray, yArray)}\")\n",
    "    draw_polynomial_from_coefficientsj17(coefficients, xArray, yArray, generation)\n",
    "    print\n",
    "    return coefficients\n",
    "\n",
    "\n",
    "def create_random_populationj17(population_size, length_of_chromosomes, alphabet):\n",
    "    \"\"\"Creates a new population with random chromosomes.\"\"\"\n",
    "    # print(\"create_populationj17(population_size, target_sequence, alphabet)\")\n",
    "    population = []\n",
    "    for _ in range(population_size):\n",
    "        random_string1 = ''.join(random.choice(alphabet) for _ in range(length_of_chromosomes))\n",
    "        random_string2 = ''.join(random.choice(alphabet) for _ in range(length_of_chromosomes))\n",
    "        random_string3 = ''.join(random.choice(alphabet) for _ in range(length_of_chromosomes))\n",
    "        random_string4 = ''.join(random.choice(alphabet) for _ in range(length_of_chromosomes))\n",
    "        random_string5 = ''.join(random.choice(alphabet) for _ in range(length_of_chromosomes))\n",
    "        random_string6 = ''.join(random.choice(alphabet) for _ in range(length_of_chromosomes))\n",
    "        random_string = random_string1 + random_string2 + random_string3 + random_string4 + random_string5 + random_string6\n",
    "        population.append(random_string)\n",
    "    # print(\"initial population\")\n",
    "    # print(population)\n",
    "    return population\n",
    "\n",
    "# Decode a part of the chromosome into a coefficient of the polynomial.\n",
    "def decoderj17(s):\n",
    "    ''' The input is a number as string, outputs the number as a float. '''\n",
    "    \n",
    "    l = len(s)\n",
    "    # The first char encodes for the sign, \n",
    "    sign = 1\n",
    "    if  float(s[0]) % 2 == 1:\n",
    "        sign = -1\n",
    "    # The second char encodes for the position of the decimal point,\n",
    "    d = float(s[1])\n",
    "    # The remaining chars encode for the number itself, \n",
    "    # without the decimal point nor sign.\n",
    "    n = float(s[2:l])\n",
    "    return sign * (n * (10**-d))\n",
    "\n",
    "def decodeFullCromosomej17(chromosome, length_of_chromosomes):\n",
    "    \"\"\"Decodes the full chromosome into the coefficients of the polynomial.\"\"\"\n",
    "    \"\"\"The chromosome is divided into 5 parts, \n",
    "        each one encoding for a coefficient of the polynomial.\"\"\"\n",
    "    chro0 = chromosome[0:length_of_chromosomes]\n",
    "    chro1 = chromosome[length_of_chromosomes:2*length_of_chromosomes]\n",
    "    chro2 = chromosome[2*length_of_chromosomes:3*length_of_chromosomes]\n",
    "    chro3 = chromosome[3*length_of_chromosomes:4*length_of_chromosomes]\n",
    "    chro4 = chromosome[4*length_of_chromosomes:5*length_of_chromosomes]\n",
    "    chro5 = chromosome[5*length_of_chromosomes:6*length_of_chromosomes]\n",
    "    a_0 = decoderj17(chro0)\n",
    "    a_1 = decoderj17(chro1)\n",
    "    a_2 = decoderj17(chro2)\n",
    "    a_3 = decoderj17(chro3)\n",
    "    a_4 = decoderj17(chro4)\n",
    "    a_5 = decoderj17(chro5)\n",
    "    return a_0, a_1, a_2, a_3, a_4, a_5\n",
    "\n",
    "def encodeFullCromosomej17(a_0, a_1, a_2, a_3, a_4, a_5, length_of_chromosomes):\n",
    "    \"\"\"Encodes the coefficients of the polynomial into a chromosome.\n",
    "        The chromosome is divided into 5 parts,\n",
    "        each one encoding for a coefficient of the polynomial.\n",
    "        The encoding of a coefficient is as follows:\n",
    "        The first char encodes for the sign,\n",
    "        The second char encodes for the position of the decimal point,\n",
    "        The remaining chars encode for the number itself,\n",
    "        without the decimal point nor sign.\n",
    "        Developed by the AI of Visual Studio Code, based on the decoder function.\"\"\"\n",
    "    def encoderj17(coefficient, length_of_chromosomes):\n",
    "        if coefficient == 0:\n",
    "            return \"000000000\" # 9 chars for the coefficient part of the chromosome\n",
    "        ''' The input is a coefficient as a float, outputs a string of digits. '''\n",
    "        # Determine the sign\n",
    "        sign = 0 if coefficient >= 0 else 1\n",
    "        # Determine the position of the decimal point\n",
    "        if coefficient == 0:\n",
    "            d = 0\n",
    "        else:\n",
    "            d = int(np.floor(np.log10(abs(coefficient)))) +1\n",
    "        d = length_of_chromosomes - d - 2 # -2 for the sign and decimal point chars\n",
    "        #print(f\"Coefficient: {coefficient}, sign: {sign}, decimal point position: {d}\")\n",
    "        # Determine the number itself without the decimal point and sign\n",
    "        n = int(abs(coefficient) * (10**d))\n",
    "        # Create the string representation of the coefficient, \n",
    "        # first the sign, then the position of the decimal point, then the number itself\n",
    "        # The string is trimmed to fit the length of the chromosome part.\n",
    "        n_str = str(n)\n",
    "        if len(n_str) > length_of_chromosomes - 2:\n",
    "            n_str = str(n)[:length_of_chromosomes - 2]\n",
    "        return str(sign) + str(d) + n_str\n",
    "    \n",
    "    #coef = -123.456789123456789\n",
    "    #print(f\"Encoding coefficient: {coef}, encoded as: {encoder(coef, length_of_chromosomes)}, decoded as: {decoder(encoder(coef, length_of_chromosomes))}\")\n",
    "\n",
    "    chro0 = encoderj17(a_0, length_of_chromosomes)\n",
    "    chro1 = encoderj17(a_1, length_of_chromosomes)\n",
    "    chro2 = encoderj17(a_2, length_of_chromosomes)\n",
    "    chro3 = encoderj17(a_3, length_of_chromosomes)\n",
    "    chro4 = encoderj17(a_4, length_of_chromosomes)\n",
    "    chro5 = encoderj17(a_5, length_of_chromosomes)\n",
    "    return chro0 + chro1 + chro2 + chro3 + chro4 + chro5\n",
    "\n",
    "def createPopulationFromCoefficientsj17(a_0, a_1, a_2, a_3, a_4, a_5, length_of_chromosomes, population_size):\n",
    "    \"\"\"Creates a new population with the perfect chromosome.\n",
    "    By the AI of Visual Studio Code, based on the encodeFullCromosome function.\"\"\"\n",
    "    perfect_chromosome = encodeFullCromosomej17(a_0, a_1, a_2, a_3, a_4, a_5, length_of_chromosomes)\n",
    "    return [perfect_chromosome] * population_size\n",
    "\n",
    "def calculate_error_from_coefficients(coefficients, xArray, yArray):\n",
    "    a_0, a_1, a_2, a_3, a_4, a_5 = coefficients\n",
    "    error = 0\n",
    "    for i in range(len(xArray)):\n",
    "        x = xArray[i]\n",
    "        y = yArray[i]\n",
    "        # Calculate the predicted y value based on the coefficients of the polynomial\n",
    "        predicted_y = a_0 + a_1 * x + a_2 * x**2 + a_3 * x**3 + a_4 * x**4 + a_5 * x**5\n",
    "        # Calculate the error as the distance\n",
    "        # between predicted and y value\n",
    "        error += abs(predicted_y - y)\n",
    "    return error\n",
    "\n",
    "def calculate_errorjOld17(chromosome, xArray, yArray):\n",
    "    \"\"\"Calculates the error of a chromosome.\n",
    "        A chromosome encodes for the coefficients of a polynomial of fith degree.\n",
    "        The error of a chromosome is the sum of \n",
    "        the vertical distances of the points to the polynomial it encodes.\n",
    "    \"\"\"\n",
    "    #  print(\"\\n calculate_errorj17(chromosome, xArray, yArray)\")\n",
    "    a_0, a_1, a_2, a_3, a_4, a_5 = decodeFullCromosomej17(chromosome, length_of_chromosomes) \n",
    "    error = 0\n",
    "    for i in range(len(xArray)):\n",
    "        x = xArray[i]\n",
    "        y = yArray[i]\n",
    "        # Calculate the predicted y value based on the coefficients of the polynomial\n",
    "        predicted_y = a_0 + a_1 * x + a_2 * x**2 + a_3 * x**3 + a_4 * x**4 + a_5 * x**5\n",
    "        # Calculate the error as the distance\n",
    "        # between predicted and y value\n",
    "        error += abs(predicted_y - y)\n",
    "    return error\n",
    "\n",
    "def calculate_errorj17(chromosome, xArray, yArray):\n",
    "    \"\"\"Calculates the error of a chromosome.\n",
    "        A chromosome encodes for the coefficients of a polynomial of fith degree.\n",
    "        The error of a chromosome is the sum of \n",
    "        the vertical distances of the points to the polynomial it encodes.\n",
    "    \"\"\"\n",
    "    #  print(\"\\n calculate_errorj17(chromosome, xArray, yArray)\")\n",
    "    coefficients = decodeFullCromosomej17(chromosome, length_of_chromosomes) \n",
    "    error = calculate_error_from_coefficients(coefficients, xArray, yArray)\n",
    "    return error\n",
    "\n",
    "def calculate_all_errorsj17(population, xArray, yArray):\n",
    "    # print(\"\\n*calculate_all_errorsj17(population, target_sequence)\")\n",
    "    \"\"\"Calculates the error of all chromosomes in the population.\"\"\"\n",
    "    errors = [calculate_errorj17(chromosome, xArray, yArray) for chromosome in population]\n",
    "    # print(\"errors: \", errors)\n",
    "    return errors\n",
    "\n",
    "def select_the_least_errorj17(population, xArray, yArray):\n",
    "    \"\"\"Selects the best chromosome with minimal error for reproduction.\"\"\"\n",
    "    errors = calculate_all_errorsj17(population, xArray, yArray)\n",
    "    smallest_error = min(errors)\n",
    "    best_chromosome_index = errors.index(smallest_error)\n",
    "    best_chromosome = population[best_chromosome_index]\n",
    "    # print(\"\\n*select_the_least_errorj17(population)\")\n",
    "    # print(\"smallest_error = \", smallest_error)\n",
    "    # print(\"The chro = \", best_chromosome )\n",
    "    return smallest_error, best_chromosome\n",
    "\n",
    "def clone_populationj17(best_chromosome, population_size):\n",
    "    \"\"\"Creates a new population by cloning the best chromosome.\"\"\"\n",
    "    return [best_chromosome] * population_size\n",
    "\n",
    "\n",
    "def mutatej17(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_allj17(population, mutation_rate, alphabet):\n",
    "    \"\"\"Mutates all chromosomes in the population.\"\"\"\n",
    "    mutated_population = []\n",
    "    for chromosome in population:\n",
    "        mutated_chromosome = mutatej17(chromosome, mutation_rate, alphabet)\n",
    "        mutated_population.append(mutated_chromosome)\n",
    "    return mutated_population\n",
    "\n",
    "def crossoverj17(parent1, parent2, length_of_chromosomes, recombination_rate):\n",
    "    \"\"\"Performs crossover between two parent chromosomes.\"\"\"\n",
    "    if random.random() < recombination_rate:\n",
    "        crossover_point = random.randint(0, length_of_chromosomes)\n",
    "        return parent1[:crossover_point] + parent2[crossover_point:]\n",
    "    else:\n",
    "        return parent1\n",
    "\n",
    "def crossover_allj17(population, length_of_chromosomes, 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 = crossoverj17(parent1, parent2, length_of_chromosomes, recombination_rate)\n",
    "        recombinant_population.append(child)\n",
    "    return recombinant_population\n",
    "\n",
    "\n",
    "\n",
    "def run_one_generationj17(population, xArray, yArray, mutation_rate, recombination_rate, alphabet):\n",
    "    \"\"\"Runs one generation of the genetic algorithm.\"\"\"\n",
    "    # Calculate fitness scores for the current population\n",
    "    smallest_error, best_chromosome  = select_the_least_errorj17(population, xArray, yArray)\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_populationj17:\n",
    "        new_population = clone_populationj17(best_chromosome, population_size)\n",
    "    if include_mutate_allj17:\n",
    "        new_population = mutate_allj17(new_population, mutation_rate, alphabet)\n",
    "    if include_crossover_allj17:\n",
    "        new_population = crossover_allj17(new_population, length_of_chromosomes, recombination_rate)\n",
    "    return smallest_error, best_chromosome, new_population\n",
    "\n",
    "\n",
    "\n",
    "\n",
    "def taskj17(xArrayInitial, yArrayInitial, xArray, yArray, mutation_rate, recombination_rate, alphabet, length_of_chromosomes):\n",
    "    # \n",
    "    # We draw the original data points, with 3 points, find and draw the regression polynomial defined by the points.\n",
    "    coefficients = draw_initial_points_and_polynomialj17( xArrayInitial, yArrayInitial)\n",
    "    \n",
    "    # Create a population with the coefficients of the given polynomial padded with zeroes to get a plynomial of fifth degree.\n",
    "    population = createPopulationFromCoefficientsj17(coefficients[0], coefficients[1], coefficients[2], 0.0, 0.0, 0.0, length_of_chromosomes, population_size)\n",
    "\n",
    "    # print(population)\n",
    "    #population = create_populationj17(population_size, length_of_chromosomes, alphabet)\n",
    "    # print(population)\n",
    "    generation = 0\n",
    "    best_chromosome = ''\n",
    "    best_fitness = 0\n",
    "    start_time = time.time()\n",
    "    smallest_error_history = [] # List to store best fitness of each generation\n",
    "    delta_draw =  number_of_generations // 10\n",
    "    if print_best_fitness:\n",
    "        print(\"Generation, best_chromosome and best_fitness\")\n",
    "    while generation < number_of_generations:\n",
    "        generation += 1\n",
    "        smallest_error, best_chromosome, population = run_one_generationj17(population, xArray,yArray, mutation_rate, recombination_rate, alphabet)\n",
    "        if print_best_fitness:\n",
    "            print(f\" {generation}  {best_chromosome} {smallest_error}\")\n",
    "        if generation % delta_draw == 0:\n",
    "            calculate_errorj17(best_chromosome, xArray, yArray)\n",
    "            coefficients = decodeFullCromosomej17(best_chromosome, length_of_chromosomes)\n",
    "            error  = calculate_errorj17(best_chromosome, xArray, yArray)\n",
    "            draw_polynomial_from_coefficientsj17(coefficients, xArray, yArray, generation, error)\n",
    "        smallest_error_history.append(smallest_error)\n",
    "    # print(f\"\\nTarget sequence matched in generation {generation}\")\n",
    "    # print(f\"Final chromosome: {best_chromosome}\")\n",
    "    totalCost = population_size * generation\n",
    "    \n",
    "    return  best_chromosome, totalCost, smallest_error_history\n",
    "\n",
    "def mainj17(xArrayInitial, yArrayInitial, xArray, yArray, mutation_rate, recombination_rate, alphabet, length_of_chromosomes):\n",
    "    print_parametersj17()\n",
    "    print(\"Total cost = population size * number of generations\")\n",
    "    best_chromosome, totalCost, smallest_error_history = taskj17(xArrayInitial, yArrayInitial, xArray, yArray, mutation_rate, recombination_rate, alphabet, length_of_chromosomes)\n",
    "    final_error = smallest_error_history[-1]\n",
    "    print(f\" The final best chromosome is {best_chromosome}\" )\n",
    "    coefficients = decodeFullCromosomej17(best_chromosome, length_of_chromosomes)\n",
    "    print(f\" Encoded coefficients: Intercept {coefficients[0]}, slope {coefficients[1]}, quadratic {coefficients[2]}, cubic {coefficients[3]}, quartic {coefficients[4]}, quintic {coefficients[5]}\")\n",
    "    print(f\" Total cost =  {totalCost} chromosomes\")\n",
    "    print(f\" Final error =  {final_error} \")\n",
    "\n",
    "    # Plot the fitness history    \n",
    "    g_values = list(range(1, len(smallest_error_history) + 1))\n",
    "    plot_functionj17(g_values, smallest_error_history, xlabel='Generation', ylabel='SmallestError', title='Smallest Error Over Generations')\n",
    "\n",
    "\n",
    "    # Perform polynomial regression\n",
    "    # Fit a polynomial of degree 5 (polynomial regression)\n",
    "    p_fitted = Polynomial.fit(xArray, yArray, deg=5)\n",
    "    a_0, a_1, a_2, a_3, a_4, a5 = p_fitted.convert().coef\n",
    "    print(f\"Polynomial regression coefficients: Intercept {a_0}, slope {a_1}, quadratic {a_2}, cubic {a_3}, quartic {a_4}, quintic {a5}\")\n",
    "    # Create the regression graph\n",
    "    x_new = np.linspace(-2,3, 100) # Generate 100 points between -2 and 3 for a smooth curve\n",
    "    y_new = p_fitted(x_new)\n",
    "\n",
    "    # The best chromosome encodes for the coefficients of the polynomial that best fits the data points\"\n",
    "    b_0, b_1, b_2, b_3, b_4, b5 = decodeFullCromosomej17(best_chromosome, length_of_chromosomes)\n",
    "    print(f\"Encoded coefficients: Intercept {b_0}, slope {b_1}, quadratic {b_2}, cubic {b_3}, quartic {b_4}, quintic {b5}\")\n",
    "    # Calculate the predicted y value based on the coefficients of the polynomial\n",
    "    our_polynomial = b_0 + b_1 * np.array(x_new ) + b_2 * np.array(x_new )**2 + b_3 * np.array(x_new )**3 + b_4 * np.array(x_new )**4 + b5 * np.array(x_new )**5\n",
    "    \n",
    "\n",
    "    # Plot  our polynomial\n",
    "    plt.figure(figsize=(10, 6))\n",
    "    plt.scatter(xArray, yArray, label='Observed Data')\n",
    "    #plt.plot(xArray, regression_polynomial, color='red', label=f'Polynomial Regression: y = {a_0:.2f} + {a_1:.2f}x + {a_2:.2f}x^2 + {a_3:.2f}x^3 + {a_4:.2f}x^4 + {a5:.2f}x^5')\n",
    "    plt.plot(x_new,        our_polynomial, color='green', label=f'Our best evolved polynomial: y = {b_0:.2f} + {b_1:.2f}x + {b_2:.2f}x^2 + {b_3:.2f}x^3 + {b_4:.2f}x^4 + {b5:.2f}x^5')\n",
    "    plt.xlabel('Independent variable (x)')\n",
    "    plt.ylabel('Dependent variable (y)')\n",
    "    plt.title(f'la Evoluciónary Regression minimizes the error of the line with respect to the data points. Error = {final_error:.2f}')\n",
    "    plt.legend()\n",
    "    plt.grid(True)\n",
    "    plt.show()\n",
    "\n",
    "\n",
    "    end_time = time.time()\n",
    "    # Calculate the difference in seconds\n",
    "    elapsed_time = end_time - start_time\n",
    "    elapsed_time = timedelta(seconds=elapsed_time)\n",
    "    print(f\"Elapsed time: {elapsed_time}\")\n",
    "    #return best_chromosome, totalCost, best_fitness_history\n",
    "\n",
    "# Call the main function with the defined parameters\n",
    "mainj17(xArrayInitial, yArrayInitial, xArray, yArray, mutation_rate, recombination_rate, alphabet, length_of_chromosomes)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "a6ccf491",
   "metadata": {},
   "source": [
    "*Nuestras observaciones.*\n",
    "\n",
    "1. La Evolución encuentra, a veces muy rápidamente, una aproximación con un pequeño error, pero con una forma poco interesante para un ser humano, y permanece atrapada en ella sin más avance durante 100000 generaciones y para un tamaño de población de 200. \n",
    "2. La Evolución es cara.  El programa converge muy lentamente. La forma final para 100000 generaciones y un tamaño poblacional de 200 es muy rudimentaria.\n",
    "3. Dar una solución a un problema más simple parece inútil para facilitar la búsqueda de una solución de uno complejo.\n",
    "\n",
    "En términos del ancestro común del gato y el perro, consideramos que no se pueden conectar dos linajes por medio de la Evolución si no es a través de un puente de baja aptitud que no es interesante para un ser humano. Esta es una predicción obligatoria para el registro fósil, el cual debe estar lleno de toda clase de monstruosidades como especies intermedias. "
   ]
  },
  {
   "cell_type": "markdown",
   "id": "2c295070",
   "metadata": {},
   "source": [
    "# EN RETROSPECTIVA\n",
    "\n",
    "Es un buen momento para analizar los puntos principales de lo que hemos hecho, y ponerlos en el contexto apropiado. \n",
    "\n",
    "**Ejercicio.** ¿Es la Evolución un hecho de la naturaleza, una fábula o una teoría?\n",
    ">\n",
    "> *Respuesta.* La Evolución es un hecho biológico maravilloso que nos hace a todos tan diferentes y, en algunos casos, muy bien sintonizados con el medio ambiente. También aceptamos la aparición de algunas especies por la Evolución. La Evolución también es amenazadora, como muestra la Evolución de los virus. La Teoría Evolutiva (TE) es una teoría sobre la Evolución. \n",
    "\n",
    "**Ejercicio.** ¿Qué dice la Teoría Evolutiva (TE)?\n",
    ">\n",
    "> *Respuesta.* La Teoría Evolutiva dice: \n",
    ">\n",
    ">> La complejidad de la vida es el resultado natural de reunir pequeños avances gracias a la selección recurrente del más apto entre una variabilidad creada por la reproducción, la recombinación y la mutación. La selección del más apto se hace automáticamente: algunos individuos sobreviven, otros no. Cuando sobrevivir produce una tendencia reproducible, decimos: los más aptos han sobrevivido. La siguiente tarea es explicar este caso de supervivencia mediante la bioquímica, la biofísica y la genómica. \n",
    "\n",
    "**Ejercicio.** ¿Consideras que la TE es científica? \n",
    ">\n",
    "> *Respuesta.* Sí. La TE Darwiniana dice que todos los seres vivos tienen un antepasado común, del cual surgió la vida en todo su esplendor. Las extensiones modernas afirman que hubo una fenomenología prebiótica que permitió el surgimiento espontáneo de la vida. La TE Darwiniana es científica porque puede ser abstraída como un Algoritmo Genético (AG), cuyas predicciones pueden ser puestas a prueba por cualquier persona en su propia casa gracias a la tecnología informática moderna, es decir, gracias a esta contribución, en la cual se pueden correr programas con un solo click. \n",
    "\n",
    "**Ejercicio.** ¿Ha pasado la Evolución tus pruebas o tests?\n",
    ">\n",
    "> *Respuesta.* La predicción más inmediata es que la Evolución, en la forma de una AG, debe funcionar. La TE supera esta prueba fundamental porque el AG puede resolver perfectamente problemas ligeramente complejos. En realidad, la Evolución genera un proceso, el Proceso Evolutivo, que comienza con la imperfección y recoge pequeños avances para llegar finalmente a la perfección cuando la tarea es sencilla. Por ejemplo, puede predecir exactamente la ecuación de la línea que mejor representa un conjunto de puntos en el plano. La respuesta dada por el AG coincide con la dada por las matemáticas mediante regresión lineal. \n",
    "\n",
    "**Ejercicio.** La Evolución resuelve el problema de la regresión lineal, que produce un polinomio de primer grado.  ¿Has desafiado a la Evolución con un polinomio de segundo grado? \n",
    ">\n",
    "> *Respuesta.* Sí, hemos dado a la Evolución la tarea de encontrar un polinomio de quinto grado que pase exactamente por un conjunto de seis puntos. \n",
    "\n",
    "**Ejercicio.** ¿Cuáles son tus resultados?\n",
    ">\n",
    "> *Respuesta.* Hemos experimentado con muchas versiones del AG, y la conclusión más favorable es: \n",
    ">\n",
    ">> Los problemas se pueden clasificar por complejidad. Aquí, ésta se determina por el grado del polinomio de ajuste. La Evolución puede resolver perfectamente un problema fácil. También puede producir soluciones aproximadas de problemas complejos, pero puede suceder que la aproximación producida no sea interesante para un ser humano.  \n",
    "\n",
    "**Ejercicio.** ¿Existe una predicción de la TE para un alto grado de complejidad, como un polinomio de quinto grado? \n",
    ">\n",
    "> *Respuesta.* Sí. La predicción obligatoria de la TE es una regla que hemos observado sin excepciones: \n",
    ">\n",
    ">> La Evolución es costosa, un precio que se debe pagar en forma de gran tamaño poblacional o demasiadas generaciones. La Evolución genera un Proceso Evolutivo, que es el registro de la batalla de la Evolución contra la complejidad. Vemos que la Evolución puede producir rápidamente soluciones aproximadas que no son interesantes para un ser humano. En algunos casos, la aproximación es interesante para un ser humano, preferentemente cuando se le conceden suficientes recursos, tiempo, memoria, variantes del AG y repeticiones. El hecho universal de que la Evolución quema recursos en grandes cantidades puede organizarse en forma de una predicción obligatoria de la TE: **Cada traza de perfección en la solución evolutiva de cualquier problema en biología debe ir acompañada de un registro superabundante de imperfecciones.** \n",
    "\n",
    "\n",
    "**Ejercicio.** Es bien conocido cómo la Ciencia Internacional resuelve el problema de la complejidad excesiva de todos los seres vivos.  ¿Acepta esa explicación?\n",
    ">\n",
    "> *Respuesta.* No. Según la Ciencia Internacional, la Evolución es una realidad que va de la simplicidad a la complejidad. La prueba que se alega de esta afirmación es inmediata: la Evolución comenzó en los mares prebióticos con todo tipo de estructuras útiles para la vida, luego aparecieron  bacterias simples, luego microorganismos con núcleos y mitocondrias separados, luego simples organismos multicelulares, como las algas y las esponjas, luego otras complejas como las medusas, a las que siguen insectos, mamíferos, monos, chimpancés y el ser humano. \n",
    ">\n",
    "> Es cierto que el registro fósil muestra que las estructuras van de simples a complejas. Por eso todos creen en la TE. Pero esa no es la predicción obligatoria de la TE, que dice que el proceso evolutivo va de lo imperfecto a lo menos imperfecto y, en algunos casos, a una aproximación interesante que puede sonar como cuasi-perfección. Las dos proposiciones son muy diferentes porque la bacteria más simple, *Mycoplasma genitalium*, es un milagro, una maravilla. Por lo tanto, no es en modo alguno un sinónimo de imperfección.  Es tan simple porque es un parásito, y sin embargo tiene 580000 pares de bases, lo que podría ser equivalente a una cadena binaria con más de un millón de bits. En comparación, nuestros estudios tratan con cadenas binarias de alrededor de 100 bits. Y sufrimos porque la asombrosa capacidad de una computadora de escritorio ordinaria puede verse abrumada. En resumen, no hay en el registro fósil ningún rastro de una batalla de la Evolución contra la complejidad, ninguna señal de un proceso que conecta la imperfección con la perfección. Por lo tanto, la TE es falsa. \n",
    "\n",
    "**Ejercicio.** ¿Qué debe hacer la Ciencia internacional para lidiar con su predicción falsificadora obligatoria?\n",
    ">\n",
    "> *Respuesta.* Un genoma, el ensamblaje de ADN de cada organismo, es un conjunto de instrucciones para continuar la vida. Por lo tanto, es software. La imperfección en el software significa, en el mejor de los casos, productos defectuosos y fallas en las funciones. Así, la Ciencia Internacional debe mostrar en el museo que la Evolución está dominada por multitud de esqueletos lisiados a lo largo de los diferentes períodos. \n",
    "\n",
    "**Ejercicio.** El número de buenos museos es pequeño.  ¿Ofrece tu investigación algún otro medio en el que un laico pueda saber si él o ella es producto de la Evolución?\n",
    ">\n",
    "> *Respuesta.* Sí. Basta con mirar nuestro propio cuerpo. El genoma humano tiene 3600 millones de pares de bases. Esto es definitivamente más de 10 millones de bits. Eso no es demasiado, pero es suficiente para mantener a la Evolución ocupada durante un largo, largo tiempo. O, para que la Evolución sea verdadera debe ser un proceso en curso que debe tener en cada estadio demasiada imperfección como para remediarla. Por lo tanto, debemos encontrar multitud de malformaciones y fallos en nuestro cuerpo. De esa manera, la imperfección estaría conectada con la perfección en la naturaleza, como predijo la TE.  ¿En dónde está la multitud de defectos esperados en mi anatomía y fisiología? \n",
    "\n",
    "**Ejercicio.** Dado que tu simulación más larga dura unos pocos días, se puede inferir que los 4500 millones de años que la Tierra lleva haciendo experimentos evolutivos a gran escala son más que suficientes para que la Evolución nos haya creado.  ¿Verdad?\n",
    ">\n",
    "> *Respuesta.* Los experimentos a gran escala producen resultados que son estadísticamente confiables. Por lo tanto, es obligatorio encontrar un predominio de esqueletos lisiados en el registro fósil y todo tipo de disfunciones y malformaciones en tu propio cuerpo. Esto es ineludible. ¿Dónde están? Muéstremelas.\n",
    "\n",
    "**Ejercicio.** La Tierra es insuficiente para explicar nuestra complejidad por medio de la Evolución. ¿Es el Universo en su conjunto la explicación correcta?\n",
    ">\n",
    "> *Respuesta.* El tiempo se multiplica por tres al pasar de la Tierra al Universo. Esto es irrelevante. Por otro lado, el número de planetas habitables en el universo observable puede ser grande, digamos, 1000. Esto también es irrelevante. De todos modos, si es $10 ^{100}$, tampoco es demasiado. Entonces, la única manera en que la Evolución puede explicar nuestra existencia es por medio de un accidente feliz que consiste en una multitud de accidentes felices. Tal posibilidad no puede ser excluida por la Ciencia. Pero no se puede reproducir. Por lo tanto, no es científica. Imaginemos que alguien gane la lotería mil millones de veces una tras otra. Es la misma historia. Entonces, si alguien cree que estamos aquí debido a un acontecimiento feliz, su fe es ciega, no científica, pero la Ciencia no puede contradecirlo.  \n",
    "\n",
    "**Ejercicio.** Tu rechazo al poder de la Evolución para explicar nuestra existencia se basa en tus simulaciones. Por lo tanto, es una generalización estadística. ¿Las matemáticas te apoyan?\n",
    ">\n",
    "> *Respuesta.* Sí. El combustible de la Evolución es MAX, que toma la mejor opción entre las propuestas de la población. Si el tamaño de la población crece, hay más opciones para elegir, y la potencia de MAX aumenta. Pero la potencia de MAX es logarítmica en el tamaño de la población. Esto significa que el número de intentos para resolver un problema debe ser exponencial en su complejidad, aquí, el número de bits que debemos especificar. Ahora, ¿puedes imaginar cuántas pruebas cuesta $2 ^{1000}$? Son más pruebas de las que se pueden intentar desde el principio de los tiempos. \n",
    "\n",
    "**Ejercicio.** Según tu experiencia a lo largo de esta contribución, ¿La Evolución se clasifica como un oráculo? \n",
    ">\n",
    "> *Respuesta.* No. Para el problema estudiado de ajustar un conjunto de 6 puntos por un polinomio de quinto grado, las matemáticas producen una solución perfecta casi instantáneamente. Las matemáticas se clasifican como un oráculo. Por el contrario, la Evolución es demasiado lenta. De todos modos, la Evolución es excelente para proponer soluciones aproximadas de bajo costo que pueden clasificarse como buenas según una métrica dada, pero que no son interesantes para un ser humano. Así que, como Oráculo, la Evolución posiblemente no se ganaría la vida. Sin embargo, si la Evolución tiene a su disposición supercomputadoras y expertos, puede lograr dar soluciones aproximadas que puedan sonar interesantes para nosotros, los seres humanos, incluso para problemas complejos. Tener experiencia significa tener la capacidad de oler dónde es factible un problema para la Evolución cuya solución podría ser interesante para la Ciencia y la humanidad. O, qué problemas interesantes carecen de una solución matemática o de IA. En este caso, la Evolución es una buena herramienta para probar, tal vez la solución resultante podría ser satisfactoria. De todos modos, **en la actualidad, no sabemos cómo hacer que la Evolución produzca perfección. Este es un desafío para todos.** \n",
    "\n",
    "**Ejercicio.** Su investigación en esta contribución se ha dirigido a encontrar por la Evolución un polinomio de quinto grado que mejor represente un conjunto de 6 puntos.  ¿Crees que es serio convertir un solo experimento en un rechazo a la teoría científica más famosa de todos los tiempos? LA TE es la teoría más importante de la Ciencia porque explica nuestra existencia (bajo el trasfondo del modelo moribundo de la cosmología del Big-Bang).\n",
    ">\n",
    "> *Respuesta.* Sí. Esto es muy serio. Nuestro trabajo no es científico porque no usamos pruebas estadísticas para respaldar nuestras afirmaciones. Tengamos presente que una prueba estadística se usa tanto para rechazar hipótesis como para no rechazarlas. Cuando se trata de rechazo se inspira más confianza que cuando no se rechaza. Por ello, la  Estadística no puede responder por las creencias de los seres humanos. Por consiguiente, nuestro trabajo está dirigido a personas, científicas o no, que tienen el valor de creer que su experiencia personal a través de la vida es invaluable. Y cada experiencia personal dice que **No hay sabiduría contra la complejidad**. Así, la vida de la mayoría de las personas es una batalla por no hundirse que produce una lista de fracasos recurrentes del tipo más diverso y que se intercalan con algunos logros. Pero, con experiencia, uno puede progresar, como predijo la TE.  Por lo tanto, cada persona debe encontrar que su vida se refleja en los resultados de nuestros programas: *La lucha contra la complejidad es dura y deja cicatrices*.  \n",
    ">\n",
    "> Ahora, la Evolución es una herramienta común que cada persona utiliza para obtener conocimiento y habilidades. Con un poco de entrenamiento, uno puede ver la Evolución en todas partes. Por ejemplo, los niños aprenden a hablar siguiendo un Proceso Evolutivo extremadamente largo. ¿Cuánto tiempo? Cuando tenía cuarenta años, era muy consciente de que mis habilidades verbales eran muy malas. Mi Proceso Evolutivo todavía estaba a medias. Escribir me ha ayudado a mejorar mi capacidad para comunicar mis ideas. Así, mi experiencia personal me dice que no hay rastro de perfección si no va acompañado de un largo historial de gran cantidad de errores, de soluciones mediocres, de propuestas imperfectas. Mi experiencia personal concuerda con la de cada quien. Si traducimos esto a la Evolución, debemos predecir dos cosas:\n",
    ">\n",
    "1. Una enorme cantidad de esqueletos lisiados en el registro fósil para cada época. \n",
    "2. La Evolución no es mágica. La Evolución es real. Y por tanto sufre luchando contra la complejidad, lo cual significa que nnuestro cuerpo debe estar lleno de toda clase de defectos de anatomía, fisiología y bioquimica.  \n",
    ">\n",
    "> Dado que las dos predicciones son obligatorias y trascendentes y no se cumplen, la TE es, obviamente, falsa.  \n",
    "\n",
    "\n",
    "**Ejercicio.** Dado que la TE es falsa, ¿significa que Dios es una conclusión científica? \n",
    ">\n",
    "> *Respuesta.* No. El gran poder de la Ciencia es resultado de la gente que recibió como desafío los vacíos de las buenas teorías. Cuando se resuelve un  desafío, la Ciencia se hace más fuerte y en muchos casos más hermosa. Además, la TE es falsa, pero la Ciencia puede recurrir al azar. La Ciencia no puede excluir una cadena de miles de felices accidentes que hacen innecesario a Dios. Por lo tanto, Dios no es una conclusión científica. Más bien, la fe en Dios se basa en la paz que el perdón de los pecados da por medio de la muerte de Jesús, y en la alegría de la vida que brota de orar por bendición tanto para amigos como para enemigos. \n",
    "\n",
    "**Ejercicio.** ¿Puedes resumir tu punto?\n",
    ">\n",
    "> *Respuesta.* Sí. Se propuso la teoría evolutiva para explicar la complejidad de la vida mediante el acopio de pequeños avances gracias a la selección del más apto entre una variabilidad creada por la reproducción, recombinación y mutación. Según nuestros estudios junto con la experiencia de cada persona en su propia vida, la Evolución genera un Proceso Evolutivo que conecta la imperfección con la perfección, cuya marca distintiva es el inmenso número de pruebas que se deben producir y verificar para ver algo interesante. Por lo tanto, una predicción obligatoria fundamental es que el registro fósil debe estar dominado por una multitud de fósiles lisiados. Otra es que nuestros propios cuerpos deben estar llenos de todo tipo de malformaciones y fallos. Ambas predicciones son fracasos flagrantes. La TE es falsa. \n",
    "\n"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "ef9050ce",
   "metadata": {},
   "source": [
    "# GRADUACIÓN\n",
    "\n",
    "Trabaja en uno de los tres temas siguientes.\n",
    "\n",
    "\n",
    "En el mundo de la Evolución hay demasiadas posibilidades.  Esta es una pesadilla que debe ser dominada por la selección de la pregunta correcta. Según el trabajo realizado aquí, la cuestión más importante se refiere al surgimiento de la perfección. Hemos formulado y probado en vano varios GAs con la esperanza de tener una luz sobre nuestro camino. Una dirección que no hemos explorado es la estructuración de la población, lo que permite ejecutar varios procesos en paralelo con la posibilidad de recombinarlos con la migración. Tal vez esto arroje luz sobre por qué existe la recombinación. Dos modelos de poblaciones estructuradas son populares:\n",
    "\n",
    "1. El modelo escalonado, en el que las poblaciones se distribuyen linealmente como una población de tortugas a lo largo de un río. \n",
    "2. El modelo insular, en el que las poblaciones se subdividen en pequeñas subpoblaciones o demes, como un conjunto de colonias de abejas, que están débilmente conectadas por la migración. Pueden formar un círculo, una estructura de dimensión uno. O, si la migración es a los primeros vecinos, aparecerá una red bidimensional.\n",
    "\n",
    "La tercera opción es ayudarte a ti mismo si buscas resultados reproducibles. Con ese objetivo\n",
    "\n",
    "3. Añade pruebas estadísticas a tus programas preferidos. Cómo programar en Python las pruebas estadísticas más populares se puede aprender [aquí](https://machinelearningmastery.com/statistical-hypothesis-tests-in-python-cheat-sheet/)\n",
    "\n",
    " "
   ]
  },
  {
   "cell_type": "markdown",
   "id": "d7f55e97",
   "metadata": {},
   "source": [
    "# CONCLUSIÓN\n",
    "\n",
    "**Ejercicio.** Redacta tus conclusiones.\n",
    ">\n",
    "> *Respuesta.* La Teoría de la Evolución dice que todos los seres vivos tienen un ancestro común, y que la vida en todo su esplendor surgió de él por la Evolución. Esta consiste en la selección recurrente del más apto que se tomó de una variabilidad creada por reproducción, recombinación y mutación. El estudio de la Evolución es un ejercicio muy desafiante. Sin embargo, la siguiente generalización nunca falla: la Evolución puede crear resultados casi perfectos, pero hay que pagar un precio, a saber, producir una gran cantidad de propuestas imperfectas. Imaginemos a un carpintero que para hacer maravillas, tiene que producir mucha basura. Esto equivale a dos predicciones obligatorias. Primera: enormes cantidades de esqueletos lisiados deben dominar el registro fósil, comenzando por los fósiles de bacterias del precámbrico. Segunda: nuestros cuerpos deben estar llenos de todo tipo de malformaciones y fallas funcionales. Ambas predicciones son fracasos flagrantes. Por lo tanto, la teoría evolutiva es falsa. Esta falsedad no convierte la fe en Dios en un hecho científico porque el materialismo siempre puede recurrir a la pura aleatoriedad para explicar cualquier cosa. Más bien, el creyente debe fortalecer su fe orando por los enemigos, que son personas que te han hecho daño o que son difíciles de amar. Esto es un poderoso remedio contra la depresión. \n"
   ]
  }
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