{ "cells": [ { "cell_type": "markdown", "metadata": {}, "source": [ "# Autovalores em ecologia\n", "#### Uma aplicação interessante da álgebra linear são modelos de população matricial, amplamente utilizados na ecologia e em problemas demográficos. Um tipo de modelo considera a distribuição etária da fertilidade e sobrevivência em uma população animal ou vegetal. Vamos ver como isso ocorre em um estudo de caso sobre coelhos." ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "##### Referência: Álgebra Linear com aplicações / Anton Howard e Chris Rorres; trad. Claus Ivo Doering. - 8. ed. - Porto Alegre: Bookman, 2001." ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "|**Em uma população de coelhos:**|\n", "|:--------------------:|\n", "|1-)metade dos coelhos recém-nascidos sobrevivem no primeiro ano de vida;|\n", "|2-)metade dos coelhos sobrevivem no segundo ano de vida;|\n", "|3-)os coelhos vivem no máximo até três anos;| \n", "|4-)coelhos produzem 0, 6, 8 outros coelhos no primeiro, segundo e terceiro anos, respectivamente.|" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Sejam $X_{t}$, $Y_{t}$ e $Z_{t}$ a quantidade de coelhos no período de 0, 1 e 2 anos de idade, respectivamente, em um certo período t de tempo após o início do estudo, podemos definir:" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "$X_{t+1} = 0X_{t} + 6Y_{t} + 8Z_{t}$" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "$X_{t+1} = 1/2X_{t} + 0Y_{t} + 0Z_{t}$" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "$X_{t+1} = 0X_{t} + 1/2Y_{t} + 0Z_{t}$" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "As coordenadas do sistema podem ser definidos em uma matriz L:\n" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "$$L = \\begin{bmatrix}\n", " 0 & 6 & 8 \\\\\n", " 0.5 & 0 & 0 \\\\\n", " 0 & 0.5 & 0 \\\\\n", " \\end{bmatrix}$$" ] }, { "cell_type": "code", "execution_count": 1, "metadata": {}, "outputs": [], "source": [ "# importando a biblioteca de funções do Python numpy\n", "import numpy as numpy \n", "# importando a biblioteca de funções do Python matplotlib\n", "import matplotlib.pyplot as plt\n", "%matplotlib inline " ] }, { "cell_type": "code", "execution_count": 2, "metadata": {}, "outputs": [], "source": [ "# definindo a matriz L\n", "L = numpy.array([[0,6,8], [0.5,0,0], [0,0.5,0]]) " ] }, { "cell_type": "code", "execution_count": 3, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "[[0. 6. 8. ]\n", " [0.5 0. 0. ]\n", " [0. 0.5 0. ]]\n" ] } ], "source": [ "#imprimindo a matriz\n", "print(\"{}\".format(L))" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Essa matriz representa a transição etária ano após ano. Multiplique essa matriz pelo vetor população para obter a população estruturada por idade no próximo ano. Vamos escrever um pouco de código em Python para ver a população em cada faixa etária crescer mais, ano após ano (conceitos usados exigem conhecimentos em Cadeias de Markov, em que um sistema muda para outro)." ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "|**Seja p a população inicial de coelhos, podemos especular:**|\n", "|:-----------:|\n", "|1-) 25 coelhos na idade 0;|\n", "|2-) 10 coelhos na idade 1;|\n", "|3-) 5 coelhos na idade 2;|" ] }, { "cell_type": "code", "execution_count": 4, "metadata": {}, "outputs": [], "source": [ "# definindo um array p, p = população inicial de coelhos\n", "p = numpy.array([25, 10, 5]) " ] }, { "cell_type": "code", "execution_count": 5, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "A população inicial de coelhos é: [25 10 5]; para 0 ano, 1 ano e 2 anos, respectivamente.\n" ] } ], "source": [ "# imprime a população inicial de coelhos\n", "print(\"A população inicial de coelhos é: {}; para 0 ano, 1 ano e 2 anos, respectivamente.\".format(p))" ] }, { "cell_type": "code", "execution_count": 6, "metadata": {}, "outputs": [], "source": [ "# função que estima a população de coelhos após x anos seguidos\n", "def novaPopulacao(anos):\n", " \n", " # definindo a população inicial de coelhos\n", " populacao = numpy.array([25, 10, 5]) \n", " # realiza 10 multiplicações sucessivas considerando o vetor população anterior em cada estado\n", " # estrutura for que varia de 0 até o ano de parada que o usuário digitar\n", " for indice in range (0, anos):\n", " # define a nova matriz população recursivamente\n", " populacao = numpy.dot(L,populacao) \n", " \n", " # retorna como resultado da função a nova população após x anos\n", " return populacao" ] }, { "cell_type": "code", "execution_count": 7, "metadata": {}, "outputs": [], "source": [ "# função que imprime um gráfico de Pizza para a população de coelhos\n", "def graficoPizza(populacao, titulo):\n", " \n", " # criando as etiquetas para o gráfico\n", " labels = '0 ano', '1 ano', '2 anos'\n", "\n", " # criando a área de plotagem\n", " fig1, ax1 = plt.subplots()\n", "\n", " # criando o gráfico\n", " ax1.pie(populacao, labels = labels, autopct = '%1.1f%%', shadow = True, startangle = 90)\n", "\n", " # com essa opção, o gráfico ficará em círculo\n", " ax1.axis('equal')\n", "\n", " # título do gráfico\n", " plt.title(titulo)\n", "\n", " # mostra o gráfico\n", " plt.show()\n", " \n", " # função não retorna nada especifico, ela é do tipo void\n", " return None" ] }, { "cell_type": "code", "execution_count": 8, "metadata": {}, "outputs": [ { "data": { "image/png": "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\n", "text/plain": [ "
" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "# chama a função que imprime o gráfico de pizza\n", "graficoPizza(novaPopulacao(anos = 0), titulo = \"População de coelhos inicial\") " ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "O nosso sistema agora vai sofrer uma mudança de estado. Vamos verificar essa mudança de estado após ter se passado 1 ano, provavelmente a população vai ter uma nova modelagem, baseado nas características de vida dos coelhos e na população que tinha no ano anterior." ] }, { "cell_type": "code", "execution_count": 9, "metadata": {}, "outputs": [ { "data": { "image/png": "iVBORw0KGgoAAAANSUhEUgAAAV0AAAD3CAYAAAC+eIeLAAAABHNCSVQICAgIfAhkiAAAAAlwSFlzAAALEgAACxIB0t1+/AAAADh0RVh0U29mdHdhcmUAbWF0cGxvdGxpYiB2ZXJzaW9uMy4xLjIsIGh0dHA6Ly9tYXRwbG90bGliLm9yZy8li6FKAAAgAElEQVR4nO3dd3gc1dn38e+9RWVVVu7Glm25LLaxCWADMt20UEyHdAihJCGkd70pT5T2xA+plEAKIdTQEgIkIkACoRiwKAZjqmWMjLstWX37znn/mLGRbdlW2d3Z1d6f69JlWTM7c+9K+unM2XPOiDEGpZRS2eFxuwCllCokGrpKKZVFGrpKKZVFGrpKKZVFGrpKKZVFGrpKKZVFGro5TkQWisi6NBxnnIisEZHrRORcEflSOupzjm1EZEa6jjcUu75eItIsIie5WVN/iIhHRB4QkUvdrkVllobuADi/wBER6RaRzSLyZxEpd7uufjoU+CnQDHwbeMDVatSufgo8Zoy5aTAPFpE/iMjbImKJyKfSW5pKJ5/bBeShM40x/xGRicAjwPeAOpdr2idjTEOv//7CtUJUn4wx/2+Ih1gO3A38XxrKURmkLd1BMsasB/4FzAUQkQki8qCIbBORVSLy6e37iki9iPxVRO4WkS4RWSYiB/XavtPluYjcLCI/6eu8IlInIu84x3lDRM7dZfunReTNXtvn7etxzqXt95zuhy0icquIBPf03EXkmyKyUUQ27Ho5LCLFIvILEXnPuRr4nYiU7uVYe6p3tog8ISLtIvK6iJw12HMAB4vIqyLS4XwPSnY5/yrn+/agiExwvi4i8mvn9ehwHj93D8/hkl7PYbWIfLbXtoUisk5EviMiLc7V0id6bQ86r/dW5/X/noh4nG0zRORJ5/wtInL3np6gMea3xpjHgOheXoft51wkIi+LSKeIrBWR+l7bapyfx4ud17dFRL7ba3uxiPzG+d5vcD4v3tc5VS/GGP3o5wf2pflJzueTgNeBHzv/fxK4HigBDga2Aic62+qBBHAB4Ae+AbwL+J3tBpjR6zw3Az9xPl8IrOu17UPABOw/mB8BeoD9em1bDxwGCDADmNKPx10KrAKmAeXAfcBte3gNTgU2Y/+xKQP+0rt+4DfAg8BIoAL4B/CzPRyrz3qd12gV8B2gCDgB6AJm7uscfbxezcDzznMfCbwJXOFsOwFoAeYBxcC1wFPOtlOAl4Aqp7bZ21+vPp7HImC6s99xQBiY16ueJPAr5xzHOa/99udyK3ZXTwVQA6wELnO23Ql81/melQBH9+NndAnwqX3ssxA40DnuB5zv5znOthrn+/lHoBQ4CIgBs53tPwKWAmOBMcCzOL8D+tHPHHG7gHz6cH6Bu4F2YA12yJZiB3AKqOi178+Am53P64GlvbZ5gI3AMc7/+x26fdT0CnC28/kjwJf7+Vx6P+4x4Mpe22Zi/5Hw9fG4m4DFvf6///b6ndDpAab32n4E8O4eauizXuAYYBPg6fW1O53Xca/n2PX1cr5nF/b6/1XA75zP/wRc1WtbufO8a7ADeSWwoHcd/Xxt79/+vHg/dMt6bb8H+D7gdQLtgF7bPgs84Xx+K/AHoHoA595n6PbxmN8Av3Y+r3G+n9W9tj8PfNT5/B3g9F7bTgGas/H7N1w+tHth4M4xxlQZY6YYY640xkSwW1HbjDFdvfZbA0zs9f+12z8xxljAOudxAyIinxSRV5zL7nbsFudoZ/Mk7F+KgT5uglNv79p9wLg+DjWh93PZ5XFjgADwUq/zPOx8vS97qncCsNZ5nXqfZ+IgzgF2gG8Xxg7X7efZUb8xphtoBSYaYx4HrgN+C2wW+42qyr4OLiKnichSp4uiHTid919bgDZjTM8uz2WCs08Ru7/2239uvoX9R+Z5p4slLSMbRKRWRP7rdGl0AFfsUi/08zXr9VxUP2nopscGYKSIVPT62mTsS+ftJm3/xOmzq3YeB/YPdaDXvuP7OomITMG+7PsCMMoYUwW8hv2LCXYYTh/E4zZgX9b3rj2Jfdm5q429n4uz73YtQASY4/xhqjLGBI0xexrh0We9Tj2Ttvdt9jrP+kGcY292et4iUgaMcs6DMeYaY8x8YA52i/6bux7A6c/8G/abk+Oc1/Yh3n9tAUY4x+79XDY4zyXB7q/99vNvMsZ82hgzAbsFfL2kZ2jeX7C7ZyYZY4LA73apd2/6+lnZsId9VR80dNPAGLMWu2/rZyJSIiIfAC4D7ui123wROU9EfMBXsC8rlzrbXgE+LiJeETkVu9+vL2XYl35bwX4DB+eNPMeNwDdEZL7zRtAMJ3D39bg7ga+KyFSxh8D9L3C3MSbZRw33AJ8SkQNEJAD8oNfrYGGH+69FZKxzrokicsoens+e6m3E7kL4loj4RWQhcCZw1yDOsTd/AS4RkYOd8PxfoNEY0ywihzktQr9TSxS7C2lXRdh9tVuBpIicBnywj/1+KCJFInIMcAZwrzEmhf16/lREKpzn/jXgdud5fUhEqp3Ht2F/D/uqAefYJdjh6Xd+Dvf0+12BfWUWFZHDgY/v7UXaxZ3A90RkjIiMBv5ne72qfzR00+dj2P1hG4C/Az8wxvy71/YHsN/AagMuAs4zxiScbV/GDpV24BPYfYK7Mca8AfwSeA67FXog8Eyv7fdij/f8C2A5xxm5r8dh99PeBjyF/QZfFPjiHmr4F3Yf4OPYb3Y9vssu33a+vlREOoH/YPcR93Ws3vV29ao3DpwFnIbdGrwe+KQx5q2BnmNvjP1u//exW6obsVvdH3U2V2KHexv2JXQrfQy1c7qUvoQdnm3YAfbgLrttcrZtwP5DfEWv5/JF7FBfjd0f+xfs7wfYbzA2iki3c8wvG2Pe3cPTeRT7CuBI7H7gCHDsHva9EviRiHRhh+Y9e9ivLz8BXgReBVYAy5yvqX4SpzNcZZAzJGeGMebCLJ7zD8AvjDErs3VOtTunlX67MaZ6X/uqwqAt3WHI6SJYz55bOkopl+iMtOHpHezuhRPdLiQXicgk7OFY47Ffpz8YY652typVKLR7QRUcEdkPe6LDMmfEyUvYQwHfcLk0VQC0e0EVHGPMRmPMMufzLuxZahN33U9EzhSRRmfK7H9EZJzz9XoRuUnsacqrpdeKbSLyNRF5zfn4ivO1MhFpEJHlztc/kp1nqnKRdi+ogiYiNcAh2MPUdrUEWGCMMSJyOfZkha8722YBx2MPv3pbRG7AnlJ7CVCLPXSrUUSexJ5evcEYs8g55x7XtVDDn4auKljOG45/A75ijOnsY5dq4G6nO6IIezjddg3GmBgQE5Et2LP3jgb+vn32mYjchz2l+WHgFyLyf8A/jTFPZ+xJqZyn3QuqIDmTHv4G3GGMuW8Pu10LXGeMORB7RlhJr22xXp+nsBswfc7qcobtzcce1/ozEfmfIZav8piGrio4IiLYi928aYz51V52DfL+VO6L+3Hop4BzRCTgTPs9F3ha7OUiw8aY27EnWMwbfPUq32n3gipER2HPClwhIq84X/uOMeahXfarB+4VkfXYU7an7u2gzmiIm7FX5QK40RjzsjNF+eciYmGvtfC59DwNlY90yJhSSmWRdi8opVQWaegqpVQWaegqpVQWaegqpVQW6egFlRNq6hr82LfcGbuHf0djj5P1Aj5v+ZsbApNuqcYeI5vCvvtGWx8f27DvULFmxcUret9OSSlX6OgFlVU1dQ3F2FNo5+zyMY0BXHl5S5e/Eai584ABnn4b9gpsTdg3nXwdeGnFxSv2tDC4UmmnoasypqauQbDXIzgee4rsXOy7BnuHfHB5prVi1j9GDfk4tlbslcZewL4rwvMrLl6h9/1SGaGhq9Kqpq5hFvbty483xix07qOVduJ9blP5/g/0eQPPNGkCHpuYSD788LoNT1Lf0Z7Bc6kCon26akhq6hpKsW85fo4x5kRncRgA7Nm2eSsEhMalkgcAf6U++Bz2XX4bqO9Y4W5pKp9p6KoBq6lrKAHOMMZ8GFjk3BU430O2T2e2dY/A/j05xvn4GfXBN7Bv5Hk79R3rsl2TiNyEfUfhLcaYufvaX+UW7V5Q/eL0zx5rjLkI+JCIVLpZTxa6FyBlrCXNa62gZ4+NEwv4L3YA/436ju6M1uMQkWOBbuBWDd38o+N01V7V1DVU1NQ1fNlY1mrgCRG5zO3AzZYR3fGtewlcsH9/TgRuBjZRH7yN+uAJma7LGPMU9kiMPUrXXS9U+mn3gupTTV3DZGOlvgpyuXg85eIpvL/Ph3VFogPYvQy4ELiQ+uAy4Crgr9R3pDJS3L6l5a4XxpiXs1/68Kahq3ZSU9dQa1LJb+PxniUe79CHduWxs2KRskFeC84D7gLeoT74S+DP1HcMJMDTIV13vdDQTbPCa76oPtXUNZw85Zv3vwAsFa/vXBEp6MD1xK3IURIf6jjg6cD1wBrqg9+lPjgiDaX1V1rueqHST0O3wE355v0HT/76354BHhWv/1C368kVkzuirb70DccYC/wEeI/64A+oD5am6bh7k5a7XmSquEKmoVugpnzzgUmTv3LP3/H4lnn8JUe6XU+uOa4nYmXgsOXYd6N4m/rgJ6gPDirUReRO4DlgpoisE5HL+titHvuuF08DLfs6pnNL+pux73rRiHPXi8HUp/ZOh4wVmJq6hqAV7f5fKQp8Wjwev9v1DFamh4w98M667mkeqzxTx3csBb5KfcfSDJ9H5RBt6RaQSV++68smlVznKSm/Mp8DN9NKepJtWQhcgAXAs9QH76A+OCkL51M5QEcvFICJn/n9LE9p8C5vacVBbteSD+Z0RjqBbL3pJcDHgXOpD/4Q+IWLw8xUFmhLdxgbc9a3ZOJn//gTX3D8qxq4/XdqNOLGVUApsBi75TvbhfOrLNHQHaYmXPbbA0tqDn7TP2LCd8Xr066E/kqZ1CITHeNiBYcDL1Mf/Bb1Qf39HIb0mzrM2K3bGxf7R1a/5A0EZ7pdT74Z1RXfWiG4/UeqGPg/4HHt6x1+NHSHkbEfqp9SPPnAV/0j9vu2tm4H5/CBTf3NtOOAV6kPftTtQlT6aOgOE+M+/KOPl1TPWeErH6mrTg3B2fFwNkYtDEQVcCf1wWuoD+ob38OAhm6eC4RqfeMv+sXvS2oOvs1THKhwu5585o2nwkdIIiN3ukiDLwIPUx8c6XYhamg0dPNYcMEFY6qOu/jpkomzPyMer34vh6imI9bqye2F2E8EXqA+OMftQtTg6S9qnhp1yucPq5h/1itFo6cscLuW4WJhT9jtEvpjGvAc9cGz3C5EDY6Gbp4JhGpl1ClXfqhs9nGP+SpGTXC7nuHkvFQ0Xy7dK4D7qQ9+z+1C1MBp6OaRQKjWWzLloK+XzTnhFk9JmfbfplFpT2LbZI9V5nYdAyDAj6kP/lnH8+YX/WbliUCo1l8ydf5Pyg8+9SeeotJsLA1YUA7siHa5XcMgfQq4XUc25A8N3TwQCNWWlIYW/LrioA9+w+MrLna7nuHo1Gi4yO0ahuBjwN3UB/P5ORQMDd0cFwjVlgVmH/v78rknXiFev7ZmMiFlkqfj6tTfdDgPuI/6oP5RznEaujksEKqtLJtzwi1ls4+9qNDvV5ZJYzpjW8tEhsMftEXAP6gPBtwuRO2Zhm6OCoRqR5WGFtwYmHnkeSKenB48mu8WdEfibteQRicD/6I+mGsz65RDQzcHBUK1o4qr51xTPvfEczVwM+/seGS4jQQ5FrhX31zLTRq6OSYQqi0vGjvtp5XzzzxfPF79pckwbyzVU+tJ5sv43IE4FbjB7SLU7jR0c0ggVFvsGzHhe5W1510oviJ9QyQLpnVEW92uIYMu1wkUuUdDN0cEQrU+b9nILwUXfPiznqJAPg3Sz2vHhyPDvfvmx9QHL3K7CPU+Dd0cEAjVeqQocHHwyI9+0xuorHK7noJhDOemIqPcLiML/kR98AS3i1A2vQW7ywKhWgHODh71sZ8Xjw/NcLueXGesFBtv+SreMhOb8YOynbpgOpd1svm+zYgIeGG/j+9H2f5lJDuTvHfte6TCKcadN47K+ZUArP35u/E3TpGiCRUF0fboAI6ivuN1twspdAXx05bjjgnMOvobGrj90/Xig/hH9X0Hm7IDypjx4xnM+PEMqi+rZv1N6wHoaOyg6qgqpn1vGi3/agGg8+VOakZ7wwUSuABB7DG8eiXlsoL5ictFgVBtjX9MzVfLZh93uNu15INkZwuR1S9QftAH+9zuLfHarVzAilk7PscLJmEwSQMeMClD66Ot1B1RlEu35smGqcDNbhdR6DR0XRII1ZZLcdlXKw8/b6F4vHo/s35oe+wPVC289P0w7UPnS52srFvJml+vYeJlEwGoWlBF14oumn/ZzNhzxrLt8W1UHRFMneOP5fvU38E4m/rg190uopBp6LogEKr1AJcEF1xwprekXC/3+iG86nk8ZVUUj997L0zl/Er2X7w/k780mc33bQbAG/BS87UaZtTPoHRKKZ2vdDJjRsmWL/4z6r3gnjDPrU1m4ynkjBZT+dEZdQ/o1ZVLNHTdcXLZ3BMvKho9ZarbheSL2Po3iDQ1su6GS9n64FXE1q4tXvv7tXvcv2xmGfEtcZJdOwfqlge2MPbMsZQsaS2aP8HLTWeX8p3HY5kuPydYxpj744c/e1js+nlJfHfW1DUMt5l4eUFnPGVZIFS7v3/s1M8HQkfMc7uWfDLiuE8x4rhPARB971U6lv4xNumzO49eiG2OUTS2CBEh0hzBJA3e8vfXCYptipFoT1A2q4xZL20q9RTbK4FHC6Ch2xmX8JWdl8qS8pOOdL40DbgOuNjFsgqShm4WBUK1VXi8X6icf9YC8Xh01bA02Pb4NgBGnjCSzhc7aX+mHfEKUiRMunLSTv2/m/+2mXHnj8MXTXV/5yBv+Tl3Rbi6Mc6PFg7vyX8vdVRuu9zzw2Bb+bhdf+Y+WVPX8FDz4kV3u1JYgdJxulnijMf9UsW8My4snTrvULfryXfifW5T+f4PjB/MY2du7nnvr+HWyemuKdekLJO6pqW2++rKrwT3stsWYFbz4kVt2aqr0GlLN3sO94+adHzJlIMPcbuQQndSODzcp/7SGvV0f7rnc/5llUftLXABxgI/A67IQlkKfSMtKwKh2irg4opDzz5UuxVcZow5x4qO7v2lSx+IMPbnXcy9vnvH17ZFDCff1kPo2m5Ovq2HtkjfV4TtUcMF94SZdV03s3/bvWMkxLf/HeUDN3Tzyb9Hdux72/I4Vy/N/Jt2T7eN3rYwcW1gWdlR/e03+UxNXUNtRotSO2joZpjTrfDxsgOOn+MrHznR7XoKXXl3omW8x+x0Y89PHezn4Qt3vtnC4iUxTpzqo+mL5Zw41cfiJX2H5ZcfjnLqDB9vfaGc5VeUMXuMl46o4dl1KV79XDkpY1ixOUUkYbh5eYIrD8vcbcwSKZI/3LKw86LSa0Z2+UcM5HdbgN/V1DVogyALNHQzb64nEDwuEFpwmNuFKDi4M9qz69eOneJjZOnOPQ4PvJ3k4oPsOSsXH+Tn/rd3H+LQGTM8tSbJZYfY+xV5haoSwSMQTxmMMUQS4PfCz5+N86XDi/B7M9OzsTHi6zyr81vWnys/UznIQxwMfDGdNam+aehmUCBUWwpcUjnvzNni8+tt03PAoli4pD/7be622M9Zl2G/Cg9beqzd9lndZjEmIFzyQJRDft/N5Q9G6IkbKoqF82f7OeT3PUyt8hAsFl7YkOLsWZmZePhQa/W2hdb1FW+WHjzUZvSPauoa9GoswzR0M+s038iJk/1jp851uxAFkrQSJ5nY2HQdL2nBso0WnzvUz8ufLafMLzu6Ib51VDGvXFHOL08p4fv/jfGjhcXcuCzOh+8N85On0tOvG0sS/8bWRd1Xll01MuYtT0cTugL4VRqOo/ZCQzdDAqHascAZFQedOlv2tliAyprxnfEtJR7p18/8uHIPG7vs1u3GLouxZbs/rLpSqK4UaqvtQUAXHOBj2aadW8Qvb0wBsP8oD7cuT3DPhwK8tiVFU2tqSM/l3Z7ijlO6fyB/rfhEum9A+eGaugaduJNBGrqZc2bRuOlVvhETDnC7EGU7qjvc77lnZ+3v45blCQBuWZ7g7Jm7j64cX+5hUtDD2y12gD72bpIDRu/8K/X9/8b40fHFJCxIOQMgPALhxOCegzGGu1pmtJ0sN1Q2l8zM1EJJP8zQcRUauhkRCNVWA8eUH3jygdrIzR3nJCJ9jln92N/CHPGnHt5utaj+VRd/Whan7ugi/r06Sejabv69Oknd0fboqw1dFqffEd7x2GtPK+ET90X4wA3dvLLJ4jvHvD9K6/63Ehw2wcuECg9VJcIR1V4OvKEbETho/MAHCvQkiF7R8tGeuvIfjUh6SjL5g3VGTV2DvvGbITojLQMCodovFlfPOTFYe/7ZbtcyXA10Rpo/mupctnH9YN/Zd92bXYG2S6zvV2wqnpKtCU3/al686PQsnaugaEs3zQKh2mnA/PI5J2i/WA4JdUTa3a5hMCxjzI1b57af7vvdiCwGLsBpNXUNC7J4voKh04DTyJkIcUHJ1HmjvOUj+r6njHLFyeFI3jUwdqwMVnGSW2su1wOnunTuYSvvfhBz3CxgTmBG7Wy3C1G9WMactcvU31z3UkfltuNivypeUn6Sm+O7T6mpazjCxfMPSxq6abK9lesfNcnjrRg93e161PsquhMtYz2mX5Mi3JayTOrXWw/vOL/4dyPb/LstxeiGb7ldwHCjoZs+U4BpgdnH7q8jFnLLvM7IblN/c1Fr1NP9obYvJq6u2OtSjNl2hs5SSy8N3fQ5QYpKraLRUw5yuxC1szPikZyfgv1U2+htxyWvDSwrOzLXWuQ+4HK3ixhONHTTIBCqDQJHlh2wcIJ4fcP7NgR5RhJW7ARy966/21cG+2TpNSO7fQNaGSybLtcVyNInV7/J+WYB4CmZOFvvCJFjJnTGWoqkf1N/sy0NK4NlSzWwyO0ihouc/GHMJ4FQrQ84vWTqvICnpDyv3iEvBEf3RHLytpNpXBksW/TOEmmioTt0c4HK0ppD5rhdiNrduYmIW2Nc+5SBlcGy5ZSauoYpbhcxHGjoDt1p4iuK+ILj9ne7ELWzokiyY44nlTMjATK4Mlg2eIBPu13EcKChOwSBUO0YIFQ67bCR4vXly2Viwdi/I5oTU3/tlcGmZ3plsGz4iNsFDAcaukMzF6B4wkydgZaDPhiJuP6O+/srg/040yuDZcOMmroGHRI5RLr2wtAci9ff5asaP9PtQtQuLGOdbSJjcDHmdqwMVjEl18beDsX5wHK3i8hn2tIdpECodjRQE5h+6Bgdm5t7gl2JlpGCK98Xe2WwA91YGSwbzne7gHynoTt4cwBTtN9MvTNEDprfFYm4cd7OuIQ/2XpZ9CcV/6/KyHDLWwAOqKlrmOZ2EflMQ3fwjsXj6/ZX7addCznozHg4kO1z5sjKYNmgEyWGQEN3EAKh2pHAtJJJcyvE5x9O/XXDgidhRY8jnrWJKinLpH6VWyuDZZqG7hBo6A6O3bUwbnqN24Wo3U3siLX4s7TUW4uzMtg1ubUyWKYtrKlrGO6t+YzR0B2c+UCPr2p8jduFqN0d0xO29r3X0D3VNnrbwtxcGSzTigFdZ2SQNHQHyFlrYbb4irq9ZVXVbtejdnd+MrNTfxMpkj/cenyurwyWaXpHiUEalm+vZthEwFc8cfY48Xj19csxxeFk+/4eK2OhuzHi67wk+rWStyoOzvWVwTJNb1o5SIX6V3oopgPiH1OjN57MQbM6Ix2ZOnaDszLYW/mzMlgmaegOkobuwB0I9PiC47RrIQedEomk/eojliT+9a1ndH8+/1YGy6T9dNWxwdHL4wEIhGo9wEygzVumt1jPOZaxzrKiY9LZlHi3p7jjkkRdoLliZj6uDJZpC4A1bheRb7SlOzBjgGJv5Zhij7+4zO1i1M5GdMW3Bj2k5dLfXhlsxnBYGSyT9M20QdCW7sBUA/hHVo9yuxC1u0PTNPW3J0H0a+0fTT1ScfaIdBxvGDvc7QLykYbuwEwCjK9yrIZuDjorFikb6rXbMF0ZLFN0CvwgaPfCwEwGwt7ykXovtBzjiVuRo2XwU38tY8wfh+/KYJkysqauoZBm4qWF/nANzCQg7A1Uaks3x0zuiLb6RAY1oqQjLuHPd14qSypOyqn7qeWJ6cAyt4vIJ9rS7adAqNYPjAJinpJyDd0cc1xPZFBTf1/qCLYtLIyVwTJFl3kcIG3p9t8owOD1iRSV6hssOebcVGTEQJoQKcukrm5d0H1NxZf1ezk0090uIN9o6PbfKMD4R04aIeLRK4QcUhJOtk33WP0Oz5aop/szPVf6llUcqf2RQ6ct3QHS0O2/0YDXVzFKf1FzzAEdkU6gX6H7VNvobVf6f1jVXVawC9Wkm7Z0B0hDt/8mAzFPcZn25+aYUyMR/75uQJlIkfzpthPCN1dcPjI7VRWMqW4XkG80dPtvLBCVolIdv5lLUiZ1BtExe9tFVwbLKG2EDJBeYvVfBZD0+Ev0Xe5cYFk+gFFd8a0Vwh6n6erKYBmna1IMkIZu/5UDSSnS0M0JxioCOLwrEu1rs64MljXemrqGrN8ENJ9p90L/lQEt4ivW7oVcYOyW7tnxcPmuTQddGSzrKoCw20XkC23p9kMgVOsFSoCU+Iq0pZsDxBiPJ54KHyGJHVN/dWUw1+gftwHQlm7/lAAWgPiKtKWbAzwiqZqO2DaPSAB0ZTCXVbhdQD7R0O2fHUErXq++IZMDPCKphT1hA7oyWA7Q0B0A7V7on1LAAPY1rHKd4I2fk4qO0JXBcoKG7gDoD2r/7GjdGmMGtbCKSq+qRND3vZ5P+Z6pOEl/4d3ndbuAfKKh2z/vB62Gbk7Y7J9btdk/1+0ylC3hdgH5RLsX+kdDV6k909AdAA3d/ukVulbKxTqUykUaugOgods/O0JX+3SV2k2fswJV3zR0++f91q2xNHSV2lm32wXkEw3d/tHuBaX2TEN3ADR0++f97oVEVOeYK7UzDd0B0NDtnxTYy2Rb8UiPy7UolUtSQIfbReQTDd3+CeO8VlYsrKGr1Ps2NC9epF1uA6Ch2w/hpsY4EAe8VrRbQ1ep973ndvCrz/MAABLdSURBVAH5RkO3/zoBf6pnW6fbhSiVQzR0B0hDt//agKJkxxbtv1LqfRq6A6Sh239bgeJUV0uPsXTYmFIODd0B0tDtv01AMYBJRLW1q5RNQ3eANHT7rwXn9UpFura6XItSuUJDd4A0dPuvA2eSRKq7dbPLtSiVCwzwrttF5BsN3f5rwZkgkezYvMnlWpTKBU3Nixd1uV1EvtHQ7b8W7Nk33sTWZg1dpeBFtwvIRxq6/RRuarSw+6/KEq1r20wqGXO7JqVcpqE7CBq6A9MElANYkU7t11WFTkN3EDR0B6YZ575yqZ427WJQBctZzH+Z23XkIw3dgdmEM4Ih2blVQ1cVLBF5q3nxIl2HZBA0dAdmM/ZrJrENb69xuxilXKRdC4OkoTsA4abGKLAFKE20rNlmxSPtbteklEuWul1AvtLQHbjlQBVAsmPzOy7XopRb/uV2AflKQ3fgXsN5My2+5V0NXVVwjDFvNi9e1Ox2HflKQ3fgVjv/SnTN8neNMcbVapTKMhFpcLuGfKahO0DhpsYe7PnmlVakM2qFO9a7XZNSWaahOwQauoPzPBAESLRt0C4GVTCMMR3AErfryGcauoOzEnuFJeIb317lci1KZY2IPNq8eFHS7TrymYbu4KwFEoAv+t6KdVY8oouaq0LxkNsF5DsN3UEINzUmgVeBEQCJljUr3K1IqcwzxiTR/twh09AdvOeAAED4nReXu1yLUtnwcPPiRXrXlCHS0B28N4AY4E9sWd2SCndscLsgpTJJRG5xu4bhQEN3kMJNjTHgGWA0QHxTk7Z21bBljNUB/MPtOoYDDd2hWQr4AcJNS18zxrJcrkepDJE7mhcv0oX700BDd2jeAdqBQKp7WzjZsbXJ7YKUygQR+b3bNQwXGrpD4NzC53FgFEBs3euvuFuRUulnrNSLzYsXvep2HcOFhu7QvYjzOoZXPvO2FQu3uVyPUmklHu/1btcwnGjoDt1m7EVwRmCMia1/s9HtgpRKF2OlWoA73a5jONHQHaJwU6MB/glUAnS/8cTLJpWIuluVUukiVzUvXqQ/z2mkoZseK3DeUDOxnnh882q9lYnKe8ZKdYrHo10LaaahmwbOtOB/AGMAul/7z1JjpXRREJXfrNRv9OaT6aehmz5LsWeoFaW6WnviW5tfcrsgpQbLWKke8RX9yu06hiMN3TQJNzWGsRcDGQ/Q89pjzxrLSrlblVKDZKV+27x4ka6elwEauun1JJAE/Mn2TZ3xLatfcLsgpQbKWFZUfEVXuV3HcKWhm0bhpsZO4FGc1m7Xsn8+aZLxiLtVKTUwJpW4oXnxola36xiuNHTT7z9ACii2Ip3RyJpX/+t2QUr1l0kmtnn8xf/jdh3DmejNbNMvEKo9BfgosAaP1zPqtC9f4S0pH+N2XQPR+cL9dC9/FAT8Y2oYffpX6Fh6L93LH8ETCAIw4thPUjr9sN0e2/LQb4i88wLeQJAJl70/4qjtiT8TWf0SRWOnMvqMrwPQ/drjWNEuKg89OztPTO1VKtzx2bXXfPwPbtcxnGlLNzOeALYBFVgpK/z2kkdcrmdAkl0tdL70D8Zf/Gs7NC2LnjefAqDi0HOYcMm1TLjk2j4DF6D8wJMY+6Ef7vQ1K9ZDbP2bTLj0OoyxiG9txkrE6HntP1Qcsijjz0ntmxXteV0DN/M0dDPAWWv3dpy1diOrnn8n2bElv25gaaUwyTjGSmGSMbzlI/v90JJJc/GWVuzyVcGkkhhjMMk44vHS+fx9VMw/C/H60lu7GjBjLGOs1MVu11EINHQz5xXgTWAsQNerjz6SL+vt+ipGU3n4uay/4RLWXXcRUhygdOo8ALqW/ZMNN32Blod+Qyra3e9jeooDBGYeycabv4QvOA4pLiO+cSWB0IJMPQ01AFak6+6113xMx5ZngYZuhjhrMtwJlAKexJbVLfGNK591uax+SUW7CTc1MvGKP1H9+VsxiRjdr/+XikNOZ+Jn/8h+l1yDt3wkbY/fOKDjBmsvYMIl1zLyhMvpePp2qo65kK7lj7D1/sW0P3tXhp6N2heTTPSIv+RKt+soFBq6GRRualyDPXZ3P4DO5//+RCrSudndqvYt2vwKvuA4vIEg4vUR2P8IYuvfxFs2AvF4EfFQcdApxDeuHNTx45vfAcA3YiI9rz3OmHPqSGxdQ2Lb+nQ+DdVPVrT7u+/98jxdkjRLNHQz734gAQRMKpHqWtZwX67PVPNVjiG+4W2sRBRjDNE1y/GPmkSye9uOfcIrn8M/esqgjt/+9O0Ej/4EWEkwTo+LeDBJvRtMtqV62pauve7Cq92uo5Bo6GZYuKmxHbgJGAdIfFPTltja155wt6q9K54wk8DMo9h481fYeNPnwRgqDjqV9if+zIY/fZ4NN32B6HuvMuLETwOQ7Gpl870/2PH4rQ9exabbvkFi23rW/fZiupY/umNbeOVzFI0P4asYhaeknOIJs9jwp8+DQNHYaVl/roXMikd7kh1bLnC7jkKj43SzIBCqFeAzwGHAOkRk1Ae/cIm3fMQkl0tTBcoYQ3zjyks33vq1P7tdS6HRlm4WOG+q/QUIAxUYYzpffODvxkomXC5NFahk24Z/aOC6Q0M3S8JNjV3AH7DH7noSre+1RVYvy6tJE2p4SEU6N8c3rfqY23UUKg3dLAo3Nb6GvTZDNUD38odfSrSuW+FuVaqQmFQylWhZ+5GtD16li5O7REM3+/4KtAIjANqfuePBVLhjg7slqUIR39r8i013fOtJt+soZBq6WRZuaowA1wPlQIlJxJIdz959l5WI9X96l1KDEN/a/ETHM3/5jtt1FDoNXReEmxrfBf4ITAC8yY5NXV0vP3R3ro/fVfkr2bHlva6X/3VeuKkxL6aiD2cauu5pxL6Z5WSA2NoV6yKrlv7T3ZLUcJSKdHX0rHzmzK5l/9RZZzlAQ9clzjCy+4CX2f7G2or/vBLbtGqpq4WpYcVKRKPht5Z8su2xG191uxZl09B1UbipMYXdzdCCswxkx7N3PZrs2Dy4RQ2U6sWkkqnwW0v+p/WR6x50uxb1Pg1dl4WbGnuAqwE/UI6xTNuTN9+b7Gp91+XSVB4zlmXCq5b+Lrzy2V+6XYvamYZuDgg3NW4ErsFu7ZaYRCzZ9uTNd6V62nXZLTVgxlgm/PaSO3pee/xr+sZZ7tHQzRHhpsbXgd9iLwNZbGI98banbrk9Fenc5HJpKo8YY1k9bzxxf88bT1wZbmqMu12P2p2Gbg4JNzW+gL0i2UTAb4U7om1P3HyrBq/qD2Msq+f1Jx4Mv7XkcmfaucpBGro5JtzU+CRwBzAJ8Fvh9kj7k7fcmg+Lnyv37Ajct5dcFm5q3LbvRyi3aOjmpkeBu7CD15fqaYu0P3nLLametnUu16VykAZuftH1dHOUswbv6cBHgPeApPiLfVXHfPI8/4j9ZrtbncoVJpVM9rzxxIPhlc9+WgM3P2jo5jAneE8FPgZsAKKISPDIj32wePwMvY1ugbPikXDXS/+4J7bhra9r4OYPDd08EAjVLgA+C2wDugAq5p1RW1JzyCkiIq4Wp1yR6mlr7Xjunr8kOzbXa+DmFw3dPBEI1c4CvgrEsZeGJDDrmNlls489Tzxen6vFqaxKtK5d2/7cPTeYWM+14aZGXZ0uz2jo5pFAqHYi8DWgDNgEUDzpwOqKQ07/iMdfXO5qcSorou+teL3zxQeuwlh3hpsa9XZPeUhDN88EQrUjgK9gL5KzFsBbMaosuODD5/oqx0x3tTiVMcZKJXveevr58JtP/QB4zFkwSeUhDd08FAjVBrDvLnwIdvAmASoOPfuokskHniDi0aGAw0gq3NHS+cL9TyRa1vwo3NSot3fKcxq6eSoQqvUBpwHnY7/B1glOd8PBp57vKSqtcrM+NXTGGGIb3nqt68UHHjfJ+C/CTY1r3a5JDZ2Gbp4LhGpnAp/D7uddD+AprSwJHvGRs3Q8b/6yErGe7uUPL42uWX4/cGu4qbHT7ZpUemjoDgOBUG0QuAS7u2E99ggHyg86dX7p1Hkni9dX7GZ9amAS2za829F47xIr3HEj8LT23w4vGrrDRCBU6wFOwp5I0Qm0AXgrx5ZXzj/zVP/IiXPcrE/tm0klouGVzy3reeOJfwO/d5b8VMOMhu4wEwjVTsXubhiNPYstCVA6/fDpZbOPPd1THBjpZn2qb/GtzW90vvjgCivcfi/woA4HG740dIehQKi2BHvdhjOAKLAFQPzFvop5Zx5dPGHW0eLxeN2sUdlSka6t3a8++mJs3etvY7du33K7JpVZGrrDmDOZ4iJgNrAZCAP4x9SMqjj49NN9laOnuVlfITPJeDi8+sUXe157fDXG+ifwULipMeJ2XSrzNHSHOaev93Ds8C3G7nKwAEqnHzYtsP+RJ3oDwQkullhQjJVKxjeteqVrWUOTFeteAdwWbmrUJTsLiIZugQiEaiuA84DjsVu8W3Zsm3n0rNIZhx3vLakY61Z9w51JJePxzauWdS1/tNkKt2/CXqh+md7DrPBo6BaYQKh2GnABMAd7lEPrjm0zj55VOv3Q47yllePdqm+4MalENLZh5QvdKx5dY0W6osADwH/CTY1Rt2tT7tDQLUDOOr0zgQ8D07DDd8fygKWhI0KlU+cd6asYVeNOhfnPJOPh6Pq3Xuhe8ehaEwtHgEeAx8NNjW1u16bcpaFbwJz+3gOwux2mYa/Vu6Pl6x8zdVQgtGB+0Ziag8XnL3WpzLyS6mlfH9vw1oqeN5/cYhKxCNAAPKkzytR2Grpqe8t3Fnb4hoAE9miHJNhDzQL7H3VASfWcQ73lIya5V2luMsl4OL51zfLwqsY3E1tWC/YwvQeBJbrerdqVhm4OEZFTgasBL3CjMWZxNs/vhO9k4FjgGMCPPbNtRyutaNyMMaWh2vn+kRMP8PhLKrJZXy4xxphU59ZV0bWvLQ83LW3HSvqwX6sG4Fkd/qX2REM3R4iIF1gJnAysA14APmaMecONegKh2jLstRxOAyZgr+ewBUht36e4es6E4uoDZvlHVc8shJEPxkomkp2tqxMtzU2R1S9tTHW1+LFfj6XA00CTjkZQ+6KhmyNE5Aig3hhzivP//wdgjPnZLvudCXwPKMLuf/2EMWaziNRjt1KnOf/+xhhzjfOYrwGXOoe40Rjzm/7W5bR+pwLHAUdit8JjzrmT2/fzj5o8oqTmoFn+0VNmestGTB4u926zYuG2RPvGpvimppXR5lc2m2S8Cvs1WAs8CryiXQhqIDR0c4SIXACcaoy53Pn/RUCtMeYLu+w3Amg3xhgRuRyYbYz5uhO6H8Qeh1sBvA2MBz4A3AwsAARoBC40xrw80Bqd1u/+2JMt5gE+7JZeK3YQA+AJBEuKJ8yq9o+aNMlXObbaW1Y1MV9WOrMS0a5Ud9u6ZPum96JrX1uV2PpuCvv1BGgHnsV+Ddfp6l9qMPSGhrmjr5ZhX7/U1cDdIrIfdmv33V7bGowxMSAmIluAccDRwN+NMT0AInIfdn/tgEM33NTY4zzu5UCotgi7VX0wdgt4e/dCtxXu6IysalwVWdW4CuekReOmjykaO63aN2K/am/5yImeorJRbq//YCWiXVa4c1Oqe9umRPvGjfFNTeuT7ZuiwCjs/uwAdpfP/cBbwCYNWjVUGrq5Yx3Qe2RANfaU3V1dC/zKGPOgiCwE6ntti/X6PIX9/c3IZX64qTGOHURvBUK192DXfgAwF3sEhNc5dxxjOuObVm2Jb1q1BVgGgHjEP3JilW/EhFG+itEjPaWVVZ6S8ipPcSAoRaVB8fpKh3rbIZOMh614tMOKhzusWE+HFenqSIXbO1Ld2zqSbRvbUt2tUezF3yudequAHuzW7CvAKucPjVJpo6GbO14AQiIyFXsh8o8CH+9jv6CzHeDifhz3KeBmEVmMHYLnYq/DkDbOm0drnI9/BUK1XuyujWrsSRhzsPuZLcADJDFWONG6NpxoXbvHyQLiK/J6SsqLPUWBIikOFHuKSovEX1Is/uIiAFLJpEnGkyaVSJhk3P48EUtYyXjSinRGTSK6vc/ZD5Rgrz1Rih2wI7GvJNYCzwHvYP/ha9HWrMokDd0cYYxJisgXsGcueYGbjDGv97FrPXCviKzHftd86j6Ou0xEbgaed75042D6cwci3NSYwv7DsB67/5NAqLYcmIi9zm81dst4InY4W9gBKNihDGCZZDyV6t6WTLEthd2KDzv7eZ39dv0owu4SMM4xxfnoAVqwxx5vwA7aTcDWcFPjjjcDlcoGfSNNuSoQqvVjX95XYbfit7dIA9iX/oFeH6Vs77KwP2LOR+/Pu7HHy3Zs/3C6QpTKCRq6SimVRUN6o0IppdTAaOgqpVQWaegqpVQWaegqpVQWaegqpVQWaegqpVQWaegqpVQWaegqpVQWaegqpVQWaegqpVQWaegqpVQWaegqpVQWaegqpVQWaegqpVQW/X/WAubQcS6aYQAAAABJRU5ErkJggg==\n", "text/plain": [ "
" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "# chama a função que imprime o gráfico de pizza\n", "graficoPizza(novaPopulacao(anos = 1), titulo = \"População de coelhos após 1 ano\") " ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Qual será o comportamento da população daqui a 10 anos? Bom, para esse fim, vamos fazer a mesma ideia de multiplicação entre matrizes, mas a cada ano posterior, devemos considerar a matriz população do ano anterior, de forma recursiva." ] }, { "cell_type": "code", "execution_count": 10, "metadata": {}, "outputs": [ { "data": { "image/png": "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\n", "text/plain": [ "
" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "# chama a função que imprime o gráfico de pizza\n", "graficoPizza(novaPopulacao(anos = 10), titulo = \"População de coelhos após 10 anos\") " ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Daqui a 100 anos, teremos uma outra população de coelhos:\n" ] }, { "cell_type": "code", "execution_count": 11, "metadata": {}, "outputs": [ { "data": { "image/png": "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\n", "text/plain": [ "
" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "# chama a função que imprime o gráfico de pizza\n", "graficoPizza(novaPopulacao(anos = 100), titulo = \"População de coelhos após 100 anos\") " ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Após um certo período de tempo, em particular quando o mesmo tende ao infinito, é fácil perceber que os vetores-estado que indicam a razão ou porcentagem de indivíduos para cada idade de coelhos em um certo tempo, convergem a um vetor fixo à medida que o número de observações cresce, e isso é bem definido na teoria de Cadeias de Markov." ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Agora vamos pegar os autovalores e autovetores do matriz L e observar algo importante." ] }, { "cell_type": "code", "execution_count": 12, "metadata": {}, "outputs": [], "source": [ "#determinando autovalores e autovetores\n", "autovalores,autovetores = numpy.linalg.eig(L) " ] }, { "cell_type": "code", "execution_count": 13, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "[ 2. -0.99999998 -1.00000002]\n" ] } ], "source": [ "# imprimindo os autovalores\n", "print(\"{}\".format(autovalores))" ] }, { "cell_type": "code", "execution_count": 14, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "[[-0.96836405 0.87287156 -0.87287156]\n", " [-0.24209101 -0.43643579 0.43643578]\n", " [-0.06052275 0.2182179 -0.21821788]]\n" ] } ], "source": [ "# imprimindo os autovetores\n", "print(\"{}\".format(autovetores))" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Vamos analisar o autovetor relacionado ao autovalor 2:" ] }, { "cell_type": "code", "execution_count": 15, "metadata": {}, "outputs": [], "source": [ "# deletando o autovetor associado ao -1, que não nos importa\n", "autovetores = numpy.delete(autovetores,1,axis=1)\n", "autovetores = numpy.delete(autovetores,1,axis=1)" ] }, { "cell_type": "code", "execution_count": 16, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "array([[15.99999841],\n", " [ 3.9999996 ],\n", " [ 0.9999999 ]])" ] }, "execution_count": 16, "metadata": {}, "output_type": "execute_result" } ], "source": [ "# multiplicando por um escalar para melhor visualização\n", "-16.52271 * autovetores" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Isso indica que a cada ano a população dobrará (autovalor = 2) obedecendo a razão 16:4:1 para 0 ano, 1 ano e 2 anos de idade dos coelhos, respectivamente (autovetor associado ao autovalor 2)." ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Agora, vamos observar melhor um outro estilo de gráfico que mostra a relação ao longo dos anos." ] }, { "cell_type": "code", "execution_count": 17, "metadata": {}, "outputs": [], "source": [ "# definindo a função que imprime um outro estilo de gráfico, mais abrangente\n", "def grafico(anos, titulo):\n", " \n", " # definindo a matriz L\n", " L = numpy.array([[0,6,8], [0.5,0,0], [0,0.5,0]]) \n", " \n", " # quantidade inicial de indivíduos com 0, 1 e 2 anos de idade, respectivamente\n", " p = numpy.array([25, 10, 5]) \n", " \n", " # tempo de anos decorridos (nesse caso serão 2 ANOS decorridos, subtraia 1 do números de anos)\n", " N = anos + 1 \n", "\n", " # inicializa uma matriz de zeros com as linhas indicando os anos decorridos e colunas a \n", " # população etária de coelhos\n", " pn = numpy.zeros((N, len(p)))\n", " # adiciona a população inicial a matriz\n", " pn[0,:] = p.copy()\n", "\n", " # estrutura de repetição, que inicia um ano após a população inicial até o ano final especificado\n", " for i in range(1,N):\n", " # adiciona a cada linha subsequente a mudança de estado da população par cada faixa etária dos \n", " # coelhos, entre as colunas\n", " pn[i,:] = L.dot(pn[i-1,:]) \n", "\n", " # define a dimensão do gráfico\n", " plt.figure(figsize=(10,5))\n", " # plota o gráfico da primeira coluna, responsável pelo avanço da população de coelhos com 0 ano \n", " # de idade\n", " plt.plot(pn[:,0],)\n", " # plota o gráfico da segunda coluna, responsável pelo avanço da população de coelhos com 1 ano \n", " # de idade\n", " plt.plot(pn[:,1],)\n", " # plota o gráfico da terceira coluna, responsável pelo avanço da população de coelhos com 2 ano\n", " # de idade\n", " plt.plot(pn[:,2],)\n", " # título do eixo x\n", " plt.xlabel('Anos')\n", " # título do gráfico\n", " plt.title(titulo);\n", " \n", " # indica que a função não retorna nenhum tipo de dado, é do tipo void\n", " return None" ] }, { "cell_type": "code", "execution_count": 18, "metadata": {}, "outputs": [ { "data": { "image/png": "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\n", "text/plain": [ "
" ] }, "metadata": { "needs_background": "light" }, "output_type": "display_data" } ], "source": [ "# chama a função que plota o gráfico\n", "grafico(anos = 2, titulo = \"População de coelhos após 2 anos\") " ] }, { "cell_type": "code", "execution_count": 19, "metadata": {}, "outputs": [ { "data": { "image/png": "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\n", "text/plain": [ "
" ] }, "metadata": { "needs_background": "light" }, "output_type": "display_data" } ], "source": [ "# chama a função que plota o gráfico\n", "grafico(anos = 5, titulo = \"População de coelhos após 5 anos\")" ] }, { "cell_type": "code", "execution_count": 20, "metadata": {}, "outputs": [ { "data": { "image/png": "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\n", "text/plain": [ "
" ] }, "metadata": { "needs_background": "light" }, "output_type": "display_data" } ], "source": [ "# chama a função que plota o gráfico\n", "grafico(anos = 10, titulo = \"População de coelhos após 10 anos\")" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Vejam que a razão entre faixas etárias de coelhos, após vários anos, começou a manter uma proporção constante, dado que o sistema não sofreu nenhum tipo de desequilíbrio externo. Portanto, Álgebra Linear é uma disciplina extremamente eficiente para resolver problemas reais, por esse motivo, ela revolucionou e vem revolucionando o mundo ao nosso redor, suas aplicações nos trouxeram comodidade por estar presente em inúmeras tecnologias do dia a dia e, saber trabalhar com ela, nos permite uma melhor compreensão de inúmeros problemas na engenharia e nos torna diferenciados como profissionais." ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "### Alguma Dúvida? Entre em Contato Comigo:" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "- [Me envie um e-mail](mailto:alysson.barbosa@ee.ufcg.edu.br);" ] } ], "metadata": { "kernelspec": { "display_name": "Python 3", "language": "python", "name": "python3" }, "language_info": { "codemirror_mode": { "name": "ipython", "version": 3 }, "file_extension": ".py", "mimetype": "text/x-python", "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", "version": "3.7.4" } }, "nbformat": 4, "nbformat_minor": 4 }