diagrama.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Diagramación de una Chacra para Forestería Análoga"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### © Equipo I+D SomosAZUCAR - Bajo licencia AGPLv3\n",
    "\n",
    "```\n",
    "Diagramador de Planos para Forestería Análoga\n",
    "Copyright (C) 2015 Sebastian Silva\n",
    "\n",
    "This program is free software: you can redistribute it and/or modify\n",
    "it under the terms of the GNU Affero General Public License as published by\n",
    "the Free Software Foundation, either version 3 of the License, or\n",
    "(at your option) any later version.\n",
    "\n",
    "This program is distributed in the hope that it will be useful,\n",
    "but WITHOUT ANY WARRANTY; without even the implied warranty of\n",
    "MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the\n",
    "GNU Affero General Public License for more details.\n",
    "\n",
    "You should have received a copy of the GNU Affero General Public License\n",
    "along with this program.  If not, see <http://www.gnu.org/licenses/>.\n",
    "```"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "El software a continuación toma una selección de especies con una población propuesta e intenta ubicarla en un terreno según ciertas reglas."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "# Bibliotecas utilizadas para confeccionar el mapa\n",
    "%matplotlib inline\n",
    "import matplotlib.pyplot as plt\n",
    "from descartes import PolygonPatch\n",
    "import matplotlib.cm as cmx\n",
    "import matplotlib.colors as colors\n",
    "import matplotlib.colorbar as colorbar\n",
    "from shapely import geometry\n",
    "from shapely import ops\n",
    "import numpy as np\n",
    "import pandas as pd\n",
    "import random\n",
    "import mpld3\n",
    "from tqdm import tqdm\n",
    "\n",
    "import time\n",
    "\n",
    "# Para realizar un video\n",
    "from moviepy import editor as mpy\n",
    "from moviepy.video.io.bindings import mplfig_to_npimage\n",
    "\n",
    "from copy import deepcopy\n",
    "\n",
    "# Emular Python3 (tuvimos que revertir a Python2 por MoviePy)\n",
    "from __future__ import (absolute_import, division,\n",
    "                        print_function, unicode_literals)\n",
    "import six\n",
    "\n",
    "# Activar extensión vega para diagramar en línea:\n",
    "# jupyter nbextension install --py vega --user\n",
    "# jupyter nbextension enable vega --user --py\n",
    "plt.ioff()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 1.- BASE DE DATOS DE CULTIVOS DE BAJÍO AMAZÓNICO\n",
    "### © Arbio - licencia por definir"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "La base de datos consiste en una lista de especies, cantidades, diámetro, y características."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Usos</th>\n",
       "      <th>Nombre</th>\n",
       "      <th>Sp</th>\n",
       "      <th>Copa</th>\n",
       "      <th>Altura</th>\n",
       "      <th>Bajio</th>\n",
       "      <th>Enredadera</th>\n",
       "      <th>Productividad</th>\n",
       "      <th>Estrato</th>\n",
       "      <th>N</th>\n",
       "      <th>...</th>\n",
       "      <th>C11</th>\n",
       "      <th>C12</th>\n",
       "      <th>Sombra</th>\n",
       "      <th>Distancia</th>\n",
       "      <th>Diametro.dosel</th>\n",
       "      <th>Altura.tot</th>\n",
       "      <th>T1a.produccion</th>\n",
       "      <th>Trecambio</th>\n",
       "      <th>pond</th>\n",
       "      <th>ind</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>38</th>\n",
       "      <td>Medicinal</td>\n",
       "      <td>Huasai brasilero / palmito</td>\n",
       "      <td>sp11</td>\n",
       "      <td>19.6</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>24.45</td>\n",
       "      <td>4</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0.60</td>\n",
       "      <td>5</td>\n",
       "      <td>5</td>\n",
       "      <td>30</td>\n",
       "      <td>60</td>\n",
       "      <td>20.0</td>\n",
       "      <td>0.21</td>\n",
       "      <td>4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>34</th>\n",
       "      <td>Medicinal</td>\n",
       "      <td>Coco</td>\n",
       "      <td>sp11</td>\n",
       "      <td>19.6</td>\n",
       "      <td>False</td>\n",
       "      <td>True</td>\n",
       "      <td>False</td>\n",
       "      <td>1.68</td>\n",
       "      <td>4</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0.00</td>\n",
       "      <td>10</td>\n",
       "      <td>5</td>\n",
       "      <td>30</td>\n",
       "      <td>60</td>\n",
       "      <td>50.0</td>\n",
       "      <td>0.01</td>\n",
       "      <td>4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>35</th>\n",
       "      <td>Medicinal</td>\n",
       "      <td>Copaiba</td>\n",
       "      <td>sp11</td>\n",
       "      <td>113.1</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>9.55</td>\n",
       "      <td>5</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "      <td>0.50</td>\n",
       "      <td>8</td>\n",
       "      <td>12</td>\n",
       "      <td>28</td>\n",
       "      <td>96</td>\n",
       "      <td>30.0</td>\n",
       "      <td>0.08</td>\n",
       "      <td>4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>43</th>\n",
       "      <td>Medicinal</td>\n",
       "      <td>Pan de arbol</td>\n",
       "      <td>sp11</td>\n",
       "      <td>78.5</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>12.10</td>\n",
       "      <td>4</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "      <td>0.50</td>\n",
       "      <td>10</td>\n",
       "      <td>10</td>\n",
       "      <td>26</td>\n",
       "      <td>90</td>\n",
       "      <td>25.0</td>\n",
       "      <td>0.10</td>\n",
       "      <td>4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>27</th>\n",
       "      <td>Medicinal</td>\n",
       "      <td>Aguaje</td>\n",
       "      <td>sp11</td>\n",
       "      <td>28.3</td>\n",
       "      <td>False</td>\n",
       "      <td>True</td>\n",
       "      <td>False</td>\n",
       "      <td>21.22</td>\n",
       "      <td>4</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "      <td>0.00</td>\n",
       "      <td>18</td>\n",
       "      <td>6</td>\n",
       "      <td>25</td>\n",
       "      <td>90</td>\n",
       "      <td>45.0</td>\n",
       "      <td>0.18</td>\n",
       "      <td>4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>50</th>\n",
       "      <td>Medicinal</td>\n",
       "      <td>Sangre grado</td>\n",
       "      <td>sp11</td>\n",
       "      <td>38.5</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>5.26</td>\n",
       "      <td>5</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0.70</td>\n",
       "      <td>7</td>\n",
       "      <td>7</td>\n",
       "      <td>24</td>\n",
       "      <td>90</td>\n",
       "      <td>18.0</td>\n",
       "      <td>0.05</td>\n",
       "      <td>4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>51</th>\n",
       "      <td>Medicinal</td>\n",
       "      <td>Sapote</td>\n",
       "      <td>sp11</td>\n",
       "      <td>113.1</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>7.37</td>\n",
       "      <td>4</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0.65</td>\n",
       "      <td>12</td>\n",
       "      <td>12</td>\n",
       "      <td>20</td>\n",
       "      <td>102</td>\n",
       "      <td>18.0</td>\n",
       "      <td>0.06</td>\n",
       "      <td>4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>45</th>\n",
       "      <td>Medicinal</td>\n",
       "      <td>Pijuayo</td>\n",
       "      <td>sp11</td>\n",
       "      <td>19.6</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>3.82</td>\n",
       "      <td>4</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0.00</td>\n",
       "      <td>6</td>\n",
       "      <td>5</td>\n",
       "      <td>20</td>\n",
       "      <td>42</td>\n",
       "      <td>20.0</td>\n",
       "      <td>0.03</td>\n",
       "      <td>4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>40</th>\n",
       "      <td>Medicinal</td>\n",
       "      <td>Mango</td>\n",
       "      <td>sp11</td>\n",
       "      <td>78.5</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>19.10</td>\n",
       "      <td>4</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "      <td>0.40</td>\n",
       "      <td>11</td>\n",
       "      <td>10</td>\n",
       "      <td>20</td>\n",
       "      <td>96</td>\n",
       "      <td>20.0</td>\n",
       "      <td>0.16</td>\n",
       "      <td>4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>52</th>\n",
       "      <td>Medicinal</td>\n",
       "      <td>Shimbillo</td>\n",
       "      <td>sp11</td>\n",
       "      <td>28.3</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>3.09</td>\n",
       "      <td>3</td>\n",
       "      <td>1</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0.00</td>\n",
       "      <td>5</td>\n",
       "      <td>6</td>\n",
       "      <td>16</td>\n",
       "      <td>54</td>\n",
       "      <td>15.0</td>\n",
       "      <td>0.03</td>\n",
       "      <td>7</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>42</th>\n",
       "      <td>Medicinal</td>\n",
       "      <td>Pacae</td>\n",
       "      <td>sp11</td>\n",
       "      <td>28.3</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>3.98</td>\n",
       "      <td>3</td>\n",
       "      <td>1</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0.00</td>\n",
       "      <td>6</td>\n",
       "      <td>6</td>\n",
       "      <td>13</td>\n",
       "      <td>48</td>\n",
       "      <td>15.0</td>\n",
       "      <td>0.03</td>\n",
       "      <td>7</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>48</th>\n",
       "      <td>Medicinal</td>\n",
       "      <td>Pomarrosa</td>\n",
       "      <td>sp11</td>\n",
       "      <td>28.3</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>14.85</td>\n",
       "      <td>3</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0.00</td>\n",
       "      <td>10</td>\n",
       "      <td>6</td>\n",
       "      <td>10</td>\n",
       "      <td>48</td>\n",
       "      <td>25.0</td>\n",
       "      <td>0.13</td>\n",
       "      <td>7</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>32</th>\n",
       "      <td>Medicinal</td>\n",
       "      <td>Carambola</td>\n",
       "      <td>sp11</td>\n",
       "      <td>19.6</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>8.96</td>\n",
       "      <td>3</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>2</td>\n",
       "      <td>1</td>\n",
       "      <td>0.00</td>\n",
       "      <td>7</td>\n",
       "      <td>5</td>\n",
       "      <td>10</td>\n",
       "      <td>42</td>\n",
       "      <td>20.0</td>\n",
       "      <td>0.08</td>\n",
       "      <td>7</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>44</th>\n",
       "      <td>Medicinal</td>\n",
       "      <td>Papaya</td>\n",
       "      <td>sp11</td>\n",
       "      <td>3.1</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>11.46</td>\n",
       "      <td>2</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0.00</td>\n",
       "      <td>6</td>\n",
       "      <td>2</td>\n",
       "      <td>9</td>\n",
       "      <td>9</td>\n",
       "      <td>3.0</td>\n",
       "      <td>0.10</td>\n",
       "      <td>22</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>29</th>\n",
       "      <td>Medicinal</td>\n",
       "      <td>Anona</td>\n",
       "      <td>sp11</td>\n",
       "      <td>28.3</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>1.70</td>\n",
       "      <td>3</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0.00</td>\n",
       "      <td>5</td>\n",
       "      <td>6</td>\n",
       "      <td>8</td>\n",
       "      <td>60</td>\n",
       "      <td>20.0</td>\n",
       "      <td>0.01</td>\n",
       "      <td>7</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>30</th>\n",
       "      <td>Medicinal</td>\n",
       "      <td>Cacao</td>\n",
       "      <td>sp11</td>\n",
       "      <td>28.3</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>0.25</td>\n",
       "      <td>3</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0.65</td>\n",
       "      <td>4</td>\n",
       "      <td>6</td>\n",
       "      <td>8</td>\n",
       "      <td>60</td>\n",
       "      <td>11.0</td>\n",
       "      <td>0.00</td>\n",
       "      <td>7</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>36</th>\n",
       "      <td>Medicinal</td>\n",
       "      <td>Copoazú</td>\n",
       "      <td>sp11</td>\n",
       "      <td>38.5</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>2.99</td>\n",
       "      <td>3</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0.50</td>\n",
       "      <td>7</td>\n",
       "      <td>7</td>\n",
       "      <td>6</td>\n",
       "      <td>42</td>\n",
       "      <td>10.0</td>\n",
       "      <td>0.03</td>\n",
       "      <td>7</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>47</th>\n",
       "      <td>Medicinal</td>\n",
       "      <td>Platano</td>\n",
       "      <td>sp11</td>\n",
       "      <td>3.1</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>3.44</td>\n",
       "      <td>2</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "      <td>0.60</td>\n",
       "      <td>3</td>\n",
       "      <td>2</td>\n",
       "      <td>6</td>\n",
       "      <td>9</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.03</td>\n",
       "      <td>22</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>31</th>\n",
       "      <td>Medicinal</td>\n",
       "      <td>Camu camu</td>\n",
       "      <td>sp11</td>\n",
       "      <td>7.1</td>\n",
       "      <td>False</td>\n",
       "      <td>True</td>\n",
       "      <td>False</td>\n",
       "      <td>58.36</td>\n",
       "      <td>2</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0.00</td>\n",
       "      <td>5</td>\n",
       "      <td>3</td>\n",
       "      <td>6</td>\n",
       "      <td>36</td>\n",
       "      <td>15.0</td>\n",
       "      <td>0.50</td>\n",
       "      <td>22</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>49</th>\n",
       "      <td>Medicinal</td>\n",
       "      <td>Pomelo</td>\n",
       "      <td>sp11</td>\n",
       "      <td>19.6</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>7.16</td>\n",
       "      <td>3</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0.00</td>\n",
       "      <td>8</td>\n",
       "      <td>5</td>\n",
       "      <td>5</td>\n",
       "      <td>48</td>\n",
       "      <td>20.0</td>\n",
       "      <td>0.06</td>\n",
       "      <td>7</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>39</th>\n",
       "      <td>Medicinal</td>\n",
       "      <td>Limón</td>\n",
       "      <td>sp11</td>\n",
       "      <td>19.6</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>5.60</td>\n",
       "      <td>2</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "      <td>0.50</td>\n",
       "      <td>5</td>\n",
       "      <td>5</td>\n",
       "      <td>5</td>\n",
       "      <td>48</td>\n",
       "      <td>15.0</td>\n",
       "      <td>0.05</td>\n",
       "      <td>22</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>37</th>\n",
       "      <td>Medicinal</td>\n",
       "      <td>Frijol palo</td>\n",
       "      <td>sp11</td>\n",
       "      <td>1.4</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>11.88</td>\n",
       "      <td>2</td>\n",
       "      <td>1</td>\n",
       "      <td>...</td>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "      <td>0.40</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>3</td>\n",
       "      <td>24</td>\n",
       "      <td>10.0</td>\n",
       "      <td>0.10</td>\n",
       "      <td>22</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>33</th>\n",
       "      <td>Medicinal</td>\n",
       "      <td>Chacruna</td>\n",
       "      <td>sp11</td>\n",
       "      <td>3.1</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>25.46</td>\n",
       "      <td>2</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0.50</td>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "      <td>3</td>\n",
       "      <td>24</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.22</td>\n",
       "      <td>22</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>53</th>\n",
       "      <td>Medicinal</td>\n",
       "      <td>Uncucha</td>\n",
       "      <td>sp11</td>\n",
       "      <td>0.6</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>9.47</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0.60</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "      <td>11</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.08</td>\n",
       "      <td>153</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>46</th>\n",
       "      <td>Medicinal</td>\n",
       "      <td>Piña</td>\n",
       "      <td>sp11</td>\n",
       "      <td>0.9</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>9.05</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0.60</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>13</td>\n",
       "      <td>5.0</td>\n",
       "      <td>0.08</td>\n",
       "      <td>153</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>41</th>\n",
       "      <td>Medicinal</td>\n",
       "      <td>Ojito de pescado</td>\n",
       "      <td>sp11</td>\n",
       "      <td>0.8</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>19.10</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1.00</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>6</td>\n",
       "      <td>3.0</td>\n",
       "      <td>0.16</td>\n",
       "      <td>153</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>28</th>\n",
       "      <td>Medicinal</td>\n",
       "      <td>Ají dulce regional</td>\n",
       "      <td>sp11</td>\n",
       "      <td>0.8</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>7.93</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0.50</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>3</td>\n",
       "      <td>3.0</td>\n",
       "      <td>0.07</td>\n",
       "      <td>153</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>27 rows × 41 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "         Usos                      Nombre    Sp   Copa Altura  Bajio  \\\n",
       "38  Medicinal  Huasai brasilero / palmito  sp11   19.6  False  False   \n",
       "34  Medicinal                        Coco  sp11   19.6  False   True   \n",
       "35  Medicinal                     Copaiba  sp11  113.1  False  False   \n",
       "43  Medicinal                Pan de arbol  sp11   78.5  False  False   \n",
       "27  Medicinal                      Aguaje  sp11   28.3  False   True   \n",
       "50  Medicinal                Sangre grado  sp11   38.5  False  False   \n",
       "51  Medicinal                      Sapote  sp11  113.1  False  False   \n",
       "45  Medicinal                     Pijuayo  sp11   19.6  False  False   \n",
       "40  Medicinal                       Mango  sp11   78.5  False  False   \n",
       "52  Medicinal                   Shimbillo  sp11   28.3  False  False   \n",
       "42  Medicinal                       Pacae  sp11   28.3  False  False   \n",
       "48  Medicinal                   Pomarrosa  sp11   28.3  False  False   \n",
       "32  Medicinal                   Carambola  sp11   19.6  False  False   \n",
       "44  Medicinal                      Papaya  sp11    3.1  False  False   \n",
       "29  Medicinal                       Anona  sp11   28.3  False  False   \n",
       "30  Medicinal                       Cacao  sp11   28.3  False  False   \n",
       "36  Medicinal                     Copoazú  sp11   38.5  False  False   \n",
       "47  Medicinal                     Platano  sp11    3.1  False  False   \n",
       "31  Medicinal                   Camu camu  sp11    7.1  False   True   \n",
       "49  Medicinal                      Pomelo  sp11   19.6  False  False   \n",
       "39  Medicinal                       Limón  sp11   19.6  False  False   \n",
       "37  Medicinal                 Frijol palo  sp11    1.4  False  False   \n",
       "33  Medicinal                    Chacruna  sp11    3.1  False  False   \n",
       "53  Medicinal                     Uncucha  sp11    0.6  False  False   \n",
       "46  Medicinal                        Piña  sp11    0.9  False  False   \n",
       "41  Medicinal            Ojito de pescado  sp11    0.8  False  False   \n",
       "28  Medicinal          Ají dulce regional  sp11    0.8  False  False   \n",
       "\n",
       "   Enredadera  Productividad  Estrato  N ...   C11  C12  Sombra  Distancia  \\\n",
       "38      False          24.45        4  0 ...     1    1    0.60          5   \n",
       "34      False           1.68        4  0 ...     0    0    0.00         10   \n",
       "35      False           9.55        5  0 ...     2    2    0.50          8   \n",
       "43      False          12.10        4  0 ...     2    2    0.50         10   \n",
       "27      False          21.22        4  0 ...     1    2    0.00         18   \n",
       "50      False           5.26        5  0 ...     0    0    0.70          7   \n",
       "51      False           7.37        4  0 ...     0    0    0.65         12   \n",
       "45      False           3.82        4  0 ...     0    0    0.00          6   \n",
       "40      False          19.10        4  0 ...     2    2    0.40         11   \n",
       "52      False           3.09        3  1 ...     0    0    0.00          5   \n",
       "42      False           3.98        3  1 ...     0    0    0.00          6   \n",
       "48      False          14.85        3  0 ...     1    1    0.00         10   \n",
       "32      False           8.96        3  0 ...     2    1    0.00          7   \n",
       "44      False          11.46        2  0 ...     1    1    0.00          6   \n",
       "29      False           1.70        3  0 ...     1    1    0.00          5   \n",
       "30      False           0.25        3  0 ...     1    0    0.65          4   \n",
       "36      False           2.99        3  0 ...     1    1    0.50          7   \n",
       "47      False           3.44        2  0 ...     2    2    0.60          3   \n",
       "31      False          58.36        2  0 ...     1    1    0.00          5   \n",
       "49      False           7.16        3  0 ...     0    0    0.00          8   \n",
       "39      False           5.60        2  0 ...     2    2    0.50          5   \n",
       "37      False          11.88        2  1 ...     2    2    0.40          1   \n",
       "33      False          25.46        2  0 ...     1    1    0.50          1   \n",
       "53      False           9.47        1  0 ...     0    0    0.60          1   \n",
       "46      False           9.05        1  0 ...     1    0    0.60          1   \n",
       "41      False          19.10        1  0 ...     0    0    1.00          1   \n",
       "28      False           7.93        1  0 ...     0    0    0.50          1   \n",
       "\n",
       "    Diametro.dosel  Altura.tot  T1a.produccion  Trecambio  pond  ind  \n",
       "38               5          30              60       20.0  0.21    4  \n",
       "34               5          30              60       50.0  0.01    4  \n",
       "35              12          28              96       30.0  0.08    4  \n",
       "43              10          26              90       25.0  0.10    4  \n",
       "27               6          25              90       45.0  0.18    4  \n",
       "50               7          24              90       18.0  0.05    4  \n",
       "51              12          20             102       18.0  0.06    4  \n",
       "45               5          20              42       20.0  0.03    4  \n",
       "40              10          20              96       20.0  0.16    4  \n",
       "52               6          16              54       15.0  0.03    7  \n",
       "42               6          13              48       15.0  0.03    7  \n",
       "48               6          10              48       25.0  0.13    7  \n",
       "32               5          10              42       20.0  0.08    7  \n",
       "44               2           9               9        3.0  0.10   22  \n",
       "29               6           8              60       20.0  0.01    7  \n",
       "30               6           8              60       11.0  0.00    7  \n",
       "36               7           6              42       10.0  0.03    7  \n",
       "47               2           6               9        1.0  0.03   22  \n",
       "31               3           6              36       15.0  0.50   22  \n",
       "49               5           5              48       20.0  0.06    7  \n",
       "39               5           5              48       15.0  0.05   22  \n",
       "37               1           3              24       10.0  0.10   22  \n",
       "33               2           3              24        NaN  0.22   22  \n",
       "53               1           2              11        1.0  0.08  153  \n",
       "46               1           1              13        5.0  0.08  153  \n",
       "41               1           1               6        3.0  0.16  153  \n",
       "28               1           1               3        3.0  0.07  153  \n",
       "\n",
       "[27 rows x 41 columns]"
      ]
     },
     "execution_count": 2,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "especies = pd.read_csv(\"db_final.csv\") ## Es una base\n",
    "especies = especies[(especies.Usos==\"Medicinal\")]\n",
    "especies = especies[(especies.ind>0)]\n",
    "especies = especies.sort_values(by=['Altura.tot'], ascending=False)\n",
    "\n",
    "# Filtros posibles de pruebas\n",
    "#especies = especies.head(8)\n",
    "#especies = especies.tail(6)\n",
    "especies"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Obtenemos un consolidado por estrato para hacernos una idea:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>especies</th>\n",
       "      <th>individuos</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>4</td>\n",
       "      <td>612</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>6</td>\n",
       "      <td>132</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>8</td>\n",
       "      <td>56</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>7</td>\n",
       "      <td>28</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>2</td>\n",
       "      <td>8</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Total</th>\n",
       "      <td>27</td>\n",
       "      <td>836</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "       especies  individuos\n",
       "1             4         612\n",
       "2             6         132\n",
       "3             8          56\n",
       "4             7          28\n",
       "5             2           8\n",
       "Total        27         836"
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "consolidado = pd.DataFrame({'especies':especies.groupby('Estrato').size(), \n",
    "                            'individuos':especies.groupby('Estrato')['ind'].sum()})\n",
    "pd.concat([consolidado,pd.DataFrame(consolidado.sum(axis=0),columns=['Total']).T])\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 2.- Linderos de las Chacra"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Los linderos están definidos como un polígono en metros, desde la ezquina inferior izquierda."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "image/svg+xml": [
       "<svg xmlns=\"http://www.w3.org/2000/svg\" xmlns:xlink=\"http://www.w3.org/1999/xlink\" width=\"100.0\" height=\"100.44\" viewBox=\"-3.72 -3.72 72.44 100.44\" preserveAspectRatio=\"xMinYMin meet\"><g transform=\"matrix(1,0,0,-1,0,93.0)\"><path fill-rule=\"evenodd\" fill=\"#66cc99\" stroke=\"#555555\" stroke-width=\"2.0\" opacity=\"0.6\" d=\"M 0.0,0.0 L 0.0,93.0 L 55.0,93.0 L 55.0,86.0 L 35.0,65.0 L 37.5,47.5 L 55.0,44.0 L 65.0,52.5 L 65.0,0.0 L 0.0,0.0 z\" /></g></svg>"
      ],
      "text/plain": [
       "<shapely.geometry.polygon.Polygon at 0x7f4079004750>"
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "chacra = geometry.Polygon([ [0,0],\n",
    "                            [0, 93],\n",
    "                            [55, 93],\n",
    "                            [55, 86],\n",
    "                            [35, 65],\n",
    "                            [37.5, 47.5],\n",
    "                            [55, 44],\n",
    "                            [65, 52.5],\n",
    "                            [65, 0] ])\n",
    "chacra"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Corresponde a una chacra de media hectárea:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "5028.75 m²\n"
     ]
    }
   ],
   "source": [
    "print (chacra.area, \"m²\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Los puntos de esta grilla pueden posteriormente ser transformados en latitud/longitud para su ubicación con un GPS."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 3.- Definir ubicaciones"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "El algoritmo consiste en un *bucle* que escoge puntos dentro del polígono que representa una chacra.\n",
    "\n",
    "El objetivo es llegar a definir la ubicación de cada individuo de una población a partir de:\n",
    "- una superficie\n",
    "- lista de especies (incluyendo cantidad de individuos)\n",
    "\n",
    "Para ello se deben respetar algunas reglas, las cuales han sido separadas y descritas respectivamente.\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "class Poblacion:\n",
    "    def __init__(self, poligono, especies, make_frame=None):\n",
    "        self.poligono = poligono\n",
    "        self.especies = especies\n",
    "        \n",
    "        # Creamos una tabla para almacenar los individuos\n",
    "        individuos_columns = ['id', 'pos', 'x', 'y', 'color', 'Diametro.dosel', \n",
    "                              'Nombre', 'Estrato', 'Diametro.punto', 'Altura.tot']\n",
    "        self.individuos = pd.DataFrame( columns=individuos_columns, )\n",
    "        self.n_individuos = 0\n",
    "        \n",
    "        # También almacenaremos a los individuos que no pudimos ubicar (de ser el caso)\n",
    "        self.excluidos = pd.DataFrame( columns=individuos_columns, )\n",
    "        self.inubicables = 0\n",
    "        self.exclusiones = []\n",
    "        \n",
    "        colores = get_colormap(len(especies))\n",
    "        \n",
    "        i=0\n",
    "        for especie in tqdm(list(especies.itertuples())):\n",
    "            i=i+1\n",
    "            n_especie = especie[0]\n",
    "            color_especie = colores(i)\n",
    "            planta_tipo = especies.loc[n_especie]\n",
    "            for n_individuo in range(especies.ind[n_especie]):\n",
    "                self.n_individuos = self.n_individuos + 1\n",
    "                planta = planta_tipo.copy()\n",
    "                planta['id'] = n_especie\n",
    "                \n",
    "                #### Algoritmo para ubicar la planta ###\n",
    "                intentos = 10\n",
    "                while intentos:\n",
    "                    intentos = intentos - 1\n",
    "                    distancia_min = 1 # 1m\n",
    "\n",
    "                    # Ubicamos un punto aleatorio *random* dentro del polígono            \n",
    "                    (minx, miny, maxx, maxy) = self.poligono.bounds\n",
    "                    while True:\n",
    "                        p = geometry.Point(random.uniform(minx, maxx), random.uniform(miny, maxy))\n",
    "                        if poligono.contains(p):\n",
    "                            pos = p\n",
    "                            break\n",
    "\n",
    "                    planta['pos'] = pos\n",
    "                    planta['x'], planta['y'] = pos.xy\n",
    "\n",
    "                    try:\n",
    "                        regla_1(self, planta)\n",
    "                        regla_2(self, planta)\n",
    "                        regla_3(self, planta)\n",
    "                    except ValueError as e:\n",
    "                        self.exclusiones.append(str(e))\n",
    "                        self.inubicables = self.inubicables + 1\n",
    "                        planta['pos'] = None          \n",
    "                        next\n",
    "                    else:\n",
    "                        if make_frame:\n",
    "                            make_frame(self)\n",
    "                        break\n",
    "\n",
    "                \n",
    "                ########################## Fin Algoritmo Ubicación\n",
    "                \n",
    "                if planta['pos']:\n",
    "                    planta['color'] = color_especie\n",
    "                    planta['Diametro.dosel'] = float(planta['Diametro.dosel'])\n",
    "                    planta['Diametro.punto'] = float(planta['Diametro.dosel']*10)\n",
    "                    self.individuos.loc[self.n_individuos] = planta\n",
    "                else:\n",
    "                    self.excluidos.loc[self.inubicables] = planta\n",
    "                self.individuos = self.individuos.dropna()\n",
    "        \n",
    "        self.individuos = self.individuos.sort_values(by=['Altura.tot'], ascending=False)\n",
    "\n",
    "        if self.inubicables:\n",
    "            print (\"No se pudieron ubicar \" + str(self.inubicables) + \" individuos.\")\n",
    "            #self.inubicables = pd.DataFrame(self.inubicables)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "El algoritmo que *ubica* las plantas, lo hace iterando por la lista de especies, desde las más altas a las más pequeñas, probando en orden una lista de reglas que deben cumplirse siempre:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "def regla_1(poblacion, planta):\n",
    "    if planta.Estrato < 3:\n",
    "        if planta.pos.distance(poblacion.poligono.exterior) < planta['Altura.tot'] * 0.3:        \n",
    "            raise ValueError('regla1')\n",
    "    else:\n",
    "        if planta.pos.distance(poblacion.poligono.exterior) < planta['Altura.tot'] * 0.3:        \n",
    "            raise ValueError('regla1')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "**Regla 1:** La la distancia de una lindero mínimo un 65% de su altura total máxima, o 30% para plantas de estratos 1 y 2. "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "def regla_2(poblacion, planta):\n",
    "    for anterior in poblacion.individuos.itertuples():\n",
    "        if planta.Estrato < 3:\n",
    "            distancia_min = (planta.Distancia / 2 ) - (planta.Distancia / 2) * planta.Sombra * 2\n",
    "        else:\n",
    "            distancia_min = planta.Distancia / 2\n",
    "        if planta.pos.distance(anterior[2]) < distancia_min:\n",
    "            raise ValueError('regla2')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "**Regla 2**: La distancia entre las plantas de estratos inferiores será proporcional a la sombra que toleran."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "def regla_3(poblacion, planta):\n",
    "    mi_estrato = int(especies.Estrato[planta.id])\n",
    "    mas_cercanos = []\n",
    "    for anterior in poblacion.individuos.itertuples():\n",
    "        if not mas_cercanos:\n",
    "            mas_cercanos = [anterior]\n",
    "        for cercano in mas_cercanos:\n",
    "            if planta.pos.distance(anterior[2]) < planta.pos.distance(cercano[2]):\n",
    "                mas_cercanos.append(anterior)\n",
    "                if len(mas_cercanos) == 3:\n",
    "                    mas_cercanos.pop(0)\n",
    "                \n",
    "    for cercano in mas_cercanos:\n",
    "        if abs(especies.Estrato[int(cercano[1])] - mi_estrato) > 1:\n",
    "            raise ValueError('regla3')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "**Regla 3**: Una de las tres plantas más cercanas debe ser de un estrato adyacente, inmediatamente mayor o menor."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Proceso de Renderizado\n",
    "\n",
    "## Definir el mapa de colores para los árboles: *f(Altura)*"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Utilizamos una escala de colores para terrenos de mapas."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "def get_colormap(N):\n",
    "    color_norm  = colors.Normalize(vmin=0, vmax=N-1)\n",
    "    scalar_map = cmx.ScalarMappable(norm=color_norm, cmap='terrain') \n",
    "    def map_index_to_rgb_color(index):\n",
    "        return scalar_map.to_rgba(index)\n",
    "    return map_index_to_rgb_color\n",
    "# http://stackoverflow.com/questions/14720331/how-to-generate-random-colors-in-matplotlib"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {
    "collapsed": false,
    "scrolled": true
   },
   "outputs": [],
   "source": [
    "class Figure:\n",
    "    def __init__(self, poblacion=None):\n",
    "        self.colores = None\n",
    "        self.poligono = None\n",
    "        self.fig = plt.figure(figsize=(7, 7))\n",
    "\n",
    "        self.ax = self.fig.add_subplot(111)\n",
    "        self.ax.set_ylim(-10,100)\n",
    "        self.ax.set_xlim(-20,90)\n",
    "\n",
    "        self.ax.grid(color='gray', alpha=0.9)\n",
    "        \n",
    "        if poblacion:\n",
    "            self.plot_poblacion(poblacion)\n",
    "            \n",
    "        # Barra de colores\n",
    "        #       def createColourbar(lwr, upr):\n",
    "        #   \"\"\"Create a colourbar with limits of lwr and upr\"\"\"\n",
    "        #    cax, kw = colorbar.make_axes(plt.gca())\n",
    "        #    norm = colors.Normalize(vmin = lwr, vmax = upr, clip = False)\n",
    "        #    c = colorbar.ColorbarBase(cax, cmap=plt.cm.get_cmap('terrain_r'), norm=norm)\n",
    "        #    return c\n",
    "\n",
    "        #cb = createColourbar(0, len(pob.especies)-1)\n",
    "        #cb.set_label('ESPECIES', labelpad=-50, y=0.45)\n",
    "\n",
    "        #cb.set_ticks(list(reversed(range(0, len(pob.especies)-1))))\n",
    "        #cb.set_ticklabels(list(pob.especies.Nombre))\n",
    "        #try:\n",
    "        #    cb.autoscale()\n",
    "        #    self.fig.colorbar(cb)\n",
    "        #except TypeError:\n",
    "        #    pass\n",
    "        \n",
    "    def plot_poblacion(self, poblacion):        \n",
    "        colormap = cmx.ScalarMappable(\n",
    "                    colors.Normalize(1, len(especies)),\n",
    "                    plt.cm.get_cmap('terrain'))\n",
    "        \n",
    "        if not self.colores:\n",
    "            cm = plt.cm.get_cmap('terrain')\n",
    "            colores = [list(cm(x)) for x in range(len(poblacion.especies))]\n",
    "            self.colores = list(reversed(colores))\n",
    "        \n",
    "        if not self.poligono:\n",
    "            self.ax.plot( *poblacion.poligono.exterior.xy )\n",
    "\n",
    "        # Los círculos y puntos representan a cada individuo\n",
    "        circulos = []\n",
    "        colores = []\n",
    "        puntos_x = []\n",
    "        puntos_y = []\n",
    "        labels = dict()\n",
    "        for planta in poblacion.individuos.iterrows():\n",
    "            circulos.append(planta[1]['pos'].buffer(planta[1]['Diametro.dosel']))\n",
    "            colores.append(planta[1]['color'])\n",
    "            puntos_x.append(planta[1]['x'])\n",
    "            puntos_y.append(planta[1]['y'])\n",
    "            labels[planta[1]['id']]=planta[1]['Nombre']\n",
    "\n",
    "        i=0\n",
    "        for poligono in circulos:\n",
    "            patch = PolygonPatch(poligono, fc=colores[i-1], alpha=0.2, zorder=1)\n",
    "            self.ax.add_patch(patch)\n",
    "            i = i+1\n",
    "            \n",
    "        self.ax.scatter(puntos_x, \n",
    "                puntos_y, \n",
    "                c=colores,\n",
    "                s=20,\n",
    "                cmap=\"terrain\",\n",
    "                vmin=0,\n",
    "                vmax=len(poblacion.especies)-1,\n",
    "                alpha=0.6, marker=\"+\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "starttime = time.time()\n",
    "frames = {}"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "def save_frame(poblacion):\n",
    "    f = Figure(poblacion)\n",
    "    t = time.time() - starttime\n",
    "    img_array = mplfig_to_npimage(f.fig)\n",
    "    frames[t] = img_array\n",
    "    del(f)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      " 48%|████▊     | 13/27 [00:14<00:23,  1.68s/it]"
     ]
    }
   ],
   "source": [
    "# Demora unos 3 minutos\n",
    "pob = Poblacion(chacra, especies, save_frame)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "seconds = sorted(frames.keys())[-1] - sorted(frames.keys())[-0]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "def make_frame(t):\n",
    "    keyframes = sorted(frames.keys())\n",
    "    t_min = min(keyframes)\n",
    "    this_frame = frames[min(keyframes, key=lambda x:abs(x-t-t_min))]\n",
    "    return this_frame\n",
    "\n",
    "anim = mpy.VideoClip(make_frame, duration=seconds)\n",
    "\n",
    "anim.write_videofile(\"vis_algoritmo.mp4\", fps=50)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "print (\"Se ubicaron %s de %s individuos.\" % \n",
    "        ( len(pob.individuos), especies.ind.sum(axis=0)))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Se puede ver qué tantas veces una regla descartó un punto, y tomarlo como un indicador de qué tan estricta es una regla."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "exclusiones = pd.DataFrame({'regla':pob.exclusiones})\n",
    "pd.DataFrame({'causales de exclusión':exclusiones.groupby('regla').size()})"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Algunas plantas pueden haber quedado excluidas por no poder ser ubicadas satisfactoriamente.\n",
    "\n",
    "En ese caso se sugiere ajustar las reglas o la tabla de especies. Aquí se dejan algunas formas de analizar los datos generados."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "pd.DataFrame({'excluidos':pob.excluidos.groupby('Nombre').size()})"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 4.- Graficar el mapa"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "A continuación se grafica el mapa de acuerdo a las ubicaciones computadas."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "f = Figure(pob)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "#from vega import VegaLite"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "\"\"\"VegaLite({\n",
    "  \"mark\": \"point\",\n",
    "  \"encoding\": {\n",
    "    \"y\": {\"type\": \"quantitative\",\"field\": \"y\"},\n",
    "    \"x\": {\"type\": \"quantitative\",\"field\": \"x\"}\n",
    "  }\n",
    "}, pob.individuos)\"\"\""
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "# Gráfico interactivo (no funciona en github)\n",
    "# mpld3.display(fig)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": []
  }
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