{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
   ],
   "source": [
    "from scipy.cluster.hierarchy import dendrogram, linkage, fcluster\n",
    "from scipy.spatial.distance import pdist, squareform\n",
    "from matplotlib import pyplot as plt\n",
    "from geopy.distance import vincenty\n",
    "import geopy\n",
    "import numpy as np\n",
    "import pandas as pd\n",
    "\n",
    "max_d = 2 # Distancia maxima de 2km]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
   ],
   "source": [
    "def calcula_distancias(locs_1, locs_2):\n",
    "    n_linhas_1 = locs_1.shape[0]\n",
    "    n_linhas_2 = locs_2.shape[0]\n",
    "    dists = np.empty((n_linhas_1, n_linhas_2))\n",
    "    for i in range(n_linhas_1):\n",
    "        for j in range(n_linhas_2):\n",
    "            dists[i, j] = geopy.distance.vincenty(locs_1[i], locs_2[j]).km\n",
    "    return dists"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>longitude</th>\n",
       "      <th>latitude</th>\n",
       "      <th>cod_localidade_tse</th>\n",
       "      <th>nom_localidade</th>\n",
       "      <th>nom_bairro</th>\n",
       "      <th>num_local</th>\n",
       "      <th>nom_local</th>\n",
       "      <th>des_endereco</th>\n",
       "      <th>codigo</th>\n",
       "      <th>lqtd_secoes</th>\n",
       "      <th>...</th>\n",
       "      <th>indigenas</th>\n",
       "      <th>grupos</th>\n",
       "      <th>efetivo</th>\n",
       "      <th>crimes_eleitorais</th>\n",
       "      <th>boca_de_urna</th>\n",
       "      <th>roubo</th>\n",
       "      <th>furto</th>\n",
       "      <th>desacato</th>\n",
       "      <th>desobediencia</th>\n",
       "      <th>CV</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>-61.504226</td>\n",
       "      <td>-10.870787</td>\n",
       "      <td>89960</td>\n",
       "      <td>RONDOLÂNDIA</td>\n",
       "      <td>CENTRO</td>\n",
       "      <td>1015</td>\n",
       "      <td>ESCOLA ESTADUAL OLAVO BILAC</td>\n",
       "      <td>RUA MATHILDE KLEMS, S/N</td>\n",
       "      <td>61899601015</td>\n",
       "      <td>10</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>295</td>\n",
       "      <td>2.000000</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>-60.941759</td>\n",
       "      <td>-10.475339</td>\n",
       "      <td>89960</td>\n",
       "      <td>RONDOLÂNDIA</td>\n",
       "      <td>ZONA RURAL</td>\n",
       "      <td>1066</td>\n",
       "      <td>ESCOLA ZAWA KAREY PANGYJY</td>\n",
       "      <td>ALDEIA INDÍGENA ZORÓ</td>\n",
       "      <td>61899601066</td>\n",
       "      <td>1</td>\n",
       "      <td>...</td>\n",
       "      <td>267</td>\n",
       "      <td>297</td>\n",
       "      <td>2.000000</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>-60.180703</td>\n",
       "      <td>-14.107886</td>\n",
       "      <td>90867</td>\n",
       "      <td>NOVA LACERDA</td>\n",
       "      <td>GLEBA SANTA AMÉLIA</td>\n",
       "      <td>1040</td>\n",
       "      <td>ESCOLA MUNICIPAL VALE DO GUAPORÉ</td>\n",
       "      <td>COMUNIDADE SANTA AMÉLIA</td>\n",
       "      <td>61908671040</td>\n",
       "      <td>1</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>298</td>\n",
       "      <td>0.180556</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>-59.967301</td>\n",
       "      <td>-15.014093</td>\n",
       "      <td>91090</td>\n",
       "      <td>VILA BELA DA SANTÍSSIMA TRINDADE</td>\n",
       "      <td>JARDIM AEROPORTO</td>\n",
       "      <td>1341</td>\n",
       "      <td>CRECHE AVIAOZINHO</td>\n",
       "      <td>AVENIDA MARTIMIANO RIBEIRO DA FONSECA, S/N</td>\n",
       "      <td>25910901341</td>\n",
       "      <td>1</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>125</td>\n",
       "      <td>0.208700</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>13</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>-59.950224</td>\n",
       "      <td>-15.003089</td>\n",
       "      <td>91090</td>\n",
       "      <td>VILA BELA DA SANTÍSSIMA TRINDADE</td>\n",
       "      <td>CENTRO</td>\n",
       "      <td>1171</td>\n",
       "      <td>CAMARA MUNICIPAL DE VILA BELA DA SANTISSIMA TR...</td>\n",
       "      <td>AV. SÃO LUIZ, S/N, VILA BELA DA SS. TRINDADE</td>\n",
       "      <td>25910901171</td>\n",
       "      <td>2</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>125</td>\n",
       "      <td>0.600000</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>5 rows × 21 columns</p>\n",
       "</div>"
      ]
     },
     "execution_count": 3,
     "metadata": {
     },
     "output_type": "execute_result"
    }
   ],
   "source": [
    "locais = pd.read_excel('Planilha para distribuicao do efetivo.xlsx', sheet_name='dados')\n",
    "locais[:5]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
   ],
   "source": [
    "coords = locais[['longitude','latitude']].values"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([[-61.50422603, -10.87078709],\n",
       "       [-60.941759  , -10.475339  ],\n",
       "       [-60.180703  , -14.107886  ],\n",
       "       ...,\n",
       "       [-50.511945  , -10.47179925],\n",
       "       [-50.51073158, -10.46768262],\n",
       "       [-50.296635  ,  -9.994842  ]])"
      ]
     },
     "execution_count": 5,
     "metadata": {
     },
     "output_type": "execute_result"
    }
   ],
   "source": [
    "coords"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
   ],
   "source": [
    "matriz_distancias = calcula_distancias(coords, coords)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([[0.00000000e+00, 6.61801777e+01, 2.29587452e+02, ...,\n",
       "        1.22413550e+03, 1.22427559e+03, 1.24901215e+03],\n",
       "       [6.61801777e+01, 0.00000000e+00, 2.16509550e+02, ...,\n",
       "        1.16121113e+03, 1.16134618e+03, 1.18553983e+03],\n",
       "       [2.29587452e+02, 2.16509550e+02, 0.00000000e+00, ...,\n",
       "        1.10042873e+03, 1.10061520e+03, 1.13048953e+03],\n",
       "       ...,\n",
       "       [1.22413550e+03, 1.16121113e+03, 1.10042873e+03, ...,\n",
       "        0.00000000e+00, 3.21690889e-01, 4.15135648e+01],\n",
       "       [1.22427559e+03, 1.16134618e+03, 1.10061520e+03, ...,\n",
       "        3.21690889e-01, 0.00000000e+00, 4.11970411e+01],\n",
       "       [1.24901215e+03, 1.18553983e+03, 1.13048953e+03, ...,\n",
       "        4.15135648e+01, 4.11970411e+01, 0.00000000e+00]])"
      ]
     },
     "execution_count": 7,
     "metadata": {
     },
     "output_type": "execute_result"
    }
   ],
   "source": [
    "matriz_distancias"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
   ],
   "source": [
    "d = matriz_distancias.shape[0]\n",
    "\n",
    "v = d*(d - 1)/2\n",
    "C = np.empty([int(round(v,0))])\n",
    "\n",
    "ic = 0\n",
    "for i in range(d):\n",
    "    for j in range(i+1,d):\n",
    "        # print(matriz_distancias[i,j])\n",
    "        C[ic] = matriz_distancias[i,j]\n",
    "        ic  =  ic + 1"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([ 66.18017766, 229.587452  , 283.50213756, ...,   0.32169089,\n",
       "        41.5135648 ,  41.19704105])"
      ]
     },
     "execution_count": 9,
     "metadata": {
     },
     "output_type": "execute_result"
    }
   ],
   "source": [
    "C"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "image/png": 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"
     },
     "execution_count": 10,
     "metadata": {
      "image/png": {
       "height": 253,
       "width": 384
      }
     },
     "output_type": "execute_result"
    }
   ],
   "source": [
    "Z = linkage(C, 'complete')\n",
    "dn = dendrogram(Z)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
   ],
   "source": [
    "# https://docs.scipy.org/doc/scipy/reference/generated/scipy.cluster.hierarchy.linkage.html"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
   ],
   "source": [
    "grupos = fcluster(Z, max_d, criterion='distance')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
   ],
   "source": [
    "locais['GRUPOS'] = grupos"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/html": [
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       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>longitude</th>\n",
       "      <th>latitude</th>\n",
       "      <th>cod_localidade_tse</th>\n",
       "      <th>nom_localidade</th>\n",
       "      <th>nom_bairro</th>\n",
       "      <th>num_local</th>\n",
       "      <th>nom_local</th>\n",
       "      <th>des_endereco</th>\n",
       "      <th>codigo</th>\n",
       "      <th>lqtd_secoes</th>\n",
       "      <th>...</th>\n",
       "      <th>grupos</th>\n",
       "      <th>efetivo</th>\n",
       "      <th>crimes_eleitorais</th>\n",
       "      <th>boca_de_urna</th>\n",
       "      <th>roubo</th>\n",
       "      <th>furto</th>\n",
       "      <th>desacato</th>\n",
       "      <th>desobediencia</th>\n",
       "      <th>CV</th>\n",
       "      <th>GRUPOS</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>-61.504226</td>\n",
       "      <td>-10.870787</td>\n",
       "      <td>89960</td>\n",
       "      <td>RONDOLÂNDIA</td>\n",
       "      <td>CENTRO</td>\n",
       "      <td>1015</td>\n",
       "      <td>ESCOLA ESTADUAL OLAVO BILAC</td>\n",
       "      <td>RUA MATHILDE KLEMS, S/N</td>\n",
       "      <td>61899601015</td>\n",
       "      <td>10</td>\n",
       "      <td>...</td>\n",
       "      <td>295</td>\n",
       "      <td>2.000000</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
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       "      <td>2</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>336</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>-60.941759</td>\n",
       "      <td>-10.475339</td>\n",
       "      <td>89960</td>\n",
       "      <td>RONDOLÂNDIA</td>\n",
       "      <td>ZONA RURAL</td>\n",
       "      <td>1066</td>\n",
       "      <td>ESCOLA ZAWA KAREY PANGYJY</td>\n",
       "      <td>ALDEIA INDÍGENA ZORÓ</td>\n",
       "      <td>61899601066</td>\n",
       "      <td>1</td>\n",
       "      <td>...</td>\n",
       "      <td>297</td>\n",
       "      <td>2.000000</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
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       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>337</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>-60.180703</td>\n",
       "      <td>-14.107886</td>\n",
       "      <td>90867</td>\n",
       "      <td>NOVA LACERDA</td>\n",
       "      <td>GLEBA SANTA AMÉLIA</td>\n",
       "      <td>1040</td>\n",
       "      <td>ESCOLA MUNICIPAL VALE DO GUAPORÉ</td>\n",
       "      <td>COMUNIDADE SANTA AMÉLIA</td>\n",
       "      <td>61908671040</td>\n",
       "      <td>1</td>\n",
       "      <td>...</td>\n",
       "      <td>298</td>\n",
       "      <td>0.180556</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>444</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>-59.967301</td>\n",
       "      <td>-15.014093</td>\n",
       "      <td>91090</td>\n",
       "      <td>VILA BELA DA SANTÍSSIMA TRINDADE</td>\n",
       "      <td>JARDIM AEROPORTO</td>\n",
       "      <td>1341</td>\n",
       "      <td>CRECHE AVIAOZINHO</td>\n",
       "      <td>AVENIDA MARTIMIANO RIBEIRO DA FONSECA, S/N</td>\n",
       "      <td>25910901341</td>\n",
       "      <td>1</td>\n",
       "      <td>...</td>\n",
       "      <td>125</td>\n",
       "      <td>0.208700</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>13</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>440</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>-59.950224</td>\n",
       "      <td>-15.003089</td>\n",
       "      <td>91090</td>\n",
       "      <td>VILA BELA DA SANTÍSSIMA TRINDADE</td>\n",
       "      <td>CENTRO</td>\n",
       "      <td>1171</td>\n",
       "      <td>CAMARA MUNICIPAL DE VILA BELA DA SANTISSIMA TR...</td>\n",
       "      <td>AV. SÃO LUIZ, S/N, VILA BELA DA SS. TRINDADE</td>\n",
       "      <td>25910901171</td>\n",
       "      <td>2</td>\n",
       "      <td>...</td>\n",
       "      <td>125</td>\n",
       "      <td>0.600000</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>439</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>5 rows × 22 columns</p>\n",
       "</div>"
      ]
     },
     "execution_count": 14,
     "metadata": {
     },
     "output_type": "execute_result"
    }
   ],
   "source": [
    "locais[:5]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
   ],
   "source": [
    "res1 = pd.ExcelWriter('res1 VMD.xlsx')\n",
    "locais.to_excel(res1,'dados',index=False)\n",
    "res1.save()"
   ]
  }
 ],
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