SIR Real Data - United Kingdom.ipynb

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     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "import pylab as pp\n",
    "import numpy as np\n",
    "import pandas as pd \n",
    "import scipy.signal as scs\n",
    "\n",
    "from scipy import integrate, interpolate, optimize\n",
    "from scipy.integrate import odeint\n",
    "from pylab import *\n",
    "import netCDF4\n",
    "\n",
    "from bokeh.models   import ColumnDataSource, RangeTool, LinearAxis, Range1d\n",
    "from bokeh.palettes import brewer, Inferno10\n",
    "from bokeh.plotting import figure, show\n",
    "from bokeh.layouts  import column\n",
    "from bokeh.io       import output_notebook\n",
    "\n",
    "output_notebook()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Dados Reais\n",
    "\n",
    "Dados referentes a cidade de Londres entre 1944 e 1964. População de aproximadamente 2.5 milhões de habitantes na época.\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "\n",
    "# Lendo o arquivo de dados no formato 'filename.csv'  \n",
    "data = pd.read_csv(\"./PG_IMT/DadosEpidemia/UKCities/London.csv\") \n",
    "# Preview das cinco primeiras linhas\n",
    "data.head()\n",
    "\n",
    "s_array = data[[\"cases\", \"births\", \"pop\",\"time\"]].to_numpy()\n",
    "\n",
    "Id = s_array[:,0]\n",
    "Bd = s_array[:,1]     \n",
    "Sd = s_array[:,2]\n",
    "t  = s_array[:,3]\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Visualizando os dados"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "\n",
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       "\n",
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\",\"dtype\":\"float64\",\"shape\":[548]},\"y\":[180,271,423,465,523,649,624,556,420,423,488,441,268,260,163,83,60,41,48,65,82,145,122,194,237,318,450,671,1387,1617,2058,3099,3340,2965,1873,1641,1122,884,591,427,282,174,127,84,97,68,88,79,58,85,75,121,174,209,458,742,929,1027,1411,1885,2110,1764,2001,2154,1843,1427,970,726,416,218,160,160,188,224,298,436,482,468,650,796,1065,1241,1230,1012,981,1015,771,1031,1093,1196,1076,1029,828,669,372,171,84,71,113,108,188,241,305,248,477,524,851,1415,2235,2973,3144,3169,2248,1976,2128,1901,1635,1265,1154,887,476,269,171,185,157,205,231,262,333,290,612,677,983,1586,1912,2265,2761,3388,3240,2278,2058,1884,1521,1237,869,576,381,212,108,90,72,103,61,51,57,66,90,90,66,109,120,114,216,262,377,403,829,1091,1174,1275,1248,1244,836,515,308,418,592,837,1056,1593,2446,3090,4675,4610,4578,6107,7061,6637,4878,3693,2228,1752,1449,960,761,456,342,207,127,119,85,59,54,124,115,69,58,44,65,77,91,168,276,474,471,441,569,462,650,1072,1384,1319,1521,1788,1677,985,520,626,1236,2058,2241,2337,3048,3201,3701,3682,2891,3168,3456,2992,2572,1985,1464,788,650,566,498,318,217,145,117,49,46,29,22,32,43,39,32,29,10,31,23,35,62,74,89,112,160,143,119,110,176,175,312,316,249,186,120,167,284,389,539,471,663,1021,1538,1795,1793,3240,5096,6038,7022,7192,5905,3025,2025,1715,1428,848,652,358,254,158,96,46,61,74,61,66,51,33,37,52,42,77,110,130,122,151,197,174,372,565,599,654,634,650,483,431,276,183,240,336,388,452,580,787,835,1472,1362,2324,3453,4101,3866,3731,3783,3420,2038,1964,1820,1336,771,474,378,238,113,56,43,51,46,66,68,84,58,66,57,120,242,320,372,415,725,577,785,1145,1049,990,1020,1076,779,504,317,194,242,362,543,633,785,1194,1283,2534,1984,2740,2961,2779,2747,2748,2348,1370,1357,1360,1157,809,652,377,250,203,111,61,46,61,41,41,35,42,41,36,33,73,81,155,190,169,151,208,199,187,283,256,235,270,286,247,141,100,134,285,444,589,702,899,1347,2300,2397,3560,6001,6742,6018,5030,5248,3211,1929,1600,1279,860,651,395,335,212,179,96,75,84,81,91,73,69,39,50,58,78,92,136,174,258,251,249,240,151,120,141,140,196,267,229,185,154,170,360,457,742,812,1250,1716,2003,1923,1778,2240,2371,2073,2215,2462,2782,1858,1385,1438,1450,1048,928,841,414,252,117,63,75,70,94,84,103,68,55,75,95,149,139,191,291,264,225,257,354,468,491,657,693,935,755,447,329,292,326,485,615,1008,1242,1505,666]},\"selected\":{\"id\":\"1113\"},\"selection_policy\":{\"id\":\"1112\"}},\"id\":\"1084\",\"type\":\"ColumnDataSource\"},{\"attributes\":{\"axis_label\":\"Data\",\"formatter\":{\"id\":\"1096\"},\"ticker\":{\"id\":\"1012\"}},\"id\":\"1011\",\"type\":\"LinearAxis\"}],\"root_ids\":[\"1089\"]},\"title\":\"Bokeh Application\",\"version\":\"2.0.1\"}};\n",
       "  var render_items = [{\"docid\":\"ca6a9b2c-8403-4da9-bbee-c7ffca02422e\",\"root_ids\":[\"1089\"],\"roots\":{\"1089\":\"e4823db0-429d-49b2-95e8-92d543a058ba\"}}];\n",
       "  root.Bokeh.embed.embed_items_notebook(docs_json, render_items);\n",
       "\n",
       "  }\n",
       "  if (root.Bokeh !== undefined) {\n",
       "    embed_document(root);\n",
       "  } else {\n",
       "    var attempts = 0;\n",
       "    var timer = setInterval(function(root) {\n",
       "      if (root.Bokeh !== undefined) {\n",
       "        clearInterval(timer);\n",
       "        embed_document(root);\n",
       "      } else {\n",
       "        attempts++;\n",
       "        if (attempts > 100) {\n",
       "          clearInterval(timer);\n",
       "          console.log(\"Bokeh: ERROR: Unable to run BokehJS code because BokehJS library is missing\");\n",
       "        }\n",
       "      }\n",
       "    }, 10, root)\n",
       "  }\n",
       "})(window);"
      ],
      "application/vnd.bokehjs_exec.v0+json": ""
     },
     "metadata": {
      "application/vnd.bokehjs_exec.v0+json": {
       "id": "1089"
      }
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "\n",
    "TOOLS=\"zoom_in,zoom_out,save\"\n",
    "p1 = figure(tools=TOOLS, plot_width=600, plot_height=300)\n",
    "p2 = figure(tools=TOOLS, plot_width=600, plot_height=300)\n",
    "p3 = figure(tools=TOOLS, plot_width=600, plot_height=300)\n",
    "\n",
    "p1.line(data[\"time\"], data[\"births\"], line_width=4, color=\"#8e44ad\", line_alpha=0.9)\n",
    "    \n",
    "p1.grid.grid_line_alpha = 0\n",
    "p1.ygrid.band_fill_color = \"olive\"\n",
    "p1.ygrid.band_fill_alpha = 0.1\n",
    "p1.yaxis.axis_label = \"Nascimentos\"\n",
    "p1.xaxis.axis_label = \"Data\"\n",
    "\n",
    "p2.line(data[\"time\"], data[\"pop\"], line_width=4, color=\"#8e44ad\", line_alpha=0.9)\n",
    "    \n",
    "p2.grid.grid_line_alpha = 0\n",
    "p2.ygrid.band_fill_color = \"olive\"\n",
    "p2.ygrid.band_fill_alpha = 0.1\n",
    "p2.yaxis.axis_label = \"População\"\n",
    "p2.xaxis.axis_label = \"Data\"\n",
    "\n",
    "p3.line(data[\"time\"], data[\"cases\"], line_width=4, color=\"#8e44ad\", line_alpha=0.9)\n",
    "    \n",
    "p3.grid.grid_line_alpha = 0\n",
    "p3.ygrid.band_fill_color = \"olive\"\n",
    "p3.ygrid.band_fill_alpha = 0.1\n",
    "p3.yaxis.axis_label = \"Casos\"\n",
    "p3.xaxis.axis_label = \"Data\"\n",
    "\n",
    "show(column(p1,p2,p3))\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Selecionando um ano específico para análise"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "\n",
       "\n",
       "\n",
       "\n",
       "\n",
       "\n",
       "  <div class=\"bk-root\" id=\"57b7b75a-86d9-445f-993c-8858bea9da43\" data-root-id=\"1258\"></div>\n"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "application/javascript": [
       "(function(root) {\n",
       "  function embed_document(root) {\n",
       "    \n",
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       "          console.log(\"Bokeh: ERROR: Unable to run BokehJS code because BokehJS library is missing\");\n",
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     "output_type": "display_data"
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   ],
   "source": [
    "\n",
    "selected_year = 1948\n",
    "\n",
    "is_1948 = (data['time'].astype(int) == selected_year)\n",
    "LD48 = data[is_1948]\n",
    "LD48.head()\n",
    "\n",
    "p = figure(tools=TOOLS, plot_width=600, plot_height=300)\n",
    "p.line(LD48[\"time\"], LD48[\"cases\"], line_width=4, color=\"#8e44ad\", line_alpha=0.9)\n",
    "    \n",
    "p.grid.grid_line_alpha = 0\n",
    "p.ygrid.band_fill_color = \"olive\"\n",
    "p.ygrid.band_fill_alpha = 0.1\n",
    "p.yaxis.axis_label = \"Casos\"\n",
    "p.xaxis.axis_label = \"Data\"\n",
    "\n",
    "show(p)\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Os dados\n",
    "\n",
    "Conhecemos o número de casos, os nascimentos e a população total. Podemos determinar os demais valores a partir da relação $S(t)+I(t)+R(t)=N$ onde **N** vamos considerar a população."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [],
   "source": [
    "\n",
    "s_array = LD48[[\"cases\", \"births\", \"pop\",\"time\"]].to_numpy()\n",
    "\n",
    "Id = s_array[:,0]\n",
    "Bd = s_array[:,1]\n",
    "Sd = s_array[:,2] - Id + Bd \n",
    "t  = s_array[:,3]\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# O problema\n",
    "\n",
    "O conjunto de equações diferenciais que caracteriza o modelo é descrito abaixo. No modelo $\\beta$ - _representa a taxa de transmissão ou taxa efetiva de contato_ e $r$ - _a taxa de remoção ou recuperação_. \n",
    "\n",
    "\n",
    "$$ \\begin{align}\n",
    "   \\frac{dS(t)}{dt} & = -\\beta S(t) I(t) \\\\\n",
    "   \\frac{dI(t)}{dt} & = \\beta S(t) I(t) - rI(t)  \\\\\n",
    "   \\frac{dR(t)}{dt} & = r I(t)\n",
    "   \\end{align}$$\n",
    "\n",
    "   Gostaríamos de identificar quais parâmetros $\\beta$ e $r$ resultam num melhor ajuste do modelo para os dados de **S**, **I** e **R**"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [],
   "source": [
    "\n",
    "def SIRmodel(y, t, Beta, r):\n",
    "    S, I = y\n",
    "    Sdot = -Beta * S * I\n",
    "    Idot = Beta * S * I  - r * I\n",
    "    return Sdot, Idot  \n",
    "\n",
    "# Resolução da simulação - Escala temporal (dias)\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Obtendo $y_s(\\theta,k) = [S \\; I \\: R]$\n",
    "\n",
    "O trecho a seguir retorna os valores sintetizados $y_s(\\theta,k) = [S \\; I \\: R]$ representa o dado sintetizado a partir de um modelo sintetizado para uma determinada amostra $k$ e $\\theta$ representa o vetor ed parâmetros $\\theta = [ \\beta \\; \\; r]^T$. A partir de uma condição inicial $y_0$.\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [],
   "source": [
    "\n",
    "def SIRsim(y0, t, theta):\n",
    "    Beta, r = theta[0], theta[1]\n",
    "    ret = integrate.odeint(SIRmodel, y0, t, args=(Beta,r))\n",
    "    S, I = ret.T\n",
    "    return S, I\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Condições inicias - $y_0$ e $\\theta_0$"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [],
   "source": [
    "\n",
    "# Valores iniciais \n",
    "I0 = Id[0] \n",
    "S0 = Sd[0]\n",
    "\n",
    "# Vetor de condições iniciais\n",
    "\n",
    "y0 = S0, I0\n",
    "\n",
    "# Beta -  taxa de contato\n",
    "# r - taxa média de recuperação (in 1/dia).\n",
    "\n",
    "# theta = [Beta, r]\n",
    "theta0 = [1e-8, 1e-1] # valores iniciais\n",
    "\n",
    "# Definição do conjunto de equações diferencias não lineares que formam o modelo.\n",
    "t = (t - 1948) * 365\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Estimação de parâmetros\n",
    "\n",
    "Para estimarmos os parâmetros do modelo $\\mathbf{\\beta}$ e $\\mathbf{r}$, vamos utilizar  inicialmente o método de mínimos quadrados. Podemos então formular o problema a partir da Equação abaixo. Na Equação $y_m(k)$ representa o dado real em cada amostra $k$; $y_s(\\theta,k)$ representa o **valor estimado** a partir da simulação do modelo para uma determinada amostra $k$ e $\\theta$ representa o vetor ed parâmetros $\\theta = [ \\beta \\; \\; r]^T$. \n",
    "\n",
    "$$ min_{\\theta}= \\sum_{k=1}^{K}\\left(y_m(k) - y_s(\\theta,k) \\right)^2 $$\n",
    "\n",
    "A equação formula a pergunta: quais os valores de $beta$ e $r$ que minizam o erro quadrático quando comparados com os dados reais."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [],
   "source": [
    "\n",
    "def ErroQuadratico(Sd,Id,y0,t,theta0,w):\n",
    "    \"\"\" function to pass to optimize.leastsq\n",
    "        The routine will square and sum the values returned by \n",
    "        this function\"\"\" \n",
    "    [S,I] = SIRsim(y0,t,theta0)\n",
    "    erroS = w[0] * (S - Sd)\n",
    "    erroI = w[1] * (I - Id)\n",
    "    EQ = np.concatenate([erroS,erroI])\n",
    "    if sum(np.isnan(EQ)) >= 1:\n",
    "        print(\"Error!!!\")\n",
    "    return EQ\n",
    "\n",
    "def objetivo(p, S, I, y0, t, w):\n",
    "    return ErroQuadratico(S,I,y0,t,p,w)\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Minimização da função custo"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[2.10765916e-08 6.83427510e-02]\n"
     ]
    }
   ],
   "source": [
    "\n",
    "# Criação das ponderações dos erros\n",
    "wS = max(Id) / max(Sd)\n",
    "w = [wS, 1]\n",
    "\n",
    "(c,kvg) = optimize.leastsq(objetivo, theta0, args=(Sd, Id, y0, t, w)) \n",
    "print(c)\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Visualização"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [
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dados\"},\"renderers\":[{\"id\":\"1394\"}]},\"id\":\"1403\",\"type\":\"LegendItem\"},{\"attributes\":{},\"id\":\"1432\",\"type\":\"Selection\"},{\"attributes\":{},\"id\":\"1496\",\"type\":\"UnionRenderers\"},{\"attributes\":{},\"id\":\"1416\",\"type\":\"Selection\"},{\"attributes\":{\"text\":\"\"},\"id\":\"1396\",\"type\":\"Title\"},{\"attributes\":{\"active_drag\":\"auto\",\"active_inspect\":\"auto\",\"active_multi\":null,\"active_scroll\":\"auto\",\"active_tap\":\"auto\",\"tools\":[{\"id\":\"1384\"},{\"id\":\"1385\"},{\"id\":\"1386\"}]},\"id\":\"1387\",\"type\":\"Toolbar\"},{\"attributes\":{\"data\":{\"x\":{\"__ndarray__\":\"ABBplGT67z+AuK9KvvotQEBeCybr+jxAIHBfkzt8RUAgMbmTAXtMQBB5CcrjvFFAYHA2ykY8VUDgUGPKqbtYQGAxkMoMO1xA4BG9ym+6X0CYBHVl6ZxhQKiLi+WaXGNA6PuhZUwcZUAobLjl/dtmQPDxzGWvm2hAMGLj5WBbakBw0vllEhtsQLBCEObD2m1A8LImZnWab0AAnR5zE61wQCDVKTPsjHFAQA0188RsckBgRUCznUxzQIB9S3N2LHRAVLtWM08MdUDc/mHzJ+x1QPw2bbMAzHZA\",\"dtype\":\"float64\",\"shape\":[27]},\"y\":{\"__ndarray__\":\"TBPYwixZSUEjJEybxl9JQfs0wHPUZUlB0kU0zGtrSUGrVqgkg3BJQYJnHH3DdUlBOntgeKh5SUGPOy/gMXxJQeT7/UeUgElBOrzML7KDSUGOfJsX/IVJQc48an8DiUlBJP04Zx6MSUF5vQdPbY9JQc591rY6kklBIz6lHlaVSUFj/nOGuZhJQbi+Qu62m0lBDn8R1n2eSUFjP+C9DKFJQaP/rqWwo0lB+L99jS6mSUFNgEx1t6hJQaNAG909q0lB+ADqRLCtSUE4wbisW7BJQY2Bh5RQsklB\",\"dtype\":\"float64\",\"shape\":[27]}},\"selected\":{\"id\":\"1416\"},\"selection_policy\":{\"id\":\"1415\"}},\"id\":\"1391\",\"type\":\"ColumnDataSource\"},{\"attributes\":{\"fill_alpha\":{\"value\":0.1},\"fill_color\":{\"value\":\"#de425b\"},\"line_alpha\":{\"value\":0.1},\"line_color\":{\"value\":\"#1f77b4\"},\"size\":{\"units\":\"screen\",\"value\":8},\"x\":{\"field\":\"x\"},\"y\":{\"field\":\"y\"}},\"id\":\"1406\",\"type\":\"Scatter\"},{\"attributes\":{\"data_source\":{\"id\":\"1434\"},\"glyph\":{\"id\":\"1435\"},\"hover_glyph\":null,\"muted_glyph\":null,\"nonselection_glyph\":{\"id\":\"1436\"},\"selection_glyph\":null,\"view\":{\"id\":\"1438\"}},\"id\":\"1437\",\"type\":\"GlyphRenderer\"},{\"attributes\":{\"label\":{\"value\":\"Infectados - dados\"},\"renderers\":[{\"id\":\"1407\"}]},\"id\":\"1417\",\"type\":\"LegendItem\"},{\"attributes\":{},\"id\":\"1449\",\"type\":\"UnionRenderers\"},{\"attributes\":{\"axis_label\":\"Dias\",\"formatter\":{\"id\":\"1398\"},\"ticker\":{\"id\":\"1377\"}},\"id\":\"1376\",\"type\":\"LinearAxis\"},{\"attributes\":{},\"id\":\"1386\",\"type\":\"SaveTool\"},{\"attributes\":{},\"id\":\"1368\",\"type\":\"DataRange1d\"},{\"attributes\":{\"line_alpha\":0.9,\"line_cap\":\"round\",\"line_color\":\"#f9bd3d\",\"line_width\":4,\"x\":{\"field\":\"x\"},\"y\":{\"field\":\"y\"}},\"id\":\"1419\",\"type\":\"Line\"}],\"root_ids\":[\"1367\"]},\"title\":\"Bokeh Application\",\"version\":\"2.0.1\"}};\n",
       "  var render_items = [{\"docid\":\"15300c70-f0a8-4d8c-986c-7270fb361259\",\"root_ids\":[\"1367\"],\"roots\":{\"1367\":\"67e2b525-fb4d-40db-b274-1268f7fb7f36\"}}];\n",
       "  root.Bokeh.embed.embed_items_notebook(docs_json, render_items);\n",
       "\n",
       "  }\n",
       "  if (root.Bokeh !== undefined) {\n",
       "    embed_document(root);\n",
       "  } else {\n",
       "    var attempts = 0;\n",
       "    var timer = setInterval(function(root) {\n",
       "      if (root.Bokeh !== undefined) {\n",
       "        clearInterval(timer);\n",
       "        embed_document(root);\n",
       "      } else {\n",
       "        attempts++;\n",
       "        if (attempts > 100) {\n",
       "          clearInterval(timer);\n",
       "          console.log(\"Bokeh: ERROR: Unable to run BokehJS code because BokehJS library is missing\");\n",
       "        }\n",
       "      }\n",
       "    }, 10, root)\n",
       "  }\n",
       "})(window);"
      ],
      "application/vnd.bokehjs_exec.v0+json": ""
     },
     "metadata": {
      "application/vnd.bokehjs_exec.v0+json": {
       "id": "1367"
      }
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "\n",
    "[Sa,Ia] = SIRsim(y0,t,c)\n",
    "\n",
    "p = figure(tools=TOOLS, y_range=(0,5000), plot_width=600, plot_height=400)\n",
    "\n",
    "p.scatter(t, Sd, legend_label=\"Suscetíveis - dados\", size=8, fill_color=\"#ffd885\", fill_alpha=0.7, line_alpha=0)\n",
    "p.scatter(t, Id, legend_label=\"Infectados - dados\", size=8, fill_color=\"#de425b\", fill_alpha=0.7, line_alpha=0)\n",
    "\n",
    "p.line(t, Sa, legend_label=\"Suscetíveis\", line_width=4, color=\"#f9bd3d\", line_cap='round', line_alpha=0.9)\n",
    "p.line(t, Ia, legend_label=\"Infectados\", line_width=4, color=\"#f4193c\", line_cap='round', line_alpha=0.9)\n",
    "\n",
    "p.grid.grid_line_alpha = 0\n",
    "p.ygrid.band_fill_color = \"olive\"\n",
    "p.ygrid.band_fill_alpha = 0.1\n",
    "p.yaxis.axis_label = \"Indivíduos\"\n",
    "p.xaxis.axis_label = \"Dias\"\n",
    "\n",
    "show(p)\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Reamostrando os dados"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "\n",
       "\n",
       "\n",
       "\n",
       "\n",
       "\n",
       "  <div class=\"bk-root\" id=\"f8e18ed2-377d-4a57-8d24-746ab033a5ab\" data-root-id=\"1582\"></div>\n"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "application/javascript": [
       "(function(root) {\n",
       "  function embed_document(root) {\n",
       "    \n",
       "  var docs_json = 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       "  root.Bokeh.embed.embed_items_notebook(docs_json, render_items);\n",
       "\n",
       "  }\n",
       "  if (root.Bokeh !== undefined) {\n",
       "    embed_document(root);\n",
       "  } else {\n",
       "    var attempts = 0;\n",
       "    var timer = setInterval(function(root) {\n",
       "      if (root.Bokeh !== undefined) {\n",
       "        clearInterval(timer);\n",
       "        embed_document(root);\n",
       "      } else {\n",
       "        attempts++;\n",
       "        if (attempts > 100) {\n",
       "          clearInterval(timer);\n",
       "          console.log(\"Bokeh: ERROR: Unable to run BokehJS code because BokehJS library is missing\");\n",
       "        }\n",
       "      }\n",
       "    }, 10, root)\n",
       "  }\n",
       "})(window);"
      ],
      "application/vnd.bokehjs_exec.v0+json": ""
     },
     "metadata": {
      "application/vnd.bokehjs_exec.v0+json": {
       "id": "1582"
      }
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "\n",
    "Sd_res, t_res = scs.resample(Sd, 365, t=t)\n",
    "Id_res, t_res = scs.resample(Id, 365, t=t)\n",
    "\n",
    "p = figure(tools=TOOLS, y_range=(0,4000), plot_width=600, plot_height=400)\n",
    "\n",
    "p.scatter(t, Id, legend_label=\"Infectados\", size=10, fill_color=\"#f4193c\", fill_alpha=0.6, line_alpha=0)\n",
    "p.scatter(t_res, Id_res, legend_label=\"Infectados - Resample\", size=4, fill_color=\"#8e44ad\", line_alpha=0)\n",
    "\n",
    "p.grid.grid_line_alpha = 0\n",
    "p.ygrid.band_fill_color = \"olive\"\n",
    "p.ygrid.band_fill_alpha = 0.1\n",
    "p.yaxis.axis_label = \"Indivíduos\"\n",
    "p.xaxis.axis_label = \"Dias\"\n",
    "\n",
    "show(p)\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Restimando os parâmetros"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[2.15762357e-07 6.89608748e-01]\n"
     ]
    },
    {
     "data": {
      "text/html": [
       "\n",
       "\n",
       "\n",
       "\n",
       "\n",
       "\n",
       "  <div class=\"bk-root\" id=\"f0727c98-c94e-4dbf-8374-6c486e48471b\" data-root-id=\"1582\"></div>\n"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
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\",\"dtype\":\"float64\",\"shape\":[365]}},\"selected\":{\"id\":\"1688\"},\"selection_policy\":{\"id\":\"1687\"}},\"id\":\"1619\",\"type\":\"ColumnDataSource\"},{\"attributes\":{\"source\":{\"id\":\"1749\"}},\"id\":\"1753\",\"type\":\"CDSView\"},{\"attributes\":{},\"id\":\"1587\",\"type\":\"LinearScale\"},{\"attributes\":{\"items\":[{\"id\":\"1618\"},{\"id\":\"1632\"},{\"id\":\"1764\"}]},\"id\":\"1617\",\"type\":\"Legend\"},{\"attributes\":{},\"id\":\"1589\",\"type\":\"LinearScale\"},{\"attributes\":{},\"id\":\"1613\",\"type\":\"BasicTickFormatter\"},{\"attributes\":{\"data_source\":{\"id\":\"1749\"},\"glyph\":{\"id\":\"1750\"},\"hover_glyph\":null,\"muted_glyph\":null,\"nonselection_glyph\":{\"id\":\"1751\"},\"selection_glyph\":null,\"view\":{\"id\":\"1753\"}},\"id\":\"1752\",\"type\":\"GlyphRenderer\"},{\"attributes\":{\"axis\":{\"id\":\"1595\"},\"band_fill_alpha\":0.1,\"band_fill_color\":\"olive\",\"dimension\":1,\"grid_line_alpha\":0,\"ticker\":null},\"id\":\"1598\",\"type\":\"Grid\"},{\"attributes\":{\"axis_label\":\"Indiv\\u00edduos\",\"formatter\":{\"id\":\"1615\"},\"ticker\":{\"id\":\"1596\"}},\"id\":\"1595\",\"type\":\"LinearAxis\"},{\"attributes\":{\"line_alpha\":0.9,\"line_cap\":\"round\",\"line_color\":\"#f4193c\",\"line_width\":4,\"x\":{\"field\":\"x\"},\"y\":{\"field\":\"y\"}},\"id\":\"1750\",\"type\":\"Line\"},{\"attributes\":{\"label\":{\"value\":\"Infectados\"},\"renderers\":[{\"id\":\"1609\"}]},\"id\":\"1618\",\"type\":\"LegendItem\"},{\"attributes\":{},\"id\":\"1821\",\"type\":\"UnionRenderers\"},{\"attributes\":{},\"id\":\"1615\",\"type\":\"BasicTickFormatter\"}],\"root_ids\":[\"1582\"]},\"title\":\"Bokeh Application\",\"version\":\"2.0.1\"}};\n",
       "  var render_items = [{\"docid\":\"8f47ef9a-bd9a-47b2-ab49-ed5a3e3e6047\",\"root_ids\":[\"1582\"],\"roots\":{\"1582\":\"f0727c98-c94e-4dbf-8374-6c486e48471b\"}}];\n",
       "  root.Bokeh.embed.embed_items_notebook(docs_json, render_items);\n",
       "\n",
       "  }\n",
       "  if (root.Bokeh !== undefined) {\n",
       "    embed_document(root);\n",
       "  } else {\n",
       "    var attempts = 0;\n",
       "    var timer = setInterval(function(root) {\n",
       "      if (root.Bokeh !== undefined) {\n",
       "        clearInterval(timer);\n",
       "        embed_document(root);\n",
       "      } else {\n",
       "        attempts++;\n",
       "        if (attempts > 100) {\n",
       "          clearInterval(timer);\n",
       "          console.log(\"Bokeh: ERROR: Unable to run BokehJS code because BokehJS library is missing\");\n",
       "        }\n",
       "      }\n",
       "    }, 10, root)\n",
       "  }\n",
       "})(window);"
      ],
      "application/vnd.bokehjs_exec.v0+json": ""
     },
     "metadata": {
      "application/vnd.bokehjs_exec.v0+json": {
       "id": "1582"
      }
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "\n",
    "(c, kvg) = optimize.leastsq(objetivo, theta0, args=(Sd_res, Id_res, y0, t_res, w)) \n",
    "print(c)\n",
    "\n",
    "[Sa,Ia] = SIRsim(y0, t_res, c)\n",
    "\n",
    "p.line(t_res, Ia, legend_label=\"Infectados - Modelo\", line_width=4, color=\"#f4193c\", line_cap='round', line_alpha=0.9)\n",
    "\n",
    "p.grid.grid_line_alpha = 0\n",
    "p.ygrid.band_fill_color = \"olive\"\n",
    "p.ygrid.band_fill_alpha = 0.1\n",
    "p.yaxis.axis_label = \"Indivíduos\"\n",
    "p.xaxis.axis_label = \"Dias\"\n",
    "\n",
    "show(p)\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Outros métodos de estimação\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "     fun: 43830917.444261\n",
       "     jac: array([2.89188102e+17, 3.06168899e+07])\n",
       " message: 'Optimization terminated successfully.'\n",
       "    nfev: 906\n",
       "     nit: 26\n",
       " success: True\n",
       "       x: array([2.16790744e-07, 6.92576449e-01])"
      ]
     },
     "execution_count": 14,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "\n",
    "import warnings\n",
    "warnings.filterwarnings(\"error\")\n",
    "\n",
    "from scipy.optimize import dual_annealing, shgo, basinhopping, differential_evolution\n",
    "                                            \n",
    "def cost_function(theta0,Sd,Id,y0,t,w): \n",
    "    \"\"\" function to pass to optimize.leastsq\n",
    "        The routine will square and sum the values returned by \n",
    "        this function\"\"\" \n",
    "    try:\n",
    "        [S, I] = SIRsim(y0, t, theta0)\n",
    "        erroS = (w[0]*(S - Sd)**2)\n",
    "        erroI = (w[1]*(I - Id)**2)\n",
    "        final_error = sum(erroI)\n",
    "    except:\n",
    "        final_error = 10**14\n",
    "    return final_error\n",
    "\n",
    "\n",
    "beta_approx = 1 / data[\"pop\"].max()\n",
    "r_approx = 1 / 365\n",
    "\n",
    "x0 = [beta_approx, r_approx]\n",
    "lower, upper = [x0[0]/10, x0[1]/10], [10*x0[0], 1000*x0[1]]\n",
    "bounds = zip(lower, upper)\n",
    "\n",
    "#res = dual_annealing(cost_function, x0=x0, maxiter=2000, bounds=list(bounds), args=(Sd_res, Id_res, y0, t_res, w))\n",
    "#res = shgo(cost_function, bounds=list(bounds), args=(Sd_res, Id_res, y0, t_res, w))\n",
    "#res = basinhopping(cost_function, x0=x0, niter=200, minimizer_kwargs=dict(args=(Sd_res, Id_res, y0, t_res, w)))\n",
    "\n",
    "res = differential_evolution(cost_function, list(bounds), args=(Sd_res, Id_res, y0, t_res, w))\n",
    "res\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "\n",
       "\n",
       "\n",
       "\n",
       "\n",
       "\n",
       "  <div class=\"bk-root\" id=\"92b8368f-6a25-4383-933b-d21a71385460\" data-root-id=\"1953\"></div>\n"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "application/javascript": [
       "(function(root) {\n",
       "  function embed_document(root) {\n",
       "    \n",
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\",\"dtype\":\"float64\",\"shape\":[365]}},\"selected\":{\"id\":\"2018\"},\"selection_policy\":{\"id\":\"2017\"}},\"id\":\"1990\",\"type\":\"ColumnDataSource\"},{\"attributes\":{\"line_alpha\":0.9,\"line_cap\":\"round\",\"line_color\":\"#f4193c\",\"line_width\":4,\"x\":{\"field\":\"x\"},\"y\":{\"field\":\"y\"}},\"id\":\"2005\",\"type\":\"Line\"},{\"attributes\":{\"axis_label\":\"Dias\",\"formatter\":{\"id\":\"1984\"},\"ticker\":{\"id\":\"1963\"}},\"id\":\"1962\",\"type\":\"LinearAxis\"},{\"attributes\":{},\"id\":\"1958\",\"type\":\"LinearScale\"},{\"attributes\":{},\"id\":\"2088\",\"type\":\"UnionRenderers\"},{\"attributes\":{},\"id\":\"1970\",\"type\":\"ZoomInTool\"}],\"root_ids\":[\"1953\"]},\"title\":\"Bokeh Application\",\"version\":\"2.0.1\"}};\n",
       "  var render_items = [{\"docid\":\"77e65e59-cdf6-41d0-b9a1-254da6cc7283\",\"root_ids\":[\"1953\"],\"roots\":{\"1953\":\"92b8368f-6a25-4383-933b-d21a71385460\"}}];\n",
       "  root.Bokeh.embed.embed_items_notebook(docs_json, render_items);\n",
       "\n",
       "  }\n",
       "  if (root.Bokeh !== undefined) {\n",
       "    embed_document(root);\n",
       "  } else {\n",
       "    var attempts = 0;\n",
       "    var timer = setInterval(function(root) {\n",
       "      if (root.Bokeh !== undefined) {\n",
       "        clearInterval(timer);\n",
       "        embed_document(root);\n",
       "      } else {\n",
       "        attempts++;\n",
       "        if (attempts > 100) {\n",
       "          clearInterval(timer);\n",
       "          console.log(\"Bokeh: ERROR: Unable to run BokehJS code because BokehJS library is missing\");\n",
       "        }\n",
       "      }\n",
       "    }, 10, root)\n",
       "  }\n",
       "})(window);"
      ],
      "application/vnd.bokehjs_exec.v0+json": ""
     },
     "metadata": {
      "application/vnd.bokehjs_exec.v0+json": {
       "id": "1953"
      }
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "\n",
    "[Sa,Ia] = SIRsim(y0, t_res, res.x)\n",
    "\n",
    "p = figure(tools=TOOLS, y_range=(0,4000), plot_width=600, plot_height=400)\n",
    "\n",
    "p.scatter(t, Id, legend_label=\"Infectados\", size=10, fill_color=\"#f4193c\", fill_alpha=0.6, line_alpha=0)\n",
    "p.scatter(t_res, Id_res, legend_label=\"Infectados - Resample\", size=4, fill_color=\"#8e44ad\", line_alpha=0)\n",
    "\n",
    "p.line(t_res, Ia, legend_label=\"Infectados - Modelo\", line_width=4, color=\"#f4193c\", line_cap='round', line_alpha=0.9)\n",
    "\n",
    "p.grid.grid_line_alpha = 0\n",
    "p.ygrid.band_fill_color = \"olive\"\n",
    "p.ygrid.band_fill_alpha = 0.1\n",
    "p.yaxis.axis_label = \"Indivíduos\"\n",
    "p.xaxis.axis_label = \"Dias\"\n",
    "\n",
    "show(p)\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Análise anual"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "\n",
       "\n",
       "\n",
       "\n",
       "\n",
       "\n",
       "  <div class=\"bk-root\" id=\"7d320a81-7ca9-4292-9bf8-f86a910053f0\" data-root-id=\"2162\"></div>\n"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "application/javascript": [
       "(function(root) {\n",
       "  function embed_document(root) {\n",
       "    \n",
       "  var docs_json = {\"f6418ec4-0815-4789-aaac-d849bffcfb16\":{\"roots\":{\"references\":[{\"attributes\":{\"below\":[{\"id\":\"2171\"}],\"center\":[{\"id\":\"2174\"},{\"id\":\"2178\"},{\"id\":\"2199\"}],\"left\":[{\"id\":\"2175\"}],\"plot_height\":300,\"renderers\":[{\"id\":\"2191\"}],\"title\":{\"id\":\"2193\"},\"toolbar\":{\"id\":\"2183\"},\"x_range\":{\"id\":\"2163\"},\"x_scale\":{\"id\":\"2167\"},\"y_range\":{\"id\":\"2165\"},\"y_scale\":{\"id\":\"2169\"}},\"id\":\"2162\",\"subtype\":\"Figure\",\"type\":\"Plot\"},{\"attributes\":{\"axis\":{\"id\":\"2171\"},\"grid_line_alpha\":0,\"ticker\":null},\"id\":\"2174\",\"type\":\"Grid\"},{\"attributes\":{\"axis\":{\"id\":\"2175\"},\"band_fill_alpha\":0.1,\"band_fill_color\":\"olive\",\"dimension\":1,\"grid_line_alpha\":0,\"ticker\":null},\"id\":\"2178\",\"type\":\"Grid\"},{\"attributes\":{\"data\":{\"x\":{\"__ndarray__\":\"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\",\"dtype\":\"float64\",\"shape\":[548]},\"y\":[180,271,423,465,523,649,624,556,420,423,488,441,268,260,163,83,60,41,48,65,82,145,122,194,237,318,450,671,1387,1617,2058,3099,3340,2965,1873,1641,1122,884,591,427,282,174,127,84,97,68,88,79,58,85,75,121,174,209,458,742,929,1027,1411,1885,2110,1764,2001,2154,1843,1427,970,726,416,218,160,160,188,224,298,436,482,468,650,796,1065,1241,1230,1012,981,1015,771,1031,1093,1196,1076,1029,828,669,372,171,84,71,113,108,188,241,305,248,477,524,851,1415,2235,2973,3144,3169,2248,1976,2128,1901,1635,1265,1154,887,476,269,171,185,157,205,231,262,333,290,612,677,983,1586,1912,2265,2761,3388,3240,2278,2058,1884,1521,1237,869,576,381,212,108,90,72,103,61,51,57,66,90,90,66,109,120,114,216,262,377,403,829,1091,1174,1275,1248,1244,836,515,308,418,592,837,1056,1593,2446,3090,4675,4610,4578,6107,7061,6637,4878,3693,2228,1752,1449,960,761,456,342,207,127,119,85,59,54,124,115,69,58,44,65,77,91,168,276,474,471,441,569,462,650,1072,1384,1319,1521,1788,1677,985,520,626,1236,2058,2241,2337,3048,3201,3701,3682,2891,3168,3456,2992,2572,1985,1464,788,650,566,498,318,217,145,117,49,46,29,22,32,43,39,32,29,10,31,23,35,62,74,89,112,160,143,119,110,176,175,312,316,249,186,120,167,284,389,539,471,663,1021,1538,1795,1793,3240,5096,6038,7022,7192,5905,3025,2025,1715,1428,848,652,358,254,158,96,46,61,74,61,66,51,33,37,52,42,77,110,130,122,151,197,174,372,565,599,654,634,650,483,431,276,183,240,336,388,452,580,787,835,1472,1362,2324,3453,4101,3866,3731,3783,3420,2038,1964,1820,1336,771,474,378,238,113,56,43,51,46,66,68,84,58,66,57,120,242,320,372,415,725,577,785,1145,1049,990,1020,1076,779,504,317,194,242,362,543,633,785,1194,1283,2534,1984,2740,2961,2779,2747,2748,2348,1370,1357,1360,1157,809,652,377,250,203,111,61,46,61,41,41,35,42,41,36,33,73,81,155,190,169,151,208,199,187,283,256,235,270,286,247,141,100,134,285,444,589,702,899,1347,2300,2397,3560,6001,6742,6018,5030,5248,3211,1929,1600,1279,860,651,395,335,212,179,96,75,84,81,91,73,69,39,50,58,78,92,136,174,258,251,249,240,151,120,141,140,196,267,229,185,154,170,360,457,742,812,1250,1716,2003,1923,1778,2240,2371,2073,2215,2462,2782,1858,1385,1438,1450,1048,928,841,414,252,117,63,75,70,94,84,103,68,55,75,95,149,139,191,291,264,225,257,354,468,491,657,693,935,755,447,329,292,326,485,615,1008,1242,1505,666]},\"selected\":{\"id\":\"2279\"},\"selection_policy\":{\"id\":\"2278\"}},\"id\":\"2188\",\"type\":\"ColumnDataSource\"},{\"attributes\":{\"axis_label\":\"Dias\",\"formatter\":{\"id\":\"2195\"},\"ticker\":{\"id\":\"2172\"}},\"id\":\"2171\",\"type\":\"LinearAxis\"},{\"attributes\":{\"source\":{\"id\":\"2188\"}},\"id\":\"2192\",\"type\":\"CDSView\"},{\"attributes\":{},\"id\":\"2278\",\"type\":\"UnionRenderers\"},{\"attributes\":{\"line_alpha\":0.1,\"line_cap\":\"round\",\"line_color\":\"#f4511e\",\"line_width\":4,\"x\":{\"field\":\"x\"},\"y\":{\"field\":\"y\"}},\"id\":\"2190\",\"type\":\"Line\"},{\"attributes\":{},\"id\":\"2172\",\"type\":\"BasicTicker\"},{\"attributes\":{\"active_drag\":\"auto\",\"active_inspect\":\"auto\",\"active_multi\":null,\"active_scroll\":\"auto\",\"active_tap\":\"auto\",\"autohide\":true,\"tools\":[{\"id\":\"2179\"},{\"id\":\"2180\"},{\"id\":\"2181\"},{\"id\":\"2182\"}]},\"id\":\"2183\",\"type\":\"Toolbar\"},{\"attributes\":{\"text\":\"\"},\"id\":\"2193\",\"type\":\"Title\"},{\"attributes\":{\"data_source\":{\"id\":\"2188\"},\"glyph\":{\"id\":\"2189\"},\"hover_glyph\":null,\"muted_glyph\":null,\"nonselection_glyph\":{\"id\":\"2190\"},\"selection_glyph\":null,\"view\":{\"id\":\"2192\"}},\"id\":\"2191\",\"type\":\"GlyphRenderer\"},{\"attributes\":{},\"id\":\"2179\",\"type\":\"ZoomInTool\"},{\"attributes\":{\"items\":[{\"id\":\"2200\"}]},\"id\":\"2199\",\"type\":\"Legend\"},{\"attributes\":{},\"id\":\"2169\",\"type\":\"LinearScale\"},{\"attributes\":{},\"id\":\"2180\",\"type\":\"ZoomOutTool\"},{\"attributes\":{},\"id\":\"2176\",\"type\":\"BasicTicker\"},{\"attributes\":{\"line_alpha\":0.9,\"line_cap\":\"round\",\"line_color\":\"#f4511e\",\"line_width\":4,\"x\":{\"field\":\"x\"},\"y\":{\"field\":\"y\"}},\"id\":\"2189\",\"type\":\"Line\"},{\"attributes\":{\"axis_label\":\"Indiv\\u00edduos\",\"formatter\":{\"id\":\"2197\"},\"ticker\":{\"id\":\"2176\"}},\"id\":\"2175\",\"type\":\"LinearAxis\"},{\"attributes\":{},\"id\":\"2181\",\"type\":\"SaveTool\"},{\"attributes\":{\"callback\":null},\"id\":\"2182\",\"type\":\"HoverTool\"},{\"attributes\":{},\"id\":\"2279\",\"type\":\"Selection\"},{\"attributes\":{},\"id\":\"2165\",\"type\":\"DataRange1d\"},{\"attributes\":{},\"id\":\"2197\",\"type\":\"BasicTickFormatter\"},{\"attributes\":{},\"id\":\"2167\",\"type\":\"LinearScale\"},{\"attributes\":{\"label\":{\"value\":\"Casos\"},\"renderers\":[{\"id\":\"2191\"}]},\"id\":\"2200\",\"type\":\"LegendItem\"},{\"attributes\":{\"end\":1964,\"start\":1944},\"id\":\"2163\",\"type\":\"Range1d\"},{\"attributes\":{},\"id\":\"2195\",\"type\":\"BasicTickFormatter\"}],\"root_ids\":[\"2162\"]},\"title\":\"Bokeh Application\",\"version\":\"2.0.1\"}};\n",
       "  var render_items = [{\"docid\":\"f6418ec4-0815-4789-aaac-d849bffcfb16\",\"root_ids\":[\"2162\"],\"roots\":{\"2162\":\"7d320a81-7ca9-4292-9bf8-f86a910053f0\"}}];\n",
       "  root.Bokeh.embed.embed_items_notebook(docs_json, render_items);\n",
       "\n",
       "  }\n",
       "  if (root.Bokeh !== undefined) {\n",
       "    embed_document(root);\n",
       "  } else {\n",
       "    var attempts = 0;\n",
       "    var timer = setInterval(function(root) {\n",
       "      if (root.Bokeh !== undefined) {\n",
       "        clearInterval(timer);\n",
       "        embed_document(root);\n",
       "      } else {\n",
       "        attempts++;\n",
       "        if (attempts > 100) {\n",
       "          clearInterval(timer);\n",
       "          console.log(\"Bokeh: ERROR: Unable to run BokehJS code because BokehJS library is missing\");\n",
       "        }\n",
       "      }\n",
       "    }, 10, root)\n",
       "  }\n",
       "})(window);"
      ],
      "application/vnd.bokehjs_exec.v0+json": ""
     },
     "metadata": {
      "application/vnd.bokehjs_exec.v0+json": {
       "id": "2162"
      }
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "\n",
    "years = data[\"time\"].astype(int).unique().tolist()\n",
    "\n",
    "p = figure(tools=TOOLS+\",hover\",\n",
    "            x_range=(min(years), max(years)),\n",
    "            plot_width=600, plot_height=300)\n",
    "\n",
    "p.line(data[\"time\"], data[\"cases\"], \n",
    "       legend_label=\"Casos\", line_width=4, color=\"#f4511e\", line_cap='round', line_alpha=0.9)\n",
    "\n",
    "p.grid.grid_line_alpha = 0\n",
    "p.ygrid.band_fill_color = \"olive\"\n",
    "p.ygrid.band_fill_alpha = 0.1\n",
    "p.yaxis.axis_label = \"Indivíduos\"\n",
    "p.xaxis.axis_label = \"Dias\"\n",
    "p.toolbar.autohide = True\n",
    "\n",
    "show(p)\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Detecção dos períodos de contágio"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "\n",
       "\n",
       "\n",
       "\n",
       "\n",
       "\n",
       "  <div class=\"bk-root\" id=\"ecbfcac8-92c3-4ffa-bd8f-aef7e3035a81\" data-root-id=\"2162\"></div>\n"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "application/javascript": [
       "(function(root) {\n",
       "  function embed_document(root) {\n",
       "    \n",
       "  var docs_json = 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Filtrado\"},\"renderers\":[{\"id\":\"2331\"}]},\"id\":\"2341\",\"type\":\"LegendItem\"},{\"attributes\":{},\"id\":\"2197\",\"type\":\"BasicTickFormatter\"},{\"attributes\":{},\"id\":\"2167\",\"type\":\"LinearScale\"},{\"attributes\":{\"line_alpha\":0.1,\"line_cap\":\"round\",\"line_color\":\"#8e44ad\",\"line_dash\":[2,4],\"line_width\":3,\"x\":{\"field\":\"x\"},\"y\":{\"field\":\"y\"}},\"id\":\"2330\",\"type\":\"Line\"},{\"attributes\":{\"label\":{\"value\":\"Casos\"},\"renderers\":[{\"id\":\"2191\"}]},\"id\":\"2200\",\"type\":\"LegendItem\"},{\"attributes\":{\"end\":1964,\"start\":1944},\"id\":\"2163\",\"type\":\"Range1d\"},{\"attributes\":{},\"id\":\"2195\",\"type\":\"BasicTickFormatter\"}],\"root_ids\":[\"2162\"]},\"title\":\"Bokeh Application\",\"version\":\"2.0.1\"}};\n",
       "  var render_items = [{\"docid\":\"65f68e85-5629-4ee1-bb75-c9cc60f677f8\",\"root_ids\":[\"2162\"],\"roots\":{\"2162\":\"ecbfcac8-92c3-4ffa-bd8f-aef7e3035a81\"}}];\n",
       "  root.Bokeh.embed.embed_items_notebook(docs_json, render_items);\n",
       "\n",
       "  }\n",
       "  if (root.Bokeh !== undefined) {\n",
       "    embed_document(root);\n",
       "  } else {\n",
       "    var attempts = 0;\n",
       "    var timer = setInterval(function(root) {\n",
       "      if (root.Bokeh !== undefined) {\n",
       "        clearInterval(timer);\n",
       "        embed_document(root);\n",
       "      } else {\n",
       "        attempts++;\n",
       "        if (attempts > 100) {\n",
       "          clearInterval(timer);\n",
       "          console.log(\"Bokeh: ERROR: Unable to run BokehJS code because BokehJS library is missing\");\n",
       "        }\n",
       "      }\n",
       "    }, 10, root)\n",
       "  }\n",
       "})(window);"
      ],
      "application/vnd.bokehjs_exec.v0+json": ""
     },
     "metadata": {
      "application/vnd.bokehjs_exec.v0+json": {
       "id": "2162"
      }
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "\n",
    "from PyAstronomy import pyasl\n",
    "\n",
    "# Filtrando os dados para o processo de derivação\n",
    "filt_cases = pyasl.smooth(data[\"cases\"], 13, 'hamming')\n",
    "\n",
    "\n",
    "# Incluindo os dados filtrados no plot\n",
    "p.line(data[\"time\"], filt_cases, line_dash=\"dotted\",\n",
    "       legend_label=\"Casos Filtrado\", line_width=3, color=\"#8e44ad\", line_cap='round', line_alpha=0.9)\n",
    "\n",
    "show(p)\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "\n",
       "\n",
       "\n",
       "\n",
       "\n",
       "\n",
       "  <div class=\"bk-root\" id=\"4f284aa1-5b2a-424e-9fb4-58d1911b9aad\" data-root-id=\"2562\"></div>\n"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "application/javascript": [
       "(function(root) {\n",
       "  function embed_document(root) {\n",
       "    \n",
       "  var docs_json = 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\",\"dtype\":\"float64\",\"shape\":[547]}},\"selected\":{\"id\":\"2613\"},\"selection_policy\":{\"id\":\"2612\"}},\"id\":\"2588\",\"type\":\"ColumnDataSource\"},{\"attributes\":{\"axis\":{\"id\":\"2575\"},\"band_fill_alpha\":0.1,\"band_fill_color\":\"olive\",\"dimension\":1,\"grid_line_alpha\":0,\"ticker\":null},\"id\":\"2578\",\"type\":\"Grid\"},{\"attributes\":{\"axis_label\":\"Indiv\\u00edduos\",\"formatter\":{\"id\":\"2597\"},\"ticker\":{\"id\":\"2576\"}},\"id\":\"2575\",\"type\":\"LinearAxis\"},{\"attributes\":{\"active_drag\":\"auto\",\"active_inspect\":\"auto\",\"active_multi\":null,\"active_scroll\":\"auto\",\"active_tap\":\"auto\",\"autohide\":true,\"tools\":[{\"id\":\"2579\"},{\"id\":\"2580\"},{\"id\":\"2581\"},{\"id\":\"2582\"}]},\"id\":\"2583\",\"type\":\"Toolbar\"},{\"attributes\":{\"line_alpha\":0.9,\"line_cap\":\"round\",\"line_color\":\"#f4511e\",\"line_width\":4,\"x\":{\"field\":\"x\"},\"y\":{\"field\":\"y\"}},\"id\":\"2589\",\"type\":\"Line\"},{\"attributes\":{},\"id\":\"2579\",\"type\":\"ZoomInTool\"},{\"attributes\":{},\"id\":\"2580\",\"type\":\"ZoomOutTool\"},{\"attributes\":{\"data_source\":{\"id\":\"2588\"},\"glyph\":{\"id\":\"2589\"},\"hover_glyph\":null,\"muted_glyph\":null,\"nonselection_glyph\":{\"id\":\"2590\"},\"selection_glyph\":null,\"view\":{\"id\":\"2592\"}},\"id\":\"2591\",\"type\":\"GlyphRenderer\"}],\"root_ids\":[\"2562\"]},\"title\":\"Bokeh Application\",\"version\":\"2.0.1\"}};\n",
       "  var render_items = [{\"docid\":\"8faf817b-eaea-45c0-a913-aa2b31124320\",\"root_ids\":[\"2562\"],\"roots\":{\"2562\":\"4f284aa1-5b2a-424e-9fb4-58d1911b9aad\"}}];\n",
       "  root.Bokeh.embed.embed_items_notebook(docs_json, render_items);\n",
       "\n",
       "  }\n",
       "  if (root.Bokeh !== undefined) {\n",
       "    embed_document(root);\n",
       "  } else {\n",
       "    var attempts = 0;\n",
       "    var timer = setInterval(function(root) {\n",
       "      if (root.Bokeh !== undefined) {\n",
       "        clearInterval(timer);\n",
       "        embed_document(root);\n",
       "      } else {\n",
       "        attempts++;\n",
       "        if (attempts > 100) {\n",
       "          clearInterval(timer);\n",
       "          console.log(\"Bokeh: ERROR: Unable to run BokehJS code because BokehJS library is missing\");\n",
       "        }\n",
       "      }\n",
       "    }, 10, root)\n",
       "  }\n",
       "})(window);"
      ],
      "application/vnd.bokehjs_exec.v0+json": ""
     },
     "metadata": {
      "application/vnd.bokehjs_exec.v0+json": {
       "id": "2562"
      }
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "\n",
    "cases_variation = np.diff(filt_cases) # Calculando a taxa de variação\n",
    "\n",
    "threshold = np.std(cases_variation)   # Calculando o threshold baseado no desvio\n",
    "                                      # padrão da taxa de variação\n",
    "threshold_vec = [threshold for k in cases_variation]\n",
    "\n",
    "p = figure(tools=TOOLS+\",hover\",\n",
    "            plot_width=600, plot_height=300)\n",
    "\n",
    "p.line(data[\"time\"][:-1], cases_variation, \n",
    "       legend_label=\"Derivada dos casos\", line_width=4, color=\"#f4511e\", line_cap='round', line_alpha=0.9)\n",
    "p.line(data[\"time\"][:-1], threshold_vec, \n",
    "       legend_label=\"Threshold\", line_width=4, color=\"#8e44ad\", line_cap='round', line_alpha=0.9)\n",
    "\n",
    "p.grid.grid_line_alpha = 0\n",
    "p.ygrid.band_fill_color = \"olive\"\n",
    "p.ygrid.band_fill_alpha = 0.1\n",
    "p.yaxis.axis_label = \"Indivíduos\"\n",
    "p.xaxis.axis_label = \"Dias\"\n",
    "p.toolbar.autohide = True\n",
    "\n",
    "show(p)\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {},
   "outputs": [],
   "source": [
    "\n",
    "def findEpidemyBreaks(cases, threshold_prop, cases_before=10):\n",
    "    \"\"\"\n",
    "    \"\"\"\n",
    "    \n",
    "    # Filtering the data\n",
    "    filt_cases = pyasl.smooth(cases, 11, 'hamming')\n",
    "    # Compute the derivative and standard deviation\n",
    "    cases_variation = np.diff(filt_cases).tolist()\n",
    "    threshold = threshold_prop * np.std(cases_variation)\n",
    "    \n",
    "    start_points, end_points = [], []\n",
    "    in_epidemy, out_epidemy = False, False\n",
    "    for k, value in enumerate(cases_variation):\n",
    "        if not in_epidemy:\n",
    "            # Check value\n",
    "            if value > threshold:\n",
    "                in_epidemy = True\n",
    "                # Find the start point\n",
    "                start_index = 0 if k-cases_before < 0 else k-cases_before\n",
    "                window = [abs(v) for v in cases_variation[start_index:k]]\n",
    "                ref_index = window.index(min(window))\n",
    "                start_points.append(k - (cases_before - ref_index))\n",
    "        else:\n",
    "            check_1 = (cases_variation[k-1] < 0)\n",
    "            check_2 = (value >= 0)\n",
    "            if check_1 and check_2:\n",
    "                in_epidemy = False\n",
    "                end_points.append(k)\n",
    "    return start_points, end_points\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "\n",
       "\n",
       "\n",
       "\n",
       "\n",
       "\n",
       "  <div class=\"bk-root\" id=\"f602b64c-971a-4b0b-ae73-7688714b5962\" data-root-id=\"3596\"></div>\n"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "application/javascript": [
       "(function(root) {\n",
       "  function embed_document(root) {\n",
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       "  var render_items = [{\"docid\":\"89baba2d-a823-4595-b40e-388cbc7afeb2\",\"root_ids\":[\"3596\"],\"roots\":{\"3596\":\"f602b64c-971a-4b0b-ae73-7688714b5962\"}}];\n",
       "  root.Bokeh.embed.embed_items_notebook(docs_json, render_items);\n",
       "\n",
       "  }\n",
       "  if (root.Bokeh !== undefined) {\n",
       "    embed_document(root);\n",
       "  } else {\n",
       "    var attempts = 0;\n",
       "    var timer = setInterval(function(root) {\n",
       "      if (root.Bokeh !== undefined) {\n",
       "        clearInterval(timer);\n",
       "        embed_document(root);\n",
       "      } else {\n",
       "        attempts++;\n",
       "        if (attempts > 100) {\n",
       "          clearInterval(timer);\n",
       "          console.log(\"Bokeh: ERROR: Unable to run BokehJS code because BokehJS library is missing\");\n",
       "        }\n",
       "      }\n",
       "    }, 10, root)\n",
       "  }\n",
       "})(window);"
      ],
      "application/vnd.bokehjs_exec.v0+json": ""
     },
     "metadata": {
      "application/vnd.bokehjs_exec.v0+json": {
       "id": "3596"
      }
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "\n",
    "start, end = findEpidemyBreaks(data[\"cases\"], 1, 12)\n",
    "\n",
    "p = figure(tools=TOOLS+\",hover\",\n",
    "            x_range=(min(years), max(years)),\n",
    "            y_range=(0, 8000),\n",
    "            plot_width=600, plot_height=400)\n",
    "\n",
    "p.line(data[\"time\"], data[\"cases\"], \n",
    "       legend_label=\"Casos\", line_width=4, color=\"#f4511e\", line_cap='round', line_alpha=0.9)\n",
    "\n",
    "\n",
    "\n",
    "windowed_data = { \"I\":[], \"S\":[], \"B\":[], \"t\":[] }\n",
    "for s, e in zip(start, end):\n",
    "    windowed_data[\"B\"].append(data[\"births\"][s:e].to_numpy())\n",
    "    windowed_data[\"S\"].append(data[\"pop\"][s:e].to_numpy())\n",
    "    windowed_data[\"I\"].append(data[\"cases\"][s:e].to_numpy())\n",
    "    windowed_data[\"t\"].append(data[\"time\"][s:e].to_numpy())\n",
    "    \n",
    "    p.line(windowed_data[\"t\"][-1], windowed_data[\"I\"][-1],\n",
    "          legend_label=\"Casos na Epidemia\", line_width=3, color=\"#8e44ad\", line_cap='round', line_alpha=0.9)\n",
    "    \n",
    "    p.line([data[\"time\"][s], data[\"time\"][s]], [0, 10000], line_dash=\"dotted\",\n",
    "          legend_label=\"Início da Epidemia\", line_width=1, color=\"#455a64\", line_cap='round', line_alpha=0.9)\n",
    "\n",
    "p.grid.grid_line_alpha = 0\n",
    "p.ygrid.band_fill_color = \"olive\"\n",
    "p.ygrid.band_fill_alpha = 0.1\n",
    "p.yaxis.axis_label = \"Indivíduos\"\n",
    "p.xaxis.axis_label = \"Ano\"\n",
    "p.toolbar.autohide = True\n",
    "\n",
    "\n",
    "index = 5\n",
    "days = (windowed_data[\"t\"][index] - windowed_data[\"t\"][index][0]) * 365\n",
    "\n",
    "p1 = figure(tools=TOOLS+\",hover\",\n",
    "            plot_width=600, plot_height=400)\n",
    "\n",
    "p1.line(days, windowed_data[\"I\"][index], \n",
    "       legend_label=\"Casos\", line_width=4, color=\"#8e44ad\", line_cap='round', line_alpha=0.9)\n",
    "\n",
    "p1.grid.grid_line_alpha = 0\n",
    "p1.ygrid.band_fill_color = \"olive\"\n",
    "p1.ygrid.band_fill_alpha = 0.1\n",
    "p1.yaxis.axis_label = \"Indivíduos\"\n",
    "p1.xaxis.axis_label = \"Dias\"\n",
    "p1.toolbar.autohide = True\n",
    "\n",
    "show(column(p,p1))\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {},
   "outputs": [],
   "source": [
    "\n",
    "final_data = {\n",
    "    \"data\": {\n",
    "        \"original\": [],\n",
    "        \"resampled\": [],\n",
    "        \"simulated\": []\n",
    "    },\n",
    "    \"pars\": {\n",
    "        \"beta\": [],\n",
    "        \"r\": []\n",
    "    }\n",
    "}\n",
    "\n",
    "zipped_data = zip(\n",
    "    windowed_data[\"S\"], \n",
    "    windowed_data[\"I\"], \n",
    "    windowed_data[\"B\"],          \n",
    "    windowed_data[\"t\"])\n",
    "\n",
    "for S, I, B, t in zipped_data:\n",
    "    year_ref = t[0]\n",
    "    S = S - I + B # Calculando os suscetiveis\n",
    "    t = (t - year_ref) * 365 # Tempo em dias \n",
    "    # Condições iniciais\n",
    "    y0 = S[0], I[0]\n",
    "    theta0 = [1e-8, 1e-1]\n",
    "    # Criando a ponderação \n",
    "    # dos erros\n",
    "    wS = max(I) / max(S)\n",
    "    w = [wS, 1]\n",
    "    # Reamostrando os dados\n",
    "    Sd_res, t_res = scs.resample(S, int(t[-1]), t=t)\n",
    "    Id_res, t_res = scs.resample(I, int(t[-1]), t=t)\n",
    "    # Estimando os parâmetros\n",
    "    bounds = zip([x0[0]/10, x0[1]/10], [10*x0[0], 1000*x0[1]])\n",
    "    res = differential_evolution(cost_function, list(bounds), args=(Sd_res, Id_res, y0, t_res, w))\n",
    "    # Simulando os dados\n",
    "    [Sa, Ia] = SIRsim(y0, t_res, res.x)\n",
    "    # Save the year data\n",
    "    final_data[\"data\"][\"original\"].append(\n",
    "        { \"I\": I, \"B\": B, \"S\": S, \"t\": t/365 + year_ref })\n",
    "    final_data[\"data\"][\"resampled\"].append(\n",
    "        {\"I\": Id_res, \"S\": Sd_res, \"t\": t_res/365 + year_ref})\n",
    "    final_data[\"data\"][\"simulated\"].append(\n",
    "        {\"I\": Ia, \"S\": Sa, \"t\": t_res/365 + year_ref})\n",
    "    final_data[\"pars\"][\"beta\"].append( res.x[0] )\n",
    "    final_data[\"pars\"][\"r\"].append( res.x[1] )\n",
    "    "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "\n",
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       "\n",
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\",\"dtype\":\"float64\",\"shape\":[531]}},\"selected\":{\"id\":\"4951\"},\"selection_policy\":{\"id\":\"4950\"}},\"id\":\"4844\",\"type\":\"ColumnDataSource\"},{\"attributes\":{\"line_alpha\":0.1,\"line_cap\":\"round\",\"line_color\":\"#0288d1\",\"line_dash\":[6],\"line_width\":3,\"x\":{\"field\":\"x\"},\"y\":{\"field\":\"y\"}},\"id\":\"4795\",\"type\":\"Line\"}],\"root_ids\":[\"4953\"]},\"title\":\"Bokeh Application\",\"version\":\"2.0.1\"}};\n",
       "  var render_items = [{\"docid\":\"9b8e91c4-9798-43da-98f8-1e42c7b6f219\",\"root_ids\":[\"4953\"],\"roots\":{\"4953\":\"91f7e37f-95b0-444c-8f35-bf644e9c9a5a\"}}];\n",
       "  root.Bokeh.embed.embed_items_notebook(docs_json, render_items);\n",
       "\n",
       "  }\n",
       "  if (root.Bokeh !== undefined) {\n",
       "    embed_document(root);\n",
       "  } else {\n",
       "    var attempts = 0;\n",
       "    var timer = setInterval(function(root) {\n",
       "      if (root.Bokeh !== undefined) {\n",
       "        clearInterval(timer);\n",
       "        embed_document(root);\n",
       "      } else {\n",
       "        attempts++;\n",
       "        if (attempts > 100) {\n",
       "          clearInterval(timer);\n",
       "          console.log(\"Bokeh: ERROR: Unable to run BokehJS code because BokehJS library is missing\");\n",
       "        }\n",
       "      }\n",
       "    }, 10, root)\n",
       "  }\n",
       "})(window);"
      ],
      "application/vnd.bokehjs_exec.v0+json": ""
     },
     "metadata": {
      "application/vnd.bokehjs_exec.v0+json": {
       "id": "4953"
      }
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "\n",
    "r = final_data[\"pars\"][\"r\"]\n",
    "beta = final_data[\"pars\"][\"beta\"]\n",
    "years = [int(t[0]) for t in windowed_data[\"t\"]]\n",
    "\n",
    "\n",
    "\n",
    "p = figure(tools=TOOLS+\",hover\",\n",
    "           y_range=(min(beta), max(beta)), \n",
    "           plot_width=600, plot_height=300)\n",
    "\n",
    "\n",
    "p.line(years, beta, \n",
    "       legend_label=\"beta\", line_width=4, color=\"#c2185b\", line_cap='round', line_alpha=0.9)\n",
    "\n",
    "p.extra_y_ranges = {\"r_axis\": Range1d(start=min(r), end=max(r))}\n",
    "p.add_layout(LinearAxis(y_range_name=\"r_axis\"), 'left')\n",
    "\n",
    "p.line(years, r, y_range_name=\"r_axis\", line_dash='dashed',\n",
    "       legend_label=\"r\", line_width=3, color=\"#8e44ad\", line_cap='round', line_alpha=0.9)\n",
    "\n",
    "\n",
    "p.grid.grid_line_alpha = 0\n",
    "p.ygrid.band_fill_color = \"olive\"\n",
    "p.ygrid.band_fill_alpha = 0.1\n",
    "p.xaxis.axis_label = \"Ano\"\n",
    "p.toolbar.autohide = True\n",
    "\n",
    "\n",
    "\n",
    "p1 = figure(tools=TOOLS+\",hover\",\n",
    "            x_range=p.x_range,\n",
    "            plot_width=600, plot_height=300)\n",
    "\n",
    "\n",
    "p1.line(data[\"time\"], data[\"cases\"],\n",
    "        legend_label=\"Casos\", line_width=2, color=\"#f4511e\", line_cap='round', line_alpha=0.9)\n",
    "\n",
    "for dataset in final_data[\"data\"][\"original\"]:\n",
    "    p1.line(dataset[\"t\"], dataset[\"I\"], \n",
    "           legend_label=\"Casos\", line_width=4, color=\"#f4511e\", line_cap='round', line_alpha=0.9)\n",
    "\n",
    "for dataset in final_data[\"data\"][\"simulated\"]:\n",
    "    p1.line(dataset[\"t\"], dataset[\"I\"], line_dash='dashed',\n",
    "           legend_label=\"Estimado\", line_width=3, color=\"#0288d1\", line_cap='round', line_alpha=0.9)\n",
    "\n",
    "    \n",
    "p1.grid.grid_line_alpha = 0\n",
    "p1.ygrid.band_fill_color = \"olive\"\n",
    "p1.ygrid.band_fill_alpha = 0.1\n",
    "p1.yaxis.axis_label = \"Indivíduos\"\n",
    "p1.xaxis.axis_label = \"Ano\"\n",
    "p1.toolbar.autohide = True\n",
    "\n",
    "\n",
    "\n",
    "show(column(p,p1))\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "\n",
       "\n",
       "\n",
       "\n",
       "\n",
       "\n",
       "  <div class=\"bk-root\" id=\"ae7adf3e-eacc-414f-bd0a-799fc9ed1f76\" data-root-id=\"5877\"></div>\n"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "application/javascript": [
       "(function(root) {\n",
       "  function embed_document(root) {\n",
       "    \n",
       "  var docs_json = 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\",\"dtype\":\"float64\",\"shape\":[531]}},\"selected\":{\"id\":\"6124\"},\"selection_policy\":{\"id\":\"6123\"}},\"id\":\"5817\",\"type\":\"ColumnDataSource\"},{\"attributes\":{\"above\":[{\"id\":\"5562\"}],\"center\":[{\"id\":\"5565\"},{\"id\":\"5569\"},{\"id\":\"5584\"}],\"left\":[{\"id\":\"5566\"}],\"plot_height\":300,\"renderers\":[{\"id\":\"5576\"},{\"id\":\"5590\"},{\"id\":\"5605\"},{\"id\":\"5621\"},{\"id\":\"5639\"},{\"id\":\"5659\"},{\"id\":\"5681\"},{\"id\":\"5705\"},{\"id\":\"5731\"},{\"id\":\"5759\"},{\"id\":\"5789\"},{\"id\":\"5821\"}],\"title\":{\"id\":\"5578\"},\"toolbar\":{\"id\":\"5571\"},\"toolbar_location\":null,\"x_range\":{\"id\":\"5554\"},\"x_scale\":{\"id\":\"5558\"},\"y_range\":{\"id\":\"5556\"},\"y_scale\":{\"id\":\"5560\"}},\"id\":\"5553\",\"subtype\":\"Figure\",\"type\":\"Plot\"},{\"attributes\":{\"data_source\":{\"id\":\"5817\"},\"glyph\":{\"id\":\"5819\"},\"hover_glyph\":null,\"muted_glyph\":null,\"nonselection_glyph\":{\"id\":\"5820\"},\"selection_glyph\":null,\"view\":{\"id\":\"5822\"}},\"id\":\"5821\",\"type\":\"GlyphRenderer\"},{\"attributes\":{\"source\":{\"id\":\"5817\"}},\"id\":\"5822\",\"type\":\"CDSView\"},{\"attributes\":{},\"id\":\"5855\",\"type\":\"DataRange1d\"},{\"attributes\":{\"fill_alpha\":0.2,\"fill_color\":\"navy\",\"level\":\"overlay\",\"line_alpha\":1.0,\"line_color\":\"black\",\"line_dash\":[2,2],\"line_width\":0.5},\"id\":\"5868\",\"type\":\"BoxAnnotation\"}],\"root_ids\":[\"5877\"]},\"title\":\"Bokeh Application\",\"version\":\"2.0.1\"}};\n",
       "  var render_items = [{\"docid\":\"f77d8ca0-5712-44b9-85ed-fb2009e656c2\",\"root_ids\":[\"5877\"],\"roots\":{\"5877\":\"ae7adf3e-eacc-414f-bd0a-799fc9ed1f76\"}}];\n",
       "  root.Bokeh.embed.embed_items_notebook(docs_json, render_items);\n",
       "\n",
       "  }\n",
       "  if (root.Bokeh !== undefined) {\n",
       "    embed_document(root);\n",
       "  } else {\n",
       "    var attempts = 0;\n",
       "    var timer = setInterval(function(root) {\n",
       "      if (root.Bokeh !== undefined) {\n",
       "        clearInterval(timer);\n",
       "        embed_document(root);\n",
       "      } else {\n",
       "        attempts++;\n",
       "        if (attempts > 100) {\n",
       "          clearInterval(timer);\n",
       "          console.log(\"Bokeh: ERROR: Unable to run BokehJS code because BokehJS library is missing\");\n",
       "        }\n",
       "      }\n",
       "    }, 10, root)\n",
       "  }\n",
       "})(window);"
      ],
      "application/vnd.bokehjs_exec.v0+json": ""
     },
     "metadata": {
      "application/vnd.bokehjs_exec.v0+json": {
       "id": "5877"
      }
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "\n",
    "source = ColumnDataSource(data=dict(date=data[\"time\"].to_numpy(), value=data[\"cases\"].to_numpy()))\n",
    "\n",
    "p = figure(plot_height=300, plot_width=600, tools=\"xpan\", toolbar_location=None,\n",
    "           x_axis_location=\"above\", x_range=(data[\"time\"][5], data[\"time\"][105]))\n",
    "\n",
    "p.line('date', 'value', source=source, \n",
    "       legend_label=\"Casos\", line_width=2, color=\"#f4511e\", line_cap='round', line_alpha=0.9)\n",
    "\n",
    "for dataset in final_data[\"data\"][\"resampled\"]:\n",
    "    rsource = ColumnDataSource(data=dict(date=dataset[\"t\"], value=dataset[\"I\"]))\n",
    "    p.scatter('date', 'value', source=rsource, \n",
    "       legend_label=\"Casos reamostrados\", fill_color=\"#8e44ad\", size=4, line_alpha=0)\n",
    "\n",
    "p.yaxis.axis_label = 'Indivíduos'\n",
    "p.grid.grid_line_alpha = 0\n",
    "p.xgrid.band_fill_color = \"navy\"\n",
    "p.xgrid.band_fill_alpha = 0.1\n",
    "p.toolbar.autohide = True\n",
    "\n",
    "select = figure(title=\"Drag the middle and edges of the selection box to change the range above\",\n",
    "                plot_height=130, plot_width=600, y_range=p.y_range,\n",
    "                y_axis_type=None, tools=\"\", toolbar_location=None)\n",
    "\n",
    "range_tool = RangeTool(x_range=p.x_range)\n",
    "range_tool.overlay.fill_color = \"navy\"\n",
    "range_tool.overlay.fill_alpha = 0.2\n",
    "\n",
    "select.line('date', 'value', source=source,\n",
    "            line_width=2, color=\"#f4511e\", line_cap='round', line_alpha=0.9)\n",
    "select.ygrid.grid_line_color = None\n",
    "select.add_tools(range_tool)\n",
    "select.toolbar.active_multi = range_tool\n",
    "select.xaxis.axis_label = 'Ano'\n",
    "\n",
    "show(column(p, select))\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "\n",
       "\n",
       "\n",
       "\n",
       "\n",
       "\n",
       "  <div class=\"bk-root\" id=\"8945213d-9c81-49b8-8f12-a427d273069a\" data-root-id=\"21020\"></div>\n"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "application/javascript": [
       "(function(root) {\n",
       "  function embed_document(root) {\n",
       "    \n",
       "  var docs_json = 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\",\"dtype\":\"float64\",\"shape\":[475]}},\"selected\":{\"id\":\"15049\"},\"selection_policy\":{\"id\":\"15048\"}},\"id\":\"13729\",\"type\":\"ColumnDataSource\"},{\"attributes\":{\"line_alpha\":0.2,\"line_cap\":\"round\",\"line_color\":\"#455a64\",\"line_dash\":[6],\"line_width\":2,\"x\":{\"field\":\"x\"},\"y\":{\"field\":\"y\"}},\"id\":\"15000\",\"type\":\"Line\"},{\"attributes\":{\"data_source\":{\"id\":\"13729\"},\"glyph\":{\"id\":\"13731\"},\"hover_glyph\":null,\"muted_glyph\":null,\"nonselection_glyph\":{\"id\":\"13732\"},\"selection_glyph\":null,\"view\":{\"id\":\"13734\"}},\"id\":\"13733\",\"type\":\"GlyphRenderer\"},{\"attributes\":{\"data\":{\"x\":[1954.5954825462,1954.5954825462],\"y\":[0,10000]},\"selected\":{\"id\":\"14111\"},\"selection_policy\":{\"id\":\"14110\"}},\"id\":\"13779\",\"type\":\"ColumnDataSource\"},{\"attributes\":{\"line_alpha\":0.1,\"line_cap\":\"round\",\"line_color\":\"#0288d1\",\"line_dash\":[6],\"line_width\":4,\"x\":{\"field\":\"date\"},\"y\":{\"field\":\"value\"}},\"id\":\"13732\",\"type\":\"Line\"},{\"attributes\":{},\"id\":\"13778\",\"type\":\"Selection\"},{\"attributes\":{\"line_alpha\":0.1,\"line_cap\":\"round\",\"line_color\":\"#455a64\",\"line_dash\":[6],\"line_width\":2,\"x\":{\"field\":\"x\"},\"y\":{\"field\":\"y\"}},\"id\":\"13781\",\"type\":\"Line\"},{\"attributes\":{\"line_alpha\":0.2,\"line_cap\":\"round\",\"line_color\":\"#455a64\",\"line_dash\":[6],\"line_width\":2,\"x\":{\"field\":\"x\"},\"y\":{\"field\":\"y\"}},\"id\":\"13780\",\"type\":\"Line\"},{\"attributes\":{\"source\":{\"id\":\"13779\"}},\"id\":\"13783\",\"type\":\"CDSView\"},{\"attributes\":{\"data_source\":{\"id\":\"13779\"},\"glyph\":{\"id\":\"13780\"},\"hover_glyph\":null,\"muted_glyph\":null,\"nonselection_glyph\":{\"id\":\"13781\"},\"selection_glyph\":null,\"view\":{\"id\":\"13783\"}},\"id\":\"13782\",\"type\":\"GlyphRenderer\"}],\"root_ids\":[\"21020\"]},\"title\":\"Bokeh Application\",\"version\":\"2.0.1\"}};\n",
       "  var render_items = [{\"docid\":\"115c1b27-a3de-4c63-a6b5-10fd634dc596\",\"root_ids\":[\"21020\"],\"roots\":{\"21020\":\"8945213d-9c81-49b8-8f12-a427d273069a\"}}];\n",
       "  root.Bokeh.embed.embed_items_notebook(docs_json, render_items);\n",
       "\n",
       "  }\n",
       "  if (root.Bokeh !== undefined) {\n",
       "    embed_document(root);\n",
       "  } else {\n",
       "    var attempts = 0;\n",
       "    var timer = setInterval(function(root) {\n",
       "      if (root.Bokeh !== undefined) {\n",
       "        clearInterval(timer);\n",
       "        embed_document(root);\n",
       "      } else {\n",
       "        attempts++;\n",
       "        if (attempts > 100) {\n",
       "          clearInterval(timer);\n",
       "          console.log(\"Bokeh: ERROR: Unable to run BokehJS code because BokehJS library is missing\");\n",
       "        }\n",
       "      }\n",
       "    }, 10, root)\n",
       "  }\n",
       "})(window);"
      ],
      "application/vnd.bokehjs_exec.v0+json": ""
     },
     "metadata": {
      "application/vnd.bokehjs_exec.v0+json": {
       "id": "21020"
      }
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "\n",
    "p1 = figure(plot_height=300, plot_width=600, tools=\"xpan\", toolbar_location=None,\n",
    "            x_axis_location=\"above\", x_range=p.x_range)\n",
    "\n",
    "p1.line('date', 'value', source=source, \n",
    "       legend_label=\"Casos\", line_width=2, color=\"#f4511e\", line_cap='round', line_alpha=0.9)\n",
    "\n",
    "for dataset in final_data[\"data\"][\"simulated\"]:\n",
    "    psource = ColumnDataSource(data=dict(date=dataset[\"t\"], value=dataset[\"I\"]))\n",
    "    p1.line('date', 'value', source=psource, line_dash=\"dashed\",\n",
    "           legend_label=\"Modelo estimado\", color=\"#0288d1\", \n",
    "           line_width=4, line_cap='round', line_alpha=0.9)\n",
    "    \n",
    "    window_bound_lower = [dataset[\"t\"][0], dataset[\"t\"][0]]\n",
    "    window_bound_upper = [dataset[\"t\"][-1], dataset[\"t\"][-1]]\n",
    "    window_limits = [0, 10000]\n",
    "    \n",
    "    p.line(window_bound_lower, window_limits, line_dash=\"dashed\",\n",
    "           legend_label=\"Janela da epidemia\", color=\"#455a64\", \n",
    "           line_width=2, line_cap='round', line_alpha=0.2)\n",
    "    p.line(window_bound_upper, window_limits, line_dash=\"dashed\",\n",
    "           legend_label=\"Janela da epidemia\", color=\"#455a64\", \n",
    "           line_width=2, line_cap='round', line_alpha=0.2)\n",
    "    p1.line(window_bound_lower, window_limits, line_dash=\"dashed\",\n",
    "           legend_label=\"Janela da epidemia\", color=\"#455a64\", \n",
    "           line_width=2, line_cap='round', line_alpha=0.2)\n",
    "    p1.line(window_bound_upper, window_limits, line_dash=\"dashed\",\n",
    "           legend_label=\"Janela da epidemia\", color=\"#455a64\", \n",
    "           line_width=2, line_cap='round', line_alpha=0.2)\n",
    "\n",
    "p1.xaxis.axis_line_alpha = 0\n",
    "p1.xaxis.major_label_text_color = None\n",
    "p1.xaxis.major_tick_line_color = None\n",
    "p1.xaxis.minor_tick_line_color = None\n",
    "p1.yaxis.axis_label = 'Indivíduos'\n",
    "p1.grid.grid_line_alpha = 0\n",
    "p1.xgrid.band_fill_color = \"navy\"\n",
    "p1.xgrid.band_fill_alpha = 0.1\n",
    "p1.toolbar.autohide = True\n",
    "\n",
    "show(column(p, p1, select))\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Salvando as variáveis\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "metadata": {},
   "outputs": [],
   "source": [
    "\n",
    "import pickle\n",
    "\n",
    "save_variable = {\n",
    "    \"data\" : data,\n",
    "    \"final\" : final_data\n",
    "}\n",
    "\n",
    "with open('UK_estimated_data.pickle', 'wb') as handle:\n",
    "    pickle.dump(save_variable, handle)\n"
   ]
  }
 ],
 "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
}