synthetic_airplane.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "a1335526-8d69-4fd8-924a-997a7b649d82",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Requirement already satisfied: verde in c:\\users\\laisr\\miniforge3\\lib\\site-packages (1.8.0)\n",
      "Requirement already satisfied: harmonica in c:\\users\\laisr\\miniforge3\\lib\\site-packages (0.6.0)\n",
      "Requirement already satisfied: pandas in c:\\users\\laisr\\miniforge3\\lib\\site-packages (2.2.2)\n",
      "Requirement already satisfied: matplotlib in c:\\users\\laisr\\miniforge3\\lib\\site-packages (3.9.0)\n",
      "Requirement already satisfied: numpy>=1.19 in c:\\users\\laisr\\miniforge3\\lib\\site-packages (from verde) (1.26.4)\n",
      "Requirement already satisfied: scipy>=1.5 in c:\\users\\laisr\\miniforge3\\lib\\site-packages (from verde) (1.13.1)\n",
      "Requirement already satisfied: xarray>=0.16 in c:\\users\\laisr\\miniforge3\\lib\\site-packages (from verde) (2024.5.0)\n",
      "Requirement already satisfied: scikit-learn>=0.24 in c:\\users\\laisr\\miniforge3\\lib\\site-packages (from verde) (1.5.0)\n",
      "Requirement already satisfied: pooch>=1.2 in c:\\users\\laisr\\miniforge3\\lib\\site-packages (from verde) (1.8.2)\n",
      "Requirement already satisfied: dask>=2021.05.0 in c:\\users\\laisr\\miniforge3\\lib\\site-packages (from verde) (2024.5.2)\n",
      "Requirement already satisfied: numba>=0.52 in c:\\users\\laisr\\miniforge3\\lib\\site-packages (from harmonica) (0.59.1)\n",
      "Requirement already satisfied: xrft>=1.0 in c:\\users\\laisr\\miniforge3\\lib\\site-packages (from harmonica) (1.0.1)\n",
      "Requirement already satisfied: python-dateutil>=2.8.2 in c:\\users\\laisr\\miniforge3\\lib\\site-packages (from pandas) (2.9.0)\n",
      "Requirement already satisfied: pytz>=2020.1 in c:\\users\\laisr\\miniforge3\\lib\\site-packages (from pandas) (2024.1)\n",
      "Requirement already satisfied: tzdata>=2022.7 in c:\\users\\laisr\\miniforge3\\lib\\site-packages (from pandas) (2024.1)\n",
      "Requirement already satisfied: contourpy>=1.0.1 in c:\\users\\laisr\\miniforge3\\lib\\site-packages (from matplotlib) (1.2.1)\n",
      "Requirement already satisfied: cycler>=0.10 in c:\\users\\laisr\\miniforge3\\lib\\site-packages (from matplotlib) (0.12.1)\n",
      "Requirement already satisfied: fonttools>=4.22.0 in c:\\users\\laisr\\miniforge3\\lib\\site-packages (from matplotlib) (4.53.0)\n",
      "Requirement already satisfied: kiwisolver>=1.3.1 in c:\\users\\laisr\\miniforge3\\lib\\site-packages (from matplotlib) (1.4.5)\n",
      "Requirement already satisfied: packaging>=20.0 in c:\\users\\laisr\\miniforge3\\lib\\site-packages (from matplotlib) (24.0)\n",
      "Requirement already satisfied: pillow>=8 in c:\\users\\laisr\\miniforge3\\lib\\site-packages (from matplotlib) (10.3.0)\n",
      "Requirement already satisfied: pyparsing>=2.3.1 in c:\\users\\laisr\\miniforge3\\lib\\site-packages (from matplotlib) (3.1.2)\n",
      "Requirement already satisfied: click>=8.1 in c:\\users\\laisr\\miniforge3\\lib\\site-packages (from dask>=2021.05.0->verde) (8.1.7)\n",
      "Requirement already satisfied: cloudpickle>=1.5.0 in c:\\users\\laisr\\miniforge3\\lib\\site-packages (from dask>=2021.05.0->verde) (3.0.0)\n",
      "Requirement already satisfied: fsspec>=2021.09.0 in c:\\users\\laisr\\miniforge3\\lib\\site-packages (from dask>=2021.05.0->verde) (2024.6.0)\n",
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      "Requirement already satisfied: toolz>=0.10.0 in c:\\users\\laisr\\miniforge3\\lib\\site-packages (from dask>=2021.05.0->verde) (0.12.1)\n",
      "Requirement already satisfied: importlib-metadata>=4.13.0 in c:\\users\\laisr\\miniforge3\\lib\\site-packages (from dask>=2021.05.0->verde) (7.1.0)\n",
      "Requirement already satisfied: llvmlite<0.43,>=0.42.0dev0 in c:\\users\\laisr\\miniforge3\\lib\\site-packages (from numba>=0.52->harmonica) (0.42.0)\n",
      "Requirement already satisfied: platformdirs>=2.5.0 in c:\\users\\laisr\\miniforge3\\lib\\site-packages (from pooch>=1.2->verde) (4.2.0)\n",
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      "Requirement already satisfied: colorama in c:\\users\\laisr\\miniforge3\\lib\\site-packages (from click>=8.1->dask>=2021.05.0->verde) (0.4.6)\n",
      "Requirement already satisfied: zipp>=0.5 in c:\\users\\laisr\\miniforge3\\lib\\site-packages (from importlib-metadata>=4.13.0->dask>=2021.05.0->verde) (3.17.0)\n",
      "Requirement already satisfied: locket in c:\\users\\laisr\\miniforge3\\lib\\site-packages (from partd>=1.2.0->dask>=2021.05.0->verde) (1.0.0)\n",
      "Requirement already satisfied: charset-normalizer<4,>=2 in c:\\users\\laisr\\miniforge3\\lib\\site-packages (from requests>=2.19.0->pooch>=1.2->verde) (3.3.2)\n",
      "Requirement already satisfied: idna<4,>=2.5 in c:\\users\\laisr\\miniforge3\\lib\\site-packages (from requests>=2.19.0->pooch>=1.2->verde) (3.6)\n",
      "Requirement already satisfied: urllib3<3,>=1.21.1 in c:\\users\\laisr\\miniforge3\\lib\\site-packages (from requests>=2.19.0->pooch>=1.2->verde) (2.2.1)\n",
      "Requirement already satisfied: certifi>=2017.4.17 in c:\\users\\laisr\\miniforge3\\lib\\site-packages (from requests>=2.19.0->pooch>=1.2->verde) (2024.2.2)\n"
     ]
    }
   ],
   "source": [
    "! pip install verde harmonica pandas matplotlib"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "8466eb68-1185-45c1-bfb4-210fa35b0f50",
   "metadata": {},
   "outputs": [],
   "source": [
    "import numpy as np\n",
    "import matplotlib.pyplot as plt\n",
    "import harmonica as hm\n",
    "import verde as vd\n",
    "import pandas as pd\n",
    "import warnings"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "736bd05f-febb-4732-a752-e06d7f6affef",
   "metadata": {},
   "outputs": [],
   "source": [
    "warnings.filterwarnings('ignore')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "4b9ef183-95c2-4c9e-8beb-66a32f428240",
   "metadata": {},
   "outputs": [],
   "source": [
    "region = [0, 100e3, 0, 90e3] \n",
    "spacing = (500,5000) # Espaçamento entre as linhas de voo\n",
    "coordinates = vd.grid_coordinates(region=region, spacing=spacing, extra_coords=500) # Coordenadas do levantamento \n"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "645312ba-dd75-4810-ae22-1e64be5bd6c5",
   "metadata": {},
   "source": [
    "Com spacing=5000, R_2 verdadeiro = 0.9969935689798417\n",
    "\n",
    "média sem blocos = mean: 0.7517748627264079\n",
    "\n",
    "média com blocos = mean: 0.6484019128353826"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "9978f733-af8a-4d89-874e-c2c117b093c1",
   "metadata": {},
   "source": [
    "Com spacing=10000, R_2 verdadeiro = -0.04194173260685585\n",
    "\n",
    "média sem blocos = mean: -0.08553868650921963\n",
    "\n",
    "média com blocos = -0.04198072658162777"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "897b45d4-5cd1-479a-af71-566a17510aa7",
   "metadata": {},
   "source": [
    "Com spacing=1000, R_2 verdadeiro = 0.9999957968369876\n",
    "\n",
    "média sem blocos = 0.9999633167325591 \n",
    "\n",
    "média com blocos = 0.9998211670181172"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "28fc2917-d093-4cdb-a39c-4ab7f6292a7c",
   "metadata": {},
   "outputs": [],
   "source": [
    "def plot_region(ax, region):\n",
    "    \"Plot the region as a solid line.\"\n",
    "    west, east, south, north = region\n",
    "    ax.add_patch(\n",
    "        plt.Rectangle((west, south), east, north, fill=None, label=\"Region Bounds\")\n",
    "    )\n",
    "\n",
    "def plot_grid(ax, coordinates, linestyles=\"dotted\", region=None, pad=50, **kwargs):\n",
    "    \"Plot the grid coordinates as dots and lines.\"\n",
    "    data_region = vd.get_region(coordinates)\n",
    "    ax.vlines(\n",
    "        coordinates[0][0],\n",
    "        ymin=data_region[2],\n",
    "        ymax=data_region[3],\n",
    "        linestyles=linestyles,\n",
    "        zorder=0,\n",
    "    )\n",
    "    ax.hlines(\n",
    "        coordinates[1][:, 1],\n",
    "        xmin=data_region[0],\n",
    "        xmax=data_region[1],\n",
    "        linestyles=linestyles,\n",
    "        zorder=0,\n",
    "    )\n",
    "    ax.scatter(*coordinates, **kwargs)\n",
    "    if pad:\n",
    "        padded = vd.pad_region(region, pad=pad)\n",
    "        plt.xlim(padded[:2])\n",
    "        plt.ylim(padded[2:])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "e4686cc1-ed60-4450-bec6-54ad5e30bec9",
   "metadata": {},
   "outputs": [
    {
     "data": {
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",
      "text/plain": [
       "<Figure size 600x600 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "easting, northing = coordinates[0], coordinates[1]\n",
    "plt.figure(figsize=(6, 6))\n",
    "ax = plt.subplot(111)\n",
    "plot_region(ax=ax, region=region)\n",
    "plot_grid(\n",
    "    coordinates=[easting,northing],\n",
    "    ax=ax,\n",
    "    region=region,\n",
    "    label=\"Square Region Grid Nodes\",\n",
    "    marker=\".\",\n",
    "    color=\"black\",\n",
    "    s=100,\n",
    ")\n",
    "\n",
    "plt.xlabel(\"Easting\")\n",
    "plt.ylabel(\"Northing\")\n",
    "plt.legend(loc=\"upper center\", bbox_to_anchor=(0.5, 1.15))\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "id": "e829750c-a14d-4075-bb36-db879f682d38",
   "metadata": {},
   "outputs": [],
   "source": [
    "\n",
    "\n",
    "prismas = [\n",
    "    [10e3, 15e3, 20e3, 35e3, -1e3,  0],\n",
    "    [60e3, 80e3, 50e3, 70e3, -2e3,  -0.5e3],\n",
    "]\n",
    "densidades = [500, -300]\n",
    "gz = hm.prism_gravity(coordinates, prismas, densidades, field=\"g_z\") #gz gerado pelos prismas\n",
    "# criando a malha regular pra plotar o R_2 verdadeiro\n",
    "grid_coordinates = vd.grid_coordinates(region=region, spacing=2000, extra_coords=500) # coordenadas da malha regular\n",
    "gz_grid = hm.prism_gravity(grid_coordinates, prismas, densidades, field=\"g_z\") #grid gz \n",
    "grid_true = vd.make_xarray_grid(grid_coordinates, gz_grid, data_names=\"g_z\", extra_coords_names=\"upward\")#grid regular"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "id": "724cc922-5fd4-4c0b-b349-11bfad4ae1fc",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.collections.QuadMesh at 0x1c3b493ad40>"
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "grid_true.g_z.plot()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "id": "f8d017c3-9588-4506-b5f9-a2b881accc11",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.colorbar.Colorbar at 0x1c3b48dbc70>"
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.scatter(coordinates[0],coordinates[1],s=5,c=gz)\n",
    "plt.colorbar() # resultado do levantamento"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "39028b6b-4090-4bb5-a10f-4d347fa83048",
   "metadata": {},
   "source": [
    "# Fontes Equivalentes"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "id": "78918f4a-d456-4216-ba7f-357b2fce8b08",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<style>#sk-container-id-1 {\n",
       "  /* Definition of color scheme common for light and dark mode */\n",
       "  --sklearn-color-text: black;\n",
       "  --sklearn-color-line: gray;\n",
       "  /* Definition of color scheme for unfitted estimators */\n",
       "  --sklearn-color-unfitted-level-0: #fff5e6;\n",
       "  --sklearn-color-unfitted-level-1: #f6e4d2;\n",
       "  --sklearn-color-unfitted-level-2: #ffe0b3;\n",
       "  --sklearn-color-unfitted-level-3: chocolate;\n",
       "  /* Definition of color scheme for fitted estimators */\n",
       "  --sklearn-color-fitted-level-0: #f0f8ff;\n",
       "  --sklearn-color-fitted-level-1: #d4ebff;\n",
       "  --sklearn-color-fitted-level-2: #b3dbfd;\n",
       "  --sklearn-color-fitted-level-3: cornflowerblue;\n",
       "\n",
       "  /* Specific color for light theme */\n",
       "  --sklearn-color-text-on-default-background: var(--sg-text-color, var(--theme-code-foreground, var(--jp-content-font-color1, black)));\n",
       "  --sklearn-color-background: var(--sg-background-color, var(--theme-background, var(--jp-layout-color0, white)));\n",
       "  --sklearn-color-border-box: var(--sg-text-color, var(--theme-code-foreground, var(--jp-content-font-color1, black)));\n",
       "  --sklearn-color-icon: #696969;\n",
       "\n",
       "  @media (prefers-color-scheme: dark) {\n",
       "    /* Redefinition of color scheme for dark theme */\n",
       "    --sklearn-color-text-on-default-background: var(--sg-text-color, var(--theme-code-foreground, var(--jp-content-font-color1, white)));\n",
       "    --sklearn-color-background: var(--sg-background-color, var(--theme-background, var(--jp-layout-color0, #111)));\n",
       "    --sklearn-color-border-box: var(--sg-text-color, var(--theme-code-foreground, var(--jp-content-font-color1, white)));\n",
       "    --sklearn-color-icon: #878787;\n",
       "  }\n",
       "}\n",
       "\n",
       "#sk-container-id-1 {\n",
       "  color: var(--sklearn-color-text);\n",
       "}\n",
       "\n",
       "#sk-container-id-1 pre {\n",
       "  padding: 0;\n",
       "}\n",
       "\n",
       "#sk-container-id-1 input.sk-hidden--visually {\n",
       "  border: 0;\n",
       "  clip: rect(1px 1px 1px 1px);\n",
       "  clip: rect(1px, 1px, 1px, 1px);\n",
       "  height: 1px;\n",
       "  margin: -1px;\n",
       "  overflow: hidden;\n",
       "  padding: 0;\n",
       "  position: absolute;\n",
       "  width: 1px;\n",
       "}\n",
       "\n",
       "#sk-container-id-1 div.sk-dashed-wrapped {\n",
       "  border: 1px dashed var(--sklearn-color-line);\n",
       "  margin: 0 0.4em 0.5em 0.4em;\n",
       "  box-sizing: border-box;\n",
       "  padding-bottom: 0.4em;\n",
       "  background-color: var(--sklearn-color-background);\n",
       "}\n",
       "\n",
       "#sk-container-id-1 div.sk-container {\n",
       "  /* jupyter's `normalize.less` sets `[hidden] { display: none; }`\n",
       "     but bootstrap.min.css set `[hidden] { display: none !important; }`\n",
       "     so we also need the `!important` here to be able to override the\n",
       "     default hidden behavior on the sphinx rendered scikit-learn.org.\n",
       "     See: https://github.com/scikit-learn/scikit-learn/issues/21755 */\n",
       "  display: inline-block !important;\n",
       "  position: relative;\n",
       "}\n",
       "\n",
       "#sk-container-id-1 div.sk-text-repr-fallback {\n",
       "  display: none;\n",
       "}\n",
       "\n",
       "div.sk-parallel-item,\n",
       "div.sk-serial,\n",
       "div.sk-item {\n",
       "  /* draw centered vertical line to link estimators */\n",
       "  background-image: linear-gradient(var(--sklearn-color-text-on-default-background), var(--sklearn-color-text-on-default-background));\n",
       "  background-size: 2px 100%;\n",
       "  background-repeat: no-repeat;\n",
       "  background-position: center center;\n",
       "}\n",
       "\n",
       "/* Parallel-specific style estimator block */\n",
       "\n",
       "#sk-container-id-1 div.sk-parallel-item::after {\n",
       "  content: \"\";\n",
       "  width: 100%;\n",
       "  border-bottom: 2px solid var(--sklearn-color-text-on-default-background);\n",
       "  flex-grow: 1;\n",
       "}\n",
       "\n",
       "#sk-container-id-1 div.sk-parallel {\n",
       "  display: flex;\n",
       "  align-items: stretch;\n",
       "  justify-content: center;\n",
       "  background-color: var(--sklearn-color-background);\n",
       "  position: relative;\n",
       "}\n",
       "\n",
       "#sk-container-id-1 div.sk-parallel-item {\n",
       "  display: flex;\n",
       "  flex-direction: column;\n",
       "}\n",
       "\n",
       "#sk-container-id-1 div.sk-parallel-item:first-child::after {\n",
       "  align-self: flex-end;\n",
       "  width: 50%;\n",
       "}\n",
       "\n",
       "#sk-container-id-1 div.sk-parallel-item:last-child::after {\n",
       "  align-self: flex-start;\n",
       "  width: 50%;\n",
       "}\n",
       "\n",
       "#sk-container-id-1 div.sk-parallel-item:only-child::after {\n",
       "  width: 0;\n",
       "}\n",
       "\n",
       "/* Serial-specific style estimator block */\n",
       "\n",
       "#sk-container-id-1 div.sk-serial {\n",
       "  display: flex;\n",
       "  flex-direction: column;\n",
       "  align-items: center;\n",
       "  background-color: var(--sklearn-color-background);\n",
       "  padding-right: 1em;\n",
       "  padding-left: 1em;\n",
       "}\n",
       "\n",
       "\n",
       "/* Toggleable style: style used for estimator/Pipeline/ColumnTransformer box that is\n",
       "clickable and can be expanded/collapsed.\n",
       "- Pipeline and ColumnTransformer use this feature and define the default style\n",
       "- Estimators will overwrite some part of the style using the `sk-estimator` class\n",
       "*/\n",
       "\n",
       "/* Pipeline and ColumnTransformer style (default) */\n",
       "\n",
       "#sk-container-id-1 div.sk-toggleable {\n",
       "  /* Default theme specific background. It is overwritten whether we have a\n",
       "  specific estimator or a Pipeline/ColumnTransformer */\n",
       "  background-color: var(--sklearn-color-background);\n",
       "}\n",
       "\n",
       "/* Toggleable label */\n",
       "#sk-container-id-1 label.sk-toggleable__label {\n",
       "  cursor: pointer;\n",
       "  display: block;\n",
       "  width: 100%;\n",
       "  margin-bottom: 0;\n",
       "  padding: 0.5em;\n",
       "  box-sizing: border-box;\n",
       "  text-align: center;\n",
       "}\n",
       "\n",
       "#sk-container-id-1 label.sk-toggleable__label-arrow:before {\n",
       "  /* Arrow on the left of the label */\n",
       "  content: \"▸\";\n",
       "  float: left;\n",
       "  margin-right: 0.25em;\n",
       "  color: var(--sklearn-color-icon);\n",
       "}\n",
       "\n",
       "#sk-container-id-1 label.sk-toggleable__label-arrow:hover:before {\n",
       "  color: var(--sklearn-color-text);\n",
       "}\n",
       "\n",
       "/* Toggleable content - dropdown */\n",
       "\n",
       "#sk-container-id-1 div.sk-toggleable__content {\n",
       "  max-height: 0;\n",
       "  max-width: 0;\n",
       "  overflow: hidden;\n",
       "  text-align: left;\n",
       "  /* unfitted */\n",
       "  background-color: var(--sklearn-color-unfitted-level-0);\n",
       "}\n",
       "\n",
       "#sk-container-id-1 div.sk-toggleable__content.fitted {\n",
       "  /* fitted */\n",
       "  background-color: var(--sklearn-color-fitted-level-0);\n",
       "}\n",
       "\n",
       "#sk-container-id-1 div.sk-toggleable__content pre {\n",
       "  margin: 0.2em;\n",
       "  border-radius: 0.25em;\n",
       "  color: var(--sklearn-color-text);\n",
       "  /* unfitted */\n",
       "  background-color: var(--sklearn-color-unfitted-level-0);\n",
       "}\n",
       "\n",
       "#sk-container-id-1 div.sk-toggleable__content.fitted pre {\n",
       "  /* unfitted */\n",
       "  background-color: var(--sklearn-color-fitted-level-0);\n",
       "}\n",
       "\n",
       "#sk-container-id-1 input.sk-toggleable__control:checked~div.sk-toggleable__content {\n",
       "  /* Expand drop-down */\n",
       "  max-height: 200px;\n",
       "  max-width: 100%;\n",
       "  overflow: auto;\n",
       "}\n",
       "\n",
       "#sk-container-id-1 input.sk-toggleable__control:checked~label.sk-toggleable__label-arrow:before {\n",
       "  content: \"▾\";\n",
       "}\n",
       "\n",
       "/* Pipeline/ColumnTransformer-specific style */\n",
       "\n",
       "#sk-container-id-1 div.sk-label input.sk-toggleable__control:checked~label.sk-toggleable__label {\n",
       "  color: var(--sklearn-color-text);\n",
       "  background-color: var(--sklearn-color-unfitted-level-2);\n",
       "}\n",
       "\n",
       "#sk-container-id-1 div.sk-label.fitted input.sk-toggleable__control:checked~label.sk-toggleable__label {\n",
       "  background-color: var(--sklearn-color-fitted-level-2);\n",
       "}\n",
       "\n",
       "/* Estimator-specific style */\n",
       "\n",
       "/* Colorize estimator box */\n",
       "#sk-container-id-1 div.sk-estimator input.sk-toggleable__control:checked~label.sk-toggleable__label {\n",
       "  /* unfitted */\n",
       "  background-color: var(--sklearn-color-unfitted-level-2);\n",
       "}\n",
       "\n",
       "#sk-container-id-1 div.sk-estimator.fitted input.sk-toggleable__control:checked~label.sk-toggleable__label {\n",
       "  /* fitted */\n",
       "  background-color: var(--sklearn-color-fitted-level-2);\n",
       "}\n",
       "\n",
       "#sk-container-id-1 div.sk-label label.sk-toggleable__label,\n",
       "#sk-container-id-1 div.sk-label label {\n",
       "  /* The background is the default theme color */\n",
       "  color: var(--sklearn-color-text-on-default-background);\n",
       "}\n",
       "\n",
       "/* On hover, darken the color of the background */\n",
       "#sk-container-id-1 div.sk-label:hover label.sk-toggleable__label {\n",
       "  color: var(--sklearn-color-text);\n",
       "  background-color: var(--sklearn-color-unfitted-level-2);\n",
       "}\n",
       "\n",
       "/* Label box, darken color on hover, fitted */\n",
       "#sk-container-id-1 div.sk-label.fitted:hover label.sk-toggleable__label.fitted {\n",
       "  color: var(--sklearn-color-text);\n",
       "  background-color: var(--sklearn-color-fitted-level-2);\n",
       "}\n",
       "\n",
       "/* Estimator label */\n",
       "\n",
       "#sk-container-id-1 div.sk-label label {\n",
       "  font-family: monospace;\n",
       "  font-weight: bold;\n",
       "  display: inline-block;\n",
       "  line-height: 1.2em;\n",
       "}\n",
       "\n",
       "#sk-container-id-1 div.sk-label-container {\n",
       "  text-align: center;\n",
       "}\n",
       "\n",
       "/* Estimator-specific */\n",
       "#sk-container-id-1 div.sk-estimator {\n",
       "  font-family: monospace;\n",
       "  border: 1px dotted var(--sklearn-color-border-box);\n",
       "  border-radius: 0.25em;\n",
       "  box-sizing: border-box;\n",
       "  margin-bottom: 0.5em;\n",
       "  /* unfitted */\n",
       "  background-color: var(--sklearn-color-unfitted-level-0);\n",
       "}\n",
       "\n",
       "#sk-container-id-1 div.sk-estimator.fitted {\n",
       "  /* fitted */\n",
       "  background-color: var(--sklearn-color-fitted-level-0);\n",
       "}\n",
       "\n",
       "/* on hover */\n",
       "#sk-container-id-1 div.sk-estimator:hover {\n",
       "  /* unfitted */\n",
       "  background-color: var(--sklearn-color-unfitted-level-2);\n",
       "}\n",
       "\n",
       "#sk-container-id-1 div.sk-estimator.fitted:hover {\n",
       "  /* fitted */\n",
       "  background-color: var(--sklearn-color-fitted-level-2);\n",
       "}\n",
       "\n",
       "/* Specification for estimator info (e.g. \"i\" and \"?\") */\n",
       "\n",
       "/* Common style for \"i\" and \"?\" */\n",
       "\n",
       ".sk-estimator-doc-link,\n",
       "a:link.sk-estimator-doc-link,\n",
       "a:visited.sk-estimator-doc-link {\n",
       "  float: right;\n",
       "  font-size: smaller;\n",
       "  line-height: 1em;\n",
       "  font-family: monospace;\n",
       "  background-color: var(--sklearn-color-background);\n",
       "  border-radius: 1em;\n",
       "  height: 1em;\n",
       "  width: 1em;\n",
       "  text-decoration: none !important;\n",
       "  margin-left: 1ex;\n",
       "  /* unfitted */\n",
       "  border: var(--sklearn-color-unfitted-level-1) 1pt solid;\n",
       "  color: var(--sklearn-color-unfitted-level-1);\n",
       "}\n",
       "\n",
       ".sk-estimator-doc-link.fitted,\n",
       "a:link.sk-estimator-doc-link.fitted,\n",
       "a:visited.sk-estimator-doc-link.fitted {\n",
       "  /* fitted */\n",
       "  border: var(--sklearn-color-fitted-level-1) 1pt solid;\n",
       "  color: var(--sklearn-color-fitted-level-1);\n",
       "}\n",
       "\n",
       "/* On hover */\n",
       "div.sk-estimator:hover .sk-estimator-doc-link:hover,\n",
       ".sk-estimator-doc-link:hover,\n",
       "div.sk-label-container:hover .sk-estimator-doc-link:hover,\n",
       ".sk-estimator-doc-link:hover {\n",
       "  /* unfitted */\n",
       "  background-color: var(--sklearn-color-unfitted-level-3);\n",
       "  color: var(--sklearn-color-background);\n",
       "  text-decoration: none;\n",
       "}\n",
       "\n",
       "div.sk-estimator.fitted:hover .sk-estimator-doc-link.fitted:hover,\n",
       ".sk-estimator-doc-link.fitted:hover,\n",
       "div.sk-label-container:hover .sk-estimator-doc-link.fitted:hover,\n",
       ".sk-estimator-doc-link.fitted:hover {\n",
       "  /* fitted */\n",
       "  background-color: var(--sklearn-color-fitted-level-3);\n",
       "  color: var(--sklearn-color-background);\n",
       "  text-decoration: none;\n",
       "}\n",
       "\n",
       "/* Span, style for the box shown on hovering the info icon */\n",
       ".sk-estimator-doc-link span {\n",
       "  display: none;\n",
       "  z-index: 9999;\n",
       "  position: relative;\n",
       "  font-weight: normal;\n",
       "  right: .2ex;\n",
       "  padding: .5ex;\n",
       "  margin: .5ex;\n",
       "  width: min-content;\n",
       "  min-width: 20ex;\n",
       "  max-width: 50ex;\n",
       "  color: var(--sklearn-color-text);\n",
       "  box-shadow: 2pt 2pt 4pt #999;\n",
       "  /* unfitted */\n",
       "  background: var(--sklearn-color-unfitted-level-0);\n",
       "  border: .5pt solid var(--sklearn-color-unfitted-level-3);\n",
       "}\n",
       "\n",
       ".sk-estimator-doc-link.fitted span {\n",
       "  /* fitted */\n",
       "  background: var(--sklearn-color-fitted-level-0);\n",
       "  border: var(--sklearn-color-fitted-level-3);\n",
       "}\n",
       "\n",
       ".sk-estimator-doc-link:hover span {\n",
       "  display: block;\n",
       "}\n",
       "\n",
       "/* \"?\"-specific style due to the `<a>` HTML tag */\n",
       "\n",
       "#sk-container-id-1 a.estimator_doc_link {\n",
       "  float: right;\n",
       "  font-size: 1rem;\n",
       "  line-height: 1em;\n",
       "  font-family: monospace;\n",
       "  background-color: var(--sklearn-color-background);\n",
       "  border-radius: 1rem;\n",
       "  height: 1rem;\n",
       "  width: 1rem;\n",
       "  text-decoration: none;\n",
       "  /* unfitted */\n",
       "  color: var(--sklearn-color-unfitted-level-1);\n",
       "  border: var(--sklearn-color-unfitted-level-1) 1pt solid;\n",
       "}\n",
       "\n",
       "#sk-container-id-1 a.estimator_doc_link.fitted {\n",
       "  /* fitted */\n",
       "  border: var(--sklearn-color-fitted-level-1) 1pt solid;\n",
       "  color: var(--sklearn-color-fitted-level-1);\n",
       "}\n",
       "\n",
       "/* On hover */\n",
       "#sk-container-id-1 a.estimator_doc_link:hover {\n",
       "  /* unfitted */\n",
       "  background-color: var(--sklearn-color-unfitted-level-3);\n",
       "  color: var(--sklearn-color-background);\n",
       "  text-decoration: none;\n",
       "}\n",
       "\n",
       "#sk-container-id-1 a.estimator_doc_link.fitted:hover {\n",
       "  /* fitted */\n",
       "  background-color: var(--sklearn-color-fitted-level-3);\n",
       "}\n",
       "</style><div id=\"sk-container-id-1\" class=\"sk-top-container\"><div class=\"sk-text-repr-fallback\"><pre>EquivalentSourcesGB(damping=1, depth=2000)</pre><b>In a Jupyter environment, please rerun this cell to show the HTML representation or trust the notebook. <br />On GitHub, the HTML representation is unable to render, please try loading this page with nbviewer.org.</b></div><div class=\"sk-container\" hidden><div class=\"sk-item\"><div class=\"sk-estimator fitted sk-toggleable\"><input class=\"sk-toggleable__control sk-hidden--visually\" id=\"sk-estimator-id-1\" type=\"checkbox\" checked><label for=\"sk-estimator-id-1\" class=\"sk-toggleable__label fitted sk-toggleable__label-arrow fitted\">&nbsp;EquivalentSourcesGB<span class=\"sk-estimator-doc-link fitted\">i<span>Fitted</span></span></label><div class=\"sk-toggleable__content fitted\"><pre>EquivalentSourcesGB(damping=1, depth=2000)</pre></div> </div></div></div></div>"
      ],
      "text/plain": [
       "EquivalentSourcesGB(damping=1, depth=2000)"
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "fontes = hm.EquivalentSourcesGB(damping=1,depth=2000)\n",
    "\n",
    "fontes.fit([coordinates[0],coordinates[1],coordinates[2]],data=gz) "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "id": "37f36086-8fb5-430d-93d5-0026020a565c",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.collections.QuadMesh at 0x1c3b5bc58d0>"
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "gz_grid_eq = fontes.grid(grid_coordinates,data_names=\"g_z\")\n",
    "gz_grid_eq.g_z.plot() # resultado utilizando fontes equivalentes (interpolação dos dados entre as linhas de voo)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "id": "653f808e-d247-4cbe-8040-9800e3808909",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.collections.QuadMesh at 0x1c3b8855300>"
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Plotando a diferença entre grid_true (levantamento na malha regular) e gz_grid_eq (fontes equivalentes)\n",
    "\n",
    "residuo = grid_true - gz_grid_eq\n",
    "residuo.g_z.plot()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "6b051337-a73f-4461-b99f-71e4debc8912",
   "metadata": {},
   "source": [
    "# R_2 verdadeiro"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "id": "93369b41-9468-47ff-9005-a812f7e1a1bf",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0.959831903760306"
      ]
     },
     "execution_count": 13,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "g_z_medio = np.sum(grid_true.g_z.values)/np.size(grid_true.g_z)\n",
    "residuo_quadrado = np.sum(residuo.g_z.values**2)\n",
    "R_2_true = 1 - (residuo_quadrado/np.sum([(gz - g_z_medio)**2 for gz in grid_true.g_z.values]))\n",
    "\n",
    "R_2_true"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "5c157b84-c981-4d1d-ada5-b93a856128cc",
   "metadata": {},
   "source": [
    "# Using cross-validation to evaluate how well\n",
    "# these equivalent sources can accurately predict the values of the field"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "id": "f24c9660-3568-4ab5-9370-e3603db7cb22",
   "metadata": {},
   "outputs": [],
   "source": [
    "\n",
    "R_2_kfold = (\n",
    "    vd.cross_val_score(\n",
    "        fontes,\n",
    "        coordinates,\n",
    "        gz,\n",
    "    )\n",
    ")\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "id": "c1e99489-075c-44b0-8ecd-54f67d2cfab5",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "min: 0.999852451243023\n",
      "max: 0.9999215224748064\n",
      "mean: 0.9998943160247336\n"
     ]
    }
   ],
   "source": [
    "print(f\"min: {np.min(R_2_kfold)}\")\n",
    "print(f\"max: {np.max(R_2_kfold)}\")\n",
    "print(f\"mean: {np.mean(R_2_kfold)}\")"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "a8e416a8-a5f9-4812-b8a4-ef8397df36fe",
   "metadata": {},
   "source": [
    "# Blocking"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "2ab47131-ff5b-4a66-8b94-25617bb711bb",
   "metadata": {},
   "source": [
    "A média dos R_2 (calculados através da validação cruzada por blocos) equivale ao R_2 verdadeiro com um tamanho de bloco de aproxidamente 5000km, que é o espaçamento entre as linhas de voo.\n",
    "\n",
    "O valor máximo dos R_2 equivale ao R_2 verdadeiro com um tamanho de bloco de aproximadamente 8000km (um pouco maior que este valor).\n",
    "\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "id": "8c9b8c40-98b8-4a4a-ae52-bb187ad744a5",
   "metadata": {},
   "outputs": [],
   "source": [
    "\n",
    "\n",
    "R_2_block = (\n",
    "    vd.cross_val_score(\n",
    "        fontes,\n",
    "        coordinates,\n",
    "        gz,\n",
    "        cv=vd.BlockKFold(spacing=5000, n_splits=5, shuffle=True, random_state=123),\n",
    "    )\n",
    ")\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "id": "488477c9-967a-40bd-87a9-13f1613f5c34",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "min: 0.9035396675612886\n",
      "max: 0.9786407498785515\n",
      "mean: 0.9524938235582715\n"
     ]
    }
   ],
   "source": [
    "print(f\"min: {np.min(R_2_block)}\")\n",
    "print(f\"max: {np.max(R_2_block)}\")\n",
    "print(f\"mean: {np.mean(R_2_block)}\")"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "4f029a98-007b-4332-a52b-183564dc145e",
   "metadata": {},
   "source": [
    "# Variando o número de splits\n",
    "Estou pegando a média dos erros para plotar"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "id": "3aded9a9-3000-4940-a333-aff379322b8e",
   "metadata": {},
   "outputs": [],
   "source": [
    "#Data are first grouped into rectangular blocks of size given by the spacing argument.\n",
    "# The blocks are then split into testing and training sets iteratively along k folds of the data\n",
    "#(k is given by n_splits).\n",
    "R_2_splits_media = [] # Variando o numero de splits\n",
    "n = np.arange(5,21)\n",
    "for n_splits in n:\n",
    "    R_2_splits_media.append(np.mean(\n",
    "        vd.cross_val_score(\n",
    "            fontes,\n",
    "            coordinates,\n",
    "            gz,\n",
    "            cv=vd.BlockKFold(spacing=5000, n_splits=n_splits, shuffle=True, random_state=123),\n",
    "        )\n",
    "    ))\n",
    "\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "id": "d4e66b77-8695-4de1-b03a-0bba052ca667",
   "metadata": {},
   "outputs": [],
   "source": [
    "# Quero achar o numero mais proximo de R_2_true dentro de R_2_block\n",
    "# E encontrar o n associado a este valor \n",
    "\n",
    "def acha_indice(R_2_true,lista):\n",
    "    \"Encontra o valor mais próximo de R_2_true dentro da lista e retorna sua posição dentro dela.\"\n",
    "    valores = []\n",
    "    for element in lista:\n",
    "        valores.append(np.abs(element-R_2_true))\n",
    "    indice = valores.index(np.min(valores))\n",
    "    return indice"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "id": "c21ca5e5-cbe7-484d-ac4f-a73ebd73d583",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.legend.Legend at 0x1c3b4421240>"
      ]
     },
     "execution_count": 20,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "indice = acha_indice(R_2_true,R_2_splits_media)\n",
    "plt.plot(n,R_2_splits_media)\n",
    "plt.xlabel(\"n_splits\")\n",
    "plt.ylabel(\"R_2\")\n",
    "plt.plot(n[indice],R_2_true,\"o\",markersize=10,label=f\"R_2 verdadeiro\")\n",
    "plt.legend()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "948da721-7200-4982-8798-d7c5bd1715eb",
   "metadata": {},
   "source": [
    "# Variando tamanho do bloco\n",
    "Estou pegando a média dos erros para plotar"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "id": "1d3ad20a-5631-4c56-aabd-2e57ab1e93c4",
   "metadata": {},
   "outputs": [],
   "source": [
    "R_2_block_media = []\n",
    "block = np.linspace(1000,10000,10)\n",
    "for spacing in block:\n",
    "    R_2_block_media.append(np.mean(\n",
    "        vd.cross_val_score(\n",
    "            fontes,\n",
    "            coordinates,\n",
    "            gz,\n",
    "            cv=vd.BlockKFold(spacing=spacing, n_splits=5, shuffle=True, random_state=123),\n",
    "        )\n",
    "    ))\n",
    "\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "id": "322bd218-ce2b-4b44-a571-f32083858715",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Text(0, 0.5, 'R_2')"
      ]
     },
     "execution_count": 22,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "indice = acha_indice(R_2_true,R_2_block_media)\n",
    "plt.plot(block[indice],R_2_true,\"o\",markersize=10,label=f\"R_2 verdadeiro\")\n",
    "plt.plot(block,R_2_block_media)\n",
    "plt.legend()\n",
    "plt.xlabel(\"Tamanho do bloco\")\n",
    "plt.ylabel(\"R_2\")\n"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "29de6cdb-9d18-4fe9-9863-078989c3a726",
   "metadata": {},
   "source": [
    "# Variando n_splits\n",
    "\n",
    "Pegando o valor máximo dos erros para plotar"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "id": "1490e3ba-6d58-4b7e-a5f0-f5a417d0d8e3",
   "metadata": {},
   "outputs": [],
   "source": [
    "R_2_splits_max = [] # Variando splits e pegando o minimo dos valores\n",
    "n = np.arange(2,11)\n",
    "for n_splits in n:\n",
    "    R_2_splits_max.append(np.max(\n",
    "        vd.cross_val_score(\n",
    "            fontes,\n",
    "            coordinates,\n",
    "            gz,\n",
    "            cv=vd.BlockKFold(spacing=5000, n_splits=n_splits, shuffle=True, random_state=123),\n",
    "        )\n",
    "    ))\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "id": "7a588614-b34b-439b-ad26-e981f871aeb3",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Text(0, 0.5, 'R_2')"
      ]
     },
     "execution_count": 24,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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rVO5A5JomLfMUb3y/lw/WppTevRZfz48R18TTp20k3p6u91DFipwBUgEqR6UXoDMMA06dKHnOj09Ayd1eJp6iPH78OMePHy/3PZvNdtZt6lK5VIBESizfeYR/fLiZozkFeHt6MKF3cwZeEeMWl3Sc4VhOAe/8tJ93ftpfepkwIsiXe66O445O0di8Xac0qgBdpiorQCLnoZ81cXcFxXb+teRX3lxRcqa8SZg/r/RvR7Pw83+wSflO5hexYHUKb63YV/qE6hA/b4Z2jWVQl1iCatX8y4QaA1QF1BulsulnTNzZniM5PPD+RrYezAZgUJcYHu3VXJe4LkOArxcjrolnSNdY/rP+N2Z/v4fU46d4KXkns5bv4a4rYrj7yoaEBrrHL1w6A1SO8zVIu93Ozp07CQ0NpU6dOiYlFHdw7NgxMjIyaNKkCVar/tEX92AYBgvXpvLk59s4VWSndi0vXvhrAn9uEWZ2NJdTbHfw5S+HmLlsDzsOnwTA29ODv3ZowIir44muU/MeqqhLYJfpQn+Ahw4dIjMzk9DQUGrVqqXr0OJUhmGQl5dHRkYGwcHB1K9f3+xIIlUiK6+I8Z/8zFe/HAagW6M6TL29LWFuckbCLIZh8N8dGfx72R7WHzgBlNxR95c2JQ9VbF6/5lxyVAG6TBf6AzQMg8OHD5OZmVn14cRtBAcHEx4eroItbmH13mM8uHATB7Py8fSw8HCPptxzVZxu2a5ChmGwZt9x/r1sD8t3/v6k/z81C+Vv18bTMdY5k3JXJhWgy3Sxf4B2u52ioqIqTCbuwsvLS5e9xC0U2x1MX7qL177bjcOA2Dq1eKV/O9o0CDY7mlvbkpbFzOV7+OqXQ6UPVewcG8L93eO5tkm9avuLmQrQZarIH6CIiFya1ON5jP5gIxtSMgHo26EBk25qiZ+P7s+pLvYdzWX28j18vOE3iuwldaFF/UDuvzaeXq3rY61mZ+hUgC6TCpCISOX6dFMaEz7ZwsmCYgJ8PXnmltbclBBhdiw5h8NZ+bz5w17eW5NCXqEdgIZ1/bjv6jhuaR+Jj2f1OGOtAnSZVIBERCpHTkExTyzewqKNaQB0jKnNy/3aEhVS8+44ckcncguZu7LkoYqZeSVDQMICfbjnqjj6d442/eydCtBlUgESEXG+TamZjP5gIweO5eFhgQeua8yo7o3wtLrelAyuLregmPfXpPDmD/s4nJ0PQHAtLwZ3iWVI11hq+3mbkksF6DKpAImIOI/dYTBr+R5eTt5JscMgMtjGtDva0qkG3FUk51dQbGfxxjRmLd/LvqO5ANTyttK/czTDr2pI/SBbleZRAbpMKkAiIs5xOCufBxduYuXeYwD0blOfZ29pTZCt5k+7IL+zOwyWbDnMv5ftLn16t5fVwq3tGnDfNXHE1fOvkhwqQJdJBUhE5PJ9s/Uw//z4ZzLziqjlbeXJm1ry1w4Nqu0t1HL5DMPg+11Hee273azZVzK5tsUCvVrV5/5r42kVGVSp318F6DKpAImIXLpThXYmf7mN91anANA6Mojpd7StsrMAUj2sP3Ccf3+3h6U7MkqXXd2kHn+7Np7EhiGVUoRVgC6TCpCIyKXZdjCbBz7YyO6MHADuuyaOf/y5Kd6eGujsrnYczmbmsj18vvkgjtONo310MCO7N+K65s6d400F6DKpAImIVIxhGMz5cT/Pfb2DQruD0AAfpt7elisb1zU7mlQTKcfymP39Hj5a/xuFxQ6ubFSX+cMTnfo9VIAukwqQiMjFO5pTwEMfbWbZryXzRyU1D+X529pQx9/H5GRSHWVk5/PWj/vo3jSUK+LqOHXfFfn81vPGRUTkki3feYR/fLiZozkF+Hh6MKF3c+66IkYDneWcQgN9Gd+zudkxVIBERKTiCort/GvJr7y5Yh8ATcMCeKV/O5qGB5icTOTiqACJiEiF7M7I4YH3N7LtUMnzXgZ3iWF8r+b4elWP+aBELoYKkIiIXBTDMFi4NpUnP9/GqSI7IX7e/OuvbZx+J49IVVABEhGRC8rMK2T8ol/4esthAK5sVJeptycQGuhrcjKRS6MCJCIi57Vq7zEeXLiJQ1n5eFktPNyjKcOvjMPDQwOdpeZSARIRkXIV2R28snQXr363G8OAhnX9eOWOdrRuULnTGYhUBRUgERE5S8qxPEYv3MjGlEwAbu/YgIk3tsTPRx8b4hr0kywiImUs3pjGhMVbyCkoJsDXkym3tuYvbSLMjiXiVKZPzvLaa68RGxuLr68viYmJrFmz5pzrFhUV8dRTTxEfH4+vry8JCQksWbKkzDp2u53HH3+chg0bYrPZiI+PZ/LkyeiB1yIi53cyv4ixCzcxZuEmcgqK6RhTm69HX6XyIy7J1DNACxcuZOzYscyaNYvExESmTZtGjx49+PXXXwkNDT1r/QkTJjB//nzeeOMNmjVrxjfffMMtt9zCTz/9RLt27QB4/vnnmTlzJnPnzqVly5asW7eOoUOHEhQUxAMPPFDVhygiUiNsTDnB6A82kXI8Dw8LjL6uCSO7x+NpNf33ZJFKYepcYImJiXTq1IlXX30VAIfDQVRUFH//+98ZN27cWetHRETw2GOPMXLkyNJlt912Gzabjfnz5wPwl7/8hbCwMN56661zrnMhmgtMRNyF3WEwa/kepibvxO4wiAy2Mf2OtnSMDTE7mkiFVeTz27RqX1hYyPr160lKSvo9jIcHSUlJrFy5stxtCgoK8PUt+8wJm83GihUrSr/u2rUrS5cuZefOnQBs3ryZFStW0LNnz0o4ChGRmutQ1ikGvLmKf33zK3aHwY0JEXw1+iqVH3ELpl0CO3r0KHa7nbCwsk8QDQsLY8eOHeVu06NHD6ZOncrVV19NfHw8S5cuZdGiRdjt9tJ1xo0bR3Z2Ns2aNcNqtWK323nmmWcYMGDAObMUFBRQUFBQ+nV2dvZlHp2ISPW2ZMsh/vnxL2SdKqKWt5Wn+rTitvaRmsRU3EaNurg7ffp0GjduTLNmzfD29mbUqFEMHToUD4/fD+PDDz9kwYIFvPfee2zYsIG5c+fy4osvMnfu3HPud8qUKQQFBZW+oqKiquJwRESq3KlCO+MX/cKI+RvIOlVEmwZBfPnAVfy1QwOVH3ErphWgunXrYrVaSU9PL7M8PT2d8PDwcrepV68eixcvJjc3lwMHDrBjxw78/f2Ji4srXefhhx9m3Lhx3HHHHbRu3ZqBAwfy4IMPMmXKlHNmGT9+PFlZWaWv1NRU5xykiEg1svVgFn+Z8QPvr0nBYoER18TznxFdaVjXz+xoIlXOtALk7e1Nhw4dWLp0aekyh8PB0qVL6dKly3m39fX1JTIykuLiYj7++GP69OlT+l5eXl6ZM0IAVqsVh8Nxzv35+PgQGBhY5iUi4iocDoO3Vuzjltd+Ys+RXEIDfJh/dyLjejbD27NGXQgQcRpTb4MfO3YsgwcPpmPHjnTu3Jlp06aRm5vL0KFDARg0aBCRkZGlZ29Wr15NWloabdu2JS0tjUmTJuFwOHjkkUdK93njjTfyzDPPEB0dTcuWLdm4cSNTp05l2LBhphyjiIiZjpws4KGPNrN85xEAkpqH8cJf2xDi521yMhFzmVqA+vXrx5EjR3jiiSc4fPgwbdu2ZcmSJaUDo1NSUsqczcnPz2fChAns3bsXf39/evXqxbx58wgODi5dZ8aMGTz++OP87W9/IyMjg4iICO677z6eeOKJqj48ERFTLfs1g4c+2szRnEJ8PD2Y8JcW3JUYrbE+Ipj8HKDqSs8BEpGarKDYzvNf/8rbP+4DoFl4AK/0b0eTsACTk4lUrop8fmsuMBGRGi4zr5ADx/I4cDyP1ON5fL75IDsOnwRgSNdYxvVshq+X1eSUItWLCpCISDXncBgczs7nwLE8Uo7nlpadlGN5HDiWS3Z+8VnbhPh582LfNvypWVg5exQRFSARkWogv8jObyfySsrNsTxSjpeUmwPH8/jt+CkK7ee+kxUgNMCHmDq1iA7xI66eH307NiA0wPe824i4MxUgEZEq8sdLVSnHckuLTsrxPA5n53O+EZleVgsNatciKqQWMSG1TpedWsTU8SM6pBY2b13iEqkIFSARESdxOAwOZedz4FguqcfzLupS1R/5+3ieLjW1iK5Ti5gQv9KiExFsw+qhu7dEnEUFSESkApx5qaps2alFiJ+3blEXqSIqQCIi/6O8S1VnzuQczs4/77aeHhYa1LYRXcdPl6pEqjEVIBFxO3+8VJVy5iyOky5V1Q/yxdOq6SVEqjsVIBEpI6egmOM5hRQ7HNgdBnbDoNhu4DAMih1GybLTr2KHgcNRdnmxw1Gyrt0o3f5/tylv+9+3cZRuU2wvf/v//Z6lOR2nt3dw+n/L3+ZkfvFFXaqKDvmfgqNLVSIuQwVIREp9tvkgj/xnM/lF5y8HruB8l6qiQmzU8tY/jyKuTP+FiwiGYfD693uZ8vUOAGxeVrysFjytHnhYLHh6WLCefnl6WPDwKLvM6mHBajn9vtVSzjYepduUvmf9fRtrOfv74/f5fRsPrJYLZLCeXm753/154OEBnh4e1PK26lKViJtTARJxc3aHwZOfb+XdlQcAuPvKhjzWqzkeuuVaRFyYCpCIGztVaOeBDzaSvC0diwUm9G7B3Vc2NDuWiEilUwEScVPHcgq4e+46NqVm4u3pwfR+benZur7ZsUREqoQKkIgb2n80lyFz1rD/WB7Btbx4c1BHOsaGmB1LRKTKqACJuJkNKScYPncdx3MLaVDbxtxhnYmv5292LBGRKqUCJOJG/m/rYR74YCP5RQ5aRwbx1pCOmjFcRNySCpCIm3h35X4mfbYVhwHdm9bj1Tvb4+ejfwJExD3pXz8RF+dwGDz/zQ5mL98LQP/O0Uzu01LPwBERt6YCJOLCCortPPTRz3y++SAAD/doyt+ujdc0DiLi9lSARFxUVl4R985bx+p9x/H0sPDCX9twa/sGZscSEakWVIBEXNBvJ/IYOmctuzJy8PfxZNZdHbiycV2zY4mIVBsqQCIuZuvBLIbOWUvGyQLCA32ZM7QTzesHmh1LRKRaUQEScSHLdx7hb/PXk1top2lYAO8M60T9IJvZsUREqh0VIBEX8eG6VMYv+gW7w6BrfB1mDexAoK+X2bFERKolFSCRGs4wDKYv3cW0b3cBcHPbCF74awLenrrNXUTkXFSARGqwIruDxz75hQ/X/QbA366N5+EeTXWbu4jIBagAidRQOQXF/G3BBr7feQQPC0y+uRUDEmPMjiUiUiOoAInUQBnZ+Qx9Zy1bD2Zj87Ly6p3tuK55mNmxRERqDBUgkRpmV/pJhsxZS1rmKer6e/PW4E4kRAWbHUtEpEZRARKpQVbvPcY9764jO7+YuLp+vDO0M9F1apkdS0SkxlEBEqkhPt98kH98uJlCu4MOMbV5c1BHavt5mx1LRKRGUgESqeYMw+CNH/by7Fc7ALihZTjT7miLr5fV5GQiIjWXCpBINWZ3GDz1+VbmrjwAwNBusUzo3QKrh25zFxG5HCpAItXUqUI7oz/YyP9tSwdgQu/mDL8qzuRUIiKuQQVIpBo6llPA8HfXsTElE29PD16+vS2929Q3O5aIiMtQARKpZvYfzWXInDXsP5ZHkM2LNwZ1pHPDELNjiYi4FBUgkWpkY8oJ7p67juO5hUQG25g7rBONQgPMjiUi4nJUgESqieRt6fz9/Q3kFzloFRnI20M6ERrga3YsERGXpAIkUg3MW7mfiZ9txWHAtU3r8dqd7fHz0X+eIiKVRf/CipjI4TB44ZtfmbV8DwB3dIri6Ztb4Wn1MDmZiIhrUwESMUlBsZ2HP/qZzzYfBOAff27CqD81wmLRM35ERCqbCpCICbJOFXHfvHWs2nscTw8Lz93Whr92aGB2LBERt6ECJFLF0jJPMeTtNezKyMHfx5OZd7Xnqsb1zI4lIuJWVIBEqtDWg1kMnbOWjJMFhAX6MGdIZ1pEBJodS0TE7agAiVSRH3Yd4f75G8gpKKZJmD/vDO1MRLDN7FgiIm5JBUikCny0LpXxi36h2GHQJa4OswZ2IMjmZXYsERG3pQIkUokMw+CVpbt5+dudAPRpG8ELf22Dj6fV5GQiIu5NBUikkhTZHUz4ZAsL16UCcP+18Tx8fVM8PHSbu4iI2VSARCpBTkExIxdsYPnOI3hY4Mk+rRh4RYzZsURE5DQVIBEny8jOZ+g7a9l6MBtfLw9m9G/Pn1uEmR1LRET+QAVIxIl2Z5xk8NtrScs8RR0/b94a0om2UcFmxxIRkf+hAiTiJGv2Heeed9eRdaqIhnX9eGdoJ2Lq+JkdS0REyqECJOIEX/x8kLELN1Nod9AuOpi3BncixM/b7FgiInIOKkAil8EwDN78YR/PfLUdgOtbhDH9jnbYvHWbu4hIdaYCJHKJ7A6DyV9s452f9gMwpGssj/+lBVbd5i4iUu2pAIlcgvwiO6M/2Mg3W9MBeKxXc4Zf1RCLReVHRKQmUAESqaDjuYUMn7uWDSmZeFs9eOn2BG5MiDA7loiIVIAKkEgFpB7PY9Dba9h3NJdAX0/eGNSRxLg6ZscSEZEKUgESuUgOh8HoDzay72gukcE23hnaicZhAWbHEhGRS6ACJHKRPlqfyoaUTPy8rSy87woa1K5ldiQREblEHmYHEKkJjucWMuXrHQA8+OcmKj8iIjVctShAr732GrGxsfj6+pKYmMiaNWvOuW5RURFPPfUU8fHx+Pr6kpCQwJIlS8qsExsbi8ViOes1cuTIyj4UcVEvLNlBZl4RzcIDGNw11uw4IiJymUwvQAsXLmTs2LFMnDiRDRs2kJCQQI8ePcjIyCh3/QkTJjB79mxmzJjBtm3bGDFiBLfccgsbN24sXWft2rUcOnSo9JWcnAxA3759q+SYxLWsP3CCD9amAjD55lZ4WU3/z0ZERC6TxTAMw8wAiYmJdOrUiVdffRUAh8NBVFQUf//73xk3btxZ60dERPDYY4+VOZtz2223YbPZmD9/frnfY8yYMXzxxRfs2rXrop7Tkp2dTVBQEFlZWQQGBl7ikYkrKLY7uOnVH9l2KJu/dmjAi30TzI4kIiLnUJHPb1N/lS0sLGT9+vUkJSWVLvPw8CApKYmVK1eWu01BQQG+vr5lltlsNlasWHHO7zF//nyGDRumh9RJhc1bdYBth7IJsnkxvmczs+OIiIiTmFqAjh49it1uJywsrMzysLAwDh8+XO42PXr0YOrUqezatQuHw0FycjKLFi3i0KFD5a6/ePFiMjMzGTJkyDlzFBQUkJ2dXeYlkpGdz0v/txOAR25oSh1/H5MTiYiIs9S4wQzTp0+ncePGNGvWDG9vb0aNGsXQoUPx8Cj/UN566y169uxJRMS5n9Q7ZcoUgoKCSl9RUVGVFV9qkKe/3E5OQTEJUcHc0Sna7DgiIuJEphagunXrYrVaSU9PL7M8PT2d8PDwcrepV68eixcvJjc3lwMHDrBjxw78/f2Ji4s7a90DBw7w7bffMnz48PPmGD9+PFlZWaWv1NTUSz8ocQk/7j7KZ5sP4mGBp/u00gSnIiIuxtQC5O3tTYcOHVi6dGnpMofDwdKlS+nSpct5t/X19SUyMpLi4mI+/vhj+vTpc9Y6c+bMITQ0lN69e593Xz4+PgQGBpZ5ifsqKLbz+KdbABh4RQytGwSZnEhERJzN9CdBjx07lsGDB9OxY0c6d+7MtGnTyM3NZejQoQAMGjSIyMhIpkyZAsDq1atJS0ujbdu2pKWlMWnSJBwOB4888kiZ/TocDubMmcPgwYPx9DT9MKUGefOHfew9kktdfx/GXt/U7DgiIlIJTG8G/fr148iRIzzxxBMcPnyYtm3bsmTJktKB0SkpKWXG9+Tn5zNhwgT27t2Lv78/vXr1Yt68eQQHB5fZ77fffktKSgrDhg2rysORGi71eB4z/rsLgMd6NyPI5mVyIhERqQymPweoOtJzgNzX8Lnr+HZ7OokNQ/jg3iv06AQRkRqkxjwHSKQ6Sd6Wzrfb0/H0sPD0za1UfkREXJgKkAhwqtDOpM+2AjD8qjgahwWYnEhERCqTCpAI8Op3u0jLPEVEkC8PXNfI7DgiIlLJVIDE7e05ksPr3+8F4IkbW1LL2/R7A0REpJKpAIlbMwyDJz7dQpHdoHvTevRoGXbhjUREpMZTARK39vnPh/hx9zF8PD148iYNfBYRcRcqQOK2svOLmPzFNgBGdm9EdJ1aJicSEZGqogIkbuvl5J0cOVlAw7p+3Hv12XPJiYiI61IBEre09WAWc3/aD8CTN7XE18tqbiAREalSKkDidhwOg8cXb8FhQO829bm6ST2zI4mISBVTARK389H6VDakZOLnbeXx3i3MjiMiIiZQARK3cjy3kClf7wDgwT83ITzI1+REIiJiBhUgcSsvLNlBZl4RzcIDGNw11uw4IiJiEhUgcRvrD5zgg7WpAEy+uRVeVv34i4i4K30CiFsotjuYsHgLAH07NKBTbIjJiURExEwqQOIW5q06wPZD2QTZvBjXs5nZcURExGQqQOLyMrLzeen/dgLwyA1NqePvY3IiERExmwqQuLynv9xOTkExCVHB3NEp2uw4IiJSDagAiUv7cfdRPtt8EA8LPN2nFVYPTXYqIiIqQOLCCortPP5pycDngVfE0LpBkMmJRESkulABEpf15g/72Hskl7r+Poy9vqnZcUREpBpRARKXlHo8jxn/3QXAhN7NCbJ5mZxIRESqExUgcUlPfr6N/CIHV8SF0KdthNlxRESkmlEBEpeTvC2db7en4+lhYXKfVlgsGvgsIiJlqQCJSzlVaGfSZ1sBGH5VHI3DAkxOJCIi1ZEKkLiUV7/bRVrmKSKCfHngukZmxxERkWpKBUhcxu6MHF7/fi8AE29qSS1vT5MTiYhIdaUCJC7BMAwmfraFIrvBn5qFcn2LMLMjiYhINaYCJC7h858P8ePuY/h4ejDpxpYa+CwiIuelAiQ1XnZ+EZO/2AbAyO6NiK5Ty+REIiJS3akASY33cvJOjpwsoGFdP+69Os7sOCIiUgOoAEmNtvVgFnN/2g/Akze1xNfLam4gERGpEVSApMZyOAwmLN6Cw4DebepzdZN6ZkcSEZEaQgVIaqyP1qeyMSUTP28rj/duYXYcERGpQVSApEY6nlvIlK93APDgn5sQHuRrciIREalJVICkRnphyQ4y84poFh7A4K6xZscREZEaRgVIapz1B07wwdpUACbf3Aovq36MRUSkYvTJITVKsd3BhMVbAOjboQGdYkNMTiQiIjVRhQpQUVERjzzyCI0aNaJz5868/fbbZd5PT0/HatVtyFJ53l15gO2HsgmyeTGuZzOz44iISA1VoQL0zDPP8O677zJixAiuv/56xo4dy3333VdmHcMwnBpQ5IyM7HymJu8E4J83NKOOv4/JiUREpKaq0HTZCxYs4M033+Qvf/kLAEOGDKFnz54MHTq09GyQ5mCSyvL0l9vJKSgmISqYOzpFmR1HRERqsAqdAUpLS6NVq1alXzdq1Ihly5bx008/MXDgQOx2u9MDigD8uPson20+iIcFnrm5FR4eKtoiInLpKlSAwsPD2bNnT5llkZGRfPfdd6xdu5YhQ4Y4M5sIAAXFdh7/tGTg88ArYmgVGWRyIhERqekqVID+9Kc/8d577521PCIigv/+97/s27fPacFEznjzh33sPZJLXX8fxl7f1Ow4IiLiAio0Bujxxx9nx44d5b4XGRnJ8uXLSU5OdkowEYDU43nM+O8uACb0bk6QzcvkRCIi4goqdAYoJiaGHj16nPP9iIgIBg8eXPp17969OXTo0KWnE7f35OfbyC9ycEVcCH3aRpgdR0REXESlPgjx+++/59SpU5X5LcSFJW9L59vt6Xh6WHj65la6w1BERJxGT4KWaulUoZ1Jn20FYPhVcTQKDTA5kYiIuBIVIKmWXv1uF2mZp4gI8uWB6xqZHUdERFyMCpBUO7szcnj9+70ATLypJbW8KzRWX0RE5IJUgKRaMQyDJz7dQpHd4E/NQrm+RZjZkURExAU5vQBp0LNcjs9/PsRPe47h4+nBpBtbauCziIhUCqcVoIKCAl566SUaNmxYuuzRRx8lJCTEWd9CXFx2fhGTv9gGwKjujYiuU8vkRCIi4qoqVIAKCgoYP348HTt2pGvXrixevBiAOXPm0LBhQ6ZNm8aDDz5Yuv748eMJDg52Zl5xYS8n7+TIyQIa1vXj3mvizI4jIiIurEKjS5944glmz55NUlISP/30E3379mXo0KGsWrWKqVOn0rdvX6xWa2VlFRe29WAWc3/aD8CTN7XEx1M/RyIiUnkqVIA++ugj3n33XW666Sa2bNlCmzZtKC4uZvPmzRqrIZfM4TCYsHgLDgN6t6nP1U3qmR1JRERcXIUugf3222906NABgFatWuHj48ODDz6o8iOX5cN1qWxMycTP28rjvVuYHUdERNxAhQqQ3W7H29u79GtPT0/8/f2dHkrcx/HcQp5bUjLB7oN/bkJ4kK/JiURExB1U6BKYYRgMGTIEHx8fAPLz8xkxYgR+fn5l1lu0aJHzEopLe2HJDjLzimgWHsCQrrFmxxERETdRoQL0x5neAe666y6nhhH3sv7ACT5YmwrA0ze3wtOq53KKiEjVqFABmjNnTmXlEFdgGJB3HApzwNsfaoXAOcaHFdsdTFi8BYC+HRrQMVbPixIRkaqjSZbk8p3KhM3vw+rZcGLf78trN4TE+yChP9iCy2zy7soDbD+UTZDNi3E9m1VpXBEREdOvObz22mvExsbi6+tLYmIia9asOee6RUVFPPXUU8THx+Pr60tCQgJLliw5a720tDTuuusu6tSpg81mo3Xr1qxbt64yD8N97f4WpraAJePhxP6y753YX7J8aouS9U5Lz85navJOAP55QzPq+PtUXV4RERFMLkALFy5k7NixTJw4kQ0bNpCQkECPHj3IyMgod/0JEyYwe/ZsZsyYwbZt2xgxYgS33HILGzduLF3nxIkTdOvWDS8vL77++mu2bdvGSy+9RO3atavqsNzH7m9hwe1QdAowTr/+6PSyolMl650uQc98uZ2cgmISooK5o1NUFYcWEREBi2EY//upVWUSExPp1KkTr776KgAOh4OoqCj+/ve/M27cuLPWj4iI4LHHHmPkyJGly2677TZsNhvz588HYNy4cfz444/88MMPl5wrOzuboKAgsrKyCAwMvOT9uLRTmSVndopOAY6L2MADvGysumUFd7y7HQ8LfDbqSlpFBlVyUBERcRcV+fw27QxQYWEh69evJykp6fcwHh4kJSWxcuXKcrcpKCjA17fsc2JsNhsrVqwo/fqzzz6jY8eO9O3bl9DQUNq1a8cbb7xROQfhzja/D0V5XFz5AXBgFOWx9tPXABh4RYzKj4iImMa0AnT06FHsdjthYWFlloeFhXH48OFyt+nRowdTp05l165dOBwOkpOTWbRoEYcOHSpdZ+/evcycOZPGjRvzzTffcP/99/PAAw8wd+7cc2YpKCggOzu7zEvOwzBKBjxXdDPgxlOfU9fPm7HXN3V+LhERkYtk+iDoipg+fTqNGzemWbNmeHt7M2rUKIYOHYqHx++H4XA4aN++Pc8++yzt2rXj3nvv5Z577mHWrFnn3O+UKVMICgoqfUVFaVzKeeUdP323V8WunnpgEOuRzpPXRxBk86qcbCIiIhfBtAJUt25drFYr6enpZZanp6cTHh5e7jb16tVj8eLF5ObmcuDAAXbs2IG/vz9xcXGl69SvX58WLcrOJ9W8eXNSUlLOmWX8+PFkZWWVvlJTUy/jyNxAYc5lbd6rid+FVxIREalEphUgb29vOnTowNKlS0uXORwOli5dSpcuXc67ra+vL5GRkRQXF/Pxxx/Tp0+f0ve6devGr7/+Wmb9nTt3EhMTc879+fj4EBgYWOYl5+F9efO/WXz05ysiIuYy9RLY2LFjeeONN5g7dy7bt2/n/vvvJzc3l6FDhwIwaNAgxo8fX7r+6tWrWbRoEXv37uWHH37ghhtuwOFw8Mgjj5Su8+CDD7Jq1SqeffZZdu/ezXvvvcfrr79e5s4xuUy1Qkoeckj5T3k+FweWku1seiSBiIiYy9QnQffr148jR47wxBNPcPjwYdq2bcuSJUtKB0anpKSUGd+Tn5/PhAkT2Lt3L/7+/vTq1Yt58+YRHBxcuk6nTp345JNPGD9+PE899RQNGzZk2rRpDBgwoKoPz3VZLCVPeF4y/sLr/nEzgMQR55weQ0REpKqY+hyg6krPAboIFXwOkIEHFi8bjN121rQYIiIizlAjngMkNZwtGPq9e/pszvl/jBxYStbrN0/lR0REqgUVILl0jZJgwIfgZaPkAlfZS1sOw4LDsICXDcuAj6DRdabEFBER+V8qQHJ5GiWVXNa64TmoHVvmrRQjlB/i/4HHP3ao/IiISLVi6iBocRG2YLhiRMnA6FMnmPbVBt5Zd5TadcJYcufV4Gk1O6GIiEgZKkDiPBYLWzOtvLK+AAcBzLi5FT4qPyIiUg3pEpg4jWEYPPHpVhwG9G5Tn6sa1zM7koiISLlUgMRpNqRksv7ACXw8PXi8d4sLbyAiImISFSBxmvmrDgBwU0IE4UG+JqcRERE5NxUgcYqjOQV8+fMhAAZ1iTU3jIiIyAWoAIlTfLgulUK7g4SoYFo3CDI7joiIyHmpAMllszsMFqxKAWDgFTEmpxEREbkwFSC5bN/tyCAt8xTBtbz4S5v6ZscRERG5IBUguWzzTg9+7tcxCl8vPfdHRESqPxUguSz7j+ayfOcRLBYYkKjLXyIiUjOoAMllWbC65OzPtU3qEV2nlslpRERELo4KkFyy/CI7H677DYCBXXT2R0REag4VILlkn20+SNapIqJCbFzTJNTsOCIiIhdNBUgu2ZknPw9IjMHqYTE5jYiIyMVTAZJLsjk1k59/y8Lb04PbO0aZHUdERKRCVIDkkry7suTsz1/a1CfEz9vkNCIiIhWjAiQVdiK3kM9/Pgjoyc8iIlIzqQBJhX24LpXCYgetIgNpGxVsdhwREZEKUwGSCnE4DOaffvbPoCtisVg0+FlERGoeFSCpkOW7jpB6/BSBvp7cmBBhdhwREZFLogIkFTLv9ODnvh2jsHlr3i8REamZVIDkoqUez+O7XzMAuEuDn0VEpAZTAZKLtmB1CoYBVzWuS8O6fmbHERERuWQqQHJR8ovsLFybAujWdxERqflUgOSifPXLIU7kFREZbOO65mFmxxEREbksKkByUeadnvfrzsRozfslIiI1ngqQXNCWtCw2pmTiZbXQr5Pm/RIRkZpPBUgu6Myt771a16euv4/JaURERC6fCpCcV1ZeEZ9uTgM0+FlERFyHCpCc10frU8kvctC8fiAdYmqbHUdERMQpVIDknBwOgwWrf7/1XfN+iYiIq1ABknNasfso+47mEuDjSZ+2mvdLRERchwqQnNOZW99v69AAPx9Pk9OIiIg4jwqQlCst8xRLt6cDmvdLRERcjwqQlOu91QdwGNA1vg6NQv3NjiMiIuJUKkByloJiOwvXpgIwqIvO/oiIiOtRAZKzLNlymKM5hYQH+pKkeb9ERMQFqQDJWc48+fnOxGg8rfoRERER16NPNylj28Fs1h04gaeHhTs075eIiLgoFSAp48yt7z1ahRMa6GtyGhERkcqhAiSlsvOLWLyxZN6vQbr1XUREXJgKkJRatP43ThXZaRLmT+eGIWbHERERqTQqQAKAYRill78075eIiLg6FSABYOWeY+w5kouft5Vb2jcwO46IiEilUgESAN49fev7re0b4K95v0RExMWpAAmHsk6RfHrer4F68rOIiLgBFSDh/TWp2B0GiQ1DaBIWYHYcERGRSqcC5OYKix28vyYF0NkfERFxHypAbu7/th3myMkC6gX4cH2LcLPjiIiIVAkVIDd3Zt6v/p2j8fbUj4OIiLgHfeK5sV8Pn2T1vuNYPSzc2Tna7DgiIiJVRgXIjc0//eDD61uEER6keb9ERMR9qAC5qZyCYhZt+A0oefKziIiIO1EBclOfbPiN3EI78fX86BJfx+w4IiIiVUoFyA1p3i8REXF3KkBuaPW+4+xMz8HmZeXWDpr3S0RE3I8KkBs6c/bn5naRBPp6mZxGRESk6qkAuZmM7Hy+2XIY0OBnERFxX9WiAL322mvExsbi6+tLYmIia9asOee6RUVFPPXUU8THx+Pr60tCQgJLliwps86kSZOwWCxlXs2aNavsw6gR3l+TSrHDoGNMbVpEBJodR0RExBSmF6CFCxcyduxYJk6cyIYNG0hISKBHjx5kZGSUu/6ECROYPXs2M2bMYNu2bYwYMYJbbrmFjRs3llmvZcuWHDp0qPS1YsWKqjicaq3I7uC9NacHP2veLxERcWOmF6CpU6dyzz33MHToUFq0aMGsWbOoVasWb7/9drnrz5s3j0cffZRevXoRFxfH/fffT69evXjppZfKrOfp6Ul4eHjpq27dulVxONXa0u3ppGcXUNffmxtaad4vERFxX6YWoMLCQtavX09SUlLpMg8PD5KSkli5cmW52xQUFODrW/apxTab7awzPLt27SIiIoK4uDgGDBhASkqK8w+ghnn39Lxf/TpF4eNpNTmNiIiIeUwtQEePHsVutxMWFlZmeVhYGIcPHy53mx49ejB16lR27dqFw+EgOTmZRYsWcejQodJ1EhMTeeedd1iyZAkzZ85k3759XHXVVZw8ebLcfRYUFJCdnV3m5Wp2Z5zkpz3H8LDAnYm6/CUiIu7N9EtgFTV9+nQaN25Ms2bN8Pb2ZtSoUQwdOhQPj98PpWfPnvTt25c2bdrQo0cPvvrqKzIzM/nwww/L3eeUKVMICgoqfUVFRVXV4VSZ+atKzoBd1zyMyGCbyWlERETMZWoBqlu3LlarlfT09DLL09PTCQ8vf4xKvXr1WLx4Mbm5uRw4cIAdO3bg7+9PXFzcOb9PcHAwTZo0Yffu3eW+P378eLKyskpfqampl35Q1VBuQTEfr9e8XyIiImeYWoC8vb3p0KEDS5cuLV3mcDhYunQpXbp0Oe+2vr6+REZGUlxczMcff0yfPn3OuW5OTg579uyhfv365b7v4+NDYGBgmZcr+XTTQU4WFNOwrh9XNtJgcBEREdMvgY0dO5Y33niDuXPnsn37du6//35yc3MZOnQoAIMGDWL8+PGl669evZpFixaxd+9efvjhB2644QYcDgePPPJI6ToPPfQQy5cvZ//+/fz000/ccsstWK1W+vfvX+XHZzbDMHh35X4ABiRG4+Gheb9EREQ8zQ7Qr18/jhw5whNPPMHhw4dp27YtS5YsKR0YnZKSUmZ8T35+PhMmTGDv3r34+/vTq1cv5s2bR3BwcOk6v/32G/379+fYsWPUq1ePK6+8klWrVlGvXr2qPjzTrT9wgh2HT+Lr5UHfDq43tklERORSWAzDMMwOUd1kZ2cTFBREVlZWjb8cNvqDjXy66SD9Okbx/F/bmB1HRESk0lTk89v0S2BSeY6cLOCrX0oeD6AnP4uIiPxOBciFfbgulSK7QduoYFpFBpkdR0REpNpQAXJRxXYHC1aVPPl5kM7+iIiIlKEC5KL+uyODg1n51K7lRa/W5d/+LyIi4q5UgFzUvNNnf27vFIWvl+b9EhER+SMVIBe090gOP+w6isUCd2neLxERkbOoALmgBatL5v3q3jSUqJBaJqcRERGpflSAXMypQjsfrSuZy0y3vouIiJRPBcjFfLY5jez8YqJCbFzT2P2efC0iInIxVIBcSMm8XyWDn+9KjNG8XyIiIuegAuRCNqVmsvVgNt6eHtzeUfN+iYiInIsKkAuZd/rsz41tIqjt521yGhERkepLBchFHM8t5IufNe+XiIjIxVABchEL16ZSaHfQpkEQbaOCzY4jIiJSrakAuQC7w2DB6tODn6/Q2R8REZELUQFyAct3ZvDbiVME2by4sU2E2XFERESqPRUgF3Dm1vfbOzbA5q15v0RERC5EBaiGO3Asl+U7jwAwQPN+iYiIXBQVoBruvdUpGAZc3aQesXX9zI4jIiJSI6gA1WD5RXYWnp73a5AGP4uIiFw0FaAa7IufD5GZV0RksI3uzULNjiMiIlJjqADVYPNW7gdgwBXRWDXvl4iIyEVTAaqhNqdmsvm3LLytmvdLRESkolSAaqj5q0pufe/VOpy6/j4mpxEREalZVIBqoBO5hXy2+SAAA7vEmhtGRESkBlIBqoH+s/43CoodtKgfSPvoYLPjiIiI1DgqQDWMw2Ew//S8XwO7xGCxaPCziIhIRakA1TDf7zrCgWN5BPh60qet5v0SERG5FCpANcyZwc9/7dCAWt6eJqcRERGpmVSAapDU43ks3ZEBwF168rOIiMglUwGqQd5bUzLv15WN6hJfz9/sOCIiIjWWClANUVBsZ+Haknm/dPZHRETk8qgA1RBf/XKI47mF1A/yJam55v0SERG5HCpANcS8lSWDn+/sHI2nVX9tIiIil0OfpDXAlrQsNqRk4mW10K+z5v0SERG5XCpANcCZW99vaFWf0ABfk9OIiIjUfCpA1VzWqSIWb0oDYKAGP4uIiDiFClA19/H638gvctA0LIBOsbXNjiMiIuISVICqMYfDKL38pXm/REREnEcFqBr7ac8x9h7Nxd/Hk5vbRZodR0RExGWoAFVj767cD8Ct7SPx99G8XyIiIs6iAlRNHcw8xbfb0wENfhYREXE2FaBq6v01KTgMuCIuhMZhAWbHERERcSkqQNVQYbGD99eUzPs18IpYc8OIiIi4IBWgamjJ1sMczSkgNMCH61uGmR1HRETE5agAVUPzT8/71b9zNF6a90tERMTp9Olazew4nM2a/cexeli4MzHa7DgiIiIuSQWomjkz63uPlmGEBWreLxERkcqgAlSNZOcX8cnGknm/7tKt7yIiIpVGBaga+WRDGnmFdhqF+tMlro7ZcURERFyWClA1YRgG887M+3WF5v0SERGpTCpA1cTKvcfYnZFDLW8rt7TXvF8iIiKVSQWomjgz6/st7SIJ9PUyOY2IiIhrUwGqBtKz8/lma8m8Xxr8LCIiUvlUgKqB91anYHcYdIqtTfP6gWbHERERcXkqQCYrsjt4f00KAAO7xJobRkRExE2oAJkseVs6GScLqOvvzQ0tw82OIyIi4hZUgEz27sr9ANzRKRpvT/11iIiIVAV94ppoV/pJVu09jocFzfslIiJShVSATHTmwYdJzcOICLaZnEZERMR9qACZJKegmEUbSub9GqTBzyIiIlVKBcgkizemkVNQTFxdP7rGa94vERGRqlQtCtBrr71GbGwsvr6+JCYmsmbNmnOuW1RUxFNPPUV8fDy+vr4kJCSwZMmSc67/3HPPYbFYGDNmTCUkvzSGYTBvZcnlrwFXxODhoXm/REREqpLpBWjhwoWMHTuWiRMnsmHDBhISEujRowcZGRnlrj9hwgRmz57NjBkz2LZtGyNGjOCWW25h48aNZ627du1aZs+eTZs2bSr7MCpk7f4T/Jp+El8vD/7aoYHZcURERNyO6QVo6tSp3HPPPQwdOpQWLVowa9YsatWqxdtvv13u+vPmzePRRx+lV69exMXFcf/999OrVy9eeumlMuvl5OQwYMAA3njjDWrXrl0Vh3LRzgx+vrltJEE2zfslIiJS1UwtQIWFhaxfv56kpKTSZR4eHiQlJbFy5cpytykoKMDX17fMMpvNxooVK8osGzlyJL179y6z73MpKCggOzu7zKuyZJzMZ8mWQ4Dm/RIRETGLqQXo6NGj2O12wsLCyiwPCwvj8OHD5W7To0cPpk6dyq5du3A4HCQnJ7No0SIOHTpUus4HH3zAhg0bmDJlykXlmDJlCkFBQaWvqKioSz+oC1i4JpUiu0H76GBaRQZV2vcRERGRczP9ElhFTZ8+ncaNG9OsWTO8vb0ZNWoUQ4cOxcOj5FBSU1MZPXo0CxYsOOtM0bmMHz+erKys0ldqamqlZC+2O3ivdN4vnf0RERExi6kFqG7dulitVtLT08ssT09PJzy8/Hmx6tWrx+LFi8nNzeXAgQPs2LEDf39/4uLiAFi/fj0ZGRm0b98eT09PPD09Wb58Oa+88gqenp7Y7faz9unj40NgYGCZV2X4dnsGh7LyCfHzpmer+pXyPUREROTCTC1A3t7edOjQgaVLl5YuczgcLF26lC5dupx3W19fXyIjIykuLubjjz+mT58+AFx33XX88ssvbNq0qfTVsWNHBgwYwKZNm7BarZV6TOfjZbXQJMyffp2i8PUyL4eIiIi78zQ7wNixYxk8eDAdO3akc+fOTJs2jdzcXIYOHQrAoEGDiIyMLB3Ps3r1atLS0mjbti1paWlMmjQJh8PBI488AkBAQACtWrUq8z38/PyoU6fOWcur2nXNw/hTs1AKih2m5hAREXF3phegfv36ceTIEZ544gkOHz5M27ZtWbJkSenA6JSUlNLxPQD5+flMmDCBvXv34u/vT69evZg3bx7BwcEmHUHFWCwWnf0RERExmcUwDMPsENVNdnY2QUFBZGVlVdp4IBEREXGuinx+17i7wEREREQulwqQiIiIuB0VIBEREXE7KkAiIiLidlSARERExO2oAImIiIjbUQESERERt6MCJCIiIm5HBUhERETcjgqQiIiIuB0VIBEREXE7KkAiIiLidkyfDb46OjM/bHZ2tslJRERE5GKd+dy+mHneVYDKcfLkSQCioqJMTiIiIiIVdfLkSYKCgs67jsW4mJrkZhwOBwcPHiQgIACLxeLUfWdnZxMVFUVqaiqBgYFO3Xd1oOOr+Vz9GF39+MD1j1HHV/NV1jEahsHJkyeJiIjAw+P8o3x0BqgcHh4eNGjQoFK/R2BgoMv+YIOOzxW4+jG6+vGB6x+jjq/mq4xjvNCZnzM0CFpERETcjgqQiIiIuB0VoCrm4+PDxIkT8fHxMTtKpdDx1Xyufoyufnzg+seo46v5qsMxahC0iIiIuB2dARIRERG3owIkIiIibkcFSERERNyOClAVmDJlCp06dSIgIIDQ0FBuvvlmfv31V7NjOdXMmTNp06ZN6TMdunTpwtdff212rErz3HPPYbFYGDNmjNlRnGLSpElYLJYyr2bNmpkdy+nS0tK46667qFOnDjabjdatW7Nu3TqzYzlFbGzsWX+HFouFkSNHmh3NKex2O48//jgNGzbEZrMRHx/P5MmTL2rKg5rk5MmTjBkzhpiYGGw2G127dmXt2rVmx7ok33//PTfeeCMRERFYLBYWL15c5n3DMHjiiSeoX78+NpuNpKQkdu3aVWX5VICqwPLlyxk5ciSrVq0iOTmZoqIirr/+enJzc82O5jQNGjTgueeeY/369axbt44//elP9OnTh61bt5odzenWrl3L7NmzadOmjdlRnKply5YcOnSo9LVixQqzIznViRMn6NatG15eXnz99dds27aNl156idq1a5sdzSnWrl1b5u8vOTkZgL59+5qczDmef/55Zs6cyauvvsr27dt5/vnneeGFF5gxY4bZ0Zxq+PDhJCcnM2/ePH755Reuv/56kpKSSEtLMztaheXm5pKQkMBrr71W7vsvvPACr7zyCrNmzWL16tX4+fnRo0cP8vPzqyagIVUuIyPDAIzly5ebHaVS1a5d23jzzTfNjuFUJ0+eNBo3bmwkJycb11xzjTF69GizIznFxIkTjYSEBLNjVKp//vOfxpVXXml2jCozevRoIz4+3nA4HGZHcYrevXsbw4YNK7Ps1ltvNQYMGGBSIufLy8szrFar8cUXX5RZ3r59e+Oxxx4zKZVzAMYnn3xS+rXD4TDCw8ONf/3rX6XLMjMzDR8fH+P999+vkkw6A2SCrKwsAEJCQkxOUjnsdjsffPABubm5dOnSxew4TjVy5Eh69+5NUlKS2VGcbteuXURERBAXF8eAAQNISUkxO5JTffbZZ3Ts2JG+ffsSGhpKu3bteOONN8yOVSkKCwuZP38+w4YNc/p8hmbp2rUrS5cuZefOnQBs3ryZFStW0LNnT5OTOU9xcTF2ux1fX98yy202m8udkd23bx+HDx8u829pUFAQiYmJrFy5skoyaC6wKuZwOBgzZgzdunWjVatWZsdxql9++YUuXbqQn5+Pv78/n3zyCS1atDA7ltN88MEHbNiwocZejz+fxMRE3nnnHZo2bcqhQ4d48sknueqqq9iyZQsBAQFmx3OKvXv3MnPmTMaOHcujjz7K2rVreeCBB/D29mbw4MFmx3OqxYsXk5mZyZAhQ8yO4jTjxo0jOzubZs2aYbVasdvtPPPMMwwYMMDsaE4TEBBAly5dmDx5Ms2bNycsLIz333+flStX0qhRI7PjOdXhw4cBCAsLK7M8LCys9L3KpgJUxUaOHMmWLVtcrs0DNG3alE2bNpGVlcV//vMfBg8ezPLly12iBKWmpjJ69GiSk5PP+u3MFfzxt+g2bdqQmJhITEwMH374IXfffbeJyZzH4XDQsWNHnn32WQDatWvHli1bmDVrlssVoLfeeouePXsSERFhdhSn+fDDD1mwYAHvvfceLVu2ZNOmTYwZM4aIiAiX+vubN28ew4YNIzIyEqvVSvv27enfvz/r1683O5rL0SWwKjRq1Ci++OILvvvuu0qfbd4M3t7eNGrUiA4dOjBlyhQSEhKYPn262bGcYv369WRkZNC+fXs8PT3x9PRk+fLlvPLKK3h6emK3282O6FTBwcE0adKE3bt3mx3FaerXr39WGW/evLnLXeo7cOAA3377LcOHDzc7ilM9/PDDjBs3jjvuuIPWrVszcOBAHnzwQaZMmWJ2NKeKj49n+fLl5OTkkJqaypo1aygqKiIuLs7saE4VHh4OQHp6epnl6enppe9VNhWgKmAYBqNGjeKTTz7hv//9Lw0bNjQ7UpVwOBwUFBSYHcMprrvuOn755Rc2bdpU+urYsSMDBgxg06ZNWK1WsyM6VU5ODnv27KF+/fpmR3Gabt26nfX4iZ07dxITE2NSosoxZ84cQkND6d27t9lRnCovLw8Pj7IfWVarFYfDYVKiyuXn50f9+vU5ceIE33zzDX369DE7klM1bNiQ8PBwli5dWrosOzub1atXV9nYUV0CqwIjR47kvffe49NPPyUgIKD0+mZQUBA2m83kdM4xfvx4evbsSXR0NCdPnuS9995j2bJlfPPNN2ZHc4qAgICzxmz5+flRp04dlxjL9dBDD3HjjTcSExPDwYMHmThxIlarlf79+5sdzWkefPBBunbtyrPPPsvtt9/OmjVreP3113n99dfNjuY0DoeDOXPmMHjwYDw9Xeuf9xtvvJFnnnmG6OhoWrZsycaNG5k6dSrDhg0zO5pTffPNNxiGQdOmTdm9ezcPP/wwzZo1Y+jQoWZHq7CcnJwyZ5H37dvHpk2bCAkJITo6mjFjxvD000/TuHFjGjZsyOOPP05ERAQ333xz1QSsknvN3BxQ7mvOnDlmR3OaYcOGGTExMYa3t7dRr14947rrrjP+7//+z+xYlcqVboPv16+fUb9+fcPb29uIjIw0+vXrZ+zevdvsWE73+eefG61atTJ8fHyMZs2aGa+//rrZkZzqm2++MQDj119/NTuK02VnZxujR482oqOjDV9fXyMuLs547LHHjIKCArOjOdXChQuNuLg4w9vb2wgPDzdGjhxpZGZmmh3rknz33XflfvYNHjzYMIySW+Eff/xxIywszPDx8TGuu+66Kv3Z1WzwIiIi4nY0BkhERETcjgqQiIiIuB0VIBEREXE7KkAiIiLidlSARERExO2oAImIiIjbUQESERERt6MCJCIiIm5HBUhE5DSLxcLixYsB2L9/PxaLhU2bNpmaSUQqhwqQiEg5oqKiOHToUOlcb8uWLcNisZCZmWluMBFxCteaLU9ExEmsVivh4eFmxxCRSqIzQCJSrVx77bU88MADPPLII4SEhBAeHs6kSZMuuJ1hGEyaNIno6Gh8fHyIiIjggQceKH0/NjaWyZMn079/f/z8/IiMjOS111475/7+eAls//79dO/eHYDatWtjsVgYMmQIAP/5z39o3bo1NpuNOnXqkJSURG5u7mX9GYhI5VMBEpFqZ+7cufj5+bF69WpeeOEFnnrqKZKTk8+7zccff8zLL7/M7Nmz2bVrF4sXL6Z169Zl1vnXv/5FQkICGzduZNy4cYwePfqC+4WSy2Eff/wxAL/++iuHDh1i+vTpHDp0iP79+zNs2DC2b9/OsmXLuPXWW9Ec0yLVny6BiUi106ZNGyZOnAhA48aNefXVV1m6dCl//vOfz7lNSkoK4eHhJCUl4eXlRXR0NJ07dy6zTrdu3Rg3bhwATZo04ccff+Tll18+736h5HJYSEgIAKGhoQQHBwOwZ88eiouLufXWW4mJiQE4q3SJSPWkM0AiUu20adOmzNf169cnIyPjvNv07duXU6dOERcXxz333MMnn3xCcXFxmXW6dOly1tfbt2+/5JwJCQlcd911tG7dmr59+/LGG29w4sSJS96fiFQdFSARqXa8vLzKfG2xWHA4HOfdJioqil9//ZV///vf2Gw2/va3v3H11VdTVFRUaTmtVivJycl8/fXXtGjRghkzZtC0aVP27dtXad9TRJxDBUhEXIbNZuPGG2/klVdeYdmyZaxcuZJffvml9P1Vq1aVWX/VqlU0b978ovbt7e0NgN1uL7PcYrHQrVs3nnzySTZu3Ii3tzeffPLJZR6JiFQ2jQESEZfwzjvvYLfbSUxMpFatWsyfPx+bzVY6Ngfgxx9/5IUXXuDmm28mOTmZjz76iC+//PKi9h8TE4PFYuGLL76gV69e2Gw2tm7dytKlS7n++usJDQ1l9erVHDly5KJLlYiYR2eARMQlBAcH88Ybb9CtWzfatGnDt99+y+eff06dOnVK1/nHP/7BunXraNeuHU8//TRTp06lR48eF7X/yMhInnzyScaNG0dYWBijRo0iMDCQ77//nl69etGkSRMmTJjASy+9RM+ePSvrMEXESSyG7tcUETcQGxvLmDFjGDNmjNlRRKQa0BkgERERcTsqQCJSIyxYsAB/f/9yXy1btjQ7nojUMLoEJiI1wsmTJ0lPTy/3PS8vrzKDnUVELkQFSERERNyOLoGJiIiI21EBEhEREbejAiQiIiJuRwVIRERE3I4KkIiIiLgdFSARERFxOypAIiIi4nZUgERERMTt/D8CLOe+i9jgYAAAAABJRU5ErkJggg==",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.plot(n,R_2_splits_max)\n",
    "indice = acha_indice(R_2_true,R_2_splits_max)\n",
    "plt.plot(n[indice],R_2_true,\"o\",markersize=10,label=f\"R_2 verdadeiro\")\n",
    "plt.legend()\n",
    "plt.xlabel(\"n_splits\")\n",
    "plt.ylabel(\"R_2\")"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "1987e99f-f6a3-48a8-b7b3-bfe031060af0",
   "metadata": {},
   "source": [
    "# Variando tamanho do bloco\n",
    "Pegando o valor máximo para plotar"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "id": "9e7e784d-f345-4de1-bbc2-e957635be4ab",
   "metadata": {},
   "outputs": [],
   "source": [
    "R_2_block_max = []\n",
    "block = np.arange(1000,10950,950)\n",
    "nsplits=5\n",
    "for spacing in block:\n",
    "    R_2_block_max.append(np.max(\n",
    "        vd.cross_val_score(\n",
    "            fontes,\n",
    "            coordinates,\n",
    "            gz,\n",
    "            cv=vd.BlockKFold(spacing=spacing, n_splits=nsplits, shuffle=True, random_state=123),\n",
    "        )\n",
    "    ))\n",
    "\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "id": "194160f0-1549-44a3-a4f7-c5e71e77780a",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Text(0, 0.5, 'R_2')"
      ]
     },
     "execution_count": 26,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.plot(block,R_2_block_max)\n",
    "indice = acha_indice(R_2_true,R_2_block_max)\n",
    "plt.plot(block[indice],R_2_true,\"o\",markersize=10,label=f\"R_2 verdadeiro\")\n",
    "plt.legend()\n",
    "plt.xlabel(\"Tamanho do bloco\")\n",
    "plt.ylabel(\"R_2\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "id": "0ac4b5dd-7768-46aa-8d1c-5455bae195d0",
   "metadata": {},
   "outputs": [],
   "source": [
    "#pcolormesh\n"
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3 (ipykernel)",
   "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": "3.10.14"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 5
}