{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "827e9aae-17df-4df6-9441-d9a6486d4b84",
   "metadata": {
    "tags": []
   },
   "outputs": [],
   "source": [
    "import rastereasy"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "0b817850-2c77-44c1-8f2b-54cb0fc303d7",
   "metadata": {},
   "source": [
    "# Dealing with shapefiles, ROI, ..."
   ]
  },
  {
   "cell_type": "markdown",
   "id": "99c50bfd-4e71-45fe-a7e2-4d716ea063e4",
   "metadata": {},
   "source": [
    "## 1) Read shapefile\n",
    "\n",
    "Two main functions : `rastereasy.shpfiles.shp2raster` and `rastereasy.shpfiles.shp2geoim`"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "33743715-fc85-412e-93c7-63a98ad997af",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Help on function shp2raster in module rastereasy.rastereasy:\n",
      "\n",
      "shp2raster(shapefile_path, dest_name, attribute='code', resolution=10, nodata=0)\n",
      "    Convert a shapefile to a GeoTIFF raster file.\n",
      "\n",
      "    Parameters\n",
      "    ----------\n",
      "    shapefile_path : str\n",
      "        Path to the input shapefile.\n",
      "    dest_name : str\n",
      "        Path to save the output raster file.\n",
      "    attribute : str, optional\n",
      "        Attribute field in the shapefile to assign values to each pixel.\n",
      "        Default is 'code'.\n",
      "    resolution : float, optional\n",
      "        Spatial resolution of the output raster in meters/degrees.\n",
      "        Default is 10.\n",
      "    nodata : int or float, optional\n",
      "        Value to assign to areas outside the shapes.\n",
      "        Default is 0.\n",
      "\n",
      "    Notes\n",
      "    -----\n",
      "    - The `shapefile_path` should be the full path to a shapefile (.shp) on the disk.\n",
      "    - To get the attributes of a shapefile, see :meth:`shpfiles.get_shapefile_attributes`\n",
      "    - The output raster will be written in GeoTIFF format to the path specified by `dest_name`.\n",
      "\n",
      "    Examples\n",
      "    --------\n",
      "    >>> shpfiles.shp2raster(\"landcover.shp\", \"landcover.tif\", attribute='landtype', resolution=5)\n",
      "\n",
      "Help on function shp2geoim in module rastereasy.rastereasy:\n",
      "\n",
      "shp2geoim(shapefile_path, attribute='code', resolution=10, nodata=0)\n",
      "    Convert a shapefile to a Geoimage object.\n",
      "\n",
      "    Parameters\n",
      "    ----------\n",
      "    shapefile_path : str\n",
      "        Path to the input shapefile.\n",
      "    attribute : str, optional\n",
      "        Attribute field in the shapefile to assign values to each pixel.\n",
      "        Default is 'code'.\n",
      "    resolution : float, optional\n",
      "        Spatial resolution of the output raster in meters/degrees.\n",
      "        Default is 10.\n",
      "    nodata : int or float, optional\n",
      "        Value to assign to areas outside the shapes.\n",
      "        Default is 0.\n",
      "\n",
      "    Returns\n",
      "    -------\n",
      "    Geoimage\n",
      "        A Geoimage object containing the rasterized data.\n",
      "\n",
      "    Notes\n",
      "    -----\n",
      "    - The `shapefile_path` should be the full path to a shapefile (.shp) on the disk.\n",
      "    - The `attribute` field will be assigned to each pixel in the rasterized Geoimage.\n",
      "    - To get the attributes of a shapefile, see :meth:`shpfiles.get_shapefile_attributes`\n",
      "    - The `resolution` sets the size of each pixel in the output image.\n",
      "\n",
      "    Examples\n",
      "    --------\n",
      "    >>> geo_img = shpfiles.shp2geoim(\"landcover.shp\", attribute='landtype', resolution=5)\n",
      "\n"
     ]
    }
   ],
   "source": [
    "help(rastereasy.shpfiles.shp2raster)\n",
    "help(rastereasy.shpfiles.shp2geoim)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "860bd7d0-73a3-45cf-bad0-2f4067a587ee",
   "metadata": {},
   "source": [
    "## 2) Convert shapefile to tif"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "282960f2-4b07-4a3c-894d-29828cb615d1",
   "metadata": {
    "tags": []
   },
   "outputs": [],
   "source": [
    "shapefile_path = './data/demo/data_shp/Roi_G5.shp'\n",
    "rastereasy.shpfiles.shp2raster(shapefile_path,'./data/results/shp2raster/raster5m.tif',resolution=5)\n",
    "rastereasy.shpfiles.shp2raster(shapefile_path,'./data/results/shp2raster/raster10m.tif',resolution=10)\n"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "b71932b9-085c-4fcb-9061-3f988e1bbc65",
   "metadata": {},
   "source": [
    "## 2) Import as Geoimage"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "8f46638e-332b-4cf8-8a5d-b6a734dfb524",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "- Size of the image:\n",
      "   - Rows (height): 3649\n",
      "   - Cols (width): 5097\n",
      "   - Bands: 1\n",
      "- Spatial resolution: 5.000057261870794  meters / degree (depending on projection system)\n",
      "- Central point latitude - longitude coordinates: (47.60953547, -2.57061505)\n",
      "- Driver: GTiff\n",
      "- Data type: int32\n",
      "- Projection system: EPSG:32630\n",
      "- Nodata: 0.0\n",
      "\n",
      "- Given names for spectral bands: \n",
      "   {'1': 1}\n",
      "\n",
      "\n",
      "- Size of the image:\n",
      "   - Rows (height): 1824\n",
      "   - Cols (width): 2548\n",
      "   - Bands: 1\n",
      "- Spatial resolution: 10.002076869605746  meters / degree (depending on projection system)\n",
      "- Central point latitude - longitude coordinates: (47.60951283, -2.57058196)\n",
      "- Driver: GTiff\n",
      "- Data type: int32\n",
      "- Projection system: EPSG:32630\n",
      "- Nodata: 0.0\n",
      "\n",
      "- Given names for spectral bands: \n",
      "   {'1': 1}\n",
      "\n",
      "\n",
      "[0 1 2 3 4 5 6 7]\n",
      "[0 1 2 3 4 5 6 7]\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "<Figure size 640x480 with 0 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 500x500 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/plain": [
       "<Figure size 640x480 with 0 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": "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",
      "text/plain": [
       "<Figure size 500x500 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "raster10m=rastereasy.Geoimage('./data/results/shp2raster/raster10m.tif')\n",
    "raster5m=rastereasy.Geoimage('./data/results/shp2raster/raster5m.tif')\n",
    "raster5m.info()\n",
    "raster10m.info()\n",
    "print(raster10m.unique())\n",
    "print(raster5m.unique())\n",
    "raster10m.visu()\n",
    "raster5m.visu()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "15de8e78-4887-40bf-a1d9-70f98d5473bd",
   "metadata": {},
   "source": [
    "## 3) Convert shapefile to geoimage"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "f510efc8-a271-4e98-a26d-3f078a500188",
   "metadata": {},
   "outputs": [],
   "source": [
    "georaster5=rastereasy.shpfiles.shp2geoim(shapefile_path,resolution=5)\n",
    "georaster10=rastereasy.shpfiles.shp2geoim(shapefile_path,resolution=10)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "75ca3b7c-e22f-4dac-8b65-b4c106bcbe72",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<Figure size 640x480 with 0 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 500x500 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/plain": [
       "<Figure size 640x480 with 0 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 500x500 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "georaster5.visu(colorbar=True)    \n",
    "georaster10.visu(colorbar=True)\n",
    "georaster5.save('./data/results/shp2raster/raster5m_fromgeoraster.tif')\n",
    "georaster10.save('./data/results/shp2raster/raster10m_fromgeoraster.tif')\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "id": "f87b2e65-9419-456d-a2c6-2fa1956115d4",
   "metadata": {},
   "outputs": [],
   "source": [
    "G5_B2=rastereasy.Geoimage('./data/demo/tostack/G5_B2.tif')\n",
    "G5_B3=rastereasy.Geoimage('./data/demo/tostack/G5_B3.tif')\n",
    "G5_B4=rastereasy.Geoimage('./data/demo/tostack/G5_B4.tif')\n",
    "G5_B8=rastereasy.Geoimage('./data/demo/tostack/G5_B8.tif')\n",
    "ROI_g5=rastereasy.Geoimage('./data/demo/data_shp/ROI_g5.tif')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "id": "e94c618e-b10c-4a1f-b79a-a4e14cb24fc4",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<Figure size 640x480 with 0 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 500x500 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "ROI_g5.visu()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "17cacb50-579c-4e09-b784-bfe5dd86f0e5",
   "metadata": {},
   "source": [
    "## 4) Select interesting areas with `extract_from_shapefile`"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "d455a004-345b-4bb3-bdbb-6e6bc7d6d2a6",
   "metadata": {},
   "source": [
    "### 1) Without modifying the image"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "537cf186-7187-4d63-93f7-39fcd705d491",
   "metadata": {},
   "source": [
    "Read a stack (for the example. `im` can be an image)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "id": "0c4e4581-e2fe-430b-8eb9-3155716407fd",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "- Size of the image:\n",
      "   - Rows (height): 2370\n",
      "   - Cols (width): 3144\n",
      "   - Bands: 4\n",
      "- Spatial resolution: 10.0  meters / degree (depending on projection system)\n",
      "- Central point latitude - longitude coordinates: (47.60615500, -2.57780166)\n",
      "- Driver: GTiff\n",
      "- Data type: uint16\n",
      "- Projection system: EPSG:32630\n",
      "\n",
      "- Given names for spectral bands: \n",
      "   {'1': 1, '2': 2, '3': 3, '4': 4}\n",
      "\n",
      "\n"
     ]
    }
   ],
   "source": [
    "im=rastereasy.Geoimage('./data/demo/tostack/G5_B2.tif')\n",
    "im_stack = im.stack(rastereasy.Geoimage('./data/demo/tostack/G5_B3.tif'),reformat_names=True)\n",
    "im_stack = im_stack.stack(rastereasy.Geoimage('./data/demo/tostack/G5_B4.tif'),reformat_names=True)\n",
    "im_stack = im_stack.stack(rastereasy.Geoimage('./data/demo/tostack/G5_B8.tif'),reformat_names=True)\n",
    "im_stack.info()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "id": "a3f7c8df-dabc-4602-8c43-9d1d833d9af1",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "- Size of the image:\n",
      "   - Rows (height): 2370\n",
      "   - Cols (width): 3144\n",
      "   - Bands: 4\n",
      "- Spatial resolution: 10.0  meters / degree (depending on projection system)\n",
      "- Central point latitude - longitude coordinates: (47.60615500, -2.57780166)\n",
      "- Driver: GTiff\n",
      "- Data type: uint16\n",
      "- Projection system: EPSG:32630\n",
      "- Nodata: 0\n",
      "\n",
      "- Given names for spectral bands: \n",
      "   {'1': 1, '2': 2, '3': 3, '4': 4}\n",
      "\n",
      "\n"
     ]
    }
   ],
   "source": [
    "keep_size=True\n",
    "value=3\n",
    "ime=im_stack.extract_from_shapefile(shapefile_path,value,keep_size=keep_size)\n",
    "ime.info()\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "id": "bf86f8b3-1c7b-484b-bec7-43fe9a51a78d",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<Figure size 640x480 with 0 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": "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",
      "text/plain": [
       "<Figure size 500x500 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/plain": [
       "<Figure size 640x480 with 0 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 500x500 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "(rastereasy.shpfiles.shp2geoim(shapefile_path,resolution=im.resolution)==value).visu(title='shapefile = %d'%value)\n",
    "if keep_size is True:\n",
    "    ((ime-im)==0).visu(1,title='extracted areas')\n",
    "else:\n",
    "    ime,imc = rastereasy.extract_common_areas(ime,im,resolution=None)\n",
    "    ((ime-imc)==0).visu(1,title='extracted areas')\n"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "0b6c94d6-f3bf-4f38-9fe0-908f0be01a38",
   "metadata": {},
   "source": [
    "### 2) With modifying the image (option `inplace=True`)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "id": "49d362c6-ef99-43ce-a2b6-198e2280a3a8",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "- Size of the image:\n",
      "   - Rows (height): 2370\n",
      "   - Cols (width): 3144\n",
      "   - Bands: 4\n",
      "- Spatial resolution: 10.0  meters / degree (depending on projection system)\n",
      "- Central point latitude - longitude coordinates: (47.60615500, -2.57780166)\n",
      "- Driver: GTiff\n",
      "- Data type: uint16\n",
      "- Projection system: EPSG:32630\n",
      "\n",
      "- Given names for spectral bands: \n",
      "   {'1': 1, '2': 2, '3': 3, '4': 4}\n",
      "\n",
      "\n",
      "- Size of the image:\n",
      "   - Rows (height): 1824\n",
      "   - Cols (width): 2548\n",
      "   - Bands: 4\n",
      "- Spatial resolution: 10.0  meters / degree (depending on projection system)\n",
      "- Central point latitude - longitude coordinates: (47.60943270, -2.57056349)\n",
      "- Driver: GTiff\n",
      "- Data type: uint16\n",
      "- Projection system: EPSG:32630\n",
      "- Nodata: 0\n",
      "\n",
      "- Given names for spectral bands: \n",
      "   {'1': 1, '2': 2, '3': 3, '4': 4}\n",
      "\n",
      "\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "<Figure size 640x480 with 0 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAcgAAAD/CAYAAAB1qUZLAAAAOnRFWHRTb2Z0d2FyZQBNYXRwbG90bGliIHZlcnNpb24zLjEwLjMsIGh0dHBzOi8vbWF0cGxvdGxpYi5vcmcvZiW1igAAAAlwSFlzAAAPYQAAD2EBqD+naQAAHo1JREFUeJzt3Ql0lNX5x/EnEPYl7AQE2dcDCIhSKbIYSkB6oBAPotAU5EChVFYRUVFBFAooaJWyFKiClFOgoB4pmxIR4SBCWUQWE+AAsrUgayAQeP/nuf5nmknuTLZJZibz/ZwzJ5l37rwzd5b85rn3vpMIx3EcAQAAHgp5ngUAAIqABADAgoAEAMCCgAQAwIKABADAgoAEAMCCgAQAwIKABADAgoAEAMCCgARyoVOnTtKsWTMJdj/88IN07dpVoqKiJCIiQtauXSt/+9vfzO8nTpzw6I+eABCQQFj43e9+JwcOHJA33nhDli5dKm3atJFQN2TIEBPwv/71rwN9V1BARQb6DgDIWzdv3pQdO3bISy+9JH/84x/d23/7299Kv379pFixYhJqvv32W1MBFy9ePNB3BQUYFSRQwP3nP/8xP8uVK+exvXDhwiZgtAoLJfr/FUaOHCnx8fFStWrVQN8dFGAEJODFtWvXZPTo0VK7dm1TZVWpUkV+9atfyZ49ezK0/f7776Vz585SsmRJue+++2TGjBkel9++fVteeeUVefDBB808YKlSpeTRRx+VLVu2eLTT+UANrFmzZsns2bOlVq1aUqJECenYsaN89913GW738OHD8sQTT0iFChVM2OnQ6SeffOK+/LXXXjP7UOPHjzf71v4o2xykTUpKirz66qtSv3598zjUrFlTnn/+ebM9EHSIWB8LHS4G8hJDrIAXw4YNk1WrVplhyaZNm8rFixdl27ZtcujQIWndurW73U8//STdunWTPn36SN++fc11JkyYIM2bN5fu3bubNlevXpW//vWv8tRTT5m5Mw3fRYsWSWxsrHzzzTfSsmVLj9v+8MMPTZsRI0bIrVu35J133pHHHnvMzCO6qqaDBw/KL3/5SxPIL7zwggndf/zjH/Kb3/xGVq9eLb179zb3SSvHMWPGmNt+/PHHpXTp0ll+DO7duyc9e/Y0/R46dKg0adLE3AcN76NHj5rFPr4kJyebU2a0mi1fvnym7fQx0cf2xRdflOjo6Cz3A8gR/X+QADKKiopyRowY4bNNx44d9f+pOh9++KF7W0pKihMdHe3ExcW5t6Wmpprtaf30009O1apVnWeeeca97fjx42Z/JUqUcE6fPu3evnPnTrN9zJgx7m0xMTFO8+bNnVu3brm33bt3z2nXrp3ToEGDDPucOXOmx+0vWbLEbNfL0/ZHTy5Lly51ChUq5Hz11Vce1503b5657tdff+3z8Xn11VdNu8xOtWrVcrLiueeec+rUqePus16vR48eWboukF1UkIAXWnnt3LlTzpw5I9WrV/faTiuyAQMGuM8XLVpUHn74YTl27JhHhaQnV1V2+fJl81OHRG1DtloFamXoovtr27atrFu3Tt5++225dOmSfPHFFzJlyhRTVenJRatSHRL98ccfPfaREytXrjRVY+PGjeW///2ve7tWs0qHiNu1a+f1+jpP2L59+0xvR4eRM6MVq1bSf//730NyYRFCDwEJeKHziHp4hM656dyhDk/qH/y6det6tKtRo0aGhS46XLh//36PbR988IG89dZbZt7wzp077u116tTJcNsNGjTIsK1hw4ZmCFUlJiaaxSqTJk0yJ5sLFy7kOiD1+EkdUq5cubLX2/BFH6v0j1dOjRo1yoRxXFycX/YHZIaABLzQ+URdSLNmzRrZuHGjzJw5U/70pz/JP//5T/fconJVhulpgLksW7ZMBg4caCpDXSyjC370etOmTZOkpKRs3zetPtVzzz1nKkYbXVSTW3o7OpeqVauNfnjw5fr16+aUGX0svIWw0mp5/fr15rFPu6goNTXVHMai23ShUtmyZTO9LSCrCEjAh2rVqskf/vAHc9JqSRfn6OrJtAGZFbpwRysp/QOfttrUoVBvlZttiNG1AtVVlRUpUkS6dOkieaVevXqyb98+iYmJydHhILoad/LkyZm205W2vlbTnjx50vzURUfp6VCyVuG6cEhXHQP+QkACFnfv3jWVjx6S4aJVn85F5uTwBleVqVWlK2h0flMP4L///vsztNfVoWnnEHWlq7Z3BYDeF/1KuPnz58uzzz5rgjz9sY++KrLsVNE677lw4UKzijUtrdy0wtTVs3k9B6lznlrJp6f3ScNVvwRBK13AnwhIwEIXvejcoh5j+MADD5iFOJs3b5Zdu3aZecTs0q9D0+pRD73o0aOHHD9+XObNm2cOH7ENQerwqAbL8OHDTSDPmTNHKlasaI4/dHn//fdNGw0GPXREq8rz58+b0D19+rSp/HJLv21H5z31kBddkKOHleiHB51H1e0bNmzw+bV1/pqD1A8Rtg8S+oFBD3vRoWvA3whIwEIP+NdhVZ171GDTSklDa+7cuSa0skvnH8+dO2cqPg0VDUadl9RVogkJCdbKq1ChQiYYdWhXV7G+9957HpWi7kO/ck2HMPWgfz1OUyvLVq1amS8l8Ae9D1rN6vClHpupVZw+Nhp6umhGFw4BBVWEHusR6DsB4Gc6D6fzabogSBfgAAgcvmoOAAALAhIAAAsCEgAAC+YgAQCwoIIEACCcD/PQZfr6pdNlypQJuX8QCwDwHx041WOd9Ys/9FAmCfeA1HDM7HsjAQDh49SpU+YLQSTcA1IrR9VeHpdIKRLouwMACJBUuSPbZJ07FyTcA9I1rKrhGBlBQAJA2HJ+/pHZdBuLdAAAsCAgAQCwICABALAgIAEAsCAgAQCwICABALAgIAEAsCAgAQCwICABALAgIAEAsCAgAQCwICABALAgIAEAsCAgAQCwICABALAgIAEAsCAgAQCwICABALAgIAEAsCAgAQDGhjN7zQl+CMjp06dLRESEjB492pw/ceKEOW87rVy50ut+Bg4cmKF9t27dPNrUrl07Qxu9fQCAf4ORkPxZpOTQrl27ZP78+dKiRQv3tpo1a8rZs2c92i1YsEBmzpwp3bt397k/DcQlS5a4zxcrVixDmylTpsiQIUPc58uUKZPTuw8A8BGGG87sldjqLSWc5Sggr1+/Lv3795eFCxfK1KlT3dsLFy4s0dHRHm3XrFkjffv2ldKlS/vcpwZi+uump4GYWRsAQNZkViluCPOQzNEQ64gRI6RHjx7SpUsXn+12794te/fulcGDB2e6z4SEBKlSpYo0atRIhg8fLhcvXszQRodUK1asKK1atTJVaWpqqtf9paSkyNWrVz1OAID/yUr4bfj/4de0p3CR7QpyxYoVsmfPHjPEmplFixZJkyZNpF27dpkOr/bp00fq1KkjSUlJ8uKLL5oh2R07dpiqVI0cOVJat24tFSpUkO3bt8vEiRPNcO7bb79t3ee0adNk8uTJ2e0eACATG/4/JAt6dRnhOI6T1canTp2SNm3ayKZNm9xzj506dZKWLVvKnDlzPNrevHlTqlWrJpMmTZJx48Zl604dO3ZM6tWrJ5s3b5aYmBhrm8WLF8vvf/97M9xrm6/UClJPLlpB6hxpJ+klkRFFsnV/AKCg8XclGBtCYZnq3JEE+ViuXLkiZcuW9U8FqUOmFy5cMJWcy927d2Xr1q3y3nvvmUByVXyrVq2S5ORkiY+Pz/adr1u3rlSqVEkSExO9BmTbtm3NEKuunNVh2fQ0NG3BCQDhIL+HQjcUwPnKbAWkhtWBAwc8tg0aNEgaN24sEyZMcIeja3i1Z8+eUrly5WzfqdOnT5s5SK1AvdG5zUKFCpl5SwDA/4TTPGHQBKSuIm3WrJnHtlKlSpmFM2m3a+WnVeW6deus+9FA1TnC3r17myFSnSuMi4szK1R1DvL555+X+vXrS2xsrGmvc5E7d+6Uzp07m/ug58eMGSMDBgyQ8uXL56znAADkxXGQvuj8YI0aNaRr167Wy48cOWLGfpVWnfv375cPPvhALl++LNWrVzfXe/31191DpPpTFwe99tprZhhXF/NoQI4dOzYv7j4AhKz8rh5jC9iwao4X6YQyXaQTFRXFIh0ABVp+BWRsCAdjnizSAQAEt7TBlVdhGRvC4ZgdBCQAFFB5EZaxYRKOioAEgDDgLdiyE5yxYRSOioAEgDDmCj1vQRkbZqGYFgEJAMgQlLFhHIwuBCQAwI1g9NM/TAYAoKAiIAEAsCAgAQCwICABALAgIAEAsCAgAQCwICABALAgIAEAsCAgAQCwICABALAgIAEAsCAgAQCwICABALAgIAEAsCAgAQCwICABALAgIAEAsCAgAQCwICABALAgIAEAsCAgAQCwICABALAgIAEAsCAgAQCwICABALAgIAEAsCAgAQCwICABALAgIAEAsCAgAQCwICABALAgIAEAsCAgAQCwICABALAgIAEAsCAgAQCwICABALAgIAEAsCAgAQCwICABALAgIAEA8HdATp8+XSIiImT06NHm/IkTJ8x522nlypU+93Xo0CHp2bOnREVFSalSpeShhx6SkydPui+/deuWjBgxQipWrCilS5eWuLg4OX/+fG7uPgAA/g/IXbt2yfz586VFixbubTVr1pSzZ896nCZPnmwCrXv37l73lZSUJO3bt5fGjRtLQkKC7N+/XyZNmiTFixd3txkzZox8+umnJmi//PJLOXPmjPTp0yendx8AAJ8iHMdxJJuuX78urVu3lrlz58rUqVOlZcuWMmfOHGvbVq1ambaLFi3yur9+/fpJkSJFZOnSpdbLr1y5IpUrV5bly5fLE088YbYdPnxYmjRpIjt27JBf/OIXGa6TkpJiTi5Xr141Ad5JeklkRJHsdhkAUECkOnckQT422VK2bFn/VpA61NmjRw/p0qWLz3a7d++WvXv3yuDBg722uXfvnnz22WfSsGFDiY2NlSpVqkjbtm1l7dq1Hvu5c+eOx+1ptXn//febgLSZNm2aGa51nTQcAQDIqmwH5IoVK2TPnj0mgDKjVaNWee3atfPa5sKFC6Yi1fnMbt26ycaNG6V3795m+FSHUtW5c+ekaNGiUq5cOY/rVq1a1VxmM3HiRPPpwHU6depUdrsKAAhjkdlprCEzatQo2bRpk8f8oM3NmzfNkKjOJfqiFaTq1auXmWdUOmS7fft2mTdvnnTs2FFyolixYuYEAECeV5A61KkVn84pRkZGmpNWee+++675/e7du+62q1atkuTkZImPj/e5z0qVKpnrNm3a1GO7Vp6uVazR0dFy+/ZtuXz5skcbXcWqlwEAENCAjImJkQMHDph5RdepTZs20r9/f/N74cKFPYZX9bANXVzjiw6d6iEdR44c8dh+9OhRqVWrlvn9wQcfNIt4Pv/8c/fl2l4D9JFHHslOFwAA8P8Qa5kyZaRZs2Ye2/SYRT02Me32xMRE2bp1q6xbt866H11go3OYOteoxo8fL08++aR06NBBOnfuLOvXrzeHdOghH0oX2ehCn7Fjx0qFChXMqqNnn33WhKNtBSsAAPkakFm1ePFiqVGjhnTt2tV6uVZ/unDGRYNS5xs1NEeOHCmNGjWS1atXm2MjXWbPni2FChUyXxCgh2/oilc9zAQAgKA5DjIU6XGQWolyHCQAhLfUvDwOEgCAgo6ABADAgoAEAMCCgAQAwIKABAAgvw7zAELRhjN7vV4WW71lvt4XAIFHBYmwC0FfQQgALgQkwjIY04ck1SOA9BhiRdiikgTgCxUkwoJWgVSCoYFhcAQLKkiEFVdIuv4Apz/vrT3yhq8gTP8cAfmNChJhiYoy8LL6oYRqEoFCBQl4QYAG7vFNexkBiUChgkTYs/0BJhyDB88FAoWARNjjDzAAG4ZYERayM0xHYAJQVJAIC4QegOyigkTYyMrqSIIUgAsBibCVfqUk4YhwlvYDI++FnzHECvAHAWHM9s1FHFrzMypIAAhDhGDmCEgACCMEY9YxxAq/4AumARQ0BCRyLf3/WSQoARQEBCQAhBG+qD/rCEgACEO2oCQ4PRGQyLVgflMx3Atk7f2b9mcwv6fzE6tY4Rf6hrKFUSD+6a3tmK70948/AMD/8H6wIyBRICq3zG7PW2gCgDcEJEJ2GDO3t0tIAvCFOUjkS0j5M0T9eSgJc5QAvCEgETJyGoxUiQBygiFW5Ji3sLIFkivcshtW/ghEqkQAOUFAIltyGjY5qeKye1s5uQ2qSwDeEJDwy+Ecrstyi2oPQLAgIJEr/qzA8ntVKtUjAF8ISOSqivTnoRKu/eQmKKlAAfgLAYlcyYsqLO0+sxJ4/ghWAEiPgESO5NfwpK/ws33RclZDkuFVAJkhIBESshpo2QlJAPCFLwpAgUN1CMAfqCBRINkqSYITQHYQkCiwCEQAucEQKwAAFgQkAAAWBCQAAP4OyOnTp0tERISMHj3anD9x4oQ5bzutXLnS574OHTokPXv2lKioKClVqpQ89NBDcvLkSfflnTp1yrDPYcOG5ebuAwDg/0U6u3btkvnz50uLFi3c22rWrClnz571aLdgwQKZOXOmdO/e3eu+kpKSpH379jJ48GCZPHmylC1bVg4ePCjFixf3aDdkyBCZMmWK+3zJkiVzevcBAPB/QF6/fl369+8vCxculKlTp7q3Fy5cWKKjoz3arlmzRvr27SulS5f2ur+XXnpJHn/8cZkxY4Z7W7169TK000BMv38AAIJmiHXEiBHSo0cP6dKli892u3fvlr1795rK0Jt79+7JZ599Jg0bNpTY2FipUqWKtG3bVtauXZuh7UcffSSVKlWSZs2aycSJEyU5OdnrflNSUuTq1aseJwAA8iwgV6xYIXv27JFp06Zl2nbRokXSpEkTadeundc2Fy5cMBWpzmd269ZNNm7cKL1795Y+ffrIl19+6W739NNPy7Jly2TLli0mHJcuXSoDBgzwul+9fzqf6Trp8C8AAHkyxHrq1CkZNWqUbNq0KcP8YHo3b96U5cuXy6RJk3y20wpS9erVS8aMGWN+b9mypWzfvl3mzZsnHTt2NNuGDh3qvk7z5s2lWrVqEhMTY+YvbcOxGqJjx451n9cKkpAEAORJBalDplrxtW7dWiIjI81Jq7x3333X/H737l1321WrVpkh0Pj4eJ/71CFTvW7Tpk09tmvlmXYVa3o6DKsSExOtlxcrVsws9kl7AgAgTypIrdgOHDjgsW3QoEHSuHFjmTBhglmkk3Z4VQ/bqFy5ss99Fi1a1BzSceTIEY/tR48elVq1anm9ns5tKq0kAQAIaECWKVPGLJBJS49ZrFixosd2req2bt0q69ats+5HA1XnCHWuUY0fP16efPJJ6dChg3Tu3FnWr18vn376qSQkJJjLdRhVh2t1pave1v79+81wrLZPe5gJAABB/WXlixcvlho1akjXrl2tl2u1eOXKFfd5DUqdb9TQHDlypDRq1EhWr15tjo10VZmbN2+WOXPmyI0bN8xcYlxcnLz88st5cfcBAJAIx3EcCQO6SEdXs3aSXhIZUSTQdwcAECCpzh1JkI9NoeZrfQrfxQoAgAX/DxIA8kn6f+KdGf6naWARkAAQhOGY/jqEZf5jiBUAQoCGZU5CFjlHBQkA+SBtBZiboHNdl4oy71FBAkA+80e4UU3mPQISAEIQFWTeIyABALAgIAEgn+V2eJTqMX8QkAAAWBCQABBCqB7zDwEJAAEIOYIu+BGQABAiQUmo5i++KAAAQuBLBAjH/EdAAkAQIQiDB0OsAABYEJAAAFgQkAAAWBCQAABYEJAAAFgQkAAAWBCQAABYEJAAAFgQkAAAWBCQAABYEJAAAFgQkAAAWBCQAABYEJAAAFgQkAAAWBCQAABYEJAAAFgQkAAAWBCQAABYEJAAAFgQkAAAWBCQAABYEJAAAFgQkAAAWBCQAABYREqYcBzH/EyVOyI//woACEOpmgNpckHCPSCvXbtmfm6TdYG+KwCAIMmFqKgor5dHOJlFaAFx7949OXPmjJQpU0YiIiIkFFy9elVq1qwpp06dkrJly0pBFQ79DIc+hks/6WPo09jTcKxevboUKuR9pjFsKkh9EGrUqCGhSF+gBfFFGo79DIc+hks/6WNo81U5urBIBwAACwISAAALAjKIFStWTF599VXzsyALh36GQx/DpZ/0MXyEzSIdAACygwoSAAALAhIAAAsCEgAACwISAAALAhIAAAsCMoBOnDghgwcPljp16kiJEiWkXr16Zmn17du3fV5HvyrPdlq5cqW73cmTJ6VHjx5SsmRJqVKliowfP15SU1PzqWe566PLjh075LHHHpNSpUqZb/Po0KGD3Lx503157dq1MzwG06dPl0DIy35eunRJ+vfvby4rV66cuZ3r169LqPSxU6dOGZ6nYcOGebSxvZ5XrFghBamPwfKezO3rVenBD927dzf9XLt2rQTjc+kPYfNVc8Ho8OHD5jti58+fL/Xr15fvvvtOhgwZIjdu3JBZs2ZZr6Pfj3j27FmPbQsWLJCZM2eaF6y6e/eueSNGR0fL9u3bTfv4+HgpUqSIvPnmmxLsfXSFRrdu3WTixIny5z//WSIjI2Xfvn0ZvjdxypQpZn8u+l27gZCX/dRw1Odw06ZNcufOHRk0aJAMHTpUli9fLqHQR6Xt9Lly0ZBIb8mSJeaxcNEPA/ktr/oYTO/J3PZTzZkzx+d3WgfDc+kXehwkgseMGTOcOnXqZOs6LVu2dJ555hn3+XXr1jmFChVyzp075972l7/8xSlbtqyTkpLihEIf27Zt67z88ss+29SqVcuZPXu2E6z80c/vv/9ej1N2du3a5d72r3/9y4mIiHB+/PFHJxT62LFjR2fUqFE+22gf16xZ4wQjf/Qx2N+T2fnb8+9//9u57777nLNnz1qft2B+LrOLIdYgc+XKFalQoUKW2+/evVv27t1rhkvSViXNmzeXqlWrurfFxsaab+g/ePCgBHsfL1y4IDt37jTDUO3atTP96Nixo2zbti1DWx1SrVixorRq1cpU0YEassqrfupzqZ++27Rp497WpUsXU2HqdUPl9frRRx9JpUqVpFmzZqZaTk5OztBmxIgRps3DDz8sixcvzvR/9YVSH4P9PZnVfiYnJ8vTTz8t77//vqmGvQnW5zLbAp3Q+J8ffvjBfKJcsGBBlq8zfPhwp0mTJh7bhgwZ4nTt2tVj240bN8wnO/0kG+x93LFjh7mvFSpUcBYvXuzs2bPHGT16tFO0aFHn6NGj7nZvvfWWs2XLFmffvn3m03i5cuWcMWPGOMHAX/184403nIYNG2a4buXKlZ25c+c6ofB6nT9/vrN+/Xpn//79zrJly0z10bt3b482U6ZMcbZt22Yeg+nTpzvFihVz3nnnHSfQ/NXHYH5PZqefQ4cOdQYPHuyzWgzW5zInCMg8MGHCBPPC8XU6dOiQx3VOnz7t1KtXz+PFl5nk5GQnKirKmTVrlsf2/Hgz5mUfv/76a3P9iRMnemxv3ry588ILL3i93qJFi5zIyEjn1q1bjr8Eup/5EZD59Xp1+fzzz80+ExMTvbaZNGmSU6NGDcdfAt3H/ArIvOznxx9/7NSvX9+5du1atoZT/f1c5icW6eSBcePGycCBA322qVu3rvt3/UfOnTt3NsNsuuAmq1atWmWGPHSyPy0d+vjmm288tp0/f959WbD3sVq1auZn06ZNPbY3adLErAT0pm3btmaIVVfoNWrUSApCP/X50qHYtLSPurI1FJ5Lb8+TSkxMNKsnvbV5/fXXJSUlxS9fmB3oPubHezKv+/nFF19IUlJShgU3cXFx8uijj0pCQkK+PJf5KtAJHe7001uDBg2cfv36Oampqdm6ri4MiIuL87og4Pz58x5DQDqE4s/qKq/6eO/ePad69eoZFq/oYqT01VZaOrSl/b506ZITCHnRT9cinW+//dZ9+YYNGwK2SCc3r1cXHX7TPunQuDdTp051ypcv7wRCXvQx2N6TOenn2bNnnQMHDnictI86fHrs2LGgfC5zi4AMIH2B6pBFTEyM+V1fgK5T2jaNGjVydu7cmWHOQP9I6orG9PTF3qxZMzOks3fvXjM3okNyvsIl2Pqoq1P1j8fKlStNXzVEihcv7h6y2r59u2mj/UtKSjLhqH2Mj4/P9z7mZT9Vt27dnFatWpnr6R9e/aP21FNPhUQftR86J6UBf/z4cTNMV7duXadDhw7u63zyySfOwoULzR9cfQx06LhkyZLOK6+8UmD6GEzvyZz20yb9EGswPZf+QEAG0JIlS7zOE7joG07P62KUtPSNVbNmTefu3bvWfZ84ccLp3r27U6JECadSpUrOuHHjnDt37jih1Mdp06aZuQt9gz3yyCPOV1995b5s9+7d5hAJnYPVQNGFSm+++WbAPo3nVT/VxYsXTSCWLl3ahOmgQYM85oGCuY8nT540QaELkXSxhv5RHj9+vHPlyhX3dfRDnlbN2r9SpUo5DzzwgDNv3jyvr+1Q7GMwvSdz+3r1FZDB9Fz6A/8PEgAAC46DBADAgoAEAMCCgAQAwIKABADAgoAEAMCCgAQAwIKABADAgoAEAMCCgAQAwIKABADAgoAEAEAy+j8HIgybJIG4iwAAAABJRU5ErkJggg==",
      "text/plain": [
       "<Figure size 500x500 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/plain": [
       "<Figure size 640x480 with 0 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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DplWoUMF0nAmdrpnfqlWrZMmSJbbL0YCqVaN9+/Y1PWLHjx8v/fr1Mz1UtQ3yj3/8ozRu3FhycnLM/NoWuXbtWunatatZB/179OjRcsMNN8hZZ51VuJL7jFNPukVZL6eWKR4F3UAbcEv2mOPh/TYl92KdM2eO1K1bV3r06GH7+rZt2+TQoUPmuWadmzZtkueff16+//57qVOnjnnfAw88EGxD1P+1c9D9999vhm5oZx4NkKHtkkjdDuzENsB0S2Q7ePkEAv/K8cF+nWFZliU+oL1YdbjHd9sbSnaWf+6wl8qduKjB0u0HWKzyu71s8IZUXdDmuHz/PmWdlBXyD5OoZWdnR52PX/PwsFTvxIXpyen2AyuA4Ag3SEXtT46P9m8CpEcV106cyO3cvHBgUcUMt0rGHaVyPHAMJ4IA6SHp3Hlpp/TnCQTuV9BFbo6P92kCpIs5dccNrXoNPHfquibCz4Ef/guUOR44ZouKAOlCbthx/Xj/Sr+UE97Gfvw/BEigAH5pXwUQzj/jHYAUITgC3kQGGUcbWkDkNO5Y4Q+xOiDxnQDeRYBM8KbYkX+nIkja/bQSJ2Jn4Fc8AP/w3Z10LpErJDOjVNKDD4NwAcBbd9LxfRskAQkAYMd3VayLtm8292JNdmCMVfUWz6/RE6gBwFl8FyBT2a5HkAMA7/BtgHQKgioAOBMBMg0IigDgfL7vpAMAgB3fBkiyOABALL4NkAz2BgDE4tsACQBALARIAABs+DpAUs0KAIjGd8M8+jZpFXYvVgAA7Pg6gwQAIBoCJAAANgiQAADYIEACAGCDAAkAgA0CJAAANgiQAADYIEACAGCDAAkAgA0CJAAANgiQAADYIEACAGCDAAkAgA0CJAAANgiQAADYIEACAGCDAAkAgA0CJAAANgiQAADYIEACAGCDAAkAgA0CJAAANgiQAADYIEACAJDsADllyhTJyMiQUaNGmb937dpl/rZ7LFiwIOaytmzZIn369JFKlSpJhQoVpH379rJ79+7g6z/88IMMHz5cqlatKhUrVpR+/frJgQMHirL6AAAkP0CuW7dOZs6cKa1btw5Oq1evnuzfvz/sMX78eBPQevXqFXVZO3fulE6dOkmzZs1kxYoVsmnTJhk3bpyULVs2OM/o0aPl1VdfNYF25cqVsm/fPrnyyisLu/oAAMSUYVmWJQk6evSotGvXTp5++mmZOHGitGnTRqZNm2Y7b9u2bc28s2fPjrq8/v37S6lSpeSFF16wff3QoUNSvXp1mTdvnlx11VVm2tatW6V58+ayZs0aufDCCwtc58OHD5vs9BK5QjIzSsVdVgCAt5yyTsoK+YeJLdnZ2cnNILWqs3fv3tK9e/eY861fv142btwoQ4YMiTrPmTNn5LXXXpMmTZpITk6O1KhRQzp06CCLFy8OW87JkyfDPk+zzZ/97GcmQNo5ceKECYqhDwAA4pVwgJw/f75s2LBBJk+eXOC8mjVqltexY8eo8xw8eNBkpNqe2bNnT3njjTekb9++pvpUq1LVV199JaVLl5bKlSuHvbdmzZrmNTu6fpoxBh5a/QsAQEoC5J49e2TkyJHy0ksvhbUP2jl+/LipEo2VPQYySHXFFVeYdkatrr3rrrvk8ssvlxkzZkhhjR071qTPgYeuOwAAKQmQWtWpGZ+2KWZmZpqHZnnTp083z0+fPh2cd+HChZKXlycDBw6Mucxq1aqZ97Zo0SJsumaegV6stWrVkh9//FG+//77sHm0F6u+ZqdMmTKmbjn0oRZt3yy5+zYmUmwAgA8lFCC7desmmzdvNu2Kgcf5558vAwYMMM9LliwZVr2qwza0c00sWnWqQzq2bdsWNn379u1Sv3598/y8884znXjeeuut4Os6vwbQiy66SApDgySBEgAQTaYkICsrS1q2bBk2Tccs6tjE0Ok7duyQVatWyZIlS2yXox1stI1Q2xrVmDFj5Nprr5XOnTtL165dZenSpWZIhw75UNqGqFW1t99+u1SpUsVkg7fddpsJjvH0YI0lECRz6rQp0nIAAD4OkPGaM2eO1K1bV3r06GH7umZ/2i4YoIFS2xs1aI4YMUKaNm0qL7/8shkbGfD4449LiRIlzA0CtIeq9njVYSaFEQiGoRmkPidIAgCKNA7SjWKNgyQ4AoB35Uac41M6DtJrCI4A4G25heh3kpIqVgAAnCAyKOrfh4+ckbOaFPxeMkgAAGwQIAEAnpRbxKF8BEgAAGzQBgnEcbVJRy7Af8gg4SvcQQlAvMgg4duebKFZIdkj4B25SboI9m2AjHZzAG495x9kkgBi8XUVa2R1W7TncD+94OGixx2oBodT+DaDjLwfa6IHJJmmN753u/vy2s2P1Ih13HGMoTCSeXHluwxSfw8yVLSDL3J64Ko2VtYJ9yCjTL94L0o4xpAuvswg7a5Mo/3CB/yLAJq+7RtvByoglXyXQSZavVPU5cD57L4/gqNz8F0gXediXwfIwm5Qu+o5gqR7cQIG3C83BedgX1axxtqwerKMZ0yc3Tz8rqQ3Dh6+Q8A9Upmc+O4Hk7/b3lCys1KbOHOCdfeBxPcHOFNo/5GiBMb//7mrzwr8wWQyyCTixOps8VSL8x0CzpdbTE1aBEj4VmRPSYIj/Cyyqclp0tHPgwAZRVFTeLiLE08IQHFwcn+K3DSfgwmQCYyVTPeXBQDJ4uTzWa5D1s33wzwSUdAVlVO+VABw471ucx22bmSQURR0CzonfYlOwH0zAXgNGWQUBMD4Rd6ej20HwAvIIIuYFZExAXATp9aC5TpsfRQB0qVfHAAkO1Cms/d+jgMDN3fSSQKyyPw7tVO2iVO6qwNO5vTjJDfJQTPeO+nQBpkETrriSZdoB1c62iQjf7cz9H/aSIH8nBwc04kq1iShF2e4dATFRF53+hUzgPQjQBYBd9v5f+naBkX9XIIkgFioYi0CgmP82yCZ2yqZ1aR8hwCiIUDCNQobGMkSARQGVawotGjByi4gBYJbosEqGQGRLBFAYfgyQHID8sIr7PYqTBaX6GcV5jPILgH3yCnmsZK+DJCp7Gjj9Y4fsbZXMsrNBQsApyQ1tEH+tPGTHdT8cqIPbDsnBMfiyDgB+Icv76RzddN2xRbkvHoSTuWvjxfXxYVXvxvAq3KTdG7gTjpJ2MjJyIy8nkmmIsgkmpWmogYAAHyZQUbeizXek2txdlBBwds+Wm/ZePCdAO6TW8wZpO876aT6NnGciJMjkWzS61k74Fc5BVwUJ7szjy+rWKPhxOoNXJQA/pETpUkmGecBqlhtxLNh4wmmnKjTy6k/wQUg9WKdo6liTeFYRjJNdyAgAigKAmQCEgmMnJwBwN1og4yCH9YFAH8jQBaAX48AAH8qUoCcMmWKZGRkyKhRo8zfu3btMn/bPRYsWBBzWVu2bJE+ffqYjjQVKlSQ9u3by+7du4OvX3LJJfmWecstt4jTskmCIwCkR+Bcnazav0K3Qa5bt05mzpwprVu3Dk6rV6+e7N+/P2y+WbNmydSpU6VXr15Rl7Vz507p1KmTDBkyRMaPH296FX388cdStmzZsPmGDh0qEyZMCP5dvnx5SabCjKEjIAKANxUqQB49elQGDBggzz77rEycODE4vWTJklKrVq2weRctWiTXXHONVKxYMery7r77brnsssvk4YcfDk5r1KhRvvk0IEYuP50IjgDgXYWqYh0+fLj07t1bunfvHnO+9evXy8aNG01mGM2ZM2fktddekyZNmkhOTo7UqFFDOnToIIsXL84370svvSTVqlWTli1bytixYyUvLy/qck+cOGHGPoY+kjW2kXt/AoDzJPv8nHAGOX/+fNmwYYOpYi3I7NmzpXnz5tKxY8eo8xw8eNBkpNqeqdnoQw89JEuXLpUrr7xSli9fLl26dDHzXX/99VK/fn2pU6eObNq0Se68807Ztm2bvPLKK7bLnTx5sqmuTRYCIgC4Q1raIPfs2SMjR46UZcuW5WsfjHT8+HGZN2+ejBs3LuZ8mkGqK664QkaPHm2et2nTRlavXi0zZswIBshhw4YF39OqVSupXbu2dOvWzbRf2lXHaoZ5++23B//WDFLbSBNFYAQAf0qoilWrTDXja9eunWRmZprHypUrZfr06eb56dOng/MuXLjQVIEOHDgw5jK1ylTf26JFi7DpmnmG9mKNpNWwaseOHbavlylTxnT2CX0AAJCSDFIzts2bN4dNGzx4sDRr1sxUeWonndDqVR22Ub169ZjLLF26tBnSodWlobZv326qVKPRtk2lmWQ6bzsHAEi/VNzYJaEAmZWVZTrIhNIxi1WrVg2brlndqlWrZMmSJbbL0YCqbYR9+/Y1f48ZM0auvfZa6dy5s3Tt2tW0Qb766quyYsUK87pWo2p1rfZ01c/SNkitjtX5Q4eZpApBEgD8JyV30pkzZ47UrVtXevToYfu6Zot6F/UADZTa3qjDPLR98bnnnpOXX37ZjI0MZJlvvvmmWZ4G1zvuuEP69etngmhx4bZzAOBMqTo/83NXCSKTBAB3B8N4f+6Ke7EmgOAIAOlT3DV5/NxVnAiOAIqKW1m6CwEyDuykANKR/YS+x+/nodw09AOhirUAft8pATiDn3+jNjdN5SaDBIBivtguygk/8F4u3lOPDDJC6E7nlh0w2b+BBiC1knFu8dPxnpOmczEZpAt3uljryE0NAH/w23Ge81N5i/McTYB0CTcEbgDwEgIkALjsgtdv2WMq2nLjQRukC3bAZO8EtFkC8IKcFJ+nfR0go21ctwfH0PeEBkO7oEiQBNzFSecnr28PX1exRgYHL+14BD7AudLR4cTr2zM33T935VVeCoyJ8nPZAbcFSo7X4kWATNLtnBi8CyCVHU84t0SXqkycAJlkbguUjJsEnIXjMTGprKYmQKZoY9u1bxKMAMA9fN2LtTg5vTHe6esHAMV93iKDBJktAFfJLaYLejJIGGSQANwgl3uxIh3c1sEIgH/kpuEingDpIGRxAOAcVLE6hFOCI9kjACfKScO5iQBZzJx+k3C7dePm5gD8iCpWF9+9pzjEurm5k9cbAIoqw7IsS3zg8OHDUqlSJflue0PJziJxTiYCJYBUdhZMdu3V4SNn5Kwmn8mhQ4ckOzs76nxkkCg0AiOAVNZWpfscQwaJIou1EzN0BECiUt3fgQwSxSY0CNKRB0BROOkcQiqFpOFnegDvBw0/IUAi5Ti4gaLjOCp+VLHCEdklw0cSQ9tu+qVzn+X7Lx4ESKQVV8Xu2V7RfuM08NzPQntcRj4PVdTt5MSenskWbdulA71Y4TheO+ALqzAniGRuu3R/vpvEu60KCpyFDQpe3O65KQyQ8fZiJUDCkbx4wBfnySHR7Zfsk1Egu/TD9+iETEd5bVvnOiBAEingSE456RS3VN7zNnLZgeep+LxULttJ0lE+DYSBB1KLNkg4lp/at5J9oo3sQGIXGFPxuShefjg20okACVf3Fkx2J4jiRoByNyd1KPGSXIdsTwIkPHXgxHrdCcEzHQe+U042XsZdpLyJAAnfSMe4NU6agHsRIOFLRa2aJfAhHZxQC+KnjNw3ATIwmuXw0TPpXhU40IJtG4LP+zZpZTvPou2bg88PHymW1fKEU9ZJ8QMdOlCc+2lB+6tbLfrpOEvlMRaIAwWNcvTNOMi9e/dKvXr10r0aAACH2LNnj9StWzfq674JkGfOnJF9+/ZJVlaWZGRkiFtubqBBXb/EWINZ3c4P5fRDGf1STsrofhr2jhw5InXq1JESJaLfDsA3Vay6EWJdKTiZ7qBe3En9WE4/lNEv5aSM7qZ3VisId9IBAMAGARIAABsESAcrU6aM3HfffeZ/L/NDOf1QRr+UkzL6h2866QAAkAgySAAAbBAgAQCwQYAEAMAGARIAABsESAAAbBAg02jXrl0yZMgQadCggZQrV04aNWpkulb/+OOPMd+jt8qzeyxYsCA43+7du6V3795Svnx5qVGjhowZM0ZOnTpVTCUrWhkD1qxZI5deeqlUqFDB3M2jc+fOcvz48eDr55xzTr5tMGXKFPFSGb/99lsZMGCAea1y5crmc44ePSrpUNhyXnLJJfm+p1tuuSVsHrv9ef78+eKlMjrlmCzqPqt08EOvXr1MORcvXixO/C6TwTe3mnOirVu3mnvEzpw5Uxo3biwfffSRDB06VI4dOyaPPPKI7Xv0/oj79+8PmzZr1iyZOnWq2WHV6dOnzYFYq1YtWb16tZl/4MCBUqpUKZk0aZI4vYyBwNGzZ08ZO3asPPnkk5KZmSkffvhhvvsmTpgwwSwvQO+1W9xSWUYNjvr9LVu2TE6ePCmDBw+WYcOGybx588Qt5VQ6n35XARokIs2dO9dsjwC9IPBKGZ10TBa1nGratGkx72nthO8yKXQcJJzj4Ycftho0aJDQe9q0aWPddNNNwb+XLFlilShRwvrqq6+C05555hkrOzvbOnHihOWGMnbo0MG65557Ys5Tv3596/HHH7ecKBll/OSTT3SMsrVu3brgtNdff93KyMiwvvzyS8st5ezSpYs1cuTImPNoORctWmQ5UTLK6PRjMpFzzwcffGCdffbZ1v79+22/Nyd/l4miitVhDh06JFWqVIl7/vXr18vGjRtNdUloZtKqVSupWbNmcFpOTo65Q//HH38sTi/jwYMHZe3ataYaqmPHjqYcXbp0kXfffTffvFqlWrVqVWnbtq3JotNVZZWKMur3qFfe559/fnBa9+7dTYap73XT/vrSSy9JtWrVpGXLliZjzsvLyzfP8OHDzTwXXHCBzJkzp8Df6nNTGZ1+TMZbzry8PLn++uvlqaeeMtlwNE79LhOW7giN//n000/NFeWsWbPifs+tt95qNW/ePGza0KFDrR49eoRNO3bsmLmy0ytZp5dxzZo1Zl2rVKlizZkzx9qwYYM1atQoq3Tp0tb27duD8z366KPW8uXLrQ8//NBcjVeuXNkaPXq0lW7JKuODDz5oNWnSJN97q1evbj399NOWW/bXmTNnWkuXLrU2bdpkvfjiiyb76Nu3b9g8EyZMsN59912zHaZMmWKVKVPGeuKJJyyvlNHJx2Qi5Rw2bJg1ZMiQmNmiU7/LwiBApsCdd95pdpxYjy1btoS9Z+/evVajRo3Cdr6C5OXlWZUqVbIeeeSRsOnFcTCmsoz//ve/zfvHjh0bNr1Vq1bWXXfdFfV9s2fPtjIzM60ffvjB8kIZiytAFtf+GvDWW2+ZZe7YsSPqPOPGjbPq1q1reaWMxRUgU1nOf/zjH1bjxo2tI0eOJFSdmuzvsjjRSScF7rjjDhk0aFDMeRo2bBh8rj/k3LVrV1PVph1u4rVw4UJT5aGN/aG06uO9994Lm3bgwIHga04vY+3atc3/LVq0CJvevHlz0xMwmg4dOpgqVu2h17RpU3F7GfW70qrYUFo+7dmarO+xOPfX0O9J7dixw/SejDbPAw88ICdOnEjKDbPTXcbiOCZTXc63335bdu7cma/DTb9+/eTiiy+WFStWFMt3WazSHaH9Tq/efv7zn1v9+/e3Tp06ldB7tWNAv379onYIOHDgQFgVkFahJCu7SmUZz5w5Y9WpUydfBxbtjBSZcYXSqi0t97fffmt5oYyBTjrvv/9+8PXc3Ny0dtIpyv4aoNVvWi6tGo9m4sSJ1llnnWV5pYxOOyYLU879+/dbmzdvDntoGbX69LPPPnPkd1lUBMg00h1Uqyy6detmnusOGHiEztO0aVNr7dq1+doM9ESpvRoj6c7esmVLU6WzceNG0zai1XKxgovTyqi9U/XksWDBAlNWDSRly5YNVlmtXr3azKPl27lzpwmOWsaBAwd6poyqZ8+eVtu2bc379KSrJ7Trrruu2MtY2HJqWbRNSoP8559/bqrpGjZsaHXu3Dn4nn/+85/Ws88+a064uh20+rh8+fLWvffe65kyOumYLGw57URWsTrpu0wGAmQazZ07N2o7QYAecPq3dkYJpQdWvXr1rNOnT9sue9euXVavXr2scuXKWdWqVbPuuOMO6+TJk5abyjh58mTTdqEH2EUXXWS98847wdfWr19vhkloG6wGFe2oNGnSpLRcjaeqjOqbb74xAbFixYommA4ePDisDcjp5dy9e7cJFNoZSTtr6El5zJgx1qFDh4Lv0Ys8zZy1jBUqVLDOPfdca8aMGVH3bTeW0UnHZFH32VgB0knfZTLwe5AAANhgHCQAADYIkAAA2CBAAgBggwAJAIANAiQAADYIkAAA2CBAAgBggwAJAIANAiQAADYIkAAA2CBAAgAg+f0fN861pPsLno8AAAAASUVORK5CYII=",
      "text/plain": [
       "<Figure size 500x500 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "keep_size=False\n",
    "value=4\n",
    "\n",
    "#Read a stack\n",
    "im=rastereasy.Geoimage('./data/demo/tostack/G5_B2.tif')\n",
    "im.stack(rastereasy.Geoimage('./data/demo/tostack/G5_B3.tif'),reformat_names=True, inplace=True)\n",
    "im.stack(rastereasy.Geoimage('./data/demo/tostack/G5_B4.tif'),reformat_names=True, inplace=True)\n",
    "im.stack(rastereasy.Geoimage('./data/demo/tostack/G5_B8.tif'),reformat_names=True, inplace=True)\n",
    "imoriginal=im.copy()\n",
    "imoriginal.info()\n",
    "\n",
    "im.extract_from_shapefile(shapefile_path,value,keep_size=keep_size,inplace=True)\n",
    "im.save('./data/results/shp2raster/extract4.tif')\n",
    "im.info()\n",
    "(rastereasy.shpfiles.shp2geoim(shapefile_path,resolution=im.resolution)==value).visu(title='shapefile = %d'%value)\n",
    "if keep_size is True:\n",
    "    ((imoriginal-im)==0).visu(1,title='extracted areas')\n",
    "else:\n",
    "    ime,imc = rastereasy.extract_common_areas(imoriginal,im,resolution=None)\n",
    "    ((ime-imc)==0).visu(1,title='extracted areas')\n"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "ed876807-36c1-454f-a58e-9d2e04e7cccf",
   "metadata": {},
   "source": [
    "### 3) By having charged the shapefile"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "060d6e38-30f1-4370-b620-6fc572e08652",
   "metadata": {},
   "source": [
    "#### 1) Without modifying the image"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "id": "f868e0a2-bd87-4462-98d8-c2088cb2adbb",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "- Size of the image:\n",
      "   - Rows (height): 2370\n",
      "   - Cols (width): 3144\n",
      "   - Bands: 4\n",
      "- Spatial resolution: 10.0  meters / degree (depending on projection system)\n",
      "- Central point latitude - longitude coordinates: (47.60615500, -2.57780166)\n",
      "- Driver: GTiff\n",
      "- Data type: uint16\n",
      "- Projection system: EPSG:32630\n",
      "\n",
      "- Given names for spectral bands: \n",
      "   {'1': 1, '2': 2, '3': 3, '4': 4}\n",
      "\n",
      "\n"
     ]
    }
   ],
   "source": [
    "#Read a stack\n",
    "shapefile_path = './data/demo/data_shp/Roi_G5.shp'\n",
    "\n",
    "shp=rastereasy.shpfiles.shp2geoim(shapefile_path,resolution=10)\n",
    "im=rastereasy.Geoimage('./data/demo/tostack/G5_B2.tif')\n",
    "im_stack = im.stack(rastereasy.Geoimage('./data/demo/tostack/G5_B3.tif'),reformat_names=True)\n",
    "im_stack = im_stack.stack(rastereasy.Geoimage('./data/demo/tostack/G5_B4.tif'),reformat_names=True)\n",
    "im_stack = im_stack.stack(rastereasy.Geoimage('./data/demo/tostack/G5_B8.tif'),reformat_names=True)\n",
    "im_stack.info()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "id": "ba02d549-a271-4859-bd3a-a85fb8a010f8",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "- Size of the image:\n",
      "   - Rows (height): 2370\n",
      "   - Cols (width): 3144\n",
      "   - Bands: 4\n",
      "- Spatial resolution: 10.0  meters / degree (depending on projection system)\n",
      "- Central point latitude - longitude coordinates: (47.60615500, -2.57780166)\n",
      "- Driver: GTiff\n",
      "- Data type: uint16\n",
      "- Projection system: EPSG:32630\n",
      "- Nodata: 0\n",
      "\n",
      "- Given names for spectral bands: \n",
      "   {'1': 1, '2': 2, '3': 3, '4': 4}\n",
      "\n",
      "\n"
     ]
    }
   ],
   "source": [
    "keep_size=True\n",
    "value=3\n",
    "ime=im_stack.extract_from_shapeimage(shp,value,keep_size=keep_size)\n",
    "ime.save('./data/results/shp2raster//extract3.tif')\n",
    "ime.info()\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "id": "644b6d5a-ace6-48d2-9879-4f62a6350bfb",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<Figure size 640x480 with 0 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": "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",
      "text/plain": [
       "<Figure size 500x500 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/plain": [
       "<Figure size 640x480 with 0 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 500x500 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "(rastereasy.shpfiles.shp2geoim(shapefile_path,resolution=im.resolution)==value).visu(title='shapefile = %d'%value)\n",
    "if keep_size is True:\n",
    "    ((ime-im)==0).visu(1,title='extracted areas')\n",
    "else:\n",
    "    ime,imc = rastereasy.extract_common_areas(ime,im,resolution=None)\n",
    "    ((ime-imc)==0).visu(1,title='extracted areas')\n"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "8857e813-12b3-41e2-b624-9f974ce00907",
   "metadata": {},
   "source": [
    "#### 2) With modifying the  image"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "id": "5b8a41d4-9704-472c-bd2e-855a3eb89535",
   "metadata": {},
   "outputs": [],
   "source": [
    "shp=rastereasy.shpfiles.shp2geoim(shapefile_path,resolution=3)\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "id": "8d341273-e8d3-47a9-8563-87a4b1b104b1",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "- Size of the image:\n",
      "   - Rows (height): 2370\n",
      "   - Cols (width): 3144\n",
      "   - Bands: 4\n",
      "- Spatial resolution: 10.0  meters / degree (depending on projection system)\n",
      "- Central point latitude - longitude coordinates: (47.60615500, -2.57780166)\n",
      "- Driver: GTiff\n",
      "- Data type: uint16\n",
      "- Projection system: EPSG:32630\n",
      "\n",
      "- Given names for spectral bands: \n",
      "   {'1': 1, '2': 2, '3': 3, '4': 4}\n",
      "\n",
      "\n",
      "- Size of the image:\n",
      "   - Rows (height): 2370\n",
      "   - Cols (width): 3144\n",
      "   - Bands: 4\n",
      "- Spatial resolution: 10.0  meters / degree (depending on projection system)\n",
      "- Central point latitude - longitude coordinates: (47.60615500, -2.57780166)\n",
      "- Driver: GTiff\n",
      "- Data type: uint16\n",
      "- Projection system: EPSG:32630\n",
      "- Nodata: 0\n",
      "\n",
      "- Given names for spectral bands: \n",
      "   {'1': 1, '2': 2, '3': 3, '4': 4}\n",
      "\n",
      "\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "<Figure size 640x480 with 0 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": "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",
      "text/plain": [
       "<Figure size 500x500 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/plain": [
       "<Figure size 640x480 with 0 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 500x500 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "keep_size=True\n",
    "value=4\n",
    "\n",
    "#Read a stack\n",
    "im=rastereasy.Geoimage('./data/demo/tostack/G5_B2.tif')\n",
    "im.stack(rastereasy.Geoimage('./data/demo/tostack/G5_B3.tif'),reformat_names=True, inplace=True)\n",
    "im.stack(rastereasy.Geoimage('./data/demo/tostack/G5_B4.tif'),reformat_names=True, inplace=True)\n",
    "im.stack(rastereasy.Geoimage('./data/demo/tostack/G5_B8.tif'),reformat_names=True, inplace=True)\n",
    "imoriginal=im.copy()\n",
    "imoriginal.info()\n",
    "\n",
    "im.extract_from_shapeimage(shp,value,keep_size=keep_size,inplace=True)\n",
    "im.save('./data/results/shp2raster//extract4.tif')\n",
    "im.info()\n",
    "(shp==value).visu(title='shapefile = %d'%value)\n",
    "if keep_size is True:\n",
    "    ((imoriginal-im)==0).visu(1,title='extracted areas')\n",
    "else:\n",
    "    ime,imc = rastereasy.extract_common_areas(imoriginal,im,resolution=None)\n",
    "    ((ime-imc)==0).visu(1,title='extracted areas')\n"
   ]
  }
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