{
 "cells": [
  {
   "cell_type": "markdown",
   "id": "f94284f8",
   "metadata": {},
   "source": [
    "# 61 Exporting Geological Maps and Custom sections from GemPy"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "ed5d4c44",
   "metadata": {},
   "source": [
    "## Set File Paths and download Tutorial Data\n",
    "\n",
    "If you downloaded the latest `GemGIS` version from the Github repository, append the path so that the package can be imported successfully. Otherwise, it is recommended to install `GemGIS` via `pip install gemgis` and import `GemGIS` using `import gemgis as gg`. In addition, the file path to the folder where the data is being stored is set. The tutorial data is downloaded using Pooch (https://www.fatiando.org/pooch/latest/index.html) and stored in the specified folder. Use `pip install pooch` if Pooch is not installed on your system yet.\n",
    "\n",
    "<img src=\"../images/tutorial61_cover.png\"> "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "id": "861c199a",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2023-05-08T10:52:39.679476Z",
     "start_time": "2023-05-08T10:52:39.629969Z"
    },
    "scrolled": true
   },
   "outputs": [],
   "source": [
    "import gemgis as gg\n",
    "\n",
    "file_path ='data/61_Exporting_geological_map_and_custom_sections_from_GemPy/'\n",
    "gg.download_gemgis_data.download_tutorial_data(filename=\"61_Exporting_geological_map_and_custom_sections_from_GemPy.zip\", dirpath=file_path)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "0222c1d0",
   "metadata": {},
   "source": [
    "## Loading the data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "id": "777c9015",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2023-05-08T10:52:39.972906Z",
     "start_time": "2023-05-08T10:52:39.938285Z"
    }
   },
   "outputs": [],
   "source": [
    "import geopandas as gpd\n",
    "import rasterio\n",
    "\n",
    "interfaces = gpd.read_file(file_path + 'interfaces.shp')\n",
    "orientations = gpd.read_file(file_path + 'orientations.shp')\n",
    "extent = [0,972,0,1069, 300, 800]\n",
    "resolution = [50, 50, 50]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "id": "b3311332",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2023-05-08T10:52:40.111692Z",
     "start_time": "2023-05-08T10:52:40.088132Z"
    }
   },
   "outputs": [
    {
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       "      <th>0</th>\n",
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       "      <td>Sand1</td>\n",
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       "      <th>2</th>\n",
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       "      <td>Sand1</td>\n",
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       "      <td>POINT (17.13494 289.08982)</td>\n",
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       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>Sand1</td>\n",
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       "      <td>Sand1</td>\n",
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     "execution_count": 24,
     "metadata": {},
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   "source": [
    "interfaces.head()"
   ]
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   "execution_count": 25,
   "id": "74462e52",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2023-05-08T10:52:40.250053Z",
     "start_time": "2023-05-08T10:52:40.218003Z"
    }
   },
   "outputs": [
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       "      <th>formation</th>\n",
       "      <th>dip</th>\n",
       "      <th>azimuth</th>\n",
       "      <th>X</th>\n",
       "      <th>Y</th>\n",
       "      <th>Z</th>\n",
       "      <th>geometry</th>\n",
       "      <th>polarity</th>\n",
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       "  </thead>\n",
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       "    <tr>\n",
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       "      <td>Ton</td>\n",
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       "      <th>1</th>\n",
       "      <td>Ton</td>\n",
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       "      <td>Ton</td>\n",
       "      <td>30.50</td>\n",
       "      <td>180.00</td>\n",
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       "      <td>957.76</td>\n",
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       "      <td>1</td>\n",
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       "      <th>3</th>\n",
       "      <td>Ton</td>\n",
       "      <td>30.50</td>\n",
       "      <td>180.00</td>\n",
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       "      <td>722.70</td>\n",
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       "      <td>Ton</td>\n",
       "      <td>30.50</td>\n",
       "      <td>180.00</td>\n",
       "      <td>766.59</td>\n",
       "      <td>348.47</td>\n",
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       "      <td>1</td>\n",
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       "  formation   dip  azimuth      X      Y      Z                     geometry  \\\n",
       "0       Ton 30.50   180.00  96.47 451.56 477.73   POINT (96.47104 451.56362)   \n",
       "1       Ton 30.50   180.00 172.76 661.88 481.73  POINT (172.76101 661.87650)   \n",
       "2       Ton 30.50   180.00 383.07 957.76 444.45  POINT (383.07389 957.75787)   \n",
       "3       Ton 30.50   180.00 592.36 722.70 480.57  POINT (592.35583 722.70229)   \n",
       "4       Ton 30.50   180.00 766.59 348.47 498.96  POINT (766.58562 348.46907)   \n",
       "\n",
       "   polarity  \n",
       "0         1  \n",
       "1         1  \n",
       "2         1  \n",
       "3         1  \n",
       "4         1  "
      ]
     },
     "execution_count": 25,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "orientations['polarity'] = 1\n",
    "orientations.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "b0a32686",
   "metadata": {},
   "source": [
    "## Creating the GemPy Model"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "id": "461a6d52",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2023-05-08T10:52:40.452072Z",
     "start_time": "2023-05-08T10:52:40.433038Z"
    }
   },
   "outputs": [],
   "source": [
    "import sys\n",
    "sys.path.append('../../../../gempy-master')\n",
    "import gempy as gp"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "id": "e5228ecd",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2023-05-08T10:52:40.636918Z",
     "start_time": "2023-05-08T10:52:40.540514Z"
    }
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Model1  2023-05-08 12:52"
      ]
     },
     "execution_count": 27,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "geo_model = gp.create_model('Model1')\n",
    "geo_model"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "11e94b6b",
   "metadata": {},
   "source": [
    "### Initiating the Model"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "id": "76102008",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2023-05-08T10:52:40.903128Z",
     "start_time": "2023-05-08T10:52:40.784307Z"
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Active grids: ['regular']\n"
     ]
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       "  <thead>\n",
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       "      <th class=\"col_heading level0 col0\" >surface</th>\n",
       "      <th class=\"col_heading level0 col1\" >series</th>\n",
       "      <th class=\"col_heading level0 col2\" >order_surfaces</th>\n",
       "      <th class=\"col_heading level0 col3\" >color</th>\n",
       "      <th class=\"col_heading level0 col4\" >id</th>\n",
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       "      <td id=\"T_11009_row1_col0\" class=\"data row1 col0\" >Ton</td>\n",
       "      <td id=\"T_11009_row1_col1\" class=\"data row1 col1\" >Default series</td>\n",
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       "      <td id=\"T_11009_row1_col4\" class=\"data row1 col4\" >2</td>\n",
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      ],
      "text/plain": [
       "  surface          series  order_surfaces    color  id\n",
       "0   Sand1  Default series               1  #015482   1\n",
       "1     Ton  Default series               2  #9f0052   2"
      ]
     },
     "execution_count": 28,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "import pandas as pd\n",
    "\n",
    "gp.init_data(geo_model, extent, resolution,\n",
    "             surface_points_df = interfaces,\n",
    "             orientations_df = orientations,\n",
    "             default_values=True)\n",
    "geo_model.surfaces"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "f15e1fdd",
   "metadata": {},
   "source": [
    "The vertices and edges are currently NaN values, so no model has been computed so far."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "id": "e0bb59a3",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2023-05-08T10:52:41.290053Z",
     "start_time": "2023-05-08T10:52:41.264429Z"
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   "outputs": [
    {
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       "      <th>isBasement</th>\n",
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       "      <th>isActive</th>\n",
       "      <th>hasData</th>\n",
       "      <th>color</th>\n",
       "      <th>vertices</th>\n",
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       "      <th>id</th>\n",
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       "    <tr>\n",
       "      <th>0</th>\n",
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       "      <td>False</td>\n",
       "      <td>True</td>\n",
       "      <td>True</td>\n",
       "      <td>#015482</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1</td>\n",
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       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>Ton</td>\n",
       "      <td>Default series</td>\n",
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       "      <td>True</td>\n",
       "      <td>False</td>\n",
       "      <td>True</td>\n",
       "      <td>True</td>\n",
       "      <td>#9f0052</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2</td>\n",
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      "text/plain": [
       "  surface          series  order_surfaces  isBasement isFault  isActive  \\\n",
       "0   Sand1  Default series               1       False   False      True   \n",
       "1     Ton  Default series               2        True   False      True   \n",
       "\n",
       "   hasData    color vertices edges sfai  id  \n",
       "0     True  #015482      NaN   NaN  NaN   1  \n",
       "1     True  #9f0052      NaN   NaN  NaN   2  "
      ]
     },
     "execution_count": 29,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "geo_model.surfaces.df"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "6d83e0fa",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2023-03-01T12:58:53.064490Z",
     "start_time": "2023-03-01T12:58:53.059434Z"
    }
   },
   "source": [
    "### Mapping Stack to Surfaces"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "id": "37e07a9d",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2023-05-08T10:52:41.752012Z",
     "start_time": "2023-05-08T10:52:41.627481Z"
    }
   },
   "outputs": [
    {
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       "  <thead>\n",
       "    <tr>\n",
       "      <th class=\"blank level0\" >&nbsp;</th>\n",
       "      <th class=\"col_heading level0 col0\" >surface</th>\n",
       "      <th class=\"col_heading level0 col1\" >series</th>\n",
       "      <th class=\"col_heading level0 col2\" >order_surfaces</th>\n",
       "      <th class=\"col_heading level0 col3\" >color</th>\n",
       "      <th class=\"col_heading level0 col4\" >id</th>\n",
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       "      <th id=\"T_ff119_level0_row0\" class=\"row_heading level0 row0\" >0</th>\n",
       "      <td id=\"T_ff119_row0_col0\" class=\"data row0 col0\" >Sand1</td>\n",
       "      <td id=\"T_ff119_row0_col1\" class=\"data row0 col1\" >Strat_Series</td>\n",
       "      <td id=\"T_ff119_row0_col2\" class=\"data row0 col2\" >1</td>\n",
       "      <td id=\"T_ff119_row0_col3\" class=\"data row0 col3\" >#015482</td>\n",
       "      <td id=\"T_ff119_row0_col4\" class=\"data row0 col4\" >1</td>\n",
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       "    <tr>\n",
       "      <th id=\"T_ff119_level0_row1\" class=\"row_heading level0 row1\" >1</th>\n",
       "      <td id=\"T_ff119_row1_col0\" class=\"data row1 col0\" >Ton</td>\n",
       "      <td id=\"T_ff119_row1_col1\" class=\"data row1 col1\" >Strat_Series</td>\n",
       "      <td id=\"T_ff119_row1_col2\" class=\"data row1 col2\" >2</td>\n",
       "      <td id=\"T_ff119_row1_col3\" class=\"data row1 col3\" >#9f0052</td>\n",
       "      <td id=\"T_ff119_row1_col4\" class=\"data row1 col4\" >2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th id=\"T_ff119_level0_row2\" class=\"row_heading level0 row2\" >2</th>\n",
       "      <td id=\"T_ff119_row2_col0\" class=\"data row2 col0\" >basement</td>\n",
       "      <td id=\"T_ff119_row2_col1\" class=\"data row2 col1\" >Strat_Series</td>\n",
       "      <td id=\"T_ff119_row2_col2\" class=\"data row2 col2\" >3</td>\n",
       "      <td id=\"T_ff119_row2_col3\" class=\"data row2 col3\" >#ffbe00</td>\n",
       "      <td id=\"T_ff119_row2_col4\" class=\"data row2 col4\" >3</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n"
      ],
      "text/plain": [
       "    surface        series  order_surfaces    color  id\n",
       "0     Sand1  Strat_Series               1  #015482   1\n",
       "1       Ton  Strat_Series               2  #9f0052   2\n",
       "2  basement  Strat_Series               3  #ffbe00   3"
      ]
     },
     "execution_count": 30,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "gp.map_stack_to_surfaces(geo_model,\n",
    "                         {\"Strat_Series\": ('Sand1', 'Ton')},\n",
    "                         remove_unused_series=True)\n",
    "geo_model.add_surfaces('basement')"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "f8810b9b",
   "metadata": {},
   "source": [
    "### Loading the Topography"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "id": "30278aea",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2023-05-08T10:52:42.093005Z",
     "start_time": "2023-05-08T10:52:41.861764Z"
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Cropped raster to geo_model.grid.extent.\n",
      "depending on the size of the raster, this can take a while...\n",
      "storing converted file...\n",
      "Active grids: ['regular' 'topography']\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "Grid Object. Values: \n",
       "array([[   9.72      ,   10.69      ,  305.        ],\n",
       "       [   9.72      ,   10.69      ,  315.        ],\n",
       "       [   9.72      ,   10.69      ,  325.        ],\n",
       "       ...,\n",
       "       [ 970.056     , 1059.28181818,  622.0892334 ],\n",
       "       [ 970.056     , 1063.16909091,  622.06713867],\n",
       "       [ 970.056     , 1067.05636364,  622.05786133]])"
      ]
     },
     "execution_count": 31,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "geo_model.set_topography(\n",
    "    source='gdal', filepath='data/61_Exporting_geological_map_and_custom_sections_from_GemPy/raster1.tif')"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "47a7e983",
   "metadata": {},
   "source": [
    "### Defining Custom Section"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "id": "65c8d9fc",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2023-05-08T10:52:42.203166Z",
     "start_time": "2023-05-08T10:52:42.107768Z"
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Active grids: ['regular' 'topography' 'sections']\n"
     ]
    },
    {
     "data": {
      "text/html": [
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>start</th>\n",
       "      <th>stop</th>\n",
       "      <th>resolution</th>\n",
       "      <th>dist</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>Section1</th>\n",
       "      <td>[1.372395262185787, 383.9794474025771]</td>\n",
       "      <td>[970.9954955186289, 383.8831909730347]</td>\n",
       "      <td>[100, 80]</td>\n",
       "      <td>969.62</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>"
      ],
      "text/plain": [
       "                                           start                                    stop resolution   dist\n",
       "Section1  [1.372395262185787, 383.9794474025771]  [970.9954955186289, 383.8831909730347]  [100, 80] 969.62"
      ]
     },
     "execution_count": 32,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "custom_section = gpd.read_file(file_path + 'customsections1.shp')\n",
    "custom_section_dict = gg.utils.to_section_dict(custom_section, section_column='section')\n",
    "geo_model.set_section_grid(custom_section_dict)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "id": "a2f906b3",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2023-05-08T10:52:42.468240Z",
     "start_time": "2023-05-08T10:52:42.283003Z"
    }
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<gempy.plot.visualization_2d.Plot2D at 0x2b0f5226bb0>"
      ]
     },
     "execution_count": 33,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1040x715 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "gp.plot.plot_section_traces(geo_model)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "3279a7dd",
   "metadata": {},
   "source": [
    "### Setting Interpolator"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 34,
   "id": "7e5a79d9",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2023-05-08T10:52:45.549020Z",
     "start_time": "2023-05-08T10:52:42.855531Z"
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Compiling theano function...\n",
      "Level of Optimization:  fast_compile\n",
      "Device:  cpu\n",
      "Precision:  float64\n",
      "Number of faults:  0\n",
      "Compilation Done!\n",
      "Kriging values: \n",
      "                   values\n",
      "range            1528.90\n",
      "$C_o$           55655.83\n",
      "drift equations      [3]\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "<gempy.core.interpolator.InterpolatorModel at 0x2b0f52261c0>"
      ]
     },
     "execution_count": 34,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "gp.set_interpolator(geo_model,\n",
    "                    compile_theano=True,\n",
    "                    theano_optimizer='fast_compile',\n",
    "                    verbose=[],\n",
    "                    update_kriging = False\n",
    "                    )"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "cabe0461",
   "metadata": {},
   "source": [
    "### Computing Model"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 35,
   "id": "da761100",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2023-05-08T10:52:56.395399Z",
     "start_time": "2023-05-08T10:52:45.552739Z"
    }
   },
   "outputs": [],
   "source": [
    "sol = gp.compute_model(geo_model, compute_mesh=True)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "f60f2086",
   "metadata": {},
   "source": [
    "The surfaces DataFrame now contains values for vertices and edges."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 36,
   "id": "75db7b7e",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2023-05-08T10:52:56.504631Z",
     "start_time": "2023-05-08T10:52:56.398312Z"
    }
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>surface</th>\n",
       "      <th>series</th>\n",
       "      <th>order_surfaces</th>\n",
       "      <th>isBasement</th>\n",
       "      <th>isFault</th>\n",
       "      <th>isActive</th>\n",
       "      <th>hasData</th>\n",
       "      <th>color</th>\n",
       "      <th>vertices</th>\n",
       "      <th>edges</th>\n",
       "      <th>sfai</th>\n",
       "      <th>id</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>Sand1</td>\n",
       "      <td>Strat_Series</td>\n",
       "      <td>1</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>True</td>\n",
       "      <td>True</td>\n",
       "      <td>#015482</td>\n",
       "      <td>[[29.160000000000004, 194.27877317428587, 305....</td>\n",
       "      <td>[[2, 1, 0], [2, 0, 3], [3, 4, 2], [2, 4, 5], [...</td>\n",
       "      <td>0.26</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>Ton</td>\n",
       "      <td>Strat_Series</td>\n",
       "      <td>2</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>True</td>\n",
       "      <td>True</td>\n",
       "      <td>#9f0052</td>\n",
       "      <td>[[29.160000000000004, 365.78652999877926, 305....</td>\n",
       "      <td>[[2, 1, 0], [2, 0, 3], [3, 4, 2], [2, 4, 5], [...</td>\n",
       "      <td>0.21</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>basement</td>\n",
       "      <td>Strat_Series</td>\n",
       "      <td>3</td>\n",
       "      <td>True</td>\n",
       "      <td>False</td>\n",
       "      <td>True</td>\n",
       "      <td>True</td>\n",
       "      <td>#ffbe00</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>3</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "    surface        series  order_surfaces  isBasement isFault  isActive  \\\n",
       "0     Sand1  Strat_Series               1       False   False      True   \n",
       "1       Ton  Strat_Series               2       False   False      True   \n",
       "2  basement  Strat_Series               3        True   False      True   \n",
       "\n",
       "   hasData    color                                           vertices  \\\n",
       "0     True  #015482  [[29.160000000000004, 194.27877317428587, 305....   \n",
       "1     True  #9f0052  [[29.160000000000004, 365.78652999877926, 305....   \n",
       "2     True  #ffbe00                                                NaN   \n",
       "\n",
       "                                               edges sfai  id  \n",
       "0  [[2, 1, 0], [2, 0, 3], [3, 4, 2], [2, 4, 5], [... 0.26   1  \n",
       "1  [[2, 1, 0], [2, 0, 3], [3, 4, 2], [2, 4, 5], [... 0.21   2  \n",
       "2                                                NaN  NaN   3  "
      ]
     },
     "execution_count": 36,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "geo_model.surfaces.df"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "6ab15b6e",
   "metadata": {},
   "source": [
    "## Plotting the 3D Model"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 37,
   "id": "21511fa9",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2023-05-08T10:52:58.391215Z",
     "start_time": "2023-05-08T10:52:56.510055Z"
    }
   },
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "C:\\Users\\jan13846\\.conda\\envs\\gemgis\\lib\\site-packages\\pyvista\\plotting\\tools.py:571: PyvistaDeprecationWarning: The usage of `parse_color` is deprecated in favor of the new `Color` class.\n",
      "  warnings.warn(\n",
      "C:\\Users\\jan13846\\.conda\\envs\\gemgis\\lib\\site-packages\\pyvista\\jupyter\\notebook.py:60: UserWarning: Failed to use notebook backend: \n",
      "\n",
      "Please install `ipyvtklink` to use this feature: https://github.com/Kitware/ipyvtklink\n",
      "\n",
      "Falling back to a static output.\n",
      "  warnings.warn(\n"
     ]
    },
    {
     "data": {
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\n",
      "text/plain": [
       "<PIL.Image.Image image mode=RGB size=1024x768>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "gpv = gp.plot_3d(geo_model, image=False, show_topography=True,\n",
    "                 plotter_type='basic', notebook=True, show_lith=True)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "efaeaf82",
   "metadata": {},
   "source": [
    "## Extracting Shapefiles from Gempy model"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "ca5c39b8",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2023-03-01T13:18:18.668043Z",
     "start_time": "2023-03-01T13:18:18.591590Z"
    }
   },
   "source": [
    "Using the following code we are able to download the custom sections and the geological map as shapefiles"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "2a73a3d4",
   "metadata": {},
   "source": [
    "### Extracting GemPy Section Lines as Shapefiles"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 38,
   "id": "e6134e15",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2023-05-08T10:52:58.437814Z",
     "start_time": "2023-05-08T10:52:58.396498Z"
    }
   },
   "outputs": [],
   "source": [
    "from shapely.geometry import LineString\n",
    "gdf_sections = geo_model.grid.sections.df.copy(deep=True)\n",
    "gdf_sections.reset_index()\n",
    "linestrings = [LineString((gdf_sections.iloc[i]['start'],gdf_sections.iloc[i]['stop'] )) for i in range(len(gdf_sections))]\n",
    "gdf_sections_new = gpd.GeoDataFrame(geometry=linestrings, data= gdf_sections.reset_index()[['index']], crs='EPSG:32632')\n",
    "gdf_sections_new.to_file(file_path + 'test_sections.shp')"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "707ff910",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2023-03-01T13:16:07.509289Z",
     "start_time": "2023-03-01T13:16:07.492633Z"
    }
   },
   "source": [
    "### Extracting GemPy Geological Map Polygons as Shapefiles"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 39,
   "id": "b1986438",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2023-05-08T10:52:58.532352Z",
     "start_time": "2023-05-08T10:52:58.441722Z"
    }
   },
   "outputs": [],
   "source": [
    "gdf = gg.postprocessing.extract_lithologies(geo_model, geo_model.grid.regular_grid.extent[:4], crs='EPSG:32632')\n",
    "gdf.to_file(file_path + 'test.shp')"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "764549bb",
   "metadata": {},
   "source": [
    "<img src=\"../images/Extracted_Files_QGIS.png\" width=700>"
   ]
  }
 ],
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