docs/Code_examples/ch2_1_gravity.ipynb

{
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  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {
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    "jupyter": {
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    }
   },
   "outputs": [],
   "source": [
    "%matplotlib inline\n",
    "from pyvista import set_plot_theme\n",
    "set_plot_theme('document')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "\n",
    "# 2.1 Forward Gravity: Simple example\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Importing gempy\n",
    "\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {
    "collapsed": false,
    "jupyter": {
     "outputs_hidden": false
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Setting Backend To: AvailableBackends.numpy\n"
     ]
    }
   ],
   "source": [
    "import gempy as gp\n",
    "import gempy_viewer as gpv\n",
    "\n",
    "# Aux imports\n",
    "import numpy as np\n",
    "import pandas as pd\n",
    "import os\n",
    "import matplotlib.pyplot as plt\n",
    "\n",
    "\n",
    "np.random.seed(1515)\n",
    "pd.set_option('display.precision', 2)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {
    "collapsed": false,
    "jupyter": {
     "outputs_hidden": false
    }
   },
   "outputs": [
    {
     "ename": "FileNotFoundError",
     "evalue": "[Errno 2] No such file or directory: '/home/spaceswimmer/Documents/data/input_data/tut_SandStone/SandStone_Points.csv'",
     "output_type": "error",
     "traceback": [
      "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
      "\u001b[0;31mFileNotFoundError\u001b[0m                         Traceback (most recent call last)",
      "Cell \u001b[0;32mIn[3], line 5\u001b[0m\n\u001b[1;32m      1\u001b[0m data_path \u001b[38;5;241m=\u001b[39m os\u001b[38;5;241m.\u001b[39mpath\u001b[38;5;241m.\u001b[39mabspath(\u001b[38;5;124m'\u001b[39m\u001b[38;5;124m../../data/input_data/tut_SandStone\u001b[39m\u001b[38;5;124m'\u001b[39m)\n\u001b[1;32m      3\u001b[0m \u001b[38;5;66;03m# Importing the data from csv\u001b[39;00m\n\u001b[0;32m----> 5\u001b[0m geo_model: gp\u001b[38;5;241m.\u001b[39mdata\u001b[38;5;241m.\u001b[39mGeoModel \u001b[38;5;241m=\u001b[39m \u001b[43mgp\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mcreate_geomodel\u001b[49m\u001b[43m(\u001b[49m\n\u001b[1;32m      6\u001b[0m \u001b[43m    \u001b[49m\u001b[43mproject_name\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[38;5;124;43m'\u001b[39;49m\u001b[38;5;124;43mGreenstone\u001b[39;49m\u001b[38;5;124;43m'\u001b[39;49m\u001b[43m,\u001b[49m\n\u001b[1;32m      7\u001b[0m \u001b[43m    \u001b[49m\u001b[43mextent\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43m[\u001b[49m\u001b[38;5;241;43m696000\u001b[39;49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;241;43m747000\u001b[39;49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;241;43m6863000\u001b[39;49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;241;43m6930000\u001b[39;49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;241;43m-\u001b[39;49m\u001b[38;5;241;43m20000\u001b[39;49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;241;43m200\u001b[39;49m\u001b[43m]\u001b[49m\u001b[43m,\u001b[49m\u001b[43m  \u001b[49m\u001b[38;5;66;43;03m# * Here we define the extent of the model\u001b[39;49;00m\n\u001b[1;32m      8\u001b[0m \u001b[43m    \u001b[49m\u001b[43mrefinement\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[38;5;241;43m5\u001b[39;49m\u001b[43m,\u001b[49m\u001b[43m  \u001b[49m\u001b[38;5;66;43;03m# * Here we define the number of octree levels. If octree levels are defined, the resolution is ignored.\u001b[39;49;00m\n\u001b[1;32m      9\u001b[0m \u001b[43m    \u001b[49m\u001b[43mimporter_helper\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mgp\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mdata\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mImporterHelper\u001b[49m\u001b[43m(\u001b[49m\n\u001b[1;32m     10\u001b[0m \u001b[43m        \u001b[49m\u001b[43mpath_to_orientations\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mdata_path\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;241;43m+\u001b[39;49m\u001b[43m \u001b[49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[38;5;124;43m/SandStone_Foliations.csv\u001b[39;49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[43m,\u001b[49m\n\u001b[1;32m     11\u001b[0m \u001b[43m        \u001b[49m\u001b[43mpath_to_surface_points\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mdata_path\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;241;43m+\u001b[39;49m\u001b[43m \u001b[49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[38;5;124;43m/SandStone_Points.csv\u001b[39;49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[43m,\u001b[49m\n\u001b[1;32m     12\u001b[0m \u001b[43m        \u001b[49m\u001b[43mhash_surface_points\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[38;5;28;43;01mNone\u001b[39;49;00m\u001b[43m,\u001b[49m\n\u001b[1;32m     13\u001b[0m \u001b[43m        \u001b[49m\u001b[43mhash_orientations\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[38;5;28;43;01mNone\u001b[39;49;00m\n\u001b[1;32m     14\u001b[0m \u001b[43m    \u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m     15\u001b[0m \u001b[43m)\u001b[49m\n",
      "File \u001b[0;32m~/Documents/NeoGen_Modeling/venv/lib/python3.12/site-packages/gempy/API/initialization_API.py:73\u001b[0m, in \u001b[0;36mcreate_geomodel\u001b[0;34m(project_name, extent, resolution, refinement, structural_frame, importer_helper)\u001b[0m\n\u001b[1;32m     71\u001b[0m     structural_frame \u001b[38;5;241m=\u001b[39m StructuralFrame\u001b[38;5;241m.\u001b[39minitialize_default_structure()\n\u001b[1;32m     72\u001b[0m \u001b[38;5;28;01mcase\u001b[39;00m\u001b[38;5;250m \u001b[39m(\u001b[38;5;28;01mNone\u001b[39;00m, \u001b[38;5;28;01m_\u001b[39;00m):\n\u001b[0;32m---> 73\u001b[0m     structural_frame \u001b[38;5;241m=\u001b[39m \u001b[43m_initialize_structural_frame\u001b[49m\u001b[43m(\u001b[49m\u001b[43mimporter_helper\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m     74\u001b[0m \u001b[38;5;28;01mcase\u001b[39;00m\u001b[38;5;250m \u001b[39m\u001b[38;5;28;01m_\u001b[39;00m:\n\u001b[1;32m     75\u001b[0m     \u001b[38;5;28;01mpass\u001b[39;00m\n",
      "File \u001b[0;32m~/Documents/NeoGen_Modeling/venv/lib/python3.12/site-packages/gempy/API/initialization_API.py:155\u001b[0m, in \u001b[0;36m_initialize_structural_frame\u001b[0;34m(importer_helper)\u001b[0m\n\u001b[1;32m    154\u001b[0m \u001b[38;5;28;01mdef\u001b[39;00m \u001b[38;5;21m_initialize_structural_frame\u001b[39m(importer_helper: ImporterHelper) \u001b[38;5;241m-\u001b[39m\u001b[38;5;241m>\u001b[39m StructuralFrame:\n\u001b[0;32m--> 155\u001b[0m     surface_points, orientations \u001b[38;5;241m=\u001b[39m \u001b[43m_read_input_points\u001b[49m\u001b[43m(\u001b[49m\u001b[43mimporter_helper\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m    157\u001b[0m     \u001b[38;5;28;01mreturn\u001b[39;00m StructuralFrame\u001b[38;5;241m.\u001b[39mfrom_data_tables(surface_points, orientations)\n",
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      "File \u001b[0;32m~/Documents/NeoGen_Modeling/venv/lib/python3.12/site-packages/gempy/API/io_API.py:23\u001b[0m, in \u001b[0;36mread_surface_points\u001b[0;34m(path, coord_x_name, coord_y_name, coord_z_name, surface_name, name_id_map, pandas_kwargs)\u001b[0m\n\u001b[1;32m     20\u001b[0m     pandas_kwargs[\u001b[38;5;124m'\u001b[39m\u001b[38;5;124msep\u001b[39m\u001b[38;5;124m'\u001b[39m] \u001b[38;5;241m=\u001b[39m \u001b[38;5;124m'\u001b[39m\u001b[38;5;124m,\u001b[39m\u001b[38;5;124m'\u001b[39m\n\u001b[1;32m     22\u001b[0m pd \u001b[38;5;241m=\u001b[39m require_pandas()\n\u001b[0;32m---> 23\u001b[0m csv \u001b[38;5;241m=\u001b[39m \u001b[43mpd\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mread_csv\u001b[49m\u001b[43m(\u001b[49m\u001b[43mpath\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[43mpandas_kwargs\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m     24\u001b[0m csv \u001b[38;5;241m=\u001b[39m _standardize(csv)\n\u001b[1;32m     26\u001b[0m surface_points: SurfacePointsTable \u001b[38;5;241m=\u001b[39m SurfacePointsTable\u001b[38;5;241m.\u001b[39mfrom_arrays(\n\u001b[1;32m     27\u001b[0m     x\u001b[38;5;241m=\u001b[39mcsv[coord_x_name]\u001b[38;5;241m.\u001b[39mvalues,\n\u001b[1;32m     28\u001b[0m     y\u001b[38;5;241m=\u001b[39mcsv[coord_y_name]\u001b[38;5;241m.\u001b[39mvalues,\n\u001b[0;32m   (...)\u001b[0m\n\u001b[1;32m     31\u001b[0m     name_id_map\u001b[38;5;241m=\u001b[39mname_id_map\n\u001b[1;32m     32\u001b[0m )\n",
      "File \u001b[0;32m~/Documents/NeoGen_Modeling/venv/lib/python3.12/site-packages/pandas/io/parsers/readers.py:1026\u001b[0m, in \u001b[0;36mread_csv\u001b[0;34m(filepath_or_buffer, sep, delimiter, header, names, index_col, usecols, dtype, engine, converters, true_values, false_values, skipinitialspace, skiprows, skipfooter, nrows, na_values, keep_default_na, na_filter, verbose, skip_blank_lines, parse_dates, infer_datetime_format, keep_date_col, date_parser, date_format, dayfirst, cache_dates, iterator, chunksize, compression, thousands, decimal, lineterminator, quotechar, quoting, doublequote, escapechar, comment, encoding, encoding_errors, dialect, on_bad_lines, delim_whitespace, low_memory, memory_map, float_precision, storage_options, dtype_backend)\u001b[0m\n\u001b[1;32m   1013\u001b[0m kwds_defaults \u001b[38;5;241m=\u001b[39m _refine_defaults_read(\n\u001b[1;32m   1014\u001b[0m     dialect,\n\u001b[1;32m   1015\u001b[0m     delimiter,\n\u001b[0;32m   (...)\u001b[0m\n\u001b[1;32m   1022\u001b[0m     dtype_backend\u001b[38;5;241m=\u001b[39mdtype_backend,\n\u001b[1;32m   1023\u001b[0m )\n\u001b[1;32m   1024\u001b[0m kwds\u001b[38;5;241m.\u001b[39mupdate(kwds_defaults)\n\u001b[0;32m-> 1026\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[43m_read\u001b[49m\u001b[43m(\u001b[49m\u001b[43mfilepath_or_buffer\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mkwds\u001b[49m\u001b[43m)\u001b[49m\n",
      "File \u001b[0;32m~/Documents/NeoGen_Modeling/venv/lib/python3.12/site-packages/pandas/io/parsers/readers.py:620\u001b[0m, in \u001b[0;36m_read\u001b[0;34m(filepath_or_buffer, kwds)\u001b[0m\n\u001b[1;32m    617\u001b[0m _validate_names(kwds\u001b[38;5;241m.\u001b[39mget(\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mnames\u001b[39m\u001b[38;5;124m\"\u001b[39m, \u001b[38;5;28;01mNone\u001b[39;00m))\n\u001b[1;32m    619\u001b[0m \u001b[38;5;66;03m# Create the parser.\u001b[39;00m\n\u001b[0;32m--> 620\u001b[0m parser \u001b[38;5;241m=\u001b[39m \u001b[43mTextFileReader\u001b[49m\u001b[43m(\u001b[49m\u001b[43mfilepath_or_buffer\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[43mkwds\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m    622\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m chunksize \u001b[38;5;129;01mor\u001b[39;00m iterator:\n\u001b[1;32m    623\u001b[0m     \u001b[38;5;28;01mreturn\u001b[39;00m parser\n",
      "File \u001b[0;32m~/Documents/NeoGen_Modeling/venv/lib/python3.12/site-packages/pandas/io/parsers/readers.py:1620\u001b[0m, in \u001b[0;36mTextFileReader.__init__\u001b[0;34m(self, f, engine, **kwds)\u001b[0m\n\u001b[1;32m   1617\u001b[0m     \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39moptions[\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mhas_index_names\u001b[39m\u001b[38;5;124m\"\u001b[39m] \u001b[38;5;241m=\u001b[39m kwds[\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mhas_index_names\u001b[39m\u001b[38;5;124m\"\u001b[39m]\n\u001b[1;32m   1619\u001b[0m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mhandles: IOHandles \u001b[38;5;241m|\u001b[39m \u001b[38;5;28;01mNone\u001b[39;00m \u001b[38;5;241m=\u001b[39m \u001b[38;5;28;01mNone\u001b[39;00m\n\u001b[0;32m-> 1620\u001b[0m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39m_engine \u001b[38;5;241m=\u001b[39m \u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43m_make_engine\u001b[49m\u001b[43m(\u001b[49m\u001b[43mf\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mengine\u001b[49m\u001b[43m)\u001b[49m\n",
      "File \u001b[0;32m~/Documents/NeoGen_Modeling/venv/lib/python3.12/site-packages/pandas/io/parsers/readers.py:1880\u001b[0m, in \u001b[0;36mTextFileReader._make_engine\u001b[0;34m(self, f, engine)\u001b[0m\n\u001b[1;32m   1878\u001b[0m     \u001b[38;5;28;01mif\u001b[39;00m \u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mb\u001b[39m\u001b[38;5;124m\"\u001b[39m \u001b[38;5;129;01mnot\u001b[39;00m \u001b[38;5;129;01min\u001b[39;00m mode:\n\u001b[1;32m   1879\u001b[0m         mode \u001b[38;5;241m+\u001b[39m\u001b[38;5;241m=\u001b[39m \u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mb\u001b[39m\u001b[38;5;124m\"\u001b[39m\n\u001b[0;32m-> 1880\u001b[0m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mhandles \u001b[38;5;241m=\u001b[39m \u001b[43mget_handle\u001b[49m\u001b[43m(\u001b[49m\n\u001b[1;32m   1881\u001b[0m \u001b[43m    \u001b[49m\u001b[43mf\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m   1882\u001b[0m \u001b[43m    \u001b[49m\u001b[43mmode\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m   1883\u001b[0m \u001b[43m    \u001b[49m\u001b[43mencoding\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43moptions\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mget\u001b[49m\u001b[43m(\u001b[49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[38;5;124;43mencoding\u001b[39;49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;28;43;01mNone\u001b[39;49;00m\u001b[43m)\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m   1884\u001b[0m \u001b[43m    \u001b[49m\u001b[43mcompression\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43moptions\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mget\u001b[49m\u001b[43m(\u001b[49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[38;5;124;43mcompression\u001b[39;49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;28;43;01mNone\u001b[39;49;00m\u001b[43m)\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m   1885\u001b[0m \u001b[43m    \u001b[49m\u001b[43mmemory_map\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43moptions\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mget\u001b[49m\u001b[43m(\u001b[49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[38;5;124;43mmemory_map\u001b[39;49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;28;43;01mFalse\u001b[39;49;00m\u001b[43m)\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m   1886\u001b[0m \u001b[43m    \u001b[49m\u001b[43mis_text\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mis_text\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m   1887\u001b[0m \u001b[43m    \u001b[49m\u001b[43merrors\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43moptions\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mget\u001b[49m\u001b[43m(\u001b[49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[38;5;124;43mencoding_errors\u001b[39;49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[38;5;124;43mstrict\u001b[39;49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[43m)\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m   1888\u001b[0m \u001b[43m    \u001b[49m\u001b[43mstorage_options\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43moptions\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mget\u001b[49m\u001b[43m(\u001b[49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[38;5;124;43mstorage_options\u001b[39;49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;28;43;01mNone\u001b[39;49;00m\u001b[43m)\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m   1889\u001b[0m \u001b[43m\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m   1890\u001b[0m \u001b[38;5;28;01massert\u001b[39;00m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mhandles \u001b[38;5;129;01mis\u001b[39;00m \u001b[38;5;129;01mnot\u001b[39;00m \u001b[38;5;28;01mNone\u001b[39;00m\n\u001b[1;32m   1891\u001b[0m f \u001b[38;5;241m=\u001b[39m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mhandles\u001b[38;5;241m.\u001b[39mhandle\n",
      "File \u001b[0;32m~/Documents/NeoGen_Modeling/venv/lib/python3.12/site-packages/pandas/io/common.py:873\u001b[0m, in \u001b[0;36mget_handle\u001b[0;34m(path_or_buf, mode, encoding, compression, memory_map, is_text, errors, storage_options)\u001b[0m\n\u001b[1;32m    868\u001b[0m \u001b[38;5;28;01melif\u001b[39;00m \u001b[38;5;28misinstance\u001b[39m(handle, \u001b[38;5;28mstr\u001b[39m):\n\u001b[1;32m    869\u001b[0m     \u001b[38;5;66;03m# Check whether the filename is to be opened in binary mode.\u001b[39;00m\n\u001b[1;32m    870\u001b[0m     \u001b[38;5;66;03m# Binary mode does not support 'encoding' and 'newline'.\u001b[39;00m\n\u001b[1;32m    871\u001b[0m     \u001b[38;5;28;01mif\u001b[39;00m ioargs\u001b[38;5;241m.\u001b[39mencoding \u001b[38;5;129;01mand\u001b[39;00m \u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mb\u001b[39m\u001b[38;5;124m\"\u001b[39m \u001b[38;5;129;01mnot\u001b[39;00m \u001b[38;5;129;01min\u001b[39;00m ioargs\u001b[38;5;241m.\u001b[39mmode:\n\u001b[1;32m    872\u001b[0m         \u001b[38;5;66;03m# Encoding\u001b[39;00m\n\u001b[0;32m--> 873\u001b[0m         handle \u001b[38;5;241m=\u001b[39m \u001b[38;5;28;43mopen\u001b[39;49m\u001b[43m(\u001b[49m\n\u001b[1;32m    874\u001b[0m \u001b[43m            \u001b[49m\u001b[43mhandle\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m    875\u001b[0m \u001b[43m            \u001b[49m\u001b[43mioargs\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mmode\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m    876\u001b[0m \u001b[43m            \u001b[49m\u001b[43mencoding\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mioargs\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mencoding\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m    877\u001b[0m \u001b[43m            \u001b[49m\u001b[43merrors\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43merrors\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m    878\u001b[0m \u001b[43m            \u001b[49m\u001b[43mnewline\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[43m,\u001b[49m\n\u001b[1;32m    879\u001b[0m \u001b[43m        \u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m    880\u001b[0m     \u001b[38;5;28;01melse\u001b[39;00m:\n\u001b[1;32m    881\u001b[0m         \u001b[38;5;66;03m# Binary mode\u001b[39;00m\n\u001b[1;32m    882\u001b[0m         handle \u001b[38;5;241m=\u001b[39m \u001b[38;5;28mopen\u001b[39m(handle, ioargs\u001b[38;5;241m.\u001b[39mmode)\n",
      "\u001b[0;31mFileNotFoundError\u001b[0m: [Errno 2] No such file or directory: '/home/spaceswimmer/Documents/data/input_data/tut_SandStone/SandStone_Points.csv'"
     ]
    }
   ],
   "source": [
    "data_path = os.path.abspath('../../data/input_data/tut_SandStone')\n",
    "\n",
    "# Importing the data from csv\n",
    "\n",
    "geo_model: gp.data.GeoModel = gp.create_geomodel(\n",
    "    project_name='Greenstone',\n",
    "    extent=[696000, 747000, 6863000, 6930000, -20000, 200],  # * Here we define the extent of the model\n",
    "    refinement=5,  # * Here we define the number of octree levels. If octree levels are defined, the resolution is ignored.\n",
    "    importer_helper=gp.data.ImporterHelper(\n",
    "        path_to_orientations=data_path + \"/SandStone_Foliations.csv\",\n",
    "        path_to_surface_points=data_path + \"/SandStone_Points.csv\",\n",
    "        hash_surface_points=None,\n",
    "        hash_orientations=None\n",
    "    )\n",
    ")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": false,
    "jupyter": {
     "outputs_hidden": false
    }
   },
   "outputs": [],
   "source": [
    "gp.map_stack_to_surfaces(\n",
    "    gempy_model=geo_model,\n",
    "    mapping_object={\n",
    "        \"EarlyGranite_Series\": 'EarlyGranite',\n",
    "        \"BIF_Series\": ('SimpleMafic2', 'SimpleBIF'),\n",
    "        \"SimpleMafic_Series\": 'SimpleMafic1', 'Basement': 'basement'\n",
    "    }\n",
    ")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": false,
    "jupyter": {
     "outputs_hidden": false
    }
   },
   "outputs": [],
   "source": [
    "gpv.plot_2d(geo_model)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Creating grid\n",
    "\n",
    "\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "First we need to define the location of the devices. For this example we\n",
    "can make a map:\n",
    "\n",
    "\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": false,
    "jupyter": {
     "outputs_hidden": false
    }
   },
   "outputs": [],
   "source": [
    "grav_res = 20\n",
    "X = np.linspace(7.050000e+05, 747000, grav_res)\n",
    "Y = np.linspace(6863000, 6925000, grav_res)\n",
    "Z = 300\n",
    "xyz = np.meshgrid(X, Y, Z)\n",
    "xy_ravel = np.vstack(list(map(np.ravel, xyz))).T\n",
    "xy_ravel"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "We can see the location of the devices relative to the model data:\n",
    "\n",
    "\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": false,
    "jupyter": {
     "outputs_hidden": false
    }
   },
   "outputs": [],
   "source": [
    "gpv.plot_2d(geo_model, direction='z', show=False)\n",
    "plt.scatter(xy_ravel[:, 0], xy_ravel[:, 1], s=1)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Now we need to create the grid centered on the devices (see:\n",
    "https://github.com/cgre-aachen/gempy/blob/master/notebooks/tutorials/ch1-3-Grids.ipynb)\n",
    "\n",
    "\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "geo_model.set_centered_grid(xy_ravel, resolution=[10, 10, 15], radius=5000)\n",
    "\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": false,
    "jupyter": {
     "outputs_hidden": false
    }
   },
   "outputs": [],
   "source": [
    "gp.set_centered_grid(\n",
    "    grid=geo_model.grid,\n",
    "    centers=xy_ravel,\n",
    "    resolution=np.array([10, 10, 15]),\n",
    "    radius=np.array([5000, 5000, 5000])\n",
    ")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": false,
    "jupyter": {
     "outputs_hidden": false
    }
   },
   "outputs": [],
   "source": [
    "geo_model.grid.centered_grid.kernel_grid_centers"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Now we need to compute the component tz (see\n",
    "https://github.com/cgre-achen/gempy/blob/master/notebooks/tutorials/ch2-2-Cell_selection.ipynb)\n",
    "\n",
    "\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": false,
    "jupyter": {
     "outputs_hidden": false
    }
   },
   "outputs": [],
   "source": [
    "gravity_gradient = gp.calculate_gravity_gradient(geo_model.grid.centered_grid)\n",
    "gravity_gradient"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": false,
    "jupyter": {
     "outputs_hidden": false
    }
   },
   "outputs": [],
   "source": [
    "geo_model.geophysics_input = gp.data.GeophysicsInput(\n",
    "    tz=gravity_gradient,\n",
    "    densities=np.array([2.61, 2.92, 3.1, 2.92, 2.61]),\n",
    ")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Once we have created a gravity interpolator we can call it from compute\n",
    "model as follows:\n",
    "\n",
    "\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": false,
    "jupyter": {
     "outputs_hidden": false
    }
   },
   "outputs": [],
   "source": [
    "geo_model.interpolation_options.mesh_extraction = False\n",
    "sol = gp.compute_model(\n",
    "    gempy_model=geo_model,\n",
    "    engine_config=gp.data.GemPyEngineConfig(\n",
    "        backend=gp.data.AvailableBackends.numpy,\n",
    "        dtype='float32'\n",
    "    )\n",
    ")\n",
    "\n",
    "grav = sol.gravity"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": false,
    "jupyter": {
     "outputs_hidden": false
    }
   },
   "outputs": [],
   "source": [
    "gpv.plot_2d(geo_model, cell_number=[-1], direction=['z'], show_data=False)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": false,
    "jupyter": {
     "outputs_hidden": false
    }
   },
   "outputs": [],
   "source": [
    "gpv.plot_2d(geo_model, cell_number=['mid'], direction='x')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": false,
    "jupyter": {
     "outputs_hidden": false
    }
   },
   "outputs": [],
   "source": [
    "gpv.plot_2d(geo_model, direction=['z'], height=7, show_results=False, show_data=True, show=False)\n",
    "plt.scatter(xy_ravel[:, 0], xy_ravel[:, 1], s=1)\n",
    "plt.imshow(sol.gravity.reshape(grav_res, grav_res),\n",
    "           extent=(xy_ravel[:, 0].min() + (xy_ravel[0, 0] - xy_ravel[1, 0]) / 2,\n",
    "                   xy_ravel[:, 0].max() - (xy_ravel[0, 0] - xy_ravel[1, 0]) / 2,\n",
    "                   xy_ravel[:, 1].min() + (xy_ravel[0, 1] - xy_ravel[30, 1]) / 2,\n",
    "                   xy_ravel[:, 1].max() - (xy_ravel[0, 1] - xy_ravel[30, 1]) / 2),\n",
    "           cmap='viridis_r', origin='lower')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Plotting lithologies\n",
    "\n",
    "If we want to compute the lithologies we will need to create a normal\n",
    "interpolator object as seen in the Chapter 1 of the tutorials\n",
    "\n",
    "\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Now we can plot all together (change the alpha parameter to see the\n",
    "gravity overlying):\n",
    "\n",
    "\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": false,
    "jupyter": {
     "outputs_hidden": false
    }
   },
   "outputs": [],
   "source": [
    "gpv.plot_2d(geo_model, cell_number=[-1], direction=['z'], show=False,\n",
    "            kwargs_regular_grid={'alpha': .5})\n",
    "\n",
    "plt.scatter(xy_ravel[:, 0], xy_ravel[:, 1], s=1)\n",
    "plt.imshow(grav.reshape(grav_res, grav_res),\n",
    "           extent=(xy_ravel[:, 0].min() + (xy_ravel[0, 0] - xy_ravel[1, 0]) / 2,\n",
    "                   xy_ravel[:, 0].max() - (xy_ravel[0, 0] - xy_ravel[1, 0]) / 2,\n",
    "                   xy_ravel[:, 1].min() + (xy_ravel[0, 1] - xy_ravel[30, 1]) / 2,\n",
    "                   xy_ravel[:, 1].max() - (xy_ravel[0, 1] - xy_ravel[30, 1]) / 2),\n",
    "           cmap='viridis_r', origin='lower', alpha=.8)\n",
    "cbar = plt.colorbar()\n",
    "cbar.set_label(r'$\\mu$gal')\n",
    "plt.show()\n",
    "\n",
    "# sphinx_gallery_thumbnail_number = -2"
   ]
  }
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