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    "<img src=\"../../data/images/gempy_logo.png\" />\n",
    "\n",
    "# <center> From Maps to Models - Tutorials for structural geological modeling using GemPy and GemGIS</center>\n",
    "\n",
    "# Model 4 - Unconformable/Truncated Layers\n",
    "\n",
    "The fourth and last notebook in this tutorial series builds upon the builds upon the [previous three notebooks](../01_basic_modeling) ([previous three notebooks on Github](https://nbviewer.org/github/cgre-aachen/gemgis_data/tree/main/notebooks/01_basic_modeling)) where parallel horizontal, parallel folded and parallel faulted layers were modeled. This notebook illustrates now how to create a simple model of unconformable layers in `GemPy`. The model consists of four layers of which only two are always parallel. These two groups (`Series`) of parallel layers are separated and truncated by an unconformity. The model has an extent of 1000 m by 1000 m with a vertical extent of 600 m. \n",
    "\n",
    "<div class=\"alert alert-block alert-success\">\n",
    "<b>In this tutorial, you will learn the following:</b> <br>\n",
    "- Get an understanding of how unconformities are modeled/displayed in GemPy<br>\n",
    "- How to build a simple model consisting of <b>unconformable layers</b> belonging to <b>multiple Series</b><br>\n",
    "\n",
    "</div>\n",
    "\n",
    "## Contents\n",
    "\n",
    "1. [Installing GemPy](#installing-gempy)\n",
    "2. [Importing Libraries](#importing-libraries)\n",
    "3. [Data Preparation](#data-preparation)\n",
    "    1. [Importing Interface Points](#importing-interface-points)\n",
    "    2. [Importing Orientations](#importing-orientations)\n",
    "4. [GemPy Model Calculation](#gempy-model-calculation)\n",
    "    1. [Creating the GemPy Model](#creating-the-gempy-model)\n",
    "    2. [Inspecting the Surfaces](#inspecting-the-surfaces)\n",
    "    3. [Inspecting the Input Data](#inspecting-the-input-data)\n",
    "    4. [Map Stack to Surfaces](#map-stack-to-surfaces)\n",
    "    5. [Plotting Input Data in 2D](#plotting-the-input-data-in-2d)\n",
    "    6. [Plotting Input Data in 3D](#plotting-the-input-data-in-3d)\n",
    "    7. [Setting the Interpolator](#setting-the-interpolator)\n",
    "    8. [Computing the Model](#computing-the-model)\n",
    "5. [Model Visualization and Post-Processing](#model-visualization-and-post-processing)\n",
    "    1. [Visualizing Cross Sections of the Computed Model](#visualizing-cross-sections-of-the-computed-model)\n",
    "    2. [Visualizing the computed model in 3D](#visualizing-the-computed-model-in-3d)\n",
    "6. [Conclusions](#conclusions)\n",
    "7. [Outlook](#outlook)\n",
    "8. [Licensing](#licensing)\n",
    "\n",
    "\n",
    "\n",
    "<img src=\"../images/model4.png\" width=500/>"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "04c77e47",
   "metadata": {},
   "source": [
    "Unconformities are the last element that `GemPy` is capable of modeling apart from folded and faulted layers. Unconformities are not calculated as a fault surface that offsets layers. Instead, a new scalar field is calculated, which is merged with other scalar fields. In order to create another scalar field, the layers just have to be defined as non-parallel layers in `gp.map_stack_to_surfaces()` by defining multiple `Series`. \n",
    "\n",
    "<img src=\"../../data/images/model3_fig1.PNG\" width=500/>\n",
    "Source: <a href=\"https://doi.org/10.5194/gmd-12-1-2019\">de la Varga et al. (2019)</a>"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "solid-hormone",
   "metadata": {},
   "source": [
    "<a id='installing-gempy'></a>\n",
    "\n",
    "# Installing GemPy\n",
    "\n",
    "If you have not installed `GemPy` yet, please follow the [installation instructions](https://docs.gempy.org/installation.html). If you encounter any issues, feel free to open a new discussion at [GemPy Discussions](https://github.com/cgre-aachen/gempy/discussions). If you encounter an error in the installation process, feel free to also open an issue at [GemPy Issues](https://github.com/cgre-aachen/gempy/issues). There, the `GemPy` development team will help you out. "
   ]
  },
  {
   "cell_type": "markdown",
   "id": "artificial-customs",
   "metadata": {},
   "source": [
    "<a id='importing-libraries'></a>\n",
    "\n",
    "# Importing Libraries\n",
    "\n",
    "For this notebook, we need the `pandas` library for the data preparation, `matplotlib` for plotting and of course the `gempy` library. The `gempy_viewer` library is used to plot the modeling results. Any warnings that may appear can be ignored for now. "
   ]
  },
  {
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   "execution_count": 1,
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     "text": [
      "Setting Backend To: AvailableBackends.numpy\n"
     ]
    }
   ],
   "source": [
    "import pandas as pd\n",
    "import gempy as gp\n",
    "import gempy_viewer as gpv\n",
    "import matplotlib.pyplot as plt"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "jewish-complex",
   "metadata": {},
   "source": [
    "<a id='data-preparation'></a>\n",
    "# Data Preparation\n",
    "\n",
    "For this model, the only thing that needs to be done is loading the already created interface points and orientations. In the next tutorials, you will create the data yourself and process it further to make it usable for GemPy. \n",
    "\n",
    "<a id='importing-interface-points'></a>\n",
    "## Importing Interface Points\n",
    "\n",
    "We are using the `pandas` library ([Pandas](https://pandas.pydata.org/docs/)) to load the interface points that were prepared beforehand and stored as CSV-file (comma-separated-file). The only information that is needed are the location of the interface point (`X`, `Y`, `Z`) and the `formation` it belongs to. You may have to adjust the `delimiter` (`'\\t'`, `','`, `';'`, `' '`) when loading the file."
   ]
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       "     X    Y    Z formation\n",
       "0  200  250 -150    Layer1\n",
       "1  200  500 -150    Layer1\n",
       "2  200  750 -150    Layer1\n",
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    "interfaces = pd.read_csv('../../data/model4/model4_interfaces.csv', \n",
    "                         delimiter = ';')\n",
    "interfaces.head()"
   ]
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  {
   "cell_type": "markdown",
   "id": "occupied-simulation",
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    "<a id='importing-orientations'></a>\n",
    "\n",
    "## Importing Orientations\n",
    "\n",
    "The orientations will also be loaded using `pandas`. In addition to the location and the formation the orientation belongs to, the dip value, azimuth value (dip direction) and a polarity value (mostly set to 1 by default) needs to be provided. As the model will feature folded layers, the dip and the azimuth are variable. Orientations are provided for all four modeled layers. "
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       "     X    Y    Z formation  dip  azimuth  polarity\n",
       "0  200  500 -150    Layer1    0        0         1\n",
       "1  800  500 -150    Layer1    0        0         1\n",
       "2  500  500 -150    Layer1    0        0         1\n",
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    "orientations = pd.read_csv('../../data/model4/model4_orientations.csv', \n",
    "                           delimiter=';')\n",
    "orientations.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "veterinary-acceptance",
   "metadata": {},
   "source": [
    "<a id='gempy-model-calculation'></a>\n",
    "\n",
    "# GemPy Model Calculation\n",
    "\n",
    "The following part presents the main steps of creating a model in `GemPy`. \n",
    "\n",
    "The creation of a `GemPy` Model follows particular steps which will be performed in the following:\n",
    "\n",
    "1. Create new model and data initiation: `gp.create_geomodel()`\n",
    "2. Map Stack to Surfaces: `gp.map_stack_to_surfaces()`\n",
    "3. [...]\n",
    "4. Computing the Model: `gp.compute_model()`\n",
    "\n",
    "<a id='creating-the-gempy-model'></a>\n",
    "\n",
    "## Creating the GemPy Model\n",
    "\n",
    "The first step is to create a new empty `GemPy` model by providing a name for it. \n",
    "\n",
    "In addition, the `extent` of the model (`xmin`, `xmax`, `ymin`, `ymax`, `zmin`, `zmax`) and the `resolution` in `X`, `Y`and `Z` direction (`res_x`, `res_y`, `res_z`, equal to the number of cells in each direction) will be set using lists of values. If you want to provide cells with a certain size, you would have to calculate the following. It is important to convert the resulting number of cells into an `int` as only integer values for the number of cells are valid. \n",
    "\n",
    "```python\n",
    "res_x = int((xmax-xmin)/cell_size_x)\n",
    "res_y = int((ymax-ymin)/cell_size_y)\n",
    "res_z = int((zmax-zmin)/cell_size_z)\n",
    "```\n",
    "\n",
    "The interface points (`surface_points_df`) and orientations (`orientations_df`) will be passed as strings with the location of the CSV files. Please mind that you may have to edit the `pandas_reader_kwargs` by adding the `'sep'` key and the delimiter `';'` as item of a dictionary."
   ]
  },
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   "source": [
    "geo_model: gp.data.GeoModel = gp.create_geomodel(\n",
    "    project_name='Model4_Truncated_Layers',\n",
    "    extent=[0, 1000, 0, 1000, -600, 0], \n",
    "    resolution=[100, 100, 100],  # * 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/model4/model4_orientations.csv',\n",
    "        path_to_surface_points='../../data/model4/model4_interfaces.csv',\n",
    "        pandas_reader_kwargs = {'sep': ';'}\n",
    "    )\n",
    ")"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "armed-story",
   "metadata": {},
   "source": [
    "<a id='inspecting-the-surfaces'></a>\n",
    "\n",
    "## Inspecting the Surfaces\n",
    "\n",
    "The model consists of four different layers or surfaces now which all belong to the `Default series`. During the next step, the proper `Series` will be assigned to the surfaces. Using the `structural_frame`-attribute again, we can check which layers were loaded."
   ]
  },
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   "outputs": [
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       "\n",
       "        <table>\n",
       "          <tr><td>Structural Groups:</td><td>\n",
       "    <table style=\"border-left:1.2px solid black;>\n",
       "      <tr><th colspan=\"2\"><b>StructuralGroup:</b></th></tr>\n",
       "      <tr><td>Name:</td><td>default_formation</td></tr>\n",
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       "          <tr><td>Fault Relations:</td><td><table style=\"border-collapse: collapse; table-layout: fixed;\"><th></th><th style=\"transform: rotate(-35deg); height:150px; vertical-align: bottom; text-align: center;\">default_fo...</th><tr><th>default_formation</th><td style=\"background-color: #FFB6C1; width: 20px; height: 20px; border: 1px solid black;\"></td></tr></table></td></tr>\n",
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       "StructuralFrame(\n",
       "\tstructural_groups=[\n",
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       "\telements=[\n",
       "Element(\n",
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       "[[False]],"
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    "geo_model.structural_frame"
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  {
   "cell_type": "markdown",
   "id": "0d2035c9",
   "metadata": {},
   "source": [
    "<a id='inspecting-the-input-data'></a>\n",
    "\n",
    "## Inspecting the Input Data\n",
    "\n",
    "The loaded interface points and orientations can again be inspected using the `surface_points_copy`- and `orientations_copy`-attributes. Using the `df`-attribute of this object will convert the displayed table in a `pandas` `DataFrame`."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "0f4e2243",
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     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "geo_model.surface_points_copy.df.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "id": "338f3a0e",
   "metadata": {},
   "outputs": [
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     "metadata": {},
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   "source": [
    "geo_model.orientations_copy.df.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "occupational-coaching",
   "metadata": {},
   "source": [
    "<a id='map-stack-to-surfaces'></a>\n",
    "\n",
    "## Map Stack to Surfaces\n",
    "\n",
    "During this step, the layers are assigned their respective `Series`. As `Layer1` and `Layer2` are parallel, they will be defined as one `Series`. However, they are not parallel to `Layer3` and `Layer4` (which are in itself parallel) and will therefore be defined in a separate series. The order within one series also defines the age relations within this series and has to be according to the depositional events of the layers."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "id": "ca6dfa3e",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2022-04-02T13:47:16.123172Z",
     "start_time": "2022-04-02T13:47:15.891195Z"
    }
   },
   "outputs": [
    {
     "data": {
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       "\n",
       "        <table>\n",
       "          <tr><td>Structural Groups:</td><td>\n",
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       "      <tr><td>Name:</td><td>Strata1</td></tr>\n",
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       "      <tr><td>Name:</td><td>Layer4</td></tr>\n",
       "    </table>\n",
       "        </td></tr>\n",
       "    </table>\n",
       "        </td></tr>\n",
       "          <tr><td>Fault Relations:</td><td><table style=\"border-collapse: collapse; table-layout: fixed;\"><th></th><th style=\"transform: rotate(-35deg); height:150px; vertical-align: bottom; text-align: center;\">Strata1</th><th style=\"transform: rotate(-35deg); height:150px; vertical-align: bottom; text-align: center;\">Strata2</th><tr><th>Strata1</th><td style=\"background-color: #FFB6C1; width: 20px; height: 20px; border: 1px solid black;\"></td><td style=\"background-color: #FFB6C1; width: 20px; height: 20px; border: 1px solid black;\"></td></tr><tr><th>Strata2</th><td style=\"background-color: #FFB6C1; width: 20px; height: 20px; border: 1px solid black;\"></td><td style=\"background-color: #FFB6C1; width: 20px; height: 20px; border: 1px solid black;\"></td></tr></table></td></tr>\n",
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       "          <tr>\n",
       "            <td><div style=\"display: inline-block; background-color: #527682; width: 20px; height: 20px; border: 1px solid black;\"></div> True</td>\n",
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       "        "
      ],
      "text/plain": [
       "StructuralFrame(\n",
       "\tstructural_groups=[\n",
       "StructuralGroup(\n",
       "\tname=Strata1,\n",
       "\tstructural_relation=StackRelationType.ERODE,\n",
       "\telements=[\n",
       "Element(\n",
       "\tname=Layer1,\n",
       "\tcolor=\u001b[38;2;1;84;130m#015482\u001b[0m,\n",
       "\tis_active=True\n",
       "),\n",
       "Element(\n",
       "\tname=Layer2,\n",
       "\tcolor=\u001b[38;2;159;0;82m#9f0052\u001b[0m,\n",
       "\tis_active=True\n",
       ")\n",
       "]\n",
       "),\n",
       "StructuralGroup(\n",
       "\tname=Strata2,\n",
       "\tstructural_relation=StackRelationType.ERODE,\n",
       "\telements=[\n",
       "Element(\n",
       "\tname=Layer3,\n",
       "\tcolor=\u001b[38;2;255;190;0m#ffbe00\u001b[0m,\n",
       "\tis_active=True\n",
       "),\n",
       "Element(\n",
       "\tname=Layer4,\n",
       "\tcolor=\u001b[38;2;114;143;2m#728f02\u001b[0m,\n",
       "\tis_active=True\n",
       ")\n",
       "]\n",
       ")\n",
       "],\n",
       "\tfault_relations=\n",
       "[[False, False],\n",
       " [False, False]],"
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "gp.map_stack_to_surfaces(gempy_model=geo_model,\n",
    "                         mapping_object=\n",
    "                         {\n",
    "                          'Strata1': ('Layer1', 'Layer2'),      \n",
    "                          'Strata2': ('Layer3', 'Layer4'),\n",
    "                         },\n",
    "                         remove_unused_series=True)\n",
    "geo_model.structural_frame"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "directed-immigration",
   "metadata": {},
   "source": [
    "<a id='plotting-the-input-data-in-2d'></a>\n",
    "\n",
    "## Plotting the input data in 2D using Matplotlib\n",
    "\n",
    "The input data can now be visualized in 2D using `matplotlib`. This might for example be useful to check if all points and measurements are defined the way we want them to. Using the function `plot_2d()`, we attain a 2D projection of our data points onto a plane of chosen direction (we can choose this attribute to be either `'x'`, `'y'`, or `'z'`)."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "id": "ee36f42b",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2022-04-02T13:47:16.549062Z",
     "start_time": "2022-04-02T13:47:16.127173Z"
    }
   },
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "C:\\Users\\ale93371\\Anaconda3\\envs\\gemgis_12\\Lib\\site-packages\\gempy_viewer\\API\\_plot_2d_API.py:176: UserWarning: FigureCanvasAgg is non-interactive, and thus cannot be shown\n",
      "  p.fig.show()\n"
     ]
    },
    {
     "data": {
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",
      "text/plain": [
       "<Figure size 1040x715 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "gpv.plot_2d(geo_model, \n",
    "           direction='z', \n",
    "           show_lith=False, \n",
    "           show_boundaries=False)\n",
    "plt.grid()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "objective-standard",
   "metadata": {},
   "source": [
    "<a id='plotting-the-input-data-in-3d'></a>\n",
    "\n",
    "## Plotting the input data in 3D using PyVista\n",
    "\n",
    "The input data can also be viszualized using the `pyvista` package. In this view, the interface points are visible as well as the orientations (marked as arrows) which indicate the normals of each orientation value. \n",
    "\n",
    "The `pyvista` package requires the Visualization Toolkit (VTK) to be installed."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "id": "03cfc42d",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2022-04-02T13:47:17.291101Z",
     "start_time": "2022-04-02T13:47:16.552063Z"
    }
   },
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "C:\\Users\\ale93371\\Anaconda3\\envs\\gemgis_12\\Lib\\site-packages\\pyvista\\jupyter\\notebook.py:56: UserWarning: Failed to use notebook backend: \n",
      "\n",
      "cannot import name 'vtk' from 'trame.widgets' (C:\\Users\\ale93371\\Anaconda3\\envs\\gemgis_12\\Lib\\site-packages\\trame\\widgets\\__init__.py)\n",
      "\n",
      "Falling back to a static output.\n",
      "  warnings.warn(\n"
     ]
    },
    {
     "data": {
      "image/jpeg": 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",
      "text/plain": [
       "<PIL.Image.Image image mode=RGB size=1024x768>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/plain": [
       "<gempy_viewer.modules.plot_3d.vista.GemPyToVista at 0x17270f41510>"
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "gpv.plot_3d(geo_model, \n",
    "            image=False, \n",
    "            show_lith=False,\n",
    "            plotter_type='basic',\n",
    "            kwargs_plotter= {'notebook':True},)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "elementary-camping",
   "metadata": {},
   "source": [
    "<a id='setting-the-interpolator'></a>\n",
    "## Setting the interpolator\n",
    "\n",
    "Unlike previous versions, GemPy 3 doesn’t rely on theano or asera. Instead, it utilizes numpy or tensorflow. Consequently, we no longer need to recompile all theano functions (TensorFlow uses eager execution; we found no notable speed difference after profiling the XLA compiler).\n",
    "\n",
    "The parameters used for the interpolation are stored in gempy.core.data.GeoModel.interpolation_options. These parameters have sensible default values that you can modify if necessary. However, we advise caution when changing these parameters unless you fully understand their implications.\n",
    "\n",
    "Display the current interpolation options "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "id": "8e27b70d",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2022-04-02T13:47:21.664940Z",
     "start_time": "2022-04-02T13:47:17.294083Z"
    }
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "InterpolationOptions(kernel_options=KernelOptions(range=1.7, c_o=10.0, uni_degree=1, i_res=4.0, gi_res=2.0, number_dimensions=3, kernel_function=AvailableKernelFunctions.cubic, kernel_solver=Solvers.DEFAULT, compute_condition_number=False, optimizing_condition_number=False, condition_number=None), evaluation_options=EvaluationOptions(_number_octree_levels=1, _number_octree_levels_surface=4, octree_curvature_threshold=-1.0, octree_error_threshold=1.0, octree_min_level=2, mesh_extraction=True, mesh_extraction_masking_options=<MeshExtractionMaskingOptions.INTERSECT: 3>, mesh_extraction_fancy=True, evaluation_chunk_size=500000, compute_scalar_gradient=False, verbose=False), debug=True, cache_mode=<CacheMode.IN_MEMORY_CACHE: 3>, cache_model_name='Model4_Truncated_Layers', block_solutions_type=<BlockSolutionType.DENSE_GRID: 2>, sigmoid_slope=5000000, debug_water_tight=False)"
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "geo_model.interpolation_options"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "innovative-cradle",
   "metadata": {},
   "source": [
    "<a id='computing-the-model'></a>\n",
    "\n",
    "## Computing the model\n",
    "\n",
    "At this point, we have all we need to compute our full model via `gp.compute_model()`. By default, this will return two separate solutions in the form of arrays. The first provides information on the lithological formations, the second on the fault network in the model, which is not present in this example. "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "id": "5b7b2377",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2022-04-02T13:47:37.437247Z",
     "start_time": "2022-04-02T13:47:21.668943Z"
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Setting Backend To: AvailableBackends.numpy\n",
      "Chunking done: 57 chunks\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "C:\\Users\\ale93371\\Anaconda3\\envs\\gemgis_12\\Lib\\site-packages\\gempy_engine\\modules\\activator\\_soft_segment.py:95: RuntimeWarning: overflow encountered in exp\n",
      "  return 1.0 / (1.0 + bt.t.exp(x))\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Chunking done: 51 chunks\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "C:\\Users\\ale93371\\Anaconda3\\envs\\gemgis_12\\Lib\\site-packages\\gempy_engine\\modules\\activator\\_soft_segment.py:95: RuntimeWarning: overflow encountered in exp\n",
      "  return 1.0 / (1.0 + bt.t.exp(x))\n"
     ]
    }
   ],
   "source": [
    "sol = gp.compute_model(geo_model, \n",
    "                       compute_mesh=True)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "protected-parcel",
   "metadata": {},
   "source": [
    "<a id='model-visualization-and-post-processing'></a>\n",
    "\n",
    "# Model Visualization and Post-Processing\n",
    "\n",
    "<a id='visualizing-cross-sections-of-the-computed-model'></a>\n",
    "\n",
    "## Visulazing Cross Sections of the computed model\n",
    "\n",
    "Cross sections in different `direction`s and at different `cell_number`s can be displayed. Here, we see the horizontal layers in the one direction and the truncated layers in the other direction."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "id": "eb54b87a",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2022-04-02T13:47:38.430323Z",
     "start_time": "2022-04-02T13:47:37.439246Z"
    }
   },
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "C:\\Users\\ale93371\\Anaconda3\\envs\\gemgis_12\\Lib\\site-packages\\gempy_viewer\\API\\_plot_2d_API.py:176: UserWarning: FigureCanvasAgg is non-interactive, and thus cannot be shown\n",
      "  p.fig.show()\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "<gempy_viewer.modules.plot_2d.visualization_2d.Plot2D at 0x172716a2f50>"
      ]
     },
     "execution_count": 13,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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      "text/plain": [
       "<Figure size 2496x1716 with 8 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "gpv.plot_2d(geo_model, \n",
    "           direction=['x', 'x', 'y', 'y'], \n",
    "           cell_number=[25, 50, 25, 75], \n",
    "           show_topography=False, \n",
    "           show_data=True)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "18218288",
   "metadata": {},
   "source": [
    "Next to the lithology data, we can also plot the calculated scalar field."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "id": "2f27b9a5",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<gempy_viewer.modules.plot_2d.visualization_2d.Plot2D at 0x172026ee610>"
      ]
     },
     "execution_count": 14,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1040x715 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "gpv.plot_2d(geo_model, direction='y', show_data=False, show_scalar=True, show_lith=False)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "several-artwork",
   "metadata": {},
   "source": [
    "<a id='visualizing-the-computed-model-in-3d'></a>\n",
    "\n",
    "# Visualizing the computed model in 3D\n",
    "\n",
    "The computed model can be visualized in 3D using the `pyvista` library. Setting `kwargs_plotter= {'notebook':True}` will open an interactive windows and the model can be rotated and zooming is possible. "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "id": "838f0e34",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2022-04-02T13:47:39.173131Z",
     "start_time": "2022-04-02T13:47:38.434317Z"
    }
   },
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "C:\\Users\\ale93371\\Anaconda3\\envs\\gemgis_12\\Lib\\site-packages\\gempy_viewer\\modules\\plot_3d\\drawer_surfaces_3d.py:38: PyVistaDeprecationWarning: \n",
      "../../../../Anaconda3/envs/gemgis_12/Lib/site-packages/gempy_viewer/modules/plot_3d/drawer_surfaces_3d.py:38: Argument 'color' must be passed as a keyword argument to function 'BasePlotter.add_mesh'.\n",
      "From version 0.50, passing this as a positional argument will result in a TypeError.\n",
      "  gempy_vista.surface_actors[element.name] = gempy_vista.p.add_mesh(\n",
      "C:\\Users\\ale93371\\Anaconda3\\envs\\gemgis_12\\Lib\\site-packages\\pyvista\\jupyter\\notebook.py:56: UserWarning: Failed to use notebook backend: \n",
      "\n",
      "cannot import name 'vtk' from 'trame.widgets' (C:\\Users\\ale93371\\Anaconda3\\envs\\gemgis_12\\Lib\\site-packages\\trame\\widgets\\__init__.py)\n",
      "\n",
      "Falling back to a static output.\n",
      "  warnings.warn(\n"
     ]
    },
    {
     "data": {
      "image/jpeg": 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",
      "text/plain": [
       "<PIL.Image.Image image mode=RGB size=1024x768>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/plain": [
       "<gempy_viewer.modules.plot_3d.vista.GemPyToVista at 0x1720835c350>"
      ]
     },
     "execution_count": 15,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "gpv.plot_3d(geo_model, \n",
    "                 image=False, \n",
    "                 show_topography=True,\n",
    "                 plotter_type='basic', \n",
    "                 kwargs_plotter= {'notebook':True},\n",
    "                 show_lith=True)"
   ]
  },
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   "cell_type": "markdown",
   "id": "smooth-characterization",
   "metadata": {},
   "source": [
    "<a id='conclusions'></a>\n",
    "# Conclusions\n",
    "\n",
    "This is the last notebook of the `Basic Modeling` module. After completing this module, you should be able to model parallel and non-parallel, folded, faulted, and unconformable layers.\n",
    "\n",
    "<div class=\"alert alert-block alert-success\">\n",
    "<b>In this tutorial, you have learnt the following:</b> <br>\n",
    "- Get an understanding of how unconformities are modeled/displayed in GemPy<br>\n",
    "- How to build a simple model consisting of <b>unconformable layers</b> belonging to <b>multiple Series</b><br>\n",
    "\n",
    "</div>\n",
    "\n",
    "\n",
    "<a id='outlook'></a>\n",
    "# Outlook\n",
    "\n",
    "All following notebooks represent the main part of the `From Maps to Models` tutorial series. There, we also introduce the `GemGIS` library, which will be a huge part of the following notebooks extending your knowledge about spatial data processing and creating input data for the `GemPy` modeling. \n",
    "\n",
    "\n",
    "[Take me to the next notebook on Github](https://nbviewer.org/github/cgre-aachen/gemgis_data/blob/main/notebooks/00_introduction_to_working_with_gemgis.ipynb)\n",
    "\n",
    "[Take me to the next notebook locally](../00_introduction_to_working_with_gemgis.ipynb)\n",
    "\n",
    "<img src=\"../../jose/images/fig1.png\" />\n",
    "\n",
    "<a id='licensing'></a>\n",
    "\n",
    "## Licensing\n",
    "\n",
    "Institute for Computational Geoscience, Geothermics and Reservoir Geophysics, RWTH Aachen University & Fraunhofer IEG, Fraunhofer Research Institution for Energy Infrastructures and Geotechnologies IEG, Authors: Alexander Juestel. For more information contact: alexander.juestel(at)ieg.fraunhofer.de\n",
    "\n",
    "All notebooks are licensed under a Creative Commons Attribution 4.0 International License (CC BY 4.0, http://creativecommons.org/licenses/by/4.0/). References for each displayed map are provided. Most of the maps originate from the books of [Powell (1992)](https://link.springer.com/book/9783540586074) and [Bennison (1990)](https://link.springer.com/book/10.1007/978-1-4615-9630-1). References for maps with unknown origin will gladly be added."
   ]
  }
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