.. DO NOT EDIT.
.. THIS FILE WAS AUTOMATICALLY GENERATED BY SPHINX-GALLERY.
.. TO MAKE CHANGES, EDIT THE SOURCE PYTHON FILE:
.. "examples_probabilistic/03_error_propagation_dips.py"
.. LINE NUMBERS ARE GIVEN BELOW.

.. only:: html

    .. note::
        :class: sphx-glr-download-link-note

        :ref:`Go to the end <sphx_glr_download_examples_probabilistic_03_error_propagation_dips.py>`
        to download the full example code.

.. rst-class:: sphx-glr-example-title

.. _sphx_glr_examples_probabilistic_03_error_propagation_dips.py:


Error Propagation for Dip Angles
==================================

This example demonstrates uncertainty quantification by varying dip angles.
We add uncertainty to orientation dips and propagate it through the geological model.

.. GENERATED FROM PYTHON SOURCE LINES 10-12

Import Libraries
----------------

.. GENERATED FROM PYTHON SOURCE LINES 12-34

.. code-block:: Python


    import numpy as np
    import gempy as gp
    import gempy_viewer as gpv
    import gempy_probability as gpp

    import torch
    import pyro
    import pyro.distributions as dist
    from pyro.distributions import Distribution

    import arviz as az
    from gempy_engine.core.backend_tensor import BackendTensor
    from gempy_engine.core.data.interpolation_input import InterpolationInput
    from gempy_probability.modules.plot.plot_gempy import plot_gempy

    # Set random seeds for reproducibility
    seed = 4003
    pyro.set_rng_seed(seed)
    torch.manual_seed(seed)
    np.random.seed(1234)








.. GENERATED FROM PYTHON SOURCE LINES 35-36

Import paths and helper functions

.. GENERATED FROM PYTHON SOURCE LINES 36-39

.. code-block:: Python

    from mineye.config import paths
    from mineye.GeoModel.model_one.probabilistic_model import create_orientation_modifier








.. GENERATED FROM PYTHON SOURCE LINES 40-42

Define Model Extent and Resolution
-----------------------------------

.. GENERATED FROM PYTHON SOURCE LINES 42-55

.. code-block:: Python


    min_x = -707521
    max_x = -675558
    min_y = 4526832
    max_y = 4551949
    max_z = 505
    model_depth = -500
    extent = [min_x, max_x, min_y, max_y, model_depth, max_z]

    # Model resolution: use octree with refinement level 5
    resolution = None
    refinement = 5








.. GENERATED FROM PYTHON SOURCE LINES 56-58

Get Data Paths
--------------

.. GENERATED FROM PYTHON SOURCE LINES 58-65

.. code-block:: Python


    mod_or_path = paths.get_orientations_path()
    mod_pts_path = paths.get_points_path()

    print(f"Orientations: {mod_or_path}")
    print(f"Points: {mod_pts_path}")





.. rst-class:: sphx-glr-script-out

 .. code-block:: none

    Orientations: /home/leguark/PycharmProjects/Mineye-Terranigma/examples/Data/Model_Input_Data/Simple-Models/orientations_mod.csv
    Points: /home/leguark/PycharmProjects/Mineye-Terranigma/examples/Data/Model_Input_Data/Simple-Models/points_mod.csv




.. GENERATED FROM PYTHON SOURCE LINES 66-68

Create GemPy Geological Model
------------------------------

.. GENERATED FROM PYTHON SOURCE LINES 68-80

.. code-block:: Python


    geo_model = gp.create_geomodel(
        project_name='dip_error_propagation',
        extent=extent,
        refinement=refinement,
        resolution=resolution,
        importer_helper=gp.data.ImporterHelper(
            path_to_orientations=mod_or_path,
            path_to_surface_points=mod_pts_path,
        )
    )








.. GENERATED FROM PYTHON SOURCE LINES 81-83

Map Geological Units
--------------------

.. GENERATED FROM PYTHON SOURCE LINES 83-91

.. code-block:: Python


    gp.map_stack_to_surfaces(
        gempy_model=geo_model,
        mapping_object={
                "Tournaisian_Plutonites": ["Tournaisian Plutonites"],
        }
    )






.. raw:: html

    <div class="output_subarea output_html rendered_html output_result">

            <table>
              <tr><td>Structural Groups:</td><td>
        <table style="border-left:1.2px solid black;>
          <tr><th colspan="2"><b>StructuralGroup:</b></th></tr>
          <tr><td>Name:</td><td>Tournaisian_Plutonites</td></tr>
          <tr><td>Structural Relation:</td><td>StackRelationType.ERODE</td></tr>
          <tr><td>Elements:</td><td>
        <table width="50%" style="border-left:15px solid #015482;">
          <tr><th colspan="2"><b>StructuralElement:</b></th></tr>
          <tr><td>Name:</td><td>Tournaisian Plutonites</td></tr>
        </table>
            </td></tr>
        </table>
            </td></tr>
              <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;">Tournaisia...</th><tr><th>Tournaisian_Plutonites</th><td style="background-color: #FFB6C1; width: 20px; height: 20px; border: 1px solid black;"></td></tr></table></td></tr>
              <tr><td></td><td>
            <table>
              <tr>
                <td><div style="display: inline-block; background-color: #527682; width: 20px; height: 20px; border: 1px solid black;"></div> True</td>
                <td><div style="display: inline-block; background-color: #FFB6C1; width: 20px; height: 20px; border: 1px solid black;"></div> False</td>
              </tr>
            </table>
            </td></tr>
            </table>
        
    </div>
    <br />
    <br />

.. GENERATED FROM PYTHON SOURCE LINES 92-94

Switch to PyTorch Backend
--------------------------

.. GENERATED FROM PYTHON SOURCE LINES 94-98

.. code-block:: Python


    BackendTensor.change_backend_gempy(engine_backend=gp.data.AvailableBackends.PYTORCH)
    print("✓ Switched to PyTorch backend")





.. rst-class:: sphx-glr-script-out

 .. code-block:: none

    Setting Backend To: AvailableBackends.PYTORCH
    ✓ Switched to PyTorch backend




.. GENERATED FROM PYTHON SOURCE LINES 99-117

Define Prior Distribution for Dips
-----------------------------------

**Prior Predictive Sampling vs. Posterior Sampling**

* **Prior Predictive Sampling**: Generating data from the model using parameters drawn
  from the prior distribution. It answers: "What kind of models/data do our initial
  beliefs produce?" It's a way to check if the model and priors are reasonable before
  considering observations.

* **Posterior Sampling**: Generating parameters that are consistent with both our
  initial beliefs (priors) AND the observed data. It answers: "What parameters are
  most likely given the data we've seen?"

In this example, we focus on **Prior Predictive Sampling** to see how uncertainty
in orientation dip angles propagates to the final structural geometry.

We'll add uncertainty to all orientation dip angles.

.. GENERATED FROM PYTHON SOURCE LINES 117-140

.. code-block:: Python


    from mineye.config.example_parameters import TharsisModelConfig
    FORMATION_COLORS = TharsisModelConfig.TharsisDataProcessingConfig.FORMATION_COLORS

    n_orientations = geo_model.orientations_copy.xyz.shape[0]
    print(f"Number of orientations: {n_orientations}")

    # Set prior: mean dip of 10° with standard deviation of 10°
    mean_orientations = torch.ones(n_orientations) * 10.0
    std_orientations = 10.0

    model_priors = {
            r'dips': dist.Normal(
                loc=mean_orientations,
                scale=torch.tensor(std_orientations, dtype=torch.float64),
                validate_args=True
            )
    }

    print(f"\nPrior distribution:")
    print(f"  Mean dip: {mean_orientations[0]:.1f}°")
    print(f"  Std: {std_orientations:.1f}°")





.. rst-class:: sphx-glr-script-out

 .. code-block:: none

    Number of orientations: 2

    Prior distribution:
      Mean dip: 10.0°
      Std: 10.0°




.. GENERATED FROM PYTHON SOURCE LINES 141-143

Create Probabilistic Model
---------------------------

.. GENERATED FROM PYTHON SOURCE LINES 143-153

.. code-block:: Python


    prob_model: gpp.GemPyPyroModel = gpp.make_gempy_pyro_model(
        priors=model_priors,
        set_interp_input_fn=create_orientation_modifier(key=r'dips'),
        likelihood_fn=None,
        obs_name=None
    )

    print("✓ Probabilistic model created")





.. rst-class:: sphx-glr-script-out

 .. code-block:: none

    Setting Backend To: AvailableBackends.PYTORCH
    ✓ Probabilistic model created




.. GENERATED FROM PYTHON SOURCE LINES 154-156

Run Prior Predictive Sampling
------------------------------

.. GENERATED FROM PYTHON SOURCE LINES 156-171

.. code-block:: Python


    n_samples = 50
    print(f"\nRunning {n_samples} prior predictive samples...")

    prior_inference_data: az.InferenceData = gpp.run_predictive(
        prob_model=prob_model,
        geo_model=geo_model,
        y_obs_list=[],
        n_samples=n_samples,
        plot_trace=True
    )

    print("✓ Prior predictive sampling complete")





.. image-sg:: /examples_probabilistic/images/sphx_glr_03_error_propagation_dips_001.png
   :alt: dips, dips
   :srcset: /examples_probabilistic/images/sphx_glr_03_error_propagation_dips_001.png
   :class: sphx-glr-single-img


.. rst-class:: sphx-glr-script-out

 .. code-block:: none


    Running 50 prior predictive samples...
    Using sequential processing for 1 surfaces
    Using sequential processing for 1 surfaces
    Using sequential processing for 1 surfaces
    Using sequential processing for 1 surfaces
    Using sequential processing for 1 surfaces
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    Using sequential processing for 1 surfaces
    Using sequential processing for 1 surfaces
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    Using sequential processing for 1 surfaces
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    Using sequential processing for 1 surfaces
    Using sequential processing for 1 surfaces
    Using sequential processing for 1 surfaces
    Using sequential processing for 1 surfaces
    Using sequential processing for 1 surfaces
    Using sequential processing for 1 surfaces
    ✓ Prior predictive sampling complete




.. GENERATED FROM PYTHON SOURCE LINES 172-174

Visualize Uncertainty
---------------------

.. GENERATED FROM PYTHON SOURCE LINES 174-207

.. code-block:: Python


    def update_model_for_plotting(geo_model: gp.data.GeoModel, sample_value: float, sample_idx: int):
        """Update model with a sampled dip value."""
        gp.modify_orientations(
            geo_model=geo_model,
            dip=sample_value,
        )


    # Create base plot
    p2d = gpv.plot_2d(
        model=geo_model,
        show_topography=False,
        legend=False,
        show_lith=False,
        show_data=False,
        show=False,
        ve=5
    )

    # Overlay sampled models
    plot_gempy(
        geo_model=geo_model,
        n_samples=20,
        samples=(prior_inference_data.prior[r'dips'].values[0, :]),
        update_model_fn=update_model_for_plotting,
        gempy_plot=p2d,
        contour_colors=[FORMATION_COLORS['Tournaisian Plutonites']]
    )
    # sphinx_gallery_thumbnail_number = 2

    print("✓ Visualization complete")




.. image-sg:: /examples_probabilistic/images/sphx_glr_03_error_propagation_dips_002.png
   :alt: Cell Number: mid Direction: y
   :srcset: /examples_probabilistic/images/sphx_glr_03_error_propagation_dips_002.png
   :class: sphx-glr-single-img


.. rst-class:: sphx-glr-script-out

 .. code-block:: none

    Setting Backend To: AvailableBackends.PYTORCH
    Using sequential processing for 1 surfaces
    /home/leguark/PycharmProjects/gempy_viewer/gempy_viewer/modules/plot_2d/drawer_contours_2d.py:38: UserWarning: The following kwargs were not used by contour: 'linewidth', 'contour_colors'
      contour_set = ax.contour(
    Setting Backend To: AvailableBackends.PYTORCH
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    Using sequential processing for 1 surfaces
    Setting Backend To: AvailableBackends.PYTORCH
    Using sequential processing for 1 surfaces
    ✓ Visualization complete




.. GENERATED FROM PYTHON SOURCE LINES 208-210

Summary Statistics
------------------

.. GENERATED FROM PYTHON SOURCE LINES 210-219

.. code-block:: Python


    samples = prior_inference_data.prior[r'dips'].values[0, :]
    print(f"\nSampled dip angle statistics:")
    print(f"  Mean: {samples.mean():.2f}°")
    print(f"  Std: {samples.std():.2f}°")
    print(f"  Min: {samples.min():.2f}°")
    print(f"  Max: {samples.max():.2f}°")
    print(f"  Target mean: {mean_orientations[0]:.2f}°")
    print(f"  Target std: {std_orientations:.2f}°")




.. rst-class:: sphx-glr-script-out

 .. code-block:: none


    Sampled dip angle statistics:
      Mean: 11.42°
      Std: 9.28°
      Min: -11.49°
      Max: 30.64°
      Target mean: 10.00°
      Target std: 10.00°





.. rst-class:: sphx-glr-timing

   **Total running time of the script:** (0 minutes 43.492 seconds)


.. _sphx_glr_download_examples_probabilistic_03_error_propagation_dips.py:

.. only:: html

  .. container:: sphx-glr-footer sphx-glr-footer-example

    .. container:: sphx-glr-download sphx-glr-download-jupyter

      :download:`Download Jupyter notebook: 03_error_propagation_dips.ipynb <03_error_propagation_dips.ipynb>`

    .. container:: sphx-glr-download sphx-glr-download-python

      :download:`Download Python source code: 03_error_propagation_dips.py <03_error_propagation_dips.py>`

    .. container:: sphx-glr-download sphx-glr-download-zip

      :download:`Download zipped: 03_error_propagation_dips.zip <03_error_propagation_dips.zip>`


.. only:: html

 .. rst-class:: sphx-glr-signature

    `Gallery generated by Sphinx-Gallery <https://sphinx-gallery.github.io>`_