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

.. only:: html

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

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

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

.. _sphx_glr_auto_examples_decomposition_workflows_plot_hdmr_custom_weights.py:


HDMR with Custom Weights
========================

Run HDMR with user-defined weight vectors and inspect how the chosen weights
affect the reconstruction.

.. GENERATED FROM PYTHON SOURCE LINES 8-78



.. image-sg:: /auto_examples/decomposition_workflows/images/sphx_glr_plot_hdmr_custom_weights_001.png
   :alt: Custom weight vectors, Row slice comparison (row=16), Mean absolute error by column
   :srcset: /auto_examples/decomposition_workflows/images/sphx_glr_plot_hdmr_custom_weights_001.png
   :class: sphx-glr-single-img


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

 .. code-block:: none

    Weight shapes: (32, 1) (32, 1)
    Available component keys: ['g_0', 'g_1', 'g_2', 'g_1,2']
    Mean absolute error: 1.1011428314305904e-20






|

.. code-block:: Python


    import matplotlib.pyplot as plt
    import numpy as np

    from hdmrlib import HDMR


    x = np.linspace(0.0, 1.0, 32)
    y = np.linspace(0.0, 1.0, 32)

    X = (
        0.5
        + np.sin(np.pi * x)[:, None]
        + np.cos(np.pi * y)[None, :]
        + 0.25 * np.outer(x, y)
    )

    weight_x = np.linspace(1.0, 2.0, 32).reshape(-1, 1)
    weight_y = np.linspace(2.0, 1.0, 32).reshape(-1, 1)

    weight_x = weight_x / weight_x.sum()
    weight_y = weight_y / weight_y.sum()

    hdmr = HDMR(
        X,
        order=2,
        weight="custom",
        custom_weights=[weight_x, weight_y],
        supports="ones",
    )

    X_reconstructed = np.asarray(hdmr.reconstruct(), dtype=np.float64)
    abs_error = np.abs(X - X_reconstructed)

    mae_by_col = np.mean(abs_error, axis=0)
    mae_total = float(np.mean(abs_error))

    mid_row = X.shape[0] // 2

    print("Weight shapes:", weight_x.shape, weight_y.shape)
    print("Available component keys:", list(hdmr.components().keys()))
    print("Mean absolute error:", mae_total)

    fig, axes = plt.subplots(1, 3, figsize=(12, 4), constrained_layout=True)

    # Panel 1: custom weights
    axes[0].plot(np.arange(weight_x.shape[0]), weight_x[:, 0], marker="o", label="weight_x")
    axes[0].plot(np.arange(weight_y.shape[0]), weight_y[:, 0], marker="s", label="weight_y")
    axes[0].set_title("Custom weight vectors")
    axes[0].set_xlabel("Index")
    axes[0].set_ylabel("Normalized weight")
    axes[0].grid(True, alpha=0.3)
    axes[0].legend()

    # Panel 2: one representative slice
    axes[1].plot(X[mid_row, :], marker="o", label="Original slice")
    axes[1].plot(X_reconstructed[mid_row, :], marker="s", label="Reconstructed slice")
    axes[1].set_title(f"Row slice comparison (row={mid_row})")
    axes[1].set_xlabel("Column index")
    axes[1].set_ylabel("Value")
    axes[1].grid(True, alpha=0.3)
    axes[1].legend()

    # Panel 3: error summary
    axes[2].plot(mae_by_col, marker="o")
    axes[2].set_title("Mean absolute error by column")
    axes[2].set_xlabel("Column index")
    axes[2].set_ylabel("Mean absolute error")
    axes[2].grid(True, alpha=0.3)

    plt.show()

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

   **Total running time of the script:** (0 minutes 0.307 seconds)


.. _sphx_glr_download_auto_examples_decomposition_workflows_plot_hdmr_custom_weights.py:

.. only:: html

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

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

      :download:`Download Jupyter notebook: plot_hdmr_custom_weights.ipynb <plot_hdmr_custom_weights.ipynb>`

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

      :download:`Download Python source code: plot_hdmr_custom_weights.py <plot_hdmr_custom_weights.py>`

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

      :download:`Download zipped: plot_hdmr_custom_weights.zip <plot_hdmr_custom_weights.zip>`


.. only:: html

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

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