.. DO NOT EDIT.
.. THIS FILE WAS AUTOMATICALLY GENERATED BY SPHINX-GALLERY.
.. TO MAKE CHANGES, EDIT THE SOURCE PYTHON FILE:
.. "examples/06_exact_values_example_1D.py"
.. LINE NUMBERS ARE GIVEN BELOW.

.. only:: html

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

        :ref:`Go to the end <sphx_glr_download_examples_06_exact_values_example_1D.py>`
        to download the full example code.

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

.. _sphx_glr_examples_06_exact_values_example_1D.py:


Exact Values
============

PyKrige demonstration and usage
as a non-exact interpolator in 1D.

.. GENERATED FROM PYTHON SOURCE LINES 9-61



.. image-sg:: /examples/images/sphx_glr_06_exact_values_example_1D_001.png
   :alt: 06 exact values example 1D
   :srcset: /examples/images/sphx_glr_06_exact_values_example_1D_001.png
   :class: sphx-glr-single-img





.. code-block:: Python


    import matplotlib.pyplot as plt
    import numpy as np

    from pykrige.ok import OrdinaryKriging

    plt.style.use("ggplot")

    np.random.seed(42)

    x = np.linspace(0, 12.5, 50)
    xpred = np.linspace(0, 12.5, 393)
    y = np.sin(x) * np.exp(-0.25 * x) + np.random.normal(-0.25, 0.25, 50)

    # compare OrdinaryKriging as an exact and non exact interpolator
    uk = OrdinaryKriging(
        x, np.zeros(x.shape), y, variogram_model="linear", exact_values=False
    )
    uk_exact = OrdinaryKriging(x, np.zeros(x.shape), y, variogram_model="linear")

    y_pred, y_std = uk.execute("grid", xpred, np.array([0.0]), backend="loop")
    y_pred_exact, y_std_exact = uk_exact.execute(
        "grid", xpred, np.array([0.0]), backend="loop"
    )


    y_pred = np.squeeze(y_pred)
    y_std = np.squeeze(y_std)

    y_pred_exact = np.squeeze(y_pred_exact)
    y_std_exact = np.squeeze(y_std_exact)


    fig, ax = plt.subplots(1, 1, figsize=(10, 4))

    ax.scatter(x, y, label="Input Data")
    ax.plot(xpred, y_pred_exact, label="Exact Prediction")
    ax.plot(xpred, y_pred, label="Non Exact Prediction")

    ax.fill_between(
        xpred,
        y_pred - 3 * y_std,
        y_pred + 3 * y_std,
        alpha=0.3,
        label="Confidence interval",
    )
    ax.legend(loc=9)
    ax.set_ylim(-1.8, 1.3)
    ax.legend(loc=9)
    plt.xlabel("X")
    plt.ylabel("Field")
    plt.show()


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

   **Total running time of the script:** (0 minutes 0.076 seconds)


.. _sphx_glr_download_examples_06_exact_values_example_1D.py:

.. only:: html

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

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

      :download:`Download Jupyter notebook: 06_exact_values_example_1D.ipynb <06_exact_values_example_1D.ipynb>`

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

      :download:`Download Python source code: 06_exact_values_example_1D.py <06_exact_values_example_1D.py>`

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

      :download:`Download zipped: 06_exact_values_example_1D.zip <06_exact_values_example_1D.zip>`


.. only:: html

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

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