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.. _sphx_glr_examples_05_kriging_02_pykrige_interface.py:


Interface to PyKrige
--------------------

To use fancier methods like
`regression kriging <https://en.wikipedia.org/wiki/Regression-kriging>`__,
we provide an interface to
`PyKrige <https://github.com/GeoStat-Framework/PyKrige>`__ (>v1.5), which means
you can pass a GSTools covariance model to the kriging routines of PyKrige.

To demonstrate the general workflow, we compare ordinary kriging of PyKrige
with the corresponding GSTools routine in 2D:

.. GENERATED FROM PYTHON SOURCE LINES 14-30

.. code-block:: Python


    import numpy as np
    from matplotlib import pyplot as plt
    from pykrige.ok import OrdinaryKriging

    import gstools as gs

    # conditioning data
    cond_x = [0.3, 1.9, 1.1, 3.3, 4.7]
    cond_y = [1.2, 0.6, 3.2, 4.4, 3.8]
    cond_val = [0.47, 0.56, 0.74, 1.47, 1.74]

    # grid definition for output field
    gridx = np.arange(0.0, 5.5, 0.1)
    gridy = np.arange(0.0, 6.5, 0.1)








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A GSTools based :any:`Gaussian` covariance model:

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.. code-block:: Python


    model = gs.Gaussian(
        dim=2, len_scale=1, anis=0.2, angles=-0.5, var=0.5, nugget=0.1
    )








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Ordinary Kriging with PyKrige
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^

One can pass the defined GSTools model as
variogram model, which will `not` be fitted to the given data.
By providing the GSTools model, rotation and anisotropy are also
automatically defined:

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.. code-block:: Python


    OK1 = OrdinaryKriging(cond_x, cond_y, cond_val, variogram_model=model)
    z1, ss1 = OK1.execute("grid", gridx, gridy)
    plt.imshow(z1, origin="lower")
    plt.show()




.. image-sg:: /examples/05_kriging/images/sphx_glr_02_pykrige_interface_001.png
   :alt: 02 pykrige interface
   :srcset: /examples/05_kriging/images/sphx_glr_02_pykrige_interface_001.png
   :class: sphx-glr-single-img





.. GENERATED FROM PYTHON SOURCE LINES 52-60

Ordinary Kriging with GSTools
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^

The :any:`Ordinary` kriging class is provided by GSTools as a shortcut to
define ordinary kriging with the general :any:`Krige` class.

PyKrige's routines are using exact kriging by default (when given a nugget).
To reproduce this behavior in GSTools, we have to set ``exact=True``.

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.. code-block:: Python


    OK2 = gs.krige.Ordinary(model, [cond_x, cond_y], cond_val, exact=True)
    OK2.structured([gridx, gridy])
    ax = OK2.plot()
    ax.set_aspect("equal")



.. image-sg:: /examples/05_kriging/images/sphx_glr_02_pykrige_interface_002.png
   :alt: Field 2D structured: (55, 65)
   :srcset: /examples/05_kriging/images/sphx_glr_02_pykrige_interface_002.png
   :class: sphx-glr-single-img






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