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

.. only:: html

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

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

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

.. _sphx_glr_auto_gallery_plot_example_arrays.py:


Donelan `run82` test case
=========================

This example shows `ewdm.Arrays` in action. We use the run82 as test case. More
information about this test case can be found in Donelan et al. 2015

.. GENERATED FROM PYTHON SOURCE LINES 12-42

.. code-block:: Python


    import numpy as np
    import xarray as xr

    from scipy.io import loadmat
    from matplotlib import pyplot as plt

    import ewdm
    from ewdm.plots import plot_directional_spectrum

    # loading matlab file
    mat_fname = "../../data/donelan_run82.mat"
    mat_data = loadmat(mat_fname, simplify_cells=True)

    sampling_rate = mat_data["fs"]
    time = np.arange(len(mat_data["eta"])) / sampling_rate
    elements = np.arange(len(mat_data["x"]))

    # creating dataset
    dataset = xr.Dataset(
        data_vars = {
            "surface_elevation": (["time", "element"], mat_data["eta"]),
            "position_x": ("element", mat_data["x"]),
            "position_y": ("element", mat_data["y"])
        },
        coords = {"time": time, "element": elements},
        attrs = {"sampling_rate": sampling_rate}
    )
    print(dataset)





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

 .. code-block:: none

    <xarray.Dataset> Size: 230kB
    Dimensions:            (time: 4096, element: 6)
    Coordinates:
      * time               (time) float64 33kB 0.0 0.25 0.5 ... 1.024e+03 1.024e+03
      * element            (element) int64 48B 0 1 2 3 4 5
    Data variables:
        surface_elevation  (time, element) float64 197kB 0.02559 0.03397 ... 0.08992
        position_x         (element) float64 48B 0.0 0.2097 ... -0.08959 0.1943
        position_y         (element) float64 48B 0.0 0.1362 ... -0.2334 -0.1573
    Attributes:
        sampling_rate:  4




.. GENERATED FROM PYTHON SOURCE LINES 43-44

Let's first have a look at the array configuration

.. GENERATED FROM PYTHON SOURCE LINES 44-57

.. code-block:: Python

    fig, ax = plt.subplots()
    ax.scatter(dataset["position_x"], dataset["position_y"], s=500, c="k")
    for element in dataset["element"]:
        ax.text(
            dataset["position_x"].sel(element=element).item(),
            dataset["position_y"].sel(element=element).item(),
            element.item(), ha="center", va="center", color="w"
        )
    ax.set_aspect('equal', adjustable='box')
    ax.set(title="Array geometry", xlabel="x [m]", ylabel="y [m]")
    print(f"Number of elements in the array: {len(dataset['element'])}")





.. image-sg:: /auto_gallery/images/sphx_glr_plot_example_arrays_001.png
   :alt: Array geometry
   :srcset: /auto_gallery/images/sphx_glr_plot_example_arrays_001.png
   :class: sphx-glr-single-img


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

 .. code-block:: none

    Number of elements in the array: 6




.. GENERATED FROM PYTHON SOURCE LINES 58-59

Let's compute the directional spectrum

.. GENERATED FROM PYTHON SOURCE LINES 59-65

.. code-block:: Python

    spec = ewdm.Arrays(dataset)
    output = spec.compute(
        cross_wavelet=True, solver="least-squares", kappa=36
    )
    print(output)





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

 .. code-block:: none

    <xarray.Dataset> Size: 114kB
    Dimensions:                   (frequency: 97, direction: 72)
    Coordinates:
      * frequency                 (frequency) float64 776B 0.03125 0.03263 ... 2.0
      * direction                 (direction) float64 576B -180.0 -175.0 ... 175.0
    Data variables:
        directional_spectrum      (frequency, direction) float64 56kB 1.565e-06 ....
        directional_distribution  (frequency, direction) float64 56kB 0.004159 .....
        frequency_spectrum        (frequency) float64 776B 0.0003762 ... 3.766e-05




.. GENERATED FROM PYTHON SOURCE LINES 66-70

Now let's plot the output. Here we can tune up the `plot_directional_spectrum`
function. For example, let's start radius ticks from 0.1 to 1.2 Hz every 0.2
Hz. Also, let's rotate them 135 degrees (northwest). Finally, let's add a
colorbar label.

.. GENERATED FROM PYTHON SOURCE LINES 70-79

.. code-block:: Python


    fig, ax = plt.subplots(figsize=(6,5))
    plot_directional_spectrum(
        output.directional_spectrum, ax=ax, levels=None, colorbar=True,
        axes_kw={"rmin": 0.1, "rmax": 1.2, "rstep": 0.2, "angle": 135},
        cbar_kw={"label": "$E(f,\\theta)$"}
    )





.. image-sg:: /auto_gallery/images/sphx_glr_plot_example_arrays_002.png
   :alt: plot example arrays
   :srcset: /auto_gallery/images/sphx_glr_plot_example_arrays_002.png
   :class: sphx-glr-single-img






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

   **Total running time of the script:** (0 minutes 0.760 seconds)


.. _sphx_glr_download_auto_gallery_plot_example_arrays.py:

.. only:: html

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

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

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

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

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

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

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


.. only:: html

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

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