.. DO NOT EDIT.
.. THIS FILE WAS AUTOMATICALLY GENERATED BY SPHINX-GALLERY.
.. TO MAKE CHANGES, EDIT THE SOURCE PYTHON FILE:
.. "auto_gallery/plot_spotter.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_spotter.py>`
        to download the full example code.

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

.. _sphx_glr_auto_gallery_plot_spotter.py:


Using Spotter buoy data
=======================

In this example we demostrate how to use `ewdm` package to compute directional wave spectrum from Spotter buoy data. In particular, we use the `displacement.csv` file that is generated after running the parsing script provided by SOFAR. This file containes time series of surface elevation and wave displacements.

We also show that for datasets with more than one hour of data, the wave spectra are computed over blocks of 30 minutes (by default).

.. GENERATED FROM PYTHON SOURCE LINES 13-40



.. image-sg:: /auto_gallery/images/sphx_glr_plot_spotter_001.png
   :alt: 2020-08-20 09:00:00, 2020-08-20 10:00:00, 2020-08-20 11:00:00, 2020-08-20 12:00:00, 2020-08-20 13:00:00, 2020-08-20 14:00:00
   :srcset: /auto_gallery/images/sphx_glr_plot_spotter_001.png
   :class: sphx-glr-single-img


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

 .. code-block:: none


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|

.. code-block:: Python


    import numpy as np
    import xarray as xr

    from matplotlib import pyplot as plt

    import ewdm
    from ewdm.sources import SpotterBuoysDataSource
    from ewdm.plots import plot_directional_spectrum

    spotter = SpotterBuoysDataSource("../../data/displacement.csv")
    dataset = spotter.read_dataset()
    spec = ewdm.Triplets(dataset)
    output = spec.compute(
        omin=-5, omax=0, nvoice=16, dd=5, kappa=36,
        block_size="60min", use="displacements"
    )

    fig, axs = plt.subplots(2, 3, figsize=(9,6), layout="tight")
    axs = axs.ravel()
    for ax, tt in zip(axs, output.time):
        plot_directional_spectrum(
            output.sel(time=tt).directional_distribution,
            ax=ax, vmin=0.003, vmax=0.015, levels=None, colorbar=False,
            axes_kw={"rmax": 0.6, "as_period": True}
        )
        ax.set_title(tt.dt.strftime("%Y-%m-%d %H:%M:%S").item())


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

   **Total running time of the script:** (0 minutes 5.110 seconds)


.. _sphx_glr_download_auto_gallery_plot_spotter.py:

.. only:: html

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

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

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

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

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

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

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


.. only:: html

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

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