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

.. only:: html

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

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

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

.. _sphx_glr_examples_spectrogram_rayleighgram.py:


.. sectionauthor:: Duncan Macleod <duncan.macleod@ligo.org>
.. currentmodule:: gwpy.timeseries

Plotting a `Spectrogram` of the Rayleigh statistic
##################################################

As described in :ref:`sphx_glr_examples_frequencyseries_rayleigh.py`, the Rayleigh
statistic can be used to study non-Gaussianity in a timeseries.
We can study the time variance of these features by plotting a
time-frequency spectrogram where we calculate the Rayleigh statistic for
each time bin.

.. GENERATED FROM PYTHON SOURCE LINES 34-36

To demonstate this, we can load some data from the LIGO Livingston
interferometer around the time of the GW151226 gravitational wave detection:

.. GENERATED FROM PYTHON SOURCE LINES 36-44

.. code-block:: Python


    from gwpy.timeseries import TimeSeries
    gwdata = TimeSeries.fetch_open_data(
        "L1",
        "Dec 26 2015 03:37",
        "Dec 26 2015 03:47",
    )








.. GENERATED FROM PYTHON SOURCE LINES 45-49

Next, we can calculate a Rayleigh statistic `Spectrogram` using the
:meth:`~gwpy.timeseries.TimeSeries.rayleigh_spectrogram` method of the
`~gwpy.timeseries.TimeSeries` and a 5-second stride with a 2-second FFT and
1-second overlap (50%):

.. GENERATED FROM PYTHON SOURCE LINES 49-51

.. code-block:: Python

    rayleigh = gwdata.rayleigh_spectrogram(5, fftlength=2, overlap=1)








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and can make a plot using the :meth:`~Spectrogram.plot` method

.. GENERATED FROM PYTHON SOURCE LINES 53-60

.. code-block:: Python

    plot = rayleigh.plot(norm="log", vmin=0.25, vmax=4)
    ax = plot.gca()
    ax.set_yscale("log")
    ax.set_ylim(30, 1500)
    ax.set_title("Sensitivity of LIGO-Livingston around GW151226")
    ax.colorbar(cmap="coolwarm", label="Rayleigh statistic")
    plot.show()



.. image-sg:: /examples/spectrogram/images/sphx_glr_rayleighgram_001.png
   :alt: Sensitivity of LIGO-Livingston around GW151226
   :srcset: /examples/spectrogram/images/sphx_glr_rayleighgram_001.png
   :class: sphx-glr-single-img






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

   **Total running time of the script:** (0 minutes 2.082 seconds)


.. _sphx_glr_download_examples_spectrogram_rayleighgram.py:

.. only:: html

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

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

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

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

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

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

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


.. only:: html

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

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