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

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

.. _sphx_glr_examples_spectrogram_ratio.py:


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

Plotting a normalised `~gwpy.spectrogram.Spectrogram`
#####################################################

The :ref:`sphx_glr_examples_spectrogram_plot.py` example showed how to
generate and display a `~gwpy.spectrogram.Spectrogram` of the LIGO-Hanford
strain data around the |GW150914|_ event.

However, because of the shape of the LIGO sensitivity curve, picking out
features in the most sensitive frequency band (a few hundred Hertz) is
very hard.

We can normalise our `~gwpy.spectrogram.Spectrogram` to highligh those
features.

.. GENERATED FROM PYTHON SOURCE LINES 39-42

Again, we import the `TimeSeries` and call
:meth:`TimeSeries.fetch_open_data` the download the strain
data for the LIGO-Hanford interferometer

.. GENERATED FROM PYTHON SOURCE LINES 42-49

.. code-block:: Python

    from gwpy.timeseries import TimeSeries
    data = TimeSeries.fetch_open_data(
        "H1",
        "Sep 14 2015 09:45",
        "Sep 14 2015 09:55",
    )








.. GENERATED FROM PYTHON SOURCE LINES 50-53

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

.. GENERATED FROM PYTHON SOURCE LINES 53-55

.. code-block:: Python

    specgram = data.spectrogram(2, fftlength=1, overlap=.5) ** (1/2.)








.. GENERATED FROM PYTHON SOURCE LINES 56-58

and can normalise it against the overall median ASD by calling the
:meth:`~gwpy.spectrogram.Spectrogram.ratio` method:

.. GENERATED FROM PYTHON SOURCE LINES 58-61

.. code-block:: Python


    normalised = specgram.ratio("median")








.. GENERATED FROM PYTHON SOURCE LINES 62-64

Finally, we can make a plot using the
:meth:`~gwpy.spectrogram.Spectrogram.plot` method

.. GENERATED FROM PYTHON SOURCE LINES 64-71

.. code-block:: Python

    plot = normalised.plot(norm="log", vmin=.1, vmax=10, cmap="Spectral_r")
    ax = plot.gca()
    ax.set_yscale("log")
    ax.set_ylim(10, 2000)
    ax.colorbar(label="Relative amplitude")
    plot.show()




.. image-sg:: /examples/spectrogram/images/sphx_glr_ratio_001.png
   :alt: ratio
   :srcset: /examples/spectrogram/images/sphx_glr_ratio_001.png
   :class: sphx-glr-single-img





.. GENERATED FROM PYTHON SOURCE LINES 72-77

Even with a normalised spectrogram, the resolution is such that a signal
as short as that of GW150914 is impossible to see.
See :ref:`sphx_glr_examples_spectrogram_spectrogram2.py` for an example that
uses a high-resolution spectrogram method to zoom in around the exact time of
the signal.


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

   **Total running time of the script:** (0 minutes 1.752 seconds)


.. _sphx_glr_download_examples_spectrogram_ratio.py:

.. only:: html

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

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

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

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

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

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

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


.. only:: html

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

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