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

.. only:: html

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

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

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

.. _sphx_glr_examples_table_rate.py:


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

Calculating (and plotting) rate versus time for an `EventTable`
###############################################################

I would like to study the rate at which event triggers are generated by the
`ExcessPower` gravitational-wave burst detection algorithm, over a small
stretch of data.

The data from which these events were generated contain a simulated
gravitational-wave signal, or hardware injection, used to validate
the performance of the LIGO detectors and downstream data analysis procedures.

.. GENERATED FROM PYTHON SOURCE LINES 36-39

First, we import the `EventTable` object and read in a set of events from
a LIGO_LW-format XML file containing a
:class:`sngl_burst <ligo.lw.lsctables.SnglBurstTable>` table

.. GENERATED FROM PYTHON SOURCE LINES 39-46

.. code-block:: Python

    from gwpy.table import EventTable
    events = EventTable.read(
        "H1-LDAS_STRAIN-968654552-10.xml.gz",
        tablename="sngl_burst",
        columns=["peak", "snr"],
    )








.. GENERATED FROM PYTHON SOURCE LINES 47-54

.. note::

   Here we manually specify the `columns` to read in order to optimise
   the `read()` operation to parse only the data we actually need.

We can calculate the rate of events (in Hertz) using the
:meth:`~EventTable.event_rate` method:

.. GENERATED FROM PYTHON SOURCE LINES 54-57

.. code-block:: Python


    rate = events.event_rate(1, start=968654552, end=968654562)








.. GENERATED FROM PYTHON SOURCE LINES 58-61

The :meth:`~EventTable.event_rate` method has returned a
`~gwpy.timeseries.TimeSeries`, so we can display this using the
:meth:`~gwpy.timeseries.TimeSeries.step` method of that object:

.. GENERATED FROM PYTHON SOURCE LINES 61-68

.. code-block:: Python


    plot = rate.step()
    ax = plot.gca()
    ax.set_xlim(968654552, 968654562)
    ax.set_ylabel("Event rate [Hz]")
    ax.set_title("LIGO Hanford Observatory event rate for HW100916")
    plot.show()



.. image-sg:: /examples/table/images/sphx_glr_rate_001.png
   :alt: LIGO Hanford Observatory event rate for HW100916
   :srcset: /examples/table/images/sphx_glr_rate_001.png
   :class: sphx-glr-single-img






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

   **Total running time of the script:** (0 minutes 0.261 seconds)


.. _sphx_glr_download_examples_table_rate.py:

.. only:: html

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

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

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

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

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

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

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


.. only:: html

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

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