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

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

.. _sphx_glr_examples_table_tiles.py:


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

Plotting an `EventTable` as 2-d tiles
#####################################

I would like to study the event triggers generated by the `ExcessPower <link>`_
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 35-38

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 38-45

.. code-block:: Python

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








.. GENERATED FROM PYTHON SOURCE LINES 46-53

.. 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 make a plot of these events as 2-dimensional tiles by specifying
the x- and y-axis columns, and the widths in those directions:

.. GENERATED FROM PYTHON SOURCE LINES 53-69

.. code-block:: Python


    plot = events.tile(
        "peak",
        "central_freq",
        "duration",
        "bandwidth",
        color="snr",
    )
    ax = plot.gca()
    ax.set_yscale("log")
    ax.set_ylabel("Frequency [Hz]")
    ax.set_epoch(968654552)
    ax.set_xlim(968654552, 968654552+10)
    ax.set_title("LIGO-Hanford event tiles for HW100916")
    ax.colorbar(clim=[1, 8], cmap="YlGnBu", label="Signal-to-noise ratio (SNR)")
    plot.show()



.. image-sg:: /examples/table/images/sphx_glr_tiles_001.png
   :alt: LIGO-Hanford event tiles for HW100916
   :srcset: /examples/table/images/sphx_glr_tiles_001.png
   :class: sphx-glr-single-img






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

   **Total running time of the script:** (0 minutes 0.377 seconds)


.. _sphx_glr_download_examples_table_tiles.py:

.. only:: html

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

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

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

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

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

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

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


.. only:: html

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

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