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

.. only:: html

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

        :ref:`Go to the end <sphx_glr_download_examples_miscellaneous_range-timeseries.py>`
        to download the full example code.

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

.. _sphx_glr_examples_miscellaneous_range-timeseries.py:


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

Generating an inspiral range timeseries
#######################################

One standard figure-of-merit for the sensitivity of a gravitational-wave
detector is the distance to which a binary neutron star (BNS) inspiral
with two 1.4 solar mass components would be detected with a signal-to-noise
ratio (SNR) of 8. We can estimate this using
:func:`gwpy.astro.range_timeseries` directly from the strain readout for
a detector.

.. GENERATED FROM PYTHON SOURCE LINES 34-39

Data access
-----------
First, we need to load some data. We can `fetch` the
`public data <https://gwosc.org/catalog/>`__
around the GW170817 BNS merger:

.. GENERATED FROM PYTHON SOURCE LINES 39-44

.. code-block:: Python


    from gwpy.timeseries import TimeSeries
    h1 = TimeSeries.fetch_open_data("H1", 1187006834, 1187010930)
    l1 = TimeSeries.fetch_open_data("L1", 1187006834, 1187010930)








.. GENERATED FROM PYTHON SOURCE LINES 45-49

Range estimation
----------------
Then, we can measure the inspiral range directly, at 30 second granularity
with a 4-second FFT length starting at 10 Hz:

.. GENERATED FROM PYTHON SOURCE LINES 49-54

.. code-block:: Python


    from gwpy.astro import range_timeseries
    h1range = range_timeseries(h1, 30, fftlength=4, fmin=10)
    l1range = range_timeseries(l1, 30, fftlength=4, fmin=10)





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

 .. code-block:: none

    /home/duncan.macleod/gwpy-nightly-build/conda/envs/gwpy-nightly-3.11/lib/python3.11/site-packages/inspiral_range/waveform.py:369: DeprecationWarning: `trapz` is deprecated. Use `trapezoid` instead, or one of the numerical integration functions in `scipy.integrate`.
      return np.sqrt(4*np.trapz((h**2)/psd, self.freq))




.. GENERATED FROM PYTHON SOURCE LINES 55-59

Visualisation
-------------
We can now plot these trends to see the variation in LIGO
sensitivity over an hour or so surrounding GW170817:

.. GENERATED FROM PYTHON SOURCE LINES 59-73

.. code-block:: Python


    plot = h1range.plot(
        label="LIGO-Hanford",
        color="gwpy:ligo-hanford",
        figsize=(12, 5),
    )
    ax = plot.gca()
    ax.plot(l1range, label="LIGO-Livingston", color="gwpy:ligo-livingston")
    ax.set_ylabel("Angle-averaged sensitive distance [Mpc]")
    ax.set_title("LIGO sensitivity to BNS around GW170817")
    ax.set_epoch(1187008882)  # <- set 0 on plot to GW170817
    ax.legend()
    plot.show()




.. image-sg:: /examples/miscellaneous/images/sphx_glr_range-timeseries_001.png
   :alt: LIGO sensitivity to BNS around GW170817
   :srcset: /examples/miscellaneous/images/sphx_glr_range-timeseries_001.png
   :class: sphx-glr-single-img





.. GENERATED FROM PYTHON SOURCE LINES 74-78

Note, the extreme dip in LIGO-Livingston's sensitivity near GW170817
is caused by a loud, transient noise event, see `Phys. Rev. Lett.
vol. 119, p. 161101 <http://doi.org/10.1103/PhysRevLett.119.161101>`_
for more information.


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

   **Total running time of the script:** (0 minutes 5.206 seconds)


.. _sphx_glr_download_examples_miscellaneous_range-timeseries.py:

.. only:: html

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

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

      :download:`Download Jupyter notebook: range-timeseries.ipynb <range-timeseries.ipynb>`

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

      :download:`Download Python source code: range-timeseries.py <range-timeseries.py>`

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

      :download:`Download zipped: range-timeseries.zip <range-timeseries.zip>`


.. only:: html

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

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