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

.. currentmodule:: gwpy.timeseries

Generate the Q-transform of a `TimeSeries`
##########################################




First, we identify the GPS time of interest:

.. code-block:: python

   gps = 968654558


and use that to define the start and end times of our required data

.. code-block:: python

   duration = 32
   start = int(round(gps - duration/2.))
   end = start + duration


next, we import the `TimeSeries` and fetch some open data from
`LOSC <//losc.ligo.org>`_:

.. code-block:: python

   from gwpy.timeseries import TimeSeries
   data = TimeSeries.fetch_open_data('H1', start, end)


and next we generate the `~TimeSeries.q_transform` of these data:

.. code-block:: python

   qspecgram = data.q_transform()


Now, we can plot the resulting `~gwpy.spectrogram.Spectrogram`, focusing on a
specific window around the interesting time

.. note::

   Using `~gwpy.spectrogram.Spectrogram.crop` is highly recommended at
   this stage because rendering the high-resolution spectrogram as it is
   done here is very slow (for experts this is because we're using
   `~matplotlib.axes.Axes.pcolormesh` and not any sort of image
   interpolation, mainly to support both linear and log scaling nicely)


.. code-block:: python

   plot = qspecgram.crop(gps-.3, gps+.1).plot(figsize=[8, 6])
   ax = plot.gca()
   ax.set_epoch(gps)
   ax.set_yscale('log')
   ax.set_xlabel('Time [milliseconds]')
   ax.set_ylim(50, 1000)
   ax.grid(True, axis='y', which='both')
   plot.add_colorbar(cmap='viridis', label='Normalized energy')
   plot.show()


I think we just detected a gravitational wave signal! But, before you get too exited, this is an example of a 'blind
injection', a simulated signal introduced into the interferometer(s) in order to test the detection process end-to-end.
For more details, see `here <http://www.ligo.org/scientists/GW100916/>`_.

.. plot:: ../examples/timeseries/qscan.py