2. Plotting a normalised
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
Spectrogram to highligh those
from gwpy.timeseries import TimeSeries data = TimeSeries.fetch_open_data( 'H1', 'Sep 14 2015 09:45', 'Sep 14 2015 09:55')
specgram = data.spectrogram(2, fftlength=1, overlap=.5) ** (1/2.)
and can normalise it against the overall median ASD by calling the
normalised = specgram.ratio('median')
Finally, we can make a plot using the
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()
Even with a normalised spectrogram, the resolution is such that a signal as short as that of GW150914 is impossible to see. The next example uses a high-resolution spectrogram method to zoom in around the exact time of the signal.