5. Plotting EventTable rate versus time for specific column bins¶
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, binned by various thresholds on signal-to-noise ratio (SNR).
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.
First, we import the EventTable object and read in a set of events from
a LIGO_LW-format XML file containing a
sngl_burst table
from gwpy.table import EventTable
events = EventTable.read('H1-LDAS_STRAIN-968654552-10.xml.gz',
tablename='sngl_burst', columns=['peak', 'snr'])
Note
Here we manually specify the columns to read in order to optimise
the read() operation to parse only the data we actually need.
Now we can use the binned_event_rates() method to
calculate the event rate in a number of bins of SNR.
rates = events.binned_event_rates(1, 'snr', [2, 3, 5, 8], operator='>=',
start=968654552, end=968654562)
Note
The list [2, 3, 5, 8] and operator >= specifies SNR tresholds of
2, 3, 5, and 8.
Finally, we can make a plot:
plot = rates.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')
ax.legend(title='SNR $>=$')
plot.show()
(png)
