detailed tutorial for open data

The tutorial is based on GW150914.py, with the addition of more in depth comments. The code has been adapted to be used for other LOSC events, i.e. all arguments are explicitly specified (e.g. interferometer_names, sample_rate, npoints..), so that they can be easily edited by the user.

examples/open_data_examples/advanced_opendata.py

+#!/usr/bin/env python
+"""
+This tutorial includes advanced specifications for analysing know events.
+This should simplify the comparison wiht LALInference results.
+Here GW150914 is used as an example.
+
+LIST OF AVAILABLE EVENTS: Run -> help(bilby.gw.utils.get_event_time(event))
+"""
+from __future__ import division, print_function
+import bilby
+
+outdir = 'outdir'
+label = 'GW150914'
+time_of_event = bilby.gw.utils.get_event_time(label)
+
+bilby.core.utils.setup_logger(outdir=outdir, label=label)
+
+# GET DATA FROM INTERFEROMETER
+interferometer_names = ['H1', 'L1']  # can also include 'V1'
+duration = 4    # length of data segment containing the signal
+roll_off = 0.2  # smoothness of transition from no signal
+# to max signal in a Tukey Window.
+psd_offset = -1024  # PSD is estimated using data from
+# 'center_time + psd_offset' to 'center_time + psd_offset + psd_duration'
+psd_duration = 100
+filter_freq = None  # low pass filter frequency to cut signal content above
+# Nyquist frequency. The condition is 2 * filter_freq >= sampling_frequency
+
+# Keyword args are passed to 'gwpy.timeseries.TimeSeries.fetch_open_data()'
+# sample_rate: most data are stored by LOSC at 4096 Hz,
+# there may be event-related data releases with a 16384 Hz rate.
+kwargs = {"sample_rate": 4096}
+# For some events a "tag" is required to download the data. (CLN = clean data)
+# kwargs = {"tag": 'CLN'}
+# For some events can specify channels: source data stream for LOSC data.
+# kwargs = {"channel": {'H1': 'H1:DCS-CALIB_STRAIN_C02',
+#                      'L1': 'L1:DCS-CALIB_STRAIN_C02',
+#                      'V1': 'V1:FAKE_h_16384Hz_4R'}}
+
+interferometers = bilby.gw.detector.get_event_data(
+    label, interferometer_names=interferometer_names,
+    duration=duration, roll_off=roll_off, psd_offset=psd_offset,
+    psd_duration=psd_duration, cache=True,
+    filter_freq=filter_freq, **kwargs)
+
+# CHOOSE PRIOR FILE
+# DEFAULT PRIOR FILES: GW150914.prior, binary_black_holes.prior,
+# binary_neutron_stars.prior
+# Needs to specify path for any other prior file.
+prior = bilby.gw.prior.BBHPriorDict(filename='GW150914.prior')
+
+# GENERATE WAVEFORM
+duration = None  # duration and sampling frequency will be overwritten
+# to match the ones in the interferometers.
+sampling_frequency = kwargs["sample_rate"]  # same at which the data is stored
+start_time = 0  # set the starting time of the time array
+
+# reference_frequency: either low freq. limit or most sensitive freq.
+# OVERVIEW OF APPROXIMANTS:
+# https://www.lsc-group.phys.uwm.edu/ligovirgo/cbcnote/Waveforms/Overview
+waveform_arguments = {'waveform_approximant': 'IMRPhenomPv2',
+                      'reference_frequency': 50}
+source_model = bilby.gw.source.lal_binary_black_hole
+
+waveform_generator = bilby.gw.WaveformGenerator(
+    duration=duration, sampling_frequency=sampling_frequency,
+    start_time=start_time,
+    frequency_domain_source_model=source_model, 
+    waveform_arguments=waveform_arguments)
+
+# CHOOSE LIKELIHOOD FUNCTION
+# Time marginalisation uses FFT and can use a prior file.
+# Distance marginalisation uses a look up table calculated at run time.
+# Phase marginalisation is done analytically using a Bessel function.
+# If prior given, used in the distance and phase marginalization.
+likelihood = bilby.gw.likelihood.GravitationalWaveTransient(
+    interferometers, waveform_generator, time_marginalization=False,
+    distance_marginalization=False, phase_marginalization=False,
+    prior=None)
+
+# RUN SAMPLER
+# Can use log_likelihood_ratio, rather than just the log_likelihood.
+# If using simulated data, pass a dictionary of injection parameters.
+# A function can be specified in 'conversion_function' and applied
+# to posterior to generate additional parameters e.g. source-frame masses.
+
+# Implemented Samplers:
+# LIST OF AVAILABLE SAMPLERS: Run -> bilby.sampler.implemented_samplers
+npoints = 500  # number of live points for the MCMC
+sampler = 'dynesty'
+
+result = bilby.run_sampler(
+    likelihood, prior, outdir=outdir, label=label,
+    sampler=sampler, npoints=npoints, use_ratio=False,
+    injection_parameters=None, 
+    conversion_function=bilby.gw.conversion.generate_all_bbh_parameters)
+
+result.plot_corner()