Adjusted typos, comments and conversation function after feedback.

examples/open_data_examples/advanced_opendata.py

@@ -19,11 +19,10 @@ bilby.core.utils.setup_logger(outdir=outdir, label=label)
 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 Turkey Window.
+# 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
-coherence_test = False  # coherence between detectors
 filter_freq = None  # low pass filter frequency to cut signal content above
 # Nyquist frequency. The condition is 2 * filter_freq >= sampling_frequency
 
@@ -46,12 +45,12 @@ interferometers = bilby.gw.detector.get_event_data(
 
 # CHOOSE PRIOR FILE
 # DEFAULT PRIOR FILES: GW150914.prior, binary_black_holes.prior,
-# binary_neutron_stars.prior, comoving.txt
+# 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  # durantion and sampling frequency will be overwritten
+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
@@ -66,11 +65,11 @@ 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,
+    frequency_domain_source_model=source_model, 
     waveform_arguments=waveform_arguments)
 
 # CHOOSE LIKELIHOOD FUNCTION
-# Time marginalisation uses FFT.
+# 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.
@@ -82,18 +81,18 @@ likelihood = bilby.gw.likelihood.GravitationalWaveTransient(
 # 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.
+# 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 = 512  # number of live points for the MCMC
+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=None,
-    default_priors_file=None)
+    injection_parameters=None, 
+    conversion_function=bilby.gw.conversion.generate_all_bbh_parameters)
 
 result.plot_corner()