likelihood_files = options.likelihood_data
if likelihood_files != cached_likelihood_files:
distributions = load_likelihood_data(likelihood_files,
verbose=options.verbose)
cached_likelihood_files = likelihood_files
#
# Run likelihood ratio calculation.
#
calc_likelihood.assign_likelihood_ratios(
connection=database.connection,
coinc_def_id=database.bb_definer_id,
offset_vectors=database.time_slide_table.as_dict(),
vetoseglists=database.vetoseglists,
events_func=lambda cursor, coinc_event_id:
calc_likelihood.sngl_burst_events_func(
cursor, coinc_event_id, database.sngl_burst_table.row_from_cols),
veto_func=calc_likelihood.sngl_burst_veto_func,
ln_likelihood_ratio_func=distributions.ln_lr_from_triggers,
verbose=options.verbose)
#
# Done with this file.
#
connection.close()
dbtables.put_connection_filename(filename,
working_filename,
verbose=options.verbose)
# # Build triangulators. The timing uncertainty of +/- 8e-5 s was # measured with lalapps_string_plot_binj and is essentially # identical for H1, H2, L1, and V1. # triangulators = stringutils.triangulators(dict.fromkeys(contents.instruments, 8e-5)) # # Run likelihood ratio calculation. # calc_likelihood.assign_likelihood_ratios( connection = contents.connection, coinc_def_id = contents.bb_definer_id, offset_vectors = contents.time_slide_table.as_dict(), vetoseglists = contents.vetoseglists, events_func = lambda cursor, coinc_event_id: calc_likelihood.sngl_burst_events_func(cursor, coinc_event_id, contents.sngl_burst_table.row_from_cols), veto_func = calc_likelihood.sngl_burst_veto_func, ln_likelihood_ratio_func = coincparamsdistributions.ln_lr_from_triggers, verbose = options.verbose ) # # Clean up. # contents.xmldoc.unlink() connection.close() dbtables.put_connection_filename(filename, working_filename, verbose = options.verbose)