# Control evaluation of the effective Fisher grid NMcs = 11 NEtas = 11 match_cntr = opts.match_value # Fill an ellipsoid of this match wide_match = 1-(1-opts.match_value)**(2/3.0) fit_cntr = match_cntr # Do the effective Fisher fit with pts above this match Nrandpts = opts.N_mass_pts # Requested number of pts to put inside the ellipsoid Nlam = opts.N_tidal_pts or 1 # # Tidal parameters # if opts.eff_lambda: # NOTE: Since dlambda tilde is effectively zero, it's assumed that the user # will set it explicitly if they want it, otherwise it's zero identically lambda1, lambda2 = lsu.tidal_lambda_from_tilde(m1, m2, opts.eff_lambda, opts.delta_eff_lambda or 0) else: lambda1, lambda2 = 0, 0 # # FIXME: Hardcoded values - eventually promote to command line arguments # template_min_freq = 40. ip_min_freq = 40. # # Setup signal and IP class # param_names = ['Mc', 'eta'] McSIG = lsu.mchirp(m1_SI, m2_SI) etaSIG = lsu.symRatio(m1_SI, m2_SI)
elif opts.coinc_xml is not None: sngl_inspiral_table = table.get_table( xmldoc, lsctables.SnglInspiralTable.tableName) assert len(sngl_inspiral_table) == len(coinc_row.ifos.split(",")) m1, m2 = None, None for sngl_row in sngl_inspiral_table: # NOTE: gstlal is exact match, but other pipelines may not be assert m1 is None or (sngl_row.mass1 == m1 and sngl_row.mass2 == m2) m1, m2 = sngl_row.mass1, sngl_row.mass2 else: raise ValueError( "Need either --mass1 --mass2 or --coinc-xml to retrieve masses.") lambda1, lambda2 = 0, 0 if opts.eff_lambda is not None: lambda1, lambda2 = lalsimutils.tidal_lambda_from_tilde( opts.mass1, opts.mass2, opts.eff_lambda, opts.deff_lambda or 0) print "Performing integration for intrinsic parameters mass 1: %f, mass 2 %f, lambda1: %f, lambda2: %f, spin1z: %1.3f, spin2z: %1.3f" % ( m1, m2, lambda1, lambda2, opts.spin1z or 0, opts.spin2z or 0) # # Template descriptors # fiducial_epoch = lal.LIGOTimeGPS(event_time.seconds, event_time.nanoseconds) # Struct to hold template parameters P = lalsimutils.ChooseWaveformParams( approx=lalsimutils.lalsim.GetApproximantFromString(opts.approximant), radec=False, fmin=opts.fmin_template, # minimum frequency of template
if opts.mass1 is not None and opts.mass2 is not None: m1, m2 = opts.mass1, opts.mass2 elif opts.coinc_xml is not None: sngl_inspiral_table = table.get_table(xmldoc, lsctables.SnglInspiralTable.tableName) assert len(sngl_inspiral_table) == len(coinc_row.ifos.split(",")) m1, m2 = None, None for sngl_row in sngl_inspiral_table: # NOTE: gstlal is exact match, but other pipelines may not be assert m1 is None or (sngl_row.mass1 == m1 and sngl_row.mass2 == m2) m1, m2 = sngl_row.mass1, sngl_row.mass2 else: raise ValueError("Need either --mass1 --mass2 or --coinc-xml to retrieve masses.") lambda1, lambda2 = 0, 0 if opts.eff_lambda is not None: lambda1, lambda2 = lalsimutils.tidal_lambda_from_tilde(opts.mass1, opts.mass2, opts.eff_lambda, opts.deff_lambda or 0) print "Performing integration for intrinsic parameters mass 1: %f, mass 2 %f, lambda1: %f, lambda2: %f, spin1z: %1.3f, spin2z: %1.3f" % (m1, m2, lambda1, lambda2, opts.spin1z or 0, opts.spin2z or 0) # # Template descriptors # fiducial_epoch = lal.LIGOTimeGPS(event_time.seconds, event_time.nanoseconds) # Struct to hold template parameters P = lalsimutils.ChooseWaveformParams( approx = lalsimutils.lalsim.GetApproximantFromString(opts.approximant), radec = False, fmin = opts.fmin_template, # minimum frequency of template fref = opts.reference_freq,
# Control evaluation of the effective Fisher grid NMcs = 11 NEtas = 11 match_cntr = opts.match_value # Fill an ellipsoid of this match wide_match = 1 - (1 - opts.match_value)**(2 / 3.0) fit_cntr = match_cntr # Do the effective Fisher fit with pts above this match Nrandpts = opts.N_mass_pts # Requested number of pts to put inside the ellipsoid Nlam = opts.N_tidal_pts or 1 # # Tidal parameters # if opts.eff_lambda: # NOTE: Since dlambda tilde is effectively zero, it's assumed that the user # will set it explicitly if they want it, otherwise it's zero identically lambda1, lambda2 = lsu.tidal_lambda_from_tilde(m1, m2, opts.eff_lambda, opts.delta_eff_lambda or 0) else: lambda1, lambda2 = 0, 0 # # FIXME: Hardcoded values - eventually promote to command line arguments # template_min_freq = 40. ip_min_freq = 40. # # Setup signal and IP class # param_names = ['Mc', 'eta'] McSIG = lsu.mchirp(m1_SI, m2_SI) etaSIG = lsu.symRatio(m1_SI, m2_SI)