# 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)