def __init__(self, eos, mass, viscosity='lessvisc', theta=0.0, phi=0.0,
distance=20.0, noise_curve='aLIGO'):
# waveform labels and directory setup
self.theta = theta
self.phi = phi
self.distance=distance
self.noise_curve = noise_curve
# Create data object and identify the requested waveform
wavedata = pmns_waveform_data.WaveData()
this_waveform = wavedata.select_wave(eos=eos, mass=mass,
viscosity=viscosity)
if len(this_waveform)>1:
print >> sys.stderr, "ERROR, too many files match the requested eos/mass/viscosity combination"
sys.exit(-1)
if len(this_waveform)==0:
print >> sys.stderr, "ERROR, no waveform with selected EOS, mass and viscosity found"
sys.exit(-1)
self.eos = eos
self.mass = mass
self.data = this_waveform[0]['data']
self.load_quadrupoles()
#
# Build filename
#
filename = "snrs_%s_horizonsnr-%.2f_eos-%s_mass-%s_viscosity-%s.txt" % (
noise_curve, horizon_snr, eos, mass, viscosity)
# XXX: should probably fix this at the module level..
if eos == "all": eos = None
if mass == "all": mass = None
if viscosity == "all": viscosity = None
#
# Create the list of dictionaries which comprises our catalogue
#
waveform_data = pdata.WaveData(eos=eos, viscosity=viscosity, mass=mass)
#
# Create Waveforms and compute SNRs
#
f = open(filename, "w")
f.writelines("# rho_full rho_post Dhor Dsens Rate\n")
rho_min = 100
rho_max = 0
for w, wave in enumerate(waveform_data.waves):
print "SNR for %s, %s ,%s (%d of %d)" % (wave['eos'], wave['mass'],
mass = "135135" total_mass = 2 * 1.35 mass1 = 1.35 mass2 = 1.35 # Hardcoded, fixed delta_t is fine for Bauswein et al: delta_t = 1. / 16384 f_lower_hz = 1000.0 # waveform not valid below here really; could put this on the # pipeline to handle... #startFreqHz = startFreq / (lal.TWOPI * massTotal * lal.MTSUN_SI) f_lower = f_lower_hz * (lal.TWOPI * total_mass * lal.MTSUN_SI) # # Create waveform catalog (EOS, mass & file path) # waveform_data = pdata.WaveData(eos=eos, mass=mass, viscosity='lessvisc') # # Pull out quadrupole data # quadrupole_data = pwave.get_quadrupole_data(waveform_data.waves[0]['data']) # # Generate Hlm's # Hlm = pwave.construct_Hlm(*quadrupole_data[1:]) wavelen = len(Hlm['l=2, m=2']) times = np.arange(0, wavelen * delta_t, delta_t) times_M = times / (lal.MTSUN_SI * total_mass)
# Compute Full SNR
#
full_snr = pycbc.filter.sigma(Hplus, psd=psd, low_frequency_cutoff=fmin)
Hplus.data *= target_sigma / full_snr
# Energy
signal_energy = pycbc.filter.sigmasq(Hplus, low_frequency_cutoff=fmin)
# ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
#
# Generate PCA template
#
#
# Create PMNS PCA instance for the reduced catalogue
#
waveform_data = pdata.WaveData(viscosity='lessvisc')
# Remove testwave_name from the catalogue:
reduced_waveform_data = waveform_data.copy() # make a copy
# Grab the mass-eos waveform we want to study
for w, wave in enumerate(waveform_data.waves):
if wave['mass'] == mass and wave['eos'] == eos:
waveidx = w
#sigma_fpeak_fisher=sigma_fpeak[NPCs-1][waveidx]
if LOO:
reduced_waveform_data.remove_wave(waveform_data.waves[waveidx])
pmpca = ppca.pmnsPCA(reduced_waveform_data,
