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Commit f029a3f5 authored by Colm Talbot's avatar Colm Talbot
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remove unused methods/functions

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1 merge request!1105Relative Binning in bilby
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bilby/gw/detector/interferometer.py
+ 0
− 46
View file @ f029a3f5
......@@ -332,52 +332,6 @@ class Interferometer(object):
return signal_ifo
def get_detector_response_relative_binning(self, waveform_polarizations,
parameters, bin_frequencies):
"""Get the detector response for a particular waveform, where the frequencies
of the waveform polarizations are only the binning frequencies and we
assume that there is no frequency mask necessary for the data. Kind of
a hacky workaround. Should do something better probably.
Parameters
-------
waveform_polarizations: dict
polarizations of the waveform
parameters: dict
parameters describing position and time of arrival of the signal
Returns
-------
array_like: A 3x3 array representation of the detector response (signal observed in the interferometer)
"""
signal = {}
for mode in waveform_polarizations.keys():
det_response = self.antenna_response(
parameters['ra'],
parameters['dec'],
parameters['geocent_time'],
parameters['psi'], mode)
signal[mode] = waveform_polarizations[mode] * det_response
signal_ifo = sum(signal.values())
time_shift = self.time_delay_from_geocenter(
parameters['ra'], parameters['dec'], parameters['geocent_time'])
# Be careful to first subtract the two GPS times which are ~1e9 sec.
# And then add the time_shift which varies at ~1e-5 sec
dt_geocent = parameters['geocent_time'] - self.strain_data.start_time
dt = dt_geocent + time_shift
signal_ifo = signal_ifo * \
np.exp(-1j * 2 * np.pi * dt * bin_frequencies)
signal_ifo *= self.calibration_model.get_calibration_factor(
bin_frequencies, prefix='recalib_{}_'.format(self.name),
**parameters)
return signal_ifo
def check_signal_duration(self, parameters, raise_error=True):
""" Check that the signal with the given parameters fits in the data
......
bilby/gw/likelihood/relative.py
+ 0
− 5
View file @ f029a3f5
......@@ -189,7 +189,6 @@ class RelativeBinningGravitationalWaveTransient(GravitationalWaveTransient):
self.per_detector_fiducial_waveform_points[name] = (
self.per_detector_fiducial_waveforms[name][self.bin_inds[name]]
)
return
def set_fiducial_waveforms(self, parameters):
parameters["fiducial"] = 1
......@@ -213,10 +212,6 @@ class RelativeBinningGravitationalWaveTransient(GravitationalWaveTransient):
interferometer.get_detector_response(
self.fiducial_polarizations, parameters))
parameters["fiducial"] = 0
return
def log_likelihood(self):
return self.log_likelihood_ratio() + self.noise_log_likelihood()
def find_maximum_likelihood_parameters(self, parameter_bounds,
iterations=1, maximization_kwargs=None):
......
bilby/gw/source.py
+ 0
− 189
View file @ f029a3f5
......@@ -882,195 +882,6 @@ def _base_waveform_frequency_sequence(
return dict(plus=h_plus.data.data, cross=h_cross.data.data)
def lal_binary_black_hole_relativebinning(
frequency_array, mass_1, mass_2, luminosity_distance, a_1, tilt_1,
phi_12, a_2, tilt_2, phi_jl, theta_jn, phase, fiducial, **kwargs):
waveform_kwargs = dict(
waveform_approximant='IMRPhenomPv2', reference_frequency=50.0,
minimum_frequency=20.0, maximum_frequency=frequency_array[-1],
catch_waveform_errors=False, pn_spin_order=-1, pn_tidal_order=-1,
pn_phase_order=-1, pn_amplitude_order=0)
waveform_kwargs.update(kwargs)
if fiducial == 1:
return _base_lal_cbc_fd_waveform(
frequency_array=frequency_array, mass_1=mass_1, mass_2=mass_2,
luminosity_distance=luminosity_distance, theta_jn=theta_jn, phase=phase,
a_1=a_1, a_2=a_2, tilt_1=tilt_1, tilt_2=tilt_2, phi_jl=phi_jl,
phi_12=phi_12, lambda_1=0.0, lambda_2=0.0, **waveform_kwargs)
else:
return _base_relativebinning_waveform(
frequency_array=frequency_array, mass_1=mass_1, mass_2=mass_2,
luminosity_distance=luminosity_distance, theta_jn=theta_jn, phase=phase,
a_1=a_1, a_2=a_2, tilt_1=tilt_1, tilt_2=tilt_2, phi_jl=phi_jl,
phi_12=phi_12, lambda_1=0.0, lambda_2=0.0, **waveform_kwargs)
def lal_binary_neutron_star_relativebinning(
frequency_array, mass_1, mass_2, luminosity_distance, a_1, tilt_1,
phi_12, a_2, tilt_2, phi_jl, lambda_1, lambda_2, theta_jn, phase,
fiducial, **kwargs):
waveform_kwargs = dict(
waveform_approximant='IMRPhenomPv2_NRTidal', reference_frequency=50.0,
minimum_frequency=20.0, maximum_frequency=frequency_array[-1],
catch_waveform_errors=False, pn_spin_order=-1, pn_tidal_order=-1,
pn_phase_order=-1, pn_amplitude_order=0)
waveform_kwargs.update(kwargs)
if fiducial == 1:
return _base_lal_cbc_fd_waveform(
frequency_array=frequency_array, mass_1=mass_1, mass_2=mass_2,
luminosity_distance=luminosity_distance, theta_jn=theta_jn, phase=phase,
a_1=a_1, a_2=a_2, tilt_1=tilt_1, tilt_2=tilt_2, phi_12=phi_12,
phi_jl=phi_jl, lambda_1=lambda_1, lambda_2=lambda_2, **waveform_kwargs)
else:
return _base_relativebinning_waveform(
frequency_array=frequency_array, mass_1=mass_1, mass_2=mass_2,
luminosity_distance=luminosity_distance, theta_jn=theta_jn, phase=phase,
a_1=a_1, a_2=a_2, tilt_1=tilt_1, tilt_2=tilt_2, phi_jl=phi_jl,
phi_12=phi_12, lambda_1=lambda_1, lambda_2=lambda_2, **waveform_kwargs)
def _base_relativebinning_waveform(
frequency_array, mass_1, mass_2, luminosity_distance, theta_jn, phase,
a_1=0.0, a_2=0.0, tilt_1=0.0, tilt_2=0.0, phi_12=0.0, phi_jl=0.0,
lambda_1=0.0, lambda_2=0.0, **waveform_kwargs):
""" Generate a cbc waveform model using lalsimulation
Parameters
----------
frequency_array: array_like
The frequencies at which we want to calculate the strain. Ignored
for the relative binning model.
mass_1: float
The mass of the heavier object in solar masses
mass_2: float
The mass of the lighter object in solar masses
luminosity_distance: float
The luminosity distance in megaparsec
a_1: float
Dimensionless primary spin magnitude
tilt_1: float
Primary tilt angle
phi_12: float
Azimuthal angle between the component spins
a_2: float
Dimensionless secondary spin magnitude
tilt_2: float
Secondary tilt angle
phi_jl: float
Azimuthal angle between the total and orbital angular momenta
theta_jn: float
Orbital inclination
phase: float
The phase at coalescence
lambda_1: float
Tidal deformability of the more massive object
lambda_2: float
Tidal deformability of the less massive object
kwargs: dict
Optional keyword arguments
Waveform arguments
------------------
Non-sampled extra data used in the source model calculation
frequency_bin_edges: np.array
Returns
-------
dict: A dictionary with the plus and cross polarisation strain modes
"""
import lal
import lalsimulation as lalsim
waveform_approximant = waveform_kwargs['waveform_approximant']
reference_frequency = waveform_kwargs['reference_frequency']
catch_waveform_errors = waveform_kwargs['catch_waveform_errors']
pn_spin_order = waveform_kwargs['pn_spin_order']
pn_tidal_order = waveform_kwargs['pn_tidal_order']
pn_phase_order = waveform_kwargs['pn_phase_order']
pn_amplitude_order = waveform_kwargs['pn_amplitude_order']
waveform_dictionary = waveform_kwargs.get(
'lal_waveform_dictionary', lal.CreateDict()
)
frequency_bin_edges = waveform_kwargs['frequency_bin_edges']
approximant = lalsim_GetApproximantFromString(waveform_approximant)
luminosity_distance = luminosity_distance * 1e6 * utils.parsec
mass_1 = mass_1 * utils.solar_mass
mass_2 = mass_2 * utils.solar_mass
iota, spin_1x, spin_1y, spin_1z, spin_2x, spin_2y, spin_2z = bilby_to_lalsimulation_spins(
theta_jn=theta_jn, phi_jl=phi_jl, tilt_1=tilt_1, tilt_2=tilt_2,
phi_12=phi_12, a_1=a_1, a_2=a_2, mass_1=mass_1, mass_2=mass_2,
reference_frequency=reference_frequency, phase=phase)
lalsim.SimInspiralWaveformParamsInsertPNSpinOrder(
waveform_dictionary, int(pn_spin_order))
lalsim.SimInspiralWaveformParamsInsertPNTidalOrder(
waveform_dictionary, int(pn_tidal_order))
lalsim.SimInspiralWaveformParamsInsertPNPhaseOrder(
waveform_dictionary, int(pn_phase_order))
lalsim.SimInspiralWaveformParamsInsertPNAmplitudeOrder(
waveform_dictionary, int(pn_amplitude_order))
lalsim_SimInspiralWaveformParamsInsertTidalLambda1(
waveform_dictionary, lambda_1)
lalsim_SimInspiralWaveformParamsInsertTidalLambda2(
waveform_dictionary, lambda_2)
for key, value in waveform_kwargs.items():
func = getattr(lalsim, "SimInspiralWaveformParamsInsert" + key, None)
if func is not None:
func(waveform_dictionary, value)
if waveform_kwargs.get('numerical_relativity_file', None) is not None:
lalsim.SimInspiralWaveformParamsInsertNumRelData(
waveform_dictionary, waveform_kwargs['numerical_relativity_file'])
if ('mode_array' in waveform_kwargs) and waveform_kwargs['mode_array'] is not None:
mode_array = waveform_kwargs['mode_array']
mode_array_lal = lalsim.SimInspiralCreateModeArray()
for mode in mode_array:
lalsim.SimInspiralModeArrayActivateMode(mode_array_lal, mode[0], mode[1])
lalsim.SimInspiralWaveformParamsInsertModeArray(waveform_dictionary, mode_array_lal)
try:
h_binned_plus, h_binned_cross = lalsim_SimInspiralChooseFDWaveformSequence(
phase, mass_1, mass_2, spin_1x, spin_1y, spin_1z, spin_2x, spin_2y,
spin_2z, reference_frequency, luminosity_distance, iota,
waveform_dictionary, approximant, frequency_bin_edges)
except Exception as e:
if not catch_waveform_errors:
raise
else:
EDOM = (e.args[0] == 'Internal function call failed: Input domain error')
if EDOM:
failed_parameters = dict(mass_1=mass_1, mass_2=mass_2,
spin_1=(spin_1x, spin_2y, spin_1z),
spin_2=(spin_2x, spin_2y, spin_2z),
luminosity_distance=luminosity_distance,
iota=iota, phase=phase,
)
logger.warning("Evaluating the waveform failed with error: {}\n".format(e) +
"The parameters were {}\n".format(failed_parameters) +
"Likelihood will be set to -inf.")
return None
else:
raise
waveform_polarizations = dict(
plus=h_binned_plus.data.data, cross=h_binned_cross.data.data)
return waveform_polarizations
def sinegaussian(frequency_array, hrss, Q, frequency, **kwargs):
r"""
A frequency-domain sine-Gaussian burst source model.
......
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