From f029a3f57e04ec1a0f2e6b41561a3bca2f52fd1d Mon Sep 17 00:00:00 2001
From: Colm Talbot <colm.talbot@ligo.org>
Date: Fri, 28 Oct 2022 12:50:09 -0700
Subject: [PATCH] remove unused methods/functions
---
bilby/gw/detector/interferometer.py | 46 -------
bilby/gw/likelihood/relative.py | 5 -
bilby/gw/source.py | 189 ----------------------------
3 files changed, 240 deletions(-)
diff --git a/bilby/gw/detector/interferometer.py b/bilby/gw/detector/interferometer.py
index a49cdfa6e..f55c9f7a3 100644
--- a/bilby/gw/detector/interferometer.py
+++ b/bilby/gw/detector/interferometer.py
@@ -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
diff --git a/bilby/gw/likelihood/relative.py b/bilby/gw/likelihood/relative.py
index f6fe1b848..32361b231 100644
--- a/bilby/gw/likelihood/relative.py
+++ b/bilby/gw/likelihood/relative.py
@@ -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):
diff --git a/bilby/gw/source.py b/bilby/gw/source.py
index affdbb6a6..1d415f518 100644
--- a/bilby/gw/source.py
+++ b/bilby/gw/source.py
@@ -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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