From c7c16d90269aa388352b8fcbd8a88b53d4f3172d Mon Sep 17 00:00:00 2001
From: Colm Talbot <colm.talbot@ligo.org>
Date: Tue, 28 May 2019 00:36:05 -0500
Subject: [PATCH] Generalise ROQ
---
bilby/gw/conversion.py | 19 ++
bilby/gw/source.py | 270 +++++++++++----------
bilby/gw/utils.py | 141 ++++++++---
examples/injection_examples/roq_example.py | 11 +-
test/gw_utils_test.py | 23 +-
5 files changed, 292 insertions(+), 172 deletions(-)
diff --git a/bilby/gw/conversion.py b/bilby/gw/conversion.py
index 0dea42aa3..c2b842e83 100644
--- a/bilby/gw/conversion.py
+++ b/bilby/gw/conversion.py
@@ -50,6 +50,25 @@ def luminosity_distance_to_comoving_distance(distance, cosmology=None):
return redshift_to_comoving_distance(redshift, cosmology)
+def bilby_to_lalsimulation_spins(
+ theta_jn, phi_jl, tilt_1, tilt_2, phi_12, a_1, a_2, mass_1, mass_2,
+ reference_frequency, phase):
+ if tilt_1 in [0, np.pi] and tilt_2 in [0, np.pi]:
+ spin_1x = 0
+ spin_1y = 0
+ spin_1z = a_1 * np.cos(tilt_1)
+ spin_2x = 0
+ spin_2y = 0
+ spin_2z = a_2 * np.cos(tilt_2)
+ iota = theta_jn
+ else:
+ iota, spin_1x, spin_1y, spin_1z, spin_2x, spin_2y, spin_2z = \
+ transform_precessing_spins(
+ theta_jn, phi_jl, tilt_1, tilt_2, phi_12, a_1, a_2, mass_1,
+ mass_2, reference_frequency, phase)
+ return iota, spin_1x, spin_1y, spin_1z, spin_2x, spin_2y, spin_2z
+
+
@np.vectorize
def transform_precessing_spins(theta_jn, phi_jl, tilt_1, tilt_2, phi_12, a_1,
a_2, mass_1, mass_2, reference_frequency, phase):
diff --git a/bilby/gw/source.py b/bilby/gw/source.py
index bdb5fcf56..5a90b5be2 100644
--- a/bilby/gw/source.py
+++ b/bilby/gw/source.py
@@ -4,14 +4,13 @@ import numpy as np
from ..core import utils
from ..core.utils import logger
-from .conversion import transform_precessing_spins
+from .conversion import bilby_to_lalsimulation_spins
from .utils import (lalsim_GetApproximantFromString,
lalsim_SimInspiralFD,
lalsim_SimInspiralChooseFDWaveform,
lalsim_SimInspiralWaveformParamsInsertTidalLambda1,
lalsim_SimInspiralWaveformParamsInsertTidalLambda2,
- lalsim_SimIMRPhenomPCalculateModelParametersFromSourceFrame,
- lalsim_SimIMRPhenomPFrequencySequence)
+ lalsim_SimInspiralChooseFDWaveformSequence)
try:
import lal
@@ -227,10 +226,9 @@ def _base_lal_cbc_fd_waveform(
approximant = lalsim_GetApproximantFromString(waveform_approximant)
- if (pn_amplitude_order != 0):
- start_frequency = lalsim.SimInspiralfLow2fStart(minimum_frequency,
- int(pn_amplitude_order),
- approximant)
+ if pn_amplitude_order != 0:
+ start_frequency = lalsim.SimInspiralfLow2fStart(
+ minimum_frequency, int(pn_amplitude_order), approximant)
else:
start_frequency = minimum_frequency
@@ -243,30 +241,27 @@ def _base_lal_cbc_fd_waveform(
mass_1 = mass_1 * utils.solar_mass
mass_2 = mass_2 * utils.solar_mass
- if tilt_1 in [0.0, np.pi] and tilt_2 in [0, np.pi]:
- spin_1x = 0.0
- spin_1y = 0.0
- spin_1z = a_1 * np.cos(tilt_1)
- spin_2x = 0.0
- spin_2y = 0.0
- spin_2z = a_2 * np.cos(tilt_2)
- iota = theta_jn
- else:
- iota, spin_1x, spin_1y, spin_1z, spin_2x, spin_2y, spin_2z = (
- transform_precessing_spins(
- theta_jn, phi_jl, tilt_1, tilt_2, phi_12, a_1, a_2, mass_1,
- mass_2, reference_frequency, phase))
+ 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)
longitude_ascending_nodes = 0.0
mean_per_ano = 0.0
waveform_dictionary = lal.CreateDict()
- 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)
+ 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)
if lalsim.SimInspiralImplementedFDApproximants(approximant):
wf_func = lalsim_SimInspiralChooseFDWaveform
@@ -291,70 +286,53 @@ def _base_lal_cbc_fd_waveform(
h_plus *= frequency_bounds
h_cross *= frequency_bounds
- return {'plus': h_plus, 'cross': h_cross}
-
-
-def sinegaussian(frequency_array, hrss, Q, frequency, **kwargs):
- tau = Q / (np.sqrt(2.0) * np.pi * frequency)
- temp = Q / (4.0 * np.sqrt(np.pi) * frequency)
- fm = frequency_array - frequency
- fp = frequency_array + frequency
-
- h_plus = ((hrss / np.sqrt(temp * (1 + np.exp(-Q**2)))) *
- ((np.sqrt(np.pi) * tau) / 2.0) *
- (np.exp(-fm**2 * np.pi**2 * tau**2) +
- np.exp(-fp**2 * np.pi**2 * tau**2)))
-
- h_cross = (-1j * (hrss / np.sqrt(temp * (1 - np.exp(-Q**2)))) *
- ((np.sqrt(np.pi) * tau) / 2.0) *
- (np.exp(-fm**2 * np.pi**2 * tau**2) -
- np.exp(-fp**2 * np.pi**2 * tau**2)))
-
- return{'plus': h_plus, 'cross': h_cross}
-
-
-def supernova(
- frequency_array, realPCs, imagPCs, file_path, luminosity_distance, **kwargs):
- """ A supernova NR simulation for injections """
-
- realhplus, imaghplus, realhcross, imaghcross = np.loadtxt(
- file_path, usecols=(0, 1, 2, 3), unpack=True)
-
- # waveform in file at 10kpc
- scaling = 1e-3 * (10.0 / luminosity_distance)
-
- h_plus = scaling * (realhplus + 1.0j * imaghplus)
- h_cross = scaling * (realhcross + 1.0j * imaghcross)
- return {'plus': h_plus, 'cross': h_cross}
-
+ return dict(plus=h_plus, cross=h_cross)
-def supernova_pca_model(
- frequency_array, pc_coeff1, pc_coeff2, pc_coeff3, pc_coeff4, pc_coeff5,
- luminosity_distance, **kwargs):
- """ Supernova signal model """
- realPCs = kwargs['realPCs']
- imagPCs = kwargs['imagPCs']
+def roq(
+ frequency_array, mass_1, mass_2, luminosity_distance, a_1, tilt_1,
+ phi_12, a_2, tilt_2, phi_jl, theta_jn, phase, **waveform_arguments):
+ logger.warning(
+ 'bilby.gw.source.roq has been deprecated and will be removed. Use '
+ 'bilby.gw.source.binary_black_hole_roq instead.')
+ return binary_black_hole_roq(
+ frequency_array=frequency_array, mass_1=mass_1, mass_2=mass_2,
+ luminosity_distance=luminosity_distance, a_1=a_1, tilt_1=tilt_1,
+ phi_12=phi_12, a_2=a_2, tilt_2=tilt_2, phi_jl=phi_jl,
+ theta_jn=theta_jn, phase=phase, **waveform_arguments)
- pc1 = realPCs[:, 0] + 1.0j * imagPCs[:, 0]
- pc2 = realPCs[:, 1] + 1.0j * imagPCs[:, 1]
- pc3 = realPCs[:, 2] + 1.0j * imagPCs[:, 2]
- pc4 = realPCs[:, 3] + 1.0j * imagPCs[:, 3]
- pc5 = realPCs[:, 4] + 1.0j * imagPCs[:, 5]
- # file at 10kpc
- scaling = 1e-23 * (10.0 / luminosity_distance)
+def binary_black_hole_roq(
+ frequency_array, mass_1, mass_2, luminosity_distance, a_1, tilt_1,
+ phi_12, a_2, tilt_2, phi_jl, theta_jn, phase, **waveform_arguments):
+ waveform_kwargs = dict(
+ waveform_approximant='IMRPhenomPv2', reference_frequency=20.0)
+ waveform_kwargs.update(waveform_arguments)
+ return _base_roq_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)
- h_plus = scaling * (pc_coeff1 * pc1 + pc_coeff2 * pc2 + pc_coeff3 * pc3 +
- pc_coeff4 * pc4 + pc_coeff5 * pc5)
- h_cross = scaling * (pc_coeff1 * pc1 + pc_coeff2 * pc2 + pc_coeff3 * pc3 +
- pc_coeff4 * pc4 + pc_coeff5 * pc5)
- return {'plus': h_plus, 'cross': h_cross}
+def binary_neutron_star_roq(
+ 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,
+ **waveform_arguments):
+ waveform_kwargs = dict(
+ waveform_approximant='IMRPhenomD_NRTidal', reference_frequency=20.0)
+ waveform_kwargs.update(waveform_arguments)
+ return _base_roq_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 roq(frequency_array, mass_1, mass_2, luminosity_distance, a_1, tilt_1,
- phi_12, a_2, tilt_2, phi_jl, theta_jn, phase, **waveform_arguments):
+def _base_roq_waveform(
+ frequency_array, mass_1, mass_2, luminosity_distance, a_1, tilt_1,
+ phi_12, a_2, tilt_2, lambda_1, lambda_2, phi_jl, theta_jn, phase,
+ **waveform_arguments):
"""
See https://git.ligo.org/lscsoft/lalsuite/blob/master/lalsimulation/src/LALSimInspiral.c#L1460
@@ -391,7 +369,7 @@ def roq(frequency_array, mass_1, mass_2, luminosity_distance, a_1, tilt_1,
frequency_nodes_linear: np.array
frequency_nodes_quadratic: np.array
reference_frequency: float
- version: str
+ approximant: str
Note: for the frequency_nodes_linear and frequency_nodes_quadratic arguments,
if using data from https://git.ligo.org/lscsoft/ROQ_data, this should be
@@ -402,59 +380,101 @@ def roq(frequency_array, mass_1, mass_2, luminosity_distance, a_1, tilt_1,
waveform_polarizations: dict
Dict containing plus and cross modes evaluated at the linear and
quadratic frequency nodes.
-
"""
frequency_nodes_linear = waveform_arguments['frequency_nodes_linear']
frequency_nodes_quadratic = waveform_arguments['frequency_nodes_quadratic']
- reference_frequency = getattr(waveform_arguments,
- 'reference_frequency', 20.0)
- versions = dict(IMRPhenomPv2=lalsim.IMRPhenomPv2_V)
- version = versions[getattr(waveform_arguments, 'version', 'IMRPhenomPv2')]
+ reference_frequency = waveform_arguments['reference_frequency']
+ approximant = lalsim_GetApproximantFromString(
+ waveform_arguments['approximant'])
luminosity_distance = luminosity_distance * 1e6 * utils.parsec
mass_1 = mass_1 * utils.solar_mass
mass_2 = mass_2 * utils.solar_mass
- if tilt_1 == 0 and tilt_2 == 0:
- spin_1x = 0
- spin_1y = 0
- spin_1z = a_1
- spin_2x = 0
- spin_2y = 0
- spin_2z = a_2
- iota = theta_jn
- else:
- iota, spin_1x, spin_1y, spin_1z, spin_2x, spin_2y, spin_2z = \
- transform_precessing_spins(
- theta_jn, phi_jl, tilt_1, tilt_2, phi_12, a_1, a_2, mass_1,
- mass_2, reference_frequency, phase)
-
- chi_1_l, chi_2_l, chi_p, theta_jn, alpha, phase_aligned, zeta =\
- lalsim_SimIMRPhenomPCalculateModelParametersFromSourceFrame(
- mass_1, mass_2, reference_frequency, phase, iota, spin_1x,
- spin_1y, spin_1z, spin_2x, spin_2y, spin_2z, version)
+ waveform_dictionary = lal.CreateDict()
+ lalsim_SimInspiralWaveformParamsInsertTidalLambda1(
+ waveform_dictionary, lambda_1)
+ lalsim_SimInspiralWaveformParamsInsertTidalLambda2(
+ waveform_dictionary, lambda_2)
+
+ 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)
+
+ h_linear_plus, h_linear_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_nodes_linear)
+
+ h_quadratic_plus, h_quadratic_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_nodes_quadratic)
waveform_polarizations = dict()
-
- h_linear_plus, h_linear_cross = lalsim_SimIMRPhenomPFrequencySequence(
- frequency_nodes_linear, chi_1_l, chi_2_l, chi_p, theta_jn,
- mass_1, mass_2, luminosity_distance,
- alpha, phase_aligned, reference_frequency, version)
- h_quadratic_plus, h_quadratic_cross = lalsim_SimIMRPhenomPFrequencySequence(
- frequency_nodes_quadratic, chi_1_l, chi_2_l, chi_p, theta_jn,
- mass_1, mass_2, luminosity_distance,
- alpha, phase_aligned, reference_frequency, version)
-
waveform_polarizations['linear'] = dict(
- plus=(np.cos(2 * zeta) * h_linear_plus.data.data +
- np.sin(2 * zeta) * h_linear_cross.data.data),
- cross=(np.cos(2 * zeta) * h_linear_cross.data.data -
- np.sin(2 * zeta) * h_linear_plus.data.data))
-
+ plus=h_linear_plus.data.data, cross=h_linear_cross.data.data)
waveform_polarizations['quadratic'] = dict(
- plus=(np.cos(2 * zeta) * h_quadratic_plus.data.data +
- np.sin(2 * zeta) * h_quadratic_cross.data.data),
- cross=(np.cos(2 * zeta) * h_quadratic_cross.data.data -
- np.sin(2 * zeta) * h_quadratic_plus.data.data))
+ plus=h_quadratic_plus.data.data, cross=h_quadratic_cross.data.data)
return waveform_polarizations
+
+
+def sinegaussian(frequency_array, hrss, Q, frequency, **kwargs):
+ tau = Q / (np.sqrt(2.0) * np.pi * frequency)
+ temp = Q / (4.0 * np.sqrt(np.pi) * frequency)
+ fm = frequency_array - frequency
+ fp = frequency_array + frequency
+
+ h_plus = ((hrss / np.sqrt(temp * (1 + np.exp(-Q**2)))) *
+ ((np.sqrt(np.pi) * tau) / 2.0) *
+ (np.exp(-fm**2 * np.pi**2 * tau**2) +
+ np.exp(-fp**2 * np.pi**2 * tau**2)))
+
+ h_cross = (-1j * (hrss / np.sqrt(temp * (1 - np.exp(-Q**2)))) *
+ ((np.sqrt(np.pi) * tau) / 2.0) *
+ (np.exp(-fm**2 * np.pi**2 * tau**2) -
+ np.exp(-fp**2 * np.pi**2 * tau**2)))
+
+ return{'plus': h_plus, 'cross': h_cross}
+
+
+def supernova(
+ frequency_array, realPCs, imagPCs, file_path, luminosity_distance, **kwargs):
+ """ A supernova NR simulation for injections """
+
+ realhplus, imaghplus, realhcross, imaghcross = np.loadtxt(
+ file_path, usecols=(0, 1, 2, 3), unpack=True)
+
+ # waveform in file at 10kpc
+ scaling = 1e-3 * (10.0 / luminosity_distance)
+
+ h_plus = scaling * (realhplus + 1.0j * imaghplus)
+ h_cross = scaling * (realhcross + 1.0j * imaghcross)
+ return {'plus': h_plus, 'cross': h_cross}
+
+
+def supernova_pca_model(
+ frequency_array, pc_coeff1, pc_coeff2, pc_coeff3, pc_coeff4, pc_coeff5,
+ luminosity_distance, **kwargs):
+ """ Supernova signal model """
+
+ realPCs = kwargs['realPCs']
+ imagPCs = kwargs['imagPCs']
+
+ pc1 = realPCs[:, 0] + 1.0j * imagPCs[:, 0]
+ pc2 = realPCs[:, 1] + 1.0j * imagPCs[:, 1]
+ pc3 = realPCs[:, 2] + 1.0j * imagPCs[:, 2]
+ pc4 = realPCs[:, 3] + 1.0j * imagPCs[:, 3]
+ pc5 = realPCs[:, 4] + 1.0j * imagPCs[:, 5]
+
+ # file at 10kpc
+ scaling = 1e-23 * (10.0 / luminosity_distance)
+
+ h_plus = scaling * (pc_coeff1 * pc1 + pc_coeff2 * pc2 + pc_coeff3 * pc3 +
+ pc_coeff4 * pc4 + pc_coeff5 * pc5)
+ h_cross = scaling * (pc_coeff1 * pc1 + pc_coeff2 * pc2 + pc_coeff3 * pc3 +
+ pc_coeff4 * pc4 + pc_coeff5 * pc5)
+
+ return {'plus': h_plus, 'cross': h_cross}
diff --git a/bilby/gw/utils.py b/bilby/gw/utils.py
index d7b56d453..16937ebae 100644
--- a/bilby/gw/utils.py
+++ b/bilby/gw/utils.py
@@ -18,6 +18,7 @@ except ImportError:
" not be able to use some of the prebuilt functions.")
try:
+ import lal
import lalsimulation as lalsim
except ImportError:
logger.warning("You do not have lalsuite installed currently. You will"
@@ -688,8 +689,33 @@ def lalsim_SimInspiralFD(
longitude_ascending_nodes, eccentricity, mean_per_ano, delta_frequency,
minimum_frequency, maximum_frequency, reference_frequency,
waveform_dictionary, approximant):
+ """
+ Safely call lalsimulation.SimInspiralFD
+
+ Parameters
+ ----------
+ phase: float, int
+ mass_1: float, int
+ mass_2: float, int
+ spin_1x: float, int
+ spin_1y: float, int
+ spin_1z: float, int
+ spin_2x: float, int
+ spin_2y: float, int
+ spin_2z: float, int
+ reference_frequency: float, int
+ luminosity_distance: float, int
+ iota: float, int
+ longitude_ascending_nodes: float, int
+ eccentricity: float, int
+ mean_per_ano: float, int
+ delta_frequency: float, int
+ minimum_frequency: float, int
+ maximum_frequency: float, int
+ waveform_dictionary: None, lal.Dict
+ approximant: int, str
+ """
- # Convert values to floats
[mass_1, mass_2, spin_1x, spin_1y, spin_1z, spin_2x, spin_2y, spin_2z,
luminosity_distance, iota, phase, longitude_ascending_nodes,
eccentricity, mean_per_ano, delta_frequency, minimum_frequency,
@@ -699,8 +725,11 @@ def lalsim_SimInspiralFD(
eccentricity, mean_per_ano, delta_frequency, minimum_frequency,
maximum_frequency, reference_frequency)
- # Note, this is the approximant number returns by GetApproximantFromString
- if isinstance(approximant, int) is False:
+ if isinstance(approximant, int):
+ pass
+ elif isinstance(approximant, str):
+ approximant = lalsim_GetApproximantFromString(approximant)
+ else:
raise ValueError("approximant not an int")
return lalsim.SimInspiralFD(
@@ -717,8 +746,33 @@ def lalsim_SimInspiralChooseFDWaveform(
longitude_ascending_nodes, eccentricity, mean_per_ano, delta_frequency,
minimum_frequency, maximum_frequency, reference_frequency,
waveform_dictionary, approximant):
+ """
+ Safely call lalsimulation.SimInspiralChooseFDWaveform
+
+ Parameters
+ ----------
+ phase: float, int
+ mass_1: float, int
+ mass_2: float, int
+ spin_1x: float, int
+ spin_1y: float, int
+ spin_1z: float, int
+ spin_2x: float, int
+ spin_2y: float, int
+ spin_2z: float, int
+ reference_frequency: float, int
+ luminosity_distance: float, int
+ iota: float, int
+ longitude_ascending_nodes: float, int
+ eccentricity: float, int
+ mean_per_ano: float, int
+ delta_frequency: float, int
+ minimum_frequency: float, int
+ maximum_frequency: float, int
+ waveform_dictionary: None, lal.Dict
+ approximant: int, str
+ """
- # Convert values to floats
[mass_1, mass_2, spin_1x, spin_1y, spin_1z, spin_2x, spin_2y, spin_2z,
luminosity_distance, iota, phase, longitude_ascending_nodes,
eccentricity, mean_per_ano, delta_frequency, minimum_frequency,
@@ -728,8 +782,11 @@ def lalsim_SimInspiralChooseFDWaveform(
eccentricity, mean_per_ano, delta_frequency, minimum_frequency,
maximum_frequency, reference_frequency)
- # Note, this is the approximant number returns by GetApproximantFromString
- if isinstance(approximant, int) is False:
+ if isinstance(approximant, int):
+ pass
+ elif isinstance(approximant, str):
+ approximant = lalsim_GetApproximantFromString(approximant)
+ else:
raise ValueError("approximant not an int")
return lalsim.SimInspiralChooseFDWaveform(
@@ -740,31 +797,53 @@ def lalsim_SimInspiralChooseFDWaveform(
waveform_dictionary, approximant)
-def lalsim_SimIMRPhenomPCalculateModelParametersFromSourceFrame(
- mass_1, mass_2, reference_frequency, phase, iota, spin_1x,
- spin_1y, spin_1z, spin_2x, spin_2y, spin_2z, version):
- [mass_1, mass_2, reference_frequency, phase, iota, spin_1x,
- spin_1y, spin_1z, spin_2x, spin_2y, spin_2z] = convert_args_list_to_float(
- mass_1, mass_2, reference_frequency, phase, iota, spin_1x,
- spin_1y, spin_1z, spin_2x, spin_2y, spin_2z)
- return lalsim.SimIMRPhenomPCalculateModelParametersFromSourceFrame(
- mass_1, mass_2, reference_frequency, phase, iota, spin_1x,
- spin_1y, spin_1z, spin_2x, spin_2y, spin_2z, version)
-
-
-def lalsim_SimIMRPhenomPFrequencySequence(
- frequency_nodes, chi_1_l, chi_2_l, chi_p, theta_jn,
- mass_1, mass_2, luminosity_distance,
- alpha, phase_aligned, reference_frequency, version):
- [chi_1_l, chi_2_l, chi_p, theta_jn, mass_1, mass_2, luminosity_distance,
- alpha, phase_aligned, reference_frequency] = convert_args_list_to_float(
- chi_1_l, chi_2_l, chi_p, theta_jn, mass_1, mass_2, luminosity_distance,
- alpha, phase_aligned, reference_frequency)
-
- return lalsim.SimIMRPhenomPFrequencySequence(
- frequency_nodes, chi_1_l, chi_2_l, chi_p, theta_jn, mass_1, mass_2,
- luminosity_distance, alpha, phase_aligned, reference_frequency, version,
- None)
+def 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_array):
+ """
+ Safely call lalsimulation.SimInspiralChooseFDWaveformSequence
+
+ Parameters
+ ----------
+ phase: float, int
+ mass_1: float, int
+ mass_2: float, int
+ spin_1x: float, int
+ spin_1y: float, int
+ spin_1z: float, int
+ spin_2x: float, int
+ spin_2y: float, int
+ spin_2z: float, int
+ reference_frequency: float, int
+ luminosity_distance: float, int
+ iota: float, int
+ waveform_dictionary: None, lal.Dict
+ approximant: int, str
+ frequency_array: np.ndarray, lal.REAL8Vector
+ """
+
+ [mass_1, mass_2, spin_1x, spin_1y, spin_1z, spin_2x, spin_2y, spin_2z,
+ luminosity_distance, iota, phase, reference_frequency] = convert_args_list_to_float(
+ mass_1, mass_2, spin_1x, spin_1y, spin_1z, spin_2x, spin_2y, spin_2z,
+ luminosity_distance, iota, phase, reference_frequency)
+
+ if isinstance(approximant, int):
+ pass
+ elif isinstance(approximant, str):
+ approximant = lalsim_GetApproximantFromString(approximant)
+ else:
+ raise ValueError("approximant not an int")
+
+ if not isinstance(frequency_array, lal.REAL8Vector):
+ old_frequency_array = frequency_array.copy()
+ frequency_array = lal.CreateREAL8Vector(len(old_frequency_array))
+ frequency_array.data = old_frequency_array
+
+ return 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_array)
def lalsim_SimInspiralWaveformParamsInsertTidalLambda1(
diff --git a/examples/injection_examples/roq_example.py b/examples/injection_examples/roq_example.py
index b98f4f2bf..cf6a28250 100644
--- a/examples/injection_examples/roq_example.py
+++ b/examples/injection_examples/roq_example.py
@@ -69,12 +69,11 @@ ifos.inject_signal(waveform_generator=waveform_generator,
# make ROQ waveform generator
search_waveform_generator = bilby.gw.waveform_generator.WaveformGenerator(
duration=duration, sampling_frequency=sampling_frequency,
- frequency_domain_source_model=bilby.gw.source.roq,
- waveform_arguments=dict(frequency_nodes_linear=freq_nodes_linear,
- frequency_nodes_quadratic=freq_nodes_quadratic,
- reference_frequency=20. * scale_factor,
- minimum_frequency=20. * scale_factor,
- approximant='IMRPhenomPv2'),
+ frequency_domain_source_model=bilby.gw.source.binary_black_hole_roq,
+ waveform_arguments=dict(
+ frequency_nodes_linear=freq_nodes_linear,
+ frequency_nodes_quadratic=freq_nodes_quadratic,
+ reference_frequency=20. * scale_factor, approximant='IMRPhenomPv2'),
parameter_conversion=bilby.gw.conversion.convert_to_lal_binary_black_hole_parameters)
# Here we add constraints on chirp mass and mass ratio to the prior, these are
diff --git a/test/gw_utils_test.py b/test/gw_utils_test.py
index 90e67fd0d..b8d1838ca 100644
--- a/test/gw_utils_test.py
+++ b/test/gw_utils_test.py
@@ -38,6 +38,10 @@ class TestGWUtils(unittest.TestCase):
self.assertTrue(np.all(psd == (freq_data * 2 * df ** 0.5)**2))
def test_time_delay_from_geocenter(self):
+ """
+ The difference in the two detector case is due to rounding error.
+ Different hardware gives different numbers in the last decimal place.
+ """
det1 = np.array([0.1, 0.2, 0.3])
det2 = np.array([0.1, 0.2, 0.5])
ra = 0.5
@@ -45,9 +49,9 @@ class TestGWUtils(unittest.TestCase):
time = 10
self.assertEqual(
gwutils.time_delay_geocentric(det1, det1, ra, dec, time), 0)
- self.assertEqual(
+ self.assertAlmostEqual(
gwutils.time_delay_geocentric(det1, det2, ra, dec, time),
- 1.3253791114055397e-10)
+ 1.3253791114055397e-10, 14)
def test_get_polarization_tensor(self):
ra = 1
@@ -171,16 +175,15 @@ class TestGWUtils(unittest.TestCase):
self.assertEqual(type(a[0]), lal.COMPLEX16FrequencySeries)
self.assertEqual(type(a[1]), lal.COMPLEX16FrequencySeries)
- with self.assertRaises(ValueError):
- a = gwutils.lalsim_SimInspiralChooseFDWaveform(
+ with self.assertRaises(RuntimeError):
+ _ = gwutils.lalsim_SimInspiralChooseFDWaveform(
35.2, 20.4, 0.1, 0.2, 0.2, 0.2, 0.2, 0.1, 1000, 2, 2.3,
- 45., 0.1, 10, 0.01, 10, 1000, 20, None, 'IMRPhenomPV2')
+ 45., 0.1, 10, 0.01, 10, 1000, 20, None, 'Fail')
- def test_lalsim_SimIMRPhenomPCalculateModelParametersFromSourceFrame(self):
- version = lalsim.IMRPhenomPv2_V
- a = gwutils.lalsim_SimIMRPhenomPCalculateModelParametersFromSourceFrame(
- 25.6, 12.2, 50, 0.2, 0, 0, 0, 0, 0, 0, 0, version)
- self.assertEqual(len(a), 7)
+ with self.assertRaises(ValueError):
+ _ = gwutils.lalsim_SimInspiralChooseFDWaveform(
+ 35.2, 20.4, 0.1, 0.2, 0.2, 0.2, 0.2, 0.1, 1000, 2, 2.3,
+ 45., 0.1, 10, 0.01, 10, 1000, 20, None, 1.5)
if __name__ == '__main__':
--
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