diff --git a/bilby/gw/source.py b/bilby/gw/source.py
index 9c6dff23613549cd7788b05ee5c571af79091179..b8d5c2e3e580820dc210eb6ea0c551082bebbb00 100644
--- a/bilby/gw/source.py
+++ b/bilby/gw/source.py
@@ -6,10 +6,15 @@ from .conversion import bilby_to_lalsimulation_spins
from .utils import (lalsim_GetApproximantFromString,
lalsim_SimInspiralFD,
lalsim_SimInspiralChooseFDWaveform,
- lalsim_SimInspiralWaveformParamsInsertTidalLambda1,
- lalsim_SimInspiralWaveformParamsInsertTidalLambda2,
lalsim_SimInspiralChooseFDWaveformSequence)
+UNUSED_KWARGS_MESSAGE = """There are unused waveform kwargs. This is deprecated behavior and will
+result in an error in future releases. Make sure all of the waveform kwargs are correctly
+spelled.
+
+Unused waveform_kwargs: {waveform_kwargs}
+"""
+
def gwsignal_binary_black_hole(frequency_array, mass_1, mass_2, luminosity_distance, a_1, tilt_1,
phi_12, a_2, tilt_2, phi_jl, theta_jn, phase, **kwargs):
@@ -480,6 +485,54 @@ def lal_eccentric_binary_black_hole_no_spins(
eccentricity=eccentricity, **waveform_kwargs)
+def set_waveform_dictionary(waveform_kwargs, lambda_1=0, lambda_2=0):
+ """
+ Add keyword arguments to the :code:`LALDict` object.
+
+ Parameters
+ ==========
+ waveform_kwargs: dict
+ A dictionary of waveform kwargs. This is modified in place to remove used arguments.
+ lambda_1: float
+ Dimensionless tidal deformability of the primary object.
+ lambda_2: float
+ Dimensionless tidal deformability of the primary object.
+
+ Returns
+ =======
+ waveform_dictionary: lal.LALDict
+ The lal waveform dictionary. This is either taken from the waveform_kwargs or created
+ internally.
+ """
+ import lalsimulation as lalsim
+ from lal import CreateDict
+ waveform_dictionary = waveform_kwargs.pop('lal_waveform_dictionary', CreateDict())
+ waveform_kwargs["TidalLambda1"] = lambda_1
+ waveform_kwargs["TidalLambda2"] = lambda_2
+ waveform_kwargs["NumRelData"] = waveform_kwargs.pop("numerical_relativity_data", None)
+
+ for key in [
+ "pn_spin_order", "pn_tidal_order", "pn_phase_order", "pn_amplitude_order"
+ ]:
+ waveform_kwargs[key[:2].upper() + key[3:].title().replace('_', '')] = waveform_kwargs.pop(key)
+
+ for key in list(waveform_kwargs.keys()).copy():
+ func = getattr(lalsim, f"SimInspiralWaveformParamsInsert{key}", None)
+ if func is None:
+ continue
+ value = waveform_kwargs.pop(key)
+ if func is not None and value is not None:
+ func(waveform_dictionary, value)
+
+ mode_array = waveform_kwargs.pop("mode_array", None)
+ if mode_array is not None:
+ 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)
+ return waveform_dictionary
+
+
def _base_lal_cbc_fd_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,
@@ -525,22 +578,16 @@ def _base_lal_cbc_fd_waveform(
=======
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']
- minimum_frequency = waveform_kwargs['minimum_frequency']
- maximum_frequency = waveform_kwargs['maximum_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']
+ waveform_approximant = waveform_kwargs.pop('waveform_approximant')
+ reference_frequency = waveform_kwargs.pop('reference_frequency')
+ minimum_frequency = waveform_kwargs.pop('minimum_frequency')
+ maximum_frequency = waveform_kwargs.pop('maximum_frequency')
+ catch_waveform_errors = waveform_kwargs.pop('catch_waveform_errors')
pn_amplitude_order = waveform_kwargs['pn_amplitude_order']
- waveform_dictionary = waveform_kwargs.get(
- 'lal_waveform_dictionary', lal.CreateDict()
- )
+ waveform_dictionary = set_waveform_dictionary(waveform_kwargs, lambda_1, lambda_2)
approximant = lalsim_GetApproximantFromString(waveform_approximant)
if pn_amplitude_order != 0:
@@ -567,35 +614,6 @@ def _base_lal_cbc_fd_waveform(
longitude_ascending_nodes = 0.0
mean_per_ano = 0.0
- 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, float(lambda_1))
- lalsim_SimInspiralWaveformParamsInsertTidalLambda2(
- waveform_dictionary, float(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)
-
if lalsim.SimInspiralImplementedFDApproximants(approximant):
wf_func = lalsim_SimInspiralChooseFDWaveform
else:
@@ -650,6 +668,9 @@ def _base_lal_cbc_fd_waveform(
h_plus[frequency_bounds] *= time_shift
h_cross[frequency_bounds] *= time_shift
+ if len(waveform_kwargs) > 0:
+ logger.warning(UNUSED_KWARGS_MESSAGE.format(waveform_kwargs))
+
return dict(plus=h_plus, cross=h_cross)
@@ -705,6 +726,7 @@ def lal_binary_black_hole_relative_binning(
waveform_kwargs.update(kwargs)
if fiducial == 1:
+ _ = waveform_kwargs.pop("frequency_bin_edges", None)
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,
@@ -712,6 +734,8 @@ def lal_binary_black_hole_relative_binning(
phi_12=phi_12, lambda_1=0.0, lambda_2=0.0, **waveform_kwargs)
else:
+ _ = waveform_kwargs.pop("minimum_frequency", None)
+ _ = waveform_kwargs.pop("maximum_frequency", None)
waveform_kwargs["frequencies"] = waveform_kwargs.pop("frequency_bin_edges")
return _base_waveform_frequency_sequence(
frequency_array=frequency_array, mass_1=mass_1, mass_2=mass_2,
@@ -748,6 +772,8 @@ def lal_binary_neutron_star_relative_binning(
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:
+ _ = waveform_kwargs.pop("minimum_frequency", None)
+ _ = waveform_kwargs.pop("maximum_frequency", None)
waveform_kwargs["frequencies"] = waveform_kwargs.pop("frequency_bin_edges")
return _base_waveform_frequency_sequence(
frequency_array=frequency_array, mass_1=mass_1, mass_2=mass_2,
@@ -822,19 +848,21 @@ def _base_roq_waveform(
if 'frequency_nodes' not in waveform_arguments:
size_linear = len(waveform_arguments['frequency_nodes_linear'])
frequency_nodes_combined = np.hstack(
- (waveform_arguments['frequency_nodes_linear'],
- waveform_arguments['frequency_nodes_quadratic'])
+ (waveform_arguments.pop('frequency_nodes_linear'),
+ waveform_arguments.pop('frequency_nodes_quadratic'))
)
frequency_nodes_unique, original_indices = np.unique(
frequency_nodes_combined, return_inverse=True
)
linear_indices = original_indices[:size_linear]
quadratic_indices = original_indices[size_linear:]
- waveform_arguments['frequency_nodes'] = frequency_nodes_unique
- waveform_arguments['linear_indices'] = linear_indices
- waveform_arguments['quadratic_indices'] = quadratic_indices
-
- waveform_arguments['frequencies'] = waveform_arguments['frequency_nodes']
+ waveform_arguments['frequencies'] = frequency_nodes_unique
+ else:
+ linear_indices = waveform_arguments.pop("linear_indices")
+ quadratic_indices = waveform_arguments.pop("quadratic_indices")
+ for key in ["frequency_nodes_linear", "frequency_nodes_quadratic"]:
+ _ = waveform_arguments.pop(key, None)
+ waveform_arguments['frequencies'] = waveform_arguments.pop('frequency_nodes')
waveform_polarizations = _base_waveform_frequency_sequence(
frequency_array=frequency_array, mass_1=mass_1, mass_2=mass_2,
luminosity_distance=luminosity_distance, theta_jn=theta_jn, phase=phase,
@@ -843,12 +871,12 @@ def _base_roq_waveform(
return {
'linear': {
- 'plus': waveform_polarizations['plus'][waveform_arguments['linear_indices']],
- 'cross': waveform_polarizations['cross'][waveform_arguments['linear_indices']]
+ 'plus': waveform_polarizations['plus'][linear_indices],
+ 'cross': waveform_polarizations['cross'][linear_indices]
},
'quadratic': {
- 'plus': waveform_polarizations['plus'][waveform_arguments['quadratic_indices']],
- 'cross': waveform_polarizations['cross'][waveform_arguments['quadratic_indices']]
+ 'plus': waveform_polarizations['plus'][quadratic_indices],
+ 'cross': waveform_polarizations['cross'][quadratic_indices]
}
}
@@ -1059,49 +1087,13 @@ def _base_waveform_frequency_sequence(
Dict containing plus and cross modes evaluated at the linear and
quadratic frequency nodes.
"""
- from lal import CreateDict
- import lalsimulation as lalsim
-
- frequencies = waveform_kwargs['frequencies']
- reference_frequency = waveform_kwargs['reference_frequency']
- approximant = lalsim_GetApproximantFromString(waveform_kwargs['waveform_approximant'])
- 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', 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, float(lambda_1))
- lalsim_SimInspiralWaveformParamsInsertTidalLambda2(
- waveform_dictionary, float(lambda_2))
-
- for key, value in waveform_kwargs.items():
- func = getattr(lalsim, "SimInspiralWaveformParamsInsert" + key, None)
- if func is not None:
- func(waveform_dictionary, value)
+ frequencies = waveform_kwargs.pop('frequencies')
+ reference_frequency = waveform_kwargs.pop('reference_frequency')
+ approximant = waveform_kwargs.pop('waveform_approximant')
+ catch_waveform_errors = waveform_kwargs.pop('catch_waveform_errors')
- 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)
+ waveform_dictionary = set_waveform_dictionary(waveform_kwargs, lambda_1, lambda_2)
+ approximant = lalsim_GetApproximantFromString(approximant)
luminosity_distance = luminosity_distance * 1e6 * utils.parsec
mass_1 = mass_1 * utils.solar_mass
@@ -1135,6 +1127,9 @@ def _base_waveform_frequency_sequence(
else:
raise
+ if len(waveform_kwargs) > 0:
+ logger.warning(UNUSED_KWARGS_MESSAGE.format(waveform_kwargs))
+
return dict(plus=h_plus.data.data, cross=h_cross.data.data)
diff --git a/test/gw/likelihood/marginalization_test.py b/test/gw/likelihood/marginalization_test.py
index d7b4f8a59785e695b5b6d58cb5f036c60b4e5101..498ca9fe1fb9f9f6b7fd42956a0a6dc192efd0f6 100644
--- a/test/gw/likelihood/marginalization_test.py
+++ b/test/gw/likelihood/marginalization_test.py
@@ -248,7 +248,6 @@ class TestMarginalizations(unittest.TestCase):
start_time=1126259640,
waveform_arguments=dict(
reference_frequency=20.0,
- minimum_frequency=20.0,
waveform_approximant="IMRPhenomPv2",
frequency_nodes_linear=np.load(f"{roq_dir}/fnodes_linear.npy"),
frequency_nodes_quadratic=np.load(f"{roq_dir}/fnodes_quadratic.npy"),
diff --git a/test/gw/likelihood_test.py b/test/gw/likelihood_test.py
index b12ffd59bdc9101bca7170c5764cd73c7a9eecbb..84298e1d9f6a7cf48b7bde1bb42d50ca4b49790b 100644
--- a/test/gw/likelihood_test.py
+++ b/test/gw/likelihood_test.py
@@ -361,7 +361,6 @@ class TestROQLikelihood(unittest.TestCase):
frequency_nodes_linear=fnodes_linear,
frequency_nodes_quadratic=fnodes_quadratic,
reference_frequency=20.0,
- minimum_frequency=20.0,
waveform_approximant="IMRPhenomPv2",
),
)
@@ -599,7 +598,6 @@ class TestRescaledROQLikelihood(unittest.TestCase):
frequency_nodes_linear=fnodes_linear,
frequency_nodes_quadratic=fnodes_quadratic,
reference_frequency=20.0,
- minimum_frequency=20.0,
waveform_approximant="IMRPhenomPv2",
),
)
diff --git a/test/gw/source_test.py b/test/gw/source_test.py
index 5f5199fd10698993036f21fdfe5517cbf7dcbff7..8f55c5b14be1151a456ad4dcf5f751346f5b8ec5 100644
--- a/test/gw/source_test.py
+++ b/test/gw/source_test.py
@@ -305,7 +305,6 @@ class TestROQBBH(unittest.TestCase):
frequency_nodes_linear=fnodes_linear,
frequency_nodes_quadratic=fnodes_quadratic,
reference_frequency=50.0,
- minimum_frequency=20.0,
waveform_approximant="IMRPhenomPv2",
)
self.frequency_array = bilby.core.utils.create_frequency_series(2048, 4)
@@ -344,15 +343,14 @@ class TestBBHfreqseq(unittest.TestCase):
theta_jn=0.3,
phase=0.0
)
- minimum_frequency = 20.0
+ self.minimum_frequency = 20.0
self.frequency_array = bilby.core.utils.create_frequency_series(2048, 8)
- self.full_frequencies_to_sequence = self.frequency_array >= minimum_frequency
+ self.full_frequencies_to_sequence = self.frequency_array >= self.minimum_frequency
+ self.frequencies = self.frequency_array[self.full_frequencies_to_sequence]
self.waveform_kwargs = dict(
waveform_approximant="IMRPhenomHM",
reference_frequency=50.0,
- minimum_frequency=minimum_frequency,
catch_waveform_errors=True,
- frequencies=self.frequency_array[self.full_frequencies_to_sequence]
)
self.bad_parameters = copy(self.parameters)
self.bad_parameters["mass_1"] = -30.0
@@ -362,12 +360,13 @@ class TestBBHfreqseq(unittest.TestCase):
del self.waveform_kwargs
del self.frequency_array
del self.bad_parameters
+ del self.minimum_frequency
def test_valid_parameters(self):
self.parameters.update(self.waveform_kwargs)
self.assertIsInstance(
bilby.gw.source.binary_black_hole_frequency_sequence(
- self.frequency_array, **self.parameters
+ self.frequency_array, frequencies=self.frequencies, **self.parameters
),
dict
)
@@ -376,7 +375,7 @@ class TestBBHfreqseq(unittest.TestCase):
self.bad_parameters.update(self.waveform_kwargs)
self.assertIsNone(
bilby.gw.source.binary_black_hole_frequency_sequence(
- self.frequency_array, **self.bad_parameters
+ self.frequency_array, frequencies=self.frequencies, **self.bad_parameters
)
)
@@ -386,16 +385,16 @@ class TestBBHfreqseq(unittest.TestCase):
raise_error_parameters["catch_waveform_errors"] = False
with self.assertRaises(Exception):
bilby.gw.source.binary_black_hole_frequency_sequence(
- self.frequency_array, **raise_error_parameters
+ self.frequency_array, frequencies=self.frequencies, **raise_error_parameters
)
def test_match_LalBBH(self):
self.parameters.update(self.waveform_kwargs)
freqseq = bilby.gw.source.binary_black_hole_frequency_sequence(
- self.frequency_array, **self.parameters
+ self.frequency_array, frequencies=self.frequencies, **self.parameters
)
lalbbh = bilby.gw.source.lal_binary_black_hole(
- self.frequency_array, **self.parameters
+ self.frequency_array, minimum_frequency=self.minimum_frequency, **self.parameters
)
self.assertEqual(freqseq.keys(), lalbbh.keys())
for mode in freqseq:
@@ -408,10 +407,10 @@ class TestBBHfreqseq(unittest.TestCase):
parameters.update(self.waveform_kwargs)
parameters['mode_array'] = [[2, 2]]
freqseq = bilby.gw.source.binary_black_hole_frequency_sequence(
- self.frequency_array, **parameters
+ self.frequency_array, frequencies=self.frequencies, **parameters
)
lalbbh = bilby.gw.source.lal_binary_black_hole(
- self.frequency_array, **parameters
+ self.frequency_array, minimum_frequency=self.minimum_frequency, **parameters
)
self.assertEqual(freqseq.keys(), lalbbh.keys())
for mode in freqseq:
@@ -426,10 +425,10 @@ class TestBBHfreqseq(unittest.TestCase):
lalsimulation.SimInspiralWaveformParamsInsertNonGRDChi0(wf_dict, 1.)
parameters['lal_waveform_dictionary'] = wf_dict
freqseq = bilby.gw.source.binary_black_hole_frequency_sequence(
- self.frequency_array, **parameters
+ self.frequency_array, frequencies=self.frequencies, **parameters
)
lalbbh = bilby.gw.source.lal_binary_black_hole(
- self.frequency_array, **parameters
+ self.frequency_array, minimum_frequency=self.minimum_frequency, **parameters
)
self.assertEqual(freqseq.keys(), lalbbh.keys())
for mode in freqseq:
@@ -455,26 +454,26 @@ class TestBNSfreqseq(unittest.TestCase):
lambda_1=1000.0,
lambda_2=1000.0
)
- minimum_frequency = 50.0
+ self.minimum_frequency = 50.0
self.frequency_array = bilby.core.utils.create_frequency_series(2048, 16)
- self.full_frequencies_to_sequence = self.frequency_array >= minimum_frequency
+ self.full_frequencies_to_sequence = self.frequency_array >= self.minimum_frequency
+ self.frequencies = self.frequency_array[self.full_frequencies_to_sequence]
self.waveform_kwargs = dict(
waveform_approximant="IMRPhenomPv2_NRTidal",
reference_frequency=50.0,
- minimum_frequency=minimum_frequency,
- frequencies=self.frequency_array[self.full_frequencies_to_sequence]
)
def tearDown(self):
del self.parameters
del self.waveform_kwargs
del self.frequency_array
+ del self.minimum_frequency
def test_with_valid_parameters(self):
self.parameters.update(self.waveform_kwargs)
self.assertIsInstance(
bilby.gw.source.binary_neutron_star_frequency_sequence(
- self.frequency_array, **self.parameters
+ self.frequency_array, frequencies=self.frequencies, **self.parameters
),
dict
)
@@ -485,16 +484,16 @@ class TestBNSfreqseq(unittest.TestCase):
self.parameters.update(self.waveform_kwargs)
with self.assertRaises(TypeError):
bilby.gw.source.binary_neutron_star_frequency_sequence(
- self.frequency_array, **self.parameters
+ self.frequency_array, frequencies=self.frequencies, **self.parameters
)
def test_match_LalBNS(self):
self.parameters.update(self.waveform_kwargs)
freqseq = bilby.gw.source.binary_neutron_star_frequency_sequence(
- self.frequency_array, **self.parameters
+ self.frequency_array, frequencies=self.frequencies, **self.parameters
)
lalbns = bilby.gw.source.lal_binary_neutron_star(
- self.frequency_array, **self.parameters
+ self.frequency_array, minimum_frequency=self.minimum_frequency, **self.parameters
)
self.assertEqual(freqseq.keys(), lalbns.keys())
for mode in freqseq: