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Commit 3362a0a4 authored by Colm Talbot's avatar Colm Talbot
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TEST: fix waveform typos in likelihood tests

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1 merge request!1268TEST: fix waveform typos in likelihood tests
Pipeline #601379 passed
Stage: initial
Stage: test
Stage: docs
Stage: deploy
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test/gw/likelihood/relative_binning_test.py
+ 2
− 2
View file @ 3362a0a4
......@@ -78,13 +78,13 @@ class TestRelativeBinningLikelihood(unittest.TestCase):
duration=duration, sampling_frequency=sampling_frequency,
frequency_domain_source_model=bilby.gw.source.lal_binary_black_hole,
waveform_arguments=dict(
reference_frequency=fmin, minimum_frequency=fmin, approximant=approximant)
reference_frequency=fmin, minimum_frequency=fmin, waveform_approximant=approximant)
)
bin_wfg = bilby.gw.waveform_generator.WaveformGenerator(
duration=duration, sampling_frequency=sampling_frequency,
frequency_domain_source_model=bilby.gw.source.lal_binary_black_hole_relative_binning,
waveform_arguments=dict(
reference_frequency=fmin, approximant=approximant, minimum_frequency=fmin)
reference_frequency=fmin, waveform_approximant=approximant, minimum_frequency=fmin)
)
ifos.inject_signal(
parameters=self.test_parameters,
......
test/gw/likelihood_test.py
+ 23
− 23
View file @ 3362a0a4
......@@ -341,7 +341,7 @@ class TestROQLikelihood(unittest.TestCase):
waveform_arguments=dict(
reference_frequency=20.0,
minimum_frequency=20.0,
approximant="IMRPhenomPv2",
waveform_approximant="IMRPhenomPv2",
),
)
......@@ -360,7 +360,7 @@ class TestROQLikelihood(unittest.TestCase):
frequency_nodes_quadratic=fnodes_quadratic,
reference_frequency=20.0,
minimum_frequency=20.0,
approximant="IMRPhenomPv2",
waveform_approximant="IMRPhenomPv2",
),
)
......@@ -597,7 +597,7 @@ class TestRescaledROQLikelihood(unittest.TestCase):
frequency_nodes_quadratic=fnodes_quadratic,
reference_frequency=20.0,
minimum_frequency=20.0,
approximant="IMRPhenomPv2",
waveform_approximant="IMRPhenomPv2",
),
)
......@@ -1240,7 +1240,7 @@ class TestMBLikelihood(unittest.TestCase):
("IMRPhenomHM", False, 4, True, 1e-3)
])
def test_matches_original_likelihood(
self, approximant, linear_interpolation, highest_mode, add_cal_errors, tolerance
self, waveform_approximant, linear_interpolation, highest_mode, add_cal_errors, tolerance
):
"""
Check if multi-band likelihood values match original likelihood values
......@@ -1249,7 +1249,7 @@ class TestMBLikelihood(unittest.TestCase):
duration=self.duration, sampling_frequency=self.sampling_frequency,
frequency_domain_source_model=bilby.gw.source.lal_binary_black_hole,
waveform_arguments=dict(
reference_frequency=self.fmin, waveform_approximant=approximant
reference_frequency=self.fmin, waveform_approximant=waveform_approximant
)
)
self.ifos.inject_signal(parameters=self.test_parameters, waveform_generator=wfg)
......@@ -1258,7 +1258,7 @@ class TestMBLikelihood(unittest.TestCase):
duration=self.duration, sampling_frequency=self.sampling_frequency,
frequency_domain_source_model=bilby.gw.source.binary_black_hole_frequency_sequence,
waveform_arguments=dict(
reference_frequency=self.fmin, waveform_approximant=approximant
reference_frequency=self.fmin, waveform_approximant=waveform_approximant
)
)
likelihood = bilby.gw.likelihood.GravitationalWaveTransient(
......@@ -1284,12 +1284,12 @@ class TestMBLikelihood(unittest.TestCase):
"""
Check if larger accuracy factor increases the accuracy.
"""
approximant = "IMRPhenomD"
waveform_approximant = "IMRPhenomD"
wfg = bilby.gw.WaveformGenerator(
duration=self.duration, sampling_frequency=self.sampling_frequency,
frequency_domain_source_model=bilby.gw.source.lal_binary_black_hole,
waveform_arguments=dict(
reference_frequency=self.fmin, waveform_approximant=approximant
reference_frequency=self.fmin, waveform_approximant=waveform_approximant
)
)
self.ifos.inject_signal(parameters=self.test_parameters, waveform_generator=wfg)
......@@ -1298,7 +1298,7 @@ class TestMBLikelihood(unittest.TestCase):
duration=self.duration, sampling_frequency=self.sampling_frequency,
frequency_domain_source_model=bilby.gw.source.binary_black_hole_frequency_sequence,
waveform_arguments=dict(
reference_frequency=self.fmin, waveform_approximant=approximant
reference_frequency=self.fmin, waveform_approximant=waveform_approximant
)
)
likelihood = bilby.gw.likelihood.GravitationalWaveTransient(
......@@ -1330,7 +1330,7 @@ class TestMBLikelihood(unittest.TestCase):
duration=self.duration, sampling_frequency=self.sampling_frequency,
frequency_domain_source_model=bilby.gw.source.binary_black_hole_frequency_sequence,
waveform_arguments=dict(
reference_frequency=self.fmin, approximant="IMRPhenomD"
reference_frequency=self.fmin, waveform_approximant="IMRPhenomD"
)
)
likelihood1 = bilby.gw.likelihood.MBGravitationalWaveTransient(
......@@ -1352,7 +1352,7 @@ class TestMBLikelihood(unittest.TestCase):
duration=self.duration, sampling_frequency=self.sampling_frequency,
frequency_domain_source_model=bilby.gw.source.binary_black_hole_frequency_sequence,
waveform_arguments=dict(
reference_frequency=self.fmin, approximant="IMRPhenomD"
reference_frequency=self.fmin, waveform_approximant="IMRPhenomD"
)
)
with self.assertRaises(TypeError):
......@@ -1368,7 +1368,7 @@ class TestMBLikelihood(unittest.TestCase):
duration=self.duration, sampling_frequency=self.sampling_frequency,
frequency_domain_source_model=bilby.gw.source.binary_black_hole_frequency_sequence,
waveform_arguments=dict(
reference_frequency=self.fmin, approximant="IMRPhenomD"
reference_frequency=self.fmin, waveform_approximant="IMRPhenomD"
)
)
for key in ["chirp_mass", "mass_1", "mass_2"]:
......@@ -1385,12 +1385,12 @@ class TestMBLikelihood(unittest.TestCase):
Check if multiband weights can be saved as a file, and a likelihood object constructed from the weights file
produces the same likelihood value.
"""
approximant = "IMRPhenomD"
waveform_approximant = "IMRPhenomD"
wfg = bilby.gw.WaveformGenerator(
duration=self.duration, sampling_frequency=self.sampling_frequency,
frequency_domain_source_model=bilby.gw.source.lal_binary_black_hole,
waveform_arguments=dict(
reference_frequency=self.fmin, approximant=approximant
reference_frequency=self.fmin, waveform_approximant=waveform_approximant
)
)
self.ifos.inject_signal(
......@@ -1401,7 +1401,7 @@ class TestMBLikelihood(unittest.TestCase):
duration=self.duration, sampling_frequency=self.sampling_frequency,
frequency_domain_source_model=bilby.gw.source.binary_black_hole_frequency_sequence,
waveform_arguments=dict(
reference_frequency=self.fmin, approximant=approximant
reference_frequency=self.fmin, waveform_approximant=waveform_approximant
)
)
likelihood_mb = bilby.gw.likelihood.MBGravitationalWaveTransient(
......@@ -1424,7 +1424,7 @@ class TestMBLikelihood(unittest.TestCase):
duration=self.duration, sampling_frequency=self.sampling_frequency,
frequency_domain_source_model=bilby.gw.source.binary_black_hole_frequency_sequence,
waveform_arguments=dict(
reference_frequency=self.fmin, approximant=approximant
reference_frequency=self.fmin, waveform_approximant=waveform_approximant
)
)
likelihood_mb_from_weights = bilby.gw.likelihood.MBGravitationalWaveTransient(
......@@ -1441,12 +1441,12 @@ class TestMBLikelihood(unittest.TestCase):
"""
Check if a likelihood object constructed from dictionary-like weights produce the same likelihood value
"""
approximant = "IMRPhenomD"
waveform_approximant = "IMRPhenomD"
wfg = bilby.gw.WaveformGenerator(
duration=self.duration, sampling_frequency=self.sampling_frequency,
frequency_domain_source_model=bilby.gw.source.lal_binary_black_hole,
waveform_arguments=dict(
reference_frequency=self.fmin, approximant=approximant
reference_frequency=self.fmin, waveform_approximant=waveform_approximant
)
)
self.ifos.inject_signal(
......@@ -1457,7 +1457,7 @@ class TestMBLikelihood(unittest.TestCase):
duration=self.duration, sampling_frequency=self.sampling_frequency,
frequency_domain_source_model=bilby.gw.source.binary_black_hole_frequency_sequence,
waveform_arguments=dict(
reference_frequency=self.fmin, approximant=approximant
reference_frequency=self.fmin, waveform_approximant=waveform_approximant
)
)
likelihood_mb = bilby.gw.likelihood.MBGravitationalWaveTransient(
......@@ -1474,7 +1474,7 @@ class TestMBLikelihood(unittest.TestCase):
duration=self.duration, sampling_frequency=self.sampling_frequency,
frequency_domain_source_model=bilby.gw.source.binary_black_hole_frequency_sequence,
waveform_arguments=dict(
reference_frequency=self.fmin, approximant=approximant
reference_frequency=self.fmin, waveform_approximant=waveform_approximant
)
)
weights = likelihood_mb.weights
......@@ -1492,7 +1492,7 @@ class TestMBLikelihood(unittest.TestCase):
("IMRPhenomHM", False, 4, False, 5e-3),
])
def test_matches_original_likelihood_low_maximum_frequency(
self, approximant, linear_interpolation, highest_mode, add_cal_errors, tolerance
self, waveform_approximant, linear_interpolation, highest_mode, add_cal_errors, tolerance
):
"""
Test for maximum frequency < sampling frequency / 2
......@@ -1504,7 +1504,7 @@ class TestMBLikelihood(unittest.TestCase):
duration=self.duration, sampling_frequency=self.sampling_frequency,
frequency_domain_source_model=bilby.gw.source.lal_binary_black_hole,
waveform_arguments=dict(
reference_frequency=self.fmin, approximant=approximant
reference_frequency=self.fmin, waveform_approximant=waveform_approximant
)
)
self.ifos.inject_signal(parameters=self.test_parameters, waveform_generator=wfg)
......@@ -1513,7 +1513,7 @@ class TestMBLikelihood(unittest.TestCase):
duration=self.duration, sampling_frequency=self.sampling_frequency,
frequency_domain_source_model=bilby.gw.source.binary_black_hole_frequency_sequence,
waveform_arguments=dict(
reference_frequency=self.fmin, approximant=approximant
reference_frequency=self.fmin, waveform_approximant=waveform_approximant
)
)
likelihood = bilby.gw.likelihood.GravitationalWaveTransient(
......
test/gw/source_test.py
+ 1
− 1
View file @ 3362a0a4
......@@ -306,7 +306,7 @@ class TestROQBBH(unittest.TestCase):
frequency_nodes_quadratic=fnodes_quadratic,
reference_frequency=50.0,
minimum_frequency=20.0,
approximant="IMRPhenomPv2",
waveform_approximant="IMRPhenomPv2",
)
self.frequency_array = bilby.core.utils.create_frequency_series(2048, 4)
......
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