From f1db65dae7b1f09529fb670c29e94ef3e1b2d7bc Mon Sep 17 00:00:00 2001
From: Colm Talbot <colm.talbot@ligo.org>
Date: Tue, 1 Nov 2022 10:52:01 -0700
Subject: [PATCH] add test of optimization of fiducial values
---
test/gw/likelihood/relative_binning.py | 41 ++++++++++++++++++++++----
1 file changed, 35 insertions(+), 6 deletions(-)
diff --git a/test/gw/likelihood/relative_binning.py b/test/gw/likelihood/relative_binning.py
index 57cead398..7277033bb 100644
--- a/test/gw/likelihood/relative_binning.py
+++ b/test/gw/likelihood/relative_binning.py
@@ -8,11 +8,11 @@ from parameterized import parameterized
class TestMBLikelihood(unittest.TestCase):
def setUp(self):
- duration = 256
+ duration = 16
fmin = 20
sampling_frequency = 8192
self.test_parameters = dict(
- chirp_mass=1.3,
+ chirp_mass=13,
mass_ratio=0.5,
a_1=0.3,
a_2=0.4,
@@ -20,7 +20,7 @@ class TestMBLikelihood(unittest.TestCase):
tilt_2=0.2,
phi_12=1.0,
phi_jl=2.0,
- luminosity_distance=200.0,
+ luminosity_distance=2000.0,
theta_jn=0.4,
psi=0.659,
phase=1.3,
@@ -59,7 +59,8 @@ class TestMBLikelihood(unittest.TestCase):
priors = bilby.gw.prior.BBHPriorDict()
priors.pop("mass_1")
priors.pop("mass_2")
- priors["chirp_mass"] = bilby.core.prior.Uniform(1.29, 1.31)
+ # priors["chirp_mass"] = bilby.core.prior.Uniform(1.29, 1.31)
+ priors["chirp_mass"] = bilby.core.prior.Uniform(12, 14)
priors["mass_ratio"] = bilby.core.prior.Uniform(0.125, 1)
priors["geocent_time"] = bilby.core.prior.Uniform(
self.test_parameters['geocent_time'] - 0.1,
@@ -81,8 +82,11 @@ class TestMBLikelihood(unittest.TestCase):
reference_frequency=fmin, approximant=approximant, minimum_frequency=fmin)
)
ifos.inject_signal(
- parameters=self.test_parameters, waveform_generator=non_bin_wfg
+ parameters=self.test_parameters,
+ waveform_generator=non_bin_wfg,
+ raise_error=False,
)
+ self.ifos = ifos
self.non_bin = bilby.gw.likelihood.GravitationalWaveTransient(
interferometers=ifos, waveform_generator=deepcopy(non_bin_wfg),
@@ -97,7 +101,8 @@ class TestMBLikelihood(unittest.TestCase):
)
self.non_bin.parameters.update(self.test_parameters)
self.reference_ln_l = self.non_bin.log_likelihood_ratio()
- print(self.binned.bin_freqs)
+ self.bin_wfg = bin_wfg
+ self.priors = priors
def tearDown(self):
del (
@@ -132,6 +137,30 @@ class TestMBLikelihood(unittest.TestCase):
1.5e-2
)
+ def test_optimization_gives_good_match(self):
+ fiducial_parameters = self.test_parameters.copy()
+ fiducial_parameters["chirp_mass"] *= 0.99
+ priors = self.priors.copy()
+ for key in [
+ "ra", "dec", "geocent_time", "phase", "psi", "theta_jn", "luminosity_distance",
+ "a_1", "a_2", "tilt_1", "tilt_2", "phi_12", "phi_jl",
+ ]:
+ priors[key] = self.test_parameters[key]
+ binned = bilby.gw.likelihood.RelativeBinningGravitationalWaveTransient(
+ interferometers=self.ifos, waveform_generator=deepcopy(self.bin_wfg),
+ priors=priors,
+ fiducial_parameters=fiducial_parameters,
+ epsilon=0.05,
+ update_fiducial_parameters=True,
+ )
+ self.non_bin.parameters.update(self.test_parameters)
+ binned.parameters.update(self.test_parameters)
+ self.assertLess(
+ abs(self.non_bin.log_likelihood_ratio() - binned.log_likelihood_ratio())
+ / self.reference_ln_l,
+ 1.5e-2
+ )
+
if __name__ == "__main__":
unittest.main()
--
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