Fix bns

bilby/gw/source.py

@@ -119,8 +119,8 @@ def lal_binary_neutron_star(
         minimum_frequency=20.0, maximum_frequency=frequency_array[-1])
     a_1 = abs(chi_1)
     a_2 = abs(chi_2)
-    tilt_1 = np.arccos(chi_1)
-    tilt_2 = np.arccos(chi_2)
+    tilt_1 = np.arccos(np.sign(chi_1))
+    tilt_2 = np.arccos(np.sign(chi_2))
     waveform_kwargs.update(kwargs)
     return _base_lal_cbc_fd_waveform(
         frequency_array=frequency_array, mass_1=mass_1, mass_2=mass_2,

examples/injection_examples/binary_neutron_star_example.py

@@ -85,11 +85,11 @@ priors['delta_lambda'] = bilby.core.prior.Uniform(
 likelihood = bilby.gw.GravitationalWaveTransient(
     interferometers=interferometers, waveform_generator=waveform_generator,
     time_marginalization=False, phase_marginalization=False,
-    distance_marginalization=False, prior=priors)
+    distance_marginalization=False, priors=priors)
 
 # Run sampler.  In this case we're going to use the `nestle` sampler
 result = bilby.run_sampler(
-    likelihood=likelihood, priors=priors, sampler='nestle', npoints=1000,
+    likelihood=likelihood, priors=priors, sampler='nestle', npoints=100,
     injection_parameters=injection_parameters, outdir=outdir, label=label,
     conversion_function=bilby.gw.conversion.generate_all_bns_parameters)
 

test/gw_source_test.py

@@ -10,9 +10,9 @@ class TestLalBBH(unittest.TestCase):
 
     def setUp(self):
         self.parameters = dict(
-            mass_1=30.0, mass_2=30.0, luminosity_distance=400.0, a_1=0.0,
-            tilt_1=0.0, phi_12=0.0, a_2=0.0, tilt_2=0.0, phi_jl=0.0, theta_jn=0.0,
-            phase=0.0)
+            mass_1=30.0, mass_2=30.0, luminosity_distance=400.0, a_1=0.4,
+            tilt_1=0.2, phi_12=1.0, a_2=0.8, tilt_2=2.7, phi_jl=2.9,
+            theta_jn=0.3, phase=0.0)
         self.waveform_kwargs = dict(
             waveform_approximant='IMRPhenomPv2', reference_frequency=50.0,
             minimum_frequency=20.0)
@@ -53,8 +53,8 @@ class TestLalBNS(unittest.TestCase):
 
     def setUp(self):
         self.parameters = dict(
-            mass_1=1.4, mass_2=1.4, luminosity_distance=400.0, chi_1=0.0,
-            chi_2=0.0, theta_jn=0.0, phase=0.0, lambda_1=0.0, lambda_2=0.0)
+            mass_1=1.4, mass_2=1.4, luminosity_distance=400.0, chi_1=0.4,
+            chi_2=0.3, theta_jn=1.7, phase=0.0, lambda_1=100.0, lambda_2=100.0)
         self.waveform_kwargs = dict(
             waveform_approximant='TaylorF2', reference_frequency=50.0,
             minimum_frequency=20.0)