From e3a658a4cbb38b6e7013559faab0c6484f2a3274 Mon Sep 17 00:00:00 2001
From: Francisco Javier Hernandez
<francisco.hernandez@ldas-pcdev5.ligo.caltech.edu>
Date: Tue, 4 Sep 2018 01:57:46 -0700
Subject: [PATCH] simplified bns example and deleted not used spins
---
.../binary_neutron_star_example.py | 64 ++++++-------------
tupak/gw/source.py | 27 +++-----
2 files changed, 27 insertions(+), 64 deletions(-)
diff --git a/examples/injection_examples/binary_neutron_star_example.py b/examples/injection_examples/binary_neutron_star_example.py
index 8da23e285..0b27f3942 100644
--- a/examples/injection_examples/binary_neutron_star_example.py
+++ b/examples/injection_examples/binary_neutron_star_example.py
@@ -22,11 +22,9 @@ np.random.seed(88170235)
# We are going to inject a binary neutron star waveform. We first establish a dictionary of parameters that
# includes all of the different waveform parameters, including masses of the two black holes (mass_1, mass_2),
-# spins of both black holes (a_1,a_2) , etc. Take into account the the waveform approximants TaylorF2 and
-# IMRPHenomD_NRTidal can only handle aligned spins, so the parameters tilt_1, tilt_2, phi_12, phi_jl must be
-# set to 0.
-injection_parameters = dict(mass_1=1.5, mass_2=1.3, a_1=0.0, a_2=0.0, tilt_1=0.0, tilt_2=0.0, phi_12=0.0, phi_jl=0,
- luminosity_distance=50., iota=0.4, psi=2.659, phase=1.3, geocent_time=1126259642.413,
+# spins of both black holes (a_1,a_2) , etc.
+injection_parameters = dict(mass_1=1.5, mass_2=1.3, a_1=0.0, a_2=0.0, luminosity_distance=50.,
+ iota=0.4, psi=2.659, phase=1.3, geocent_time=1126259642.413,
ra=1.375, dec=-1.2108, lambda1=400, lambda2=450)
# Set the duration and sampling frequency of the data segment that we're going to inject the signal into. For the
@@ -49,60 +47,36 @@ hf_signal = waveform_generator.frequency_domain_strain()
# Set up interferometers. In this case we'll use three interferometers (LIGO-Hanford (H1), LIGO-Livingston (L1),
# and Virgo (V1)). These default to their design sensitivity and start at 40 Hz.
-H1 = tupak.gw.detector.get_empty_interferometer('H1')
-H1.minimum_frequency = 40
-H1.set_strain_data_from_power_spectral_density(sampling_frequency=sampling_frequency, duration=duration,
- start_time = start_time)
-H1.inject_signal(parameters=injection_parameters,
- injection_polarizations=hf_signal,
- waveform_generator=waveform_generator)
-
-H1.save_data(outdir, label=label)
-H1.plot_data(signal=H1.get_detector_response(hf_signal,injection_parameters), outdir=outdir, label=label)
-
-
-#second interferometer
-L1 = tupak.gw.detector.get_empty_interferometer('L1')
-L1.minimum_frequency = 40
-L1.set_strain_data_from_power_spectral_density(sampling_frequency=sampling_frequency, duration=duration,
- start_time = start_time)
-L1.inject_signal(parameters=injection_parameters,
- injection_polarizations=hf_signal,
- waveform_generator=waveform_generator)
-
-L1.save_data(outdir, label=label)
-L1.plot_data(signal=L1.get_detector_response(hf_signal,injection_parameters), outdir=outdir, label=label)
-
-#third interferometer
-V1 = tupak.gw.detector.get_empty_interferometer('V1')
-V1.minimum_frequency = 40
-V1.set_strain_data_from_power_spectral_density(sampling_frequency=sampling_frequency, duration=duration,
- start_time = start_time)
-V1.inject_signal(parameters=injection_parameters,
- injection_polarizations=hf_signal,
- waveform_generator=waveform_generator)
-
-V1.save_data(outdir, label=label)
-V1.plot_data(signal=V1.get_detector_response(hf_signal,injection_parameters), outdir=outdir, label=label)
-IFOs = np.array([H1,L1,V1])
+interferometers = tupak.gw.detector.InterferometerList(['H1', 'L1', 'V1'])
+for interferometer in interferometers:
+ interferometer.minimum_frequency = 40
+interferometers.set_strain_data_from_power_spectral_densities(
+ sampling_frequency=sampling_frequency, duration=duration,
+ start_time = start_time)
+interferometers.inject_signal(parameters=injection_parameters, waveform_generator=waveform_generator)
+
#priors
priors = tupak.gw.prior.BBHPriorSet()
+priors.pop('tilt_1')
+priors.pop('tilt_2')
+priors.pop('phi_12')
+priors.pop('phi_jl')
priors['lambda1'] = tupak.prior.Uniform(0, 3000, '$\\Lambda_1$')
priors['lambda2'] = tupak.prior.Uniform(0, 3000, '$\\Lambda_2$')
priors['mass_1'] = tupak.prior.Uniform(1, 2, '$m_1$')
priors['mass_2'] = tupak.prior.Uniform(1, 2, '$m_2$')
-for key in ['a_1', 'a_2', 'tilt_1', 'tilt_2', 'phi_12', 'phi_jl', 'psi',
- 'geocent_time','ra','dec','iota','luminosity_distance','phase']:
+for key in ['a_1', 'a_2', 'psi','geocent_time','ra','dec',
+ 'iota','luminosity_distance','phase']:
priors[key] = injection_parameters[key]
# Initialise the likelihood by passing in the interferometer data (IFOs) and the waveoform generator
-likelihood = tupak.gw.GravitationalWaveTransient(interferometers=IFOs, waveform_generator=waveform_generator,
+likelihood = tupak.gw.GravitationalWaveTransient(interferometers=interferometers, waveform_generator=waveform_generator,
time_marginalization=False, phase_marginalization=False,
distance_marginalization=False, prior=priors)
# Run sampler. In this case we're going to use the `nestle` sampler
-result = tupak.run_sampler(likelihood=likelihood, priors=priors, sampler='nestle', npoints=500,
+result = tupak.run_sampler(likelihood=likelihood, priors=priors, sampler='nestle', npoints=1000,
injection_parameters=injection_parameters, outdir=outdir, label=label)
result.plot_corner()
diff --git a/tupak/gw/source.py b/tupak/gw/source.py
index b8f70fa77..38ae719a2 100644
--- a/tupak/gw/source.py
+++ b/tupak/gw/source.py
@@ -254,7 +254,7 @@ def supernova_pca_model(
return {'plus': h_plus, 'cross': h_cross}
def lal_binary_neutron_star(
- frequency_array, mass_1, mass_2, luminosity_distance, a_1, tilt_1, phi_12, a_2, tilt_2, phi_jl,
+ frequency_array, mass_1, mass_2, luminosity_distance, a_1, a_2,
iota, phase, ra, dec, geocent_time, psi, lambda1, lambda2, **kwargs):
""" A Binary Black Hole waveform model using lalsimulation
@@ -269,17 +269,9 @@ def lal_binary_neutron_star(
luminosity_distance: float
The luminosity distance in megaparsec
a_1: float
- Dimensionless primary spin magnitude
- tilt_1: float
- Primary tilt angle. TaylorF2 and IMRPhenomD_NRTidal only handle aligned spin, set this value to 0
- phi_12: float
- TaylorF2 and IMRPhenomD_NRTidal only handle aligned spin, set this value to 0
+ Dimensionless spin magnitude
a_2: float
Dimensionless secondary spin magnitude.
- tilt_2: float
- Secondary tilt angle. TaylorF2 and IMRPhenomD_NRTidal only handle aligned spin, set this value to 0
- phi_jl: float
- TaylorF2 and IMRPhenomD_NRTidal only handle aligned spin, set this value to 0
iota: float
Orbital inclination
phase: float
@@ -319,15 +311,12 @@ def lal_binary_neutron_star(
mass_1 = mass_1 * utils.solar_mass
mass_2 = mass_2 * utils.solar_mass
- if tilt_1 == 0 and tilt_2 == 0 and phi_12 == 0 and phi_jl==0:
- spin_1x = 0
- spin_1y = 0
- spin_1z = a_1
- spin_2x = 0
- spin_2y = 0
- spin_2z = a_2
- else:
- raise ValueError('The waveform approximants TaylorF2 and IMRPhenomD_NRTidal only support aligned spins')
+ spin_1x = 0
+ spin_1y = 0
+ spin_1z = a_1
+ spin_2x = 0
+ spin_2y = 0
+ spin_2z = a_2
longitude_ascending_nodes = 0.0
eccentricity = 0.0
--
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