Resolve "add neutron star merger to examples"

I added the lal_binary_neutron_star model with an example file binary_neutron_star_example.py . I had to include an import lal in the file source.py to add tidal deformabilities.

For the bns approximants TaylorF2 and IMRPhenomD_NRTdidal, the parameters tilt_1, phi_12, tilt_2, phi_jl must be set to zero, since these can only handle aligned spins.

examples/injection_examples/binary_neutron_star_example.py

+#!/bin/python
+"""
+Tutorial to demonstrate running parameter estimation on a binary neutron star system taking into account tidal deformabilities.
+
+This example estimates the masses using a uniform prior in both component masses and also estimates the tidal deformabilities
+using a uniform prior in both tidal deformabilities
+"""
+
+from __future__ import division, print_function
+
+import numpy as np
+
+import tupak
+
+# Specify the output directory and the name of the simulation.
+outdir = 'outdir'
+label = 'bns_example'
+tupak.core.utils.setup_logger(outdir=outdir, label=label)
+
+# Set up a random seed for result reproducibility.  This is optional!
+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,
+                            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 
+# TaylorF2 waveform, we cut the signal close to the isco frequency
+duration = 8
+sampling_frequency = 2*1570.
+start_time = injection_parameters['geocent_time'] + 2 - duration
+
+# Fixed arguments passed into the source model. The analysis is started at 40 Hz.
+waveform_arguments = dict(waveform_approximant='TaylorF2',
+                          reference_frequency=50.,minimum_frequency=40.0)
+
+# Create the waveform_generator using a LAL BinaryBlackHole source function
+waveform_generator = tupak.gw.WaveformGenerator(duration=duration,
+                                             sampling_frequency=sampling_frequency,
+                                             frequency_domain_source_model=tupak.gw.source.lal_binary_neutron_star,
+                                             parameters=injection_parameters,
+                                             waveform_arguments=waveform_arguments)
+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])
+
+#priors
+priors = tupak.gw.prior.BBHPriorSet()
+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']:
+    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,
+                                              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,
+                           injection_parameters=injection_parameters, outdir=outdir, label=label)
+
+result.plot_corner()
+