add non tensor example

examples/injection_examples/non_tensor.py

+#!/usr/bin/env python
+"""
+A demonstration of a simple model with more than just the two polarization modes
+allowed in general relativity.
+
+We adapt the sine-Gaussian burst model to include vector polarizations with an
+unknown contribution from the vector modes.
+"""
+from __future__ import division, print_function
+import bilby
+import numpy as np
+
+
+def vector_tensor_sine_gaussian(frequency_array, hrss, Q, frequency, epsilon):
+    """
+    Vector-Tensor sine-Gaussian burst model
+
+    This is just like the bilby.gw.source.sinegaussian function but adds a
+    vector-polarized component.
+
+    Parameters
+    ----------
+    frequency_array: array-like
+        Frequency array on which to calculate the waveform.
+    hrss: float
+    Q: float
+    frequency: float
+    epsilon: float
+        Relative size of the vector modes compared to the tensor modes.
+    """
+    waveform_polarizations = bilby.gw.source.sinegaussian(
+        frequency_array, hrss, Q, frequency, 0, 0, 0, 0)
+
+    waveform_polarizations['x'] = epsilon * waveform_polarizations['plus']
+    waveform_polarizations['y'] = epsilon * waveform_polarizations['cross']
+    return waveform_polarizations
+
+
+duration = 4.
+sampling_frequency = 2048.
+
+outdir = 'outdir'
+label = 'vector_tensor'
+bilby.core.utils.setup_logger(outdir=outdir, label=label)
+
+np.random.seed(170801)
+
+injection_parameters = dict(
+    hrss=1e-22, Q=5.0, frequency=200.0, ra=1.375, dec=-1.2108,
+    geocent_time=1126259642.413, psi=2.659, epsilon=0.2)
+
+waveform_generator =\
+    bilby.gw.waveform_generator.WaveformGenerator(
+        duration=duration, sampling_frequency=sampling_frequency,
+        frequency_domain_source_model=vector_tensor_sine_gaussian)
+
+ifos = bilby.gw.detector.InterferometerList(['H1', 'L1', 'V1'])
+ifos.set_strain_data_from_power_spectral_densities(
+    sampling_frequency=sampling_frequency, duration=duration,
+    start_time=injection_parameters['geocent_time']-3)
+ifos.inject_signal(waveform_generator=waveform_generator,
+                   parameters=injection_parameters)
+
+priors = dict()
+for key in ['psi', 'geocent_time', 'hrss', 'Q', 'frequency']:
+    priors[key] = injection_parameters[key]
+priors['ra'] = bilby.core.prior.Uniform(0, 2 * np.pi, latex_label='$\\alpha$')
+priors['dec'] = bilby.core.prior.Cosine(latex_label='$\\delta$')
+priors['epsilon'] = bilby.core.prior.Uniform(0, 1, latex_label='$\\epsilon$')
+
+vector_tensor_likelihood = bilby.gw.likelihood.GravitationalWaveTransient(
+    interferometers=ifos, waveform_generator=waveform_generator)
+
+# Run sampler.  In this case we're going to use the `dynesty` sampler
+vector_tensor_result = bilby.core.sampler.run_sampler(
+    likelihood=vector_tensor_likelihood, priors=priors, sampler='nestle',
+    npoints=1000, injection_parameters=injection_parameters,
+    outdir=outdir, label='vector_tensor')
+
+vector_tensor_result.plot_corner()
+
+tensor_likelihood = bilby.gw.likelihood.GravitationalWaveTransient(
+    interferometers=ifos, waveform_generator=waveform_generator)
+
+priors['epsilon'] = 0
+
+# Run sampler.  In this case we're going to use the `dynesty` sampler
+tensor_result = bilby.core.sampler.run_sampler(
+    likelihood=tensor_likelihood, priors=priors, sampler='nestle', npoints=1000,
+    injection_parameters=injection_parameters, outdir=outdir, label='tensor')
+
+# make some plots of the outputs
+tensor_result.plot_corner()
+
+bilby.result.plot_multiple(
+    [tensor_result, vector_tensor_result], labels=['Tensor', 'Vector + Tensor'],
+    parameters=dict(ra=1.375, dec=-1.2108), evidences=True)