update basic tutorial

tutorials/BasicTutorial.py

@@ -4,8 +4,9 @@ import peyote
 
 peyote.utils.setup_logger()
 
-time_duration = 1.
-sampling_frequency = 4096.
+time_duration = 4.
+sampling_frequency = 2048.
+outdir = 'outdir'
 
 injection_parameters = dict(mass_1=36., mass_2=29., a_1=0, a_2=0, tilt_1=0, tilt_2=0, phi_1=0, phi_2=0,
                             luminosity_distance=2500., iota=0.4, psi=2.659, phase=1.3, geocent_time=1126259642.413,
@@ -13,46 +14,30 @@ injection_parameters = dict(mass_1=36., mass_2=29., a_1=0, a_2=0, tilt_1=0, tilt
 
 # Create the waveform_generator using a LAL BinaryBlackHole source function
 waveform_generator = peyote.waveform_generator.WaveformGenerator(
-    sampling_frequency=sampling_frequency,
-    time_duration=time_duration,
+    sampling_frequency=sampling_frequency, time_duration=time_duration,
     frequency_domain_source_model=peyote.source.lal_binary_black_hole,
     parameters=injection_parameters)
 hf_signal = waveform_generator.frequency_domain_strain()
 
 # Set up interferometers.
-IFOs = [peyote.detector.get_empty_interferometer(name) for name in ['H1', 'L1', 'V1']]
-
-for IFO in IFOs:
-    IFO.set_data(sampling_frequency=sampling_frequency, duration=time_duration, from_power_spectral_density=True)
-    IFO.inject_signal(waveform_polarizations=hf_signal, parameters=injection_parameters)
-
-# Plot the noise and signal
-fig, ax = plt.subplots()
-for IFO in IFOs:
-    plt.loglog(IFO.frequency_array, np.abs(IFO.data), lw=1.5, label='{} noise+signal'.format(IFO.name))
-    plt.loglog(IFO.frequency_array, IFO.amplitude_spectral_density_array, lw=1.5, label='{} ASD'.format(IFO.name))
-plt.xlim(10, 1000)
-plt.legend()
-plt.xlabel(r'frequency')
-plt.ylabel(r'strain')
-fig.savefig('data')
+IFOs = [peyote.detector.get_inteferometer_with_fake_noise_and_injection(
+    name, injection_polarizations=hf_signal, injection_parameters=injection_parameters,
+    sampling_frequency=sampling_frequency, time_duration=time_duration, outdir=outdir)
+    for name in ['H1', 'L1', 'V1']]
 
 # Set up likelihood
 likelihood = peyote.likelihood.Likelihood(IFOs, waveform_generator)
 
 # Set up prior
-priors = {}
-priors['mass_1'] = peyote.prior.Uniform(
-    lower=35, upper=37, name='mass_1', latex_label='$m_1$')
-priors['luminosity_distance'] = peyote.prior.create_default_prior('luminosity_distance')
-for key in ['mass_2', 'a_1', 'a_2', 'tilt_1', 'tilt_2', 'phi_1', 'phi_2', 'phase', 'psi', 'iota', 'ra',
-            'dec', 'geocent_time']:
+priors = dict()
+# These parameters will not be sampled
+for key in ['a_1', 'a_2', 'tilt_1', 'tilt_2', 'phi_1', 'phi_2', 'phase', 'psi', 'iota', 'ra', 'dec', 'geocent_time']:
     priors[key] = injection_parameters[key]
 
 # Run sampler
 result = peyote.sampler.run_sampler(likelihood=likelihood, priors=priors, sampler='dynesty',
                                     label='BasicTutorial', use_ratio=True, npoints=500, verbose=True,
-                                    injection_parameters=injection_parameters)
+                                    injection_parameters=injection_parameters, outdir=outdir)
 result.plot_corner()
 result.plot_walks()
 result.plot_distributions()