import pyfstat import numpy as np import matplotlib.pyplot as plt plt.style.use('thesis') F0 = 30.0 F1 = -1e-10 F2 = 0 Alpha = 5e-3 Delta = 6e-2 tstart = 1000000000 duration = 100*86400 data_tstart = tstart - duration data_tend = data_tstart + 3*duration tref = .5*(data_tstart+data_tend) h0 = 5e-24 sqrtSX = 1e-22 transient = pyfstat.Writer( label='transient', outdir='data', tref=tref, tstart=tstart, F0=F0, F1=F1, F2=F2, duration=duration, Alpha=Alpha, Delta=Delta, h0=h0, sqrtSX=sqrtSX, minStartTime=data_tstart, maxStartTime=data_tend) transient.make_data() print transient.predict_fstat() DeltaF0 = 1e-7 DeltaF1 = 1e-13 VF0 = (np.pi * duration * DeltaF0)**2 / 3.0 VF1 = (np.pi * duration**2 * DeltaF1)**2 * 4/45. print '\nV={:1.2e}, VF0={:1.2e}, VF1={:1.2e}\n'.format(VF0*VF1, VF0, VF1) theta_prior = {'F0': {'type': 'unif', 'lower': F0-DeltaF0/2., 'upper': F0+DeltaF0/2.}, 'F1': {'type': 'unif', 'lower': F1-DeltaF1/2., 'upper': F1+DeltaF1/2.}, 'F2': F2, 'Alpha': Alpha, 'Delta': Delta } ntemps = 3 log10temperature_min = -1 nwalkers = 100 nsteps = [100, 100] mcmc = pyfstat.MCMCSearch( label='transient_search_initial_stage', outdir='data', sftfilepath='data/*transient*sft', theta_prior=theta_prior, tref=tref, minStartTime=data_tstart, maxStartTime=data_tend, nsteps=nsteps, nwalkers=nwalkers, ntemps=ntemps, log10temperature_min=log10temperature_min) mcmc.run() mcmc.plot_cumulative_max() mcmc.print_summary() theta_prior = {'F0': {'type': 'unif', 'lower': F0-DeltaF0/2., 'upper': F0+DeltaF0/2.}, 'F1': {'type': 'unif', 'lower': F1-DeltaF1/2., 'upper': F1+DeltaF1/2.}, 'F2': F2, 'Alpha': Alpha, 'Delta': Delta, 'transient_tstart': {'type': 'unif', 'lower': data_tstart, 'upper': data_tend}, 'transient_duration': {'type': 'halfnorm', 'loc': 0, 'scale': 0.5*duration} } nwalkers = 500 nsteps = [200, 200] mcmc = pyfstat.MCMCTransientSearch( label='transient_search', outdir='data', sftfilepath='data/*transient*sft', theta_prior=theta_prior, tref=tref, minStartTime=data_tstart, maxStartTime=data_tend, nsteps=nsteps, nwalkers=nwalkers, ntemps=ntemps, log10temperature_min=log10temperature_min) mcmc.run() mcmc.plot_corner() mcmc.print_summary()