Skip to content
Snippets Groups Projects
Select Git revision
  • d6d939e9d01a0ae9564ce6e8017209438ea37640
  • trunk
  • RELEASE_6_5_DRIVEDB
  • RELEASE_6_6_DRIVEDB
  • RELEASE_7_0_DRIVEDB
  • RELEASE_7_2_DRIVEDB
  • RELEASE_7_3_DRIVEDB
  • RELEASE_6_0_DRIVEDB
  • RELEASE_6_1_DRIVEDB
  • RELEASE_6_2_DRIVEDB
  • RELEASE_6_3_DRIVEDB
  • RELEASE_6_4_DRIVEDB
  • tags/RELEASE_7_4
  • tags/RELEASE_7_3
  • RELEASE_5_41_DRIVEDB
  • RELEASE_5_42_DRIVEDB
  • RELEASE_5_43_DRIVEDB
  • tags/RELEASE_7_2
  • tags/RELEASE_7_1
  • tags/RELEASE_7_0
  • RELEASE_5_40_DRIVEDB
21 results

smartd.cpp

Blame
  • transient_search_using_MCMC.py 2.57 KiB
    import pyfstat
    import numpy as np
    
    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 = 1e-23
    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()
    
    DeltaF0 = 6e-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 = [750, 250]
    
    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()
    
    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(add_prior=True)
    mcmc.print_summary()