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semi_coherent_search_using_MCMC.py

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  • semi_coherent_search_using_MCMC.py 873 B
    import pyfstat
    
    F0 = 30.0
    F1 = -1e-10
    F2 = 0
    Alpha = 5e-3
    Delta = 6e-2
    tref = 362750407.0
    
    tstart = 1000000000
    duration = 100*86400
    tend = tstart + duration
    
    theta_prior = {'F0': {'type': 'unif', 'lower': F0*(1-1e-6), 'upper': F0*(1+1e-5)},
                   'F1': {'type': 'unif', 'lower': F1*(1+1e-2), 'upper': F1*(1-1e-2)},
                   'F2': F2,
                   'Alpha': Alpha,
                   'Delta': Delta
                   }
    
    ntemps = 1
    log10beta_min = -1
    nwalkers = 100
    nsteps = [500, 500, 500]
    
    mcmc = pyfstat.MCMCSemiCoherentSearch(
        label='semi_coherent_search_using_MCMC', outdir='data', nsegs=20,
        sftfilepattern='data/*basic*sft', theta_prior=theta_prior, tref=tref,
        minStartTime=tstart, maxStartTime=tend, nsteps=nsteps, nwalkers=nwalkers,
        ntemps=ntemps, log10beta_min=log10beta_min)
    mcmc.run()
    mcmc.plot_corner(add_prior=True)
    mcmc.print_summary()