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11 results

tests.py

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    • Gregory Ashton's avatar
      0428e2aa
      Comment out all convergence testing methods · 0428e2aa
      Gregory Ashton authored
       This removes the convergence testing ideas previously implemented
       (currently juts commented, but later to be fully removed). These are
      clearly not useful without further study, which in itself would be a
      better time to develop an implementation.
      0428e2aa
      History
      Comment out all convergence testing methods
      Gregory Ashton authored
       This removes the convergence testing ideas previously implemented
       (currently juts commented, but later to be fully removed). These are
      clearly not useful without further study, which in itself would be a
      better time to develop an implementation.
    fully_coherent_search.py 787 B
    from pyfstat import MCMCSearch
    
    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': 'norm', 'loc': F0, 'scale': abs(1e-6*F0)},
                   'F1': {'type': 'norm', 'loc': F1, 'scale': abs(1e-6*F1)},
                   'F2': F2,
                   'Alpha': Alpha,
                   'Delta': Delta
                   }
    
    ntemps = 1
    nwalkers = 100
    nsteps = [100, 500, 1000]
    
    mcmc = MCMCSearch('fully_coherent', 'data', sftfilepath='data/*basic*sft',
                      theta_prior=theta_prior, tref=tref, tstart=tstart, tend=tend,
                      nsteps=nsteps, nwalkers=nwalkers, ntemps=ntemps,
                      scatter_val=1e-10)
    mcmc.run()
    mcmc.plot_corner()
    mcmc.print_summary()