fully_coherent_search_using_MCMC_on_glitching_data.py 963 Bytes
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import numpy as np
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from pyfstat import MCMCSearch

F0 = 30.0
F1 = -1e-10
F2 = 0
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Alpha = np.radians(83.6292)
Delta = np.radians(22.0144)

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tref = 362750407.0

tstart = 1000000000
duration = 100*86400
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tend = tstart + duration
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theta_prior = {'F0': {'type': 'unif', 'lower': F0-1e-4, 'upper': F0+1e-4},
               'F1': {'type': 'unif', 'lower': F1*(1+1e-3), 'upper': F1*(1-1e-3)},
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               'F2': F2,
               'Alpha': Alpha,
               'Delta': Delta
               }

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ntemps = 2
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log10beta_min = -0.01
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nwalkers = 100
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nsteps = [500, 500]
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mcmc = MCMCSearch('fully_coherent_search_using_MCMC_on_glitching_data', 'data',
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                  sftfilepattern='data/*_glitch*.sft',
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                  theta_prior=theta_prior, tref=tref, minStartTime=tstart, maxStartTime=tend,
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                  nsteps=nsteps, nwalkers=nwalkers, ntemps=ntemps,
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                  log10beta_min=log10beta_min)
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mcmc.run()
mcmc.plot_corner(add_prior=True)
mcmc.print_summary()