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pykat_LLO.py
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Daniel Brown authoredDaniel Brown authored
fully_coherent_search_using_MCMC_on_glitching_data.py 984 B
import numpy as np
from pyfstat import MCMCSearch
F0 = 30.0
F1 = -1e-10
F2 = 0
Alpha = np.radians(83.6292)
Delta = np.radians(22.0144)
tref = 362750407.0
tstart = 1000000000
duration = 100*86400
tend = tstart + duration
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)},
'F2': F2,
'Alpha': Alpha,
'Delta': Delta
}
ntemps = 2
log10temperature_min = -0.01
nwalkers = 100
nsteps = [500, 500]
mcmc = MCMCSearch('fully_coherent_search_using_MCMC_on_glitching_data', 'data',
sftfilepattern='data/*_glitch*.sft',
theta_prior=theta_prior, tref=tref, minStartTime=tstart, maxStartTime=tend,
nsteps=nsteps, nwalkers=nwalkers, ntemps=ntemps,
log10temperature_min=log10temperature_min)
mcmc.run()
mcmc.plot_corner(add_prior=True)
mcmc.print_summary()