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Binary CW example: Semicoherent MCMC searchΒΆ
MCMC search of a CW signal produced by a source in a binary system using the semicoherent F-statistic.
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import numpy as np
import os
# If False, sky priors are used
directed_search = True
# If False, ecc and argp priors are used
known_eccentricity = True
label = "PyFstat_example_semi_coherent_binary_search_using_MCMC"
outdir = os.path.join("PyFstat_example_data", label)
# Properties of the GW data
data_parameters = {
"sqrtSX": 1e-23,
"tstart": 1000000000,
"duration": 10 * 86400,
"detectors": "H1",
}
tend = data_parameters["tstart"] + data_parameters["duration"]
mid_time = 0.5 * (data_parameters["tstart"] + tend)
# Properties of the signal
depth = 0.1
signal_parameters = {
"F0": 30.0,
"F1": 0,
"F2": 0,
"Alpha": 0.15,
"Delta": 0.45,
"tp": mid_time,
"argp": 0.3,
"asini": 10.0,
"ecc": 0.1,
"period": 45 * 24 * 3600.0,
"tref": mid_time,
"h0": data_parameters["sqrtSX"] / depth,
"cosi": 1.0,
}
data = pyfstat.BinaryModulatedWriter(
label=label, outdir=outdir, **data_parameters, **signal_parameters
)
data.make_data()
theta_prior = {
"F0": signal_parameters["F0"],
"F1": signal_parameters["F1"],
"F2": signal_parameters["F2"],
"asini": {
"type": "unif",
"lower": 0.9 * signal_parameters["asini"],
"upper": 1.1 * signal_parameters["asini"],
},
"period": {
"type": "unif",
"lower": 0.9 * signal_parameters["period"],
"upper": 1.1 * signal_parameters["period"],
},
"tp": {
"type": "unif",
"lower": mid_time - signal_parameters["period"] / 2.0,
"upper": mid_time + signal_parameters["period"] / 2.0,
},
}
if directed_search:
for key in "Alpha", "Delta":
theta_prior[key] = signal_parameters[key]
else:
theta_prior.update(
{
"Alpha": {
"type": "unif",
"lower": signal_parameters["Alpha"] - 0.01,
"upper": signal_parameters["Alpha"] + 0.01,
},
"Delta": {
"type": "unif",
"lower": signal_parameters["Delta"] - 0.01,
"upper": signal_parameters["Delta"] + 0.01,
},
}
)
if known_eccentricity:
for key in "ecc", "argp":
theta_prior[key] = signal_parameters[key]
else:
theta_prior.update(
{
"ecc": {
"type": "unif",
"lower": signal_parameters["ecc"] - 5e-2,
"upper": signal_parameters["ecc"] + 5e-2,
},
"argp": {
"type": "unif",
"lower": signal_parameters["argp"] - np.pi / 2,
"upper": signal_parameters["argp"] + np.pi / 2,
},
}
)
ntemps = 3
log10beta_min = -1
nwalkers = 150
nsteps = [100, 200]
mcmc = pyfstat.MCMCSemiCoherentSearch(
label=label,
outdir=outdir,
nsegs=10,
sftfilepattern=os.path.join(outdir, "*{}*sft".format(label)),
theta_prior=theta_prior,
tref=signal_parameters["tref"],
minStartTime=data_parameters["tstart"],
maxStartTime=tend,
nsteps=nsteps,
nwalkers=nwalkers,
ntemps=ntemps,
log10beta_min=log10beta_min,
binary=True,
)
mcmc.run(
plot_walkers=True,
walker_plot_args={"plot_det_stat": True, "injection_parameters": signal_parameters},
)
mcmc.plot_corner(add_prior=True, truths=signal_parameters)
mcmc.plot_prior_posterior(injection_parameters=signal_parameters)
mcmc.print_summary()
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Total running time of the script: ( 0 minutes 0.000 seconds)