"F0": 100.0,
"F1": 0,
"F2": 0,
"Alpha": 0.0,
"Delta": 0.5,
"tp": data_parameters["tstart"],
"asini": 25.0,
"period": 50 * 86400,
"tref": data_parameters["tstart"],
"h0": data_parameters["sqrtSX"] / depth,
"cosi": 1.0,
}
# making data
data = pyfstat.BinaryModulatedWriter(label=label,
outdir=outdir,
**data_parameters,
**signal_parameters)
data.make_data()
print("Loading SFT data and computing normalized power...")
times, freqs, sft_data = pyfstat.helper_functions.get_sft_array(
data.sftfilepath)
normalized_power = (2 * sft_data**2 /
(data_parameters["Tsft"] * data_parameters["sqrtSX"]**2))
plotfile = os.path.join(outdir, label + ".png")
print(f"Plotting to file: {plotfile}")
fig, ax = plt.subplots(figsize=(0.8 * 16, 0.8 * 9))
ax.grid(which="both")
ax.set(xlabel="Time [days]", ylabel="Frequency [Hz]", ylim=(99.98, 100.02))
c = ax.pcolormesh(
"cosi": 1,
"phi": np.pi,
"psi": np.pi / 8,
}
PFS_input = get_predict_fstat_parameters_from_dict({
**phase_parameters,
**amplitude_parameters
})
# Let me grab tref here, since it won't really be needed in phase_parameters
tref = phase_parameters.pop("tref")
data = pyfstat.BinaryModulatedWriter(
label=label,
outdir=outdir,
tref=tref,
**gw_data,
**phase_parameters,
**amplitude_parameters,
)
data.make_data()
# The predicted twoF, given by lalapps_predictFstat can be accessed by
twoF = data.predict_fstat()
print("Predicted twoF value: {}\n".format(twoF))
# Create a search object for each of the possible SFT combinations
# (H1 only, L1 only, H1 + L1).
ifo_constraints = ["L1", "H1", None]
compute_fstat_per_ifo = [
pyfstat.ComputeFstat(
sftfilepattern=os.path.join(
"F2": 0,
"Alpha": 0.5,
"Delta": 0.5,
"period": 85 * 24 * 3600.0,
"asini": 4.0,
"tp": mid_time * 1.05,
"argp": 0.0 if circular_orbit else 0.54,
"ecc": 0.0 if circular_orbit else 0.7,
"h0": data_parameters["sqrtSX"] / depth,
"cosi": 1.0,
}
print("Generating SFTs with injected signal...")
writer = pyfstat.BinaryModulatedWriter(
label="simulated_signal",
outdir=outdir,
**data_parameters,
**signal_parameters,
)
writer.make_data()
print("")
print("Performing Grid Search...")
# Create ad-hoc grid and compute Fstatistic around injection point
# There's no class supporting a binary search in the same way as
# grid_based_searches.GridSearch, so we do it by hand constructing
# a grid and using core.ComputeFstat.
half_points_per_dimension = 2
search_keys = ["period", "asini", "tp", "argp", "ecc"]
search_keys_label = [
r"$P$ [s]",