Directed grid search: Linear spindown

Search for CW signal including one spindown parameter using a parameter space grid (i.e. no MCMC).

  8 import pyfstat
  9 import numpy as np
 10 import os
 11
 12 label = "PyFstat_example_grid_search_F0F1"
 13 outdir = os.path.join("PyFstat_example_data", label)
 14
 15 # Properties of the GW data
 16 sqrtSX = 1e-23
 17 tstart = 1000000000
 18 duration = 10 * 86400
 19 tend = tstart + duration
 20 tref = 0.5 * (tstart + tend)
 21 IFOs = "H1"
 22
 23 # parameters for injected signals
 24 depth = 20
 25 inj = {
 26     "tref": tref,
 27     "F0": 30.0,
 28     "F1": -1e-10,
 29     "F2": 0,
 30     "Alpha": 1.0,
 31     "Delta": 1.5,
 32     "h0": sqrtSX / depth,
 33     "cosi": 0.0,
 34 }
 35
 36 data = pyfstat.Writer(
 37     label=label,
 38     outdir=outdir,
 39     tstart=tstart,
 40     duration=duration,
 41     sqrtSX=sqrtSX,
 42     detectors=IFOs,
 43     **inj,
 44 )
 45 data.make_data()
 46
 47 m = 0.01
 48 dF0 = np.sqrt(12 * m) / (np.pi * duration)
 49 dF1 = np.sqrt(180 * m) / (np.pi * duration**2)
 50 dF2 = 1e-17
 51 N = 100
 52 DeltaF0 = N * dF0
 53 DeltaF1 = N * dF1
 54 F0s = [inj["F0"] - DeltaF0 / 2.0, inj["F0"] + DeltaF0 / 2.0, dF0]
 55 F1s = [inj["F1"] - DeltaF1 / 2.0, inj["F1"] + DeltaF1 / 2.0, dF1]
 56 F2s = [inj["F2"]]
 57 Alphas = [inj["Alpha"]]
 58 Deltas = [inj["Delta"]]
 59 search = pyfstat.GridSearch(
 60     label=label,
 61     outdir=outdir,
 62     sftfilepattern=data.sftfilepath,
 63     F0s=F0s,
 64     F1s=F1s,
 65     F2s=F2s,
 66     Alphas=Alphas,
 67     Deltas=Deltas,
 68     tref=tref,
 69     minStartTime=tstart,
 70     maxStartTime=tend,
 71 )
 72 search.run()
 73
 74 # report details of the maximum point
 75 max_dict = search.get_max_twoF()
 76 print(
 77     "max2F={:.4f} from GridSearch, offsets from injection: {:s}.".format(
 78         max_dict["twoF"],
 79         ", ".join(
 80             [
 81                 "{:.4e} in {:s}".format(max_dict[key] - inj[key], key)
 82                 for key in max_dict.keys()
 83                 if not key == "twoF"
 84             ]
 85         ),
 86     )
 87 )
 88 search.generate_loudest()
 89
 90 print("Plotting 2F(F0)...")
 91 search.plot_1D(xkey="F0", xlabel="freq [Hz]", ylabel="$2\\mathcal{F}$")
 92 print("Plotting 2F(F1)...")
 93 search.plot_1D(xkey="F1")
 94 print("Plotting 2F(F0,F1)...")
 95 search.plot_2D(xkey="F0", ykey="F1", colorbar=True)
 96
 97 print("Making gridcorner plot...")
 98 F0_vals = np.unique(search.data["F0"]) - inj["F0"]
 99 F1_vals = np.unique(search.data["F1"]) - inj["F1"]
100 twoF = search.data["twoF"].reshape((len(F0_vals), len(F1_vals)))
101 xyz = [F0_vals, F1_vals]
102 labels = [
103     "$f - f_0$",
104     "$\\dot{f} - \\dot{f}_0$",
105     "$\\widetilde{2\\mathcal{F}}$",
106 ]
107 fig, axes = pyfstat.gridcorner(
108     twoF, xyz, projection="log_mean", labels=labels, whspace=0.1, factor=1.8
109 )
110 fig.savefig(os.path.join(outdir, label + "_projection_matrix.png"))

Total running time of the script: ( 0 minutes 0.000 seconds)

Gallery generated by Sphinx-Gallery