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Targeted grid search with line-robust BSGL statisticΒΆ

Search for a monochromatic (no spindown) signal using a parameter space grid (i.e. no MCMC) and the line-robust BSGL statistic to distinguish an astrophysical signal from an artifact in a single detector.

 11 import os
 12
 13 import numpy as np
 14
 15 import pyfstat
 16
 17 label = "PyFstat_example_grid_search_BSGL"
 18 outdir = os.path.join("PyFstat_example_data", label)
 19 logger = pyfstat.set_up_logger(label=label, outdir=outdir)
 20
 21 F0 = 30.0
 22 F1 = 0
 23 F2 = 0
 24 Alpha = 1.0
 25 Delta = 1.5
 26
 27 # Properties of the GW data - first we make data for two detectors,
 28 # both including Gaussian noise and a coherent 'astrophysical' signal.
 29 depth = 70
 30 sqrtS = "1e-23"
 31 h0 = float(sqrtS) / depth
 32 cosi = 0
 33 IFOs = "H1,L1"
 34 sqrtSX = ",".join(np.repeat(sqrtS, len(IFOs.split(","))))
 35 tstart = 1000000000
 36 duration = 100 * 86400
 37 tend = tstart + duration
 38 tref = 0.5 * (tstart + tend)
 39
 40 data = pyfstat.Writer(
 41     label=label,
 42     outdir=outdir,
 43     tref=tref,
 44     tstart=tstart,
 45     duration=duration,
 46     F0=F0,
 47     F1=F1,
 48     F2=F2,
 49     Alpha=Alpha,
 50     Delta=Delta,
 51     h0=h0,
 52     cosi=cosi,
 53     sqrtSX=sqrtSX,
 54     detectors=IFOs,
 55     SFTWindowType="tukey",
 56     SFTWindowBeta=0.001,
 57     Band=1,
 58 )
 59 data.make_data()
 60
 61 # Now we add an additional single-detector artifact to H1 only.
 62 # For simplicity, this is modelled here as a fully modulated CW-like signal,
 63 # just restricted to the single detector.
 64 SFTs_H1 = data.sftfilepath.split(";")[0]
 65 extra_writer = pyfstat.Writer(
 66     label=label,
 67     outdir=outdir,
 68     tref=tref,
 69     F0=F0 + 0.01,
 70     F1=F1,
 71     F2=F2,
 72     Alpha=Alpha,
 73     Delta=Delta,
 74     h0=10 * h0,
 75     cosi=cosi,
 76     sqrtSX=0,  # don't add yet another set of Gaussian noise
 77     noiseSFTs=SFTs_H1,
 78     SFTWindowType="tukey",
 79     SFTWindowBeta=0.001,
 80 )
 81 extra_writer.make_data()
 82
 83 # set up search parameter ranges
 84 dF0 = 0.0001
 85 DeltaF0 = 1000 * dF0
 86 F0s = [F0 - DeltaF0 / 2.0, F0 + DeltaF0 / 2.0, dF0]
 87 F1s = [F1]
 88 F2s = [F2]
 89 Alphas = [Alpha]
 90 Deltas = [Delta]
 91
 92 # first search: standard F-statistic
 93 # This should show a weak peak from the coherent signal
 94 # and a larger one from the "line artifact" at higher frequency.
 95 searchF = pyfstat.GridSearch(
 96     label + "_twoF",
 97     outdir,
 98     os.path.join(outdir, "*" + label + "*sft"),
 99     F0s,
100     F1s,
101     F2s,
102     Alphas,
103     Deltas,
104     tref,
105     tstart,
106     tend,
107 )
108 searchF.run()
109
110 logger.info("Plotting 2F(F0)...")
111 searchF.plot_1D(xkey="F0")
112
113 # second search: line-robust statistic BSGL activated
114 searchBSGL = pyfstat.GridSearch(
115     label + "_BSGL",
116     outdir,
117     os.path.join(outdir, "*" + label + "*sft"),
118     F0s,
119     F1s,
120     F2s,
121     Alphas,
122     Deltas,
123     tref,
124     tstart,
125     tend,
126     BSGL=True,
127 )
128 searchBSGL.run()
129
130 # The actual output statistic is log10BSGL.
131 # The peak at the higher frequency from the "line artifact" should now
132 # be massively suppressed.
133 logger.info("Plotting log10BSGL(F0)...")
134 searchBSGL.plot_1D(xkey="F0")

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

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