Update glitch examples

examples/glitch_examples/make_simulated_data.py

@@ -17,7 +17,7 @@ h0 = 5e-24
 # Properties of the GW data
 sqrtSX = 1e-22
 tstart = 1000000000
-duration = 100*86400
+duration = 50*86400
 tend = tstart+duration
 tref = tstart + 0.5*duration
 
@@ -26,10 +26,6 @@ data = Writer(
     F2=F2, duration=duration, Alpha=Alpha, Delta=Delta, h0=h0, sqrtSX=sqrtSX)
 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)
-
 # Next, taking the same signal parameters, we include a glitch half way through
 dtglitch = duration/2.0
 delta_F0 = 5e-6

examples/glitch_examples/semicoherent_glitch_robust_directed_MCMC_search_on_1_glitch.py

@@ -2,6 +2,7 @@ import numpy as np
 import matplotlib.pyplot as plt
 import pyfstat
 import gridcorner
+import time
 from make_simulated_data import tstart, duration, tref, F0, F1, F2, Alpha, Delta, delta_F0, dtglitch, outdir
 
 plt.style.use('./paper.mplstyle')
@@ -34,21 +35,25 @@ theta_prior = {
 ntemps = 3
 log10beta_min = -0.5
 nwalkers = 100
-nsteps = [500, 1000]
+nsteps = [250, 250]
 
 mcmc = pyfstat.MCMCGlitchSearch(
     label=label, sftfilepattern='data/*1_glitch*sft', theta_prior=theta_prior,
     tref=tref, minStartTime=tstart, maxStartTime=tstart+duration,
     nsteps=nsteps, nwalkers=nwalkers, ntemps=ntemps,
     log10beta_min=log10beta_min, nglitch=1)
-print delta_F0
 mcmc.transform_dictionary['F0'] = dict(
     subtractor=F0, symbol='$f-f^\mathrm{s}$')
 mcmc.transform_dictionary['F1'] = dict(
     subtractor=F1, symbol='$\dot{f}-\dot{f}^\mathrm{s}$')
 
+t1 = time.time()
 mcmc.run()
+dT = time.time() - t1
 fig_and_axes = gridcorner._get_fig_and_axes(4, 2, 0.05)
 mcmc.plot_corner(label_offset=0.35, truths=[0, 0, delta_F0, 50],
                  fig_and_axes=fig_and_axes)
 mcmc.print_summary()
+
+print('Prior widths =', F0_width, F1_width)
+print("Actual run time = {}".format(dT))

examples/glitch_examples/semicoherent_glitch_robust_directed_grid_search_on_1_glitch.py

 import pyfstat
 import numpy as np
 import matplotlib.pyplot as plt
-from make_simulated_data import tstart, duration, tref, F0, F1, F2, Alpha, Delta, delta_F0, outdir
+from make_simulated_data import tstart, duration, tref, F0, F1, F2, Alpha, Delta, delta_F0, outdir, dtglitch
+import time
 
 try:
     from gridcorner import gridcorner
@@ -17,7 +18,7 @@ plt.style.use('./paper.mplstyle')
 Nstar = 1000
 F0_width = np.sqrt(Nstar)*np.sqrt(12)/(np.pi*duration)
 F1_width = np.sqrt(Nstar)*np.sqrt(180)/(np.pi*duration**2)
-N = 30
+N = 20
 F0s = [F0-F0_width/2., F0+F0_width/2., F0_width/N]
 F1s = [F1-F1_width/2., F1+F1_width/2., F1_width/N]
 F2s = [F2]
@@ -29,14 +30,15 @@ tglitchs = [tstart+0.1*duration, tstart+0.9*duration, 0.8*float(duration)/N]
 delta_F0s = [0, max_delta_F0, max_delta_F0/N]
 delta_F1s = [0]
 
-print 'Prior widths=', F0_width, F1_width
 
+t1 = time.time()
 search = pyfstat.GridGlitchSearch(
     label, outdir, 'data/*1_glitch*sft', F0s=F0s, F1s=F1s, F2s=F2s,
     Alphas=Alphas, Deltas=Deltas, tref=tref, minStartTime=tstart,
     maxStartTime=tstart+duration, tglitchs=tglitchs, delta_F0s=delta_F0s,
     delta_F1s=delta_F1s)
 search.run()
+dT = time.time() - t1
 
 F0_vals = np.unique(search.data[:, 0]) - F0
 F1_vals = np.unique(search.data[:, 1]) - F1
@@ -51,6 +53,11 @@ labels = ['$f - f^\mathrm{s}$\n[Hz]', '$\dot{f} - \dot{f}^\mathrm{s}$\n[Hz/s]',
           '$\delta f$\n[Hz]', '$t^g_0$\n[days]', '$\widehat{2\mathcal{F}}$']
 fig, axes = gridcorner(
     twoF, xyz, projection='log_mean', labels=labels,
-    showDvals=False, lines=[0, 0, delta_F0, 50], label_offset=0.35)
+    showDvals=False, lines=[0, 0, delta_F0, dtglitch/86400.], label_offset=0.35)
 fig.savefig('{}/{}_projection_matrix.png'.format(outdir, label),
             bbox_inches='tight')
+
+
+print('Prior widths =', F0_width, F1_width)
+print("Actual run time = {}".format(dT))
+print("Actual number of grid points = {}".format(search.data.shape[0]))