diff --git a/examples/glitch_robust_search.py b/examples/glitch_robust_search.py
new file mode 100644
index 0000000000000000000000000000000000000000..86e16b7736587f834b4549443c1824993bc0fbf5
--- /dev/null
+++ b/examples/glitch_robust_search.py
@@ -0,0 +1,54 @@
+import numpy as np
+import pyfstat
+
+outdir = 'data'
+label = 'glitch_robust_search'
+
+# Properties of the GW data
+tstart = 1000000000
+Tspan = 60 * 86400
+
+# Fixed properties of the signal
+F0s = 30
+F1s = -1e-8
+F2s = 0
+Alpha = np.radians(83.6292)
+Delta = np.radians(22.0144)
+
+tref = tstart + .5 * Tspan
+
+sftfilepath = 'data/*glitching_signal*sft'
+
+F0_width = np.sqrt(3)/(np.pi*Tspan)
+F1_width = np.sqrt(45/4.)/(np.pi*Tspan**2)
+DeltaF0 = 50 * F0_width
+DeltaF1 = 50 * F1_width
+
+theta_prior = {'F0': {'type': 'unif',
+ 'lower': F0s-DeltaF0,
+ 'upper': F0s+DeltaF0},
+ 'F1': {'type': 'unif',
+ 'lower': F1s-DeltaF1,
+ 'upper': F1s+DeltaF1},
+ 'F2': F2s,
+ 'delta_F0': {'type': 'unif',
+ 'lower': 0,
+ 'upper': 1e-5},
+ 'delta_F1': {'type': 'unif',
+ 'lower': -1e-11,
+ 'upper': 1e-11},
+ 'tglitch': {'type': 'unif',
+ 'lower': tstart+0.1*Tspan,
+ 'upper': tstart+0.9*Tspan},
+ 'Alpha': Alpha,
+ 'Delta': Delta,
+ }
+
+search = pyfstat.MCMCGlitchSearch(
+ label=label, outdir=outdir, sftfilepath=sftfilepath,
+ theta_prior=theta_prior, nglitch=1, tref=tref, nsteps=[500, 500],
+ ntemps=3, log10temperature_min=-0.5, minStartTime=tstart,
+ maxStartTime=tstart+Tspan)
+search.run()
+search.plot_corner(label_offset=0.8, add_prior=True)
+search.print_summary()
diff --git a/examples/glitch_robust_search_make_simulated_data.py b/examples/glitch_robust_search_make_simulated_data.py
new file mode 100644
index 0000000000000000000000000000000000000000..106eddaea2821d34c433490f53f69597261c64e6
--- /dev/null
+++ b/examples/glitch_robust_search_make_simulated_data.py
@@ -0,0 +1,40 @@
+import numpy as np
+import pyfstat
+
+outdir = 'data'
+label = 'simulated_glitching_signal'
+
+# Properties of the GW data
+tstart = 1000000000
+Tspan = 60 * 86400
+
+tref = tstart + .5 * Tspan
+
+# Fixed properties of the signal
+F0s = 30
+F1s = -1e-8
+F2s = 0
+Alpha = np.radians(83.6292)
+Delta = np.radians(22.0144)
+h0 = 1e-25
+sqrtSX = 1e-24
+psi = -0.1
+phi = 0
+cosi = 0.5
+
+# Glitch properties
+dtglitch = 0.45 * Tspan # time (in secs) after minStartTime
+dF0 = 5e-6
+dF1 = 1e-12
+
+
+detectors = 'H1'
+
+glitch_data = pyfstat.Writer(
+ label=label, outdir=outdir, tref=tref, tstart=tstart,
+ F0=F0s, F1=F1s, F2=F2s, duration=Tspan, Alpha=Alpha,
+ Delta=Delta, sqrtSX=sqrtSX, dtglitch=dtglitch,
+ h0=h0, cosi=cosi, phi=phi, psi=psi,
+ delta_F0=dF0, delta_F1=dF1, add_noise=True)
+
+glitch_data.make_data()
diff --git a/examples/transient_search_using_MCMC.py b/examples/transient_search_using_MCMC.py
index c5c54c3c2fc318318e7b11c7b1c14025b6ded97f..12125f0c237cbbd3f6bc6e58539a741f737aab22 100644
--- a/examples/transient_search_using_MCMC.py
+++ b/examples/transient_search_using_MCMC.py
@@ -1,64 +1,20 @@
-import pyfstat
-import numpy as np
-import matplotlib.pyplot as plt
+#!/usr/bin/env python
-plt.style.use('thesis')
+import pyfstat
F0 = 30.0
F1 = -1e-10
F2 = 0
-Alpha = 5e-3
-Delta = 6e-2
-
-tstart = 1000000000
-duration = 100*86400
-data_tstart = tstart - duration
-data_tend = data_tstart + 3*duration
-tref = .5*(data_tstart+data_tend)
-
-h0 = 1e-23
-sqrtSX = 1e-22
-
-transient = pyfstat.Writer(
- label='transient', outdir='data', tref=tref, tstart=tstart, F0=F0, F1=F1,
- F2=F2, duration=duration, Alpha=Alpha, Delta=Delta, h0=h0, sqrtSX=sqrtSX,
- minStartTime=data_tstart, maxStartTime=data_tend)
-transient.make_data()
-print transient.predict_fstat()
-
+Alpha = 0.5
+Delta = 1
+minStartTime = 1000000000
+maxStartTime = minStartTime + 200*86400
+Tspan = maxStartTime - minStartTime
+tref = minStartTime
DeltaF0 = 6e-7
DeltaF1 = 1e-13
-VF0 = (np.pi * duration * DeltaF0)**2 / 3.0
-VF1 = (np.pi * duration**2 * DeltaF1)**2 * 4/45.
-print '\nV={:1.2e}, VF0={:1.2e}, VF1={:1.2e}\n'.format(VF0*VF1, VF0, VF1)
-
-theta_prior = {'F0': {'type': 'unif',
- 'lower': F0-DeltaF0/2.,
- 'upper': F0+DeltaF0/2.},
- 'F1': {'type': 'unif',
- 'lower': F1-DeltaF1/2.,
- 'upper': F1+DeltaF1/2.},
- 'F2': F2,
- 'Alpha': Alpha,
- 'Delta': Delta
- }
-
-ntemps = 3
-log10temperature_min = -1
-nwalkers = 100
-nsteps = [750, 250]
-
-mcmc = pyfstat.MCMCSearch(
- label='transient_search_initial_stage', outdir='data',
- sftfilepath='data/*transient*sft', theta_prior=theta_prior, tref=tref,
- minStartTime=data_tstart, maxStartTime=data_tend, nsteps=nsteps,
- nwalkers=nwalkers, ntemps=ntemps,
- log10temperature_min=log10temperature_min)
-mcmc.run()
-mcmc.plot_cumulative_max()
-mcmc.print_summary()
theta_prior = {'F0': {'type': 'unif',
'lower': F0-DeltaF0/2.,
@@ -70,22 +26,24 @@ theta_prior = {'F0': {'type': 'unif',
'Alpha': Alpha,
'Delta': Delta,
'transient_tstart': {'type': 'unif',
- 'lower': data_tstart,
- 'upper': data_tend},
+ 'lower': minStartTime,
+ 'upper': maxStartTime},
'transient_duration': {'type': 'halfnorm',
- 'loc': 0,
- 'scale': 0.5*duration}
+ 'loc': 0.001*Tspan,
+ 'scale': 0.5*Tspan}
}
-nwalkers = 500
-nsteps = [200, 200]
+ntemps = 2
+log10temperature_min = -1
+nwalkers = 100
+nsteps = [100, 100]
mcmc = pyfstat.MCMCTransientSearch(
label='transient_search', outdir='data',
- sftfilepath='data/*transient*sft', theta_prior=theta_prior, tref=tref,
- minStartTime=data_tstart, maxStartTime=data_tend, nsteps=nsteps,
- nwalkers=nwalkers, ntemps=ntemps,
+ sftfilepath='data/*simulated_transient_signal*sft',
+ theta_prior=theta_prior, tref=tref, minStartTime=minStartTime,
+ maxStartTime=maxStartTime, nsteps=nsteps, nwalkers=nwalkers, ntemps=ntemps,
log10temperature_min=log10temperature_min)
mcmc.run()
-mcmc.plot_corner(add_prior=True)
+mcmc.plot_corner(label_offset=0.7)
mcmc.print_summary()
diff --git a/examples/transient_search_using_MCMC_make_simulated_data.py b/examples/transient_search_using_MCMC_make_simulated_data.py
new file mode 100644
index 0000000000000000000000000000000000000000..4fa3dd1d1157446b5de54dfb9b7f3b132889fdc1
--- /dev/null
+++ b/examples/transient_search_using_MCMC_make_simulated_data.py
@@ -0,0 +1,26 @@
+#!/usr/bin/env python
+
+import pyfstat
+
+F0 = 30.0
+F1 = -1e-10
+F2 = 0
+Alpha = 0.5
+Delta = 1
+
+minStartTime = 1000000000
+maxStartTime = minStartTime + 200*86400
+
+transient_tstart = minStartTime + 50*86400
+transient_duration = 100*86400
+tref = minStartTime
+
+h0 = 1e-23
+sqrtSX = 1e-22
+
+transient = pyfstat.Writer(
+ label='simulated_transient_signal', outdir='data', tref=tref,
+ tstart=transient_tstart, F0=F0, F1=F1, F2=F2, duration=transient_duration,
+ Alpha=Alpha, Delta=Delta, h0=h0, sqrtSX=sqrtSX, minStartTime=minStartTime,
+ maxStartTime=maxStartTime)
+transient.make_data()