Adds new paper specific examples

Paper/Examples/single_glitch.py

+import pyfstat
+import numpy as np
+import matplotlib.pyplot as plt
+
+sqrtSX = 1e-22
+tstart = 1000000000
+duration = 100*86400
+tend = tstart+duration
+
+# Define parameters of the Crab pulsar as an example
+tref = .5*(tstart + tend)
+F0 = 30.0
+F1 = -1e-10
+F2 = 0
+Alpha = 5e-3
+Delta = 6e-2
+
+# Signal strength
+depth = 10
+h0 = sqrtSX / depth
+
+VF0 = VF1 = 200
+dF0 = np.sqrt(3)/(np.pi*duration)
+dF1 = np.sqrt(45/4.)/(np.pi*duration**2)
+DeltaF0 = VF0 * dF0
+DeltaF1 = VF1 * dF1
+
+# Next, taking the same signal parameters, we include a glitch half way through
+dtglitch = duration/2.0
+delta_F0 = 0.25*DeltaF0
+delta_F1 = -0.1*DeltaF1
+
+glitch_data = pyfstat.Writer(
+    label='single_glitch', outdir='data', tref=tref, tstart=tstart, F0=F0,
+    F1=F1, F2=F2, duration=duration, Alpha=Alpha, Delta=Delta, h0=h0,
+    sqrtSX=sqrtSX, dtglitch=dtglitch, delta_F0=delta_F0, delta_F1=delta_F1)
+glitch_data.make_data()
+
+F0s = [F0-DeltaF0/2., F0+DeltaF0/2., 1*dF0]
+F1s = [F1-DeltaF1/2., F1+DeltaF1/2., 1*dF1]
+F2s = [F2]
+Alphas = [Alpha]
+Deltas = [Delta]
+search = pyfstat.GridSearch(
+    'single_glitch_F0F1_grid', 'data', 'data/*single_glitch*sft', F0s, F1s,
+    F2s, Alphas, Deltas, tref, tstart, tend)
+search.run()
+search.plot_2D('F0', 'F1')
+
+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 = -0.05
+nwalkers = 100
+nsteps = [500, 500]
+
+mcmc = pyfstat.MCMCSearch(
+    'single_glitch', 'data', sftfilepath='data/*_single_glitch*.sft',
+    theta_prior=theta_prior, tref=tref, minStartTime=tstart, maxStartTime=tend,
+    nsteps=nsteps, nwalkers=nwalkers, ntemps=ntemps,
+    log10temperature_min=log10temperature_min)
+
+mcmc.run()
+mcmc.plot_corner(figsize=(3.2, 3.2))
+mcmc.print_summary()
+
+
+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,
+               'tglitch': {'type': 'unif', 'lower': tstart+0.1*duration,
+                           'upper': tend-0.1*duration},
+               'delta_F0': {'type': 'halfnorm', 'loc': 0, 'scale': 1e-3*F0},
+               'delta_F1': {'type': 'norm', 'loc': 0, 'scale': 1e-3*abs(F1)},
+               }
+ntemps = 3
+log10temperature_min = -0.1
+nwalkers = 100
+nsteps = [1000, 1000]
+glitch_mcmc = pyfstat.MCMCGlitchSearch(
+    'single_glitch_glitchSearch', 'data',
+    sftfilepath='data/*_single_glitch*.sft', theta_prior=theta_prior,
+    tref=tref, minStartTime=tstart, maxStartTime=tend, nsteps=nsteps,
+    nwalkers=nwalkers, ntemps=ntemps,
+    log10temperature_min=log10temperature_min)
+glitch_mcmc.run()
+glitch_mcmc.plot_corner(figsize=(3.2, 3.2))
+glitch_mcmc.print_summary()
+

Paper/Examples/transient_search_using_MCMC.py

+import pyfstat
+import numpy as np
+import matplotlib.pyplot as plt
+
+plt.style.use('thesis')
+
+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()
+
+
+
+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.,
+                      'upper': F0+DeltaF0/2.},
+               'F1': {'type': 'unif',
+                      'lower': F1-DeltaF1/2.,
+                      'upper': F1+DeltaF1/2.},
+               'F2': F2,
+               'Alpha': Alpha,
+               'Delta': Delta,
+               'transient_tstart': {'type': 'unif',
+                                    'lower': data_tstart,
+                                    'upper': data_tend},
+               'transient_duration': {'type': 'halfnorm',
+                                      'loc': 0,
+                                      'scale': 0.5*duration}
+               }
+
+nwalkers = 500
+nsteps = [200, 200]
+
+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,
+    log10temperature_min=log10temperature_min)
+mcmc.run()
+mcmc.plot_corner(add_prior=True)
+mcmc.print_summary()

Paper/paper_cw_mcmc.tex

@@ -1110,8 +1110,14 @@ a simulated transient signal and Gaussian noise.}
 
 
 \subsection{Glitches}
-\label{sec_glitches}
 
+\label{sec_glitches}
+\begin{figure}[htb]
+\centering
+\includegraphics[width=0.5\textwidth]{single_glitch_F0F1_grid_2D}
+\caption{}
+\label{fig:}
+\end{figure}
 \section{Conclusion}
 \label{sec_conclusion}