Commit e22e9b59 authored by Gregory Ashton's avatar Gregory Ashton
Browse files

Minor updates to examples in paper

parent 9e56db0b
......@@ -53,7 +53,7 @@ nsteps = [50, 50]
mcmc = pyfstat.MCMCSearch(
label='fully_coherent_search_using_MCMC', outdir='data',
sftfilepath='data/*'+data_label+'*sft', theta_prior=theta_prior, tref=tref,
sftfilepath='data/*'+data_label+'-*sft', theta_prior=theta_prior, tref=tref,
minStartTime=tstart, maxStartTime=tend, nsteps=nsteps, nwalkers=nwalkers,
ntemps=ntemps, log10temperature_min=log10temperature_min)
mcmc.run(context='paper', subtractions=[30, -1e-10])
......
......@@ -55,7 +55,10 @@ mcmc = pyfstat.MCMCSearch(
nwalkers=nwalkers, ntemps=ntemps,
log10temperature_min=log10temperature_min)
mcmc.run()
mcmc.plot_cumulative_max()
fig, ax = plt.subplots()
mcmc.plot_cumulative_max(ax=ax)
ax.set_xlabel('Days from $t_\mathrm{start}$')
fig.savefig('data/transient_search_initial_stage_twoFcumulative')
mcmc.print_summary()
theta_prior = {'F0': {'type': 'unif',
......@@ -69,9 +72,9 @@ theta_prior = {'F0': {'type': 'unif',
'Delta': Delta,
'transient_tstart': {'type': 'unif',
'lower': data_tstart,
'upper': data_tend},
'upper': data_tend-0.2*duration},
'transient_duration': {'type': 'halfnorm',
'loc': 0,
'loc': 0.01*duration,
'scale': 0.5*duration}
}
......
\begin{tabular}{c|cccccc}
Stage & $\Nseg$ & $\Tcoh^{\rm days}$ &$\Nsteps$ & $\V$ & $\Vsky$ & $\Vpe$ \\ \hline
0 & 100 & 1.0 & 200 & $1{\times}10^{2}$ & 7.0 & 10.0 \\
1 & 56 & 1.8 & 200 & $1{\times}10^{3}$ & 20.0 & 40.0 \\
2 & 31 & 3.2 & 200 & $1{\times}10^{4}$ & 70.0 & $1{\times}10^{2}$ \\
3 & 17 & 5.9 & 200 & $1{\times}10^{5}$ & $2{\times}10^{2}$ & $5{\times}10^{2}$ \\
4 & 9 & 11.1 & 200 & $1{\times}10^{6}$ & $8{\times}10^{2}$ & $2{\times}10^{3}$ \\
5 & 5 & 20.0 & 200 & $1{\times}10^{7}$ & $2{\times}10^{3}$ & $5{\times}10^{3}$ \\
6 & 2 & 50.0 & 200 & $1{\times}10^{8}$ & $3{\times}10^{3}$ & $3{\times}10^{4}$ \\
7 & 1 & 100.0 & 200,200 & $3{\times}10^{8}$ & $4{\times}10^{3}$ & $6{\times}10^{4}$ \\
0 & 100 & 1.0 & 200 & 95.0 & 6.8 & 14.0 \\
1 & 56 & 1.8 & 200 & $9.6{\times}10^{2}$ & 22.0 & 45.0 \\
2 & 31 & 3.2 & 200 & $1.0{\times}10^{4}$ & 69.0 & $1.5{\times}10^{2}$ \\
3 & 17 & 5.9 & 200 & $1.1{\times}10^{5}$ & $2.3{\times}10^{2}$ & $4.8{\times}10^{2}$ \\
4 & 9 & 11.1 & 200 & $1.3{\times}10^{6}$ & $7.5{\times}10^{2}$ & $1.7{\times}10^{3}$ \\
5 & 5 & 20.0 & 200 & $1.1{\times}10^{7}$ & $2.0{\times}10^{3}$ & $5.5{\times}10^{3}$ \\
6 & 2 & 50.0 & 200 & $1.0{\times}10^{8}$ & $3.3{\times}10^{3}$ & $3.1{\times}10^{4}$ \\
7 & 1 & 100.0 & 200,200 & $2.7{\times}10^{8}$ & $4.4{\times}10^{3}$ & $6.2{\times}10^{4}$ \\
\end{tabular}
Paper/follow_up_walkers.png

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Paper/follow_up_walkers.png

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Paper/follow_up_walkers.png
Paper/follow_up_walkers.png
Paper/follow_up_walkers.png
Paper/follow_up_walkers.png
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......@@ -53,15 +53,15 @@
\title{MCMC follow-up of continuous gravitational wave candidates}
\author{G. Ashton}
\email[E-mail: ]{gregory.ashton@ligo.org}
\affiliation{Max Planck Institut f{\"u}r Gravitationsphysik
(Albert Einstein Institut) and Leibniz Universit\"at Hannover,
30161 Hannover, Germany}
\author{R. Prix}
\affiliation{Max Planck Institut f{\"u}r Gravitationsphysik
(Albert Einstein Institut) and Leibniz Universit\"at Hannover,
30161 Hannover, Germany}
% \author{G. Ashton}
% \email[E-mail: ]{gregory.ashton@ligo.org}
% \affiliation{Max Planck Institut f{\"u}r Gravitationsphysik
% (Albert Einstein Institut) and Leibniz Universit\"at Hannover,
% 30161 Hannover, Germany}
% \author{R. Prix}
% \affiliation{Max Planck Institut f{\"u}r Gravitationsphysik
% (Albert Einstein Institut) and Leibniz Universit\"at Hannover,
% 30161 Hannover, Germany}
\date{\today}
......@@ -1215,13 +1215,13 @@ the improvement in fit due to the inclustion of the transient parameters was
sufficient to compensate for the greater prior volume and produce an
improvement in the evidence for the model.
\begin{figure}[htb]
\begin{figure*}[htb]
\centering
\includegraphics[width=0.45\textwidth]{transient_search_corner}
\includegraphics[width=0.8\textwidth]{transient_search_corner}
\caption{Posterior distributions for a targeted search of data containing
a simulated transient signal and Gaussian noise.}
\label{fig_transient_posterior}
\end{figure}
\end{figure*}
......
Paper/transient_search_corner.png

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Paper/transient_search_corner.png

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Paper/transient_search_corner.png
Paper/transient_search_corner.png
Paper/transient_search_corner.png
Paper/transient_search_corner.png
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