Adds new points to the recovery plots

Paper/AllSkyMC/AllSkyMC_repeat.sh

@@ -4,7 +4,7 @@
 export PATH="/home/gregory.ashton/anaconda2/bin:$PATH"
 export MPLCONFIGDIR=/home/gregory.ashton/.config/matplotlib
 
-for ((n=0;n<1;n++))
+for ((n=0;n<10;n++))
 do
 /home/gregory.ashton/anaconda2/bin/python generate_data.py "$1" /local/user/gregory.ashton --no-template-counting --no-interactive
 done

Paper/AllSkyMC/generate_data.py

@@ -32,6 +32,7 @@ DeltaAlpha = 0.02
 DeltaDelta = 0.02
 
 depths = np.linspace(100, 400, 9)
+depths = [118.75, 156.25]
 
 nsteps = 50
 run_setup = [((nsteps, 0), 20, False),

Paper/AllSkyMC/generate_table.py

@@ -82,7 +82,7 @@ mcmc = pyfstat.MCMCFollowUpSearch(
     sftfilepath='{}/*{}*sft'.format(outdir, data_label),
     theta_prior=theta_prior,
     tref=tref, minStartTime=tstart, maxStartTime=tend,
-    nwalkers=nwalkers, ntemps=ntemps, nsteps=[nsteps, nsteps]
+    nwalkers=nwalkers, ntemps=ntemps, nsteps=[nsteps, nsteps],
     log10temperature_min=log10temperature_min)
-#mcmc.run(Nsegs0=20, R=10)
-mcmc.run(run_setup)
+mcmc.run(Nsegs0=20, R=10)
+#mcmc.run(run_setup)

Paper/AllSkyMC/submitfile

@@ -9,4 +9,4 @@ Log=CollectedOutput/log.$(Cluster).$(Process)
 request_cpus = 1
 request_memory = 16 GB
 
-Queue 70
+Queue 1

Paper/DirectedMC/DirectedMC_repeat.sh

@@ -4,7 +4,7 @@
 export PATH="/home/gregory.ashton/anaconda2/bin:$PATH"
 export MPLCONFIGDIR=/home/gregory.ashton/.config/matplotlib
 
-for ((n=0;n<1;n++))
+for ((n=0;n<10;n++))
 do
 /home/gregory.ashton/anaconda2/bin/python generate_data.py "$1" /local/user/gregory.ashton --no-template-counting --no-interactive
 done

Paper/DirectedMC/generate_data.py

@@ -31,6 +31,7 @@ DeltaF0 = VF0 * np.sqrt(3)/(np.pi*Tspan)
 DeltaF1 = VF1 * np.sqrt(45/4.)/(np.pi*Tspan**2)
 
 depths = np.linspace(100, 400, 9)
+depths = [118.75, 156.25]
 
 nsteps = 25
 run_setup = [((nsteps, 0), 20, False),

Paper/DirectedMC/plot_data.py

@@ -33,9 +33,6 @@ for fn in filenames:
     df = pd.read_csv(
         fn, sep=' ', names=['depth', 'h0', 'dF0', 'dF1', 'twoF', 'runTime'])
     df['CLUSTER_ID'] = fn.split('_')[1]
-    if len(df) != 9:
-        print len(df), fn
-    else:
     df_list.append(df)
 df = pd.concat(df_list)
 
@@ -81,10 +78,9 @@ fig.tight_layout()
 fig.savefig('directed_recovery.png')
 
 
-total_number_steps = 5*20.
-df_clean = df[df.CLUSTER_ID == '969049']  # Hack due to a change in the code
+total_number_steps = 5*25.
 fig, ax = plt.subplots()
-ax.hist(df_clean.runTime/total_number_steps, bins=50)
+ax.hist(df.runTime/total_number_steps, bins=50)
 ax.set_xlabel('run-time per step [s]')
 fig.tight_layout()
 fig.savefig('runTimeHist.png')

Paper/DirectedMC/submitfile

@@ -9,4 +9,4 @@ Log=CollectedOutput/log.$(Cluster).$(Process)
 request_cpus = 1
 request_memory = 16 GB
 
-Queue 6
+Queue 1