diff --git a/Paper/AllSkyMC/generate_data.py b/Paper/AllSkyMC/generate_data.py
index abcb5ddf995d9218c1d28a1a069eb006fa363844..81bc4a3878a9ffefe09ada9a5fb4923e606993d4 100644
--- a/Paper/AllSkyMC/generate_data.py
+++ b/Paper/AllSkyMC/generate_data.py
@@ -28,8 +28,10 @@ VF0 = VF1 = 100
DeltaF0 = VF0 * np.sqrt(3)/(np.pi*Tspan)
DeltaF1 = VF1 * np.sqrt(45/4.)/(np.pi*Tspan**2)
-#depths = np.linspace(100, 400, 7)
-depths = [50, 75]
+DeltaAlpha = 0.02
+DeltaDelta = 0.02
+
+depths = np.linspace(100, 400, 7)
nsteps = 50
run_setup = [((nsteps, 0), 20, False),
@@ -38,22 +40,15 @@ run_setup = [((nsteps, 0), 20, False),
((nsteps, 0), 3, False),
((nsteps, nsteps), 1, False)]
-DeltaAlpha = 0.05
-DeltaDelta = 0.05
for depth in depths:
h0 = sqrtSX / float(depth)
F0 = F0_center + np.random.uniform(-0.5, 0.5)*DeltaF0
F1 = F1_center + np.random.uniform(-0.5, 0.5)*DeltaF1
- Alpha = np.random.uniform(0, 2*np.pi)
- Delta = np.arccos(2*np.random.uniform(0, 1)-1)-np.pi/2
- fAlpha = np.random.uniform(0, 1)
- Alpha_min = Alpha - DeltaAlpha*(1-fAlpha)
- Alpha_max = Alpha + DeltaAlpha*fAlpha
- fDelta = np.random.uniform(0, 1)
- Delta_min = Delta - DeltaDelta*(1-fDelta)
- Delta_max = Delta + DeltaDelta*fDelta
-
+ Alpha_center = np.random.uniform(0, 2*np.pi)
+ Delta_center = np.arccos(2*np.random.uniform(0, 1)-1)-np.pi/2
+ Alpha = Alpha_center + np.random.uniform(-0.5, 0.5)*DeltaAlpha
+ Delta = Delta_center + np.random.uniform(-0.5, 0.5)*DeltaDelta
psi = np.random.uniform(-np.pi/4, np.pi/4)
phi = np.random.uniform(0, 2*np.pi)
cosi = np.random.uniform(-1, 1)
@@ -68,21 +63,21 @@ for depth in depths:
startTime = time.time()
theta_prior = {'F0': {'type': 'unif',
- 'lower': F0-DeltaF0/2.,
- 'upper': F0+DeltaF0/2.},
+ 'lower': F0_center-DeltaF0,
+ 'upper': F0_center+DeltaF0},
'F1': {'type': 'unif',
- 'lower': F1-DeltaF1/2.,
- 'upper': F1+DeltaF1/2.},
+ 'lower': F1_center-DeltaF1,
+ 'upper': F1_center+DeltaF1},
'F2': F2,
'Alpha': {'type': 'unif',
- 'lower': Alpha_min,
- 'upper': Alpha_max},
+ 'lower': Alpha_center-DeltaAlpha,
+ 'upper': Alpha_center+DeltaAlpha},
'Delta': {'type': 'unif',
- 'lower': Delta_min,
- 'upper': Delta_max},
+ 'lower': Delta_center-DeltaDelta,
+ 'upper': Delta_center+DeltaDelta},
}
- ntemps = 1
+ ntemps = 2
log10temperature_min = -1
nwalkers = 100
diff --git a/Paper/AllSkyMC/generate_failures.py b/Paper/AllSkyMC/generate_failures.py
new file mode 100644
index 0000000000000000000000000000000000000000..d6da9c087bcab87e3dc63207a1337f4710c101cb
--- /dev/null
+++ b/Paper/AllSkyMC/generate_failures.py
@@ -0,0 +1,93 @@
+import pyfstat
+import numpy as np
+import os
+import time
+
+outdir = 'data'
+
+label = 'run_failures'
+data_label = '{}_data'.format(label)
+results_file_name = '{}/MCResults_failures.txt'.format(outdir)
+
+# Properties of the GW data
+sqrtSX = 2e-23
+tstart = 1000000000
+Tspan = 100*86400
+tend = tstart + Tspan
+
+# Fixed properties of the signal
+F0_center = 30
+F1_center = 1e-10
+F2 = 0
+tref = .5*(tstart+tend)
+
+
+VF0 = VF1 = 100
+DeltaF0 = VF0 * np.sqrt(3)/(np.pi*Tspan)
+DeltaF1 = VF1 * np.sqrt(45/4.)/(np.pi*Tspan**2)
+
+DeltaAlpha = 0.02
+DeltaDelta = 0.02
+
+depths = [140]
+
+nsteps = 50
+run_setup = [((nsteps, 0), 20, False),
+ ((nsteps, 0), 11, False),
+ ((nsteps, 0), 6, False),
+ ((nsteps, 0), 3, False),
+ ((nsteps, nsteps), 1, False)]
+
+
+for depth in depths:
+ h0 = sqrtSX / float(depth)
+ F0 = F0_center + np.random.uniform(-0.5, 0.5)*DeltaF0
+ F1 = F1_center + np.random.uniform(-0.5, 0.5)*DeltaF1
+ Alpha_center = np.random.uniform(0, 2*np.pi)
+ Delta_center = np.arccos(2*np.random.uniform(0, 1)-1)-np.pi/2
+ Alpha = Alpha_center + np.random.uniform(-0.5, 0.5)*DeltaAlpha
+ Delta = Delta_center + np.random.uniform(-0.5, 0.5)*DeltaDelta
+ psi = np.random.uniform(-np.pi/4, np.pi/4)
+ phi = np.random.uniform(0, 2*np.pi)
+ cosi = np.random.uniform(-1, 1)
+
+ data = pyfstat.Writer(
+ label=data_label, outdir=outdir, tref=tref,
+ tstart=tstart, F0=F0, F1=F1, F2=F2, duration=Tspan, Alpha=Alpha,
+ Delta=Delta, h0=h0, sqrtSX=sqrtSX, psi=psi, phi=phi, cosi=cosi,
+ detector='H1,L1')
+ data.make_data()
+ predicted_twoF = data.predict_fstat()
+
+ startTime = time.time()
+ theta_prior = {'F0': {'type': 'unif',
+ 'lower': F0_center-DeltaF0,
+ 'upper': F0_center+DeltaF0},
+ 'F1': {'type': 'unif',
+ 'lower': F1_center-DeltaF1,
+ 'upper': F1_center+DeltaF1},
+ 'F2': F2,
+ 'Alpha': {'type': 'unif',
+ 'lower': Alpha_center-DeltaAlpha,
+ 'upper': Alpha_center+DeltaAlpha},
+ 'Delta': {'type': 'unif',
+ 'lower': Delta_center-DeltaDelta,
+ 'upper': Delta_center+DeltaDelta},
+ }
+ theta_prior = {'F0': {'upper': 30.000006381121477, 'lower': 29.999993618878523, 'type': 'unif'}, 'F1': {'upper': 1.0143020701400378e-10, 'lower': 9.8569792985996225e-11, 'type': 'unif'}, 'F2': 0, 'Delta': {'upper': -0.20155527961896461, 'lower': -0.24155527961896459, 'type': 'unif'}, 'Alpha': {'upper': 2.8924321897264367, 'lower': 2.8524321897264366, 'type': 'unif'}}
+
+ ntemps = 2
+ log10temperature_min = -1
+ nwalkers = 100
+
+ mcmc = pyfstat.MCMCFollowUpSearch(
+ label=label, outdir=outdir,
+ sftfilepath='{}/*{}*sft'.format(outdir, data_label),
+ theta_prior=theta_prior,
+ tref=tref, minStartTime=tstart, maxStartTime=tend,
+ nwalkers=nwalkers, ntemps=ntemps,
+ log10temperature_min=log10temperature_min)
+ mcmc.run(run_setup=run_setup, create_plots=True, log_table=False,
+ gen_tex_table=False)
+ d, maxtwoF = mcmc.get_max_twoF()
+ print 'MaxtwoF = {}'.format(maxtwoF)
diff --git a/Paper/AllSkyMC/generate_table.py b/Paper/AllSkyMC/generate_table.py
index e304f107748cf58b9c78625f9c1f816cb70bf8ac..9fa71a16cc184996ade28e8430bd0473eb5e3118 100644
--- a/Paper/AllSkyMC/generate_table.py
+++ b/Paper/AllSkyMC/generate_table.py
@@ -23,8 +23,8 @@ VF0 = VF1 = 100
DeltaF0 = VF0 * np.sqrt(3)/(np.pi*Tspan)
DeltaF1 = VF1 * np.sqrt(45/4.)/(np.pi*Tspan**2)
-DeltaAlpha = 0.05
-DeltaDelta = 0.05
+DeltaAlpha = 0.02
+DeltaDelta = 0.02
depth = 100
@@ -41,8 +41,10 @@ theta = np.random.uniform(0, 2*np.pi)
F0 = F0_center + 3*np.sqrt(r)*np.cos(theta)/(np.pi**2 * Tspan**2)
F1 = F1_center + 45*np.sqrt(r)*np.sin(theta)/(4*np.pi**2 * Tspan**4)
-Alpha = 0
-Delta = 0
+Alpha_center = 0
+Delta_center = 0
+Alpha = Alpha_center + np.random.uniform(-0.5, 0.5)*DeltaAlpha
+Delta = Delta_center + np.random.uniform(-0.5, 0.5)*DeltaDelta
psi = np.random.uniform(-np.pi/4, np.pi/4)
phi = np.random.uniform(0, 2*np.pi)
@@ -57,21 +59,21 @@ data.make_data()
predicted_twoF = data.predict_fstat()
theta_prior = {'F0': {'type': 'unif',
- 'lower': F0-DeltaF0/2.,
- 'upper': F0+DeltaF0/2.},
+ 'lower': F0_center-DeltaF0,
+ 'upper': F0_center+DeltaF0},
'F1': {'type': 'unif',
- 'lower': F1-DeltaF1/2.,
- 'upper': F1+DeltaF1/2.},
+ 'lower': F1_center-DeltaF1,
+ 'upper': F1_center+DeltaF1},
'F2': F2,
'Alpha': {'type': 'unif',
- 'lower': Alpha-DeltaAlpha/2.,
- 'upper': Alpha+DeltaAlpha/2.},
+ 'lower': Alpha_center-DeltaAlpha,
+ 'upper': Alpha_center+DeltaAlpha},
'Delta': {'type': 'unif',
- 'lower': Delta-DeltaDelta/2.,
- 'upper': Delta+DeltaDelta/2.},
+ 'lower': Delta_center-DeltaDelta,
+ 'upper': Delta_center+DeltaDelta},
}
-ntemps = 1
+ntemps = 2
log10temperature_min = -1
nwalkers = 100
@@ -82,4 +84,5 @@ mcmc = pyfstat.MCMCFollowUpSearch(
tref=tref, minStartTime=tstart, maxStartTime=tend,
nwalkers=nwalkers, ntemps=ntemps,
log10temperature_min=log10temperature_min)
-mcmc.run(run_setup)
+mcmc.run(Nsegs0=20, R=10)
+#mcmc.run(run_setup)
diff --git a/Paper/allsky_setup_run_setup.tex b/Paper/allsky_setup_run_setup.tex
index 1d765771ee4de15b1a45e08e3ca6ab86da3dc83b..d98ab7f945e231e2516c301f4356b95a29502856 100644
--- a/Paper/allsky_setup_run_setup.tex
+++ b/Paper/allsky_setup_run_setup.tex
@@ -1,8 +1,8 @@
\begin{tabular}{c|cccccc}
Stage & $\Nseg$ & $\Tcoh^{\rm days}$ &$\Nsteps$ & $\V$ & $\Vsky$ & $\Vpe$ \\ \hline
-0 & 20 & 5.0 & 50 & $2{\times}10^{2}$ & 10.0 & 10.0 \\
-1 & 11 & 9.1 & 50 & $2{\times}10^{3}$ & 40.0 & 50.0 \\
-2 & 6 & 16.7 & 50 & $2{\times}10^{4}$ & $1{\times}10^{2}$ & $2{\times}10^{2}$ \\
-3 & 3 & 33.3 & 50 & $1{\times}10^{5}$ & $2{\times}10^{2}$ & $6{\times}10^{2}$ \\
-4 & 1 & 100.0 & 50,50 & $8{\times}10^{5}$ & $3{\times}10^{2}$ & $2{\times}10^{3}$ \\
+0 & 20 & 5.0 & 100 & $4{\times}10^{2}$ & 8.0 & 60.0 \\
+1 & 11 & 9.1 & 100 & $4{\times}10^{3}$ & 20.0 & $2{\times}10^{2}$ \\
+2 & 6 & 16.7 & 100 & $4{\times}10^{4}$ & 70.0 & $6{\times}10^{2}$ \\
+3 & 3 & 33.3 & 100 & $3{\times}10^{5}$ & $1{\times}10^{2}$ & $2{\times}10^{3}$ \\
+4 & 1 & 100.0 & 100,100 & $2{\times}10^{6}$ & $2{\times}10^{2}$ & $1{\times}10^{4}$ \\
\end{tabular}
diff --git a/Paper/paper_cw_mcmc.tex b/Paper/paper_cw_mcmc.tex
index d394131de3fd09ea1ff776957139ce715d57b4a9..cf8081ef101f51ffaf52ae206f8983b7542d9442 100644
--- a/Paper/paper_cw_mcmc.tex
+++ b/Paper/paper_cw_mcmc.tex
@@ -1002,7 +1002,8 @@ in Figure~\ref{fig_allsky_MC_follow_up}.
\begin{table}[htb]
\caption{Run-setup for the all-sky follow-up Monte-Carlo study, generated with
-$\mathcal{R}=10$ and $\Nseg^0=20$.}
+$\mathcal{R}=10$ and $\Nseg^0=20$. Note that the number of representative
+templates will vary over the sky. \comment{Hmm?}}
\label{tab_allsky_MC_follow_up}
\input{allsky_setup_run_setup}
\end{table}