diff --git a/pyfstat/mcmc_based_searches.py b/pyfstat/mcmc_based_searches.py
index 4c0b7c4941953918466241ee760e2811c2bb0338..3b7a6d42254f9f389bbd3b5fb013f87c99e4bf71 100644
--- a/pyfstat/mcmc_based_searches.py
+++ b/pyfstat/mcmc_based_searches.py
@@ -1934,24 +1934,23 @@ class MCMCFollowUpSearch(MCMCSemiCoherentSearch):
if args.no_template_counting:
V_vals.append([1, 1, 1])
else:
- V, Vsky, Vpe = get_V_estimate(
+ V = get_V_estimate(
rs[1], self.tref, self.minStartTime, self.maxStartTime,
DeltaOmega, DeltaFs, fiducial_freq,
self.search.detector_names, self.earth_ephem,
self.sun_ephem)
- V_vals.append([V, Vsky, Vpe])
+ V_vals.append(V)
if log_table:
logging.info('Using run-setup as follows:')
- logging.info('Stage | nburn | nprod | nsegs | Tcoh d | resetp0 |'
- ' V = Vsky x Vpe')
+ logging.info(
+ 'Stage | nburn | nprod | nsegs | Tcoh d | resetp0 | V')
for i, rs in enumerate(run_setup):
Tcoh = (self.maxStartTime - self.minStartTime) / rs[1] / 86400
if V_vals[i] is None:
vtext = 'N/A'
else:
- vtext = '{:1.0e} = {:1.0e} x {:1.0e}'.format(
- V_vals[i][0], V_vals[i][1], V_vals[i][2])
+ vtext = '{:1.0e}'.format(V_vals[i])
logging.info('{} | {} | {} | {} | {} | {} | {}'.format(
str(i).ljust(5), str(rs[0][0]).ljust(5),
str(rs[0][1]).ljust(5), str(rs[1]).ljust(5),
@@ -1960,54 +1959,28 @@ class MCMCFollowUpSearch(MCMCSemiCoherentSearch):
if gen_tex_table:
filename = '{}/{}_run_setup.tex'.format(self.outdir, self.label)
- if DeltaOmega > 0:
- with open(filename, 'w+') as f:
- f.write(r'\begin{tabular}{c|cccccc}' + '\n')
- f.write(r'Stage & $\Nseg$ & $\Tcoh^{\rm days}$ &'
- r'$\Nsteps$ & $\V$ & $\Vsky$ & $\Vpe$ \\ \hline'
- '\n')
- for i, rs in enumerate(run_setup):
- Tcoh = float(
- self.maxStartTime - self.minStartTime)/rs[1]/86400
- line = r'{} & {} & {} & {} & {} & {} & {} \\' + '\n'
- if V_vals[i][0] is None:
- V = Vsky = Vpe = 'N/A'
- else:
- V, Vsky, Vpe = V_vals[i]
- if rs[0][-1] == 0:
- nsteps = rs[0][0]
- else:
- nsteps = '{},{}'.format(*rs[0])
- line = line.format(i, rs[1], '{:1.1f}'.format(Tcoh),
- nsteps,
- helper_functions.texify_float(V),
- helper_functions.texify_float(Vsky),
- helper_functions.texify_float(Vpe))
- f.write(line)
- f.write(r'\end{tabular}' + '\n')
- else:
- with open(filename, 'w+') as f:
- f.write(r'\begin{tabular}{c|cccc}' + '\n')
- f.write(r'Stage & $\Nseg$ & $\Tcoh^{\rm days}$ &'
- r'$\Nsteps$ & $\Vpe$ \\ \hline'
- '\n')
- for i, rs in enumerate(run_setup):
- Tcoh = float(
- self.maxStartTime - self.minStartTime)/rs[1]/86400
- line = r'{} & {} & {} & {} & {} \\' + '\n'
- if V_vals[i] is None:
- V = Vsky = Vpe = 'N/A'
- else:
- V, Vsky, Vpe = V_vals[i]
- if rs[0][-1] == 0:
- nsteps = rs[0][0]
- else:
- nsteps = '{},{}'.format(*rs[0])
- line = line.format(i, rs[1], '{:1.1f}'.format(Tcoh),
- nsteps,
- helper_functions.texify_float(Vpe))
- f.write(line)
- f.write(r'\end{tabular}' + '\n')
+ with open(filename, 'w+') as f:
+ f.write(r'\begin{tabular}{c|cccc}' + '\n')
+ f.write(r'Stage & $\Nseg$ & $\Tcoh^{\rm days}$ &'
+ r'$\Nsteps$ & $\V$ \\ \hline'
+ '\n')
+ for i, rs in enumerate(run_setup):
+ Tcoh = float(
+ self.maxStartTime - self.minStartTime)/rs[1]/86400
+ line = r'{} & {} & {} & {} & {} \\' + '\n'
+ if V_vals[i] is None:
+ V = 'N/A'
+ else:
+ V = V_vals[i]
+ if rs[0][-1] == 0:
+ nsteps = rs[0][0]
+ else:
+ nsteps = '{},{}'.format(*rs[0])
+ line = line.format(i, rs[1], '{:1.1f}'.format(Tcoh),
+ nsteps,
+ helper_functions.texify_float(V))
+ f.write(line)
+ f.write(r'\end{tabular}' + '\n')
if args.setup_only:
logging.info("Exit as requested by setup_only flag")
diff --git a/pyfstat/optimal_setup_functions.py b/pyfstat/optimal_setup_functions.py
index 1c98f0d29e35c8405dbfbbe9a66a70379acd2b0e..0108246a8ba1a4e9667911a2532c8f7178b0beaf 100644
--- a/pyfstat/optimal_setup_functions.py
+++ b/pyfstat/optimal_setup_functions.py
@@ -61,11 +61,11 @@ def get_nsegs_ip1(
Vip1 = get_V_estimate(
nsegs_ip1, tref, minStartTime, maxStartTime, DeltaOmega,
DeltaFs, fiducial_freq, detector_names, earth_ephem, sun_ephem)
- if Vip1[0] is None:
+ if Vip1 is None:
return 1e6
else:
log10Vip1 = np.log10(Vip1)
- return np.abs(log10Vi[0] + log10R - log10Vip1[0])
+ return np.abs(log10Vi + log10R - log10Vip1)
res = scipy.optimize.minimize(f, .5*nsegs_i, method='Powell', tol=0.1,
options={'maxiter': 10})
nsegs_ip1 = int(res.x)
@@ -82,7 +82,7 @@ def get_nsegs_ip1(
def get_V_estimate(
nsegs, tref, minStartTime, maxStartTime, DeltaOmega, DeltaFs,
fiducial_freq, detector_names, earth_ephem, sun_ephem):
- """ Returns V, Vsky, Vpe estimated from the super-sky metric
+ """ Returns V estimated from the super-sky metric
Parameters
----------
@@ -141,4 +141,4 @@ def get_V_estimate(
Vsky = 1
if Vpe == 0:
Vpe = 1
- return (Vsky * Vpe, Vsky, Vpe)
+ return Vsky * Vpe