Commit 901d6ad9 authored by Gregory Ashton's avatar Gregory Ashton
Browse files

Minor modifications to the logging output and reflow args

parent a6d1a00b
......@@ -478,8 +478,9 @@ class MCMCSearch(BaseSearchClass):
def __init__(self, label, outdir, sftfilepath, theta_prior, tref,
tstart, tend, nsteps=[100, 100, 100], nwalkers=100, ntemps=1,
log10temperature_min=-5, theta_initial=None, scatter_val=1e-4,
binary=False, BSGL=False, minCoverFreq=None, maxCoverFreq=None,
detector=None, earth_ephem=None, sun_ephem=None, theta0_idx=0):
binary=False, BSGL=False, minCoverFreq=None,
maxCoverFreq=None, detector=None, earth_ephem=None,
sun_ephem=None, theta0_idx=0):
"""
Parameters
label, outdir: str
......@@ -699,8 +700,8 @@ class MCMCSearch(BaseSearchClass):
logging.info('Running {}/{} initialisation with {} steps'.format(
j+1, ninit_steps, n))
sampler = self.run_sampler_with_progress_bar(sampler, n, p0)
logging.info("Mean acceptance fraction: {0:.3f}"
.format(np.mean(sampler.acceptance_fraction)))
logging.info("Mean acceptance fraction: {}"
.format(np.mean(sampler.acceptance_fraction, axis=1)))
if self.ntemps > 1:
logging.info("Tswap acceptance fraction: {}"
.format(sampler.tswap_acceptance_fraction))
......@@ -721,8 +722,8 @@ class MCMCSearch(BaseSearchClass):
logging.info('Running final burn and prod with {} steps'.format(
nburn+nprod))
sampler = self.run_sampler_with_progress_bar(sampler, nburn+nprod, p0)
logging.info("Mean acceptance fraction: {0:.3f}"
.format(np.mean(sampler.acceptance_fraction)))
logging.info("Mean acceptance fraction: {}"
.format(np.mean(sampler.acceptance_fraction, axis=1)))
if self.ntemps > 1:
logging.info("Tswap acceptance fraction: {}"
.format(sampler.tswap_acceptance_fraction))
......@@ -749,8 +750,8 @@ class MCMCSearch(BaseSearchClass):
samples_plt = copy.copy(self.samples)
theta_symbols_plt = copy.copy(self.theta_symbols)
theta_symbols_plt = [s.replace('_{glitch}', r'_\textrm{glitch}') for s
in theta_symbols_plt]
theta_symbols_plt = [s.replace('_{glitch}', r'_\textrm{glitch}')
for s in theta_symbols_plt]
if tglitch_ratio:
for j, k in enumerate(self.theta_keys):
......@@ -1653,7 +1654,7 @@ class Writer(BaseSearchClass):
if self.dtglitch is None or self.dtglitch == self.duration:
self.tbounds = [self.tstart, self.tend]
elif np.size(self.dtglitch) == 1:
self.tbounds = [self.tstart, self.tstart+self.dtglitch, self.tend]
self.tbounds = [self.tstart, self.tstart+self.dtglitch, self.tend]
else:
self.tglitch = self.tstart + np.array(self.dtglitch)
self.tbounds = [self.tstart] + list(self.tglitch) + [self.tend]
......
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