def main(args):
utils.mkdir(args.output_dir)
for cls in Plot.registry:
try:
cls.make(args.dirname, args.output_dir, args.prefix, args.type)
except IOError as err:
print(err)
def main(args):
#Read the command line arguments and load the
#ini file that created the run
args = parser.parse_args(args)
#Make the directory for the outputs to go in.
mkdir(args.outdir)
outputs = {}
for i, ini_filename in enumerate(args.inifile):
sampler, ini = read_input(ini_filename, args.text, args.weights)
processor_class = postprocessor_for_sampler(sampler)
#We do not know how to postprocess everything.
if processor_class is None:
print "I do not know how to postprocess output from the %s sampler" % sampler
sampler = None
continue
#Create and run the postprocessor
processor = processor_class(ini, ini_filename, i, **vars(args))
#Inherit any plots from the previous postprocessor
#so we can make plots with multiple datasets on
processor.outputs.update(outputs)
#We can load extra plots to make from a python
#script here
if args.extra:
processor.load_extra_steps(args.extra)
#Run the postprocessor and make the outputs for this chain
processor.run()
#Save the outputs ready for the next post-processor in case
#they want to add to it (e.g. two constriants on the same axes)
outputs = processor.outputs
if sampler is None:
return
#Run any tweaks that the user specified
if args.tweaks:
tweaks = Tweaks.instances_from_file(args.tweaks)
for tweak in tweaks:
processor.apply_tweaks(tweak)
#Save all the image files and close the text files
processor.finalize()
def sample(self):
n_grade = 2 if self.pipeline.do_fast_slow else 1
grade_dims = (ct.c_int * n_grade)()
grade_frac = (ct.c_double * n_grade)()
if self.pipeline.do_fast_slow:
grade_dims[0] = self.pipeline.n_slow_params
grade_dims[1] = self.pipeline.n_fast_params
grade_frac[0] = 1 - self.fast_fraction
grade_frac[1] = self.fast_fraction
print(
"Telling Polychord to spend fraction {} if its time in the fast subspace (adjust with fast_fraction option)"
.format(self.fast_fraction))
else:
grade_dims[0] = self.pipeline.nvaried
grade_frac[0] = 1.0
n_nlives = 0
loglikes = (ct.c_double * n_nlives)()
nlives = (ct.c_int * n_nlives)()
base_dir = self.base_dir.encode('ascii')
polychord_outfile_root = self.polychord_outfile_root.encode('ascii')
output_to_file = len(polychord_outfile_root) > 0
if output_to_file:
mkdir(self.base_dir)
mkdir(os.path.join(self.base_dir, "clusters"))
if self.num_repeats == 0:
num_repeats = 3 * grade_dims[0]
print(
"Polychord num_repeats = {} (3 * n_slow_params [{}])".format(
num_repeats, grade_dims[0]))
else:
num_repeats = self.num_repeats
print("Polychord num_repeats = {} (from parameter file)".format(
num_repeats))
self._run(
self.wrapped_likelihood, #loglike,
self.wrapped_prior, #prior,
self.wrapped_output_logger, #dumper,
self.live_points, #nlive
num_repeats, #nrepeats
self.nprior, #nprior
True, #do_clustering
self.feedback, #feedback
self.tolerance, #precision_criterion
self.log_zero, #logzero
self.max_iterations, #max_ndead
self.boost_posteriors, #boost_posterior
self.weighted_posteriors, #posteriors
self.equally_weighted_posteriors, #equals
self.cluster_posteriors, #cluster_posteriors
True, #write_resume - always
False, #write_paramnames
self.resume, #read_resume
output_to_file, #write_stats
output_to_file, #write_live
output_to_file, #write_dead
output_to_file, #write_prior
self.compression_factor, #compression_factor
self.ndim, #nDims
self.nderived, #nDerived
base_dir, #base_dir
polychord_outfile_root, #file_root
n_grade, #nGrade
grade_frac, #grade_frac
grade_dims, #grade_dims
n_nlives, #n_nlives
loglikes, #loglikes
nlives, #nlives
self.random_seed, #seed
)
self.converged = True
def main(args):
#Read the command line arguments and load the
#ini file that created the run
args = parser.parse_args(args)
for ini_filename in args.inifile:
if not os.path.exists(ini_filename):
raise ValueError("The file (or directory) {} does not exist.".format(ini_filename))
#Make the directory for the outputs to go in.
mkdir(args.outdir)
outputs = {}
#Deal with legends, if any
if args.legend:
labels = args.legend.split("|")
if len(labels)!=len(args.inifile):
raise ValueError("You specified {} legend names but {} files to plot".format(len(labels), len(args.inifile)))
else:
labels = args.inifile
if len(args.inifile)>1 and args.run_max_post:
raise ValueError("Can only use the --run-max-post argument with a single parameter file for now")
for i,ini_filename in enumerate(args.inifile):
sampler, ini = read_input(ini_filename, args.text, args.weights)
processor_class = postprocessor_for_sampler(sampler.split()[-1])
#We do not know how to postprocess everything.
if processor_class is None:
print("I do not know how to postprocess output from the %s sampler"%sampler)
sampler = None
continue
#Create and run the postprocessor
processor = processor_class(ini, labels[i], i, **vars(args))
#Inherit any plots from the previous postprocessor
#so we can make plots with multiple datasets on
processor.outputs.update(outputs)
#We can load extra plots to make from a python
#script here
if args.extra:
processor.load_extra_steps(args.extra)
#Optionally add a step in which we
if args.run_max_post:
processor.add_rerun_bestfit_step(args.run_max_post)
#Run the postprocessor and make the outputs for this chain
processor.run()
#Save the outputs ready for the next post-processor in case
#they want to add to it (e.g. two constriants on the same axes)
outputs = processor.outputs
if sampler is None:
return
#Run any tweaks that the user specified
if args.tweaks:
tweaks = Tweaks.instances_from_file(args.tweaks)
for tweak in tweaks:
processor.apply_tweaks(tweak)
#Save all the image files and close the text files
processor.finalize()