def _generate_from_current(self):
"""Generates a waveform from the current parameters.
"""
try:
new_waveform = self.generator(**self.current_params)
return new_waveform
except RuntimeError as e:
if self.record_failures:
import h5py
from pycbc.io.hdf import dump_state
global failed_counter
if self.mpi_enabled:
outname = 'failed/params_%s.hdf' % self.mpi_rank
else:
outname = 'failed/params.hdf'
if not os.path.exists('failed'):
os.makedirs('failed')
with h5py.File(outname) as f:
dump_state(self.current_params, f,
dsetname=str(failed_counter))
failed_counter += 1
# we'll get a RuntimeError if lalsimulation failed to generate
# the waveform for whatever reason
strparams = ' | '.join(['{}: {}'.format(
p, str(val)) for p, val in self.current_params.items()])
raise FailedWaveformError("Failed to generate waveform with "
"parameters:\n{}\nError was: {}"
.format(strparams, e))
def save_state(self, tnum_finished, filename):
"""Save the current state of the background buffers"""
from pycbc.io.hdf import dump_state
self.tnum_finished = tnum_finished
logging.info('Writing checkpoint file at template %s', tnum_finished)
fp = h5py.File(filename, 'w')
dump_state(self, fp, protocol=cPickle.HIGHEST_PROTOCOL)
fp.close()
def write_results(self, filename):
"""Writes samples, model stats, acceptance fraction, and random state
to the given file.
Parameters
-----------
filename : str
The file to write to. The file is opened using the ``io`` class
in an an append state.
"""
with self.io(filename, 'a') as fp:
# write samples
fp.write_samples(self.samples, self.samples.keys())
# write log evidence
fp.write_logevidence(self.logz, self.logz_err)
# write full ultranest formatted results
dump_state(self.result, fp,
path='sampler_info',
dsetname='presult')
def write_pickled_data_into_checkpoint_file(self, state):
"""Dump the sampler state into checkpoint file
"""
if 'sampler_info/saved_state' not in self:
self.create_group('sampler_info/saved_state')
dump_state(state, self, path='sampler_info/saved_state')