Source code for pycbc.inference.io.emcee_pt

# Copyright (C) 2018 Collin Capano
# This program is free software; you can redistribute it and/or modify it
# under the terms of the GNU General Public License as published by the
# Free Software Foundation; either version 3 of the License, or (at your
# self.option) any later version.
#
# This program is distributed in the hope that it will be useful, but
# WITHOUT ANY WARRANTY; without even the implied warranty of
# MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the GNU General
# Public License for more details.
#
# You should have received a copy of the GNU General Public License along
# with this program; if not, write to the Free Software Foundation, Inc.,
# 51 Franklin Street, Fifth Floor, Boston, MA  02110-1301, USA.


"""Provides I/O support for emcee_pt.
"""


import numpy

from .base_sampler import BaseSamplerFile
from .base_mcmc import EnsembleMCMCMetadataIO
from .base_multitemper import (CommonMultiTemperedMetadataIO,
                               write_samples,
                               ensemble_read_raw_samples)


[docs] class EmceePTFile(EnsembleMCMCMetadataIO, CommonMultiTemperedMetadataIO, BaseSamplerFile): """Class to handle file IO for the ``emcee`` sampler.""" name = 'emcee_pt_file' @property def betas(self): """The betas that were used.""" return self[self.sampler_group].attrs["betas"]
[docs] def write_samples(self, samples, **kwargs): r"""Writes samples to the given file. Calls :py:func:`base_multitemper.write_samples`. See that function for details. Parameters ---------- samples : dict The samples to write. Each array in the dictionary should have shape ntemps x nwalkers x niterations. \**kwargs : All other keyword arguments are passed to :py:func:`base_multitemper.write_samples`. """ write_samples(self, samples, **kwargs)
[docs] def read_raw_samples(self, fields, **kwargs): r"""Base function for reading samples. Calls :py:func:`base_multitemper.ensemble_read_raw_samples`. See that function for details. Parameters ----------- fields : list The list of field names to retrieve. \**kwargs : All other keyword arguments are passed to :py:func:`base_multitemper.ensemble_read_raw_samples`. Returns ------- dict A dictionary of field name -> numpy array pairs. """ return ensemble_read_raw_samples(self, fields, **kwargs)
[docs] def write_sampler_metadata(self, sampler): """Adds writing betas to MultiTemperedMCMCIO. """ super(EmceePTFile, self).write_sampler_metadata(sampler) self[self.sampler_group].attrs["betas"] = sampler.betas
[docs] def read_acceptance_fraction(self, temps=None, walkers=None): """Reads the acceptance fraction. Parameters ----------- temps : (list of) int, optional The temperature index (or a list of indices) to retrieve. If None, acfs from all temperatures and all walkers will be retrieved. walkers : (list of) int, optional The walker index (or a list of indices) to retrieve. If None, samples from all walkers will be obtained. Returns ------- array Array of acceptance fractions with shape (requested temps, requested walkers). """ group = self.sampler_group + '/acceptance_fraction' if walkers is None: wmask = numpy.ones(self.nwalkers, dtype=bool) else: wmask = numpy.zeros(self.nwalkers, dtype=bool) wmask[walkers] = True if temps is None: tmask = numpy.ones(self.ntemps, dtype=bool) else: tmask = numpy.zeros(self.ntemps, dtype=bool) tmask[temps] = True return self[group][:][numpy.ix_(tmask, wmask)]
[docs] def write_acceptance_fraction(self, acceptance_fraction): """Write acceptance_fraction data to file. Results are written to ``[sampler_group]/acceptance_fraction``; the resulting dataset has shape (ntemps, nwalkers). Parameters ----------- acceptance_fraction : numpy.ndarray Array of acceptance fractions to write. Must have shape ntemps x nwalkers. """ # check assert acceptance_fraction.shape == (self.ntemps, self.nwalkers), ( "acceptance fraction must have shape ntemps x nwalker") group = self.sampler_group + '/acceptance_fraction' try: self[group][:] = acceptance_fraction except KeyError: # dataset doesn't exist yet, create it self[group] = acceptance_fraction