Source code for

# Copyright (C) 2019 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
# 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 abstract base class for all samplers."""

import time
from abc import (ABCMeta, abstractmethod)

from .base_hdf import BaseInferenceFile

[docs]class BaseSamplerFile(BaseInferenceFile, metaclass=ABCMeta): """Base HDF class for all samplers. This adds abstract methods ``write_resume_point`` and ``write_sampler_metadata`` to :py:class:`BaseInferenceFile`. """
[docs] def write_run_start_time(self): """Writes the current (UNIX) time to the file. Times are stored as a list in the file's ``attrs``, with name ``run_start_time``. If the attrbute already exists, the current time is appended. Otherwise, the attribute will be created and time added. """ attrname = "run_start_time" try: times = self.attrs[attrname].tolist() except KeyError: times = [] times.append(time.time()) self.attrs[attrname] = times
@property def run_start_time(self): """The (UNIX) time pycbc inference began running. If the run resumed from a checkpoint, the time the last checkpoint started is reported. """ return self.attrs['run_start_time'][-1]
[docs] def write_run_end_time(self): """"Writes the curent (UNIX) time as the ``run_end_time`` attribute. """ self.attrs["run_end_time"] = time.time()
@property def run_end_time(self): """The (UNIX) time pycbc inference finished. """ return self.attrs["run_end_time"]
[docs] @abstractmethod def write_resume_point(self): """Should write the point that a sampler starts up. How the resume point is indexed is up to the sampler. For example, MCMC samplers use the number of iterations that are stored in the checkpoint file. """ pass
[docs] @abstractmethod def write_sampler_metadata(self, sampler): """This should write the given sampler's metadata to the file. This should also include the model's metadata. """ pass
[docs] def update_checkpoint_history(self): """Writes a copy of relevant metadata to the file's checkpoint history. All data are written to ``sampler_info/checkpoint_history``. If the group does not exist yet, it will be created. This function writes the current time and the time since the last checkpoint to the file. It will also call :py:func:`_update_sampler_history` to write sampler-specific history. """ path = '/'.join([self.sampler_group, 'checkpoint_history']) try: history = self[path] except KeyError: # assume history doesn't exist yet self.create_group(path) history = self[path] # write the checkpoint time current_time = time.time() self.write_data('checkpoint_time', current_time, path=path, append=True) # get the amount of time since the last checkpoint checkpoint_times = history['checkpoint_time'][()] if len(checkpoint_times) == 1: # this is the first checkpoint, get the run time for comparison lasttime = self.run_start_time else: lasttime = checkpoint_times[-2] # if a resume happened since the last checkpoint, use the resume # time instad if lasttime < self.run_start_time: lasttime = self.run_start_time self.write_data('checkpoint_dt', current_time-lasttime, path=path, append=True) # write any sampler-specific history self._update_sampler_history()
def _update_sampler_history(self): """Writes sampler-specific history to the file. This function does nothing. Classes that inherit from it may override it to add any extra information they would like written. This is called by :py:func:`update_checkpoint_history`. """ pass
[docs] def validate(self): """Runs a validation test. This checks that a samples group exist, and that there are more than one sample stored to it. Returns ------- bool : Whether or not the file is valid as a checkpoint file. """ try: group = '{}/{}'.format(self.samples_group, self.variable_params[0]) checkpoint_valid = self[group].size != 0 except KeyError: checkpoint_valid = False return checkpoint_valid