Source code for pycbc.distributions.utils

# Copyright (C) 2021  Shichao Wu
# 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
# 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.

# =============================================================================
#                                   Preamble
# =============================================================================
This module provides functions for drawing samples from a standalone .ini file
in a Python script, rather than in the command line.
import logging
import numpy as np

from pycbc.types.config import InterpolatingConfigParser
from pycbc import transforms
from pycbc import distributions

logger = logging.getLogger('pycbc.distributions.utils')

[docs]def prior_from_config(cp, prior_section='prior'): """Loads a prior distribution from the given config file. Parameters ---------- cp : pycbc.workflow.WorkflowConfigParser The config file to read. sections : list of str, optional The sections to retrieve the prior from. If ``None`` (the default), will look in sections starting with 'prior'. Returns ------- distributions.JointDistribution The prior distribution. """ # Read variable and static parameters from the config file variable_params, static_params = distributions.read_params_from_config( cp, prior_section=prior_section, vargs_section='variable_params', sargs_section='static_params') # Read waveform_transforms to apply to priors from the config file if any(cp.get_subsections('waveform_transforms')): waveform_transforms = transforms.read_transforms_from_config( cp, 'waveform_transforms') else: waveform_transforms = None # Read constraints to apply to priors from the config file constraints = distributions.read_constraints_from_config( cp, transforms=waveform_transforms, static_args=static_params) # Get PyCBC distribution instances for each variable parameter in the # config file dists = distributions.read_distributions_from_config(cp, prior_section) # construct class that will return draws from the prior return distributions.JointDistribution(variable_params, *dists, **{"constraints": constraints})
[docs]def draw_samples_from_config(path, num=1, seed=150914): r""" Generate sampling points from a standalone .ini file. Parameters ---------- path : str The path to the .ini file. num : int The number of samples. seed: int The random seed for sampling. Returns -------- samples : The parameter values and names of sample(s). Examples -------- Draw a sample from the distribution defined in the .ini file: >>> import numpy as np >>> from pycbc.distributions.utils import draw_samples_from_config >>> # A path to the .ini file. >>> CONFIG_PATH = "./pycbc_bbh_prior.ini" >>> random_seed = np.random.randint(low=0, high=2**32-1) >>> sample = draw_samples_from_config( >>> path=CONFIG_PATH, num=1, seed=random_seed) >>> # Print all parameters. >>> print(sample.fieldnames) >>> print(sample) >>> # Print a certain parameter, for example 'mass1'. >>> print(sample[0]['mass1']) """ np.random.seed(seed) # Initialise InterpolatingConfigParser class. config_parser = InterpolatingConfigParser() # Read the file file = open(path, 'r') config_parser.read_file(file) file.close() # Construct class that will draw the samples. prior_dists = prior_from_config(cp=config_parser) # Draw samples from prior distribution. samples = prior_dists.rvs(size=int(num)) # Apply parameter transformation. if any(config_parser.get_subsections('waveform_transforms')): waveform_transforms = transforms.read_transforms_from_config( config_parser, 'waveform_transforms') samples = transforms.apply_transforms(samples, waveform_transforms) return samples