Source code for pycbc.distributions

# Copyright (C)  2016 Collin Capano, Christopher M. Biwer, Alex Nitz
# 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.
This modules provides classes and functions for drawing and calculating the
probability density function of distributions.
# imports needed for functions below
from pycbc.workflow import ConfigParser as _ConfigParser
from pycbc.distributions import constraints
from pycbc import VARARGS_DELIM as _VARARGS_DELIM

# Promote some classes/functions to the distributions name space
from pycbc.distributions.angular import UniformAngle, SinAngle, CosAngle, \
from pycbc.distributions.arbitrary import Arbitrary, FromFile
from pycbc.distributions.gaussian import Gaussian
from pycbc.distributions.power_law import UniformPowerLaw, UniformRadius
from pycbc.distributions.sky_location import UniformSky
from pycbc.distributions.uniform import Uniform
from pycbc.distributions.uniform_log import UniformLog10
from pycbc.distributions.spins import IndependentChiPChiEff
from pycbc.distributions.qnm import UniformF0Tau
from pycbc.distributions.joint import JointDistribution
from pycbc.distributions.external import External
from pycbc.distributions.fixedsamples import FixedSamples

# a dict of all available distributions
distribs = { : IndependentChiPChiEff, : Arbitrary, : FromFile, : Gaussian, : UniformPowerLaw, : UniformRadius, : Uniform, : UniformAngle, : CosAngle, : SinAngle, : UniformSolidAngle, : UniformSky, : UniformLog10, : UniformF0Tau, External, FixedSamples

[docs]def read_distributions_from_config(cp, section="prior"): """Returns a list of PyCBC distribution instances for a section in the given configuration file. Parameters ---------- cp : WorflowConfigParser An open config file to read. section : {"prior", string} Prefix on section names from which to retrieve the distributions. Returns ------- list A list of the parsed distributions. """ dists = [] variable_args = [] for subsection in cp.get_subsections(section): name = cp.get_opt_tag(section, "name", subsection) dist = distribs[name].from_config(cp, section, subsection) if set(dist.params).isdisjoint(variable_args): dists.append(dist) variable_args += dist.params else: raise ValueError("Same parameter in more than one distribution.") return dists
def _convert_liststring_to_list(lstring): """Checks if an argument of the configuration file is a string of a list and returns the corresponding list (of strings). The argument is considered to be a list if it starts with '[' and ends with ']'. List elements should be comma separated. For example, passing `'[foo bar, cat]'` will result in `['foo bar', 'cat']` being returned. If the argument does not start and end with '[' and ']', the argument will just be returned as is. """ if lstring[0]=='[' and lstring[-1]==']': lstring = [str(lstring[1:-1].split(',')[n].strip().strip("'")) for n in range(len(lstring[1:-1].split(',')))] return lstring
[docs]def read_params_from_config(cp, prior_section='prior', vargs_section='variable_args', sargs_section='static_args'): """Loads static and variable parameters from a configuration file. Parameters ---------- cp : WorkflowConfigParser An open config parser to read from. prior_section : str, optional Check that priors exist in the given section. Default is 'prior.' vargs_section : str, optional The section to get the parameters that will be varied/need priors defined for them. Default is 'variable_args'. sargs_section : str, optional The section to get the parameters that will remain fixed. Default is 'static_args'. Returns ------- variable_args : list The names of the parameters to vary in the PE run. static_args : dict Dictionary of names -> values giving the parameters to keep fixed. """ # sanity check that each parameter in [variable_args] has a priors section variable_args = cp.options(vargs_section) subsections = cp.get_subsections(prior_section) tags = set([p for tag in subsections for p in tag.split('+')]) missing_prior = set(variable_args) - tags if any(missing_prior): raise KeyError("You are missing a priors section in the config file " "for parameter(s): {}".format(', '.join(missing_prior))) # sanity check that each parameter with a priors section is in # [variable_args] missing_variable = tags - set(variable_args) if any(missing_variable): raise KeyError("Prior section found for parameter(s) {} but not " "listed as variable parameter(s)." .format(', '.join(missing_variable))) # get static args try: static_args = dict([(key, cp.get_opt_tags(sargs_section, key, [])) for key in cp.options(sargs_section)]) except _ConfigParser.NoSectionError: static_args = {} # sanity check that each parameter in [variable_args] # is not repeated in [static_args] for arg in variable_args: if arg in static_args: raise KeyError("Parameter {} found both in static_args and in " "variable_args sections.".format(arg)) # try converting values to float for key in static_args: val = static_args[key] try: # the following will raise a ValueError if it cannot be cast to # float (as we would expect for string arguments) static_args[key] = float(val) except ValueError: # try converting to a list of strings; this function will just # return val if it does not begin (end) with [ (]) static_args[key] = _convert_liststring_to_list(val) return variable_args, static_args
[docs]def read_constraints_from_config(cp, transforms=None, constraint_section='constraint'): """Loads parameter constraints from a configuration file. Parameters ---------- cp : WorkflowConfigParser An open config parser to read from. transforms : list, optional List of transforms to apply to parameters before applying constraints. constraint_section : str, optional The section to get the constraints from. Default is 'constraint'. Returns ------- list List of ``Constraint`` objects. Empty if no constraints were provided. """ cons = [] for subsection in cp.get_subsections(constraint_section): name = cp.get_opt_tag(constraint_section, "name", subsection) constraint_arg = cp.get_opt_tag( constraint_section, "constraint_arg", subsection) # get any other keyword arguments kwargs = {} section = constraint_section + "-" + subsection extra_opts = [key for key in cp.options(section) if key not in ["name", "constraint_arg"]] for key in extra_opts: val = cp.get(section, key) if key == "required_parameters": val = val.split(_VARARGS_DELIM) else: try: val = float(val) except ValueError: pass kwargs[key] = val cons.append(constraints.constraints[name](constraint_arg, transforms=transforms, **kwargs)) return cons