# Copyright (C) 2020 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
# 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.
"""Jump proposals that use a bounded normal distribution."""
from epsie import proposals as epsie_proposals
from .normal import (epsie_from_config, epsie_adaptive_from_config,
epsie_at_adaptive_from_config)
[docs]class EpsieBoundedNormal(epsie_proposals.BoundedNormal):
"""Adds ``from_config`` method to epsie's bounded normal proposal."""
[docs] @classmethod
def from_config(cls, cp, section, tag):
r"""Loads a proposal from a config file.
This calls :py:func:`epsie_from_config` with ``cls`` set to
:py:class:`epsie.proposals.BoundedNormal` and ``with_boundaries`` set
to True. See that function for details on options that can be read.
Example::
[jump_proposal-mchrip+q]
name = bounded_normal
min-q = 1
max-q = 8
min-mchirp = 20
max-mchirp = 80
Parameters
----------
cp : WorkflowConfigParser instance
Config file to read from.
section : str
The name of the section to look in.
tag : str
:py:const:`pycbc.VARARGS_DELIM` separated list of parameter names
to create proposals for.
Returns
-------
:py:class:`epsie.proposals.BoundedNormal`:
A bounded normal proposal for use with ``epsie`` samplers.
"""
return epsie_from_config(cls, cp, section, tag, with_boundaries=True)
[docs]class EpsieAdaptiveBoundedNormal(epsie_proposals.AdaptiveBoundedNormal):
"""Adds ``from_config`` method to epsie's adaptive normal proposal."""
[docs] @classmethod
def from_config(cls, cp, section, tag):
"""Loads a proposal from a config file.
This calls :py:func:`epsie_adaptive_from_config` with ``cls`` set to
:py:class:`epsie.proposals.AdaptiveBoundedNormal`. See that function
for details on options that can be read.
Example::
[jump_proposal-q]
name = adaptive_bounded_normal
adaptation-duration = 1000
min-q = 1
max-q = 8
Parameters
----------
cp : WorkflowConfigParser instance
Config file to read from.
section : str
The name of the section to look in.
tag : str
:py:const:`pycbc.VARARGS_DELIM` separated list of parameter names
to create proposals for.
Returns
-------
:py:class:`epsie.proposals.AdaptiveBoundedNormal`:
An adaptive normal proposal for use with ``epsie`` samplers.
"""
return epsie_adaptive_from_config(cls, cp, section, tag)
[docs]class EpsieATAdaptiveBoundedNormal(epsie_proposals.ATAdaptiveBoundedNormal):
"""Adds ``from_config`` method to epsie's adaptive bounded proposal."""
[docs] @classmethod
def from_config(cls, cp, section, tag):
"""Loads a proposal from a config file.
This calls :py:func:`epsie_adaptive_from_config` with ``cls`` set to
:py:class:`epsie.proposals.AdaptiveBoundedProposal`. See that function
for details on options that can be read.
Example::
[jump_proposal-q]
name = adaptive_bounded_proposal
min-q = 1
max-q = 8
Parameters
----------
cp : WorkflowConfigParser instance
Config file to read from.
section : str
The name of the section to look in.
tag : str
:py:const:`pycbc.VARARGS_DELIM` separated list of parameter names
to create proposals for.
Returns
-------
:py:class:`epsie.proposals.AdaptiveBoundedProposal`:
An adaptive bounded proposal for use with ``epsie`` samplers.
"""
return epsie_at_adaptive_from_config(cls, cp, section, tag,
with_boundaries=True)