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OpenMC/openmc/settings.py

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from collections import Iterable
from numbers import Real, Integral
import warnings
from xml.etree import ElementTree as ET
import sys
import numpy as np
from openmc.clean_xml import *
from openmc.checkvalue import (check_type, check_length, check_value,
check_greater_than, check_less_than)
if sys.version_info[0] >= 3:
basestring = str
class SettingsFile(object):
"""Settings file used for an OpenMC simulation. Corresponds directly to the
settings.xml input file.
Attributes
----------
batches : int
Number of batches to simulate
generations_per_batch : int
Number of generations per batch
inactive : int
Number of inactive batches
particles : int
Number of particles per generation
keff_trigger : dict
Dictionary defining a trigger on eigenvalue. The dictionary must have
two keys, 'type' and 'threshold'. Acceptable values corresponding to
type are 'variance', 'std_dev', and 'rel_err'. The threshold value
should be a float indicating the variance, standard deviation, or
relative error used.
source_file : str
Path to a source file
output : dict
Dictionary indicating what files to output. Valid keys are 'summary',
'cross_sections', 'tallies', and 'distribmats'. Values corresponding to
each key should be given as a boolean value.
output_path : str
Path to write output to
verbosity : int
Verbosity during simulation between 1 and 10
statepoint_batches : Iterable of int
List of batches at which to write statepoint files
statepoint_interval : int
Number of batches after which a new statepoint file should be written
sourcepoint_batches : Iterable of int
List of batches at which to write source files
sourcepoint_interval : int
Number of batches after which a new source file should be written
sourcepoint_separate : bool
Indicate whether the souce should be written as part of the statepoint
file or on its own
sourcepoint_write : bool
Indicate whether the source should be written at all
sourcepoint_overwrite : bool
Indicate whether to
confidence_intervals : bool
If True, uncertainties on tally results will be reported as the
half-width of the 95% two-sided confidence interval. If False,
uncertainties on tally results will be reported as the sample standard
deviation.
cross_sections : str
Indicates the path to an XML cross section listing file (usually named
cross_sections.xml). If it is not set, the :envvar:`CROSS_SECTIONS`
environment variable will be used to find the path to the XML cross
section listing.
energy_grid : str
Set the method used to search energy grids. Acceptable values are
'nuclide', 'logarithm', and 'material-union'.
ptables : bool
Determine whether probability tables are used.
run_cmfd : bool
Indicate if coarse mesh finite difference acceleration is to be used
seed : int
Seed for the linear congruential pseudorandom number generator
survival_biasing : bool
Indicate whether survival biasing is to be used
weight : float
Weight cutoff below which particle undergo Russian roulette
weight_avg : float
Weight assigned to particles that are not killed after Russian roulette
entropy_dimension : tuple or list
Number of Shannon entropy mesh cells in the x, y, and z directions,
respectively
entropy_lower_left : tuple or list
Coordinates of the lower-left point of the Shannon entropy mesh
entropy_upper_right : tuple or list
Coordinates of the upper-right point of the Shannon entropy mesh
trigger_active : bool
Indicate whether tally triggers are used
trigger_max_batches : int
Maximum number of batches simulated. If this is set, the number of
batches specified via ``batches`` is interpreted as the minimum number
of batches
trigger_batch_interval : int
Number of batches in between convergence checks
no_reduce : bool
Indicate that all user-defined and global tallies should not be reduced
across processes in a parallel calculation.
threads : int
Number of OpenMP threads
trace : tuple or list
Show detailed information about a single particle, indicated by three
integers: the batch number, generation number, and particle number
track : tuple or list
Specify particles for which track files should be written. Each particle
is identified by a triplet with the batch number, generation number, and
particle number.
ufs_dimension : tuple or list
Number of uniform fission site (UFS) mesh cells in the x, y, and z
directions, respectively
ufs_lower_left : tuple or list
Coordinates of the lower-left point of the UFS mesh
ufs_upper_right : tuple or list
Coordinates of the upper-right point of the UFS mesh
"""
def __init__(self):
# Eigenvalue subelement
self._batches = None
self._generations_per_batch = None
self._inactive = None
self._particles = None
self._keff_trigger = None
# Source subelement
self._source_subelement = None
self._source_file = None
self._source_space_type = None
self._source_space_params = None
self._source_angle_type = None
self._source_angle_params = None
self._source_energy_type = None
self._source_energy_params = None
self._confidence_intervals = None
self._cross_sections = None
self._energy_grid = None
self._ptables = None
self._run_cmfd = None
self._seed = None
self._survival_biasing = None
# Entropy subelement
self._entropy_dimension = None
self._entropy_lower_left = None
self._entropy_upper_right = None
# Trigger subelement
self._trigger_subelement = None
self._trigger_active = None
self._trigger_max_batches = None
self._trigger_batch_interval = None
self._output = None
self._output_path = None
# Statepoint subelement
self._statepoint_batches = None
self._statepoint_interval = None
self._sourcepoint_batches = None
self._sourcepoint_interval = None
self._sourcepoint_separate = None
self._sourcepoint_write = None
self._sourcepoint_overwrite = None
self._threads = None
self._no_reduce = None
self._verbosity = None
self._trace = None
self._track = None
# Cutoff subelement
self._weight = None
self._weight_avg = None
# Uniform fission source subelement
self._ufs_dimension = 1
self._ufs_lower_left = None
self._ufs_upper_right = None
# Domain decomposition subelement
self._dd_mesh_dimension = None
self._dd_mesh_lower_left = None
self._dd_mesh_upper_right = None
self._dd_nodemap = None
self._dd_allow_leakage = False
self._dd_count_interactions = False
self._settings_file = ET.Element("settings")
self._eigenvalue_subelement = None
self._source_element = None
@property
def batches(self):
return self._batches
@property
def generations_per_batch(self):
return self._generations_per_batch
@property
def inactive(self):
return self._inactive
@property
def particles(self):
return self._particles
@property
def keff_trigger(self):
return self._keff_trigger
@property
def source_file(self):
return self._source_file
@property
def source_space_type(self):
return self._source_space_type
@property
def source_space_params(self):
return self._source_space_params
@property
def source_angle_type(self):
return self._source_angle_type
@property
def source_angle_params(self):
return self._source_angle_params
@property
def source_energy_type(self):
return self._source_energy_type
@property
def source_energy_params(self):
return self._source_energy_params
@property
def confidence_intervals(self):
return self._confidence_intervals
@property
def cross_sections(self):
return self._cross_sections
@property
def energy_grid(self):
return self._energy_grid
@property
def ptables(self):
return self._ptables
@property
def run_cmfd(self):
return self._run_cmfd
@property
def seed(self):
return self._seed
@property
def survival_biasing(self):
return self._survival_biasing
@property
def entropy_dimension(self):
return self._entropy_dimension
@property
def entropy_lower_left(self):
return self._entropy_lower_left
@property
def entropy_upper_right(self):
return self._entropy_upper_right
@property
def trigger_active(self):
return self._trigger_active
@property
def trigger_max_batches(self):
return self._trigger_max_batches
@property
def trigger_batch_interval(self):
return self._batch_interval
@property
def output(self):
return self._output
@property
def output_path(self):
return self._output_path
@property
def statepoint_batches(self):
return self._statepoint_batches
@property
def statepoint_interval(self):
return self._statepoint_interval
@property
def sourcepoint_batches(self):
return self._sourcepoint_interval
@property
def sourcepoint_interval(self):
return self._sourcepoint_interval
@property
def sourcepoint_separate(self):
return self._sourcepoint_separate
@property
def sourcepoint_write(self):
return self._sourcepoint_write
@property
def sourcepoint_overwrite(self):
return self._sourcepoint_overwrite
@property
def threads(self):
return self._threads
@property
def no_reduce(self):
return self._no_reduce
@property
def verbosity(self):
return self._verbosity
@property
def trace(self):
return self._trace
@property
def track(self):
return self._track
@property
def weight(self):
return self._weight
@property
def weight_avg(self):
return self._weight_avg
@property
def ufs_dimension(self):
return self._ufs_dimension
@property
def ufs_lower_left(self):
return self._ufs_lower_left
@property
def ufs_upper_right(self):
return self._ufs_upper_right
@property
def dd_mesh_dimension(self):
return self._dd_mesh_dimension
@property
def dd_mesh_lower_left(self):
return self._dd_mesh_lower_left
@property
def dd_mesh_upper_right(self):
return self._dd_mesh_upper_right
@property
def dd_nodemap(self):
return self._dd_nodemap
@property
def dd_allow_leakage(self):
return self._dd_allow_leakage
@property
def dd_count_interactions(self):
return self._dd_count_interactions
@batches.setter
def batches(self, batches):
check_type('batches', batches, Integral)
check_greater_than('batches', batches, 0)
self._batches = batches
@generations_per_batch.setter
def generations_per_batch(self, generations_per_batch):
check_type('generations per patch', generations_per_batch, Integral)
check_greater_than('generations per batch', generations_per_batch, 0)
self._generations_per_batch = generations_per_batch
@inactive.setter
def inactive(self, inactive):
check_type('inactive batches', inactive, Integral)
check_greater_than('inactive batches', inactive, 0, True)
self._inactive = inactive
@particles.setter
def particles(self, particles):
check_type('particles', particles, Integral)
check_greater_than('particles', particles, 0)
self._particles = particles
@keff_trigger.setter
def keff_trigger(self, keff_trigger):
if not isinstance(keff_trigger, dict):
msg = 'Unable to set a trigger on keff from "{0}" which ' \
'is not a Python dictionary'.format(keff_trigger)
raise ValueError(msg)
elif 'type' not in keff_trigger:
msg = 'Unable to set a trigger on keff from "{0}" which ' \
'does not have a "type" key'.format(keff_trigger)
raise ValueError(msg)
elif keff_trigger['type'] not in ['variance', 'std_dev', 'rel_err']:
msg = 'Unable to set a trigger on keff with ' \
'type "{0}"'.format(keff_trigger['type'])
raise ValueError(msg)
elif 'threshold' not in keff_trigger:
msg = 'Unable to set a trigger on keff from "{0}" which ' \
'does not have a "threshold" key'.format(keff_trigger)
raise ValueError(msg)
elif not isinstance(keff_trigger['threshold'], Real):
msg = 'Unable to set a trigger on keff with ' \
'threshold "{0}"'.format(keff_trigger['threshold'])
raise ValueError(msg)
self._keff_trigger = keff_trigger
@source_file.setter
def source_file(self, source_file):
check_type('source file', source_file, basestring)
self._source_file = source_file
def set_source_space(self, stype, params):
"""Defined the spatial bounds of the external/starting source.
Parameters
----------
stype : str
The type of spatial distribution. Valid options are "box",
"fission", and "point". A "box" spatial distribution has coordinates
sampled uniformly in a parallelepiped. A "fission" spatial
distribution samples locations from a "box" distribution but only
locations in fissionable materials are accepted. A "point" spatial
distribution has coordinates specified by a triplet.
params : Iterable of float
For a "box" or "fission" spatial distribution, ``params`` should be
given as six real numbers, the first three of which specify the
lower-left corner of a parallelepiped and the last three of which
specify the upper-right corner. Source sites are sampled uniformly
through that parallelepiped.
For a "point" spatial distribution, ``params`` should be given as
three real numbers which specify the (x,y,z) location of an
isotropic point source
"""
check_type('source space type', stype, basestring)
check_value('source space type', stype, ['box', 'fission', 'point'])
check_type('source space parameters', params, Iterable, Real)
if stype in ['box', 'fission']:
check_length('source space parameters for a '
'box/fission distribution', params, 6)
elif stype == 'point':
check_length('source space parameters for a point source',
params, 3)
self._source_space_type = stype
self._source_space_params = params
def set_source_angle(self, stype, params=[]):
"""Defined the angular distribution of the external/starting source.
Parameters
----------
stype : str
The type of angular distribution. Valid options are "isotropic" and
"monodirectional". The angle of the particle emitted from a source
site is isotropic if the "isotropic" option is given. The angle of
the particle emitted from a source site is the direction specified
in ``params`` if the "monodirectional" option is given.
params : Iterable of float
For an "isotropic" angular distribution, ``params`` should not
be specified.
For a "monodirectional" angular distribution, ``params`` should
be given as three floats which specify the angular cosines
with respect to each axis.
"""
check_type('source angle type', stype, basestring)
check_value('source angle type', stype,
['isotropic', 'monodirectional'])
check_type('source angle parameters', params, Iterable, Real)
if stype == 'isotropic' and params is not None:
msg = 'Unable to set source angle parameters since they are not ' \
'it is not supported for isotropic type sources'
raise ValueError(msg)
elif stype == 'monodirectional':
check_length('source angle parameters for a monodirectional '
'source', params, 3)
self._source_angle_type = stype
self._source_angle_params = params
def set_source_energy(self, stype, params=[]):
"""Defined the energy distribution of the external/starting source.
Parameters
----------
stype : str
The type of energy distribution. Valid options are "monoenergetic",
"watt", and "maxwell". The "monoenergetic" option produces source
sites at a single energy. The "watt" option produces source sites
whose energy is sampled from a Watt fission spectrum. The "maxwell"
option produce source sites whose energy is sampled from a Maxwell
fission spectrum.
params : Iterable of float
For a "monoenergetic" energy distribution, ``params`` should be
given as the energy in MeV of the source sites.
For a "watt" energy distribution, ``params`` should be given as two
real numbers :math:`a` and :math:`b` that parameterize the
distribution :math:`p(E) dE = c e^{-E/a} \sinh \sqrt{b \, E} dE`.
For a "maxwell" energy distribution, ``params`` should be given as
one real number :math:`a` that parameterizes the distribution
:math:`p(E) dE = c E e^{-E/a} dE`.
"""
check_type('source energy type', stype, basestring)
check_value('source energy type', stype,
['monoenergetic', 'watt', 'maxwell'])
check_type('source energy parameters', params, Iterable, Real)
if stype in ['monoenergetic', 'maxwell']:
check_length('source energy parameters for a monoenergetic '
'or Maxwell source', params, 1)
elif stype == 'watt':
check_length('source energy parameters for a Watt source',
params, 2)
self._source_energy_type = stype
self._source_energy_params = params
@output.setter
def output(self, output):
if not isinstance(output, dict):
msg = 'Unable to set output to "{0}" which is not a Python ' \
'dictionary of string keys and boolean values'.format(output)
raise ValueError(msg)
for element in output:
keys = ['summary', 'cross_sections', 'tallies', 'distribmats']
if element not in keys:
msg = 'Unable to set output to "{0}" which is unsupported by ' \
'OpenMC'.format(element)
raise ValueError(msg)
if not isinstance(output[element], (bool, np.bool)):
msg = 'Unable to set output for "{0}" to a non-boolean ' \
'value "{1}"'.format(element, output[element])
raise ValueError(msg)
self._output = output
@output_path.setter
def output_path(self, output_path):
check_type('output path', output_path, basestring)
self._output_path = output_path
@verbosity.setter
def verbosity(self, verbosity):
check_type('verbosity', verbosity, Integral)
check_greater_than('verbosity', verbosity, 1, True)
check_less_than('verbosity', verbosity, 10, True)
self._verbosity = verbosity
@statepoint_batches.setter
def statepoint_batches(self, batches):
check_type('statepoint batches', batches, Iterable, Integral)
for batch in batches:
check_greater_than('statepoint batch', batch, 0)
self._statepoint_batches = batches
@statepoint_interval.setter
def statepoint_interval(self, interval):
check_type('statepoint interval', interval, Integral)
self._statepoint_interval = interval
@sourcepoint_batches.setter
def sourcepoint_batches(self, batches):
check_type('sourcepoint batches', batches, Iterable, Integral)
for batch in batches:
check_greater_than('sourcepoint batch', batch, 0)
self._sourcepoint_batches = batches
@sourcepoint_interval.setter
def sourcepoint_interval(self, interval):
check_type('sourcepoint interval', interval, Integral)
self._sourcepoint_interval = interval
@sourcepoint_separate.setter
def sourcepoint_separate(self, source_separate):
check_type('sourcepoint separate', source_separate, bool)
self._sourcepoint_separate = source_separate
@sourcepoint_write.setter
def sourcepoint_write(self, source_write):
check_type('sourcepoint write', source_write, bool)
self._sourcepoint_write = source_write
@sourcepoint_overwrite.setter
def sourcepoint_overwrite(self, source_overwrite):
check_type('sourcepoint overwrite', source_overwrite, bool)
self._sourcepoint_overwrite = source_overwrite
@confidence_intervals.setter
def confidence_intervals(self, confidence_intervals):
check_type('confidence interval', confidence_intervals, bool)
self._confidence_intervals = confidence_intervals
@cross_sections.setter
def cross_sections(self, cross_sections):
check_type('cross sections', cross_sections, basestring)
self._cross_sections = cross_sections
@energy_grid.setter
def energy_grid(self, energy_grid):
check_value('energy grid', energy_grid,
['nuclide', 'logarithm', 'material-union'])
self._energy_grid = energy_grid
@ptables.setter
def ptables(self, ptables):
check_type('probability tables', ptables, bool)
self._ptables = ptables
@run_cmfd.setter
def run_cmfd(self, run_cmfd):
check_type('run_cmfd', run_cmfd, bool)
self._run_cmfd = run_cmfd
@seed.setter
def seed(self, seed):
check_type('random number generator seed', seed, Integral)
check_greater_than('random number generator seed', seed, 0)
self._seed = seed
@survival_biasing.setter
def survival_biasing(self, survival_biasing):
check_type('survival biasing', survival_biasing, bool)
self._survival_biasing = survival_biasing
@weight.setter
def weight(self, weight):
check_type('weight cutoff', weight, Real)
check_greater_than('weight cutoff', weight, 0.0)
self._weight = weight
@weight_avg.setter
def weight_avg(self, weight_avg):
check_type('average survival weight', weight_avg, Real)
check_greater_than('average survival weight', weight_avg, 0.0)
self._weight_avg = weight_avg
@entropy_dimension.setter
def entropy_dimension(self, dimension):
check_type('entropy mesh dimension', dimension, Iterable, Integral)
check_length('entropy mesh dimension', dimension, 3)
self._entropy_dimension = dimension
@entropy_lower_left.setter
def entropy_lower_left(self, lower_left):
check_type('entropy mesh lower left corner', lower_left,
Iterable, Real)
check_length('entropy mesh lower left corner', lower_left, 3)
self._entropy_lower_left = lower_left
@entropy_upper_right.setter
def entropy_upper_right(self, upper_right):
check_type('entropy mesh upper right corner', upper_right,
Iterable, Real)
check_length('entropy mesh upper right corner', upper_right, 3)
self._entropy_upper_right = upper_right
@trigger_active.setter
def trigger_active(self, trigger_active):
check_type('trigger active', trigger_active, bool)
self._trigger_active = trigger_active
@trigger_max_batches.setter
def trigger_max_batches(self, trigger_max_batches):
check_type('trigger maximum batches', trigger_max_batches, Integral)
check_greater_than('trigger maximum batches', trigger_max_batches, 0)
self._trigger_max_batches = trigger_max_batches
@trigger_batch_interval.setter
def trigger_batch_interval(self, trigger_batch_interval):
check_type('trigger batch interval', trigger_batch_interval, Integral)
check_greater_than('trigger batch interval', trigger_batch_interval, 0)
self._trigger_batch_interval = trigger_batch_interval
@no_reduce.setter
def no_reduce(self, no_reduce):
check_type('no reduction option', no_reduce, bool)
self._no_reduce = no_reduce
@threads.setter
def threads(self, threads):
check_type('number of threads', threads, Integral)
check_greater_than('number of threads', threads, 0)
self._threads = threads
@trace.setter
def trace(self, trace):
check_type('trace', trace, Iterable, Integral)
check_length('trace', trace, 3)
check_greater_than('trace batch', trace[0], 0)
check_greater_than('trace generation', trace[1], 0)
check_greater_than('trace particle', trace[2], 0)
self._trace = trace
@track.setter
def track(self, track):
check_type('track', track, Iterable, Integral)
if len(track) % 3 != 0:
msg = 'Unable to set the track to "{0}" since its length is ' \
'not a multiple of 3'.format(track)
raise ValueError(msg)
for t in zip(track[::3], track[1::3], track[2::3]):
check_greater_than('track batch', t[0], 0)
check_greater_than('track generation', t[0], 0)
check_greater_than('track particle', t[0], 0)
self._track = track
@ufs_dimension.setter
def ufs_dimension(self, dimension):
check_type('UFS mesh dimension', dimension, Iterable, Integral)
check_length('UFS mesh dimension', dimension, 3)
for dim in dimension:
check_greater_than('UFS mesh dimension', dim, 1, True)
self._ufs_dimension = dimension
@ufs_lower_left.setter
def ufs_lower_left(self, lower_left):
check_type('UFS mesh lower left corner', lower_left, Iterable, Real)
check_length('UFS mesh lower left corner', lower_left, 3)
self._ufs_lower_left = lower_left
@ufs_upper_right.setter
def ufs_upper_right(self, upper_right):
check_type('UFS mesh upper right corner', upper_right, Iterable, Real)
check_length('UFS mesh upper right corner', upper_right, 3)
self._ufs_upper_right = upper_right
@dd_mesh_dimension.setter
def dd_mesh_dimension(self, dimension):
# TODO: remove this when domain decomposition is merged
warnings.warn('This feature is not yet implemented in a release '
'version of openmc')
check_type('DD mesh dimension', dimension, Iterable, Integral)
check_length('DD mesh dimension', dimension, 3)
self._dd_mesh_dimension = dimension
@dd_mesh_lower_left.setter
def dd_mesh_lower_left(self, lower_left):
# TODO: remove this when domain decomposition is merged
warnings.warn('This feature is not yet implemented in a release '
'version of openmc')
check_type('DD mesh lower left corner', lower_left, Iterable, Real)
check_length('DD mesh lower left corner', lower_left, 3)
self._dd_mesh_lower_left = lower_left
@dd_mesh_upper_right.setter
def dd_mesh_upper_right(self, upper_right):
# TODO: remove this when domain decomposition is merged
warnings.warn('This feature is not yet implemented in a release '
'version of openmc')
check_type('DD mesh upper right corner', upper_right, Iterable, Real)
check_length('DD mesh upper right corner', upper_right, 3)
self._dd_mesh_upper_right = upper_right
@dd_nodemap.setter
def dd_nodemap(self, nodemap):
# TODO: remove this when domain decomposition is merged
warnings.warn('This feature is not yet implemented in a release '
'version of openmc')
check_type('DD nodemap', nodemap, Iterable)
nodemap = np.array(nodemap).flatten()
if self._dd_mesh_dimension is None:
msg = 'Must set DD mesh dimension before setting the nodemap'
raise ValueError(msg)
else:
len_nodemap = np.prod(self._dd_mesh_dimension)
if len(nodemap) < len_nodemap or len(nodemap) > len_nodemap:
msg = 'Unable to set DD nodemap with length "{0}" which ' \
'does not have the same dimensionality as the domain ' \
'mesh'.format(len(nodemap))
raise ValueError(msg)
self._dd_nodemap = nodemap
@dd_allow_leakage.setter
def dd_allow_leakage(self, allow):
# TODO: remove this when domain decomposition is merged
warnings.warn('This feature is not yet implemented in a release '
'version of openmc')
check_type('DD allow leakage', allow, bool)
self._dd_allow_leakage = allow
@dd_count_interactions.setter
def dd_count_interactions(self, interactions):
# TODO: remove this when domain decomposition is merged
warnings.warn('This feature is not yet implemented in a release '
'version of openmc')
check_type('DD count interactions', interactions, bool)
self._dd_count_interactions = interactions
def _create_eigenvalue_subelement(self):
self._create_particles_subelement()
self._create_batches_subelement()
self._create_inactive_subelement()
self._create_generations_per_batch_subelement()
self._create_keff_trigger_subelement()
def _create_batches_subelement(self):
if self._batches is not None:
if self._eigenvalue_subelement is None:
self._eigenvalue_subelement = ET.SubElement(self._settings_file,
"eigenvalue")
element = ET.SubElement(self._eigenvalue_subelement, "batches")
element.text = str(self._batches)
def _create_generations_per_batch_subelement(self):
if self._generations_per_batch is not None:
if self._eigenvalue_subelement is None:
self._eigenvalue_subelement = ET.SubElement(self._settings_file,
"eigenvalue")
element = ET.SubElement(self._eigenvalue_subelement,
"generations_per_batch")
element.text = str(self._generations_per_batch)
def _create_inactive_subelement(self):
if self._inactive is not None:
if self._eigenvalue_subelement is None:
self._eigenvalue_subelement = ET.SubElement(self._settings_file,
"eigenvalue")
element = ET.SubElement(self._eigenvalue_subelement, "inactive")
element.text = str(self._inactive)
def _create_particles_subelement(self):
if self._particles is not None:
if self._eigenvalue_subelement is None:
self._eigenvalue_subelement = ET.SubElement(self._settings_file,
"eigenvalue")
element = ET.SubElement(self._eigenvalue_subelement, "particles")
element.text = str(self._particles)
def _create_keff_trigger_subelement(self):
if self._keff_trigger is not None:
if self._eigenvalue_subelement is None:
self._eigenvalue_subelement = ET.SubElement(self._settings_file,
"eigenvalue")
element = ET.SubElement(self._eigenvalue_subelement, "keff_trigger")
for key in self._keff_trigger:
subelement = ET.SubElement(element, key)
subelement.text = str(self._keff_trigger[key]).lower()
def _create_source_subelement(self):
self._create_source_space_subelement()
self._create_source_energy_subelement()
self._create_source_angle_subelement()
def _create_source_space_subelement(self):
if self._source_space_params is not None:
if self._source_subelement is None:
self._source_subelement = ET.SubElement(self._settings_file,
"source")
element = ET.SubElement(self._source_subelement, "space")
element.set("type", self._source_space_type)
subelement = ET.SubElement(element, "parameters")
subelement.text = ' '.join(map(str, self._source_space_params))
def _create_source_angle_subelement(self):
if self._source_angle_params is not None:
if self._source_subelement is None:
self._source_subelement = ET.SubElement(self._settings_file,
"source")
element = ET.SubElement(self._source_subelement, "angle")
element.set("type", self._source_angle_type)
subelement = ET.SubElement(element, "parameters")
subelement.text = ' '.join(map(str, self._source_angle_params))
def _create_source_energy_subelement(self):
if self._source_energy_params is not None:
if self._source_subelement is None:
self._source_subelement = ET.SubElement(self._settings_file,
"source")
element = ET.SubElement(self._source_subelement, "energy")
element.set("type", self._source_energy_type)
subelement = ET.SubElement(element, "parameters")
subelement.text = ' '.join(map(str, self._source_energy_params))
def _create_output_subelement(self):
if self._output is not None:
element = ET.SubElement(self._settings_file, "output")
for key in self._output:
subelement = ET.SubElement(element, key)
subelement.text = str(self._output[key]).lower()
self._create_output_path_subelement()
def _create_output_path_subelement(self):
if self._output_path is not None:
element = ET.SubElement(self._settings_file, "output_path")
element.text = self._output_path
def _create_verbosity_subelement(self):
if self._verbosity is not None:
element = ET.SubElement(self._settings_file, "verbosity")
element.text = str(self._verbosity)
def _create_statepoint_subelement(self):
# Batches subelement
if self._statepoint_batches is not None:
element = ET.SubElement(self._settings_file, "state_point")
subelement = ET.SubElement(element, "batches")
subelement.text = ' '.join(map(str, self._statepoint_batches))
# Interval subelement
elif self._statepoint_interval is not None:
element = ET.SubElement(self._settings_file, "state_point")
subelement = ET.SubElement(element, "interval")
subelement.text = str(self._statepoint_interval)
def _create_sourcepoint_subelement(self):
# Batches subelement
if self._sourcepoint_batches is not None:
element = ET.SubElement(self._settings_file, "source_point")
subelement = ET.SubElement(element, "batches")
subelement.text = ' '.join(map(str, self._sourcepoint_batches))
# Interval subelement
elif self._sourcepoint_interval is not None:
element = ET.SubElement(self._settings_file, "source_point")
subelement = ET.SubElement(element, "interval")
subelement.text = str(self._sourcepoint_interval)
# Separate subelement
if self._sourcepoint_separate is not None:
subelement = ET.SubElement(element, "separate")
subelement.text = str(self._sourcepoint_separate).lower()
# Write subelement
if self._sourcepoint_write is not None:
subelement = ET.SubElement(element, "write")
subelement.text = str(self._sourcepoint_write).lower()
# Overwrite latest subelement
if self._sourcepoint_overwrite is not None:
subelement = ET.SubElement(element, "overwrite_latest")
subelement.text = str(self._sourcepoint_overwrite).lower()
def _create_confidence_intervals(self):
if self._confidence_intervals is not None:
element = ET.SubElement(self._settings_file, "confidence_intervals")
element.text = str(self._confidence_intervals).lower()
def _create_cross_sections_subelement(self):
if self._cross_sections is not None:
element = ET.SubElement(self._settings_file, "cross_sections")
element.text = str(self._cross_sections)
def _create_energy_grid_subelement(self):
if self._energy_grid is not None:
element = ET.SubElement(self._settings_file, "energy_grid")
element.text = str(self._energy_grid)
def _create_ptables_subelement(self):
if self._ptables is not None:
element = ET.SubElement(self._settings_file, "ptables")
element.text = str(self._ptables).lower()
def _create_run_cmfd_subelement(self):
if self._run_cmfd is not None:
element = ET.SubElement(self._settings_file, "run_cmfd")
element.text = str(self._run_cmfd).lower()
def _create_seed_subelement(self):
if self._seed is not None:
element = ET.SubElement(self._settings_file, "seed")
element.text = str(self._seed)
def _create_survival_biasing_subelement(self):
if self._survival_biasing is not None:
element = ET.SubElement(self._settings_file, "survival_biasing")
element.text = str(self._survival_biasing).lower()
def _create_cutoff_subelement(self):
if self._weight is not None:
element = ET.SubElement(self._settings_file, "cutoff")
subelement = ET.SubElement(element, "weight")
subelement.text = str(self._weight)
subelement = ET.SubElement(element, "weight_avg")
subelement.text = str(self._weight_avg)
def _create_entropy_subelement(self):
if self._entropy_lower_left is not None and \
self._entropy_upper_right is not None:
element = ET.SubElement(self._settings_file, "entropy")
subelement = ET.SubElement(element, "dimension")
subelement.text = ' '.join(map(str, self._entropy_dimension))
subelement = ET.SubElement(element, "lower_left")
subelement.text = ' '.join(map(str, self._entropy_lower_left))
subelement = ET.SubElement(element, "upper_right")
subelement.text = ' '.join(map(str, self._entropy_upper_right))
def _create_trigger_subelement(self):
self._create_trigger_active_subelement()
self._create_trigger_max_batches_subelement()
self._create_trigger_batch_interval_subelement()
def _create_trigger_active_subelement(self):
if self._trigger_active is not None:
if self._trigger_subelement is None:
self._trigger_subelement = ET.SubElement(self._settings_file,
"trigger")
element = ET.SubElement(self._trigger_subelement, "active")
element.text = str(self._trigger_active).lower()
def _create_trigger_max_batches_subelement(self):
if self._trigger_max_batches is not None:
if self._trigger_subelement is None:
self._trigger_subelement = ET.SubElement(self._settings_file,
"trigger")
element = ET.SubElement(self._trigger_subelement, "max_batches")
element.text = str(self._trigger_max_batches)
def _create_trigger_batch_interval_subelement(self):
if self._trigger_batch_interval is not None:
if self._trigger_subelement is None:
self._trigger_subelement = ET.SubElement(self._settings_file,
"trigger")
element = ET.SubElement(self._trigger_subelement, "batch_interval")
element.text = str(self._trigger_batch_interval)
def _create_no_reduce_subelement(self):
if self._no_reduce is not None:
element = ET.SubElement(self._settings_file, "no_reduce")
element.text = str(self._no_reduce).lower()
def _create_threads_subelement(self):
if self._threads is not None:
element = ET.SubElement(self._settings_file, "threads")
element.text = str(self._threads)
def _create_trace_subelement(self):
if self._trace is not None:
element = ET.SubElement(self._settings_file, "trace")
element.text = ' '.join(map(str, self._trace))
def _create_track_subelement(self):
if self._track is not None:
element = ET.SubElement(self._settings_file, "track")
element.text = ' '.join(map(str, self._track))
def _create_ufs_subelement(self):
if self._ufs_lower_left is not None and \
self._ufs_upper_right is not None:
element = ET.SubElement(self._settings_file, "uniform_fs")
subelement = ET.SubElement(element, "dimension")
subelement.text = str(self._ufs_dimension)
subelement = ET.SubElement(element, "lower_left")
subelement.text = ' '.join(map(str, self._ufs_lower_left))
subelement = ET.SubElement(element, "upper_right")
subelement.text = ' '.join(map(str, self._ufs_upper_right))
def _create_dd_subelement(self):
if self._dd_mesh_lower_left is not None and \
self._dd_mesh_upper_right is not None and \
self._dd_mesh_dimension is not None:
element = ET.SubElement(self._settings_file, "domain_decomposition")
subelement = ET.SubElement(element, "mesh")
subsubelement = ET.SubElement(subelement, "dimension")
subsubelement.text = ' '.join(map(str, self._dd_mesh_dimension))
subsubelement = ET.SubElement(subelement, "lower_left")
subsubelement.text = ' '.join(map(str, self._dd_mesh_lower_left))
subsubelement = ET.SubElement(subelement, "upper_right")
subsubelement.text = ' '.join(map(str, self._dd_mesh_upper_right))
if self._dd_nodemap is not None:
subelement = ET.SubElement(element, "nodemap")
subelement.text = ' '.join(map(str, self._dd_nodemap))
subelement = ET.SubElement(element, "allow_leakage")
subelement.text = str(self._dd_allow_leakage).lower()
subelement = ET.SubElement(element, "count_interactions")
subelement.text = str(self._dd_count_interactions).lower()
def export_to_xml(self):
"""Create a settings.xml file that can be used for a simulation.
"""
self._create_eigenvalue_subelement()
self._create_source_subelement()
self._create_output_subelement()
self._create_statepoint_subelement()
self._create_sourcepoint_subelement()
self._create_confidence_intervals()
self._create_cross_sections_subelement()
self._create_energy_grid_subelement()
self._create_ptables_subelement()
self._create_run_cmfd_subelement()
self._create_seed_subelement()
self._create_survival_biasing_subelement()
self._create_cutoff_subelement()
self._create_entropy_subelement()
self._create_trigger_subelement()
self._create_no_reduce_subelement()
self._create_threads_subelement()
self._create_verbosity_subelement()
self._create_trace_subelement()
self._create_track_subelement()
self._create_ufs_subelement()
self._create_dd_subelement()
# Clean the indentation in the file to be user-readable
clean_xml_indentation(self._settings_file)
# Write the XML Tree to the settings.xml file
tree = ET.ElementTree(self._settings_file)
tree.write("settings.xml", xml_declaration=True,
encoding='utf-8', method="xml")
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