from collections.abc import Iterable, MutableSequence, Mapping
from pathlib import Path
from numbers import Real, Integral
import warnings
from xml.etree import ElementTree as ET
import sys
import numpy as np
from openmc._xml import clean_indentation, get_text
import openmc.checkvalue as cv
from openmc import VolumeCalculation, Source, RegularMesh
_RUN_MODES = ['eigenvalue', 'fixed source', 'plot', 'volume', 'particle restart']
_RES_SCAT_METHODS = ['dbrc', 'rvs']
[docs]class Settings(object):
"""Settings used for an OpenMC simulation.
Attributes
----------
batches : int
Number of batches to simulate
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.
create_fission_neutrons : bool
Indicate whether fission neutrons should be created or not.
cutoff : dict
Dictionary defining weight cutoff and energy cutoff. The dictionary may
have six keys, 'weight', 'weight_avg', 'energy_neutron', 'energy_photon',
'energy_electron', and 'energy_positron'. Value for 'weight'
should be a float indicating weight cutoff below which particle undergo
Russian roulette. Value for 'weight_avg' should be a float indicating
weight assigned to particles that are not killed after Russian
roulette. Value of energy should be a float indicating energy in eV
below which particle type will be killed.
dagmc : bool
Indicate that a CAD-based DAGMC geometry will be used.
electron_treatment : {'led', 'ttb'}
Whether to deposit all energy from electrons locally ('led') or create
secondary bremsstrahlung photons ('ttb').
energy_mode : {'continuous-energy', 'multi-group'}
Set whether the calculation should be continuous-energy or multi-group.
entropy_mesh : openmc.RegularMesh
Mesh to be used to calculate Shannon entropy. If the mesh dimensions are
not specified. OpenMC assigns a mesh such that 20 source sites per mesh
cell are to be expected on average.
generations_per_batch : int
Number of generations per batch
inactive : int
Number of inactive batches
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.
log_grid_bins : int
Number of bins for logarithmic energy grid search
max_order : None or int
Maximum scattering order to apply globally when in multi-group mode.
no_reduce : bool
Indicate that all user-defined and global tallies should not be reduced
across processes in a parallel calculation.
output : dict
Dictionary indicating what files to output. Acceptable keys are:
:path: String indicating a directory where output files should be
written
:summary: Whether the 'summary.h5' file should be written (bool)
:tallies: Whether the 'tallies.out' file should be written (bool)
particles : int
Number of particles per generation
photon_transport : bool
Whether to use photon transport.
ptables : bool
Determine whether probability tables are used.
resonance_scattering : dict
Settings for resonance elastic scattering. Accepted keys are 'enable'
(bool), 'method' (str), 'energy_min' (float), 'energy_max' (float), and
'nuclides' (list). The 'method' can be set to 'dbrc' (Doppler broadening
rejection correction) or 'rvs' (relative velocity sampling). If not
specified, 'rvs' is the default method. The 'energy_min' and
'energy_max' values indicate the minimum and maximum energies above and
below which the resonance elastic scattering method is to be
applied. The 'nuclides' list indicates what nuclides the method should
be applied to. In its absence, the method will be applied to all
nuclides with 0 K elastic scattering data present.
run_mode : {'eigenvalue', 'fixed source', 'plot', 'volume', 'particle restart'}
The type of calculation to perform (default is 'eigenvalue')
seed : int
Seed for the linear congruential pseudorandom number generator
source : Iterable of openmc.Source
Distribution of source sites in space, angle, and energy
sourcepoint : dict
Options for writing source points. Acceptable keys are:
:batches: list of batches at which to write source
:overwrite: bool indicating whether to overwrite
:separate: bool indicating whether the source should be written as a
separate file
:write: bool indicating whether or not to write the source
statepoint : dict
Options for writing state points. Acceptable keys are:
:batches: list of batches at which to write source
survival_biasing : bool
Indicate whether survival biasing is to be used
tabular_legendre : dict
Determines if a multi-group scattering moment kernel expanded via
Legendre polynomials is to be converted to a tabular distribution or
not. Accepted keys are 'enable' and 'num_points'. The value for
'enable' is a bool stating whether the conversion to tabular is
performed; the value for 'num_points' sets the number of points to use
in the tabular distribution, should 'enable' be True.
temperature : dict
Defines a default temperature and method for treating intermediate
temperatures at which nuclear data doesn't exist. Accepted keys are
'default', 'method', 'range', 'tolerance', and 'multipole'. The value
for 'default' should be a float representing the default temperature in
Kelvin. The value for 'method' should be 'nearest' or 'interpolation'.
If the method is 'nearest', 'tolerance' indicates a range of temperature
within which cross sections may be used. The value for 'range' should be
a pair a minimum and maximum temperatures which are used to indicate
that cross sections be loaded at all temperatures within the
range. 'multipole' is a boolean indicating whether or not the windowed
multipole method should be used to evaluate resolved resonance cross
sections.
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.
trigger_active : bool
Indicate whether tally triggers are used
trigger_batch_interval : int
Number of batches in between convergence checks
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
ufs_mesh : openmc.RegularMesh
Mesh to be used for redistributing source sites via the uniform fision
site (UFS) method.
verbosity : int
Verbosity during simulation between 1 and 10. Verbosity levels are
described in :ref:`verbosity`.
volume_calculations : VolumeCalculation or iterable of VolumeCalculation
Stochastic volume calculation specifications
"""
def __init__(self):
# Run mode subelement (default is 'eigenvalue')
self._run_mode = 'eigenvalue'
self._batches = None
self._generations_per_batch = None
self._inactive = None
self._particles = None
self._keff_trigger = None
# Energy mode subelement
self._energy_mode = None
self._max_order = None
# Source subelement
self._source = cv.CheckedList(Source, 'source distributions')
self._confidence_intervals = None
self._electron_treatment = None
self._photon_transport = None
self._ptables = None
self._seed = None
self._survival_biasing = None
# Shannon entropy mesh
self._entropy_mesh = None
# Trigger subelement
self._trigger_active = None
self._trigger_max_batches = None
self._trigger_batch_interval = None
self._output = None
# Output options
self._statepoint = {}
self._sourcepoint = {}
self._no_reduce = None
self._verbosity = None
self._trace = None
self._track = None
self._tabular_legendre = {}
self._temperature = {}
# Cutoff subelement
self._cutoff = None
# Uniform fission source subelement
self._ufs_mesh = None
self._resonance_scattering = {}
self._volume_calculations = cv.CheckedList(
VolumeCalculation, 'volume calculations')
self._create_fission_neutrons = None
self._log_grid_bins = None
self._dagmc = False
@property
def run_mode(self):
return self._run_mode
@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 energy_mode(self):
return self._energy_mode
@property
def max_order(self):
return self._max_order
@property
def source(self):
return self._source
@property
def confidence_intervals(self):
return self._confidence_intervals
@property
def electron_treatment(self):
return self._electron_treatment
@property
def ptables(self):
return self._ptables
@property
def photon_transport(self):
return self._photon_transport
@property
def seed(self):
return self._seed
@property
def survival_biasing(self):
return self._survival_biasing
@property
def entropy_mesh(self):
return self._entropy_mesh
@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._trigger_batch_interval
@property
def output(self):
return self._output
@property
def sourcepoint(self):
return self._sourcepoint
@property
def statepoint(self):
return self._statepoint
@property
def no_reduce(self):
return self._no_reduce
@property
def verbosity(self):
return self._verbosity
@property
def tabular_legendre(self):
return self._tabular_legendre
@property
def temperature(self):
return self._temperature
@property
def trace(self):
return self._trace
@property
def track(self):
return self._track
@property
def cutoff(self):
return self._cutoff
@property
def ufs_mesh(self):
return self._ufs_mesh
@property
def resonance_scattering(self):
return self._resonance_scattering
@property
def volume_calculations(self):
return self._volume_calculations
@property
def create_fission_neutrons(self):
return self._create_fission_neutrons
@property
def log_grid_bins(self):
return self._log_grid_bins
@property
def dagmc(self):
return self._dagmc
@run_mode.setter
def run_mode(self, run_mode):
cv.check_value('run mode', run_mode, _RUN_MODES)
self._run_mode = run_mode
@batches.setter
def batches(self, batches):
cv.check_type('batches', batches, Integral)
cv.check_greater_than('batches', batches, 0)
self._batches = batches
@generations_per_batch.setter
def generations_per_batch(self, generations_per_batch):
cv.check_type('generations per patch', generations_per_batch, Integral)
cv.check_greater_than('generations per batch', generations_per_batch, 0)
self._generations_per_batch = generations_per_batch
@inactive.setter
def inactive(self, inactive):
cv.check_type('inactive batches', inactive, Integral)
cv.check_greater_than('inactive batches', inactive, 0, True)
self._inactive = inactive
@particles.setter
def particles(self, particles):
cv.check_type('particles', particles, Integral)
cv.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
@energy_mode.setter
def energy_mode(self, energy_mode):
cv.check_value('energy mode', energy_mode,
['continuous-energy', 'multi-group'])
self._energy_mode = energy_mode
@max_order.setter
def max_order(self, max_order):
if max_order is not None:
cv.check_type('maximum scattering order', max_order, Integral)
cv.check_greater_than('maximum scattering order', max_order, 0,
True)
self._max_order = max_order
@source.setter
def source(self, source):
if not isinstance(source, MutableSequence):
source = [source]
self._source = cv.CheckedList(Source, 'source distributions', source)
@output.setter
def output(self, output):
cv.check_type('output', output, Mapping)
for key, value in output.items():
cv.check_value('output key', key, ('summary', 'tallies', 'path'))
if key in ('summary', 'tallies'):
cv.check_type("output['{}']".format(key), value, bool)
else:
cv.check_type("output['path']", value, str)
self._output = output
@verbosity.setter
def verbosity(self, verbosity):
cv.check_type('verbosity', verbosity, Integral)
cv.check_greater_than('verbosity', verbosity, 1, True)
cv.check_less_than('verbosity', verbosity, 10, True)
self._verbosity = verbosity
@sourcepoint.setter
def sourcepoint(self, sourcepoint):
cv.check_type('sourcepoint options', sourcepoint, Mapping)
for key, value in sourcepoint.items():
if key == 'batches':
cv.check_type('sourcepoint batches', value, Iterable, Integral)
for batch in value:
cv.check_greater_than('sourcepoint batch', batch, 0)
elif key == 'separate':
cv.check_type('sourcepoint separate', value, bool)
elif key == 'write':
cv.check_type('sourcepoint write', value, bool)
elif key == 'overwrite':
cv.check_type('sourcepoint overwrite', value, bool)
else:
raise ValueError("Unknown key '{}' encountered when setting "
"sourcepoint options.".format(key))
self._sourcepoint = sourcepoint
@statepoint.setter
def statepoint(self, statepoint):
cv.check_type('statepoint options', statepoint, Mapping)
for key, value in statepoint.items():
if key == 'batches':
cv.check_type('statepoint batches', value, Iterable, Integral)
for batch in value:
cv.check_greater_than('statepoint batch', batch, 0)
else:
raise ValueError("Unknown key '{}' encountered when setting "
"statepoint options.".format(key))
self._statepoint = statepoint
@confidence_intervals.setter
def confidence_intervals(self, confidence_intervals):
cv.check_type('confidence interval', confidence_intervals, bool)
self._confidence_intervals = confidence_intervals
@electron_treatment.setter
def electron_treatment(self, electron_treatment):
cv.check_value('electron treatment', electron_treatment, ['led', 'ttb'])
self._electron_treatment = electron_treatment
@photon_transport.setter
def photon_transport(self, photon_transport):
cv.check_type('photon transport', photon_transport, bool)
self._photon_transport = photon_transport
@dagmc.setter
def dagmc(self, dagmc):
cv.check_type('dagmc geometry', dagmc, bool)
self._dagmc = dagmc
@ptables.setter
def ptables(self, ptables):
cv.check_type('probability tables', ptables, bool)
self._ptables = ptables
@seed.setter
def seed(self, seed):
cv.check_type('random number generator seed', seed, Integral)
cv.check_greater_than('random number generator seed', seed, 0)
self._seed = seed
@survival_biasing.setter
def survival_biasing(self, survival_biasing):
cv.check_type('survival biasing', survival_biasing, bool)
self._survival_biasing = survival_biasing
@cutoff.setter
def cutoff(self, cutoff):
if not isinstance(cutoff, Mapping):
msg = 'Unable to set cutoff from "{0}" which is not a '\
' Python dictionary'.format(cutoff)
raise ValueError(msg)
for key in cutoff:
if key == 'weight':
cv.check_type('weight cutoff', cutoff[key], Real)
cv.check_greater_than('weight cutoff', cutoff[key], 0.0)
elif key == 'weight_avg':
cv.check_type('average survival weight', cutoff[key], Real)
cv.check_greater_than('average survival weight',
cutoff[key], 0.0)
elif key in ['energy_neutron', 'energy_photon', 'energy_electron',
'energy_positron']:
cv.check_type('energy cutoff', cutoff[key], Real)
cv.check_greater_than('energy cutoff', cutoff[key], 0.0)
else:
msg = 'Unable to set cutoff to "{0}" which is unsupported by '\
'OpenMC'.format(key)
self._cutoff = cutoff
@entropy_mesh.setter
def entropy_mesh(self, entropy):
cv.check_type('entropy mesh', entropy, RegularMesh)
if entropy.dimension:
cv.check_length('entropy mesh dimension', entropy.dimension, 3)
cv.check_length('entropy mesh lower-left corner', entropy.lower_left, 3)
cv.check_length('entropy mesh upper-right corner', entropy.upper_right, 3)
self._entropy_mesh = entropy
@trigger_active.setter
def trigger_active(self, trigger_active):
cv.check_type('trigger active', trigger_active, bool)
self._trigger_active = trigger_active
@trigger_max_batches.setter
def trigger_max_batches(self, trigger_max_batches):
cv.check_type('trigger maximum batches', trigger_max_batches, Integral)
cv.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):
cv.check_type('trigger batch interval', trigger_batch_interval, Integral)
cv.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):
cv.check_type('no reduction option', no_reduce, bool)
self._no_reduce = no_reduce
@tabular_legendre.setter
def tabular_legendre(self, tabular_legendre):
cv.check_type('tabular_legendre settings', tabular_legendre, Mapping)
for key, value in tabular_legendre.items():
cv.check_value('tabular_legendre key', key,
['enable', 'num_points'])
if key == 'enable':
cv.check_type('enable tabular_legendre', value, bool)
elif key == 'num_points':
cv.check_type('num_points tabular_legendre', value, Integral)
cv.check_greater_than('num_points tabular_legendre', value, 0)
self._tabular_legendre = tabular_legendre
@temperature.setter
def temperature(self, temperature):
cv.check_type('temperature settings', temperature, Mapping)
for key, value in temperature.items():
cv.check_value('temperature key', key,
['default', 'method', 'tolerance', 'multipole',
'range'])
if key == 'default':
cv.check_type('default temperature', value, Real)
elif key == 'method':
cv.check_value('temperature method', value,
['nearest', 'interpolation'])
elif key == 'tolerance':
cv.check_type('temperature tolerance', value, Real)
elif key == 'multipole':
cv.check_type('temperature multipole', value, bool)
elif key == 'range':
cv.check_length('temperature range', value, 2)
for T in value:
cv.check_type('temperature', T, Real)
self._temperature = temperature
@trace.setter
def trace(self, trace):
cv.check_type('trace', trace, Iterable, Integral)
cv.check_length('trace', trace, 3)
cv.check_greater_than('trace batch', trace[0], 0)
cv.check_greater_than('trace generation', trace[1], 0)
cv.check_greater_than('trace particle', trace[2], 0)
self._trace = trace
@track.setter
def track(self, track):
cv.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]):
cv.check_greater_than('track batch', t[0], 0)
cv.check_greater_than('track generation', t[0], 0)
cv.check_greater_than('track particle', t[0], 0)
self._track = track
@ufs_mesh.setter
def ufs_mesh(self, ufs_mesh):
cv.check_type('UFS mesh', ufs_mesh, RegularMesh)
cv.check_length('UFS mesh dimension', ufs_mesh.dimension, 3)
cv.check_length('UFS mesh lower-left corner', ufs_mesh.lower_left, 3)
cv.check_length('UFS mesh upper-right corner', ufs_mesh.upper_right, 3)
self._ufs_mesh = ufs_mesh
@resonance_scattering.setter
def resonance_scattering(self, res):
cv.check_type('resonance scattering settings', res, Mapping)
keys = ('enable', 'method', 'energy_min', 'energy_max', 'nuclides')
for key, value in res.items():
cv.check_value('resonance scattering dictionary key', key, keys)
if key == 'enable':
cv.check_type('resonance scattering enable', value, bool)
elif key == 'method':
cv.check_value('resonance scattering method', value,
_RES_SCAT_METHODS)
elif key == 'energy_min':
name = 'resonance scattering minimum energy'
cv.check_type(name, value, Real)
cv.check_greater_than(name, value, 0)
elif key == 'energy_max':
name = 'resonance scattering minimum energy'
cv.check_type(name, value, Real)
cv.check_greater_than(name, value, 0)
elif key == 'nuclides':
cv.check_type('resonance scattering nuclides', value,
Iterable, str)
self._resonance_scattering = res
@volume_calculations.setter
def volume_calculations(self, vol_calcs):
if not isinstance(vol_calcs, MutableSequence):
vol_calcs = [vol_calcs]
self._volume_calculations = cv.CheckedList(
VolumeCalculation, 'stochastic volume calculations', vol_calcs)
@create_fission_neutrons.setter
def create_fission_neutrons(self, create_fission_neutrons):
cv.check_type('Whether create fission neutrons',
create_fission_neutrons, bool)
self._create_fission_neutrons = create_fission_neutrons
@log_grid_bins.setter
def log_grid_bins(self, log_grid_bins):
cv.check_type('log grid bins', log_grid_bins, Real)
cv.check_greater_than('log grid bins', log_grid_bins, 0)
self._log_grid_bins = log_grid_bins
def _create_run_mode_subelement(self, root):
elem = ET.SubElement(root, "run_mode")
elem.text = self._run_mode
def _create_batches_subelement(self, root):
if self._batches is not None:
element = ET.SubElement(root, "batches")
element.text = str(self._batches)
def _create_generations_per_batch_subelement(self, root):
if self._generations_per_batch is not None:
element = ET.SubElement(root, "generations_per_batch")
element.text = str(self._generations_per_batch)
def _create_inactive_subelement(self, root):
if self._inactive is not None:
element = ET.SubElement(root, "inactive")
element.text = str(self._inactive)
def _create_particles_subelement(self, root):
if self._particles is not None:
element = ET.SubElement(root, "particles")
element.text = str(self._particles)
def _create_keff_trigger_subelement(self, root):
if self._keff_trigger is not None:
element = ET.SubElement(root, "keff_trigger")
for key in self._keff_trigger:
subelement = ET.SubElement(element, key)
subelement.text = str(self._keff_trigger[key]).lower()
def _create_energy_mode_subelement(self, root):
if self._energy_mode is not None:
element = ET.SubElement(root, "energy_mode")
element.text = str(self._energy_mode)
def _create_max_order_subelement(self, root):
if self._max_order is not None:
element = ET.SubElement(root, "max_order")
element.text = str(self._max_order)
def _create_source_subelement(self, root):
for source in self.source:
root.append(source.to_xml_element())
def _create_volume_calcs_subelement(self, root):
for calc in self.volume_calculations:
root.append(calc.to_xml_element())
def _create_output_subelement(self, root):
if self._output is not None:
element = ET.SubElement(root, "output")
for key, value in self._output.items():
subelement = ET.SubElement(element, key)
if key in ('summary', 'tallies'):
subelement.text = str(value).lower()
else:
subelement.text = value
def _create_verbosity_subelement(self, root):
if self._verbosity is not None:
element = ET.SubElement(root, "verbosity")
element.text = str(self._verbosity)
def _create_statepoint_subelement(self, root):
if self._statepoint:
element = ET.SubElement(root, "state_point")
if 'batches' in self._statepoint:
subelement = ET.SubElement(element, "batches")
subelement.text = ' '.join(
str(x) for x in self._statepoint['batches'])
def _create_sourcepoint_subelement(self, root):
if self._sourcepoint:
element = ET.SubElement(root, "source_point")
if 'batches' in self._sourcepoint:
subelement = ET.SubElement(element, "batches")
subelement.text = ' '.join(
str(x) for x in self._sourcepoint['batches'])
if 'separate' in self._sourcepoint:
subelement = ET.SubElement(element, "separate")
subelement.text = str(self._sourcepoint['separate']).lower()
if 'write' in self._sourcepoint:
subelement = ET.SubElement(element, "write")
subelement.text = str(self._sourcepoint['write']).lower()
# Overwrite latest subelement
if 'overwrite' in self._sourcepoint:
subelement = ET.SubElement(element, "overwrite_latest")
subelement.text = str(self._sourcepoint['overwrite']).lower()
def _create_confidence_intervals(self, root):
if self._confidence_intervals is not None:
element = ET.SubElement(root, "confidence_intervals")
element.text = str(self._confidence_intervals).lower()
def _create_electron_treatment_subelement(self, root):
if self._electron_treatment is not None:
element = ET.SubElement(root, "electron_treatment")
element.text = str(self._electron_treatment)
def _create_photon_transport_subelement(self, root):
if self._photon_transport is not None:
element = ET.SubElement(root, "photon_transport")
element.text = str(self._photon_transport).lower()
def _create_ptables_subelement(self, root):
if self._ptables is not None:
element = ET.SubElement(root, "ptables")
element.text = str(self._ptables).lower()
def _create_seed_subelement(self, root):
if self._seed is not None:
element = ET.SubElement(root, "seed")
element.text = str(self._seed)
def _create_survival_biasing_subelement(self, root):
if self._survival_biasing is not None:
element = ET.SubElement(root, "survival_biasing")
element.text = str(self._survival_biasing).lower()
def _create_cutoff_subelement(self, root):
if self._cutoff is not None:
element = ET.SubElement(root, "cutoff")
for key, value in self._cutoff.items():
subelement = ET.SubElement(element, key)
subelement.text = str(value)
def _create_entropy_mesh_subelement(self, root):
if self.entropy_mesh is not None:
# See if a <mesh> element already exists -- if not, add it
path = "./mesh[@id='{}']".format(self.entropy_mesh.id)
if root.find(path) is None:
root.append(self.entropy_mesh.to_xml_element())
subelement = ET.SubElement(root, "entropy_mesh")
subelement.text = str(self.entropy_mesh.id)
def _create_trigger_subelement(self, root):
if self._trigger_active is not None:
trigger_element = ET.SubElement(root, "trigger")
element = ET.SubElement(trigger_element, "active")
element.text = str(self._trigger_active).lower()
if self._trigger_max_batches is not None:
element = ET.SubElement(trigger_element, "max_batches")
element.text = str(self._trigger_max_batches)
if self._trigger_batch_interval is not None:
element = ET.SubElement(trigger_element, "batch_interval")
element.text = str(self._trigger_batch_interval)
def _create_no_reduce_subelement(self, root):
if self._no_reduce is not None:
element = ET.SubElement(root, "no_reduce")
element.text = str(self._no_reduce).lower()
def _create_tabular_legendre_subelements(self, root):
if self.tabular_legendre:
element = ET.SubElement(root, "tabular_legendre")
subelement = ET.SubElement(element, "enable")
subelement.text = str(self._tabular_legendre['enable']).lower()
if 'num_points' in self._tabular_legendre:
subelement = ET.SubElement(element, "num_points")
subelement.text = str(self._tabular_legendre['num_points'])
def _create_temperature_subelements(self, root):
if self.temperature:
for key, value in sorted(self.temperature.items()):
element = ET.SubElement(root,
"temperature_{}".format(key))
if isinstance(value, bool):
element.text = str(value).lower()
elif key == 'range':
element.text = ' '.join(str(T) for T in value)
else:
element.text = str(value)
def _create_trace_subelement(self, root):
if self._trace is not None:
element = ET.SubElement(root, "trace")
element.text = ' '.join(map(str, self._trace))
def _create_track_subelement(self, root):
if self._track is not None:
element = ET.SubElement(root, "track")
element.text = ' '.join(map(str, self._track))
def _create_ufs_mesh_subelement(self, root):
if self.ufs_mesh is not None:
# See if a <mesh> element already exists -- if not, add it
path = "./mesh[@id='{}']".format(self.ufs_mesh.id)
if root.find(path) is None:
root.append(self.ufs_mesh.to_xml_element())
subelement = ET.SubElement(root, "ufs_mesh")
subelement.text = str(self.ufs_mesh.id)
def _create_resonance_scattering_subelement(self, root):
res = self.resonance_scattering
if res:
elem = ET.SubElement(root, 'resonance_scattering')
if 'enable' in res:
subelem = ET.SubElement(elem, 'enable')
subelem.text = str(res['enable']).lower()
if 'method' in res:
subelem = ET.SubElement(elem, 'method')
subelem.text = res['method']
if 'energy_min' in res:
subelem = ET.SubElement(elem, 'energy_min')
subelem.text = str(res['energy_min'])
if 'energy_max' in res:
subelem = ET.SubElement(elem, 'energy_max')
subelem.text = str(res['energy_max'])
if 'nuclides' in res:
subelem = ET.SubElement(elem, 'nuclides')
subelem.text = ' '.join(res['nuclides'])
def _create_create_fission_neutrons_subelement(self, root):
if self._create_fission_neutrons is not None:
elem = ET.SubElement(root, "create_fission_neutrons")
elem.text = str(self._create_fission_neutrons).lower()
def _create_log_grid_bins_subelement(self, root):
if self._log_grid_bins is not None:
elem = ET.SubElement(root, "log_grid_bins")
elem.text = str(self._log_grid_bins)
def _create_dagmc_subelement(self, root):
if self._dagmc:
elem = ET.SubElement(root, "dagmc")
elem.text = str(self._dagmc).lower()
def _eigenvalue_from_xml_element(self, root):
elem = root.find('eigenvalue')
if elem is not None:
self._run_mode_from_xml_element(elem)
self._particles_from_xml_element(elem)
self._batches_from_xml_element(elem)
self._inactive_from_xml_element(elem)
self._generations_per_batch_from_xml_element(elem)
def _run_mode_from_xml_element(self, root):
text = get_text(root, 'run_mode')
if text is not None:
self.run_mode = text
def _particles_from_xml_element(self, root):
text = get_text(root, 'particles')
if text is not None:
self.particles = int(text)
def _batches_from_xml_element(self, root):
text = get_text(root, 'batches')
if text is not None:
self.batches = int(text)
def _inactive_from_xml_element(self, root):
text = get_text(root, 'inactive')
if text is not None:
self.inactive = int(text)
def _generations_per_batch_from_xml_element(self, root):
text = get_text(root, 'generations_per_batch')
if text is not None:
self.generations_per_batch = int(text)
def _keff_trigger_from_xml_element(self, root):
elem = root.find('keff_trigger')
if elem is not None:
trigger = get_text(elem, 'type')
threshold = float(get_text(elem, 'threshold'))
self.keff_trigger = {'type': trigger, 'threshold': threshold}
def _source_from_xml_element(self, root):
for elem in root.findall('source'):
self.source.append(Source.from_xml_element(elem))
def _output_from_xml_element(self, root):
elem = root.find('output')
if elem is not None:
self.output = {}
for key in ('summary', 'tallies', 'path'):
value = get_text(elem, key)
if value is not None:
if key in ('summary', 'tallies'):
value = value in ('true', '1')
self.output[key] = value
def _statepoint_from_xml_element(self, root):
elem = root.find('state_point')
if elem is not None:
text = get_text(elem, 'batches')
if text is not None:
self.statepoint['batches'] = [int(x) for x in text.split()]
def _sourcepoint_from_xml_element(self, root):
elem = root.find('source_point')
if elem is not None:
for key in ('separate', 'write', 'overwrite_latest', 'batches'):
value = get_text(elem, key)
if value is not None:
if key in ('separate', 'write'):
value = value in ('true', '1')
elif key == 'overwrite_latest':
value = value in ('true', '1')
key = 'overwrite'
else:
value = [int(x) for x in value.split()]
self.sourcepoint[key] = value
def _confidence_intervals_from_xml_element(self, root):
text = get_text(root, 'confidence_intervals')
if text is not None:
self.confidence_intervals = text in ('true', '1')
def _electron_treatment_from_xml_element(self, root):
text = get_text(root, 'electron_treatment')
if text is not None:
self.electron_treatment = text
def _energy_mode_from_xml_element(self, root):
text = get_text(root, 'energy_mode')
if text is not None:
self.energy_mode = text
def _max_order_from_xml_element(self, root):
text = get_text(root, 'max_order')
if text is not None:
self.max_order = int(text)
def _photon_transport_from_xml_element(self, root):
text = get_text(root, 'photon_transport')
if text is not None:
self.photon_transport = text in ('true', '1')
def _ptables_from_xml_element(self, root):
text = get_text(root, 'ptables')
if text is not None:
self.ptables = text in ('true', '1')
def _seed_from_xml_element(self, root):
text = get_text(root, 'seed')
if text is not None:
self.seed = int(text)
def _survival_biasing_from_xml_element(self, root):
text = get_text(root, 'survival_biasing')
if text is not None:
self.survival_biasing = text in ('true', '1')
def _cutoff_from_xml_element(self, root):
elem = root.find('cutoff')
if elem is not None:
self.cutoff = {}
for key in ('energy_neutron', 'energy_photon', 'energy_electron',
'energy_positron', 'weight', 'weight_avg'):
value = get_text(elem, key)
if value is not None:
self.cutoff[key] = float(value)
def _entropy_mesh_from_xml_element(self, root):
text = get_text(root, 'entropy_mesh')
if text is not None:
path = "./mesh[@id='{}']".format(int(text))
elem = root.find(path)
if elem is not None:
self.entropy_mesh = RegularMesh.from_xml_element(elem)
def _trigger_from_xml_element(self, root):
elem = root.find('trigger')
if elem is not None:
self.trigger_active = get_text(elem, 'active') in ('true', '1')
text = get_text(elem, 'max_batches')
if text is not None:
self.trigger_max_batches = int(text)
text = get_text(elem, 'batch_interval')
if text is not None:
self.trigger_batch_interval = int(text)
def _no_reduce_from_xml_element(self, root):
text = get_text(root, 'no_reduce')
if text is not None:
self.no_reduce = text in ('true', '1')
def _verbosity_from_xml_element(self, root):
text = get_text(root, 'verbosity')
if text is not None:
self.verbosity = int(text)
def _tabular_legendre_from_xml_element(self, root):
elem = root.find('tabular_legendre')
if elem is not None:
text = get_text(elem, 'enable')
self.tabular_legendre['enable'] = text in ('true', '1')
text = get_text(elem, 'num_points')
if text is not None:
self.tabular_legendre['num_points'] = int(text)
def _temperature_from_xml_element(self, root):
text = get_text(root, 'temperature_default')
if text is not None:
self.temperature['default'] = float(text)
text = get_text(root, 'temperature_tolerance')
if text is not None:
self.temperature['tolerance'] = float(text)
text = get_text(root, 'temperature_method')
if text is not None:
self.temperature['method'] = text
text = get_text(root, 'temperature_range')
if text is not None:
self.temperature['range'] = [float(x) for x in text.split()]
text = get_text(root, 'temperature_multipole')
if text is not None:
self.temperature['multipole'] = text in ('true', '1')
def _trace_from_xml_element(self, root):
text = get_text(root, 'trace')
if text is not None:
self.trace = [int(x) for x in text.split()]
def _track_from_xml_element(self, root):
text = get_text(root, 'track')
if text is not None:
self.track = [int(x) for x in text.split()]
def _ufs_mesh_from_xml_element(self, root):
text = get_text(root, 'ufs_mesh')
if text is not None:
path = "./mesh[@id='{}']".format(int(text))
elem = root.find(path)
if elem is not None:
self.ufs_mesh = RegularMesh.from_xml_element(elem)
def _resonance_scattering_from_xml_element(self, root):
elem = root.find('resonance_scattering')
if elem is not None:
keys = ('enable', 'method', 'energy_min', 'energy_max', 'nuclides')
for key in keys:
value = get_text(elem, key)
if value is not None:
if key == 'enable':
value = value in ('true', '1')
elif key in ('energy_min', 'energy_max'):
value = float(value)
elif key == 'nuclides':
value = value.split()
self.resonance_scattering[key] = value
def _create_fission_neutrons_from_xml_element(self, root):
text = get_text(root, 'create_fission_neutrons')
if text is not None:
self.create_fission_neutrons = text in ('true', '1')
def _log_grid_bins_from_xml_element(self, root):
text = get_text(root, 'log_grid_bins')
if text is not None:
self.log_grid_bins = int(text)
def _dagmc_from_xml_element(self, root):
text = get_text(root, 'dagmc')
if text is not None:
self.dagmc = text in ('true', '1')
[docs] def export_to_xml(self, path='settings.xml'):
"""Export simulation settings to an XML file.
Parameters
----------
path : str
Path to file to write. Defaults to 'settings.xml'.
"""
# Reset xml element tree
root_element = ET.Element("settings")
self._create_run_mode_subelement(root_element)
self._create_particles_subelement(root_element)
self._create_batches_subelement(root_element)
self._create_inactive_subelement(root_element)
self._create_generations_per_batch_subelement(root_element)
self._create_keff_trigger_subelement(root_element)
self._create_source_subelement(root_element)
self._create_output_subelement(root_element)
self._create_statepoint_subelement(root_element)
self._create_sourcepoint_subelement(root_element)
self._create_confidence_intervals(root_element)
self._create_electron_treatment_subelement(root_element)
self._create_energy_mode_subelement(root_element)
self._create_max_order_subelement(root_element)
self._create_photon_transport_subelement(root_element)
self._create_ptables_subelement(root_element)
self._create_seed_subelement(root_element)
self._create_survival_biasing_subelement(root_element)
self._create_cutoff_subelement(root_element)
self._create_entropy_mesh_subelement(root_element)
self._create_trigger_subelement(root_element)
self._create_no_reduce_subelement(root_element)
self._create_verbosity_subelement(root_element)
self._create_tabular_legendre_subelements(root_element)
self._create_temperature_subelements(root_element)
self._create_trace_subelement(root_element)
self._create_track_subelement(root_element)
self._create_ufs_mesh_subelement(root_element)
self._create_resonance_scattering_subelement(root_element)
self._create_volume_calcs_subelement(root_element)
self._create_create_fission_neutrons_subelement(root_element)
self._create_log_grid_bins_subelement(root_element)
self._create_dagmc_subelement(root_element)
# Clean the indentation in the file to be user-readable
clean_indentation(root_element)
# Check if path is a directory
p = Path(path)
if p.is_dir():
p /= 'settings.xml'
# Write the XML Tree to the settings.xml file
tree = ET.ElementTree(root_element)
tree.write(str(p), xml_declaration=True, encoding='utf-8')
[docs] @classmethod
def from_xml(cls, path='settings.xml'):
"""Generate settings from XML file
Parameters
----------
path : str, optional
Path to settings XML file
Returns
-------
openmc.Settings
Settings object
"""
tree = ET.parse(path)
root = tree.getroot()
settings = cls()
settings._eigenvalue_from_xml_element(root)
settings._run_mode_from_xml_element(root)
settings._particles_from_xml_element(root)
settings._batches_from_xml_element(root)
settings._inactive_from_xml_element(root)
settings._generations_per_batch_from_xml_element(root)
settings._keff_trigger_from_xml_element(root)
settings._source_from_xml_element(root)
settings._output_from_xml_element(root)
settings._statepoint_from_xml_element(root)
settings._sourcepoint_from_xml_element(root)
settings._confidence_intervals_from_xml_element(root)
settings._electron_treatment_from_xml_element(root)
settings._energy_mode_from_xml_element(root)
settings._max_order_from_xml_element(root)
settings._photon_transport_from_xml_element(root)
settings._ptables_from_xml_element(root)
settings._seed_from_xml_element(root)
settings._survival_biasing_from_xml_element(root)
settings._cutoff_from_xml_element(root)
settings._entropy_mesh_from_xml_element(root)
settings._trigger_from_xml_element(root)
settings._no_reduce_from_xml_element(root)
settings._verbosity_from_xml_element(root)
settings._tabular_legendre_from_xml_element(root)
settings._temperature_from_xml_element(root)
settings._trace_from_xml_element(root)
settings._track_from_xml_element(root)
settings._ufs_mesh_from_xml_element(root)
settings._resonance_scattering_from_xml_element(root)
settings._create_fission_neutrons_from_xml_element(root)
settings._log_grid_bins_from_xml_element(root)
settings._dagmc_from_xml_element(root)
# TODO: Get volume calculations
return settings