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Subdomain-averaged multi-group cross-section calculation now working
This commit is contained in:
Will Boyd
parent
665b8226e8
commit
ecda3bef5e
2 changed files with 62 additions and 46 deletions
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@ -217,7 +217,7 @@ class MultiGroupXS(object):
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"""Finds and stores the offset of the domain tally filter"""
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tally = self.tallies.values()[0]
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domain_filter = tally.find_filter(self.domain_type, [self.domain.id])
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domain_filter = tally.find_filter(self.domain_type)
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self._offset = domain_filter.offset
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def set_subdomain_index(self, subdomain_id, index):
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@ -280,7 +280,9 @@ class MultiGroupXS(object):
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cv.check_type('subdomains', subdomains, Iterable, Integral)
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if subdomains == 'all':
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num_subdomains = len(self.subdomain_indices)
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tally = self.tallies.values()[0]
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domain_filter = tally.find_filter(self.domain_type)
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num_subdomains = domain_filter.num_bins
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indices = np.arange(num_subdomains)
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else:
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indices = np.zeros(len(subdomains), dtype=np.int64)
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@ -329,19 +331,22 @@ class MultiGroupXS(object):
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cv.check_type('offsets', indices, Iterable, Integral)
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if indices == 'all':
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indices = self.get_subdomain_indices()
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tally = self.tallies.values()[0]
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domain_filter = tally.find_filter(self.domain_type)
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num_subdomains = domain_filter.num_bins
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subdomains = np.arange(num_subdomains)
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else:
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subdomains = np.zeros(len(indices), dtype=np.int64)
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keys = self.subdomain_indices.keys()
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values = self.subdomain_indices.values()
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subdomains = np.zeros(len(indices), dtype=np.int64)
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keys = self.subdomain_indices.keys()
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values = self.subdomain_indices.values()
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for i, index in enumerate(indices):
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if index in values:
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subdomains[i] = keys[values.index(index)]
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else:
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msg = 'Unable to get subdomain for index "{0}" since it ' \
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'is not a valid index'.format(index)
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raise ValueError(msg)
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for i, index in enumerate(indices):
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if index in values:
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subdomains[i] = keys[values.index(index)]
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else:
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msg = 'Unable to get subdomain for index "{0}" since it ' \
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'is not a valid index'.format(index)
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raise ValueError(msg)
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return subdomains
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@ -520,11 +525,11 @@ class MultiGroupXS(object):
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if subdomains != 'all':
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cv.check_iterable_type('subdomains', subdomains, Integral)
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subdomain_indices = self.get_subdomain_indices(subdomains)
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subdomain_indices = [(index,) for index in subdomain_indices]
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# subdomain_indices = [(index,) for index in subdomain_indices]
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# Clone this MultiGroupXS to initialize the condensed version
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avg_xs = copy.deepcopy(self)
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avg_xs.domain_type = 'avg. ' + avg_xs.domain_type
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avg_xs._domain_type = 'avg. ' + avg_xs.domain_type
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# Reset subdomain indices and offsets for distribcell domains
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if self.domain_type == 'distribcell':
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@ -534,7 +539,7 @@ class MultiGroupXS(object):
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# Overwrite tallies with new subdomain-averaged versions
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avg_xs._tallies = {}
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for tally_type, tally in self.tallies.items():
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tally_sum = tally.summation(filters=[self.domain_type],
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tally_sum = tally.summation(filter=self.domain_type,
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filter_bins=subdomain_indices)
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tally_sum /= len(subdomains)
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avg_xs.tallies[tally_type] = tally_sum
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@ -1281,13 +1286,19 @@ class Chi(MultiGroupXS):
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# FIXME: Make filter bins simpler in Tally.summation(...)
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# Construct energy group filter bins to sum across
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'''
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filter_bins = []
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for group in range(1, self.num_groups+1):
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group_bounds = self.energy_groups.get_group_bounds(group)
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filter_bins.append((group_bounds,))
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energy_bins = [filter_bins]
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'''
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sum_nu_fission_in = nu_fission_in.summation(filters=['energy'],
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energy_bins = []
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for group in range(1, self.num_groups+1):
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energy_bins.append(self.energy_groups.get_group_bounds(group))
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sum_nu_fission_in = nu_fission_in.summation(filter='energy',
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filter_bins=energy_bins)
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# FIXME: Need ability to override energy groups with group numbers
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@ -1299,7 +1310,7 @@ class Chi(MultiGroupXS):
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self._xs_tally = nu_fission_out / sum_nu_fission_in
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# Normalize chi to 1.0
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norm = self.xs_tally.summation(filters=['energyout'],
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norm = self.xs_tally.summation(filter='energyout',
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filter_bins=energy_bins)
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# FIXME: CrossFilter for energy + energy messes up tally arithmetic
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@ -9,7 +9,7 @@ import sys
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import numpy as np
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from openmc import Mesh, Filter, Trigger, Nuclide
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from openmc import Mesh, Filter, Trigger, Nuclide, FILTER_TYPES
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from openmc.cross import CrossScore, CrossNuclide, CrossFilter
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from openmc.summary import Summary
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import openmc.checkvalue as cv
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@ -78,8 +78,8 @@ class Tally(object):
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mean : ndarray
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An array containing the sample mean for each bin
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std_dev : ndarray
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An array containing the sample standard deviation for each bin
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"""
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def __init__(self, tally_id=None, name=''):
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@ -713,7 +713,7 @@ class Tally(object):
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filter_type : str
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The type of Filter (e.g., 'cell', 'energy', etc.)
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filter_bin : int, list
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filter_bin : int, tuple
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The bin is an integer ID for 'material', 'surface', 'cell',
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'cellborn', and 'universe' Filters. The bin is an integer for the
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cell instance ID for 'distribcell' Filters. The bin is a 2-tuple of
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@ -2277,6 +2277,8 @@ class Tally(object):
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if filter_type in ['energy', 'energyout']:
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bin_indices.append(bin_index)
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bin_indices.append(bin_index+1)
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elif filter_type == 'distribcell':
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bin_indices.append(0)
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else:
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bin_indices.append(bin_index)
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@ -2292,13 +2294,13 @@ class Tally(object):
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return new_tally
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def summation(self, scores=[], filters=[], filter_bins=[], nuclides=[]):
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"""Build a sliced tally for the specified filters, scores and nuclides.
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def summation(self, scores=[], filter=None, filter_bins=[], nuclides=[]):
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"""Build a sliced tally for the specified filter bins, nuclides, scores.
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This method constructs a new tally to encapsulate a subset of the data
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represented by this tally. The subset of data to include in the tally
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slice is determined by the scores, filters and nuclides specified in
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the input parameters.
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slice is determined by the scores, filter bins and nuclides specified
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in the input parameters.
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Parameters
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----------
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@ -2306,21 +2308,19 @@ class Tally(object):
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A list of one or more score strings to sum across
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(e.g., ['absorption', 'nu-fission']; default is [])
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filters : list
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A list of filter type strings to sum across
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(e.g., ['mesh', 'energy']; default is [])
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filter : str
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A filter type string (e.g., 'cell', 'energy') corresponding to the
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filter bins to sum across
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filter_bins : list of Iterables
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A list of the filter bins corresponding to the filter_types
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parameter (e.g., [(1,), (0., 0.625e-6)]; default is []). Each bin
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in the list is the integer ID for 'material', 'surface', 'cell',
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'cellborn', and 'universe' Filters. Each bin is an integer for the
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cell instance ID for 'distribcell Filters. Each bin is a 2-tuple of
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floats for 'energy' and 'energyout' filters corresponding to the
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energy boundaries of the bin of interest. The bin is a (x,y,z)
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3-tuple for 'mesh' filters corresponding to the mesh cell of
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interest. The order of the bins in the list must correspond to the
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filter_types parameter.
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filter_bins : Iterable of Integral or tuple
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A list of the filter bins corresponding to the filters parameter
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Each bin in the list is the integer ID for 'material', 'surface',
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'cell', 'cellborn', and 'universe' Filters. Each bin is an integer
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for the cell instance ID for 'distribcell Filters. Each bin is a
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2-tuple of floats for 'energy' and 'energyout' filters corresponding
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to the energy boundaries of the bin of interest. Each bin is an
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(x,y,z) 3-tuple for 'mesh' filters corresponding to the mesh cell of
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interest.
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nuclides : list
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A list of nuclide name strings to sum across
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@ -2347,15 +2347,20 @@ class Tally(object):
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else:
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nuclides = [[nuclide] for nuclide in nuclides]
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# If user did not specify any filter bins, do not sum across filter bins
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if len(filters) == 0:
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# Sum across any filter bins specified by the user
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if filter in FILTER_TYPES.values():
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filter_bins = [[(filter_bin,)] for filter_bin in filter_bins]
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filters = [[filter]]
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# If user did not specify a filter type, do not sum across filter bins
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else:
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filter_bins = [[]]
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filters = [[]]
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# Sum across any filter bins specified by the user
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'''
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else:
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filter_bins = list(itertools.product(*filter_bins))
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filter_bins = [list(filter_bin) for filter_bin in filter_bins]
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filters = [filters]
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# filter_bins = list(itertools.product(*filter_bins))
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filter_bins = [[filter_bin] for filter_bin in filter_bins]
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filters = [[filter]]
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'''
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# Initialize Tally sum
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tally_sum = 0
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