mirror of
https://github.com/openmc-dev/openmc.git
synced 2026-07-28 22:26:08 -04:00
Refactored Tally.get_values(...) routine to return scalar and/or vector-valued quantities
This commit is contained in:
Will Boyd
parent
05bd905462
commit
926526dc6a
6 changed files with 364 additions and 216 deletions
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@ -104,7 +104,7 @@ class Filter(object):
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self._type = type
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elif not type in FILTER_TYPES.values():
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msg = 'Unable to set Filter type to {0} since it is not one ' \
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msg = 'Unable to set Filter type to "{0}" since it is not one ' \
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'of the supported types'.format(type)
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raise ValueError(msg)
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@ -118,7 +118,7 @@ class Filter(object):
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self.num_bins = 0
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elif self._type is None:
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msg = 'Unable to set bins for Filter to {0} since ' \
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msg = 'Unable to set bins for Filter to "{0}" since ' \
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'the Filter type has not yet been set'.format(bins)
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raise ValueError(msg)
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@ -136,12 +136,12 @@ class Filter(object):
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for edge in bins:
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if not is_integer(edge):
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msg = 'Unable to add bin {0} to a {1} Filter since ' \
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msg = 'Unable to add bin "{0}" to a {1} Filter since ' \
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'it is a non-integer'.format(edge, self._type)
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raise ValueError(msg)
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elif edge < 0:
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msg = 'Unable to add bin {0} to a {1} Filter since ' \
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msg = 'Unable to add bin "{0}" to a {1} Filter since ' \
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'it is a negative integer'.format(edge, self._type)
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raise ValueError(msg)
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@ -151,22 +151,22 @@ class Filter(object):
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for edge in bins:
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if not is_integer(edge) and not is_float(edge):
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msg = 'Unable to add bin edge {0} to {1} Filter since ' \
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'it is a non-integer or floating point ' \
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msg = 'Unable to add bin edge "{0}" to a {1} Filter ' \
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'since it is a non-integer or floating point ' \
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'value'.format(edge, self._type)
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raise ValueError(msg)
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elif edge < 0.:
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msg = 'Unable to add bin edge {0} to {1} Filter since it ' \
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'is a negative value'.format(edge, self._type)
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msg = 'Unable to add bin edge "{0}" to a {1} Filter ' \
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'since it is a negative value'.format(edge, self._type)
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raise ValueError(msg)
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# Check that bin edges are monotonically increasing
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for index in range(len(bins)):
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if index > 0 and bins[index] < bins[index-1]:
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msg = 'Unable to add bin edges {0} to {1} Filter since ' \
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'they are not monotonically ' \
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msg = 'Unable to add bin edges "{0}" to a {1} Filter ' \
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'since they are not monotonically ' \
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'increasing'.format(bins, self._type)
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raise ValueError(msg)
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@ -175,17 +175,17 @@ class Filter(object):
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elif self._type == 'mesh':
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if not len(bins) == 1:
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msg = 'Unable to add bins {0} to a mesh Filter since ' \
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msg = 'Unable to add bins "{0}" to a mesh Filter since ' \
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'only a single mesh can be used per tally'.format(bins)
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raise ValueError(msg)
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elif not is_integer(bins[0]):
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msg = 'Unable to add bin {0} to mesh Filter since it ' \
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msg = 'Unable to add bin "{0}" to mesh Filter since it ' \
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'is a non-integer'.format(bins[0])
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raise ValueError(msg)
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elif bins[0] < 0:
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msg = 'Unable to add bin {0} to mesh Filter since it ' \
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msg = 'Unable to add bin "{0}" to mesh Filter since it ' \
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'is a negative integer'.format(bins[0])
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raise ValueError(msg)
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@ -198,7 +198,7 @@ class Filter(object):
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def num_bins(self, num_bins):
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if not is_integer(num_bins) or num_bins < 0:
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msg = 'Unable to set the number of bins {0} for a {1} Filter ' \
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msg = 'Unable to set the number of bins "{0}" for a {1} Filter ' \
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'since it is not a positive ' \
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'integer'.format(num_bins, self._type)
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raise ValueError(msg)
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@ -210,7 +210,7 @@ class Filter(object):
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def mesh(self, mesh):
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if not isinstance(mesh, Mesh):
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msg = 'Unable to set Mesh to {0} for Filter since it is not a ' \
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msg = 'Unable to set Mesh to "{0}" for Filter since it is not a ' \
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'Mesh object'.format(mesh)
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raise ValueError(msg)
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@ -223,7 +223,7 @@ class Filter(object):
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def offset(self, offset):
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if not is_integer(offset):
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msg = 'Unable to set offset {0} for a {1} Filter since it is a ' \
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msg = 'Unable to set offset "{0}" for a {1} Filter since it is a ' \
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'non-integer value'.format(offset, self._type)
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raise ValueError(msg)
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@ -234,12 +234,12 @@ class Filter(object):
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def stride(self, stride):
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if not is_integer(stride):
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msg = 'Unable to set stride {0} for a {1} Filter since it is a ' \
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msg = 'Unable to set stride "{0}" for a {1} Filter since it is a ' \
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'non-integer value'.format(stride, self._type)
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raise ValueError(msg)
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if stride < 0:
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msg = 'Unable to set stride {0} for a {1} Filter since it is a ' \
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msg = 'Unable to set stride "{0}" for a {1} Filter since it is a ' \
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'negative value'.format(stride, self._type)
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raise ValueError(msg)
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@ -288,17 +288,63 @@ class Filter(object):
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return merged_filter
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def get_bin_index(self, bin):
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def get_bin_index(self, filter_bin):
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"""Returns the index in the Filter for some bin.
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Parameters
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----------
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filter_bin : int, tuple
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The bin is the integer ID for 'material', 'surface', 'cell',
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'cellborn', and 'universe' Filters. The bin is an integer for
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the cell instance ID for 'distribcell' Filters. The bin is
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a 2-tuple of floats for 'energy' and 'energyout' filters
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corresponding to the energy boundaries of the bin of interest.
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The bin is a (x,y,z) 3-tuple for 'mesh' filters corresponding to
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the mesh cell of interest.
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"""
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# FIXME: This does not work for distribcells!!!
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try:
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index = self._bins.index(bin)
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# Filter bins for a mesh are an (x,y,z) tuple
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if self.type == 'mesh':
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# Convert (x,y,z) to a single bin -- this is similar to
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# subroutine mesh_indices_to_bin in openmc/src/mesh.F90.
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if (len(self.mesh.dimension) == 3):
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nx, ny, nz = self.mesh.dimension
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val = (filter_bin[0] - 1) * ny * nz + \
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(filter_bin[1] - 1) * nz + \
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(filter_bin[2] - 1)
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else:
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nx, ny = self.mesh.dimension
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val = (filter_bin[0] - 1) * ny + \
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(filter_bin[1] - 1)
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filter_index = val
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# Use lower energy bound to find index for energy Filters
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elif self.type in ['energy', 'energyout']:
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val = self.bins.index(filter_bin[0])
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filter_index = val
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# Filter bins for distribcell are the "IDs" of each unique placement
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# of the Cell in the Geometry (integers starting at 0)
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elif self._type == 'distribcell':
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filter_index = filter_bin
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# Use ID for all other Filters (e.g., material, cell, etc.)
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else:
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val = self.bins.index(filter_bin)
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filter_index = val
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except ValueError:
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msg = 'Unable to get the bin index for Filter since {0} ' \
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'is not one of the bins'.format(bin)
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msg = 'Unable to get the bin index for Filter since "{0}" ' \
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'is not one of the bins'.format(filter_bin)
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raise ValueError(msg)
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return index
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return filter_index
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def __repr__(self):
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@ -1,5 +1,6 @@
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import copy
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import os
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import itertools
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from xml.etree import ElementTree as ET
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import numpy as np
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@ -257,8 +258,8 @@ class Tally(object):
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def add_trigger(self, trigger):
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if not isinstance(trigger, Trigger):
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msg = 'Unable to add a tally trigger for for Tally ID={0} to ' \
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'{1} since it is not a valid estimator type'.format(trigger)
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msg = 'Unable to add a tally trigger for Tally ID={0} to ' \
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'since "{1}" is not a Trigger'.format(self.id, trigger)
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raise ValueError(msg)
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self._triggers.append(trigger)
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@ -291,7 +292,7 @@ class Tally(object):
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if not is_string(name):
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msg = 'Unable to set name for Tally ID={0} with a non-string ' \
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'value {1}'.format(self.id, name)
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'value "{1}"'.format(self.id, name)
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raise ValueError(msg)
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else:
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@ -303,8 +304,8 @@ class Tally(object):
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global filters
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if not isinstance(filter, Filter):
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msg = 'Unable to add Filter {0} to Tally ID={1} since it is not ' \
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'a Filter object'.format(filter, self.id)
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msg = 'Unable to add Filter "{0}" to Tally ID={1} since it is ' \
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'not a Filter object'.format(filter, self.id)
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raise ValueError(msg)
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self._filters.append(filter)
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@ -317,8 +318,8 @@ class Tally(object):
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def add_score(self, score):
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if not is_string(score):
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msg = 'Unable to add score {0} to Tally ID={1} since it is not a ' \
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'string'.format(score, self.id)
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msg = 'Unable to add score "{0}" to Tally ID={1} since it is ' \
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'not a string'.format(score, self.id)
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raise ValueError(msg)
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# If the score is already in the Tally, don't add it again
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@ -337,13 +338,13 @@ class Tally(object):
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def num_realizations(self, num_realizations):
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if not is_integer(num_realizations):
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msg = 'Unable to set the number of realizations to {0} for ' \
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msg = 'Unable to set the number of realizations to "{0}" for ' \
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'Tally ID={1} since it is not an ' \
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'integer'.format(num_realizations)
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raise ValueError(msg)
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elif num_realizations < 0:
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msg = 'Unable to set the number of realizations to {0} for ' \
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msg = 'Unable to set the number of realizations to "{0}" for ' \
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'Tally ID={1} since it is a negative ' \
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'value'.format(num_realizations)
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raise ValueError(msg)
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@ -354,13 +355,13 @@ class Tally(object):
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def set_results(self, sum, sum_sq):
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if not isinstance(sum, (tuple, list, np.ndarray)):
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msg = 'Unable to set the sum to {0}for Tally ID={1} since ' \
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msg = 'Unable to set the sum to "{0}" for Tally ID={1} since ' \
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'it is not a Python tuple/list or NumPy ' \
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'array'.format(sum, self.id)
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raise ValueError(msg)
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if not isinstance(sum_sq, (tuple, list, np.ndarray)):
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msg = 'Unable to set the sum to {0}for Tally ID={1} since ' \
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msg = 'Unable to set the sum to "{0}" for Tally ID={1} since ' \
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'it is not a Python tuple/list or NumPy ' \
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'array'.format(sum_sq, self.id)
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raise ValueError(msg)
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@ -372,7 +373,7 @@ class Tally(object):
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def remove_score(self, score):
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if not score in self.scores:
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msg = 'Unable to remove score {0} from Tally ID={1} since the ' \
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msg = 'Unable to remove score "{0}" from Tally ID={1} since the ' \
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'Tally does not contain this score'.format(score, self.id)
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ValueError(msg)
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@ -382,7 +383,7 @@ class Tally(object):
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def remove_filter(self, filter):
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if not filter in self.filters:
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msg = 'Unable to remove filter {0} from Tally ID={1} since the ' \
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msg = 'Unable to remove filter "{0}" from Tally ID={1} since the ' \
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'Tally does not contain this filter'.format(filter, self.id)
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ValueError(msg)
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@ -392,7 +393,7 @@ class Tally(object):
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def remove_nuclide(self, nuclide):
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if not nuclide in self.nuclides:
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msg = 'Unable to remove nuclide {0} from Tally ID={1} since the ' \
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msg = 'Unable to remove nuclide "{0}" from Tally ID={1} since the ' \
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'Tally does not contain this nuclide'.format(nuclide, self.id)
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ValueError(msg)
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@ -570,131 +571,244 @@ class Tally(object):
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return element
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def find_filter(self, filter_type, bins):
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def find_filter(self, filter_type):
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filter = None
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# Look through all of this Tally's Filters for the type requested
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for test_filter in self.filters:
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# Determine if the Filter has the same type as the one requested
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if test_filter.type != filter_type:
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continue
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# Determine if the Filter has the same bin edges as the one requested
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elif test_filter.bins != bins:
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continue
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else:
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if test_filter.type == filter_type:
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filter = test_filter
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break
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# If we found the Filter, return it
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if not filter is None:
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return filter
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# Otherwise, throw an Exception
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else:
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msg = 'Unable to find filter type {0} with bin edges {1} in ' \
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'Tally ID={2}'.format(filter_type, bins, self.id)
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# If we did not find the Filter, throw an Exception
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if filter is None:
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msg = 'Unable to find filter type "{0}" in ' \
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'Tally ID={1}'.format(filter_type, self.id)
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raise ValueError(msg)
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return filter
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def get_filter_index(self, filter_type, filter_bin):
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"""Returns the index in the Tally's results array for a Filter bin
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Parameters
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----------
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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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The bin is an integer ID for 'material', 'surface', 'cell',
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'cellborn', and 'universe' Filters. The bin is an integer for
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the cell instance ID for 'distribcell' Filters. The bin is
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a 2-tuple of floats for 'energy' and 'energyout' filters
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corresponding to the energy boundaries of the bin of interest.
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The bin is a (x,y,z) 3-tuple for 'mesh' filters corresponding to
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the mesh cell of interest.
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"""
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# Find the equivalent Filter in this Tally's list of Filters
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filter = self.find_filter(filter_type)
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# Get the index for the requested bin from the Filter and return it
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filter_index = filter.get_bin_index(filter_bin)
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return filter_index
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def get_nuclide_index(self, nuclide):
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"""Returns the index in the Tally's results array for a Nuclide bin
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Parameters
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----------
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nuclide : str
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The name of the Nuclide (e.g., 'H-1', 'U-238')
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"""
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nuclide_index = -1
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# Look for the user-requested nuclide in all of the Tally's Nuclides
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for i, test_nuclide in enumerate(self.nuclides):
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# If the Summary was linked, then values are Nuclide objects
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if isinstance(test_nuclide, Nuclide):
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if test_nuclide._name == nuclide:
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nuclide_index = i
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break
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# If the Summary has not been linked, then values are ZAIDs
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else:
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if test_nuclide == nuclide:
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nuclide_index = i
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break
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if nuclide_index == -1:
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msg = 'Unable to get the nuclide index for Tally since "{0}" ' \
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'is not one of the nuclides'.format(nuclide)
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raise ValueError(msg)
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else:
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return nuclide_index
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def get_score_index(self, score):
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try:
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index = self.scores.index(score)
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except ValueError:
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msg = 'Unable to get the score index for Tally since {0} ' \
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'is not one of the bins'.format(bin)
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raise ValueError(msg)
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return index
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def get_value(self, score, filters, filter_bins, nuclide=None, value='mean'):
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"""Returns a tally score value given a list of filters to satisfy.
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"""Returns the index in the Tally's results array for a score bin
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Parameters
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----------
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score : str
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The score string of interest
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filters : list
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A list of the filters of interest
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filter_bins : list
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A list of the filter bins of interest. These are integers for
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material, surface, cell, cellborn, distribcell, universe filters,
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and floats for energy or energyout filters. The bins are tuples
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of three integers (x,y,z) for mesh filters. The order of the bins
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in the list is assumed to correspond to the order of the filters.
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nuclide : Nuclide
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The Nuclide of interest
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value : str
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A string for the type of value to return ('mean' (default), 'std_dev',
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'sum', or 'sum_sq' are accepted)
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The score string (e.g., 'absorption', 'nu-fission')
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"""
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# Determine the score index from the score string
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score_index = self.scores.index(score)
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try:
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||||
score_index = self.scores.index(score)
|
||||
|
||||
# Determine the nuclide index from the nuclide string/object
|
||||
if not nuclide is None:
|
||||
nuclide_index = self.nuclides.index(nuclide)
|
||||
except ValueError:
|
||||
msg = 'Unable to get the score index for Tally since "{0}" ' \
|
||||
'is not one of the scores'.format(score)
|
||||
raise ValueError(msg)
|
||||
|
||||
return score_index
|
||||
|
||||
|
||||
def get_values(self, scores=[], filters=[], filter_bins=[],
|
||||
nuclides=[], value='mean'):
|
||||
"""Returns a tally score value given a list of filters to satisfy.
|
||||
|
||||
This routine constructs a 3D NumPy array for the requested Tally data
|
||||
indexed by filter bin, nuclide bin, and score index. The routine will
|
||||
order the data in the array
|
||||
|
||||
Parameters
|
||||
----------
|
||||
scores : list
|
||||
A list of one or more score strings
|
||||
(e.g., ['absorption', 'nu-fission']; default is [])
|
||||
|
||||
filters : list
|
||||
A list of filter type strings
|
||||
(e.g., ['mesh', 'energy']; default is [])
|
||||
|
||||
filter_bins : list
|
||||
A list of the filter bins corresponding to the filter_types
|
||||
parameter (e.g., [1, (0., 0.625e-6)]; default is []). Each bin
|
||||
in the list is the integer ID for 'material', 'surface', 'cell',
|
||||
'cellborn', and 'universe' Filters. Each bin is an integer for
|
||||
the cell instance ID for 'distribcell Filters. Each bin is
|
||||
a 2-tuple of floats for 'energy' and 'energyout' filters
|
||||
corresponding to the energy boundaries of the bin of interest.
|
||||
The bin is a (x,y,z) 3-tuple for 'mesh' filters corresponding
|
||||
to the mesh cell of interest. The order of the bins in the list
|
||||
must correspond of the filter_types parameter.
|
||||
|
||||
nuclides : list
|
||||
A list of nuclide name strings
|
||||
(e.g., ['U-235', 'U-238']; default is [])
|
||||
|
||||
value : str
|
||||
A string for the type of value to return - 'mean' (default),
|
||||
'std_dev', 'rel_err', 'sum', or 'sum_sq' are accepted
|
||||
"""
|
||||
|
||||
# Compute batch statistics if not yet computed
|
||||
self.compute_std_dev()
|
||||
|
||||
############################ FILTERS #########################
|
||||
# Determine the score indices from any of the requested scores
|
||||
if filters:
|
||||
|
||||
# Initialize empty list of indices for each bin in each Filter
|
||||
filter_indices = []
|
||||
|
||||
# Loop over all of the Tally's Filters
|
||||
for i, filter in enumerate(self.filters):
|
||||
|
||||
# Initialize empty list of indices for this Filter's bins
|
||||
filter_indices.append([])
|
||||
|
||||
user_filter = False
|
||||
|
||||
# If a user-requested Filter, get the user-requested bins
|
||||
for j, test_filter in enumerate(filters):
|
||||
if filter.type == test_filter:
|
||||
bins = filter_bins[j]
|
||||
user_filter = True
|
||||
break
|
||||
|
||||
# If not a user-requested Filter, get all bins
|
||||
if not user_filter:
|
||||
|
||||
# Create list of 2- or 3-tuples tuples for mesh cell bins
|
||||
if filter.type == 'mesh':
|
||||
dimension = filter.mesh.dimension
|
||||
xyz = map(lambda x: np.arange(1,x+1), dimension)
|
||||
bins = list(itertools.product(*xyz))
|
||||
|
||||
# Create list of 2-tuples for energy boundary bins
|
||||
elif filter.type in ['energy', 'energyout']:
|
||||
bins = []
|
||||
for i in range(filter.num_bins):
|
||||
bins.append((filter.bins[i], filter.bins[i+1]))
|
||||
|
||||
# Create list of IDs for bins for all other Filter types
|
||||
else:
|
||||
bins = filter.bins
|
||||
|
||||
# Add indices for each bin in this Filter to the list
|
||||
for bin in bins:
|
||||
filter_indices[i].append(
|
||||
self.get_filter_index(filter.type, bin))
|
||||
|
||||
# Apply cross-product sum between all filter bin indices
|
||||
filter_indices = map(sum, itertools.product(*filter_indices))
|
||||
|
||||
# If user did not specify any specific Filters, use them all
|
||||
else:
|
||||
nuclide_index = 0
|
||||
filter_indices = np.arange(self.num_filter_bins)
|
||||
|
||||
# Initialize index for Filter in Tally.results[:,:,:]
|
||||
filter_index = 0
|
||||
############################ NUCLIDES ########################
|
||||
# Determine the score indices from any of the requested scores
|
||||
if nuclides:
|
||||
nuclide_indices = np.zeros(len(nuclides), dtype=np.int)
|
||||
for i, nuclide in enumerate(nuclides):
|
||||
nuclide_indices[i] = self.get_nuclide_index(nuclide)
|
||||
|
||||
# Iterate over specified Filters to compute filter index
|
||||
for i, filter in enumerate(filters):
|
||||
# If user did not specify any specific Nuclides, use them all
|
||||
else:
|
||||
nuclide_indices = np.arange(self.num_nuclides)
|
||||
|
||||
# Find the equivalent Filter in this Tally's list of Filters
|
||||
test_filter = self.find_filter(filter.type, filter.bins)
|
||||
############################# SCORES #########################
|
||||
# Determine the score indices from any of the requested scores
|
||||
if scores:
|
||||
score_indices = np.zeros(len(scores), dtype=np.int)
|
||||
for i, score in enumerate(scores):
|
||||
score_indices[i] = self.get_score_index(score)
|
||||
|
||||
# Filter bins for a mesh are an (x,y,z) tuple
|
||||
if filter.type == 'mesh':
|
||||
# If user did not specify any specific scores, use them all
|
||||
else:
|
||||
score_indices = np.arange(self.num_scores)
|
||||
|
||||
# Get the dimensions of the corresponding mesh
|
||||
nx, ny, nz = test_filter.mesh.dimension
|
||||
|
||||
# Convert (x,y,z) to a single bin -- this is similar to
|
||||
# subroutine mesh_indices_to_bin in openmc/src/mesh.F90.
|
||||
val = ((filter_bins[i][0] - 1) * ny * nz +
|
||||
(filter_bins[i][1] - 1) * nz +
|
||||
(filter_bins[i][2] - 1))
|
||||
filter_index += val * test_filter.stride
|
||||
|
||||
# Filter bins for distribcell are the "IDs" of each unique placement
|
||||
# of the Cell in the Geometry (integers starting at 0)
|
||||
elif filter.type == 'distribcell':
|
||||
bin = filter_bins[i]
|
||||
filter_index += bin * test_filter.stride
|
||||
|
||||
else:
|
||||
bin = filter_bins[i]
|
||||
bin_index = test_filter.get_bin_index(bin)
|
||||
filter_index += bin_index * test_filter.stride
|
||||
# Construct cross-product of all three index types with each other
|
||||
indices = np.ix_(filter_indices, nuclide_indices, score_indices)
|
||||
|
||||
# Return the desired result from Tally
|
||||
if value == 'mean':
|
||||
return self.mean[filter_index, nuclide_index, score_index]
|
||||
data = self.mean[indices]
|
||||
elif value == 'std_dev':
|
||||
return self.std_dev[filter_index, nuclide_index, score_index]
|
||||
data = self.std_dev[indices]
|
||||
elif value == 'rel_err':
|
||||
data = self.std_dev[indices] / self.mean[indices]
|
||||
elif value == 'sum':
|
||||
return self.sum[filter_index, nuclide_index, score_index]
|
||||
data = self.sum[indices]
|
||||
elif value == 'sum_sq':
|
||||
return self.sum_sq[filter_index, nuclide_index, score_index]
|
||||
data = self.sum_sq[indices]
|
||||
else:
|
||||
msg = 'Unable to return results from Tally ID={0} for score {1} ' \
|
||||
'since the value {2} is not \'mean\', \'std_dev\', ' \
|
||||
'\'sum\', or \'sum_sq\''.format(self.id, score, value)
|
||||
msg = 'Unable to return results from Tally ID={0} since the ' \
|
||||
'the requested value "{1}" is not \'mean\', \'std_dev\', ' \
|
||||
'\rel_err\', \'sum\', or \'sum_sq\''.format(self.id, value)
|
||||
raise LookupError(msg)
|
||||
|
||||
return data.squeeze()
|
||||
|
||||
|
||||
def get_pandas_dataframe(self, filters=True, nuclides=True,
|
||||
scores=True, summary=None):
|
||||
|
|
@ -1004,19 +1118,19 @@ class Tally(object):
|
|||
|
||||
if not is_string(filename):
|
||||
msg = 'Unable to export the results for Tally ID={0} to ' \
|
||||
'filename={1} since it is not a ' \
|
||||
'filename="{1}" since it is not a ' \
|
||||
'string'.format(self.id, filename)
|
||||
raise ValueError(msg)
|
||||
|
||||
elif not is_string(directory):
|
||||
msg = 'Unable to export the results for Tally ID={0} to ' \
|
||||
'directory={1} since it is not a ' \
|
||||
'directory="{1}" since it is not a ' \
|
||||
'string'.format(self.id, directory)
|
||||
raise ValueError(msg)
|
||||
|
||||
elif not format in ['hdf5', 'pkl', 'csv']:
|
||||
msg = 'Unable to export the results for Tally ID={0} to ' \
|
||||
'format {1} since it is not supported'.format(self.id, format)
|
||||
msg = 'Unable to export the results for Tally ID={0} to format ' \
|
||||
'"{1}" since it is not supported'.format(self.id, format)
|
||||
raise ValueError(msg)
|
||||
|
||||
elif not isinstance(append, (bool, np.bool)):
|
||||
|
|
|
|||
|
|
@ -57,7 +57,7 @@ class Trigger(object):
|
|||
|
||||
if not trigger_type in ['variance', 'std_dev', 'rel_err']:
|
||||
msg = 'Unable to create a tally trigger with ' \
|
||||
'type {0}'.format(trigger_type)
|
||||
'type "{0}"'.format(trigger_type)
|
||||
raise ValueError(msg)
|
||||
|
||||
self._trigger_type = trigger_type
|
||||
|
|
@ -68,7 +68,7 @@ class Trigger(object):
|
|||
|
||||
if not is_float(threshold):
|
||||
msg = 'Unable to set a tally trigger threshold with ' \
|
||||
'threshold {0}'.format(threshold)
|
||||
'threshold "{0}"'.format(threshold)
|
||||
raise ValueError(msg)
|
||||
|
||||
self._threshold = threshold
|
||||
|
|
@ -77,7 +77,7 @@ class Trigger(object):
|
|||
def add_score(self, score):
|
||||
|
||||
if not is_string(score):
|
||||
msg = 'Unable to add score {0} to tally trigger since ' \
|
||||
msg = 'Unable to add score "{0}" to tally trigger since ' \
|
||||
'it is not a string'.format(score)
|
||||
raise ValueError(msg)
|
||||
|
||||
|
|
|
|||
|
|
@ -18,15 +18,15 @@ else:
|
|||
sp.read_results()
|
||||
|
||||
# extract tally results and convert to vector
|
||||
tally1 = sp.get_tally('flux', [openmc.Filter('mesh', [1])], \
|
||||
[-1], estimator='tracklength')
|
||||
tally2 = sp.get_tally('flux', [openmc.Filter('mesh', [2])], \
|
||||
[-1], estimator='analog')
|
||||
tally3 = sp.get_tally('nu-fission', [openmc.Filter('mesh', [2])], \
|
||||
[-1], estimator='analog')
|
||||
tally4 = sp.get_tally('current', [openmc.Filter('mesh', [2]), \
|
||||
tally1 = sp.get_tally(scores=['flux'], filters=[openmc.Filter('mesh', [1])], \
|
||||
estimator='tracklength')
|
||||
tally2 = sp.get_tally(scores=['flux'], filters=[openmc.Filter('mesh', [2])], \
|
||||
estimator='analog')
|
||||
tally3 = sp.get_tally(scores=['nu-fission'], \
|
||||
filters=[openmc.Filter('mesh', [2])], estimator='analog')
|
||||
tally4 = sp.get_tally(scores=['current'], filters=[openmc.Filter('mesh', [2]), \
|
||||
openmc.Filter('surface', [1,2,3,4,5,6])], \
|
||||
[-1], estimator='analog')
|
||||
estimator='analog')
|
||||
|
||||
results1 = np.zeros((tally1.sum.size + tally1.sum.size, ))
|
||||
results1[0::2] = tally1.sum.ravel()
|
||||
|
|
|
|||
|
|
@ -18,15 +18,15 @@ else:
|
|||
sp.read_results()
|
||||
|
||||
# extract tally results and convert to vector
|
||||
tally1 = sp.get_tally('flux', [openmc.Filter('mesh', [1])], \
|
||||
[-1], estimator='tracklength')
|
||||
tally2 = sp.get_tally('flux', [openmc.Filter('mesh', [2])], \
|
||||
[-1], estimator='analog')
|
||||
tally3 = sp.get_tally('nu-fission', [openmc.Filter('mesh', [2])], \
|
||||
[-1], estimator='analog')
|
||||
tally4 = sp.get_tally('current', [openmc.Filter('mesh', [2]), \
|
||||
tally1 = sp.get_tally(scores=['flux'], filters=[openmc.Filter('mesh', [1])], \
|
||||
estimator='tracklength')
|
||||
tally2 = sp.get_tally(scores=['flux'], filters=[openmc.Filter('mesh', [2])], \
|
||||
estimator='analog')
|
||||
tally3 = sp.get_tally(scores=['nu-fission'], \
|
||||
filters=[openmc.Filter('mesh', [2])], estimator='analog')
|
||||
tally4 = sp.get_tally(scores=['current'], filters=[openmc.Filter('mesh', [2]), \
|
||||
openmc.Filter('surface', [1,2,3,4,5,6])], \
|
||||
[-1], estimator='analog')
|
||||
estimator='analog')
|
||||
|
||||
results1 = np.zeros((tally1.sum.size + tally1.sum.size, ))
|
||||
results1[0::2] = tally1.sum.ravel()
|
||||
|
|
|
|||
|
|
@ -21,89 +21,77 @@ sp3.compute_stdev()
|
|||
|
||||
# analyze sp1
|
||||
# compare distrib sum to cell
|
||||
sp1_t1 = sp1._tallies[1]
|
||||
sp1_t2 = sp1._tallies[2]
|
||||
sp1_t1 = sp1.tallies[1]
|
||||
sp1_t2 = sp1.tallies[2]
|
||||
|
||||
distribcell_filter = sp1_t1.find_filter(filter_type='distribcell', bins=[2])
|
||||
sp1_t1_d1 = sp1_t1.get_value(score='total', filters=[distribcell_filter],
|
||||
filter_bins=[0], value='mean')
|
||||
sp1_t1_d2 = sp1_t1.get_value(score='total', filters=[distribcell_filter],
|
||||
filter_bins=[1], value='mean')
|
||||
sp1_t1_d3 = sp1_t1.get_value(score='total', filters=[distribcell_filter],
|
||||
filter_bins=[2], value='mean')
|
||||
sp1_t1_d4 = sp1_t1.get_value(score='total', filters=[distribcell_filter],
|
||||
filter_bins=[3], value='mean')
|
||||
sp1_t1_d1 = sp1_t1.get_values(scores=['total'], filters=['distribcell'],
|
||||
filter_bins=[(0,)], value='mean')
|
||||
sp1_t1_d2 = sp1_t1.get_values(scores=['total'], filters=['distribcell'],
|
||||
filter_bins=[(1,)], value='mean')
|
||||
sp1_t1_d3 = sp1_t1.get_values(scores=['total'], filters=['distribcell'],
|
||||
filter_bins=[(2,)], value='mean')
|
||||
sp1_t1_d4 = sp1_t1.get_values(scores=['total'], filters=['distribcell'],
|
||||
filter_bins=[(3,)], value='mean')
|
||||
sp1_t1_sum = sp1_t1_d1 + sp1_t1_d2 + sp1_t1_d3 + sp1_t1_d4
|
||||
|
||||
cell_filter = sp1_t2.find_filter(filter_type='cell', bins=[2])
|
||||
sp1_t2_c201 = sp1_t2.get_value(score='total', filters=[cell_filter],
|
||||
filter_bins=[2], value='mean')
|
||||
cell_filter = sp1_t2.find_filter(filter_type='cell')
|
||||
sp1_t2_c201 = sp1_t2.get_values(scores=['total'], value='mean')
|
||||
|
||||
|
||||
# analyze sp2
|
||||
sp2_t1 = sp2._tallies[1]
|
||||
cell_filter = sp2_t1.find_filter(filter_type='cell', bins=[2,4,6,8])
|
||||
sp2_t1_c201 = sp2_t1.get_value(score='total', filters=[cell_filter],
|
||||
filter_bins=[2], value='mean')
|
||||
sp2_t1_c203 = sp2_t1.get_value(score='total', filters=[cell_filter],
|
||||
filter_bins=[4], value='mean')
|
||||
sp2_t1_c205 = sp2_t1.get_value(score='total', filters=[cell_filter],
|
||||
filter_bins=[6], value='mean')
|
||||
sp2_t1_c207 = sp2_t1.get_value(score='total', filters=[cell_filter],
|
||||
filter_bins=[8], value='mean')
|
||||
sp2_t1 = sp2.tallies[1]
|
||||
sp2_t1_c201 = sp2_t1.get_values(scores=['total'], filters=['cell'],
|
||||
filter_bins=[(2,)], value='mean')
|
||||
sp2_t1_c203 = sp2_t1.get_values(scores=['total'], filters=['cell'],
|
||||
filter_bins=[(4,)], value='mean')
|
||||
sp2_t1_c205 = sp2_t1.get_values(scores=['total'], filters=['cell'],
|
||||
filter_bins=[(6,)], value='mean')
|
||||
sp2_t1_c207 = sp2_t1.get_values(scores=['total'], filters=['cell'],
|
||||
filter_bins=[(8,)], value='mean')
|
||||
|
||||
|
||||
# analyze sp3
|
||||
sp3_t1 = sp3._tallies[1]
|
||||
sp3_t2 = sp3._tallies[2]
|
||||
sp3_t3 = sp3._tallies[3]
|
||||
sp3_t4 = sp3._tallies[4]
|
||||
sp3_t5 = sp3._tallies[5]
|
||||
sp3_t6 = sp3._tallies[6]
|
||||
sp3_t1 = sp3.tallies[1]
|
||||
sp3_t2 = sp3.tallies[2]
|
||||
sp3_t3 = sp3.tallies[3]
|
||||
sp3_t4 = sp3.tallies[4]
|
||||
sp3_t5 = sp3.tallies[5]
|
||||
sp3_t6 = sp3.tallies[6]
|
||||
|
||||
cell_filter = sp3_t1.find_filter(filter_type='cell', bins=[1])
|
||||
distribcell_filter = sp3_t2.find_filter(filter_type='distribcell', bins=[1])
|
||||
sp3_t1_c1 = sp3_t1.get_value(score='total', filters=[cell_filter],
|
||||
filter_bins=[1], value='mean')
|
||||
sp3_t2_d1 = sp3_t2.get_value(score='total', filters=[distribcell_filter],
|
||||
filter_bins=[0], value='mean')
|
||||
sp3_t1_c1 = sp3_t1.get_values(scores=['total'], filters=['cell'],
|
||||
filter_bins=[(1,)], value='mean')
|
||||
sp3_t2_d1 = sp3_t2.get_values(scores=['total'], filters=['distribcell'],
|
||||
filter_bins=[(0,)], value='mean')
|
||||
|
||||
cell_filter = sp3_t3.find_filter(filter_type='cell', bins=[26])
|
||||
distribcell_filter = sp3_t4.find_filter(filter_type='distribcell', bins=[26])
|
||||
sp3_t3_c60 = sp3_t3.get_value(score='total', filters=[cell_filter],
|
||||
filter_bins=[26], value='mean')
|
||||
sp3_t3_c60 = sp3_t3.get_values(scores=['total'], filters=['cell'],
|
||||
filter_bins=[(26,)], value='mean')
|
||||
sp3_t4_d = 0
|
||||
for i in range(241):
|
||||
sp3_t4_d += sp3_t4.get_value(score='total', filters=[distribcell_filter],
|
||||
filter_bins=[i], value='mean')
|
||||
sp3_t4_d += sp3_t4.get_values(scores=['total'], filters=['distribcell'],
|
||||
filter_bins=[(i,)], value='mean')
|
||||
|
||||
cell_filter = sp3_t5.find_filter(filter_type='cell', bins=[19])
|
||||
distribcell_filter = sp3_t6.find_filter(filter_type='distribcell', bins=[19])
|
||||
sp3_t5_c27 = sp3_t5.get_value(score='total', filters=[cell_filter],
|
||||
filter_bins=[19], value='mean')
|
||||
sp3_t6_d = 0
|
||||
for i in range(63624):
|
||||
sp3_t6_d += sp3_t6.get_value(score='total', filters=[distribcell_filter],
|
||||
filter_bins=[i], value='mean')
|
||||
sp3_t5_c27 = sp3_t5.get_values(scores=['total'], filters=['cell'],
|
||||
filter_bins=[(19,)], value='mean')
|
||||
sp3_t6_d = sum(sp3_t6.get_values(scores=['total'], value='mean'))
|
||||
|
||||
# set up output string
|
||||
outstr = ''
|
||||
|
||||
outstr += "{0:12.6E}\n".format(sp1_t1_sum)
|
||||
outstr += "{0:12.6E}\n".format(sp1_t2_c201)
|
||||
outstr += "{0:12.6E}\n".format(sp2_t1_c201)
|
||||
outstr += "{0:12.6E}\n".format(sp1_t1_d4)
|
||||
outstr += "{0:12.6E}\n".format(sp2_t1_c203)
|
||||
outstr += "{0:12.6E}\n".format(sp1_t1_d1)
|
||||
outstr += "{0:12.6E}\n".format(sp2_t1_c205)
|
||||
outstr += "{0:12.6E}\n".format(sp1_t1_d3)
|
||||
outstr += "{0:12.6E}\n".format(sp2_t1_c207)
|
||||
outstr += "{0:12.6E}\n".format(sp1_t1_d2)
|
||||
outstr += "{0:12.6E}\n".format(sp3_t1_c1)
|
||||
outstr += "{0:12.6E}\n".format(sp3_t2_d1)
|
||||
outstr += "{0:12.6E}\n".format(sp3_t3_c60)
|
||||
outstr += "{0:12.6E}\n".format(sp3_t4_d)
|
||||
outstr += "{0:12.6E}\n".format(sp3_t5_c27)
|
||||
outstr += "{0:12.6E}\n".format(sp1_t2_c201[()])
|
||||
outstr += "{0:12.6E}\n".format(sp2_t1_c201[()])
|
||||
outstr += "{0:12.6E}\n".format(sp1_t1_d4[()])
|
||||
outstr += "{0:12.6E}\n".format(sp2_t1_c203[()])
|
||||
outstr += "{0:12.6E}\n".format(sp1_t1_d1[()])
|
||||
outstr += "{0:12.6E}\n".format(sp2_t1_c205[()])
|
||||
outstr += "{0:12.6E}\n".format(sp1_t1_d3[()])
|
||||
outstr += "{0:12.6E}\n".format(sp2_t1_c207[()])
|
||||
outstr += "{0:12.6E}\n".format(sp1_t1_d2[()])
|
||||
outstr += "{0:12.6E}\n".format(sp3_t1_c1[()])
|
||||
outstr += "{0:12.6E}\n".format(sp3_t2_d1[()])
|
||||
outstr += "{0:12.6E}\n".format(sp3_t3_c60[()])
|
||||
outstr += "{0:12.6E}\n".format(sp3_t4_d[()])
|
||||
outstr += "{0:12.6E}\n".format(sp3_t5_c27[()])
|
||||
outstr += "{0:12.6E}\n".format(sp3_t6_d)
|
||||
|
||||
# write results to file
|
||||
|
|
|
|||
Loading…
Add table
Add a link
Reference in a new issue