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https://github.com/openmc-dev/openmc.git
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Added new tally slice and merge test
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wbinventor@gmail.com
parent
bbbb115196
commit
23353fa097
4 changed files with 216 additions and 1 deletions
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@ -797,7 +797,7 @@ class AggregateFilter(object):
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@bins.setter
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def bins(self, bins):
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cv.check_iterable_type('bins', bins, Iterable)
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self._bins = map(tuple, bins)
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self._bins = list(map(tuple, bins))
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@aggregate_op.setter
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def aggregate_op(self, aggregate_op):
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1
tests/test_tally_slice_merge/inputs_true.dat
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1
tests/test_tally_slice_merge/inputs_true.dat
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@ -0,0 +1 @@
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8d1ab9e4add51b99045e990ac9c3dad9447e9720d811bc430d4bfdd7c2c035424bcb7750e4a4d0ec0460ea1ef4be46ac58372ed01d55f5d8cfeebbce75559066
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49
tests/test_tally_slice_merge/results_true.dat
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49
tests/test_tally_slice_merge/results_true.dat
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@ -0,0 +1,49 @@
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energy [MeV] cell nuclide score mean std. dev.
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0 (0.0e+00 - 6.3e-07) 21 U-235 fission 0.098638 0.009195 energy [MeV] cell nuclide score mean std. dev.
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0 (0.0e+00 - 6.3e-07) 21 U-235 nu-fission 0.240351 0.022405 energy [MeV] cell nuclide score mean std. dev.
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0 (0.0e+00 - 6.3e-07) 21 U-238 fission 1.371663e-07 1.284884e-08 energy [MeV] cell nuclide score mean std. dev.
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0 (0.0e+00 - 6.3e-07) 21 U-238 nu-fission 3.418304e-07 3.202044e-08 energy [MeV] cell nuclide score mean std. dev.
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0 (6.3e-07 - 2.0e+01) 21 U-235 fission 0.027879 0.000602 energy [MeV] cell nuclide score mean std. dev.
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0 (6.3e-07 - 2.0e+01) 21 U-235 nu-fission 0.068241 0.001458 energy [MeV] cell nuclide score mean std. dev.
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0 (6.3e-07 - 2.0e+01) 21 U-238 fission 0.016638 0.001146 energy [MeV] cell nuclide score mean std. dev.
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0 (6.3e-07 - 2.0e+01) 21 U-238 nu-fission 0.045776 0.003342 energy [MeV] cell nuclide score mean std. dev.
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0 (0.0e+00 - 6.3e-07) 27 U-235 fission 0.057752 0.004818 energy [MeV] cell nuclide score mean std. dev.
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0 (0.0e+00 - 6.3e-07) 27 U-235 nu-fission 0.140724 0.011739 energy [MeV] cell nuclide score mean std. dev.
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0 (0.0e+00 - 6.3e-07) 27 U-238 fission 8.177167e-08 7.061683e-09 energy [MeV] cell nuclide score mean std. dev.
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0 (0.0e+00 - 6.3e-07) 27 U-238 nu-fission 2.037822e-07 1.759834e-08 energy [MeV] cell nuclide score mean std. dev.
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0 (6.3e-07 - 2.0e+01) 27 U-235 fission 0.01763 0.001937 energy [MeV] cell nuclide score mean std. dev.
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0 (6.3e-07 - 2.0e+01) 27 U-235 nu-fission 0.04314 0.004737 energy [MeV] cell nuclide score mean std. dev.
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0 (6.3e-07 - 2.0e+01) 27 U-238 fission 0.009883 0.001934 energy [MeV] cell nuclide score mean std. dev.
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0 (6.3e-07 - 2.0e+01) 27 U-238 nu-fission 0.027068 0.005207 energy [MeV] cell nuclide score mean std. dev.
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0 (0.0e+00 - 6.3e-07) 21 U-235 fission 9.863775e-02 9.194846e-03
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1 (0.0e+00 - 6.3e-07) 21 U-235 nu-fission 2.403506e-01 2.240508e-02
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2 (0.0e+00 - 6.3e-07) 21 U-238 fission 1.371663e-07 1.284884e-08
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3 (0.0e+00 - 6.3e-07) 21 U-238 nu-fission 3.418304e-07 3.202044e-08
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4 (0.0e+00 - 6.3e-07) 27 U-235 fission 5.775195e-02 4.817512e-03
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5 (0.0e+00 - 6.3e-07) 27 U-235 nu-fission 1.407242e-01 1.173883e-02
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6 (0.0e+00 - 6.3e-07) 27 U-238 fission 8.177167e-08 7.061683e-09
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7 (0.0e+00 - 6.3e-07) 27 U-238 nu-fission 2.037822e-07 1.759834e-08
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8 (6.3e-07 - 2.0e+01) 21 U-235 fission 2.787911e-02 6.020399e-04
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9 (6.3e-07 - 2.0e+01) 21 U-235 nu-fission 6.824140e-02 1.457590e-03
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10 (6.3e-07 - 2.0e+01) 21 U-238 fission 1.663756e-02 1.145703e-03
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11 (6.3e-07 - 2.0e+01) 21 U-238 nu-fission 4.577562e-02 3.342394e-03
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12 (6.3e-07 - 2.0e+01) 27 U-235 fission 1.763014e-02 1.937151e-03
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13 (6.3e-07 - 2.0e+01) 27 U-235 nu-fission 4.313951e-02 4.737423e-03
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14 (6.3e-07 - 2.0e+01) 27 U-238 fission 9.883451e-03 1.933519e-03
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15 (6.3e-07 - 2.0e+01) 27 U-238 nu-fission 2.706776e-02 5.206818e-03 sum(distribcell) energy [MeV] nuclide score mean std. dev.
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0 (0, 100, 2000, 30000) (0.0e+00 - 6.3e-07) U-235 fission 0 0
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1 (0, 100, 2000, 30000) (0.0e+00 - 6.3e-07) U-235 nu-fission 0 0
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2 (0, 100, 2000, 30000) (0.0e+00 - 6.3e-07) U-238 fission 0 0
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3 (0, 100, 2000, 30000) (0.0e+00 - 6.3e-07) U-238 nu-fission 0 0
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4 (0, 100, 2000, 30000) (6.3e-07 - 2.0e+01) U-235 fission 0 0
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5 (0, 100, 2000, 30000) (6.3e-07 - 2.0e+01) U-235 nu-fission 0 0
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6 (0, 100, 2000, 30000) (6.3e-07 - 2.0e+01) U-238 fission 0 0
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7 (0, 100, 2000, 30000) (6.3e-07 - 2.0e+01) U-238 nu-fission 0 0
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8 (500, 5000, 50000) (0.0e+00 - 6.3e-07) U-235 fission 0 0
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9 (500, 5000, 50000) (0.0e+00 - 6.3e-07) U-235 nu-fission 0 0
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10 (500, 5000, 50000) (0.0e+00 - 6.3e-07) U-238 fission 0 0
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11 (500, 5000, 50000) (0.0e+00 - 6.3e-07) U-238 nu-fission 0 0
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12 (500, 5000, 50000) (6.3e-07 - 2.0e+01) U-235 fission 0 0
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13 (500, 5000, 50000) (6.3e-07 - 2.0e+01) U-235 nu-fission 0 0
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14 (500, 5000, 50000) (6.3e-07 - 2.0e+01) U-238 fission 0 0
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15 (500, 5000, 50000) (6.3e-07 - 2.0e+01) U-238 nu-fission 0 0
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165
tests/test_tally_slice_merge/test_tally_slice_merge.py
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165
tests/test_tally_slice_merge/test_tally_slice_merge.py
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@ -0,0 +1,165 @@
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#!/usr/bin/env python
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import os
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import sys
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import glob
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import hashlib
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import itertools
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sys.path.insert(0, os.pardir)
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from testing_harness import PyAPITestHarness
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import openmc
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class TallySliceMergeTestHarness(PyAPITestHarness):
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def _build_inputs(self):
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# The summary.h5 file needs to be created to read in the tallies
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self._input_set.settings.output = {'summary': True}
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# Initialize the tallies file
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tallies_file = openmc.TalliesFile()
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# Define nuclides and scores to add to both tallies
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self.nuclides = ['U-235', 'U-238']
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self.scores = ['fission', 'nu-fission']
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# Define filters for energy and spatial domain
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low_energy = openmc.Filter(type='energy', bins=[0., 0.625e-6])
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high_energy = openmc.Filter(type='energy', bins=[0.625e-6, 20.])
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merged_energies = low_energy.merge(high_energy)
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cell_21 = openmc.Filter(type='cell', bins=[21])
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cell_27 = openmc.Filter(type='cell', bins=[27])
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distribcell_filter = openmc.Filter(type='distribcell', bins=[21])
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self.cell_filters = [cell_21, cell_27]
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self.energy_filters = [low_energy, high_energy]
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# Initialize cell tallies with filters, nuclides and scores
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tallies = []
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for cell_filter in self.energy_filters:
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for energy_filter in self.cell_filters:
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for nuclide in self.nuclides:
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for score in self.scores:
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tally = openmc.Tally()
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tally.estimator = 'tracklength'
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tally.add_score(score)
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tally.add_nuclide(nuclide)
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tally.add_filter(cell_filter)
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tally.add_filter(energy_filter)
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tallies.append(tally)
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# Merge all cell tallies together
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while len(tallies) != 1:
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halfway = int(len(tallies) / 2)
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zip_split = zip(tallies[:halfway], tallies[halfway:])
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tallies = list(map(lambda xy: xy[0].merge(xy[1]), zip_split))
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# Specify a name for the tally
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tallies[0].name = 'cell tally'
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# Initialize a distribcell tally
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distribcell_tally = openmc.Tally(name='distribcell tally')
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distribcell_tally.estimator = 'tracklength'
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distribcell_tally.add_filter(distribcell_filter)
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distribcell_tally.add_filter(merged_energies)
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for score in self.scores:
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distribcell_tally.add_score(score)
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for nuclide in self.nuclides:
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distribcell_tally.add_nuclide(nuclide)
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# Add tallies to a TalliesFile
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tallies_file = openmc.TalliesFile()
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tallies_file.add_tally(tallies[0])
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tallies_file.add_tally(distribcell_tally)
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# Export tallies to file
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self._input_set.tallies = tallies_file
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super(TallySliceMergeTestHarness, self)._build_inputs()
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def _get_results(self, hash_output=False):
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"""Digest info in the statepoint and return as a string."""
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# Read the statepoint file.
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statepoint = glob.glob(os.path.join(os.getcwd(), self._sp_name))[0]
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sp = openmc.StatePoint(statepoint)
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# Read the summary file.
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summary = glob.glob(os.path.join(os.getcwd(), 'summary.h5'))[0]
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su = openmc.Summary(summary)
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sp.link_with_summary(su)
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# Extract the cell tally
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tallies = [sp.get_tally(name='cell tally')]
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# Slice the tallies by cell filter bins
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cell_filter_prod = itertools.product(tallies, self.cell_filters)
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tallies = map(lambda tf: tf[0].get_slice(filters=[tf[1].type],
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filter_bins=[tf[1].get_bin(0)]), cell_filter_prod)
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# Slice the tallies by energy filter bins
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energy_filter_prod = itertools.product(tallies, self.energy_filters)
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tallies = map(lambda tf: tf[0].get_slice(filters=[tf[1].type],
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filter_bins=[(tf[1].get_bin(0),)]), energy_filter_prod)
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# Slice the tallies by nuclide
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nuclide_prod = itertools.product(tallies, self.nuclides)
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tallies = map(lambda tn: tn[0].get_slice(nuclides=[tn[1]]), nuclide_prod)
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# Slice the tallies by score
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score_prod = itertools.product(tallies, self.scores)
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tallies = map(lambda ts: ts[0].get_slice(scores=[ts[1]]), score_prod)
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# Initialize an output string
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outstr = ''
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# Append sliced Tally Pandas DataFrames to output string
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for tally in tallies:
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df = tally.get_pandas_dataframe()
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outstr += df.to_string()
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# Merge all tallies together
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while len(list(tallies)) != 1:
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tallies = list(tallies)
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halfway = int(len(tallies) / 2)
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zip_split = zip(tallies[:halfway], tallies[halfway:])
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tallies = map(lambda xy: xy[0].merge(xy[1]), zip_split)
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# Append merged Tally Pandas DataFrame to output string
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df = tallies[0].get_pandas_dataframe()
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outstr += df.to_string()
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# Extract the distribcell tally
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distribcell_tally = sp.get_tally(name='distribcell tally')
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# Sum up a few subdomains from the distribcell tally
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sum1 = distribcell_tally.summation(filter_type='distribcell',
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filter_bins=[0,100,2000,30000])
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# Sum up a few subdomains from the distribcell tally
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sum2 = distribcell_tally.summation(filter_type='distribcell',
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filter_bins=[500,5000,50000])
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# Merge the distribcell tally slices
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merge_tally = sum1.merge(sum2)
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# Append merged Tally Pandas DataFrame to output string
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df = merge_tally.get_pandas_dataframe()
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outstr += df.to_string()
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# Hash the results if necessary
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if hash_output:
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sha512 = hashlib.sha512()
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sha512.update(outstr.encode('utf-8'))
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outstr = sha512.hexdigest()
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return outstr
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def _cleanup(self):
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super(TallySliceMergeTestHarness, self)._cleanup()
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f = os.path.join(os.getcwd(), 'tallies.xml')
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if os.path.exists(f): os.remove(f)
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if __name__ == '__main__':
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harness = TallySliceMergeTestHarness('statepoint.10.h5', True)
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harness.main()
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