Added test for MGXS library subdomain-averaging across distribcells

openmc/aggregate.py

@@ -405,5 +405,5 @@ class AggregateFilter(object):
         aggregate_bin_array = np.repeat(aggregate_bin_array, datasize)
 
         # Construct Pandas DataFrame for the AggregateFilter
-        df = pd.DataFrame({self.aggregate_filter.type: aggregate_bin_array})
-        return df
+        df = pd.DataFrame({self.type: aggregate_bin_array})
+        return df

openmc/mgxs/mgxs.py

@@ -1219,7 +1219,7 @@ class MGXS(object):
             df = self.xs_tally.get_pandas_dataframe(summary=summary)
 
         # Remove the score column since it is homogeneous and redundant
-        if summary and self.domain_type == 'distribcell':
+        if summary and 'distribcell' in self.domain_type:
             df = df.drop('score', level=0, axis=1)
         else:
             df = df.drop('score', axis=1)

tests/test_mgxs_library_condense/test_mgxs_library_condense.py

@@ -63,8 +63,6 @@ class MGXSTestHarness(PyAPITestHarness):
                 df = mgxs.get_pandas_dataframe()
                 outstr += df.to_string()
 
-        print(outstr)
-
         # Hash the results if necessary
         if hash_output:
             sha512 = hashlib.sha512()

tests/test_mgxs_library_distribcell/inputs_true.dat

@@ -0,0 +1 @@
+224a9e84e87c8a21385326d34ef27c046107d4a2ace6ee85d7a36142a3726e12532e2fc1a318ab707437e0b306a81c6d2b80c531d4c3210d4162242e6265ba70

tests/test_mgxs_library_distribcell/results_true.dat

@@ -0,0 +1,5 @@
+                                    sum(distribcell)  group in nuclide      mean  std. dev.
+0  sum(0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, ...         1   total  0.720213   1.424323                                    sum(distribcell)  group in nuclide  mean  std. dev.
+0  sum(0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, ...         1   total     0          0                                    sum(distribcell)  group in  group out nuclide     mean  std. dev.
+0  sum(0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, ...         1          1   total  0.70466   1.403916                                    sum(distribcell)  group out nuclide  mean  std. dev.
+0  sum(0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, ...          1   total     0          0

tests/test_mgxs_library_distribcell/test_mgxs_library_distribcell.py

@@ -0,0 +1,85 @@
+#!/usr/bin/env python
+
+import os
+import sys
+import glob
+import hashlib
+sys.path.insert(0, os.pardir)
+from testing_harness import PyAPITestHarness
+import openmc
+import openmc.mgxs
+
+
+class MGXSTestHarness(PyAPITestHarness):
+    def _build_inputs(self):
+
+        # The openmc.mgxs module needs a summary.h5 file
+        self._input_set.settings.output = {'summary': True}
+
+        # Generate inputs using parent class routine
+        super(MGXSTestHarness, self)._build_inputs()
+
+        # Initialize a one-group structure
+        energy_groups = openmc.mgxs.EnergyGroups(group_edges=[0, 20.])
+
+        # Initialize MGXS Library for a few cross section types
+        # for one material-filled cell in the geometry
+        self.mgxs_lib = openmc.mgxs.Library(self._input_set.geometry.geometry)
+        self.mgxs_lib.by_nuclide = False
+        self.mgxs_lib.mgxs_types = ['transport', 'nu-fission',
+                                    'nu-scatter matrix', 'chi']
+        self.mgxs_lib.energy_groups = energy_groups
+        self.mgxs_lib.domain_type = 'distribcell'
+        material_cells = self.mgxs_lib.openmc_geometry.get_all_material_cells()
+        self.mgxs_lib.domains = [material_cells[-1]]
+        self.mgxs_lib.build_library()
+
+        # Initialize a tallies file
+        self._input_set.tallies = openmc.TalliesFile()
+        self.mgxs_lib.add_to_tallies_file(self._input_set.tallies, merge=False)
+        self._input_set.tallies.export_to_xml()
+
+    def _get_results(self, hash_output=False):
+        """Digest info in the statepoint and return as a string."""
+
+        # Read the statepoint file.
+        statepoint = glob.glob(os.path.join(os.getcwd(), self._sp_name))[0]
+        sp = openmc.StatePoint(statepoint)
+
+        # Read the summary file.
+        summary = glob.glob(os.path.join(os.getcwd(), 'summary.h5'))[0]
+        su = openmc.Summary(summary)
+        sp.link_with_summary(su)
+
+        # Load the MGXS library from the statepoint
+        self.mgxs_lib.load_from_statepoint(sp)
+
+        # Average the MGXS across distribcell subdomains
+        avg_lib = self.mgxs_lib.get_subdomain_avg_library()
+
+        # Build a string from Pandas Dataframe for each 1-group MGXS
+        outstr = ''
+        for domain in avg_lib.domains:
+            for mgxs_type in avg_lib.mgxs_types:
+                mgxs = avg_lib.get_mgxs(domain, mgxs_type)
+                df = mgxs.get_pandas_dataframe()
+                outstr += df.to_string()
+
+        # Hash the results if necessary
+        if hash_output:
+            sha512 = hashlib.sha512()
+            sha512.update(outstr.encode('utf-8'))
+            outstr = sha512.hexdigest()
+
+        return outstr
+
+
+    def _cleanup(self):
+        super(MGXSTestHarness, self)._cleanup()
+        f = os.path.join(os.getcwd(), 'tallies.xml')
+        if os.path.exists(f): os.remove(f)
+
+
+if __name__ == '__main__':
+    harness = MGXSTestHarness('statepoint.10.*', True)
+    harness.main()