Fixed bug when getting Pandas DataFrame from distribcell tally with 2D Lattice

openmc/opencg_compatible.py

@@ -901,7 +901,9 @@ def get_opencg_lattice(openmc_lattice):
 
     # Convert 2D universes array to 3D for OpenCG
     if len(universes.shape) == 2:
-        universes.shape = (1,) + universes.shape
+        new_universes = universes.copy()
+        new_universes.shape = (1,) + universes.shape
+        universes = new_universes
 
     # Initialize an empty array for the OpenCG nested Universes in this Lattice
     universe_array = np.ndarray(tuple(np.array(dimension)[::-1]),

openmc/statepoint.py

@@ -75,6 +75,9 @@ class StatePoint(object):
         energy of the source site.
     source_present : bool
         Indicate whether source sites are present
+    sparse : bool
+        Whether or not the tallies uses SciPy's LIL sparse matrix format for
+        compressed data storage
     tallies : dict
         Dictionary whose keys are tally IDs and whose values are Tally objects
     tallies_present : bool
@@ -110,6 +113,7 @@ class StatePoint(object):
         self._tallies_read = False
         self._summary = False
         self._global_tallies = None
+        self._sparse = False
 
     def close(self):
         self._f.close()
@@ -318,6 +322,10 @@ class StatePoint(object):
     def source_present(self):
         return self._f['source_present'].value > 0
 
+    @property
+    def sparse(self):
+        return self._sparse
+
     @property
     def tallies(self):
         if not self._tallies_read:
@@ -340,7 +348,8 @@ class StatePoint(object):
             for tally_key in tally_keys:
 
                 # Read the Tally size specifications
-                n_realizations = self._f['{0}{1}/n_realizations'.format(base, tally_key)].value
+                n_realizations = \
+                    self._f['{0}{1}/n_realizations'.format(base, tally_key)].value
 
                 # Create Tally object and assign basic properties
                 tally = openmc.Tally(tally_id=tally_key)
@@ -350,7 +359,8 @@ class StatePoint(object):
                 tally.num_realizations = n_realizations
 
                 # Read the number of Filters
-                n_filters = self._f['{0}{1}/n_filters'.format(base, tally_key)].value
+                n_filters = \
+                    self._f['{0}{1}/n_filters'.format(base, tally_key)].value
 
                 subbase = '{0}{1}/filter '.format(base, tally_key)
 
@@ -358,7 +368,8 @@ class StatePoint(object):
                 for j in range(1, n_filters+1):
 
                     # Read the Filter type
-                    filter_type = self._f['{0}{1}/type'.format(subbase, j)].value.decode()
+                    filter_type = \
+                        self._f['{0}{1}/type'.format(subbase, j)].value.decode()
 
                     n_bins = self._f['{0}{1}/n_bins'.format(subbase, j)].value
 
@@ -380,7 +391,8 @@ class StatePoint(object):
                     tally.add_filter(filter)
 
                 # Read Nuclide bins
-                nuclide_names = self._f['{0}{1}/nuclides'.format(base, tally_key)].value
+                nuclide_names = \
+                    self._f['{0}{1}/nuclides'.format(base, tally_key)].value
 
                 # Add all Nuclides to the Tally
                 for name in nuclide_names:
@@ -415,6 +427,7 @@ class StatePoint(object):
                     tally.add_score(score)
 
                 # Add Tally to the global dictionary of all Tallies
+                tally.sparse = self.sparse
                 self._tallies[tally_key] = tally
 
             self._tallies_read = True
@@ -439,6 +452,26 @@ class StatePoint(object):
     def with_summary(self):
         return False if self.summary is None else True
 
+    @sparse.setter
+    def sparse(self, sparse):
+        """Convert tally data from NumPy arrays to SciPy list of lists (LIL)
+        sparse matrices, and vice versa.
+
+        This property may be used to reduce the amount of data in memory during
+        tally data processing. The tally data will be stored as SciPy LIL
+        matrices internally within each Tally object. All tally data access
+        properties and methods will return data as a dense NumPy array.
+
+        """
+
+        cv.check_type('sparse', sparse, bool)
+        self._sparse = sparse
+
+        # Update tally sparsities
+        if self._tallies_read:
+            for tally_id in self.tallies:
+                self.tallies[tally_id].sparse = self.sparse
+
     def get_tally(self, scores=[], filters=[], nuclides=[],
                   name=None, id=None, estimator=None):
         """Finds and returns a Tally object with certain properties.

openmc/universe.py

@@ -1081,7 +1081,7 @@ class RectLattice(Lattice):
         # For 2D Lattices
         if len(self._dimension) == 2:
             offset = self._offsets[i[1]-1, i[2]-1, 0, distribcell_index-1]
-            offset += self._universes[i[1]][i[2]].get_cell_instance(path,
+            offset += self._universes[i[1]-1][i[2]-1].get_cell_instance(path,
                                                               distribcell_index)
 
         # For 3D Lattices