Using a separate dictionary for interpolation values

include/openmc/interpolate.h

@@ -61,6 +61,9 @@ inline double interpolate(const std::vector<double>& xs,
 {
   int idx = lower_bound_index(xs.begin(), xs.end(), x);
 
+  if (idx == xs.size())
+    idx--;
+
   switch (i) {
   case Interpolation::lin_lin:
     return interpolate_lin_lin(xs[idx], xs[idx + 1], ys[idx], ys[idx + 1], x);

openmc/data/function.py

@@ -13,7 +13,7 @@ from openmc.mixin import EqualityMixin
 from .data import EV_PER_MEV
 
 INTERPOLATION_SCHEME = {1: 'histogram', 2: 'linear-linear', 3: 'linear-log',
-                        4: 'log-linear', 5: 'log-log', 6 : 'quadratic', 7 : 'cubic'}
+                        4: 'log-linear', 5: 'log-log'}
 
 
 def sum_functions(funcs):

openmc/filter.py

@@ -12,7 +12,6 @@ import pandas as pd
 import openmc
 import openmc.checkvalue as cv
 from .cell import Cell
-from .data.function import INTERPOLATION_SCHEME
 from .material import Material
 from .mixin import IDManagerMixin
 from .surface import Surface
@@ -1896,6 +1895,11 @@ class EnergyFunctionFilter(Filter):
 
     """
 
+    # keys selected to match those in function.py where possible
+    INTERPOLATION_SCHEMES = {2: 'linear-linear', 3: 'linear-log',
+                             4: 'log-linear', 5: 'log-log',
+                             6 : 'quadratic', 7 : 'cubic'}
+
     def __init__(self, energy, y, interpolation='linear-linear', filter_id=None):
         self.energy = energy
         self.y = y
@@ -1963,7 +1967,7 @@ class EnergyFunctionFilter(Filter):
         out = cls(energy, y, filter_id=filter_id)
         if 'interpolation' in group:
             out.interpolation =  \
-                openmc.data.INTERPOLATION_SCHEME[group['interpolation'][()]]
+                cls.INTERPOLATION_SCHEMES[group['interpolation'][()]]
 
         return out
 
@@ -2053,7 +2057,7 @@ class EnergyFunctionFilter(Filter):
     @interpolation.setter
     def interpolation(self, val):
         cv.check_type('interpolation', val, str)
-        cv.check_value('interpolation', val, INTERPOLATION_SCHEME.values())
+        cv.check_value('interpolation', val, self.INTERPOLATION_SCHEMES.values())
         self._interpolation = val
 
     def to_xml_element(self):

tests/regression_tests/filter_energyfun/test.py

@@ -73,9 +73,7 @@ class FilterEnergyFunHarness(PyAPITestHarness):
         br_tally = sp.tallies[2] / sp.tallies[1]
         dataframes_string += br_tally.get_pandas_dataframe().to_string() + '\n'
 
-
         for t_id in (3, 4, 5):
-            # Write out the log-log interpolation as well
             ef_tally = sp.tallies[t_id]
             dataframes_string += ef_tally.get_pandas_dataframe().to_string() + '\n'