Merge pull request #2371 from shimwell/adding_tabular_to_energy_filter

added get_tabular method to energyfilters

openmc/filter.py

@@ -1340,6 +1340,36 @@ class EnergyFilter(RealFilter):
             cv.check_greater_than('filter value', v0, 0., equality=True)
             cv.check_greater_than('filter value', v1, 0., equality=True)
 
+    def get_tabular(self, values, **kwargs):
+        """Create a tabulated distribution based on tally results with an energy filter
+
+        This method provides an easy way to create a distribution in energy
+        (e.g., a source spectrum) based on tally results that were obtained from
+        using an :class:`~openmc.EnergyFilter`.
+
+        Parameters
+        ----------
+        values : iterable of float
+            Array of numeric values, typically from a tally result
+        **kwargs
+            Keyword arguments passed to :class:`openmc.stats.Tabular`
+
+        Returns
+        -------
+        openmc.stats.Tabular
+            Tabular distribution with histogram interpolation
+        """
+
+        probabilities = np.array(values, dtype=float)
+        probabilities /= probabilities.sum()
+
+        # Determine probability per eV, adding extra 0 at the end since it is a histogram
+        probability_per_ev = probabilities / np.diff(self.values)
+        probability_per_ev = np.append(probability_per_ev, 0.0)
+
+        kwargs.setdefault('interpolation', 'histogram')
+        return openmc.stats.Tabular(self.values, probability_per_ev, **kwargs)
+
     @property
     def lethargy_bin_width(self):
         """Calculates the base 10 log width of energy bins which is useful when

tests/unit_tests/test_filters.py

@@ -269,3 +269,23 @@ def test_energyfunc():
     np.testing.assert_allclose(f.energy, new_f.energy)
     np.testing.assert_allclose(f.y, new_f.y)
     assert f.interpolation == new_f.interpolation
+
+
+def test_tabular_from_energyfilter():
+    efilter = openmc.EnergyFilter([0.0, 10.0, 20.0, 25.0])
+    tab = efilter.get_tabular(values=[5, 10, 10])
+
+    assert tab.x.tolist() == [0.0, 10.0, 20.0, 25.0]
+
+    # combination of different values passed into get_tabular and different
+    # width energy bins results in a doubling value for each p value
+    assert tab.p.tolist() == [0.02, 0.04, 0.08, 0.0]
+
+    # distribution should integrate to unity
+    assert tab.integral() == approx(1.0)
+
+    # 'histogram' is the default
+    assert tab.interpolation == 'histogram'
+
+    tab = efilter.get_tabular(values=np.array([10, 10, 5]), interpolation='linear-linear')
+    assert tab.interpolation == 'linear-linear'