Implement to/from_hdf5 methods for Python Sum class

openmc/data/function.py

@@ -578,6 +578,45 @@ class Sum(EqualityMixin):
         cv.check_type('functions', functions, Iterable, Callable)
         self._functions = functions
 
+    def to_hdf5(self, group, name='xy'):
+        """Write sum of functions to an HDF5 group
+
+        Parameters
+        ----------
+        group : h5py.Group
+            HDF5 group to write to
+        name : str
+            Name of the dataset to create
+
+        """
+        sum_group = group.create_group(name)
+        sum_group.attrs['type'] = np.string_(type(self).__name__)
+        sum_group.attrs['n'] = len(self.functions)
+        for i, f in enumerate(self.functions):
+            f.to_hdf5(sum_group, f'func_{i+1}')
+
+    @classmethod
+    def from_hdf5(cls, group):
+        """Generate sum of functions from an HDF5 group
+
+        Parameters
+        ----------
+        group : h5py.Group
+            Group to read from
+
+        Returns
+        -------
+        openmc.data.Sum
+            Functions read from the group
+
+        """
+        n = group.attrs['n']
+        functions = [
+            Function1D.from_hdf5(group[f'func_{i+1}'])
+            for i in range(n)
+        ]
+        return cls(functions)
+
 
 class Regions1D(EqualityMixin):
     r"""Piecewise composition of multiple functions.

src/endf.cpp

@@ -102,6 +102,8 @@ unique_ptr<Function1D> read_function(hid_t group, const char* name)
     func = make_unique<CoherentElasticXS>(obj_id);
   } else if (func_type == "IncoherentElastic") {
     func = make_unique<IncoherentElasticXS>(obj_id);
+  } else if (func_type == "Sum") {
+    func = make_unique<Sum1D>(obj_id);
   } else {
     throw std::runtime_error {"Unknown function type " + func_type +
                               " for dataset " + object_name(obj_id)};