more uncontroversial changes

nifty5/domains/log_rg_space.py

@@ -93,10 +93,10 @@ class LogRGSpace(StructuredDomain):
         Returns
         -------
         LogRGSpace
-            The parter domain
+            The partner domain
         """
         codomain_bindistances = 1./(self.bindistances*self.shape)
-        return LogRGSpace(self.shape, codomain_bindistances, self._t_0, True)
+        return LogRGSpace(self.shape, codomain_bindistances, self._t_0, not self.harmonic)
 
     def get_k_length_array(self):
         """Generates array of distances to origin of the space.

nifty5/domains/rg_space.py

@@ -181,7 +181,7 @@ class RGSpace(StructuredDomain):
         Returns
         -------
         RGSpace
-            The parter domain
+            The partner domain
         """
         distances = 1. / (np.array(self.shape)*np.array(self.distances))
         return RGSpace(self.shape, distances, not self.harmonic)

nifty5/operators/block_diagonal_operator.py

@@ -30,7 +30,7 @@ class BlockDiagonalOperator(EndomorphicOperator):
         Domain and target of the operator.
     operators : dict
         Dictionary with subdomain names as keys and :class:`LinearOperator` s
-        as items.
+        as items. Any missing item will be treated as unity operator.
     """
     def __init__(self, domain, operators):
         if not isinstance(domain, MultiDomain):
@@ -44,13 +44,17 @@ class BlockDiagonalOperator(EndomorphicOperator):
 
     def apply(self, x, mode):
         self._check_input(x, mode)
-        val = tuple(op.apply(v, mode=mode) if op is not None else None
+        val = tuple(op.apply(v, mode=mode) if op is not None else v
                     for op, v in zip(self._ops, x.values()))
         return MultiField(self._domain, val)
 
     def draw_sample(self, from_inverse=False, dtype=np.float64):
-        val = tuple(op.draw_sample(from_inverse, dtype)
-                    if op is not None else None for op in self._ops)
+        from ..sugar import from_random
+        val = tuple(
+            op.draw_sample(from_inverse, dtype)
+            if op is not None
+            else from_random('normal', self._domain[key], dtype=dtype)
+            for op, key in zip(self._ops, self._domain.keys()))
         return MultiField(self._domain, val)
 
     def _combine_chain(self, op):