diff --git a/nifty/operators/linear_operator/linear_operator.py b/nifty/operators/linear_operator/linear_operator.py
index f21c8e0eaa373f6868e6740218e1367575419ee1..bf0160ba964562ca2d80fceb4da95f8491642cd9 100644
--- a/nifty/operators/linear_operator/linear_operator.py
+++ b/nifty/operators/linear_operator/linear_operator.py
@@ -249,8 +249,8 @@ class LinearOperator(Loggable, object):
                 raise
         return y
 
-    def inverse_adjoint_times(self, x, spaces=None, **kwargs):
-        return self.adjoint_inverse_times(x, spaces, **kwargs)
+    def inverse_adjoint_times(self, x, spaces=None):
+        return self.adjoint_inverse_times(x, spaces)
 
     def _times(self, x, spaces):
         raise NotImplementedError(
diff --git a/nifty/spaces/rg_space/rg_space.py b/nifty/spaces/rg_space/rg_space.py
index d943625c046cab9637a52d6cdca7498e5341583e..cb70c66452be8bc762b53ea91801ac077ee91304 100644
--- a/nifty/spaces/rg_space/rg_space.py
+++ b/nifty/spaces/rg_space/rg_space.py
@@ -48,25 +48,25 @@ class RGSpace(Space):
 
         NIFTY subclass for spaces of regular Cartesian grids.
 
-            Parameters
-            ----------
-            shape : {int, numpy.ndarray}
-                Number of grid points or numbers of gridpoints along each axis.
-            zerocenter : {bool, numpy.ndarray}, *optional*
-            Whether x==0 (or k==0, respectively) is located in the center of
-            the grid (or the center of each axis speparately) or not.
+        Parameters
+        ----------
+        shape : {int, numpy.ndarray}
+            Number of grid points or numbers of gridpoints along each axis.
+        zerocenter : {bool, numpy.ndarray}, *optional*
+        Whether x==0 (or k==0, respectively) is located in the center of
+        the grid (or the center of each axis speparately) or not.
+        (default: False).
+        distances : {float, numpy.ndarray}, *optional*
+            Distance between two grid points along each axis
+            (default: None).
+            If distances==None:
+                if harmonic==True, all distances will be set to 1
+                if harmonic==False, the distance along each axis will be
+                  set to the inverse of the number of points along that
+                  axis.
+        harmonic : bool, *optional*
+        Whether the space represents a grid in position or harmonic space.
             (default: False).
-            distances : {float, numpy.ndarray}, *optional*
-                Distance between two grid points along each axis
-                (default: None).
-                If distances==None:
-                    if harmonic==True, all distances will be set to 1
-                    if harmonic==False, the distance along each axis will be
-                      set to the inverse of the number of points along that
-                      axis.
-            harmonic : bool, *optional*
-            Whether the space represents a grid in position or harmonic space.
-                (default: False).
 
         Attributes
         ----------
@@ -92,15 +92,6 @@ class RGSpace(Space):
 
     def __init__(self, shape, zerocenter=False, distances=None,
                  harmonic=False):
-        """
-            Sets the attributes for an RGSpace class instance.
-
-
-
-            Returns
-            -------
-            None
-        """
         self._harmonic = bool(harmonic)
 
         super(RGSpace, self).__init__()
@@ -218,16 +209,17 @@ class RGSpace(Space):
         """ Calculates an n-dimensional array with its entries being the
         lengths of the vectors from the zero point of the grid.
 
-            Parameters
-            ----------
+        Parameters
+        ----------
         distribution_strategy : str
             The distribution_strategy which shall be used the returned
             distributed_data_object.
 
-            Returns
-            -------
+        Returns
+        -------
         distributed_data_object
-            A d2o containing the distances
+            A d2o containing the distances.
+
         """
 
         shape = self.shape