Documentation update

Wrappers/Python/cil/optimisation/operators/Operator.py

@@ -71,6 +71,15 @@ def norm(self, **kwargs):
 
     def set_norm(self, norm=None):
         '''Sets the norm of the operator to a custom value.
+
+        Parameter
+        ---------
+        norm: Positive real valued number of `None`
+
+        Note
+        ----
+        The passed values are cached so that when self.norm() is called, the saved value will be returned and not calculated via the power method. 
+        If `None` is passed, the cache is cleared prompting the function to call the power method to calculate the norm the next time self.norm() is called. 
         '''
 
         if norm is not None:
@@ -361,10 +370,16 @@ class ScaledOperator(Operator):
     of the result of direct and adjoint of the operator with the scalar.
     For the rest it behaves like the operator it holds.
 
-    :param operator: a Operator or LinearOperator
-    :param scalar: a scalar multiplier
+    Parameters
+    ----------
+    operator: a Operator or LinearOperator
+
+    scalar: a scalar multiplier
+
+
 
-    Example:
+    Example
+    -------
        The scaled operator behaves like the following:
 
     .. code-block:: python
@@ -379,11 +394,6 @@ class ScaledOperator(Operator):
     '''
 
     def __init__(self, operator, scalar, **kwargs):
-        '''creator
-
-        :param operator: a Operator or LinearOperator
-        :param scalar: a scalar multiplier
-        :type scalar: Number'''
 
         super(ScaledOperator, self).__init__(domain_geometry=operator.domain_geometry(),
                                              range_geometry=operator.range_geometry())
@@ -420,9 +430,7 @@ def norm(self, **kwargs):
         return numpy.abs(self.scalar) * self.operator.norm(**kwargs)
 
     def is_linear(self):
-        '''returns whether the operator is linear
-
-        :returns: boolean '''
+        '''returns a `boolean` indicating whether the operator is linear '''
         return self.operator.is_linear()