Documentation update

TomographicImaging · Nov 7, 2023 · 8de3bd6 · 8de3bd6
1 parent 1eea20b
commit 8de3bd6
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Showing 2 changed files with 6 additions and 2 deletions.
diff --git a/Wrappers/Python/cil/optimisation/operators/BlockOperator.py b/Wrappers/Python/cil/optimisation/operators/BlockOperator.py
@@ -54,7 +54,10 @@ class BlockOperator(Operator):
 
     BlockOperators have a generic shape M x N, and when applied on an 
     Nx1 BlockDataContainer, will yield and Mx1 BlockDataContainer.
-    Notice: BlockDatacontainer are only allowed to have the shape of N x 1, with
+  
+    Note
+    -----
+    BlockDatacontainer are only allowed to have the shape of N x 1, with
     N rows and 1 column.
 
     User may specify the shape of the block, by default is a row vector
@@ -299,6 +302,7 @@ def get_output_shape(self, xshape, adjoint=False):
         Examples
         --------
         A(N,M) direct u(M,1) -> N,1
+        
         A(N,M)^T adjoint u(N,1) -> M,1
         '''
         rows, cols = self.shape

diff --git a/Wrappers/Python/cil/optimisation/operators/Operator.py b/Wrappers/Python/cil/optimisation/operators/Operator.py
@@ -72,7 +72,7 @@ def norm(self, **kwargs):
     def set_norm(self, norm=None):
         '''Sets the norm of the operator to a custom value.
 
-        Parameter
+        Parameters
         ---------
         norm: Positive real valued number of `None`