added corrections to files which shoudl go?

2 files changed, 5 insertions, 58 deletions

diff --git a/Wrappers/Python/ccpi/optimisation/functions/FunctionComposition.py b/Wrappers/Python/ccpi/optimisation/functions/FunctionComposition.py
index 5b6defc..f24dc10 100644
--- a/Wrappers/Python/ccpi/optimisation/functions/FunctionComposition.py
+++ b/Wrappers/Python/ccpi/optimisation/functions/FunctionComposition.py
@@ -7,9 +7,11 @@ Created on Wed Mar  6 19:45:06 2019
 """
 
 import numpy as np
-from ccpi.optimisation.funcs import Function
+#from ccpi.optimisation.funcs import Function
+from ccpi.optimisation.functions import Function
 from ccpi.framework import DataContainer, ImageData, ImageGeometry 
 from ccpi.framework import BlockDataContainer 
+from ccpi.optimisation.functions import BlockFunction
 
 class FunctionOperatorComposition(Function):
     
@@ -51,63 +53,7 @@ class FunctionOperatorComposition(Function):
         return self.adjoint(self.function.gradient(self.operator.direct(x)))
         
                        
-class BlockFunction(Function):
-    
-    def __init__(self, operator, *functions):
-                
-        self.functions = functions      
-        self.operator = operator
-        self.length = len(self.functions)
-        
-        super(BlockFunction, self).__init__()
-        
-    def __call__(self, x):
-    
-        tmp = operator.direct(x)       
-                
-        t = 0                
-        for i in range(tmp.shape[0]):
-            t += self.functions[i](tmp.get_item(i))               
-        return t
-    
-    def call_adjoint(self, x):
-    
-        tmp = operator.adjoint(x)       
-                
-        t = 0                
-        for i in range(tmp.shape[0]):
-            t += self.functions[i](tmp.get_item(i))               
-        return t 
-    
-    def convex_conjugate(self, x):
-               
-        ''' Convex_conjugate does not take into account the BlockOperator'''        
-        t = 0                
-        for i in range(x.shape[0]):
-            t += self.functions[i].convex_conjugate(x.get_item(i))               
-        return t  
-    
-    
-    def proximal_conjugate(self, x, tau, out = None):
-         
-        ''' proximal_conjugate does not take into account the BlockOperator'''
-        out = [None]*self.length
-        for i in range(self.length):
-            out[i] = self.functions[i].proximal_conjugate(x.get_item(i), tau)
-
-        return CompositeDataContainer(*out) 
-    
-    def proximal(self, x, tau, out = None):
-     
-        ''' proximal does not take into account the BlockOperator'''
-        out = [None]*self.length
-        for i in range(self.length):
-            out[i] = self.functions[i].proximal(x.get_item(i), tau)
 
-        return CompositeDataContainer(*out)     
-    
-    def gradient(self,x, out=None):
-        pass
     
     
 class FunctionComposition_new(Function):
diff --git a/Wrappers/Python/ccpi/optimisation/functions/functions.py b/Wrappers/Python/ccpi/optimisation/functions/functions.py
index f40abb9..8632920 100644
--- a/Wrappers/Python/ccpi/optimisation/functions/functions.py
+++ b/Wrappers/Python/ccpi/optimisation/functions/functions.py
@@ -9,7 +9,8 @@ Created on Thu Feb  7 13:10:56 2019
 """
 
 import numpy as np
-from ccpi.optimisation.funcs import Function
+#from ccpi.optimisation.funcs import Function
+from ccpi.optimisation.functions import Function
 from ccpi.framework import DataContainer, ImageData, ImageGeometry 
 from operators import CompositeDataContainer, Identity, CompositeOperator
 from numbers import Number