removed FunctionComposition.py

1 files changed, 0 insertions, 121 deletions

diff --git a/Wrappers/Python/ccpi/optimisation/functions/FunctionComposition.py b/Wrappers/Python/ccpi/optimisation/functions/FunctionComposition.py
deleted file mode 100644
index f24dc10..0000000
--- a/Wrappers/Python/ccpi/optimisation/functions/FunctionComposition.py
+++ /dev/null
@@ -1,121 +0,0 @@
-#!/usr/bin/env python3
-# -*- coding: utf-8 -*-
-"""
-Created on Wed Mar  6 19:45:06 2019
-
-@author: evangelos
-"""
-
-import numpy as np
-#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):
-    
-    def __init__(self, function, operator):
-        
-        self.function = functions      
-        self.operator = operator
-        self.grad_Lipschitz_cnst = 2*self.function.alpha*operator.norm()**2
-        super(FunctionOperatorComposition, self).__init__()
-        
-    def __call__(self, x):
-    
-        return self.function(operator.direct(x))   
-
-    def call_adjoint(self, x):
-    
-        return self.function(operator.adjoint(x))  
-
-    def convex_conjugate(self, x):
-        
-        return self.function.convex_conjugate(x)
-
-    def proximal(self, x, tau):
-        
-        ''' proximal does not take into account the Operator'''
-        
-        return self.function.proximal(x, tau, out=None)
-
-    def proximal_conjugate(self, x, tau):    
-
-        ''' proximal conjugate does not take into account the Operator'''
-        
-        return self.function.proximal_conjugate(x, tau, out=None) 
-
-    def gradient(self, x):
-        
-        ''' Gradient takes into account the Operator'''
-        
-        return self.adjoint(self.function.gradient(self.operator.direct(x)))
-        
-                       
-
-    
-    
-class FunctionComposition_new(Function):
-    
-     def __init__(self, operator, *functions):
-        
-        self.functions = functions      
-        self.operator = operator
-        self.length = len(self.functions)
-          
-        super(FunctionComposition_new, self).__init__()
-                    
-     def __call__(self, x):
-         
-        if isinstance(x, ImageData):
-            x =  CompositeDataContainer(x)         
-        
-        t = 0                
-        for i in range(x.shape[0]):
-            t += self.functions[i](x.get_item(i))               
-        return t 
-    
-     def convex_conjugate(self, x):
-         
-        if isinstance(x, ImageData):
-            x =  CompositeDataContainer(x)         
-        
-        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):
-     
-        if isinstance(x, ImageData):
-            x =  CompositeDataContainer(x)
-            
-        out = [None]*self.length
-        for i in range(self.length):
-            out[i] = self.functions[i].proximal_conjugate(x.get_item(i), tau)
-        
-        if self.length==1:
-            return ImageData(*out)   
-        else:
-            return CompositeDataContainer(*out)   
-
-     def proximal(self, x, tau, out = None):
-     
-        if isinstance(x, ImageData):
-            x =  CompositeDataContainer(x)
-            
-        out = [None]*self.length
-        for i in range(self.length):
-            out[i] = self.functions[i].proximal(x.get_item(i), tau)
-        
-        if self.length==1:
-            return ImageData(*out)   
-        else:
-            return CompositeDataContainer(*out) 
-        
-        
-if __name__ == '__main__':
-
-    from  operators import Operator
-    from  IdentityOperator import Identity
\ No newline at end of file