memopt fixes

5 files changed, 28 insertions, 56 deletions

diff --git a/Wrappers/Python/ccpi/framework/BlockDataContainer.py b/Wrappers/Python/ccpi/framework/BlockDataContainer.py
index 9bec1fe..f1d6d9a 100755
--- a/Wrappers/Python/ccpi/framework/BlockDataContainer.py
+++ b/Wrappers/Python/ccpi/framework/BlockDataContainer.py
@@ -78,9 +78,13 @@ class BlockDataContainer(object):
                     a = el.is_compatible(other)

                 else:

                     a = el.shape == other.shape

+#                print ("current element" , el.shape, "other ", other.shape, "same shape" , a)

                 ret = ret and a

             return ret

-

+        

+        

+#        elif issubclass(other.__class__, DataContainer):

+#            return self.get_item(0).shape == other.shape

         return len(self.containers) == len(other.containers)

 

     def get_item(self, row):

@@ -350,32 +354,3 @@ class BlockDataContainer(object):
         '''Inline truedivision'''

         return self.__idiv__(other)

 

-if __name__ == '__main__':

-    

-    M, N, K = 2,3,5

-    from ccpi.framework import ImageGeometry, BlockGeometry

-    

-    ig = ImageGeometry(N, M)

-    u = ig.allocate('random_int')

-    

-    BG = BlockGeometry(ig, ig)

-    U = BG.allocate('random_int')

-    

-    U_nested = BlockDataContainer(BlockDataContainer(u, u), u)

-    

-    

-    res1 = U + u

-    res2 = U_nested + u

-#    res2 = u + U

-

-    

-    

-    

-    

-    

-    

-    

-    

-    

-    

-    
\ No newline at end of file
diff --git a/Wrappers/Python/ccpi/optimisation/functions/BlockFunction.py b/Wrappers/Python/ccpi/optimisation/functions/BlockFunction.py
index 9917d99..8cce290 100644
--- a/Wrappers/Python/ccpi/optimisation/functions/BlockFunction.py
+++ b/Wrappers/Python/ccpi/optimisation/functions/BlockFunction.py
@@ -7,7 +7,7 @@ Created on Fri Mar  8 10:01:31 2019
 """
 
 import numpy as np
-#from ccpi.optimisation.funcs import Function
+
 from ccpi.optimisation.functions import Function
 from ccpi.framework import BlockDataContainer
 from numbers import Number
diff --git a/Wrappers/Python/ccpi/optimisation/functions/L2NormSquared.py b/Wrappers/Python/ccpi/optimisation/functions/L2NormSquared.py
index 9e0e424..9508c13 100644
--- a/Wrappers/Python/ccpi/optimisation/functions/L2NormSquared.py
+++ b/Wrappers/Python/ccpi/optimisation/functions/L2NormSquared.py
@@ -20,38 +20,36 @@
 import numpy
 from ccpi.optimisation.functions import Function
 from ccpi.optimisation.functions.ScaledFunction import ScaledFunction
-from ccpi.framework import DataContainer, ImageData, ImageGeometry  
 
-############################   L2NORM FUNCTION   #############################
 class L2NormSquared(Function):
     
-    def __init__(self, **kwargs):
-        
-        ''' L2NormSquared class
-            f : ImageGeometry --> R
-            
-            Cases: f(x) = ||x||^{2}_{2}
-                   f(x) = || x - b ||^{2}_{2}     
-        
-        '''
+    ''' 
+    
+    Class: L2NormSquared 
         
-        #TODO need x, b to live in the same geometry if b is not None
-                        
+    Cases:  a) f(x) = ||x||^{2}
+    
+            b) f(x) = ||x - b||^{2}, b
+                             
+    '''    
+    
+    def __init__(self, **kwargs):
+                                
         super(L2NormSquared, self).__init__()
         self.b = kwargs.get('b',None)  
 
     def __call__(self, x):
-        ''' Evaluates L2NormSq at point x'''
         
+        """ 
+        
+        Evaluate L2NormSquared at x: f(x)
+        
+        
+        """
+            
         y = x
         if self.b is not None: 
-#            x.subtract(self.b, out = x)
             y = x - self.b
-#        else:
-#            y
-#        if out is None:
-#            return x.squared_norm()
-#        else:
         try:
             return y.squared_norm()
         except AttributeError as ae:
@@ -61,6 +59,8 @@ class L2NormSquared(Function):
             
         
     def gradient(self, x, out=None):
+        
+        
         ''' Evaluates gradient of L2NormSq at point x'''
         if out is not None:
             out.fill(x)
diff --git a/Wrappers/Python/ccpi/optimisation/functions/MixedL21Norm.py b/Wrappers/Python/ccpi/optimisation/functions/MixedL21Norm.py
index 0c658a4..0c7eb85 100755
--- a/Wrappers/Python/ccpi/optimisation/functions/MixedL21Norm.py
+++ b/Wrappers/Python/ccpi/optimisation/functions/MixedL21Norm.py
@@ -102,9 +102,6 @@ class MixedL21Norm(Function):
             res = (sum(x**2).sqrt()).maximum(1.0)             
             out.fill(x/res)
 
-            
-
-
     def __rmul__(self, scalar):
         return ScaledFunction(self, scalar) 
 
diff --git a/Wrappers/Python/wip/pdhg_TV_denoising.py b/Wrappers/Python/wip/pdhg_TV_denoising.py
index 22fee90..f276b46 100755
--- a/Wrappers/Python/wip/pdhg_TV_denoising.py
+++ b/Wrappers/Python/wip/pdhg_TV_denoising.py
@@ -90,8 +90,8 @@ print ("normK", normK)
 sigma = 1
 tau = 1/(sigma*normK**2)
 
-opt = {'niter':100}
-opt1 = {'niter':100, 'memopt': True}
+opt = {'niter':1000}
+opt1 = {'niter':1000, 'memopt': True}
 
 t1 = timer()
 res, time, primal, dual, pdgap = PDHG_old(f, g, operator, tau = tau, sigma = sigma, opt = opt)