few fixes cleaning the simple_demo_ccpi

2 files changed, 32 insertions, 2 deletions

diff --git a/Wrappers/Python/ccpi/framework.py b/Wrappers/Python/ccpi/framework.py
index ed8bac6..9ccc22d 100644
--- a/Wrappers/Python/ccpi/framework.py
+++ b/Wrappers/Python/ccpi/framework.py
@@ -96,7 +96,14 @@ class ImageGeometry:
                             self.center_y, 
                             self.center_z, 
                             self.channels)
-        
+    def __str__ (self):
+        repres = ""
+        repres += "Number of channels: {0}\n".format(self.channels)
+        repres += "voxel_num : x{0},y{1},z{2}\n".format(self.voxel_num_x, self.voxel_num_y, self.voxel_num_z)
+        repres += "voxel_size : x{0},y{1},z{2}\n".format(self.voxel_size_x, self.voxel_size_y, self.voxel_size_z)
+        repres += "center : x{0},y{1},z{2}\n".format(self.center_x, self.center_y, self.center_z)
+        return repres
+    
     
 class AcquisitionGeometry:
     
@@ -168,7 +175,7 @@ class AcquisitionGeometry:
     def __str__ (self):
         repres = ""
         repres += "Number of dimensions: {0}\n".format(self.dimension)
-        repres += "angles: {0}\n".format(len(self.angles))
+        repres += "angles: {0}\n".format(self.angles)
         repres += "voxel_num : h{0},v{1}\n".format(self.pixel_num_h, self.pixel_num_v)
         repres += "voxel size: h{0},v{1}\n".format(self.pixel_size_h, self.pixel_size_v)
         repres += "geometry type: {0}\n".format(self.geom_type)
diff --git a/Wrappers/Python/ccpi/optimisation/ops.py b/Wrappers/Python/ccpi/optimisation/ops.py
index 6460986..993f2de 100755
--- a/Wrappers/Python/ccpi/optimisation/ops.py
+++ b/Wrappers/Python/ccpi/optimisation/ops.py
@@ -157,3 +157,26 @@ def PowerMethodNonsquare(op,numiters):
         s[it] = (x1*x0).sum() / (x0*x0).sum()
         x0 = (1.0/x1norm)*x1
     return numpy.sqrt(s[-1]), numpy.sqrt(s), x0
+
+class LinearOperatorMatrix(Operator):
+    def __init__(self,A):
+        self.A = A
+        self.s1 = None   # Largest singular value, initially unknown
+        super(LinearOperatorMatrix, self).__init__()
+        
+    def direct(self,x):
+        return DataContainer(numpy.dot(self.A,x.as_array()))
+    
+    def adjoint(self,x):
+        return DataContainer(numpy.dot(self.A.transpose(),x.as_array()))
+    
+    def size(self):
+        return self.A.shape
+    
+    def get_max_sing_val(self):
+        # If unknown, compute and store. If known, simply return it.
+        if self.s1 is None:
+            self.s1 = svds(self.A,1,return_singular_vectors=False)[0]
+            return self.s1
+        else:
+            return self.s1