added and updated unittests

4 files changed, 75 insertions, 11 deletions

diff --git a/Wrappers/Python/test/test_BlockDataContainer.py b/Wrappers/Python/test/test_BlockDataContainer.py
index ec69225..6c0bede 100755
--- a/Wrappers/Python/test/test_BlockDataContainer.py
+++ b/Wrappers/Python/test/test_BlockDataContainer.py
@@ -18,6 +18,8 @@ from ccpi.framework import BlockDataContainer
 #from ccpi.optimisation.Algorithms import CGLS

 import functools

 

+from ccpi.optimisation.operators import Gradient, Identity, BlockOperator

+

 class TestBlockDataContainer(unittest.TestCase):

     def skiptest_BlockDataContainerShape(self):

         print ("test block data container")

@@ -327,6 +329,39 @@ class TestBlockDataContainer(unittest.TestCase):
         numpy.testing.assert_almost_equal(nbdc2.get_item(1).get_item(0).as_array()[0][0][0] , 1. , decimal=5)

         numpy.testing.assert_almost_equal(nbdc2.get_item(1).get_item(1).as_array()[0][0][0] , 3./2 , decimal=5)

 

-        

+        c5 = nbdc.get_item(0).power(2).sum()

+        c5a = nbdc.power(2).sum()

+        print ("sum", c5a, c5)

+

         print ("test_Nested_BlockDataContainer OK")

-        

+    def stest_NestedBlockDataContainer2(self):

+        M, N = 2, 3

+        ig = ImageGeometry(voxel_num_x = M, voxel_num_y = N) 

+        ag = ig

+        u = ig.allocate(1)

+        op1 = Gradient(ig)

+        op2 = Identity(ig, ag)

+

+        operator = BlockOperator(op1, op2, shape=(2,1)) 

+

+        d1 = op1.direct(u)

+        d2 = op2.direct(u)

+

+        d = operator.direct(u)

+

+        dd = operator.domain_geometry()

+        ww = operator.range_geometry()

+

+        print(d.get_item(0).get_item(0).as_array())

+        print(d.get_item(0).get_item(1).as_array())

+        print(d.get_item(1).as_array())

+

+        c1 = d + d

+

+        c2 = 2*d

+

+        c3 = d / (d+0.0001)

+

+

+        c5 = d.get_item(0).power(2).sum()

+

diff --git a/Wrappers/Python/test/test_BlockOperator.py b/Wrappers/Python/test/test_BlockOperator.py
index 8bd673b..951aa0a 100644
--- a/Wrappers/Python/test/test_BlockOperator.py
+++ b/Wrappers/Python/test/test_BlockOperator.py
@@ -4,6 +4,7 @@ from ccpi.framework import BlockDataContainer
 from ccpi.optimisation.ops import TomoIdentity
 from ccpi.framework import ImageGeometry, ImageData
 import numpy
+from ccpi.optimisation.operators import FiniteDiff
 
 class TestBlockOperator(unittest.TestCase):
 
@@ -102,6 +103,7 @@ class TestBlockOperator(unittest.TestCase):
     def test_TomoIdentity(self):
         ig = ImageGeometry(10,20,30)
         img = ig.allocate()
+        print (img.shape, ig.shape)
         self.assertTrue(img.shape == (30,20,10))
         self.assertEqual(img.sum(), 0)
         Id = TomoIdentity(ig)
@@ -288,3 +290,24 @@ class TestBlockOperator(unittest.TestCase):
         plt.imshow(cgsmall.get_output().get_item(0,0).subset(vertical=0).as_array())
         plt.title('Composite CGLS\nsmall lambda')
         plt.show()
+
+    def test_FiniteDiffOperator(self):
+        N, M = 200, 300
+
+        
+        ig = ImageGeometry(voxel_num_x = M, voxel_num_y = N)    
+        u = ig.allocate('random_int')
+        G = FiniteDiff(ig, direction=0, bnd_cond = 'Neumann')
+        print(type(u), u.as_array())    
+        print(G.direct(u).as_array())
+
+        # Gradient Operator norm, for one direction should be close to 2
+        numpy.testing.assert_allclose(G.norm(), numpy.sqrt(4), atol=0.1)
+
+        M1, N1, K1 = 200, 300, 2
+        ig1 = ImageGeometry(voxel_num_x = M1, voxel_num_y = N1, channels = K1)
+        u1 = ig1.allocate('random_int')
+        G1 = FiniteDiff(ig1, direction=2, bnd_cond = 'Periodic')
+        print(ig1.shape==u1.shape)
+        print (G1.norm())
+        numpy.testing.assert_allclose(G1.norm(), numpy.sqrt(4), atol=0.1)
\ No newline at end of file
diff --git a/Wrappers/Python/test/test_DataContainer.py b/Wrappers/Python/test/test_DataContainer.py
index 47feb95..7a7e6a0 100755
--- a/Wrappers/Python/test/test_DataContainer.py
+++ b/Wrappers/Python/test/test_DataContainer.py
@@ -495,9 +495,10 @@ class TestDataContainer(unittest.TestCase):
         self.assertEqual(order[1], image.dimension_labels[1])
         self.assertEqual(order[2], image.dimension_labels[2])
     def test_AcquisitionGeometry_allocate(self):
-        ageometry = AcquisitionGeometry(dimension=2, angles=numpy.linspace(0, 180, num=10),
-                                        geom_type='parallel', pixel_num_v=3,
-                                        pixel_num_h=5, channels=2)
+        ageometry = AcquisitionGeometry(dimension=2, 
+                            angles=numpy.linspace(0, 180, num=10),
+                            geom_type='parallel', pixel_num_v=3,
+                            pixel_num_h=5, channels=2)
         sino = ageometry.allocate()
         shape = sino.shape
         print ("shape", shape)
@@ -509,8 +510,8 @@ class TestDataContainer(unittest.TestCase):
         self.assertEqual(1,sino.as_array()[shape[0]-1][shape[1]-1][shape[2]-1][shape[3]-1])
         print (sino.dimension_labels, sino.shape, ageometry)
         
-        default_order = ['channel' , ' angle' ,
-                                          'vertical' , 'horizontal']
+        default_order = ['channel' , 'angle' ,
+                         'vertical' , 'horizontal']
         self.assertEqual(default_order[0], sino.dimension_labels[0])
         self.assertEqual(default_order[1], sino.dimension_labels[1])
         self.assertEqual(default_order[2], sino.dimension_labels[2])
diff --git a/Wrappers/Python/test/test_functions.py b/Wrappers/Python/test/test_functions.py
index 554d400..6a44641 100644
--- a/Wrappers/Python/test/test_functions.py
+++ b/Wrappers/Python/test/test_functions.py
@@ -49,11 +49,12 @@ class TestFunction(unittest.TestCase):
         noisy_data = ImageData(np.random.randint(10, size=ag))
         
         d = ImageData(np.random.randint(10, size=ag))
-        
-        g = L2NormSq(alpha=0.5, b=noisy_data)
+        alpha = 0.5
+        # scaled function
+        g = alpha * L2NormSq(b=noisy_data)
         
         # Compare call of g
-        a2 = g.alpha*(d - noisy_data).power(2).sum()
+        a2 = alpha*(d - noisy_data).power(2).sum()
         #print(a2, g(d)) 
         self.assertEqual(a2, g(d))
         
@@ -63,7 +64,11 @@ class TestFunction(unittest.TestCase):
         #print( a3, g.convex_conjugate(d))
     
     
-    
+    def stest_ScaledFunctin(self):
+        ig = (N,N)
+        ag = ig       
+        op1 = Gradient(ig)
+        op2 = Identity(ig, ag)
     
     
 #