Merge branch 'norm2sq_bugfix' into composite_operator_datacontainer

4 files changed, 11 insertions, 11 deletions

diff --git a/Wrappers/Python/ccpi/optimisation/functions/Norm2Sq.py b/Wrappers/Python/ccpi/optimisation/functions/Norm2Sq.py
index b553d7c..0b6bb0b 100755
--- a/Wrappers/Python/ccpi/optimisation/functions/Norm2Sq.py
+++ b/Wrappers/Python/ccpi/optimisation/functions/Norm2Sq.py
@@ -21,7 +21,7 @@ import numpy
 import warnings
 
 # Define a class for squared 2-norm
-class Norm2sq(Function):
+class Norm2Sq(Function):
     '''
     f(x) = c*||A*x-b||_2^2
     
@@ -38,7 +38,7 @@ class Norm2sq(Function):
     '''
     
     def __init__(self,A,b,c=1.0,memopt=False):
-        super(Norm2sq, self).__init__()
+        super(Norm2Sq, self).__init__()
     
         self.A = A  # Should be an operator, default identity
         self.b = b  # Default zero DataSet?
diff --git a/Wrappers/Python/ccpi/optimisation/functions/__init__.py b/Wrappers/Python/ccpi/optimisation/functions/__init__.py
index a82ee3e..c0eab31 100644
--- a/Wrappers/Python/ccpi/optimisation/functions/__init__.py
+++ b/Wrappers/Python/ccpi/optimisation/functions/__init__.py
@@ -10,4 +10,4 @@ from .FunctionOperatorComposition import FunctionOperatorComposition
 from .MixedL21Norm import MixedL21Norm
 from .IndicatorBox import IndicatorBox
 from .KullbackLeibler import KullbackLeibler
-from .Norm2Sq import Norm2sq
+from .Norm2Sq import Norm2Sq
diff --git a/Wrappers/Python/test/test_functions.py b/Wrappers/Python/test/test_functions.py
index af419c7..523008d 100644
--- a/Wrappers/Python/test/test_functions.py
+++ b/Wrappers/Python/test/test_functions.py
@@ -20,7 +20,7 @@ from ccpi.optimisation.operators import Gradient
 from ccpi.optimisation.functions import L2NormSquared
 from ccpi.optimisation.functions import L1Norm, MixedL21Norm
 
-from ccpi.optimisation.functions import Norm2sq
+from ccpi.optimisation.functions import Norm2Sq
 from ccpi.optimisation.functions import ZeroFunction
 
 from ccpi.optimisation.functions import FunctionOperatorComposition
@@ -298,7 +298,7 @@ class TestFunction(unittest.TestCase):
         b = ig.allocate(ImageGeometry.RANDOM_INT) 
         
         A = 0.5 * Identity(ig)
-        old_chisq = Norm2sq(A, b, 1.0)
+        old_chisq = Norm2Sq(A, b, 1.0)
         new_chisq = FunctionOperatorComposition(A, L2NormSquared(b=b))
 
         yold = old_chisq(u)
@@ -364,4 +364,4 @@ class TestFunction(unittest.TestCase):
         
         proxc = f.proximal_conjugate(x,1.2)
         f.proximal_conjugate(x, 1.2, out=out)
-        numpy.testing.assert_array_equal(proxc.as_array(), out.as_array())
\ No newline at end of file
+        numpy.testing.assert_array_equal(proxc.as_array(), out.as_array())
diff --git a/Wrappers/Python/test/test_run_test.py b/Wrappers/Python/test/test_run_test.py
index 9b4d53b..a6c13f4 100755
--- a/Wrappers/Python/test/test_run_test.py
+++ b/Wrappers/Python/test/test_run_test.py
@@ -8,7 +8,7 @@ from ccpi.framework import ImageGeometry
 from ccpi.framework import AcquisitionGeometry
 from ccpi.optimisation.algorithms import FISTA
 #from ccpi.optimisation.algs import FBPD
-from ccpi.optimisation.functions import Norm2sq
+from ccpi.optimisation.functions import Norm2Sq
 from ccpi.optimisation.functions import ZeroFunction
 from ccpi.optimisation.funcs import Norm1
 from ccpi.optimisation.funcs import Norm2
@@ -80,7 +80,7 @@ class TestAlgorithms(unittest.TestCase):
                 lam = 10
                 opt = {'memopt': True}
                 # Create object instances with the test data A and b.
-                f = Norm2sq(A, b, c=0.5, memopt=True)
+                f = Norm2Sq(A, b, c=0.5, memopt=True)
                 g0 = ZeroFunction()
 
                 # Initial guess
@@ -144,7 +144,7 @@ class TestAlgorithms(unittest.TestCase):
                 lam = 10
                 opt = {'memopt': True}
                 # Create object instances with the test data A and b.
-                f = Norm2sq(A, b, c=0.5, memopt=True)
+                f = Norm2Sq(A, b, c=0.5, memopt=True)
                 g0 = ZeroFunction()
 
                 # Initial guess
@@ -218,7 +218,7 @@ class TestAlgorithms(unittest.TestCase):
             x_init = DataContainer(np.random.randn(n, 1))
 
             # Create object instances with the test data A and b.
-            f = Norm2sq(A, b, c=0.5, memopt=True)
+            f = Norm2Sq(A, b, c=0.5, memopt=True)
             f.L = LinearOperator.PowerMethod(A, 25, x_init)[0]
             print ("Lipschitz", f.L)
             g0 = ZeroFun()
@@ -286,7 +286,7 @@ class TestAlgorithms(unittest.TestCase):
             y.array = y.array + 0.1*np.random.randn(N, N)
 
             # Data fidelity term
-            f_denoise = Norm2sq(I, y, c=0.5, memopt=True)
+            f_denoise = Norm2Sq(I, y, c=0.5, memopt=True)
             x_init = ImageData(geometry=ig)
             f_denoise.L = LinearOperator.PowerMethod(I, 25, x_init)[0]