diff options
Diffstat (limited to 'Wrappers/Python')
| -rwxr-xr-x | Wrappers/Python/ccpi/optimisation/functions/Norm2Sq.py | 4 | ||||
| -rw-r--r-- | Wrappers/Python/ccpi/optimisation/functions/__init__.py | 2 | ||||
| -rw-r--r-- | Wrappers/Python/test/test_functions.py | 6 | ||||
| -rwxr-xr-x | Wrappers/Python/test/test_run_test.py | 10 |
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] |