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-rwxr-xr-xWrappers/Python/wip/pdhg_TV_denoising.py4
-rw-r--r--Wrappers/Python/wip/pdhg_TV_tomography2D.py4
2 files changed, 4 insertions, 4 deletions
diff --git a/Wrappers/Python/wip/pdhg_TV_denoising.py b/Wrappers/Python/wip/pdhg_TV_denoising.py
index eedeeb8..2072ea3 100755
--- a/Wrappers/Python/wip/pdhg_TV_denoising.py
+++ b/Wrappers/Python/wip/pdhg_TV_denoising.py
@@ -14,7 +14,7 @@ import matplotlib.pyplot as plt
from ccpi.optimisation.algorithms import PDHG, PDHG_old
from ccpi.optimisation.operators import BlockOperator, Identity, Gradient
-from ccpi.optimisation.functions import ZeroFun, L2NormSquared, \
+from ccpi.optimisation.functions import ZeroFunction, L2NormSquared, \
MixedL21Norm, FunctionOperatorComposition, BlockFunction, ScaledFunction
from skimage.util import random_noise
@@ -66,7 +66,7 @@ if method == '0':
f2 = 0.5 * L2NormSquared(b = noisy_data)
f = BlockFunction(f1, f2)
- g = ZeroFun()
+ g = ZeroFunction()
else:
diff --git a/Wrappers/Python/wip/pdhg_TV_tomography2D.py b/Wrappers/Python/wip/pdhg_TV_tomography2D.py
index 159f2ea..e0868f7 100644
--- a/Wrappers/Python/wip/pdhg_TV_tomography2D.py
+++ b/Wrappers/Python/wip/pdhg_TV_tomography2D.py
@@ -16,7 +16,7 @@ import matplotlib.pyplot as plt
from ccpi.optimisation.algorithms import PDHG, PDHG_old
from ccpi.optimisation.operators import BlockOperator, Identity, Gradient
-from ccpi.optimisation.functions import ZeroFun, L2NormSquared, \
+from ccpi.optimisation.functions import ZeroFunction, L2NormSquared, \
MixedL21Norm, BlockFunction, ScaledFunction
from ccpi.astra.ops import AstraProjectorSimple
@@ -90,7 +90,7 @@ operator = BlockOperator(op1, op2, shape=(2,1) )
alpha = 50
f = BlockFunction( alpha * MixedL21Norm(), \
0.5 * L2NormSquared(b = noisy_data) )
-g = ZeroFun()
+g = ZeroFunction()
# Compute operator Norm
normK = operator.norm()