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| author | epapoutsellis <epapoutsellis@gmail.com> | 2019-04-14 20:05:07 +0100 |
|---|---|---|
| committer | epapoutsellis <epapoutsellis@gmail.com> | 2019-04-14 20:05:07 +0100 |
| commit | 8c6e2906397d9543756abf9b69088a94c980c216 (patch) | |
| tree | 0008bd50450f218d2658c404f3915986f9dcca42 | |
| parent | 580b6224747325f6540330d469ae8a2aefc9c5e3 (diff) | |
| download | framework-8c6e2906397d9543756abf9b69088a94c980c216.tar.gz framework-8c6e2906397d9543756abf9b69088a94c980c216.tar.bz2 framework-8c6e2906397d9543756abf9b69088a94c980c216.tar.xz framework-8c6e2906397d9543756abf9b69088a94c980c216.zip | |
fix pdhg examples
| -rwxr-xr-x | Wrappers/Python/wip/pdhg_TV_denoising.py | 4 | ||||
| -rw-r--r-- | Wrappers/Python/wip/pdhg_TV_tomography2D.py | 4 |
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() |