From ab15b31baf13d3e4528e1cd713ab609a5ed39f0d Mon Sep 17 00:00:00 2001
From: Edoardo Pasca <edo.paskino@gmail.com>
Date: Mon, 14 May 2018 16:57:16 +0200
Subject: Import (#13)
* add dependency on ccpi-regulariser
* fixed import names
---
Wrappers/Python/ccpi/plugins/regularisers.py | 14 +++++++-------
1 file changed, 7 insertions(+), 7 deletions(-)
(limited to 'Wrappers/Python/ccpi')
diff --git a/Wrappers/Python/ccpi/plugins/regularisers.py b/Wrappers/Python/ccpi/plugins/regularisers.py
index 46464a9..29d4397 100644
--- a/Wrappers/Python/ccpi/plugins/regularisers.py
+++ b/Wrappers/Python/ccpi/plugins/regularisers.py
@@ -18,14 +18,14 @@
# limitations under the License.
# This requires CCPi-Regularisation toolbox to be installed
-from ccpi.filters.regularisers import ROF_TV, FGP_TV, SB_TV
+from ccpi.filters import regularisers
from ccpi.filters.cpu_regularisers import TV_ENERGY
from ccpi.framework import DataContainer
from ccpi.optimisation.ops import Operator
import numpy as np
-class _ROF_TV_(Operator):
+class ROF_TV(Operator):
def __init__(self,lambdaReg,iterationsTV,tolerance,time_marchstep,device):
# set parameters
self.lambdaReg = lambdaReg
@@ -43,13 +43,13 @@ class _ROF_TV_(Operator):
'number_of_iterations' :self.iterationsTV ,\
'time_marching_parameter':self.time_marchstep}
- out = ROF_TV(pars['input'],
+ out = regularisers.ROF_TV(pars['input'],
pars['regularization_parameter'],
pars['number_of_iterations'],
pars['time_marching_parameter'], self.device)
return DataContainer(out)
-class _FGP_TV_(Operator):
+class FGP_TV(Operator):
def __init__(self,lambdaReg,iterationsTV,tolerance,methodTV,nonnegativity,printing,device):
# set parameters
self.lambdaReg = lambdaReg
@@ -73,7 +73,7 @@ class _FGP_TV_(Operator):
'nonneg': self.nonnegativity ,\
'printingOut': self.printing}
- out = FGP_TV(pars['input'],
+ out = regularisers.FGP_TV(pars['input'],
pars['regularization_parameter'],
pars['number_of_iterations'],
pars['tolerance_constant'],
@@ -83,7 +83,7 @@ class _FGP_TV_(Operator):
return DataContainer(out)
-class _SB_TV_(Operator):
+class SB_TV(Operator):
def __init__(self,lambdaReg,iterationsTV,tolerance,methodTV,printing,device):
# set parameters
self.lambdaReg = lambdaReg
@@ -105,7 +105,7 @@ class _SB_TV_(Operator):
'methodTV': self.methodTV ,\
'printingOut': self.printing}
- out = SB_TV(pars['input'],
+ out = regularisers.SB_TV(pars['input'],
pars['regularization_parameter'],
pars['number_of_iterations'],
pars['tolerance_constant'],
--
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