From ab15b31baf13d3e4528e1cd713ab609a5ed39f0d Mon Sep 17 00:00:00 2001 From: Edoardo Pasca 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'], -- cgit v1.2.3