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| author | Edoardo Pasca <edo.paskino@gmail.com> | 2018-05-14 16:57:16 +0200 |
|---|---|---|
| committer | GitHub <noreply@github.com> | 2018-05-14 16:57:16 +0200 |
| commit | ab15b31baf13d3e4528e1cd713ab609a5ed39f0d (patch) | |
| tree | 2205da6b8b72117ea123bd41314d3f5032891928 /Wrappers/Python/ccpi | |
| parent | 6e028f10427459b4ce8975cd5e6b85d761dba8b8 (diff) | |
| download | framework-plugins-ab15b31baf13d3e4528e1cd713ab609a5ed39f0d.tar.gz framework-plugins-ab15b31baf13d3e4528e1cd713ab609a5ed39f0d.tar.bz2 framework-plugins-ab15b31baf13d3e4528e1cd713ab609a5ed39f0d.tar.xz framework-plugins-ab15b31baf13d3e4528e1cd713ab609a5ed39f0d.zip | |
Import (#13)
* add dependency on ccpi-regulariser
* fixed import names
Diffstat (limited to 'Wrappers/Python/ccpi')
| -rw-r--r-- | Wrappers/Python/ccpi/plugins/regularisers.py | 14 |
1 files changed, 7 insertions, 7 deletions
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'], |