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| author | Daniil Kazantsev <dkazanc@hotmail.com> | 2018-05-11 15:42:35 +0100 |
|---|---|---|
| committer | Daniil Kazantsev <dkazanc@hotmail.com> | 2018-05-11 15:42:35 +0100 |
| commit | cfd675c4dcc9ca090e6401f70c68bdc34da004db (patch) | |
| tree | dba4ed6ea4cfb31161a2e6931e86c159281a3646 /Wrappers/Python/ccpi | |
| parent | 0dd1cadcfead9a2a5f225e1500c97cc00a8068d6 (diff) | |
| download | framework-plugins-cfd675c4dcc9ca090e6401f70c68bdc34da004db.tar.gz framework-plugins-cfd675c4dcc9ca090e6401f70c68bdc34da004db.tar.bz2 framework-plugins-cfd675c4dcc9ca090e6401f70c68bdc34da004db.tar.xz framework-plugins-cfd675c4dcc9ca090e6401f70c68bdc34da004db.zip | |
further corrections, SB-TV added
Diffstat (limited to 'Wrappers/Python/ccpi')
| -rw-r--r-- | Wrappers/Python/ccpi/plugins/regularisers.py | 12 |
1 files changed, 6 insertions, 6 deletions
diff --git a/Wrappers/Python/ccpi/plugins/regularisers.py b/Wrappers/Python/ccpi/plugins/regularisers.py index 6d865cc..9f4d3fc 100644 --- a/Wrappers/Python/ccpi/plugins/regularisers.py +++ b/Wrappers/Python/ccpi/plugins/regularisers.py @@ -32,10 +32,10 @@ class _ROF_TV_(Operator): self.iterationsTV = iterationsTV self.time_marchstep = time_marchstep self.device = device # string for 'cpu' or 'gpu' - def __call__(self,x,x1,typeEnergy): + def __call__(self,x): # evaluate objective function of TV gradient # typeEnergy is either 1 (LS + TV for denoising) or 2 (just TV fidelity) - EnergyValTV = TV_ENERGY(np.asarray(x.as_array(), dtype=np.float32), np.asarray(x1.as_array(), dtype=np.float32), self.lambdaReg, typeEnergy) + EnergyValTV = TV_ENERGY(np.asarray(x.as_array(), dtype=np.float32), np.asarray(x.as_array(), dtype=np.float32), self.lambdaReg, 2) return EnergyValTV def prox(self,x,Lipshitz): pars = {'algorithm' : ROF_TV, \ @@ -60,10 +60,10 @@ class _FGP_TV_(Operator): self.nonnegativity = nonnegativity self.printing = printing self.device = device # string for 'cpu' or 'gpu' - def __call__(self,x,x1,typeEnergy): + def __call__(self,x): # evaluate objective function of TV gradient # typeEnergy is either 1 (LS + TV for denoising) or 2 (just TV fidelity) - EnergyValTV = TV_ENERGY(np.asarray(x.as_array(), dtype=np.float32), np.asarray(x1.as_array(), dtype=np.float32), self.lambdaReg, typeEnergy) + EnergyValTV = TV_ENERGY(np.asarray(x.as_array(), dtype=np.float32), np.asarray(x.as_array(), dtype=np.float32), self.lambdaReg, 2) return EnergyValTV def prox(self,x,Lipshitz): pars = {'algorithm' : FGP_TV, \ @@ -94,10 +94,10 @@ class _SB_TV_(Operator): self.methodTV = methodTV self.printing = printing self.device = device # string for 'cpu' or 'gpu' - def __call__(self,x,typeEnergy): + def __call__(self,x): # evaluate objective function of TV gradient # typeEnergy is either 1 (LS + TV for denoising) or 2 (just TV fidelity) - EnergyValTV = TV_ENERGY(np.asarray(x.as_array(), dtype=np.float32), np.asarray(x.as_array(), dtype=np.float32), self.lambdaReg, typeEnergy) + EnergyValTV = TV_ENERGY(np.asarray(x.as_array(), dtype=np.float32), np.asarray(x.as_array(), dtype=np.float32), self.lambdaReg, 2) return EnergyValTV def prox(self,x,Lipshitz): pars = {'algorithm' : SB_TV, \ |