diff options
Diffstat (limited to 'Wrappers/Python/wip')
| -rw-r--r-- | Wrappers/Python/wip/demo_compare_RGLTK_TV_denoising.py | 8 | ||||
| -rw-r--r-- | Wrappers/Python/wip/demo_simple_RGLTK.py | 8 | 
2 files changed, 8 insertions, 8 deletions
diff --git a/Wrappers/Python/wip/demo_compare_RGLTK_TV_denoising.py b/Wrappers/Python/wip/demo_compare_RGLTK_TV_denoising.py index bb9b89f..19cd86f 100644 --- a/Wrappers/Python/wip/demo_compare_RGLTK_TV_denoising.py +++ b/Wrappers/Python/wip/demo_compare_RGLTK_TV_denoising.py @@ -10,7 +10,7 @@ from ccpi.optimisation.algs import FISTA, FBPD, CGLS  from ccpi.optimisation.funcs import Norm2sq, ZeroFun, Norm1, TV2D  from ccpi.optimisation.ops import LinearOperatorMatrix, Identity -from ccpi.plugins.regularisers import _ROF_TV_, _FGP_TV_, _SB_TV_ +from ccpi.plugins.regularisers import ROF_TV, FGP_TV, SB_TV  # All external imports  import numpy as np @@ -117,7 +117,7 @@ plt.legend()  plt.show()  #%% FISTA with ROF-TV regularisation -g_rof = _ROF_TV_(lambdaReg = lam_tv, +g_rof = ROF_TV(lambdaReg = lam_tv,                   iterationsTV=2000,                   tolerance=0,                   time_marchstep=0.0009, @@ -136,7 +136,7 @@ plt.show()  print(EnergytotalROF)  #%% FISTA with FGP-TV regularisation -g_fgp = _FGP_TV_(lambdaReg = lam_tv, +g_fgp = FGP_TV(lambdaReg = lam_tv,                   iterationsTV=5000,                   tolerance=0,                   methodTV=0, @@ -157,7 +157,7 @@ plt.show()  print(EnergytotalFGP)  #%% Split-Bregman-TV regularisation -g_sb = _SB_TV_(lambdaReg = lam_tv, +g_sb = SB_TV(lambdaReg = lam_tv,                 iterationsTV=1000,                 tolerance=0,                 methodTV=0, diff --git a/Wrappers/Python/wip/demo_simple_RGLTK.py b/Wrappers/Python/wip/demo_simple_RGLTK.py index d92799a..5564503 100644 --- a/Wrappers/Python/wip/demo_simple_RGLTK.py +++ b/Wrappers/Python/wip/demo_simple_RGLTK.py @@ -8,7 +8,7 @@ from ccpi.framework import ImageData , ImageGeometry, AcquisitionGeometry  from ccpi.optimisation.algs import FISTA, FBPD, CGLS  from ccpi.optimisation.funcs import Norm2sq, Norm1, TV2D  from ccpi.astra.ops import AstraProjectorSimple -from ccpi.plugins.regularisers import _ROF_TV_, _FGP_TV_, _SB_TV_ +from ccpi.plugins.regularisers import ROF_TV, FGP_TV, SB_TV  # All external imports  import numpy as np @@ -108,7 +108,7 @@ plt.show()  # Set up the ROF variant of TV from the CCPi Regularisation Toolkit and run  # TV-reconstruction using FISTA -g_rof = _ROF_TV_(lambdaReg = lamtv, +g_rof = ROF_TV(lambdaReg = lamtv,                   iterationsTV=50,                   tolerance=1e-5,                   time_marchstep=0.01, @@ -127,7 +127,7 @@ plt.semilogy(criter_rof)  plt.show()  # Repeat for FGP variant. -g_fgp = _FGP_TV_(lambdaReg = lamtv, +g_fgp = FGP_TV(lambdaReg = lamtv,                   iterationsTV=50,                   tolerance=1e-5,                   methodTV=0, @@ -146,7 +146,7 @@ plt.semilogy(criter_fgp)  plt.show()  # Repeat for SB variant. -g_sb = _SB_TV_(lambdaReg = lamtv, +g_sb = SB_TV(lambdaReg = lamtv,                   iterationsTV=50,                   tolerance=1e-5,                   methodTV=0,  | 
