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| author | algol <dkazanc@hotmail.com> | 2018-04-16 15:16:32 +0100 |
|---|---|---|
| committer | algol <dkazanc@hotmail.com> | 2018-04-16 15:16:32 +0100 |
| commit | 57727584760e6b1a980071587e1f1e8910c7d6a3 (patch) | |
| tree | b6dd09825750854bf6c87cee8e544c2278ac5586 /Wrappers | |
| parent | 37e460b0eb2f8d67621dec37aef2d51efa192435 (diff) | |
| download | regularization-57727584760e6b1a980071587e1f1e8910c7d6a3.tar.gz regularization-57727584760e6b1a980071587e1f1e8910c7d6a3.tar.bz2 regularization-57727584760e6b1a980071587e1f1e8910c7d6a3.tar.xz regularization-57727584760e6b1a980071587e1f1e8910c7d6a3.zip | |
SB TV demos all work
Diffstat (limited to 'Wrappers')
| -rw-r--r-- | Wrappers/Python/ccpi/filters/regularisers.py | 4 | ||||
| -rw-r--r-- | Wrappers/Python/src/cpu_regularisers.pyx | 6 |
2 files changed, 5 insertions, 5 deletions
diff --git a/Wrappers/Python/ccpi/filters/regularisers.py b/Wrappers/Python/ccpi/filters/regularisers.py index 53623c0..50c4374 100644 --- a/Wrappers/Python/ccpi/filters/regularisers.py +++ b/Wrappers/Python/ccpi/filters/regularisers.py @@ -2,8 +2,8 @@ script which assigns a proper device core function based on a flag ('cpu' or 'gpu') """ -from ccpi.filters.cpu_regularisers_cython import TV_ROF_CPU, TV_FGP_CPU, dTV_FGP_CPU -from ccpi.filters.gpu_regularisers import TV_ROF_GPU, TV_FGP_GPU, dTV_FGP_GPU +from ccpi.filters.cpu_regularisers_cython import TV_ROF_CPU, TV_FGP_CPU, TV_SB_CPU, dTV_FGP_CPU +from ccpi.filters.gpu_regularisers import TV_ROF_GPU, TV_FGP_GPU, TV_SB_GPU, dTV_FGP_GPU def ROF_TV(inputData, regularisation_parameter, iterations, time_marching_parameter,device='cpu'): diff --git a/Wrappers/Python/src/cpu_regularisers.pyx b/Wrappers/Python/src/cpu_regularisers.pyx index b8d2523..417670d 100644 --- a/Wrappers/Python/src/cpu_regularisers.pyx +++ b/Wrappers/Python/src/cpu_regularisers.pyx @@ -20,7 +20,7 @@ cimport numpy as np cdef extern float TV_ROF_CPU_main(float *Input, float *Output, float lambdaPar, int iterationsNumb, float tau, int dimX, int dimY, int dimZ); cdef extern float TV_FGP_CPU_main(float *Input, float *Output, float lambdaPar, int iterationsNumb, float epsil, int methodTV, int nonneg, int printM, int dimX, int dimY, int dimZ); -cdef extern float TV_SB_CPU_main(float *Input, float *Output, float lambdaPar, int iterationsNumb, float epsil, int methodTV, int printM, int dimX, int dimY, int dimZ); +cdef extern float SB_TV_CPU_main(float *Input, float *Output, float lambdaPar, int iterationsNumb, float epsil, int methodTV, int printM, int dimX, int dimY, int dimZ); cdef extern float dTV_FGP_CPU_main(float *Input, float *InputRef, float *Output, float lambdaPar, int iterationsNumb, float epsil, float eta, int methodTV, int nonneg, int printM, int dimX, int dimY, int dimZ); @@ -152,7 +152,7 @@ def TV_SB_2D(np.ndarray[np.float32_t, ndim=2, mode="c"] inputData, np.zeros([dims[0],dims[1]], dtype='float32') #/* Run SB-TV iterations for 2D data */ - TV_SB_CPU_main(&inputData[0,0], &outputData[0,0], regularisation_parameter, + SB_TV_CPU_main(&inputData[0,0], &outputData[0,0], regularisation_parameter, iterationsNumb, tolerance_param, methodTV, @@ -176,7 +176,7 @@ def TV_SB_3D(np.ndarray[np.float32_t, ndim=3, mode="c"] inputData, np.zeros([dims[0], dims[1], dims[2]], dtype='float32') #/* Run SB-TV iterations for 3D data */ - TV_SB_CPU_main(&inputData[0,0,0], &outputData[0,0,0], regularisation_parameter, + SB_TV_CPU_main(&inputData[0,0,0], &outputData[0,0,0], regularisation_parameter, iterationsNumb, tolerance_param, methodTV, |