all python code updated

4 files changed, 87 insertions, 79 deletions

diff --git a/src/Matlab/mex_compile/compileCPU_mex_Linux.m b/src/Matlab/mex_compile/compileCPU_mex_Linux.m
index f3d9ce1..d8035f4 100644
--- a/src/Matlab/mex_compile/compileCPU_mex_Linux.m
+++ b/src/Matlab/mex_compile/compileCPU_mex_Linux.m
@@ -11,7 +11,7 @@ copyfile(pathcopyFrom1, 'regularisers_CPU');
 copyfile(pathcopyFrom2, 'regularisers_CPU');
 
 cd regularisers_CPU
-
+%%
 Pathmove = sprintf(['..' fsep 'installed' fsep], 1i);
 
 fprintf('%s \n', '<<<<<<<<<<<Compiling CPU regularisers>>>>>>>>>>>>>');
@@ -27,56 +27,55 @@ movefile('FGP_TV.mex*',Pathmove);
 fprintf('%s \n', 'Compiling SB-TV...');
 mex SB_TV.c SB_TV_core.c utils.c CFLAGS="\$CFLAGS -fopenmp -Wall -std=c99" LDFLAGS="\$LDFLAGS -fopenmp"
 movefile('SB_TV.mex*',Pathmove);
-
-fprintf('%s \n', 'Compiling dFGP-TV...');
-mex FGP_dTV.c FGP_dTV_core.c utils.c CFLAGS="\$CFLAGS -fopenmp -Wall -std=c99" LDFLAGS="\$LDFLAGS -fopenmp"
-movefile('FGP_dTV.mex*',Pathmove);
-
-fprintf('%s \n', 'Compiling TNV...');
-mex TNV.c TNV_core.c utils.c CFLAGS="\$CFLAGS -fopenmp -Wall -std=c99" LDFLAGS="\$LDFLAGS -fopenmp"
-movefile('TNV.mex*',Pathmove);
-
-fprintf('%s \n', 'Compiling NonLinear Diffusion...');
-mex NonlDiff.c Diffusion_core.c utils.c CFLAGS="\$CFLAGS -fopenmp -Wall -std=c99" LDFLAGS="\$LDFLAGS -fopenmp"
-movefile('NonlDiff.mex*',Pathmove);
-
-fprintf('%s \n', 'Compiling Anisotropic diffusion of higher order...');
-mex Diffusion_4thO.c Diffus4th_order_core.c utils.c CFLAGS="\$CFLAGS -fopenmp -Wall -std=c99" LDFLAGS="\$LDFLAGS -fopenmp"
-movefile('Diffusion_4thO.mex*',Pathmove);
-
-fprintf('%s \n', 'Compiling TGV...');
-mex TGV.c TGV_core.c utils.c CFLAGS="\$CFLAGS -fopenmp -Wall -std=c99" LDFLAGS="\$LDFLAGS -fopenmp"
-movefile('TGV.mex*',Pathmove);
-
-fprintf('%s \n', 'Compiling ROF-LLT...');
-mex LLT_ROF.c LLT_ROF_core.c utils.c CFLAGS="\$CFLAGS -fopenmp -Wall -std=c99" LDFLAGS="\$LDFLAGS -fopenmp"
-movefile('LLT_ROF.mex*',Pathmove);
-
-fprintf('%s \n', 'Compiling NonLocal-TV...');
-mex PatchSelect.c PatchSelect_core.c utils.c CFLAGS="\$CFLAGS -fopenmp -Wall -std=c99" LDFLAGS="\$LDFLAGS -fopenmp"
-mex Nonlocal_TV.c Nonlocal_TV_core.c utils.c CFLAGS="\$CFLAGS -fopenmp -Wall -std=c99" LDFLAGS="\$LDFLAGS -fopenmp"
-movefile('Nonlocal_TV.mex*',Pathmove);
-movefile('PatchSelect.mex*',Pathmove);
-
-fprintf('%s \n', 'Compiling additional tools...');
-mex TV_energy.c utils.c CFLAGS="\$CFLAGS -fopenmp -Wall -std=c99" LDFLAGS="\$LDFLAGS -fopenmp"
-movefile('TV_energy.mex*',Pathmove);
+% 
+% fprintf('%s \n', 'Compiling dFGP-TV...');
+% mex FGP_dTV.c FGP_dTV_core.c utils.c CFLAGS="\$CFLAGS -fopenmp -Wall -std=c99" LDFLAGS="\$LDFLAGS -fopenmp"
+% movefile('FGP_dTV.mex*',Pathmove);
+% 
+% fprintf('%s \n', 'Compiling TNV...');
+% mex TNV.c TNV_core.c utils.c CFLAGS="\$CFLAGS -fopenmp -Wall -std=c99" LDFLAGS="\$LDFLAGS -fopenmp"
+% movefile('TNV.mex*',Pathmove);
+% 
+% fprintf('%s \n', 'Compiling NonLinear Diffusion...');
+% mex NonlDiff.c Diffusion_core.c utils.c CFLAGS="\$CFLAGS -fopenmp -Wall -std=c99" LDFLAGS="\$LDFLAGS -fopenmp"
+% movefile('NonlDiff.mex*',Pathmove);
+% 
+% fprintf('%s \n', 'Compiling Anisotropic diffusion of higher order...');
+% mex Diffusion_4thO.c Diffus4th_order_core.c utils.c CFLAGS="\$CFLAGS -fopenmp -Wall -std=c99" LDFLAGS="\$LDFLAGS -fopenmp"
+% movefile('Diffusion_4thO.mex*',Pathmove);
+% 
+% fprintf('%s \n', 'Compiling TGV...');
+% mex TGV.c TGV_core.c utils.c CFLAGS="\$CFLAGS -fopenmp -Wall -std=c99" LDFLAGS="\$LDFLAGS -fopenmp"
+% movefile('TGV.mex*',Pathmove);
+% 
+% fprintf('%s \n', 'Compiling ROF-LLT...');
+% mex LLT_ROF.c LLT_ROF_core.c utils.c CFLAGS="\$CFLAGS -fopenmp -Wall -std=c99" LDFLAGS="\$LDFLAGS -fopenmp"
+% movefile('LLT_ROF.mex*',Pathmove);
+% 
+% fprintf('%s \n', 'Compiling NonLocal-TV...');
+% mex PatchSelect.c PatchSelect_core.c utils.c CFLAGS="\$CFLAGS -fopenmp -Wall -std=c99" LDFLAGS="\$LDFLAGS -fopenmp"
+% mex Nonlocal_TV.c Nonlocal_TV_core.c utils.c CFLAGS="\$CFLAGS -fopenmp -Wall -std=c99" LDFLAGS="\$LDFLAGS -fopenmp"
+% movefile('Nonlocal_TV.mex*',Pathmove);
+% movefile('PatchSelect.mex*',Pathmove);
+% 
+% fprintf('%s \n', 'Compiling additional tools...');
+% mex TV_energy.c utils.c CFLAGS="\$CFLAGS -fopenmp -Wall -std=c99" LDFLAGS="\$LDFLAGS -fopenmp"
+% movefile('TV_energy.mex*',Pathmove);
 
 %############Inpainters##############%
-fprintf('%s \n', 'Compiling Nonlinear/Linear diffusion inpainting...');
-mex NonlDiff_Inp.c Diffusion_Inpaint_core.c utils.c CFLAGS="\$CFLAGS -fopenmp -Wall -std=c99" LDFLAGS="\$LDFLAGS -fopenmp"
-movefile('NonlDiff_Inp.mex*',Pathmove);
-
-fprintf('%s \n', 'Compiling Nonlocal marching method for inpainting...');
-mex NonlocalMarching_Inpaint.c NonlocalMarching_Inpaint_core.c utils.c CFLAGS="\$CFLAGS -fopenmp -Wall -std=c99" LDFLAGS="\$LDFLAGS -fopenmp"
-movefile('NonlocalMarching_Inpaint.mex*',Pathmove);
-
+% fprintf('%s \n', 'Compiling Nonlinear/Linear diffusion inpainting...');
+% mex NonlDiff_Inp.c Diffusion_Inpaint_core.c utils.c CFLAGS="\$CFLAGS -fopenmp -Wall -std=c99" LDFLAGS="\$LDFLAGS -fopenmp"
+% movefile('NonlDiff_Inp.mex*',Pathmove);
+% 
+% fprintf('%s \n', 'Compiling Nonlocal marching method for inpainting...');
+% mex NonlocalMarching_Inpaint.c NonlocalMarching_Inpaint_core.c utils.c CFLAGS="\$CFLAGS -fopenmp -Wall -std=c99" LDFLAGS="\$LDFLAGS -fopenmp"
+% movefile('NonlocalMarching_Inpaint.mex*',Pathmove);
+% 
 delete SB_TV_core* ROF_TV_core* FGP_TV_core* FGP_dTV_core* TNV_core* utils* Diffusion_core* Diffus4th_order_core* TGV_core* LLT_ROF_core* CCPiDefines.h
 delete PatchSelect_core* Nonlocal_TV_core*
 delete Diffusion_Inpaint_core* NonlocalMarching_Inpaint_core*
 fprintf('%s \n', '<<<<<<< Regularisers successfully compiled! >>>>>>>');
 
-%pathA2 = sprintf(['..' fsep '..' fsep], 1i);
-% cd(pathA2);
-cd('/home/kjy41806/Documents/SOFT/CCPi-Regularisation-Toolkit/demos')
-%cd demos
+pathA2 = sprintf(['..' fsep '..' fsep '..' fsep '..' fsep 'demos'], 1i);
+cd(pathA2);
+
diff --git a/src/Matlab/mex_compile/regularisers_CPU/FGP_TV.c b/src/Matlab/mex_compile/regularisers_CPU/FGP_TV.c
index 603e0f4..f160b15 100644
--- a/src/Matlab/mex_compile/regularisers_CPU/FGP_TV.c
+++ b/src/Matlab/mex_compile/regularisers_CPU/FGP_TV.c
@@ -29,10 +29,10 @@
  * 4. eplsilon: tolerance constant
  * 5. TV-type: methodTV - 'iso' (0) or 'l1' (1)
  * 6. nonneg: 'nonnegativity (0 is OFF by default)
- * 7. print information: 0 (off) or 1 (on)
  *
  * Output:
  * [1] Filtered/regularized image
+ * [2] Information vector which contains [iteration no., reached tolerance]
  *
  * This function is based on the Matlab's code and paper by
  * [1] Amir Beck and Marc Teboulle, "Fast Gradient-Based Algorithms for Constrained Total Variation Image Denoising and Deblurring Problems"
@@ -44,10 +44,10 @@ void mexFunction(
         int nrhs, const mxArray *prhs[])
         
 {
-    int number_of_dims, iter, methTV, printswitch, nonneg;
+    int number_of_dims, iter, methTV, nonneg;
     mwSize dimX, dimY, dimZ;
     const mwSize *dim_array;
-    float *Input, *Output=NULL, *Output2=NULL, lambda, epsil;
+    float *Input, *infovec=NULL, *Output=NULL, lambda, epsil;
     
     number_of_dims = mxGetNumberOfDimensions(prhs[0]);
     dim_array = mxGetDimensions(prhs[0]);
@@ -57,11 +57,10 @@ void mexFunction(
     
     Input  = (float *) mxGetData(prhs[0]); /*noisy image (2D/3D) */
     lambda =  (float) mxGetScalar(prhs[1]); /* regularization parameter */
-    iter = 300; /* default iterations number */
-    epsil = 0.0001; /* default tolerance constant */
+    iter = 400; /* default iterations number */
+    epsil = 0.0; /* default tolerance constant */
     methTV = 0;  /* default isotropic TV penalty */
     nonneg = 0; /* default nonnegativity switch, off - 0 */
-//    printswitch = 0; /*default print is switched, off - 0 */
     
     if (mxGetClassID(prhs[0]) != mxSINGLE_CLASS) {mexErrMsgTxt("The input image must be in a single precision"); }
     
@@ -81,17 +80,19 @@ void mexFunction(
     
     
     /*Handling Matlab output data*/
-    dimX = dim_array[0]; dimY = dim_array[1]; dimZ = dim_array[2];
-    
+    dimX = dim_array[0]; dimY = dim_array[1]; dimZ = dim_array[2];    
+       
     if (number_of_dims == 2) {
         dimZ = 1; /*2D case*/
-        Output = (float*)mxGetPr(plhs[0] = mxCreateNumericArray(2, dim_array, mxSINGLE_CLASS, mxREAL));
-        Output2 = (float*)mxGetPr(plhs[1] = mxCreateNumericArray(2, dim_array, mxSINGLE_CLASS, mxREAL));
+        Output = (float*)mxGetPr(plhs[0] = mxCreateNumericArray(2, dim_array, mxSINGLE_CLASS, mxREAL));        
     }
     if (number_of_dims == 3) {    
-    Output = (float*)mxGetPr(plhs[0] = mxCreateNumericArray(3, dim_array, mxSINGLE_CLASS, mxREAL));
-    }
+        Output = (float*)mxGetPr(plhs[0] = mxCreateNumericArray(3, dim_array, mxSINGLE_CLASS, mxREAL));
+    }    
+    int vecdim[1];
+    vecdim[0] = 2;
+    infovec = (float*)mxGetPr(plhs[1] = mxCreateNumericArray(1, vecdim, mxSINGLE_CLASS, mxREAL));
     
     /* running the function */
-    TV_FGP_CPU_main(Input, Output, Output2, lambda, iter, epsil, methTV, nonneg, dimX, dimY, dimZ);
+    TV_FGP_CPU_main(Input, Output, infovec, lambda, iter, epsil, methTV, nonneg, dimX, dimY, dimZ);
 }
diff --git a/src/Matlab/mex_compile/regularisers_CPU/ROF_TV.c b/src/Matlab/mex_compile/regularisers_CPU/ROF_TV.c
index 55ef2b1..a7d431f 100644
--- a/src/Matlab/mex_compile/regularisers_CPU/ROF_TV.c
+++ b/src/Matlab/mex_compile/regularisers_CPU/ROF_TV.c
@@ -29,9 +29,11 @@
  * 2. lambda - regularization parameter [REQUIRED]
  * 3. Number of iterations, for explicit scheme >= 150 is recommended  [REQUIRED]
  * 4. tau - marching step for explicit scheme, ~1 is recommended [REQUIRED]
+ * 5. eplsilon: tolerance constant [REQUIRED]
  *
  * Output:
  * [1] Regularized image/volume 
+ * [2] Information vector which contains [iteration no., reached tolerance]
  *
  * This function is based on the paper by
  * [1] Rudin, Osher, Fatemi, "Nonlinear Total Variation based noise removal algorithms"
@@ -47,7 +49,8 @@ void mexFunction(
     int number_of_dims, iter_numb;
     mwSize dimX, dimY, dimZ;
     const mwSize *dim_array_i;
-    float *Input, *Output=NULL, lambda, tau;    
+    float *Input, *Output=NULL, lambda, tau, epsil;    
+    float *infovec=NULL;
     
     dim_array_i = mxGetDimensions(prhs[0]);
     number_of_dims = mxGetNumberOfDimensions(prhs[0]);
@@ -57,9 +60,10 @@ void mexFunction(
     lambda =  (float) mxGetScalar(prhs[1]); /* regularization parameter */
     iter_numb =  (int) mxGetScalar(prhs[2]); /* iterations number */
     tau =  (float) mxGetScalar(prhs[3]); /* marching step parameter */  
+    epsil = (float) mxGetScalar(prhs[4]); /* tolerance */  
     
     if (mxGetClassID(prhs[0]) != mxSINGLE_CLASS) {mexErrMsgTxt("The input image must be in a single precision"); }
-    if(nrhs != 4) mexErrMsgTxt("Four inputs reqired: Image(2D,3D), regularization parameter, iterations number,  marching step constant");
+    if(nrhs != 5) mexErrMsgTxt("Four inputs reqired: Image(2D,3D), regularization parameter, iterations number,  marching step constant, tolerance");
     /*Handling Matlab output data*/
     dimX = dim_array_i[0]; dimY = dim_array_i[1]; dimZ = dim_array_i[2];        
     
@@ -72,6 +76,10 @@ void mexFunction(
     if (number_of_dims == 3) {
         Output = (float*)mxGetPr(plhs[0] = mxCreateNumericArray(3, dim_array_i, mxSINGLE_CLASS, mxREAL));
     }
+    
+    int vecdim[1];
+    vecdim[0] = 2;
+    infovec = (float*)mxGetPr(plhs[1] = mxCreateNumericArray(1, vecdim, mxSINGLE_CLASS, mxREAL));
      
-    TV_ROF_CPU_main(Input, Output, lambda, iter_numb, tau, dimX, dimY, dimZ);    
+    TV_ROF_CPU_main(Input, Output, infovec, lambda, iter_numb, tau, epsil, dimX, dimY, dimZ);    
 }
\ No newline at end of file
diff --git a/src/Matlab/mex_compile/regularisers_CPU/SB_TV.c b/src/Matlab/mex_compile/regularisers_CPU/SB_TV.c
index 8636322..495f1c9 100644
--- a/src/Matlab/mex_compile/regularisers_CPU/SB_TV.c
+++ b/src/Matlab/mex_compile/regularisers_CPU/SB_TV.c
@@ -28,10 +28,10 @@
 * 3. Number of iterations [OPTIONAL parameter]
 * 4. eplsilon - tolerance constant [OPTIONAL parameter]
 * 5. TV-type: 'iso' or 'l1' [OPTIONAL parameter]
-* 6. print information: 0 (off) or 1 (on)  [OPTIONAL parameter]
 *
-* Output:
-* 1. Filtered/regularized image
+ * Output:
+ * [1] Regularized image/volume 
+ * [2] Information vector which contains [iteration no., reached tolerance]
 *
 * This function is based on the Matlab's code and paper by
 * [1]. Goldstein, T. and Osher, S., 2009. The split Bregman method for L1-regularized problems. SIAM journal on imaging sciences, 2(2), pp.323-343.
@@ -42,40 +42,36 @@ void mexFunction(
         int nrhs, const mxArray *prhs[])
         
 {
-    int number_of_dims, iter, methTV, printswitch;
+    int number_of_dims, iter, methTV;
     mwSize dimX, dimY, dimZ;
     const mwSize *dim_array;
     
     float *Input, *Output=NULL, lambda, epsil;
+    float *infovec=NULL;
     
     number_of_dims = mxGetNumberOfDimensions(prhs[0]);
     dim_array = mxGetDimensions(prhs[0]);
     
     /*Handling Matlab input data*/
-    if ((nrhs < 2) || (nrhs > 6)) mexErrMsgTxt("At least 2 parameters is required, all parameters are: Image(2D/3D), Regularization parameter, Regularization parameter, iterations number, tolerance, penalty type ('iso' or 'l1'), print switch");
+    if ((nrhs < 2) || (nrhs > 5)) mexErrMsgTxt("At least 2 parameters is required, all parameters are: Image(2D/3D), Regularisation parameter,iterations number, tolerance, penalty type ('iso' or 'l1')");
     
     Input  = (float *) mxGetData(prhs[0]); /*noisy image (2D/3D) */
     lambda =  (float) mxGetScalar(prhs[1]); /* regularization parameter */
-    iter = 100; /* default iterations number */
-    epsil = 0.0001; /* default tolerance constant */
+    iter = 200; /* default iterations number */
+    epsil = 1.0e-06; /* default tolerance constant */
     methTV = 0;  /* default isotropic TV penalty */
-    printswitch = 0; /*default print is switched, off - 0 */
     
     if (mxGetClassID(prhs[0]) != mxSINGLE_CLASS) {mexErrMsgTxt("The input image must be in a single precision"); }
     
-    if ((nrhs == 3) || (nrhs == 4) || (nrhs == 5) || (nrhs == 6))  iter = (int) mxGetScalar(prhs[2]); /* iterations number */
-    if ((nrhs == 4) || (nrhs == 5) || (nrhs == 6))  epsil =  (float) mxGetScalar(prhs[3]); /* tolerance constant */
-    if ((nrhs == 5) || (nrhs == 6))  {
+    if ((nrhs == 3) || (nrhs == 4) || (nrhs == 5))  iter = (int) mxGetScalar(prhs[2]); /* iterations number */
+    if ((nrhs == 4) || (nrhs == 5))  epsil =  (float) mxGetScalar(prhs[3]); /* tolerance constant */
+    if ((nrhs == 5))  {
         char *penalty_type;
         penalty_type = mxArrayToString(prhs[4]); /* choosing TV penalty: 'iso' or 'l1', 'iso' is the default */
         if ((strcmp(penalty_type, "l1") != 0) && (strcmp(penalty_type, "iso") != 0)) mexErrMsgTxt("Choose TV type: 'iso' or 'l1',");
         if (strcmp(penalty_type, "l1") == 0)  methTV = 1;  /* enable 'l1' penalty */
         mxFree(penalty_type);
     }
-    if (nrhs == 6)  {
-        printswitch = (int) mxGetScalar(prhs[5]);
-        if ((printswitch != 0) && (printswitch != 1)) mexErrMsgTxt("Print can be enabled by choosing 1 or off - 0");
-    }
     
     /*Handling Matlab output data*/
     dimX = dim_array[0]; dimY = dim_array[1]; dimZ = dim_array[2];
@@ -86,6 +82,10 @@ void mexFunction(
     }
     if (number_of_dims == 3) Output = (float*)mxGetPr(plhs[0] = mxCreateNumericArray(3, dim_array, mxSINGLE_CLASS, mxREAL));
     
+    int vecdim[1];
+    vecdim[0] = 2;
+    infovec = (float*)mxGetPr(plhs[1] = mxCreateNumericArray(1, vecdim, mxSINGLE_CLASS, mxREAL));    
+    
     /* running the function */
-    SB_TV_CPU_main(Input, Output, lambda, iter, epsil, methTV, printswitch, dimX, dimY, dimZ);
+    SB_TV_CPU_main(Input, Output, infovec, lambda, iter, epsil, methTV, dimX, dimY, dimZ);
 }