fixes gpu issues with pdtv

2 files changed, 47 insertions, 52 deletions

diff --git a/src/Matlab/mex_compile/regularisers_CPU/PD_TV.c b/src/Matlab/mex_compile/regularisers_CPU/PD_TV.c
index e5ab1e4..f8f5272 100644
--- a/src/Matlab/mex_compile/regularisers_CPU/PD_TV.c
+++ b/src/Matlab/mex_compile/regularisers_CPU/PD_TV.c
@@ -30,8 +30,7 @@
  * 5. TV-type: methodTV - 'iso' (0) or 'l1' (1)
  * 6. nonneg: 'nonnegativity (0 is OFF by default, 1 is ON)
  * 7. lipschitz_const: convergence related parameter
- * 8. tau: convergence related parameter
- 
+
  * Output:
  * [1] TV - Filtered/regularized image/volume
  * [2] Information vector which contains [iteration no., reached tolerance]
@@ -41,19 +40,19 @@
 void mexFunction(
         int nlhs, mxArray *plhs[],
         int nrhs, const mxArray *prhs[])
-        
+
 {
     int number_of_dims, iter, methTV, nonneg;
     mwSize dimX, dimY, dimZ;
     const mwSize *dim_array;
-    float *Input, *infovec=NULL, *Output=NULL, lambda, epsil, lipschitz_const, tau;
-    
+    float *Input, *infovec=NULL, *Output=NULL, lambda, epsil, lipschitz_const;
+
     number_of_dims = mxGetNumberOfDimensions(prhs[0]);
     dim_array = mxGetDimensions(prhs[0]);
-    
+
     /*Handling Matlab input data*/
-    if ((nrhs < 2) || (nrhs > 7)) mexErrMsgTxt("At least 2 parameters is required, all parameters are: Image(2D/3D), Regularization parameter, iterations number, tolerance, penalty type ('iso' or 'l1'), nonnegativity switch, lipschitz_const");
-    
+    if ((nrhs < 2) || (nrhs > 6)) mexErrMsgTxt("At least 2 parameters is required, all parameters are: Image(2D/3D), Regularization parameter, iterations number, tolerance, penalty type ('iso' or 'l1'), nonnegativity switch, lipschitz_const");
+
     Input  = (float *) mxGetData(prhs[0]); /*noisy image (2D/3D) */
     lambda =  (float) mxGetScalar(prhs[1]); /* regularization parameter */
     iter = 500; /* default iterations number */
@@ -61,40 +60,39 @@ void mexFunction(
     methTV = 0;  /* default isotropic TV penalty */
     nonneg = 0; /* default nonnegativity switch, off - 0 */
     lipschitz_const = 8.0; /* lipschitz_const */
-    tau = 0.0025; /* tau convergence const */
-    
+
+
     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) || (nrhs == 7) || (nrhs == 8))  iter = (int) mxGetScalar(prhs[2]); /* iterations number */
-    if ((nrhs == 4) || (nrhs == 5) || (nrhs == 6) || (nrhs == 7) || (nrhs == 8))  epsil =  (float) mxGetScalar(prhs[3]); /* tolerance constant */
-    if ((nrhs == 5) || (nrhs == 6) || (nrhs == 7) || (nrhs == 8))  {
+
+    if ((nrhs == 3) || (nrhs == 4) || (nrhs == 5) || (nrhs == 6) || (nrhs == 7))  iter = (int) mxGetScalar(prhs[2]); /* iterations number */
+    if ((nrhs == 4) || (nrhs == 5) || (nrhs == 6) || (nrhs == 7))  epsil =  (float) mxGetScalar(prhs[3]); /* tolerance constant */
+    if ((nrhs == 5) || (nrhs == 6) || (nrhs == 7))  {
         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) || (nrhs == 7) || (nrhs == 8))  {
+    if ((nrhs == 6) || (nrhs == 7))  {
         nonneg = (int) mxGetScalar(prhs[5]);
         if ((nonneg != 0) && (nonneg != 1)) mexErrMsgTxt("Nonnegativity constraint can be enabled by choosing 1 or off - 0");
     }
-    if ((nrhs == 7) || (nrhs == 8)) lipschitz_const = (float) mxGetScalar(prhs[6]);
-    if (nrhs == 8) tau = (float) mxGetScalar(prhs[7]);   
-    
+    if (nrhs == 7) lipschitz_const = (float) mxGetScalar(prhs[6]);
+
     /*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));        
+        Output = (float*)mxGetPr(plhs[0] = mxCreateNumericArray(2, dim_array, mxSINGLE_CLASS, mxREAL));
     }
-    if (number_of_dims == 3) {    
+    if (number_of_dims == 3) {
         Output = (float*)mxGetPr(plhs[0] = mxCreateNumericArray(3, dim_array, mxSINGLE_CLASS, mxREAL));
-    }    
+    }
     mwSize vecdim[1];
     vecdim[0] = 2;
     infovec = (float*)mxGetPr(plhs[1] = mxCreateNumericArray(1, vecdim, mxSINGLE_CLASS, mxREAL));
-    
-    /* running the function */    
-    PDTV_CPU_main(Input, Output, infovec, lambda, iter,  epsil, lipschitz_const, methTV, nonneg, tau, dimX, dimY, dimZ);
+
+    /* running the function */
+    PDTV_CPU_main(Input, Output, infovec, lambda, iter,  epsil, lipschitz_const, methTV, nonneg, dimX, dimY, dimZ);
 }
diff --git a/src/Matlab/mex_compile/regularisers_GPU/PD_TV_GPU.cpp b/src/Matlab/mex_compile/regularisers_GPU/PD_TV_GPU.cpp
index e853dd3..2c037a5 100644
--- a/src/Matlab/mex_compile/regularisers_GPU/PD_TV_GPU.cpp
+++ b/src/Matlab/mex_compile/regularisers_GPU/PD_TV_GPU.cpp
@@ -30,8 +30,7 @@
  * 5. TV-type: methodTV - 'iso' (0) or 'l1' (1)
  * 6. nonneg: 'nonnegativity (0 is OFF by default, 1 is ON)
  * 7. lipschitz_const: convergence related parameter
- * 8. tau: convergence related parameter
- 
+
  * Output:
  * [1] TV - Filtered/regularized image/volume
  * [2] Information vector which contains [iteration no., reached tolerance]
@@ -42,19 +41,19 @@
 void mexFunction(
         int nlhs, mxArray *plhs[],
         int nrhs, const mxArray *prhs[])
-        
+
 {
     int number_of_dims, iter, methTV, nonneg;
     mwSize dimX, dimY, dimZ;
     const mwSize *dim_array;
-    float *Input, *infovec=NULL, *Output=NULL, lambda, epsil, lipschitz_const, tau;
-    
+    float *Input, *infovec=NULL, *Output=NULL, lambda, epsil, lipschitz_const;
+
     number_of_dims = mxGetNumberOfDimensions(prhs[0]);
     dim_array = mxGetDimensions(prhs[0]);
-    
+
     /*Handling Matlab input data*/
-    if ((nrhs < 2) || (nrhs > 7)) mexErrMsgTxt("At least 2 parameters is required, all parameters are: Image(2D/3D), Regularization parameter, iterations number, tolerance, penalty type ('iso' or 'l1'), nonnegativity switch, lipschitz_const");
-    
+    if ((nrhs < 2) || (nrhs > 6)) mexErrMsgTxt("At least 2 parameters is required, all parameters are: Image(2D/3D), Regularization parameter, iterations number, tolerance, penalty type ('iso' or 'l1'), nonnegativity switch, lipschitz_const");
+
     Input  = (float *) mxGetData(prhs[0]); /*noisy image (2D/3D) */
     lambda =  (float) mxGetScalar(prhs[1]); /* regularization parameter */
     iter = 500; /* default iterations number */
@@ -62,40 +61,38 @@ void mexFunction(
     methTV = 0;  /* default isotropic TV penalty */
     nonneg = 0; /* default nonnegativity switch, off - 0 */
     lipschitz_const = 8.0; /* lipschitz_const */
-    tau = 0.0025; /* tau convergence const */
-    
+
     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) || (nrhs == 7) || (nrhs == 8))  iter = (int) mxGetScalar(prhs[2]); /* iterations number */
-    if ((nrhs == 4) || (nrhs == 5) || (nrhs == 6) || (nrhs == 7) || (nrhs == 8))  epsil =  (float) mxGetScalar(prhs[3]); /* tolerance constant */
-    if ((nrhs == 5) || (nrhs == 6) || (nrhs == 7) || (nrhs == 8))  {
+
+    if ((nrhs == 3) || (nrhs == 4) || (nrhs == 5) || (nrhs == 6) || (nrhs == 7))  iter = (int) mxGetScalar(prhs[2]); /* iterations number */
+    if ((nrhs == 4) || (nrhs == 5) || (nrhs == 6) || (nrhs == 7))  epsil =  (float) mxGetScalar(prhs[3]); /* tolerance constant */
+    if ((nrhs == 5) || (nrhs == 6) || (nrhs == 7))  {
         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) || (nrhs == 7) || (nrhs == 8))  {
+    if ((nrhs == 6) || (nrhs == 7))  {
         nonneg = (int) mxGetScalar(prhs[5]);
         if ((nonneg != 0) && (nonneg != 1)) mexErrMsgTxt("Nonnegativity constraint can be enabled by choosing 1 or off - 0");
     }
-    if ((nrhs == 7) || (nrhs == 8)) lipschitz_const = (float) mxGetScalar(prhs[6]);
-    if (nrhs == 8) tau = (float) mxGetScalar(prhs[7]);   
-    
+    if (nrhs == 7) lipschitz_const = (float) mxGetScalar(prhs[6]);
+
     /*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));        
+        Output = (float*)mxGetPr(plhs[0] = mxCreateNumericArray(2, dim_array, mxSINGLE_CLASS, mxREAL));
     }
-    if (number_of_dims == 3) {    
+    if (number_of_dims == 3) {
         Output = (float*)mxGetPr(plhs[0] = mxCreateNumericArray(3, dim_array, mxSINGLE_CLASS, mxREAL));
-    }    
+    }
     mwSize vecdim[1];
     vecdim[0] = 2;
     infovec = (float*)mxGetPr(plhs[1] = mxCreateNumericArray(1, vecdim, mxSINGLE_CLASS, mxREAL));
-    
-    /* running the function */    
-    TV_PD_GPU_main(Input, Output, infovec, lambda, iter,  epsil, lipschitz_const, methTV, nonneg, tau, dimX, dimY, dimZ);
+
+    /* running the function */
+    TV_PD_GPU_main(Input, Output, infovec, lambda, iter,  epsil, lipschitz_const, methTV, nonneg, dimX, dimY, dimZ);
 }