diff options
| -rw-r--r-- | src/Python/fista_module.cpp | 5 |
1 files changed, 1 insertions, 4 deletions
diff --git a/src/Python/fista_module.cpp b/src/Python/fista_module.cpp index aca3be0..f3add76 100644 --- a/src/Python/fista_module.cpp +++ b/src/Python/fista_module.cpp @@ -328,7 +328,6 @@ bp::list FGP_TV(np::ndarray input, double d_mu, int iter, double d_epsil, int me else { dim_array[2] = input.shape(2); } - // Parameter handling is be done in Python ///*Handling Matlab input data*/ //if ((nrhs < 2) || (nrhs > 5)) mexErrMsgTxt("At least 2 parameters is required: Image(2D/3D), Regularization parameter. The full list of parameters: Image(2D/3D), Regularization parameter, iterations number, tolerance, penalty type ('iso' or 'l1')"); @@ -513,13 +512,11 @@ bp::list FGP_TV(np::ndarray input, double d_mu, int iter, double d_epsil, int me P3_old = reinterpret_cast<float *>(npP3_old.get_data()); R1 = reinterpret_cast<float *>(npR1.get_data()); R2 = reinterpret_cast<float *>(npR2.get_data()); - R2 = reinterpret_cast<float *>(npR3.get_data()); + R3 = reinterpret_cast<float *>(npR3.get_data()); /* begin iterations */ for (ll = 0; ll<iter; ll++) { - /* computing the gradient of the objective function */ Obj_func3D(A, D, R1, R2, R3, lambda, dimX, dimY, dimZ); - /*Taking a step towards minus of the gradient*/ Grad_func3D(P1, P2, P3, D, R1, R2, R3, lambda, dimX, dimY, dimZ); |