From 033c2030a05c7aa4c832e7a5e9fd13346d05e33d Mon Sep 17 00:00:00 2001
From: algol <dkazanc@hotmail.com>
Date: Tue, 1 May 2018 14:48:45 +0100
Subject: some correction

---
 Core/inpainters_CPU/Diffusion_Inpaint_core.c |  9 ++++++-
 Wrappers/Python/ccpi/filters/regularisers.py |  3 +--
 Wrappers/Python/demos/demo_cpu_inpainters.py | 40 ++++++++++++++++------------
 3 files changed, 32 insertions(+), 20 deletions(-)

diff --git a/Core/inpainters_CPU/Diffusion_Inpaint_core.c b/Core/inpainters_CPU/Diffusion_Inpaint_core.c
index e6972ab..56e0421 100644
--- a/Core/inpainters_CPU/Diffusion_Inpaint_core.c
+++ b/Core/inpainters_CPU/Diffusion_Inpaint_core.c
@@ -47,13 +47,19 @@ int signNDF_inc(float x) {
 
 float Diffusion_Inpaint_CPU_main(float *Input, unsigned char *Mask, float *Output, float lambdaPar, float sigmaPar, int iterationsNumb, float tau, int penaltytype, int dimX, int dimY, int dimZ)
 {
-    int i;
+    int i,pointsone;
     float sigmaPar2;
     sigmaPar2 = sigmaPar/sqrt(2.0f);
     
     /* copy into output */
     copyIm(Input, Output, dimX, dimY, dimZ);
     
+    pointsone = 0;
+    for (i=0; i<dimY*dimX*dimZ; i++) if (Mask[i] == 1) pointsone++;
+        
+    if (pointsone == 0) printf("%s \n", "Nothing to inpaint, zero mask!");
+    else {
+    
     if (dimZ == 1) {
     /* running 2D diffusion iterations */
     for(i=0; i < iterationsNumb; i++) {
@@ -68,6 +74,7 @@ float Diffusion_Inpaint_CPU_main(float *Input, unsigned char *Mask, float *Outpu
             else NonLinearDiff_Inp_3D(Input, Mask, Output, lambdaPar, sigmaPar2, tau, penaltytype, dimX, dimY, dimZ);
 		}
 	}
+	}
     return *Output;
 }
 /********************************************************************/
diff --git a/Wrappers/Python/ccpi/filters/regularisers.py b/Wrappers/Python/ccpi/filters/regularisers.py
index e62c020..8120f72 100644
--- a/Wrappers/Python/ccpi/filters/regularisers.py
+++ b/Wrappers/Python/ccpi/filters/regularisers.py
@@ -113,5 +113,4 @@ def NDF(inputData, regularisation_parameter, edge_parameter, iterations,
 def NDF_INP(inputData, maskData, regularisation_parameter, edge_parameter, iterations,
                      time_marching_parameter, penalty_type):
         return NDF_INPAINT_CPU(inputData, maskData, regularisation_parameter, 
-        edge_parameter, iterationsNumb, 
-        time_marching_parameter, penalty_type)
+        edge_parameter, iterations, time_marching_parameter, penalty_type)
diff --git a/Wrappers/Python/demos/demo_cpu_inpainters.py b/Wrappers/Python/demos/demo_cpu_inpainters.py
index a022bc8..b067b11 100644
--- a/Wrappers/Python/demos/demo_cpu_inpainters.py
+++ b/Wrappers/Python/demos/demo_cpu_inpainters.py
@@ -20,30 +20,36 @@ def printParametersToString(pars):
                 txt += "{0} = {1}".format(key, value.__name__)
             elif key == 'input':
                 txt += "{0} = {1}".format(key, np.shape(value))
-            elif key == 'refdata':
+            elif key == 'maskData':
                 txt += "{0} = {1}".format(key, np.shape(value))
             else:
                 txt += "{0} = {1}".format(key, value)
             txt += '\n'
         return txt
 ###############################################################################
-#%%
+
 # read sinogram and the mask
 filename = os.path.join(".." , ".." , ".." , "data" ,"SinoInpaint.mat")
 sino = io.loadmat(filename)
-sino_no_cut = sino.get('Sinogram')
+sino_full = sino.get('Sinogram')
 Mask = sino.get('Mask')
-[angles_dim,detectors_dim] = sino_no_cut.shape
-sinogram = sino_no_cut/np.max(sino_no_cut)
+[angles_dim,detectors_dim] = sino_full.shape
+sino_full = sino_full/np.max(sino_full)
 #apply mask to sinogram
-sino_cut = sinogram*(1-Mask)
+sino_cut = sino_full*(1-Mask)
+sino_cut_new = np.zeros((angles_dim,detectors_dim),'float32')
+#sino_cut_new = sino_cut.copy(order='c')
+sino_cut_new[:] = sino_cut[:]
+mask = np.zeros((angles_dim,detectors_dim),'uint8')
+#mask =Mask.copy(order='c')
+mask[:] = Mask[:]
 
 plt.figure(1)
 plt.subplot(121)
-plt.imshow(sino_cut,vmin=0.0, vmax=1)
+plt.imshow(sino_cut_new,vmin=0.0, vmax=1)
 plt.title('Missing Data sinogram')
 plt.subplot(122)
-plt.imshow(Mask)
+plt.imshow(mask)
 plt.title('Mask')
 plt.show()
 #%%
@@ -56,15 +62,15 @@ fig = plt.figure(2)
 plt.suptitle('Performance of linear inpainting using the CPU')
 a=fig.add_subplot(1,2,1)
 a.set_title('Missing data sinogram')
-imgplot = plt.imshow(sino_cut,cmap="gray")
+imgplot = plt.imshow(sino_cut_new,cmap="gray")
 
 # set parameters
 pars = {'algorithm' : NDF_INP, \
-        'input' : sino_cut,\
-        'maskData' : Mask,\
-        'regularisation_parameter':6000,\
+        'input' : sino_cut_new,\
+        'maskData' : mask,\
+        'regularisation_parameter':1000,\
         'edge_parameter':0.0,\
-        'number_of_iterations' :5000 ,\
+        'number_of_iterations' :1000 ,\
         'time_marching_parameter':0.000075,\
         'penalty_type':1
         }
@@ -78,7 +84,7 @@ ndf_inp_linear = NDF_INP(pars['input'],
               pars['time_marching_parameter'], 
               pars['penalty_type'])
              
-rms = rmse(sinogram, ndf_inp_linear)
+rms = rmse(sino_full, ndf_inp_linear)
 pars['rmse'] = rms
 
 txtstr = printParametersToString(pars)
@@ -107,8 +113,8 @@ imgplot = plt.imshow(sino_cut,cmap="gray")
 
 # set parameters
 pars = {'algorithm' : NDF_INP, \
-        'input' : sino_cut,\
-        'maskData' : Mask,\
+        'input' : sino_cut_new,\
+        'maskData' : mask,\
         'regularisation_parameter':80,\
         'edge_parameter':0.00009,\
         'number_of_iterations' :1500 ,\
@@ -125,7 +131,7 @@ ndf_inp_nonlinear = NDF_INP(pars['input'],
               pars['time_marching_parameter'], 
               pars['penalty_type'])
              
-rms = rmse(sinogram, ndf_inp_nonlinear)
+rms = rmse(sino_full, ndf_inp_nonlinear)
 pars['rmse'] = rms
 
 txtstr = printParametersToString(pars)
-- 
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