adjusted renormalisation of resynthetised reference scan for spots going outside the detector

XRStools/XRS_swissknife.py

@@ -1288,18 +1288,25 @@ def loadscan_2Dimages_galaxies_foilscan(mydata):
 
     hf[   "image"  ]  = roiob.input_image
 
+
+    rois_dict_group = hf.require_group("rois_dict" ) 
+    
     for roikey, (origin, box) in roiob.red_rois.items():
         roigroup=roikey+"/"
         hf.require_group(  roigroup   )
         hf[  roigroup +"origin"  ] =  origin
         hf[  roigroup +"mask"    ] =  box
        
-        
+        if roikey in rois_dict_group:
+            del rois_dict_group[roikey]
+            
+        rois_dict_group[roikey] = h5py.SoftLink(  "/"+ roigroup )
 
     filename, dataname = split_hdf5_address( mydata["expdata"]       )
 
     data =  np.array(h5py.File(filename,"r")[dataname][:])
 
+    
     for roikey, (origin, box) in roiob.red_rois.items():
 
         roigroup=roikey[3:]+"/"  # with "ROI" removed, nly numerical part
@@ -3946,6 +3953,10 @@ def superR_recreate_rois(mydata):
 
          ## where new rois and bnew scan are written
          target_filename : "newrois.h5:ROI_B_FIT8/"
+
+         ## filter_rois=1 activates a filtering mechanism which discards ROIS according to a 
+         ## simple statistical criteria which is har coded in file reponse_percussionelle.py
+         ## routine get_spots_list
          filter_rois      : 1
     """
     foil_scan_address = mydata["old_scan_address"]

XRStools/reponse_percussionelle.py

@@ -1433,7 +1433,9 @@ def DOROIS(filename = "../nonregressions/demo_imaging.hdf5" , groupname = "ROI_B
 
             
             for i in range(len(newspots)):
-                newspots[i] = newspots[i]/newspots[i].sum()
+                spot_sum = newspots[i].sum()
+                if spot_sum:
+                    newspots[i] = newspots[i]/spot_sum
 
                 
             h5["matrix"] = newspots