Index: /fact/tools/pyscripts/tools/cleaning/begin.py
===================================================================
--- /fact/tools/pyscripts/tools/cleaning/begin.py	(revision 13087)
+++ /fact/tools/pyscripts/tools/cleaning/begin.py	(revision 13088)
@@ -13,5 +13,6 @@
 from plotters import *
 import time as t
-confirm_next_step = True # this is for user interaction
+from coor import Coordinator
+confirm_next_step = False# this is for user interaction
 
 data_file_name = '/media/daten_platte/FACT/data/20120229_144.fits.gz'
@@ -29,63 +30,110 @@
 extract = GlobalMaxFinder(40,200)
 
-plotA = CamPlotter('amplitudes')
-plotT = CamPlotter('times')
-plotCA = CamPlotter('cleaned amplitudes')
+#plotA = CamPlotter('amplitudes')
+#plotT = CamPlotter('times')
+#plotCA = CamPlotter('cleaned amplitudes')
 
-coreTHR = 50 # copied from F. Temme
-edgeTHR = 20 # copied from F. Temme
+#plotArea = HistPlotter('area', 1440, (0,1440) )
+#plotSize = HistPlotter('size', 1000, (0,10000) )
+
+#funnyPlot = Plotter('area vs log(size')
+
+
+coreTHR = 45 # copied from F. Temme
+edgeTHR = 18 # copied from F. Temme
 
 # get dictionary of next neighbors
 nn = Coordinator().nn
 
+print 'Core threshold=', coreTHR
+print 'Edge threshold=', edgeTHR
+print '*'*70
+
+areas = []
+sizes = []
+
 for data,startcell,tt in run:
-    data = despike(data)
-    data = smooth(data)
-    amplitude, time_of_max = extract(data)
-    
-    plotA.name='amplitudes EvtID:' + str(run.event_id.value) + ' TT:' + str(tt)
-    plotA(amplitude)
-    plotT(time_of_max)
-    
-    # Here we start the cleaning ... just like that...
-    print 'cleaning away all pixel <' , coreTHR
-    coor_chid_candidates = np.where( amplitude > coreTHR)[0]
-    coor_chids = [] # coor chids, which survive Gauks step 1
-    survivors = [] # coor & edge pixel 
-    print 'number of coor candidates:', len(coor_chid_candidates)
-    
-    print 'throwing away all pixel w/o any neighbor' 
-    # get rid of single coor pics
-    for cand in coor_chid_candidates:
-        neighbor_found = False
-        # loop over all neigbors of cand'idate
-        for n in nn[cand]:
-            if n in coor_chid_candidates:
-                neighbor_found = True
-        if neighbor_found:
-            coor_chids.append(cand)
-            
-    print 'after deletion of single coor pixels'
-    print 'number of coor pixel', len(coor_chids)
-    
-    #add edge pixel to the edge of the coors
-    print 'resurrecting edge pixels ... i.e. all pixel >', edgeTHR
-    survivors = coor_chids[:]
-    for coor in coor_chids:
-        for n in nn[coor]:
-            # if neighbor is a core pixel, then do nothing
-            if n in coor_chids:
-                pass
-            elif amplitude[n] > edgeTHR:
-                survivors.append(n)
-    
-    print 'total number of pixel in cleaned event', len(survivors)
-    
-    plotCA( 
-    
-    if confirm_next_step:
-        user_input = raw_input("'q'-quit, 'r'-run, anything else goes one step")
-        if user_input.find('q') != -1:
-            sys.exit(0)
-        elif user_input.find('r') != -1:
-            confirm_next_step = False
+    if tt==4:
+        data = despike(data)
+        data = smooth(data)
+        amplitude, time_of_max = extract(data)
+        
+        #plotA.name='amplitudes EvtID:' + str(run.event_id.value) + ' TT:' + str(tt)
+        #plotA(amplitude)
+        #plotT(time_of_max)
+        
+        # Here we start the cleaning ... just like that...
+        #print 'cleaning away all pixel <' , coreTHR
+        core_chid_candidates = np.where( amplitude > coreTHR)[0]
+        core_chids = [] # coor chids, which survive Gauks step 1
+        survivors = [] # coor & edge pixel 
+        #print 'number of core candidates:', len(core_chid_candidates)
+        
+        #print 'throwing away all pixel w/o any neighbor' 
+        # get rid of single coor pics
+        for cand in core_chid_candidates:
+            neighbor_found = False
+            # loop over all neigbors of cand'idate
+            for n in nn[cand]:
+                if n in core_chid_candidates:
+                    neighbor_found = True
+            if neighbor_found:
+                core_chids.append(cand)
+                
+        #print 'after deletion of single coor pixels'
+        
+        
+        #add edge pixel to the edge of the coors
+        #print 'resurrecting edge pixels ... i.e. all pixel >', edgeTHR
+        survivors = core_chids[:]
+        for coor in core_chids:
+            for n in nn[coor]:
+                # if neighbor is a core pixel, then do nothing
+                if n in core_chids:
+                    pass
+                elif amplitude[n] > edgeTHR:
+                    survivors.append(n)
+        survivors = np.array(survivors, dtype=int)
+        print '#survivors', len(survivors), 'evtID', run.event_id.value
+        
+        #plotCA(data=amplitude, mask=survivors)
+        
+        size = 0
+        for pixel in survivors:
+            size += amplitude[pixel]
+        
+        if len(survivors) > 0:
+            areas.append( len(survivors) )
+            sizes.append( size )
+        
+        
+        #plotArea(areas, 'areas of ' + str(run.event_id.value) + 'events')
+        #plotSize(sizes, 'sizes of ' + str(run.event_id.value) + 'events')
+        
+        if confirm_next_step:
+            user_input = raw_input("'q'-quit, 'r'-run, anything else goes one step")
+            number=None
+            try:
+                number=int(user_input)
+            except:
+                number=None
+            if user_input.find('q') != -1:
+                sys.exit(0)
+            elif user_input.find('r') != -1:
+                confirm_next_step = False
+            elif number!=None:
+                run += number
+                
+        total_event_number = run.event_id.value
+
+plt.ion()
+myfig = plt.figure()
+myn = myfig.number
+logsize = np.log10(np.array(sizes))
+areas = np.array(areas)
+
+plt.figure(myn)
+plt.title('area vs. log10(size) of '+ str(total_event_number) + 'events')
+plt.xlabel('log10(size/1mV)')
+plt.ylabel('area [#pixel]')
+plt.plot( logsize,areas, '.')