Index: fact/tools/pyscripts/pyfact/extractor.py
===================================================================
--- fact/tools/pyscripts/pyfact/extractor.py	(revision 12977)
+++ fact/tools/pyscripts/pyfact/extractor.py	(revision 12981)
@@ -1,3 +1,3 @@
- #!/usr/bin/python
+#!/usr/bin/python
 #
 # Dominik Neise, Werner Lustermann
@@ -6,5 +6,6 @@
 import numpy as np
 import matplotlib.pyplot as plt
-#import * from fir_filter
+from generator import *
+from fir_filter import *
 
 class GlobalMaxFinder(object):
@@ -23,13 +24,20 @@
         
     def __call__(self, data):
-        time = np.argmax( data[ : , self.min:self.max ], 1)
-        amplitude = np.max( data[ : , self.min:self.max], 1)
-        return amplitude, time
+        if data.ndim > 1:
+            time = np.argmax( data[ : , self.min:self.max ], 1)
+            amplitude = np.max( data[ : , self.min:self.max], 1)
+        else:
+            time = np.argmax( data[self.min:self.max])
+            amplitude = np.max( data[self.min:self.max])
+        return amplitude, time+self.min
 
     def __str__(self):
         s = self.name + '\n'
         s += 'window:\n'
-        s += '(min,max) = (' + str(self.min) + ',' + str(self.max) + ')\n'
+        s += '(min,max) = (' + str(self.min) + ',' + str(self.max) + ')'
         return s
+        
+    def test(self):
+        pass
 
 
@@ -49,10 +57,10 @@
         for pixel in range( data.shape[0] ):
             integral[pixel] = data[pixel, self.min:self.max].sum()
-        return integtral
+        return integral
 
     def __str__(self):
         s = self.name + '\n'
         s += 'window:\n'
-        s += '(min,max) = (' + str(self.min) + ',' + str(self.max) + ')\n'
+        s += '(min,max) = (' + str(self.min) + ',' + str(self.max) + ')'
         return s    
 
@@ -74,6 +82,6 @@
         for pix_data in data:
             hits = []
-            for i in range( data.shape[1] ):
-                if ( slope > 0 ):
+            for i in range( data.shape[1]-1 ):
+                if ( self.slope > 0 ):
                     if ( pix_data[i] > 0 ):
                         continue
@@ -99,12 +107,82 @@
 
 
+def plotter(signal, text):
+    x=range(len(signal))
+    ax = plt.plot(x, signal, 'b.', label='signal')
+    plt.title(text)
+    plt.xlabel('sample')
+    plt.legend()
+    plt.grid(True)
+    plt.show()
+    
+def histplotter(signal, text):
+    plt.xlabel('time of zero crossing')
+    plt.title(text)
+    plt.axis([0, 300,0,1440])
+    plt.grid(True)
+    n, bins, patches = plt.hist(signal, 3000, facecolor='r', alpha=0.75)
+    plt.show()
+
 
 if __name__ == '__main__':
     """ test the extractors """
+    sg = SignalGenerator()
+    pulse_str = 'len 300 bsl -0.5 noise 0.5 triangle 10 65 8 100' 
+    pulse = sg(pulse_str)
+    event = []
+    for i in range(1440):
+        event.append(sg(pulse_str))
+    event = np.array(event)
+    print 'test event with 1000 pixel generated, like this:'
+    print pulse_str
+    print
     
-    gmf = GlobalMaxFinder((12,40))
+    # Test GlobalMaxFinder
+    gmf = GlobalMaxFinder(30,250)
     print gmf
-    fwi = FixedWindowIntegrator(1,3)
+    amplitude, time = gmf(event)
+    if abs(amplitude.mean() - 10) < 0.5:
+        print "Test 1: OK GlobalMaxFinder found amplitude correctly", amplitude.mean()
+    if abs(time.mean() - 65) < 2:
+        print "Test 1: OK GlobalMaxFinder found time correctly", time.mean()
+    else:
+        print "BAD: time mean:", time.mean()
+    
+    print 
+    
+    # Test FixedWindowIntegrator
+    fwi = FixedWindowIntegrator(50,200)
     print fwi
+    integral = fwi(event)
+    #value of integral should be: 150*bsl + 8*10/2 + 100*10/2 = 465
+    if abs( integral.mean() - 465) < 2:
+        print "Test 2: OK FixedWindowIntegrator found integral correctly", integral.mean()
+    else:
+        print "Test 2:  X FixedWindowIntegrator integral.mean failed:", integral.mean()
+    
+    print
+    cfd = CFD()
+    sa = SlidingAverage(8)
+    print sa
+    cfd_out = sa(event)
+    cfd_out = cfd(cfd_out   )
+    cfd_out = sa(cfd_out)
     zx = ZeroXing()
     print zx
+    list_of_list_of_times = zx(cfd_out)
+    times = []
+    for list_of_times in list_of_list_of_times:
+        times.extend(list_of_times)
+    times = np.array(times)
+    
+    hist,bins = np.histogram(times,3000,(0,300))
+    most_probable_time = np.argmax(hist)
+    print 'most probable time of zero-crossing', most_probable_time/10.
+    print 'this includes filter delays ... for average filter setting 8 this turns out to be 78.8 most of the time'
+    
+    #histplotter(times.flatten(), 'times.flatten()')
+    #plotter(cfd_out[0], 'cfd_out')
+    #plotter (pulse, pulse_str)
+    
+
+