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Markus Feldmann 2009-05-21 konvertiere Daten

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1. #!/usr/bin/env python
2. # encoding: utf8
3. #
4. # Autor: Markus Feldmann
5. #
6.  
7. import wx
8. from matplotlib.figure import Figure
9. from matplotlib.backends.backend_wxagg import FigureCanvasWxAgg
10. import cPickle
11. import pickle
12. import time
13. import numpy
14. import os
15.  
16. class HistoApp(wx.App):
17.     def OnInit(self):
18.         f_daten = file('../../../peakdaten.dat','r')
19.         starttime, endtime, samp_rate = cPickle.load(f_daten)
20.         f_daten.close()
21.         wx.EVT_CLOSE(self, self.OnQuit)
22.         timescale, nitems = self.gettimescale(starttime, endtime)
23.         print "Mehrfrequente Messung",\
24.             "\nStartzeit: ",time.ctime(float(starttime)),\
25.             "\nEndzeit: ",time.ctime(float(endtime)),\
26.             "\nGesamte Zeitspanne: ",float(endtime - starttime)," sek.",\
27.             "\nZeitdifferenz von Sample zum nächsten: ",float(timescale)," sek.",\
28.             "\nAnzahl Samples: ",nitems
29.         print 'Stufe 1'
30.         self.extrahierePeaks(starttime,endtime,timescale,nitems)
31.         print 'Stufe 2'
32.         self.frame = HistoFrame(parent=None,\
33.                                     title='Histogramm einer Mehrfrequenten Impulsmessung',\
34.                                     size=(640, 480))
35.         self.frame.Show()
36.         return True
37.    
38.     def gettimescale(self,starttime, endtime):
39.         filename = '../../../peakdetektor1.hex'
40.         file_size = os.path.getsize(filename)
41.         nitems = 0
42.         nitems = file_size
43.         if nitems is not 0:
44.             #Zeitabstand von einem Sample zum naechsten
45.             timescale = float(endtime - starttime)/float(nitems)
46.         else:
47.             timescale = float(endtime - starttime)
48.         return timescale, nitems
49.    
50.     def extrahierePeaks(self,starttime,endtime,timescale,nitems):
51.         f_output = open('../../../peakswerteundzeit.dat','wb')
52.         f_p_1 = open('../../../peakdetektor1.hex','rb')
53.         f_p_2 = open('../../../peakdetektor2.hex','rb')
54.         f_p_3 = open('../../../peakdetektor3.hex','rb')
55.         f_pv_1 = open('../../../peakband1.hex','rb')
56.         f_pv_2 = open('../../../peakband2.hex','rb')
57.         f_pv_3 = open('../../../peakband3.hex','rb')
58.         a_p_1 = numpy.fromfile(f_p_1,dtype='b',count=-1)
59.         a_p_2 = numpy.fromfile(f_p_2,dtype='b',count=-1)
60.         a_p_3 = numpy.fromfile(f_p_3,dtype='b',count=-1)
61.         a_pv_1 = numpy.fromfile(f_pv_1,dtype='f',count=-1)
62.         a_pv_2 = numpy.fromfile(f_pv_2,dtype='f',count=-1)
63.         a_pv_3 = numpy.fromfile(f_pv_3,dtype='f',count=-1)
64.         i = 0
65.         a_time = []
66.         a_a = []
67.         a_b = []
68.         a_c = []
69.         a_ar = []
70.         a_ai = []
71.         a_br = []
72.         a_bi = []
73.         a_cr = []
74.         a_ci = []
75.         while i <= nitems-1:
76.             if (a_p_1[i] or a_p_2[i] or a_p_3[i]):
77.                 a_time += [timescale*i]
78.                 a_a.append(a_p_1[i])
79. #                 print "Mit i ist ",i," ergibt sich für a_p_1[i] ",a_p_1[i],\
80. #                     "und für a_a ",a_a[:]
81.                 a_b.append(a_p_2[i])
82.                 a_c.append(a_p_3[i])
83.                 a_ar.append(a_pv_1[i*2])
84.                 a_ai.append(a_pv_1[i*2+1])
85.                 a_br.append(a_pv_2[i*2])
86.                 a_bi.append(a_pv_2[i*2+1])
87.                 a_cr.append(a_pv_3[i*2])
88.                 a_ci.append(a_pv_3[i*2+1])
89.             i += 1
90.         cPickle.dump(a_time,f_output)
91.         cPickle.dump(a_a,f_output)
92.         cPickle.dump(a_b,f_output)
93.         cPickle.dump(a_c,f_output)
94.         cPickle.dump(a_ar,f_output)
95.         cPickle.dump(a_ai,f_output)
96.         cPickle.dump(a_br,f_output)
97.         cPickle.dump(a_bi,f_output)
98.         cPickle.dump(a_cr,f_output)
99.         cPickle.dump(a_ci,f_output)
100.         f_output.flush()
101.         f_output.close()
102.  
103.     def OnQuit(self):
104.         f_peaks_1.close()
105.         f_peaks_2.close()
106.         f_peaks_3.close()
107.         f_peakvalue_1.close()
108.         f_peakvalue_2.close()
109.         f_peakvalue_3.close()
110.        
111. class HistoFrame(wx.Frame):
112.     def __init__(self, *args, **kwargs):
113.         wx.Frame.__init__(self, *args, **kwargs)
114.         self.Bind(wx.EVT_MENU, self.onQuit, id=105)
115.         self.makeMenu()
116.         self.graphWindow = GraphWindow(self)
117.  
118.     def makeMenu(self):
119.         menubar = wx.MenuBar()
120.         file = wx.Menu()
121.         quit = wx.MenuItem(file, 105, '&Quit\tCtrrl+Q', 'Quit the Application')
122.         file.AppendItem(quit)
123.         menubar.Append(file, '&File')
124.         self.SetMenuBar(menubar)
125.  
126.     def onQuit(self,event):
127.         self.Close()
128.  
129. class GraphWindow(wx.Window):
130.     def __init__(self, *args, **kwargs):
131.         wx.Window.__init__(self, *args, **kwargs)
132.         self.lines = []
133.         self.figure = Figure()
134.         self.canvas = FigureCanvasWxAgg(self, -1, self.figure)
135.         f_dat = open('../../../peakswerteundzeit.dat','rb')
136.         nitems = 2
137.         self.a_time = cPickle.load(f_dat)
138.         self.a_a = cPickle.load(f_dat)
139.         self.a_b = cPickle.load(f_dat)
140.         self.a_c = cPickle.load(f_dat)
141.         self.a_ar = cPickle.load(f_dat)
142.         self.a_ai = cPickle.load(f_dat)
143.         self.a_br = cPickle.load(f_dat)
144.         self.a_bi = cPickle.load(f_dat)
145.         self.a_cr = cPickle.load(f_dat)
146.         self.a_ci = cPickle.load(f_dat)
147.         self.draw(nitems)
148.  
149.     def draw(self,nitems):
150.         if not hasattr(self, 'subplot1'):
151.             self.subplot1 = self.figure.add_subplot(211)
152.             self.subplot2 = self.figure.add_subplot(212)
153.         a = numpy.array(self.a_a[0:nitems])
154.         b = numpy.array(self.a_b[0:nitems])
155.         c = numpy.array(self.a_c[0:nitems])
156.         d = numpy.array(self.a_time[0:nitems])
157.         print a, b, c, d, numpy.add(a,b)
158.         bar1 = self.subplot1.bar(d,a, color='red', edgecolor='red',align='edge')
159.         bar2 = self.subplot1.bar(d,b, color='green', edgecolor='green',align='edge',
160.                                  bottom=a)
161.         bar3 = self.subplot1.bar(d,c, color='blue', edgecolor='blue',align='edge',
162.                                  bottom=numpy.add(a,b))
163.  
164.        
165. if __name__ == '__main__':
166.     app = HistoApp(0)
167.     app.MainLoop()

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