From 983df3163a56a9bf144200f1104fc110c4134e05 2013-01-08 22:53:56
From: Miguel Valdez <miguel.urco@jro.igp.gob.pe>
Date: 2013-01-08 22:53:56
Subject: [PATCH] test de la codificacion

---

diff --git a/schainpy/test/testcode.py b/schainpy/test/testcode.py
new file mode 100644
index 0000000..57562c5
--- /dev/null
+++ b/schainpy/test/testcode.py
@@ -0,0 +1,146 @@
+import numpy
+import scipy.signal
+import matplotlib
+matplotlib.use("TKAgg")
+import pylab as pl
+
+import time
+
+def getInverseFilter(code, lenfilter=None):
+    
+    nBauds = len(code)
+    
+    if lenfilter == None:
+        lenfilter = 10*nBauds
+    
+    codeBuffer = numpy.zeros((lenfilter), dtype=numpy.float32)
+    codeBuffer[0:nBauds] = code
+    
+    inverse_filter = numpy.real(numpy.fft.ifft(1.0/numpy.fft.fft(codeBuffer)))
+    inverse_filter = numpy.roll(inverse_filter, shift=120)
+    
+#    pl.plot(codeBuffer)
+#    pl.plot(inverse_filter)
+#    pl.show()
+    
+    return inverse_filter
+
+def getSignal(nChannels, nHeis):
+    
+    u = numpy.complex(1,2)
+    u  /= numpy.abs(u)
+    
+    signal = numpy.random.rand(nChannels, nHeis)
+    signal = signal.astype(numpy.complex)
+    
+    signal *= u
+    
+    return signal
+
+def time_decoding(signal, code):
+    
+    ini = time.time()
+    
+    nBauds = len(code)
+    nChannels, nHeis = signal.shape
+    datadec = numpy.zeros((nChannels, nHeis - nBauds + 1), dtype=numpy.complex)
+    
+    tmpcode = code.astype(numpy.complex)
+    #######################################
+    ini = time.time()
+        
+    for i in range(nChannels):
+        datadec[i,:] = numpy.correlate(signal[i,:], code, mode='valid')/nBauds
+    
+    print time.time() - ini
+    
+    return datadec
+
+def freq_decoding(signal, code):
+    
+    ini = time.time()
+    
+    nBauds = len(code)
+    nChannels, nHeis = signal.shape
+    
+    codeBuffer = numpy.zeros((nHeis), dtype=numpy.float32)
+        
+    codeBuffer[0:nBauds] = code
+    
+    fft_code = numpy.conj(numpy.fft.fft(codeBuffer)).reshape(1, -1)
+    
+    ######################################
+    ini = time.time()
+    
+    fft_data = numpy.fft.fft(signal, axis=1)
+    
+    conv = fft_data*fft_code
+    
+    data = numpy.fft.ifft(conv, axis=1)/nBauds
+    
+    datadec = data[:,:-nBauds+1]
+    
+    print time.time() - ini
+    
+    return datadec
+
+def fftconvol_decoding(signal, code):
+    
+    ini = time.time()
+    
+    nBauds = len(code)
+    nChannels, nHeis = signal.shape
+    datadec = numpy.zeros((nChannels, nHeis - nBauds + 1), dtype=numpy.complex)
+    
+    tmpcode = code.astype(numpy.complex)
+    #######################################
+    ini = time.time()
+        
+    for i in range(nChannels):
+        datadec[i,:] = scipy.signal.fftconvolve(signal[i,:], code[-1::-1], mode='valid')/nBauds
+    
+    print time.time() - ini
+    
+    return datadec
+
+def filter_decoding(signal, code):
+    
+    ini = time.time()
+    
+    nBauds = len(code)
+    nChannels, nHeis = signal.shape
+    
+    inverse_filter = getInverseFilter(code)
+    
+    datadec = numpy.zeros((nChannels, nHeis + len(inverse_filter) - 1), dtype=numpy.complex)
+    #######################################
+    ini = time.time()
+        
+    for i in range(nChannels):
+        datadec[i,:] = numpy.convolve(signal[i,:], inverse_filter, mode='full')
+    
+    datadec = datadec[:,120:120+nHeis]
+    
+    print time.time() - ini
+    
+    return datadec
+
+nChannels, nHeis = 8, 3900
+index = 300
+code = numpy.array([1, 1, -1, -1, -1, 1, 1, 1, -1, -1, -1, -1, -1, -1, -1, 1, -1, 1, -1, 1, 1, -1, 1, 1, -1, -1, 1, -1])
+signal = getSignal(nChannels, nHeis)
+signal[0,index:index+len(code)] = code*10
+
+signalout = time_decoding(signal, code)
+signalout1 = freq_decoding(signal, code)
+signalout2 = fftconvol_decoding(signal, code)
+signalout3 = filter_decoding(signal, code)
+
+#pl.plot(numpy.abs(signal[0]))
+pl.plot(numpy.abs(signalout[0]))
+#pl.plot(numpy.abs(signalout1[0]))
+#pl.plot(numpy.abs(signalout2[0]))
+pl.plot(numpy.abs(signalout3[0])+1.0)
+pl.show()
+
+        
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