-Now plotting each of the 4 captured timesamples.

libraries/dsp/correlator/tb/python/tc_correlator.py

@@ -35,6 +35,7 @@ COMPLEX_WIDTH = 16
 NOF_INPUTS = 10
 NOF_OUTPUTS = NOF_INPUTS*(NOF_INPUTS+1)/2
 NOF_CHANNELS = 64
+NOF_TIMESAMPLES = 4
 
 #BUFFER_DEPTH = 256
 BUFFER_WIDTH = 64 #2*COMPLEX_WIDTH
@@ -55,17 +56,19 @@ for output_nr in range(NOF_OUTPUTS):
     data.append( db.read_data_buffer(streamNr=output_nr, n=2*256, radix='uns', width=BUFFER_WIDTH, nofColumns=12)[0] )
 
 ###############################################################################
-# 'data' is now a 2d array of [NOF_OUTPUTS][NOF_CHANNELS]. We want to group the
-# outputs by channel, so transpose this 2d array into [NOF_CHANNELS][NOF_OUTPUTS]
+# 'data' is now a 2d array of [NOF_OUTPUTS][NOF_TIMESAMPLES*NOF_CHANNELS]. We
+# want to group the outputs by channel, so transpose this 2d array into 
+# [NOF_TIMESAMPLES*NOF_CHANNELS][NOF_OUTPUTS]
 ###############################################################################
 data = transpose(data)
 
+for sample_nr in range(NOF_TIMESAMPLES):
     mat_list = []
     for channel_nr in range(NOF_CHANNELS):
         ###############################################################################
         # Convert the unsigned words to complex
         ###############################################################################
-    channel_data = data[channel_nr]
+        channel_data = data[sample_nr*NOF_CHANNELS+channel_nr]
         for index,word in enumerate(channel_data):
             word_bits = CommonBits(word, BUFFER_WIDTH)
             re = word_bits[BUFFER_WIDTH-1:BUFFER_WIDTH/2]