-Fixed extraction of complex values from PCAP file;

-Added comments;
-Plotted apertif_unb1_correlator output from hardware:
 . We can see correlation matrices with almost correc phases, but in
   the wrong place and with wrong phase ranges.
 . Overall the plots look good given the fact that we're using wrong
   filter coefficients.

applications/apertif/designs/apertif_unb1_correlator/tb/python/tc_apertif_unb1_correlator_offload.py

@@ -25,8 +25,13 @@ Purpose:
 Description:
 . Processes PCAP dump files stored by e.g. tcpdump.
 Usage:
-. Capture a PCAP file: sudo /usr/sbin/tcpdump -vvxSnelfi eth1 -n dst port 4000 -c 1000 -w ~/apertif_unb1_correlator_offload.dump
-  
+. Capture a PCAP file: 
+  . sudo /usr/sbin/tcpdump -vvxSnelfi eth1 -n dst port 4000 -c 1000 -w ~/apertif_unb1_correlator_offload.dump
+. Examine a PCAP file with this script:
+  . python tc_apertif_unb1_correlator_offload.py ~/apertif_unb1_correlator_offload.dump
+Extra:
+. Print back a dumped PCAP file to the screen (example: 1 packet, -c 1):
+  . sudo /usr/sbin/tcpdump -e -c 1 -vvX -r ~/apertif_unb1_correlator_offload.dump 
 """
 
 import struct
@@ -47,7 +52,7 @@ def dumpfile_to_array(dumpfile):
     # Strip off the PCAP header
     pcap_global_hdr_raw = f.read(24)
 
-    for packet in range(64): # FIXME: 64 packets (channels) maar mag ook veelvoud van 64ch zijn.
+    for packet in range(960): # 960 channels = 15 integration periods of 64 channels.
         pcap_pkt_hdr_raw = f.read(16)
         eth_hdr_raw = f.read(14)
         ip_hdr_raw = f.read(20)
@@ -143,14 +148,15 @@ def dumpfile_to_array(dumpfile):
         # Visibilities: 300 visibilities * 32b complex (64b total) = 600 
         #               little endian signed integers.
         ###########################################################################
-        visibilities_struct = struct.unpack('>600i', visibilities_raw)
+        visibilities_struct = struct.unpack('600i', visibilities_raw)
 
         # Split the 600-word list into a 300-tuple list
         visibilities_tuples = split_list(visibilities_struct, 2)
 
         # Convert the tuples to complex
-        visibilities_complex = [complex(*i) for i in visibilities_tuples]
+        visibilities_complex = [complex(i[0],i[1]) for i in visibilities_tuples]
 
+        # Print the complex values
         for i,v in enumerate(visibilities_complex):
             print 'Packet', packet, '-', 'Visibility %03d              ' %i, v
 
@@ -167,8 +173,12 @@ if __name__ == '__main__':
     # Read the dump file and pour it visibility content in a 2d array
     dump_arr = dumpfile_to_array(sys.argv[1])
 
+    # Split the list into sublists of 64 channels (one integration period)
+    integration_periods = split_list(dump_arr, 64)
+
+    for integration_period in integration_periods:
         # The correlator outputs channels in the same order as the FFT, so reorder first:
-    integration_period = fft_reorder(dump_arr)
+        reordered_integration_period = fft_reorder(integration_period)
         # Plot the phase shifts
-    plot_phase_shifts(integration_period, NOF_VISIBILITIES)
+        plot_phase_shifts(reordered_integration_period, NOF_VISIBILITIES)