def algortihmtest(metric_c, argvL):
limit_length = [0,30]
metric_command = metric_c
argvList = argvL
[split_data, split_rssi, pilot_step] = pds.simulated_tracebase(metric_command, argvList)
[pilot_data_alltrace, pilot_ser_alltrace] = pds.simulated_pilot_generate(split_data, split_rssi, pilot_step, metric_command, argvList)
other_data_alltrace = pds.simulated_unkonw_symbol(split_data, split_rssi, pilot_step, metric_command, argvList)
unkonwSymbolp = pds.UnkonwSymbolPayload(split_data, pilot_step)
# print len(split_data), len(split_rssi), len(pilot_data_alltrace), len(pilot_ser_alltrace), len(other_data_alltrace), len(unkonwSymbolp)
print '[+]start est_ser'
est_ser = estimate_ser(pilot_data_alltrace, pilot_ser_alltrace, other_data_alltrace, limit_length, argvList[0] * 2 +1)
# print 'start gt_ser'
# gt_ser = groudtruth(unkonwSymbolp, limit_length)
# print 'rstart rt_err'
# print '[est]',len(est_ser[0]), '[gt]:', len(gt_ser[0])
# rt_err = relatederror(est_ser, gt_ser)
# for i in range(len(rt_err)):
# print "%d:" % (i), rt_err[i][len(rt_err[i])-1]
# print '[debug]write no diff rssi data trace'
other_nodiff_data_trace = pds.simulated_unkonw_symbol(split_data, split_rssi, pilot_step, metric_command, argvList)
gr.print_gnuplot(est_ser, unkonwSymbolp,other_nodiff_data_trace,limit_length)
# print '[debug]write detailed result'
print_detail_result(est_ser, unkonwSymbolp, other_nodiff_data_trace, limit_length,metric_command)
# print '[debug]print rssi info'
print_split_trace(split_data, split_rssi, pilot_step, limit_length)
# print "[!]calc metric"
[accur_alltrace, detailAccur_alltrace] = Calc_metric(est_ser, unkonwSymbolp,limit_length)
ave_tppreci = 0; ave_tnpreci = 0; avetn_recall = 0
for i in range(len(accur_alltrace)):
# print "%d:[preci]%s, [tp_rec]:%s,[tn_rec]%s, [tp_pre]%s, [tn_pre]%s" %\
# (i, str(accur_alltrace[i][0]), accur_alltrace[i][1],
# str(accur_alltrace[i][2]), str(accur_alltrace[i][3]), str(accur_alltrace[i][4])),
# print "[fp]:%s, [fn]:%s, [tp]:%s, [tn]:%s" % (str(detailAccur_alltrace[i][0]),str(detailAccur_alltrace[i][1]),str(detailAccur_alltrace[i][2]),str(detailAccur_alltrace[i][3]) )
ave_tppreci += accur_alltrace[i][3]
ave_tnpreci += accur_alltrace[i][4]
avetn_recall += accur_alltrace[i][2]
print '[metrics]:%s_%s{%s-%s}, [ave_tpprecision]:%s, [ave_tnpreci]%s, [ave_tnrecall]:%s' % \
( limit_length[0], limit_length[1],
metric_command, str(argvList[0]),
str(ave_tppreci/len(accur_alltrace)), str(ave_tnpreci/ len(accur_alltrace)), str(avetn_recall/len(accur_alltrace)))
def allrssitrace():
[split_data, split_rssi, pilot_step] = pds.simulated_tracebase(True)
intofile = []
for i in range(34, 35):
tempstr = []
for j in range(len(split_data[i])):
tempstr.append('%d ' % (j))
if split_data[i][j] == '0':
tempstr.append('210 ')
else:
tempstr.append('245 ')
ft = split_rssi[i][j]
tempstr.append(str(ft) + '\n')
intofile.extend(''.join(tempstr))
# [dataTrace, rssiTrace] = scaledRSSI(dataTrace, rssiTrace)
f = open('rssi_data.txt', 'w')
f.writelines(intofile)
f.close()
def allrssitrace():
[split_data, split_rssi, pilot_step] = pds.simulated_tracebase(True)
intofile = []
for i in range(34,35):
tempstr = []
for j in range(len(split_data[i])):
tempstr.append('%d ' % (j))
if split_data[i][j] == '0':
tempstr.append('210 ')
else:
tempstr.append('245 ')
ft = split_rssi[i][j]
tempstr.append(str(ft) + '\n')
intofile.extend(''.join(tempstr))
# [dataTrace, rssiTrace] = scaledRSSI(dataTrace, rssiTrace)
f = open('rssi_data.txt', 'w')
f.writelines(intofile)
f.close()
def algortihmtest(metric_c, argvL):
limit_length = [0, 30]
metric_command = metric_c
argvList = argvL
[split_data, split_rssi,
pilot_step] = pds.simulated_tracebase(metric_command, argvList)
[pilot_data_alltrace, pilot_ser_alltrace
] = pds.simulated_pilot_generate(split_data, split_rssi, pilot_step,
metric_command, argvList)
other_data_alltrace = pds.simulated_unkonw_symbol(split_data, split_rssi,
pilot_step,
metric_command, argvList)
unkonwSymbolp = pds.UnkonwSymbolPayload(split_data, pilot_step)
# print len(split_data), len(split_rssi), len(pilot_data_alltrace), len(pilot_ser_alltrace), len(other_data_alltrace), len(unkonwSymbolp)
print '[+]start est_ser'
est_ser = estimate_ser(pilot_data_alltrace, pilot_ser_alltrace,
other_data_alltrace, limit_length,
argvList[0] * 2 + 1)
# print 'start gt_ser'
# gt_ser = groudtruth(unkonwSymbolp, limit_length)
# print 'rstart rt_err'
# print '[est]',len(est_ser[0]), '[gt]:', len(gt_ser[0])
# rt_err = relatederror(est_ser, gt_ser)
# for i in range(len(rt_err)):
# print "%d:" % (i), rt_err[i][len(rt_err[i])-1]
# print '[debug]write no diff rssi data trace'
other_nodiff_data_trace = pds.simulated_unkonw_symbol(
split_data, split_rssi, pilot_step, metric_command, argvList)
gr.print_gnuplot(est_ser, unkonwSymbolp, other_nodiff_data_trace,
limit_length)
# print '[debug]write detailed result'
print_detail_result(est_ser, unkonwSymbolp, other_nodiff_data_trace,
limit_length, metric_command)
# print '[debug]print rssi info'
print_split_trace(split_data, split_rssi, pilot_step, limit_length)
# print "[!]calc metric"
[accur_alltrace,
detailAccur_alltrace] = Calc_metric(est_ser, unkonwSymbolp, limit_length)
ave_tppreci = 0
ave_tnpreci = 0
avetn_recall = 0
for i in range(len(accur_alltrace)):
# print "%d:[preci]%s, [tp_rec]:%s,[tn_rec]%s, [tp_pre]%s, [tn_pre]%s" %\
# (i, str(accur_alltrace[i][0]), accur_alltrace[i][1],
# str(accur_alltrace[i][2]), str(accur_alltrace[i][3]), str(accur_alltrace[i][4])),
# print "[fp]:%s, [fn]:%s, [tp]:%s, [tn]:%s" % (str(detailAccur_alltrace[i][0]),str(detailAccur_alltrace[i][1]),str(detailAccur_alltrace[i][2]),str(detailAccur_alltrace[i][3]) )
ave_tppreci += accur_alltrace[i][3]
ave_tnpreci += accur_alltrace[i][4]
avetn_recall += accur_alltrace[i][2]
print '[metrics]:%s_%s{%s-%s}, [ave_tpprecision]:%s, [ave_tnpreci]%s, [ave_tnrecall]:%s' % \
( limit_length[0], limit_length[1],
metric_command, str(argvList[0]),
str(ave_tppreci/len(accur_alltrace)), str(ave_tnpreci/ len(accur_alltrace)), str(avetn_recall/len(accur_alltrace)))
