if args.file:
inf = open(args.file, "r")
else:
inf = sys.stdin
rc = csv.reader(inf)
timestamps = dict()
value = dict()
def isnum(x):
return re.match(r'[0-9.]+', x)
val = ""
for row in rc:
r = csv_formats.parse_csv_row(row)
if r is None:
continue
ts, cpu, event, val = r.ts, r.cpu, r.ev, r.val
if event not in assigned:
level = gen_level.get_level(event)
assigned[event] = cur_colors[level][0]
cur_colors[level] = cur_colors[level][1:]
if len(cur_colors[level]) == 0:
cur_colors[level] = all_colors
value[event] = []
timestamps[event] = []
timestamps[event].append(float(ts))
try:
value[event].append(float(val.replace("%","")))
except ValueError:
inf = open(args.file, "r")
else:
inf = sys.stdin
rc = csv.reader(inf)
timestamps = dict()
value = dict()
def isnum(x):
return re.match(r'[0-9.]+', x)
val = ""
for row in rc:
r = csv_formats.parse_csv_row(row)
if r is None:
continue
ts, cpu, event, val = r.ts, r.cpu, r.ev, r.val
if event not in assigned:
level = gen_level.get_level(event)
assigned[event] = cur_colors[level][0]
cur_colors[level] = cur_colors[level][1:]
if len(cur_colors[level]) == 0:
cur_colors[level] = all_colors
value[event] = []
timestamps[event] = []
timestamps[event].append(float(ts))
try:
value[event].append(float(val.replace("%", "")))
except ValueError:
events = collections.OrderedDict()
out = []
times = []
cpus = []
rc = csv.reader(args.inputfile)
res = []
writer = csv.writer(args.output, lineterminator='\n')
lastcpu = None
cpu = None
lineno = 1
for row in rc:
if len(row) > 0 and (row[0] == "Timestamp" or row[0].startswith("#")):
lineno += 1
continue
r = csv_formats.parse_csv_row(row, error_exit=args.error_exit)
if r is None:
print("at line %d" % lineno, file=sys.stderr)
lineno += 1
continue
ts, cpu, ev, val = r.ts, r.cpu, r.ev, r.val
if ts != timestamp or (cpu != lastcpu and not args.normalize_cpu):
if timestamp:
if args.cpu and cpu != args.cpu:
continue
# delay in case we didn't see all headers
# only need to do that for toplev, directly output for perf?
# could limit buffering to save memory?
out.append(res)
times.append(timestamp)