def main():
parser = argparse.ArgumentParser(description=__doc__)
parser.add_argument('--metrics', metavar='M[,M]*', default=defaultMetrics,
help='Comma separated list of metrics to print. ' + metricsDescription)
parser.add_argument('--avg', metavar='N', type=int, default=1,
help='Print average every N records.')
parser.add_argument('--start', metavar='T', type=float, default=0,
help='Start trace at time T (drop records with compute start before T ms).')
parser.add_argument('--gp', action='store_true', help='Print GNUPlot format.')
parser.add_argument('--no-header', action='store_true', help='Omit the header row.')
parser.add_argument('name', metavar='filename', help='Trace file.')
args = parser.parse_args()
metrics = args.metrics.split(',')
count = args.gp and (not hasTimestamp(metricts) or len(metrics) == 1)
if not args.no_header:
pu.printHeader(allMetrics, metrics, args.gp, count)
with open(args.name) as f:
trace = json.load(f)
if args.start > 0:
trace = skipTrace(trace, args.start)
trace = pu.filterData(trace, allMetrics, metrics)
if args.avg > 1:
trace = avgData(trace, args.avg, hasTimestamp(metrics))
pu.printCsv(trace, count)
def main():
parser = argparse.ArgumentParser(description=__doc__)
parser.add_argument('--features', metavar='F[,F]*', default=defaultFeatures,
help='Comma separated list of features to print. ' + featuresDescription)
parser.add_argument('--total', action='store_true', help='Add total time row.')
parser.add_argument('--gp', action='store_true', help='Print GNUPlot format.')
parser.add_argument('--no-header', action='store_true', help='Omit the header row.')
parser.add_argument('--threshold', metavar='T', default=0.0, type=float,
help='Threshold of percentage difference.')
parser.add_argument('--reference', metavar='R', help='Reference profile file name.')
parser.add_argument('name', metavar='filename', help='Profile file.')
args = parser.parse_args()
global allFeatures
features = args.features.split(',')
for f in features:
if not f in allFeatures:
print('Feature {} not recognized'.format(f))
return
count = args.gp and not hasNames(features)
profile = None
reference = None
with open(args.name) as f:
profile = json.load(f)
profileCount = profile[0]['count']
profile = profile[1:]
if args.reference:
with open(args.reference) as f:
reference = json.load(f)
referenceCount = reference[0]['count']
reference = reference[1:]
allFeatures = mergeHeaders(allFeatures)
features = mergeHeaders(features, hasNames(features))
if not args.no_header:
if reference:
comment = '#' if args.gp else ''
print(comment + 'reference count: {} - profile count: {}'.format(referenceCount, profileCount))
pu.printHeader(allFeatures, features, args.gp, count)
if reference:
profile = alignData(reference, profile, args.threshold)
if args.total:
profile.append(totalData(allFeatures, profile))
if reference:
total = profile[len(profile) - 1]
total['% difference'] = (total['averageMs'] / total['refAverageMs'] - 1)*100
profile = pu.filterData(profile, allFeatures, features)
pu.printCsv(profile, count)