import argparse import csv import re import matplotlib import matplotlib.pyplot as plt parser = argparse.ArgumentParser() parser.add_argument("file", help="Input file with queue levels") parser.add_argument("--include-filter", help="Regular expression for element:pad names that should be included") parser.add_argument("--exclude-filter", help="Regular expression for element:pad names that should be excluded") parser.add_argument("--no-latency", help="do not include latency (enabled by default)", action="store_true") args = parser.parse_args() include_filter = None if args.include_filter is not None: include_filter = re.compile(args.include_filter) exclude_filter = None if args.exclude_filter is not None: exclude_filter = re.compile(args.exclude_filter) pads = {} with open(args.file, mode='r', encoding='utf_8', newline='') as csvfile: reader = csv.reader(csvfile, delimiter=',', quotechar='|') for row in reader: if len(row) != 7: continue if include_filter is not None and not include_filter.match(row[1]): continue if exclude_filter is not None and exclude_filter.match(row[1]): continue if not row[1] in pads: pads[row[1]] = { 'buffer-clock-time': [], 'pipeline-clock-time': [], 'lateness': [], 'latency': [], } wallclock = float(row[0]) / 1000000000.0 pads[row[1]]['buffer-clock-time'].append((wallclock, float(row[3]) / 1000000000.0)) pads[row[1]]['pipeline-clock-time'].append((wallclock, float(row[4]) / 1000000000.0)) pads[row[1]]['lateness'].append((wallclock, float(row[5]) / 1000000000.0)) pads[row[1]]['latency'].append((wallclock, float(row[6]) / 1000000000.0)) matplotlib.rcParams['figure.dpi'] = 200 prop_cycle = plt.rcParams['axes.prop_cycle'] colors = prop_cycle.by_key()['color'] fig, ax1 = plt.subplots() ax1.set_xlabel("wallclock (s)") ax1.set_ylabel("time (s)") ax1.tick_params(axis='y') for (i, (pad, values)) in enumerate(pads.items()): # cycle colors i = i % len(colors) ax1.plot( [x[0] for x in values['lateness']], [x[1] for x in values['lateness']], '.', label = '{}: lateness'.format(pad), color = colors[i], ) if not args.no_latency: ax1.plot( [x[0] for x in values['latency']], [x[1] for x in values['latency']], '-', label = '{}: latency'.format(pad), color = colors[i], ) fig.tight_layout() plt.legend(loc='best') plt.show()