title = "Bitrate plot from {}".format(os.path.basename(datfile)) dat = eval(open(datfile, "rt").read()) start, data, end = dat secs = (end - start) / 1e9 width = max(math.ceil(secs), 30) * 10 harness.WINDOW = (end - start) / width img = numpy.zeros((len(data), width)) best = numpy.zeros(width) idx = [0] * len(data) for i in range(0, width): t = (i + .5) / width * (end - start) + start ps = [harness.packet_stats(data[r], t, r) for r, _ in enumerate(data)] badnesses = [bits.tx_time(rix, p, 1500) for rix, p in enumerate(ps)] best[i] = perm[numpy.argmin(badnesses)] for j, p in enumerate(ps): img[perm[j], i] = p fig, ax = pylab.subplots() ax.set_xlim(0, secs) ax.set_ylim(-.5, 11.5) ax.set_xlabel("Time (s)") # Hide the right and top spines ax.spines['left'].set_visible(False) ax.spines['right'].set_visible(False)
def apply_rate(t): ps = [harness.packet_stats(data[r], t, r) for r, _ in enumerate(rates.RATES)] badnesses = [bits.tx_time(rix, p, 1500) for rix, p in enumerate(ps)] least_bad = min(enumerate(badnesses), key=lambda x: x[1]) return [(least_bad[0], 1)]