def tx_time(self, nbytes=1500):
return bits.tx_time(self.idx, self.probability, nbytes)
def tx_time(self, nbytes=1500):
return bits.tx_time(self.idx, self.probability, nbytes)
def tx_time(self):
prob = self.probability / (1 << self.alg.SCALE)
return bits.tx_time(self.idx, prob, self.alg.NBYTES)
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)]
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)
ax.spines['top'].set_visible(False)
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)
ax.spines['top'].set_visible(False)
def tx_time(self):
prob = self.probability / (1 << self.alg.SCALE)
return bits.tx_time(self.idx, prob, self.alg.NBYTES)