def plotVectors(json, coincidence=0, name="", minTime=30, maxTime=1700,
labels=False):
delims = readDelims()
macAddresses = {}
json["packets"].apply(lambda row: addPacket(row, macAddresses), axis=1)
sum = np.zeros(json["last"], dtype=np.int)
for val in macAddresses.values():
diff = val[1] - val[0]
if ((diff > minTime) and (diff < maxTime) and (val[2] >= coincidence)):
sum[val[0]: val[1]] += 1
plot.xlabel('Seconds since start')
plot.ylabel('Devices', color='b')
plot.step(range(int(json["last"])), sum.tolist())
actual = [stop['actual'] for stop in delims]
stopx = [stop['start'] for stop in delims]
ax2 = plot.twinx()
ax2.step(stopx, actual, 'r', where="post")
(t1.set_color for t1 in ax2.get_yticklabels())
ax2.set_ylabel('Riders', color='r')
plot.ylim(0, 30)
plot.xlim(0, json["last"])
if(labels):
for stop in delims:
annotate(stop["code"], stop["start"], stop["actual"], 10, 10)
makeWidePlot("bus", "vectors")
plot.show()
def plotPacketHistogram(jason, cutoff=120):
macAddresses = {}
jason["packets"].apply(lambda row: addPacket(row, macAddresses), axis=1)
packetAxis = [val[2] for val in macAddresses.values()
if (val[0]+jason["last"]-val[1]) < cutoff]
xmax = len(packetAxis)
plot.xlim(0, xmax)
plot.yscale('log')
plot.bar(range(xmax), sorted(packetAxis), color="black", log=True)
plot.xlabel("Unique MAC addresses present for the entire class period")
plot.ylabel('Number of Packets seen for each MAC address')
plot.title('April 7th, Classroom Packet Distribution')
graphlib.makeWidePlot("class","packethist")
plot.show()