In [62]:

    

%matplotlib inline

import flowtools
from collections import defaultdict
import glob
from datetime import datetime


    

In [63]:

    

files = glob.glob("hpcf-flows/2011-10-26/ft-*")
files[:10]


    

    
Out[63]:





['hpcf-flows/2011-10-26/ft-v05.2011-10-26.001000-0400',
 'hpcf-flows/2011-10-26/ft-v05.2011-10-26.002000-0400',
 'hpcf-flows/2011-10-26/ft-v05.2011-10-26.003000-0400',
 'hpcf-flows/2011-10-26/ft-v05.2011-10-26.004500-0400',
 'hpcf-flows/2011-10-26/ft-v05.2011-10-26.005500-0400',
 'hpcf-flows/2011-10-26/ft-v05.2011-10-26.010000-0400',
 'hpcf-flows/2011-10-26/ft-v05.2011-10-26.011500-0400',
 'hpcf-flows/2011-10-26/ft-v05.2011-10-26.012000-0400',
 'hpcf-flows/2011-10-26/ft-v05.2011-10-26.013500-0400',
 'hpcf-flows/2011-10-26/ft-v05.2011-10-26.015000-0400']

In [64]:

    

#flowset = (flowfile for flowfile in files[0])


    

In [65]:

    

total = defaultdict(int)

hourly = []
for i in range(24):
    hourly.append(defaultdict(int))

count = 0
for flowfile in files:
    for flow in flowtools.FlowSet(flowfile):
        srcIP = flow.srcaddr
        dstIP = flow.dstaddr
        timestamp = datetime.fromtimestamp(flow.unix_secs)
        octets = flow.dOctets
        hourly [timestamp.hour][(srcIP, dstIP)] += octets
        total[(srcIP, dstIP)] += octets
        #count += 1
        #if count > 1000:
        #    break


    

In [66]:

    

toplot = []

pairs = [(bytes, pair) for (pair, bytes) in total.items()]

pairs.sort(reverse=True)

flows = []
data = np.zeros((10,24))

count = 0
for bytes, pair in pairs[:10]:
    flows.append( pair)
    for i in range(len(hourly)):
        data[count,i] = hourly[i][pair]
    count += 1


    

In [67]:

    

data.shape


    

    
Out[67]:





(10, 24)

In [68]:

    

ind = np.arange(24)
bottom = np.cumsum(data, axis=0)
d_colors = ['#2166ac',
                '#fee090',
                '#fdbb84',
                '#fc8d59',
                '#e34a33',
                '#b30000',
                '#777777','#ff3333', '#33ff33', '#3333ff', '#33ffff']
plt.bar(ind, data[0], color=d_colors[0])
for j in xrange(1, data.shape[0]):
    plt.bar(ind, data[j], bottom=bottom[j-1], color=d_colors[j])
plt.legend( flows ,loc=(1.1,0.1))


    

    
Out[68]:





<matplotlib.legend.Legend at 0x1052f4050>






    

In [68]:

    




    

In [68]: