mb=[]
t=[]
with open(ad,'r') as f:
k=0
for line in f:
if k==0:
k=1
continue
mb.append(float(line.split(',')[3]))
t.append(float(line.split(',')[1]))
down=down+mb
t,a1=order(t,mb)
xmin=min(min(t),xmin)
xmax=max(max(t),xmax)
tt.append(t)
out.append(eventDetection(a1,num.std(a1),l,p))
pl.subplot(2,2,pn)
pn=pn+1
pl.plot(t,a1)
pl.xlabel('Time',fontsize=20)
pl.suptitle('Download Throughput for different uos in comcast',fontsize=20)
pl.show()
#~ f, (ax1, ax2) = pl.subplots(2, sharex=True, sharey=False)
#~ ax1.plot(range(len(a1)),a1)
#~ pl.ylabel('Sequence Magnitude',fontsize=20)
#~ pl.xlabel('Sample Number',fontsize=20)
for j in [0,1,2,3]:
pl.subplot(2,2,j)
for w in out[j]:
if w[1]>0 :
pl.vlines(tt[j][w[0]],0,abs(w[1]),color='green',linewidths=4)
p=.01
N=3000
mu, sigma, n = 0, 1, N
a = num.random.normal(mu,sigma,n)
#~ diff=sigDiff(sigma,l) # has to be replaced by t-statistics
#~ print diff
a[100:140]=a[100:140]-2
a[200:227]=a[200:227]+2
a[260]=-5.0
a[500:520]=a[500:520]+1
a[670:700]=a[670:700]-2
a[1000:1500]=a[1000:1500]+1
a[2000:2227]=a[2000:2227]-5
a[2227:2500]=a[2227:2500]+3
#~ a,ev1=genEvent(l,.1,1,.1)
out=eventDetection(a,1,l,p)
f, (ax1, ax2) = pl.subplots(2, sharex=True, sharey=False)
ax1.plot(range(len(a)),a)
pl.ylabel('Sequence Magnitude',fontsize=20)
pl.xlabel('Sample Number',fontsize=20)
for w in out:
if w[1]>0 :
ax2.vlines(w[0],0,abs(w[1]),color='green',linewidths=4)
else:
ax2.vlines(w[0],0,abs(w[1]),color='red',linewidths=4)
pl.ylabel('Event Power',fontsize=20)
f.subplots_adjust(hspace=0)
pl.setp([a.get_xticklabels() for a in f.axes[:-1]], visible=False)
pl.show()
