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()