Ejemplo n.º 1
0
        [1, 0.5, 0.2, .1, .06, .03, .025, .02, .015, .01, .008, .007])
    ns = np.zeros(dts.shape)
    ptimes = np.zeros(dts.shape)
    ctimes = np.zeros(dts.shape)

    for i in range(len(dts)):
        M = getexamplematrix(dts[i])
        ns[i] = M.shape[0]
        print "N=%i" % ns[i]
        start = time.time()
        dtw(M)
        end = time.time()
        ptimes[i] = end - start

        start = time.time()
        cdtw.cdtw(M)
        end = time.time()
        ctimes[i] = end - start

plt.subplot(2, 1, 1)
pl.plot(ns, ptimes, '*-', color="blue", linewidth=4, label="python")
pl.plot(ns, ctimes, '*-', color="red", linewidth=4, label="c")
#pl.xlabel( 'matrix size')
pl.ylabel('runtime (sec)')
#lpl.legend()

plt.subplot(2, 1, 2)
pl.plot(ns, np.sqrt(ptimes), '*-', color="blue", linewidth=4, label="python")
pl.plot(ns, np.sqrt(ctimes), '*-', color="red", linewidth=4, label="c")
pl.xlabel('matrix size')
pl.ylabel(r'sqrt(runtime)')
Ejemplo n.º 2
0
    ns=np.zeros(dts.shape)
    ptimes=np.zeros(dts.shape)
    ctimes=np.zeros(dts.shape)


    for i in range(len(dts)):
        M=getexamplematrix( dts[i] )
        ns[i]=M.shape[0]
        print "N=%i"%ns[i]
        start=time.time()
        dtw(M)
        end=time.time()
        ptimes[i]=end-start

        start=time.time()
        cdtw.cdtw(M)
        end=time.time()
        ctimes[i]=end-start


plt.subplot(2,1,1)
pl.plot( ns,ptimes, '*-', color="blue", linewidth=4, label="python")
pl.plot( ns,ctimes, '*-', color="red", linewidth=4, label="c")
#pl.xlabel( 'matrix size')
pl.ylabel( 'runtime (sec)')
#lpl.legend()

plt.subplot(2,1,2)
pl.plot( ns,np.sqrt(ptimes), '*-', color="blue", linewidth=4, label="python")
pl.plot( ns,np.sqrt(ctimes), '*-', color="red", linewidth=4, label="c")
pl.xlabel( 'matrix size')
Ejemplo n.º 3
0
import numpy as np
import cdtw
import plotdtw

dt=0.2
M=plotdtw.getexamplematrix(dt)
p=cdtw.cdtw(M)

plotdtw.plotdtw( M, np.row_stack((p[1,:],p[0,:])))
Ejemplo n.º 4
0
import numpy as np
import cdtw
import plotdtw

dt = 0.2
M = plotdtw.getexamplematrix(dt)
p = cdtw.cdtw(M)

plotdtw.plotdtw(M, np.row_stack((p[1, :], p[0, :])))