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.. currentmodule:: mlpy
Dynamic Time Warping (DTW)
==========================
Standard DTW
------------
.. autofunction:: dtw_std(x, y, dist_only=True)
Example
Reproducing the Fig. 2 example in [Salvador04]_.
>>> import mlpy
>>> import matplotlib.pyplot as plt
>>> import matplotlib.cm as cm
>>> x = [0,0,0,0,1,1,2,2,3,2,1,1,0,0,0,0]
>>> y = [0,0,1,1,2,2,3,3,3,3,2,2,1,1,0,0]
>>> dist, cost, path = mlpy.dtw_std(x, y, dist_only=False)
>>> dist
0.0
>>> fig = plt.figure(1)
>>> ax = fig.add_subplot(111)
>>> plot1 = plt.imshow(cost.T, origin='lower', cmap=cm.gray, interpolation='nearest')
>>> plot2 = plt.plot(path[0], path[1], 'w')
>>> xlim = ax.set_xlim((-0.5, cost.shape[0]-0.5))
>>> ylim = ax.set_ylim((-0.5, cost.shape[1]-0.5))
>>> plt.show()
.. image:: images/dtw.png
.. [Salvador04] S Salvador and P Chan. FastDTW: Toward Accurate Dynamic Time Warping in Linear Time and Space. 3rd Wkshp. on Mining Temporal and Sequential Data, ACM KDD '04, 2004.
Subsequence DTW
---------------
.. autofunction:: dtw_subsequence(x, y)
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