#ucrdtw
Python extension for UCR Suite highly optimized subsequence search using Dynamic Time Warping (DTW)
Based on the paper Searching and Mining Trillions of Time Series Subsequences under Dynamic Time Warping
More info on the UCR Suite web page http://www.cs.ucr.edu/~eamonn/UCRsuite.html
###Requirements Python 2.7, numpy 1.8
###Usage
import _ucrdtw
import numpy as np
import matplotlib.pyplot as plt
data = np.cumsum(np.random.uniform(-0.5, 0.5, 1000000))
query = np.cumsum(np.random.uniform(-0.5, 0.5, 100))
loc, dist = _ucrdtw.ucrdtw(data, query, 0.05, True)
query = np.concatenate((np.linspace(0.0, 0.0, loc), query)) + (data[loc] - query[0])
plt.figure()
plt.plot(data)
plt.plot(query)
plt.show()