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Project Description
##Dynamic Time Warping Project


This module implements:

Distance functions:
* manhattan
* euclidean
* squared euclidean

Local constraints(step patterns, step functions):
* [well known step patterns dp1, dp2, dp3][1]
* [local constraints classified by Sakoe-Chiba][2]
Global constraints(windows):
* Itakura parallelogram
* [Sakoe-chiba band, Palival adjustment window][3]

import numpy as np
from cdtw import pydtw
r = np.array([1,2,3,4])
q = np.array([2,3,4,5])
d = pydtw.dtw(r,q,pydtw.Settings(step = 'p0sym', #Sakoe-Chiba symmetric step with slope constraint p = 0
window = 'palival', #type of the window
param = 2.0, #window parameter
norm = False, #normalization
compute_path = True))

#array([[ 1., 3., 6., inf],
# [ 1., 2., 4., 7.],
# [ 2., 1., 2., 4.],
# [ inf, 2., 1., 2.]])
#[(0, 0), (1, 0), (2, 1), (3, 2), (3, 3)]


Release History

Release History


This version

History Node

TODO: Figure out how to actually get changelog content.

Changelog content for this version goes here.

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