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    "info": {
        "author": "Aliaksei Halachkin",
        "author_email": "aliaksei.h(you know what)gmail.com",
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        "description": "##Dynamic Time Warping Project\r\n\r\n[Examples](http://nbviewer.ipython.org/github/honeyext/cdtw/blob/master/examples.ipynb)\r\n\r\nThis module implements:\r\n\r\nDistance functions:\r\n * manhattan \r\n * euclidean \r\n * squared euclidean\r\n\r\nLocal constraints(step patterns, step functions):\r\n * [well known step patterns dp1, dp2, dp3][1]\r\n * [local constraints classified by Sakoe-Chiba][2]\r\nimpo\r\nGlobal constraints(windows):\r\n * Itakura parallelogram\r\n * [Sakoe-chiba band, Palival adjustment window][3]\r\n \r\n```python\r\nimport numpy as np\r\nfrom cdtw import pydtw\r\nr = np.array([1,2,3,4])\r\nq = np.array([2,3,4,5])\r\nd = pydtw.dtw(r,q,pydtw.Settings(step = 'p0sym',     #Sakoe-Chiba symmetric step with slope constraint p = 0\r\n                                window = 'palival', #type of the window\r\n                                param = 2.0,        #window parameter\r\n                                norm = False,       #normalization\r\n                                compute_path = True))\r\n\r\nd.get_dist()\r\n#2.0\r\nd.get_cost()\r\n#array([[  1.,   3.,   6.,  inf],\r\n#       [  1.,   2.,   4.,   7.],\r\n#       [  2.,   1.,   2.,   4.],\r\n#       [ inf,   2.,   1.,   2.]])\r\nd.get_path()\r\n#[(0, 0), (1, 0), (2, 1), (3, 2), (3, 3)]\r\n\r\n  \r\n\r\n\r\n```\r\n\r\n[1]: http://cyber.felk.cvut.cz/gerstner/teaching/zbd/dtw.pdf\r\n[2]: http://ieeexplore.ieee.org/xpl/login.jsp?tp=&arnumber=1163055&url=http%3A%2F%2Fieeexplore.ieee.org%2Fxpls%2Fabs_all.jsp%3Farnumber%3D1163055\r\n[3]: https://maxwell.ict.griffith.edu.au/spl/publications/papers/sigpro82_kkp_dtw.pdf",
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        "name": "cdtw",
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