Merge pull request #8 from capkuro/develop

Added fastdtw

dtw.py

@@ -1,4 +1,5 @@
-from numpy import array, zeros, argmin, inf
+from numpy import array, zeros, argmin, inf, equal
+from scipy.spatial.distance import cdist
 
 def dtw(x, y, dist):
     """
@@ -32,6 +33,38 @@ def dtw(x, y, dist):
         path = _traceback(D0)
     return D1[-1, -1] / sum(D1.shape), C, D1, path
 
+def fastdtw(x, y, dist):
+    """
+    Computes Dynamic Time Warping (DTW) of two sequences in a faster way.
+    Instead of iterating through each element and calculating each distance,
+    this uses the cdist function from scipy (https://docs.scipy.org/doc/scipy/reference/generated/scipy.spatial.distance.cdist.html)
+
+    :param array x: N1*M array
+    :param array y: N2*M array
+    :param string or func dist: distance parameter for cdist. When string is given, cdist uses optimized functions for the distance metrics.
+    If a string is passed, the distance function can be 'braycurtis', 'canberra', 'chebyshev', 'cityblock', 'correlation', 'cosine', 'dice', 'euclidean', 'hamming', 'jaccard', 'kulsinski', 'mahalanobis', 'matching', 'minkowski', 'rogerstanimoto', 'russellrao', 'seuclidean', 'sokalmichener', 'sokalsneath', 'sqeuclidean', 'wminkowski', 'yule'.
+    Returns the minimum distance, the cost matrix, the accumulated cost matrix, and the wrap path.
+    """
+    assert len(x)
+    assert len(y)
+    r, c = len(x), len(y)
+    D0 = zeros((r + 1, c + 1))
+    D0[0, 1:] = inf
+    D0[1:, 0] = inf
+    D1 = D0[1:, 1:]
+    D0[1:,1:] = cdist(x,y,dist)
+    C = D1.copy()
+    for i in range(r):
+        for j in range(c):
+            D1[i, j] += min(D0[i, j], D0[i, j+1], D0[i+1, j])
+    if len(x)==1:
+        path = zeros(len(y)), range(len(y))
+    elif len(y) == 1:
+        path = range(len(x)), zeros(len(x))
+    else:
+        path = _traceback(D0)
+    return D1[-1, -1] / sum(D1.shape), C, D1, path
+
 def _traceback(D):
     i, j = array(D.shape) - 2
     p, q = [i], [j]

setup.py

@@ -11,7 +11,7 @@
       url='https://github.com/pierre-rouanet/dtw',
       license='GNU GENERAL PUBLIC LICENSE Version 3',
 
-      install_requires=['numpy'],
+      install_requires=['numpy', 'scipy'],
       setup_requires=['setuptools_git >= 0.3', ],
 
       py_modules=['dtw'],