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wannesm / dtaidistance

Time series distances: Dynamic Time Warping (fast DTW implementation in C)
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Calculate to Percentage #181

Closed rabihiawaludin closed 1 year ago

rabihiawaludin commented 1 year ago

Hi, can dtw distance show as percentage?

wannesm commented 1 year ago

Can you be more precise (or provide a reference or example)? I am not aware of a method that translates a distance to a percentage in general.

rabihiawaludin commented 1 year ago

for example i have array like this s1 = [0, 0, 1, 2, 1, 0, 1, 0, 0] s2 = [0, 0, 1, 2, 1, 0, 1, 0, 0] the distance should be 0.0 if the distance is 0.0, this means that matrix 1 and matrix 2 have the same value, then the similarity of the two matrices is 100%

now, if i change array to s1 = [0, 0, 1, 2, 1, 0, 1, 0, 0] s2 = [0, 0, 1, 2, 1, 0, 1, 2, 0] the distance change to 1.0 in this case the similarity of the two matrces percentage must also change, must be less than 100%

@wannesm

wannesm commented 1 year ago

What you need is indeed 'similarity' instead of 'distance', which is in the range [0,1]. Multiple transformations exist, of which the two most popular ones seem to be sim = exp(-dist / r) and sim = 1/(r + dist), with r a parameter to control the sensitivity (or avoiding dividing by 0). With numpy you can apply this directly to a distance matrix or arrays of distance values, thus:

distance_matrix = dtw.distance_matrix(series)
similarity_matrix = np.exp(-distance_matrix / r)
rabihiawaludin commented 1 year ago

can you give me an example? especially for similatiry_matrix.

actually i use this dwt to calculate the similarity of 2 matrix, from feature exttraction (mfcc) @wannesm

wannesm commented 1 year ago

This is now documented here: https://dtaidistance.readthedocs.io/en/latest/usage/similarity.html