Calculate Euclidean Distance within points in numpy array

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無奈伤痛
無奈伤痛 2021-01-14 01:46

I have 3D array as

 A = [[x1 y1 z1]
      [x2 y2 z2]
      [x3 y3 z3]]

I have to find euclidean distance between each points so that I\'ll

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  • 2021-01-14 01:56

    You can do something like this:

    >>> import numpy as np
    >>> from itertools import combinations
    >>> A = np.array([[1, 2, 3], [4, 5, 6], [10, 20, 30]])
    >>> [np.linalg.norm(a-b) for a, b in combinations(A, 2)]
    [5.196152422706632, 33.674916480965472, 28.930952282978865]
    
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  • 2021-01-14 02:12

    Consider using scipy.spatial.distance.pdist.

    You can do like this.

    >>> A = np.array([[1, 2, 3], [4, 5, 6], [10, 20, 30]])
    >>> scipy.spatial.distance.pdist(A)
    array([  5.19615242,  33.67491648,  28.93095228])
    

    But be careful the order of the output distance is (row0,row1),(row0,row2) and (row1,row2).

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