Calculate Distances Between One Point in Matrix From All Other Points

Question

I am new to Python and I need to implement a clustering algorithm. For that, I will need to calculate distances between the given input data.

Consider the following inpu

Answer 1

From this thread's you can use the e_dist function there and also obtain the same results.

Addendum

Timing: on my memory starved laptop, I can only do a comparison to a smaller sample than @Psidom 's using his norm_app function.

a = np.random.randint(0,9,(5000,3))

%timeit norm_app(a) 1.91 s ± 13.5 ms per loop (mean ± std. dev. of 7 runs, 1 loop each)

%timeit e_dist(a, a) 631 ms ± 3.64 ms per loop (mean ± std. dev. of 7 runs, 1 loop each)

a 
array([[1, 2, 8],
       [7, 4, 2],
       [9, 1, 7],
       [0, 1, 5],
       [6, 4, 3]])

dm = e_dist(a, a)  # get the def from the link

dm
Out[7]: 
array([[ 0.  ,  8.72,  8.12,  3.32,  7.35],
       [ 8.72,  0.  ,  6.16,  8.19,  1.41],
       [ 8.12,  6.16,  0.  ,  9.22,  5.83],
       [ 3.32,  8.19,  9.22,  0.  ,  7.  ],
       [ 7.35,  1.41,  5.83,  7.  ,  0.  ]])

idx = np.argsort(dm)

closest = a[idx]

closest
Out[10]: 
array([[[1, 2, 8],
        [0, 1, 5],
        [6, 4, 3],
        [9, 1, 7],
        [7, 4, 2]],

       [[7, 4, 2],
        [6, 4, 3],
        [9, 1, 7],
        [0, 1, 5],
        [1, 2, 8]],

       [[9, 1, 7],
        [6, 4, 3],
        [7, 4, 2],
        [1, 2, 8],
        [0, 1, 5]],

       [[0, 1, 5],
        [1, 2, 8],
        [6, 4, 3],
        [7, 4, 2],
        [9, 1, 7]],

       [[6, 4, 3],
        [7, 4, 2],
        [9, 1, 7],
        [0, 1, 5],
        [1, 2, 8]]])