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

I suggest using pdist and squareform from scipy.spatial.distance

Consider the following array of points:

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

If you want to display all distances between point [1,2,8] and the other points:

squareform(pdist(a))

Out[1]: array([[ 0.        ,  8.71779789,  8.1240384 ,  3.31662479,  7.34846923],
               [ 8.71779789,  0.        ,  6.164414  ,  8.18535277,  1.41421356],
               [ 8.1240384 ,  6.164414  ,  0.        ,  9.21954446,  5.83095189],
               [ 3.31662479,  8.18535277,  9.21954446,  0.        ,  7.        ],
               [ 7.34846923,  1.41421356,  5.83095189,  7.        ,  0.        ]])

I you want to display the shortest distance between point [1,2,8] and the closest point:

sorted(squareform(pdist(a))[0])[1]

Out[2]: 3.3166247903553998

[0] being the index of your first point ([1,2,8])

[1] being the index of the second minimum value (to avoid zeros)

If you want to display the index of the closest point to [1,2,8]:

np.argsort(squareform(pdist(a))[0])[1]

Out[3]: 3