a.py

import numpy as np


mytype = [('id', 'uint32'), ('x', 'float64'), ('y', 'float64')]
a = np.array([(1, 0.5, 0.3), (3, 0.2, 0.1),
              (5, 0.1, 0.3), (8, 0.1, 0.5)], dtype=mytype)

c = a[['x', 'y']]
b = c.view(np.float64).reshape(c.shape + (-1,))

relavancy = np.linalg.norm(b[:, np.newaxis] - b, axis=2)

print(relavancy)