Computing Euclidean distance for numpy in python

Question

I am new to Python so this question might look trivia. However, I did not find a similar case to mine. I have a matrix of coordinates for 20 nodes. I want to compute the euc

Answer 1

What I figure you wanted to do: You said you wanted a 20 by 20 matrix... but the one you coded is triangular.

Thus I coded a complete 20x20 matrix instead.

distances = []
for i in range(len(ncoord)):
    given_i = []
    for j in range(len(ncoord)):
        d_val = math.sqrt((ncoord[i, 0]-ncoord[j,0])**2+(ncoord[i,1]-ncoord[j,1])**2)
        given_i.append(d_val)

    distances.append(given_i)

    # distances[i][j] = distance from i to j

SciPy way:

from scipy.spatial.distance import cdist
# Isn't scipy nice - can also use pdist... works in the same way but different recall method.
distances = cdist(ncoord, ncoord, 'euclidean')