Euclidean code for medium broadcasting

broadcasting.py

import numpy as np
from sklearn.datasets import load_iris

Load data:
data, _ = load_iris(return_X_y=True)

def euc_matrix(A):
    # generate distance matrix:
    B = np.rot90(A[:,:,None],1,(1,2)) #[:,:,None] is needed to add a dimension
    C = np.rot90(B,1,(0,1))
    return np.sqrt(np.sum((B-C)**2, axis=2))

mat = euc_matrix(data)