Norm of vector and matrix

# Times were captured with the timeit module import numpy as np # Norm of vector a = [41,23,22,15,6,11] np_a = np.array(a) print(np.linalg.norm(np_a)) # 0.3047s print(sum([val**2 for val in a])**0.5) # 0.028s, no external library needed # Result in both cases: 55.4616984954 # Norm of matrix A = [ [18,22,21,10], [13,6,4,11], [7,15,20,18], [6,5,11,16] ] np_A = np.array(A) print(np.linalg.norm(np_A)) # 0.3744s print(np.sqrt(np.sum(np_A**2))) # 0.4466s print(sum([val**2 for sublist in A for val in sublist])**0.5) # 0.0725s, no library # Result in all cases: 55.9195851201