Compare timing for loop merge operations using different methods

loop_timing_analysis.py

import time
import random
import numpy as np

A = [random.random() for i in range(65536)]
B = [random.random() for i in range(65536)]
C = [random.random() for i in range(65536)]
D = [random.random() for i in range(65536)]
E = [random.random() for i in range(65536)]
F = [random.random() for i in range(65536)]

a = time.time()
X = []; Y = []; Z = []
for i in range(65536):
	X.append(A[i])
	X.append(D[i])
	Y.append(B[i])
	Y.append(E[i])
	Z.append(C[i])
	Z.append(F[i])
Q = (X, Y, Z)
a = (time.time() - a)

b = time.time()
Q = ([*A, *D], [*B, *E], [*C, *F])
b = (time.time() - b)

c = time.time()
Q = (np.concatenate((A, D)), np.concatenate((B, E)), np.concatenate((C, F)))
c = time.time() - c

print('1. For loop: %f;\n2. Pointers: %f;\n3. Numpy   : %f;' % (a, b, c))

1. For loop: 0.042167;
2. Pointers: 0.003162;
3. Numpy   : 0.020149;