Testing numpy computation speed up for numpy.multiply vs numpy.dot in special case: for $V \in R^{n \times n}$ and $U \in R^n$, compare the speed up for numpy.dot(V, numpy.diag(U)) and numpy.multiply(V, U)

test_numpy_multiply_dot.py

import numpy as np
from pyriemann.estimation import Covariances
from timeit import Timer

n, t = 1500, 3000
n_repeat = 100

X = np.random.rand(1, n, t)
U = np.random.rand(n)
cov = Covariances()
V = cov.transform(X)
V = V[0,:,:]

t = Timer("numpy.dot(V, numpy.diag(U))", "import numpy; from __main__ import U, V")
dp = np.array(t.repeat(n_repeat, 1))
print ("dot product for ", n, "x", n, " by diag(", n, ") :",  "%.2f+/-%.4f seconds"
       % (dp.mean(), dp.std()))
# print ("result is:", np.dot(V, np.diag(U)))

t = Timer("numpy.multiply(V, U)", "import numpy; from __main__ import U, V")
ml = np.array(t.repeat(n_repeat, 1))
print ("multiply for ", n, "x", n, " by ", n, " :", "%.2f+/-%.4f seconds"
       % (ml.mean(), ml.std()))
# print ("result is:", np.multiply(V, U))