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Test numpy installation.
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import numpy as np | |
import numpy.random as npr | |
import time | |
# --- Test 1 | |
N = 100 | |
n = 2000 | |
A = npr.randn(n, n) | |
B = npr.randn(n, n) | |
t = time.time() | |
for i in range(N): | |
C = np.dot(A, B) | |
td = time.time() - t | |
print("dotted two (%d,%d) matrices in %0.1f ms" % (n, n, 1e3 * td / N)) | |
# --- Test 2 | |
N = 100 | |
n = 10000 | |
A = npr.randn(n) | |
B = npr.randn(n) | |
t = time.time() | |
for i in range(N): | |
C = np.dot(A, B) | |
td = time.time() - t | |
print("dotted two (%d) vectors in %0.2f us" % (n, 1e6 * td / N)) | |
# --- Test 3 | |
m, n = (2000, 2000) | |
A = npr.randn(m, n) | |
t = time.time() | |
[U, s, V] = np.linalg.svd(A, full_matrices=False) | |
td = time.time() - t | |
print("SVD of (%d,%d) matrix in %0.3f s" % (m, n, td)) | |
# --- Test 4 | |
n = 2000 | |
A = npr.randn(n, n) | |
t = time.time() | |
w, v = np.linalg.eig(A) | |
td = time.time() - t | |
print("Eigendecomp of (%d,%d) matrix in %0.3f s" % (n, n, td)) |
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