python-blosc2/bench/ndarray/miniexpr-eval.py at 302124a7876d2742d79905d3c1a06a5c3b79cef0 · Blosc/python-blosc2 · GitHub

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from time import time
import blosc2
import numpy as np
import numexpr as ne

N = 10_000
# dtype= np.int32
dtype= np.float32
# dtype= np.float64
cparams = blosc2.CParams(codec=blosc2.Codec.BLOSCLZ, clevel=1)

t0 = time()
# a = blosc2.ones((N, N), dtype=dtype, cparams=cparams)
# a = blosc2.arange(np.prod((N, N)), shape=(N, N), dtype=dtype, cparams=cparams)
a = blosc2.linspace(0., 1., np.prod((N, N)), shape=(N, N), dtype=dtype, cparams=cparams)
print(f"Time to create data: {(time() - t0) * 1000 :.4f} ms")
t0 = time()
b = a.copy()
c = a.copy()
print(f"Time to copy data: {(time() - t0) * 1000 :.4f} ms")

t0 = time()
res = (2 * a**2 - 3 * b + c + 1.2).compute(cparams=cparams)
t = time() - t0
print(f"Time to evaluate: {t * 1000 :.4f} ms", end=" ")
print(f"Speed (GB/s): {(a.nbytes * 4 / 1e9) / t:.2f}")
# print(res.info)

na = a[:]
nb = b[:]
nc = c[:]

t0 = time()
nres = 2 * na**2 - 3 * nb + nc + 1.2
nt = time() - t0
print(f"Time to evaluate with NumPy: {nt * 1000 :.4f} ms", end=" ")
print(f"Speed (GB/s): {(na.nbytes * 4 / 1e9) / nt:.2f}")
print(f"Speedup Blosc2 vs NumPy: {nt / t:.2f}x")
np.testing.assert_allclose(res, nres, rtol=1e-5)

t0 = time()
neres = ne.evaluate("2 * na**2 - 3 * nb + nc + 1.2")
net = time() - t0
print(f"Time to evaluate with NumExpr: {net * 1000 :.4f} ms", end=" ")
print(f"Speed (GB/s): {(na.nbytes * 4 / 1e9) / net:.2f}")
print(f"Speedup Blosc2 vs NumExpr: {net / t:.2f}x")
np.testing.assert_allclose(res, neres, rtol=1e-5)