run_numpy_bench.py

# License: BSD (3-clause)
# Author: Denis A. Engemann <denis-alexander.engemann@inria.fr>

# Based on :
# https://gist.github.com/markus-beuckelmann/8bc25531b11158431a5b09a45abd6276

import platform
import psutil
import datetime
from time import time

import numpy as np
import pandas as pd

# Let's take the randomness out of random numbers (for reproducibility)
rng = np.random.RandomState(0)

p = 2048

A = np.random.random((p, p))
B = np.random.random((p, p))

E = np.random.random((int(p / 2), int(p / 4)))
F = np.random.random((int(p / 2), int(p / 2)))

G = np.random.random((int(p / 2), int(p / 2)))


def bench(function, runs=50):
    deltas = list()
    for ii in range(runs):
        tt = time()
        function()
        delta = time() - tt
        deltas.append(delta)
    return np.array(deltas)


results = dict(
    dot=bench(lambda: A @ B),
    svd=bench(lambda: np.linalg.svd(E, full_matrices = False)),
    eigh=bench(lambda: np.linalg.eigh(G))
)

results_df = pd.DataFrame(results)

results_df['ram'] = str(
    round(psutil.virtual_memory().total / (1024.0 **3))) + " GB"

results_df['arch'] = platform.machine()
results_df['version'] = platform.platform()

date = datetime.datetime.now().strftime("%Y-%m-%dT%H:%M:%S.%f")
results_df.to_csv('numpy/bench-%s.csv' % date[:-7])