linear equation performance

lin_eq_benchmark.py

import scipy.linalg
import numpy as np
import sys


num_samples = 500000
n = 7


def inv(Q, x, num_eqs):
    for _ in range(num_samples):
        Q_inv = np.linalg.inv(Q)
        for eq in range(num_eqs):
            Q_inv.dot(x)


def solve(Q, x, num_eqs):
    for _ in range(num_samples):
        for eq in range(num_eqs):
            np.linalg.solve(Q, x)


def chol(Q, x, num_eqs):
    for _ in range(num_samples):
        ch = scipy.linalg.cholesky(Q)
        for eq in range(num_eqs):
            scipy.linalg.solve_triangular(ch, x)


if __name__ == '__main__':
    np.random.seed(0)
    Q = np.random.rand(n, n)
    Q = Q + Q.T + n * np.identity(n)
    x = np.zeros(n)
    num_eqs = int(sys.argv[2])
    if sys.argv[1] == '0':
        inv(Q, x, num_eqs)
    elif sys.argv[1] == '1':
        chol(Q, x, num_eqs)
    elif sys.argv[1] == '2':
        solve(Q, x, num_eqs)
    else:
        raise Exception