mc-basic.py

import numpy as np

xs = np.linspace(2, 5, 10000)  # 10000 samples of x between 2 and 5
ys = np.linspace(1, 2, 10000)  # 10000 samples of y between 1 and 2
ix = np.random.randint(0, 10000, size=(10000, 2))  # random index, 2 parameters


def my_model(x, y):
    ... # do some magic
    return 42  # spit out your evaluation of the model for a given x, y


N = 200

results = []

for i in range(N):
    xi, yi = ix[i, 0], ix[i, 1]
    x = xs[xi]
    y = ys[yi]

    results.append(my_model(x, y))