simulate.py

def simulate_model_runs():
    rng = np.random.RandomState(42)

    for i in range(0, 300):
        j = i / 100
        scalabilities = rng.normal(loc=1.0, scale=j, size=60)

        a = rng.normal(size=60)
        b = rng.normal(size=60) + scalabilities
        c = rng.normal(size=60) + scalabilities * 2
        slope, intercept, r_value, p_value, std_err = scipy.stats.linregress(b - a, c - b)
        print('{},{}'.format(j, r_value))