env_test.py

from Source.Auxiliary import *


def main():
    average = np.array([[9, 10, 7],
                        [3, 3, 2],
                        [4, 4, 5],
                        [3, 3.5, 3],
                        [1.5, 2, 2]])

    variance = np.array([[1, 1, 1],
                         [0.5, 0.5, 0.5],
                         [0.5, 0.5, 0.5],
                         [0.5, 0.5, 0.5],
                         [0.5, 0.5, 0.5]])

    prices = generate_prices(np.array([8, 3, 5, 4, 2]))

    costs = np.array([0.8, 0.3, 0.5, 0.4, 0.2])

    class_probability = np.array([0.4, 0.2, 0.4])

    lambdas = np.array([1, 2, 3])

    alphas_par = np.array([5, 1, 1, 1, 1, 1])

    np.random.seed(5)
    P = np.random.uniform(0.1, 0.5, size=(5, 5, 3))

    secondary_products = np.array([[1, 4],
                                   [0, 2],
                                   [3, 0],
                                   [2, 4],
                                   [0, 1]])

    env1 = EnvironmentPricing(average, variance, prices, costs, lambdas, alphas_par, P, secondary_products,
                              class_probability=class_probability, lambda_secondary=0.5)
    alphas_ratio = env1.alpha_ratio_otd()
    data = env1.round_single_day(n_daily_users=100, alpha_ratio=alphas_ratio, arms_pulled=[0, 0, 0, 0, 0])

    print("Customer 1:", data[0])
    print("Customer 2:", data[1])
    print("Customer 3:", data[2])


main()