Монте-Карлогийн загварчлалыг Python -оор гүйцэигэх жишээ

# Ball Mill Capacity and Monte Carlo Simulation
# G.Davaatseren

import matplotlib.pyplot as plt
import numpy as np


def Q(W, F80):
    D = 5.5
    L = 6.5
    bd = 7.9
    fsi = 0.85
    phi = 0.35
    Cf = 1
    P80 = 135
    Q1 = 8.01 * (D ** 3.3) * (L / D) * bd * (phi - 0.937 * phi * phi) * (fsi - 0.1 * fsi / (2 ** (9 - 10 * fsi)))
    Q2 = Cf * W * (10 / np.sqrt(P80) - 10 / np.sqrt(F80))
    return Q1 / Q2


# -------------------------------------------------------
# test data for Erdenet
Wi = np.array([17.41, 17.46, 16.37, 18.23, 18, 17.07, 17.43, 17.37, 16.82, 19.5])
W_mean = np.mean(Wi)
W_std = np.std(Wi)
# -----------------------------------------------------
# Generation of the Bond Work Index
w_index = np.random.normal(W_mean, W_std, 1000)
# feed_size= np.random.normal(9500,200, 1000)

feed_size = [9500, 10000, 12000, ]
for i in feed_size:
    tph = np.round(Q(w_index, i), 0)

plt.hist(tph)

plt.show()

# print(round(Q(W_mean,9000),0))