如何在matplotlib图表中创建3d方框并统计每个方框中的总点数？

import matplotlib.pyplot as plt
from mpl_toolkits.mplot3d import Axes3D
import numpy as np

fig = plt.figure()
ax = fig.add_subplot(111, projection='3d')

x_box = np.array([0, 1, 1, 0, 0, 1, 1, 0])
y_box = np.array([0, 0, 1, 1, 0, 0, 1, 1])
z_box = np.array([0, 0, 0, 0, 1, 1, 1, 1])
num_boxes = len(x_box) // 4  # 方框的数量

for i in range(num_boxes):
    ax.plot(x_box[i*4:(i+1)*4], y_box[i*4:(i+1)*4], z_box[i*4:(i+1)*4], color='blue')

num_points = 1000  # 随机点的数量
points = np.random.rand(num_points, 3)  # 生成随机点的坐标

counts = np.zeros(num_boxes)  # 统计每个方框中的点数

for point in points:
    for i in range(num_boxes):
        if (x_box[i*4] <= point[0] <= x_box[i*4+1]) and (y_box[i*4] <= point[1] <= y_box[i*4+2]) and (z_box[i*4] <= point[2] <= z_box[i*4+4]):
            counts[i] += 1

for i in range(num_boxes):
    print("方框{}中的点数：{}".format(i+1, counts[i]))