python matlibplot绘制3D图形

这篇文章主要为大家详细介绍了python matlibplot绘制3D图形，具有一定的参考价值，感兴趣的小伙伴们可以参考一下

本文实例为大家分享了python matlibplot绘制3D图形的具体代码，供大家参考，具体内容如下

1、散点图使用scatter

from mpl_toolkits.mplot3d import Axes3D import numpy as np from matplotlib import pyplot as plt # 生成3D示例数据 mu_vec1 = np.array([0,0,0]) # 均值向量 cov_mat1 = np.array([[1,0,0],[0,1,0],[0,0,1]]) # 协方差矩阵 class1_sample = np.random.multivariate_normal(mu_vec1, cov_mat1, 20) class2_sample = np.random.multivariate_normal(mu_vec1 + 1, cov_mat1, 20) class3_sample = np.random.multivariate_normal(mu_vec1 + 2, cov_mat1, 20) # class1_sample.shape -> (20, 3), 20 rows, 3 columns fig = plt.figure(figsize=(8,8)) ax = fig.add_subplot(111, projection='3d') ax.scatter(class1_sample[:,0], class1_sample[:,1], class1_sample[:,2], marker='x', color='blue', s=40, label='class 1') ax.scatter(class2_sample[:,0], class2_sample[:,1], class2_sample[:,2], marker='o', color='green', s=40, label='class 2') ax.scatter(class3_sample[:,0], class3_sample[:,1], class3_sample[:,2], marker='^', color='red', s=40, label='class 3') ax.set_xlabel('variable X') ax.set_ylabel('variable Y') ax.set_zlabel('variable Z') plt.title('3D Scatter Plot') plt.show()

2、直线使用plot3D

from mpl_toolkits.mplot3d import Axes3D import matplotlib.pyplot as plt import numpy as np from itertools import product, combinations fig = plt.figure(figsize=(7,7)) ax = fig.gca(projection='3d') ax.set_aspect("equal") # 画点 # 立方体里的点 X_inside = np.array([[0,0,0],[0.2,0.2,0.2],[0.1, -0.1, -0.3]]) X_outside = np.array([[-1.2,0.3,-0.3],[0.8,-0.82,-0.9],[1, 0.6, -0.7], [0.8,0.7,0.2],[0.7,-0.8,-0.45],[-0.3, 0.6, 0.9], [0.7,-0.6,-0.8]]) for row in X_inside: ax.scatter(row[0], row[1], row[2], color="r", s=50, marker='^') for row in X_outside: ax.scatter(row[0], row[1], row[2], color="k", s=50) # 画立方体 h = [-0.5, 0.5] for s, e in combinations(np.array(list(product(h,h,h))), 2): if np.sum(np.abs(s-e)) == h[1]-h[0]: ax.plot3D(*zip(s,e), color="g") ax.set_xlim(-1.5, 1.5) ax.set_ylim(-1.5, 1.5) ax.set_zlim(-1.5, 1.5) plt.show()

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