2024-04-24 13:37:14 发布
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得到了三维高斯分布的均值和sigmas,然后用python代码绘制三维分布图,得到分布图。
这是基于mpl_工具包的文档和基于scipy multinormal pdf的答案
import matplotlib.pyplot as plt from mpl_toolkits.mplot3d import Axes3D import numpy as np from scipy.stats import multivariate_normal x, y = np.mgrid[-1.0:1.0:30j, -1.0:1.0:30j] # Need an (N, 2) array of (x, y) pairs. xy = np.column_stack([x.flat, y.flat]) mu = np.array([0.0, 0.0]) sigma = np.array([.5, .5]) covariance = np.diag(sigma**2) z = multivariate_normal.pdf(xy, mean=mu, cov=covariance) # Reshape back to a (30, 30) grid. z = z.reshape(x.shape) fig = plt.figure() ax = fig.add_subplot(111, projection='3d') ax.plot_surface(x,y,z) #ax.plot_wireframe(x,y,z) plt.show()
参考:
Generating 3D Gaussian distribution in Python
http://matplotlib.org/mpl_toolkits/mplot3d/tutorial.h
这是基于mpl_工具包的文档和基于scipy multinormal pdf的答案
参考:
Generating 3D Gaussian distribution in Python
http://matplotlib.org/mpl_toolkits/mplot3d/tutorial.h
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