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我想做的事情與this問題的答案一樣,但不是在MATLAB中,而是在Python中使用matplotlib。到目前爲止,我已經完成了三維繪圖的代碼投影多變量分佈到2D圖?
import numpy as np
import matplotlib.pyplot as plt
from scipy.stats import multivariate_normal
from mpl_toolkits.mplot3d import Axes3D
mu_x = 0
mu_y = 0
x = np.linspace(-10,10,500)
y = np.linspace(-10,10,500)
X, Y = np.meshgrid(x,y)
pos = np.empty(X.shape + (2,))
pos[:, :, 0] = X; pos[:, :, 1] = Y
rv = multivariate_normal([mu_x, mu_y], [[1, 0.8], [0.8, 1]])
fig = plt.figure(figsize=(10,5))
ax = fig.gca(projection='3d')
ax.plot_surface(X, Y, rv.pdf(pos),cmap='viridis',linewidth=0)
ax.set_xlabel('X axis')
ax.set_ylabel('Y axis')
ax.set_zlabel('Z axis')
ax.auto_scale_xyz([-10, 10], [-10, 10], [0, 0.5])
plt.show()
但是我怎樣才能把它投影到2D輪廓圖?我想
plt.figure()
CS = plt.contour(X, Y, rv)
plt.clabel(CS, inline=1, fontsize=10)
但顯然這是不正確的,因爲Z是不是數組類型(我得到的線CS = plt.contour(X, Y, rv)
錯誤TypeError: float() argument must be a string or a number
)。我如何將多變量分佈投影到二維等高線圖上?謝謝!