3D散点图和投影KDE图

Question

有人可以告诉我为什么此代码中的XZ投影未出现在X-Z平面上？

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

# Sample data
np.random.seed(42)
x = np.random.randn(100)
y = np.random.randn(100)
z = np.random.randn(100)

# Create figure and 3D axes
fig = plt.figure(figsize=(10, 8))
ax = fig.add_subplot(111, projection='3d')

# Scatter plot
ax.scatter(x, y, z, c='b', marker='o')

# KDE for projections
def kde_projection(data1, data2):
    values = np.vstack([data1, data2])
    kernel = kde.gaussian_kde(values)
    
    x_range = np.linspace(data1.min(), data1.max(), 100)
    y_range = np.linspace(data2.min(), data2.max(), 100)
    X, Y = np.meshgrid(x_range, y_range)
    positions = np.vstack([X.ravel(), Y.ravel()])
    Z = np.reshape(kernel(positions).T, X.shape)
    return X, Y, Z

# Projections with KDE
# XY plane
X_xy, Y_xy, Z_xy = kde_projection(x, y)
ax.contour(X_xy, Y_xy, Z_xy, zdir='z', offset=z.min()-1, cmap='Blues')

# XZ plane
X_xz, Z_xz, Y_xz = kde_projection(x, z)
ax.contour(X_xz, Y_xz, Z_xz, zdir='y', offset=y.min()-1, cmap='Reds')

# YZ plane
Y_yz, Z_yz, X_yz = kde_projection(y, z)
ax.contour(X_yz, Y_yz, Z_yz, zdir='x', offset=x.min()-1, cmap='Greens')

# Set labels and limits
ax.set_xlabel('X')
ax.set_ylabel('Y')
ax.set_zlabel('Z')

ax.set_xlim(x.min() - 1, x.max() + 1)
ax.set_ylim(y.min() - 1, y.max() + 1)
ax.set_zlim(z.min() - 1, z.max() + 1)

# Show plot
plt.show()

将Yz和XY的投影删除在各自的飞机上，但XZ不想工作...我不确定我是否缺少某些东西，但我认为该模式应适用于所有三个飞机。 thanks.

x_xz，y_xz，z_xz = kde_proctive（x，z）

Answer 1