python">import matplotlib.pyplot as plt
import numpy as np# 创建一些正常分布的数据
mean = [0, 0]
cov = [[1, 1], [1, 2]]
x, y = np.random.multivariate_normal(mean, cov, 3000).T# Set up the axes with gridspec
fig = plt.figure(figsize=(6, 6))
grid = plt.GridSpec(4, 4, hspace=0.2, wspace=0.2)
main_ax = fig.add_subplot(grid[:-1, 1:])
y_hist = fig.add_subplot(grid[:-1, 0], xticklabels=[], sharey=main_ax)
x_hist = fig.add_subplot(grid[-1, 1:], yticklabels=[], sharex=main_ax)# scatter points on the main axes
main_ax.plot(x, y, 'ok', markersize=3, alpha=0.2)# histogram on the attached axes
x_hist.hist(x, 40, histtype='stepfilled',orientation='vertical', color='gray')
x_hist.invert_yaxis()y_hist.hist(y, 40, histtype='stepfilled',orientation='horizontal', color='gray')
y_hist.invert_xaxis()

python"># Path: 子图.ipynb
mean = [0, 0]
cov = [[1, 1], [1, 2]]
x, y = np.random.multivariate_normal(mean, cov, 3000).Tfig = plt.figure(figsize=(6, 6))
grid = plt.GridSpec(4, 4, hspace=0.2, wspace=0.2)
main_ax = fig.add_subplot(grid[:-1, 1:])
y_hist = fig.add_subplot(grid[:-1, 3], xticklabels=[], sharey=main_ax)
x_hist = fig.add_subplot(grid[-1, 1:], yticklabels=[], sharex=main_ax)main_ax.plot(x, y, 'ok', markersize=3, alpha=0.2)x_hist.hist(x, 40, histtype='stepfilled',orientation='vertical', color='blue')
x_hist.invert_yaxis()y_hist.hist(y, 40, histtype='stepfilled',orientation='horizontal', color='blue')
y_hist.invert_xaxis()