使用Python绘制2D内核密度估计图 [英] Plotting 2D Kernel Density Estimation with Python

问题描述

我想绘制一个2D内核密度估计值.我发现海运包装在这里非常有用.但是，经过长时间的搜索，我无法弄清楚如何使y轴和x轴不透明.另外，如何在轮廓上显示密度值?如果有人可以帮助我，我将不胜感激.下面请看我的代码和图表.

I would like to plot a 2D kernel density estimation. I find the seaborn package very useful here. However, after searching for a long time, I couldn't figure out how to make the y-axis and x-axis non-transparent. Also, how to show the values of the density on the contour? I would be very appreciated if someone could help me out. Below please see my code and graph.

import numpy as np
import seaborn as sns
import matplotlib.pyplot as pl

Y = np.random.multivariate_normal((0, 0), [[0.8, 0.05], [0.05, 0.7]], 100)
ax = sns.kdeplot(Y, shade = True, cmap = "PuBu")
ax.patch.set_facecolor('white')
ax.collections[0].set_alpha(0)
ax.set_xlabel('$Y_1$', fontsize = 15)
ax.set_ylabel('$Y_0$', fontsize = 15)
pl.xlim(-3, 3)
pl.ylim(-3, 3)
pl.plot([-3, 3], [-3, 3], color = "black", linewidth = 1)
pl.show()

推荐答案

以下是仅使用scipy和matplotlib的解决方案:

Here is a solution using scipy and matplotlib only :

import numpy as np
import matplotlib.pyplot as pl
import scipy.stats as st

data = np.random.multivariate_normal((0, 0), [[0.8, 0.05], [0.05, 0.7]], 100)
x = data[:, 0]
y = data[:, 1]
xmin, xmax = -3, 3
ymin, ymax = -3, 3

# Peform the kernel density estimate
xx, yy = np.mgrid[xmin:xmax:100j, ymin:ymax:100j]
positions = np.vstack([xx.ravel(), yy.ravel()])
values = np.vstack([x, y])
kernel = st.gaussian_kde(values)
f = np.reshape(kernel(positions).T, xx.shape)

fig = pl.figure()
ax = fig.gca()
ax.set_xlim(xmin, xmax)
ax.set_ylim(ymin, ymax)
# Contourf plot
cfset = ax.contourf(xx, yy, f, cmap='Blues')
## Or kernel density estimate plot instead of the contourf plot
#ax.imshow(np.rot90(f), cmap='Blues', extent=[xmin, xmax, ymin, ymax])
# Contour plot
cset = ax.contour(xx, yy, f, colors='k')
# Label plot
ax.clabel(cset, inline=1, fontsize=10)
ax.set_xlabel('Y1')
ax.set_ylabel('Y0')

pl.show()

前面的代码给出以下结果:

The previous code gives the following result :

.这是预期的结果吗?

这篇关于使用Python绘制2D内核密度估计图的文章就介绍到这了，希望我们推荐的答案对大家有所帮助，也希望大家多多支持IT屋！