使用matplotlib在散点图中创建置信椭圆 [英] Creating a Confidence Ellipses in a sccatterplot using matplotlib

问题描述

如何使用matplotlib在散点图中创建置信椭圆?

How to creating a Confidence Ellipses in a sccatterplot using matplotlib?

以下代码在创建散点图之前一直有效.然后，有人熟悉推杆吗 散点图中的置信椭圆吗?

The following code works until creating scatter plot. Then, does anyone familiar with putting Confidence Ellipses over the scatter plot?

import numpy as np
import matplotlib.pyplot as plt
x = [5,7,11,15,16,17,18]
y = [8, 5, 8, 9, 17, 18, 25]

plt.scatter(x,y)
plt.show()

以下是SAS的置信椭圆的参考.

Following is the reference for Confidence Ellipses from SAS.

http://support.sas.com/documentation/cdl/zh-CN/grstatproc/62603/HTML/default/viewer.htm#a003160800.htm

sas中的代码如下:

The code in sas is like this:

proc sgscatter data=sashelp.iris(where=(species="Versicolor"));
  title "Versicolor Length and Width";
  compare y=(sepalwidth petalwidth)
          x=(sepallength petallength)
          / reg ellipse=(type=mean) spacing=4;
run;

推荐答案

以下代码绘制一个，两个和三个标准偏差大小的椭圆:

The following code draws a one, two, and three standard deviation sized ellipses:

x = [5,7,11,15,16,17,18]
y = [8, 5, 8, 9, 17, 18, 25]
cov = np.cov(x, y)
lambda_, v = np.linalg.eig(cov)
lambda_ = np.sqrt(lambda_)
from matplotlib.patches import Ellipse
import matplotlib.pyplot as plt
ax = plt.subplot(111, aspect='equal')
for j in xrange(1, 4):
    ell = Ellipse(xy=(np.mean(x), np.mean(y)),
                  width=lambda_[0]*j*2, height=lambda_[1]*j*2,
                  angle=np.rad2deg(np.arccos(v[0, 0])))
    ell.set_facecolor('none')
    ax.add_artist(ell)
plt.scatter(x, y)
plt.show()

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