如何在图上添加回归线和回归线方程

Question

我有以下输入文件和代码/脚本在图表上添加回归线，但代码会出现此错误：ValueError: x and y must have same first dimension。我无法弄清楚那个错误。

如何在图表上添加回归线和回归线方程？

输入文件：

-5.06   -4.27
-6.69   -7.28
-3.80   -3.51
-3.88   -2.79
-0.90   -0.81
 2.10    2.59
-1.08    0.28
-5.00   -3.39
 2.67    2.92
 2.48    2.85
-5.10   -3.49
 2.88    3.09
 2.30    2.67
-3.47   -2.20
-0.90   -0.79

脚本：

#!/usr/bin/python
import numpy as np
import pylab as plot
import matplotlib.pyplot as plt
import numpy, scipy, pylab, random
from matplotlib.ticker import MultipleLocator
import matplotlib as mpl
from matplotlib.ticker import MaxNLocator
from scipy import stats

with open("input.txt", "r") as f:
    x=[]
    y=[]

    for line in f:
        if not line.strip() or line.startswith('@') or line.startswith('#'): continue
        row = line.split()
        x.append(float(row[0]))
        y.append(float(row[1]))

fig = plt.figure(figsize=(2.2,2.2), dpi=300)
ax = plt.subplot(111)

plt.xlim(4, -8)
plt.ylim(4, -8)

ax.xaxis.set_major_locator(MaxNLocator(6))
ax.yaxis.set_major_locator(MaxNLocator(6))

ax.xaxis.set_minor_locator(MultipleLocator(1))
ax.yaxis.set_minor_locator(MultipleLocator(1))


#regression part
slope, intercept, r_value, p_value, std_err = stats.linregress(x,y)
line = slope*x+intercept
plt.plot(x, line, 'r', label='fitted line')
#end

plt.scatter(x,y,color=['black','black','black','black','black','black','black','black','black','black','black','black','black','black','black'], s=3.5)


plt.savefig("output.png", dpi=300)

Answer 1

您不能将列表与浮点数相乘。因此，您可以从输入列表x创建一个numpy数组，

line = slope*np.array(x)+intercept

理想情况下，您可以使用np.genfromtxt，

读取数据

x,y = np.genfromtxt("input.txt", unpack=True) 

完整示例：

import numpy as np
import matplotlib.pyplot as plt
from matplotlib.ticker import MultipleLocator
from matplotlib.ticker import MaxNLocator
from scipy import stats

x,y = np.genfromtxt("input.txt", unpack=True) 

fig = plt.figure(figsize=(2.2,2.2), dpi=300)
ax = plt.subplot(111)

plt.xlim(4, -8)
plt.ylim(4, -8)

ax.xaxis.set_major_locator(MaxNLocator(6))
ax.yaxis.set_major_locator(MaxNLocator(6))

ax.xaxis.set_minor_locator(MultipleLocator(1))
ax.yaxis.set_minor_locator(MultipleLocator(1))


#regression part
slope, intercept, r_value, p_value, std_err = stats.linregress(x,y)

line = slope*x+intercept
plt.plot(x, line, 'r', label='y={:.2f}x+{:.2f}'.format(slope,intercept))
#end

plt.scatter(x,y, color="k", s=3.5)
plt.legend(fontsize=9)

plt.show()

Answer 2

你可以尝试为回归线添加这段代码：

# To plot the regression line
plt.plot(X, (B0 + B1*x), label = 'y = {:.2f} + {:.2f}*x'.format(B0, B1))
plt.legend(loc='lower right')

以下是我编写的线性回归代码的可视化截图：