Python使用matplotlib,numpy,scipy进行散点的平滑曲线化方法

首先给出一个没有smooth过的曲线

import matplotlib.pyplot as plt
import numpy as np
 
T = np.array([6, 7, 8, 9, 10, 11, 12])
power = np.array([1.53E+03, 5.92E+02, 2.04E+02, 7.24E+01, 2.72E+01, 1.10E+01, 4.70E+00])
 
plt.plot(T,power)
plt.show()

输出的曲线如下图

使用scipy库可以进行曲线的smooth

代码如下

import matplotlib.pyplot as plt
import numpy as np
from scipy.interpolate import spline
 
T = np.array([6, 7, 8, 9, 10, 11, 12])
power = np.array([1.53E+03, 5.92E+02, 2.04E+02, 7.24E+01, 2.72E+01, 1.10E+01, 4.70E+00])
xnew = np.linspace(T.min(),T.max(),300) #300 represents number of points to make between T.min and T.max
 
power_smooth = spline(T,power,xnew)
 
plt.plot(xnew,power_smooth)
plt.show()

输出的图片为

转载自：https://blog.csdn.net/cdqn10086/article/details/70143616

import matplotlib.pyplot as plt
import numpy as np
from scipy.interpolate import spline
 
T = np.array([6, 7, 8, 9, 10, 11, 12])
power = np.array([1.53E+03, 5.92E+02, 2.04E+02, 7.24E+01, 2.72E+01, 1.10E+01, 4.70E+00])
xnew = np.linspace(T.min(),T.max(),300) #300 represents number of points to make between T.min and T.max
 
power_smooth = spline(T,power,xnew)
 
plt.plot(xnew,power_smooth)
plt.show()

 

Interpolation (scipy.interpolate)

https://docs.scipy.org/doc/scipy/reference/tutorial/interpolate.html

 

Python/Matplotlib光滑曲线画图---Scipy库函数使用

https://blog.csdn.net/gsww404/article/details/77916986