利用Python的scipy包实现曲线的拟合

import numpy as np
import pandas as pd
import matplotlib.pyplot as plt
from scipy.optimize import curve_fit


# 自定义函数
def func(x,a,b):
    return a*pow(x,b)


data = pd.read_excel(r‘C:UsersYBMDesktopdata.xlsx‘)
x = data[‘x‘]
y = data[‘y‘]

popt,pcov = curve_fit(x,y)
a = popt[0]
b = popt[1]
yvals = func(x,b)

plot1 = plt.plot(x,y,‘s‘,label=‘original values‘)
plot2 = plt.plot(x,yvals,‘r‘,label=‘polyfit values‘)
plt.xlabel(‘x‘)
plt.ylabel(‘y‘)
plt.legend(loc=4) # 指定legend的位置在右下角
plt.title(‘curve_fit‘)

import numpy as np
import pandas as pd
import matplotlib.pyplot as plt
from scipy.optimize import curve_fit


def func(x,b,c):
    return a * np.exp(-b * x) + c


xdata = np.linspace(0,4,50)
y = func(xdata,2.5,1.3,0.5)
y_noise = 0.2 * np.random.normal(size=xdata.size)
ydata = y + y_noise
plt.plot(xdata,ydata,‘b-‘,label=‘data‘)

popt,pcov = curve_fit(func,xdata,ydata)
a = popt[0]
b = popt[1]
c = popt[2]
yvals = func(xdata,c)
plot1 = plt.plot(xdata,label=‘original values‘)
plot2 = plt.plot(xdata,label=‘polyfit values‘)
# 或：
plt.plot(xdata,func(xdata,*popt),‘r-‘,label=‘fit‘)

# 限制参数范围：0<a<3,0<b<2， 0<c<1
popt,pcov = curve_fit(func,bounds=(0,[3.,2.,1.]))
plt.plot(xdata,label=‘fit‘)