Python拟合逻辑曲线怎么进行参数范围设定，依据是什么 popt, pcov = curve_fit(func, xdata, ydata,bounds=(0, [160,6, 10,20]))
完整代码如下
from scipy.optimize import curve_fit
import matplotlib.pyplot as plt
import numpy as np
import pandas as pd
#三次曲线方程
def func(x,a, b, c, d):
return (a/(1+np.exp(-b * x+c)))+d
if name=='main'
data=pd.read_excel('1生长曲线.xlsx')
xdata=np.array(data['1Time'])
ydata =np.array(data['1OD730'])
plt.plot(xdata,ydata,'b-')
popt, pcov = curve_fit(func, xdata, ydata,bounds=(0, [160,6, 10,20]))#popt数组中，三个值分别是待求参数a,b,c
y_pred = [func(i, popt[0],popt[1],popt[2],popt[3]) for i in xdata]
plt.plot(xdata,y_pred,'r--')
print(popt)
from sklearn.metrics import r2_score
r2 = r2_score(ydata , y_pred )
print('指数函数拟合R方为:',r2)