<Plot:来自curve_fit和lmfit的不正确的拟合>
案子-A回来了,
OptimizeWarning: Covariance of the parameters could not beestimated (如果省略几个初始数据点,则fit将返回一些结果,这些结果并不坏,但仍然与已知的最佳拟合结果不同)。: Optimal parameters not found: Number of calls to function has reached maxfev = 5000.将maxfev设置为更高,则fit
使用这些fit参数作为初始猜测,将fit扩展到整个数组,这给出了一个类似于的图。matplotlib.pyplot as pltfrom numpy import genfromtxttemperature = csv[:,1]
P = pressure
# defines the function and initial fit光敏电阻产生的数据并不是
/anaconda3/lib/python3.8/site-packages/sklearn/pipeline.py in fit(self, X, y, **fit_params)
~/opt/anaconda3/lib/python3.8/site-packages/sklearn/pipeline.py in fit_transform(self,
不幸的是,我得到了一个错误: File "C:\Python35\lib\site-packages_fit(X, y, **fit_params)
File "C:\Python35\lib\site-packages\sklearn\pipeline.py", line 213, in _fit**f
\Python37\site-packages\sklearn\model_selection\_search.py in fit(self, X, y, groups, **fit_params)fit_params)
~\AppData\Roaming\Python\Python37\site-packages\sklearn\pipeline.py in fit(self, X, y, *This is necessary when loading the tr