Is there a good way to optimize p0 in scipy.optimize.curve_fit?
This is not algorithmic. It all depends on the model and data. E.g., if there's a sinusoid, a rough guess for the period (e.g. from the distance between maxima) goes a long way etc
I am trying to use curve fit to fit some temperature that looks like a sinusoid function added to a linear function. My initial predictions are way off and I believe it is because I need to adjust p0, however I was wondering if there was a good way to get an initial guess for p0 or if its just an endless game of guess and check. Alternatively, if there is a better way to get the regression line please let me know!
Thanks!