Pass tuple as input argument for scipy.optimize.curve_fit

Question

I have the following code:

import numpy as np
from scipy.optimize import curve_fit


def func(x, p): return p[0] + p[1] + x


popt, pcov = curve_fit(func, np.ara         


        

Answer 1

Problem

When using curve_fit you must explicitly say the number of fit parameters. Doing something like:

def f(x, *p):
    return sum( [p[i]*x**i for i in range(len(p))] )

would be great, since it would be a general nth-order polynomial fitting function, but unfortunately, in my SciPy 0.12.0, it raises:

ValueError: Unable to determine number of fit parameters.

Solution

So you should do:

def f_1(x, p0, p1):
    return p0 + p1*x

def f_2(x, p0, p1, p2):
    return p0 + p1*x + p2*x**2

and so forth...

Then you can call using the p0 argument:

curve_fit(f_1, xdata, ydata, p0=(0,0))