Passing additional arguments using scipy.optimize.curve_fit?

Question

I am writing a program in Python that will fit Gaussian and Lorentzian shapes to some given resonance data. I originally began using scipy.optimize.leastsq but

Answer 1

The great thing about python is that you can define functions that return other functions, try currying:

def make_mix(numg): 
    def mix(x, *p): 
        ng = numg
        p1 = p[:3*ng]
        p2 = p[3*ng:]
        a = sumarray(gaussian(x,p1),lorentzian(x,p2))
        return a
    return mix

and then

leastsq, covar = opt.curve_fit(make_mix(numg),energy,intensity,inputtot)