Python/curve_fit: cannot pass array with init guess

问题

I have this function to compute some sort of polynomial:

def pipoly(df,pj):
    n=np.size(pj)
    p=pj[0]
    for j in range(1,n):
        p+=pj[j]*df**j
    return p

pj is supposed to be an array that contains the initial guesses of the coefficients of the polynomial; the degree of the polynomial is hence determined by the function itself in the first line. df is a scalar variable. This function is passed to scipy.optimize's curve_fit as

parfit,covfig=curve_fit(pipoly,[f-f0[j] for f in f_df[if0[j]:if0[i]]],
                            pmode_xp[ph][if0[j]:if0[i]],
                            p0=([pmode0[ph][-1],(pmode_xp[ph][if0[i]]-pmode_xp[ph][if0[j]])/df]))

The first two arguments after the name of the function are arrays (1D slices of 2D arrays), and I have confirmed that they have the same length. The third argument after pipoly is supposed to be a tuple with the initial guesses for pj, which I printed out before: [0.4586590267346888, 0.7419930843896957]. So why is Python complaining that TypeError: pipoly() takes 2 positional arguments but 3 were given? And if I remove the p0 argument, I'm told that the pj is considered a scalar and can therefore not have an index. How do I make it clear to pipoly that pj is to be an array?

回答1:

Your statement:

pj is supposed to be an array that contains the coefficients of the polynomial;

is wrong. According to curve_fit() docs:

scipy.optimize.curve_fit(f, xdata, ydata, p0=None, sigma=None, absolute_sigma=False, check_finite=True, bounds=(-inf, inf), method=None, jac=None, **kwargs)[source] Use non-linear least squares to fit a function, f, to data.

Assumes ydata = f(xdata, *params) + eps

That means that your pipoly() function, to be used by curve_fit() must take a number of arguments equal to the number of parameters of you polynomial plus one (the variable, which is the first argument).
The error:

TypeError: pipoly() takes 2 positional arguments but 3 were given?

is telling you that pipoly receives 3 arguments because you probably were testing a linear polinomyal, so the three arguments were the independent variable and two parameter (the [f-f0[j] for f in f_df[if0[j]:if0[i]]] stuff is a 2-length list).
As you write it, instead it takes 2 argument only.

You can easily solve your problem by adding an asterisk before pj:

def pipoly(df,*pj):
    n=len(pj) #len() is sufficient here, but np.size() works too.
    p=pj[0]
    for j in range(1,n):
        p+=pj[j]*df**j
    return p

This way your function accepts a variable number of arguments. Here more on the meaning and the use of the asterisk in python function parameters.

来源：https://stackoverflow.com/questions/54974948/python-curve-fit-cannot-pass-array-with-init-guess