imap_processing.idex.idex_l2a.chi_square

imap_processing.idex.idex_l2a.chi_square(observed: ndarray, expected: ndarray, num_params: int) → tuple[float, float]

Calculate the chi-square and reduced chi-square statistics.

This implementation follows the approach used in lmfit.minimize()’s _calculate_statistics() method, which calculates chi-square as the sum of squared residuals:

chisqr = (residual**2).sum()

And reduced chi-square as the chi-square divided by degrees of freedom:

ndata = len(residual) nfree = ndata - number_of_parameters redchi = chisqr / max(1, nfree)

Parameters:

• observed (numpy.ndarray) – The observed signal.

• expected (numpy.ndarray) – The expected signal calculated with the fit parameters.

• num_params (int) – The number of parameters used in the fit.

Returns:

• chisqr (float) – The chi-square value.

• redchi (float) – The reduced chi-square value.