qspec.analyze.odr_fit  (  f ,  x ,  y ,  sigma_x = None ,  sigma_y = None ,  p0 = None ,  p0_d = None ,  p0_fixed = None ,  report = False ,  ** kwargs  )[source]

Parameters:

fCallable

The model function to fit to the data.

xndarray | Iterable

The x data.

yndarray | Iterable

The y data.

sigma_xndarray | Iterable

The 1-sigma uncertainty of the x data.

sigma_yndarray | Iterable

The 1-sigma uncertainty of the y data.

p0ndarray | Iterable

A numpy array or an Iterable of the initial guesses for the parameters. Must have at least the same length as the minimum number of parameters required by the function 'f'. If 'p0' is None, 1 is taken as an initial guess for all non-keyword parameters.

p0_dndarray | Iterable

A numpy array or an Iterable of the uncertainties of the initial guesses for the parameters. Must have the same length as p0.

p0_fixedndarray | Iterable

A numpy array or an Iterable of bool values specifying, whether to fix a parameter. Must have the same length as p0.

reportbool

Whether to print the result of the fit.

kwargsNone

Additional keyword arguments are passed to odr.ODR.

Returns:

out(ndarray, ndarray)

popt, pcov. The optimal parameters and their covariance matrix.