satlas.stats.fitting.chisquare_fit

satlas.stats.fitting.chisquare_fit(f, x, y, yerr=None, xerr=None, func=None, verbose=True, hessian=False, method='leastsq')

Use a non-linear least squares minimization (Levenberg-Marquardt) algorithm to minimize the chi-square of the fit to data x and y with errorbars yerr.

Parameters:

• f (BaseModel) – Model object containing all the information about the fit; will be fitted to the given data.
• x (array_like) – Experimental data for the x-axis.
• y (array_like) – Experimental data for the y-axis.
• yerr (array_like) – Uncertainties on y.

Other Parameters:  

• xerr (array_like, optional) – Uncertainties on x.
• func (function, optional) – Uses the provided function on the fitvalue to calculate the errorbars.
• verbose (boolean, optional) – When set to True, a tqdm-progressbar in the terminal is maintained. Defaults to True.
• hessian (boolean, optional) – When set to True, the SATLAS implementation of the Hessian uncertainty estimate is calculated, otherwise the LMFIT version is used. Defaults to False.
• method (string, optional) – Sets the method to be used by lmfit for the fitting. See lmfit for all options.

Returns:

success, message – Boolean indicating the success of the convergence, and the message from the optimizer.

Return type:

tuple