Scipy

class zfit.minimize.Scipy(minimizer='L-BFGS-B', tolerance=None, verbosity=5, name=None, **minimizer_options)[source]

Bases: zfit.minimizers.baseminimizer.BaseMinimizer

minimize(loss, params=None)

Fully minimize the loss with respect to params.

Parameters

  • loss (ZfitLoss) – Loss to be minimized.

  • params (Optional[Iterable[ZfitParameter]]) – The parameters with respect to which to minimize the loss. If None, the parameters will be taken from the loss.

Return type

FitResult

Returns

The fit result.

step(loss, params=None)

Perform a single step in the minimization (if implemented).

Parameters

params (Union[Iterable[ZfitParameter], None, Iterable[str]]) –

Returns:

Raises

MinimizeStepNotImplementedError – if the step method is not implemented in the minimizer.

Minuit BFGS