# EDM#

class zfit.minimize.EDM(tol, loss, params, name='edm')[source]#

Bases: zfit.minimizers.termination.ConvergenceCriterion

Estimated distance to minimum.

This criterion estimates the distance to the minimum by using

$EDM = g^T \cdot H^{-1} \cdot g$

with H the hessian matrix (approximation) and g the gradient.

This is the same criterion as iminuit uses internally as well.

Parameters
• tol (float) – Tolerance for the criterion. If the criterion value is below the tol (usually), it is converged.

• loss (ZfitLoss) – loss that will we minimized.

• params (TypeVar(ParamTypeInput, zfit.core.interfaces.ZfitParameter, Union[int, float, complex, Tensor, zfit.core.interfaces.ZfitParameter])) – Parameters that will be minimized.

• name (Optional[str]) – Human readable name or description.

calculate(result)#

Evaluate the convergence criterion and store it in last_value

Parameters

() (result) –

converged(result)#

Calculate the criterion and check if it is below the tolerance.

Parameters

result (zfit.core.fitresult.FitResult) – Return the result which contains all the information

Returns:

Return type

bool