5.15.1. minimizer.auto

eminus.minimizer.auto(scf, Nit, cost=scf_step, grad=get_grad, condition=check_convergence, betat=3e-5, cgform=1)

Automatic preconditioned conjugate-gradient minimization algorithm.

This function chooses an sd step over the pccg step if the energy goes up.

Parameters:

• scf – SCF object.

• Nit – Maximum number of SCF steps.

Keyword Arguments:

• cost – Function that will run every SCF step.

• grad – Function that calculates the respective gradient.

• condition – Function to check and log the convergence condition.

• betat – Step size.

• cgform – Conjugate gradient form.

Returns:

Total energies per SCF cycle.