SteepestDescent

class optking.stepAlgorithms.SteepestDescent(molsys, history, params)

Bases: OptimizationAlgorithm

Steepest descent with step size adjustment

Notes

dq = c * fq

Methods Summary

expected_energy(dq, fq, H)	Quadratic energy model
requires()	Returns tuple with strings ('energy', 'gradient', 'hessian') for what the algorithm needs to compute a new point
step(fq, *args, **kwargs)	Basic form of the algorithm
step_size_scalar(fq)	Perform two point calculation of steepest descent step_size
supports_trust_region()	Returns boolean for whether a trust region should be used with this method

Methods Documentation

expected_energy(dq, fq, H)

Quadratic energy model

requires()

Returns tuple with strings (‘energy’, ‘gradient’, ‘hessian’) for what the algorithm needs to compute a new point

step(fq, *args, **kwargs)

Basic form of the algorithm

step_size_scalar(fq)

Perform two point calculation of steepest descent step_size

supports_trust_region()

Returns boolean for whether a trust region should be used with this method