`scipy.optimize._trustregion_dogleg:DoglegSubproblem.solve`

source: /scipy/optimize/_trustregion_dogleg.py :62

Signature

def solve ( self , trust_radius )

Summary

Minimize a function using the dog-leg trust-region algorithm.

Extended Summary

This algorithm requires function values and first and second derivatives. It also performs a costly Hessian decomposition for most iterations, and the Hessian is required to be positive definite.

Parameters

trust_radius : float: We are allowed to wander only this far away from the origin.

Returns

p : ndarray: The proposed step.
hits_boundary : bool: True if the proposed step is on the boundary of the trust region.

Notes

The Hessian is required to be positive definite.

Aliases

scipy.optimize._trustregion_dogleg.DoglegSubproblem.solve