ó î&]\c@`s‘dZddlmZmZmZddlZddlZddlZ ddl m Z m Z gZ d dddd„Zde fd„ƒYZdS( s$Newton-CG trust-region optimization.i(tdivisiontprint_functiontabsolute_importNi(t_minimize_trust_regiontBaseQuadraticSubproblemcK`sp|dkrtdƒ‚n|dkrB|dkrBtdƒ‚nt||d|d|d|d|dt|S( s2 Minimization of scalar function of one or more variables using the Newton conjugate gradient trust-region algorithm. Options ------- initial_trust_radius : float Initial trust-region radius. max_trust_radius : float Maximum value of the trust-region radius. No steps that are longer than this value will be proposed. eta : float Trust region related acceptance stringency for proposed steps. gtol : float Gradient norm must be less than `gtol` before successful termination. s<Jacobian is required for Newton-CG trust-region minimizationsdEither the Hessian or the Hessian-vector product is required for Newton-CG trust-region minimizationtargstjacthessthesspt subproblemN(tNonet ValueErrorRtCGSteihaugSubproblem(tfuntx0RRRRttrust_region_options((s>lib/python2.7/site-packages/scipy/optimize/_trustregion_ncg.pyt_minimize_trust_ncg s  R cB`seZdZd„ZRS(s:Quadratic subproblem solved by a conjugate gradient methodcC`stj|jƒ}tdtj|jƒƒ|j}|j|krSt}||fS|}|j}| }xtrû|j |ƒ}tj ||ƒ} | dkr |j |||ƒ\} } || |} || |} || ƒ|| ƒkr÷| }n| }t}||fStj ||ƒ}|| }|||}t j j|ƒ|krˆ|j |||ƒ\} } || |}t}||fS|||}tj ||ƒ}tj|ƒ|krÍt}||fS||}| ||}|}|}|}qlWdS(s´ Solve the subproblem using a conjugate gradient method. 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 ----- This is algorithm (7.2) of Nocedal and Wright 2nd edition. Only the function that computes the Hessian-vector product is required. The Hessian itself is not required, and the Hessian does not need to be positive semidefinite. gà?iN(tnpt zeros_likeRtmintmathtsqrttjac_magtFalsetTrueRtdottget_boundaries_intersectionstscipytlinalgtnorm(tselft trust_radiustp_origint tolerancet hits_boundarytztrtdtBdtdBdttattbtpatpbt p_boundaryt r_squaredtalphatz_nexttr_nexttr_next_squaredt beta_nexttd_next((s>lib/python2.7/site-packages/scipy/optimize/_trustregion_ncg.pytsolve.sL"          (t__name__t __module__t__doc__R4(((s>lib/python2.7/site-packages/scipy/optimize/_trustregion_ncg.pyR ,s((R7t __future__RRRRtnumpyRt scipy.linalgRt _trustregionRRt__all__R RR (((s>lib/python2.7/site-packages/scipy/optimize/_trustregion_ncg.pyts