`scipy.optimize._trustregion_constr.equality_constrained_sqp:equality_constrained_sqp`

source: /scipy/optimize/_trustregion_constr/equality_constrained_sqp.py :17

Signature

   def     equality_constrained_sqp (    fun_and_constr    ,    grad_and_jac    ,    lagr_hess    ,    x0    ,    fun0    ,    grad0    ,    constr0    ,    jac0    ,    stop_criteria    ,    state    ,    initial_penalty    ,    initial_trust_radius    ,    factorization_method    ,    trust_lb    =  None   ,    trust_ub    =  None   ,    scaling    =  <function default_scaling at 0x0000>     )

Summary

Solve nonlinear equality-constrained problem using trust-region SQP.

Extended Summary

Solve optimization problem:

minimize fun(x) subject to: constr(x) = 0

using Byrd-Omojokun Trust-Region SQP method described in ^[1]. Several implementation details are based on ^[2] and ^[3], p. 549.

Aliases

scipy.optimize._trustregion_constr.equality_constrained_sqp.equality_constrained_sqp