pub fn user_grad_lag(nlp: &dyn IpoptNlp, glx: &[Number]) -> Vec<Number> ⓘExpand description
The algorithm’s own ∇L (var-x, scaled: obj·∇f + J̃ᵀỹ − z̃_L + z̃_U,
upstream curr_grad_lag_x) as the unscaled ∇f + Jᵀλ − z_L + z_U of the
TNLP nlp wraps — ÷ obj, the row factors cancelling in J̃ᵀỹ — at
full x, 0 at a column the algorithm does not hold (upstream
ResortX(…, usefixedvals=false)). Its ∇f and J are the ones the
algorithm evaluated at the iterate, so this costs no evaluation.