Trait NewtonProblem 

pub trait NewtonProblem: BasicProblem {
    // Required methods
    fn num_hessian_non_zeros(&self) -> usize;
    fn hessian_indices(&self, rows: &mut [i32], cols: &mut [i32]) -> bool;
    fn hessian_values(&self, x: &[f64], vals: &mut [f64]) -> bool;
}

An extension to the BasicProblem trait that enables full Newton iterations in Ipopt.

If this trait is NOT implemented by your problem, Ipopt will be set to perform Quasi-Newton Approximation for second derivatives. This interface asks for the Hessian matrix in sparse triplet form.

Required Methods

fn num_hessian_non_zeros(&self) -> usize

Number of non-zeros in the Hessian matrix.

fn hessian_indices(&self, rows: &mut [i32], cols: &mut [i32]) -> bool

Hessian indices.

These are the row and column indices of the non-zeros in the sparse representation of the matrix. This is a symmetric matrix, fill the lower left triangular half only. If your problem is constrained (i.e. you are ultimately implementing ConstrainedProblem), ensure that you provide coordinates for non-zeros of the constraint hessian as well. This function is internally called by Ipopt callback eval_h.

fn hessian_values(&self, x: &[f64], vals: &mut [f64]) -> bool

Objective Hessian values.

Each value must correspond to the row and column as specified in hessian_indices. This function is internally called by Ipopt callback eval_h and each value is premultiplied by Ipopt’s obj_factor as necessary.

Implementors