Struct ConstrainedQuadratic 

pub struct ConstrainedQuadratic<M, V> {
    pub c: V,
    pub a: M,
    pub b: V,
}

Available on crate feature problems only.

Linearly-constrained quadratic min Σ (xᵢ − cᵢ)² s.t. A x ≤ b. Holds the objective center c, constraint matrix A, and right-hand side b; M is the (dense) matrix backend and V the matching vector backend.

Fields

c: V

Center c of the quadratic; the unconstrained minimizer.

a: M

Constraint matrix A (m × n, dense).

b: V

Right-hand side b ∈ ℝᵐ.

Implementations

impl<M, V> ConstrainedQuadratic<M, V>

pub fn new(c: V, a: M, b: V) -> Self

Build the fixture from an objective center and the constraints A x ≤ b.

Trait Implementations

impl CostFunction for ConstrainedQuadratic<Array2<f64>, Array1<f64>>

Available on crate feature ndarray only.

type Param = ArrayBase<OwnedRepr<f64>, Dim<[usize; 1]>>

The parameter type the objective is defined over.

type Output = f64

Scalar cost type. In practice f64 (see AGENTS.md’s provisional choices).

fn cost(&self, x: &Array1<f64>) -> f64

Evaluate the objective at param.

impl CostFunction for ConstrainedQuadratic<DenseMatrix, Vec<f64>>

type Param = Vec<f64>

The parameter type the objective is defined over.

type Output = f64

Scalar cost type. In practice f64 (see AGENTS.md’s provisional choices).

fn cost(&self, x: &Vec<f64>) -> f64

Evaluate the objective at param.

impl CostFunction for ConstrainedQuadratic<Mat<f64>, Col<f64>>

Available on crate feature faer only.

type Param = Col<Own<f64>>

The parameter type the objective is defined over.

type Output = f64

Scalar cost type. In practice f64 (see AGENTS.md’s provisional choices).

fn cost(&self, x: &Col<f64>) -> f64

Evaluate the objective at param.

impl CostFunction for ConstrainedQuadratic<DMatrix<f64>, DVector<f64>>

Available on crate feature nalgebra only.

type Param = Matrix<f64, Dyn, Const<1>, VecStorage<f64, Dyn, Const<1>>>

The parameter type the objective is defined over.

type Output = f64

Scalar cost type. In practice f64 (see AGENTS.md’s provisional choices).

fn cost(&self, x: &DVector<f64>) -> f64

Evaluate the objective at param.

impl Gradient for ConstrainedQuadratic<Array2<f64>, Array1<f64>>

Available on crate feature ndarray only.

type Param = ArrayBase<OwnedRepr<f64>, Dim<[usize; 1]>>

The parameter type the gradient is defined over (matches CostFunction::Param).

type Gradient = ArrayBase<OwnedRepr<f64>, Dim<[usize; 1]>>

The gradient type. Typically the same as Param.

fn gradient(&self, x: &Array1<f64>) -> Array1<f64>

Evaluate the gradient at param.

impl Gradient for ConstrainedQuadratic<DenseMatrix, Vec<f64>>

type Param = Vec<f64>

The parameter type the gradient is defined over (matches CostFunction::Param).

type Gradient = Vec<f64>

The gradient type. Typically the same as Param.

fn gradient(&self, x: &Vec<f64>) -> Vec<f64>

Evaluate the gradient at param.

impl Gradient for ConstrainedQuadratic<Mat<f64>, Col<f64>>

Available on crate feature faer only.

type Param = Col<Own<f64>>

The parameter type the gradient is defined over (matches CostFunction::Param).

type Gradient = Col<Own<f64>>

The gradient type. Typically the same as Param.

fn gradient(&self, x: &Col<f64>) -> Col<f64>

Evaluate the gradient at param.

impl Gradient for ConstrainedQuadratic<DMatrix<f64>, DVector<f64>>

Available on crate feature nalgebra only.

type Param = Matrix<f64, Dyn, Const<1>, VecStorage<f64, Dyn, Const<1>>>

The parameter type the gradient is defined over (matches CostFunction::Param).

type Gradient = Matrix<f64, Dyn, Const<1>, VecStorage<f64, Dyn, Const<1>>>

The gradient type. Typically the same as Param.

fn gradient(&self, x: &DVector<f64>) -> DVector<f64>

Evaluate the gradient at param.

impl<M, V> HasSpec for ConstrainedQuadratic<M, V>

const SPEC: &'static ProblemSpec

The catalogue entry for this problem type.

impl LinearInequalityConstraints for ConstrainedQuadratic<Array2<f64>, Array1<f64>>

Available on crate feature ndarray only.

type Matrix = ArrayBase<OwnedRepr<f64>, Dim<[usize; 2]>>

The m × n constraint-matrix type. Consumers bound this on MatVec<Param> + MatTransposeVec<Param>.

fn a(&self) -> &Array2<f64>

The constraint matrix A (m rows = number of inequalities).

fn b(&self) -> &Array1<f64>

The right-hand side b ∈ ℝᵐ.

impl LinearInequalityConstraints for ConstrainedQuadratic<DenseMatrix, Vec<f64>>

type Matrix = DenseMatrix

The m × n constraint-matrix type. Consumers bound this on MatVec<Param> + MatTransposeVec<Param>.

fn a(&self) -> &DenseMatrix

The constraint matrix A (m rows = number of inequalities).

fn b(&self) -> &Vec<f64>

The right-hand side b ∈ ℝᵐ.

impl LinearInequalityConstraints for ConstrainedQuadratic<Mat<f64>, Col<f64>>

Available on crate feature faer only.

type Matrix = Mat<Own<f64>>

The m × n constraint-matrix type. Consumers bound this on MatVec<Param> + MatTransposeVec<Param>.

fn a(&self) -> &Mat<f64>

The constraint matrix A (m rows = number of inequalities).

fn b(&self) -> &Col<f64>

The right-hand side b ∈ ℝᵐ.

impl LinearInequalityConstraints for ConstrainedQuadratic<DMatrix<f64>, DVector<f64>>

Available on crate feature nalgebra only.

type Matrix = Matrix<f64, Dyn, Dyn, VecStorage<f64, Dyn, Dyn>>

The m × n constraint-matrix type. Consumers bound this on MatVec<Param> + MatTransposeVec<Param>.

fn a(&self) -> &DMatrix<f64>

The constraint matrix A (m rows = number of inequalities).

fn b(&self) -> &DVector<f64>

The right-hand side b ∈ ℝᵐ.