Trait levenberg_marquardt::LeastSquaresProblem

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pub trait LeastSquaresProblem<F, M, N> where
    F: ComplexField + Copy,
    N: Dim,
    M: Dim, {
    type ResidualStorage: RawStorageMut<F, M> + Storage<F, M> + IsContiguous;
    type JacobianStorage: RawStorageMut<F, M, N> + Storage<F, M, N> + IsContiguous;
    type ParameterStorage: RawStorageMut<F, N> + Storage<F, N> + IsContiguous + Clone;
    fn set_params(&mut self, x: &Vector<F, N, Self::ParameterStorage>);
    fn params(&self) -> Vector<F, N, Self::ParameterStorage>;
    fn residuals(&self) -> Option<Vector<F, M, Self::ResidualStorage>>;
    fn jacobian(&self) -> Option<Matrix<F, M, N, Self::JacobianStorage>>;
}

Expand description

A least squares minimization problem.

This is what LevenbergMarquardt needs to compute the residuals and the Jacobian. See the module documentation for a usage example.

Associated Types

type ResidualStorage: RawStorageMut<F, M> + Storage<F, M> + IsContiguous

Storage type used for the residuals. Use nalgebra::storage::Owned<F, M> if you want to use VectorN or MatrixMN.

type JacobianStorage: RawStorageMut<F, M, N> + Storage<F, M, N> + IsContiguous

type ParameterStorage: RawStorageMut<F, N> + Storage<F, N> + IsContiguous + Clone

Required methods

fn set_params(&mut self, x: &Vector<F, N, Self::ParameterStorage>)

Set the stored parameters $\vec{x}$ .

fn params(&self) -> Vector<F, N, Self::ParameterStorage>

Get the current parameter vector $\vec{x}$ .

fn residuals(&self) -> Option<Vector<F, M, Self::ResidualStorage>>

Compute the residual vector.

fn jacobian(&self) -> Option<Matrix<F, M, N, Self::JacobianStorage>>

Compute the Jacobian of the residual vector.

Implementors