[−][src]Trait levenberg_marquardt::LeastSquaresProblem

pub trait LeastSquaresProblem<F, M, N> where
    F: ComplexField,
    N: Dim,
    M: Dim, {
    type ResidualStorage: ContiguousStorageMut<F, M>;
    type JacobianStorage: ContiguousStorageMut<F, M, N>;
    type ParameterStorage: ContiguousStorageMut<F, N> + 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>>;
}

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: ContiguousStorageMut<F, M>`

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

`type JacobianStorage: ContiguousStorageMut<F, M, N>`

`type ParameterStorage: ContiguousStorageMut<F, N> + Clone`

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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.

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Implementors

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