[−][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;
    pub fn set_params(&mut self, x: &Vector<F, N, Self::ParameterStorage>);

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

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

    pub 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>[src]

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>[src]

type ParameterStorage: ContiguousStorageMut<F, N> + Clone[src]

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Required methods

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

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

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

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

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

Compute the residual vector.

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

Compute the Jacobian of the residual vector.

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Implementors

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