Trait ndarray_linalg::least_squares::LeastSquaresSvd [−][src]
pub trait LeastSquaresSvd<D, E, I> where
D: Data<Elem = E>,
E: Scalar + Lapack,
I: Dimension, { fn least_squares(
&self,
rhs: &ArrayBase<D, I>
) -> Result<LeastSquaresResult<E, I>>; }
Expand description
Solve least squares for immutable references
Required methods
fn least_squares(
&self,
rhs: &ArrayBase<D, I>
) -> Result<LeastSquaresResult<E, I>>
fn least_squares(
&self,
rhs: &ArrayBase<D, I>
) -> Result<LeastSquaresResult<E, I>>
Solve a least squares problem of the form Ax = rhs
by calling A.least_squares(&rhs). A and rhs
are unchanged.
A and rhs must have the same layout, i.e. they must
be both either row- or column-major format, otherwise a
IncompatibleShape error is raised.
Implementations on Foreign Types
Solve least squares for immutable references and a single
column vector as a right-hand side.
E is one of f32, f64, c32, c64. D1, D2 can be any
valid representation for ArrayBase (over E).
Solve a least squares problem of the form Ax = rhs
by calling A.least_squares(&rhs), where rhs is a
single column vector. A and rhs are unchanged.
A and rhs must have the same layout, i.e. they must
be both either row- or column-major format, otherwise a
IncompatibleShape error is raised.
Solve least squares for immutable references and matrix
(=mulitipe vectors) as a right-hand side.
E is one of f32, f64, c32, c64. D1, D2 can be any
valid representation for ArrayBase (over E).
Solve a least squares problem of the form Ax = rhs
by calling A.least_squares(&rhs), where rhs is
matrix. A and rhs are unchanged.
A and rhs must have the same layout, i.e. they must
be both either row- or column-major format, otherwise a
IncompatibleShape error is raised.