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.