Struct bayes_estimate::noise::CoupledNoise
source · pub struct CoupledNoise<N: RealField, D: Dim, QD: Dim>{
pub q: OVector<N, QD>,
pub G: OMatrix<N, D, QD>,
}
Expand description
Additive noise.
Noise represented as a noise variance vector and a noise coupling matrix. The noise covariance is G.q.G’.
Fields§
§q: OVector<N, QD>
Noise variance
G: OMatrix<N, D, QD>
Noise coupling
Implementations§
source§impl<N: Copy + RealField, D: Dim> CoupledNoise<N, D, D>
impl<N: Copy + RealField, D: Dim> CoupledNoise<N, D, D>
Creates a CoupledNoise from an UncorrelatedNoise. The resulting ‘G’ is an identity matrix.
Creates a CoupledNoise from the Cholesky factor of a CorrelatedNoise. The CorrelatedNoise must be PSD. The resulting ‘q’ is always a vector of 1s.
Auto Trait Implementations§
impl<N, D, QD> !RefUnwindSafe for CoupledNoise<N, D, QD>
impl<N, D, QD> !Send for CoupledNoise<N, D, QD>
impl<N, D, QD> !Sync for CoupledNoise<N, D, QD>
impl<N, D, QD> !Unpin for CoupledNoise<N, D, QD>
impl<N, D, QD> !UnwindSafe for CoupledNoise<N, D, QD>
Blanket Implementations§
source§impl<T> BorrowMut<T> for Twhere
T: ?Sized,
impl<T> BorrowMut<T> for Twhere
T: ?Sized,
source§fn borrow_mut(&mut self) -> &mut T
fn borrow_mut(&mut self) -> &mut T
Mutably borrows from an owned value. Read more
§impl<SS, SP> SupersetOf<SS> for SPwhere
SS: SubsetOf<SP>,
impl<SS, SP> SupersetOf<SS> for SPwhere
SS: SubsetOf<SP>,
§fn to_subset(&self) -> Option<SS>
fn to_subset(&self) -> Option<SS>
The inverse inclusion map: attempts to construct
self
from the equivalent element of its
superset. Read more§fn is_in_subset(&self) -> bool
fn is_in_subset(&self) -> bool
Checks if
self
is actually part of its subset T
(and can be converted to it).§fn to_subset_unchecked(&self) -> SS
fn to_subset_unchecked(&self) -> SS
Use with care! Same as
self.to_subset
but without any property checks. Always succeeds.§fn from_subset(element: &SS) -> SP
fn from_subset(element: &SS) -> SP
The inclusion map: converts
self
to the equivalent element of its superset.