Struct bayes_estimate::noise::CoupledNoise [−][src]
pub struct CoupledNoise<N: RealField, D: Dim, QD: Dim> where
DefaultAllocator: Allocator<N, D, QD> + Allocator<N, QD>, { pub q: OVector<N, QD>, pub G: OMatrix<N, D, QD>, }
Expand description
Additive noise.
Noise represented as a the 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
impl<N: Copy + RealField, D: Dim> CoupledNoise<N, D, D> where
DefaultAllocator: Allocator<N, D, D> + Allocator<N, D>,
impl<N: Copy + RealField, D: Dim> CoupledNoise<N, D, D> where
DefaultAllocator: Allocator<N, D, D> + Allocator<N, D>,
Creates a CoupledNoise from an 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
Mutably borrows from an owned value. Read more
type Output = T
type Output = T
Should always be Self
The inverse inclusion map: attempts to construct self from the equivalent element of its
superset. Read more
pub fn is_in_subset(&self) -> bool
pub fn is_in_subset(&self) -> bool
Checks if self is actually part of its subset T (and can be converted to it).
pub fn to_subset_unchecked(&self) -> SS
pub fn to_subset_unchecked(&self) -> SS
Use with care! Same as self.to_subset but without any property checks. Always succeeds.
pub fn from_subset(element: &SS) -> SP
pub fn from_subset(element: &SS) -> SP
The inclusion map: converts self to the equivalent element of its superset.