Struct bayes_estimate::estimators::information_root::InformationRootState [−][src]
Information State.
Linear representation as a information root state vector and the information root (upper triangular) matrix. For a given KalmanState the information root state inverse(R).inverse(R)’ == X, r == R.x For a given InformationState the information root state R’.R == I, r == invserse(R).i
Fields
r: VectorN<N, D>
Information root state vector
R: MatrixN<N, D>
Information root matrix (upper triangular)
Implementations
impl<N: RealField, D: Dim> InformationRootState<N, D> where
DefaultAllocator: Allocator<N, D, D> + Allocator<N, D>,
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DefaultAllocator: Allocator<N, D, D> + Allocator<N, D>,
pub fn new_zero(d: D) -> InformationRootState<N, D>
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pub fn init_information(
&mut self,
state: &InformationState<N, D>
) -> Result<N, &'static str>
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&mut self,
state: &InformationState<N, D>
) -> Result<N, &'static str>
pub fn information_state(
&self
) -> Result<(N, InformationState<N, D>), &'static str>
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&self
) -> Result<(N, InformationState<N, D>), &'static str>
impl<N: RealField, D: Dim> InformationRootState<N, D> where
DefaultAllocator: Allocator<N, D, D> + Allocator<N, D>,
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DefaultAllocator: Allocator<N, D, D> + Allocator<N, D>,
pub fn predict<QD: Dim>(
&mut self,
x_pred: &VectorN<N, D>,
fx: &MatrixN<N, D>,
noise: &CoupledNoise<N, D, QD>
) -> Result<(), &'static str> where
D: DimAdd<QD>,
DefaultAllocator: Allocator<N, DimSum<D, QD>, DimSum<D, QD>> + Allocator<N, DimSum<D, QD>> + Allocator<N, D, QD> + Allocator<N, QD>,
DimSum<D, QD>: DimMin<DimSum<D, QD>>,
DefaultAllocator: Allocator<N, DimMinimum<DimSum<D, QD>, DimSum<D, QD>>> + Allocator<N, DimMinimum<DimSum<D, QD>, DimSum<D, QD>>, DimSum<D, QD>>,
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&mut self,
x_pred: &VectorN<N, D>,
fx: &MatrixN<N, D>,
noise: &CoupledNoise<N, D, QD>
) -> Result<(), &'static str> where
D: DimAdd<QD>,
DefaultAllocator: Allocator<N, DimSum<D, QD>, DimSum<D, QD>> + Allocator<N, DimSum<D, QD>> + Allocator<N, D, QD> + Allocator<N, QD>,
DimSum<D, QD>: DimMin<DimSum<D, QD>>,
DefaultAllocator: Allocator<N, DimMinimum<DimSum<D, QD>, DimSum<D, QD>>> + Allocator<N, DimMinimum<DimSum<D, QD>, DimSum<D, QD>>, DimSum<D, QD>>,
pub fn predict_inv_model<QD: Dim>(
&mut self,
x_pred: &VectorN<N, D>,
fx_inv: &MatrixN<N, D>,
noise: &CoupledNoise<N, D, QD>
) -> Result<N, &'static str> where
D: DimAdd<QD>,
DefaultAllocator: Allocator<N, DimSum<D, QD>, DimSum<D, QD>> + Allocator<N, DimSum<D, QD>> + Allocator<N, D, QD> + Allocator<N, QD>,
DimSum<D, QD>: DimMin<DimSum<D, QD>>,
DefaultAllocator: Allocator<N, DimMinimum<DimSum<D, QD>, DimSum<D, QD>>> + Allocator<N, DimMinimum<DimSum<D, QD>, DimSum<D, QD>>, DimSum<D, QD>>,
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&mut self,
x_pred: &VectorN<N, D>,
fx_inv: &MatrixN<N, D>,
noise: &CoupledNoise<N, D, QD>
) -> Result<N, &'static str> where
D: DimAdd<QD>,
DefaultAllocator: Allocator<N, DimSum<D, QD>, DimSum<D, QD>> + Allocator<N, DimSum<D, QD>> + Allocator<N, D, QD> + Allocator<N, QD>,
DimSum<D, QD>: DimMin<DimSum<D, QD>>,
DefaultAllocator: Allocator<N, DimMinimum<DimSum<D, QD>, DimSum<D, QD>>> + Allocator<N, DimMinimum<DimSum<D, QD>, DimSum<D, QD>>, DimSum<D, QD>>,
pub fn observe_info<ZD: Dim>(
&mut self,
z: &VectorN<N, ZD>,
hx: &MatrixMN<N, ZD, D>,
noise_inv: &MatrixN<N, ZD>
) -> Result<(), &'static str> where
DefaultAllocator: Allocator<N, D, D> + Allocator<N, ZD, D> + Allocator<N, ZD, ZD> + Allocator<N, D> + Allocator<N, ZD>,
D: DimAdd<ZD> + DimAdd<U1>,
DefaultAllocator: Allocator<N, DimSum<D, ZD>, DimSum<D, U1>> + Allocator<N, DimSum<D, ZD>>,
DimSum<D, ZD>: DimMin<DimSum<D, U1>>,
DefaultAllocator: Allocator<N, DimMinimum<DimSum<D, ZD>, DimSum<D, U1>>> + Allocator<N, DimMinimum<DimSum<D, ZD>, DimSum<D, U1>>, DimSum<D, U1>>,
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&mut self,
z: &VectorN<N, ZD>,
hx: &MatrixMN<N, ZD, D>,
noise_inv: &MatrixN<N, ZD>
) -> Result<(), &'static str> where
DefaultAllocator: Allocator<N, D, D> + Allocator<N, ZD, D> + Allocator<N, ZD, ZD> + Allocator<N, D> + Allocator<N, ZD>,
D: DimAdd<ZD> + DimAdd<U1>,
DefaultAllocator: Allocator<N, DimSum<D, ZD>, DimSum<D, U1>> + Allocator<N, DimSum<D, ZD>>,
DimSum<D, ZD>: DimMin<DimSum<D, U1>>,
DefaultAllocator: Allocator<N, DimMinimum<DimSum<D, ZD>, DimSum<D, U1>>> + Allocator<N, DimMinimum<DimSum<D, ZD>, DimSum<D, U1>>, DimSum<D, U1>>,
Trait Implementations
impl<N: Clone + SimdRealField, D: Clone + Dim> Clone for InformationRootState<N, D> where
DefaultAllocator: Allocator<N, D, D> + Allocator<N, D>,
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DefaultAllocator: Allocator<N, D, D> + Allocator<N, D>,
fn clone(&self) -> InformationRootState<N, D>
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pub fn clone_from(&mut self, source: &Self)
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impl<N: RealField, D: Dim> Estimator<N, D> for InformationRootState<N, D> where
DefaultAllocator: Allocator<N, D, D> + Allocator<N, D>,
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DefaultAllocator: Allocator<N, D, D> + Allocator<N, D>,
impl<N: RealField, D: Dim, ZD: Dim> ExtendedLinearObserver<N, D, ZD> for InformationRootState<N, D> where
DefaultAllocator: Allocator<N, D, D> + Allocator<N, ZD, D> + Allocator<N, ZD, ZD> + Allocator<N, D> + Allocator<N, ZD>,
D: DimAdd<ZD> + DimAdd<U1>,
DefaultAllocator: Allocator<N, DimSum<D, ZD>, DimSum<D, U1>> + Allocator<N, DimSum<D, ZD>>,
DimSum<D, ZD>: DimMin<DimSum<D, U1>>,
DefaultAllocator: Allocator<N, DimMinimum<DimSum<D, ZD>, DimSum<D, U1>>> + Allocator<N, DimMinimum<DimSum<D, ZD>, DimSum<D, U1>>, DimSum<D, U1>>,
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DefaultAllocator: Allocator<N, D, D> + Allocator<N, ZD, D> + Allocator<N, ZD, ZD> + Allocator<N, D> + Allocator<N, ZD>,
D: DimAdd<ZD> + DimAdd<U1>,
DefaultAllocator: Allocator<N, DimSum<D, ZD>, DimSum<D, U1>> + Allocator<N, DimSum<D, ZD>>,
DimSum<D, ZD>: DimMin<DimSum<D, U1>>,
DefaultAllocator: Allocator<N, DimMinimum<DimSum<D, ZD>, DimSum<D, U1>>> + Allocator<N, DimMinimum<DimSum<D, ZD>, DimSum<D, U1>>, DimSum<D, U1>>,
fn observe_innovation(
&mut self,
s: &VectorN<N, ZD>,
hx: &MatrixMN<N, ZD, D>,
noise: &CorrelatedNoise<N, ZD>
) -> Result<(), &'static str>
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&mut self,
s: &VectorN<N, ZD>,
hx: &MatrixMN<N, ZD, D>,
noise: &CorrelatedNoise<N, ZD>
) -> Result<(), &'static str>
impl<N: RealField, D: Dim> KalmanEstimator<N, D> for InformationRootState<N, D> where
DefaultAllocator: Allocator<N, D, D> + Allocator<N, D>,
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DefaultAllocator: Allocator<N, D, D> + Allocator<N, D>,
fn init(&mut self, state: &KalmanState<N, D>) -> Result<(), &'static str>
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fn kalman_state(&self) -> Result<KalmanState<N, D>, &'static str>
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impl<N: PartialEq + SimdRealField, D: PartialEq + Dim> PartialEq<InformationRootState<N, D>> for InformationRootState<N, D> where
DefaultAllocator: Allocator<N, D, D> + Allocator<N, D>,
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DefaultAllocator: Allocator<N, D, D> + Allocator<N, D>,
fn eq(&self, other: &InformationRootState<N, D>) -> bool
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fn ne(&self, other: &InformationRootState<N, D>) -> bool
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impl<N: SimdRealField, D: Dim> StructuralPartialEq for InformationRootState<N, D> where
DefaultAllocator: Allocator<N, D, D> + Allocator<N, D>,
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DefaultAllocator: Allocator<N, D, D> + Allocator<N, D>,
Auto Trait Implementations
impl<N, D> !RefUnwindSafe for InformationRootState<N, D>
impl<N, D> !Send for InformationRootState<N, D>
impl<N, D> !Sync for InformationRootState<N, D>
impl<N, D> !Unpin for InformationRootState<N, D>
impl<N, D> !UnwindSafe for InformationRootState<N, D>
Blanket Implementations
impl<T> Any for T where
T: 'static + ?Sized,
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T: 'static + ?Sized,
impl<T> Borrow<T> for T where
T: ?Sized,
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T: ?Sized,
impl<T> BorrowMut<T> for T where
T: ?Sized,
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T: ?Sized,
pub fn borrow_mut(&mut self) -> &mut T
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impl<T> From<T> for T
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impl<T, U> Into<U> for T where
U: From<T>,
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U: From<T>,
impl<T> Same<T> for T
type Output = T
Should always be Self
impl<SS, SP> SupersetOf<SS> for SP where
SS: SubsetOf<SP>,
SS: SubsetOf<SP>,
pub fn to_subset(&self) -> Option<SS>
pub fn is_in_subset(&self) -> bool
pub fn to_subset_unchecked(&self) -> SS
pub fn from_subset(element: &SS) -> SP
impl<T> ToOwned for T where
T: Clone,
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T: Clone,
type Owned = T
The resulting type after obtaining ownership.
pub fn to_owned(&self) -> T
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pub fn clone_into(&self, target: &mut T)
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impl<T, U> TryFrom<U> for T where
U: Into<T>,
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U: Into<T>,
type Error = Infallible
The type returned in the event of a conversion error.
pub fn try_from(value: U) -> Result<T, <T as TryFrom<U>>::Error>
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impl<T, U> TryInto<U> for T where
U: TryFrom<T>,
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U: TryFrom<T>,
type Error = <U as TryFrom<T>>::Error
The type returned in the event of a conversion error.
pub fn try_into(self) -> Result<U, <U as TryFrom<T>>::Error>
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impl<V, T> VZip<V> for T where
V: MultiLane<T>,
V: MultiLane<T>,