Struct bayes_estimate::estimators::sir::SampleState [−][src]
Sample state.
State distribution is represented as state samples and their likelihood.
Fields
s: Samples<N, D>
State samples
w: Likelihoods
and their likelihoods (bootstrap weights)
rng: Box<dyn RngCore>
A PRNG use to draw random samples
Implementations
impl<N: RealField, D: Dim> SampleState<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_equal_likelihood(
s: Vec<VectorN<N, D>>,
rng: Box<dyn RngCore>
) -> SampleState<N, D>
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s: Vec<VectorN<N, D>>,
rng: Box<dyn RngCore>
) -> SampleState<N, D>
pub fn predict(&mut self, f: fn(_: &VectorN<N, D>) -> VectorN<N, D>)
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Predict state using a state prediction function ‘f’.
pub fn predict_sampled(
&mut self,
f: impl Fn(&VectorN<N, D>, &mut dyn RngCore) -> VectorN<N, D>
)
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&mut self,
f: impl Fn(&VectorN<N, D>, &mut dyn RngCore) -> VectorN<N, D>
)
pub fn observe<LikelihoodFn>(&mut self, l: LikelihoodFn) where
LikelihoodFn: Fn(&VectorN<N, D>) -> f32,
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LikelihoodFn: Fn(&VectorN<N, D>) -> f32,
Observe sample likehoods using a likelihood function ‘l’. The sample likelihoods are multiplied by the observed likelihoods.
pub fn observe_likelihood(&mut self, l: Likelihoods)
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Observe sample likehoods directly. The sample likelihoods are multiplied by these likelihoods.
pub fn update_resample(
&mut self,
resampler: &mut Resampler,
roughener: &mut Roughener<N, D>
) -> Result<(u32, f32), &'static str>
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&mut self,
resampler: &mut Resampler,
roughener: &mut Roughener<N, D>
) -> Result<(u32, f32), &'static str>
Resample using likelihoods and roughen the sample state. Error returns: When the resampler fails due to numeric problems with the likelihoods Returns: number of unique samples, smallest normalised likelohood, to determine numerical conditioning of likehoods
Trait Implementations
impl<N: RealField, D: Dim> Estimator<N, D> for SampleState<N, D> where
DefaultAllocator: Allocator<N, D>,
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DefaultAllocator: Allocator<N, D>,
impl<N: RealField, D: Dim> KalmanEstimator<N, D> for SampleState<N, D> where
DefaultAllocator: Allocator<N, D, D> + Allocator<N, U1, D> + Allocator<N, D>,
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DefaultAllocator: Allocator<N, D, D> + Allocator<N, U1, 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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Auto Trait Implementations
impl<N, D> !RefUnwindSafe for SampleState<N, D>
impl<N, D> !Send for SampleState<N, D>
impl<N, D> !Sync for SampleState<N, D>
impl<N, D> !Unpin for SampleState<N, D>
impl<N, D> !UnwindSafe for SampleState<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, 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>,