pub struct Model<L, Pr, Po, Payload = ()>where
L: Likelihood<Payload>,
Pr: Prior,
Po: Posterior,
Payload: Default,{ /* private fields */ }
Expand description
Bayesian model, consisting of a prior, a posterior and a likelihood model.
Thereby, Payload
is a custom payload of the model instance.
This can be used to define custom caching mechanisms. See
here
for an example.
Implementations§
source§impl<L, Pr, Po, Payload> Model<L, Pr, Po, Payload>where
L: Likelihood<Payload>,
Pr: Prior,
Po: Posterior,
Payload: Default,
impl<L, Pr, Po, Payload> Model<L, Pr, Po, Payload>where L: Likelihood<Payload>, Pr: Prior, Po: Posterior, Payload: Default,
source§impl<L, Pr, Po, Payload> Model<L, Pr, Po, Payload>where
L: Likelihood<Payload>,
Pr: Prior,
Po: Posterior,
Payload: Default,
impl<L, Pr, Po, Payload> Model<L, Pr, Po, Payload>where L: Likelihood<Payload>, Pr: Prior, Po: Posterior, Payload: Default,
pub fn likelihood_mut(&mut self) -> &mut L
pub fn prior_mut(&mut self) -> &mut Pr
pub fn posterior_mut(&mut self) -> &mut Po
source§impl<Event, PosteriorEvent, Data, L, Pr, Po, Payload> Model<L, Pr, Po, Payload>where
Payload: Default,
Event: Hash + Eq + Clone,
PosteriorEvent: Hash + Eq + Clone,
L: Likelihood<Payload, Event = Event, Data = Data>,
Pr: Prior<Event = Event>,
Po: Posterior<BaseEvent = Event, Event = PosteriorEvent, Data = Data>,
impl<Event, PosteriorEvent, Data, L, Pr, Po, Payload> Model<L, Pr, Po, Payload>where Payload: Default, Event: Hash + Eq + Clone, PosteriorEvent: Hash + Eq + Clone, L: Likelihood<Payload, Event = Event, Data = Data>, Pr: Prior<Event = Event>, Po: Posterior<BaseEvent = Event, Event = PosteriorEvent, Data = Data>,
sourcepub fn compute<U: IntoIterator<Item = PosteriorEvent>>(
&self,
universe: U,
data: &Data
) -> ModelInstance<Event, PosteriorEvent>
pub fn compute<U: IntoIterator<Item = PosteriorEvent>>( &self, universe: U, data: &Data ) -> ModelInstance<Event, PosteriorEvent>
Compute model for a given universe of events.
sourcepub fn compute_from_marginal<M>(
&self,
marginal: &M,
data: &Data
) -> ModelInstance<Event, PosteriorEvent>where
M: Marginal<Data = Data, Event = PosteriorEvent, BaseEvent = Event>,
pub fn compute_from_marginal<M>( &self, marginal: &M, data: &Data ) -> ModelInstance<Event, PosteriorEvent>where M: Marginal<Data = Data, Event = PosteriorEvent, BaseEvent = Event>,
Compute model via the exploration of the marginal distribution of the data.
Trait Implementations§
source§impl<L, Pr, Po, Payload> Clone for Model<L, Pr, Po, Payload>where
L: Likelihood<Payload> + Clone,
Pr: Prior + Clone,
Po: Posterior + Clone,
Payload: Default + Clone,
impl<L, Pr, Po, Payload> Clone for Model<L, Pr, Po, Payload>where L: Likelihood<Payload> + Clone, Pr: Prior + Clone, Po: Posterior + Clone, Payload: Default + Clone,
source§impl<L, Pr, Po, Payload> Debug for Model<L, Pr, Po, Payload>where
L: Likelihood<Payload> + Debug,
Pr: Prior + Debug,
Po: Posterior + Debug,
Payload: Default + Debug,
impl<L, Pr, Po, Payload> Debug for Model<L, Pr, Po, Payload>where L: Likelihood<Payload> + Debug, Pr: Prior + Debug, Po: Posterior + Debug, Payload: Default + Debug,
source§impl<L, Pr, Po, Payload> Default for Model<L, Pr, Po, Payload>where
L: Likelihood<Payload> + Default,
Pr: Prior + Default,
Po: Posterior + Default,
Payload: Default + Default,
impl<L, Pr, Po, Payload> Default for Model<L, Pr, Po, Payload>where L: Likelihood<Payload> + Default, Pr: Prior + Default, Po: Posterior + Default, Payload: Default + Default,
source§impl<'de, L, Pr, Po, Payload> Deserialize<'de> for Model<L, Pr, Po, Payload>where
L: Likelihood<Payload> + Deserialize<'de>,
Pr: Prior + Deserialize<'de>,
Po: Posterior + Deserialize<'de>,
Payload: Default,
impl<'de, L, Pr, Po, Payload> Deserialize<'de> for Model<L, Pr, Po, Payload>where L: Likelihood<Payload> + Deserialize<'de>, Pr: Prior + Deserialize<'de>, Po: Posterior + Deserialize<'de>, Payload: Default,
source§fn deserialize<__D>(__deserializer: __D) -> Result<Self, __D::Error>where
__D: Deserializer<'de>,
fn deserialize<__D>(__deserializer: __D) -> Result<Self, __D::Error>where __D: Deserializer<'de>,
Deserialize this value from the given Serde deserializer. Read more
source§impl<L, Pr, Po, Payload> Hash for Model<L, Pr, Po, Payload>where
L: Likelihood<Payload> + Hash,
Pr: Prior + Hash,
Po: Posterior + Hash,
Payload: Default + Hash,
impl<L, Pr, Po, Payload> Hash for Model<L, Pr, Po, Payload>where L: Likelihood<Payload> + Hash, Pr: Prior + Hash, Po: Posterior + Hash, Payload: Default + Hash,
source§impl<L, Pr, Po, Payload> Ord for Model<L, Pr, Po, Payload>where
L: Likelihood<Payload> + Ord,
Pr: Prior + Ord,
Po: Posterior + Ord,
Payload: Default + Ord,
impl<L, Pr, Po, Payload> Ord for Model<L, Pr, Po, Payload>where L: Likelihood<Payload> + Ord, Pr: Prior + Ord, Po: Posterior + Ord, Payload: Default + Ord,
1.21.0 · source§fn max(self, other: Self) -> Selfwhere
Self: Sized,
fn max(self, other: Self) -> Selfwhere Self: Sized,
Compares and returns the maximum of two values. Read more
source§impl<L, Pr, Po, Payload> PartialEq<Model<L, Pr, Po, Payload>> for Model<L, Pr, Po, Payload>where
L: Likelihood<Payload> + PartialEq,
Pr: Prior + PartialEq,
Po: Posterior + PartialEq,
Payload: Default + PartialEq,
impl<L, Pr, Po, Payload> PartialEq<Model<L, Pr, Po, Payload>> for Model<L, Pr, Po, Payload>where L: Likelihood<Payload> + PartialEq, Pr: Prior + PartialEq, Po: Posterior + PartialEq, Payload: Default + PartialEq,
source§impl<L, Pr, Po, Payload> PartialOrd<Model<L, Pr, Po, Payload>> for Model<L, Pr, Po, Payload>where
L: Likelihood<Payload> + PartialOrd,
Pr: Prior + PartialOrd,
Po: Posterior + PartialOrd,
Payload: Default + PartialOrd,
impl<L, Pr, Po, Payload> PartialOrd<Model<L, Pr, Po, Payload>> for Model<L, Pr, Po, Payload>where L: Likelihood<Payload> + PartialOrd, Pr: Prior + PartialOrd, Po: Posterior + PartialOrd, Payload: Default + PartialOrd,
1.0.0 · source§fn le(&self, other: &Rhs) -> bool
fn le(&self, other: &Rhs) -> bool
This method tests less than or equal to (for
self
and other
) and is used by the <=
operator. Read moresource§impl<L, Pr, Po, Payload> Serialize for Model<L, Pr, Po, Payload>where
L: Likelihood<Payload> + Serialize,
Pr: Prior + Serialize,
Po: Posterior + Serialize,
Payload: Default,
impl<L, Pr, Po, Payload> Serialize for Model<L, Pr, Po, Payload>where L: Likelihood<Payload> + Serialize, Pr: Prior + Serialize, Po: Posterior + Serialize, Payload: Default,
impl<L, Pr, Po, Payload> Copy for Model<L, Pr, Po, Payload>where L: Likelihood<Payload> + Copy, Pr: Prior + Copy, Po: Posterior + Copy, Payload: Default + Copy,
impl<L, Pr, Po, Payload> Eq for Model<L, Pr, Po, Payload>where L: Likelihood<Payload> + Eq, Pr: Prior + Eq, Po: Posterior + Eq, Payload: Default + Eq,
impl<L, Pr, Po, Payload> StructuralEq for Model<L, Pr, Po, Payload>where L: Likelihood<Payload>, Pr: Prior, Po: Posterior, Payload: Default,
impl<L, Pr, Po, Payload> StructuralPartialEq for Model<L, Pr, Po, Payload>where L: Likelihood<Payload>, Pr: Prior, Po: Posterior, Payload: Default,
Auto Trait Implementations§
impl<L, Pr, Po, Payload> RefUnwindSafe for Model<L, Pr, Po, Payload>where L: RefUnwindSafe, Payload: RefUnwindSafe, Po: RefUnwindSafe, Pr: RefUnwindSafe,
impl<L, Pr, Po, Payload> Send for Model<L, Pr, Po, Payload>where L: Send, Payload: Send, Po: Send, Pr: Send,
impl<L, Pr, Po, Payload> Sync for Model<L, Pr, Po, Payload>where L: Sync, Payload: Sync, Po: Sync, Pr: Sync,
impl<L, Pr, Po, Payload> Unpin for Model<L, Pr, Po, Payload>where L: Unpin, Payload: Unpin, Po: Unpin, Pr: Unpin,
impl<L, Pr, Po, Payload> UnwindSafe for Model<L, Pr, Po, Payload>where L: UnwindSafe, Payload: UnwindSafe, Po: UnwindSafe, Pr: UnwindSafe,
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
source§impl<Q, K> Equivalent<K> for Qwhere
Q: Eq + ?Sized,
K: Borrow<Q> + ?Sized,
impl<Q, K> Equivalent<K> for Qwhere Q: Eq + ?Sized, K: Borrow<Q> + ?Sized,
source§fn equivalent(&self, key: &K) -> bool
fn equivalent(&self, key: &K) -> bool
Compare self to
key
and return true
if they are equal.§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.