CTBN

causal_hub::models

Trait CTBN 

Source 
pub trait CTBN {
    type CIM;
    type InitialDistribution;
    type Event;
    type Trajectory;
    type Trajectories;

    // Required methods
    fn new<I>(graph: DiGraph, cims: I) -> Self
       where I: IntoIterator<Item = Self::CIM>;
    fn initial_distribution(&self) -> &Self::InitialDistribution;
    fn graph(&self) -> &DiGraph;
    fn cims(&self) -> &Map<String, Self::CIM>;
    fn parameters_size(&self) -> usize;
    fn with_optionals<I>(
        name: Option<String>,
        description: Option<String>,
        initial_distribution: Self::InitialDistribution,
        graph: DiGraph,
        cims: I,
    ) -> Self
       where I: IntoIterator<Item = Self::CIM>;
}
Expand description

A trait for continuous time Bayesian networks (CTBNs).

Required Associated Types§

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type CIM

The type of the CIM.

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type InitialDistribution

The type of the initial distribution.

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type Event

The type of the observed event.

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type Trajectory

The type of the observed trajectory.

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type Trajectories

The type of a collection of trajectories.

Required Methods§

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fn new<I>(graph: DiGraph, cims: I) -> Self
where I: IntoIterator<Item = Self::CIM>,

Constructs a new CTBN.

§Arguments
  • graph - The underlying graph.
  • cims - The conditional intensity matrices.
§Notes

The distribution of the initial state (i.e. initial distribution) is uniform. See with_initial_distribution to specify the initial distribution.

§Returns

A new CTBN instance.

Source

fn initial_distribution(&self) -> &Self::InitialDistribution

Returns the initial distribution.

§Returns

A reference to the initial distribution.

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fn graph(&self) -> &DiGraph

Returns the underlying graph.

§Returns

A reference to the graph.

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fn cims(&self) -> &Map<String, Self::CIM>

Returns the a map labels-distributions.

§Returns

A reference to the CIMs.

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fn parameters_size(&self) -> usize

Returns the parameters size.

§Returns

The parameters size.

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fn with_optionals<I>( name: Option<String>, description: Option<String>, initial_distribution: Self::InitialDistribution, graph: DiGraph, cims: I, ) -> Self
where I: IntoIterator<Item = Self::CIM>,

Creates a new categorical continuous-time Bayesian network with optional fields.

§Arguments
  • name - The name of the model.
  • description - The description of the model.
  • graph - The underlying graph.
  • cims - The conditional intensity matrices.
§Panics
  • Panics if name is an empty string.
  • Panics if description is an empty string.
§Returns

A new categorical continuous-time Bayesian network instance.

Dyn Compatibility§

This trait is not dyn compatible.

In older versions of Rust, dyn compatibility was called "object safety", so this trait is not object safe.

Implementors§