Struct CausalRepresentationModel 

pub struct CausalRepresentationModel {

    pub config: CausalRepresentationConfig,
    pub model_id: Uuid,
    pub causal_graph: CausalGraph,
    pub structural_equations: HashMap<String, StructuralEquation>,
    pub variable_embeddings: HashMap<String, Array1<f32>>,
    pub latent_factors: Array2<f32>,
    pub factual_network: Array2<f32>,
    pub counterfactual_network: Array2<f32>,
    pub shared_network: Array2<f32>,
    pub observational_data: Vec<HashMap<String, f32>>,
    pub interventional_data: Vec<(HashMap<String, f32>, Intervention)>,
    pub entities: HashMap<String, usize>,
    pub relations: HashMap<String, usize>,
    pub training_stats: Option<TrainingStats>,
    pub is_trained: bool,
}

Causal representation learning model

Fields

config: CausalRepresentationConfig

model_id: Uuid

causal_graph: CausalGraph

Learned causal graph

structural_equations: HashMap<String, StructuralEquation>

Structural equations

variable_embeddings: HashMap<String, Array1<f32>>

Embeddings for variables

latent_factors: Array2<f32>

Latent factors (disentangled representations)

factual_network: Array2<f32>

Twin network for counterfactuals

counterfactual_network: Array2<f32>

shared_network: Array2<f32>

observational_data: Vec<HashMap<String, f32>>

Training data storage

interventional_data: Vec<(HashMap<String, f32>, Intervention)>

entities: HashMap<String, usize>

Entity and relation mappings

relations: HashMap<String, usize>

training_stats: Option<TrainingStats>

Training state

is_trained: bool

Implementations

impl CausalRepresentationModel

pub fn new(config: CausalRepresentationConfig) -> Self

Create new causal representation model

pub fn add_observational_data(&mut self, data: HashMap<String, f32>)

Add observational data

pub fn add_interventional_data( &mut self, data: HashMap<String, f32>, intervention: Intervention, )

Add interventional data

pub fn discover_causal_structure(&mut self) -> Result<()>

Discover causal structure

pub fn learn_structural_equations(&mut self) -> Result<()>

Learn structural equations

pub fn intervene( &self, intervention: &Intervention, ) -> Result<HashMap<String, f32>>

Perform intervention

pub fn answer_counterfactual( &self, query: &CounterfactualQuery, ) -> Result<HashMap<String, f32>>

Answer counterfactual query

pub fn generate_explanation( &self, query_var: &str, evidence: &HashMap<String, f32>, ) -> Result<String>

Generate causal explanation

pub fn learn_disentangled_representations(&mut self) -> Result<()>

Learn disentangled representations

Trait Implementations

impl Debug for CausalRepresentationModel

fn fmt(&self, f: &mut Formatter<'_>) -> Result

Formats the value using the given formatter.

impl EmbeddingModel for CausalRepresentationModel

fn config(&self) -> &ModelConfig

fn model_id(&self) -> &Uuid

fn model_type(&self) -> &'static str

fn add_triple(&mut self, triple: Triple) -> Result<()>

fn train<'life0, 'async_trait>( &'life0 mut self, epochs: Option<usize>, ) -> Pin<Box<dyn Future<Output = Result<TrainingStats>> + Send + 'async_trait>>

where Self: 'async_trait, 'life0: 'async_trait,

fn get_entity_embedding(&self, entity: &str) -> Result<Vector>

fn get_relation_embedding(&self, relation: &str) -> Result<Vector>

fn score_triple( &self, subject: &str, _predicate: &str, object: &str, ) -> Result<f64>

fn predict_objects( &self, subject: &str, predicate: &str, k: usize, ) -> Result<Vec<(String, f64)>>

fn predict_subjects( &self, predicate: &str, object: &str, k: usize, ) -> Result<Vec<(String, f64)>>

fn predict_relations( &self, subject: &str, object: &str, k: usize, ) -> Result<Vec<(String, f64)>>

fn get_entities(&self) -> Vec<String>

fn get_relations(&self) -> Vec<String>

fn get_stats(&self) -> ModelStats

fn save(&self, _path: &str) -> Result<()>

fn load(&mut self, _path: &str) -> Result<()>

fn clear(&mut self)

fn is_trained(&self) -> bool

fn encode<'life0, 'life1, 'async_trait>( &'life0 self, texts: &'life1 [String], ) -> Pin<Box<dyn Future<Output = Result<Vec<Vec<f32>>>> + Send + 'async_trait>>

where Self: 'async_trait, 'life0: 'async_trait, 'life1: 'async_trait,

Encode text strings into embeddings