Struct SchemaStatistics 

pub struct SchemaStatistics {
    pub domain_count: usize,
    pub predicate_count: usize,
    pub variable_count: usize,
    pub total_cardinality: usize,
    pub avg_cardinality: f64,
    pub max_cardinality: usize,
    pub min_cardinality: usize,
    pub arity_distribution: HashMap<usize, usize>,
    pub domain_usage_frequency: HashMap<String, usize>,
    pub unused_domains: Vec<String>,
    pub predicates_by_arity: HashMap<usize, Vec<String>>,
}

Comprehensive statistics about a schema.

Fields

domain_count: usize

Number of domains defined.

predicate_count: usize

Number of predicates defined.

variable_count: usize

Number of variables bound.

total_cardinality: usize

Total cardinality across all domains.

avg_cardinality: f64

Average domain cardinality.

max_cardinality: usize

Maximum domain cardinality.

min_cardinality: usize

Minimum domain cardinality.

arity_distribution: HashMap<usize, usize>

Distribution of predicate arities.

domain_usage_frequency: HashMap<String, usize>

Most common domain types in predicates.

unused_domains: Vec<String>

Domains that are never used in predicates.

predicates_by_arity: HashMap<usize, Vec<String>>

Predicates grouped by arity.

Implementations

impl SchemaStatistics

pub fn compute(table: &SymbolTable) -> Self

Compute statistics for a symbol table.

Example

use tensorlogic_adapters::{SymbolTable, DomainInfo, PredicateInfo, SchemaStatistics};

let mut table = SymbolTable::new();
table.add_domain(DomainInfo::new("Person", 100)).unwrap();
table.add_predicate(PredicateInfo::new(
    "knows",
    vec!["Person".to_string(), "Person".to_string()]
)).unwrap();

let stats = SchemaStatistics::compute(&table);
assert_eq!(stats.domain_count, 1);
assert_eq!(stats.predicate_count, 1);

pub fn most_used_domains(&self, n: usize) -> Vec<(String, usize)>

Get the most frequently used domains.

pub fn least_used_domains(&self, n: usize) -> Vec<(String, usize)>

Get the least frequently used domains (excluding unused).

pub fn complexity_score(&self) -> f64

Calculate schema complexity score.

This is a heuristic metric based on:

• Number of domains
• Number of predicates
• Arity distribution
• Domain usage patterns

Trait Implementations

impl Clone for SchemaStatistics

fn clone(&self) -> SchemaStatistics

Returns a duplicate of the value.

fn clone_from(&mut self, source: &Self)

Performs copy-assignment from source.

impl Debug for SchemaStatistics

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

Formats the value using the given formatter.