Struct GraphProximityObjective 

pub struct GraphProximityObjective {
    pub max_distance: u32,
}

Scores a candidate by graph proximity to anchor nodes.

Score formula (linear decay):

d ≤ max_distance → score = 1.0 − (d as f64 / max_distance as f64)
d > max_distance → score = 0.0
missing          → score = 0.0

Direct anchor hits (d = 0) score 1.0. The boundary d == max_distance scores 0.0; anything beyond also scores 0.0.

Fields

max_distance: u32

Maximum hop distance to consider. Candidates beyond this score 0.0.

Trait Implementations

impl Objective<RetrievalCandidate> for GraphProximityObjective

fn score( &self, candidate: &RetrievalCandidate, _context: &ObjectiveContext, ) -> f64

Evaluate a single candidate.

fn name(&self) -> &str

Get the name of this objective.

fn precision(&self, _candidate: &T, _context: &ObjectiveContext) -> f64

Precision (inverse variance) of the score estimate; default 1.0 (fully trusted).

fn passes_score(&self, score: f64, context: &ObjectiveContext) -> bool

Check if a score passes the threshold; non-finite scores never pass.

fn passes(&self, candidate: &T, context: &ObjectiveContext) -> bool

Check if a candidate passes the threshold.

fn batch_score( &self, candidates: &[T], context: &ObjectiveContext, ) -> Vec<(usize, f64)>

Score a batch of candidates and return passing (index, score) pairs.

fn select<'a>( &self, candidates: &'a [T], context: &ObjectiveContext, ) -> Vec<Selection<&'a T>>

Select all passing candidates in score-descending order.

fn select_top<'a>( &self, candidates: &'a [T], n: usize, context: &ObjectiveContext, ) -> Vec<Selection<&'a T>>

Select the top N candidates by precision-weighted score.