use std::collections::BTreeMap;
use crate::metrics::precision::compute_precision;
use crate::PredScore;
use crate::Relevance;
use crate::TrueScore;
pub fn compute_average_precision<K>(
trues: &BTreeMap<K, TrueScore>,
sorted_preds: &[Relevance<K, PredScore>],
k: usize,
rel_lvl: TrueScore,
) -> f64
where
K: Eq + Ord,
{
let k = if k == 0 { sorted_preds.len() } else { k };
if k == 0 {
return 0.0;
}
let n_rels = trues.values().filter(|&&rel| rel >= rel_lvl).count();
if n_rels == 0 {
return 0.0;
}
let mut sum = 0.0;
for (i, pred) in sorted_preds.iter().enumerate().take(k) {
if let Some(&rel) = trues.get(&pred.doc_id) {
if rel >= rel_lvl {
sum += compute_precision(trues, sorted_preds, i + 1, rel_lvl);
}
}
}
sum / n_rels as f64
}