//! Tests for [`super`].

use super::*;

#[test]
fn macro_average_counts_an_unpredicted_class_as_zero() {
    // Skipping it would let a layer raise its macro precision by predicting
    // a hard class less often, which is backwards.
    let classes = vec!["a".to_string(), "b".to_string()];
    let mut counts = BTreeMap::new();
    counts.insert(
        "a".to_string(),
        Counts {
            tp: 10,
            fp: 0,
            fn_: 0,
        },
    );
    counts.insert(
        "b".to_string(),
        Counts {
            tp: 0,
            fp: 0,
            fn_: 10,
        },
    );
    assert_eq!(
        macro_average(&classes, &counts, Counts::precision),
        Some(0.5)
    );
}

#[test]
fn class_points_score_an_absent_class_as_zero() {
    // A class missing from a sample's scores is a real zero, not a gap: the
    // index considered it and gave it no neighbourhood weight. Treating it
    // as missing would drop true negatives and inflate precision.
    let p = vec![Prediction {
        truth: "instrument.drum.kick".into(),
        top1: Some("instrument.drum.kick".into()),
        scores: BTreeMap::from([("instrument.drum.kick".to_string(), 0.9)]),
        fold: 0,
        origin: "kick".into(),
    }];
    let pts = class_points(&p, "instrument.drum.snare");
    assert_eq!(pts.len(), 1);
    assert!((pts[0].score - 0.0).abs() < f64::EPSILON);
    assert!(!pts[0].actual);
}

#[test]
fn k_sweep_always_contains_the_runtime_k() {
    // Safe to set: this test does not read the env, it checks the invariant
    // the parser must hold whatever the env said.
    let ks = k_sweep_from_env();
    assert!(ks.contains(&DEFAULT_K));
    assert!(ks.windows(2).all(|w| w[0] < w[1]), "sorted and deduped");
}