"""Tests for search evaluation ranking metrics (NDCG, ERR)."""

from scripts.evaluation.eval_framework.constants import (
    RELEVANCE_EXACT,
    RELEVANCE_HIGH,
    RELEVANCE_IRRELEVANT,
    RELEVANCE_LOW,
)
from scripts.evaluation.eval_framework.metrics import compute_query_metrics


def test_err_matches_documented_three_item_examples():
    # Model A: [Exact, Irrelevant, High] -> ERR ≈ 0.992667
    m_a = compute_query_metrics(
        [RELEVANCE_EXACT, RELEVANCE_IRRELEVANT, RELEVANCE_HIGH],
        ideal_labels=[RELEVANCE_EXACT],
    )
    assert abs(m_a["ERR@5"] - (0.99 + (1.0 / 3.0) * 0.8 * 0.01)) < 1e-5

    # Model B: [High, Low, Exact] -> ERR ≈ 0.8694
    m_b = compute_query_metrics(
        [RELEVANCE_HIGH, RELEVANCE_LOW, RELEVANCE_EXACT],
        ideal_labels=[RELEVANCE_EXACT],
    )
    expected_b = 0.8 + 0.5 * 0.1 * 0.2 + (1.0 / 3.0) * 0.99 * 0.18
    assert abs(m_b["ERR@5"] - expected_b) < 1e-5