| |
| """Pruebas que formalizan las conclusiones de la auditoría de métricas 100%.""" |
| from __future__ import annotations |
|
|
| import csv |
| import unittest |
| from collections import defaultdict |
| from pathlib import Path |
|
|
| ROOT = Path(__file__).resolve().parents[1] |
|
|
|
|
| def parse_node(node_id: str): |
| parts = node_id.split("_") |
| return parts[1], int(parts[2][1:]) |
|
|
|
|
| def feature_key(src, tgt): |
| sp, spos = parse_node(src) |
| tp, tpos = parse_node(tgt) |
| return (sp, spos, tp, tpos) |
|
|
|
|
| def deterministic_label(src, tgt): |
| sp, spos = parse_node(src) |
| tp, tpos = parse_node(tgt) |
| if sp == tp: |
| return "none" |
| if tpos == 2 - spos: |
| return "mirrorOf" |
| if (spos in (0, 2) and tpos == 1) or (spos == 1 and tpos in (0, 2)): |
| return "creates" |
| return "none" |
|
|
|
|
| class PerfectMetricsAuditTests(unittest.TestCase): |
| @classmethod |
| def setUpClass(cls): |
| with (ROOT / "datasets" / "relation_candidates.csv").open(encoding="utf-8", newline="") as fh: |
| cls.rows = list(csv.DictReader(fh)) |
|
|
| def test_gold_matches_deterministic_rule(self): |
| for row in self.rows: |
| self.assertEqual( |
| deterministic_label(row["source"], row["target"]), |
| row["relation"], |
| msg=row, |
| ) |
|
|
| def test_label_is_function_of_phase_position_only(self): |
| by_feat = defaultdict(set) |
| for row in self.rows: |
| by_feat[feature_key(row["source"], row["target"])].add(row["relation"]) |
| for key, labels in by_feat.items(): |
| self.assertEqual(len(labels), 1, f"clave {key} tiene etiquetas {labels}") |
|
|
| def test_loo_features_fully_recoverable_from_train(self): |
| """En cada fold LOO, todo par de test es recuperable por lookup de features.""" |
| for held in range(1, 14): |
| train = {} |
| test = [] |
| for row in self.rows: |
| key = feature_key(row["source"], row["target"]) |
| if int(row["triad_index"]) == held: |
| test.append((key, row["relation"])) |
| else: |
| train[key] = row["relation"] |
| for key, lab in test: |
| self.assertEqual(train.get(key), lab) |
|
|
| def test_model_does_not_use_triad_index_in_features(self): |
| """Sanity: features_for_node en pi_hgat_t no incluye índice de tríada.""" |
| src = (ROOT / "experiments" / "optional" / "pi_hgat_t.py").read_text(encoding="utf-8") |
| self.assertIn("sin etiqueta léxica ni número de tríada", src) |
| self.assertIn("phase == \"adv\"", src) |
| self.assertIn("position == 0", src) |
|
|
|
|
| if __name__ == "__main__": |
| unittest.main() |
|
|
