File size: 2,693 Bytes
66f9450 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 | #!/usr/bin/env python3
"""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()
|