| """Tests for dual-input hybrid helpers.""" |
|
|
| import numpy as np |
| import pandas as pd |
| import pytest |
|
|
| from src.features.metadata_features import extract_metadata_features |
| from src.models.hybrid_ensemble import compute_performance_weights |
|
|
|
|
| def test_extract_metadata_features(): |
| df = pd.DataFrame({"Text": ["Hello!! WORLD?", "ok"], "IsToxic": [1, 0]}) |
| meta = extract_metadata_features(df) |
| assert list(meta.columns) == [ |
| "char_length", |
| "word_count", |
| "exclamation_ratio", |
| "question_ratio", |
| "caps_ratio", |
| ] |
| assert meta.loc[0, "exclamation_ratio"] > 0 |
|
|
|
|
| def test_compute_performance_weights_bounds(): |
| y = np.array([0, 1, 1, 0]) |
| b = np.array([0.2, 0.8, 0.7, 0.3]) |
| l = np.array([0.3, 0.6, 0.75, 0.25]) |
| bw, lw, info = compute_performance_weights( |
| b, l, y, min_lr_weight=0.15, max_lr_weight=0.45 |
| ) |
| assert pytest.approx(bw + lw, rel=1e-5) == 1.0 |
| assert 0.15 <= lw <= 0.45 |
| assert "bert_val_score" in info |
|
|
|
|
| def test_load_dual_track_data_generates_clean_text(tmp_path, monkeypatch): |
| pytest.importorskip("spacy") |
| raw = tmp_path / "raw.csv" |
| pd.DataFrame( |
| { |
| "CommentId": [1, 2], |
| "Text": ["Visit http://x.com now!!!", "nice video"], |
| "IsToxic": [1, 0], |
| } |
| ).to_csv(raw, index=False) |
|
|
| from src.data import dual_loader as dl |
|
|
| monkeypatch.setattr( |
| dl.TextPreprocessor, |
| "__init__", |
| lambda self, config_path=None: None, |
| ) |
| monkeypatch.setattr( |
| dl.TextPreprocessor, |
| "transform", |
| lambda self, s: s.str.lower(), |
| ) |
|
|
| out = dl.load_dual_track_data( |
| raw, |
| processed_preprocessed=tmp_path / "pre.csv", |
| processed_stats=tmp_path / "missing_stats.csv", |
| write_preprocessed_if_missing=True, |
| project_root=tmp_path, |
| ) |
| assert "clean_text" in out.columns |
| assert (out["char_length"] > 0).all() |
|
|
