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46cc63a | 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 | """Tests for expert threshold tuning (no model download)."""
import numpy as np
from src.evaluation.threshold_tuning import predict_with_threshold, search_best_threshold
from src.models.hybrid_ensemble import tune_ensemble_threshold
def test_search_best_threshold_prefers_high_recall_slice():
y = np.array([0, 0, 1, 1, 1])
probs = np.array([0.1, 0.2, 0.55, 0.7, 0.9])
t, score = search_best_threshold(y, probs, metric="f1_toxic")
preds = predict_with_threshold(probs, t)
assert score > 0
assert 0.05 <= t <= 0.95
assert preds.shape == y.shape
def test_tune_ensemble_threshold():
y_val = np.array([0, 1, 1, 0])
a = np.array([0.2, 0.8, 0.7, 0.3])
b = np.array([0.3, 0.6, 0.75, 0.25])
t, _ = tune_ensemble_threshold(a, b, y_val, bert_weight=0.7, lr_weight=0.3)
assert 0.05 <= t <= 0.95
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