import numpy as np

from scripts.eval_graph_feature_classifier import metrics as graph_metrics
from scripts.run_graph_text_stack import score as stack_metrics


def test_graph_metrics_compute_both_class_accuracies():
    y = np.array([0, 1, 0, 1], dtype=np.int8)
    pred = np.array([0, 1, 1, 0], dtype=np.int8)
    result = graph_metrics(y, pred, pair_count=2)
    assert result["accuracy"] == 0.5
    assert result["safe_accuracy"] == 0.5
    assert result["vulnerable_accuracy"] == 0.5
    assert result["pair_pass_at_1"] == 0.5


def test_stack_metric_flags_safe_collapse():
    y = np.array([0, 1, 0, 1], dtype=np.int8)
    pred = np.zeros(4, dtype=np.int8)
    result = stack_metrics(y, pred, n_pairs=2)
    assert result["safe_accuracy"] == 1.0
    assert result["vulnerable_accuracy"] == 0.0
    assert result["predicted_vulnerable_fraction"] == 0.0
    assert result["pair_pass_at_1"] == 0.0