import runpy
from pathlib import Path

import numpy as np
import pytest

SCRIPT = runpy.run_path(
    str(Path(__file__).resolve().parents[1] / "scripts" / "build_complete_comparison.py")
)
_decode_action = SCRIPT["_decode_action"]
_extract_component = SCRIPT["_extract_component"]
_prediction_metrics = SCRIPT["_prediction_metrics"]


def test_decode_action_uses_statistics_and_nonzero_history_anchor() -> None:
    history_xy = np.array([[8.0, -4.0], [10.0, -3.0]])
    action = np.array([[1.0, -1.0], [0.0, 2.0]])
    decoded = _decode_action(
        action,
        history_xy,
        mean=np.array([0.5, 0.25]),
        scale=np.array([2.0, 0.5]),
    )
    np.testing.assert_allclose(decoded, np.array([[12.5, -3.25], [13.0, -2.0]]))


def test_extract_component_requires_one_ordered_nonempty_pair() -> None:
    text = "<|cot_start|>keep left<|cot_end|>"
    assert _extract_component(text, "cot") == "keep left"
    with pytest.raises(ValueError):
        _extract_component(text + text, "cot")
    with pytest.raises(ValueError):
        _extract_component("<|cot_start|><|cot_end|>", "cot")


def test_prediction_metrics_use_normalized_action_and_euclidean_xy() -> None:
    target_action = np.zeros((2, 2))
    predicted_action = np.ones((2, 2))
    target_xy = np.zeros((2, 2))
    predicted_xy = np.array([[3.0, 4.0], [0.0, 0.0]])
    assert _prediction_metrics(predicted_action, predicted_xy, target_action, target_xy) == {
        "action_mse": 1.0,
        "ade_m": 2.5,
        "fde_m": 0.0,
        "max_error_m": 5.0,
    }