"""Tests para adf_kpss_stationarity."""

import numpy as np

from adf_kpss_stationarity import adf_kpss_stationarity


def test_random_walk_es_no_estacionario():
    # Random walk = suma acumulada de ruido: tiene raiz unitaria.
    rng = np.random.default_rng(123)
    paseo = np.cumsum(rng.normal(0.0, 1.0, 400)).tolist()
    res = adf_kpss_stationarity(paseo)
    assert res["verdict"] == "non_stationary"
    assert res["adf"]["stationary"] is False
    assert res["kpss"]["stationary"] is False


def test_ruido_blanco_es_estacionario():
    # Ruido blanco gaussiano: estacionario por construccion.
    rng = np.random.default_rng(42)
    ruido = rng.normal(0.0, 1.0, 400).tolist()
    res = adf_kpss_stationarity(ruido)
    assert res["verdict"] == "stationary"
    assert res["adf"]["stationary"] is True
    assert res["kpss"]["stationary"] is True
    assert res["warning"] is None


def test_serie_con_tendencia_no_es_estacionaria():
    # Tendencia lineal determinista + ruido pequeno: KPSS la marca no estacionaria.
    rng = np.random.default_rng(7)
    serie = [0.1 * i + rng.normal(0, 0.5) for i in range(300)]
    res = adf_kpss_stationarity(serie)
    assert res["verdict"] != "stationary"
    assert res["warning"] is not None


def test_muestra_insuficiente_devuelve_nota():
    res = adf_kpss_stationarity([1, 2, 3, 4, 5])
    assert res["n"] == 5
    assert res["note"] == "datos insuficientes"
    assert res["verdict"] is None


def test_descarta_none_y_nan():
    rng = np.random.default_rng(1)
    base = rng.normal(0, 1, 200).tolist()
    sucio = []
    for i, v in enumerate(base):
        sucio.append(v)
        if i % 20 == 0:
            sucio.append(None)
            sucio.append(float("nan"))
    res = adf_kpss_stationarity(sucio)
    assert res["n"] == 200  # las None/NaN no cuentan


def test_warning_presente_si_no_estacionaria():
    # Tendencia lineal fuerte: garantiza no estacionariedad (verdict != stationary).
    rng = np.random.default_rng(99)
    serie = [0.5 * i + rng.normal(0, 0.3) for i in range(300)]
    res = adf_kpss_stationarity(serie)
    assert res["verdict"] != "stationary"
    assert res["warning"] is not None
    assert "espuria" in res["warning"].lower()


def test_estructura_basica_del_dict():
    rng = np.random.default_rng(5)
    ruido = rng.normal(0, 1, 100).tolist()
    res = adf_kpss_stationarity(ruido)
    for key in ("n", "alpha", "adf", "kpss", "verdict"):
        assert key in res
    for sub in ("stat", "p_value", "lags", "stationary", "conclusion"):
        assert sub in res["adf"]
        assert sub in res["kpss"]