# -*- coding: utf-8 -*-
"""Unit tests: baseline forecasters."""
import numpy as np

from src.baselines import NaiveBaseline, NaiveConfig, DriftBaseline, DriftConfig
from src.forecasting.target import ForecastContext
from src.forecasting.interface import Series


def _ctx():
    return ForecastContext(symbol="XAUUSD", timeframe="H1", horizon=10, atr_period=20)


def test_naive_random_walk_neutral():
    close = np.arange(1, 101, dtype=float)
    s = Series(symbol="XAUUSD", timeframe="H1", timestamp=[f"t{i}" for i in range(100)],
               open=list(close), high=list(close + 0.5), low=list(close - 0.5),
               close=list(close))
    rec = NaiveBaseline(NaiveConfig()).forecast(s, 50, _ctx())
    assert rec.normalized_expected_return == 0.0
    assert rec.forecast_direction == "NEUTRAL"


def test_drift_directional_on_up_trend():
    close = np.cumsum(np.full(120, 0.1)) + 100.0
    s = Series(symbol="XAUUSD", timeframe="H1", timestamp=[f"t{i}" for i in range(120)],
               open=list(close), high=list(close + 0.5), low=list(close - 0.5),
               close=list(close))
    rec = DriftBaseline(DriftConfig(lookback=40)).forecast(s, 90, _ctx())
    assert rec.normalized_expected_return is not None
    assert rec.normalized_expected_return > 0
    assert rec.forecast_direction == "LONG"