32 lines
1.3 KiB
Python
32 lines
1.3 KiB
Python
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# -*- coding: utf-8 -*-
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"""Unit tests: baseline forecasters."""
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import numpy as np
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from src.baselines import NaiveBaseline, NaiveConfig, DriftBaseline, DriftConfig
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from src.forecasting.target import ForecastContext
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from src.forecasting.interface import Series
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def _ctx():
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return ForecastContext(symbol="XAUUSD", timeframe="H1", horizon=10, atr_period=20)
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def test_naive_random_walk_neutral():
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close = np.arange(1, 101, dtype=float)
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s = Series(symbol="XAUUSD", timeframe="H1", timestamp=[f"t{i}" for i in range(100)],
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open=list(close), high=list(close + 0.5), low=list(close - 0.5),
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close=list(close))
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rec = NaiveBaseline(NaiveConfig()).forecast(s, 50, _ctx())
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assert rec.normalized_expected_return == 0.0
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assert rec.forecast_direction == "NEUTRAL"
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def test_drift_directional_on_up_trend():
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close = np.cumsum(np.full(120, 0.1)) + 100.0
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s = Series(symbol="XAUUSD", timeframe="H1", timestamp=[f"t{i}" for i in range(120)],
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open=list(close), high=list(close + 0.5), low=list(close - 0.5),
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close=list(close))
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rec = DriftBaseline(DriftConfig(lookback=40)).forecast(s, 90, _ctx())
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assert rec.normalized_expected_return is not None
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assert rec.normalized_expected_return > 0
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assert rec.forecast_direction == "LONG"
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