75d1af7fcc
Add atr_sl_mult and atr_tp_mult parameters to _calc_labels_vectorized and generate_dataset_vectorized, defaulting to existing constants (1.5, 2.0) for full backward compatibility. Callers (train scripts, backtester) can now pass symbol-specific multipliers without modifying module-level constants. Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
57 lines
2.1 KiB
Python
57 lines
2.1 KiB
Python
import numpy as np
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import pandas as pd
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import pytest
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from src.dataset_builder import generate_dataset_vectorized, _calc_labels_vectorized
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@pytest.fixture
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def signal_df():
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"""시그널이 발생하는 데이터."""
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rng = np.random.default_rng(7)
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n = 800
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trend = np.linspace(1.5, 3.0, n)
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noise = np.cumsum(rng.normal(0, 0.04, n))
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close = np.clip(trend + noise, 0.01, None)
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high = close * (1 + rng.uniform(0, 0.015, n))
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low = close * (1 - rng.uniform(0, 0.015, n))
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volume = rng.uniform(1e6, 3e6, n)
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volume[::30] *= 3.0
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return pd.DataFrame({
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"open": close, "high": high, "low": low,
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"close": close, "volume": volume,
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})
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def test_sltp_params_are_passed_through(signal_df):
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"""SL/TP 배수가 generate_dataset_vectorized에 전달되어야 한다."""
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# 파라미터가 수용되는지(TypeError 없이) 확인하는 것이 핵심
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r1 = generate_dataset_vectorized(
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signal_df, atr_sl_mult=1.5, atr_tp_mult=2.0,
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adx_threshold=0, volume_multiplier=1.5,
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)
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r2 = generate_dataset_vectorized(
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signal_df, atr_sl_mult=2.0, atr_tp_mult=2.0,
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adx_threshold=0, volume_multiplier=1.5,
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)
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# 두 결과 모두 DataFrame이어야 한다
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assert isinstance(r1, pd.DataFrame)
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assert isinstance(r2, pd.DataFrame)
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# 신호가 충분히 많을 경우, 다른 SL 배수는 레이블 분포에 영향을 줄 수 있다
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if len(r1) > 10 and len(r2) > 10:
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assert not (r1["label"].values == r2["label"].values).all() or len(r1) != len(r2), \
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"SL 배수가 다르면 레이블이 달라져야 한다"
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def test_default_sltp_backward_compatible(signal_df):
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"""SL/TP 파라미터 미지정 시 기존 기본값(1.5, 2.0)으로 동작해야 한다."""
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r_default = generate_dataset_vectorized(
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signal_df, adx_threshold=0, volume_multiplier=1.5,
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)
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r_explicit = generate_dataset_vectorized(
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signal_df, atr_sl_mult=1.5, atr_tp_mult=2.0,
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adx_threshold=0, volume_multiplier=1.5,
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)
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if len(r_default) > 0:
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assert len(r_default) == len(r_explicit)
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assert (r_default["label"].values == r_explicit["label"].values).all()
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