dsyoon
b52d61b777
로고스/루트 레거시를 제거하고 deepcoin 패키지·scripts 01~05 CLI·docs/reference로 데이터·GT·분석·매칭·운영 단계를 정리했다. config와 .env 기반 설정, trade_anaysis.html 동기화 포함. Co-authored-by: Cursor <cursoragent@cursor.com>
99 lines
3.0 KiB
Python
99 lines
3.0 KiB
Python
"""
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general_analysis lookback 컨텍스트 특징 (패턴·파동·VP·하모닉) 봉별 적용.
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"""
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from __future__ import annotations
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import pandas as pd
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from deepcoin.analysis.general_analysis_config import CONTEXT_TAIL_ROWS, LOOKBACK_BARS
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from deepcoin.analysis.general_analysis_core import ga_col
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from deepcoin.analysis.general_analysis_harmonic import (
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general_analysis_harmonic_columns,
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general_analysis_harmonic_snapshot,
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)
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from deepcoin.analysis.general_analysis_patterns import general_analysis_apply_patterns_to_bars
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from deepcoin.analysis.general_analysis_volume import (
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general_analysis_volume_columns,
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general_analysis_volume_snapshot,
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)
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from deepcoin.analysis.general_analysis_wave import general_analysis_apply_wave_to_bars
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def general_analysis_apply_volume_to_bars(
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df: pd.DataFrame,
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interval: int,
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tail_rows: int | None = None,
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) -> pd.DataFrame:
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"""Volume Profile 컬럼을 최근 봉에 롤링 적용."""
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out = df.copy()
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for k in general_analysis_volume_columns():
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out[ga_col(k)] = 0.0 if k != "vp_in_value_area" else 0
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lb = LOOKBACK_BARS.get(interval, 80)
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n = len(out)
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if n < lb + 1:
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return out
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if tail_rows is None:
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tail_rows = CONTEXT_TAIL_ROWS.get(interval, 5000)
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start = max(lb, n - tail_rows)
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for i in range(start, n):
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snap = general_analysis_volume_snapshot(out.iloc[i - lb : i])
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idx = out.index[i]
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for k, v in snap.items():
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out.at[idx, k] = v
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return out
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def general_analysis_apply_harmonic_to_bars(
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df: pd.DataFrame,
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interval: int,
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tail_rows: int | None = None,
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) -> pd.DataFrame:
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"""하모닉 패턴 컬럼 롤링 적용."""
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out = df.copy()
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for k in general_analysis_harmonic_columns():
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default = "none" if k == "harmonic_label" else 0
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out[ga_col(k)] = default
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lb = LOOKBACK_BARS.get(interval, 80)
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n = len(out)
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if n < lb + 1:
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return out
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if tail_rows is None:
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tail_rows = CONTEXT_TAIL_ROWS.get(interval, 5000)
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start = max(lb, n - tail_rows)
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for i in range(start, n):
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snap = general_analysis_harmonic_snapshot(out.iloc[i - lb : i])
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idx = out.index[i]
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for k, v in snap.items():
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out.at[idx, k] = v
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return out
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def general_analysis_apply_context_features(
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df: pd.DataFrame,
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interval: int,
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tail_rows: int | None = None,
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) -> pd.DataFrame:
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"""
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패턴·파동·VP·하모닉 lookback 라벨을 봉 시계열에 병합.
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Args:
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df: general_analysis_enrich_bars 1단계 결과.
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interval: 분봉 간격(분).
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tail_rows: 롤링 적용 봉 수 상한.
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Returns:
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컨텍스트 ga_* 컬럼이 추가된 DataFrame.
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"""
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out = general_analysis_apply_patterns_to_bars(df, interval, tail_rows)
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out = general_analysis_apply_wave_to_bars(out, interval, tail_rows)
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out = general_analysis_apply_volume_to_bars(out, interval, tail_rows)
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out = general_analysis_apply_harmonic_to_bars(out, interval, tail_rows)
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return out
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