WLD DeepCoin 단계별 구조 재편 및 설정·문서 통합

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>

deepcoin/analysis/general_analysis_context.py

@@ -0,0 +1,98 @@
+"""
+general_analysis lookback 컨텍스트 특징 (패턴·파동·VP·하모닉) 봉별 적용.
+"""
+
+from __future__ import annotations
+
+import pandas as pd
+
+from deepcoin.analysis.general_analysis_config import CONTEXT_TAIL_ROWS, LOOKBACK_BARS
+from deepcoin.analysis.general_analysis_core import ga_col
+from deepcoin.analysis.general_analysis_harmonic import (
+    general_analysis_harmonic_columns,
+    general_analysis_harmonic_snapshot,
+)
+from deepcoin.analysis.general_analysis_patterns import general_analysis_apply_patterns_to_bars
+from deepcoin.analysis.general_analysis_volume import (
+    general_analysis_volume_columns,
+    general_analysis_volume_snapshot,
+)
+from deepcoin.analysis.general_analysis_wave import general_analysis_apply_wave_to_bars
+
+
+def general_analysis_apply_volume_to_bars(
+    df: pd.DataFrame,
+    interval: int,
+    tail_rows: int | None = None,
+) -> pd.DataFrame:
+    """Volume Profile 컬럼을 최근 봉에 롤링 적용."""
+    out = df.copy()
+    for k in general_analysis_volume_columns():
+        out[ga_col(k)] = 0.0 if k != "vp_in_value_area" else 0
+
+    lb = LOOKBACK_BARS.get(interval, 80)
+    n = len(out)
+    if n < lb + 1:
+        return out
+    if tail_rows is None:
+        tail_rows = CONTEXT_TAIL_ROWS.get(interval, 5000)
+    start = max(lb, n - tail_rows)
+
+    for i in range(start, n):
+        snap = general_analysis_volume_snapshot(out.iloc[i - lb : i])
+        idx = out.index[i]
+        for k, v in snap.items():
+            out.at[idx, k] = v
+
+    return out
+
+
+def general_analysis_apply_harmonic_to_bars(
+    df: pd.DataFrame,
+    interval: int,
+    tail_rows: int | None = None,
+) -> pd.DataFrame:
+    """하모닉 패턴 컬럼 롤링 적용."""
+    out = df.copy()
+    for k in general_analysis_harmonic_columns():
+        default = "none" if k == "harmonic_label" else 0
+        out[ga_col(k)] = default
+
+    lb = LOOKBACK_BARS.get(interval, 80)
+    n = len(out)
+    if n < lb + 1:
+        return out
+    if tail_rows is None:
+        tail_rows = CONTEXT_TAIL_ROWS.get(interval, 5000)
+    start = max(lb, n - tail_rows)
+
+    for i in range(start, n):
+        snap = general_analysis_harmonic_snapshot(out.iloc[i - lb : i])
+        idx = out.index[i]
+        for k, v in snap.items():
+            out.at[idx, k] = v
+
+    return out
+
+
+def general_analysis_apply_context_features(
+    df: pd.DataFrame,
+    interval: int,
+    tail_rows: int | None = None,
+) -> pd.DataFrame:
+    """
+    패턴·파동·VP·하모닉 lookback 라벨을 봉 시계열에 병합.
+
+    Args:
+        df: general_analysis_enrich_bars 1단계 결과.
+        interval: 분봉 간격(분).
+        tail_rows: 롤링 적용 봉 수 상한.
+
+    Returns:
+        컨텍스트 ga_* 컬럼이 추가된 DataFrame.
+    """
+    out = general_analysis_apply_patterns_to_bars(df, interval, tail_rows)
+    out = general_analysis_apply_wave_to_bars(out, interval, tail_rows)
+    out = general_analysis_apply_volume_to_bars(out, interval, tail_rows)
+    out = general_analysis_apply_harmonic_to_bars(out, interval, tail_rows)
+    return out