e68bb44083
미래 데이터를 쓰지 않는 causal 신호/tier와 전기간 복리 포트폴리오 비교로 GT 대비 sim_sized 검증 경로를 정리하고, 일한도·매수 상한·live_buy 스케일을 제거한다. Co-authored-by: Cursor <cursoragent@cursor.com>
720 lines
22 KiB
Python
720 lines
22 KiB
Python
"""
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WLD 볼린저 밴드 차트.
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python scripts/05_chart_bb.py
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python scripts/05_chart_truth.py
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python scripts/02_ground_truth.py
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"""
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from __future__ import annotations
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import sys
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import webbrowser
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from pathlib import Path
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import numpy as np
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import pandas as pd
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import plotly.graph_objs as go
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from plotly.subplots import make_subplots
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from config import (
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CHART_LOOKBACK_DAYS,
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COIN_NAME,
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DISPARITY_OVERBOUGHT,
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DISPARITY_OVERSOLD,
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DISPARITY_PERIODS,
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ENTRY_INTERVAL,
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GROUND_TRUTH_FILE,
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GT_INITIAL_CASH_KRW,
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GT_MARKER_SIZE_MAX,
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GT_MARKER_SIZE_MIN,
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LIVE_ORDER_KRW,
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MACD_FAST,
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MACD_SIGNAL,
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MACD_SLOW,
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STOCH_D_PERIOD,
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STOCH_K_PERIOD,
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SYMBOL,
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TRADING_FEE_RATE,
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TREND_INTERVAL_1D,
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TREND_INTERVAL_1H,
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)
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from deepcoin.common.indicators import apply_bar_indicators, disparity_column, get_trend
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from deepcoin.ops.monitor import Monitor
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from deepcoin.data.mtf_bb import interval_label, load_frames_from_db
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from deepcoin.ops.chart_report import wrap_chart_report_page
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from deepcoin.paths import CHART_BB_HTML, CHART_TRUTH_HTML, resolve_ground_truth_file
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OUTPUT_HTML = CHART_BB_HTML
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TRUTH_HTML = CHART_TRUTH_HTML
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GROUND_TRUTH_PATH = resolve_ground_truth_file()
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REPORT_DIR = CHART_BB_HTML.parent
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def interval_chart_label(interval_min: int) -> str:
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"""차트 제목용 봉 라벨."""
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if interval_min >= 1440:
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return "일봉"
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return f"{interval_min}분봉"
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def _marker_hover_text(
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label: str,
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t: dict,
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*,
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default_order_krw: float | None = None,
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extra_lines: list[str] | None = None,
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) -> str:
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"""
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차트 마커 툴팁: 체결가(price)와 체결 원화(amount_krw)를 함께 표시.
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Args:
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label: 정답/시뮬 매수·매도 라벨.
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t: trade dict (price, amount_krw, weight, memo …).
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default_order_krw: amount_krw 없을 때 표시할 기본 원화(시뮬 고정 주문).
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extra_lines: 툴팁 하단 추가 줄.
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Returns:
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hovertext HTML 줄바꿈 문자열.
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"""
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action = t.get("action", t.get("side", ""))
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amt_label = "매수금액" if action == "buy" else "매도금액"
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lines = [
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label,
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str(t.get("dt", ""))[:16],
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f"체결가 ₩{float(t['price']):,.0f}",
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]
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ak = t.get("amount_krw")
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if ak is not None and float(ak) > 0:
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lines.append(f"{amt_label} ₩{float(ak):,.0f}")
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elif default_order_krw is not None and action == "buy":
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lines.append(f"{amt_label} ₩{float(default_order_krw):,.0f}")
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else:
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lines.append(f"{amt_label} (미배분)")
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if t.get("weight") is not None:
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lines.append(f"비중 {float(t.get('weight', 1)) * 100:.0f}%")
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if extra_lines:
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lines.extend(extra_lines)
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memo = t.get("memo", "")
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if memo:
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lines.append(str(memo))
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rule_id = t.get("rule_id", "")
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if rule_id:
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lines.append(str(rule_id))
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return "<br>".join(lines)
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def _trade_amount_krw(t: dict) -> float:
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"""
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마커 크기·툴팁용 체결 원화. amount_krw 없으면 비중×초기자본으로 상대 크기만 추정.
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Args:
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t: trade dict.
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Returns:
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원화 금액(0 이상).
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"""
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ak = t.get("amount_krw")
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if ak is not None and float(ak) > 0:
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return float(ak)
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return max(float(t.get("weight", 1.0)), 0.05) * float(GT_INITIAL_CASH_KRW)
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def _marker_sizes(pts: list[dict]) -> list[float]:
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"""
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체결 원화(amount_krw)에 비례한 삼각형 크기.
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같은 trace(매수 또는 매도) 안에서 최소·최대 금액으로 선형 스케일.
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Args:
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pts: 동일 action의 trade dict 리스트.
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Returns:
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plotly marker size(diameter) 리스트.
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"""
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if not pts:
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return []
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lo, hi = float(GT_MARKER_SIZE_MIN), float(GT_MARKER_SIZE_MAX)
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amounts = [_trade_amount_krw(t) for t in pts]
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amin, amax = min(amounts), max(amounts)
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sizes: list[float] = []
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for amount in amounts:
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if amax > amin:
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ratio = (amount - amin) / (amax - amin)
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else:
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ratio = 0.5
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ratio = max(ratio, 0.08)
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sizes.append(lo + (hi - lo) * ratio)
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return sizes
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def _add_sim_markers(fig, trades: list[dict], row: int = 1) -> None:
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"""
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시뮬(규칙) 매수·매도 마커 — 원형, GT 삼각형과 구분.
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Args:
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fig: plotly Figure.
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trades: dt, action, price, forward_ret_pct, rule_id 키.
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row: subplot row.
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"""
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for action, color, label in [
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("buy", "#059669", "시뮬 매수"),
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("sell", "#b91c1c", "시뮬 매도"),
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]:
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pts = [t for t in trades if t.get("action") == action]
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if not pts:
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continue
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fig.add_trace(
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go.Scatter(
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x=[pd.Timestamp(t["dt"]) for t in pts],
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y=[float(t["price"]) for t in pts],
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mode="markers",
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name=label,
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legendgroup=label,
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marker=dict(
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symbol="circle",
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size=9,
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color=color,
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line=dict(width=1, color="#fff"),
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opacity=0.75,
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),
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hovertext=[
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_marker_hover_text(
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label,
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t,
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default_order_krw=LIVE_ORDER_KRW,
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extra_lines=[
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f"leg_gt {float(t.get('forward_ret_pct', 0)):+.2f}%",
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],
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)
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for t in pts
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],
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hovertemplate="%{hovertext}<extra></extra>",
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),
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row=row,
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col=1,
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)
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def _add_truth_markers(fig, trades: list[dict], row: int = 1) -> None:
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"""정답 매수·매도 마커 (삼각형 크기 = 체결 원화 금액)."""
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for action, color, symbol, label in [
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("buy", "#16a34a", "triangle-up", "정답 매수"),
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("sell", "#dc2626", "triangle-down", "정답 매도"),
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]:
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pts = [t for t in trades if t.get("action") == action]
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if not pts:
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continue
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sizes = _marker_sizes(pts)
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fig.add_trace(
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go.Scatter(
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x=[pd.Timestamp(t["dt"]) for t in pts],
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y=[t["price"] for t in pts],
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mode="markers",
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name=label,
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legendgroup=label,
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marker=dict(
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symbol=symbol,
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size=sizes,
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sizemode="diameter",
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color=color,
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line=dict(width=1.5, color="#111"),
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),
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hovertext=[
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_marker_hover_text(label, t)
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for t in pts
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],
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hovertemplate="%{hovertext}<extra></extra>",
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),
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row=row,
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col=1,
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)
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def build_chart_html(
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df: pd.DataFrame,
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trend: str,
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interval_min: int = ENTRY_INTERVAL,
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note: str = "",
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truth_trades: list[dict] | None = None,
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sim_trades: list[dict] | None = None,
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title_suffix: str = "BB 차트",
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pnl_summary: dict | None = None,
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legend_html: str | None = None,
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footer_sections: str | None = None,
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cards_html: str | None = None,
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) -> str:
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"""BB·이격도·RSI·MACD·스토캐스틱·거래량 차트 HTML."""
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df = apply_bar_indicators(df.copy())
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iv_label = interval_chart_label(interval_min)
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close_last = float(df["Close"].iloc[-1])
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bb_pos = None
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if "bb_pos" in df.columns and pd.notna(df["bb_pos"].iloc[-1]):
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bb_pos = float(df["bb_pos"].iloc[-1])
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disp_title = "이격도 " + ",".join(str(p) for p in DISPARITY_PERIODS)
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fig = make_subplots(
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rows=6,
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cols=1,
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shared_xaxes=True,
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vertical_spacing=0.03,
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row_heights=[0.42, 0.11, 0.11, 0.11, 0.13, 0.12],
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subplot_titles=(
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f"{COIN_NAME} ({SYMBOL}) {iv_label}",
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disp_title,
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f"Stochastic ({STOCH_K_PERIOD},{STOCH_D_PERIOD})",
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"RSI (14)",
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f"MACD ({MACD_FAST},{MACD_SLOW},{MACD_SIGNAL})",
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"거래량",
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),
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)
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disp_colors = ("#0d9488", "#7c3aed", "#ca8a04")
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fig.add_trace(
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go.Candlestick(
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x=df.index,
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open=df["Open"],
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high=df["High"],
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low=df["Low"],
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close=df["Close"],
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name=f"{iv_label} 캔들",
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increasing_line_color="#ef4444",
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decreasing_line_color="#3b82f6",
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),
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row=1,
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col=1,
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)
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if "MA" in df.columns:
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fig.add_trace(
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go.Scatter(
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x=df.index,
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y=df["MA"],
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name="BB 중심",
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line=dict(color="#64748b", width=1, dash="dot"),
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),
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row=1,
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col=1,
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)
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if "Upper" in df.columns:
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fig.add_trace(
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go.Scatter(
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x=df.index,
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y=df["Upper"],
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name="BB 상단",
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line=dict(color="#94a3b8", width=1),
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),
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row=1,
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col=1,
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)
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if "Lower" in df.columns:
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fig.add_trace(
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go.Scatter(
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x=df.index,
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y=df["Lower"],
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name="BB 하단",
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line=dict(color="#94a3b8", width=1),
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),
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row=1,
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col=1,
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)
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if truth_trades:
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_add_truth_markers(fig, truth_trades, row=1)
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if sim_trades:
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_add_sim_markers(fig, sim_trades, row=1)
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disp_row = 2
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for i, p in enumerate(DISPARITY_PERIODS):
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col = disparity_column(p)
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if col not in df.columns:
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continue
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color = disp_colors[i % len(disp_colors)]
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fig.add_trace(
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go.Scatter(
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x=df.index,
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y=df[col],
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name=f"D.I. {p}",
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line=dict(color=color, width=1),
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),
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row=disp_row,
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col=1,
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)
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if any(disparity_column(p) in df.columns for p in DISPARITY_PERIODS):
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fig.add_hline(
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y=100, line_dash="solid", line_color="#64748b", row=disp_row, col=1
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)
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fig.add_hline(
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y=DISPARITY_OVERBOUGHT,
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line_dash="dot",
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line_color="#ef4444",
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row=disp_row,
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col=1,
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)
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fig.add_hline(
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y=DISPARITY_OVERSOLD,
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line_dash="dot",
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line_color="#16a34a",
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row=disp_row,
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col=1,
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)
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stoch_row = 3
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if "stoch_k" in df.columns:
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fig.add_trace(
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go.Scatter(
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x=df.index,
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y=df["stoch_k"],
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name="Stoch %K",
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line=dict(color="#0ea5e9", width=1),
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),
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row=stoch_row,
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col=1,
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)
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fig.add_trace(
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go.Scatter(
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x=df.index,
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y=df["stoch_d"],
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name="Stoch %D",
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line=dict(color="#f97316", width=1),
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),
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row=stoch_row,
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col=1,
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)
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fig.add_hline(y=80, line_dash="dot", line_color="#9ca3af", row=stoch_row, col=1)
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fig.add_hline(y=20, line_dash="dot", line_color="#9ca3af", row=stoch_row, col=1)
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rsi_row = 4
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if "RSI" in df.columns:
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fig.add_trace(
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go.Scatter(
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x=df.index,
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y=df["RSI"],
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name="RSI",
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line=dict(color="#7c3aed"),
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),
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row=rsi_row,
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col=1,
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)
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fig.add_hline(y=70, line_dash="dot", line_color="#9ca3af", row=rsi_row, col=1)
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fig.add_hline(y=30, line_dash="dot", line_color="#9ca3af", row=rsi_row, col=1)
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macd_row = 5
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vol_row = 6
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if "macd_hist" in df.columns:
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colors = np.where(df["macd_hist"].astype(float) >= 0, "#ef4444", "#3b82f6")
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fig.add_trace(
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go.Bar(
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x=df.index,
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y=df["macd_hist"],
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name="MACD Hist",
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marker_color=colors,
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),
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row=macd_row,
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col=1,
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)
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fig.add_trace(
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go.Scatter(
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x=df.index,
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y=df["macd_line"],
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name="MACD",
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line=dict(color="#2563eb", width=1),
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),
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row=macd_row,
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col=1,
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)
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fig.add_trace(
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go.Scatter(
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x=df.index,
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y=df["macd_signal"],
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name="Signal",
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line=dict(color="#ea580c", width=1, dash="dot"),
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),
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row=macd_row,
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col=1,
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)
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fig.add_trace(
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go.Bar(
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x=df.index,
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y=df["Volume"],
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name="Volume",
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marker_color="#cbd5e1",
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),
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row=vol_row,
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col=1,
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)
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fig.update_layout(
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height=1180,
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template="plotly_white",
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xaxis_rangeslider_visible=False,
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legend=dict(orientation="h", y=1.05, x=0),
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margin=dict(l=60, r=30, t=90, b=40),
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)
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fig.update_yaxes(title_text="가격 (KRW)", row=1, col=1)
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fig.update_yaxes(title_text="이격도", row=2, col=1)
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fig.update_yaxes(title_text="Stoch", row=3, col=1, range=[0, 100])
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fig.update_yaxes(title_text="RSI", row=4, col=1, range=[0, 100])
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fig.update_yaxes(title_text="MACD", row=5, col=1)
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chart_html = fig.to_html(full_html=False, include_plotlyjs="cdn")
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note_html = f"<p class='note'>{note}</p>" if note else ""
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bb_pos_txt = f"{bb_pos:.2f}" if bb_pos is not None else "-"
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pnl = pnl_summary or {}
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if truth_trades and not pnl:
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from deepcoin.ground_truth.ground_truth import simulate_truth_portfolio
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pnl = simulate_truth_portfolio(
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truth_trades,
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initial_cash=GT_INITIAL_CASH_KRW,
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fee_rate=TRADING_FEE_RATE,
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last_price=close_last,
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)
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trade_rows = ""
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trade_table = footer_sections or ""
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if footer_sections is None and truth_trades:
|
||
from deepcoin.ground_truth.ground_truth import simulate_truth_portfolio_steps
|
||
|
||
steps = simulate_truth_portfolio_steps(
|
||
truth_trades,
|
||
initial_cash=GT_INITIAL_CASH_KRW,
|
||
fee_rate=TRADING_FEE_RATE,
|
||
)
|
||
step_key = {
|
||
(s["dt"], s["action"], float(s["price"]), float(s["weight"])): s
|
||
for s in steps
|
||
}
|
||
sorted_trades = sorted(truth_trades, key=lambda x: x["dt"])
|
||
trade_rows += f"""
|
||
<tr class="initial-row">
|
||
<td>시작</td>
|
||
<td>-</td>
|
||
<td>-</td>
|
||
<td>-</td>
|
||
<td><b>₩{GT_INITIAL_CASH_KRW:,.0f}</b></td>
|
||
<td>초기 현금 (보유 0)</td>
|
||
</tr>"""
|
||
for t in sorted_trades:
|
||
cls = "buy" if t["action"] == "buy" else "sell"
|
||
mark = "매수" if t["action"] == "buy" else "매도"
|
||
ret = t.get("forward_return_pct")
|
||
ret_s = f" (+{ret}%)" if ret is not None else ""
|
||
w = float(t.get("weight", 1.0))
|
||
key = (t["dt"], t["action"], float(t["price"]), w)
|
||
step = step_key.get(key)
|
||
if step:
|
||
total_s = f"₩{step['total_asset_krw']:,.0f}"
|
||
hold_s = f" (현금 ₩{step['cash_krw']:,.0f} + 코인 {step['holding_qty']:,.2f}개)"
|
||
else:
|
||
total_s = "-"
|
||
hold_s = ""
|
||
trade_rows += f"""
|
||
<tr>
|
||
<td>{t['dt'][:16]}</td>
|
||
<td class="{cls}">{mark}</td>
|
||
<td>{w*100:.0f}%</td>
|
||
<td>₩{t['price']:,.0f}{ret_s}</td>
|
||
<td><b>{total_s}</b>{hold_s}</td>
|
||
<td>{t.get('memo', '')}</td>
|
||
</tr>"""
|
||
if not trade_table and truth_trades:
|
||
if not trade_rows:
|
||
trade_rows = "<tr><td colspan='6'>타점 없음</td></tr>"
|
||
mark_note = ""
|
||
if pnl.get("mark_price"):
|
||
mark_note = (
|
||
f" 총보유자산(미청산 포함)은 종가 ₩{pnl['mark_price']:,.0f} 평가."
|
||
)
|
||
trade_table = f"""
|
||
<h2>정답 타점 (ground_truth)</h2>
|
||
<p class="meta">삼각형 크기 = 체결 금액(매수/매도 각각 min~max). 매수: 저점 분할 / 매도: 고점 1~2회.
|
||
총평가 = 체결 직후 현금 + 보유×체결가.{mark_note}</p>
|
||
<table>
|
||
<thead><tr><th>시각</th><th>구분</th><th>비중</th><th>가격</th><th>총 평가금액</th><th>해석</th></tr></thead>
|
||
<tbody>{trade_rows}</tbody>
|
||
</table>"""
|
||
|
||
pnl_cards = ""
|
||
if truth_trades and pnl.get("initial_cash_krw") is not None:
|
||
from deepcoin.ops.chart_report import card_html, initial_change_pct
|
||
|
||
change_pct = initial_change_pct(pnl)
|
||
pnl_cards = (
|
||
card_html("초기 금액", f"₩{pnl['initial_cash_krw']:,.0f}")
|
||
+ card_html("총보유자산", f"₩{pnl['final_asset_krw']:,.0f}")
|
||
+ card_html("초기 대비 증감율", f"{change_pct:+.2f}%")
|
||
+ card_html("수수료", f"₩{pnl['total_fees_krw']:,.0f}")
|
||
)
|
||
if pnl.get("holding_qty", 0) > 0:
|
||
pnl_cards += card_html(
|
||
"미청산",
|
||
f"{pnl['holding_qty']}개 (₩{pnl['holding_value_krw']:,.0f})",
|
||
)
|
||
|
||
default_legend = (
|
||
"▲ <b>정답 매수</b> · ▼ <b>정답 매도</b> — 크기=체결금액. "
|
||
"매수=총자산×비중×leg티어(상위 대형). "
|
||
"툴팁: 체결가·매수/매도금액.<br>"
|
||
"● <b>시뮬 매수</b> · ● <b>시뮬 매도</b> — 원 = holdout 발화 "
|
||
f"(매수 ₩{LIVE_ORDER_KRW:,.0f}/회)."
|
||
)
|
||
if cards_html:
|
||
cards_inner = cards_html
|
||
else:
|
||
cards_inner = f"""
|
||
<div class="card"><span>종가</span><b>₩{close_last:,.2f}</b></div>
|
||
<div class="card"><span>BB %B</span><b>{bb_pos_txt}</b></div>
|
||
<div class="card"><span>정답 타점</span><b>{len(truth_trades) if truth_trades else 0}건</b></div>
|
||
{pnl_cards}"""
|
||
return wrap_chart_report_page(
|
||
page_title=f"{SYMBOL} {title_suffix}",
|
||
heading=f"{COIN_NAME} ({SYMBOL}) {title_suffix}",
|
||
meta_line=f"추세(참고): {trend} | 기간: {df.index[0]} ~ {df.index[-1]} | 봉 수: {len(df)}",
|
||
note_html=note_html,
|
||
legend_html=legend_html or default_legend,
|
||
cards_html=cards_inner,
|
||
chart_html=chart_html,
|
||
sections_html=trade_table,
|
||
)
|
||
|
||
|
||
def _frames_to_mtf(
|
||
frames: dict[int, pd.DataFrame],
|
||
) -> tuple[pd.DataFrame, pd.DataFrame, pd.DataFrame]:
|
||
"""전 간격 frames에서 1d/1h/3m 추출."""
|
||
df_3m = frames.get(ENTRY_INTERVAL)
|
||
if df_3m is None or df_3m.empty:
|
||
raise ValueError(f"{ENTRY_INTERVAL}분봉 데이터 없음")
|
||
df_1d = frames.get(TREND_INTERVAL_1D)
|
||
if df_1d is None or df_1d.empty:
|
||
df_1d = df_3m
|
||
df_1h = frames.get(TREND_INTERVAL_1H)
|
||
if df_1h is None or df_1h.empty:
|
||
df_1h = df_3m
|
||
return df_1d, df_1h, df_3m
|
||
|
||
|
||
def load_chart_frames() -> dict[int, pd.DataFrame] | None:
|
||
"""coins.db 전 간격 로드. 부족 시 None."""
|
||
monitor = Monitor(cooldown_file=None)
|
||
print(f"DB 조회: 최근 {CHART_LOOKBACK_DAYS}일 (CHART_LOOKBACK_DAYS)")
|
||
frames = load_frames_from_db(monitor, SYMBOL, lookback_days=CHART_LOOKBACK_DAYS)
|
||
if ENTRY_INTERVAL not in frames:
|
||
print("coins.db 데이터 부족. python scripts/01_download.py 실행 후 재시도.")
|
||
return None
|
||
return frames
|
||
|
||
|
||
def run_ground_truth_chart(open_browser: bool = True) -> Path:
|
||
"""
|
||
정답 타점을 생성·저장하고 마커가 포함된 HTML 차트를 만듭니다.
|
||
|
||
Args:
|
||
open_browser: True면 브라우저로 HTML을 엽니다.
|
||
|
||
Returns:
|
||
HTML 파일 경로.
|
||
"""
|
||
from deepcoin.ground_truth.ground_truth import run_from_db
|
||
|
||
data = run_from_db()
|
||
frames = load_chart_frames()
|
||
if frames is None:
|
||
raise RuntimeError("차트 데이터 로드 실패")
|
||
|
||
df_1d, df_1h, df_3m = _frames_to_mtf(frames)
|
||
trend = get_trend(df_1d, df_1h)
|
||
df_chart = apply_bar_indicators(df_3m)
|
||
trades = data.get("trades") or []
|
||
|
||
summary = data.get("summary") or {}
|
||
html = build_chart_html(
|
||
df_chart,
|
||
trend,
|
||
note=data.get("note", ""),
|
||
truth_trades=trades,
|
||
title_suffix=f"정답 타점 ({CHART_LOOKBACK_DAYS}일)",
|
||
pnl_summary=summary if summary.get("pnl_krw") is not None else None,
|
||
)
|
||
REPORT_DIR.mkdir(parents=True, exist_ok=True)
|
||
TRUTH_HTML.write_text(html, encoding="utf-8")
|
||
print(f"HTML: {TRUTH_HTML}")
|
||
if open_browser:
|
||
webbrowser.open(TRUTH_HTML.resolve().as_uri())
|
||
return TRUTH_HTML
|
||
|
||
|
||
def run_chart(open_browser: bool = True) -> Path:
|
||
"""
|
||
3분봉 BB 차트 HTML을 생성합니다.
|
||
|
||
Args:
|
||
open_browser: True면 기본 브라우저로 HTML을 엽니다.
|
||
|
||
Returns:
|
||
저장된 HTML 경로.
|
||
"""
|
||
frames = load_chart_frames()
|
||
if frames is None:
|
||
raise RuntimeError("차트 데이터 로드 실패")
|
||
|
||
df_1d, df_1h, df_3m = _frames_to_mtf(frames)
|
||
trend = get_trend(df_1d, df_1h)
|
||
df_chart = apply_bar_indicators(df_3m)
|
||
print(f"\n추세(참고): {trend}")
|
||
print(f"3분: {df_chart.index[0]} ~ {df_chart.index[-1]} ({len(df_chart)}봉)")
|
||
|
||
html = build_chart_html(
|
||
df_chart,
|
||
trend,
|
||
note="자동 매수·매도 전략은 사용하지 않습니다.",
|
||
)
|
||
REPORT_DIR.mkdir(parents=True, exist_ok=True)
|
||
OUTPUT_HTML.write_text(html, encoding="utf-8")
|
||
print(f"HTML: {OUTPUT_HTML}")
|
||
if open_browser:
|
||
webbrowser.open(OUTPUT_HTML.resolve().as_uri())
|
||
return OUTPUT_HTML
|
||
|
||
|
||
def print_usage() -> None:
|
||
print(
|
||
"""
|
||
DeepCoin simulation.py
|
||
|
||
python simulation.py
|
||
WLD 3분봉 BB 차트 → docs/charts/wld_bb_chart.html
|
||
|
||
python simulation.py truth
|
||
정답 타점 생성 → ground_truth_trades.json
|
||
차트 → docs/02_ground_truth/wld_ground_truth_chart.html
|
||
"""
|
||
)
|
||
|
||
|
||
def main() -> None:
|
||
if len(sys.argv) > 1 and sys.argv[1] in ("-h", "--help", "help"):
|
||
print_usage()
|
||
return
|
||
if len(sys.argv) > 1 and sys.argv[1] in ("truth", "ground-truth", "gt"):
|
||
print("=" * 60)
|
||
print("정답 타점 생성 + 차트")
|
||
print("=" * 60)
|
||
run_ground_truth_chart()
|
||
print("\n완료.")
|
||
return
|
||
if len(sys.argv) > 1:
|
||
print(f"알 수 없는 옵션: {sys.argv[1]}\n")
|
||
print_usage()
|
||
return
|
||
print("=" * 60)
|
||
print("WLD BB 차트 (매매 전략 없음)")
|
||
print("=" * 60)
|
||
run_chart()
|
||
print("\n완료.")
|
||
|
||
|
||
if __name__ == "__main__":
|
||
main()
|