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https://github.com/xavierchuan/FX-ML-Trading-Engine.git
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xiaochuan
139 lines
4.1 KiB
Python
139 lines
4.1 KiB
Python
# scripts/plot_indicators.py
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import os
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from datetime import datetime
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import numpy as np
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import pandas as pd
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import plotly.graph_objects as go
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from plotly.subplots import make_subplots
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BASE_DIR = os.path.dirname(os.path.dirname(__file__))
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DERIVED_DATA_DIR = os.path.join(BASE_DIR, "data", "derived")
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CHARTS_DIR = os.path.join(BASE_DIR, "charts")
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os.makedirs(CHARTS_DIR, exist_ok=True)
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DATA_PATH = os.path.join(DERIVED_DATA_DIR, "EURUSD_H1_with_indicators.csv")
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# 自动生成带时间戳的输出文件名
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timestamp = datetime.now().strftime("%Y%m%d_%H%M")
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OUTPUT_PATH = os.path.join(CHARTS_DIR, f"EURUSD_H1_with_indicators_{timestamp}.html")
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df = pd.read_csv(DATA_PATH, parse_dates=["time"])
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# 计算均线（若已存在将覆盖为最新计算）
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if {"close"}.issubset(df.columns):
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df["SMA_20"] = df["close"].rolling(20).mean()
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df["SMA_200"] = df["close"].rolling(200).mean()
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# 创建两行子图，共享x轴
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fig = make_subplots(rows=2, cols=1, shared_xaxes=True,
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vertical_spacing=0.1,
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row_heights=[0.7, 0.3],
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specs=[[{"type": "candlestick"}],
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[{"secondary_y": True}]])
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# 第一个子图：蜡烛图 + 均线
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fig.add_trace(go.Candlestick(
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x=df['time'],
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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='Candlestick'
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), row=1, col=1)
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if 'SMA_20' in df.columns:
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fig.add_trace(go.Scatter(
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x=df['time'], y=df['SMA_20'],
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line=dict(color='blue', width=1),
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name='SMA 20'
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), row=1, col=1)
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if 'EMA_50' in df.columns:
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fig.add_trace(go.Scatter(
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x=df['time'], y=df['EMA_50'],
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line=dict(color='orange', width=1),
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name='EMA 50'
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), row=1, col=1)
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# 绘制 SMA 200
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if 'SMA_200' in df.columns:
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fig.add_trace(go.Scatter(
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x=df['time'], y=df['SMA_200'],
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line=dict(width=1),
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name='SMA 200'
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), row=1, col=1)
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# 金叉/死叉标记：SMA20 与 SMA200 交叉
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if 'SMA_20' in df.columns and 'SMA_200' in df.columns:
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sign = np.sign(df["SMA_20"] - df["SMA_200"])
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cross = sign.diff().fillna(0).ne(0) & df["SMA_20"].notna() & df["SMA_200"].notna()
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golden = cross & (sign > 0)
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dead = cross & (sign < 0)
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# 金叉
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fig.add_trace(go.Scatter(
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x=df.loc[golden, "time"], y=df.loc[golden, "SMA_20"],
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mode="markers", name="Golden Cross",
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marker_symbol="triangle-up", marker_size=9
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), row=1, col=1)
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# 死叉
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fig.add_trace(go.Scatter(
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x=df.loc[dead, "time"], y=df.loc[dead, "SMA_20"],
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mode="markers", name="Dead Cross",
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marker_symbol="triangle-down", marker_size=9
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), row=1, col=1)
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# 第二个子图：RSI 和 MACD
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rsi_exists = 'RSI' in df.columns
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macd_exists = 'MACD' in df.columns and 'MACD_signal' in df.columns and 'MACD_hist' in df.columns
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if rsi_exists:
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fig.add_trace(go.Scatter(
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x=df['time'], y=df['RSI'],
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line=dict(color='purple', width=1),
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name='RSI'
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), row=2, col=1, secondary_y=False)
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if macd_exists:
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# MACD 柱状图
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fig.add_trace(go.Bar(
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x=df['time'], y=df['MACD_hist'],
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marker_color='grey',
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name='MACD Hist'
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), row=2, col=1, secondary_y=True)
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# MACD 线
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fig.add_trace(go.Scatter(
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x=df['time'], y=df['MACD'],
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line=dict(color='blue', width=1),
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name='MACD'
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), row=2, col=1, secondary_y=True)
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# MACD 信号线
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fig.add_trace(go.Scatter(
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x=df['time'], y=df['MACD_signal'],
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line=dict(color='orange', width=1, dash='dot'),
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name='MACD Signal'
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), row=2, col=1, secondary_y=True)
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# 布局设置
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fig.update_layout(
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title="EUR/USD with Technical Indicators",
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xaxis_title="Time",
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yaxis_title="Price",
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xaxis_rangeslider_visible=False,
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legend=dict(orientation="h", yanchor="bottom", y=1.02, xanchor="right", x=1)
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)
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# RSI y轴范围限制
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if rsi_exists:
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fig.update_yaxes(title_text="RSI", row=2, col=1, secondary_y=False, range=[0, 100])
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# MACD y轴标题
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if macd_exists:
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fig.update_yaxes(title_text="MACD", row=2, col=1, secondary_y=True)
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# 保存图表
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fig.write_html(OUTPUT_PATH)
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print(f"✅ 图表已保存至 {OUTPUT_PATH}")
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