添加CCI上下界；添加POC，poc计算显示区域最新的k线相比poc的收益 poc_range_profit%

chart.py

@@ -2,11 +2,14 @@ import pandas as pd
 from db_config import DatabaseManager, DatabaseConfig
 from loguru import logger
 import talib as ta
+import numpy as np
 from lightweight_charts import Chart
 
 
 import random
 
+horizontal_lines = {}
+
 
 def get_fixed_color_based_on_period(period):
     # 使用周期值作为随机种子，确保相同周期生成相同颜色
@@ -30,7 +33,9 @@ def add_ema(df, chart, period: int = 50):
     name = f"EMA {period}"
     df[name] = ta.EMA(df["close"], timeperiod=period)
     color = get_fixed_color_based_on_period(period)
-    line = chart.create_line(name, color=color, width=2)
+    line = chart.create_line(
+        name, color=color, width=2, price_label=False, price_line=False
+    )
     line.set(df[["time", name]])
 
 
@@ -46,6 +51,27 @@ def add_cci(df, chart, period: int = 14, height: float = 0.1, position: str = "b
     cci_chart.time_scale(visible=False)
     cci_line = cci_chart.create_line(name="cci", color="#FF0000", width=2)
     cci_line.set(df[["time", "cci"]])
+    df = df[["time"]].copy()
+    df["h"] = 100
+    df["l"] = -100
+    cci_line = cci_chart.create_line(
+        name="h",
+        color="#D4C21C",
+        width=1,
+        style="dashed",
+        price_label=False,
+        price_line=False,
+    )
+    cci_line.set(df[["time", "h"]])
+    cci_line = cci_chart.create_line(
+        name="l",
+        color="#D4C21C",
+        width=1,
+        style="dashed",
+        price_label=False,
+        price_line=False,
+    )
+    cci_line.set(df[["time", "l"]])
 
 
 def add_macd(df, chart, height: float = 0.1, position: str = "bottom"):
@@ -70,9 +96,13 @@ def add_macd(df, chart, height: float = 0.1, position: str = "bottom"):
     )
     histogram.set(hist_data)
 
-    macd_line = macd_chart.create_line(name="macd", color="#2962FF", width=2)
+    macd_line = macd_chart.create_line(
+        name="macd", color="#2962FF", width=2, price_label=False, price_line=False
+    )
     macd_line.set(df[["time", "macd"]])
-    signal_line = macd_chart.create_line(name="signal", color="#FF0000", width=2)
+    signal_line = macd_chart.create_line(
+        name="signal", color="#FF0000", width=2, price_label=False, price_line=False
+    )
     signal_line.set(df[["time", "signal"]])
 
 
@@ -229,13 +259,64 @@ def resample_data(df: pd.DataFrame, timeframe: str) -> pd.DataFrame:
     return resampled
 
 
+def POC(df, bins: int = 50):
+    low, high = df["low"].min(), df["high"].max()
+    edges = np.linspace(low, high, bins + 1)
+    # 为每根K线生成 bins 个均匀价格点，并分配等量成交量
+    prices = np.concatenate(
+        [np.linspace(r["low"], r["high"], bins) for _, r in df.iterrows()]
+    )
+    volumes = np.repeat(df["volume"].values / bins, bins)
+    # 分箱求和
+    vol_profile, _ = np.histogram(prices, bins=edges, weights=volumes)
+    # 返回最大成交量区间的中点
+    idx = np.argmax(vol_profile)
+    poc = (edges[idx] + edges[idx + 1]) / 2
+    return poc
+
+
+def on_range_change_poc(chart, bars_before, bars_after):
+    df = chart.candle_data
+    if df is None or df.empty:
+        return
+
+    total_bars = len(df)
+    if bars_after < 0:
+        start_idx = max(0, int(bars_before))
+        end_idx = total_bars
+    else:
+        start_idx = int(bars_before)
+        end_idx = max(0, int(total_bars - bars_after))
+    df_range = df.iloc[start_idx:end_idx]
+    # logger.info(
+    #     f"Calculating POC for bars {start_idx} to {end_idx}, total_bars={total_bars}, bars_before={bars_before}, bars_after={bars_after}"
+    # )
+    # logger.info(f"df_range_len: {len(df_range)}")
+    poc = POC(df_range)
+    poc_line_name = "POC"
+    if poc_line_name in horizontal_lines:
+        horizontal_lines[poc_line_name].delete()
+    # 添加新的 POC 水平线
+    latest_close = df_range["close"].iloc[-1]
+    profit = (latest_close - poc) / poc * 100
+    poc_line = chart.horizontal_line(
+        price=poc, color="#FF0000", width=4, style="solid", text=f"{poc:.2f}"
+    )
+    chart.legend(
+        visible=True,
+        text=f"POC: {poc:.2f}, poc_range_profit%: {profit:.1f}%, tf_cnt: {len(df_range)}",
+    )
+
+    horizontal_lines[poc_line_name] = poc_line
+
+
 def plot_chart(df, symbol: str, name: str, timeframe: str):
     """
     df: DataFrame
     time, open, high, low, close, volume, [buy, sell]可选 buy=1 买入信号, sell=1 卖出信号
 
     """
-    chart = Chart(toolbox=True, inner_height=0.6, maximize=True)
+    chart = Chart(toolbox=True, inner_height=0.8, maximize=True)
 
     chart.topbar.textbox("symbol", symbol)
     chart.topbar.textbox("name", name)
@@ -246,6 +327,7 @@ def plot_chart(df, symbol: str, name: str, timeframe: str):
     )
 
     chart.set(df)
+    chart.events.range_change += on_range_change_poc
     add_ema(df, chart, period=10)
     add_ema(df, chart, period=20)
     add_ema(df, chart, period=30)