459 lines
20 KiB
Python
459 lines
20 KiB
Python
from core.db.db_huge_volume_data import DBHugeVolumeData
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from core.utils import timestamp_to_datetime, transform_date_time_to_timestamp
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import matplotlib.pyplot as plt
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import seaborn as sns
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from openpyxl import Workbook
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from openpyxl.drawing.image import Image
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from PIL import Image as PILImage
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import core.logger as logging
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from datetime import datetime, timezone, timedelta
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from core.utils import get_current_date_time
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import pandas as pd
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import os
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import re
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import openpyxl
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from openpyxl.styles import Font
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logger = logging.logger
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sns.set_theme(style="whitegrid")
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# 设置中文
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plt.rcParams["font.sans-serif"] = ["SimHei"]
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plt.rcParams["axes.unicode_minus"] = False
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class HugeVolumeChart:
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def __init__(
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self,
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data: pd.DataFrame,
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output_folder: str = "./output/huge_volume_statistics/",
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):
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"""
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初始化
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data: 数据
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data中的列名为：
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symbol: 币种
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bar: 周期
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window_size: 窗口大小
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huge_volume: 是否巨量
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volume_ratio_percentile_10: 10%分位数
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volume_ratio_percentile_10_mean: 10%分位数平均值
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price_type: 价格类型
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next_period: 下一个周期
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average_return: 平均回报
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max_return: 最大回报
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min_return: 最小回报
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rise_count: 上涨次数
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rise_ratio: 上涨比例
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fall_count: 下跌次数
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fall_ratio: 下跌比例
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draw_count: 持平次数
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draw_ratio: 持平比例
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total_count: 总次数
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output_folder: 输出文件夹
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"""
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self.data = data
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# remove 1D bar
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self.data = self.data[self.data["bar"] != "1D"]
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self.data.reset_index(drop=True, inplace=True)
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self.output_folder = output_folder
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os.makedirs(self.output_folder, exist_ok=True)
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self.temp_dir = os.path.join(self.output_folder, "temp")
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os.makedirs(self.temp_dir, exist_ok=True)
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self.symbol_list = self.data["symbol"].unique().tolist()
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# sort symbol_list
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self.symbol_list.sort()
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self.bar_list = self.data["bar"].unique().tolist()
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self.bar_list.sort()
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self.window_size_list = self.data["window_size"].unique().tolist()
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self.window_size_list.sort()
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self.next_period_list = self.data["next_period"].unique().tolist()
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self.next_period_list.sort()
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self.volume_ratio_percentile_10_list = (
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self.data["volume_ratio_percentile_10"].unique().tolist()
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)
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self.volume_ratio_percentile_10_list.sort()
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self.price_type_list = self.data["price_type"].unique().tolist()
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self.price_type_list.sort()
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def plot_entrance(self, include_heatmap: bool = True, include_line: bool = True):
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"""
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绘制上涨下跌图入口
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"""
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charts_dict = {}
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if include_heatmap:
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heatmap_plot_dict = self.plot_heatmap_entrance()
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if include_line:
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line_plot_dict = self.plot_line_chart_entrance()
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if include_line:
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charts_dict.update(line_plot_dict)
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if include_heatmap:
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charts_dict.update(heatmap_plot_dict)
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return charts_dict
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def plot_line_chart_entrance(self):
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"""
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绘制折线图入口
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"""
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charts_dict = {}
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# 根据price_type_list，得到各个price_type的平均rise_ratio，平均fall_ratio，平均draw_ratio, 平均average_return
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total_chart_path = self.plot_pice_rise_fall(data=self.data, prefix="总体")
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charts_dict["总体"] = {"总体": total_chart_path}
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self.plot_window_size_rise_fall(charts_dict=charts_dict)
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self.plot_window_size_bar_rise_fall(charts_dict=charts_dict)
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self.plot_window_size_bar_next_period_rise_fall(charts_dict=charts_dict)
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self.plot_symbol_rise_fall(charts_dict=charts_dict)
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self.plot_symbol_bar_rise_fall(charts_dict=charts_dict)
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self.plot_symbol_bar_window_size_rise_fall(charts_dict=charts_dict)
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self.plot_symbol_bar_window_size_next_period_rise_fall(charts_dict=charts_dict)
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# self.plot_symbol_bar_window_size_volume_ratio_percentile_10_mean_rise_fall(charts_dict=charts_dict)
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# self.plot_symbol_bar_window_size_volume_ratio_percentile_10_mean_next_period_rise_fall(charts_dict=charts_dict)
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self.output_excel(chart_type="line_chart", charts_dict=charts_dict)
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return charts_dict
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def plot_heatmap_entrance(self):
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"""
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绘制热力图入口
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"""
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charts_dict = {}
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self.plot_symbol_heatmap(charts_dict=charts_dict, ratio_column="rise_ratio", title=f"Rise Ratio Heatmap by Window Size and Bar")
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self.plot_symbol_heatmap(charts_dict=charts_dict, ratio_column="fall_ratio", title=f"Fall Ratio Heatmap by Window Size and Bar")
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self.plot_symbol_heatmap(charts_dict=charts_dict, ratio_column="average_return", title=f"Average Return Heatmap by Window Size and Bar")
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self.output_excel(chart_type="heatmap_chart", charts_dict=charts_dict)
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return charts_dict
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def plot_symbol_heatmap(self,
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charts_dict: dict,
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ratio_column: str = "rise_ratio",
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title: str = "Rise Ratio Heatmap by Window Size and Bar"
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):
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"""
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绘制symbol热力图
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"""
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for symbol in self.symbol_list:
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charts_dict[f"{symbol}_{ratio_column}_heatmap"] = {}
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for price_type in self.price_type_list:
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logger.info(f"绘制{symbol} {price_type} {ratio_column}热力图")
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df = self.data[(self.data["symbol"] == symbol) & (self.data["price_type"] == price_type)]
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pivot_table = df.pivot_table(values=ratio_column, index='window_size', columns='bar', aggfunc='mean')
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plt.figure(figsize=(10, 6))
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# 热力图以红色渐变为主,红色表示高，绿色表示低
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sns.heatmap(pivot_table, annot=True, cmap='RdYlGn_r', fmt='.3f')
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plt.xlabel('Period')
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plt.ylabel('Window Size')
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plt.title(f"{title} {price_type}")
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# plt.show()
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chart_path = os.path.join(self.temp_dir, f'{symbol}_{price_type}_{ratio_column}_heatmap.png')
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plt.savefig(chart_path, bbox_inches='tight', dpi=100)
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plt.close()
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charts_dict[f"{symbol}_{ratio_column}_heatmap"][f"{symbol}_{price_type}_{ratio_column}_heatmap"] = chart_path
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def plot_window_size_rise_fall(self, charts_dict: dict):
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"""
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不区分symbol, 绘制window_size上涨下跌图
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"""
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charts_dict["window_size"] = {}
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for window_size in self.window_size_list:
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data = self.data[self.data["window_size"] == window_size]
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chart_path = self.plot_pice_rise_fall(data, prefix=f"window_size_{window_size}")
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charts_dict["window_size"][f"window_size_{window_size}"] = chart_path
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def plot_window_size_bar_rise_fall(self, charts_dict: dict):
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"""
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不区分symbol, 根据window_size绘制bar上涨下跌图
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"""
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charts_dict["window_size_bar"] = {}
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for window_size in self.window_size_list:
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for bar in self.bar_list:
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data = self.data[
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(self.data["window_size"] == window_size)
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& (self.data["bar"] == bar)
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]
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chart_path = self.plot_pice_rise_fall(
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data, prefix=f"window_size_{window_size}_bar_{bar}"
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)
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charts_dict["window_size_bar"][f"window_size_{window_size}_bar_{bar}"] = chart_path
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def plot_window_size_bar_next_period_rise_fall(self, charts_dict: dict):
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"""
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不区分symbol, 根据window_size, bar, next_period上涨下跌图
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"""
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charts_dict["window_size_bar_period"] = {}
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for window_size in self.window_size_list:
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for bar in self.bar_list:
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for next_period in self.next_period_list:
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data = self.data[
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(self.data["window_size"] == window_size)
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& (self.data["bar"] == bar)
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& (self.data["next_period"] == next_period)
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]
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chart_path = self.plot_pice_rise_fall(
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data,
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prefix=f"window_size_{window_size}_bar_{bar}_next_period_{next_period}"
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)
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charts_dict["window_size_bar_period"][f"window_size_{window_size}_bar_{bar}_next_period_{next_period}"] = chart_path
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def plot_symbol_rise_fall(self, charts_dict: dict):
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"""
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区分symbol, 绘制symbol上涨下跌图
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"""
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for symbol in self.symbol_list:
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charts_dict[f"{symbol}_总体"] = {}
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data = self.data[self.data["symbol"] == symbol]
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chart_path = self.plot_pice_rise_fall(data, prefix=symbol)
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charts_dict[f"{symbol}_总体"][symbol] = chart_path
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def plot_symbol_bar_rise_fall(self, charts_dict: dict):
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"""
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区分symbol, bar, 绘制symbol上涨下跌图
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"""
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for symbol in self.symbol_list:
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charts_dict[f"{symbol}_bar"] = {}
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for bar in self.bar_list:
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data = self.data[
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(self.data["symbol"] == symbol) & (self.data["bar"] == bar)
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]
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chart_path = self.plot_pice_rise_fall(data, prefix=f"{symbol}_{bar}")
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charts_dict[f"{symbol}_bar"][f"{symbol}_{bar}"] = chart_path
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def plot_symbol_bar_window_size_rise_fall(self, charts_dict: dict):
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"""
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区分symbol, bar, window_size, 绘制symbol上涨下跌图
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"""
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for symbol in self.symbol_list:
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charts_dict[f"{symbol}_bar_window_size"] = {}
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for bar in self.bar_list:
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for window_size in self.window_size_list:
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data = self.data[
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(self.data["symbol"] == symbol)
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& (self.data["bar"] == bar)
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& (self.data["window_size"] == window_size)
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]
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chart_path = self.plot_pice_rise_fall(
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data, prefix=f"{symbol}_{bar}_ws_{window_size}"
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)
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charts_dict[f"{symbol}_bar_window_size"][f"{symbol}_{bar}_ws_{window_size}"] = chart_path
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def plot_symbol_bar_window_size_next_period_rise_fall(self, charts_dict: dict):
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"""
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区分symbol, bar, window_size, next_period, 绘制symbol上涨下跌图
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"""
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for symbol in self.symbol_list:
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charts_dict[f"{symbol}_bar_ws_period"] = {}
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for bar in self.bar_list:
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for window_size in self.window_size_list:
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for next_period in self.next_period_list:
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data = self.data[
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(self.data["symbol"] == symbol)
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& (self.data["bar"] == bar)
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& (self.data["window_size"] == window_size)
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& (self.data["next_period"] == next_period)
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]
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chart_path = self.plot_pice_rise_fall(
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data,
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prefix=f"{symbol}_{bar}_ws_{window_size}_next_period_{next_period}"
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)
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charts_dict[f"{symbol}_bar_ws_period"][f"{symbol}_{bar}_ws_{window_size}_next_period_{next_period}"] = chart_path
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def plot_symbol_bar_window_size_volume_ratio_percentile_10_mean_rise_fall(self, charts_dict: dict):
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"""
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区分symbol, bar, window_size, volume_ratio_percentile_10_mean, 绘制symbol上涨下跌图
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"""
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for symbol in self.symbol_list:
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charts_dict[f"{symbol}_bar_window_size_vol_per"] = {}
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for bar in self.bar_list:
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for window_size in self.window_size_list:
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for (
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volume_ratio_percentile_10
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) in self.volume_ratio_percentile_10_list:
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data = self.data[
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(self.data["symbol"] == symbol)
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& (self.data["bar"] == bar)
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& (self.data["window_size"] == window_size)
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& (
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self.data["volume_ratio_percentile_10"]
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== volume_ratio_percentile_10
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)
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]
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chart_path = self.plot_pice_rise_fall(
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data,
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prefix=f"{symbol}_{bar}_ws_{window_size}_vol_per_{volume_ratio_percentile_10}"
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)
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charts_dict[f"{symbol}_bar_window_size_vol_per"][f"{symbol}_{bar}_ws_{window_size}_vol_per_{volume_ratio_percentile_10}"] = chart_path
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def plot_symbol_bar_window_size_volume_ratio_percentile_10_mean_next_period_rise_fall(
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self,
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charts_dict: dict,
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):
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"""
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区分symbol, bar, window_size, volume_ratio_percentile_10_mean, next_period, 绘制symbol上涨下跌图
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"""
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for symbol in self.symbol_list:
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charts_dict[f"{symbol}_bar_ws_vol_period"] = {}
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for bar in self.bar_list:
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for window_size in self.window_size_list:
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for (
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volume_ratio_percentile_10
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) in self.volume_ratio_percentile_10_list:
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for next_period in self.next_period_list:
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data = self.data[
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(self.data["symbol"] == symbol)
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& (self.data["bar"] == bar)
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& (self.data["window_size"] == window_size)
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& (
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self.data["volume_ratio_percentile_10"]
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== volume_ratio_percentile_10
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)
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& (self.data["next_period"] == next_period)
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]
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chart_path = self.plot_pice_rise_fall(
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data,
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prefix=f"{symbol}_{bar}_ws_{window_size}_vol_per_{volume_ratio_percentile_10}_next_period_{next_period}"
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)
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charts_dict[f"{symbol}_bar_ws_vol_period"][f"{symbol}_{bar}_ws_{window_size}_vol_per_{volume_ratio_percentile_10}_next_period_{next_period}"] = chart_path
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def plot_pice_rise_fall(self, data: pd.DataFrame, prefix: str = ""):
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"""
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绘制价格上涨下跌图
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"""
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logger.info(f"绘制价格上涨下跌图: {prefix}")
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# 根据price_type_list，得到各个price_type的平均rise_ratio，平均fall_ratio，平均draw_ratio, 平均average_return
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price_type_data_dict = {}
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for price_type in self.price_type_list:
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filtered_data = data[data["price_type"] == price_type]
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average_rise_ratio = filtered_data["rise_ratio"].mean()
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average_fall_ratio = filtered_data["fall_ratio"].mean()
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average_draw_ratio = filtered_data["draw_ratio"].mean()
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average_average_return = filtered_data["average_return"].mean()
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price_type_data_dict[price_type] = {
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"average_rise_ratio": average_rise_ratio,
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"average_fall_ratio": average_fall_ratio,
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"average_draw_ratio": average_draw_ratio,
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"average_average_return": average_average_return,
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}
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# 准备数据用于绘图
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price_types = list(price_type_data_dict.keys())
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rise_ratios = [
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price_type_data_dict[pt]["average_rise_ratio"] for pt in price_types
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]
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fall_ratios = [
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price_type_data_dict[pt]["average_fall_ratio"] for pt in price_types
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]
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draw_ratios = [
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price_type_data_dict[pt]["average_draw_ratio"] for pt in price_types
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]
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avg_returns = [
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price_type_data_dict[pt]["average_average_return"] for pt in price_types
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]
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# 创建子图，保持2x2布局
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fig, ((ax1, ax2), (ax3, ax4)) = plt.subplots(2, 2, figsize=(15, 12))
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# 绘制上涨比例
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bars1 = ax1.bar(price_types, rise_ratios, color="green", alpha=0.7)
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ax1.set_title(f"{prefix}总体平均上涨比例")
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ax1.set_ylabel("上涨比例")
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ax1.tick_params(axis="x", rotation=0)
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ax1.bar_label(bars1, fmt="%.2f")
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# 绘制下跌比例
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bars2 = ax2.bar(price_types, fall_ratios, color="red", alpha=0.7)
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ax2.set_title(f"{prefix}平均下跌比例")
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ax2.set_ylabel("下跌比例")
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ax2.tick_params(axis="x", rotation=0)
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ax2.bar_label(bars2, fmt="%.2f")
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# 绘制持平比例
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bars3 = ax3.bar(price_types, draw_ratios, color="gray", alpha=0.7)
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ax3.set_title(f"{prefix}平均持平比例")
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ax3.set_ylabel("持平比例")
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ax3.tick_params(axis="x", rotation=0)
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ax3.bar_label(bars3, fmt="%.2f")
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# 绘制平均回报
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bars4 = ax4.bar(price_types, avg_returns, color="blue", alpha=0.7)
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ax4.set_title(f"{prefix}平均回报")
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ax4.set_ylabel("平均回报")
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ax4.tick_params(axis="x", rotation=0)
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ax4.bar_label(bars4, fmt="%.2f")
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# 调整布局，增加底部空间和垂直间距以显示完整的x轴标签
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plt.tight_layout()
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plt.subplots_adjust(bottom=0.15, hspace=0.4)
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# plt.show()
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chart_path = os.path.join(self.temp_dir, f'{prefix}.png')
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plt.savefig(chart_path, bbox_inches='tight', dpi=100)
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plt.close()
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return chart_path
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def output_excel(self, chart_type: str, charts_dict: dict):
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"""
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输出Excel文件，包含所有图表
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charts_dict: 图表数据字典，格式为：
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{
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"sheet_name": {
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"chart_name": "chart_path"
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}
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}
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"""
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logger.info(f"输出Excel文件，包含所有{chart_type}图表")
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file_name = f"huge_volume_{chart_type}_{get_current_date_time()}.xlsx"
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file_path = os.path.join(self.output_folder, file_name)
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# Create Excel file and worksheet
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wb = Workbook()
|
||
wb.remove(wb.active) # Remove default sheet
|
||
|
||
for sheet_name, chart_data_dict in charts_dict.items():
|
||
try:
|
||
ws = wb.create_sheet(title=sheet_name)
|
||
row_offset = 1
|
||
for chart_name, chart_path in chart_data_dict.items():
|
||
# Load image to get dimensions
|
||
with PILImage.open(chart_path) as img:
|
||
width_px, height_px = img.size
|
||
|
||
# Convert pixel height to Excel row height (approximate: 1 point = 1.333 pixels, 1 row ≈ 15 points for 20 pixels)
|
||
pixels_per_point = 1.333
|
||
points_per_row = 15 # Default row height in points
|
||
pixels_per_row = (
|
||
points_per_row * pixels_per_point
|
||
) # ≈ 20 pixels per row
|
||
chart_rows = max(
|
||
10, int(height_px / pixels_per_row)
|
||
) # Minimum 10 rows for small charts
|
||
|
||
# Add chart title
|
||
# 支持中文标题
|
||
ws[f"A{row_offset}"] = chart_name.encode("utf-8").decode("utf-8")
|
||
ws[f"A{row_offset}"].font = openpyxl.styles.Font(bold=True, size=12)
|
||
row_offset += 2 # Add 2 rows for title and spacing
|
||
|
||
# Insert chart image
|
||
img = Image(chart_path)
|
||
ws.add_image(img, f"A{row_offset}")
|
||
|
||
# Update row offset (chart height + padding)
|
||
row_offset += chart_rows + 5 # Add 5 rows for padding between charts
|
||
except Exception as e:
|
||
logger.error(f"输出Excel Sheet {sheet_name} 失败: {e}")
|
||
continue
|
||
|
||
# Save Excel file
|
||
wb.save(file_path)
|
||
print(f"Excel file saved as {file_path}")
|
||
|
||
for sheet_name, chart_data_dict in charts_dict.items():
|
||
for chart_name, chart_path in chart_data_dict.items():
|
||
try:
|
||
os.remove(chart_path)
|
||
except Exception as e:
|
||
logger.error(f"删除临时文件失败: {e}")
|