etf/rotation/experiment_select_num.py

#!/usr/bin/env python3
"""
select_num A/B 实验：对比 Top-1 / Top-2 / Top-3 的表现

用法:
    python rotation/experiment_select_num.py
"""

import os
import sys
import yaml
import json
import tempfile
import numpy as np
import pandas as pd
from pathlib import Path
from datetime import datetime

PROJECT_ROOT = Path(__file__).parent.parent
sys.path.insert(0, str(PROJECT_ROOT))

from rotation.simple_rotation import SimpleRotationStrategy


def run_with_select_num(config_path: str, select_num: int, output_dir: Path) -> dict:
    """运行一次策略，覆盖 select_num"""
    print(f"\n{'='*60}")
    print(f"  实验: select_num = {select_num}")
    print(f"{'='*60}\n")

    # 读取原始配置，修改 select_num，写入临时文件
    with open(config_path, 'r', encoding='utf-8') as f:
        cfg = yaml.safe_load(f)
    cfg['rotation']['select_num'] = select_num

    tmp_path = output_dir / f'config_select_{select_num}.yaml'
    with open(tmp_path, 'w', encoding='utf-8') as f:
        yaml.dump(cfg, f, default_flow_style=False, allow_unicode=True)

    strategy = SimpleRotationStrategy(config_path=str(tmp_path))
    result = strategy.run()

    if result:
        # 导出到子目录
        sub_dir = output_dir / f'select_{select_num}'
        sub_dir.mkdir(parents=True, exist_ok=True)
        strategy.export_results(output_dir=str(sub_dir))
        return result.get('metrics', {})
    return {}


def print_comparison(all_metrics: dict):
    """打印对比表格"""
    print(f"\n\n{'='*80}")
    print(f"  select_num 实验对比结果")
    print(f"{'='*80}\n")

    header = f"{'指标':<16}"
    for n in sorted(all_metrics.keys()):
        header += f"{'Top-'+str(n):>12}"
    print(header)
    print("-" * (16 + 12 * len(all_metrics)))

    rows = [
        ('累计收益', 'total_return', '{:.2%}'),
        ('年化收益', 'annual_return', '{:.2%}'),
        ('最大回撤', 'max_drawdown', '{:.2%}'),
        ('夏普比率', 'sharpe_ratio', '{:.2f}'),
        ('Calmar比率', 'calmar_ratio', '{:.2f}'),
        ('日胜率', 'win_rate', '{:.2%}'),
        ('交易日数', 'n_days', '{}'),
        ('调仓次数', 'rebalance_count', '{}'),
    ]

    for label, key, fmt in rows:
        row = f"{label:<16}"
        for n in sorted(all_metrics.keys()):
            val = all_metrics[n].get(key, 0)
            row += f"{fmt.format(val):>12}"
        print(row)

    print(f"\n{'='*80}")


def plot_comparison(all_metrics: dict, output_dir: Path):
    """生成对比图表"""
    import matplotlib
    matplotlib.use("Agg")
    import matplotlib.pyplot as plt

    fig, axes = plt.subplots(1, 3, figsize=(16, 5))
    fig.suptitle("select_num A/B Experiment", fontsize=14, fontweight="bold")

    nums = sorted(all_metrics.keys())
    colors = ['#E74C3C', '#3498DB', '#2ECC71']

    # 1. 收益对比
    ax = axes[0]
    annuals = [all_metrics[n].get('annual_return', 0) for n in nums]
    totals = [all_metrics[n].get('total_return', 0) for n in nums]
    x = np.arange(len(nums))
    w = 0.35
    ax.bar(x - w/2, [a*100 for a in annuals], w, label='Annual %', color='#E74C3C', alpha=0.8)
    ax.bar(x + w/2, [t*100 for t in totals], w, label='Total %', color='#3498DB', alpha=0.8)
    ax.set_xticks(x)
    ax.set_xticklabels([f'Top-{n}' for n in nums])
    ax.set_ylabel('Return (%)')
    ax.set_title('Returns')
    ax.legend()
    ax.grid(True, alpha=0.3)

    # 2. 风险对比
    ax = axes[1]
    dds = [abs(all_metrics[n].get('max_drawdown', 0)) * 100 for n in nums]
    ax.bar(x, dds, color='#E74C3C', alpha=0.7)
    ax.set_xticks(x)
    ax.set_xticklabels([f'Top-{n}' for n in nums])
    ax.set_ylabel('Max Drawdown (%)')
    ax.set_title('Risk')
    ax.grid(True, alpha=0.3)

    # 3. 夏普 & Calmar
    ax = axes[2]
    sharpes = [all_metrics[n].get('sharpe_ratio', 0) for n in nums]
    calmars = [all_metrics[n].get('calmar_ratio', 0) for n in nums]
    ax.bar(x - w/2, sharpes, w, label='Sharpe', color='#2ECC71', alpha=0.8)
    ax.bar(x + w/2, calmars, w, label='Calmar', color='#F39C12', alpha=0.8)
    ax.set_xticks(x)
    ax.set_xticklabels([f'Top-{n}' for n in nums])
    ax.set_ylabel('Ratio')
    ax.set_title('Risk-Adjusted')
    ax.legend()
    ax.grid(True, alpha=0.3)

    plt.tight_layout()
    chart_path = output_dir / 'select_num_comparison.png'
    plt.savefig(str(chart_path), dpi=150, bbox_inches="tight")
    plt.close()
    print(f"\n  + Chart: {chart_path}")


def plot_nav_comparison(output_dir: Path):
    """加载三组 NAV 画在同一张图上"""
    import matplotlib
    matplotlib.use("Agg")
    import matplotlib.pyplot as plt

    fig, ax = plt.subplots(figsize=(14, 6))
    colors = {'1': '#E74C3C', '2': '#3498DB', '3': '#2ECC71'}

    for n in [1, 2, 3]:
        nav_path = output_dir / f'select_{n}' / 'simple_rotation_nav.csv'
        if nav_path.exists():
            df = pd.read_csv(nav_path, parse_dates=['date'])
            ax.plot(df['date'], df['nav'], label=f'Top-{n}', linewidth=1.5, color=colors[str(n)])

    ax.set_title("NAV Curve Comparison (select_num)", fontsize=14, fontweight="bold")
    ax.set_ylabel("NAV")
    ax.set_yscale("log")
    ax.legend(fontsize=11)
    ax.grid(True, alpha=0.3)
    plt.tight_layout()

    nav_chart = output_dir / 'select_num_nav_comparison.png'
    plt.savefig(str(nav_chart), dpi=150, bbox_inches="tight")
    plt.close()
    print(f"  + NAV Chart: {nav_chart}")


if __name__ == "__main__":
    if 'FLASK_API_URL' not in os.environ:
        os.environ['FLASK_API_URL'] = 'https://k3s.tokenpluse.xyz'

    config_path = str(Path(__file__).parent / 'config_simple.yaml')
    output_dir = PROJECT_ROOT / 'results' / 'experiment_select_num'
    output_dir.mkdir(parents=True, exist_ok=True)

    all_metrics = {}
    for n in [1, 2, 3]:
        metrics = run_with_select_num(config_path, n, output_dir)
        if metrics:
            all_metrics[n] = metrics

    if all_metrics:
        print_comparison(all_metrics)
        plot_comparison(all_metrics, output_dir)
        plot_nav_comparison(output_dir)

        # 保存原始指标
        metrics_path = output_dir / 'experiment_metrics.json'
        with open(metrics_path, 'w', encoding='utf-8') as f:
            json.dump({str(k): v for k, v in all_metrics.items()}, f, ensure_ascii=False, indent=2)
        print(f"  + Metrics: {metrics_path}")