"""
基础功能测试
"""

import sys
import os
import pandas as pd
import numpy as np
from datetime import datetime, timedelta

# 添加项目根目录到路径
sys.path.append(os.path.dirname(os.path.dirname(os.path.abspath(__file__))))

from data.data_processor import DataProcessor
from core.kline import KLine
from core.fractal import Fractal
from core.chan_analyzer import ChanAnalyzer


def create_test_data():
    """创建测试用的K线数据"""
    dates = pd.date_range(start='2024-01-01', periods=100, freq='H')
    
    # 生成模拟价格数据
    np.random.seed(42)
    base_price = 50000
    prices = [base_price]
    
    for i in range(99):
        change = np.random.normal(0, 100)  # 价格变化
        new_price = max(prices[-1] + change, 1000)  # 确保价格为正
        prices.append(new_price)
    
    # 生成OHLCV数据
    data = []
    for i, date in enumerate(dates):
        if i == 0:
            open_price = prices[i]
        else:
            open_price = data[-1]['close']
            
        close_price = prices[i]
        high_price = max(open_price, close_price) + np.random.uniform(0, 50)
        low_price = min(open_price, close_price) - np.random.uniform(0, 50)
        volume = np.random.uniform(1000, 10000)
        
        data.append({
            'open': open_price,
            'high': high_price,
            'low': low_price,
            'close': close_price,
            'volume': volume
        })
    
    df = pd.DataFrame(data, index=dates)
    return df


def test_data_processor():
    """测试数据处理器"""
    print("测试数据处理器...")
    
    # 创建测试数据
    test_data = create_test_data()
    
    # 验证数据
    processor = DataProcessor()
    is_valid = processor.validate_klines(test_data)
    print(f"数据验证结果: {is_valid}")
    
    # 清理数据
    cleaned_data = processor.clean_klines(test_data)
    print(f"清理后数据量: {len(cleaned_data)}")
    
    # 添加技术指标
    data_with_indicators = processor.add_technical_indicators(cleaned_data)
    print(f"技术指标列: {list(data_with_indicators.columns)}")
    
    return cleaned_data


def test_kline_processor():
    """测试K线处理器"""
    print("\n测试K线处理器...")
    
    test_data = create_test_data()
    
    # K线包含关系处理
    kline_processor = KLine(test_data)
    processed_data = kline_processor.get_processed_data()
    
    print(f"原始K线数量: {len(test_data)}")
    print(f"处理后K线数量: {len(processed_data)}")
    
    # 可视化信息
    viz_info = kline_processor.visualize_containment()
    print(f"合并统计: {viz_info}")
    
    return processed_data


def test_fractal_detector():
    """测试分型识别器"""
    print("\n测试分型识别器...")
    
    processed_data = test_kline_processor()
    
    # 分型识别
    fractal_detector = Fractal(processed_data, min_strength=1)
    fractals = fractal_detector.detect_fractals()
    
    print(f"检测到分型数量: {len(fractals)}")
    
    # 分型统计
    stats = fractal_detector.get_fractal_statistics()
    print(f"分型统计: {stats}")
    
    return fractals


def test_chan_analyzer():
    """测试综合分析器"""
    print("\n测试综合分析器...")
    
    test_data = create_test_data()
    
    # 完整分析
    analyzer = ChanAnalyzer(test_data)
    summary = analyzer.run_full_analysis(fractal_strength=1)
    
    print("分析结果摘要:")
    for key, value in summary.items():
        print(f"  {key}: {value}")
    
    # 获取最新信号
    latest_signals = analyzer.get_latest_signals(24)
    print(f"\n最新信号数量: {len(latest_signals)}")
    
    # 市场结构
    market_structure = analyzer.get_current_market_structure()
    print(f"当前市场结构: {market_structure}")
    
    return analyzer


def run_all_tests():
    """运行所有测试"""
    print("=" * 50)
    print("缠论分析系统基础功能测试")
    print("=" * 50)
    
    try:
        # 测试各个模块
        test_data_processor()
        test_kline_processor()
        test_fractal_detector()
        analyzer = test_chan_analyzer()
        
        print("\n" + "=" * 50)
        print("所有测试完成！")
        print("=" * 50)
        
        return True
        
    except Exception as e:
        print(f"\n测试失败: {e}")
        import traceback
        traceback.print_exc()
        return False


if __name__ == "__main__":
    success = run_all_tests()
    sys.exit(0 if success else 1)