import numpy as np
import pandas as pd
from blindbox_analysis import blindbox_config, print_tree, profit_statistic

def generate_random_data(blindbox_name: str, num_records: int):
    """
    生成随机盲盒数据
    """
    np.random.seed(42)  # 固定随机种子，确保结果可复现

    dataset = []
    for i in range(num_records):
        # 随机生成用户ID和用户名
        uid = np.random.randint(1000, 2000)
        username = f'user_{uid}'

        blindbox_info = blindbox_config[blindbox_name]
        pity_info = blindbox_info.get('pity', None)

        # 抽选盲盒物品
        rand_num = np.random.rand()
        sum_prob = 0
        selected_item = None
        for item, item_info in blindbox_info['items'].items():
            prob = item_info['probability'] / 100
            if rand_num > sum_prob and rand_num <= sum_prob + prob:
                selected_item = (item, item_info)
                break
            sum_prob += prob

        if selected_item is None:
            raise ValueError("未能选中任何物品")

        # 构建随机数据记录
        dataset.append({
            'uid': uid,
            'username': username,
            'blindbox_name': blindbox_name,
            'blindbox_price': blindbox_info['price'],
            'item_name': selected_item[0],
            'item_price': selected_item[1]['price'],
            'profit': selected_item[1]['price'] - blindbox_info['price'],
            'time': pd.Timestamp.now()
        })

        if pity_info:
            # 模拟保底机制
            if (i + 1) % pity_info['threshold'] == 0:
                dataset.append({
                    'uid': uid,
                    'username': username,
                    'blindbox_name': blindbox_name,
                    'blindbox_price': blindbox_info['price'],
                    'item_name': pity_info['item_name'],
                    'item_price': pity_info['price'],
                    'profit': pity_info['price'] - blindbox_info['price'],
                    'time': pd.Timestamp.now()
                })

    return pd.DataFrame(dataset)

if __name__ == "__main__":
    # 生成随机数据
    stats = {}
    for box_name in blindbox_config.keys():
        df = generate_random_data(box_name, 10000)
        stats[box_name] = profit_statistic(df)

    print_tree(stats)