from datetime import datetime, timedelta
import struct
import pandas as pd


def read_binary_file(file_path):

    df = pd.DataFrame()

    with open(file_path, "rb") as file:
        index = 0

        # 读取前8个字节，表示数据列数
        column_bytes = file.read(8)
        if not column_bytes:
            return  # 文件结束
        column_count = struct.unpack("<d", column_bytes)[0]
        column_count_int = int(column_count)
        print(f"Column Count: {column_count_int}")

        # 读取接下来的8个字节，表示日期
        date_bytes = file.read(8)
        date_float = struct.unpack("<d", date_bytes)[0]
        date_str = str(int(date_float))
        year = int(date_str[:4])
        month = int(date_str[4:6])
        day = int(date_str[6:8])
        # start_date = datetime(year, month, day)
        # print(f"Date: {datetime(year, month, day)}")

        # 第一个时间戳所有数据
        # time_bytes = file.read(8)
        # time = struct.unpack("<d", time_bytes)[0]
        # print(f"Time: {time}")
        # hours = int(time / 60)
        # first_date = start_date + timedelta(hours=hours)

        # print(f"Minute: {minute}")
        # data_size = column_count_int * 8  # 每个数据点8个字节
        # file.seek(data_size, 1)
        # time1_bytes = file.read(8)
        # time1 = struct.unpack("<d", time1_bytes)[0]
        # print(f"Time: {time1}")
        # file.seek(data_size, 1)
        # time2_bytes = file.read(8)
        # time2 = struct.unpack("<d", time2_bytes)[0]
        # print(f"Time: {time2}")
        # for i in range(column_count_int):
        #     print(i)
        #     if i > 10:
        #         break
        #     data_bytes = file.read(8)
        #     data = struct.unpack("<d", data_bytes)[0]
        #     print(f"Data: {data}")
        while True:
            # print("index", index)
            if index > 25:
                break
            time_bytes = file.read(8)
            time = struct.unpack("<d", time_bytes)[0]
            # print(f"time: {time}")

            # 读取数据矩阵
            data_size = column_count_int * 8  # 每个数据点8个字节
            data_bytes = file.read(data_size)
            data_matrix = struct.unpack(f"<{column_count_int}d", data_bytes)
            data_matrix = [data_matrix]
            new_df = pd.DataFrame(data_matrix)
            df = pd.concat([df, new_df], ignore_index=True)
            # print(f"Data Matrix: {data_matrix}")
            index = index + 1
        print("index", index)
    return df


if __name__ == "__main__":
    # 使用函数读取文件
    file_path = "lz.out/lz.rivqdown.dat"
    df = read_binary_file(file_path)
    print(df.shape)
    print(df.head())