import pandas as pd

from global_var import global_var_init
cycle, fs_ecg, fs_ppg, record_name, record_name_csv = global_var_init()


def find_large_values(excel_file, threshold=0.6):  # 调整阈值
    # 读取Excel文件中的所有sheet
    df = pd.read_excel(excel_file, sheet_name=None)
    
    # 存储结果的列表
    results = []
    
    # 遍历每一个sheet
    for sheet_name, data in df.items():
        # 获取每一个单元格的行列位置和数据
        for row_idx in range(data.shape[0]):
            for col_idx in range(data.shape[1]):
                value = data.iat[row_idx, col_idx]
                # 检查是否大于阈值
                if isinstance(value, (int, float)) and value > threshold:
                    cell_location = (sheet_name, row_idx + 2, col_idx + 1)  # Excel行列从1开始计数
                    results.append(cell_location)
    
    return results

def append_to_file(results, output_file):
    with open(output_file, 'a') as f:
        f.write("")
        for result in results:
            f.write(f'Sheet: {result[0]}, Row: {result[1]}, Column: {result[2]}\n')
        f.write("########################\n")

def main():

    excel_file = f"D://python_study//big_boss//doc//output//{record_name}_output.xlsx"  # Excel文件路径
    output_file = f"D://python_study//big_boss//doc//output//processed.txt"  # 输出文件路径
    results = find_large_values(excel_file)

    # 将结果追加到文件
    append_to_file(results, output_file)

if __name__ == "__main__":
    
    main()