import pandas as pd

# 读取两个csv文件
human_score_df = pd.read_csv('logs/other/human.csv')
machine_score_df = pd.read_csv('logs/other/result_diff_test_score_53.84256314043283.csv')

result_df = pd.DataFrame(columns=['question', 'answer', 'predict_finetune', 'predict_origin', 'acc_finetune', 'human_acc_finetune', 'acc_origin', 'human_acc_origin', 'fluency_finetune', 'human_fluency_finetune', 'diff_score', 'human_diff_score'])
result_df_row_index = 0
for row_index, row in machine_score_df.iterrows():
    acc_finetune_diff = row['acc_finetune'] - human_score_df.loc[row_index, '准确度（微调后']
    acc_origin_diff = row['acc_origin'] - human_score_df.loc[row_index, '准确度（微调前']
    fluency_finetune_diff = row['fluency_finetune'] - human_score_df.loc[row_index, '流畅度（微调后']
    diff_score_diff = row['diff_score'] - human_score_df.loc[row_index, '是否超过原模型']
    print("准确度（微调后）差值：", abs(acc_finetune_diff),end=' ')
    print("准确度（微调前）差值：", abs(acc_origin_diff),end=' ')
    print("流畅度（微调后）差值：", abs(fluency_finetune_diff),end=' ')
    print("是否超过原模型差值：", abs(diff_score_diff))
    if abs(acc_finetune_diff) >= 2:
        result_df.loc[result_df_row_index, 'question'] = machine_score_df.loc[row_index, 'question']
        result_df.loc[result_df_row_index, 'answer'] = machine_score_df.loc[row_index, 'answer']
        result_df.loc[result_df_row_index, 'predict_finetune'] = machine_score_df.loc[row_index, 'predict_finetune']
        result_df.loc[result_df_row_index, 'predict_origin'] = machine_score_df.loc[row_index, 'predict_origin']
        result_df.loc[result_df_row_index, 'acc_finetune'] = machine_score_df.loc[row_index, 'acc_finetune']
        result_df.loc[result_df_row_index, 'human_acc_finetune'] = human_score_df.loc[row_index, '准确度（微调后']
        result_df.loc[result_df_row_index, 'acc_origin'] = machine_score_df.loc[row_index, 'acc_origin']
        result_df.loc[result_df_row_index, 'human_acc_origin'] = human_score_df.loc[row_index, '准确度（微调前']
        result_df.loc[result_df_row_index, 'fluency_finetune'] = machine_score_df.loc[row_index, 'fluency_finetune']
        result_df.loc[result_df_row_index, 'human_fluency_finetune'] = human_score_df.loc[row_index, '流畅度（微调后']
        result_df.loc[result_df_row_index, 'diff_score'] = machine_score_df.loc[row_index, 'diff_score']
        result_df.loc[result_df_row_index, 'human_diff_score'] = human_score_df.loc[row_index, '是否超过原模型']
        result_df_row_index += 1


result_df.to_csv('logs/other/diff.csv', index=False)
# 信息的准确性应当被首要考虑，多余的未知真假的信息不应该带来加分。