feat:添加测试脚本

ad/model_predict_analyse.py

@@ -85,7 +85,7 @@ def segment_calc_diff_rate_by_score(df: pd.DataFrame, segment_file_path: str, st
 
     # 完整的分段文件保存
     csv_data = group_df.to_csv(sep="\t", index=False)
-    with client.write(segment_file_path, encoding='utf-8') as writer:
+    with client.write(segment_file_path, encoding='utf-8', overwrite=True) as writer:
         writer.write(csv_data)
 
     filtered_df = group_df[(abs(group_df['segment_diff_rate']) >= 0.2) & (group_df['segment_label_cnt'] >= 1000)]
@@ -110,7 +110,7 @@ def read_and_calibration_predict(predict_path: str, step=100) -> [pd.DataFrame,
     predict_basename = os.path.basename(predict_path)
     if predict_basename.endswith("/"):
         predict_basename = predict_basename[:-1]
-    df, segment_df = segment_calc_diff_rate_by_score(df, segment_file_path=f"{SEGMENT_BASE_PATH}/{predict_basename}", step=100)
+    df, segment_df = segment_calc_diff_rate_by_score(df, segment_file_path=f"{SEGMENT_BASE_PATH}/{predict_basename}.txt", step=100)
 
     # 生成校准后的分数
     df['score_2'] = df['score'] / (1 + df['segment_diff_rate'])