awg 更新分析报告

evaluation_processing/analysis.py

@@ -135,6 +135,11 @@ def put_analysis_report_to_html(args, df_predict, df_accuracy):
             agg_dict['deviationAssessment'] = [np.nanmean, np.nansum]
             rename_cols.append('考核分数平均值')
             rename_cols.append('考核总分数')
+        if 'qualificationRate' in df_accuracy.columns:
+            agg_dict['qualificationRate'] = [np.nanmean]
+            rename_cols.append('合格率平均值')
+
+
         # 进行分组聚合，如果有需要聚合的列
         summary_df = df_accuracy.groupby('model').agg(agg_dict).reset_index()
         summary_df.columns = rename_cols
@@ -242,7 +247,7 @@ def put_analysis_report_to_html(args, df_predict, df_accuracy):
     if not os.path.exists(directory):
         os.makedirs(directory)
     file_path = os.path.join(directory, filename)
-    path = f"http://ds3:10010/{filename}"
+    path = f"http://ds1:10010/{filename}"
     # 将 HTML 内容写入文件
     with open(file_path, "w", encoding="utf-8") as f:
         f.write(html_content)

evaluation_processing/analysis_report.py

@@ -318,6 +318,9 @@ def put_analysis_report_to_html(args, df_clean, df_predict, df_accuracy):
             agg_dict['deviationAssessment'] = [np.nanmean, np.nansum]
             rename_cols.append('考核分数平均值')
             rename_cols.append('考核总分数')
+        if 'qualificationRate' in df_accuracy.columns:
+            agg_dict['qualificationRate'] = [np.nanmean]
+            rename_cols.append('合格率平均值')
         # 进行分组聚合，如果有需要聚合的列
         summary_df = df_accuracy.groupby('model').agg(agg_dict).reset_index()
         summary_df.columns = rename_cols
@@ -449,7 +452,7 @@ def put_analysis_report_to_html(args, df_clean, df_predict, df_accuracy):
     if not os.path.exists(directory):
         os.makedirs(directory)
     file_path = os.path.join(directory, filename)
-    path = f"http://ds3:10010/{filename}"
+    path = f"http://ds1:10010/{filename}"
     # 将 HTML 内容写入文件
     with open(file_path, "w", encoding="utf-8") as f:
         f.write(html_content)