测试脚本优化

bin/test.py

@@ -44,9 +44,16 @@ def load_test_data():
     return old_users, test_orders
 
 
+def _sd(n1, n2):
+    if n2 == 0:
+        return 0
+    else:
+        return n1 / n2
+
+
 def evaluation(result_detail):
 
-    top_n_list = [1, 3, 5, 10, 20, 50, 100]
+    top_n_list = [1, 3, 5, 10, 20, 50]
     metrics = {
         'all_test_cnt': 0,
         'all_recall_cnt': 0,
@@ -97,28 +104,23 @@ def evaluation(result_detail):
             if rd['is_recall']:
                 metrics['new_user_recall_cnt'] += 1
 
-
-    logger.info('==' * 20 + ' 测试结果 ' + '==' * 20)
-    logger.info('')
-    logger.info('相关参数配置: 相似用户数(k) %s ；每个相似用户召回咨询师数(top_n) %s', args.k, args.top_n)
-
     logger.info('--' * 45)
     logger.info('')
     logger.info('{:<13}{:<7}{:<7}{:<7}'.format('', '样本数', '召回数', '召回率'))
-    logger.info('{:<10}{:<10}{:<10}{:<10.2%}'.format('整体\u3000', metrics['all_test_cnt'], metrics['all_recall_cnt'], metrics['all_recall_cnt'] / metrics['all_test_cnt']))
-    logger.info('{:<10}{:<10}{:<10}{:<10.2%}'.format('老用户', metrics['old_user_test_cnt'], metrics['old_user_recall_cnt'], metrics['old_user_recall_cnt'] / metrics['old_user_test_cnt']))
-    logger.info('{:<10}{:<10}{:<10}{:<10.2%}'.format('新用户', metrics['new_user_test_cnt'], metrics['new_user_recall_cnt'], metrics['new_user_recall_cnt'] / metrics['new_user_test_cnt']))
+    logger.info('{:<10}{:<10}{:<10}{:<10.2%}'.format('整体\u3000', metrics['all_test_cnt'], metrics['all_recall_cnt'], _sd(metrics['all_recall_cnt'], metrics['all_test_cnt'])))
+    logger.info('{:<10}{:<10}{:<10}{:<10.2%}'.format('老用户', metrics['old_user_test_cnt'], metrics['old_user_recall_cnt'], _sd(metrics['old_user_recall_cnt'], metrics['old_user_test_cnt'])))
+    logger.info('{:<10}{:<10}{:<10}{:<10.2%}'.format('新用户', metrics['new_user_test_cnt'], metrics['new_user_recall_cnt'], _sd(metrics['new_user_recall_cnt'], metrics['new_user_test_cnt'])))
     
     logger.info('--' * 45)
     logger.info('')
-    logger.info('用户自己召回数 {:<4} 占总召回比例 {:.2%}'.format(metrics['same_user_recall_cnt'], metrics['same_user_recall_cnt'] / metrics['all_recall_cnt']))
-    logger.info('相似用户召回数 {:<4} 占总召回比例 {:.2%}'.format(metrics['similar_user_recall_cnt'], metrics['similar_user_recall_cnt'] / metrics['all_recall_cnt']))
-    logger.info('兜底用户召回数 {:<4} 占总召回比例 {:.2%}'.format(metrics['default_recall_cnt'], metrics['default_recall_cnt'] / metrics['all_recall_cnt']))
+    logger.info('用户自己召回数 {:<4} 占总召回比例 {:.2%}'.format(metrics['same_user_recall_cnt'], _sd(metrics['same_user_recall_cnt'], metrics['all_recall_cnt'])))
+    logger.info('相似用户召回数 {:<4} 占总召回比例 {:.2%}'.format(metrics['similar_user_recall_cnt'], _sd(metrics['similar_user_recall_cnt'], metrics['all_recall_cnt'])))
+    logger.info('兜底用户召回数 {:<4} 占总召回比例 {:.2%}'.format(metrics['default_recall_cnt'], _sd(metrics['default_recall_cnt'], metrics['all_recall_cnt'])))
 
     logger.info('--' * 45)
     logger.info('')
     for i, n in enumerate(top_n_list):
-        logger.info('top {:<2} 的召回数 {:<4} 召回率 {:.2%}'.format(n, metrics['top_n_recall_cnt'][i], metrics['top_n_recall_cnt'][i] / metrics['all_test_cnt']))
+        logger.info('top {:<2} 的召回数 {:<4} 召回率 {:.2%}'.format(n, metrics['top_n_recall_cnt'][i], _sd(metrics['top_n_recall_cnt'][i], metrics['all_test_cnt'])))
 
 
 def do_test(args):
@@ -159,10 +161,23 @@ def do_test(args):
             'recall_counselors': recommend_result,
             'is_recall': len(recall_resons) > 0,
             'recall_reason': '|'.join(recall_resons),
+            'update_time': order_info['update_time'],
         })
-    logger.info('测试结束')
+    logger.info('测试数据推荐完成')
 
     # 测试结果统计
+    logger.info('==' * 20 + ' 测试结果 ' + '==' * 20)
+    logger.info('')
+    logger.info('相关参数配置: 相似用户数(k) %s ；每个相似用户召回咨询师数(top_n) %s', args.k, args.top_n)
+
+    if args.show_result_by_day:
+        days = set(map(lambda x: x['update_time'], result_detail))
+        for d in sorted(days):
+            logger.info('')
+            logger.info('**' * 15 + ' 订单日期 ' + d + '**' * 15)
+
+            evaluation(filter(lambda x: x['update_time'] == d, result_detail))
+    else:
         evaluation(result_detail)
 
     if args.save_test_result:
@@ -179,6 +194,9 @@ def update_test_data(args):
     elif re.match(r'-\d+', args.start_date):
         now = datetime.now()
         start_date = (now - timedelta(days=int(args.start_date[1:]))).strftime('%Y-%m-%d')
+    elif args.start_date == '0':
+        now = datetime.now()
+        start_date = now.strftime('%Y-%m-%d')
     else:
         logger.error('args.start_date 参数格式错误，%s', args.start_date)
         raise
@@ -207,6 +225,7 @@ if __name__ == '__main__':
     parser.add_argument('--top_n', default=5, type=int, help='每个相似用户召回的咨询师数量')
     parser.add_argument('--max_test', default=0, type=int, help='最多测试数据量')
     parser.add_argument('--save_test_result', default=False, action='store_true', help='保存测试详情结果')
+    parser.add_argument('--show_result_by_day', default=False, action='store_true', help='测试结果是否按天展示')
     
     parser.add_argument('--do_update_test_data', default=False, action='store_true', help='是否更新测试数据')
     parser.add_argument('--start_date', default='-1', type=str, help='测试订单创建的开始时间，可以是"%Y-%m-%d"格式，也可以是 -3 表示前3天')