聚烯烃日度预测，上传市场信息平台

config_juxiting.py

@@ -241,16 +241,16 @@ table_name = 'v_tbl_crude_oil_warning'
 
 
 # 开关
-is_train = False  # 是否训练
+is_train = True  # 是否训练
 is_debug = False  # 是否调试
-is_eta = False  # 是否使用eta接口
+is_eta = True  # 是否使用eta接口
 is_market = False  # 是否通过市场信息平台获取特征 ,在is_eta 为true 的情况下生效
 is_timefurture = True  # 是否使用时间特征
 is_fivemodels = False  # 是否使用之前保存的最佳的5个模型
 is_edbcode = False  # 特征使用edbcoding列表中的
 is_edbnamelist = False  # 自定义特征，对应上面的edbnamelist
 is_update_eta = True  # 预测结果上传到eta
-is_update_report = False  # 是否上传报告
+is_update_report = True  # 是否上传报告
 is_update_warning_data = False  # 是否上传预警数据
 is_del_corr = 0.6  # 是否删除相关性高的特征,取值为 0-1 ，0 为不删除，0.6 表示删除相关性小于0.6的特征
 is_del_tow_month = True  # 是否删除两个月不更新的特征

main_juxiting.py

@@ -82,6 +82,68 @@ global_config.update({
 })
 
 
+
+
+
+def push_market_value():
+    config.logger.info('发送预测结果到市场信息平台')
+    # 读取预测数据和模型评估数据
+    predict_file_path = os.path.join(config.dataset, 'predict.csv')
+    model_eval_file_path = os.path.join(config.dataset, 'model_evaluation.csv')
+    try:
+        predictdata_df = pd.read_csv(predict_file_path)
+        top_models_df = pd.read_csv(model_eval_file_path)
+    except FileNotFoundError as e:
+        config.logger.error(f"文件未找到: {e}")
+        return
+
+    predictdata = predictdata_df.copy()
+
+    # 取模型前十
+    top_models = top_models_df['模型(Model)'].head(10).tolist()
+    # 去掉FDBformer
+    if 'FEDformer' in top_models:
+        top_models.remove('FEDformer')
+
+    # 计算前十模型的均值
+    predictdata_df['top_models_mean'] = predictdata_df[top_models].mean(axis=1)
+
+    # 打印日期和前十模型均值
+    print(predictdata_df[['ds', 'top_models_mean']])
+
+    # 准备要推送的数据
+    first_mean = predictdata_df['top_models_mean'].iloc[0]
+    last_mean = predictdata_df['top_models_mean'].iloc[-1]
+    # 保留两位小数
+    first_mean = round(first_mean, 2)
+    last_mean = round(last_mean, 2)
+
+    predictdata = [
+        {
+            "dataItemNo": global_config['bdwd_items']['ciri'],
+            "dataDate": global_config['end_time'].replace('-',''),
+            "dataStatus": "add",
+            "dataValue": first_mean
+        },
+        {
+            "dataItemNo": global_config['bdwd_items']['benzhou'],
+            "dataDate": global_config['end_time'].replace('-',''),
+            "dataStatus": "add",
+            "dataValue": last_mean
+        }
+    ]
+
+    print(predictdata)
+
+    # 推送数据到市场信息平台
+    try:
+        push_market_data(predictdata)
+    except Exception as e:
+        config.logger.error(f"推送数据失败: {e}")
+
+
+
+
 def predict_main():
     """
     主预测函数，用于从 ETA 获取数据、处理数据、训练模型并进行预测。
@@ -388,13 +450,15 @@ def predict_main():
 if __name__ == '__main__':
     # global end_time
     # 遍历2024-11-25 到 2024-12-3 之间的工作日日期
-    for i_time in pd.date_range('2025-3-19', '2025-3-29', freq='B'):
-        try:
-            global_config['end_time'] = i_time.strftime('%Y-%m-%d')
-            predict_main()
-        except Exception as e:
-            logger.info(f'预测失败：{e}')
-            continue
+    # for i_time in pd.date_range('2025-3-19', '2025-3-29', freq='B'):
+    #     try:
+    #         global_config['end_time'] = i_time.strftime('%Y-%m-%d')
+    #         predict_main()
+    #     except Exception as e:
+    #         logger.info(f'预测失败：{e}')
+    #         continue
 
     # predict_main()
+    
+    push_market_value()