Merge branch 'main' of https://gitea.jayhgq.cn/liurui/PriceForecast

config_jingbo.py

@@ -167,12 +167,12 @@ upload_data = {
 
 ### 开关
 is_train = True # 是否训练
-is_debug = True # 是否调试
+is_debug = False # 是否调试
 is_eta = False # 是否使用eta接口
 is_timefurture = True # 是否使用时间特征
-is_fivemodels = True # 是否使用之前保存的最佳的5个模型
-is_edbcode = True # 特征使用edbcoding列表中的
-is_edbnamelist = True # 自定义特征，对应上面的edbnamelist
+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  = False  # 预测结果上传到eta
 is_update_report = False # 是否上传报告
 

main.py

@@ -65,6 +65,7 @@ def predict_main():
     else:
         for row in first_row.itertuples(index=False):
             row_dict = row._asdict()
+            row_dict['ds'] = row_dict['ds'].strftime('%Y-%m-%d %H:%M:%S')
             check_query = sqlitedb.select_data('trueandpredict',where_condition = f"ds = '{row.ds}'")
             if len(check_query) > 0:
                 set_clause = ", ".join([f"{key} = '{value}'" for key, value in row_dict.items()])
@@ -117,25 +118,25 @@ def predict_main():
     row,col = df.shape
     
     now = datetime.datetime.now().strftime('%Y%m%d%H%M%S')
-    # ex_Model(df,
-    #         horizon=horizon,
-    #         input_size=input_size,
-    #         train_steps=train_steps,
-    #         val_check_steps=val_check_steps,
-    #         early_stop_patience_steps=early_stop_patience_steps,
-    #         is_debug=is_debug,
-    #         dataset=dataset,
-    #         is_train=is_train,
-    #         is_fivemodels=is_fivemodels,
-    #         val_size=val_size,
-    #         test_size=test_size,
-    #         settings=settings,
-    #         now=now,
-    #         etadata = etadata,
-    #         modelsindex = modelsindex,
-    #         data = data,
-    #         is_eta=is_eta,
-    #         )
+    ex_Model(df,
+            horizon=horizon,
+            input_size=input_size,
+            train_steps=train_steps,
+            val_check_steps=val_check_steps,
+            early_stop_patience_steps=early_stop_patience_steps,
+            is_debug=is_debug,
+            dataset=dataset,
+            is_train=is_train,
+            is_fivemodels=is_fivemodels,
+            val_size=val_size,
+            test_size=test_size,
+            settings=settings,
+            now=now,
+            etadata = etadata,
+            modelsindex = modelsindex,
+            data = data,
+            is_eta=is_eta,
+            )
 
     # # 模型评估
     model_results3 = model_losss(sqlitedb)