03211552

models_processing/model_tf/async_query_task.py

@@ -62,18 +62,6 @@ def get_progress(task_id):
     return jsonify(progress)
 
 
-@app.route('/training_progress/')
-def get_progress(task_id):
-    """查询训练进度接口"""
-    with progress_lock:
-        progress = training_progress.get(task_id, {
-            'status': 'not_found',
-            'progress': 0,
-            'message': '任务不存在'
-        })
-
-    return jsonify(progress)
-
 def async_training_task(task_id):
     """异步训练任务"""
     args = {}  # 根据实际情况获取参数

models_processing/model_tf/tf_bp_pre.py

@@ -52,6 +52,9 @@ def model_prediction_bp():
     try:
         # ------------ 获取数据，预处理预测数据------------
         pre_data = get_data_from_mongo(args)
+        if args.get('algorithm_test', 0):
+            field_mapping = {'clearsky_ghi': 'clearskyGhi', 'dni_calcd': 'dniCalcd','surface_pressure': 'surfacePressure'}
+            pre_data = pre_data.rename(columns=field_mapping)
         feature_scaler, target_scaler = get_scaler_model_from_mongo(args)
         bp.opt.cap = round(target_scaler.transform(np.array([[float(args['cap'])]]))[0, 0], 2)
         # ------------ 获取模型，预测结果------------

models_processing/model_tf/tf_cnn_pre.py

@@ -52,6 +52,9 @@ def model_prediction_bp():
     print("Program starts execution!")
     try:
         pre_data = get_data_from_mongo(args)
+        if args.get('algorithm_test', 0):
+            field_mapping = {'clearsky_ghi': 'clearskyGhi', 'dni_calcd': 'dniCalcd','surface_pressure': 'surfacePressure'}
+            pre_data = pre_data.rename(columns=field_mapping)
         feature_scaler, target_scaler = get_scaler_model_from_mongo(args)
         cnn.opt.cap = round(target_scaler.transform(np.array([[float(args['cap'])]]))[0, 0], 2)
 

models_processing/model_tf/tf_lstm_pre.py

@@ -52,6 +52,9 @@ def model_prediction_bp():
     print("Program starts execution!")
     try:
         pre_data = get_data_from_mongo(args)
+        if args.get('algorithm_test', 0):
+            field_mapping = {'clearsky_ghi': 'clearskyGhi', 'dni_calcd': 'dniCalcd','surface_pressure': 'surfacePressure'}
+            pre_data = pre_data.rename(columns=field_mapping)
         feature_scaler, target_scaler = get_scaler_model_from_mongo(args)
         ts.opt.cap = round(target_scaler.transform(np.array([[float(args['cap'])]]))[0, 0], 2)
         ts.get_model(args)

models_processing/model_tf/tf_test_pre.py

@@ -52,6 +52,9 @@ def model_prediction_test():
     print("Program starts execution!")
     try:
         pre_data = get_data_from_mongo(args)
+        if args.get('algorithm_test', 0):
+            field_mapping = {'clearsky_ghi': 'clearskyGhi', 'dni_calcd': 'dniCalcd','surface_pressure': 'surfacePressure'}
+            pre_data = pre_data.rename(columns=field_mapping)
         feature_scaler, target_scaler = get_scaler_model_from_mongo(args)
         ts.opt.cap = round(target_scaler.transform(np.array([[float(args['cap'])]]))[0, 0], 2)