03250932

models_processing/model_tf/bp.yaml

@@ -36,7 +36,6 @@ full_field: true
 history_hours: 1
 new_field: true
 features:
-- time
 - temperature10
 - temperature190
 - direction160

models_processing/model_tf/cnn.yaml

@@ -36,7 +36,6 @@ full_field: true
 history_hours: 1
 new_field: true
 features:
-- time
 - temperature10
 - temperature190
 - direction160

models_processing/model_tf/test.py

@@ -0,0 +1,23 @@
+#!/usr/bin/env python
+# -*- coding:utf-8 -*-
+# @FileName  :test.py
+# @Time      :2025/3/25 09:16
+# @Author    :David
+# @Company: shenyang JY
+
+{"features": ["temperature190", "temperature10", "direction160", "direction40", "temperature110",
+              "speed60", "direction80", "mcc", "temperature150", "speed20", "speed110",
+              "globalr", "solarZenith", "speed190", "direction120", "direction200",
+              "temperature90", "speed150", "temperature50", "direction30",
+              "temperature160", "direction170", "temperature20",
+              "direction70", "direction130", "temperature200", "speed70", "temperature120",
+              "speed30", "speed100", "speed80", "speed180", "dniCalcd", "speed140",
+              "temperature60", "temperature170", "temperature30", "direction20",
+              "humidity2", "direction180", "direction60", "direction140", "hcc", "speed40",
+              "clearskyGhi", "temperature130", "lcc", "speed90", "tcc", "temperature2",
+              "speed170", "direction100", "temperature70", "speed130", "direction190", "temperature40",
+              "direction10", "temperature180", "direction150", "direction50", "speed50", "direction90",
+              "temperature100", "speed10", "temperature140", "speed120", "speed200", "radiation", "tpr",
+              "surfacePressure", "direction110", "speed160", "temperature80"]}
+if __name__ == "__main__":
+    run_code = 0

models_processing/model_tf/tf_bp_train.py

@@ -57,7 +57,7 @@ def model_training_bp():
         model = bp.train_init() if bp.opt.Model['add_train'] else bp.get_keras_model(bp.opt)
         if bp.opt.Model['add_train']:
             if model:
-                feas = json.loads(bp.model_params).get('features', args['features'])
+                feas = json.loads(bp.model_params).get('features', dh.opt.features)
                 if set(feas).issubset(set(dh.opt.features)):
                     dh.opt.features = list(feas)
                     train_x, train_y, valid_x, valid_y, scaled_train_bytes, scaled_target_bytes, scaled_cap = dh.train_data_handler(train_data)

models_processing/model_tf/tf_cnn_train.py

@@ -59,7 +59,7 @@ def model_training_bp():
         model = cnn.train_init() if cnn.opt.Model['add_train'] else cnn.get_keras_model(cnn.opt)
         if cnn.opt.Model['add_train']:
             if model:
-                feas = json.loads(cnn.model_params).get('features', args['features'])
+                feas = json.loads(cnn.model_params).get('features', dh.opt.features)
                 if set(feas).issubset(set(dh.opt.features)):
                     dh.opt.features = list(feas)
                     train_x, train_y, valid_x, valid_y, scaled_train_bytes, scaled_target_bytes, scaled_cap = dh.train_data_handler(train_data)

models_processing/model_tf/tf_lstm_train.py

@@ -56,7 +56,7 @@ def model_training_bp():
         model = ts.train_init() if ts.opt.Model['add_train'] else ts.get_keras_model(ts.opt)
         if ts.opt.Model['add_train']:
             if model:
-                feas = json.loads(ts.model_params).get('features', args['features'])
+                feas = json.loads(ts.model_params).get('features', dh.opt.features)
                 if set(feas).issubset(set(dh.opt.features)):
                     dh.opt.features = list(feas)
                     train_x, train_y, valid_x, valid_y, scaled_train_bytes, scaled_target_bytes, scaled_cap = dh.train_data_handler(train_data)

models_processing/model_tf/tf_test_train.py

@@ -56,7 +56,7 @@ def model_training_test():
         model = ts.train_init() if ts.opt.Model['add_train'] else ts.get_keras_model(ts.opt)
         if ts.opt.Model['add_train']:
             if model:
-                feas = json.loads(ts.model_params).get('features', args['features'])
+                feas = json.loads(ts.model_params).get('features', dh.opt.features)
                 if set(feas).issubset(set(dh.opt.features)):
                     dh.opt.features = list(feas)
                     train_x, train_y, valid_x, valid_y, scaled_train_bytes, scaled_target_bytes, scaled_cap = dh.train_data_handler(