epoch 0 time corrected

deployment/nbeats/predict.py

@@ -127,6 +127,7 @@ def main():
         dataset_preprocessor.prepare_csv()
         for metric in predicted_metrics:
             predictions = None
+            global time_0
             time_0 = time_0 + prediction_cycle * 1000
             for i in range(number_of_forward_predictions[metric]):
                 prediction_msgs, prediction = predict(

deployment/tft/main.py

@@ -89,14 +89,14 @@ def main():
     )
 
     # msg1 = Msg()
-    # msg1.body = '[{"metric": "cpu_usage", "level": 3, "publish_rate": 6000}]'
+    # msg1.body = '[{"metric": "cpu_usage", "level": 3, "publish_rate": 60000}]'
     # msg2 = Msg()
     # msg2.body = """{
     #     "metrics": ["cpu_usage"],
     #     "timestamp": 0,
     #     "epoch_start": 0,
     #     "number_of_forward_predictions": 8,
-    #     "prediction_horizon": 12000}"""
+    #     "prediction_horizon": 600}"""
 
     # StartListener(start_conn.conn, START_APP_TOPIC).on_message(msg1)
     # StartForecastingListener(start_conn.conn, START_APP_TOPIC).on_message(msg2)

deployment/tft/predict.py

@@ -127,6 +127,7 @@ def main():
         dataset_preprocessor.prepare_csv()
         for metric in predicted_metrics:
             predictions = None
+            global time_0
             time_0 = time_0 + prediction_cycle * 1000
             for i in range(number_of_forward_predictions[metric]):
                 prediction_msgs, prediction = predict(