Commit 287210d3 authored by Anna Warno's avatar Anna Warno
Browse files

time 0 corrected

parent edcb8ea9
...@@ -96,11 +96,10 @@ def main(): ...@@ -96,11 +96,10 @@ def main():
tl = Timeloop() tl = Timeloop()
time_0 = msg["epoch_start"]
dataset_preprocessor.prepare_csv() dataset_preprocessor.prepare_csv()
for metric in predicted_metrics: for metric in predicted_metrics:
predictions = None predictions = None
global time_0
time_0 = time_0 + prediction_cycle * 1000 time_0 = time_0 + prediction_cycle * 1000
for i in range(number_of_forward_predictions[metric]): for i in range(number_of_forward_predictions[metric]):
prediction_msgs, prediction = predict( prediction_msgs, prediction = predict(
...@@ -165,6 +164,7 @@ if __name__ == "__main__": ...@@ -165,6 +164,7 @@ if __name__ == "__main__":
} }
for m in msg["all_metrics"] for m in msg["all_metrics"]
} }
time_0 = msg["epoch_start"]
prediction_horizon = msg["prediction_horizon"] * 1000 prediction_horizon = msg["prediction_horizon"] * 1000
predicted_metrics = set(msg["metrics"]) predicted_metrics = set(msg["metrics"])
prediction_cycle = msg["prediction_horizon"] prediction_cycle = msg["prediction_horizon"]
......
...@@ -96,11 +96,10 @@ def main(): ...@@ -96,11 +96,10 @@ def main():
tl = Timeloop() tl = Timeloop()
time_0 = msg["epoch_start"]
dataset_preprocessor.prepare_csv() dataset_preprocessor.prepare_csv()
for metric in predicted_metrics: for metric in predicted_metrics:
predictions = None predictions = None
global time_0
time_0 = time_0 + prediction_cycle * 1000 time_0 = time_0 + prediction_cycle * 1000
for i in range(number_of_forward_predictions[metric]): for i in range(number_of_forward_predictions[metric]):
prediction_msgs, prediction = predict( prediction_msgs, prediction = predict(
...@@ -165,6 +164,7 @@ if __name__ == "__main__": ...@@ -165,6 +164,7 @@ if __name__ == "__main__":
} }
for m in msg["all_metrics"] for m in msg["all_metrics"]
} }
time_0 = msg["epoch_start"]
prediction_horizon = msg["prediction_horizon"] * 1000 prediction_horizon = msg["prediction_horizon"] * 1000
predicted_metrics = set(msg["metrics"]) predicted_metrics = set(msg["metrics"])
prediction_cycle = msg["prediction_horizon"] prediction_cycle = msg["prediction_horizon"]
......
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