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I fetch multiple timeseries data to Pandas DataFrame and validate_data and feed it to Pca_AD. Single threading serial execution worked fine, but with converting to threads to parallel execution on 3 parallel threads I get random result with anomalies-returned and drive to to_event casts TypeError. Plotting data is normal graph pattern and anomaly=anomalies plots normally, but to_events does not "complete". Between different runs different call to_events fails, like first dataset 3 then next run maybe 2 and 3 is ok. Third run could be that dataset 2 works but 1/3 are not.
I've tried also with threads.local() but it does not change anything. Without threading I did not observe this behaviour.
type is same for all
<class 'pandas.core.series.Series'>
When checking the output for logging.error for some reason there is no "freq"-parameter, anomaly data which has freq works well. Also non-working returns time stamps not time ranges.
I fetch multiple timeseries data to Pandas DataFrame and validate_data and feed it to Pca_AD. Single threading serial execution worked fine, but with converting to threads to parallel execution on 3 parallel threads I get random result with anomalies-returned and drive to to_event casts TypeError. Plotting data is normal graph pattern and anomaly=anomalies plots normally, but to_events does not "complete". Between different runs different call to_events fails, like first dataset 3 then next run maybe 2 and 3 is ok. Third run could be that dataset 2 works but 1/3 are not.
I've tried also with threads.local() but it does not change anything. Without threading I did not observe this behaviour.
type is same for all
<class 'pandas.core.series.Series'>
When checking the output for logging.error for some reason there is no "freq"-parameter, anomaly data which has freq works well. Also non-working returns time stamps not time ranges.
Non-working
Working structure.
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