v1.9.1

Version 1.9.1 (March 4, 2025)

Bug Fixes / Improvements:

Filling in missing time periods for detectors with zero actuations didn't work for incremental processing, this has been fixed by tracking a list of known detectors between each run, similar to the unmatched event tracking. So how it works is you provide a dataframe or file path of known detectors, it will filter out detectors last seen more than n days ago, and then will fill in missing time periods with zeros for the remaining detectors.

known_detectors_df='path/to/known_detectors.csv'
# or supply Pandas DataFrame directly

from src.atspm import SignalDataProcessor, sample_data

# Set up all parameters
params = {
    # Global Settings
    'raw_data': sample_data.data,
    'bin_size': 15, 
# Performance Measures
'aggregations': [
    {'name': 'actuations', 'params': {
            'fill_in_missing': True,
            'known_detectors_df_or_path': known_detectors_df,
            'known_detectors_max_days_old': 2
    }}
]
}

After you run the processor, here's how to query the known detectors table:

processor = SignalDataProcessor(**params)
processor.load()
processor.aggregate()
# get all table names from the database
known_detectors_df = processor.conn.query("SELECT * FROM known_detectors;").df()

Here's what the known detectors table could look like:

DeviceId	Detector	LastSeen
1	1	2025-03-04 00:00:00
1	2	2025-03-04 00:00:00
2	1	2025-03-04 00:00:00