The behvaioral.data_classes.PostparsedDataset class has a _calc_giant_component method. This method builds the semantic network for the dataset, and returns the giant component ("GC"; its largest connected component).
In case the semantic network has no edges, the procedure for getting its largest CC fails with a ValueError.
Instead, it should return a default value.
If currently the GC is of type tuple (verify), then an empty tuple may be an appropriate default value.
Whatever default value is chosen, it's important to also implement in FeatureExtractor that when the default GC is received, GC-based features turn to None. If a numeric value is outputted for those features, users may not notice that GC creation has failed.
The
behvaioral.data_classes.PostparsedDatasetclass has a_calc_giant_componentmethod. This method builds the semantic network for the dataset, and returns the giant component ("GC"; its largest connected component).In case the semantic network has no edges, the procedure for getting its largest CC fails with a
ValueError.Instead, it should return a default value.
If currently the GC is of type
tuple(verify), then an empty tuple may be an appropriate default value.Whatever default value is chosen, it's important to also implement in
FeatureExtractorthat when the default GC is received, GC-based features turn toNone. If a numeric value is outputted for those features, users may not notice that GC creation has failed.