auviewer.patternset module
Class and related functionality for pattern sets.
- class auviewer.patternset.PatternSet(projparent, dbmodel)[source]
Bases:
objectRepresents a pattern set.
- addPatterns(df, validate=True)[source]
Add patterns to the pattern set. By default, the rows will be validated (e.g. for matching file ID & filename). This may be skipped in the case of extremely high volume, but it may lead to database integrity issues to do so.
During validation, if filename is present and file_id is not, then file_id will be populated according to the filename. If both are populated, then the file_id will be validated to match the filename. The provided pattern set must contain ‘file_id’ and/or ‘filename’ columns as well as [‘series’, ‘left’, ‘right’, ‘label’]. :return: None
- assignToUsers(user_ids)[source]
Assign the pattern set to user(s). Idempotent. :param user_ids: May be single user ID or list of user IDs. :return: None
- Parameters:
user_ids (int | List[int])
- Return type:
None
- delete(deletePatterns=False)[source]
Deletes the pattern set from the database and the parent project instance. If the pattern set has patterns, the deletion will fail, unless the deletePatterns flag is True, in which case it will first delete the child patterns.
- deletePatterns()[source]
Delete the patterns belonging to this pattern set. :return: number of deleted patterns
- Return type:
int
- deleteUnannotatedPatterns()[source]
Delete all patterns which have not yet been annotated from the set. :return: number of deleted patterns
- Return type:
int
- getAnnotationCount()[source]
Returns a count of annotations which annotate any pattern in this set.
- Return type:
int
- getAnnotations()[source]
Returns a DataFrame of the annotations in this set.
- Return type:
DataFrame
- refresh()[source]
Refresh model & update the count of patterns belonging to this set (this is normally an internally-used method).