pm4py.statistics.overlap.interval_events.log package#

This file is part of PM4Py (More Info: https://pm4py.fit.fraunhofer.de).

PM4Py is free software: you can redistribute it and/or modify it under the terms of the GNU General Public License as published by the Free Software Foundation, either version 3 of the License, or (at your option) any later version.

PM4Py is distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License for more details.

You should have received a copy of the GNU General Public License along with PM4Py. If not, see <https://www.gnu.org/licenses/>.

Submodules#

pm4py.statistics.overlap.interval_events.log.get module#

This file is part of PM4Py (More Info: https://pm4py.fit.fraunhofer.de).

PM4Py is free software: you can redistribute it and/or modify it under the terms of the GNU General Public License as published by the Free Software Foundation, either version 3 of the License, or (at your option) any later version.

PM4Py is distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License for more details.

You should have received a copy of the GNU General Public License along with PM4Py. If not, see <https://www.gnu.org/licenses/>.

class pm4py.statistics.overlap.interval_events.log.get.Parameters(value)[source]#

Bases: Enum

An enumeration.

START_TIMESTAMP_KEY = 'pm4py:param:start_timestamp_key'#
TIMESTAMP_KEY = 'pm4py:param:timestamp_key'#
pm4py.statistics.overlap.interval_events.log.get.apply(log: Union[EventLog, EventStream], parameters: Optional[Dict[Union[str, Parameters], Any]] = None) List[int][source]#

Counts the intersections of each interval event with the other interval events of the log (all the events are considered, not looking at the activity)

Parameters#

log

Event log

parameters

Parameters of the algorithm, including: - Parameters.START_TIMESTAMP_KEY => the attribute to consider as start timestamp - Parameters.TIMESTAMP_KEY => the attribute to consider as timestamp

Returns#

overlap

For each interval event, ordered by the order of appearance in the log, associates the number of intersecting events.