pm4py.algo.label_splitting 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/>.

Subpackages#

Submodules#

pm4py.algo.label_splitting.algorithm 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.algo.label_splitting.algorithm.Variants(value)[source]#

Bases: Enum

An enumeration.

CONTEXTUAL = <module 'pm4py.algo.label_splitting.variants.contextual' from 'C:\\Users\\berti\\pm4py-core\\pm4py\\algo\\label_splitting\\variants\\contextual.py'>#
pm4py.algo.label_splitting.algorithm.apply(log: Union[EventLog, EventStream, DataFrame], variant=Variants.CONTEXTUAL, parameters: Optional[Dict[Any, Any]] = None) DataFrame[source]#

Applies a technique of label-splitting, to distinguish between different meanings of the same activity. The result is a Pandas dataframe where the label-splitting has been applied.

Minimum Viable Example:

import pm4py from pm4py.algo.label_splitting import algorithm as label_splitter

log = pm4py.read_xes(“tests/input_data/receipt.xes”) log2 = label_splitter.apply(log)

Parameters#

log

Event log

parameters

Variant-specific parameters

Returns#

dataframe

Pandas dataframe with the re-labeling