pm4py.algo.discovery.ocel.link_analysis.variants package

Submodules

pm4py.algo.discovery.ocel.link_analysis.variants.classic 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.discovery.ocel.link_analysis.variants.classic.Parameters

Bases: enum.Enum

An enumeration.

INDEX_COLUMN = 'index_column'

IN_COLUMN = 'in_column'

KEEP_FIRST_OCCURRENCE = 'keep_first_occurrence'

LOOK_FORWARD = 'look_forward'

OUT_COLUMN = 'out_column'

PROPAGATE = 'propagate'

SORTING_COLUMN = 'sorting_column'

pm4py.algo.discovery.ocel.link_analysis.variants.classic.apply(dataframe: pandas.core.frame.DataFrame, parameters: Optional[Dict[Any, Any]] = None) → pandas.core.frame.DataFrame

Performs a link analysis between the entries of the current dataframe. The link analysis permits advanced filtering based on events connected in an output-input relation (e.g., the OUT column of the first is equal to the IN column of the second).

When OUT_COLUMN = IN_COLUMN = CASE ID, it can be equivalent to the directly-follows graph (when Parameters.KEEP_FIRST_OCCURRENCE = True), and to the eventually-follows graph (when Parameters.KEEP_FIRST_OCCURRENCE = False).

Parameters:

• dataframe – Pandas dataframe
• parameters – Parameters of the algorithm, including: - Parameters.OUT_COLUMN => the output column of the dataframe - Parameters.IN_COLUMN => the input column of the dataframe - Parameters.SORTING_COLUMN => the column on top of which the - Parameters.INDEX_COLUMN => the attribute to use for the indexing - Parameters.LOOK_FORWARD => filters the relations in which the second event has an index >= than the index of the first event. - Parameters.KEEP_FIRST_OCCURRENCE => keep, for every source event, only the first-occurring relationship with a target event (OUT=IN). - Parameters.PROPAGATE => propagate the relationships between events, in such a way that the entire document flow chain can be reconstructed.

Returns:

Link analysis dataframe

Return type:

link_analysis_dataframe

pm4py.algo.discovery.ocel.link_analysis.variants.classic.propagate_associations(associations: Dict[str, Set[str]]) → Dict[str, Set[str]]

Propagate the associations, such that the eventually-follows flow between the events of the event log is considered

Parameters:associations – Associations between events Returns:Propagated associations Return type:propagated_associations

Module contents

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/>.