pm4py.algo.discovery.dfg.variants 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.algo.discovery.dfg.variants.case_attributes 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.dfg.variants.case_attributes.Parameters(value)[source]#

Bases: Enum

An enumeration.

ACTIVITY_KEY = 'pm4py:param:activity_key'#
CASE_ATTRIBUTES = 'case_attributes'#
RETURN_NODES_ATTRIBUTES = 'return_nodes_attributes'#
pm4py.algo.discovery.dfg.variants.case_attributes.apply(log: EventLog, parameters: Optional[Dict[Union[str, Parameters], Any]] = None) Union[Tuple[Dict[Tuple[str, str], Dict[str, Dict[str, Any]]], Dict[str, Dict[str, Dict[str, Any]]]], Dict[Tuple[str, str], Dict[str, Dict[str, Any]]]][source]#

Discovers a directly-follows graph from an event log, with the edges that are annotated with the different values for the given case attributes.

Parameters#

log

Event log

parameters

Parameters of the variant, including: - Parameters.ACTIVITY_KEY => the attribute to use as activity - Parameters.CASE_ATTRIBUTES => the case attributes that are used to annotate the edges (default: the case ID) - Parameters.RETURN_NODES_ATTRIBUTES => (optional) returns also a dictionary with the values of the attributes for each activity of the graph (default: False)

Returns#

dfg
Directly-follows graph (with the edges annotated with the specified case attributes), e.g.:
{(‘register request’, ‘examine casually’): {‘creator’: {‘Fluxicon Nitro’: 3}, ‘concept:name’:

{‘3’: 1, ‘6’: 1, ‘5’: 1}} …

nodes
(Optional) dictionary of activities (annotated with the specified case attributes), e.g.:
{‘register request’: {‘creator’: {‘Fluxicon Nitro’: 6}, ‘concept:name’:

{‘3’: 1, ‘2’: 1, ‘1’: 1, ‘6’: 1, ‘5’: 1, ‘4’: 1}} …

pm4py.algo.discovery.dfg.variants.clean 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.dfg.variants.clean.Parameters(value)[source]#

Bases: Enum

An enumeration.

ACTIVITY_KEY = 'pm4py:param:activity_key'#
CASE_ID_KEY = 'pm4py:param:case_id_key'#
TIMESTAMP_KEY = 'pm4py:param:timestamp_key'#
pm4py.algo.discovery.dfg.variants.clean.apply(log: DataFrame, parameters: Optional[Dict[str, Any]] = None) DirectlyFollowsGraph[source]#

pm4py.algo.discovery.dfg.variants.clean_polars module#

pm4py.algo.discovery.dfg.variants.clean_time 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.dfg.variants.clean_time.Parameters(value)[source]#

Bases: Enum

An enumeration.

ACTIVITY_KEY = 'pm4py:param:activity_key'#
CASE_ID_KEY = 'pm4py:param:case_id_key'#
TIMESTAMP_KEY = 'pm4py:param:timestamp_key'#
pm4py.algo.discovery.dfg.variants.clean_time.apply(log: DataFrame, parameters=None)[source]#

pm4py.algo.discovery.dfg.variants.freq_triples 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.dfg.variants.freq_triples.Parameters(value)[source]#

Bases: Enum

An enumeration.

ACTIVITY_KEY = 'pm4py:param:activity_key'#
pm4py.algo.discovery.dfg.variants.freq_triples.apply(log: Union[EventLog, EventStream], parameters: Optional[Dict[Union[str, Parameters], Any]] = None) Dict[Tuple[str, str, str], int][source]#
pm4py.algo.discovery.dfg.variants.freq_triples.freq_triples(log: Union[EventLog, EventStream], parameters: Optional[Dict[Union[str, Parameters], Any]] = None) Dict[Tuple[str, str, str], int][source]#

Counts the number of directly follows occurrences, i.e. of the form <…a,b…>, in an event log.

Parameters#

log

Trace log

parameters
Possible parameters passed to the algorithms:

activity_key -> Attribute to use as activity

Returns#

dfg

DFG graph

pm4py.algo.discovery.dfg.variants.native 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.dfg.variants.native.Parameters(value)[source]#

Bases: Enum

An enumeration.

ACTIVITY_KEY = 'pm4py:param:activity_key'#
WINDOW = 'window'#
KEEP_ONCE_PER_CASE = 'keep_once_per_case'#
pm4py.algo.discovery.dfg.variants.native.apply(log: Union[EventLog, EventStream], parameters: Optional[Dict[Union[str, Parameters], Any]] = None) Dict[Tuple[str, str], int][source]#
pm4py.algo.discovery.dfg.variants.native.native(log: Union[EventLog, EventStream], parameters: Optional[Dict[Union[str, Parameters], Any]] = None) Dict[Tuple[str, str], int][source]#

Counts the number of directly follows occurrences, i.e. of the form <…a,b…>, in an event log.

Parameters#

log

Trace log

parameters
Possible parameters passed to the algorithms:

activity_key -> Attribute to use as activity

Returns#

dfg

DFG graph

pm4py.algo.discovery.dfg.variants.performance 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.dfg.variants.performance.Parameters(value)[source]#

Bases: Enum

An enumeration.

ACTIVITY_KEY = 'pm4py:param:activity_key'#
START_TIMESTAMP_KEY = 'pm4py:param:start_timestamp_key'#
TIMESTAMP_KEY = 'pm4py:param:timestamp_key'#
AGGREGATION_MEASURE = 'aggregationMeasure'#
BUSINESS_HOURS = 'business_hours'#
BUSINESS_HOUR_SLOTS = 'business_hour_slots'#
WORKCALENDAR = 'workcalendar'#
pm4py.algo.discovery.dfg.variants.performance.apply(log: Union[EventLog, EventStream], parameters: Optional[Dict[Union[str, Parameters], Any]] = None) Dict[Tuple[str, str], float][source]#
pm4py.algo.discovery.dfg.variants.performance.performance(log: Union[EventLog, EventStream], parameters: Optional[Dict[Union[str, Parameters], Any]] = None) Dict[Tuple[str, str], float][source]#

Measure performance between couples of attributes in the DFG graph

Parameters#

log

Log

parameters
Possible parameters passed to the algorithms:

aggregationMeasure -> performance aggregation measure (min, max, mean, median) activity_key -> Attribute to use as activity timestamp_key -> Attribute to use as timestamp

  • Parameters.BUSINESS_HOURS => calculates the difference of time based on the business hours, not the total time.

    Default: False

  • Parameters.BUSINESS_HOURS_SLOTS =>

work schedule of the company, provided as a list of tuples where each tuple represents one time slot of business hours. One slot i.e. one tuple consists of one start and one end time given in seconds since week start, e.g. [

(7 * 60 * 60, 17 * 60 * 60), ((24 + 7) * 60 * 60, (24 + 12) * 60 * 60), ((24 + 13) * 60 * 60, (24 + 17) * 60 * 60),

] meaning that business hours are Mondays 07:00 - 17:00 and Tuesdays 07:00 - 12:00 and 13:00 - 17:00

Returns#

dfg

DFG graph