pm4py.objects.dfg.utils package¶

Submodules¶

pm4py.objects.dfg.utils.dfg_alignment 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/>.

pm4py.objects.dfg.utils.dfg_playout 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/>.

pm4py.objects.dfg.utils.dfg_utils 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/>.

pm4py.objects.dfg.utils.dfg_utils.add_to_most_probable_component(comps, act2, ingoing, outgoing)[source]¶

Adds a lost component in parallel cut detection to the most probable component

Parameters:	comps – Connected components act2 – Activity that has been missed ingoing – Map of ingoing attributes outgoing – Map of outgoing attributes
Returns:	Fixed connected components
Return type:	comps

pm4py.objects.dfg.utils.dfg_utils.filter_dfg_on_act(dfg, listact)[source]¶

Filter a DFG graph on a list of attributes (to produce a projected DFG graph)

Parameters:	dfg – Current DFG graph listact – List of attributes to filter on

pm4py.objects.dfg.utils.dfg_utils.get_activities_direction(dfg, activities)[source]¶

Calculate activities direction (in a similar way to Heuristics Miner)

Parameters:	dfg – Directly-follows graph activities – (if provided) activities of the subtree
Returns:	Dictionary that contains for each direction a number that goes from -1 (all ingoing edges) to 1 (all outgoing edges)
Return type:	direction

pm4py.objects.dfg.utils.dfg_utils.get_activities_dirlist(activities_direction)[source]¶

Form an ordered list out of a dictionary that contains for each activity the direction (going from -1 if all ingoing edges, to 1 if all outgoing edges)

Parameters:	activities_direction – Dictionary that contains for each direction a number that goes from -1 (all ingoing edges) to 1 (all outgoing edges)
Returns:	Sorted list of couples of activity plus the direction
Return type:	dirlist

pm4py.objects.dfg.utils.dfg_utils.get_activities_from_dfg(dfg)[source]¶

Get the list of attributes directly from DFG graph

Parameters:	dfg – Directly-Follows graph
Returns:	List of activities that are present in the DFG graph
Return type:	list_activities

pm4py.objects.dfg.utils.dfg_utils.get_activities_self_loop(dfg)[source]¶

Get attributes that are in self-loop in this subtree

Parameters:	dfg – Directly-follows graph
Returns:	Activities of the graph that are in subloop
Return type:	self_loop_act

pm4py.objects.dfg.utils.dfg_utils.get_all_activities_connected_as_input_to_activity(dfg, activity)[source]¶

Gets all the activities that are connected as input to a given activity

Parameters:	dfg – Directly-follows graph activity – Activity
Returns:	All activities connected as input to a given activities
Return type:	all_activities

pm4py.objects.dfg.utils.dfg_utils.get_all_activities_connected_as_output_to_activity(dfg, activity)[source]¶

Gets all the activities that are connected as output to a given activity

Parameters:	dfg – Directly-follows graph activity – Activity
Returns:	All activities connected as output to a given activity
Return type:	all_activities

pm4py.objects.dfg.utils.dfg_utils.get_alphabet(dfg)[source]¶

pm4py.objects.dfg.utils.dfg_utils.get_connected_components(ingoing, outgoing, activities, force_insert_missing_acti=True)[source]¶

Get connected components in the DFG graph

Parameters:	ingoing – Ingoing attributes outgoing – Outgoing attributes activities – Activities to consider force_insert_missing_acti – Force the insertion of a missing activity

pm4py.objects.dfg.utils.dfg_utils.get_dfg_np_matrix(dfg)[source]¶

Gets a Numpy matrix describing the DFG graph, along with a dictionary making correspondence between indexes and activities names

Parameters:	dfg – Directly-Follows graph
Returns:	matrix – Matrix describing the DFG index_corresp – Dictionary making correspondence between indexes and activities names

pm4py.objects.dfg.utils.dfg_utils.get_dfg_sa_ea_act_from_variants(variants, parameters=None)[source]¶

Gets the DFG, the start and end activities, and the activities from the dictionary/set/list of variants in the log

Parameters:

variants – Dictionary/set/list of variants
parameters – Parameters of the algorithm, including: - variants_sep: the delimiter splitting activities in a variant

Returns:

dfg – DFG
list_act – List of different activities
start_activities – Start activities
end_activities – End activities

pm4py.objects.dfg.utils.dfg_utils.get_ingoing_edges(dfg)[source]¶: Get ingoing edges of the provided DFG graph

pm4py.objects.dfg.utils.dfg_utils.get_inputs_of_outside_activities_reached_by_end_activities(initial_dfg, dfg, activities)[source]¶

Get inputs of outside activities going to start activities

Parameters:	initial_dfg – Initial DFG dfg – Directly-follows graph activities – Activities contained in the DFG

pm4py.objects.dfg.utils.dfg_utils.get_max_activity_count(dfg, act)[source]¶

Get maximum count of an ingoing/outgoing edge related to an activity

Parameters:	dfg – Directly-Follows graph act – Activity
Returns:	Maximum count of ingoing/outgoing edges to attributes
Return type:	max_value

pm4py.objects.dfg.utils.dfg_utils.get_outgoing_edges(dfg)[source]¶: Gets outgoing edges of the provided DFG graph

pm4py.objects.dfg.utils.dfg_utils.get_outputs_of_outside_activities_going_to_start_activities(initial_dfg, dfg, activities)[source]¶

Get outputs of outside activities going to start activities

Parameters:	initial_dfg – Initial DFG dfg – Directly-follows graph activities – Activities contained in the DFG

pm4py.objects.dfg.utils.dfg_utils.get_predecessors(dfg, activities_model=None)[source]¶

Gets the predecessors of any node of the DFG graph

Parameters:	dfg – DFG activities_model – Activities of the process model (if None, it is inferred from the process model)
Returns:	Dictionary associating to each node all the ascendants
Return type:	predecessors

pm4py.objects.dfg.utils.dfg_utils.get_successors(dfg, activities_model=None)[source]¶

Gets the successors of any node of the DFG graph

Parameters:	dfg – DFG activities_model – Activities of the process model (if None, it is inferred from the process model)
Returns:	Dictionary associating to each node all the descendants
Return type:	successors

pm4py.objects.dfg.utils.dfg_utils.get_transitive_relations(dfg, alphabet)[source]¶

Parameters:	dfg – directly follows relation (counter describing activity pairs)
Returns:	tuple with two dicts. first argument maps an activit on all other activities that are able to reach the activity (‘transitive pre set’) second argument maps an activity on all other activities that it can reach (transitively) (‘transitive post set’)

pm4py.objects.dfg.utils.dfg_utils.infer_end_activities(dfg)[source]¶

Infer end activities from a Directly-Follows Graph

Parameters:	dfg – Directly-Follows Graph
Returns:	End activities in the log
Return type:	end_activities

pm4py.objects.dfg.utils.dfg_utils.infer_end_activities_from_succ_connections_and_current_dfg(initial_dfg, dfg, activities, include_self=True)[source]¶

Infer the end activities from the previous connections

Parameters:	initial_dfg – Initial DFG dfg – Directly-follows graph activities – List of the activities contained in DFG

pm4py.objects.dfg.utils.dfg_utils.infer_start_activities(dfg)[source]¶

Infer start activities from a Directly-Follows Graph

Parameters:	dfg – Directly-Follows Graph
Returns:	Start activities in the log
Return type:	start_activities

pm4py.objects.dfg.utils.dfg_utils.infer_start_activities_from_prev_connections_and_current_dfg(initial_dfg, dfg, activities, include_self=True)[source]¶

Infer the start activities from the previous connections

Parameters:	initial_dfg – Initial DFG dfg – Directly-follows graph activities – List of the activities contained in DFG

pm4py.objects.dfg.utils.dfg_utils.max_occ_all_activ(dfg)[source]¶: Get maximum ingoing/outgoing sum of values related to attributes in DFG graph

pm4py.objects.dfg.utils.dfg_utils.max_occ_among_specif_activ(dfg, activities)[source]¶: Get maximum ingoing/outgoing sum of values related to attributes in DFG graph (here attributes to consider are specified)

pm4py.objects.dfg.utils.dfg_utils.negate(dfg)[source]¶

Negate relationship in the DFG graph

Parameters:	dfg – Directly-Follows graph
Returns:	Negated Directly-Follows graph (for parallel cut detection)
Return type:	negated_dfg

pm4py.objects.dfg.utils.dfg_utils.sum_activities_count(dfg, activities, enable_halving=True)[source]¶

Gets the sum of specified attributes count inside a DFG

Parameters:	dfg – Directly-Follows graph activities – Activities to sum enable_halving – Halves the sum in specific occurrences
Returns:
Return type:	Sum of start attributes count

pm4py.objects.dfg.utils.dfg_utils.sum_end_activities_count(dfg)[source]¶

Gets the sum of end attributes count inside a DFG

Parameters:	dfg – Directly-Follows graph
Returns:
Return type:	Sum of start attributes count

pm4py.objects.dfg.utils.dfg_utils.sum_ingoutg_val_activ(dictio, activity)[source]¶

Gets the sum of ingoing/outgoing values of an activity

Parameters:	dictio – Dictionary activity – Current examined activity
Returns:
Return type:	summ

pm4py.objects.dfg.utils.dfg_utils.sum_start_activities_count(dfg)[source]¶

Gets the sum of start attributes count inside a DFG

Parameters:	dfg – Directly-Follows graph
Returns:
Return type:	Sum of start attributes count

pm4py.objects.dfg.utils.dfg_utils.transform_dfg_to_directed_nx_graph(dfg, activities=None)[source]¶

Transform DFG to directed NetworkX graph

Returns:	G – NetworkX digraph nodes_map – Correspondence between digraph nodes and activities

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/>.