pm4py.objects.petri_net.utils package¶

Submodules¶

pm4py.objects.petri_net.utils.align_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/>.

class pm4py.objects.petri_net.utils.align_utils.DijkstraSearchTuple(g, m, p, t, l)[source]¶: Bases: object

class pm4py.objects.petri_net.utils.align_utils.DijkstraSearchTupleForAntiAndMulti(g, m, r)[source]¶: Bases: object

class pm4py.objects.petri_net.utils.align_utils.SearchTuple(f, g, h, m, p, t, x, trust)[source]¶: Bases: object

class pm4py.objects.petri_net.utils.align_utils.TweakedSearchTuple(f, g, h, m, p, t, x, trust, virgin)[source]¶: Bases: object

pm4py.objects.petri_net.utils.align_utils.add_markings(curr, add)[source]¶

pm4py.objects.petri_net.utils.align_utils.construct_standard_cost_function(synchronous_product_net, skip)[source]¶: Returns the standard cost function, which is: * event moves: cost 1000 * model moves: cost 1000 * tau moves: cost 1 * sync moves: cost 0 :param synchronous_product_net: :param skip: :return:

pm4py.objects.petri_net.utils.align_utils.discountedEditDistance(s1, s2, exponent=2, modeled=True)[source]¶: Fast implementation of the discounted distance Inspired from the faster version of the edit distance

pm4py.objects.petri_net.utils.align_utils.get_visible_transitions_eventually_enabled_by_marking(net, marking)[source]¶

Get visible transitions eventually enabled by marking (passing possibly through hidden transitions) :Parameters: * net – Petri net

marking – Current marking

pm4py.objects.petri_net.utils.align_utils.levenshtein(seq1, seq2)[source]¶: Edit distance without substitution

pm4py.objects.petri_net.utils.align_utils.pretty_print_alignments(alignments)[source]¶

Takes an alignment and prints it to the console, e.g.:: A | B | C | D |

A | B | C | >> |

Parameters:	alignment – <class ‘list’>
Returns:	Nothing

pm4py.objects.petri_net.utils.align_utils.search_path_among_sol(sync_net: pm4py.objects.petri_net.obj.PetriNet, ini: pm4py.objects.petri_net.obj.Marking, fin: pm4py.objects.petri_net.obj.Marking, activated_transitions: List[pm4py.objects.petri_net.obj.PetriNet.Transition], skip='>>') → Tuple[List[pm4py.objects.petri_net.obj.PetriNet.Transition], bool, int][source]¶

(Efficient method) Searches a firing sequence among the X vector that is the solution of the (extended) marking equation

Parameters:

sync_net – Synchronous product net
ini – Initial marking of the net
fin – Final marking of the net
activated_transitions – Transitions that have non-zero occurrences in the X vector
skip – Skip transition

Returns:

firing_sequence – Firing sequence
reach_fm – Boolean value that tells if the final marking is reached by the firing sequence
explained_events – Number of explained events

pm4py.objects.petri_net.utils.check_soundness 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.petri_net.utils.check_soundness.check_easy_soundness_net_in_fin_marking(net, ini, fin)[source]¶

Checks the easy soundness of a Petri net having the initial and the final marking

Parameters:	net – Petri net ini – Initial marking fin – Final marking
Returns:	Boolean value
Return type:	boolean

pm4py.objects.petri_net.utils.check_soundness.check_easy_soundness_of_wfnet(net)[source]¶

Checks the easy soundness of a workflow net

Parameters:	net – Petri net
Returns:	Boolean value
Return type:	boolean

pm4py.objects.petri_net.utils.check_soundness.check_sink_place_presence(net)[source]¶

Check if there is a unique sink place with empty connections

Parameters:	net – Petri net
Returns:	Unique source place (or None otherwise)
Return type:	place

pm4py.objects.petri_net.utils.check_soundness.check_source_and_sink_reachability(net, unique_source, unique_sink)[source]¶

Checks reachability of the source and the sink place from all simulation nodes (places/transitions) of the Petri net

Parameters:	net – Petri net unique_source – Unique source place of the Petri net unique_sink – Unique sink place of the Petri net
Returns:	Boolean value that is true if each node is in a path from the source place to the sink place
Return type:	boolean

pm4py.objects.petri_net.utils.check_soundness.check_source_place_presence(net)[source]¶

Check if there is a unique source place with empty connections

Parameters:	net – Petri net
Returns:	Unique source place (or None otherwise)
Return type:	place

pm4py.objects.petri_net.utils.check_soundness.check_source_sink_place_conditions(net)[source]¶

Check some conditions on the source/sink place important for a sound workflow net

Parameters:	net – Petri net
Returns:	Boolean value (True is good)
Return type:	boolean

pm4py.objects.petri_net.utils.check_soundness.check_wfnet(net)[source]¶

Check if the Petri net is a workflow net

Parameters:	net – Petri net
Returns:	Boolean value that is true when the Petri net is a workflow net
Return type:	boolean

pm4py.objects.petri_net.utils.consumption_matrix 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.objects.petri_net.utils.consumption_matrix.ConsumptionMatrix(net: pm4py.objects.petri_net.obj.PetriNet)[source]¶

Bases: object

c_matrix¶

Gets the Numpy representation of the consumption matrix

Returns:	C matrix
Return type:	C

places¶

Gets the places in the order in which they have been inserted in the consumption matrix

Returns:	Dictionary associating to each place an incremental number
Return type:	place_indices

transitions¶

Gets the transitions in the order in which they have been inserted in the consumption matrix

Returns:	Dictionary associating to each transition an incremental number
Return type:	trans_indices

pm4py.objects.petri_net.utils.consumption_matrix.construct(net: pm4py.objects.petri_net.obj.PetriNet) → pm4py.objects.petri_net.utils.consumption_matrix.ConsumptionMatrix[source]¶

Construct a consumption matrix given a Petri net

Parameters:	net – Petri net
Returns:	Consumption matrix object
Return type:	cons_mat

pm4py.objects.petri_net.utils.decomposition 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.petri_net.utils.decomposition.decompose(net, im, fm)[source]¶

pm4py.objects.petri_net.utils.decomposition.get_graph_components(places, inv_trans, trans_dup_label, tmap)[source]¶

pm4py.objects.petri_net.utils.decomposition.merge_comp(comp1, comp2)[source]¶

pm4py.objects.petri_net.utils.decomposition.merge_sublist_nets(list_nets)[source]¶

pm4py.objects.petri_net.utils.embed_stochastic_map 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.petri_net.utils.embed_stochastic_map.apply(smap, parameters=None)[source]¶

Embed the stochastic map into the Petri net

Parameters:	smap – Stochastic map parameters – Possible parameters of the algorithm
Returns:
Return type:	void

pm4py.objects.petri_net.utils.embed_stochastic_map.extract(net, parameters=None)[source]¶

Extract the stochastic map from the Petri net

Parameters:	net – Petri net parameters – Possible parameters of the algorithm
Returns:
Return type:	void

pm4py.objects.petri_net.utils.explore_path 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.petri_net.utils.final_marking 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.petri_net.utils.final_marking.discover_final_marking(petri)[source]¶

Discovers final marking from a Petri net

Parameters:	petri – Petri net
Returns:	Final marking
Return type:	final_marking

pm4py.objects.petri_net.utils.incidence_matrix 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.objects.petri_net.utils.incidence_matrix.IncidenceMatrix(net)[source]¶

Bases: object

a_matrix¶

encode_marking(marking)[source]¶

places¶

transitions¶

pm4py.objects.petri_net.utils.incidence_matrix.construct(net)[source]¶

pm4py.objects.petri_net.utils.initial_marking 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.petri_net.utils.initial_marking.discover_initial_marking(petri)[source]¶

Discovers initial marking from a Petri net

Parameters:	petri – Petri net
Returns:	Initial marking of the Petri net
Return type:	initial_marking

pm4py.objects.petri_net.utils.networkx_graph 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.petri_net.utils.networkx_graph.create_networkx_directed_graph(net, weight=None)[source]¶

Create a NetworkX directed graph from a Petri net

Parameters:	net – Petri net
Returns:	graph – NetworkX digraph inv_dictionary – Correspondence between NetworkX nodes and Petri net entities

pm4py.objects.petri_net.utils.networkx_graph.create_networkx_directed_graph_ret_dict_both_ways(net, weight=None)[source]¶

Create a NetworkX directed graph from a Petri net

Parameters:	net – Petri net
Returns:	graph – NetworkX digraph dictionary – dict mapping Petri net nodes to NetworkX nodes inv_dictionary – dict mapping NetworkX nodes to Petri net nodes

pm4py.objects.petri_net.utils.networkx_graph.create_networkx_undirected_graph(net, unique_source, unique_sink)[source]¶

Create a NetworkX undirected graph from a Petri net, returning also correspondences for the unique source and the unique sink places that were discovered

Parameters:

net – Petri net
unique_source – Unique source place
unique_sink – Unique sink place

Returns:

graph – NetworkX graph
unique_source_corr – Correspondence in the NetworkX graph of the unique source place
unique_sink_corr – Correspondence in the NetworkX graph of the unique sink place
inv_dictionary – Correspondence between NetworkX nodes and Petri net entities

pm4py.objects.petri_net.utils.performance_map 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.petri_net.utils.performance_map.aggregate_statistics(statistics, measure='frequency', aggregation_measure=None, stat_locale: dict = {})[source]¶

Gets aggregated statistics

Parameters:	statistics – Individual element statistics (including unaggregated performances) measure – Desidered view on data (frequency or performance) aggregation_measure – Aggregation measure (e.g. mean, min) to use stat_locale – Dict to locale the stat strings
Returns:	Aggregated statistics for arcs, transitions, places
Return type:	aggregated_statistics

pm4py.objects.petri_net.utils.performance_map.aggregate_stats(statistics, elem, aggregation_measure)[source]¶

Aggregate the statistics

Parameters:	statistics – Element statistics elem – Current element aggregation_measure – Aggregation measure (e.g. mean, min) to use
Returns:	Aggregated statistics
Return type:	aggr_stat

pm4py.objects.petri_net.utils.performance_map.calculate_annotation_for_trace(trace, net, initial_marking, act_trans, activity_key, ht_perf_method='last')[source]¶

Calculate annotation for a trace in the variant, in order to retrieve information useful for calculate frequency/performance for all the traces belonging to the variant

Parameters:	trace – Trace net – Petri net initial_marking – Initial marking act_trans – Activated transitions during token replay of the given trace activity_key – Attribute that identifies the activity (must be specified if different from concept:name) ht_perf_method – Method to use in order to annotate hidden transitions (performance value could be put on the last possible point (last) or in the first possible point (first)
Returns:	Statistics annotation for the given trace
Return type:	annotation

pm4py.objects.petri_net.utils.performance_map.filter_cases_exceeding_specified_acti_performance(log, transition_performance, activity, lower_bound)[source]¶

Filter cases exceeding the specified activity performance threshold

Parameters:	log – Event log transition_performance – Dictionary where each transition label is associated to performance measures activity – Target activity (of the filter) lower_bound – Lower bound (filter cases which have a duration of the activity exceeding)
Returns:	Filtered log
Return type:	filtered_log

pm4py.objects.petri_net.utils.performance_map.find_min_max_arc_frequency(statistics)[source]¶

Find minimum and maximum arc frequency

Parameters:	statistics – Element statistics
Returns:	min_frequency – Minimum arc frequency max_frequency – Maximum arc frequency

pm4py.objects.petri_net.utils.performance_map.find_min_max_arc_performance(statistics, aggregation_measure)[source]¶

Find minimum and maximum arc performance

Parameters:

statistics – Element statistics
aggregation_measure – Aggregation measure (e.g. mean, min) to use

Returns:

min_performance – Minimum performance
max_performance – Maximum performance

pm4py.objects.petri_net.utils.performance_map.find_min_max_trans_frequency(statistics)[source]¶

Find minimum and maximum transition frequency

Parameters:	statistics – Element statistics
Returns:	min_frequency – Minimum transition frequency (in the replay) max_frequency – Maximum transition frequency (in the replay)

pm4py.objects.petri_net.utils.performance_map.get_idx_exceeding_specified_acti_performance(log, transition_performance, activity, lower_bound)[source]¶

Get indexes of the cases exceeding the specified activity performance threshold

Parameters:	log – Event log transition_performance – Dictionary where each transition label is associated to performance measures activity – Target activity (of the filter) lower_bound – Lower bound (filter cases which have a duration of the activity exceeding)
Returns:	A list of indexes in the log
Return type:	idx

pm4py.objects.petri_net.utils.performance_map.get_transition_performance_with_token_replay(log, net, im, fm)[source]¶

Gets the transition performance through the usage of token-based replay

Parameters:	log – Event log net – Petri net im – Initial marking fm – Final marking
Returns:	Dictionary where each transition label is associated to performance measures
Return type:	transition_performance

pm4py.objects.petri_net.utils.performance_map.single_element_statistics(log, net, initial_marking, aligned_traces, variants_idx, activity_key='concept:name', timestamp_key='time:timestamp', ht_perf_method='last', parameters=None)[source]¶

Get single Petrinet element statistics

Parameters:	log – Log net – Petri net initial_marking – Initial marking aligned_traces – Result of the token-based replay variants_idx – Variants along with indexes of belonging traces activity_key – Activity key (must be specified if different from concept:name) timestamp_key – Timestamp key (must be specified if different from time:timestamp) ht_perf_method – Method to use in order to annotate hidden transitions (performance value could be put on the last possible point (last) or in the first possible point (first) parameters – Possible parameters of the algorithm
Returns:	Petri net element statistics (frequency, unaggregated performance)
Return type:	statistics

pm4py.objects.petri_net.utils.petri_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.petri_net.utils.petri_utils.acyclic_net_variants(net, initial_marking, final_marking, activity_key='concept:name')[source]¶

Given an acyclic accepting Petri net, initial and final marking extracts a set of variants (in form of traces) replayable on the net. Warning: this function is based on a marking exploration. If the accepting Petri net contains loops, the method will not work properly as it stops the search if a specific marking has already been encountered.

Parameters:	param net: An acyclic workflow net param initial_marking: The initial marking of the net. param final_marking: The final marking of the net. param activity_key: activity key to use
Returns:
Return type:	return: variants: `list` Set of variants - in the form of Trace objects - obtainable executing the net

pm4py.objects.petri_net.utils.petri_utils.add_arc_from_to(fr, to, net: pm4py.objects.petri_net.obj.PetriNet, weight=1, type=None) → pm4py.objects.petri_net.obj.PetriNet.Arc[source]¶

Adds an arc from a specific element to another element in some net. Assumes from and to are in the net!

Parameters:	fr (transition/place from) to (transition/place to) net (net to use) weight (weight associated to the arc)
Returns:
Return type:	None

pm4py.objects.petri_net.utils.petri_utils.add_place(net: pm4py.objects.petri_net.obj.PetriNet, name=None) → pm4py.objects.petri_net.obj.PetriNet.Place[source]¶

pm4py.objects.petri_net.utils.petri_utils.add_transition(net: pm4py.objects.petri_net.obj.PetriNet, name=None, label=None) → pm4py.objects.petri_net.obj.PetriNet.Transition[source]¶

pm4py.objects.petri_net.utils.petri_utils.construct_trace_net(trace, trace_name_key='concept:name', activity_key='concept:name')[source]¶

Creates a trace net, i.e. a trace in Petri net form.

Parameters:	trace (`list` input trace, assumed to be a list of events) trace_name_key (`str` key of the attribute that defines the name of the trace) activity_key (`str` key of the attribute of the events that defines the activity name)
Returns:	tuple
Return type:	`tuple` of the net, initial marking and the final marking

pm4py.objects.petri_net.utils.petri_utils.construct_trace_net_cost_aware(trace, costs, trace_name_key='concept:name', activity_key='concept:name')[source]¶

Creates a trace net, i.e. a trace in Petri net form mapping specific costs to transitions.

Parameters:	trace (`list` input trace, assumed to be a list of events) costs (`list` list of costs, length should be equal to the length of the input trace) trace_name_key (`str` key of the attribute that defines the name of the trace) activity_key (`str` key of the attribute of the events that defines the activity name)
Returns:	tuple
Return type:	`tuple` of the net, initial marking, final marking and map of costs

pm4py.objects.petri_net.utils.petri_utils.decorate_places_preset_trans(net: pm4py.objects.petri_net.obj.PetriNet)[source]¶

Decorate places with information useful for the replay

Parameters:	net – Petri net

pm4py.objects.petri_net.utils.petri_utils.decorate_transitions_prepostset(net: pm4py.objects.petri_net.obj.PetriNet)[source]¶

Decorate transitions with sub and addition markings

Parameters:	net – Petri net

pm4py.objects.petri_net.utils.petri_utils.get_arc_type(elem)[source]¶

pm4py.objects.petri_net.utils.petri_utils.get_cycles_petri_net_places(net)[source]¶

Get the cycles of a Petri net (returning only list of places belonging to the cycle)

Parameters:	net – Petri net
Returns:	Cycles (places) of the Petri net
Return type:	cycles

Deprecated since version 2.2.7: This will be removed in 3.0.0.

pm4py.objects.petri_net.utils.petri_utils.get_cycles_petri_net_transitions(net)[source]¶

Get the cycles of a Petri net (returning only list of transitions belonging to the cycle)

Parameters:	net – Petri net
Returns:	Cycles (transitions) of the Petri net
Return type:	cycles

Deprecated since version 2.2.7: This will be removed in 3.0.0.

pm4py.objects.petri_net.utils.petri_utils.get_places_shortest_path(net, place_to_populate, current_place, places_shortest_path, actual_list, rec_depth, max_rec_depth)[source]¶

Get shortest path between places lead by hidden transitions

Parameters:	net – Petri net place_to_populate – Place that we are populating the shortest map of current_place – Current visited place (must explore its transitions) places_shortest_path – Current dictionary actual_list – Actual list of transitions to enable rec_depth – Recursion depth max_rec_depth – Maximum recursion depth

pm4py.objects.petri_net.utils.petri_utils.get_places_shortest_path_by_hidden(net: pm4py.objects.petri_net.obj.PetriNet, max_rec_depth)[source]¶

Get shortest path between places lead by hidden transitions

Parameters:	net – Petri net max_rec_depth – Maximum recursion depth

pm4py.objects.petri_net.utils.petri_utils.get_s_components_from_petri(net, im, fm, rec_depth=0, curr_s_comp=None, visited_places=None, list_s_components=None, max_rec_depth=6)[source]¶

Gets the S-components from a Petri net

Parameters:	net – Petri net im – Initial marking fm – Final marking curr_s_comp – Current S component visited_places – Visited places list_s_components – List of S-components max_rec_depth – Maximum recursion depth
Returns:	List of S-components
Return type:	s_components

pm4py.objects.petri_net.utils.petri_utils.get_strongly_connected_subnets(net)[source]¶

Get the strongly connected components subnets in the Petri net

Parameters:	net – Petri net
Returns:	List of strongly connected transitions of the Petri net
Return type:	strongly_connected_transitions

Deprecated since version 2.2.7: This will be removed in 3.0.0.

pm4py.objects.petri_net.utils.petri_utils.get_transition_by_name(net: pm4py.objects.petri_net.obj.PetriNet, transition_name) → Optional[pm4py.objects.petri_net.obj.PetriNet.Transition][source]¶

Get a transition by its name

Parameters:	net – Petri net transition_name – Transition name
Returns:	Transition object
Return type:	transition

pm4py.objects.petri_net.utils.petri_utils.invert_spaths_dictionary(spaths)[source]¶

Invert the shortest paths (between places) dictionary, from target-source to source-target

Parameters:	spaths – Shortest paths dictionary
Returns:	Inverted shortest paths dictionary
Return type:	inv_spaths

pm4py.objects.petri_net.utils.petri_utils.is_sub_marking(sub_marking: pm4py.objects.petri_net.obj.Marking, marking: pm4py.objects.petri_net.obj.Marking) → bool[source]¶

pm4py.objects.petri_net.utils.petri_utils.merge(trgt: Optional[pm4py.objects.petri_net.obj.PetriNet] = None, nets=None) → pm4py.objects.petri_net.obj.PetriNet[source]¶

pm4py.objects.petri_net.utils.petri_utils.place_set_as_marking(places) → pm4py.objects.petri_net.obj.Marking[source]¶

pm4py.objects.petri_net.utils.petri_utils.post_set(elem, arc_type=None) → Set[T][source]¶

pm4py.objects.petri_net.utils.petri_utils.pre_set(elem, arc_type=None) → Set[T][source]¶

pm4py.objects.petri_net.utils.petri_utils.remove_arc(net: pm4py.objects.petri_net.obj.PetriNet, arc: pm4py.objects.petri_net.obj.PetriNet.Arc) → pm4py.objects.petri_net.obj.PetriNet[source]¶

Removes an arc from a Petri net

Parameters:	net – Petri net arc – Arc of the Petri net
Returns:	Petri net
Return type:	net

pm4py.objects.petri_net.utils.petri_utils.remove_place(net: pm4py.objects.petri_net.obj.PetriNet, place: pm4py.objects.petri_net.obj.PetriNet.Place) → pm4py.objects.petri_net.obj.PetriNet[source]¶

Remove a place from a Petri net

Parameters:	net – Petri net place – Place to remove
Returns:	Petri net
Return type:	net

pm4py.objects.petri_net.utils.petri_utils.remove_transition(net: pm4py.objects.petri_net.obj.PetriNet, trans: pm4py.objects.petri_net.obj.PetriNet.Transition) → pm4py.objects.petri_net.obj.PetriNet[source]¶

Remove a transition from a Petri net

Parameters:	net – Petri net trans – Transition to remove
Returns:	Petri net
Return type:	net

pm4py.objects.petri_net.utils.petri_utils.remove_unconnected_components(net: pm4py.objects.petri_net.obj.PetriNet) → pm4py.objects.petri_net.obj.PetriNet[source]¶

Remove unconnected components from a Petri net

Parameters:	net – Petri net
Returns:	Cleaned Petri net
Return type:	net

pm4py.objects.petri_net.utils.projection 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.petri_net.utils.projection.project_net_on_matrix(net, activities, parameters=None)[source]¶

Project a Petri net with: - only visible transitions - where each place preset/postset is disjoint - with unique visible transitions on a numeric matrix

Parameters:	net – Petri net activities – List of activities parameters – Possible parameters of the algorithm

pm4py.objects.petri_net.utils.projection.project_net_on_place(place)[source]¶

Project a Petri net on a place

Parameters:	place – Place
Returns:	net – (Place) net im – Empty initial marking fm – Empty final marking

pm4py.objects.petri_net.utils.reachability_graph 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.objects.petri_net.utils.reachability_graph.Parameters[source]¶

Bases: enum.Enum

An enumeration.

MAX_ELAB_TIME = 'max_elab_time'¶

PETRI_SEMANTICS = 'petri_semantics'¶

pm4py.objects.petri_net.utils.reachability_graph.construct_reachability_graph(net, initial_marking, use_trans_name=False, parameters=None)[source]¶

Creates a reachability graph of a certain Petri net. DO NOT ATTEMPT WITH AN UNBOUNDED PETRI NET, EVER.

Parameters:	net (Petri net) initial_marking (initial marking of the Petri net.)
Returns:	re_gr
Return type:	Transition system that represents the reachability graph of the input Petri net.

pm4py.objects.petri_net.utils.reachability_graph.construct_reachability_graph_from_flow(incoming_transitions, outgoing_transitions, use_trans_name=False, parameters=None)[source]¶

Construct the reachability graph from the marking flow

Parameters:	incoming_transitions – Incoming transitions outgoing_transitions – Outgoing transitions use_trans_name – Use the transition name
Returns:	Transition system that represents the reachability graph of the input Petri net.
Return type:	re_gr

pm4py.objects.petri_net.utils.reachability_graph.marking_flow_petri(net, im, return_eventually_enabled=False, parameters=None)[source]¶

Construct the marking flow of a Petri net

Parameters:	net – Petri net im – Initial marking return_eventually_enabled – Return the eventually enabled (visible) transitions

pm4py.objects.petri_net.utils.reachability_graph.staterep(name)[source]¶

Creates a string representation for a state of a transition system. Necessary because graphviz does not support symbols simulation than alphanimerics and ‘_’. TODO: find a better representation.

Parameters:	name (the name of a state)
Returns:
Return type:	Version of the name filtered of non-alphanumerical characters (except ‘_’)

pm4py.objects.petri_net.utils.reduction 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.petri_net.utils.reduction.apply_a_rule(net)[source]¶

Apply the Abstraction (A) rule

Parameters:	net – Reset Inhibitor net

pm4py.objects.petri_net.utils.reduction.apply_elp_rule(net, im=None)[source]¶

Apply the Elimination of Self-Loop Places (ELP) rule

Parameters:	net – Reset Inhibitor net

pm4py.objects.petri_net.utils.reduction.apply_elt_rule(net)[source]¶

Apply the Elimination of Self-Loop Transitions (ELT) rule

Parameters:	net – Reset Inhibitor net

pm4py.objects.petri_net.utils.reduction.apply_fpp_rule(net, im=None)[source]¶

Apply the Fusion of Parallel Places (FPP) rule

Parameters:	net – Reset Inhibitor net

pm4py.objects.petri_net.utils.reduction.apply_fpt_rule(net)[source]¶

Apply the Fusion of Parallel Transitions (FPT) rule

Parameters:	net – Reset Inhibitor net

pm4py.objects.petri_net.utils.reduction.apply_fsp_rule(net, im=None, fm=None)[source]¶

Apply the Fusion of Series Places (FSP) rule

Parameters:	net – Reset Inhibitor net

pm4py.objects.petri_net.utils.reduction.apply_fst_rule(net)[source]¶

Apply the Fusion of Series Transitions (FST) rule

Parameters:	net – Reset Inhibitor net

pm4py.objects.petri_net.utils.reduction.apply_r_rule(net)[source]¶

Apply the Reset Reduction (R) rule

Parameters:	net – Reset Inhibitor net

pm4py.objects.petri_net.utils.reduction.apply_reset_inhibitor_net_reduction(net, im=None, fm=None)[source]¶

Apply a thorough reduction to the Reset Inhibitor net

Parameters:	net – Reset Inhibitor net

pm4py.objects.petri_net.utils.reduction.apply_simple_reduction(net)[source]¶

Apply a simple reduction to the Petri net

Parameters:	net – Petri net

pm4py.objects.petri_net.utils.reduction.power_set(iterable, min=0)[source]¶

pm4py.objects.petri_net.utils.reduction.reduce_single_entry_transitions(net)[source]¶

Reduces the number of the single entry transitions in the Petri net

Parameters:	net – Petri net

pm4py.objects.petri_net.utils.reduction.reduce_single_exit_transitions(net)[source]¶

Reduces the number of the single exit transitions in the Petri net

Parameters:	net – Petri net

pm4py.objects.petri_net.utils.synchronous_product 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.petri_net.utils.synchronous_product.construct(pn1, im1, fm1, pn2, im2, fm2, skip)[source]¶

Constructs the synchronous product net of two given Petri nets.

Parameters:	pn1 – Petri net 1 im1 – Initial marking of Petri net 1 fm1 – Final marking of Petri net 1 pn2 – Petri net 2 im2 – Initial marking of Petri net 2 fm2 – Final marking of Petri net 2 skip – Symbol to be used as skip
Returns:
Return type:	return: Synchronous product net and associated marking labels are of the form (a,>>)

pm4py.objects.petri_net.utils.synchronous_product.construct_cost_aware(pn1, im1, fm1, pn2, im2, fm2, skip, pn1_costs, pn2_costs, sync_costs)[source]¶

Constructs the synchronous product net of two given Petri nets.

Parameters:	pn1 – Petri net 1 im1 – Initial marking of Petri net 1 fm1 – Final marking of Petri net 1 pn2 – Petri net 2 im2 – Initial marking of Petri net 2 fm2 – Final marking of Petri net 2 skip – Symbol to be used as skip pn1_costs – dictionary mapping transitions of pn1 to corresponding costs pn2_costs – dictionary mapping transitions of pn2 to corresponding costs pn1_costs – dictionary mapping pairs of transitions in pn1 and pn2 to costs sync_costs – Costs of sync moves
Returns:
Return type:	return: Synchronous product net and associated marking labels are of the form (a,>>)

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/>.