pm4py.evaluation.soundness.woflan package

Subpackages

• pm4py.evaluation.soundness.woflan.graphs package
  • Subpackages
    • pm4py.evaluation.soundness.woflan.graphs.minimal_coverability_graph package
      • Submodules
      • pm4py.evaluation.soundness.woflan.graphs.minimal_coverability_graph.minimal_coverability_graph module
      • Module contents
    • pm4py.evaluation.soundness.woflan.graphs.reachability_graph package
      • Submodules
      • pm4py.evaluation.soundness.woflan.graphs.reachability_graph.reachability_graph module
      • Module contents
    • pm4py.evaluation.soundness.woflan.graphs.restricted_coverability_graph package
      • Submodules
      • pm4py.evaluation.soundness.woflan.graphs.restricted_coverability_graph.restricted_coverability_graph module
      • Module contents
  • Submodules
  • pm4py.evaluation.soundness.woflan.graphs.utility module
  • Module contents
• pm4py.evaluation.soundness.woflan.not_well_handled_pairs package
  • Submodules
  • pm4py.evaluation.soundness.woflan.not_well_handled_pairs.not_well_handled_pairs module
  • Module contents
• pm4py.evaluation.soundness.woflan.place_invariants package
  • Submodules
  • pm4py.evaluation.soundness.woflan.place_invariants.place_invariants module
  • pm4py.evaluation.soundness.woflan.place_invariants.s_component module
  • pm4py.evaluation.soundness.woflan.place_invariants.uniform_invariant module
  • pm4py.evaluation.soundness.woflan.place_invariants.utility module
  • Module contents

Submodules

pm4py.evaluation.soundness.woflan.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.evaluation.soundness.woflan.algorithm.Outputs

Bases: enum.Enum

An enumeration.

DEAD_TASKS = 'dead_tasks'

LEFT = 'left'

LOCKING_SCENARIOS = 'locking_scenarios'

MCG = 'mcg'

NOT_WELL_HANDLED_PAIRS = 'not_well_handled_pairs'

PLACE_INVARIANTS = 'place_invariants'

RESTRICTED_COVERABILITY_TREE = 'restricted_coverability_tree'

R_G = 'r_g'

R_G_S_C = 'r_g_s_c'

S_COMPONENTS = 's_components'

S_C_NET = 's_c_net'

UNCOVERED_PLACES_S_COMPONENT = 'uncovered_places_s_component'

UNCOVERED_PLACES_UNIFORM = 'uncovered_places_uniform'

UNCOVERED_PLACES_WEIGHTED = 'uncovered_places_weighted'

UNIFORM_PLACE_INVARIANTS = 'uniform_place_invariants'

WEIGHTED_PLACE_INVARIANTS = 'weighted_place_invariants'

class pm4py.evaluation.soundness.woflan.algorithm.Parameters

Bases: enum.Enum

An enumeration.

PRINT_DIAGNOSTICS = 'print_diagnostics'

RETURN_ASAP_WHEN_NOT_SOUND = 'return_asap_when_not_sound'

RETURN_DIAGNOSTICS = 'return_diagnostics'

pm4py.evaluation.soundness.woflan.algorithm.apply(net, i_m, f_m, parameters=None)

Apply the Woflan Soundness check. Trough this process, different steps are executed. :param net: Petri Net representation of PM4Py :param i_m: initial marking of given Net. Marking object of PM4Py :param f_m: final marking of given Net. Marking object of PM4Py :return: True, if net is sound; False otherwise.

Deprecated since version 2.2.2: This will be removed in 3.0.0. deprecated version of WOFLAN; use pm4py.algo.analysis.woflan

pm4py.evaluation.soundness.woflan.algorithm.compute_non_live_sequences(woflan_object)

We want to compute the sequences of transitions which lead to deadlocks. To do this, we first compute a reachbility graph (possible, since we know that the Petri Net is bounded) and then we convert it to a spanning tree. Afterwards, we compute the paths which lead to nodes from which the final marking cannot be reached. Note: We are searching for the shortest sequence. After the first red node, all successors are also red. Therefore, we do not have to consider them. :param woflan_object: Object that contains the necessary information :return: List of sequence of transitions, each sequence is a list

pm4py.evaluation.soundness.woflan.algorithm.compute_unbounded_sequences(woflan_object)

We compute the sequences which lead to an infinite amount of tokens. To do this, we compute a restricted coverability tree. The tree works similar to the graph, despite we consider tree characteristics during the construction. :param woflan_object: Woflan object that contains all needed information. :return: List of unbounded sequences, each sequence is a list of transitions

pm4py.evaluation.soundness.woflan.algorithm.short_circuit_petri_net(net, print_diagnostics=False)

Fist, sink and source place are identified. Then, a transition from source to sink is added to short-circuited the given petri net. If there is no unique source and sink place, an error gets returned :param net: Petri net that is going to be short circuited :return:

pm4py.evaluation.soundness.woflan.algorithm.step_1(woflan_object, return_asap_when_unsound=False)

In the first step, we check if the input is given correct. We check if net is an PM4Py Petri Net representation and if the exist a correct entry for the initial and final marking. :param woflan_object: Object that contains all necessary information :return: Proceed with step 2 if ok; else False

pm4py.evaluation.soundness.woflan.algorithm.step_10(woflan_object, return_asap_when_unsound=False)

pm4py.evaluation.soundness.woflan.algorithm.step_11(woflan_object, return_asap_when_unsound=False)

pm4py.evaluation.soundness.woflan.algorithm.step_12(woflan_object, return_asap_when_unsound=False)

pm4py.evaluation.soundness.woflan.algorithm.step_13(woflan_object, return_asap_when_unsound=False)

pm4py.evaluation.soundness.woflan.algorithm.step_2(woflan_object, return_asap_when_unsound=False)

This method checks if a given Petri net is a workflow net. First, the Petri Net gets short-circuited (connect start and end place with a tau-transition. Second, the Petri Net gets converted into a networkx graph. Finally, it is tested if the resulting graph is a strongly connected component. :param woflan_object: Woflan objet containing all information :return: Bool=True if net is a WF-Net

pm4py.evaluation.soundness.woflan.algorithm.step_3(woflan_object, return_asap_when_unsound=False)

pm4py.evaluation.soundness.woflan.algorithm.step_4(woflan_object, return_asap_when_unsound=False)

pm4py.evaluation.soundness.woflan.algorithm.step_5(woflan_object, return_asap_when_unsound=False)

pm4py.evaluation.soundness.woflan.algorithm.step_6(woflan_object, return_asap_when_unsound=False)

pm4py.evaluation.soundness.woflan.algorithm.step_7(woflan_object, return_asap_when_unsound=False)

pm4py.evaluation.soundness.woflan.algorithm.step_8(woflan_object, return_asap_when_unsound=False)

pm4py.evaluation.soundness.woflan.algorithm.step_9(woflan_object, return_asap_when_unsound=False)

class pm4py.evaluation.soundness.woflan.algorithm.woflan(net, initial_marking, final_marking, print_diagnostics=False)

Bases: object

get_dead_tasks()

get_final_marking()

get_initial_marking()

get_left()

get_locking_scenarios()

get_mcg()

get_net()

get_not_well_handled_pairs()

get_output()

Returns a dictionary representation of the entities that are calculated during WOFLAN

get_place_invariants()

get_r_g()

get_r_g_s_c()

get_restricted_coverability_tree()

get_s_c_net()

get_s_components()

get_uncovered_places_s_component()

get_uncovered_places_uniform()

get_uncovered_places_weighted()

get_uniform_place_invariants()

get_weighted_place_invariants()

set_dead_tasks(dead_tasks)

set_left(left)

set_locking_scenarios(scenarios)

set_mcg(mcg)

set_not_well_handled_pairs(not_well_handled_pairs)

set_place_invariants(invariants)

set_r_g(r_g)

set_r_g_s_c(r_g)

set_restricted_coverability_tree(graph)

set_s_c_net(s_c_net)

set_s_components(s_components)

set_uncovered_places_s_component(uncovered_places)

set_uncovered_places_uniform(places)

set_uncovered_places_weighted(places)

set_uniform_place_invariants(invariants)

set_weighted_place_invariants(invariants)

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/>.