pm4py.algo.analysis.marking_equation.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.analysis.marking_equation.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.analysis.marking_equation.variants.classic.Parameters(value)[source]#

Bases: Enum

An enumeration.

CASE_ID_KEY = 'pm4py:param:case_id_key'#
ACTIVITY_KEY = 'pm4py:param:activity_key'#
COSTS = 'costs'#
INCIDENCE_MATRIX = 'incidence_matrix'#
A = 'A_matrix'#
FULL_BOOTSTRAP_REQUIRED = 'full_bootstrap_required'#
class pm4py.algo.analysis.marking_equation.variants.classic.MarkingEquationSolver(net: PetriNet, im: Marking, fm: Marking, parameters: Optional[Dict[Any, Any]] = None)[source]#

Bases: object

get_components() Tuple[Any, Any, Any, Any, Any][source]#

Retrieve the components (Numpy matrixes) of the problem

Returns#

c

objective function

Aub

Inequalities matrix

bub

Inequalities vector

Aeq

Equalities matrix

beq

Equalities vector

change_ini_vec(ini: Marking)[source]#

Changes the initial marking of the synchronous product net

Parameters#

ini

Initial marking

get_x_vector(sol_points: List[int]) List[int][source]#

Returns the x vector of the solution

Parameters#

sol_points

Solution of the integer problem

Returns#

x

X vector

get_h(sol_points: List[int]) int[source]#

Returns the value of the heuristics

Parameters#

sol_points

Solution of the integer problem

Returns#

h

Heuristics value

get_activated_transitions(sol_points: List[int]) List[Transition][source]#

Gets the transitions of the synchronous product net that are non-zero in the solution of the marking equation

Parameters#

sol_points

Solution of the integer problem

Returns#

act_trans

Activated transitions

solve() Tuple[int, List[int]][source]#

Solves the marking equation, returning the heuristics and the x vector

Returns#

h

Heuristics value

x

X vector

solve_given_components(c, Aub, bub, Aeq, beq)[source]#

Solves the linear problem given the components

Parameters#

c

Objective vector

Aub

Inequalities matrix

bub

Inequalities vector

Aeq

Equalities matrix

beq

Equalities vector

Returns#

h

Heuristics value

x

X vector

get_firing_sequence(x: List[int]) Tuple[List[Transition], bool, int][source]#

Gets a firing sequence from the X vector

Parameters#

x

X vector

Returns#

firing_sequence

Firing sequence

reach_fm

Boolean value that is true whether the firing sequence reaches the final marking

explained_events

Number of explaned events by the firing sequence

pm4py.algo.analysis.marking_equation.variants.classic.build(net: PetriNet, im: Marking, fm: Marking, parameters: Optional[Dict[Any, Any]] = None) MarkingEquationSolver[source]#

Builds the marking equation out of a Petri net

Parameters#

net

Petri net

im

Initial marking

fm

Final marking

parameters

Parameters of the algorithm, including: - Parameters.CASE_ID_KEY => attribute to use as case identifier - Parameters.ACTIVITY_KEY => attribute to use as activity - Parameters.COSTS => (if provided) the cost function (otherwise the default cost function is applied) - Parameters.INCIDENCE_MATRIX => (if provided) the incidence matrix of the Petri net - Parameters.A => (if provided) the A numpy matrix of the incidence matrix - Parameters.FULL_BOOTSTRAP_REQUIRED => The preset/postset of places/transitions need to be inserted

pm4py.algo.analysis.marking_equation.variants.classic.get_h_value(solver: MarkingEquationSolver, parameters: Optional[Dict[Any, Any]] = None) int[source]#

Gets the heuristics value from the marking equation

Parameters#

solver

Marking equation solver (class in this file)

parameters

Possible parameters of the algorithm