pm4py.util.lp package#

PM4Py – A Process Mining Library for Python

This program is free software: you can redistribute it and/or modify it under the terms of the GNU Affero General Public License as published by the Free Software Foundation, either version 3 of the License, or any later version.

This program 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 Affero General Public License for more details.

You should have received a copy of the GNU Affero General Public License along with this program. If not, see this software project’s root or visit <https://www.gnu.org/licenses/>.

Website: https://processintelligence.solutions Contact: info@processintelligence.solutions

Subpackages#

Submodules#

pm4py.util.lp.solver module#

PM4Py – A Process Mining Library for Python

You should have received a copy of the GNU Affero General Public License along with this program. If not, see this software project’s root or visit <https://www.gnu.org/licenses/>.

Website: https://processintelligence.solutions Contact: info@processintelligence.solutions

class pm4py.util.lp.solver.Parameters(value, names=<not given>, *values, module=None, qualname=None, type=None, start=1, boundary=None)[source]#

Bases: Enum

REQUIRE_ILP = 'require_ilp'#

pm4py.util.lp.solver.apply(c, Aub, bub, Aeq, beq, parameters=None, variant='cvxopt_solver_custom_align')[source]#

Gets the overall solution of the problem

Parameters#

c: c parameter of the algorithm
Aub: A_ub parameter of the algorithm
bub: b_ub parameter of the algorithm
Aeq: A_eq parameter of the algorithm
beq: b_eq parameter of the algorithm
parameters: Possible parameters of the algorithm
variant: Variant of the algorithm, possible values: pulp, scipy

Returns#

sol: Solution of the LP problem by the given algorithm

pm4py.util.lp.solver.get_prim_obj_from_sol(sol, parameters=None, variant='cvxopt_solver_custom_align')[source]#

Gets the primal objective from the solution of the LP problem

Parameters#

sol: Solution of the ILP problem by the given algorithm
parameters: Possible parameters of the algorithm
variant: Variant of the algorithm, possible values: pulp, scipy

Returns#

prim_obj: Primal objective

pm4py.util.lp.solver.get_points_from_sol(sol, parameters=None, variant='cvxopt_solver_custom_align')[source]#

Gets the points from the solution

Parameters#

sol: Solution of the LP problem by the given algorithm
parameters: Possible parameters of the algorithm
variant: Variant of the algorithm, possible values: pulp, scipy

Returns#

points: Point of the solution