pm4py.util.lp.variants package#
PM4Py – A Process Mining Library for Python
Copyright (C) 2024 Process Intelligence Solutions UG (haftungsbeschränkt)
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
Submodules#
pm4py.util.lp.variants.cvxopt_solver module#
PM4Py – A Process Mining Library for Python
Copyright (C) 2024 Process Intelligence Solutions UG (haftungsbeschränkt)
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
- pm4py.util.lp.variants.cvxopt_solver.apply(c, Aub, bub, Aeq, beq, parameters=None)[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
Returns#
- sol
Solution of the LP problem by the given algorithm
pm4py.util.lp.variants.cvxopt_solver_custom_align module#
PM4Py – A Process Mining Library for Python
Copyright (C) 2024 Process Intelligence Solutions UG (haftungsbeschränkt)
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
- pm4py.util.lp.variants.cvxopt_solver_custom_align.apply(c, Aub, bub, Aeq, beq, parameters=None)[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
Returns#
- sol
Solution of the LP problem by the given algorithm
- pm4py.util.lp.variants.cvxopt_solver_custom_align.get_prim_obj_from_sol(sol, parameters=None)[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
Returns#
- prim_obj
Primal objective
pm4py.util.lp.variants.cvxopt_solver_custom_align_ilp module#
PM4Py – A Process Mining Library for Python
Copyright (C) 2024 Process Intelligence Solutions UG (haftungsbeschränkt)
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
- class pm4py.util.lp.variants.cvxopt_solver_custom_align_ilp.Parameters(value, names=<not given>, *values, module=None, qualname=None, type=None, start=1, boundary=None)[source]#
Bases:
Enum- INTEGRALITY = 'integrality'#
- pm4py.util.lp.variants.cvxopt_solver_custom_align_ilp.apply(c, Aub, bub, Aeq, beq, parameters=None)[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
Returns#
- sol
Solution of the LP problem by the given algorithm
- pm4py.util.lp.variants.cvxopt_solver_custom_align_ilp.get_prim_obj_from_sol(sol, parameters=None)[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
Returns#
- prim_obj
Primal objective
pm4py.util.lp.variants.pulp_solver module#
PM4Py – A Process Mining Library for Python
Copyright (C) 2024 Process Intelligence Solutions UG (haftungsbeschränkt)
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
- class pm4py.util.lp.variants.pulp_solver.Parameters(value, names=<not given>, *values, module=None, qualname=None, type=None, start=1, boundary=None)[source]#
Bases:
Enum- REQUIRE_ILP = 'require_ilp'#
- INTEGRALITY = 'integrality'#
- BOUNDS = 'bounds'#
- pm4py.util.lp.variants.pulp_solver.get_variable_name(index)[source]#
Generates a variable name with leading zeros to ensure consistent length.
- pm4py.util.lp.variants.pulp_solver.apply(c, Aub, bub, Aeq=None, beq=None, parameters=None)[source]#
Solves a linear programming problem using PuLP with all inputs as Python lists or lists of lists.
pm4py.util.lp.variants.scipy_solver module#
PM4Py – A Process Mining Library for Python
Copyright (C) 2024 Process Intelligence Solutions UG (haftungsbeschränkt)
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
- class pm4py.util.lp.variants.scipy_solver.Parameters[source]#
Bases:
object- INTEGRALITY = 'integrality'#
- METHOD = 'method'#
- BOUNDS = 'bounds'#
- pm4py.util.lp.variants.scipy_solver.apply(c: list, Aub: ndarray, bub: matrix, Aeq: matrix, beq: matrix, parameters: Dict[Any, Any] | None = None) OptimizeResult[source]#