pm4py.algo.simulation.montecarlo package
Subpackages
Submodules
pm4py.algo.simulation.montecarlo.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.algo.simulation.montecarlo.algorithm.Variants(value)[source]
Bases:
enum.Enum
An enumeration.
- PETRI_SEMAPH_FIFO = <module 'pm4py.algo.simulation.montecarlo.variants.petri_semaph_fifo' from 'C:\\Users\\berti\\pm4py-core\\pm4py\\algo\\simulation\\montecarlo\\variants\\petri_semaph_fifo.py'>
- pm4py.algo.simulation.montecarlo.algorithm.apply(log: Union[pm4py.objects.log.obj.EventLog, pandas.core.frame.DataFrame], net: pm4py.objects.petri_net.obj.PetriNet, im: pm4py.objects.petri_net.obj.Marking, fm: pm4py.objects.petri_net.obj.Marking, variant=Variants.PETRI_SEMAPH_FIFO, parameters: Optional[Dict[Any, Any]] = None) Tuple[pm4py.objects.log.obj.EventLog, Dict[str, Any]] [source]
Performs a Monte Carlo simulation of an accepting Petri net without duplicate transitions and where the preset is always distinct from the postset
- Parameters
log – Event log
net – Accepting Petri net without duplicate transitions and where the preset is always distinct from the postset
im – Initial marking
fm – Final marking
variant – Variant of the algorithm to use: - Variants.PETRI_SEMAPH_FIFO
parameters –
- Parameters of the algorithm:
Parameters.PARAM_NUM_SIMULATIONS => (default: 100) Parameters.PARAM_FORCE_DISTRIBUTION => Force a particular stochastic distribution (e.g. normal) when the stochastic map is discovered from the log (default: None; no distribution is forced) Parameters.PARAM_ENABLE_DIAGNOSTICS => Enable the printing of diagnostics (default: True) Parameters.PARAM_DIAGN_INTERVAL => Interval of time in which diagnostics of the simulation are printed (default: 32) Parameters.PARAM_CASE_ARRIVAL_RATIO => Case arrival of new cases (default: None; inferred from the log) Parameters.PARAM_PROVIDED_SMAP => Stochastic map that is used in the simulation (default: None; inferred from the log) Parameters.PARAM_MAP_RESOURCES_PER_PLACE => Specification of the number of resources available per place (default: None; each place gets the default number of resources) Parameters.PARAM_DEFAULT_NUM_RESOURCES_PER_PLACE => Default number of resources per place when not specified (default: 1; each place gets 1 resource and has to wait for the resource to finish) Parameters.PARAM_SMALL_SCALE_FACTOR => Scale factor for the sleeping time of the actual simulation (default: 864000.0, 10gg) Parameters.PARAM_MAX_THREAD_EXECUTION_TIME => Maximum execution time per thread (default: 60.0, 1 minute)
- Returns
simulated_log – Simulated event log
simulation_result –
- Result of the simulation:
Outputs.OUTPUT_PLACES_INTERVAL_TREES => inteval trees that associate to each place the times in which it was occupied. Outputs.OUTPUT_TRANSITIONS_INTERVAL_TREES => interval trees that associate to each transition the intervals of time in which it could not fire because some token was in the output. Outputs.OUTPUT_CASES_EX_TIME => Throughput time of the cases included in the simulated log Outputs.OUTPUT_MEDIAN_CASES_EX_TIME => Median of the throughput times Outputs.OUTPUT_CASE_ARRIVAL_RATIO => Case arrival ratio that was specified in the simulation Outputs.OUTPUT_TOTAL_CASES_TIME => Total time occupied by cases of the simulated log
pm4py.algo.simulation.montecarlo.outputs 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.simulation.montecarlo.outputs.Outputs(value)[source]
Bases:
enum.Enum
An enumeration.
- OUTPUT_CASES_EX_TIME = 'cases_ex_time'
- OUTPUT_CASE_ARRIVAL_RATIO = 'input_case_arrival_ratio'
- OUTPUT_MEDIAN_CASES_EX_TIME = 'median_cases_ex_time'
- OUTPUT_PLACES_INTERVAL_TREES = 'places_interval_trees'
- OUTPUT_TOTAL_CASES_TIME = 'total_cases_time'
- OUTPUT_TRANSITIONS_INTERVAL_TREES = 'transitions_interval_trees'
pm4py.algo.simulation.montecarlo.parameters 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.simulation.montecarlo.parameters.Parameters(value)[source]
Bases:
enum.Enum
An enumeration.
- ACTIVITY_KEY = 'pm4py:param:activity_key'
- PARAM_CASE_ARRIVAL_RATIO = 'case_arrival_ratio'
- PARAM_DEFAULT_NUM_RESOURCES_PER_PLACE = 'default_num_resources_per_place'
- PARAM_DIAGN_INTERVAL = 'diagn_interval'
- PARAM_ENABLE_DIAGNOSTICS = 'enable_diagnostics'
- PARAM_FORCE_DISTRIBUTION = 'force_distribution'
- PARAM_MAP_RESOURCES_PER_PLACE = 'map_resources_per_place'
- PARAM_MAX_THREAD_EXECUTION_TIME = 'max_thread_exec_time'
- PARAM_NUM_SIMULATIONS = 'num_simulations'
- PARAM_PROVIDED_SMAP = 'provided_stochastic_map'
- PARAM_SMALL_SCALE_FACTOR = 'small_scale_factor'
- TIMESTAMP_KEY = 'pm4py:param:timestamp_key'
- TOKEN_REPLAY_VARIANT = 'token_replay_variant'
pm4py.algo.simulation.montecarlo.simulator 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/>.
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/>.