pm4py.algo.discovery.inductive.variants.im_f package
Subpackages
Submodules
pm4py.algo.discovery.inductive.variants.im_f.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.discovery.inductive.variants.im_f.algorithm.Parameters(value)[source]
Bases:
enum.Enum
An enumeration.
- ACTIVITY_KEY = 'pm4py:param:activity_key'
- CASE_ID_KEY = 'pm4py:param:case_id_key'
- CONCURRENT_KEY = 'concurrent'
- EMPTY_TRACE_KEY = 'empty_trace'
- NOISE_THRESHOLD = 'noiseThreshold'
- ONCE_PER_TRACE_KEY = 'once_per_trace'
- START_TIMESTAMP_KEY = 'pm4py:param:start_timestamp_key'
- STRICT_TAU_LOOP_KEY = 'strict_tau_loop'
- TAU_LOOP_KEY = 'tau_loop'
- TIMESTAMP_KEY = 'pm4py:param:timestamp_key'
- pm4py.algo.discovery.inductive.variants.im_f.algorithm.apply(log, parameters)[source]
Apply the IM_F algorithm to a log obtaining a Petri net along with an initial and final marking
- Parameters
log – Log
parameters –
- Parameters of the algorithm, including:
Parameters.ACTIVITY_KEY -> attribute of the log to use as activity name (default concept:name)
- Returns
net – Petri net
initial_marking – Initial marking
final_marking – Final marking
- pm4py.algo.discovery.inductive.variants.im_f.algorithm.apply_tree(log, parameters)[source]
Apply the IM_FF algorithm to a log obtaining a process tree
- Parameters
log – Log
parameters –
- Parameters of the algorithm, including:
Parameters.ACTIVITY_KEY -> attribute of the log to use as activity name (default concept:name)
- Returns
Process tree
- Return type
process_tree
Deprecated since version 2.2.10: This will be removed in 3.0.0. use newer IM implementation (IM_CLEAN)
- pm4py.algo.discovery.inductive.variants.im_f.algorithm.apply_tree_variants(variants, parameters=None)[source]
Apply the IM_F algorithm to a dictionary of variants obtaining a process tree
- Parameters
variants – Variants
parameters –
- Parameters of the algorithm, including:
Parameters.ACTIVITY_KEY -> attribute of the log to use as activity name (default concept:name)
- Returns
Process tree
- Return type
process_tree
- pm4py.algo.discovery.inductive.variants.im_f.algorithm.apply_variants(variants, parameters=None)[source]
Apply the IM_F algorithm to a dictionary of variants, obtaining a Petri net along with an initial and final marking
- Parameters
variants – Variants
parameters –
- Parameters of the algorithm, including:
Parameters.ACTIVITY_KEY -> attribute of the log to use as activity name (default concept:name)
- Returns
net – Petri net
initial_marking – Initial marking
final_marking – Final marking
pm4py.algo.discovery.inductive.variants.im_f.fall_through_infrequent 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/>.
pm4py.algo.discovery.inductive.variants.im_f.splitting_infrequent 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/>.
- pm4py.algo.discovery.inductive.variants.im_f.splitting_infrequent.cut_trace_between_two_points(trace, point_a, point_b)[source]
- pm4py.algo.discovery.inductive.variants.im_f.splitting_infrequent.filter_trace_on_cut_partition(trace, partition, activity_key)[source]
- pm4py.algo.discovery.inductive.variants.im_f.splitting_infrequent.find_split_point(trace, cut_partition, start, ignore, activity_key)[source]
- pm4py.algo.discovery.inductive.variants.im_f.splitting_infrequent.split_loop_infrequent(cut, l, activity_key)[source]
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/>.