pm4py.algo.discovery.inductive.variants.im_f package

Subpackages

• pm4py.algo.discovery.inductive.variants.im_f.data_structures package
  • Submodules
  • pm4py.algo.discovery.inductive.variants.im_f.data_structures.subtree_infrequent module
  • Module contents

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

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)

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_infrequent_petrinet(tree)

pm4py.algo.discovery.inductive.variants.im_f.algorithm.apply_tree(log, parameters)

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)

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)

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.fall_through_infrequent.empty_trace_filtering(l, f)

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)

pm4py.algo.discovery.inductive.variants.im_f.splitting_infrequent.filter_trace_on_cut_partition(trace, partition, activity_key)

pm4py.algo.discovery.inductive.variants.im_f.splitting_infrequent.find_split_point(trace, cut_partition, start, ignore, activity_key)

pm4py.algo.discovery.inductive.variants.im_f.splitting_infrequent.split_loop_infrequent(cut, l, activity_key)

pm4py.algo.discovery.inductive.variants.im_f.splitting_infrequent.split_sequence_infrequent(cut, l, activity_key)

pm4py.algo.discovery.inductive.variants.im_f.splitting_infrequent.split_xor_infrequent(cut, l, activity_key)

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/>.