pm4py.algo.clustering.trace_attribute_driven package

Submodules

pm4py.algo.clustering.trace_attribute_driven.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.clustering.trace_attribute_driven.algorithm.Variants[source]

Bases: enum.Enum

An enumeration.

DFG = <module 'pm4py.algo.clustering.trace_attribute_driven.dfg.dfg_dist' from '/home/docs/checkouts/readthedocs.org/user_builds/pm4py-source/checkouts/latest/pm4py/algo/clustering/trace_attribute_driven/dfg/dfg_dist.py'>
VARIANT_AVG_LEVEN(percent, alpha)
VARIANT_AVG_VEC(percent, alpha)
VARIANT_DMM_LEVEN(percent, alpha)
VARIANT_DMM_VEC(percent, alpha)
pm4py.algo.clustering.trace_attribute_driven.algorithm.apply(log: Union[pm4py.objects.log.obj.EventLog, pm4py.objects.log.obj.EventStream, pandas.core.frame.DataFrame], trace_attribute: str, variant=<function eval_DMM_leven>, parameters: Optional[Dict[Any, Any]] = None) → Any[source]

Apply the hierarchical clustering to a log starting from a trace attribute.

MSc Thesis is available at: https://www.pads.rwth-aachen.de/global/show_document.asp?id=aaaaaaaaalpxgft&download=1 Defense slides are available at: https://www.pads.rwth-aachen.de/global/show_document.asp?id=aaaaaaaaalpxgqx&download=1

Parameters:
  • log – Log
  • trace_attribute – Trace attribute to exploit for the clustering
  • variant – Variant of the algorithm to apply, possible values: - Variants.VARIANT_DMM_LEVEN (that is the default) - Variants.VARIANT_AVG_LEVEN - Variants.VARIANT_DMM_VEC - Variants.VARIANT_AVG_VEC - Variants.DFG
Returns:

  • tree – Hierarchical cluster tree
  • leafname – Root node
pm4py.algo.clustering.trace_attribute_driven.algorithm.bfs(tree)[source]

pm4py.algo.clustering.trace_attribute_driven.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.clustering.trace_attribute_driven.parameters.Parameters[source]

Bases: enum.Enum

An enumeration.

ACTIVITY_KEY = 'pm4py:param:activity_key'
ATTRIBUTE_KEY = 'pm4py:param:attribute_key'
BINARIZE = 'binarize'
LOWER_PERCENT = 'lower_percent'
POSITIVE = 'positive'
SINGLE = 'single'

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/>.