pm4py.algo.organizational_mining.local_diagnostics package#

PM4Py – A Process Mining Library for Python

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.algo.organizational_mining.local_diagnostics.algorithm module#

PM4Py – A Process Mining Library for Python

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.algo.organizational_mining.local_diagnostics.algorithm.Parameters(value, names=<not given>, *values, module=None, qualname=None, type=None, start=1, boundary=None)[source]#

Bases: Enum

RESOURCE_KEY = 'pm4py:param:resource_key'#

ACTIVITY_KEY = 'pm4py:param:activity_key'#

GROUP_KEY = 'pm4py:param:group_key'#

class pm4py.algo.organizational_mining.local_diagnostics.algorithm.Outputs(value, names=<not given>, *values, module=None, qualname=None, type=None, start=1, boundary=None)[source]#

Bases: Enum

GROUP_RELATIVE_FOCUS = 'group_relative_focus'#

GROUP_RELATIVE_STAKE = 'group_relative_stake'#

GROUP_COVERAGE = 'group_coverage'#

GROUP_MEMBER_CONTRIBUTION = 'group_member_contribution'#

pm4py.algo.organizational_mining.local_diagnostics.algorithm.apply_from_clustering_or_roles(log_obj: DataFrame | EventLog, ja_clustering_or_roles: Dict[str, List[str]], parameters: Dict[Any, str] | None = None) → Dict[str, Any][source]#

Provides the local diagnostics for the organizational model starting from a log object and the results of the similar activities clustering / the roles detection algorithm.

The approach implemented is the one described in: Yang, Jing, et al. “OrgMining 2.0: A Novel Framework for Organizational Model Mining from Event Logs.” arXiv preprint arXiv:2011.12445 (2020).

Parameters#

log_obj: Log object
ja_clustering_or_roles: Result of the similar activities clustering / the roles detection algorithm
parameters: Parameters of the algorithm, including: - pm4py:param:resource_key => the resource attribute - pm4py:param:activity_key => the activity attribute - pm4py:param:group_key => the group

Returns#

Dictionary containing four keys:

group_relative_focus => relative focus metric
group_relative_stake => relative stake metric
group_coverage => group coverage metric
group_member_contribution => group member contribution metric

pm4py.algo.organizational_mining.local_diagnostics.algorithm.apply_from_group_attribute(log_obj: DataFrame | EventLog, parameters: Dict[Any, str] | None = None) → Dict[str, Any][source]#

Provides the local diagnostics for the organizational model starting from a log object and considering the group specified by the attribute

The approach implemented is the one described in: Yang, Jing, et al. “OrgMining 2.0: A Novel Framework for Organizational Model Mining from Event Logs.” arXiv preprint arXiv:2011.12445 (2020).

Parameters#

log_obj: Log object
parameters: Parameters of the algorithm, including: - pm4py:param:resource_key => the resource attribute - pm4py:param:activity_key => the activity attribute - pm4py:param:group_key => the group

Returns#

Dictionary containing four keys:

group_relative_focus => relative focus metric
group_relative_stake => relative stake metric
group_coverage => group coverage metric
group_member_contribution => group member contribution metric