pm4py.algo.organizational_mining package#

PM4Py â€“ 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

Subpackages#

Submodules#

pm4py.algo.organizational_mining.util 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.util.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'#

pm4py.algo.organizational_mining.util.get_groups_from_log(log_obj: DataFrame | EventLog, parameters: Dict[Any, str] | None = None) → Dict[str, Dict[str, int]][source]#

From the log object, where events have a group, a resource and an activity attribute, gets a dictionary where the first key is a group, the second key is a resource and the value is the number of events done by the resource when belonging to the given group.

Parameters#

log_obj: Log object
parameters: Parameters of the algorithm, including: - Parameters.RESOURCE_KEY => the resource attribute - Parameters.ACTIVITY_KEY => the activity attribute - Parameters.GROUP_KEY => the group

Returns#

dict: Aforementioned dictionary

pm4py.algo.organizational_mining.util.get_res_act_from_log(log_obj: DataFrame | EventLog, parameters: Dict[Any, str] | None = None) → Tuple[Dict[str, Dict[str, int]], Dict[str, Dict[str, int]]][source]#

From the log object, where events have a group, a resource and an activity attribute, gets two dictionaries: - The first, where the first key is the resource, the second key is the activity and the third is the number of

events of the given activity done by the given resource

The second, where the first key is the activity, the second key is the resource and the third is the number of
events of the given activity done by the given resource

Parameters#

log_obj: Log object
parameters: Parameters of the algorithm, including: - Parameters.RESOURCE_KEY => the resource attribute - Parameters.ACTIVITY_KEY => the activity attribute - Parameters.GROUP_KEY => the group

Returns#

res_act: Dictionary resources-activities-occurrences
act_res: Dictionary activities-resources-occurrences

pm4py.algo.organizational_mining.util.get_resources_from_log(log_obj: DataFrame | EventLog, parameters: Dict[Any, str] | None = None) → Dict[str, int][source]#

Gets the resources, along with the respective number of events, from the log object

Parameters#

log_obj: Log object
parameters: Parameters of the algorithm, including: - Parameters.RESOURCE_KEY => the resource attribute - Parameters.ACTIVITY_KEY => the activity attribute - Parameters.GROUP_KEY => the group

Returns#

resources_dictionary: Dictionary of resources along with their occurrences