pm4py.algo.discovery.performance_spectrum 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

Subpackages#

pm4py.algo.discovery.performance_spectrum.variants package

Submodules#

pm4py.algo.discovery.performance_spectrum.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.discovery.performance_spectrum.algorithm.Parameters(value, names=<not given>, *values, module=None, qualname=None, type=None, start=1, boundary=None)[source]#

Bases: Enum

ACTIVITY_KEY = 'pm4py:param:activity_key'#

TIMESTAMP_KEY = 'pm4py:param:timestamp_key'#

CASE_ID_KEY = 'pm4py:param:case_id_key'#

ATTRIBUTE_KEY = 'pm4py:param:attribute_key'#

PARAMETER_SAMPLE_SIZE = 'sample_size'#

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

Bases: Enum

LIST_ACTIVITIES = 'list_activities'#

POINTS = 'points'#

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

Bases: Enum

DATAFRAME = <module 'pm4py.algo.discovery.performance_spectrum.variants.dataframe' from 'C:\\Users\\berti\\pm4py-core\\pm4py\\algo\\discovery\\performance_spectrum\\variants\\dataframe.py'>#

LOG = <module 'pm4py.algo.discovery.performance_spectrum.variants.log' from 'C:\\Users\\berti\\pm4py-core\\pm4py\\algo\\discovery\\performance_spectrum\\variants\\log.py'>#

DATAFRAME_DISCONNECTED = <module 'pm4py.algo.discovery.performance_spectrum.variants.dataframe_disconnected' from 'C:\\Users\\berti\\pm4py-core\\pm4py\\algo\\discovery\\performance_spectrum\\variants\\dataframe_disconnected.py'>#

LOG_DISCONNECTED = <module 'pm4py.algo.discovery.performance_spectrum.variants.log_disconnected' from 'C:\\Users\\berti\\pm4py-core\\pm4py\\algo\\discovery\\performance_spectrum\\variants\\log_disconnected.py'>#

pm4py.algo.discovery.performance_spectrum.algorithm.apply(log: EventLog | EventStream | DataFrame, list_activities: List[str], variant=None, parameters: Dict[Any, Any] | None = None) → Dict[str, Any][source]#

Finds the performance spectrum provided a log/dataframe and a list of activities

Parameters#

log

Event log/Dataframe

list_activities

List of activities interesting for the performance spectrum (at least two)

variant

Variant to be used (see Variants Enum)

parameters

Parameters of the algorithm, including:

Parameters.ACTIVITY_KEY
Parameters.TIMESTAMP_KEY

Returns#

ps: Performance spectrum object (dictionary)