pm4py.algo.evaluation.precision.dfg 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.evaluation.precision.dfg.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.evaluation.precision.dfg.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'#

pm4py.algo.evaluation.precision.dfg.algorithm.apply(log: EventLog | EventStream, dfg: Dict[Tuple[str, str], int], start_activities: Dict[str, int], end_activities: Dict[str, int], parameters: Dict[str | Parameters, Any] | None = None) → float[source]#

Computes the precision of a directly-follows graph using the ETConformance approach

Parameters#

log: Event log
dfg: Directly-follows graph
start_activities: Start activities
end_activities: End activities
parameters: Parameters of the algorithm: - Parameters.ACTIVITY_KEY: the key to use

Returns#

precision: Precision value