pm4py.algo.organizational_mining.sna.variants.pandas package#
PM4Py – A Process Mining Library for Python
Copyright (C) 2024 Process Intelligence Solutions UG (haftungsbeschränkt)
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.sna.variants.pandas.handover module#
PM4Py – A Process Mining Library for Python
Copyright (C) 2024 Process Intelligence Solutions UG (haftungsbeschränkt)
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
- class pm4py.algo.organizational_mining.sna.variants.pandas.handover.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'#
- RESOURCE_KEY = 'pm4py:param:resource_key'#
- CASE_ID_KEY = 'pm4py:param:case_id_key'#
- BETA = 'beta'#
- pm4py.algo.organizational_mining.sna.variants.pandas.handover.apply(log: DataFrame, parameters: Dict[str | Parameters, Any] | None = None) SNA[source]#
Calculates the HW metric
Parameters#
- log
Log
- parameters
- Possible parameters of the algorithm:
Paramters.BETA -> beta value as described in the Wil SNA paper
Returns#
- tuple
Tuple containing the metric matrix and the resources list. Moreover, last boolean indicates that the metric is directed.
pm4py.algo.organizational_mining.sna.variants.pandas.jointactivities module#
PM4Py – A Process Mining Library for Python
Copyright (C) 2024 Process Intelligence Solutions UG (haftungsbeschränkt)
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
- class pm4py.algo.organizational_mining.sna.variants.pandas.jointactivities.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'#
- RESOURCE_KEY = 'pm4py:param:resource_key'#
- METRIC_NORMALIZATION = 'metric_normalization'#
- pm4py.algo.organizational_mining.sna.variants.pandas.jointactivities.apply(log: DataFrame, parameters: Dict[str | Parameters, Any] | None = None) SNA[source]#
Calculates the Joint Activities / Similar Task metric
Parameters#
- log
Log
- parameters
Possible parameters of the algorithm
Returns#
- tuple
Tuple containing the metric matrix and the resources list. Moreover, last boolean indicates that the metric is directed.
pm4py.algo.organizational_mining.sna.variants.pandas.subcontracting module#
PM4Py – A Process Mining Library for Python
Copyright (C) 2024 Process Intelligence Solutions UG (haftungsbeschränkt)
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
- class pm4py.algo.organizational_mining.sna.variants.pandas.subcontracting.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'#
- RESOURCE_KEY = 'pm4py:param:resource_key'#
- CASE_ID_KEY = 'pm4py:param:case_id_key'#
- N = 'n'#
- pm4py.algo.organizational_mining.sna.variants.pandas.subcontracting.apply(log: DataFrame, parameters: Dict[str | Parameters, Any] | None = None) SNA[source]#
Calculates the Subcontracting metric
Parameters#
- log
Log
- parameters
- Possible parameters of the algorithm:
Parameters.N -> n of the algorithm proposed in the Wil SNA paper
Returns#
- tuple
Tuple containing the metric matrix and the resources list
pm4py.algo.organizational_mining.sna.variants.pandas.working_together module#
PM4Py – A Process Mining Library for Python
Copyright (C) 2024 Process Intelligence Solutions UG (haftungsbeschränkt)
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
- class pm4py.algo.organizational_mining.sna.variants.pandas.working_together.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'#
- RESOURCE_KEY = 'pm4py:param:resource_key'#
- CASE_ID_KEY = 'pm4py:param:case_id_key'#
- METRIC_NORMALIZATION = 'metric_normalization'#
- pm4py.algo.organizational_mining.sna.variants.pandas.working_together.apply(log: DataFrame, parameters: Dict[str | Parameters, Any] | None = None) SNA[source]#
Calculates the Working Together metric
Parameters#
- log
Log
- parameters
Possible parameters of the algorithm
Returns#
- tuple
Tuple containing the metric matrix and the resources list. Moreover, last boolean indicates that the metric is not directed.