pm4py.statistics.attributes.common 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.statistics.attributes.common.get 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.statistics.attributes.common.get.Parameters(value, names=<not given>, *values, module=None, qualname=None, type=None, start=1, boundary=None)[source]#
Bases:
Enum- GRAPH_POINTS = 'graph_points'#
- POINT_TO_SAMPLE = 'points_to_sample'#
- pm4py.statistics.attributes.common.get.get_sorted_attributes_list(attributes)[source]#
Gets sorted attributes list
Parameters#
- attributes
Dictionary of attributes associated with their count
Returns#
- listact
Sorted end attributes list
- pm4py.statistics.attributes.common.get.get_attributes_threshold(alist, decreasing_factor, min_activity_count=1, max_activity_count=25)[source]#
Get attributes cutting threshold
Parameters#
- alist
Sorted attributes list
- decreasing_factor
Decreasing factor of the algorithm
- min_activity_count
Minimum number of activities to include
- max_activity_count
Maximum number of activities to include
Returns#
- threshold
Activities cutting threshold
- pm4py.statistics.attributes.common.get.get_kde_numeric_attribute(values, parameters=None)[source]#
Gets the KDE estimation for the distribution of a numeric attribute values
Parameters#
- values
Values of the numeric attribute value
- parameters
- Possible parameters of the algorithm, including:
graph_points -> number of points to include in the graph
Returns#
- x
X-axis values to represent
- y
Y-axis values to represent
- pm4py.statistics.attributes.common.get.get_kde_numeric_attribute_json(values, parameters=None)[source]#
Gets the KDE estimation for the distribution of a numeric attribute values (expressed as JSON)
Parameters#
- values
Values of the numeric attribute value
- parameters
- Possible parameters of the algorithm, including:
graph_points: number of points to include in the graph
Returns#
- json
JSON representing the graph points
- pm4py.statistics.attributes.common.get.get_kde_date_attribute(values, parameters=None)[source]#
Gets the KDE estimation for the distribution of a date attribute values
Parameters#
- values
Values of the date attribute value
- parameters
- Possible parameters of the algorithm, including:
graph_points -> number of points to include in the graph
Returns#
- x
X-axis values to represent
- y
Y-axis values to represent
- pm4py.statistics.attributes.common.get.get_kde_date_attribute_json(values, parameters=None)[source]#
Gets the KDE estimation for the distribution of a date attribute values (expressed as JSON)
Parameters#
- values
Values of the date attribute value
- parameters
- Possible parameters of the algorithm, including:
graph_points: number of points to include in the graph
Returns#
- json
JSON representing the graph points