pm4py.algo.filtering.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.filtering.dfg.dfg_filtering 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

pm4py.algo.filtering.dfg.dfg_filtering.generate_nx_graph_from_dfg(dfg, start_activities, end_activities, activities_count)[source]#

Generate a NetworkX graph for reachability-checking purposes out of the DFG

Parameters#

dfg: DFG
start_activities: Start activities
end_activities: End activities
activities_count: Activities of the DFG along with their count

Returns#

G: NetworkX digraph
start_node: Identifier of the start node (connected to all the start activities)
end_node: Identifier of the end node (connected to all the end activities)

pm4py.algo.filtering.dfg.dfg_filtering.filter_dfg_on_activities_percentage(dfg0, start_activities0, end_activities0, activities_count0, percentage)[source]#

Filters a DFG (complete, and so connected) on the specified percentage of activities (but ensuring that every node is still reachable from the start and to the end)

Parameters#

dfg0: (Complete, and so connected) DFG
start_activities0: Start activities
end_activities0: End activities
activities_count0: Activities of the DFG along with their count
percentage: Percentage of activities

Returns#

dfg: (Filtered) DFG
start_activities: (Filtered) start activities
end_activities: (Filtered) end activities
activities_count: (Filtered) activities of the DFG along with their count

pm4py.algo.filtering.dfg.dfg_filtering.filter_dfg_on_paths_percentage(dfg0, start_activities0, end_activities0, activities_count0, percentage, keep_all_activities=False)[source]#

Filters a DFG (complete, and so connected) on the specified percentage of paths (but ensuring that every node is still reachable from the start and to the end)

Parameters#

dfg0: (Complete, and so connected) DFG
start_activities0: Start activities
end_activities0: End activities
activities_count0: Activities of the DFG along with their count
percentage: Percentage of paths
keep_all_activities: Decides if all the activities (also the ones connected by the low occurrences edges) should be kept, or only the ones appearing in the edges with more occurrences (default).

Returns#

dfg: (Filtered) DFG
start_activities: (Filtered) start activities
end_activities: (Filtered) end activities
activities_count: (Filtered) activities of the DFG along with their count

pm4py.algo.filtering.dfg.dfg_filtering.filter_dfg_keep_connected(dfg0, start_activities0, end_activities0, activities_count0, threshold, keep_all_activities=False)[source]#

Filters a DFG (complete, and so connected) on the specified dependency threshold (Heuristics Miner dependency) (but ensuring that every node is still reachable from the start and to the end)

Parameters#

dfg0: (Complete, and so connected) DFG
start_activities0: Start activities
end_activities0: End activities
activities_count0: Activities of the DFG along with their count
threshold: Dependency threshold as in the Heuristics Miner
keep_all_activities: Decides if all the activities should be kept, or only the ones appearing in the edges with higher threshold (default).

Returns#

dfg: (Filtered) DFG
start_activities: (Filtered) start activities
end_activities: (Filtered) end activities
activities_count: (Filtered) activities of the DFG along with their count

pm4py.algo.filtering.dfg.dfg_filtering.filter_dfg_to_activity(dfg0, start_activities0, end_activities0, activities_count0, target_activity, parameters=None)[source]#

Filters the DFG, making “target_activity” the only possible end activity of the graph

Parameters#

dfg0: Directly-follows graph
start_activities0: Start activities
end_activities0: End activities
activities_count0: Activities count
target_activity: Target activity (only possible end activity after the filtering)
parameters: Parameters

Returns#

dfg: Filtered DFG
start_activities: Filtered start activities
end_activities: Filtered end activities
activities_count: Filtered activities count

pm4py.algo.filtering.dfg.dfg_filtering.filter_dfg_from_activity(dfg0, start_activities0, end_activities0, activities_count0, source_activity, parameters=None)[source]#

Filters the DFG, making “source_activity” the only possible source activity of the graph

Parameters#

dfg0: Directly-follows graph
start_activities0: Start activities
end_activities0: End activities
activities_count0: Activities count
source_activity: Source activity (only possible start activity after the filtering)
parameters: Parameters

Returns#

dfg: Filtered DFG
start_activities: Filtered start activities
end_activities: Filtered end activities
activities_count: Filtered activities count

pm4py.algo.filtering.dfg.dfg_filtering.filter_dfg_contain_activity(dfg0, start_activities0, end_activities0, activities_count0, activity, parameters=None)[source]#

Filters the DFG keeping only nodes that can reach / are reachable from activity

Parameters#

dfg0: Directly-follows graph
start_activities0: Start activities
end_activities0: End activities
activities_count0: Activities count
activity: Activity that should be reachable / should reach all the nodes of the filtered graph
parameters: Parameters

Returns#

dfg: Filtered DFG
start_activities: Filtered start activities
end_activities: Filtered end activities
activities_count: Filtered activities count

pm4py.algo.filtering.dfg.dfg_filtering.clean_dfg_based_on_noise_thresh(dfg, activities, noise_threshold, parameters=None)[source]#

Clean Directly-Follows graph based on noise threshold

Parameters#

dfg: Directly-Follows graph
activities: Activities in the DFG graph
noise_threshold: Noise threshold

Returns#

newDfg: Cleaned dfg based on noise threshold