pm4py.vis.view_ocdfg#

pm4py.vis.view_ocdfg(ocdfg: Dict[str, Any], annotation: str = 'frequency', act_metric: str = 'events', edge_metric='event_couples', act_threshold: int = 0, edge_threshold: int = 0, performance_aggregation: str = 'mean', format: str = 'png', bgcolor: str = 'white', rankdir: str = 'LR', graph_title: str | None = None, variant_str: str = 'classic')[source]#

Views an OC-DFG (object-centric directly-follows graph).

Parameters:

  • ocdfg – Object-centric directly-follows graph

  • annotation (str) – The annotation to use (“frequency” or “performance”)

  • act_metric (str) – The metric for activities (“events”, “unique_objects”, “total_objects”)

  • edge_metric (str) – The metric for edges (“event_couples”, “unique_objects”, “total_objects”)

  • act_threshold (int) – Threshold on activities frequency (default: 0)

  • edge_threshold (int) – Threshold on edges frequency (default: 0)

  • performance_aggregation (str) – Aggregation measure for performance: mean, median, min, max, sum

  • format (str) – Format of the output (if ‘html’ is provided, GraphvizJS is used)

  • bgcolor (str) – Background color (default: white)

  • rankdir (str) – Graph direction (“LR” or “TB”)

  • graph_title – Title of the visualization (if provided)

  • variant_str (str) – Variant of the visualization (“classic” or “elkjs”)

import pm4py

ocdfg = pm4py.discover_ocdfg(ocel)
pm4py.view_ocdfg(ocdfg, annotation='frequency', format='svg')
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