pm4py.visualization.ocel.ocdfg.variants.elkjs module#

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class pm4py.visualization.ocel.ocdfg.variants.elkjs.Parameters(*values)[source]#

Bases: Enum

ENCODING = 'encoding'#
IFRAME_WIDTH = 'iframe_width'#
IFRAME_HEIGHT = 'iframe_height'#
LOCAL_JUPYTER_FILE_NAME = 'local_jupyter_file_name'#
PERFORMANCE_AGGREGATION_MEASURE = 'aggregationMeasure'#
ANNOTATION = 'annotation'#
ACT_METRIC = 'act_metric'#
EDGE_METRIC = 'edge_metric'#
ACT_THRESHOLD = 'act_threshold'#
EDGE_THRESHOLD = 'edge_threshold'#
pm4py.visualization.ocel.ocdfg.variants.elkjs.wrap_text(text: str, max_length: int = 15) → str[source]#
pm4py.visualization.ocel.ocdfg.variants.elkjs.get_html_file_contents()[source]#
pm4py.visualization.ocel.ocdfg.variants.elkjs.apply(ocdfg: Dict[str, Any], parameters: Dict[Any, Any] | None = None) → str[source]#

Visualizes an OC-DFG using ELK.JS.

Parameters:

  • ocdfg – OC-DFG

  • parameters – Parameters of the algorithm:

    • Parameters.ACT_METRIC => the metric to use for the activities. Available values:

      • “events” => number of events (default)

      • “unique_objects” => number of unique objects

      • “total_objects” => number of total objects

    • Parameters.EDGE_METRIC => the metric to use for the edges. Available values:

      • “event_couples” => number of event couples (default)

      • “unique_objects” => number of unique objects

      • “total_objects” => number of total objects

    • Parameters.ANNOTATION => the annotation to use for the visualization. Values:

      • “frequency”: frequency annotation

      • “performance”: performance annotation

    • Parameters.PERFORMANCE_AGGREGATION_MEASURE => the aggregation measure to use for the performance:

      • mean

      • median

      • min

      • max

      • sum

Returns:

Visualization file

Return type:

viz

pm4py.visualization.ocel.ocdfg.variants.elkjs.view(temp_file_name, parameters=None)[source]#

View the SNA visualization on the screen

Parameters:

  • temp_file_name – Temporary file name

  • parameters – Possible parameters of the algorithm

pm4py.visualization.ocel.ocdfg.variants.elkjs.save(temp_file_name, dest_file, parameters=None)[source]#

Save the SNA visualization from a temporary file to a well-defined destination file

Parameters:

  • temp_file_name – Temporary file name

  • dest_file – Destination file

  • parameters – Possible parameters of the algorithm