pm4py.visualization.sna package

Submodules

pm4py.visualization.sna.visualizer module

class pm4py.visualization.sna.visualizer.Variants(value)[source]

Bases: enum.Enum

An enumeration.

NETWORKX = <module 'pm4py.visualization.sna.variants.networkx' from 'C:\\Users\\berti\\FRAUNHOFER\\pm4py-core\\pm4py\\visualization\\sna\\variants\\networkx.py'>
PYVIS = <module 'pm4py.visualization.sna.variants.pyvis' from 'C:\\Users\\berti\\FRAUNHOFER\\pm4py-core\\pm4py\\visualization\\sna\\variants\\pyvis.py'>
pm4py.visualization.sna.visualizer.apply(metric_values, parameters=None, variant=<Variants.NETWORKX: <module 'pm4py.visualization.sna.variants.networkx' from 'C:\\Users\\berti\\FRAUNHOFER\\pm4py-core\\pm4py\\visualization\\sna\\variants\\networkx.py'>>)[source]

Perform SNA visualization starting from the Matrix Container object and the Resource-Resource matrix

Parameters
  • metric_values – Value of the metrics

  • parameters – Possible parameters of the algorithm

  • variant

    Variant of the algorithm to use, possible values:
    • Variants.NETWORKX

    • Variants.PYVIS

Returns

Name of a temporary file where the visualization is placed

Return type

temp_file_name

pm4py.visualization.sna.visualizer.save(temp_file_name, dest_file, parameters=None, variant=<Variants.NETWORKX: <module 'pm4py.visualization.sna.variants.networkx' from 'C:\\Users\\berti\\FRAUNHOFER\\pm4py-core\\pm4py\\visualization\\sna\\variants\\networkx.py'>>)[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

pm4py.visualization.sna.visualizer.view(temp_file_name, parameters=None, variant=<Variants.NETWORKX: <module 'pm4py.visualization.sna.variants.networkx' from 'C:\\Users\\berti\\FRAUNHOFER\\pm4py-core\\pm4py\\visualization\\sna\\variants\\networkx.py'>>)[source]

View the SNA visualization on the screen

Parameters
  • temp_file_name – Temporary file name

  • parameters – Possible parameters of the algorithm

Module contents