Process tree and log generator

Provides scripts to generate random process trees and simulate these trees into event logs.

Detailed information on the workings of the generator and simulator can be found in the paper: Jouck, Toon, and Benoît Depaire. “PTandLogGenerator: A Generator for Artificial Event Data.” In Proceedings of the BPM Demo Track 2016 (BPMD 2016), 1789:23–27. Rio de Janeiro: CEUR workshop proceedings, 2016. http://ceur-ws.org/Vol-1789/.

Process tree generator

• Input: parameter file for populations (example parameter file located in the '/data/parameter_files' folder).
  Each line of the csv-file characterizes one population: mode;min;max;sequence;choice;parallel;loop;or;silent;duplicate;lt_dependency;infrequent;no_models;unfold;max_repeat

  • mode: most frequent number of visible activities
  • min: minimum number of visible activities
  • max: maximum number of visible activities
  • sequence: probability to add a sequence operator to tree
  • choice: probability to add a choice operator to tree
  • parallel: probability to add a parallel operator to tree
  • loop: probability to add a loop operator to tree
  • or: probability to add an or operator to tree
  • silent: probability to add silent activity to a choice or loop operator
  • duplicate: probability to duplicate an activity label
  • lt_dependency: probability to add a random dependency to the tree
  • infrequent: probability to make a choice have infrequent paths
  • no_models: number of trees to generate from model population
  • unfold: whether or not to unfold loops in order to include choices underneath in dependencies: 0=False, 1=True
    • if lt_dependency <= 0: this should always be 0 (False)
    • if lt_dependency > 0: this can be 1 or 0 (True or False)
  • max_repeat: maximum number of repetitions of a loop (only used when unfolding is True)

• Output: collection of process trees in the 'data/trees' folder:

  • newick tree format (*.nw)
  • process tree markup language (*.ptml)
  • (optional) image file (*.png)

• Usage: callable from command line:
  $python generate_newick_trees.py [-h] [--t [timeout]] [--g [graphviz]] input

  Generate process trees from input population.

  positional arguments:
  input: input csv-formatted file in which the population parameters are specified, example: ../data/parameter_files/example_parameters.csv

  optional arguments:
  -h, --help : show this help message and exit
  --t abort tree generation after timeout seconds, default=10000
  --g indicate whether to render graphviz image of tree, default=False

Log simulator

• Input:

  • process trees in newick tree files
  • size: the number of traces in the event log
  • noise: the probability of inserting noise
  • timestamps: include timestamps (start and end for each activity?)

• Output: event log in XES format (default) or csv-file format 'case_id', 'act_name'[,'start_time','end_time']

• Usage: callable from command line
  call plugin: $python generate_logs.py [-h] [--i [input_folder]] [--t [timestamps]] [--f [format]] size noise

  Simulate event logs from process trees.

  positional arguments:
  size: number of traces to simulate
  noise: probability to insert noise into trace

  optional arguments:
  -h, --help : show this help message and exit
  --i [input_folder] : specify the relative address to the trees folder, default=../data/trees/
  --t [timestamps] : indicate whether to include timestamps or not, default=False
  --f [format] : indicate which format to use for the log: xes or csv, default=xes

DataExtend

• Input:
  • a sample of process trees (default folder: ../data/trees/)
  • a target determinism level
  • a maximum number of input nodes (of each decision)
  • a maximum number of intervals (to discretize numerical value)
  • a number of cases to generate in each log

*Output: a sample of event logs with case attributes

*Usage: run the generate_data_trees_and_logs.py and adapt the parameters