Lucio Nardelli - Director Hernán Ponce de León
Parse logs (as .xes or .txt Files) and calculate the minimum convex hull using Pyhull (https://pythonhosted.org/pyhull) of the Parikh's vector of the the events in the traces.
We use two different high-level techniques to handle large logs: projection and sampling
After getting the convex hull, some automatic simplifications are made in order to get a "nicer" model.
As a final step, the resulting PNML is generated according to the international standard.
In order to use it, some requirements are that must be met. It can be done via Pip:
pip install -r requirements.txt
or see the file requirements.txt for an exhaustive list or dependencies.
Used for parsing the log file and get the Parikh's vector representation of the traces.
Usage:
./parser.py <LOG filename> [--verbose]
If --verbose is no used, just a summary is printed. Otherwise a full representation of the traces will we printed to the standard output.
Similar to the previous, but only the full trace is converted to a Parikh's vector, not the prefixes.
Usage:
./negative_parser.py <negative XES LOG filename> [--verbose]
Search, representation and simplification of a Convex Hull. Points can be a list of lists or a file with the list of lists as the first line of it.
Usage:
Usage: ./qhull.py <points> [--debug][--verbose]
A wrap up of the elements necessary for:
- Parsing
- Getting the convex hull
- Applying the automatic simplifications w.r.t. the negative traces -Generation of the Petri Net according to the Petri Net Markup Language (PNML http://www.pnml.org/)
- Generation of an output file of performance statistics.
Usage:
Usage: ./pach.py <LOG_filename> [--debug][--verbose]
[--negative <Negative points filename>] [max_coefficient]]
[--sampling [<number of samplings>] [<sampling size>]]
[--projection [<max group size>] [<connected model>]]
[--smt-matrix [<timeout>]]
[--smt-iter [<timeout>]]
[--sanity-check]
Arguments:
- LOG_filename : The file where the positive log is
--debug: Open a Python Debugger just before calling PacH--verbose: Verbose mode.--negative- Negative_points_filename>
[max_coefficient]: Optional argument. Only try to remove facets with at least one coefficient bigger than max_coefficient.
--sampling: Whether to do sampling or notnumber of samplings: Number of samples to getsampling size: The size of each sample
--projection: Whether to do projection or not[max group size]: Maximum number of dimension in each cluster[connected model]: Whether to connect the cluster or not
--smt-matrix: Matrix simplification of all the equations system at once[timeout]: Optional argument to set a timeout for SMT simplification
--smt-iter: SMT simplification to each individual facet of the convex hull[timeout]: Optional argument to set a timeout for SMT simplification
--sanity-check: Perform some sanity check after each new hull.
Output:
The program will generate two files.
- PNML representation of the simplified convex hull.
- A file with a summary and performance details
- Example of output file:
Statistic of {positive}: with negative traces from {negative}
benchmark -> {benchmark }
positive -> {positive traces file}
dimension -> {dimension}
traces -> {positive traces}
events -> {total events found in positive traces}
negative -> {negative traces file}
complexity -> {complexity of the model}
exec_time -> {execution time}
overall_time -> {overall time}
details
parse_traces -> {time parsing traces}
parse_negatives -> {time parsing negatives}
do_sampling -> {time doing sampling}
do_projection -> {time doing projection}
convexHull -> {time computing hyperspaces}
shift&rotate -> {time simplifying hull with SMT} OR {Time simplifying each facet with SMT}
simplify -> {Time spent simplifying without SMT}
Tool to compare all 3 simplifications (Polyhedra, STM-Matrix, SMT-Iterative) w.r.t. a unique convex hull representation.
Usage:
Usage: ./comparator_xes.py <LOG filename> [--debug]
[--negative <Negative points filename>] [max_coefficient]]
[--sampling [<number of samplings>] [<sampling size>]]
[--projection [<max group size>] [<connected model>]]
[--smt-matrix [<timeout>]]
[--smt-iter [<timeout>]]
If using config file, this are the options
samp_num : Number of samples to take (Default no sample, use all elements)
nfilename : Negative traces file location
max_coef : Maximum allowed in halfspaces. If no coefficient is bigger than this, won't try to simplify
proj_size : Number for maximum dimension to project to (Default no projection, 0 for no limit)
proj_connected : Boolean indicating whether to (try to) connect clusters (default: True)
smt_timeout_matrix : Timeout for smt solution finding when simplifying all hull at once
samp_size : Number of elements to take on each sample (No default)
sanity_check : Performs sanity check that all traces are inside hull
smt_timeout_iter : Timeout for smt solution finding when simplifying one halfspace at the time
filename : Location of .xes file with traces or .pnml file with Petri net model
Arguments:
Analogous to the ones of pach.py.
Tool to compare all 3 simplifications (Polyhedra, STM-Matrix, SMT-Iterative) applied to ProM/ILPMiner output.
Usage:
Usage: ./comparator_pnml.py <PNML filename> [--debug]
[--negative <Negative XES points filename>] [max_coefficient]]
[--smt-matrix [<timeout>]]
[--smt-iter [<timeout>]]
If using config file, this are the options
samp_num : Number of samples to take (Default no sample, use all elements)
nfilename : Negative traces file location
max_coef : Maximum allowed in halfspaces. If no coefficient is bigger than this, won't try to simplify
proj_size : Number for maximum dimension to project to (Default no projection, 0 for no limit)
proj_connected : Boolean indicating whether to (try to) connect clusters (default: True)
smt_timeout_matrix : Timeout for smt solution finding when simplifying all hull at once
samp_size : Number of elements to take on each sample (No default)
sanity_check : Performs sanity check that all traces are inside hull
smt_timeout_iter : Timeout for smt solution finding when simplifying one halfspace at the time
filename : Location of .xes file with traces or .pnml file with Petri net model
Arguments:
Analogous to the ones of pach.py.