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LPSolve issue when calling Evolutionary Tree Miner
Hi,
I am experiencing an issue regarding the LPSolve library files while trying to call the Evolutionary Tree Miner from my plugin using the default parameters. As soon as I start executing the plugin, I get this message from the Eclipse console that keeps being printed in an endless loop: Successfully loaded bfp_etaPFI file. The status of the execution does not change or progress beyond this point. I know this file is part of the LPSolve library which I assume it's being used from the ETM. Has anyone experienced this?
I am using Windows 10, ProM 6.9, JRE 8, LP Solve 5.5.4 and Eclipse version 2020-06. Here is the code that I am running regarding the ETM:
I am experiencing an issue regarding the LPSolve library files while trying to call the Evolutionary Tree Miner from my plugin using the default parameters. As soon as I start executing the plugin, I get this message from the Eclipse console that keeps being printed in an endless loop: Successfully loaded bfp_etaPFI file. The status of the execution does not change or progress beyond this point. I know this file is part of the LPSolve library which I assume it's being used from the ETM. Has anyone experienced this?
I am using Windows 10, ProM 6.9, JRE 8, LP Solve 5.5.4 and Eclipse version 2020-06. Here is the code that I am running regarding the ETM:
public Petrinet applyETM(PluginContext context, XLog log) throws ConnectionCannotBeObtained { | |
ETMParam param = ETMParamFactory.buildStandardParam(log); | |
ETM etm = new ETM(param); | |
etm.run(); | |
NAryTree tree = etm.getResult(); | |
ProcessTree processTree = NAryTreeToProcessTree.convert(tree, param.getCentralRegistry().getEventClasses()); | |
PetrinetWithMarkings petrinetwithmarkings = null; | |
try { | |
petrinetwithmarkings = ProcessTree2Petrinet.convert(processTree); | |
} catch (NotYetImplementedException e) { | |
e.printStackTrace(); | |
} catch (InvalidProcessTreeException e) { | |
e.printStackTrace(); | |
} | |
return petrinetwithmarkings.petrinet; | |
} | |
Appreciate any ideas or recommendations! Thanks, Nina |
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