Difference between revisions of "Known bugs"

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If you happen to encounter something not listed here, please [[reporting problems|report it]].
 
If you happen to encounter something not listed here, please [[reporting problems|report it]].
  
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== Version 6.2 ==
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{| border="0" style="text-align:left"
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|-
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!'''Bug'''
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| There is a small error in LRMMeasure that slows the modeling process if LRM is used together with another measure.
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|-
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!'''Status'''
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| Fixed in next version
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|-
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!'''Workaround'''
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| In src/matlab/measures/@LRMMeasure/calculateMeasure.m, replace line 204 by: <source lang="matlab">dtot(:,k) = (sum(d,1) ./ numTp) + dtot(:,k);</source>
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|-
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|}
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== Version 6.1.1 ==
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{| border="0" style="text-align:left"
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|-
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!'''Bug'''
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| When modeling complex data, depending on the measure/error function used, the model generation process my be sub-optimal in some cases
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|-
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!'''Status'''
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| Fixed in next version
 +
|-
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!'''Workaround'''
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| Execute the error function you use (default = beeq) with a couple of complex numbers.  The result must be a real number (non-complex).  If this is not the case, fix the function (or ask us to send you a new one) or use a different function (also make sure to test it).
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|-
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|}
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== Version 6.1 ==
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{| border="0" style="text-align:left"
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|-
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!'''Bug'''
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| When using the LS-SVM models and you have not compiled the mex files the toolbox crashes with "Too many open files".
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|-
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!'''Status'''
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| Fixed in next version
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|-
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!'''Workaround'''
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| In /src/matlab/contrib/LS-SVMlab/trainlssvm.m replace on line 259 the text <source lang="bash">'model.implementation=''CFILE''</source> with the text <source lang="bash">'model.implementation=''MATLAB''</source>
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|-
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|}
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{| border="0" style="text-align:left"
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|-
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!'''Bug'''
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| The ParetoModelBuilder can crash with "unknown function createModelFromIndividual()".
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|-
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!'''Status'''
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| Fixed in next version
 +
|-
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!'''Workaround'''
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| Replace the offending line (line 70 in modelbuilders/@ParetoModelbuilder/runLoop.m) with: "model = createModel(getModelFactory(s), populationEntry);".  Make also sure that you have set the option ''paretoMode="true"''.
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|-
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|}
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{| border="0" style="text-align:left"
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|-
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!'''Bug'''
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| When building models multi-objectively the toolbox uses a lot of diskspace and signals a lot of new best models
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|-
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!'''Status'''
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| Fixed in next version
 +
|-
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!'''Workaround'''
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| Remove in modelbuilders/@AdaptiveModelbuilder/private/orderBestModels.m, the condition "length(s.bestModels) == 1" so the if looks like "if ( oldBestModelId ~= newBestModelId )"
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|-
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|}
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 +
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<!--
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== Version 6.0.1 ==
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{| border="0" style="text-align:left"
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|-
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!'''Bug'''
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| getExpression does not work for rational models with complex outputs. It produces output different from evaluate, and evaluate is the one producing the correct output.
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|-
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!'''Status'''
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| Fixed in next version
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|-
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!'''Workaround'''
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| Please wait for release
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|-
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|}
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== Version 6.0 ==
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{| border="0" style="text-align:left"
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|-
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!'''Bug'''
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| You get an error like "No appropriate method or public field isProjectMode for class ibbt.sumo.config.ContextConfig"
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|-
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!'''Status'''
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| Fixed in 6.0.1
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|-
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!'''Workaround'''
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| Please upgrade to 6.0.1
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|-
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|}
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 +
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{| border="0" style="text-align:left"
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|-
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!'''Bug'''
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| The Kriging models do not work with combineOutputs=true in some cases
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|-
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!'''Status'''
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| Fixed in SVN
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|-
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!'''Workaround'''
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| Please upgrade to 6.0.1
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|-
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|}
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 +
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{| border="0" style="text-align:left"
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|-
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!'''Bug'''
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| The automatic model type selection algorithm (heterogeneous evolution) does not work with Matlab 2008a and later
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|-
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!'''Status'''
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| Fixed in SVN
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|-
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!'''Workaround'''
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| Use an older Matlab version (e.g., 2007a)
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|-
 +
|}
  
 
== Version 5.0 ==
 
== Version 5.0 ==
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 +
We have found some important bugs in 5.0 that affect various parts of the model generation process. This could mean (in some cases) that the final models you get are not really as good as they could be.  This has been fixed in 6.0 and we are working hard to release it as soon as possible.
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Latest revision as of 13:25, 8 October 2009

While we always try to test each release as much as we can, inevitably some bugs will always slip through unnoticed. This page only shows the most important bugs that have surfaced after the release was made.

To stay up to date with the latest news and releases, we also recommend subscribing to our newsletter here. Traffic will be kept to a minimum and you can unsubscribe at any time.

If you happen to encounter something not listed here, please report it.

Version 6.2

Bug There is a small error in LRMMeasure that slows the modeling process if LRM is used together with another measure.
Status Fixed in next version
Workaround In src/matlab/measures/@LRMMeasure/calculateMeasure.m, replace line 204 by: 
dtot(:,k) = (sum(d,1) ./ numTp) + dtot(:,k);


Version 6.1.1

Bug When modeling complex data, depending on the measure/error function used, the model generation process my be sub-optimal in some cases
Status Fixed in next version
Workaround Execute the error function you use (default = beeq) with a couple of complex numbers. The result must be a real number (non-complex). If this is not the case, fix the function (or ask us to send you a new one) or use a different function (also make sure to test it).

Version 6.1

Bug When using the LS-SVM models and you have not compiled the mex files the toolbox crashes with "Too many open files".
Status Fixed in next version
Workaround In /src/matlab/contrib/LS-SVMlab/trainlssvm.m replace on line 259 the text 
'model.implementation=''CFILE''
with the text 
'model.implementation=''MATLAB''


Bug The ParetoModelBuilder can crash with "unknown function createModelFromIndividual()".
Status Fixed in next version
Workaround Replace the offending line (line 70 in modelbuilders/@ParetoModelbuilder/runLoop.m) with: "model = createModel(getModelFactory(s), populationEntry);". Make also sure that you have set the option paretoMode="true".


Bug When building models multi-objectively the toolbox uses a lot of diskspace and signals a lot of new best models
Status Fixed in next version
Workaround Remove in modelbuilders/@AdaptiveModelbuilder/private/orderBestModels.m, the condition "length(s.bestModels) == 1" so the if looks like "if ( oldBestModelId ~= newBestModelId )"


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