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]].
 +
 +
== Version 6.2 ==
 +
 +
 +
{| border="0" style="text-align:left"
 +
|-
 +
!'''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: <source lang="matlab">dtot(:,k) = (sum(d,1) ./ numTp) + dtot(:,k);</source>
 +
|-
 +
|}
 +
 +
 +
== Version 6.1.1 ==
 +
 +
 +
{| border="0" style="text-align:left"
 +
|-
 +
!'''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 ==
 +
 +
{| border="0" style="text-align:left"
 +
|-
 +
!'''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 <source lang="bash">'model.implementation=''CFILE''</source> with the text <source lang="bash">'model.implementation=''MATLAB''</source>
 +
|-
 +
|}
 +
  
  
−
== Version 5.0 ==
 
 
{| border="0" style="text-align:left"
 
{| border="0" style="text-align:left"
 
|-
 
|-
 
!'''Bug'''
 
!'''Bug'''
−
| Consecutive runs on the same dataset are not independent (can cause dataset depleted exceptions)
+
| The ParetoModelBuilder can crash with "unknown function createModelFromIndividual()".
 
|-
 
|-
 
!'''Status'''  
 
!'''Status'''  
−
| Fixed in SVN.
+
| Fixed in next version
 
|-
 
|-
 
!'''Workaround'''  
 
!'''Workaround'''  
−
| Wait for next release.
+
| 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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|-
 
|-
 
!'''Bug'''
 
!'''Bug'''
−
| Duplicate samples and samples with NaN/Inf values are not filtered properly.
+
| When building models multi-objectively the toolbox uses a lot of diskspace and signals a lot of new best models
 
|-
 
|-
 
!'''Status'''  
 
!'''Status'''  
−
| Fixed in SVN.
+
| Fixed in next version
 
|-
 
|-
 
!'''Workaround'''  
 
!'''Workaround'''  
−
| Wait for next release. Simulators that may return invalid values or duplicate samples should be avoided until then.
+
| Remove in modelbuilders/@AdaptiveModelbuilder/private/orderBestModels.m, the condition "length(s.bestModels) == 1" so the if looks like "if ( oldBestModelId ~= newBestModelId )"
 
|-
 
|-
 
|}
 
|}
  
 +
 +
<!--
 +
 +
== Version 6.0.1 ==
  
 
{| border="0" style="text-align:left"
 
{| border="0" style="text-align:left"
 
|-
 
|-
 
!'''Bug'''
 
!'''Bug'''
−
| You get the following error: "Failed to create object of type ANNGeneticInterface, error is "Undefined variable "logger" or class "logger.severe"
+
| 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.
 
|-
 
|-
 
!'''Status'''  
 
!'''Status'''  
−
| Fixed in SVN.
+
| Fixed in next version
 
|-
 
|-
 
!'''Workaround'''  
 
!'''Workaround'''  
−
| Simply remove the offending line or set complex handling to split or modulus (you are trying to model complex data with ANNs).
+
| Please wait for release
 
|-
 
|-
 
|}
 
|}
  
−
== Version 4.2 ==
+
== Version 6.0 ==
 +
 
 
{| border="0" style="text-align:left"
 
{| border="0" style="text-align:left"
 
|-
 
|-
 
!'''Bug'''
 
!'''Bug'''
−
| Loading the random state from file gives a directory does not exist error.
+
| You get an error like "No appropriate method or public field isProjectMode for class ibbt.sumo.config.ContextConfig"
 
|-
 
|-
 
!'''Status'''  
 
!'''Status'''  
−
| Fixed in SVN.
+
| Fixed in 6.0.1
 
|-
 
|-
 
!'''Workaround'''  
 
!'''Workaround'''  
−
| Upgrade to the next version.
+
| Please upgrade to 6.0.1
 
|-
 
|-
 
|}
 
|}
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|-
 
|-
 
!'''Bug'''
 
!'''Bug'''
−
| When starting the toolbox for the first time you get an error like "The class ContextConfig cannot be found, make sure java is running"
+
| The Kriging models do not work with combineOutputs=true in some cases
 
|-
 
|-
 
!'''Status'''  
 
!'''Status'''  
−
| Fixed in SVN.
+
| Fixed in SVN
 
|-
 
|-
 
!'''Workaround'''  
 
!'''Workaround'''  
−
| This is a bug in Matlab itself. Please [[contact]] us for instructions on how to fix this.
+
| Please upgrade to 6.0.1
 
|-
 
|-
 
|}
 
|}
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|-
 
|-
 
!'''Bug'''
 
!'''Bug'''
−
| When starting the toolbox for the first time you get an error like "The class be.ac.ua.coms.m3.config.Util has no field or method named genHash"
+
| The automatic model type selection algorithm (heterogeneous evolution) does not work with Matlab 2008a and later
 
|-
 
|-
 
!'''Status'''  
 
!'''Status'''  
−
| Fixed in SVN.
+
| Fixed in SVN
 
|-
 
|-
 
!'''Workaround'''  
 
!'''Workaround'''  
−
| This is a bug in Matlab itself. Please [[contact]] us for instructions on how to fix this.
+
| Use an older Matlab version (e.g., 2007a)
 
|-
 
|-
 
|}
 
|}
  
 +
== Version 5.0 ==
 +
 +
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.
  
 
{| border="0" style="text-align:left"
 
{| border="0" style="text-align:left"
 
|-
 
|-
 
!'''Bug'''
 
!'''Bug'''
−
| When the TestSamples measure is used without a dataset the testset is not calculated correctly!!
+
| Consecutive runs on the same dataset are not independent (can cause dataset depleted exceptions)
 
|-
 
|-
 
!'''Status'''  
 
!'''Status'''  
Line 100: Line 156:
 
|-
 
|-
 
!'''Workaround'''  
 
!'''Workaround'''  
−
| Replace the line 'tmp(testSet,:) = [];' by 'tmp(testSet,:) = NaN;'
+
| Wait for next release.
 
|-
 
|-
 
|}
 
|}
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|-
 
|-
 
!'''Bug'''
 
!'''Bug'''
−
| The optimization framework may fail in specific circumstances
+
| Duplicate samples and samples with NaN/Inf values are not filtered properly (for example you get Matrix dimension mismatch errors).
 
|-
 
|-
 
!'''Status'''  
 
!'''Status'''  
−
| The framework is currently under redesign and a much improved, more robust, version will be released with 5.0
+
| Fixed in SVN.
 
|-
 
|-
 
!'''Workaround'''  
 
!'''Workaround'''  
−
| Upgrade to 5.0 when it becomes available.
+
| Wait for next release or simply disable the relevant code. Simulators that may return invalid values or duplicate samples should be avoided until then.
 
|-
 
|-
 
|}
 
|}
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|-
 
|-
 
!'''Bug'''
 
!'''Bug'''
−
| The BatchModelBuilder fails with an error
+
| You get the following error: "Failed to create object of type ANNGeneticInterface, error is "Undefined variable "logger" or class "logger.severe"
 
|-
 
|-
 
!'''Status'''  
 
!'''Status'''  
−
| Fixed in SVN
+
| Fixed in SVN.
 
|-
 
|-
 
!'''Workaround'''  
 
!'''Workaround'''  
−
| Simply remove the offending line
+
| Simply remove the offending line or set complex handling to split or modulus (you are trying to model complex data with ANNs).
 
|-
 
|-
 
|}
 
|}
 +
 +
-->

Latest revision as of 14:25, 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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