Difference between revisions of "Changelog"

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Below you will find the detailed list of changes in every new release.  For a more high level overview see the [[Whats new]] page.
 
Below you will find the detailed list of changes in every new release.  For a more high level overview see the [[Whats new]] page.
  
== 5.0 - Released February 2008 ==
+
== 5.0 - Released April 2008 ==
 
* A major new release with countless fixes, improvements, new sampling and modeling algorithms, and much more.
 
* A major new release with countless fixes, improvements, new sampling and modeling algorithms, and much more.
 
* This release will also see a full rebranding.  From hereon the M3-Toolbox will be known as the '''SUrrogate MOdeling Toolbox''' or '''SUMO Toolbox'''.
 
* This release will also see a full rebranding.  From hereon the M3-Toolbox will be known as the '''SUrrogate MOdeling Toolbox''' or '''SUMO Toolbox'''.

Revision as of 10:51, 8 March 2008

Below you will find the detailed list of changes in every new release. For a more high level overview see the Whats new page.

5.0 - Released April 2008

  • A major new release with countless fixes, improvements, new sampling and modeling algorithms, and much more.
  • This release will also see a full rebranding. From hereon the M3-Toolbox will be known as the SUrrogate MOdeling Toolbox or SUMO Toolbox.

4.2 - Released 18 October 2007

  • Fixed the 'Known bugs' for v4.1 (see Wiki)
  • Simulators can be passed options through an <Options> tag
  • Added a fixed model builder so you can manually force which model parameters to use
  • Removed ProActive dependency for the SGE distributed backend
  • Improved Makefile under unix/linux
  • Data produced by simulators no longer needs to be pre-scaled to [-1 1], this can be done automatically from the simulator configuration file
  • Deprecated the optimization framework. It is currently under re-design and a better, more integrated version, will be released with the next toolbox version.
  • Lots of cleanups, minor bugfixes and small feature enhancements

4.1 - Released 27 July 2007

  • Fixed the 'Known bugs' for v4.0 (see Wiki)
  • Vastly improved test sample distribution if a test set is created on the fly
  • Gradient sample selector now works with complex outputs and has improved neighbourhood selection
  • Speed and usability improvements in the profiler framework
  • Improvements in the profiler DockedView widget (added a right click context menu)
  • Addition of some new examples
  • Added an option (on by default) that selects a certain percentage of the grid sample selector's points randomly, making the algorithm more robust
  • Some cleanups, minor bugfixes and feature enhancements

4.0 - Released 22 June 2007

  • IMPORTANT: the best model score is now 0 instead of 1, this is more intuitive
  • Reworked and improved the model scoring mechanism, now based on a pareto analysis. This makes it possible to combine multpile measures in a sensible way.
  • Added a proof of concept surrogate driven optimization framework. Note this is an initial implementation which works, but don't expect state of the art results.
  • Cleanup and refactoring of the profiler framework
  • The profiling of model parameters has been totally reworked and this can now easily be tracked in a nice GUI widget
  • Cleanup of error function logic so you can now easily use different error functions (relative, RMS, ...) in the measures
  • Improved model plotting
  • Support for the SVMlight library (you must download it yourself in order to use it)
  • Added a MinMax measure which can be used to suppress spikes in rational models
  • Support for extinction prevention in the heterogenetic modeler
  • Fixed warnings (and in some cases errors) when loading models from disk
  • Respect the maximum running time more accurately
  • Many cleanups, minor bugfixes and feature enhancements

3.3 - Released 2 May 2007

  • Fixed incorrect summary at the end of a run
  • Fixed bug due to duplicate sample points
  • Ability to evaluate multiple samples in parallel locally (support for dual/multi-core machines)
  • Speedups when reading in datasets
  • Added 2 new modelbuilders that optimize the parameters using;
    • Pattern Search (requires the Matlab direct search toolbox)
    • Simulated Annealing (requires Matlab v7.4 and the direct search toolbox)
    • The Matlab Optimization Toolbox (includes different gradient based methods like BGFS)
  • A new density based sample selction algorithm (VoronoiSampleSelector)
  • New simulator examples to test with
  • Addition of a profiler to generate levelplots
  • Ability to generate Matlab API documentation using m2html
  • New neural network training algorithms based on Differential Evolution and Particle Swarm Optimization
  • It is now possible to call the toolbox with specific samples/values directly, e.g., go('myConfigFile.xml',xValues,yValues);
  • Many minor bugfixes and feature enhancements

3.2 - Released 9 Mar 2007

  • Many important bugfixes
  • Documentation improvements
  • Fully working support for RBF models
  • New measure profilers that track the errors on measures
  • Many new predefined functions and datasets to test with. We now have over 50 examples!

3.1 - Released 28 Feb 2007

  • Small bugfixes and usability improvements
  • Improved documentation
  • Working implementation of a heterogenous evolutionary modelbuilder
  • More examples

3.0 - Released 14 Feb 2007

  • Availability of pre-built binaries
  • Extensive refactoring and code cleanups
  • Many bugfixes and usability improvements
  • Resilience against simulator crashes
  • Ability to set the maximum running time for one sample evaluation
  • Vastly improved Genetic model builder + a neural network implementation
  • Addition of a RandomModelBuilder to use as a baseline benchmark
  • Possible to add dummy input variables or to model only a subset of the available inputs while clamping others
  • Improved multiple output support
    • outputs can be modeled in parallel
    • each output can be configured separately (eg. per output: model type, accuracy requirements (measure), sample selection algorithm, complex handling flag, etc)
    • mutliple outputs can be combined into one model if the model type supports this
  • Noisy (gaussian, outliers, ...) versions of a given output can be automatically added
  • New and improved directory structure for output data
  • New model types:
    • Kriging (based on the DACE MATLAB Kriging Toolbox by Lophaven, Nielsen and Sondergaard)
    • Splines (based on the MATLAB Splines Toolbox, only for 1D and 2D)
  • Now matlab scripts can be used as datasources (simulators) as well
  • New initial experimental design
    • Based on a dataset
    • Combination of existing designs
    • Based on the complexity of different 1D fits
  • Addition of new datasets and predefined functions as modeling examples

2.0 - Released 15 Nov 2006

  • initial release