Changelog

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

• 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