aGrUM/pyAgrum 0.22.9 released

ANNOUNCE: aGrUM 0.22.9

aGrUM/pyAgrum 0.22.9 is out.

Changelog for 0.22.9

This tag is a pre-relase for 1.0.0 (!).

• aGrUM

  • Added a new Multithreaded facility which supports easily both openMP and STL.
  • Enabled exceptions raised by threads to be catched.
  • Made gum::CredalNetworks and gum::learning::BNLearner use the new multithreading facility.
  • Made a fully new architecture for scheduling inferences.
  • Added a sequential and a parallel schedulers for inferences.
  • Enabled gum::LazyPropagation and gum::ShaferShenoy to use schedulers for their inferences.
  • gum::DiscretizedVariable can now be declared as "empirical". Meaning that the lower and upper ticks are not always hard limits.
  • improve a bit API for gum::IntegerVariable.

• pyAgrum

  • add a way to export BN samples as a pandas.DataFrame instead of csv files in pyAgrum.BNDatabaseGenerator and in the function pyAgrum.generateSamples(....).
  • gum.BNLearner can now take a pandas.DataFrame as data source in its constructor.
  • Add support for default number of thread in gum.config.
  • Added methods to get/set the number of threads used by pyAgrum.BNLearner, pyAgrum.LazyPropagation and pyAgrum.ShaferShenoy.
  • small change in pyAgrum.skbn.Discretizer.audit : show the domain size for discrete variable.
  • better graphical diff between BN, even if a node is missing using pyAgrum.bn_vs_bn functionalities.
  • empirical gum.DiscretizedVariable used in pyAgrum.skbn.Discretizer
  • new configuration for (LaTeX) fractions in gum.lib.notebook.showCPT (see tutorial)
  • update a bit pyAgrum.IntegerVariable wrapper and documentation.