aGrUM/pyAgrum 0.13 released

Posted on jeu. 14 juin 2018 in News


aGrUM/pyAgrum 0.13 is out. 0.13.2 is the current version.

Changelog 0.13.0 (from gitlab)

  • aGrUM
    • inference: Loopy Belief Propagation (LBP)
    • inference: new approximated inference : Monte-Carlo/Importance/Weighted Sampling + the same using LBP as a Dirichlet prior (Loopy...).
    • learning: new algorithm 3off2 and miic
    • learning: new database handling framework (allows for coping with missing values and with different types of variables)
    • learning: possibility to load data from nanodbc databases (e.g., postgres, sqlite)
    • learning: add a progress Listener/Signaler in BNDatabaseGenerator
    • potential: API extension (findAll,argmax,argmin,fillWith(pot,map))
    • variable: new constructor for LabelizedVariable with labels as vector of string + posLabel (std::string)
    • variable: new constructor with vector of ticks for gum::DiscretizedVariable
    • graph: API extension (addNodes(n))
    • graph: API change (addNode(id)->addNodeWithId(id))
    • Changes and bug fixe in in BIF and NET writer/reader
  • pyAgrum
    • wheels for python 3.3 and 3.4
    • access to the new learning framework using BNLearner
    • access to the new inference algorithms
    • new methods Instantiation.fromdict and Instantiation.todict
    • DiscreteVariable.toDiscretized/toLabelized/toRange copy the variable instead of giving a (not readonly) reference
  • O3PRM
    • new syntax for types
    • read and write Bayesian Network with O3PRM syntax
  • Documentations
  • act
    • new command guideline for a few easy checks
  • many bug fixes