ANNOUNCE: aGrUM 0.12.0

Changelog (from gitlab)

• API
  • new class EssentialGraph
  • new class MarkovBlanket
  • improved targets in MarginalTargettedInference
• pyAgrum
  • update notebooks
  • new swig-based documentation framework
  • transparent background for dot graphs
  • more windows-compliant agrum.lib.bn2csv
• aGrUM
  • PRM bug fixes
  • improved CI in gitlab
  • improved exception messages in BN learning …

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pyagrum.lib.notebook offers some helpers and graphical representation of internal objets of agrum : Potential, Graph, Bayesian network, inference, etc. See pyAgrum doc for more details.

From aGrUM 0.11.2, pyagrum.lib.ipython proposes an equivalent API (a subset of the notebook API) for ipython graphical console. For instance …

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There are 3 types of discrete random variables in aGrUM/pyAgrum : LabelizedVariable, DiscretizedVariable and RangeVariable. The 3 types are mainly provided in order to ease the modelisation. Derived from DiscreteVariable, they share a common API

{% include_code types-of-variables_common.pytest lang:python lines:5-100 %}

They essentially differ by the means to create …

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