pyAgrum
=======
``pyAgrum`` is a scientific C++ and Python library dedicated to Bayesian Networks and other Probabilistic Graphical Models. It provides a high-level interface to the part of aGrUM allowing to create, model, learn, use, calculate with and embed Bayesian Networks and other graphical models. Some specific (python and C++) codes are added in order to simplify and extend the ``aGrUM`` API.
Example
=======
.. code:: python
import pyAgrum as gum
# Creating BayesNet with 4 variables
bn=gum.BayesNet('WaterSprinkler')
print(bn)
# Adding nodes the long way
c=bn.add(gum.LabelizedVariable('c','cloudy ?',["Yes","No"]))
print(c)
# Adding nodes the short way
s, r, w = [ bn.add(name, 2) for name in "srw" ]
print (s,r,w)
print (bn)
# Addings arcs c -> s, c -> r, s -> w, r -> w
bn.addArc(c,s)
for link in [(c,r),(s,w),(r,w)]:
bn.addArc(*link)
print(bn)
# or, equivalenlty, creating the BN with 4 variables, and the arcs in one line
bn=gum.fastBN("w<-r<-c{Yes|No}->s->w")
# Filling CPTs
bn.cpt("c").fillWith([0.5,0.5])
bn.cpt("s")[0,:]=0.5 # equivalent to [0.5,0.5]
bn.cpt("s")[{"c":1}]=[0.9,0.1]
bn.cpt("w")[0,0,:] = [1, 0] # r=0,s=0
bn.cpt("w")[0,1,:] = [0.1, 0.9] # r=0,s=1
bn.cpt("w")[{"r":1,"s":0}] = [0.1, 0.9] # r=1,s=0
bn.cpt("w")[1,1,:] = [0.01, 0.99] # r=1,s=1
bn.cpt("r")[{"c":0}]=[0.8,0.2]
bn.cpt("r")[{"c":1}]=[0.2,0.8]
# Saving BN as a BIF file
gum.saveBN(bn,"WaterSprinkler.bif")
# Loading BN from a BIF file
bn2=gum.loadBN("WaterSprinkler.bif")
# Inference
ie=gum.LazyPropagation(bn)
ie.makeInference()
print (ie.posterior("w"))
# Adding hard evidence
ie.setEvidence({"s": 1, "c": 0})
ie.makeInference()
print(ie.posterior("w"))
# Adding soft and hard evidence
ie.setEvidence({"s": [0.5, 1], "c": 0})
ie.makeInference()
print(ie.posterior("w"))
LICENSE
=======
Copyright (C) 2005,2023 by Pierre-Henri WUILLEMIN et Christophe GONZALES
{prenom.nom}_at_lip6.fr
The aGrUM/pyAgrum library and all its derivatives are distributed under the LGPL3 license, see https://www.gnu.org/licenses/lgpl-3.0.en.html.
Authors
=======
- Pierre-Henri Wuillemin
- Christophe Gonzales
Maintainers
===========
- Lionel Torti
- Gaspard Ducamp
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"description": "\npyAgrum\n=======\n\n``pyAgrum`` is a scientific C++ and Python library dedicated to Bayesian Networks and other Probabilistic Graphical Models. It provides a high-level interface to the part of aGrUM allowing to create, model, learn, use, calculate with and embed Bayesian Networks and other graphical models. Some specific (python and C++) codes are added in order to simplify and extend the ``aGrUM`` API.\n\nExample\n=======\n\n.. code:: python\n\n import pyAgrum as gum\n\n # Creating BayesNet with 4 variables\n bn=gum.BayesNet('WaterSprinkler')\n print(bn)\n\n # Adding nodes the long way\n c=bn.add(gum.LabelizedVariable('c','cloudy ?',[\"Yes\",\"No\"]))\n print(c)\n\n # Adding nodes the short way\n s, r, w = [ bn.add(name, 2) for name in \"srw\" ] \n print (s,r,w)\n print (bn)\n\n # Addings arcs c -> s, c -> r, s -> w, r -> w\n bn.addArc(c,s)\n for link in [(c,r),(s,w),(r,w)]:\n bn.addArc(*link)\n print(bn)\n\n # or, equivalenlty, creating the BN with 4 variables, and the arcs in one line\n bn=gum.fastBN(\"w<-r<-c{Yes|No}->s->w\")\n\n # Filling CPTs\n bn.cpt(\"c\").fillWith([0.5,0.5])\n bn.cpt(\"s\")[0,:]=0.5 # equivalent to [0.5,0.5]\n bn.cpt(\"s\")[{\"c\":1}]=[0.9,0.1]\n bn.cpt(\"w\")[0,0,:] = [1, 0] # r=0,s=0\n bn.cpt(\"w\")[0,1,:] = [0.1, 0.9] # r=0,s=1\n bn.cpt(\"w\")[{\"r\":1,\"s\":0}] = [0.1, 0.9] # r=1,s=0\n bn.cpt(\"w\")[1,1,:] = [0.01, 0.99] # r=1,s=1\n bn.cpt(\"r\")[{\"c\":0}]=[0.8,0.2]\n bn.cpt(\"r\")[{\"c\":1}]=[0.2,0.8]\n\n # Saving BN as a BIF file\n gum.saveBN(bn,\"WaterSprinkler.bif\")\n\n # Loading BN from a BIF file\n bn2=gum.loadBN(\"WaterSprinkler.bif\")\n\n # Inference\n ie=gum.LazyPropagation(bn)\n ie.makeInference()\n print (ie.posterior(\"w\"))\n\n # Adding hard evidence\n ie.setEvidence({\"s\": 1, \"c\": 0})\n ie.makeInference()\n print(ie.posterior(\"w\"))\n\n # Adding soft and hard evidence\n ie.setEvidence({\"s\": [0.5, 1], \"c\": 0})\n ie.makeInference()\n print(ie.posterior(\"w\"))\n\nLICENSE\n=======\n\nCopyright (C) 2005,2023 by Pierre-Henri WUILLEMIN et Christophe GONZALES\n{prenom.nom}_at_lip6.fr \n\nThe aGrUM/pyAgrum library and all its derivatives are distributed under the LGPL3 license, see https://www.gnu.org/licenses/lgpl-3.0.en.html.\n\nAuthors\n=======\n\n- Pierre-Henri Wuillemin\n- Christophe Gonzales\n\nMaintainers\n===========\n\n- Lionel Torti\n- Gaspard Ducamp\n",
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