Skip to main content
Pre-release

This release is a pre-release and may not be stable for production use.

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.

Important

Since pyAgrum 2.0.0, the package name follows PEP8 rules and is now pyagrum (lowercase). Please use import pyagrum instead of import pyAgrum in your code.

See the CHANGELOG for more details.

Example

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) 2005-2024 by Pierre-Henri WUILLEMIN et Christophe GONZALES {prenom.nom}_at_lip6.fr

The aGrUM/pyAgrum library and all its derivatives are distributed under the dual LGPLv3+MIT license, see LICENSE.LGPL and LICENSE.MIT.

You can therefore integrate this library into your software solution but it will remain covered by either the LGPL v.3 license or the MIT license or, as aGrUM itself, by the dual LGPLv3+MIT license at your convenience. If you wish to integrate the aGrUM library into your product without being affected by this license, please contact us (info@agrum.org).

This library depends on different third-party codes. See src/aGrUM/tools/externals for specific COPYING and explicit permission of the authors, if needed.

If you use aGrUM/pyAgrum as a dependency of your own project, you are not contaminated by the GPL license of some of these third-party codes as long as you use only their aGrUM/pyAgrum interfaces and not their native interfaces.

Authors

  • Pierre-Henri Wuillemin

  • Christophe Gonzales

Maintainers

  • Lionel Torti

  • Gaspard Ducamp

Release files for pyAgrum-nightly 2.0.1.dev202504101743172129

For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.

Built distributions (wheels)

Table of built distributions (wheels) for pyAgrum-nightly 2.0.1.dev202504101743172129
File
pyagrum_nightly-2.0.1.dev202504101743172129-cp310-abi3-win_amd64.whl CPython 3.10 abi3 Windows x86-64 Details
pyagrum_nightly-2.0.1.dev202504101743172129-cp310-abi3-manylinux2014_x86_64.whl CPython 3.10 abi3 Linux glibc 2.17+ x86-64 Details
pyagrum_nightly-2.0.1.dev202504101743172129-cp310-abi3-manylinux2014_aarch64.whl CPython 3.10 abi3 Linux glibc 2.17+ ARM64 Details
pyagrum_nightly-2.0.1.dev202504101743172129-cp310-abi3-macosx_11_0_arm64.whl CPython 3.10 abi3 macOS 11.0+ ARM64 Details
pyagrum_nightly-2.0.1.dev202504101743172129-cp310-abi3-macosx_10_13_x86_64.whl CPython 3.10 abi3 macOS 10.13+ x86-64 Details

Total release size: 44.3 MB

Release files / pyagrum_nightly-2.0.1.dev202504101743172129-cp310-abi3-win_amd64.whl

Download URL pyagrum_nightly-2.0.1.dev202504101743172129-cp310-abi3-win_amd64.whl
Size 4.5 MB
Tags CPython 3.10 Windows x86-64 abi3
SHA-256 checksum
How to use checksums
37173851074b9c4a0aec699b64a022f50b92d17b7df4da5b108c1f2c38e02f5d
BLAKE2b-256 checksum
How to use checksums
f06784f163568f45252358d504b54ed7593f1bf69bc9abb06816ac6aecc443ca
Upload date
Uploaded using Trusted Publishing?
What is trusted publishing?
No
Uploaded via twine/6.1.0 CPython/3.8.10

Release files / pyagrum_nightly-2.0.1.dev202504101743172129-cp310-abi3-manylinux2014_x86_64.whl

Download URL pyagrum_nightly-2.0.1.dev202504101743172129-cp310-abi3-manylinux2014_x86_64.whl
Size 12.7 MB
Tags CPython 3.10 Linux glibc 2.17+ x86-64 abi3
SHA-256 checksum
How to use checksums
ee8e3b3f264d13e7c34ec6e554c8196a19d338e9d1b21a66cb810c51b7c7131e
BLAKE2b-256 checksum
How to use checksums
31a22ee3f73e94f486dc474e2c34a3cacf0c597e2c6c6d342ff482d6e4de023e
Upload date
Uploaded using Trusted Publishing?
What is trusted publishing?
No
Uploaded via twine/6.1.0 CPython/3.8.10

Release files / pyagrum_nightly-2.0.1.dev202504101743172129-cp310-abi3-manylinux2014_aarch64.whl

Download URL pyagrum_nightly-2.0.1.dev202504101743172129-cp310-abi3-manylinux2014_aarch64.whl
Size 11.8 MB
Tags CPython 3.10 Linux glibc 2.17+ ARM64 abi3
SHA-256 checksum
How to use checksums
1599ca57353683fb8bb5f8c9fa479066d60762640300984d8ef217ed355025bf
BLAKE2b-256 checksum
How to use checksums
4c1881c1b60ba466dc7b77a7a77d10dadedd60a01e9b575156318b9b0116ac38
Upload date
Uploaded using Trusted Publishing?
What is trusted publishing?
No
Uploaded via twine/6.1.0 CPython/3.8.10

Release files / pyagrum_nightly-2.0.1.dev202504101743172129-cp310-abi3-macosx_11_0_arm64.whl

Download URL pyagrum_nightly-2.0.1.dev202504101743172129-cp310-abi3-macosx_11_0_arm64.whl
Size 7.3 MB
Tags CPython 3.10 abi3 macOS 11.0+ ARM64
SHA-256 checksum
How to use checksums
47f07c2e5137c305dd6782902a0f32b5ec2b48b0c7b90945f004fdbefba2f2f8
BLAKE2b-256 checksum
How to use checksums
bc0afe21798f2c7a6c68eadb7e52e0716ce03451e8f8ffcad4312343bc50af32
Upload date
Uploaded using Trusted Publishing?
What is trusted publishing?
No
Uploaded via twine/6.1.0 CPython/3.8.10

Release files / pyagrum_nightly-2.0.1.dev202504101743172129-cp310-abi3-macosx_10_13_x86_64.whl

Download URL pyagrum_nightly-2.0.1.dev202504101743172129-cp310-abi3-macosx_10_13_x86_64.whl
Size 8.1 MB
Tags CPython 3.10 abi3 macOS 10.13+ x86-64
SHA-256 checksum
How to use checksums
bd1aab0b1beb0d81d97c6dd5288e0fa1b10d173cdde9576dbc839038617554f1
BLAKE2b-256 checksum
How to use checksums
7a18324b1dea0486f11733ed015eecf9c1f34ce9a8a109234be9f8c350eb583f
Upload date
Uploaded using Trusted Publishing?
What is trusted publishing?
No
Uploaded via twine/6.1.0 CPython/3.8.10

Release history Release notifications | RSS feed

This release
Anthropic, PBC Visionary sponsor Bloomberg Visionary sponsor Hudson River Trading Visionary sponsor Meta Visionary sponsor NVIDIA Visionary sponsor Microsoft Sustainability sponsor Depot Continuous Integration AWS Cloud computing and Security Sponsor Datadog Monitoring Fastly CDN Google Download Analytics Sentry Error logging StatusPage Status page