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 2.2.1.9.dev202510111759295983

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 2.2.1.9.dev202510111759295983
File
pyagrum_nightly-2.2.1.9.dev202510111759295983-cp310-abi3-win_amd64.whl CPython 3.10 abi3 Windows x86-64 Details
pyagrum_nightly-2.2.1.9.dev202510111759295983-cp310-abi3-manylinux2014_x86_64.whl CPython 3.10 abi3 Linux glibc 2.17+ x86-64 Details
pyagrum_nightly-2.2.1.9.dev202510111759295983-cp310-abi3-manylinux2014_aarch64.whl CPython 3.10 abi3 Linux glibc 2.17+ ARM64 Details
pyagrum_nightly-2.2.1.9.dev202510111759295983-cp310-abi3-macosx_11_0_arm64.whl CPython 3.10 abi3 macOS 11.0+ ARM64 Details
pyagrum_nightly-2.2.1.9.dev202510111759295983-cp310-abi3-macosx_10_15_x86_64.whl CPython 3.10 abi3 macOS 10.15+ x86-64 Details

Total release size: 24.1 MB

Release files / pyagrum_nightly-2.2.1.9.dev202510111759295983-cp310-abi3-win_amd64.whl

Download URL pyagrum_nightly-2.2.1.9.dev202510111759295983-cp310-abi3-win_amd64.whl
Size 3.0 MB
Tags CPython 3.10 Windows x86-64 abi3
SHA-256 checksum
How to use checksums
401bd76eda11c8028dbc4de26e34a8b8564f871cfefb781974497cf8a92a10c9
BLAKE2b-256 checksum
How to use checksums
7a5b66a700324c3a9637b210739bd9fc83227ec77687c7b0ad0fd6e33d9e707a
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-2.2.1.9.dev202510111759295983-cp310-abi3-manylinux2014_x86_64.whl

Download URL pyagrum_nightly-2.2.1.9.dev202510111759295983-cp310-abi3-manylinux2014_x86_64.whl
Size 6.4 MB
Tags CPython 3.10 Linux glibc 2.17+ x86-64 abi3
SHA-256 checksum
How to use checksums
cd3b5d60384cf75cf149ccfb742d98055afbf94b4b14c73fdde398685d26fe59
BLAKE2b-256 checksum
How to use checksums
7f35d5bc0ba6d0437d16ac987454926ad4aa7602a36da22182f37834d2371462
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-2.2.1.9.dev202510111759295983-cp310-abi3-manylinux2014_aarch64.whl

Download URL pyagrum_nightly-2.2.1.9.dev202510111759295983-cp310-abi3-manylinux2014_aarch64.whl
Size 5.9 MB
Tags CPython 3.10 Linux glibc 2.17+ ARM64 abi3
SHA-256 checksum
How to use checksums
9ad9f3b7f22d32cad492d45c7937153ed14d6f72cd9dd871fb27c30ef0f594e1
BLAKE2b-256 checksum
How to use checksums
b242878a9f0cfae45b50e605754ac4d6cc7da9dfa90c9ebc8023bd0231655d70
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-2.2.1.9.dev202510111759295983-cp310-abi3-macosx_11_0_arm64.whl

Download URL pyagrum_nightly-2.2.1.9.dev202510111759295983-cp310-abi3-macosx_11_0_arm64.whl
Size 4.1 MB
Tags CPython 3.10 abi3 macOS 11.0+ ARM64
SHA-256 checksum
How to use checksums
b4c3e21d6c04f7e94573f0d19cfb7caf0b6fab3f2e281dd84f7ef599a131dad7
BLAKE2b-256 checksum
How to use checksums
7cb7f2028e65b30b654e6a688d66b8fe960257426a881ce5447fabe6a42ffadc
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-2.2.1.9.dev202510111759295983-cp310-abi3-macosx_10_15_x86_64.whl

Download URL pyagrum_nightly-2.2.1.9.dev202510111759295983-cp310-abi3-macosx_10_15_x86_64.whl
Size 4.7 MB
Tags CPython 3.10 abi3 macOS 10.15+ x86-64
SHA-256 checksum
How to use checksums
4032e79245933ae0def21356dd7784482c35f7b4d79d302432dd44eba63fa461
BLAKE2b-256 checksum
How to use checksums
b816fa26ef42375b3f75c587eb2243d6d0b1af05122ab48e1e788e17f10a1046
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