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 2.3.0.9.dev202511261762170379

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 2.3.0.9.dev202511261762170379
File
pyagrum_nightly-2.3.0.9.dev202511261762170379-cp310-abi3-win_amd64.whl CPython 3.10 abi3 Windows x86-64 Details
pyagrum_nightly-2.3.0.9.dev202511261762170379-cp310-abi3-manylinux2014_x86_64.whl CPython 3.10 abi3 Linux glibc 2.17+ x86-64 Details
pyagrum_nightly-2.3.0.9.dev202511261762170379-cp310-abi3-manylinux2014_aarch64.whl CPython 3.10 abi3 Linux glibc 2.17+ ARM64 Details
pyagrum_nightly-2.3.0.9.dev202511261762170379-cp310-abi3-macosx_11_0_arm64.whl CPython 3.10 abi3 macOS 11.0+ ARM64 Details
pyagrum_nightly-2.3.0.9.dev202511261762170379-cp310-abi3-macosx_10_15_x86_64.whl CPython 3.10 abi3 macOS 10.15+ x86-64 Details

Total release size: 24.8 MB

Release files / pyagrum_nightly-2.3.0.9.dev202511261762170379-cp310-abi3-win_amd64.whl

Download URL pyagrum_nightly-2.3.0.9.dev202511261762170379-cp310-abi3-win_amd64.whl
Size 3.1 MB
Tags CPython 3.10 Windows x86-64 abi3
SHA-256 checksum
How to use checksums
c1b903bdb3f10ab267a863c48eaabd95f9d07756d039f60670c6a8be0b1ffc37
BLAKE2b-256 checksum
How to use checksums
2075dc2b93b8dea2b1340a281eaf9a5d11c587fba2d8611263786eea91be59a6
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-2.3.0.9.dev202511261762170379-cp310-abi3-manylinux2014_x86_64.whl

Download URL pyagrum_nightly-2.3.0.9.dev202511261762170379-cp310-abi3-manylinux2014_x86_64.whl
Size 6.6 MB
Tags CPython 3.10 Linux glibc 2.17+ x86-64 abi3
SHA-256 checksum
How to use checksums
45c21a33a8242ba101ee9fafe808e9d0edf4546a4fa17cceb48a9f12cdd6f9d5
BLAKE2b-256 checksum
How to use checksums
fde3ba054d0b5a1a410862246676f4624e0792ed627ee6b4d957c36db92d671c
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-2.3.0.9.dev202511261762170379-cp310-abi3-manylinux2014_aarch64.whl

Download URL pyagrum_nightly-2.3.0.9.dev202511261762170379-cp310-abi3-manylinux2014_aarch64.whl
Size 6.0 MB
Tags CPython 3.10 Linux glibc 2.17+ ARM64 abi3
SHA-256 checksum
How to use checksums
6e845eee88eca5024daabceeac80f68a31bde674eb4686d1a15792f678441517
BLAKE2b-256 checksum
How to use checksums
a8cea532d40b6f15f48b5493889c8911134e9d1da260cfdac1b468bfaec19232
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-2.3.0.9.dev202511261762170379-cp310-abi3-macosx_11_0_arm64.whl

Download URL pyagrum_nightly-2.3.0.9.dev202511261762170379-cp310-abi3-macosx_11_0_arm64.whl
Size 4.2 MB
Tags CPython 3.10 abi3 macOS 11.0+ ARM64
SHA-256 checksum
How to use checksums
5b927a59b4fa5b2463c6a842f3d18d2564e16f41dadeb76bd0ca27fb9b0b0ce3
BLAKE2b-256 checksum
How to use checksums
5da57c73aaa26f7a00d4bcfc5b17f27b690c6fb44f7dc43c8b15989c5fa5e28d
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-2.3.0.9.dev202511261762170379-cp310-abi3-macosx_10_15_x86_64.whl

Download URL pyagrum_nightly-2.3.0.9.dev202511261762170379-cp310-abi3-macosx_10_15_x86_64.whl
Size 4.8 MB
Tags CPython 3.10 abi3 macOS 10.15+ x86-64
SHA-256 checksum
How to use checksums
7ba26ceae4b3f2b81a83f71269e6f22b9fd9791752c53d0631e2c5b855d06fde
BLAKE2b-256 checksum
How to use checksums
1170e450d61bdf3a6a76b79afcd2dabbbf5dc86517923417ee2c445e1a2afb90
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