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 2.2.0.9.dev202508211753652324

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 2.2.0.9.dev202508211753652324
File
pyagrum_nightly-2.2.0.9.dev202508211753652324-cp310-abi3-win_amd64.whl CPython 3.10 abi3 Windows x86-64 Details
pyagrum_nightly-2.2.0.9.dev202508211753652324-cp310-abi3-manylinux2014_x86_64.whl CPython 3.10 abi3 Linux glibc 2.17+ x86-64 Details
pyagrum_nightly-2.2.0.9.dev202508211753652324-cp310-abi3-manylinux2014_aarch64.whl CPython 3.10 abi3 Linux glibc 2.17+ ARM64 Details
pyagrum_nightly-2.2.0.9.dev202508211753652324-cp310-abi3-macosx_11_0_arm64.whl CPython 3.10 abi3 macOS 11.0+ ARM64 Details
pyagrum_nightly-2.2.0.9.dev202508211753652324-cp310-abi3-macosx_10_15_x86_64.whl CPython 3.10 abi3 macOS 10.15+ x86-64 Details

Total release size: 24.0 MB

Release files / pyagrum_nightly-2.2.0.9.dev202508211753652324-cp310-abi3-win_amd64.whl

Download URL pyagrum_nightly-2.2.0.9.dev202508211753652324-cp310-abi3-win_amd64.whl
Size 2.9 MB
Tags CPython 3.10 Windows x86-64 abi3
SHA-256 checksum
How to use checksums
5070da0328a2c2b40f92227f66923ec18b4f02fbd08acc4a92c74afc847dd5ca
BLAKE2b-256 checksum
How to use checksums
d01183d23567392cc608f9d0c0718f39a70142aa2e75af00029b6cc27e5ec31f
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-2.2.0.9.dev202508211753652324-cp310-abi3-manylinux2014_x86_64.whl

Download URL pyagrum_nightly-2.2.0.9.dev202508211753652324-cp310-abi3-manylinux2014_x86_64.whl
Size 6.2 MB
Tags CPython 3.10 Linux glibc 2.17+ x86-64 abi3
SHA-256 checksum
How to use checksums
de4d9a7eefea00b00a66a512b702724b81387d86edfbad4fa0b7a0e81d45f4e8
BLAKE2b-256 checksum
How to use checksums
432c13a9b483459c96388a68956cc5fd7040f43bd8a0f677790797a26f4f47ee
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-2.2.0.9.dev202508211753652324-cp310-abi3-manylinux2014_aarch64.whl

Download URL pyagrum_nightly-2.2.0.9.dev202508211753652324-cp310-abi3-manylinux2014_aarch64.whl
Size 5.7 MB
Tags CPython 3.10 Linux glibc 2.17+ ARM64 abi3
SHA-256 checksum
How to use checksums
344f60640a515a03c1886deb068c314b4181aefd2a30dc957e164e1d82cd84eb
BLAKE2b-256 checksum
How to use checksums
1a12fd42713ed65e991e45e47e34d5efe4f8bca6468c2e8dca1e5dc784d078d5
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-2.2.0.9.dev202508211753652324-cp310-abi3-macosx_11_0_arm64.whl

Download URL pyagrum_nightly-2.2.0.9.dev202508211753652324-cp310-abi3-macosx_11_0_arm64.whl
Size 4.3 MB
Tags CPython 3.10 abi3 macOS 11.0+ ARM64
SHA-256 checksum
How to use checksums
a5f30af2479d3ec2cec310c02d99686ccb1d1a0348a81a088d9b1778b49b1644
BLAKE2b-256 checksum
How to use checksums
fc2f92461def88f4a7db2e2f9a21f1c19f224ba79e3a91e48a22c7d7aededa80
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-2.2.0.9.dev202508211753652324-cp310-abi3-macosx_10_15_x86_64.whl

Download URL pyagrum_nightly-2.2.0.9.dev202508211753652324-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
f749cb04658494e1448eb96bcaef411c6cb3e2ea50f1de1e6340405878078f7a
BLAKE2b-256 checksum
How to use checksums
8976d9147a8e46493bc8874e2f90b50f34c51c9281455a20a993a637f7d62ba4
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