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.dev202508061753652324

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.dev202508061753652324
File
pyagrum_nightly-2.2.0.9.dev202508061753652324-cp310-abi3-win_amd64.whl CPython 3.10 abi3 Windows x86-64 Details
pyagrum_nightly-2.2.0.9.dev202508061753652324-cp310-abi3-manylinux2014_x86_64.whl CPython 3.10 abi3 Linux glibc 2.17+ x86-64 Details
pyagrum_nightly-2.2.0.9.dev202508061753652324-cp310-abi3-manylinux2014_aarch64.whl CPython 3.10 abi3 Linux glibc 2.17+ ARM64 Details
pyagrum_nightly-2.2.0.9.dev202508061753652324-cp310-abi3-macosx_11_0_arm64.whl CPython 3.10 abi3 macOS 11.0+ ARM64 Details
pyagrum_nightly-2.2.0.9.dev202508061753652324-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.dev202508061753652324-cp310-abi3-win_amd64.whl

Download URL pyagrum_nightly-2.2.0.9.dev202508061753652324-cp310-abi3-win_amd64.whl
Size 2.9 MB
Tags CPython 3.10 Windows x86-64 abi3
SHA-256 checksum
How to use checksums
f6f9a937bbb81dce2371de0dcf32e9c1374e3df6632bba8cc4b3def3971e3cc2
BLAKE2b-256 checksum
How to use checksums
895c81f102757f1312d81b6ba7e613bdb02d140530483a36c61553f08f48359f
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.dev202508061753652324-cp310-abi3-manylinux2014_x86_64.whl

Download URL pyagrum_nightly-2.2.0.9.dev202508061753652324-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
eba16dca5529b1cf1888cc229f95df5365c5216377288e78adad3cdad98ad2ed
BLAKE2b-256 checksum
How to use checksums
627de20344cff5d2eab13820022c660c6461e8760e2d62e8443d39773db08446
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.dev202508061753652324-cp310-abi3-manylinux2014_aarch64.whl

Download URL pyagrum_nightly-2.2.0.9.dev202508061753652324-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
ef9ed0b110e83c7c3e72fdf87eecdbe3217de2b552c54d0ce635744ad189d371
BLAKE2b-256 checksum
How to use checksums
ed799226c85986738657a0efcd7ed31d5b1128605ae24b8d494aac4628caae99
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.dev202508061753652324-cp310-abi3-macosx_11_0_arm64.whl

Download URL pyagrum_nightly-2.2.0.9.dev202508061753652324-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
86e81957ad76b9caa8b9665975e8d90f9bce99ff71c5edf05c1a2b8523ed1aa4
BLAKE2b-256 checksum
How to use checksums
bf8fd981377fc42f05aae2b100e9f49ee4c4f35470d17dd3794807b4183359d9
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.dev202508061753652324-cp310-abi3-macosx_10_15_x86_64.whl

Download URL pyagrum_nightly-2.2.0.9.dev202508061753652324-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
c92c54394f8a02ab7d3c180aa74a5b334b760bf626ac6000d00ebcfbff7ed1cc
BLAKE2b-256 checksum
How to use checksums
e568d6d2502a617f4231f47cd129681dbd1b23ce0a4cc9fc581124a93a4912b9
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