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.dev202508241753652324

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.dev202508241753652324
File
pyagrum_nightly-2.2.0.9.dev202508241753652324-cp310-abi3-win_amd64.whl CPython 3.10 abi3 Windows x86-64 Details
pyagrum_nightly-2.2.0.9.dev202508241753652324-cp310-abi3-manylinux2014_x86_64.whl CPython 3.10 abi3 Linux glibc 2.17+ x86-64 Details
pyagrum_nightly-2.2.0.9.dev202508241753652324-cp310-abi3-manylinux2014_aarch64.whl CPython 3.10 abi3 Linux glibc 2.17+ ARM64 Details
pyagrum_nightly-2.2.0.9.dev202508241753652324-cp310-abi3-macosx_11_0_arm64.whl CPython 3.10 abi3 macOS 11.0+ ARM64 Details
pyagrum_nightly-2.2.0.9.dev202508241753652324-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.dev202508241753652324-cp310-abi3-win_amd64.whl

Download URL pyagrum_nightly-2.2.0.9.dev202508241753652324-cp310-abi3-win_amd64.whl
Size 2.9 MB
Tags CPython 3.10 Windows x86-64 abi3
SHA-256 checksum
How to use checksums
08c7da47c622065cf81dddf0c5845de2c73c60fb1f77a20b9c21fe2d86243726
BLAKE2b-256 checksum
How to use checksums
ef65ae02c5979760c1813ec4e5c31a89906e276e164387cd741eb88a7691b467
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.dev202508241753652324-cp310-abi3-manylinux2014_x86_64.whl

Download URL pyagrum_nightly-2.2.0.9.dev202508241753652324-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
137e77fc495f059eae7966bbf216cb81afda32f2a3636e7c99d3ac156f1ac12f
BLAKE2b-256 checksum
How to use checksums
926edfc7f39fe9659280f74490dd92b17310b0eb65dcf162a0493216e9c24de3
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.dev202508241753652324-cp310-abi3-manylinux2014_aarch64.whl

Download URL pyagrum_nightly-2.2.0.9.dev202508241753652324-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
2c6fa24be55e5a0ef8c5c450d50be8a8a7a9a41ba0909c0de613145636367768
BLAKE2b-256 checksum
How to use checksums
dbd25dce4729f6618288f62579dc60807b8ed7978fbd272c8935c4a2f0d4f054
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.dev202508241753652324-cp310-abi3-macosx_11_0_arm64.whl

Download URL pyagrum_nightly-2.2.0.9.dev202508241753652324-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
86a8924aa049ae40be96ff4bdf2fdfa1b53f0341d0f72024b1e5e2f70152455d
BLAKE2b-256 checksum
How to use checksums
6a25977b409c87af2a90f77d30a8a6418d4e815ab9661911eb51cd74f724dceb
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.dev202508241753652324-cp310-abi3-macosx_10_15_x86_64.whl

Download URL pyagrum_nightly-2.2.0.9.dev202508241753652324-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
1f94253f26613d8bc3ddd4d12d79dbf13dc8a1ae46c4624fb22e9dadf317d2fc
BLAKE2b-256 checksum
How to use checksums
7f46e06fbaf712d387ce35b303a85fe93da516d3547398a5d1854f9302cb859e
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