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 3.0.0.9.dev202607181784318865

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 3.0.0.9.dev202607181784318865
File
pyagrum_nightly-3.0.0.9.dev202607181784318865-cp310-abi3-win_amd64.whl CPython 3.10 abi3 Windows x86-64 Details
pyagrum_nightly-3.0.0.9.dev202607181784318865-cp310-abi3-manylinux2014_x86_64.whl CPython 3.10 abi3 Linux glibc 2.17+ x86-64 Details
pyagrum_nightly-3.0.0.9.dev202607181784318865-cp310-abi3-manylinux2014_aarch64.whl CPython 3.10 abi3 Linux glibc 2.17+ ARM64 Details
pyagrum_nightly-3.0.0.9.dev202607181784318865-cp310-abi3-macosx_11_0_arm64.whl CPython 3.10 abi3 macOS 11.0+ ARM64 Details
pyagrum_nightly-3.0.0.9.dev202607181784318865-cp310-abi3-macosx_10_15_x86_64.whl CPython 3.10 abi3 macOS 10.15+ x86-64 Details

Total release size: 20.6 MB

Release files / pyagrum_nightly-3.0.0.9.dev202607181784318865-cp310-abi3-win_amd64.whl

Download URL pyagrum_nightly-3.0.0.9.dev202607181784318865-cp310-abi3-win_amd64.whl
Size 3.5 MB
Tags CPython 3.10 Windows x86-64 abi3
SHA-256 checksum
How to use checksums
f1635ebb96b566ce62c66852d4b170ee81cdc7625e139fbf2c66bcdc57aed73d
BLAKE2b-256 checksum
How to use checksums
48bf8927ab9effd53319b24ef92a8c4a5735058fccdab4fa3a8aa929c7471e37
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-3.0.0.9.dev202607181784318865-cp310-abi3-manylinux2014_x86_64.whl

Download URL pyagrum_nightly-3.0.0.9.dev202607181784318865-cp310-abi3-manylinux2014_x86_64.whl
Size 5.4 MB
Tags CPython 3.10 Linux glibc 2.17+ x86-64 abi3
SHA-256 checksum
How to use checksums
3d86d29141baf30737d793c6028b17d8ab2de02dd1e1db172d8ca95cb7f37819
BLAKE2b-256 checksum
How to use checksums
8394af0f437c9a758fe763349c4ea70bd20dba78e58c4e058219e5ae23670d2e
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-3.0.0.9.dev202607181784318865-cp310-abi3-manylinux2014_aarch64.whl

Download URL pyagrum_nightly-3.0.0.9.dev202607181784318865-cp310-abi3-manylinux2014_aarch64.whl
Size 4.6 MB
Tags CPython 3.10 Linux glibc 2.17+ ARM64 abi3
SHA-256 checksum
How to use checksums
f3a0bf3c2a425de9035fcce0f1b6e70d5adcef5d0945d5c54526ac176763c263
BLAKE2b-256 checksum
How to use checksums
72ac4ef1afa122ef60e24404f34920198b186b665055a8c348897d8650ca6505
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-3.0.0.9.dev202607181784318865-cp310-abi3-macosx_11_0_arm64.whl

Download URL pyagrum_nightly-3.0.0.9.dev202607181784318865-cp310-abi3-macosx_11_0_arm64.whl
Size 3.4 MB
Tags CPython 3.10 abi3 macOS 11.0+ ARM64
SHA-256 checksum
How to use checksums
4cef0963c8e37bf6814279adbfff90a279397e0cfc82073e0f798925b1c86263
BLAKE2b-256 checksum
How to use checksums
c33842aaaf7a87fe064c1c5de71d46be3932b2bf529db20104865d102c04ba20
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-3.0.0.9.dev202607181784318865-cp310-abi3-macosx_10_15_x86_64.whl

Download URL pyagrum_nightly-3.0.0.9.dev202607181784318865-cp310-abi3-macosx_10_15_x86_64.whl
Size 3.8 MB
Tags CPython 3.10 abi3 macOS 10.15+ x86-64
SHA-256 checksum
How to use checksums
c823a4f82bf9ebc43010ffd8597b13df97a4e788dfdfc3d73a834eb48c749107
BLAKE2b-256 checksum
How to use checksums
0b1a7b87a65951b13a761f8ed5b4e3e0b3ee4c4fe55ce186a46eef4c8447f6d5
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