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 2.3.1.9.dev202601161765915415

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 2.3.1.9.dev202601161765915415
File
pyagrum_nightly-2.3.1.9.dev202601161765915415-cp310-abi3-win_amd64.whl CPython 3.10 abi3 Windows x86-64 Details
pyagrum_nightly-2.3.1.9.dev202601161765915415-cp310-abi3-manylinux2014_x86_64.whl CPython 3.10 abi3 Linux glibc 2.17+ x86-64 Details
pyagrum_nightly-2.3.1.9.dev202601161765915415-cp310-abi3-manylinux2014_aarch64.whl CPython 3.10 abi3 Linux glibc 2.17+ ARM64 Details
pyagrum_nightly-2.3.1.9.dev202601161765915415-cp310-abi3-macosx_11_0_arm64.whl CPython 3.10 abi3 macOS 11.0+ ARM64 Details
pyagrum_nightly-2.3.1.9.dev202601161765915415-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-2.3.1.9.dev202601161765915415-cp310-abi3-win_amd64.whl

Download URL pyagrum_nightly-2.3.1.9.dev202601161765915415-cp310-abi3-win_amd64.whl
Size 3.1 MB
Tags CPython 3.10 Windows x86-64 abi3
SHA-256 checksum
How to use checksums
670fe6229ef95ddad0fa2595629adb501df6e1c5aa28aefb4a0a2d8bba5a4fb2
BLAKE2b-256 checksum
How to use checksums
36785c268be248b2b41183ed9374adafc6a575a48d5486d5307518d42f4ed317
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-2.3.1.9.dev202601161765915415-cp310-abi3-manylinux2014_x86_64.whl

Download URL pyagrum_nightly-2.3.1.9.dev202601161765915415-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
bbec8dbe8c178926bb60766776e6b1888b844528320c6a85e6b4a5090f9905dc
BLAKE2b-256 checksum
How to use checksums
b2bff82974267e75d4f1362495b0d5827e56c6cb6fbeaf4814c0d3871456657e
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-2.3.1.9.dev202601161765915415-cp310-abi3-manylinux2014_aarch64.whl

Download URL pyagrum_nightly-2.3.1.9.dev202601161765915415-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
bafea2454c5a2702507085bfb2a9bdf85f3e369af8157c62aec78159659b8845
BLAKE2b-256 checksum
How to use checksums
a8932be5bb5c8faf9583b7970e1f0f4fc937461658f04a901a45f28ce03fb941
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-2.3.1.9.dev202601161765915415-cp310-abi3-macosx_11_0_arm64.whl

Download URL pyagrum_nightly-2.3.1.9.dev202601161765915415-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
e40a675c109b70e6d8ef0614f3ae811b281a5cedbba01b7ca530a860aea2bb93
BLAKE2b-256 checksum
How to use checksums
22fabba704b0e842f67cfa2be8808eb301fd9fe035fd43158e21196f66c8d3bd
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-2.3.1.9.dev202601161765915415-cp310-abi3-macosx_10_15_x86_64.whl

Download URL pyagrum_nightly-2.3.1.9.dev202601161765915415-cp310-abi3-macosx_10_15_x86_64.whl
Size 4.9 MB
Tags CPython 3.10 abi3 macOS 10.15+ x86-64
SHA-256 checksum
How to use checksums
af187e4f2607279cb75fec369338b057d3dc01e90ac13c4c126678f8b1ebbfcf
BLAKE2b-256 checksum
How to use checksums
f85faf289e202159fd5aa80e907daa04fc163f921c178200d1c8e0aef62b7374
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