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 2.1.0.dev202505051746168413

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 2.1.0.dev202505051746168413
File
pyagrum_nightly-2.1.0.dev202505051746168413-cp310-abi3-win_amd64.whl CPython 3.10 abi3 Windows x86-64 Details
pyagrum_nightly-2.1.0.dev202505051746168413-cp310-abi3-manylinux2014_x86_64.whl CPython 3.10 abi3 Linux glibc 2.17+ x86-64 Details
pyagrum_nightly-2.1.0.dev202505051746168413-cp310-abi3-manylinux2014_aarch64.whl CPython 3.10 abi3 Linux glibc 2.17+ ARM64 Details
pyagrum_nightly-2.1.0.dev202505051746168413-cp310-abi3-macosx_11_0_arm64.whl CPython 3.10 abi3 macOS 11.0+ ARM64 Details
pyagrum_nightly-2.1.0.dev202505051746168413-cp310-abi3-macosx_10_13_x86_64.whl CPython 3.10 abi3 macOS 10.13+ x86-64 Details

Total release size: 23.8 MB

Release files / pyagrum_nightly-2.1.0.dev202505051746168413-cp310-abi3-win_amd64.whl

Download URL pyagrum_nightly-2.1.0.dev202505051746168413-cp310-abi3-win_amd64.whl
Size 2.9 MB
Tags CPython 3.10 Windows x86-64 abi3
SHA-256 checksum
How to use checksums
c72b816675f18f38d9a94b964c05b1aa5abe864d50bb8a3d9bcd40358a39e009
BLAKE2b-256 checksum
How to use checksums
223f25d084f73b3c108cba9da75014f4ca02deef7774773153f55ba5d7c9aada
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-2.1.0.dev202505051746168413-cp310-abi3-manylinux2014_x86_64.whl

Download URL pyagrum_nightly-2.1.0.dev202505051746168413-cp310-abi3-manylinux2014_x86_64.whl
Size 6.1 MB
Tags CPython 3.10 Linux glibc 2.17+ x86-64 abi3
SHA-256 checksum
How to use checksums
6d8173675e6d9f6d59246ec11438305dcd1eb1f9a7cfde6b533f7d1919d6b329
BLAKE2b-256 checksum
How to use checksums
275e3742988e781637f0d0a8bcd4f850778395878d9685e04f51f11907251f9c
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-2.1.0.dev202505051746168413-cp310-abi3-manylinux2014_aarch64.whl

Download URL pyagrum_nightly-2.1.0.dev202505051746168413-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
5a4b6476a66bd52f844b6f143626496f83eaed9aec2fc1238f5a5f8c6c7f4388
BLAKE2b-256 checksum
How to use checksums
ba69ff6c1c810da9e041e3ab8f305bc7deb43fa50769a5af89b8d0e9d5c7e557
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-2.1.0.dev202505051746168413-cp310-abi3-macosx_11_0_arm64.whl

Download URL pyagrum_nightly-2.1.0.dev202505051746168413-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
563b7c7a32a26c91d46e19dd7e7325db80f34ed95731e31220ecc28945d98aa3
BLAKE2b-256 checksum
How to use checksums
8e9e7cf4ac6b3e00274f89bed74d4bfcf579b22b0c5410dfa698fa9a92e09fcd
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-2.1.0.dev202505051746168413-cp310-abi3-macosx_10_13_x86_64.whl

Download URL pyagrum_nightly-2.1.0.dev202505051746168413-cp310-abi3-macosx_10_13_x86_64.whl
Size 4.8 MB
Tags CPython 3.10 abi3 macOS 10.13+ x86-64
SHA-256 checksum
How to use checksums
6e5cabfab53fc449057886bfae57d16a6ac75ab80cc8e0aed1a4ac1fd180465c
BLAKE2b-256 checksum
How to use checksums
2566c64224d769b8ff739fd3f291b07cab5ac5e325096385bf50d5ecfbfb1f5a
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