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 2.0.1.dev202504091743172129

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 2.0.1.dev202504091743172129
File
pyagrum_nightly-2.0.1.dev202504091743172129-cp310-abi3-win_amd64.whl CPython 3.10 abi3 Windows x86-64 Details
pyagrum_nightly-2.0.1.dev202504091743172129-cp310-abi3-manylinux2014_x86_64.whl CPython 3.10 abi3 Linux glibc 2.17+ x86-64 Details
pyagrum_nightly-2.0.1.dev202504091743172129-cp310-abi3-manylinux2014_aarch64.whl CPython 3.10 abi3 Linux glibc 2.17+ ARM64 Details
pyagrum_nightly-2.0.1.dev202504091743172129-cp310-abi3-macosx_11_0_arm64.whl CPython 3.10 abi3 macOS 11.0+ ARM64 Details
pyagrum_nightly-2.0.1.dev202504091743172129-cp310-abi3-macosx_10_13_x86_64.whl CPython 3.10 abi3 macOS 10.13+ x86-64 Details

Total release size: 44.3 MB

Release files / pyagrum_nightly-2.0.1.dev202504091743172129-cp310-abi3-win_amd64.whl

Download URL pyagrum_nightly-2.0.1.dev202504091743172129-cp310-abi3-win_amd64.whl
Size 4.5 MB
Tags CPython 3.10 Windows x86-64 abi3
SHA-256 checksum
How to use checksums
946a8e56cb77b5dafb1aab25af48c52245ede1b7981452aac533007d52f6226e
BLAKE2b-256 checksum
How to use checksums
d1de32487d36de93f7058b1ffe0959bc006f3b2e3b8ed001f239eeb8e5e59e6f
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-2.0.1.dev202504091743172129-cp310-abi3-manylinux2014_x86_64.whl

Download URL pyagrum_nightly-2.0.1.dev202504091743172129-cp310-abi3-manylinux2014_x86_64.whl
Size 12.7 MB
Tags CPython 3.10 Linux glibc 2.17+ x86-64 abi3
SHA-256 checksum
How to use checksums
c09759818deb85f94cc395705016610aaff3052035bf49ebdc54af7171262ad8
BLAKE2b-256 checksum
How to use checksums
a910e4a7b8636204280cd593c1c178cba8757b3fa0362172f8f4b37e11a20d3a
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-2.0.1.dev202504091743172129-cp310-abi3-manylinux2014_aarch64.whl

Download URL pyagrum_nightly-2.0.1.dev202504091743172129-cp310-abi3-manylinux2014_aarch64.whl
Size 11.8 MB
Tags CPython 3.10 Linux glibc 2.17+ ARM64 abi3
SHA-256 checksum
How to use checksums
6424004dcc65bd97eb84c762ffaee9727e4e7b63689279110d670e4edfd1fb7a
BLAKE2b-256 checksum
How to use checksums
b2844a4a25768c73627f598f49962a5cdbf38312dc888aa7bb0b00a291db4d0b
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-2.0.1.dev202504091743172129-cp310-abi3-macosx_11_0_arm64.whl

Download URL pyagrum_nightly-2.0.1.dev202504091743172129-cp310-abi3-macosx_11_0_arm64.whl
Size 7.3 MB
Tags CPython 3.10 abi3 macOS 11.0+ ARM64
SHA-256 checksum
How to use checksums
0c0273e73ab34872f11ec0f6ff0dd0a594bb844451b46fc5baa1e0b42e02e4af
BLAKE2b-256 checksum
How to use checksums
e7a5dc46785828f5e554feff9a1a9236ec64ca5240ad77160b7e0fecfe978b22
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-2.0.1.dev202504091743172129-cp310-abi3-macosx_10_13_x86_64.whl

Download URL pyagrum_nightly-2.0.1.dev202504091743172129-cp310-abi3-macosx_10_13_x86_64.whl
Size 8.1 MB
Tags CPython 3.10 abi3 macOS 10.13+ x86-64
SHA-256 checksum
How to use checksums
d66878c6ef0a1a7d91816107fd5e5eca9b2d9153900b82f37e3d198789f15b63
BLAKE2b-256 checksum
How to use checksums
d1167c7ab51fcb695e392c6ed410564328096bcff227ab479e510bb513c7f2df
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