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.dev202508031753652324

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.dev202508031753652324
File
pyagrum_nightly-2.2.0.9.dev202508031753652324-cp310-abi3-win_amd64.whl CPython 3.10 abi3 Windows x86-64 Details
pyagrum_nightly-2.2.0.9.dev202508031753652324-cp310-abi3-manylinux2014_x86_64.whl CPython 3.10 abi3 Linux glibc 2.17+ x86-64 Details
pyagrum_nightly-2.2.0.9.dev202508031753652324-cp310-abi3-manylinux2014_aarch64.whl CPython 3.10 abi3 Linux glibc 2.17+ ARM64 Details
pyagrum_nightly-2.2.0.9.dev202508031753652324-cp310-abi3-macosx_11_0_arm64.whl CPython 3.10 abi3 macOS 11.0+ ARM64 Details
pyagrum_nightly-2.2.0.9.dev202508031753652324-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.dev202508031753652324-cp310-abi3-win_amd64.whl

Download URL pyagrum_nightly-2.2.0.9.dev202508031753652324-cp310-abi3-win_amd64.whl
Size 2.9 MB
Tags CPython 3.10 Windows x86-64 abi3
SHA-256 checksum
How to use checksums
f8976c56f912f32d85acbddac92b4d401ec2866fe8f7fd165eb14df3ef7dfa49
BLAKE2b-256 checksum
How to use checksums
87beed434502510d31f3f5c06b3f0059e54a62feab0031ce468f8f15768b6c0f
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.dev202508031753652324-cp310-abi3-manylinux2014_x86_64.whl

Download URL pyagrum_nightly-2.2.0.9.dev202508031753652324-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
b7a30dc6d31c20d856e8a252c219bd85c95b25e844bdebb822806a0810c35d71
BLAKE2b-256 checksum
How to use checksums
efb87af83634a084d718f9a20c7dff85b8ea0175bcd75cbe016fa910e1b60dd5
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.dev202508031753652324-cp310-abi3-manylinux2014_aarch64.whl

Download URL pyagrum_nightly-2.2.0.9.dev202508031753652324-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
111359fe7ccffbfac16f0f39b22397061f56457471d08115963fc53056ac3505
BLAKE2b-256 checksum
How to use checksums
b353707f8cf94e715b48fc8f399732096d9a42a58ad20ee6432caff8631cf0c1
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.dev202508031753652324-cp310-abi3-macosx_11_0_arm64.whl

Download URL pyagrum_nightly-2.2.0.9.dev202508031753652324-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
8c49f638ce7f2fcf3b2b9497910552bad168191a4e5d0222e5f88926e564c045
BLAKE2b-256 checksum
How to use checksums
23f82c255fbff9dcee958944bb66ab42b3a0f6d044e0a6e169e4c07f54f1e1ee
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.dev202508031753652324-cp310-abi3-macosx_10_15_x86_64.whl

Download URL pyagrum_nightly-2.2.0.9.dev202508031753652324-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
db3662c1107d6fb83e934f8dcaa89b573e4c082903fcae73da10ee547c92bf9c
BLAKE2b-256 checksum
How to use checksums
4d303fceab48fbcbb93412adcb6ccd9782a06fa98930cc94a831b1845402ae30
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