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.dev202607291784631574

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.dev202607291784631574
File
pyagrum_nightly-3.0.0.9.dev202607291784631574-cp310-abi3-win_amd64.whl CPython 3.10 abi3 Windows x86-64 Details
pyagrum_nightly-3.0.0.9.dev202607291784631574-cp310-abi3-manylinux2014_x86_64.whl CPython 3.10 abi3 Linux glibc 2.17+ x86-64 Details
pyagrum_nightly-3.0.0.9.dev202607291784631574-cp310-abi3-manylinux2014_aarch64.whl CPython 3.10 abi3 Linux glibc 2.17+ ARM64 Details
pyagrum_nightly-3.0.0.9.dev202607291784631574-cp310-abi3-macosx_11_0_arm64.whl CPython 3.10 abi3 macOS 11.0+ ARM64 Details
pyagrum_nightly-3.0.0.9.dev202607291784631574-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.dev202607291784631574-cp310-abi3-win_amd64.whl

Download URL pyagrum_nightly-3.0.0.9.dev202607291784631574-cp310-abi3-win_amd64.whl
Size 3.5 MB
Tags CPython 3.10 Windows x86-64 abi3
SHA-256 checksum
How to use checksums
3fbed78a4df3f29d60598f96f66a88b2b7fda32fd5f5756e1c2677cb66415c59
BLAKE2b-256 checksum
How to use checksums
91d8de902901d47b7f16a2fcab9c2701d2103d0b38ea11a8f49a5c0c54abd4e2
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.dev202607291784631574-cp310-abi3-manylinux2014_x86_64.whl

Download URL pyagrum_nightly-3.0.0.9.dev202607291784631574-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
ed95bf622c42f4940c0f4f641fd4a393f57fb7a645936e958b55a451bba2a024
BLAKE2b-256 checksum
How to use checksums
cadbd60667f541bb6d19cc6bf23957eb0b0ce0584563822ea303478bbf056660
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.dev202607291784631574-cp310-abi3-manylinux2014_aarch64.whl

Download URL pyagrum_nightly-3.0.0.9.dev202607291784631574-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
eeca63790e56cf0fb60f1f984bf99a0e996f3e32b11fbc5abf403e3e98cb702d
BLAKE2b-256 checksum
How to use checksums
fa92da86893c84901160a2e542805b318513621b3098f4cc80b4d6be72167150
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.dev202607291784631574-cp310-abi3-macosx_11_0_arm64.whl

Download URL pyagrum_nightly-3.0.0.9.dev202607291784631574-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
bfc2aaa0341a895c39b76c0cf8675cef76172f3e1582f53697926beea021030f
BLAKE2b-256 checksum
How to use checksums
1a902d174bdc411daa9324e1fbd571d6673954467089df3b42a8a5f03b668b39
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.dev202607291784631574-cp310-abi3-macosx_10_15_x86_64.whl

Download URL pyagrum_nightly-3.0.0.9.dev202607291784631574-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
4f2c3b9ab8190858f8fe30400f9c9a95ecaa569cf505ae7e99affd66d52bc47c
BLAKE2b-256 checksum
How to use checksums
03ba8c9f1cc345d2d4e7e536d5455af03778b75e61c43c966942b5eda4a20a69
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