Skip to main content

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 3.1.1

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 3.1.1
File
pyagrum-3.1.1-cp310-abi3-win_amd64.whl CPython 3.10 abi3 Windows x86-64 Details
pyagrum-3.1.1-cp310-abi3-manylinux2014_x86_64.whl CPython 3.10 abi3 Linux glibc 2.17+ x86-64 Details
pyagrum-3.1.1-cp310-abi3-manylinux2014_aarch64.whl CPython 3.10 abi3 Linux glibc 2.17+ ARM64 Details
pyagrum-3.1.1-cp310-abi3-macosx_11_0_arm64.whl CPython 3.10 abi3 macOS 11.0+ ARM64 Details
pyagrum-3.1.1-cp310-abi3-macosx_10_15_x86_64.whl CPython 3.10 abi3 macOS 10.15+ x86-64 Details

Total release size: 20.8 MB

Release files / pyagrum-3.1.1-cp310-abi3-win_amd64.whl

Download URL pyagrum-3.1.1-cp310-abi3-win_amd64.whl
Size 3.5 MB
Tags CPython 3.10 Windows x86-64 abi3
SHA-256 checksum
How to use checksums
c405dd4bb97c7546caf0e43d342a88f9e55a9ca7c0e711526a76702319d46399
BLAKE2b-256 checksum
How to use checksums
165bb586b90e520928437577092a3601d3ca2c82b05070baad91cf8b1d3b2747
Upload date
Uploaded using Trusted Publishing?
What is trusted publishing?
No
Uploaded via twine/6.1.0 CPython/3.8.10

Release files / pyagrum-3.1.1-cp310-abi3-manylinux2014_x86_64.whl

Download URL pyagrum-3.1.1-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
e09799abde542fe4e4b9f9d1bfecd0914b6e3fd5f5587c46a9511150f6c91b60
BLAKE2b-256 checksum
How to use checksums
02519207df53ab55779bbee6ff3eadfc833a855079b9e69de0e38bdff9ee9864
Upload date
Uploaded using Trusted Publishing?
What is trusted publishing?
No
Uploaded via twine/6.1.0 CPython/3.8.10

Release files / pyagrum-3.1.1-cp310-abi3-manylinux2014_aarch64.whl

Download URL pyagrum-3.1.1-cp310-abi3-manylinux2014_aarch64.whl
Size 4.7 MB
Tags CPython 3.10 Linux glibc 2.17+ ARM64 abi3
SHA-256 checksum
How to use checksums
1468242656fbee9011815ba67023bb88bf07aba93c6cc1a098dd259262fdb1b1
BLAKE2b-256 checksum
How to use checksums
edbb1be82316e6b979f2c70e09710ad17320b109cc7bf556b28724a228bcbd16
Upload date
Uploaded using Trusted Publishing?
What is trusted publishing?
No
Uploaded via twine/6.1.0 CPython/3.8.10

Release files / pyagrum-3.1.1-cp310-abi3-macosx_11_0_arm64.whl

Download URL pyagrum-3.1.1-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
ac6e5fdfe9ea41a1d66bc001e790955a33885155f3c10865faafcbb4f9e0cd93
BLAKE2b-256 checksum
How to use checksums
5944bcd383d9a98fec61e70637df26242169e2cb88e11b0ebfb61f53487cc616
Upload date
Uploaded using Trusted Publishing?
What is trusted publishing?
No
Uploaded via twine/6.1.0 CPython/3.8.10

Release files / pyagrum-3.1.1-cp310-abi3-macosx_10_15_x86_64.whl

Download URL pyagrum-3.1.1-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
9299eb8bb128ee334e6efacf83e9ca3e5f49f6d09257b9ed0bee63e972ca83f0
BLAKE2b-256 checksum
How to use checksums
a6ac890e273132678aee6b8f84fac409efd04665aac615445739c738fdba415c
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

3.1.1 This release

5 release files

3.0.0

5 release files

2.3.2

5 release files

2.3.1

5 release files

2.3.0

5 release files

2.2.1

5 release files

2.2.0

5 release files

2.1.1

5 release files

2.1.0

5 release files

2.0.1

5 release files

2.0.0

5 release files

1.9.0

20 release files

1.8.3

20 release files

1.8.1

20 release files

1.7.1

20 release files

1.7.0

20 release files

1.6.1

20 release files

1.6.0

20 release files

1.5.1

20 release files

1.3.2

15 release files

1.3.1

15 release files

1.1.0

15 release files

1.0.0

15 release files

0.12.0

0.9.3.5

1 release file

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