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.dev202607271784631574

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.dev202607271784631574
File
pyagrum_nightly-3.0.0.9.dev202607271784631574-cp310-abi3-win_amd64.whl CPython 3.10 abi3 Windows x86-64 Details
pyagrum_nightly-3.0.0.9.dev202607271784631574-cp310-abi3-manylinux2014_x86_64.whl CPython 3.10 abi3 Linux glibc 2.17+ x86-64 Details
pyagrum_nightly-3.0.0.9.dev202607271784631574-cp310-abi3-manylinux2014_aarch64.whl CPython 3.10 abi3 Linux glibc 2.17+ ARM64 Details
pyagrum_nightly-3.0.0.9.dev202607271784631574-cp310-abi3-macosx_11_0_arm64.whl CPython 3.10 abi3 macOS 11.0+ ARM64 Details
pyagrum_nightly-3.0.0.9.dev202607271784631574-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.dev202607271784631574-cp310-abi3-win_amd64.whl

Download URL pyagrum_nightly-3.0.0.9.dev202607271784631574-cp310-abi3-win_amd64.whl
Size 3.5 MB
Tags CPython 3.10 Windows x86-64 abi3
SHA-256 checksum
How to use checksums
c65c958e545813a8bca93e8368e59883c03ceaa84369103ba27d94d2c5cf40e4
BLAKE2b-256 checksum
How to use checksums
82ff29ed1f4716abe13923dbf02e75454e57cae1e4a54e006f90c9808b204454
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.dev202607271784631574-cp310-abi3-manylinux2014_x86_64.whl

Download URL pyagrum_nightly-3.0.0.9.dev202607271784631574-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
9684e663e6a97af7251eaf1a0061d1827f15c3a6a71c8cf02b43897cd403d86d
BLAKE2b-256 checksum
How to use checksums
c9972a9d1cba6909779c29312aa815e70984eb6c417a85d45c681396c57540e2
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.dev202607271784631574-cp310-abi3-manylinux2014_aarch64.whl

Download URL pyagrum_nightly-3.0.0.9.dev202607271784631574-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
9005aad8ef0b2b9861e741e09b4aad2360e94fd0659f4a3244ba28c06cba6231
BLAKE2b-256 checksum
How to use checksums
6c3628e112d9aa248e843e92245b8165a86a907fcb084359217587285ebab895
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.dev202607271784631574-cp310-abi3-macosx_11_0_arm64.whl

Download URL pyagrum_nightly-3.0.0.9.dev202607271784631574-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
ed07123838ba183292805c22156815408da60be5ad75f7ba857c3e92f4d406cd
BLAKE2b-256 checksum
How to use checksums
524352fe26ade01ee743101b9df9ca31af283b22b0b0255699955c75990d951c
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.dev202607271784631574-cp310-abi3-macosx_10_15_x86_64.whl

Download URL pyagrum_nightly-3.0.0.9.dev202607271784631574-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
e42f3c9ef8f9ba2069d3423040a2c36e89fcaa74c800d9474b161879ecc74d23
BLAKE2b-256 checksum
How to use checksums
805b0b68a8f9a30027d06622bf2757811e342b81fc5f8bd3ec6036476a9ac3c8
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