pyagrum

Bayesian networks and other Probabilistic Graphical Models.

Project description

Description: 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 the C++ aGrUM library 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. The module is mainly generated by the SWIG interface generator.

Project details

Release history Release notifications | RSS feed

This version

1.1.0

May 13, 2022

1.0.0

Apr 19, 2022

0.22.9

Mar 29, 2022

0.22.8

Feb 22, 2022

0.22.7

Feb 2, 2022

0.22.6

Jan 29, 2022

0.22.5

Dec 8, 2021

0.22.4

Nov 19, 2021

0.22.3

Nov 2, 2021

0.22.2

Sep 21, 2021

0.22.1

Sep 8, 2021

0.22.0

Aug 6, 2021

0.21.0

Jul 24, 2021

0.20.3

Jun 7, 2021

0.20.2

May 2, 2021

0.20.1

Apr 15, 2021

0.20.0

Apr 8, 2021

0.19.3

Mar 3, 2021

0.19.2

Feb 21, 2021

0.19.1

Feb 13, 2021

0.19.0

Jan 5, 2021

0.18.2

Nov 1, 2020

0.18.1

Jul 20, 2020

0.18.0

Jun 11, 2020

0.17.3

Apr 27, 2020

0.17.2

Mar 23, 2020

0.17.1

Feb 11, 2020

0.17.0

Jan 22, 2020

0.16.4

Dec 15, 2019

0.16.3

Oct 18, 2019

0.16.2

Sep 21, 2019

0.16.1

Sep 20, 2019

0.16.0

Aug 27, 2019

0.15.2

Jul 13, 2019

0.15.1

Jun 16, 2019

0.15.0

May 9, 2019

0.14.3

Apr 3, 2019

0.14.2

Feb 28, 2019

0.14.1

Feb 8, 2019

0.13.6

Jan 8, 2019

0.13.5

Dec 21, 2018

0.13.4.9

Dec 19, 2018

0.13.3

Nov 1, 2018

0.13.2.1

Jun 11, 2018

0.13.1.2

Jun 7, 2018

0.13.1.1

Jun 7, 2018

0.13.0.1

May 29, 2018

0.12.1.0

Apr 9, 2018

0.12.0.9.1

May 25, 2018

0.12.0.3

Sep 29, 2017

0.12.0.1

Jun 27, 2017

0.12.0

Jun 27, 2017

0.11.2

May 10, 2017

0.11.1.9

Apr 3, 2017

0.10.4.3

Feb 7, 2017

0.10.3.4

Jan 5, 2017

0.10.1.1

Dec 13, 2016

0.10.0.1

Dec 3, 2016

0.9.3.7

Nov 4, 2016

0.9.3.6

Oct 31, 2016

0.9.3.5

Oct 31, 2016

0.9.3.4

Oct 28, 2016

Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Built Distributions

pyAgrum-1.1.0-cp310-cp310-win_amd64.whl (2.5 MB view hashes)

Uploaded May 13, 2022 cp310

pyAgrum-1.1.0-cp310-cp310-manylinux2014_x86_64.whl (5.6 MB view hashes)

Uploaded May 13, 2022 cp310

pyAgrum-1.1.0-cp310-cp310-manylinux2014_aarch64.whl (5.2 MB view hashes)

Uploaded May 13, 2022 cp310

pyAgrum-1.1.0-cp310-cp310-macosx_11_0_arm64.whl (3.9 MB view hashes)

Uploaded May 13, 2022 cp310

pyAgrum-1.1.0-cp310-cp310-macosx_10_9_x86_64.whl (4.2 MB view hashes)

Uploaded May 13, 2022 cp310

pyAgrum-1.1.0-cp39-cp39-win_amd64.whl (2.5 MB view hashes)

Uploaded May 13, 2022 cp39

pyAgrum-1.1.0-cp39-cp39-manylinux2014_x86_64.whl (5.6 MB view hashes)

Uploaded May 13, 2022 cp39

pyAgrum-1.1.0-cp39-cp39-manylinux2014_aarch64.whl (5.2 MB view hashes)

Uploaded May 13, 2022 cp39

pyAgrum-1.1.0-cp39-cp39-macosx_11_0_arm64.whl (3.9 MB view hashes)

Uploaded May 13, 2022 cp39

pyAgrum-1.1.0-cp39-cp39-macosx_10_9_x86_64.whl (4.2 MB view hashes)

Uploaded May 13, 2022 cp39

pyAgrum-1.1.0-cp38-cp38-win_amd64.whl (2.5 MB view hashes)

Uploaded May 13, 2022 cp38

pyAgrum-1.1.0-cp38-cp38-manylinux2014_x86_64.whl (5.6 MB view hashes)

Uploaded May 13, 2022 cp38

pyAgrum-1.1.0-cp38-cp38-manylinux2014_aarch64.whl (5.2 MB view hashes)

Uploaded May 13, 2022 cp38

pyAgrum-1.1.0-cp38-cp38-macosx_11_0_arm64.whl (3.9 MB view hashes)

Uploaded May 13, 2022 cp38

pyAgrum-1.1.0-cp38-cp38-macosx_10_9_x86_64.whl (4.2 MB view hashes)

Uploaded May 13, 2022 cp38

Hashes for pyAgrum-1.1.0-cp310-cp310-win_amd64.whl

Hashes for pyAgrum-1.1.0-cp310-cp310-win_amd64.whl
Algorithm	Hash digest
SHA256	`747918d5654f97b9b553aace8cca5781604fe83ef5a98a90fc5cc71834933c28`
MD5	`e1df629658f3a4b719139801a8aac237`
BLAKE2-256	`aa08a327f172d06ebc1229e23195efe0dc32bbb85ffe7209efec8b81a47fdf14`

Hashes for pyAgrum-1.1.0-cp310-cp310-manylinux2014_x86_64.whl

Hashes for pyAgrum-1.1.0-cp310-cp310-manylinux2014_x86_64.whl
Algorithm	Hash digest
SHA256	`5f8b445474cdc9e876f3cc6a35623ad2fb1daa6ab17360c088428ee63773c4d7`
MD5	`781833b1cca3f9de4a011c49b902e41b`
BLAKE2-256	`74a5e9e2c7465ab370084e45b811ca9b129a11d73f1d1b0d65a8151711231b6c`

Hashes for pyAgrum-1.1.0-cp310-cp310-manylinux2014_aarch64.whl

Hashes for pyAgrum-1.1.0-cp310-cp310-manylinux2014_aarch64.whl
Algorithm	Hash digest
SHA256	`dd8b9a1a470e7929d260bbde51027c73d707aa13b94adacc9b9a549e29d586cd`
MD5	`b0dff02930c15f9fda9240cd0e740e0d`
BLAKE2-256	`3fa4ec31c4845ca6a82e4cd2b77ef8ba5eea19f4bf5ef5f8f525fde9484dd604`

Hashes for pyAgrum-1.1.0-cp310-cp310-macosx_11_0_arm64.whl

Hashes for pyAgrum-1.1.0-cp310-cp310-macosx_11_0_arm64.whl
Algorithm	Hash digest
SHA256	`c4ce98696755ed7043d649fb73b6e3422238731266f97d79caecc2ff21ff8c2c`
MD5	`852e1528049f5383458f12ebdd069716`
BLAKE2-256	`876a08dbc9b6057fb206bf5cf0d63d3fc863dfe0fe9ccd3be5ea5fa864b9fa3a`

Hashes for pyAgrum-1.1.0-cp310-cp310-macosx_10_9_x86_64.whl

Hashes for pyAgrum-1.1.0-cp310-cp310-macosx_10_9_x86_64.whl
Algorithm	Hash digest
SHA256	`5b0818311a43a4e3897bf5ecbb0e4fc2123a86fca6fde5e8d34ab7498a882e0f`
MD5	`0ae49bac6c030a67e1ddee05c08313c4`
BLAKE2-256	`179c837002e2b8d463ffd4eb0ade990509d9492975d28fdcf0a36de98b17b6a2`

Hashes for pyAgrum-1.1.0-cp39-cp39-win_amd64.whl

Hashes for pyAgrum-1.1.0-cp39-cp39-win_amd64.whl
Algorithm	Hash digest
SHA256	`4e0ff76ba7430707c6a628616fb66fc35c636196624fc26bf6518f3d511815bb`
MD5	`eb0f8f2ac93e76fb92c817f5338c6305`
BLAKE2-256	`0ae30f48bf4497a347a4a8889a1c51516c9757c2cccd4917aeea9ac5bc1c9be2`

Hashes for pyAgrum-1.1.0-cp39-cp39-manylinux2014_x86_64.whl

Hashes for pyAgrum-1.1.0-cp39-cp39-manylinux2014_x86_64.whl
Algorithm	Hash digest
SHA256	`c5635814fb4ada493a3bcf9ad456efc9e8de71c70e1bab9027eb641a8e51f8ee`
MD5	`5884d1fb1524f45da0efe926d64ae929`
BLAKE2-256	`50a58bcd1a53d6fecba20e8535b37de3523843a9bd3e6545016d28a47bdbb890`

Hashes for pyAgrum-1.1.0-cp39-cp39-manylinux2014_aarch64.whl

Hashes for pyAgrum-1.1.0-cp39-cp39-manylinux2014_aarch64.whl
Algorithm	Hash digest
SHA256	`6f427495d0907349951f2368ced7143189f28233906dab543e6dca9f0b145c19`
MD5	`afe04041d47b81d5a3f2fcc9c5223817`
BLAKE2-256	`d7f031a1edf0b7d90ab15b052c05d5b4c3930f718098c8f02811d44c589f98d2`

Hashes for pyAgrum-1.1.0-cp39-cp39-macosx_11_0_arm64.whl

Hashes for pyAgrum-1.1.0-cp39-cp39-macosx_11_0_arm64.whl
Algorithm	Hash digest
SHA256	`a7fbc74fee2a5363e22600cf7f9bcd09dfdf7f27231dc72ef3951f3dba3a7f2d`
MD5	`33f74bf6dd5297ddefe4bd81649fb8d5`
BLAKE2-256	`adedb05a5fb214b3d6d356cf31662e22f140659acb0b42c23a09ab6920bbda1a`

Hashes for pyAgrum-1.1.0-cp39-cp39-macosx_10_9_x86_64.whl

Hashes for pyAgrum-1.1.0-cp39-cp39-macosx_10_9_x86_64.whl
Algorithm	Hash digest
SHA256	`db13e42a157930a522e2e6ed3447de99e3cac6edd030e705cb9a1e023a316cb3`
MD5	`998d9f88aefe116b2e99c0e02638bad7`
BLAKE2-256	`1d9511ac89708046d8b8f5ef7f377468d7faca529c4e9e40b8c41486b8da7827`

Hashes for pyAgrum-1.1.0-cp38-cp38-win_amd64.whl

Hashes for pyAgrum-1.1.0-cp38-cp38-win_amd64.whl
Algorithm	Hash digest
SHA256	`b59a53e632a218746ad2881dd3414d5dc69fe097706cdf601b6d8fc22d43dd09`
MD5	`219da494eceb3f9dad048bbb037e8f93`
BLAKE2-256	`013accf1e44a88933e8eadb9c6aafdec717bdddb9f964c9cd338dcc6dc3362b2`

Hashes for pyAgrum-1.1.0-cp38-cp38-manylinux2014_x86_64.whl

Hashes for pyAgrum-1.1.0-cp38-cp38-manylinux2014_x86_64.whl
Algorithm	Hash digest
SHA256	`c7f1f14d37dcfc2882b6171c074fdb44a398064f91ec2267743aae0c7522e0ac`
MD5	`d709bb7b9f179266df14e3fba0d9a755`
BLAKE2-256	`672fe0d7737d8340fd310a4d68d66d6bfb6106722434bc14ed26d91ece637041`

Hashes for pyAgrum-1.1.0-cp38-cp38-manylinux2014_aarch64.whl

Hashes for pyAgrum-1.1.0-cp38-cp38-manylinux2014_aarch64.whl
Algorithm	Hash digest
SHA256	`f815f8b588efdfba2b220d43a5c2e0994f7be7509f80a649cb7e42a3abda26f8`
MD5	`6b3190d1dc20e191aa8322d43c73de47`
BLAKE2-256	`fe2159b5141ed38ccb9a267c9ffc9d501f3ff41939c59ec6bbd2e4f2ade41a0a`

Hashes for pyAgrum-1.1.0-cp38-cp38-macosx_11_0_arm64.whl

Hashes for pyAgrum-1.1.0-cp38-cp38-macosx_11_0_arm64.whl
Algorithm	Hash digest
SHA256	`3c74e0ff9f98b2e8c9b7f581bac2ed1615779adf624743598bf6bdd1e4bb5dfc`
MD5	`064f85fe030b912290bf3f5f61d5fe11`
BLAKE2-256	`470d6d51ddb8275bed4db6ea3c9e35f06de79d92bc749536251080ee80e07640`

Hashes for pyAgrum-1.1.0-cp38-cp38-macosx_10_9_x86_64.whl

Hashes for pyAgrum-1.1.0-cp38-cp38-macosx_10_9_x86_64.whl
Algorithm	Hash digest
SHA256	`11f24e212447ab4af2b07b06dacc31b6ce9f6810b756c94b8c4bc2f126e4ee9a`
MD5	`be552e2710f4865aff69177c6682341a`
BLAKE2-256	`5e26ab59fd63b8b4e1e4e1181da48b57f177d9b06c07211bf59395b8486dba9f`