Skip to main content

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.

Release history Release notifications | RSS feed

This version

1.8.0

Download files

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

Source Distributions

No source distribution files available for this release.See tutorial on generating distribution archives.

Built Distributions

If you're not sure about the file name format, learn more about wheel file names.

pyAgrum-1.8.0-cp311-cp311-win_amd64.whl (2.6 MB view details)

Uploaded CPython 3.11Windows x86-64

pyAgrum-1.8.0-cp311-cp311-manylinux2014_x86_64.whl (5.6 MB view details)

Uploaded CPython 3.11

pyAgrum-1.8.0-cp311-cp311-manylinux2014_aarch64.whl (5.2 MB view details)

Uploaded CPython 3.11

pyAgrum-1.8.0-cp311-cp311-macosx_11_0_arm64.whl (3.8 MB view details)

Uploaded CPython 3.11macOS 11.0+ ARM64

pyAgrum-1.8.0-cp311-cp311-macosx_10_9_x86_64.whl (4.3 MB view details)

Uploaded CPython 3.11macOS 10.9+ x86-64

pyAgrum-1.8.0-cp310-cp310-win_amd64.whl (2.6 MB view details)

Uploaded CPython 3.10Windows x86-64

pyAgrum-1.8.0-cp310-cp310-manylinux2014_x86_64.whl (5.6 MB view details)

Uploaded CPython 3.10

pyAgrum-1.8.0-cp310-cp310-manylinux2014_aarch64.whl (5.2 MB view details)

Uploaded CPython 3.10

pyAgrum-1.8.0-cp310-cp310-macosx_11_0_arm64.whl (3.8 MB view details)

Uploaded CPython 3.10macOS 11.0+ ARM64

pyAgrum-1.8.0-cp310-cp310-macosx_10_9_x86_64.whl (4.3 MB view details)

Uploaded CPython 3.10macOS 10.9+ x86-64

pyAgrum-1.8.0-cp39-cp39-win_amd64.whl (2.6 MB view details)

Uploaded CPython 3.9Windows x86-64

pyAgrum-1.8.0-cp39-cp39-manylinux2014_x86_64.whl (5.6 MB view details)

Uploaded CPython 3.9

pyAgrum-1.8.0-cp39-cp39-manylinux2014_aarch64.whl (5.2 MB view details)

Uploaded CPython 3.9

pyAgrum-1.8.0-cp39-cp39-macosx_11_0_arm64.whl (3.8 MB view details)

Uploaded CPython 3.9macOS 11.0+ ARM64

pyAgrum-1.8.0-cp39-cp39-macosx_10_9_x86_64.whl (4.3 MB view details)

Uploaded CPython 3.9macOS 10.9+ x86-64

pyAgrum-1.8.0-cp38-cp38-win_amd64.whl (2.6 MB view details)

Uploaded CPython 3.8Windows x86-64

pyAgrum-1.8.0-cp38-cp38-manylinux2014_x86_64.whl (5.6 MB view details)

Uploaded CPython 3.8

pyAgrum-1.8.0-cp38-cp38-manylinux2014_aarch64.whl (5.2 MB view details)

Uploaded CPython 3.8

pyAgrum-1.8.0-cp38-cp38-macosx_11_0_arm64.whl (3.8 MB view details)

Uploaded CPython 3.8macOS 11.0+ ARM64

pyAgrum-1.8.0-cp38-cp38-macosx_10_9_x86_64.whl (4.3 MB view details)

Uploaded CPython 3.8macOS 10.9+ x86-64

File details

Details for the file pyAgrum-1.8.0-cp311-cp311-win_amd64.whl.

File metadata

  • Download URL: pyAgrum-1.8.0-cp311-cp311-win_amd64.whl
  • Upload date:
  • Size: 2.6 MB
  • Tags: CPython 3.11, Windows x86-64
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/4.0.2 CPython/3.11.3

File hashes

Hashes for pyAgrum-1.8.0-cp311-cp311-win_amd64.whl
Algorithm Hash digest
SHA256 90176ecfa2a986844d90925a2983b9a57a5ddbb69d6360033409f3b6e4a5ab2c
MD5 e3d5d2b0312344aab5bbbe8f22ea4259
BLAKE2b-256 b6c7ceabc6d1ff7002cb18a8b9b6b4770326e2bbae0657b1faea99d2dfec6b50

See more details on using hashes here.

File details

Details for the file pyAgrum-1.8.0-cp311-cp311-manylinux2014_x86_64.whl.

File metadata

File hashes

Hashes for pyAgrum-1.8.0-cp311-cp311-manylinux2014_x86_64.whl
Algorithm Hash digest
SHA256 0c12b9956236312348acda329819b95605885b3cd3d7ebe556fdee92525bd522
MD5 03b7da4c0d6e028aaca8299b11b73b84
BLAKE2b-256 e8b421c6dd60754cb4feca48a8ad91cc9081a2a6a5c5143d95e53ecbafd156c7

See more details on using hashes here.

File details

Details for the file pyAgrum-1.8.0-cp311-cp311-manylinux2014_aarch64.whl.

File metadata

File hashes

Hashes for pyAgrum-1.8.0-cp311-cp311-manylinux2014_aarch64.whl
Algorithm Hash digest
SHA256 01257aa99e6a98336a87146766b6d6297e0e85fb55033c9fc39a137a53ecc80e
MD5 495deaf34706b26bc82752222f9920fa
BLAKE2b-256 4c73d4f93840f65530a7d3a939d5b631ded80400424aa3d5b89cc2f675041891

See more details on using hashes here.

File details

Details for the file pyAgrum-1.8.0-cp311-cp311-macosx_11_0_arm64.whl.

File metadata

File hashes

Hashes for pyAgrum-1.8.0-cp311-cp311-macosx_11_0_arm64.whl
Algorithm Hash digest
SHA256 b78153ab05a2448a3d41b838e6eed63448d5e726accfbc2b97c97a75e030d037
MD5 de19a5474ab8bf28b8d3a5edeb3c352b
BLAKE2b-256 581e88e5eeb802883b17d2d5051ed1e36461486acf12d67bd1af8a3c5eeb3a3d

See more details on using hashes here.

File details

Details for the file pyAgrum-1.8.0-cp311-cp311-macosx_10_9_x86_64.whl.

File metadata

File hashes

Hashes for pyAgrum-1.8.0-cp311-cp311-macosx_10_9_x86_64.whl
Algorithm Hash digest
SHA256 a67032d3cb40538cc9621ffc51654a5c3706e720ef4ca2f44fbe4db43cda3d36
MD5 02a8671f393afc6d182aca20bf90a498
BLAKE2b-256 945d46242ce872315c80177989ad7bf072a0a13e3afbab542fce160366ffc121

See more details on using hashes here.

File details

Details for the file pyAgrum-1.8.0-cp310-cp310-win_amd64.whl.

File metadata

  • Download URL: pyAgrum-1.8.0-cp310-cp310-win_amd64.whl
  • Upload date:
  • Size: 2.6 MB
  • Tags: CPython 3.10, Windows x86-64
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/4.0.2 CPython/3.11.3

File hashes

Hashes for pyAgrum-1.8.0-cp310-cp310-win_amd64.whl
Algorithm Hash digest
SHA256 1895b18930bf25698a1f2d335b4b0e1b8580568ef078eed62754e2c6fcf4e27a
MD5 cd4ffafe5dc62e544ddeab539b96d3b5
BLAKE2b-256 b4e85b7423fd59dab3226b1b84a41f78ac34e0f62b376daf8dad26b662ba16bb

See more details on using hashes here.

File details

Details for the file pyAgrum-1.8.0-cp310-cp310-manylinux2014_x86_64.whl.

File metadata

File hashes

Hashes for pyAgrum-1.8.0-cp310-cp310-manylinux2014_x86_64.whl
Algorithm Hash digest
SHA256 661c39f86f9e27365640582c404895ef2989b1a81fa15a09cee331e155478b27
MD5 7b4169c2c2ce7a5f447dabc3d52e8af4
BLAKE2b-256 8bb0c7616fb333da8905f562670cb7072587932005edb2a55ffa9326c5e733f1

See more details on using hashes here.

File details

Details for the file pyAgrum-1.8.0-cp310-cp310-manylinux2014_aarch64.whl.

File metadata

File hashes

Hashes for pyAgrum-1.8.0-cp310-cp310-manylinux2014_aarch64.whl
Algorithm Hash digest
SHA256 4cc84356fe62564849dcdc3a7fdec08de0813689f56bf91430db7a4b89e6af1c
MD5 bb5a37dc16e70ede7f9aad926585a33f
BLAKE2b-256 470bbf1d9bb69a51685db24c18c35a442baad03e86d1795a1acecccb4cd9bab2

See more details on using hashes here.

File details

Details for the file pyAgrum-1.8.0-cp310-cp310-macosx_11_0_arm64.whl.

File metadata

File hashes

Hashes for pyAgrum-1.8.0-cp310-cp310-macosx_11_0_arm64.whl
Algorithm Hash digest
SHA256 a9b472c99a9f651b2f290f798e4efda2abec4d85f41cf0ed4d6f22534f5c097b
MD5 2d2261324e8c4f00487e0e408484a836
BLAKE2b-256 02f940fe85c0cc678efb4909aa6d164045f279def443e67082a2a7b57c9d1eb8

See more details on using hashes here.

File details

Details for the file pyAgrum-1.8.0-cp310-cp310-macosx_10_9_x86_64.whl.

File metadata

File hashes

Hashes for pyAgrum-1.8.0-cp310-cp310-macosx_10_9_x86_64.whl
Algorithm Hash digest
SHA256 9fdf1ee7a4bc266786c773f992271f24c6a1bb6fc38369021b15ff554d6f369d
MD5 2bcdf78dfb8000eebc693ebad3172884
BLAKE2b-256 ffab90c781aa46c3c2bf5222b39ac51fdda2e706eca0308846134b0242952f80

See more details on using hashes here.

File details

Details for the file pyAgrum-1.8.0-cp39-cp39-win_amd64.whl.

File metadata

  • Download URL: pyAgrum-1.8.0-cp39-cp39-win_amd64.whl
  • Upload date:
  • Size: 2.6 MB
  • Tags: CPython 3.9, Windows x86-64
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/4.0.2 CPython/3.11.3

File hashes

Hashes for pyAgrum-1.8.0-cp39-cp39-win_amd64.whl
Algorithm Hash digest
SHA256 005a13c14eae72193563e3048b4b4dbf16a187cc7b9c2a9969e8d0fde4cff6f3
MD5 d713b96df60cf15c9cd4536638ba5090
BLAKE2b-256 65c02569a3a2ca87914f1eb68317f69b1ad99951e0b814a2b208e51436d10df3

See more details on using hashes here.

File details

Details for the file pyAgrum-1.8.0-cp39-cp39-manylinux2014_x86_64.whl.

File metadata

File hashes

Hashes for pyAgrum-1.8.0-cp39-cp39-manylinux2014_x86_64.whl
Algorithm Hash digest
SHA256 52a9768b6b24849e713d0f6c7f73007290c2ab4491d8df47586fdbed29bc09d8
MD5 7f9eb6cf3d875fdec344a2c6558b3aef
BLAKE2b-256 86f61671bd0fbd8fe39116fef0f4791640d915db9a6ff9ab10b0dc28e0129cb3

See more details on using hashes here.

File details

Details for the file pyAgrum-1.8.0-cp39-cp39-manylinux2014_aarch64.whl.

File metadata

File hashes

Hashes for pyAgrum-1.8.0-cp39-cp39-manylinux2014_aarch64.whl
Algorithm Hash digest
SHA256 c64757e9aef180167efb09a95ce9b561d4674423b72f8987d2ccab148060a411
MD5 1fd109183b85752a9c982834e627c0ab
BLAKE2b-256 76dead7affcc5c9813d4f08b563207fe091e90f28b50acf78dbdca371c7a2be2

See more details on using hashes here.

File details

Details for the file pyAgrum-1.8.0-cp39-cp39-macosx_11_0_arm64.whl.

File metadata

File hashes

Hashes for pyAgrum-1.8.0-cp39-cp39-macosx_11_0_arm64.whl
Algorithm Hash digest
SHA256 9fecfe2717114b835d2018b84a9bf2ff39405f86bda17f35918a744633fb768f
MD5 c9c809043f9b7ab26e52d02b808e61ce
BLAKE2b-256 c0877adb9e74e4758bdd82b01ee56c30582b5023ea68c09003376092c8bcd2e3

See more details on using hashes here.

File details

Details for the file pyAgrum-1.8.0-cp39-cp39-macosx_10_9_x86_64.whl.

File metadata

File hashes

Hashes for pyAgrum-1.8.0-cp39-cp39-macosx_10_9_x86_64.whl
Algorithm Hash digest
SHA256 ddd6ca108975d02fe3d5acbc450d4b39b1431b50f6f22c40407e08fc45485ad7
MD5 64e20dd27f65b46a3cb5ede873d1bb64
BLAKE2b-256 ed825b20c74963d1f230c41992b14340c47b434cfa2457f963d7ecaecf99f12a

See more details on using hashes here.

File details

Details for the file pyAgrum-1.8.0-cp38-cp38-win_amd64.whl.

File metadata

  • Download URL: pyAgrum-1.8.0-cp38-cp38-win_amd64.whl
  • Upload date:
  • Size: 2.6 MB
  • Tags: CPython 3.8, Windows x86-64
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/4.0.2 CPython/3.11.3

File hashes

Hashes for pyAgrum-1.8.0-cp38-cp38-win_amd64.whl
Algorithm Hash digest
SHA256 c69651a63aa9cecbd8204f4f89935e8fdaa09a13e2d0be9594c6f3dd4588f08b
MD5 f9c9df3544374df3bb435dc3ebf9dbe5
BLAKE2b-256 3b6ac4a65475e12a4c3696f16b399b0fe007e959cde1a7019d2c0c33eb49c0a8

See more details on using hashes here.

File details

Details for the file pyAgrum-1.8.0-cp38-cp38-manylinux2014_x86_64.whl.

File metadata

File hashes

Hashes for pyAgrum-1.8.0-cp38-cp38-manylinux2014_x86_64.whl
Algorithm Hash digest
SHA256 3faa090828176bdf268448f14721db15575465cc6315e08250bb845068f104dc
MD5 376e523951982f867f7e02381cfdf3b1
BLAKE2b-256 1a4741436dc7a3da8ce2901d95c923b08c02f7f53f2167ce373203ec319900f4

See more details on using hashes here.

File details

Details for the file pyAgrum-1.8.0-cp38-cp38-manylinux2014_aarch64.whl.

File metadata

File hashes

Hashes for pyAgrum-1.8.0-cp38-cp38-manylinux2014_aarch64.whl
Algorithm Hash digest
SHA256 17084ad375fd465b8ee0bb597e7f47b4c940409f7ce6e81d768e10d71cf15fe5
MD5 2a17bac23614b3c39fa2e05ca22caf61
BLAKE2b-256 02d0cb1e87c5029a41b57d118048445df5ca2811fc07106f0495c9a5863f604f

See more details on using hashes here.

File details

Details for the file pyAgrum-1.8.0-cp38-cp38-macosx_11_0_arm64.whl.

File metadata

File hashes

Hashes for pyAgrum-1.8.0-cp38-cp38-macosx_11_0_arm64.whl
Algorithm Hash digest
SHA256 2dc58f9065d7d7dc97fb8a84f13a35a9df547b7db86709524c2ee85d2917c0a8
MD5 8ba64142eb30e204bb2146a29278eb68
BLAKE2b-256 8f925be6bd1f15e6be0fe5973918f5fbeb156fec70cf5e9a0fffb1e8d6eb32ed

See more details on using hashes here.

File details

Details for the file pyAgrum-1.8.0-cp38-cp38-macosx_10_9_x86_64.whl.

File metadata

File hashes

Hashes for pyAgrum-1.8.0-cp38-cp38-macosx_10_9_x86_64.whl
Algorithm Hash digest
SHA256 b237c947fefc388dae4cf778c38fb627789d42479e79531c651490a69bc9ab00
MD5 43cb1c3df048bd71f4a714ec07a93911
BLAKE2b-256 914c4fdd520f122bff82ded92c65eded2f9b58c28798d87bb4b49f166a130b47

See more details on using hashes here.

Supported by

AWS Cloud computing and Security Sponsor Datadog Monitoring Depot Continuous Integration Fastly CDN Google Download Analytics Pingdom Monitoring Sentry Error logging StatusPage Status page