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

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

pyAgrum_nightly-1.5.2.9.dev202302061674421262-cp311-cp311-win_amd64.whl (2.6 MB view details)

Uploaded CPython 3.11 Windows x86-64

pyAgrum_nightly-1.5.2.9.dev202302061674421262-cp311-cp311-macosx_11_0_arm64.whl (4.0 MB view details)

Uploaded CPython 3.11 macOS 11.0+ ARM64

pyAgrum_nightly-1.5.2.9.dev202302061674421262-cp311-cp311-macosx_10_9_x86_64.whl (4.3 MB view details)

Uploaded CPython 3.11 macOS 10.9+ x86-64

pyAgrum_nightly-1.5.2.9.dev202302061674421262-cp310-cp310-win_amd64.whl (2.6 MB view details)

Uploaded CPython 3.10 Windows x86-64

pyAgrum_nightly-1.5.2.9.dev202302061674421262-cp310-cp310-macosx_11_0_arm64.whl (4.0 MB view details)

Uploaded CPython 3.10 macOS 11.0+ ARM64

pyAgrum_nightly-1.5.2.9.dev202302061674421262-cp310-cp310-macosx_10_9_x86_64.whl (4.3 MB view details)

Uploaded CPython 3.10 macOS 10.9+ x86-64

pyAgrum_nightly-1.5.2.9.dev202302061674421262-cp39-cp39-win_amd64.whl (2.6 MB view details)

Uploaded CPython 3.9 Windows x86-64

pyAgrum_nightly-1.5.2.9.dev202302061674421262-cp39-cp39-macosx_11_0_arm64.whl (4.0 MB view details)

Uploaded CPython 3.9 macOS 11.0+ ARM64

pyAgrum_nightly-1.5.2.9.dev202302061674421262-cp39-cp39-macosx_10_9_x86_64.whl (4.3 MB view details)

Uploaded CPython 3.9 macOS 10.9+ x86-64

pyAgrum_nightly-1.5.2.9.dev202302061674421262-cp38-cp38-win_amd64.whl (2.6 MB view details)

Uploaded CPython 3.8 Windows x86-64

pyAgrum_nightly-1.5.2.9.dev202302061674421262-cp38-cp38-macosx_11_0_arm64.whl (4.0 MB view details)

Uploaded CPython 3.8 macOS 11.0+ ARM64

pyAgrum_nightly-1.5.2.9.dev202302061674421262-cp38-cp38-macosx_10_9_x86_64.whl (4.3 MB view details)

Uploaded CPython 3.8 macOS 10.9+ x86-64

File details

Details for the file pyAgrum_nightly-1.5.2.9.dev202302061674421262-cp311-cp311-win_amd64.whl.

File metadata

File hashes

Hashes for pyAgrum_nightly-1.5.2.9.dev202302061674421262-cp311-cp311-win_amd64.whl
Algorithm Hash digest
SHA256 c096f5b03fea906cee832e17a0c1cd3f3994f106cd9fb119bd1a49ed87ff0653
MD5 dafa6899d9d9b9af16874628e2eedead
BLAKE2b-256 30ba0fd86402b7bd76641743f7d148b506bfb8b0c471cbfe2c2479d03138ac34

See more details on using hashes here.

File details

Details for the file pyAgrum_nightly-1.5.2.9.dev202302061674421262-cp311-cp311-manylinux2014_x86_64.whl.

File metadata

File hashes

Hashes for pyAgrum_nightly-1.5.2.9.dev202302061674421262-cp311-cp311-manylinux2014_x86_64.whl
Algorithm Hash digest
SHA256 5b579ff240d4dd1b97ff448670d8d411145fa456198a4503001f845bbee1c377
MD5 7bdce242f6d8364819404a43f1b3bbe5
BLAKE2b-256 9e59e39e231dc3635bb0a3e659a0d148e1af5f616ed6167215d43e021581fa74

See more details on using hashes here.

File details

Details for the file pyAgrum_nightly-1.5.2.9.dev202302061674421262-cp311-cp311-manylinux2014_aarch64.whl.

File metadata

File hashes

Hashes for pyAgrum_nightly-1.5.2.9.dev202302061674421262-cp311-cp311-manylinux2014_aarch64.whl
Algorithm Hash digest
SHA256 8a54ea52493b1abdb430f72122140de5bcbc426359a769eb6e579da45598ec6b
MD5 0c32f4930fe2b991b45b8b7e1d2de7be
BLAKE2b-256 1a988d9f31c8424c0b416bf6223a15f0fd0e4209a3aa66621af753f1c93a0289

See more details on using hashes here.

File details

Details for the file pyAgrum_nightly-1.5.2.9.dev202302061674421262-cp311-cp311-macosx_11_0_arm64.whl.

File metadata

File hashes

Hashes for pyAgrum_nightly-1.5.2.9.dev202302061674421262-cp311-cp311-macosx_11_0_arm64.whl
Algorithm Hash digest
SHA256 1a3bd68bafb7f72e0c1e1da0894f5a7b2d2c0e418e4f6f71dd4227d70cb06300
MD5 5e689b3b1b5d53f2c223fa5d4ccb45fd
BLAKE2b-256 9ee74f2ce243f9f034d09155352cb566e11310c6ebb7f57cdf1f0e728343dfcd

See more details on using hashes here.

File details

Details for the file pyAgrum_nightly-1.5.2.9.dev202302061674421262-cp311-cp311-macosx_10_9_x86_64.whl.

File metadata

File hashes

Hashes for pyAgrum_nightly-1.5.2.9.dev202302061674421262-cp311-cp311-macosx_10_9_x86_64.whl
Algorithm Hash digest
SHA256 53721ebc20ea2be27fd63b92134d10d22c33c4749bef6d58280ea4b18c55b8b2
MD5 7b679a1f74aa138539a3087de7a32fba
BLAKE2b-256 d99cb635bc117aa29c2760fe2866355882e1c7ecf41ecde559ca32f038251c66

See more details on using hashes here.

File details

Details for the file pyAgrum_nightly-1.5.2.9.dev202302061674421262-cp310-cp310-win_amd64.whl.

File metadata

File hashes

Hashes for pyAgrum_nightly-1.5.2.9.dev202302061674421262-cp310-cp310-win_amd64.whl
Algorithm Hash digest
SHA256 c0f039e8d21240e2d12fa69bda0df69adc86619ae3218d64cc7dc83ae5d81108
MD5 bdd12aa72a9f55e0a091ea159ce7c4e5
BLAKE2b-256 b8db8faaa6a1db3a95178f04eedf60c6bdbe460aa39b7441cc806533cade2694

See more details on using hashes here.

File details

Details for the file pyAgrum_nightly-1.5.2.9.dev202302061674421262-cp310-cp310-manylinux2014_x86_64.whl.

File metadata

File hashes

Hashes for pyAgrum_nightly-1.5.2.9.dev202302061674421262-cp310-cp310-manylinux2014_x86_64.whl
Algorithm Hash digest
SHA256 cf19b0f3e40d626c292e6cd444ef34372d7060a7a1345e2cbad997f29001aeef
MD5 d297f0d52db9e5773aa6b64238ffaec1
BLAKE2b-256 60627e428871d7ba45d0b88296c10581b9d090337a229ad88c3af5aed39d3bcc

See more details on using hashes here.

File details

Details for the file pyAgrum_nightly-1.5.2.9.dev202302061674421262-cp310-cp310-manylinux2014_aarch64.whl.

File metadata

File hashes

Hashes for pyAgrum_nightly-1.5.2.9.dev202302061674421262-cp310-cp310-manylinux2014_aarch64.whl
Algorithm Hash digest
SHA256 4c299858e19c649c6f8c344d337b5e121925d751981f38a960310a2763601bac
MD5 12f7b9e564bebeb947fc5cb6653e58f5
BLAKE2b-256 07fc94a65e4b57f8f803427ffbbaf9d542d69ae0730f05c0b3d87593b6228c2f

See more details on using hashes here.

File details

Details for the file pyAgrum_nightly-1.5.2.9.dev202302061674421262-cp310-cp310-macosx_11_0_arm64.whl.

File metadata

File hashes

Hashes for pyAgrum_nightly-1.5.2.9.dev202302061674421262-cp310-cp310-macosx_11_0_arm64.whl
Algorithm Hash digest
SHA256 f51cb5f583cb79467ee3fe63be156ad7dbfe7d392398807848d4e877df5f3c7b
MD5 21c6fca4f7355bc74c156a81ad96beae
BLAKE2b-256 8c3ac25e2de90f335de5e3aa959d980e06803d0e5558fe0f9700f792fecd0b59

See more details on using hashes here.

File details

Details for the file pyAgrum_nightly-1.5.2.9.dev202302061674421262-cp310-cp310-macosx_10_9_x86_64.whl.

File metadata

File hashes

Hashes for pyAgrum_nightly-1.5.2.9.dev202302061674421262-cp310-cp310-macosx_10_9_x86_64.whl
Algorithm Hash digest
SHA256 d7ab742142f89ea6f99f2ff1c0cc42e0aafb7c08fa17ad525ddf0ea80cd01727
MD5 012795f44b0d2d23ebad36cf45c6b262
BLAKE2b-256 62f55b9b48c78a1cd03b1fbb3ad257bb1db4d7ec63667aeabc9e51698da0c6ec

See more details on using hashes here.

File details

Details for the file pyAgrum_nightly-1.5.2.9.dev202302061674421262-cp39-cp39-win_amd64.whl.

File metadata

File hashes

Hashes for pyAgrum_nightly-1.5.2.9.dev202302061674421262-cp39-cp39-win_amd64.whl
Algorithm Hash digest
SHA256 a8b4006bf8f2638d53c65fa02a2c326aa34375ac0ba0bd9d5a792911c3e58bb3
MD5 55325135db79d0772f9be45dc32f670d
BLAKE2b-256 60497eb5e03582d470a4330d67d82ebd1ecfbe9e302f9f80a76ffaefdad021e8

See more details on using hashes here.

File details

Details for the file pyAgrum_nightly-1.5.2.9.dev202302061674421262-cp39-cp39-manylinux2014_x86_64.whl.

File metadata

File hashes

Hashes for pyAgrum_nightly-1.5.2.9.dev202302061674421262-cp39-cp39-manylinux2014_x86_64.whl
Algorithm Hash digest
SHA256 e13e3e4d0d099ac787f59a1b028a02fe5973c499607071c566513cd593380a56
MD5 5a01de0182366a8761848d91aae6fdd3
BLAKE2b-256 3ae79bf9f5e22cb7588279ed93e53ae162f03cbb6512374b2dcd4f1d9cf18aca

See more details on using hashes here.

File details

Details for the file pyAgrum_nightly-1.5.2.9.dev202302061674421262-cp39-cp39-manylinux2014_aarch64.whl.

File metadata

File hashes

Hashes for pyAgrum_nightly-1.5.2.9.dev202302061674421262-cp39-cp39-manylinux2014_aarch64.whl
Algorithm Hash digest
SHA256 d185e56b45b3c61b93a1ecccc5f910f262cf91997228f3bac616439adb6e4dc1
MD5 cba894d5faa901eb10462601674101ff
BLAKE2b-256 bbadc11aecc03493fbba2c00e51276c326b8f7302fa99db002f904a1aece5f07

See more details on using hashes here.

File details

Details for the file pyAgrum_nightly-1.5.2.9.dev202302061674421262-cp39-cp39-macosx_11_0_arm64.whl.

File metadata

File hashes

Hashes for pyAgrum_nightly-1.5.2.9.dev202302061674421262-cp39-cp39-macosx_11_0_arm64.whl
Algorithm Hash digest
SHA256 ca8c94101bf3d6bb1c6d3e0cfbc63e3cab74ace02712e82d4da7a5752c47ab8c
MD5 00d3d6388487fa11dc0ad7e261244b37
BLAKE2b-256 f60b6839bfb699fe825ba37abb356b898adc44788fb31fb8fd469d59c87cf7fb

See more details on using hashes here.

File details

Details for the file pyAgrum_nightly-1.5.2.9.dev202302061674421262-cp39-cp39-macosx_10_9_x86_64.whl.

File metadata

File hashes

Hashes for pyAgrum_nightly-1.5.2.9.dev202302061674421262-cp39-cp39-macosx_10_9_x86_64.whl
Algorithm Hash digest
SHA256 f132328a31d8c7d6d0449aecd2499496b40a685e4a27fc93699a06fa46af6030
MD5 df20983f630f7316be411b957a62c5fe
BLAKE2b-256 e0ef08800ad59bee587f333ce467cb43dd572ec4a40d16344b241de614d8e10f

See more details on using hashes here.

File details

Details for the file pyAgrum_nightly-1.5.2.9.dev202302061674421262-cp38-cp38-win_amd64.whl.

File metadata

File hashes

Hashes for pyAgrum_nightly-1.5.2.9.dev202302061674421262-cp38-cp38-win_amd64.whl
Algorithm Hash digest
SHA256 72f10f382c81ece69928b5d62ba06c4b9a6b26ca7e7ea8f760f378dd82c12775
MD5 252916d0360b336695b7c0404b161932
BLAKE2b-256 d922b86a11edda1bc62a90536f2ae847e5f7c6a0b797ec65603d1f6b9684228d

See more details on using hashes here.

File details

Details for the file pyAgrum_nightly-1.5.2.9.dev202302061674421262-cp38-cp38-manylinux2014_x86_64.whl.

File metadata

File hashes

Hashes for pyAgrum_nightly-1.5.2.9.dev202302061674421262-cp38-cp38-manylinux2014_x86_64.whl
Algorithm Hash digest
SHA256 3f1307473c559676ff6da907fb87f88546dd4a830c78da3560a108f7763dfd41
MD5 a785aac2d9a5eb2a0a25745bf81246f3
BLAKE2b-256 0ee92cc8892d4a9cd7f855e8262737020ea30435a34010edf9666a9226fdf66d

See more details on using hashes here.

File details

Details for the file pyAgrum_nightly-1.5.2.9.dev202302061674421262-cp38-cp38-manylinux2014_aarch64.whl.

File metadata

File hashes

Hashes for pyAgrum_nightly-1.5.2.9.dev202302061674421262-cp38-cp38-manylinux2014_aarch64.whl
Algorithm Hash digest
SHA256 06b90cc3bf5eed6d26b5a760b4792f9158e8dfad0cdadc59b4292bbd28efc056
MD5 9b85583ed3023f1e123c6819c1bbe18c
BLAKE2b-256 f0fb90ce3beeae1cc9b2e1df89e6cef1bd1b154238b0cf5d399797067585bee7

See more details on using hashes here.

File details

Details for the file pyAgrum_nightly-1.5.2.9.dev202302061674421262-cp38-cp38-macosx_11_0_arm64.whl.

File metadata

File hashes

Hashes for pyAgrum_nightly-1.5.2.9.dev202302061674421262-cp38-cp38-macosx_11_0_arm64.whl
Algorithm Hash digest
SHA256 a59c8d4f7d2b5a1436256d4ae5d57815a7ee40b087e361e3f64c5902e099f9f3
MD5 14a3d2cb34f8b7a6f71a2fd01a27cafa
BLAKE2b-256 fd4944ca05a8664c136fc3ec548ff4159486ad256c1576df9f252fe64455690d

See more details on using hashes here.

File details

Details for the file pyAgrum_nightly-1.5.2.9.dev202302061674421262-cp38-cp38-macosx_10_9_x86_64.whl.

File metadata

File hashes

Hashes for pyAgrum_nightly-1.5.2.9.dev202302061674421262-cp38-cp38-macosx_10_9_x86_64.whl
Algorithm Hash digest
SHA256 05faa146020cfeb5a74467108c29e0f9014142e394c2081ec2d9766b4bbb65a6
MD5 e4e7148700e5f3b2f234ada1120360a5
BLAKE2b-256 061deaeef028f952b33d8bb779532c4113abb5340ce837bb6885c4a5e5c33dd8

See more details on using hashes here.

Supported by

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