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.dev202302161676359240-cp311-cp311-win_amd64.whl (2.6 MB view details)

Uploaded CPython 3.11 Windows x86-64

pyAgrum_nightly-1.5.2.9.dev202302161676359240-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.dev202302161676359240-cp311-cp311-macosx_10_9_x86_64.whl (4.4 MB view details)

Uploaded CPython 3.11 macOS 10.9+ x86-64

pyAgrum_nightly-1.5.2.9.dev202302161676359240-cp310-cp310-win_amd64.whl (2.6 MB view details)

Uploaded CPython 3.10 Windows x86-64

pyAgrum_nightly-1.5.2.9.dev202302161676359240-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.dev202302161676359240-cp310-cp310-macosx_10_9_x86_64.whl (4.4 MB view details)

Uploaded CPython 3.10 macOS 10.9+ x86-64

pyAgrum_nightly-1.5.2.9.dev202302161676359240-cp39-cp39-win_amd64.whl (2.6 MB view details)

Uploaded CPython 3.9 Windows x86-64

pyAgrum_nightly-1.5.2.9.dev202302161676359240-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.dev202302161676359240-cp39-cp39-macosx_10_9_x86_64.whl (4.4 MB view details)

Uploaded CPython 3.9 macOS 10.9+ x86-64

pyAgrum_nightly-1.5.2.9.dev202302161676359240-cp38-cp38-win_amd64.whl (2.6 MB view details)

Uploaded CPython 3.8 Windows x86-64

pyAgrum_nightly-1.5.2.9.dev202302161676359240-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.dev202302161676359240-cp38-cp38-macosx_10_9_x86_64.whl (4.4 MB view details)

Uploaded CPython 3.8 macOS 10.9+ x86-64

File details

Details for the file pyAgrum_nightly-1.5.2.9.dev202302161676359240-cp311-cp311-win_amd64.whl.

File metadata

File hashes

Hashes for pyAgrum_nightly-1.5.2.9.dev202302161676359240-cp311-cp311-win_amd64.whl
Algorithm Hash digest
SHA256 35a1cfcbf1c7258d9996e5ac2811b1ff01f4f1de9e5ee081b7ac7b77dfda77e8
MD5 b45b6322c59d627a208c41c871d8e5b7
BLAKE2b-256 4da8515c83e13d8c5d731e22f11f7052ac99f52684b9d4269bca9d431317eb2b

See more details on using hashes here.

File details

Details for the file pyAgrum_nightly-1.5.2.9.dev202302161676359240-cp311-cp311-manylinux2014_x86_64.whl.

File metadata

File hashes

Hashes for pyAgrum_nightly-1.5.2.9.dev202302161676359240-cp311-cp311-manylinux2014_x86_64.whl
Algorithm Hash digest
SHA256 ed5325431b131516828cfcb3faab6a6338456ad74d656ae076106cdaafe75e32
MD5 0dba8ebad0fa438bcc2f990e761754e3
BLAKE2b-256 12a445d8e662dc0cc70a6a455a7461f6bbfeecf1e4233499587dd08edffd0a6a

See more details on using hashes here.

File details

Details for the file pyAgrum_nightly-1.5.2.9.dev202302161676359240-cp311-cp311-manylinux2014_aarch64.whl.

File metadata

File hashes

Hashes for pyAgrum_nightly-1.5.2.9.dev202302161676359240-cp311-cp311-manylinux2014_aarch64.whl
Algorithm Hash digest
SHA256 27ba157130e6ca0d9774ca734a6425da8655ec55aa8f4b702cf7f487a4f300c1
MD5 ecdb5b9e98943542d837e237b358a344
BLAKE2b-256 24f9a6f9080c39f9a64d69bdb88f90b9ce2beb02360d188faa12245a22d047ff

See more details on using hashes here.

File details

Details for the file pyAgrum_nightly-1.5.2.9.dev202302161676359240-cp311-cp311-macosx_11_0_arm64.whl.

File metadata

File hashes

Hashes for pyAgrum_nightly-1.5.2.9.dev202302161676359240-cp311-cp311-macosx_11_0_arm64.whl
Algorithm Hash digest
SHA256 1380cd7bc7cc22efa2ef7c84adb6548e04a3c06ad1686ec2a2b8d11b5b3c5312
MD5 60722e51bdcd3fee49e5e396b411294b
BLAKE2b-256 92e8df8f65976cff868370e32aee87efeb83dc36b3851c237d0dcf4678cc967e

See more details on using hashes here.

File details

Details for the file pyAgrum_nightly-1.5.2.9.dev202302161676359240-cp311-cp311-macosx_10_9_x86_64.whl.

File metadata

File hashes

Hashes for pyAgrum_nightly-1.5.2.9.dev202302161676359240-cp311-cp311-macosx_10_9_x86_64.whl
Algorithm Hash digest
SHA256 8c0dc3f6a4c1bd8c49a3fa2f37fdaefd1300d31d787333b8d5b2b7cafc802470
MD5 7352ce8f80cbd3926a41715252b30d74
BLAKE2b-256 c73c545a89e7eff38930d9c7d15076da2d815b77270e82b7eeab339b3dc8cfc0

See more details on using hashes here.

File details

Details for the file pyAgrum_nightly-1.5.2.9.dev202302161676359240-cp310-cp310-win_amd64.whl.

File metadata

File hashes

Hashes for pyAgrum_nightly-1.5.2.9.dev202302161676359240-cp310-cp310-win_amd64.whl
Algorithm Hash digest
SHA256 f7d5aaf3a6f8178ca290926fe65a2156a5771b042bc6d3585374f57907c40486
MD5 b545164b72699d782d889d22d080c4b7
BLAKE2b-256 373b363c1ed80cd6711361062e377d8b02af7900926be9c91d75dc97237744b3

See more details on using hashes here.

File details

Details for the file pyAgrum_nightly-1.5.2.9.dev202302161676359240-cp310-cp310-manylinux2014_x86_64.whl.

File metadata

File hashes

Hashes for pyAgrum_nightly-1.5.2.9.dev202302161676359240-cp310-cp310-manylinux2014_x86_64.whl
Algorithm Hash digest
SHA256 d70b5a332c681a5231b759cfc183a750f7a756303d38b9bdfe6bf7456173eb73
MD5 481ab4c5821f25788684cc6f6ac0126f
BLAKE2b-256 3a579b909b2cfa41a92785273996e683b5996a8d0b06291940f7ccef89dfb72b

See more details on using hashes here.

File details

Details for the file pyAgrum_nightly-1.5.2.9.dev202302161676359240-cp310-cp310-manylinux2014_aarch64.whl.

File metadata

File hashes

Hashes for pyAgrum_nightly-1.5.2.9.dev202302161676359240-cp310-cp310-manylinux2014_aarch64.whl
Algorithm Hash digest
SHA256 c9cba338fbbc0fcdb4a56ec200e8e8d65bb5f59eeebba0adb3ed5df9068c8b5c
MD5 1e1479adbeb600b183ab20b01d50c838
BLAKE2b-256 d9db076ca41431882790543a9698ee172a3c9a922b4c00eb3d844608146ac00b

See more details on using hashes here.

File details

Details for the file pyAgrum_nightly-1.5.2.9.dev202302161676359240-cp310-cp310-macosx_11_0_arm64.whl.

File metadata

File hashes

Hashes for pyAgrum_nightly-1.5.2.9.dev202302161676359240-cp310-cp310-macosx_11_0_arm64.whl
Algorithm Hash digest
SHA256 790eef8b08a83589745219419785e4dab8da19db36a6f09020a0606f29daae7d
MD5 8783bb70b1e83bdb0b0502f2ff164959
BLAKE2b-256 a0be17d97426048f2233d50f53fe26b3754e066baa2a7b515c32f32d7507d16b

See more details on using hashes here.

File details

Details for the file pyAgrum_nightly-1.5.2.9.dev202302161676359240-cp310-cp310-macosx_10_9_x86_64.whl.

File metadata

File hashes

Hashes for pyAgrum_nightly-1.5.2.9.dev202302161676359240-cp310-cp310-macosx_10_9_x86_64.whl
Algorithm Hash digest
SHA256 ce799cf384679e6399279fbe9acad309d97b39573438fc496c70cb216437a832
MD5 a25faa3e0a41ff685d56b538022348b7
BLAKE2b-256 180694e8c179465cf48cb9644d6af8c15a4e8099d1c3518fe15ca0bc437a0513

See more details on using hashes here.

File details

Details for the file pyAgrum_nightly-1.5.2.9.dev202302161676359240-cp39-cp39-win_amd64.whl.

File metadata

File hashes

Hashes for pyAgrum_nightly-1.5.2.9.dev202302161676359240-cp39-cp39-win_amd64.whl
Algorithm Hash digest
SHA256 4631efc56bc723a7a6817c6a0ed4dc3cc109d6fd2115cf85e7c7ea8b3dd0591b
MD5 5d3352eed27292f1b2408b1c75afc5f0
BLAKE2b-256 47660293ad3971d9e134efcc7ced32db53c9342418a67fa8e042c4b24caf6986

See more details on using hashes here.

File details

Details for the file pyAgrum_nightly-1.5.2.9.dev202302161676359240-cp39-cp39-manylinux2014_x86_64.whl.

File metadata

File hashes

Hashes for pyAgrum_nightly-1.5.2.9.dev202302161676359240-cp39-cp39-manylinux2014_x86_64.whl
Algorithm Hash digest
SHA256 e02b27915ece71e7495f230e6fb7813c997c2717bbb98f57b4e208d16e1eb4bd
MD5 60f4d09eb06c21b06dbdcab8ebc9fa7e
BLAKE2b-256 f2377c2a948c37b75cd725a013a9b67230a78e77e66fdbb1323529ce813fa3ae

See more details on using hashes here.

File details

Details for the file pyAgrum_nightly-1.5.2.9.dev202302161676359240-cp39-cp39-manylinux2014_aarch64.whl.

File metadata

File hashes

Hashes for pyAgrum_nightly-1.5.2.9.dev202302161676359240-cp39-cp39-manylinux2014_aarch64.whl
Algorithm Hash digest
SHA256 e596c322615e6e9eb43a67d26a1c968d87b84fae3b070f2815f0a6104b0b5e46
MD5 60c0c547500015e5c4b816fa63400469
BLAKE2b-256 1f206828e2a6a61f47bf80795ac70915a3eebee3639220ec34c0561b574b4ca9

See more details on using hashes here.

File details

Details for the file pyAgrum_nightly-1.5.2.9.dev202302161676359240-cp39-cp39-macosx_11_0_arm64.whl.

File metadata

File hashes

Hashes for pyAgrum_nightly-1.5.2.9.dev202302161676359240-cp39-cp39-macosx_11_0_arm64.whl
Algorithm Hash digest
SHA256 d8abdac284b066ec26862f8874c85b6b17fcb2867c239a554cec409df876ed75
MD5 eee0891d849513972ca32a6bb9a87d75
BLAKE2b-256 a51938f67d020b1be34919794fca7d8ce69cf14331d54cdbba3d121e31f035da

See more details on using hashes here.

File details

Details for the file pyAgrum_nightly-1.5.2.9.dev202302161676359240-cp39-cp39-macosx_10_9_x86_64.whl.

File metadata

File hashes

Hashes for pyAgrum_nightly-1.5.2.9.dev202302161676359240-cp39-cp39-macosx_10_9_x86_64.whl
Algorithm Hash digest
SHA256 0d887d64e70b43cad4271b531c0c7ab39ba0eb3cc9eb996a6558e80b54346a8c
MD5 c14951752bf9282f8e8c624f712fa78f
BLAKE2b-256 4f55e670f2b11f1d49184455325d4a0a44f80b2bd27456397fdaafbf127f3a8f

See more details on using hashes here.

File details

Details for the file pyAgrum_nightly-1.5.2.9.dev202302161676359240-cp38-cp38-win_amd64.whl.

File metadata

File hashes

Hashes for pyAgrum_nightly-1.5.2.9.dev202302161676359240-cp38-cp38-win_amd64.whl
Algorithm Hash digest
SHA256 e7dc98f0e2bcc561c52684511618cf2a2e05c6eec93d76542f9a669c102c05dd
MD5 3a65371208d35234ef351de65fc7207c
BLAKE2b-256 e57544bfe1c77f5382f5a84f0cc67543574e425ec9f33a2becec1f45789fa996

See more details on using hashes here.

File details

Details for the file pyAgrum_nightly-1.5.2.9.dev202302161676359240-cp38-cp38-manylinux2014_x86_64.whl.

File metadata

File hashes

Hashes for pyAgrum_nightly-1.5.2.9.dev202302161676359240-cp38-cp38-manylinux2014_x86_64.whl
Algorithm Hash digest
SHA256 d4a09dd5bd2c4dfe4617607cfb540ff0a230a90f1dc11f4358bf3aa300ca3334
MD5 1ad9c6dcc7c2b8ab3a559d6a5e2610e8
BLAKE2b-256 32cf3699984f7bee9d36d12175deda19dbcaa6b6d4a4ab252781451e13858e5a

See more details on using hashes here.

File details

Details for the file pyAgrum_nightly-1.5.2.9.dev202302161676359240-cp38-cp38-manylinux2014_aarch64.whl.

File metadata

File hashes

Hashes for pyAgrum_nightly-1.5.2.9.dev202302161676359240-cp38-cp38-manylinux2014_aarch64.whl
Algorithm Hash digest
SHA256 099b4396531cc809ed1c4d522ec5c468ca93b445c0cb506eb1064ccff8be063f
MD5 218263482b7538674310cf8f3318bb45
BLAKE2b-256 a1bc6c181f2b3703ce785ca356f046a3e2a25a9de1df045b9696f025a1986b12

See more details on using hashes here.

File details

Details for the file pyAgrum_nightly-1.5.2.9.dev202302161676359240-cp38-cp38-macosx_11_0_arm64.whl.

File metadata

File hashes

Hashes for pyAgrum_nightly-1.5.2.9.dev202302161676359240-cp38-cp38-macosx_11_0_arm64.whl
Algorithm Hash digest
SHA256 e3a4062b9bcf82abe06ce062696015674757579193a8c728083b271010266017
MD5 56a4bdae3a4abcca32a55a69032cba86
BLAKE2b-256 be7885aadc8ef502cc92a9d1dcf1416d2aabe1334e942f47644dd4bcf90350bd

See more details on using hashes here.

File details

Details for the file pyAgrum_nightly-1.5.2.9.dev202302161676359240-cp38-cp38-macosx_10_9_x86_64.whl.

File metadata

File hashes

Hashes for pyAgrum_nightly-1.5.2.9.dev202302161676359240-cp38-cp38-macosx_10_9_x86_64.whl
Algorithm Hash digest
SHA256 1469999a125f66a9400398459d858e8175316bf02a2b6d4124e8902cf9f49918
MD5 0fe278d16178f2f5d158d2dbbfc78374
BLAKE2b-256 cbfc89021a133bd0214e4680ebf5deae829d6b54e3b58018200b7bd61d1094e1

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