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.dev202301271674421262-cp311-cp311-win_amd64.whl (2.6 MB view details)

Uploaded CPython 3.11 Windows x86-64

pyAgrum_nightly-1.5.2.9.dev202301271674421262-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.dev202301271674421262-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.dev202301271674421262-cp310-cp310-win_amd64.whl (2.6 MB view details)

Uploaded CPython 3.10 Windows x86-64

pyAgrum_nightly-1.5.2.9.dev202301271674421262-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.dev202301271674421262-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.dev202301271674421262-cp39-cp39-win_amd64.whl (2.6 MB view details)

Uploaded CPython 3.9 Windows x86-64

pyAgrum_nightly-1.5.2.9.dev202301271674421262-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.dev202301271674421262-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.dev202301271674421262-cp38-cp38-win_amd64.whl (2.6 MB view details)

Uploaded CPython 3.8 Windows x86-64

pyAgrum_nightly-1.5.2.9.dev202301271674421262-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.dev202301271674421262-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.dev202301271674421262-cp311-cp311-win_amd64.whl.

File metadata

File hashes

Hashes for pyAgrum_nightly-1.5.2.9.dev202301271674421262-cp311-cp311-win_amd64.whl
Algorithm Hash digest
SHA256 4e21accb13f8b4d6bb7f7814ee20022ee76e82131e1006f073ab31c79dcabf9c
MD5 355df75cbe737478204dded44c71d767
BLAKE2b-256 ca90084db0bd1ff40753bdacc88dad17fe93c243ecc18bb3394b20ce05f7c970

See more details on using hashes here.

File details

Details for the file pyAgrum_nightly-1.5.2.9.dev202301271674421262-cp311-cp311-manylinux2014_x86_64.whl.

File metadata

File hashes

Hashes for pyAgrum_nightly-1.5.2.9.dev202301271674421262-cp311-cp311-manylinux2014_x86_64.whl
Algorithm Hash digest
SHA256 f201a3aa76acac1757cc7fc5fde83cd24eeab5be417bb056885d7dc36be6018f
MD5 59f26447d62c66b7738dd2793e2fa61f
BLAKE2b-256 99107bf55e9b602438f95010b7dbb494516df2d62aca273244c49435d52941c8

See more details on using hashes here.

File details

Details for the file pyAgrum_nightly-1.5.2.9.dev202301271674421262-cp311-cp311-manylinux2014_aarch64.whl.

File metadata

File hashes

Hashes for pyAgrum_nightly-1.5.2.9.dev202301271674421262-cp311-cp311-manylinux2014_aarch64.whl
Algorithm Hash digest
SHA256 e841b8492acbadeee2076b6f54d78568d55f41d9ea9bf901db1aae17b726a5a5
MD5 517f01544cc2d57190b4cc3cf80f4c60
BLAKE2b-256 5da2fd8777640933917d36296a32894caeb4e4687fbc557fa2b0fe35f3493d97

See more details on using hashes here.

File details

Details for the file pyAgrum_nightly-1.5.2.9.dev202301271674421262-cp311-cp311-macosx_11_0_arm64.whl.

File metadata

File hashes

Hashes for pyAgrum_nightly-1.5.2.9.dev202301271674421262-cp311-cp311-macosx_11_0_arm64.whl
Algorithm Hash digest
SHA256 fc7e5f2aa7f80e810697032e7d007b106d5f1550aee64ee3c70a6887c25601ce
MD5 3b5aac644798362eb254c5b177ec0f18
BLAKE2b-256 5eef5ef05262d94a6da65e5fc4fc9316c3e9d7c0332c7b7722b3619042ea78b0

See more details on using hashes here.

File details

Details for the file pyAgrum_nightly-1.5.2.9.dev202301271674421262-cp311-cp311-macosx_10_9_x86_64.whl.

File metadata

File hashes

Hashes for pyAgrum_nightly-1.5.2.9.dev202301271674421262-cp311-cp311-macosx_10_9_x86_64.whl
Algorithm Hash digest
SHA256 02c856ccfa947651f68f79cea0b77e825381bed02550aa501bdc635d22017129
MD5 a2154b5312cb4c6b4a900d400b826b6b
BLAKE2b-256 ac4afdfc65fc06985ca7ed59fe6156392bda41a116779b675d683dbe8636605f

See more details on using hashes here.

File details

Details for the file pyAgrum_nightly-1.5.2.9.dev202301271674421262-cp310-cp310-win_amd64.whl.

File metadata

File hashes

Hashes for pyAgrum_nightly-1.5.2.9.dev202301271674421262-cp310-cp310-win_amd64.whl
Algorithm Hash digest
SHA256 d008936b78924a7d44970f51a3044afa3bbfc06cdcb99f03f62447368f053e28
MD5 a97e5769af4f5ff1f09d9b57b52bcf28
BLAKE2b-256 82cad53a1d5572b15ec1b7fc3b3e48872c394692bde1fe1c5b960e77f367a10c

See more details on using hashes here.

File details

Details for the file pyAgrum_nightly-1.5.2.9.dev202301271674421262-cp310-cp310-manylinux2014_x86_64.whl.

File metadata

File hashes

Hashes for pyAgrum_nightly-1.5.2.9.dev202301271674421262-cp310-cp310-manylinux2014_x86_64.whl
Algorithm Hash digest
SHA256 2d0c4f752b668fe97d129cf417fbf16239b626555ad2435813c72777603a5fa6
MD5 91245482b1214a61c1e39dedd36b14dd
BLAKE2b-256 32d032e979eea7c72929b18266b45fb072b89fd9930e91ffcaa481e79c037205

See more details on using hashes here.

File details

Details for the file pyAgrum_nightly-1.5.2.9.dev202301271674421262-cp310-cp310-manylinux2014_aarch64.whl.

File metadata

File hashes

Hashes for pyAgrum_nightly-1.5.2.9.dev202301271674421262-cp310-cp310-manylinux2014_aarch64.whl
Algorithm Hash digest
SHA256 db7647af624bf11b7bdd79edb71ed809b9ad0d9e78148299564abe2bb1852914
MD5 f400153fc7203b14c071f81e44788954
BLAKE2b-256 966a7870fb888b075f160dda0bcfd22ae6ac5e2d30f3b90c89e625c0af46e3de

See more details on using hashes here.

File details

Details for the file pyAgrum_nightly-1.5.2.9.dev202301271674421262-cp310-cp310-macosx_11_0_arm64.whl.

File metadata

File hashes

Hashes for pyAgrum_nightly-1.5.2.9.dev202301271674421262-cp310-cp310-macosx_11_0_arm64.whl
Algorithm Hash digest
SHA256 a12a8439be44f8f0b7fe6a9d59717ffc93c2da3d8b56a644f48578a61a38733f
MD5 6e07e6e9fd465e483ae0776e2f507112
BLAKE2b-256 1e45301fb56797e69a1a500646819f95a943d898b2a99b014991ae9eeb2a5c93

See more details on using hashes here.

File details

Details for the file pyAgrum_nightly-1.5.2.9.dev202301271674421262-cp310-cp310-macosx_10_9_x86_64.whl.

File metadata

File hashes

Hashes for pyAgrum_nightly-1.5.2.9.dev202301271674421262-cp310-cp310-macosx_10_9_x86_64.whl
Algorithm Hash digest
SHA256 2b415c5ba958377adf9a8cfcffc97ed22d72e49089060da63f165f2f886104a4
MD5 0f43f8ba71a3e75cf819bc397844ee37
BLAKE2b-256 e87810508949739287d87ab5eb619ca57f8691cec025f63dacc4f3d2d7d8fb06

See more details on using hashes here.

File details

Details for the file pyAgrum_nightly-1.5.2.9.dev202301271674421262-cp39-cp39-win_amd64.whl.

File metadata

File hashes

Hashes for pyAgrum_nightly-1.5.2.9.dev202301271674421262-cp39-cp39-win_amd64.whl
Algorithm Hash digest
SHA256 3819429e4859304caf3841dce9cf15e00d1318f8a871a152168665ad9f5c14df
MD5 c2862d1a755a06ef8f5e5a636026a0ba
BLAKE2b-256 ae374725e6c948a424b8a432a18ab03208c27674827333cfe646d1c1327d78b6

See more details on using hashes here.

File details

Details for the file pyAgrum_nightly-1.5.2.9.dev202301271674421262-cp39-cp39-manylinux2014_x86_64.whl.

File metadata

File hashes

Hashes for pyAgrum_nightly-1.5.2.9.dev202301271674421262-cp39-cp39-manylinux2014_x86_64.whl
Algorithm Hash digest
SHA256 bba1103a15ea10063a5bfb35bc5983bf73a0b40b6df8b4181d35745539174cf3
MD5 738a811c44603d5c1fc1d5e0c67a9b4a
BLAKE2b-256 8c33f3462139aed7b6f2031aeda3f1f2b29649f22d03fce737901b00c8b1a412

See more details on using hashes here.

File details

Details for the file pyAgrum_nightly-1.5.2.9.dev202301271674421262-cp39-cp39-manylinux2014_aarch64.whl.

File metadata

File hashes

Hashes for pyAgrum_nightly-1.5.2.9.dev202301271674421262-cp39-cp39-manylinux2014_aarch64.whl
Algorithm Hash digest
SHA256 60df76216f9159f9edda7827736f126493f51265e5107a814661418f3d5df1df
MD5 1c547c5997dba11e2c178ef86082bb45
BLAKE2b-256 ac3d12084bde335b4a309ae457b65b8616294816ec8a28cb54c6d39267f869b4

See more details on using hashes here.

File details

Details for the file pyAgrum_nightly-1.5.2.9.dev202301271674421262-cp39-cp39-macosx_11_0_arm64.whl.

File metadata

File hashes

Hashes for pyAgrum_nightly-1.5.2.9.dev202301271674421262-cp39-cp39-macosx_11_0_arm64.whl
Algorithm Hash digest
SHA256 0cd14d1911d4da58c8e1db4a3eee01e3c345343a253c240bc0c93c10533c1a11
MD5 6fa0748ff3ce92cfcb7d12ff302bcb00
BLAKE2b-256 03c8e1b905718e22c4ce511bb20f735607fb0d7deac16ee22198111288af47c1

See more details on using hashes here.

File details

Details for the file pyAgrum_nightly-1.5.2.9.dev202301271674421262-cp39-cp39-macosx_10_9_x86_64.whl.

File metadata

File hashes

Hashes for pyAgrum_nightly-1.5.2.9.dev202301271674421262-cp39-cp39-macosx_10_9_x86_64.whl
Algorithm Hash digest
SHA256 ef2b43575b595c31f388d097dd0f1b202450ffaf7ba40c92d5b20c84580f1225
MD5 cde182cf4189bf4bba485e28454b0a1f
BLAKE2b-256 7b01e92d5c84ecc8f6b582c6996b4295ff6fc2c8fdac79a7efd0aa895c032f99

See more details on using hashes here.

File details

Details for the file pyAgrum_nightly-1.5.2.9.dev202301271674421262-cp38-cp38-win_amd64.whl.

File metadata

File hashes

Hashes for pyAgrum_nightly-1.5.2.9.dev202301271674421262-cp38-cp38-win_amd64.whl
Algorithm Hash digest
SHA256 23300f50a61100aa502b5689574d0ffb214eef747d499284de3c7e31a4b213cf
MD5 3707df5c79304c34623a13b78a82b21b
BLAKE2b-256 6aa70d29ca4d7705f30d34eb5b401f338614376a9273cd9fee800c839e99cbf7

See more details on using hashes here.

File details

Details for the file pyAgrum_nightly-1.5.2.9.dev202301271674421262-cp38-cp38-manylinux2014_x86_64.whl.

File metadata

File hashes

Hashes for pyAgrum_nightly-1.5.2.9.dev202301271674421262-cp38-cp38-manylinux2014_x86_64.whl
Algorithm Hash digest
SHA256 2cee16f6f7bcfe5f3f05f457baeed7a012abaac766e2ba54bd8e58a9b57a5f7b
MD5 3bdb3cc5a1fa1963f82abc0032d60b1b
BLAKE2b-256 4da28f28806f27177fbe5d16877a45e05d7bff516afd5686f6ea3617a30a4b47

See more details on using hashes here.

File details

Details for the file pyAgrum_nightly-1.5.2.9.dev202301271674421262-cp38-cp38-manylinux2014_aarch64.whl.

File metadata

File hashes

Hashes for pyAgrum_nightly-1.5.2.9.dev202301271674421262-cp38-cp38-manylinux2014_aarch64.whl
Algorithm Hash digest
SHA256 b201b58006aaeb872b4288206791fb87c9ce4a5fc5e51e61addeb9f83dea90f4
MD5 ee2c07425a59d52189cd69e25518bc5d
BLAKE2b-256 48afc1693aa19e083bf26b006f7ac7f44a190a5aede8654931cb058195990ff3

See more details on using hashes here.

File details

Details for the file pyAgrum_nightly-1.5.2.9.dev202301271674421262-cp38-cp38-macosx_11_0_arm64.whl.

File metadata

File hashes

Hashes for pyAgrum_nightly-1.5.2.9.dev202301271674421262-cp38-cp38-macosx_11_0_arm64.whl
Algorithm Hash digest
SHA256 1f45c7862a3ea54de857bdd6935a00531802d10938a8d7ddafd8922114a35cde
MD5 275c97e91e871dfec4c5f8631d230f86
BLAKE2b-256 1ab30a164785f11d3b5ba060679a35170fffe8330633fd2f29c255f8734dc835

See more details on using hashes here.

File details

Details for the file pyAgrum_nightly-1.5.2.9.dev202301271674421262-cp38-cp38-macosx_10_9_x86_64.whl.

File metadata

File hashes

Hashes for pyAgrum_nightly-1.5.2.9.dev202301271674421262-cp38-cp38-macosx_10_9_x86_64.whl
Algorithm Hash digest
SHA256 d12d2f5c7771872b737ff228d3682980a4468ef30aa00fb1dae6c7c73e39bb3c
MD5 44cd71957eaa9fedd2ef3e0b6028b93c
BLAKE2b-256 faf68ab942678ffa41ce5d38dd3906530876d435bf850848078b8a3f614200cc

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