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-1.8.2.9.dev202306061685780492-cp311-cp311-win_amd64.whl (2.6 MB view details)

Uploaded CPython 3.11 Windows x86-64

pyAgrum_nightly-1.8.2.9.dev202306061685780492-cp311-cp311-macosx_11_0_arm64.whl (3.8 MB view details)

Uploaded CPython 3.11 macOS 11.0+ ARM64

pyAgrum_nightly-1.8.2.9.dev202306061685780492-cp311-cp311-macosx_10_9_x86_64.whl (4.3 MB view details)

Uploaded CPython 3.11 macOS 10.9+ x86-64

pyAgrum_nightly-1.8.2.9.dev202306061685780492-cp310-cp310-win_amd64.whl (2.6 MB view details)

Uploaded CPython 3.10 Windows x86-64

pyAgrum_nightly-1.8.2.9.dev202306061685780492-cp310-cp310-macosx_11_0_arm64.whl (3.8 MB view details)

Uploaded CPython 3.10 macOS 11.0+ ARM64

pyAgrum_nightly-1.8.2.9.dev202306061685780492-cp310-cp310-macosx_10_9_x86_64.whl (4.3 MB view details)

Uploaded CPython 3.10 macOS 10.9+ x86-64

pyAgrum_nightly-1.8.2.9.dev202306061685780492-cp39-cp39-win_amd64.whl (2.6 MB view details)

Uploaded CPython 3.9 Windows x86-64

pyAgrum_nightly-1.8.2.9.dev202306061685780492-cp39-cp39-macosx_11_0_arm64.whl (3.8 MB view details)

Uploaded CPython 3.9 macOS 11.0+ ARM64

pyAgrum_nightly-1.8.2.9.dev202306061685780492-cp39-cp39-macosx_10_9_x86_64.whl (4.3 MB view details)

Uploaded CPython 3.9 macOS 10.9+ x86-64

pyAgrum_nightly-1.8.2.9.dev202306061685780492-cp38-cp38-win_amd64.whl (2.6 MB view details)

Uploaded CPython 3.8 Windows x86-64

pyAgrum_nightly-1.8.2.9.dev202306061685780492-cp38-cp38-macosx_11_0_arm64.whl (3.8 MB view details)

Uploaded CPython 3.8 macOS 11.0+ ARM64

pyAgrum_nightly-1.8.2.9.dev202306061685780492-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-1.8.2.9.dev202306061685780492-cp311-cp311-win_amd64.whl.

File metadata

File hashes

Hashes for pyAgrum_nightly-1.8.2.9.dev202306061685780492-cp311-cp311-win_amd64.whl
Algorithm Hash digest
SHA256 aa9353e20811c7de5e2ebd1f6b964ee4ab98ccb7d3a93255668ddd54ae42c7df
MD5 0a82d3501bb0412c62c7cdd8f7071b0c
BLAKE2b-256 bee19454fcb5cb522ac76c6ea890914520c0cce8477cc25155c2457a3bfa92cb

See more details on using hashes here.

File details

Details for the file pyAgrum_nightly-1.8.2.9.dev202306061685780492-cp311-cp311-manylinux2014_x86_64.whl.

File metadata

File hashes

Hashes for pyAgrum_nightly-1.8.2.9.dev202306061685780492-cp311-cp311-manylinux2014_x86_64.whl
Algorithm Hash digest
SHA256 7adad586ec40cf015420147197406e2c1ab1bae5505a19180d1c201d84a754ba
MD5 9b5a42a06b447869be6d376d4e75d30d
BLAKE2b-256 42a84d9bbed99e45072f2ba5afb85a83eeb2fbd84c14060df7e461f6ef330b5e

See more details on using hashes here.

File details

Details for the file pyAgrum_nightly-1.8.2.9.dev202306061685780492-cp311-cp311-manylinux2014_aarch64.whl.

File metadata

File hashes

Hashes for pyAgrum_nightly-1.8.2.9.dev202306061685780492-cp311-cp311-manylinux2014_aarch64.whl
Algorithm Hash digest
SHA256 8c5f57f5ae2efbdba950ff9bb6d702bd45cd75aab2d26bd51bc75eceac91a81a
MD5 a6c5bfae5b23ee8ea35b6bd4fb6fc06f
BLAKE2b-256 ca64f15f842d531d157a13e0b7bef04da5a7682f8d27ac4d199c009497d7c4a4

See more details on using hashes here.

File details

Details for the file pyAgrum_nightly-1.8.2.9.dev202306061685780492-cp311-cp311-macosx_11_0_arm64.whl.

File metadata

File hashes

Hashes for pyAgrum_nightly-1.8.2.9.dev202306061685780492-cp311-cp311-macosx_11_0_arm64.whl
Algorithm Hash digest
SHA256 b8b0b411f4b53b23c8587a64100b432a040650d2cdab681796ff6d45b794f5dd
MD5 a9166ff9e38626c5f84175b06a9938d8
BLAKE2b-256 17b2086bd1bd28320b70756eabf6c5a7c24cff5ac434f777f57a9cf74642a9c1

See more details on using hashes here.

File details

Details for the file pyAgrum_nightly-1.8.2.9.dev202306061685780492-cp311-cp311-macosx_10_9_x86_64.whl.

File metadata

File hashes

Hashes for pyAgrum_nightly-1.8.2.9.dev202306061685780492-cp311-cp311-macosx_10_9_x86_64.whl
Algorithm Hash digest
SHA256 53e4cadda964f5d043bd71596f7cb4ebb050ca3d20a8b8966f786811c7aa8989
MD5 1732abc91d48ec3c26d15ae9b2a3edf7
BLAKE2b-256 65c48e3b1b3ee04cf4ba1c91ae0466912c0e961e7a40b725546b0ccf8b9b536b

See more details on using hashes here.

File details

Details for the file pyAgrum_nightly-1.8.2.9.dev202306061685780492-cp310-cp310-win_amd64.whl.

File metadata

File hashes

Hashes for pyAgrum_nightly-1.8.2.9.dev202306061685780492-cp310-cp310-win_amd64.whl
Algorithm Hash digest
SHA256 583f2d24c4fe1e2c72d15791645044d8c51f632ce77eab3327364a23534e6efb
MD5 758ad055f8e28456f3fd20aa23a305b2
BLAKE2b-256 d0d3ffe5693afc417cd70a8d7b1c005609cee2f0eeca8cd86234890ed5ea52a7

See more details on using hashes here.

File details

Details for the file pyAgrum_nightly-1.8.2.9.dev202306061685780492-cp310-cp310-manylinux2014_x86_64.whl.

File metadata

File hashes

Hashes for pyAgrum_nightly-1.8.2.9.dev202306061685780492-cp310-cp310-manylinux2014_x86_64.whl
Algorithm Hash digest
SHA256 4942f8fe59985498c44c5077d5ef92d27146ee49d2a04a2720652eb3bbd65431
MD5 53a0437077c6f2b8bae406ec82ee7a82
BLAKE2b-256 5d769429a3cb6b6019a2c95aaf79ac1aa2ea526c010de6f91f7a0084bb4db766

See more details on using hashes here.

File details

Details for the file pyAgrum_nightly-1.8.2.9.dev202306061685780492-cp310-cp310-manylinux2014_aarch64.whl.

File metadata

File hashes

Hashes for pyAgrum_nightly-1.8.2.9.dev202306061685780492-cp310-cp310-manylinux2014_aarch64.whl
Algorithm Hash digest
SHA256 25db5f6cbd24e981242c7e023f0a6dc47b68f2d5e97386f87647ab73d792df84
MD5 7e8baa92bace719363ce80134bb63498
BLAKE2b-256 28c7a885241beb787a75d066813ed0c067f714ff46362672ca423d76ac7a5baa

See more details on using hashes here.

File details

Details for the file pyAgrum_nightly-1.8.2.9.dev202306061685780492-cp310-cp310-macosx_11_0_arm64.whl.

File metadata

File hashes

Hashes for pyAgrum_nightly-1.8.2.9.dev202306061685780492-cp310-cp310-macosx_11_0_arm64.whl
Algorithm Hash digest
SHA256 02756a4b79ae0e8cbf7b96d297ff8f041370daacba0646ec3ceb9e609bef7781
MD5 b70d930d1fbe5833260b67d6a0c9d847
BLAKE2b-256 9688fbb94d75f8d713e92e4505e2f1e437758c9296f3144266e7134d2513dbf6

See more details on using hashes here.

File details

Details for the file pyAgrum_nightly-1.8.2.9.dev202306061685780492-cp310-cp310-macosx_10_9_x86_64.whl.

File metadata

File hashes

Hashes for pyAgrum_nightly-1.8.2.9.dev202306061685780492-cp310-cp310-macosx_10_9_x86_64.whl
Algorithm Hash digest
SHA256 5841f72ba47f9c3518f2468e6e5b2d26a029c31dc1357cad2ba6941008a33af7
MD5 cdceb1e7eaa9c4bd58dab247d739b0c2
BLAKE2b-256 476b45b4155ae8b83cc387500dc61b2150836af914b80ea72e08d23f3e1e7e11

See more details on using hashes here.

File details

Details for the file pyAgrum_nightly-1.8.2.9.dev202306061685780492-cp39-cp39-win_amd64.whl.

File metadata

File hashes

Hashes for pyAgrum_nightly-1.8.2.9.dev202306061685780492-cp39-cp39-win_amd64.whl
Algorithm Hash digest
SHA256 7014ffed763dbb090bf39c695481b9270ab25b5a8524db97eabd202468cc78fc
MD5 4b8b66161da572de0b6a348e02b00edf
BLAKE2b-256 4aec8d720b76437f3686dd2af0a4639d65b9df8fa1ac46824e1a9d4ec552806c

See more details on using hashes here.

File details

Details for the file pyAgrum_nightly-1.8.2.9.dev202306061685780492-cp39-cp39-manylinux2014_x86_64.whl.

File metadata

File hashes

Hashes for pyAgrum_nightly-1.8.2.9.dev202306061685780492-cp39-cp39-manylinux2014_x86_64.whl
Algorithm Hash digest
SHA256 ed20576b2dcf32f2816e90c9eca118c1800f5080da908962bc6ab5801c89cde3
MD5 525bf84aa703591d391df5e20853c12c
BLAKE2b-256 333e567a2edd88dd00ce74fedbbf873ed942c366cdaa474e5d88a95e640d7165

See more details on using hashes here.

File details

Details for the file pyAgrum_nightly-1.8.2.9.dev202306061685780492-cp39-cp39-manylinux2014_aarch64.whl.

File metadata

File hashes

Hashes for pyAgrum_nightly-1.8.2.9.dev202306061685780492-cp39-cp39-manylinux2014_aarch64.whl
Algorithm Hash digest
SHA256 93af9d975c7bb6c3b1aaecb79cb348dd5e768ef170f7e8b376358a89a6bc988a
MD5 4505cd1b2adf0cc0c40fbe2599881470
BLAKE2b-256 0e22bb016cee0f10a8812002fe75ddbf84e3104a908967faee9c61b2bceffca6

See more details on using hashes here.

File details

Details for the file pyAgrum_nightly-1.8.2.9.dev202306061685780492-cp39-cp39-macosx_11_0_arm64.whl.

File metadata

File hashes

Hashes for pyAgrum_nightly-1.8.2.9.dev202306061685780492-cp39-cp39-macosx_11_0_arm64.whl
Algorithm Hash digest
SHA256 17d0f8142405ea0e81d5369b2c382f4763c305a2ae348e94f27d51a032c6dcd1
MD5 76bcf65047d4f76877b6e5fb401c2638
BLAKE2b-256 87bcd02c41e580ec4a4dc641b5ceb609c4011ca4853879b737bacf8163e44d97

See more details on using hashes here.

File details

Details for the file pyAgrum_nightly-1.8.2.9.dev202306061685780492-cp39-cp39-macosx_10_9_x86_64.whl.

File metadata

File hashes

Hashes for pyAgrum_nightly-1.8.2.9.dev202306061685780492-cp39-cp39-macosx_10_9_x86_64.whl
Algorithm Hash digest
SHA256 1e616005b8bdca55e9730aa816bf4e41d6c3e28b7930bcb43a8a95c82c37f157
MD5 a3e8828e760bd4ddee7db44fc32592b6
BLAKE2b-256 a2d07f09b4abf5a8e51ef011db46d53562c6e53b2d336cddca1030d1b5a4c94a

See more details on using hashes here.

File details

Details for the file pyAgrum_nightly-1.8.2.9.dev202306061685780492-cp38-cp38-win_amd64.whl.

File metadata

File hashes

Hashes for pyAgrum_nightly-1.8.2.9.dev202306061685780492-cp38-cp38-win_amd64.whl
Algorithm Hash digest
SHA256 039433ae2fba9c80072a1cb02aa51f80eec8527292cda6d5921870b3ed444507
MD5 e9d7b890fe18f053270b30ea1dd5ca94
BLAKE2b-256 202523e29c2d56a4a53cc35869500138fe675fa2701728d6db73404457dfe3fd

See more details on using hashes here.

File details

Details for the file pyAgrum_nightly-1.8.2.9.dev202306061685780492-cp38-cp38-manylinux2014_x86_64.whl.

File metadata

File hashes

Hashes for pyAgrum_nightly-1.8.2.9.dev202306061685780492-cp38-cp38-manylinux2014_x86_64.whl
Algorithm Hash digest
SHA256 5d94864bb6edfebc3d07c9c6649dac68bfdfac1f240e9cfd376d106e9e30c2e9
MD5 4bc99ff1f0ae50b63323877e63561694
BLAKE2b-256 2c5ea5cb0c0a1650668ef645fbcaaf40094510ea2c4fed4f38268b797095b844

See more details on using hashes here.

File details

Details for the file pyAgrum_nightly-1.8.2.9.dev202306061685780492-cp38-cp38-manylinux2014_aarch64.whl.

File metadata

File hashes

Hashes for pyAgrum_nightly-1.8.2.9.dev202306061685780492-cp38-cp38-manylinux2014_aarch64.whl
Algorithm Hash digest
SHA256 e5712fe4e71758641b6fac2fc690022356ca0c2712397933c7c28fe833a4b5f0
MD5 664ae28ea7f5ba6ae8b4dc2808ad99e7
BLAKE2b-256 a1483a83ccd87e990b0247fe351e82e18ef919c98bfd71e34976d092b6def554

See more details on using hashes here.

File details

Details for the file pyAgrum_nightly-1.8.2.9.dev202306061685780492-cp38-cp38-macosx_11_0_arm64.whl.

File metadata

File hashes

Hashes for pyAgrum_nightly-1.8.2.9.dev202306061685780492-cp38-cp38-macosx_11_0_arm64.whl
Algorithm Hash digest
SHA256 cf26c8124e91e50e8218dfb29a82f19bd578bd7e7b1e93fe68f2dfa235f3306d
MD5 9005858931147250092919656d6d26c9
BLAKE2b-256 2577633f444460ea06ac3fada79c33fb762046cce26876b3235a65053744bb21

See more details on using hashes here.

File details

Details for the file pyAgrum_nightly-1.8.2.9.dev202306061685780492-cp38-cp38-macosx_10_9_x86_64.whl.

File metadata

File hashes

Hashes for pyAgrum_nightly-1.8.2.9.dev202306061685780492-cp38-cp38-macosx_10_9_x86_64.whl
Algorithm Hash digest
SHA256 8ef89b94f82df24e6de7ec7f0c6d2b508381a0c4ecc64060d443898951a8463d
MD5 f18d4850a0989c203fbd57c09b61496b
BLAKE2b-256 e4ef4996b9d058e126d1b89c5a355c86c6be47e760561d6371758e627ea8821f

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