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

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

pyAgrum_nightly-1.10.0.9.dev202312241702974667-cp312-cp312-win_amd64.whl (2.6 MB view details)

Uploaded CPython 3.12Windows x86-64

pyAgrum_nightly-1.10.0.9.dev202312241702974667-cp312-cp312-macosx_11_0_arm64.whl (4.1 MB view details)

Uploaded CPython 3.12macOS 11.0+ ARM64

pyAgrum_nightly-1.10.0.9.dev202312241702974667-cp312-cp312-macosx_10_9_x86_64.whl (4.3 MB view details)

Uploaded CPython 3.12macOS 10.9+ x86-64

pyAgrum_nightly-1.10.0.9.dev202312241702974667-cp311-cp311-win_amd64.whl (2.6 MB view details)

Uploaded CPython 3.11Windows x86-64

pyAgrum_nightly-1.10.0.9.dev202312241702974667-cp311-cp311-macosx_11_0_arm64.whl (4.1 MB view details)

Uploaded CPython 3.11macOS 11.0+ ARM64

pyAgrum_nightly-1.10.0.9.dev202312241702974667-cp311-cp311-macosx_10_9_x86_64.whl (4.3 MB view details)

Uploaded CPython 3.11macOS 10.9+ x86-64

pyAgrum_nightly-1.10.0.9.dev202312241702974667-cp310-cp310-win_amd64.whl (2.6 MB view details)

Uploaded CPython 3.10Windows x86-64

pyAgrum_nightly-1.10.0.9.dev202312241702974667-cp310-cp310-macosx_11_0_arm64.whl (4.1 MB view details)

Uploaded CPython 3.10macOS 11.0+ ARM64

pyAgrum_nightly-1.10.0.9.dev202312241702974667-cp310-cp310-macosx_10_9_x86_64.whl (4.3 MB view details)

Uploaded CPython 3.10macOS 10.9+ x86-64

pyAgrum_nightly-1.10.0.9.dev202312241702974667-cp39-cp39-win_amd64.whl (2.6 MB view details)

Uploaded CPython 3.9Windows x86-64

pyAgrum_nightly-1.10.0.9.dev202312241702974667-cp39-cp39-macosx_11_0_arm64.whl (4.1 MB view details)

Uploaded CPython 3.9macOS 11.0+ ARM64

pyAgrum_nightly-1.10.0.9.dev202312241702974667-cp39-cp39-macosx_10_9_x86_64.whl (4.3 MB view details)

Uploaded CPython 3.9macOS 10.9+ x86-64

pyAgrum_nightly-1.10.0.9.dev202312241702974667-cp38-cp38-win_amd64.whl (2.6 MB view details)

Uploaded CPython 3.8Windows x86-64

pyAgrum_nightly-1.10.0.9.dev202312241702974667-cp38-cp38-macosx_11_0_arm64.whl (4.1 MB view details)

Uploaded CPython 3.8macOS 11.0+ ARM64

pyAgrum_nightly-1.10.0.9.dev202312241702974667-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_nightly-1.10.0.9.dev202312241702974667-cp312-cp312-win_amd64.whl.

File metadata

File hashes

Hashes for pyAgrum_nightly-1.10.0.9.dev202312241702974667-cp312-cp312-win_amd64.whl
Algorithm Hash digest
SHA256 a87b80f60f53d53bd440b3dad973b125c99b9d5512fe973e7bc8d8ea93cd9649
MD5 b770090b1fcd1d83e23ad30c5e277eba
BLAKE2b-256 3d7f00ac8feca72426afdb13bb9f88438b87d9b903f80b7411ae810983314f92

See more details on using hashes here.

File details

Details for the file pyAgrum_nightly-1.10.0.9.dev202312241702974667-cp312-cp312-manylinux2014_x86_64.whl.

File metadata

File hashes

Hashes for pyAgrum_nightly-1.10.0.9.dev202312241702974667-cp312-cp312-manylinux2014_x86_64.whl
Algorithm Hash digest
SHA256 33b0af8d32214b3dc2c4298bbdc89b15d1f863094ed80540a387d2165ad2c191
MD5 74c770ec1fb334de2514c8d806d32fd1
BLAKE2b-256 7ecb507cd154d7b9934b72b2c7f298304032a77d0c626ccd16cfef904f17a2a1

See more details on using hashes here.

File details

Details for the file pyAgrum_nightly-1.10.0.9.dev202312241702974667-cp312-cp312-manylinux2014_aarch64.whl.

File metadata

File hashes

Hashes for pyAgrum_nightly-1.10.0.9.dev202312241702974667-cp312-cp312-manylinux2014_aarch64.whl
Algorithm Hash digest
SHA256 4300da97c7ab83c14b03d6509ddd8ae90b6c907f2e834e1b72682f83fe5a2a42
MD5 988c4775b8192dbdd898f1e254703614
BLAKE2b-256 f158e7f16e14c35ffb762275ea62b77c726db9448c8661e4f7a56132bd70caaf

See more details on using hashes here.

File details

Details for the file pyAgrum_nightly-1.10.0.9.dev202312241702974667-cp312-cp312-macosx_11_0_arm64.whl.

File metadata

File hashes

Hashes for pyAgrum_nightly-1.10.0.9.dev202312241702974667-cp312-cp312-macosx_11_0_arm64.whl
Algorithm Hash digest
SHA256 39502228a716a39f944871212a9bf57c6366a18917b37f9cbf904d775c4e3fa0
MD5 c625235b615df78ee11c16c7e828b825
BLAKE2b-256 d887326b74222e8f4b798d6e6e2d9a142dc1efabd980b122790ad298cea0c2e1

See more details on using hashes here.

File details

Details for the file pyAgrum_nightly-1.10.0.9.dev202312241702974667-cp312-cp312-macosx_10_9_x86_64.whl.

File metadata

File hashes

Hashes for pyAgrum_nightly-1.10.0.9.dev202312241702974667-cp312-cp312-macosx_10_9_x86_64.whl
Algorithm Hash digest
SHA256 7db09080e8c5ce923f2ab5ffd3292044373c7996013bf0c2a29b128d0705bc60
MD5 af637dbdd110c35cef1696b7b04f6660
BLAKE2b-256 a3bd46d76bf69fbe7208f815e417f8e7c18bd253bd9662ca6f6005109f0b9a5a

See more details on using hashes here.

File details

Details for the file pyAgrum_nightly-1.10.0.9.dev202312241702974667-cp311-cp311-win_amd64.whl.

File metadata

File hashes

Hashes for pyAgrum_nightly-1.10.0.9.dev202312241702974667-cp311-cp311-win_amd64.whl
Algorithm Hash digest
SHA256 aed814647f3b8f872185daab9bb036e5c055bee3147cb3c607bb7c369a85a7b8
MD5 5d82e3f1e7f0f48751a0a43ccfffed3c
BLAKE2b-256 5ba10ad7c74f0d774f3121d41fdb6dd4ed184bc875d65b000d2f1dccc2b42f5c

See more details on using hashes here.

File details

Details for the file pyAgrum_nightly-1.10.0.9.dev202312241702974667-cp311-cp311-manylinux2014_x86_64.whl.

File metadata

File hashes

Hashes for pyAgrum_nightly-1.10.0.9.dev202312241702974667-cp311-cp311-manylinux2014_x86_64.whl
Algorithm Hash digest
SHA256 d18c3eba67e330930424bbc337a2526ff7e3b37a719d6b3c5d9bf1e1c2e98ea1
MD5 202d535ef413a96485af8a5e41612f3e
BLAKE2b-256 2c2c049f9d0f8c6c9d1ebecdee1355a81d6087938d842fa5ae465e52fc66ab14

See more details on using hashes here.

File details

Details for the file pyAgrum_nightly-1.10.0.9.dev202312241702974667-cp311-cp311-manylinux2014_aarch64.whl.

File metadata

File hashes

Hashes for pyAgrum_nightly-1.10.0.9.dev202312241702974667-cp311-cp311-manylinux2014_aarch64.whl
Algorithm Hash digest
SHA256 fc08b978dc55f4a0cef53ec64653c116b336ef116937423154df8bd82e2371e8
MD5 c078989854c1f535e18ad0cc7b4bca61
BLAKE2b-256 2b863e142782d617b14380f0c398d913195704cfbf671181708430c2d1e3da03

See more details on using hashes here.

File details

Details for the file pyAgrum_nightly-1.10.0.9.dev202312241702974667-cp311-cp311-macosx_11_0_arm64.whl.

File metadata

File hashes

Hashes for pyAgrum_nightly-1.10.0.9.dev202312241702974667-cp311-cp311-macosx_11_0_arm64.whl
Algorithm Hash digest
SHA256 ae4605dd85bd3908b4aa92078c90bc9b90ed3ac063086cc5b2f603ef909777f3
MD5 03fced7708481e369904f699b9de6ba1
BLAKE2b-256 26b95842a22e59e81a2b6cd66535d5a591a8553da14e19776424591648209b59

See more details on using hashes here.

File details

Details for the file pyAgrum_nightly-1.10.0.9.dev202312241702974667-cp311-cp311-macosx_10_9_x86_64.whl.

File metadata

File hashes

Hashes for pyAgrum_nightly-1.10.0.9.dev202312241702974667-cp311-cp311-macosx_10_9_x86_64.whl
Algorithm Hash digest
SHA256 6081c55dff49488fe2523e34cc3393ef24dbb4c98dd19f18f43af933d867ae9f
MD5 f9f75a0f88982a269c8aa1a5689c58bc
BLAKE2b-256 be429c4c84a89366c4411cd04d3338aa9acfe5deb74435c4f6e817e6d6c8da91

See more details on using hashes here.

File details

Details for the file pyAgrum_nightly-1.10.0.9.dev202312241702974667-cp310-cp310-win_amd64.whl.

File metadata

File hashes

Hashes for pyAgrum_nightly-1.10.0.9.dev202312241702974667-cp310-cp310-win_amd64.whl
Algorithm Hash digest
SHA256 98898fea630f46ccdbdf9feafcdd2ae7b042dd973680d2888c4c0cefb263ad40
MD5 ceabe5cffa5e1cf4b2e3679a463adfa1
BLAKE2b-256 35d7b1bca7e5504f2baa6b7456176dbe837429f3c495ae67963301b724d86638

See more details on using hashes here.

File details

Details for the file pyAgrum_nightly-1.10.0.9.dev202312241702974667-cp310-cp310-manylinux2014_x86_64.whl.

File metadata

File hashes

Hashes for pyAgrum_nightly-1.10.0.9.dev202312241702974667-cp310-cp310-manylinux2014_x86_64.whl
Algorithm Hash digest
SHA256 024421af6f92a9974aae4da175bf1688d48b4058ea482563672d30f23e3cbd71
MD5 8f219c4c58e1c2938c4ef8f3f9646d29
BLAKE2b-256 d0eef5d56291adb0f53d52364bd1b9fda755c29e4d1b8c2e6f6676e6bdb9c94d

See more details on using hashes here.

File details

Details for the file pyAgrum_nightly-1.10.0.9.dev202312241702974667-cp310-cp310-manylinux2014_aarch64.whl.

File metadata

File hashes

Hashes for pyAgrum_nightly-1.10.0.9.dev202312241702974667-cp310-cp310-manylinux2014_aarch64.whl
Algorithm Hash digest
SHA256 2cffb429de4b425591c1e18262f80130dbc5115661172ffa5c266a5779004c81
MD5 cd02994b899e6066956b997c17f3816c
BLAKE2b-256 7c92fc3825f958bbc2211ea18d6f2b7fed863874563a82bb92b10329b88dcd5c

See more details on using hashes here.

File details

Details for the file pyAgrum_nightly-1.10.0.9.dev202312241702974667-cp310-cp310-macosx_11_0_arm64.whl.

File metadata

File hashes

Hashes for pyAgrum_nightly-1.10.0.9.dev202312241702974667-cp310-cp310-macosx_11_0_arm64.whl
Algorithm Hash digest
SHA256 25590fa1413c2db92f5e7cfa24e1c2839ad76ee03d665b12d618767d20cf153c
MD5 c10cd0f29baccb0b8477a0101f47b1e1
BLAKE2b-256 f4c27d45c09144b4164e96a234155d76cca8bbe110fe9d3342d025d525fec0b5

See more details on using hashes here.

File details

Details for the file pyAgrum_nightly-1.10.0.9.dev202312241702974667-cp310-cp310-macosx_10_9_x86_64.whl.

File metadata

File hashes

Hashes for pyAgrum_nightly-1.10.0.9.dev202312241702974667-cp310-cp310-macosx_10_9_x86_64.whl
Algorithm Hash digest
SHA256 92c95ac1f09148aaeb0bdebcf4bc103cbc0ee78eb440a12092428cddf0237e68
MD5 82db5d2980a4d8d6b2de07fe26c54ba9
BLAKE2b-256 64de1e77d113b599cb35d7f5da5ac0f16c4224b4d3ad5480fca81ca83c47de00

See more details on using hashes here.

File details

Details for the file pyAgrum_nightly-1.10.0.9.dev202312241702974667-cp39-cp39-win_amd64.whl.

File metadata

File hashes

Hashes for pyAgrum_nightly-1.10.0.9.dev202312241702974667-cp39-cp39-win_amd64.whl
Algorithm Hash digest
SHA256 d5986b9f5a23ef7ad29654ae6409302e909815a45a6f3066f994a5ecc5e6ee38
MD5 3baf85d500400814769ac0c4c72d0401
BLAKE2b-256 3ee5eb264f3b38f081fa99d6f73e9a7db20a49f3e1301f8d702118e1f483eb1a

See more details on using hashes here.

File details

Details for the file pyAgrum_nightly-1.10.0.9.dev202312241702974667-cp39-cp39-manylinux2014_x86_64.whl.

File metadata

File hashes

Hashes for pyAgrum_nightly-1.10.0.9.dev202312241702974667-cp39-cp39-manylinux2014_x86_64.whl
Algorithm Hash digest
SHA256 3cf0c7860a6cecbdd84c64251bf264324211867df6a76cf2425e54051196edbd
MD5 f288c24a27b8f9d07d6c763d52cdb84f
BLAKE2b-256 46e75e9f07c794c566dc60260239537606a62614429f0d5580328f15b3b405b9

See more details on using hashes here.

File details

Details for the file pyAgrum_nightly-1.10.0.9.dev202312241702974667-cp39-cp39-manylinux2014_aarch64.whl.

File metadata

File hashes

Hashes for pyAgrum_nightly-1.10.0.9.dev202312241702974667-cp39-cp39-manylinux2014_aarch64.whl
Algorithm Hash digest
SHA256 6bf05a14c1bff4c2fdfe0cf449c6f1242b222b6b755e15b580921b48a40e6ad9
MD5 223401fb8d7e1e8bdc5e3bc59b05aa26
BLAKE2b-256 a09456cdb624a22b72265d5267f75a279b931bf615303685d73513e7f47be3fe

See more details on using hashes here.

File details

Details for the file pyAgrum_nightly-1.10.0.9.dev202312241702974667-cp39-cp39-macosx_11_0_arm64.whl.

File metadata

File hashes

Hashes for pyAgrum_nightly-1.10.0.9.dev202312241702974667-cp39-cp39-macosx_11_0_arm64.whl
Algorithm Hash digest
SHA256 6f88c12039e928eed9111a450e76f5fb42195b2d2c5960912da2b459af27fbbc
MD5 bdd0a0ce907668922985a09e0bbdff36
BLAKE2b-256 915c9777d7f9bd6a03deda09c6b10d0852dbd496ad7ff8b33f08eb558fe7bc03

See more details on using hashes here.

File details

Details for the file pyAgrum_nightly-1.10.0.9.dev202312241702974667-cp39-cp39-macosx_10_9_x86_64.whl.

File metadata

File hashes

Hashes for pyAgrum_nightly-1.10.0.9.dev202312241702974667-cp39-cp39-macosx_10_9_x86_64.whl
Algorithm Hash digest
SHA256 4c83b03799d98079b011182ab0b6c1099fc41413edbcea480ba770cab351975e
MD5 1998d6bdfc6706b7320b2b9938a64cec
BLAKE2b-256 2448ca764d079df1f3c9d73bd544b00f0f49304213810acc97a93e8bff8e1b33

See more details on using hashes here.

File details

Details for the file pyAgrum_nightly-1.10.0.9.dev202312241702974667-cp38-cp38-win_amd64.whl.

File metadata

File hashes

Hashes for pyAgrum_nightly-1.10.0.9.dev202312241702974667-cp38-cp38-win_amd64.whl
Algorithm Hash digest
SHA256 94b48e9359e12c4cf4458ac6deb8d21bb9075da52735a75d2b0bd5dfc019e53e
MD5 013c64dfedfc353917ceed6886cdc290
BLAKE2b-256 685a46dc067b321ec70bc856ec05f882d90444d0d2986ec2f60b6a08cd665228

See more details on using hashes here.

File details

Details for the file pyAgrum_nightly-1.10.0.9.dev202312241702974667-cp38-cp38-manylinux2014_x86_64.whl.

File metadata

File hashes

Hashes for pyAgrum_nightly-1.10.0.9.dev202312241702974667-cp38-cp38-manylinux2014_x86_64.whl
Algorithm Hash digest
SHA256 6dc891e25b975a69c5a3ea7d175bc464b2693f60b1b32b414b4c7d9e293d7296
MD5 e968e442d39c9be0e5706bb1ef44bb44
BLAKE2b-256 a0d692b23e8572ccacd01ee2471c25cdc179a7dcc612feff15641bc6a6c6ee6c

See more details on using hashes here.

File details

Details for the file pyAgrum_nightly-1.10.0.9.dev202312241702974667-cp38-cp38-manylinux2014_aarch64.whl.

File metadata

File hashes

Hashes for pyAgrum_nightly-1.10.0.9.dev202312241702974667-cp38-cp38-manylinux2014_aarch64.whl
Algorithm Hash digest
SHA256 ee4aed5156e5112d42f2eaa5724fc72d8861141b2e5b3fd579131cb7e5d4e96f
MD5 ae1417d3ca366227b524c7fb2d09da36
BLAKE2b-256 37fd0f8a652baa06d16610937cccbde70c3ef8d35dd12a49cdf8e7feff2b4129

See more details on using hashes here.

File details

Details for the file pyAgrum_nightly-1.10.0.9.dev202312241702974667-cp38-cp38-macosx_11_0_arm64.whl.

File metadata

File hashes

Hashes for pyAgrum_nightly-1.10.0.9.dev202312241702974667-cp38-cp38-macosx_11_0_arm64.whl
Algorithm Hash digest
SHA256 f9bfd5ac89abde84da860ffa20de048ffcff0a07c076a0412cb60df75c256f74
MD5 36b3bb22d7ce63a82191d2b38c8afe85
BLAKE2b-256 aa24a6c0ef0110cfab2522736ccd97230bdc6c4b6d862f8e137c0cd7ed230b51

See more details on using hashes here.

File details

Details for the file pyAgrum_nightly-1.10.0.9.dev202312241702974667-cp38-cp38-macosx_10_9_x86_64.whl.

File metadata

File hashes

Hashes for pyAgrum_nightly-1.10.0.9.dev202312241702974667-cp38-cp38-macosx_10_9_x86_64.whl
Algorithm Hash digest
SHA256 f2fe9534038e022a866be79cedc572930db5f0121792a3a292787d244ba6cb57
MD5 7ca1a3dc3653571296d49003a33e511d
BLAKE2b-256 19f5c6262de57f57d39467847408db3709771f5025935e02c8c6207e3d7e1d67

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