PyLBFGS

LBFGS and OWL-QN optimization algorithms

These details have not been verified by PyPI

Project links

Homepage

Intended Audience
- Developers
- Science/Research
License
- OSI Approved :: MIT License
Operating System
- POSIX
Programming Language
- Cython
- Python
Topic
- Scientific/Engineering
- Software Development

Project description

PyLBFGS

This is a Python wrapper around Naoaki Okazaki (chokkan)’s liblbfgs library of quasi-Newton optimization routines (limited memory BFGS and OWL-QN).

This package aims to provide a cleaner interface to the LBFGS algorithm than is currently available in SciPy, and to provide the OWL-QN algorithm to Python users.

Part of the Dedupe.io cloud service and open source toolset for de-duplicating and finding fuzzy matches in your data.

Installing

Type:

pip install pylbfgs

Hacking

Type:

pip install "pip>=10"
pip install -r requirements.txt
pip install -e .

To run the test suite:

pytest tests

Authors

PyLBFGS was written by Lars Buitinck.

Alexis Mignon submitted a patch for error handling.

Project details

These details have not been verified by PyPI

Project links

Homepage

Intended Audience
- Developers
- Science/Research
License
- OSI Approved :: MIT License
Operating System
- POSIX
Programming Language
- Cython
- Python
Topic
- Scientific/Engineering
- Software Development

Release history Release notifications | RSS feed

0.2.0.16

Jun 20, 2024

0.2.0.15

Dec 16, 2023

This version

0.2.0.14

Dec 18, 2021

0.2.0.13

Jan 6, 2020

0.2.0.12

Aug 7, 2018

0.2.0.11

May 24, 2018

0.2.0.10

May 18, 2018

0.2.0.9

May 18, 2018

0.2.0.8

Apr 17, 2018

0.2.0.7

Apr 17, 2018

0.2.0.6

Apr 17, 2018

0.2.0.5

May 16, 2017

0.2.0.4

May 16, 2017

0.2.0.3

Sep 10, 2015

0.2.0.2

Aug 20, 2015

0.2.0.1

Aug 19, 2015

0.1.13

Aug 19, 2015

0.1.12

Aug 19, 2015

0.1.11

Aug 19, 2015

0.1.10

Aug 19, 2015

0.1.9

May 22, 2015

0.1.8

May 20, 2015

0.1.7

May 6, 2015

0.1.6

Apr 24, 2015

0.1.5

Apr 24, 2015

0.1.4

Apr 24, 2015

0.1.3

Apr 16, 2015

0.1.2

Apr 16, 2015

0.1.1

Apr 16, 2015

0.1

Apr 16, 2015

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Algorithm	Hash digest
SHA256	`a1603198330cfc2628e4c5eb925928b90870c7f27f0b7f263ed03cb38580fc6c`
MD5	`0949cae845eea233a24d718d193d44de`
BLAKE2b-256	`ad4c75d19f0962eb38e0268ef463e6029005f476b2cdad3ebffb9e5183e87055`

Hashes for PyLBFGS-0.2.0.14-cp38-cp38-manylinux_2_17_aarch64.manylinux2014_aarch64.whl

Hashes for PyLBFGS-0.2.0.14-cp38-cp38-manylinux_2_17_aarch64.manylinux2014_aarch64.whl
Algorithm	Hash digest
SHA256	`b697972eed2a79f3d1c5e5e7f5f9066c16dce0c737cfcd8734aa22a9a6c7d05e`
MD5	`84ec15bd9ac4a7a05f6893a2613d4594`
BLAKE2b-256	`b786853458ce2c54002fe0181a87c6775590121338cd57e509250de8ea1db3c2`

Hashes for PyLBFGS-0.2.0.14-cp38-cp38-manylinux_2_5_x86_64.manylinux1_x86_64.manylinux_2_12_x86_64.manylinux2010_x86_64.whl

Hashes for PyLBFGS-0.2.0.14-cp38-cp38-manylinux_2_5_x86_64.manylinux1_x86_64.manylinux_2_12_x86_64.manylinux2010_x86_64.whl
Algorithm	Hash digest
SHA256	`b0198f3019d78193a215d742830c88135c8a2c7ceec5d5e41b1bbd096fe2213a`
MD5	`8b40166eb4da744d469e2158fefa5421`
BLAKE2b-256	`c09d854fa8bf1bfef5afb0f565b7d23b6df8f2820f9307398e4c013f92cdc872`

Hashes for PyLBFGS-0.2.0.14-cp38-cp38-manylinux_2_5_i686.manylinux1_i686.manylinux_2_12_i686.manylinux2010_i686.whl

Hashes for PyLBFGS-0.2.0.14-cp38-cp38-manylinux_2_5_i686.manylinux1_i686.manylinux_2_12_i686.manylinux2010_i686.whl
Algorithm	Hash digest
SHA256	`3efb2a830e31f3772c2a0d5ca3100cfe65298a647c71681e0560bbee53a2ef90`
MD5	`bcbe43aeb4cf620e44b5e3ed3ce454f7`
BLAKE2b-256	`4cc08f3e1a1b943ad198a5b5d8aaceac9a3c17fff36fddfd143cffd4ba752a07`

Hashes for PyLBFGS-0.2.0.14-cp38-cp38-macosx_11_0_arm64.whl

Hashes for PyLBFGS-0.2.0.14-cp38-cp38-macosx_11_0_arm64.whl
Algorithm	Hash digest
SHA256	`1dd1f01c392a0f99665df33eb492030ad9f4fb96bc9fe63292bf4c8c1e7f341d`
MD5	`39613bc7ecfc58c813ceea1a10126767`
BLAKE2b-256	`c5086aaf56bc4322a44cb799d6d14cc716e5e3bfaee3484935cd9734fa65a79b`

Hashes for PyLBFGS-0.2.0.14-cp38-cp38-macosx_10_9_x86_64.whl

Hashes for PyLBFGS-0.2.0.14-cp38-cp38-macosx_10_9_x86_64.whl
Algorithm	Hash digest
SHA256	`977d24a2f5cd34ba3d4d4fbe9e55eac9ef226aff4ffc53490fe7fb9f05c4b010`
MD5	`7f2b851a3b9c745b66420c8ec46614d2`
BLAKE2b-256	`0ace99abed2349fba3ad2cfe19eabb64a4f960bc2a6568d9d623719f8099fd58`

Hashes for PyLBFGS-0.2.0.14-cp38-cp38-macosx_10_9_universal2.whl

Hashes for PyLBFGS-0.2.0.14-cp38-cp38-macosx_10_9_universal2.whl
Algorithm	Hash digest
SHA256	`50c9638db3f5e28a85dd0329e3b769a59acf9c2eb73dc6a668a0604ecf29b32a`
MD5	`ec9787121da52c4ae2baa12268d863d8`
BLAKE2b-256	`9c25106284ce87e00c48e3a33514da0ac4da6b85824fe82a5442726a5824b502`

Hashes for PyLBFGS-0.2.0.14-cp37-cp37m-win_amd64.whl

Hashes for PyLBFGS-0.2.0.14-cp37-cp37m-win_amd64.whl
Algorithm	Hash digest
SHA256	`f850fbee9339f51b881fcbd6b0ff924396cc828e335e4cf189ede4c0d47e0083`
MD5	`be9af2886a135581509291024237a7f4`
BLAKE2b-256	`5808542ca4aed339cdb225cd2d3dbe3f0a22cbd6fe34096ca789402ab82e9403`

Hashes for PyLBFGS-0.2.0.14-cp37-cp37m-win32.whl

Hashes for PyLBFGS-0.2.0.14-cp37-cp37m-win32.whl
Algorithm	Hash digest
SHA256	`7ccc7922ffe6463838d91b59973dfe63a46f2eca73a2b45cb9f57770b5d5aff6`
MD5	`5923d51d10ffe697aafa3ed51a6f986f`
BLAKE2b-256	`f418dd06e9ec6610c3b2486b5a769872f433b6754a51554aaf236ed730134df6`

Hashes for PyLBFGS-0.2.0.14-cp37-cp37m-manylinux_2_17_aarch64.manylinux2014_aarch64.whl

Hashes for PyLBFGS-0.2.0.14-cp37-cp37m-manylinux_2_17_aarch64.manylinux2014_aarch64.whl
Algorithm	Hash digest
SHA256	`c9313a7ed808bfee8a7ff6f8545f21afa8dcd557c9b582ea865b4c28971d2bde`
MD5	`a4d89972a9be5e72ef87a943b8955106`
BLAKE2b-256	`073e1bb04b5e42ef674af47263e90932a8e32258a99261646d26de227e1e1973`

Hashes for PyLBFGS-0.2.0.14-cp37-cp37m-manylinux_2_5_x86_64.manylinux1_x86_64.manylinux_2_12_x86_64.manylinux2010_x86_64.whl

Hashes for PyLBFGS-0.2.0.14-cp37-cp37m-manylinux_2_5_x86_64.manylinux1_x86_64.manylinux_2_12_x86_64.manylinux2010_x86_64.whl
Algorithm	Hash digest
SHA256	`b0e265c74f200d18c35763721156bcede5f1b76aa3d188bb79dda6ed48b5231d`
MD5	`0ff3dfe88044d148796bf85f5b153462`
BLAKE2b-256	`4f341ac0f6f9f1b490b6cb738b153e7097ed676afeb52e4e59067df7e0a78a2e`

Hashes for PyLBFGS-0.2.0.14-cp37-cp37m-manylinux_2_5_i686.manylinux1_i686.manylinux_2_12_i686.manylinux2010_i686.whl

Hashes for PyLBFGS-0.2.0.14-cp37-cp37m-manylinux_2_5_i686.manylinux1_i686.manylinux_2_12_i686.manylinux2010_i686.whl
Algorithm	Hash digest
SHA256	`d0937d4e0ce03f79260f7ac711e50ceecbd6736f762327f0f8e0e08c30952354`
MD5	`3d64a802f276ba2991f03af45d73eac5`
BLAKE2b-256	`de9ccfb37dde1439bf9856db3b0ae4bb20e8d80e086b7b6d77f35cdcd8be5ce6`

Hashes for PyLBFGS-0.2.0.14-cp37-cp37m-macosx_10_9_x86_64.whl

Hashes for PyLBFGS-0.2.0.14-cp37-cp37m-macosx_10_9_x86_64.whl
Algorithm	Hash digest
SHA256	`dbd6366d1229662e8cd121153468f7224e5e1939c15285f77cb6c87b84da987a`
MD5	`3dadd9de997aabe8647a71f28d2640a3`
BLAKE2b-256	`b86cb5cfd3f1145b5e98ceaec7347608b580f7d84cefa3c61f1181eb649bdef7`

Hashes for PyLBFGS-0.2.0.14-cp36-cp36m-win_amd64.whl

Hashes for PyLBFGS-0.2.0.14-cp36-cp36m-win_amd64.whl
Algorithm	Hash digest
SHA256	`86fac1c53dc0c6da5fccb0b05d3a0f34cb2a576fa57909cb0a4ef92bda2928c1`
MD5	`37344ef3fe3ab01c636bb8863f31197b`
BLAKE2b-256	`ae11390cf14035caa2d857e648902aa020ee06cd47d1a3a4d8c31488155a4f55`

Hashes for PyLBFGS-0.2.0.14-cp36-cp36m-win32.whl

Hashes for PyLBFGS-0.2.0.14-cp36-cp36m-win32.whl
Algorithm	Hash digest
SHA256	`454f2a126b8592b38e6deaaf9f7b03f2a7890e1200f1c3698c85fab1abadf0e2`
MD5	`01579e92f62f4a0c862158b35a7764c7`
BLAKE2b-256	`c7b84490398b9daf2b26f58ce7b365100e8b969dffbe38661d61a2f23f8c8afa`

Hashes for PyLBFGS-0.2.0.14-cp36-cp36m-manylinux_2_17_aarch64.manylinux2014_aarch64.whl

Hashes for PyLBFGS-0.2.0.14-cp36-cp36m-manylinux_2_17_aarch64.manylinux2014_aarch64.whl
Algorithm	Hash digest
SHA256	`7b05e9ba5f229ff84f2dd8e5e1deabeee2df9b7ab887c5a2f8ecf14658e7fb90`
MD5	`b6080debcc68ba9379f4b1e2f904eb02`
BLAKE2b-256	`77e9c22977df290d264331eda4fe0eb780c04c4a5f6e6da719b99465f0e3a2e6`

Hashes for PyLBFGS-0.2.0.14-cp36-cp36m-manylinux_2_5_x86_64.manylinux1_x86_64.manylinux_2_12_x86_64.manylinux2010_x86_64.whl

Hashes for PyLBFGS-0.2.0.14-cp36-cp36m-manylinux_2_5_x86_64.manylinux1_x86_64.manylinux_2_12_x86_64.manylinux2010_x86_64.whl
Algorithm	Hash digest
SHA256	`4069ef8babe788b5ecae22c9fd59491abb82359f56db48d86061ab577e2002e9`
MD5	`4f6efa464de42deadcac0564f96253cd`
BLAKE2b-256	`f5694771701791150f3732a1b69b1eee930b0056f43adb278bac1336e2850ca7`

Hashes for PyLBFGS-0.2.0.14-cp36-cp36m-manylinux_2_5_i686.manylinux1_i686.manylinux_2_12_i686.manylinux2010_i686.whl

Hashes for PyLBFGS-0.2.0.14-cp36-cp36m-manylinux_2_5_i686.manylinux1_i686.manylinux_2_12_i686.manylinux2010_i686.whl
Algorithm	Hash digest
SHA256	`7db6dac1e0671b9c806753260b581a772b8ff764ab34e1d70115f82cbeb6d8ee`
MD5	`e90f0706ac4af4d8b24d47613000e9eb`
BLAKE2b-256	`62a85d10a3a2a41f03aaf384ebe1ddbdb68b6ab4f87ddd2293ea03c0ce39a31e`

Hashes for PyLBFGS-0.2.0.14-cp36-cp36m-macosx_10_9_x86_64.whl

Hashes for PyLBFGS-0.2.0.14-cp36-cp36m-macosx_10_9_x86_64.whl
Algorithm	Hash digest
SHA256	`5140598839f34890f4fa44e2fc1f212f03f1e5d4c8bd1bd7b995bcf91af3a163`
MD5	`6dea61bc8470125e218e5df9d2c5bf87`
BLAKE2b-256	`98ddeaf7d9c8dfa3a5bdbc655bd990c3b192fefcc440e16f838fa9caae73baff`