Add a quaternion dtype to NumPy

Navigation

Verified details

These details have been verified by PyPI
Maintainers
Avatar for moboyle79 from gravatar.com moboyle79

Unverified details

These details have not been verified by PyPI
Project links
Meta
Report project as malware

Project description

This package creates a quaternion type in python, and further enables numpy to create and manipulate arrays of quaternions. The usual algebraic operations (addition and multiplication) are available, along with numerous properties like norm and various types of distance measures between two quaternions. There are also additional functions like “squad” and “slerp” interpolation, and conversions to and from axis-angle, matrix, and Euler-angle representations of rotations. The core of the code is written in C for speed.

Project details

Verified details

These details have been verified by PyPI
Maintainers
Avatar for moboyle79 from gravatar.com moboyle79

Unverified details

These details have not been verified by PyPI
Project links
Meta

Release history Release notifications | RSS feed

2024.0.13

2024.0.12

2024.0.11

2024.0.10

2024.0.9

2024.0.8

2024.0.7

2024.0.3

2024.0.2

2023.0.4

2023.0.3

2023.0.2

2023.0.1

2023.0.0

2022.4.4

2022.4.3

2022.4.2

2022.4.1

2022.3.1

2022.2.10.14.20.39

2022.2.9.19.55.57 yanked

Reason this release was yanked:

Bad dependencies

2021.11.4.15.26.3

2021.10.7.23.40.37

2021.8.30.10.33.11

2021.8.30.10.8.27

2021.8.26.15.40.13

2021.8.25.12.59.41

2021.7.28.16.11.54

This version

2021.7.13.7.29.27

2021.6.9.13.34.11

2021.4.5.14.42.35

2021.4.4.21.44.8

2021.3.17.16.51.43

2021.3.17.16.10.20

2021.3.17.7.29.41

2021.3.11.10.32.22

2021.3.6.15.24.2

2021.0.0a0 pre-release

2020.11.2.17.0.49

2020.9.5.14.42.2

2020.9.2.20.23.42

2020.9.2.16.39.41

2020.7.30.15.57.32 yanked

Reason this release was yanked:

Failed tests

2020.5.19.15.27.24

2020.5.11.13.33.35

2020.5.1.9.54.41

2020.4.29.8.34.20

2020.4.24.9.29.7

2020.4.21.14.53.58

2019.12.11.22.25.52

2019.10.3.10.26.21

2019.9.30.17.47.33

2019.7.23.15.26.49

2019.7.15.12.50.36

2019.7.3.22.46.7

2019.6.26.15.8.24

2019.6.26.13.52.49

2019.6.26.13.19.17

2019.6.26.0.0.13

2019.6.25.23.51.47

2019.6.25.23.8.37

2019.6.25.22.33.21

2019.6.11.17.26.3

2019.6.11.17.4.37

2019.5.24.16.21.1

2019.5.24.11.54.47

2019.3.21.14.22.55

2019.3.21.14.12.56

2019.3.21.13.27.35

2019.3.21.13.18.24

2019.3.20.15.5.52

2019.3.18.14.33.20

2018.12.24.11.8.55

2018.11.28.14.6.55

2018.11.6.10.44.9

2018.11.3.1.0.41

2018.10.1.22.5.32

2018.10.1.21.10.14

2018.10.1.21.9.15

2018.10.1.21.7.41

2018.10.1.20.37.16

2018.10.1.20.36.5

2018.10.1.20.33.23

2018.10.1.20.3.3

2018.10.1.20.1.54

2018.10.1.20.0.24

2018.10.1.19.38.42

2018.10.1.19.37.47

2018.10.1.19.36.0

2018.10.1.19.24.0

2018.10.1.19.22.42

2018.10.1.19.21.23

2018.10.1.19.4.38

2018.10.1.19.3.34

2018.10.1.19.2.10

2018.10.1.18.56.16

2018.10.1.18.55.10

2018.10.1.18.54.1

2018.10.1.17.6.20

2018.10.1.16.30.46

2018.10.1.15.59.11

2018.10.1.15.39.8

2018.10.1.15.34.19

2018.10.1.15.18.24

2018.10.1.15.1.2

2018.9.30.23.2.27

2018.9.30.22.24.11

2018.9.30.22.1.29

2018.8.13.16.17.9

2018.7.5.21.55.13

2018.7.5.15.18.26

2018.7.4.22.45.56

2018.6.18.16.33.12

2018.6.13.15.29.2

2018.5.31.16.8.42

2018.5.31.15.38.2

2018.5.31.13.56.17

2018.5.17.10.19.59

2018.5.17.10.9.55

2018.5.16.9.16.21

2018.5.10.13.50.12

2018.5.9.21.48.54

2018.5.9.20.48.6

2018.5.9.17.41.0

2018.5.9.17.32.22

2018.5.9.12.22.4

2018.5.2.21.39.8

2018.4.26.9.35.2

2018.4.18.16.18.52

2018.4.18.16.15.4

2018.4.16.17.4.9

2018.03.06.20.03.47

2018.03.02.09.28.43

2018.02.24.23.05.39

2018.02.22.22.24.39

2018.02.21.15.41.17

2017.11.26.19.00.13

2017.11.26.19.0.13

2017.10.20.10.41.30

2017.10.19.15.47.40

2017.10.14.11.13.13.dev206252663 pre-release

2017.10.14.11.11.56

2017.10.04.16.20.25.dev180388366 pre-release

2017.10.04.13.50.36.dev52395737 pre-release

2017.07.13.12.10.29.dev114912538 pre-release

2017.07.13.12.09.11.dev31661272 pre-release

2017.06.28.13.11.35.dev177226304 pre-release

2017.06.09.12.19.46.dev119623821 pre-release

2017.06.05.21.19.52.dev20097538 pre-release

2017.06.05.21.14.57.dev19253288 pre-release

2017.06.02.13.32.11.dev17910925 pre-release

2017.05.24.14.05.54.dev33077846 pre-release

2017.05.23.14.39.48.dev53804477 pre-release

2017.05.08.13.59.46.dev255649235 pre-release

2017.04.05.14.49.15.dev261789573 pre-release

2017.03.29.15.26.47.dev5411921 pre-release

2017.03.16.21.51.57.dev242408302 pre-release

2017.03.14.01.52.59.dev139985168 pre-release

2017.03.13.14.50.58.dev88917002 pre-release

2017.03.13.14.42.16.dev259768242 pre-release

2017.03.13.12.04.42.dev87917346 pre-release

2017.03.10.04.36.28.dev170668370 pre-release

2017.03.02.17.14.39.dev234032961 pre-release

2017.03.01.14.16.51.dev141622364 pre-release

2017.02.28.dev244535353 pre-release

2017.02.28.dev21024698 pre-release

2017.01.08.dev232822920 pre-release

2016.11.30.dev220855819 pre-release

2016.11.30.dev101697805 pre-release

2016.11.30.dev51027772 pre-release

2016.11.30.dev43897183 pre-release

2016.10.31.dev83815479 pre-release

2016.10.12.dev268044850 pre-release

2016.10.12.dev209377407 pre-release

2016.08.30.dev142425726 pre-release

2016.08.30.dev40560191 pre-release

2016.08.29.dev258356679 pre-release

2016.08.29.dev231774547 pre-release

2016.08.27.dev94615536 pre-release

2016.08.25.dev221305696 pre-release

Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

numpy-quaternion-2021.7.13.7.29.27.tar.gz (57.5 kB view details)

Uploaded Source

Built Distributions

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

numpy_quaternion-2021.7.13.7.29.27-cp39-cp39-win_amd64.whl (60.7 kB view details)

Uploaded CPython 3.9Windows x86-64

numpy_quaternion-2021.7.13.7.29.27-cp39-cp39-win32.whl (56.2 kB view details)

Uploaded CPython 3.9Windows x86

numpy_quaternion-2021.7.13.7.29.27-cp39-cp39-manylinux_2_5_x86_64.manylinux1_x86_64.manylinux_2_12_x86_64.manylinux2010_x86_64.whl (192.7 kB view details)

Uploaded CPython 3.9manylinux: glibc 2.12+ x86-64manylinux: glibc 2.5+ x86-64

numpy_quaternion-2021.7.13.7.29.27-cp39-cp39-manylinux_2_5_i686.manylinux1_i686.manylinux_2_12_i686.manylinux2010_i686.whl (163.8 kB view details)

Uploaded CPython 3.9manylinux: glibc 2.12+ i686manylinux: glibc 2.5+ i686

numpy_quaternion-2021.7.13.7.29.27-cp39-cp39-macosx_10_9_x86_64.whl (56.7 kB view details)

Uploaded CPython 3.9macOS 10.9+ x86-64

numpy_quaternion-2021.7.13.7.29.27-cp38-cp38-win_amd64.whl (60.6 kB view details)

Uploaded CPython 3.8Windows x86-64

numpy_quaternion-2021.7.13.7.29.27-cp38-cp38-win32.whl (56.2 kB view details)

Uploaded CPython 3.8Windows x86

numpy_quaternion-2021.7.13.7.29.27-cp38-cp38-manylinux_2_5_x86_64.manylinux1_x86_64.manylinux_2_12_x86_64.manylinux2010_x86_64.whl (194.3 kB view details)

Uploaded CPython 3.8manylinux: glibc 2.12+ x86-64manylinux: glibc 2.5+ x86-64

numpy_quaternion-2021.7.13.7.29.27-cp38-cp38-manylinux_2_5_i686.manylinux1_i686.manylinux_2_12_i686.manylinux2010_i686.whl (164.9 kB view details)

Uploaded CPython 3.8manylinux: glibc 2.12+ i686manylinux: glibc 2.5+ i686

numpy_quaternion-2021.7.13.7.29.27-cp38-cp38-macosx_10_9_x86_64.whl (56.8 kB view details)

Uploaded CPython 3.8macOS 10.9+ x86-64

numpy_quaternion-2021.7.13.7.29.27-cp37-cp37m-win_amd64.whl (60.5 kB view details)

Uploaded CPython 3.7mWindows x86-64

numpy_quaternion-2021.7.13.7.29.27-cp37-cp37m-win32.whl (56.1 kB view details)

Uploaded CPython 3.7mWindows x86

numpy_quaternion-2021.7.13.7.29.27-cp37-cp37m-manylinux_2_5_x86_64.manylinux1_x86_64.manylinux_2_12_x86_64.manylinux2010_x86_64.whl (189.0 kB view details)

Uploaded CPython 3.7mmanylinux: glibc 2.12+ x86-64manylinux: glibc 2.5+ x86-64

numpy_quaternion-2021.7.13.7.29.27-cp37-cp37m-manylinux_2_5_i686.manylinux1_i686.manylinux_2_12_i686.manylinux2010_i686.whl (161.8 kB view details)

Uploaded CPython 3.7mmanylinux: glibc 2.12+ i686manylinux: glibc 2.5+ i686

numpy_quaternion-2021.7.13.7.29.27-cp37-cp37m-macosx_10_9_x86_64.whl (56.5 kB view details)

Uploaded CPython 3.7mmacOS 10.9+ x86-64

numpy_quaternion-2021.7.13.7.29.27-cp36-cp36m-win_amd64.whl (60.5 kB view details)

Uploaded CPython 3.6mWindows x86-64

numpy_quaternion-2021.7.13.7.29.27-cp36-cp36m-win32.whl (56.1 kB view details)

Uploaded CPython 3.6mWindows x86

numpy_quaternion-2021.7.13.7.29.27-cp36-cp36m-manylinux_2_5_x86_64.manylinux1_x86_64.manylinux_2_12_x86_64.manylinux2010_x86_64.whl (187.9 kB view details)

Uploaded CPython 3.6mmanylinux: glibc 2.12+ x86-64manylinux: glibc 2.5+ x86-64

numpy_quaternion-2021.7.13.7.29.27-cp36-cp36m-manylinux_2_5_i686.manylinux1_i686.manylinux_2_12_i686.manylinux2010_i686.whl (160.8 kB view details)

Uploaded CPython 3.6mmanylinux: glibc 2.12+ i686manylinux: glibc 2.5+ i686

numpy_quaternion-2021.7.13.7.29.27-cp36-cp36m-macosx_10_9_x86_64.whl (56.5 kB view details)

Uploaded CPython 3.6mmacOS 10.9+ x86-64

File details

Details for the file numpy-quaternion-2021.7.13.7.29.27.tar.gz.

File metadata

  • Download URL: numpy-quaternion-2021.7.13.7.29.27.tar.gz
  • Upload date:
  • Size: 57.5 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/3.4.2 importlib_metadata/4.6.1 pkginfo/1.7.1 requests/2.26.0 requests-toolbelt/0.9.1 tqdm/4.61.2 CPython/3.9.6

File hashes

Hashes for numpy-quaternion-2021.7.13.7.29.27.tar.gz
Algorithm Hash digest
SHA256 ba32a60c3197e382a6d082163be8fc91e5431a6d9dca16c15607a9df9a689b49
MD5 363880d4e2482c29b42ad4caf15b2b6a
BLAKE2b-256 584edc53292e5b9e72279e7d99757c30fe765fd6d480a8507c8a80bf1a66a70a

See more details on using hashes here.

File details

Details for the file numpy_quaternion-2021.7.13.7.29.27-cp39-cp39-win_amd64.whl.

File metadata

  • Download URL: numpy_quaternion-2021.7.13.7.29.27-cp39-cp39-win_amd64.whl
  • Upload date:
  • Size: 60.7 kB
  • Tags: CPython 3.9, Windows x86-64
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/3.4.2 importlib_metadata/4.6.1 pkginfo/1.7.1 requests/2.26.0 requests-toolbelt/0.9.1 tqdm/4.61.2 CPython/3.9.6

File hashes

Hashes for numpy_quaternion-2021.7.13.7.29.27-cp39-cp39-win_amd64.whl
Algorithm Hash digest
SHA256 4dfe87016a8edb71d3c57f3442147c5a2b6a388ab1e402b0ddaa6fe403aa1f48
MD5 e6d2f582530224409299b873724bee97
BLAKE2b-256 2d04b7c150515b16937821e273e211fc91777bad3f65bb1f2aef31531ec45fcb

See more details on using hashes here.

File details

Details for the file numpy_quaternion-2021.7.13.7.29.27-cp39-cp39-win32.whl.

File metadata

  • Download URL: numpy_quaternion-2021.7.13.7.29.27-cp39-cp39-win32.whl
  • Upload date:
  • Size: 56.2 kB
  • Tags: CPython 3.9, Windows x86
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/3.4.2 importlib_metadata/4.6.1 pkginfo/1.7.1 requests/2.26.0 requests-toolbelt/0.9.1 tqdm/4.61.2 CPython/3.9.6

File hashes

Hashes for numpy_quaternion-2021.7.13.7.29.27-cp39-cp39-win32.whl
Algorithm Hash digest
SHA256 b446af7b3e21f18b809d43f906f01ab574d968a32be424f6daeadc42dd2fb33f
MD5 dd5e5ae157a3adac78e250f3df8d401c
BLAKE2b-256 421b14d59014800c585cde3bd83bb6197efa5e29f5a1ba98a283897380e4d4c6

See more details on using hashes here.

File details

Details for the file numpy_quaternion-2021.7.13.7.29.27-cp39-cp39-manylinux_2_5_x86_64.manylinux1_x86_64.manylinux_2_12_x86_64.manylinux2010_x86_64.whl.

File metadata

File hashes

Hashes for numpy_quaternion-2021.7.13.7.29.27-cp39-cp39-manylinux_2_5_x86_64.manylinux1_x86_64.manylinux_2_12_x86_64.manylinux2010_x86_64.whl
Algorithm Hash digest
SHA256 bba100327920955d904b9a6bff2d235c4b9565fbf0d2f058fb5729c6f076decf
MD5 63a3234d089bb22d2c7fe5d30e521948
BLAKE2b-256 f114367c8468bd484374f9cc8a13fcf88ce3fa2bb835ad303aac1f825fd76655

See more details on using hashes here.

File details

Details for the file numpy_quaternion-2021.7.13.7.29.27-cp39-cp39-manylinux_2_5_i686.manylinux1_i686.manylinux_2_12_i686.manylinux2010_i686.whl.

File metadata

File hashes

Hashes for numpy_quaternion-2021.7.13.7.29.27-cp39-cp39-manylinux_2_5_i686.manylinux1_i686.manylinux_2_12_i686.manylinux2010_i686.whl
Algorithm Hash digest
SHA256 49f8463c17890988c995a39ed54ffc4e1dcbdaaed39fb5ad43d50f8d6550276d
MD5 c92322c088fb5ff75a70a516fd2ea636
BLAKE2b-256 de10f5e113173ab17d01a76699d8599164e7a31ffb70da4c90f9d6477cc0029a

See more details on using hashes here.

File details

Details for the file numpy_quaternion-2021.7.13.7.29.27-cp39-cp39-macosx_10_9_x86_64.whl.

File metadata

File hashes

Hashes for numpy_quaternion-2021.7.13.7.29.27-cp39-cp39-macosx_10_9_x86_64.whl
Algorithm Hash digest
SHA256 49115baa8dbd351b16b4f56a41a3473a9eba4bfa9c38354fbfb1e7ae6c7b05bd
MD5 1981a5e2d020533162e79a5d0c5206be
BLAKE2b-256 03e42bd5964129792b7ffcb3a206bdd1caca72788dbfb3a35717ca74b4a79a3b

See more details on using hashes here.

File details

Details for the file numpy_quaternion-2021.7.13.7.29.27-cp38-cp38-win_amd64.whl.

File metadata

  • Download URL: numpy_quaternion-2021.7.13.7.29.27-cp38-cp38-win_amd64.whl
  • Upload date:
  • Size: 60.6 kB
  • Tags: CPython 3.8, Windows x86-64
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/3.4.2 importlib_metadata/4.6.1 pkginfo/1.7.1 requests/2.26.0 requests-toolbelt/0.9.1 tqdm/4.61.2 CPython/3.9.6

File hashes

Hashes for numpy_quaternion-2021.7.13.7.29.27-cp38-cp38-win_amd64.whl
Algorithm Hash digest
SHA256 80aa99f0b37c65eb087dd5fea2afa493bff12a20ce859c59ccdf540c5d7de4cc
MD5 30b83623d7c7dee6b2728e999f8e7bc2
BLAKE2b-256 5b5b2a1944ad355b49c31f128ede8674212354af065b8a5d8bb4427e85312f1b

See more details on using hashes here.

File details

Details for the file numpy_quaternion-2021.7.13.7.29.27-cp38-cp38-win32.whl.

File metadata

  • Download URL: numpy_quaternion-2021.7.13.7.29.27-cp38-cp38-win32.whl
  • Upload date:
  • Size: 56.2 kB
  • Tags: CPython 3.8, Windows x86
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/3.4.2 importlib_metadata/4.6.1 pkginfo/1.7.1 requests/2.26.0 requests-toolbelt/0.9.1 tqdm/4.61.2 CPython/3.9.6

File hashes

Hashes for numpy_quaternion-2021.7.13.7.29.27-cp38-cp38-win32.whl
Algorithm Hash digest
SHA256 81cd1c4892d857ca4b016b21d680336258d864610c6c5e0517ed504ae34158b5
MD5 21ac8da47062929e88478091ff5fbbbd
BLAKE2b-256 c2fedd947fe62e855c14492d77435f6e01c031e78063783b75a2b6ab0c1a232c

See more details on using hashes here.

File details

Details for the file numpy_quaternion-2021.7.13.7.29.27-cp38-cp38-manylinux_2_5_x86_64.manylinux1_x86_64.manylinux_2_12_x86_64.manylinux2010_x86_64.whl.

File metadata

File hashes

Hashes for numpy_quaternion-2021.7.13.7.29.27-cp38-cp38-manylinux_2_5_x86_64.manylinux1_x86_64.manylinux_2_12_x86_64.manylinux2010_x86_64.whl
Algorithm Hash digest
SHA256 cee1cfa384888c4e9b770fac2d189eee3abc3f2c66b195857cdc85a907a02a47
MD5 eff5419d44b294e8b770b744ed365c68
BLAKE2b-256 1043b251e370b5e7f26bd254f4f2ab49ab78647f1d28a6140dba71775d514ffc

See more details on using hashes here.

File details

Details for the file numpy_quaternion-2021.7.13.7.29.27-cp38-cp38-manylinux_2_5_i686.manylinux1_i686.manylinux_2_12_i686.manylinux2010_i686.whl.

File metadata

File hashes

Hashes for numpy_quaternion-2021.7.13.7.29.27-cp38-cp38-manylinux_2_5_i686.manylinux1_i686.manylinux_2_12_i686.manylinux2010_i686.whl
Algorithm Hash digest
SHA256 8a9e5cfb67f26bc93afdfc6a86887516ab709efd0f3c102ccb6355c56411e8b3
MD5 b841aab1f827c3b4fe2d95e3c2ef2ad9
BLAKE2b-256 21768b7b44a715a4809c4f3d7c8e062899240000536eb72918646ecbe7eaf662

See more details on using hashes here.

File details

Details for the file numpy_quaternion-2021.7.13.7.29.27-cp38-cp38-macosx_10_9_x86_64.whl.

File metadata

File hashes

Hashes for numpy_quaternion-2021.7.13.7.29.27-cp38-cp38-macosx_10_9_x86_64.whl
Algorithm Hash digest
SHA256 a15ff0259c8ea1427817107338800583ee2aa604a0bda42290222d5a4720094c
MD5 9d5d74d604baccefdf2e86ed3a27592e
BLAKE2b-256 180864771ec8eead39ac711632f3048164d2be54b1f3b27df8f22201796e1745

See more details on using hashes here.

File details

Details for the file numpy_quaternion-2021.7.13.7.29.27-cp37-cp37m-win_amd64.whl.

File metadata

  • Download URL: numpy_quaternion-2021.7.13.7.29.27-cp37-cp37m-win_amd64.whl
  • Upload date:
  • Size: 60.5 kB
  • Tags: CPython 3.7m, Windows x86-64
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/3.4.2 importlib_metadata/4.6.1 pkginfo/1.7.1 requests/2.26.0 requests-toolbelt/0.9.1 tqdm/4.61.2 CPython/3.9.6

File hashes

Hashes for numpy_quaternion-2021.7.13.7.29.27-cp37-cp37m-win_amd64.whl
Algorithm Hash digest
SHA256 121e379f8d2c55dde6948d8fcb4e04430ee73c61799343270955906d9e81eac3
MD5 8bec168511c83b70566d715c42ac5c95
BLAKE2b-256 7ba458fbba2491a801f05d5554e8b06c9380fabea159892932fe686b844df933

See more details on using hashes here.

File details

Details for the file numpy_quaternion-2021.7.13.7.29.27-cp37-cp37m-win32.whl.

File metadata

  • Download URL: numpy_quaternion-2021.7.13.7.29.27-cp37-cp37m-win32.whl
  • Upload date:
  • Size: 56.1 kB
  • Tags: CPython 3.7m, Windows x86
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/3.4.2 importlib_metadata/4.6.1 pkginfo/1.7.1 requests/2.26.0 requests-toolbelt/0.9.1 tqdm/4.61.2 CPython/3.9.6

File hashes

Hashes for numpy_quaternion-2021.7.13.7.29.27-cp37-cp37m-win32.whl
Algorithm Hash digest
SHA256 d4bb656c4c5a11c49d48ef8e87ac1ac9d1d9bb30531a1c51873b5e9401ddeca3
MD5 e71817dcca6ae643fdc8025e42136dbf
BLAKE2b-256 e79bf0c99acace7713878e0f4c65dfc59ce1e9ba5cea340d3972cba5b48f46d0

See more details on using hashes here.

File details

Details for the file numpy_quaternion-2021.7.13.7.29.27-cp37-cp37m-manylinux_2_5_x86_64.manylinux1_x86_64.manylinux_2_12_x86_64.manylinux2010_x86_64.whl.

File metadata

File hashes

Hashes for numpy_quaternion-2021.7.13.7.29.27-cp37-cp37m-manylinux_2_5_x86_64.manylinux1_x86_64.manylinux_2_12_x86_64.manylinux2010_x86_64.whl
Algorithm Hash digest
SHA256 4f9ac028a72ef62c84fb2ad56be4111c2b85eefaa2af4c929935378063051c47
MD5 fb3301da288da38971bdfb7bcdae2c0e
BLAKE2b-256 d6d7f630a21621b93846003be715d75efbd79ca5f7a4d9fe51b24d9ebd2f7182

See more details on using hashes here.

File details

Details for the file numpy_quaternion-2021.7.13.7.29.27-cp37-cp37m-manylinux_2_5_i686.manylinux1_i686.manylinux_2_12_i686.manylinux2010_i686.whl.

File metadata

File hashes

Hashes for numpy_quaternion-2021.7.13.7.29.27-cp37-cp37m-manylinux_2_5_i686.manylinux1_i686.manylinux_2_12_i686.manylinux2010_i686.whl
Algorithm Hash digest
SHA256 556150a6ecf66ca1edc0df1c25418a4c7829f908d36721f4ae9449b5c8f580d8
MD5 b527062de798e3ddeaf7e001b655fc6b
BLAKE2b-256 44f093fe3b628ffbab2b5b99b20e14aedd7d4bea609537e7407ca74e309713f4

See more details on using hashes here.

File details

Details for the file numpy_quaternion-2021.7.13.7.29.27-cp37-cp37m-macosx_10_9_x86_64.whl.

File metadata

File hashes

Hashes for numpy_quaternion-2021.7.13.7.29.27-cp37-cp37m-macosx_10_9_x86_64.whl
Algorithm Hash digest
SHA256 80e397a563eeacc9f69048bbd16c9e50a844f9ae949de057cbaa863352a058c4
MD5 0a67794b1a468181e74ac5d2ca4a2b8f
BLAKE2b-256 36578819b9d4f2fa971ecd343f263a547ded8eb617ec744ad2a741d21ae6c47e

See more details on using hashes here.

File details

Details for the file numpy_quaternion-2021.7.13.7.29.27-cp36-cp36m-win_amd64.whl.

File metadata

  • Download URL: numpy_quaternion-2021.7.13.7.29.27-cp36-cp36m-win_amd64.whl
  • Upload date:
  • Size: 60.5 kB
  • Tags: CPython 3.6m, Windows x86-64
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/3.4.2 importlib_metadata/4.6.1 pkginfo/1.7.1 requests/2.26.0 requests-toolbelt/0.9.1 tqdm/4.61.2 CPython/3.9.6

File hashes

Hashes for numpy_quaternion-2021.7.13.7.29.27-cp36-cp36m-win_amd64.whl
Algorithm Hash digest
SHA256 40cfdc7afd4b737b2381c8fd90e18c20b3f06b67647453a2e97b198d5df40178
MD5 5db3ccb75ba9f02b3931d872f0a71d74
BLAKE2b-256 a50c85e6b3beb92cef92c06a2d55071d879bae2d17f6cfe54f67265a21e752be

See more details on using hashes here.

File details

Details for the file numpy_quaternion-2021.7.13.7.29.27-cp36-cp36m-win32.whl.

File metadata

  • Download URL: numpy_quaternion-2021.7.13.7.29.27-cp36-cp36m-win32.whl
  • Upload date:
  • Size: 56.1 kB
  • Tags: CPython 3.6m, Windows x86
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/3.4.2 importlib_metadata/4.6.1 pkginfo/1.7.1 requests/2.26.0 requests-toolbelt/0.9.1 tqdm/4.61.2 CPython/3.9.6

File hashes

Hashes for numpy_quaternion-2021.7.13.7.29.27-cp36-cp36m-win32.whl
Algorithm Hash digest
SHA256 12ef51d8728fdb5ede0f11278b6b6eba76985a907fa2dc67e6c1362c97e975aa
MD5 3a2cd0ea36eef98eabae2d46cd3e4a19
BLAKE2b-256 c5e84be57771076cae412538ec33fb0bac253cdea0e00f045cff9b1d90ffa9e9

See more details on using hashes here.

File details

Details for the file numpy_quaternion-2021.7.13.7.29.27-cp36-cp36m-manylinux_2_5_x86_64.manylinux1_x86_64.manylinux_2_12_x86_64.manylinux2010_x86_64.whl.

File metadata

File hashes

Hashes for numpy_quaternion-2021.7.13.7.29.27-cp36-cp36m-manylinux_2_5_x86_64.manylinux1_x86_64.manylinux_2_12_x86_64.manylinux2010_x86_64.whl
Algorithm Hash digest
SHA256 a342eaea6d50b94872a0da09a85f261f563224b46111371e709fd6ada345c395
MD5 fe89ab0e9558e3a6cd18731e585986a7
BLAKE2b-256 d9265a7ae49693139140eae1710270fb88da44abbafeb78a57e853718d44460b

See more details on using hashes here.

File details

Details for the file numpy_quaternion-2021.7.13.7.29.27-cp36-cp36m-manylinux_2_5_i686.manylinux1_i686.manylinux_2_12_i686.manylinux2010_i686.whl.

File metadata

File hashes

Hashes for numpy_quaternion-2021.7.13.7.29.27-cp36-cp36m-manylinux_2_5_i686.manylinux1_i686.manylinux_2_12_i686.manylinux2010_i686.whl
Algorithm Hash digest
SHA256 0a5e616ef2c17749f89d1914b4f304a2904c2672d6737514fcd33bc83c55b454
MD5 2dec4d89464b829e9e2570d6b27d0eb8
BLAKE2b-256 b72ae35bf43beb9a007320eb2a72ca4c83504bbc8d4de71d9cd92f3cb81defff

See more details on using hashes here.

File details

Details for the file numpy_quaternion-2021.7.13.7.29.27-cp36-cp36m-macosx_10_9_x86_64.whl.

File metadata

File hashes

Hashes for numpy_quaternion-2021.7.13.7.29.27-cp36-cp36m-macosx_10_9_x86_64.whl
Algorithm Hash digest
SHA256 86649e5b59dcc44753e0e03078bc1431800f47ed097faf8a271353c84a6c5ae7
MD5 ad93a61ab27158a17a4b69246830e81a
BLAKE2b-256 a024308670e8d0a98e76f593f3bcb1ced86cf58f033d2a6b337a196d5a010c82

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