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

2021.7.13.7.29.27

This version

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-2021.6.9.13.34.11.tar.gz (57.2 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-2021.6.9.13.34.11-cp39-cp39-win_amd64.whl (60.6 kB view details)

Uploaded CPython 3.9Windows x86-64

numpy_quaternion-2021.6.9.13.34.11-cp39-cp39-win32.whl (56.2 kB view details)

Uploaded CPython 3.9Windows x86

numpy_quaternion-2021.6.9.13.34.11-cp39-cp39-manylinux2010_x86_64.whl (192.6 kB view details)

Uploaded CPython 3.9manylinux: glibc 2.12+ x86-64

numpy_quaternion-2021.6.9.13.34.11-cp39-cp39-manylinux2010_i686.whl (163.6 kB view details)

Uploaded CPython 3.9manylinux: glibc 2.12+ i686

numpy_quaternion-2021.6.9.13.34.11-cp39-cp39-manylinux1_x86_64.whl (192.6 kB view details)

Uploaded CPython 3.9

numpy_quaternion-2021.6.9.13.34.11-cp39-cp39-manylinux1_i686.whl (163.6 kB view details)

Uploaded CPython 3.9

numpy_quaternion-2021.6.9.13.34.11-cp39-cp39-macosx_10_9_x86_64.whl (56.6 kB view details)

Uploaded CPython 3.9macOS 10.9+ x86-64

numpy_quaternion-2021.6.9.13.34.11-cp38-cp38-win_amd64.whl (60.5 kB view details)

Uploaded CPython 3.8Windows x86-64

numpy_quaternion-2021.6.9.13.34.11-cp38-cp38-win32.whl (56.1 kB view details)

Uploaded CPython 3.8Windows x86

numpy_quaternion-2021.6.9.13.34.11-cp38-cp38-manylinux2010_x86_64.whl (194.2 kB view details)

Uploaded CPython 3.8manylinux: glibc 2.12+ x86-64

numpy_quaternion-2021.6.9.13.34.11-cp38-cp38-manylinux2010_i686.whl (164.7 kB view details)

Uploaded CPython 3.8manylinux: glibc 2.12+ i686

numpy_quaternion-2021.6.9.13.34.11-cp38-cp38-manylinux1_x86_64.whl (194.2 kB view details)

Uploaded CPython 3.8

numpy_quaternion-2021.6.9.13.34.11-cp38-cp38-manylinux1_i686.whl (164.7 kB view details)

Uploaded CPython 3.8

numpy_quaternion-2021.6.9.13.34.11-cp38-cp38-macosx_10_9_x86_64.whl (56.7 kB view details)

Uploaded CPython 3.8macOS 10.9+ x86-64

numpy_quaternion-2021.6.9.13.34.11-cp37-cp37m-win_amd64.whl (60.4 kB view details)

Uploaded CPython 3.7mWindows x86-64

numpy_quaternion-2021.6.9.13.34.11-cp37-cp37m-win32.whl (56.0 kB view details)

Uploaded CPython 3.7mWindows x86

numpy_quaternion-2021.6.9.13.34.11-cp37-cp37m-manylinux2010_x86_64.whl (188.9 kB view details)

Uploaded CPython 3.7mmanylinux: glibc 2.12+ x86-64

numpy_quaternion-2021.6.9.13.34.11-cp37-cp37m-manylinux2010_i686.whl (161.7 kB view details)

Uploaded CPython 3.7mmanylinux: glibc 2.12+ i686

numpy_quaternion-2021.6.9.13.34.11-cp37-cp37m-manylinux1_x86_64.whl (188.9 kB view details)

Uploaded CPython 3.7m

numpy_quaternion-2021.6.9.13.34.11-cp37-cp37m-manylinux1_i686.whl (161.7 kB view details)

Uploaded CPython 3.7m

numpy_quaternion-2021.6.9.13.34.11-cp37-cp37m-macosx_10_9_x86_64.whl (56.4 kB view details)

Uploaded CPython 3.7mmacOS 10.9+ x86-64

numpy_quaternion-2021.6.9.13.34.11-cp36-cp36m-win_amd64.whl (60.4 kB view details)

Uploaded CPython 3.6mWindows x86-64

numpy_quaternion-2021.6.9.13.34.11-cp36-cp36m-win32.whl (56.0 kB view details)

Uploaded CPython 3.6mWindows x86

numpy_quaternion-2021.6.9.13.34.11-cp36-cp36m-manylinux2010_x86_64.whl (187.8 kB view details)

Uploaded CPython 3.6mmanylinux: glibc 2.12+ x86-64

numpy_quaternion-2021.6.9.13.34.11-cp36-cp36m-manylinux2010_i686.whl (160.7 kB view details)

Uploaded CPython 3.6mmanylinux: glibc 2.12+ i686

numpy_quaternion-2021.6.9.13.34.11-cp36-cp36m-manylinux1_x86_64.whl (187.8 kB view details)

Uploaded CPython 3.6m

numpy_quaternion-2021.6.9.13.34.11-cp36-cp36m-manylinux1_i686.whl (160.7 kB view details)

Uploaded CPython 3.6m

numpy_quaternion-2021.6.9.13.34.11-cp36-cp36m-macosx_10_9_x86_64.whl (56.4 kB view details)

Uploaded CPython 3.6mmacOS 10.9+ x86-64

File details

Details for the file numpy-quaternion-2021.6.9.13.34.11.tar.gz.

File metadata

  • Download URL: numpy-quaternion-2021.6.9.13.34.11.tar.gz
  • Upload date:
  • Size: 57.2 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/3.4.1 importlib_metadata/4.5.0 pkginfo/1.7.0 requests/2.25.1 requests-toolbelt/0.9.1 tqdm/4.61.0 CPython/3.9.5

File hashes

Hashes for numpy-quaternion-2021.6.9.13.34.11.tar.gz
Algorithm Hash digest
SHA256 1079e9252bec47fe2b5fd0f710cabb6699573f32e21ccbe3a210a4a2da57c555
MD5 5725426fa3fea44ca78a2b232f203e42
BLAKE2b-256 0aa17a2cec9f263a7a8a6c92095a0a6f2f9096164c177b34b24c8c5cc5a4236a

See more details on using hashes here.

File details

Details for the file numpy_quaternion-2021.6.9.13.34.11-cp39-cp39-win_amd64.whl.

File metadata

  • Download URL: numpy_quaternion-2021.6.9.13.34.11-cp39-cp39-win_amd64.whl
  • Upload date:
  • Size: 60.6 kB
  • Tags: CPython 3.9, Windows x86-64
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/3.4.1 importlib_metadata/4.5.0 pkginfo/1.7.0 requests/2.25.1 requests-toolbelt/0.9.1 tqdm/4.61.0 CPython/3.9.5

File hashes

Hashes for numpy_quaternion-2021.6.9.13.34.11-cp39-cp39-win_amd64.whl
Algorithm Hash digest
SHA256 37b79a92a32511a29c07e35b3dd7368fea8dee4a52be7ad5eb76e38ade1488e6
MD5 b276e0b34df37b0bbc58c9408f202c84
BLAKE2b-256 18c0896f431237ae6c7270a08ffadc688de420b2533cbe331a40f8d37f87c34c

See more details on using hashes here.

File details

Details for the file numpy_quaternion-2021.6.9.13.34.11-cp39-cp39-win32.whl.

File metadata

  • Download URL: numpy_quaternion-2021.6.9.13.34.11-cp39-cp39-win32.whl
  • Upload date:
  • Size: 56.2 kB
  • Tags: CPython 3.9, Windows x86
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/3.4.1 importlib_metadata/4.5.0 pkginfo/1.7.0 requests/2.25.1 requests-toolbelt/0.9.1 tqdm/4.61.0 CPython/3.9.5

File hashes

Hashes for numpy_quaternion-2021.6.9.13.34.11-cp39-cp39-win32.whl
Algorithm Hash digest
SHA256 d53a7a0e042c91bad2216a8373917a33a27a9089575b254f2613936443fff769
MD5 1c3a1697d27f10d6cfb1f40b76d53bd9
BLAKE2b-256 3aa0b4032c4de4fdd58f614abe13c4ecd2765e3706cb062b0b2fbf1e30599545

See more details on using hashes here.

File details

Details for the file numpy_quaternion-2021.6.9.13.34.11-cp39-cp39-manylinux2010_x86_64.whl.

File metadata

File hashes

Hashes for numpy_quaternion-2021.6.9.13.34.11-cp39-cp39-manylinux2010_x86_64.whl
Algorithm Hash digest
SHA256 49b6e7d624497c43ab429cdb2b695138ad03aeac925ae1121fbc8517735450a8
MD5 c091a3d791a144ccd475a52a11c8dd55
BLAKE2b-256 652fa628baf202b8938e36609e07f3c8f5deb60b35dc519f0430501169dee959

See more details on using hashes here.

File details

Details for the file numpy_quaternion-2021.6.9.13.34.11-cp39-cp39-manylinux2010_i686.whl.

File metadata

  • Download URL: numpy_quaternion-2021.6.9.13.34.11-cp39-cp39-manylinux2010_i686.whl
  • Upload date:
  • Size: 163.6 kB
  • Tags: CPython 3.9, manylinux: glibc 2.12+ i686
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/3.4.1 importlib_metadata/4.5.0 pkginfo/1.7.0 requests/2.25.1 requests-toolbelt/0.9.1 tqdm/4.61.0 CPython/3.9.5

File hashes

Hashes for numpy_quaternion-2021.6.9.13.34.11-cp39-cp39-manylinux2010_i686.whl
Algorithm Hash digest
SHA256 2c3a49bbfe85225514edb7717d3b6c8e5e247556503aa6d7b8b9e514f72eb836
MD5 a7f2af823b726a207c3b83a701f1fbdc
BLAKE2b-256 b1be2ea88971ea553e5eeb08da49e660b73b9f33e6eb3b2e130f9b6d071d879e

See more details on using hashes here.

File details

Details for the file numpy_quaternion-2021.6.9.13.34.11-cp39-cp39-manylinux1_x86_64.whl.

File metadata

File hashes

Hashes for numpy_quaternion-2021.6.9.13.34.11-cp39-cp39-manylinux1_x86_64.whl
Algorithm Hash digest
SHA256 3399f655269f4ca17473b09c804e6534b89d152e03b9fecaea0e047a4f727802
MD5 98b706243e3dfb4dc69fba4db5227e05
BLAKE2b-256 ee64bb3fc42b420965cb8fb3f5bec2ec0f5bf1450e0a665ca5b4dadc6fb5ef12

See more details on using hashes here.

File details

Details for the file numpy_quaternion-2021.6.9.13.34.11-cp39-cp39-manylinux1_i686.whl.

File metadata

File hashes

Hashes for numpy_quaternion-2021.6.9.13.34.11-cp39-cp39-manylinux1_i686.whl
Algorithm Hash digest
SHA256 2505e63e3fd9222715081887a440c2b37921fec34ef973b30f7ac00bc2c9cd0d
MD5 20c96fe324c43b165dce8f440ce167c7
BLAKE2b-256 5c088177ccf76e124970fd2d1a2a7ea6d45963fa44d6a86ebe8e9e7841e31092

See more details on using hashes here.

File details

Details for the file numpy_quaternion-2021.6.9.13.34.11-cp39-cp39-macosx_10_9_x86_64.whl.

File metadata

File hashes

Hashes for numpy_quaternion-2021.6.9.13.34.11-cp39-cp39-macosx_10_9_x86_64.whl
Algorithm Hash digest
SHA256 75f02b257994d2b33928d8bcaed4790cea037ff49ff56e92c51b002a280d7585
MD5 7ec8fe731bc0a44c52bed39281da55b5
BLAKE2b-256 c466ffcea15cf9815a8b7b1f2167b15a7bbe184a05c04c9e4c8939682ff4085f

See more details on using hashes here.

File details

Details for the file numpy_quaternion-2021.6.9.13.34.11-cp38-cp38-win_amd64.whl.

File metadata

  • Download URL: numpy_quaternion-2021.6.9.13.34.11-cp38-cp38-win_amd64.whl
  • Upload date:
  • Size: 60.5 kB
  • Tags: CPython 3.8, Windows x86-64
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/3.4.1 importlib_metadata/4.5.0 pkginfo/1.7.0 requests/2.25.1 requests-toolbelt/0.9.1 tqdm/4.61.0 CPython/3.9.5

File hashes

Hashes for numpy_quaternion-2021.6.9.13.34.11-cp38-cp38-win_amd64.whl
Algorithm Hash digest
SHA256 0aed92ef8424ea411426c4278044631ec842aae84044a0200b943f6f0635c756
MD5 4dba7538c74ac2bad22f071ac644061f
BLAKE2b-256 56a25dca47da2dc456ad2087d84afe3ee41b7328494c86be6d3629b812b553bd

See more details on using hashes here.

File details

Details for the file numpy_quaternion-2021.6.9.13.34.11-cp38-cp38-win32.whl.

File metadata

  • Download URL: numpy_quaternion-2021.6.9.13.34.11-cp38-cp38-win32.whl
  • Upload date:
  • Size: 56.1 kB
  • Tags: CPython 3.8, Windows x86
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/3.4.1 importlib_metadata/4.5.0 pkginfo/1.7.0 requests/2.25.1 requests-toolbelt/0.9.1 tqdm/4.61.0 CPython/3.9.5

File hashes

Hashes for numpy_quaternion-2021.6.9.13.34.11-cp38-cp38-win32.whl
Algorithm Hash digest
SHA256 5e1a7613ddbed6375c9121b1007dafb46fc3e32af44917eded2af39de34232b8
MD5 aacc7b6acf93178a941a803e96c6a3b0
BLAKE2b-256 7cc0066d44d50cdefef303e58bc73163379326f62a006cb9b9b5622cfe95db76

See more details on using hashes here.

File details

Details for the file numpy_quaternion-2021.6.9.13.34.11-cp38-cp38-manylinux2010_x86_64.whl.

File metadata

File hashes

Hashes for numpy_quaternion-2021.6.9.13.34.11-cp38-cp38-manylinux2010_x86_64.whl
Algorithm Hash digest
SHA256 a8eefcb2559f30a8b84e28515cec1b9524da5bd32e8fc73ec4b77540b1c40a8d
MD5 e237f8bb337042b3c759b6e71520faea
BLAKE2b-256 57aae29db596bf5449ccb79119aff78bf1a66f4a24be3734ce617b9b0ed5aa71

See more details on using hashes here.

File details

Details for the file numpy_quaternion-2021.6.9.13.34.11-cp38-cp38-manylinux2010_i686.whl.

File metadata

  • Download URL: numpy_quaternion-2021.6.9.13.34.11-cp38-cp38-manylinux2010_i686.whl
  • Upload date:
  • Size: 164.7 kB
  • Tags: CPython 3.8, manylinux: glibc 2.12+ i686
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/3.4.1 importlib_metadata/4.5.0 pkginfo/1.7.0 requests/2.25.1 requests-toolbelt/0.9.1 tqdm/4.61.0 CPython/3.9.5

File hashes

Hashes for numpy_quaternion-2021.6.9.13.34.11-cp38-cp38-manylinux2010_i686.whl
Algorithm Hash digest
SHA256 c10c2c05169d699678718cfa180485a89b2ff371b83d3f2ed7c9087ff2661b66
MD5 7f61d6893e9c7802f6b739b6d2a92158
BLAKE2b-256 13d7135fab87d6e1d930169d0a891fe26ec124f1fa8d6d3616061db8f8469432

See more details on using hashes here.

File details

Details for the file numpy_quaternion-2021.6.9.13.34.11-cp38-cp38-manylinux1_x86_64.whl.

File metadata

File hashes

Hashes for numpy_quaternion-2021.6.9.13.34.11-cp38-cp38-manylinux1_x86_64.whl
Algorithm Hash digest
SHA256 5d7a7e04f1bb6ef3a7273325d20e1faedbfcb9987b8f607569c0197943926501
MD5 694b42c84bbc28742a40c162d5f80539
BLAKE2b-256 89f4dad138beea8fafe88fca7f539d57380513746ff4b3a1dc92df38bded773c

See more details on using hashes here.

File details

Details for the file numpy_quaternion-2021.6.9.13.34.11-cp38-cp38-manylinux1_i686.whl.

File metadata

File hashes

Hashes for numpy_quaternion-2021.6.9.13.34.11-cp38-cp38-manylinux1_i686.whl
Algorithm Hash digest
SHA256 e488dfd5ffd87e08b37f0d143ba9a1a5c6866dc3166fd340470cd8da86836b75
MD5 342812eb2c5f3ba076568638c75fc052
BLAKE2b-256 6982a0e69e407a024e12ad0c921e6e5d705dae2a1813d2de65480c8276b4a9e9

See more details on using hashes here.

File details

Details for the file numpy_quaternion-2021.6.9.13.34.11-cp38-cp38-macosx_10_9_x86_64.whl.

File metadata

File hashes

Hashes for numpy_quaternion-2021.6.9.13.34.11-cp38-cp38-macosx_10_9_x86_64.whl
Algorithm Hash digest
SHA256 2d470420acc3b842d952656f7c6fda5ef620e1445aaa159445b65ede624b5855
MD5 703c9ef03c66f249b7603a4d2296c414
BLAKE2b-256 05bb03da8a7efef583c86a6588161d7d582ab022dfac009c861bd8f13ff90691

See more details on using hashes here.

File details

Details for the file numpy_quaternion-2021.6.9.13.34.11-cp37-cp37m-win_amd64.whl.

File metadata

  • Download URL: numpy_quaternion-2021.6.9.13.34.11-cp37-cp37m-win_amd64.whl
  • Upload date:
  • Size: 60.4 kB
  • Tags: CPython 3.7m, Windows x86-64
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/3.4.1 importlib_metadata/4.5.0 pkginfo/1.7.0 requests/2.25.1 requests-toolbelt/0.9.1 tqdm/4.61.0 CPython/3.9.5

File hashes

Hashes for numpy_quaternion-2021.6.9.13.34.11-cp37-cp37m-win_amd64.whl
Algorithm Hash digest
SHA256 bad7a2bf269352e36d06ca1b102254ede5dd55504946d031e78f2752202378e3
MD5 6df87cd3907d335861f85d7a36c2df83
BLAKE2b-256 a188727e488d7cdeb014f6da9c13b3dd844f8d6f71fef74f073538c939d1c7c6

See more details on using hashes here.

File details

Details for the file numpy_quaternion-2021.6.9.13.34.11-cp37-cp37m-win32.whl.

File metadata

  • Download URL: numpy_quaternion-2021.6.9.13.34.11-cp37-cp37m-win32.whl
  • Upload date:
  • Size: 56.0 kB
  • Tags: CPython 3.7m, Windows x86
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/3.4.1 importlib_metadata/4.5.0 pkginfo/1.7.0 requests/2.25.1 requests-toolbelt/0.9.1 tqdm/4.61.0 CPython/3.9.5

File hashes

Hashes for numpy_quaternion-2021.6.9.13.34.11-cp37-cp37m-win32.whl
Algorithm Hash digest
SHA256 e7d020151bd4162753bbe73a1d4cd0edfa29bedfbbe84f460292692d23a7b87b
MD5 1f01b5e4b12f9b3851b43a398d93351d
BLAKE2b-256 b321a157debc3359a846311470f44bfac44421c1f726ef8724d083565a020261

See more details on using hashes here.

File details

Details for the file numpy_quaternion-2021.6.9.13.34.11-cp37-cp37m-manylinux2010_x86_64.whl.

File metadata

File hashes

Hashes for numpy_quaternion-2021.6.9.13.34.11-cp37-cp37m-manylinux2010_x86_64.whl
Algorithm Hash digest
SHA256 e289ca2dde38781271688db8c339cc99703cbe1c788a74ea9aa84a134fa06819
MD5 535bfe28b60b7cbfffdd17866a3fb183
BLAKE2b-256 4e2c8961bc30bb43c936f50768e19aab1a1d4140e8bb3c58a1ff32b06979cdf2

See more details on using hashes here.

File details

Details for the file numpy_quaternion-2021.6.9.13.34.11-cp37-cp37m-manylinux2010_i686.whl.

File metadata

  • Download URL: numpy_quaternion-2021.6.9.13.34.11-cp37-cp37m-manylinux2010_i686.whl
  • Upload date:
  • Size: 161.7 kB
  • Tags: CPython 3.7m, manylinux: glibc 2.12+ i686
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/3.4.1 importlib_metadata/4.5.0 pkginfo/1.7.0 requests/2.25.1 requests-toolbelt/0.9.1 tqdm/4.61.0 CPython/3.9.5

File hashes

Hashes for numpy_quaternion-2021.6.9.13.34.11-cp37-cp37m-manylinux2010_i686.whl
Algorithm Hash digest
SHA256 6f8b55f3d96f9967106370a4dd5a2cf9b3782ddb5083df9c43a9f1266225f9e0
MD5 1e0d52e1b22f467dbb24e96494bd3748
BLAKE2b-256 1a4973cd8eefad03a02649503391e3341d4bfa77091b0d19139722f6172d2034

See more details on using hashes here.

File details

Details for the file numpy_quaternion-2021.6.9.13.34.11-cp37-cp37m-manylinux1_x86_64.whl.

File metadata

File hashes

Hashes for numpy_quaternion-2021.6.9.13.34.11-cp37-cp37m-manylinux1_x86_64.whl
Algorithm Hash digest
SHA256 620eae215d248ab216be66c295281626c01084ff14c30c0be97e4a849f5cbe30
MD5 aaa0f67285a89c42f2e272c48219acec
BLAKE2b-256 c74656e706c00c746047374244740df26c41ac1431d22e1b44a461f3dc4f23d0

See more details on using hashes here.

File details

Details for the file numpy_quaternion-2021.6.9.13.34.11-cp37-cp37m-manylinux1_i686.whl.

File metadata

File hashes

Hashes for numpy_quaternion-2021.6.9.13.34.11-cp37-cp37m-manylinux1_i686.whl
Algorithm Hash digest
SHA256 fe9ce600be00af443f20e17947069994954c086059048a60fcdf47733044ec8a
MD5 0568a82d5f0e89c269c69fd91f667c52
BLAKE2b-256 8767478bb981264ed567aeb6ac5c745f564027a2f038f04057619e5e1123b344

See more details on using hashes here.

File details

Details for the file numpy_quaternion-2021.6.9.13.34.11-cp37-cp37m-macosx_10_9_x86_64.whl.

File metadata

File hashes

Hashes for numpy_quaternion-2021.6.9.13.34.11-cp37-cp37m-macosx_10_9_x86_64.whl
Algorithm Hash digest
SHA256 e32c9b47aca4e9c2ffc4ddd761a5dece09b71d255d818968ee71007c5234e4ac
MD5 dd316ed2ae5c1e937da5aa044cd66d65
BLAKE2b-256 c45a2ee476ae984bd9cedd45a9f0570fe5ecadc9a7d64eac5e81d3d209583ed3

See more details on using hashes here.

File details

Details for the file numpy_quaternion-2021.6.9.13.34.11-cp36-cp36m-win_amd64.whl.

File metadata

  • Download URL: numpy_quaternion-2021.6.9.13.34.11-cp36-cp36m-win_amd64.whl
  • Upload date:
  • Size: 60.4 kB
  • Tags: CPython 3.6m, Windows x86-64
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/3.4.1 importlib_metadata/4.5.0 pkginfo/1.7.0 requests/2.25.1 requests-toolbelt/0.9.1 tqdm/4.61.0 CPython/3.9.5

File hashes

Hashes for numpy_quaternion-2021.6.9.13.34.11-cp36-cp36m-win_amd64.whl
Algorithm Hash digest
SHA256 f5ed2ec4a091d41d2e8640fdc9a1267ae3cd809209588a4967507409033ad072
MD5 761c131b6f1eaebf3db3bae97feac6af
BLAKE2b-256 5ce5b531af74aeac8fdbe5ba68187a6fe3873e7096968b1d4f6dd7ff3235b3b1

See more details on using hashes here.

File details

Details for the file numpy_quaternion-2021.6.9.13.34.11-cp36-cp36m-win32.whl.

File metadata

  • Download URL: numpy_quaternion-2021.6.9.13.34.11-cp36-cp36m-win32.whl
  • Upload date:
  • Size: 56.0 kB
  • Tags: CPython 3.6m, Windows x86
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/3.4.1 importlib_metadata/4.5.0 pkginfo/1.7.0 requests/2.25.1 requests-toolbelt/0.9.1 tqdm/4.61.0 CPython/3.9.5

File hashes

Hashes for numpy_quaternion-2021.6.9.13.34.11-cp36-cp36m-win32.whl
Algorithm Hash digest
SHA256 eb4190ab07bc77682e976d77e95d48b40f75da7fa7d7439a6464f94ff81a0ab1
MD5 8748ff9d7c1b5277e4b6cb970fbf47d9
BLAKE2b-256 0e842af3b6b35a4ce819e746da401d140c555c47784747032e9f7b55bb694ef3

See more details on using hashes here.

File details

Details for the file numpy_quaternion-2021.6.9.13.34.11-cp36-cp36m-manylinux2010_x86_64.whl.

File metadata

File hashes

Hashes for numpy_quaternion-2021.6.9.13.34.11-cp36-cp36m-manylinux2010_x86_64.whl
Algorithm Hash digest
SHA256 cccf3a3edf94794cc2198ac3dc8394c12cab6af0916da6ff4b5b8ee52323a7d3
MD5 c283a075a31ba3e8752fa33d00b2b5a0
BLAKE2b-256 90aea104d4488c63766393c0348cf5da75cbaafab58aab927372c60ddbd48661

See more details on using hashes here.

File details

Details for the file numpy_quaternion-2021.6.9.13.34.11-cp36-cp36m-manylinux2010_i686.whl.

File metadata

  • Download URL: numpy_quaternion-2021.6.9.13.34.11-cp36-cp36m-manylinux2010_i686.whl
  • Upload date:
  • Size: 160.7 kB
  • Tags: CPython 3.6m, manylinux: glibc 2.12+ i686
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/3.4.1 importlib_metadata/4.5.0 pkginfo/1.7.0 requests/2.25.1 requests-toolbelt/0.9.1 tqdm/4.61.0 CPython/3.9.5

File hashes

Hashes for numpy_quaternion-2021.6.9.13.34.11-cp36-cp36m-manylinux2010_i686.whl
Algorithm Hash digest
SHA256 d6795d9e02984ea47b0bcc3d168412c386e8cadbc15ca05e91ae49284d2f1f70
MD5 c35e38865aed2b4287f689b5a16186e8
BLAKE2b-256 6d436da04b70ecec4b0c2c23ac0a77b0a060cc313592823451599b0ad85da6ff

See more details on using hashes here.

File details

Details for the file numpy_quaternion-2021.6.9.13.34.11-cp36-cp36m-manylinux1_x86_64.whl.

File metadata

File hashes

Hashes for numpy_quaternion-2021.6.9.13.34.11-cp36-cp36m-manylinux1_x86_64.whl
Algorithm Hash digest
SHA256 1e990c3d59c776a7a0ba66d21f3ec920ef9b2ce7a7c7b7cb581ff910f3c8f374
MD5 f7982eef806a35e9db7bcacc856801ec
BLAKE2b-256 5c060941ba54b70d085456052121ccb22e52c9a886edfc9e82ea912fa6aa696e

See more details on using hashes here.

File details

Details for the file numpy_quaternion-2021.6.9.13.34.11-cp36-cp36m-manylinux1_i686.whl.

File metadata

File hashes

Hashes for numpy_quaternion-2021.6.9.13.34.11-cp36-cp36m-manylinux1_i686.whl
Algorithm Hash digest
SHA256 682d452d8d48643a86ed1b23a803563703489cb1168444b4368899c9bf7bea8c
MD5 fd1444a6b9c9d68c7c370c54c55e38f4
BLAKE2b-256 4c8380a3fe502da424c05127c6f4ebb0c7bfe7c938907bb2119d2a7166daef40

See more details on using hashes here.

File details

Details for the file numpy_quaternion-2021.6.9.13.34.11-cp36-cp36m-macosx_10_9_x86_64.whl.

File metadata

File hashes

Hashes for numpy_quaternion-2021.6.9.13.34.11-cp36-cp36m-macosx_10_9_x86_64.whl
Algorithm Hash digest
SHA256 2a59fcb2da032ffbe6ac5be8cf75566fe856073a8f2715c61d8ba357d482e660
MD5 3655a694d63448fe26b0737a866e240b
BLAKE2b-256 441a0379ee21074f5de05c3ee0d790316a6e0ba3a300dd58aa871729c583bbfa

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