Skip to main content

Add a quaternion dtype to NumPy

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


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 Distribution

numpy-quaternion-2020.9.2.20.23.42.tar.gz (41.8 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-2020.9.2.20.23.42-cp38-cp38-win_amd64.whl (58.9 kB view details)

Uploaded CPython 3.8Windows x86-64

numpy_quaternion-2020.9.2.20.23.42-cp38-cp38-win32.whl (54.9 kB view details)

Uploaded CPython 3.8Windows x86

numpy_quaternion-2020.9.2.20.23.42-cp38-cp38-manylinux2010_x86_64.whl (192.1 kB view details)

Uploaded CPython 3.8manylinux: glibc 2.12+ x86-64

numpy_quaternion-2020.9.2.20.23.42-cp38-cp38-manylinux2010_i686.whl (163.2 kB view details)

Uploaded CPython 3.8manylinux: glibc 2.12+ i686

numpy_quaternion-2020.9.2.20.23.42-cp38-cp38-macosx_10_9_x86_64.whl (54.8 kB view details)

Uploaded CPython 3.8macOS 10.9+ x86-64

numpy_quaternion-2020.9.2.20.23.42-cp37-cp37m-win_amd64.whl (58.8 kB view details)

Uploaded CPython 3.7mWindows x86-64

numpy_quaternion-2020.9.2.20.23.42-cp37-cp37m-win32.whl (54.8 kB view details)

Uploaded CPython 3.7mWindows x86

numpy_quaternion-2020.9.2.20.23.42-cp37-cp37m-manylinux2010_x86_64.whl (187.8 kB view details)

Uploaded CPython 3.7mmanylinux: glibc 2.12+ x86-64

numpy_quaternion-2020.9.2.20.23.42-cp37-cp37m-manylinux2010_i686.whl (160.3 kB view details)

Uploaded CPython 3.7mmanylinux: glibc 2.12+ i686

numpy_quaternion-2020.9.2.20.23.42-cp37-cp37m-macosx_10_9_x86_64.whl (54.5 kB view details)

Uploaded CPython 3.7mmacOS 10.9+ x86-64

numpy_quaternion-2020.9.2.20.23.42-cp36-cp36m-win_amd64.whl (58.8 kB view details)

Uploaded CPython 3.6mWindows x86-64

numpy_quaternion-2020.9.2.20.23.42-cp36-cp36m-win32.whl (54.8 kB view details)

Uploaded CPython 3.6mWindows x86

numpy_quaternion-2020.9.2.20.23.42-cp36-cp36m-manylinux2010_x86_64.whl (186.8 kB view details)

Uploaded CPython 3.6mmanylinux: glibc 2.12+ x86-64

numpy_quaternion-2020.9.2.20.23.42-cp36-cp36m-manylinux2010_i686.whl (159.3 kB view details)

Uploaded CPython 3.6mmanylinux: glibc 2.12+ i686

numpy_quaternion-2020.9.2.20.23.42-cp36-cp36m-macosx_10_9_x86_64.whl (54.5 kB view details)

Uploaded CPython 3.6mmacOS 10.9+ x86-64

File details

Details for the file numpy-quaternion-2020.9.2.20.23.42.tar.gz.

File metadata

  • Download URL: numpy-quaternion-2020.9.2.20.23.42.tar.gz
  • Upload date:
  • Size: 41.8 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/3.2.0 pkginfo/1.5.0.1 requests/2.24.0 setuptools/49.3.1 requests-toolbelt/0.9.1 tqdm/4.48.2 CPython/3.8.5

File hashes

Hashes for numpy-quaternion-2020.9.2.20.23.42.tar.gz
Algorithm Hash digest
SHA256 efc65485b790fd4e0d51ee5ae4db661598d064fb22d82bfbdb3c3f525ebf3889
MD5 6b7a3b5a112b7097b395f9fd34e73946
BLAKE2b-256 3962cbdf96a12f7fe398c55ad134b05a882eaa45494123b39a38d83cb059c337

See more details on using hashes here.

File details

Details for the file numpy_quaternion-2020.9.2.20.23.42-cp38-cp38-win_amd64.whl.

File metadata

  • Download URL: numpy_quaternion-2020.9.2.20.23.42-cp38-cp38-win_amd64.whl
  • Upload date:
  • Size: 58.9 kB
  • Tags: CPython 3.8, Windows x86-64
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/3.2.0 pkginfo/1.5.0.1 requests/2.24.0 setuptools/49.3.1 requests-toolbelt/0.9.1 tqdm/4.48.2 CPython/3.8.5

File hashes

Hashes for numpy_quaternion-2020.9.2.20.23.42-cp38-cp38-win_amd64.whl
Algorithm Hash digest
SHA256 259d1fb8c314ac57b191d4eca9ea7c0f93247e2d0335e319435288318de1a268
MD5 c77d8fba819ec314c923c044840b1af8
BLAKE2b-256 a791f777765100fca1234ac50fe0877062318374126d657908a7655968e5cedc

See more details on using hashes here.

File details

Details for the file numpy_quaternion-2020.9.2.20.23.42-cp38-cp38-win32.whl.

File metadata

  • Download URL: numpy_quaternion-2020.9.2.20.23.42-cp38-cp38-win32.whl
  • Upload date:
  • Size: 54.9 kB
  • Tags: CPython 3.8, Windows x86
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/3.2.0 pkginfo/1.5.0.1 requests/2.24.0 setuptools/49.3.1 requests-toolbelt/0.9.1 tqdm/4.48.2 CPython/3.8.5

File hashes

Hashes for numpy_quaternion-2020.9.2.20.23.42-cp38-cp38-win32.whl
Algorithm Hash digest
SHA256 1c9af0fec54793261b18f3568b67c908c31555f2f6af59905a49db3fab8690d2
MD5 ebff7d8bdf5122af75a0b2188b5d255e
BLAKE2b-256 72eb1df40b3dc745e4baec8b0bbe29b900ef87486cc40fbc4c70ebcb1d366811

See more details on using hashes here.

File details

Details for the file numpy_quaternion-2020.9.2.20.23.42-cp38-cp38-manylinux2010_x86_64.whl.

File metadata

File hashes

Hashes for numpy_quaternion-2020.9.2.20.23.42-cp38-cp38-manylinux2010_x86_64.whl
Algorithm Hash digest
SHA256 7b604ac94ca7afd38372e9db847f3431d51f37d47ee96545056b7388078da77e
MD5 3b9d88ecd158ba290c0fc607d546fc44
BLAKE2b-256 b106bc2ed25ebb852ae7180c7b5c29ce68f20d69149b0c203455a077ae5ef4e9

See more details on using hashes here.

File details

Details for the file numpy_quaternion-2020.9.2.20.23.42-cp38-cp38-manylinux2010_i686.whl.

File metadata

File hashes

Hashes for numpy_quaternion-2020.9.2.20.23.42-cp38-cp38-manylinux2010_i686.whl
Algorithm Hash digest
SHA256 117a5ca485f9111d598e3673b926989f7b5e6af5d3e29a58068b7387265435e3
MD5 bc208300ba20b8eb70829edb012475e4
BLAKE2b-256 f70ee4e10eab03405480957d280a77f68d1da45689ff79ae40d04aef6b6d55cf

See more details on using hashes here.

File details

Details for the file numpy_quaternion-2020.9.2.20.23.42-cp38-cp38-manylinux1_x86_64.whl.

File metadata

File hashes

Hashes for numpy_quaternion-2020.9.2.20.23.42-cp38-cp38-manylinux1_x86_64.whl
Algorithm Hash digest
SHA256 ddcfacfa44065d26bbf7b6948aa13215ab0eb671d3d32c8a71f10c9baf382382
MD5 de541ecaf2410d901a8279200b1b0b65
BLAKE2b-256 3afc4586634179a1d8ff845172bc52d20c443ac76ce7eebb0c3005325ae06a4a

See more details on using hashes here.

File details

Details for the file numpy_quaternion-2020.9.2.20.23.42-cp38-cp38-manylinux1_i686.whl.

File metadata

File hashes

Hashes for numpy_quaternion-2020.9.2.20.23.42-cp38-cp38-manylinux1_i686.whl
Algorithm Hash digest
SHA256 f472c51c2671f57b763790daac9eddc493d1d62ce7d2eed7bb495542d118f98e
MD5 02fb73d3d9446096a77b37f9b54d26e4
BLAKE2b-256 76c3f495b6cffaeb346cc9157d3ccca1fba462643b2976270ace74b001d193e1

See more details on using hashes here.

File details

Details for the file numpy_quaternion-2020.9.2.20.23.42-cp38-cp38-macosx_10_9_x86_64.whl.

File metadata

File hashes

Hashes for numpy_quaternion-2020.9.2.20.23.42-cp38-cp38-macosx_10_9_x86_64.whl
Algorithm Hash digest
SHA256 cffce01a2a20d593475d62eddb2f580d832030965862b6f75bf2c481ee3ad1b5
MD5 1d69625ff263bf1222bff30fa99b6e82
BLAKE2b-256 7a0406e9e92562877efd4bf5be717734fd883c4fc0fb36934800f7130e928f3c

See more details on using hashes here.

File details

Details for the file numpy_quaternion-2020.9.2.20.23.42-cp37-cp37m-win_amd64.whl.

File metadata

  • Download URL: numpy_quaternion-2020.9.2.20.23.42-cp37-cp37m-win_amd64.whl
  • Upload date:
  • Size: 58.8 kB
  • Tags: CPython 3.7m, Windows x86-64
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/3.2.0 pkginfo/1.5.0.1 requests/2.24.0 setuptools/49.3.1 requests-toolbelt/0.9.1 tqdm/4.48.2 CPython/3.8.5

File hashes

Hashes for numpy_quaternion-2020.9.2.20.23.42-cp37-cp37m-win_amd64.whl
Algorithm Hash digest
SHA256 e96063723691c716073c322ecbcc7f392598debbc52f8964eeaf5c919bcc419d
MD5 1bdc35c4d59d16befab1c711db81cfc1
BLAKE2b-256 6ec8edb08b8ebc7c531816d976a5ec7ebc1abd79f92e8f03676170d869046117

See more details on using hashes here.

File details

Details for the file numpy_quaternion-2020.9.2.20.23.42-cp37-cp37m-win32.whl.

File metadata

  • Download URL: numpy_quaternion-2020.9.2.20.23.42-cp37-cp37m-win32.whl
  • Upload date:
  • Size: 54.8 kB
  • Tags: CPython 3.7m, Windows x86
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/3.2.0 pkginfo/1.5.0.1 requests/2.24.0 setuptools/49.3.1 requests-toolbelt/0.9.1 tqdm/4.48.2 CPython/3.8.5

File hashes

Hashes for numpy_quaternion-2020.9.2.20.23.42-cp37-cp37m-win32.whl
Algorithm Hash digest
SHA256 9d2bebdbe72dfb9784eec2c37fdec05cabd3425fd57faba1d7a7959867f658df
MD5 7bcb645ce4ada6ed5dd49519ea648269
BLAKE2b-256 2fabc8d29c66959ffb64d05f5daece9a3774b484cdda67c17235d4b6f111006b

See more details on using hashes here.

File details

Details for the file numpy_quaternion-2020.9.2.20.23.42-cp37-cp37m-manylinux2010_x86_64.whl.

File metadata

File hashes

Hashes for numpy_quaternion-2020.9.2.20.23.42-cp37-cp37m-manylinux2010_x86_64.whl
Algorithm Hash digest
SHA256 c5a94e1296ba832a161a456530f3cb07d9f904cc3a3980ee8ba0eaaaa4563634
MD5 cbaf70dcd25155c073ae87ab6b0d817f
BLAKE2b-256 5fdcedd4ece80096d88ec29c571ef373c5f147e023a05ee170ad8b79c7c52c44

See more details on using hashes here.

File details

Details for the file numpy_quaternion-2020.9.2.20.23.42-cp37-cp37m-manylinux2010_i686.whl.

File metadata

File hashes

Hashes for numpy_quaternion-2020.9.2.20.23.42-cp37-cp37m-manylinux2010_i686.whl
Algorithm Hash digest
SHA256 0926ed6db307accc1795ba63de8ffa1292562ccee0c087b0fc871073703d62af
MD5 489773a90e542042092a56c4101acd52
BLAKE2b-256 bb9bbb0d58572bff6bf575efd4bf2c862cbc7166f63946d9cdd4ee10180faf6d

See more details on using hashes here.

File details

Details for the file numpy_quaternion-2020.9.2.20.23.42-cp37-cp37m-manylinux1_x86_64.whl.

File metadata

File hashes

Hashes for numpy_quaternion-2020.9.2.20.23.42-cp37-cp37m-manylinux1_x86_64.whl
Algorithm Hash digest
SHA256 5389c894aebb92bb42b1b2fe896718bb153a89c7239f450c06c29937db87b1d3
MD5 e72987fae1a6658a1815433d4a5d1e49
BLAKE2b-256 830b9374edcdcb540f0c7648aab2116adf400c4e087861d275be90a2299e26c9

See more details on using hashes here.

File details

Details for the file numpy_quaternion-2020.9.2.20.23.42-cp37-cp37m-manylinux1_i686.whl.

File metadata

File hashes

Hashes for numpy_quaternion-2020.9.2.20.23.42-cp37-cp37m-manylinux1_i686.whl
Algorithm Hash digest
SHA256 125f42f82e7d4d396d02ec405c9c0713c461e74336577212ac383570efefeedf
MD5 734b92452786ac2c5f7c587168a9225f
BLAKE2b-256 3dfee6783c9c25bff0b79890afebb0023796edf768db9f6fe130bf94097c4f35

See more details on using hashes here.

File details

Details for the file numpy_quaternion-2020.9.2.20.23.42-cp37-cp37m-macosx_10_9_x86_64.whl.

File metadata

File hashes

Hashes for numpy_quaternion-2020.9.2.20.23.42-cp37-cp37m-macosx_10_9_x86_64.whl
Algorithm Hash digest
SHA256 28cc812a8cc7f7f451459595c3795efd3d971800732ae875d9538d5de9d12e28
MD5 1cfe8749267f7cf3ea32180fe09ab067
BLAKE2b-256 794c397d3f878dc65e670b65ede245a6f644e383100a404441e12ed48c85ae36

See more details on using hashes here.

File details

Details for the file numpy_quaternion-2020.9.2.20.23.42-cp36-cp36m-win_amd64.whl.

File metadata

  • Download URL: numpy_quaternion-2020.9.2.20.23.42-cp36-cp36m-win_amd64.whl
  • Upload date:
  • Size: 58.8 kB
  • Tags: CPython 3.6m, Windows x86-64
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/3.2.0 pkginfo/1.5.0.1 requests/2.24.0 setuptools/49.3.1 requests-toolbelt/0.9.1 tqdm/4.48.2 CPython/3.8.5

File hashes

Hashes for numpy_quaternion-2020.9.2.20.23.42-cp36-cp36m-win_amd64.whl
Algorithm Hash digest
SHA256 d30e5a5d78e2b72337249db364030af4a13f1bac6c834eb5bec6b7acda2e0b17
MD5 9b353dd4fb37dedd022fc5018daa33dc
BLAKE2b-256 91539368011050db89ae4e6debe3dfdd9180088c4dbb3a3074b9b037ea4a587a

See more details on using hashes here.

File details

Details for the file numpy_quaternion-2020.9.2.20.23.42-cp36-cp36m-win32.whl.

File metadata

  • Download URL: numpy_quaternion-2020.9.2.20.23.42-cp36-cp36m-win32.whl
  • Upload date:
  • Size: 54.8 kB
  • Tags: CPython 3.6m, Windows x86
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/3.2.0 pkginfo/1.5.0.1 requests/2.24.0 setuptools/49.3.1 requests-toolbelt/0.9.1 tqdm/4.48.2 CPython/3.8.5

File hashes

Hashes for numpy_quaternion-2020.9.2.20.23.42-cp36-cp36m-win32.whl
Algorithm Hash digest
SHA256 9fd3e907ef786eda3d5ed0a93bb8f2b51b16629fe6d21826e7b7820c7320d54e
MD5 a2027f11c3089f4f90183f76b67b9fe0
BLAKE2b-256 f0a9bd70677580be20853c2a42f9fd86aa0278b1dcfde477060f547fc42cf00c

See more details on using hashes here.

File details

Details for the file numpy_quaternion-2020.9.2.20.23.42-cp36-cp36m-manylinux2010_x86_64.whl.

File metadata

File hashes

Hashes for numpy_quaternion-2020.9.2.20.23.42-cp36-cp36m-manylinux2010_x86_64.whl
Algorithm Hash digest
SHA256 3bfe720c7a132680dc10cff44d1b0abcb7cf04f53cec9ca2f26982ab13823994
MD5 6733e3140493fe208f0f0950f236f2e0
BLAKE2b-256 e473a4cc719104a56ded7b8b1bb8d9201d3d2720cc68c5317cdea50bfb3b72e2

See more details on using hashes here.

File details

Details for the file numpy_quaternion-2020.9.2.20.23.42-cp36-cp36m-manylinux2010_i686.whl.

File metadata

File hashes

Hashes for numpy_quaternion-2020.9.2.20.23.42-cp36-cp36m-manylinux2010_i686.whl
Algorithm Hash digest
SHA256 512c30130fd99bf23aa98850447642633716a4dd32cf55e6dc3a4e4f2ce28649
MD5 9d369ddae0493a018d5f60d50e7ee128
BLAKE2b-256 7185c59f6dc6b7934bb1e64ed989e2587c1ce2ebb4b9319055d7d50f81e4b62b

See more details on using hashes here.

File details

Details for the file numpy_quaternion-2020.9.2.20.23.42-cp36-cp36m-manylinux1_x86_64.whl.

File metadata

File hashes

Hashes for numpy_quaternion-2020.9.2.20.23.42-cp36-cp36m-manylinux1_x86_64.whl
Algorithm Hash digest
SHA256 2b425ca52fd79cfecd8d816c6a65306802b76d6be11145b9d8d8fc9e68a65423
MD5 4c08c51a17ce784fd84c5298638f8290
BLAKE2b-256 3c1d2d5d262b9054ea4ea874236bc8666ba09ef9c3857f236c38d81cd67a15a2

See more details on using hashes here.

File details

Details for the file numpy_quaternion-2020.9.2.20.23.42-cp36-cp36m-manylinux1_i686.whl.

File metadata

File hashes

Hashes for numpy_quaternion-2020.9.2.20.23.42-cp36-cp36m-manylinux1_i686.whl
Algorithm Hash digest
SHA256 dd3064022942ed7a97e96ad1116b5165636072bae8b00c8ead7351b48fb84540
MD5 e55865cbca866b79e84ca8f04f46bd28
BLAKE2b-256 2ab5be0c6d193ccf487c62943d29a47d0c0ca2c56715e4dc4a2838f9d1cc02f2

See more details on using hashes here.

File details

Details for the file numpy_quaternion-2020.9.2.20.23.42-cp36-cp36m-macosx_10_9_x86_64.whl.

File metadata

File hashes

Hashes for numpy_quaternion-2020.9.2.20.23.42-cp36-cp36m-macosx_10_9_x86_64.whl
Algorithm Hash digest
SHA256 e6040f99242704374dd408d35c5be049b16ea44ee7bdbf18e676b53c87bfd786
MD5 0f7cf408e4f4deed293ae16151831687
BLAKE2b-256 95a2f44e69df12fe31b5c3984161dfb840e783f08c3122cdb22c650c3dcd342b

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