Skip to main content

Add built-in support for quaternions 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 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.

numpy_quaternion-2019.3.21.13.18.24-cp37-cp37m-win_amd64.whl (56.0 kB view details)

Uploaded CPython 3.7mWindows x86-64

numpy_quaternion-2019.3.21.13.18.24-cp36-cp36m-win_amd64.whl (56.0 kB view details)

Uploaded CPython 3.6mWindows x86-64

numpy_quaternion-2019.3.21.13.18.24-cp35-cp35m-win_amd64.whl (56.0 kB view details)

Uploaded CPython 3.5mWindows x86-64

numpy_quaternion-2019.3.21.13.18.24-cp27-cp27m-win_amd64.whl (50.2 kB view details)

Uploaded CPython 2.7mWindows x86-64

File details

Details for the file numpy_quaternion-2019.3.21.13.18.24-cp37-cp37m-win_amd64.whl.

File metadata

  • Download URL: numpy_quaternion-2019.3.21.13.18.24-cp37-cp37m-win_amd64.whl
  • Upload date:
  • Size: 56.0 kB
  • Tags: CPython 3.7m, Windows x86-64
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/1.13.0 pkginfo/1.5.0.1 requests/2.21.0 setuptools/40.6.2 requests-toolbelt/0.9.1 tqdm/4.31.1 CPython/3.7.2

File hashes

Hashes for numpy_quaternion-2019.3.21.13.18.24-cp37-cp37m-win_amd64.whl
Algorithm Hash digest
SHA256 c62971ed1a2a865cad5f7ca46fd65bc0b4406c3e7bb59c425e1069d3bdd97f46
MD5 aa2d49169eace01f84c90142d0c16216
BLAKE2b-256 d03113c09dd7d0ff7769986ac5b6bbcecdd5bcfce660c80160de6782447975c4

See more details on using hashes here.

File details

Details for the file numpy_quaternion-2019.3.21.13.18.24-cp36-cp36m-win_amd64.whl.

File metadata

  • Download URL: numpy_quaternion-2019.3.21.13.18.24-cp36-cp36m-win_amd64.whl
  • Upload date:
  • Size: 56.0 kB
  • Tags: CPython 3.6m, Windows x86-64
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/1.13.0 pkginfo/1.5.0.1 requests/2.21.0 setuptools/40.6.2 requests-toolbelt/0.9.1 tqdm/4.31.1 CPython/3.6.8

File hashes

Hashes for numpy_quaternion-2019.3.21.13.18.24-cp36-cp36m-win_amd64.whl
Algorithm Hash digest
SHA256 986f68cb9bda1fbc872c36e2627c7a87e8c3d143f54f2e32f48bbb3cc8cb28b0
MD5 a11fb452ac8eeaef80c129c7994b4ba2
BLAKE2b-256 68c4da03ed2dbfc3b0d5fe8105931735775f0d6739d0b657057fa00174eb5d5f

See more details on using hashes here.

File details

Details for the file numpy_quaternion-2019.3.21.13.18.24-cp35-cp35m-win_amd64.whl.

File metadata

  • Download URL: numpy_quaternion-2019.3.21.13.18.24-cp35-cp35m-win_amd64.whl
  • Upload date:
  • Size: 56.0 kB
  • Tags: CPython 3.5m, Windows x86-64
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/1.13.0 pkginfo/1.5.0.1 requests/2.21.0 setuptools/28.8.0 requests-toolbelt/0.9.1 tqdm/4.31.1 CPython/3.5.4

File hashes

Hashes for numpy_quaternion-2019.3.21.13.18.24-cp35-cp35m-win_amd64.whl
Algorithm Hash digest
SHA256 b9ae4cb41b852ec33531ccd1f39bcba132b18c148caa487cecc82b9ede752f2b
MD5 c2a61c2056b933289237b804b0f27f2e
BLAKE2b-256 eb73a0eb12a80cf48a40ed7dae7e3ab6e9d367fde537eee80d9db136819454a5

See more details on using hashes here.

File details

Details for the file numpy_quaternion-2019.3.21.13.18.24-cp27-cp27m-win_amd64.whl.

File metadata

  • Download URL: numpy_quaternion-2019.3.21.13.18.24-cp27-cp27m-win_amd64.whl
  • Upload date:
  • Size: 50.2 kB
  • Tags: CPython 2.7m, Windows x86-64
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/1.13.0 pkginfo/1.5.0.1 requests/2.21.0 setuptools/39.0.1 requests-toolbelt/0.9.1 tqdm/4.31.1 CPython/2.7.15

File hashes

Hashes for numpy_quaternion-2019.3.21.13.18.24-cp27-cp27m-win_amd64.whl
Algorithm Hash digest
SHA256 dcbef52511077fd7efcef7de8be8585591dd264e709a266d08b0cce5ed7681c7
MD5 be91bae3928bfa3e843e9bf116ac9e4d
BLAKE2b-256 50abda0678d9f824aca8c0223921e409256aaffaf9ee782c086d8d6a3a0d0ea3

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