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-2019.3.21.14.12.56-cp37-cp37m-win_amd64.whl (56.0 kB view details)

Uploaded CPython 3.7mWindows x86-64

numpy_quaternion-2019.3.21.14.12.56-cp36-cp36m-win_amd64.whl (56.0 kB view details)

Uploaded CPython 3.6mWindows x86-64

numpy_quaternion-2019.3.21.14.12.56-cp35-cp35m-win_amd64.whl (56.0 kB view details)

Uploaded CPython 3.5mWindows x86-64

numpy_quaternion-2019.3.21.14.12.56-cp27-cp27m-win_amd64.whl (50.2 kB view details)

Uploaded CPython 2.7mWindows x86-64

File details

Details for the file numpy_quaternion-2019.3.21.14.12.56-cp37-cp37m-win_amd64.whl.

File metadata

  • Download URL: numpy_quaternion-2019.3.21.14.12.56-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-2019.3.21.14.12.56-cp37-cp37m-win_amd64.whl
Algorithm Hash digest
SHA256 cb0b2534b316157f7a7da58b6399cb5eee3b187c445a21c0dbe7e07d6530f453
MD5 616d2d1abd72c29dbcb342fe3e7a151a
BLAKE2b-256 68ca1adbfd2149a08bb29b67b00f42207d8e6f6a7d94ca52e832df9fd46011e8

See more details on using hashes here.

File details

Details for the file numpy_quaternion-2019.3.21.14.12.56-cp36-cp36m-win_amd64.whl.

File metadata

  • Download URL: numpy_quaternion-2019.3.21.14.12.56-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-2019.3.21.14.12.56-cp36-cp36m-win_amd64.whl
Algorithm Hash digest
SHA256 6522ce312fb2a8d8c37720db592a3e8f44df4eccf5646b00df73d3122593add8
MD5 2d323550d2d215c1cd387b34fadc5ea2
BLAKE2b-256 cd1f19bd3078230d5105adad007d949858876f33bf0e0a8e9a4ce612133f47bd

See more details on using hashes here.

File details

Details for the file numpy_quaternion-2019.3.21.14.12.56-cp35-cp35m-win_amd64.whl.

File metadata

  • Download URL: numpy_quaternion-2019.3.21.14.12.56-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-2019.3.21.14.12.56-cp35-cp35m-win_amd64.whl
Algorithm Hash digest
SHA256 97a997aa9eb1576bf2ed81473f2b84efa95728f5f47e35d21675bdea9d09a8a6
MD5 c733df4e65b4fb7f59b617603378f5d0
BLAKE2b-256 fc547c79fba4f674a1108dfe0d19871d8eb6107c37462ad4da3c62e7e415668c

See more details on using hashes here.

File details

Details for the file numpy_quaternion-2019.3.21.14.12.56-cp27-cp27m-win_amd64.whl.

File metadata

  • Download URL: numpy_quaternion-2019.3.21.14.12.56-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-2019.3.21.14.12.56-cp27-cp27m-win_amd64.whl
Algorithm Hash digest
SHA256 1dbde1ccc392d134e94cb3511e2e641df36940ab139aa900aa3dff5dd20c1595
MD5 a53b47df4f953d3b9d3de65f08e2dc0f
BLAKE2b-256 4fdc735cb555aca50f9d90a172f1a208f0038d2b3264a19b974d974a41ba792c

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