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-2018.8.13.16.17.9-cp36-cp36m-win_amd64.whl (53.9 kB view details)

Uploaded CPython 3.6mWindows x86-64

numpy_quaternion-2018.8.13.16.17.9-cp35-cp35m-win_amd64.whl (53.9 kB view details)

Uploaded CPython 3.5mWindows x86-64

numpy_quaternion-2018.8.13.16.17.9-cp34-cp34m-win_amd64.whl (50.8 kB view details)

Uploaded CPython 3.4mWindows x86-64

numpy_quaternion-2018.8.13.16.17.9-cp27-cp27m-win_amd64.whl (47.7 kB view details)

Uploaded CPython 2.7mWindows x86-64

File details

Details for the file numpy_quaternion-2018.8.13.16.17.9-cp36-cp36m-win_amd64.whl.

File metadata

  • Download URL: numpy_quaternion-2018.8.13.16.17.9-cp36-cp36m-win_amd64.whl
  • Upload date:
  • Size: 53.9 kB
  • Tags: CPython 3.6m, Windows x86-64
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/1.11.0 pkginfo/1.4.2 requests/2.19.1 setuptools/39.0.1 requests-toolbelt/0.8.0 tqdm/4.24.0 CPython/3.6.6

File hashes

Hashes for numpy_quaternion-2018.8.13.16.17.9-cp36-cp36m-win_amd64.whl
Algorithm Hash digest
SHA256 65b7e06994df1d1f969a4300a662df94afa5358ebac869e3f2bac9a3a9547362
MD5 42ca0d2dbc04b4510a969a4ccf9f7198
BLAKE2b-256 4398b38e5ded26432b204fb6fd2d419a2eff8d62033f93b5ea42c074ad22c388

See more details on using hashes here.

File details

Details for the file numpy_quaternion-2018.8.13.16.17.9-cp35-cp35m-win_amd64.whl.

File metadata

  • Download URL: numpy_quaternion-2018.8.13.16.17.9-cp35-cp35m-win_amd64.whl
  • Upload date:
  • Size: 53.9 kB
  • Tags: CPython 3.5m, Windows x86-64
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/1.11.0 pkginfo/1.4.2 requests/2.19.1 setuptools/28.8.0 requests-toolbelt/0.8.0 tqdm/4.24.0 CPython/3.5.3

File hashes

Hashes for numpy_quaternion-2018.8.13.16.17.9-cp35-cp35m-win_amd64.whl
Algorithm Hash digest
SHA256 a9af7d3f3fb230c579c4eb94e64ae216b86237103d11d9512f7e4058b7ffb4e8
MD5 3b3aa6d47ec8d6d4ab6d81a51067fb6b
BLAKE2b-256 75e0d912a2d679edd07ec7a282bcad8ae67190a0df178298835ccead51b12628

See more details on using hashes here.

File details

Details for the file numpy_quaternion-2018.8.13.16.17.9-cp34-cp34m-win_amd64.whl.

File metadata

  • Download URL: numpy_quaternion-2018.8.13.16.17.9-cp34-cp34m-win_amd64.whl
  • Upload date:
  • Size: 50.8 kB
  • Tags: CPython 3.4m, Windows x86-64
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/1.11.0 pkginfo/1.4.2 requests/2.19.1 setuptools/18.2 requests-toolbelt/0.8.0 tqdm/4.24.0 CPython/3.4.4

File hashes

Hashes for numpy_quaternion-2018.8.13.16.17.9-cp34-cp34m-win_amd64.whl
Algorithm Hash digest
SHA256 8cb40cc6f256c93c9c162567f892ff288514b6e2c1e8535aee11afff854bc25e
MD5 73c978cb2fee495a9d7676f4848b0ffd
BLAKE2b-256 0a7dcaa31cc40e52df51ef9b124347d239094f60513698bf08b0962bc66b8901

See more details on using hashes here.

File details

Details for the file numpy_quaternion-2018.8.13.16.17.9-cp27-cp27m-win_amd64.whl.

File metadata

  • Download URL: numpy_quaternion-2018.8.13.16.17.9-cp27-cp27m-win_amd64.whl
  • Upload date:
  • Size: 47.7 kB
  • Tags: CPython 2.7m, Windows x86-64
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/1.11.0 pkginfo/1.4.2 requests/2.19.1 setuptools/39.0.1 requests-toolbelt/0.8.0 tqdm/4.24.0 CPython/2.7.15

File hashes

Hashes for numpy_quaternion-2018.8.13.16.17.9-cp27-cp27m-win_amd64.whl
Algorithm Hash digest
SHA256 ae5baa189f3a8775ac46d02b0c6f6f71545af3d972a9860d2d1863ac98a7dad6
MD5 ced16e443229c9dcae710d5c09b95c7b
BLAKE2b-256 446490afe91dd1b6670f766bb198989a1ae36037aa961220780e03434a28c9a8

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