scikit-kinematics - Documentation

scikit-kinematics is a library for scientific data analysis, with a focus on 3d kinematics.

It is hosted under https://github.com/thomas-haslwanter/scikit-kinematics, and contains the following modules:

imus Analysis routines for IMU-recordings
  • calculation of orientation from velocity, recorded with IMUs or space-fixed systems (four different algorithms are implemente here:

    • simple quaternion integration

    • a quaternion Kalman filter

    • Madgwick’s algorithm

    • Mahony’s algorithm

  • calculation of position and orientation from IMU-signals

  • The sub-directory sensors contains utility to import in data from xio, XSens, and yei system

markers Analysis routines for 3D movements from marker-based video recordings
  • a function that takes recordings from video-systems (e.g. Optotrak) and calculates position and orientation

  • calculation of joint movements from marker recordings

quat Functions for working with quaternions:
  • quaternion multiplication, inversion, conjugate

  • conversions to rotation matrices, axis angles, vectors

  • a Quaternion class, including operator overloading for multiplication and division

  • also work on data arrays

rotmat Functions for working with rotation matrices
  • rotation matrices for rotations about the x-, y-, and z-axis

  • symbolic rotation matrices

  • conversions to Euler, Fick, Helmholtz angles

  • spatial transformation matrices

  • Denavit-Hartenberg transformations

vector Functions for working with vectors
  • angle between vectors

  • Gram-Schmidt orthogonalization

  • projection

  • normalization

  • rotation

  • also work on data arrays

simulation Functions to simulate ideal IMU-signalsG

view Visualization of time-series data, and of 3D orientations.

Note: Since 2021 Mac OSX no longer supports OpenGL. As a consequence, the module view is no longer automatically loaded, but has to be imported separately, with e.g. from skinematics import view!

In addition, the packages includes the general module

misc Mainly GUI-functions for directory- and file selection etc.

_images/viewer_large.png

Interactively analyze time-series data.

_images/orientation_viewer.png

Visualize 3D orientations.

Installation

The simplest way to install skinematics is a two-step process

>>> pip install scikit-kinematics

However, you can also install from the source files. To do this, just go to the root directory of the package, and type

>>> python setup.py install

Note: After skinematics is installed, I typically import it in Python with:

>>> import skinematics as skin

Upgrading

For upgrading to the latest version, you have to type

>>> pip install --upgrade --no-deps scikit-kinematics

Warning: Do not use pip install scikit-kinematics -U, since that command also upgrades dependencies such as numpy. This can break e.g. WinPython, since the numpy-version including MKL may be replaced by one without MKL.

Dependencies

numpy, scipy, matplotlib, pandas, sympy

Testing

The easiest way to test the package is with unittest. Open a terminal, and type (on the command-line!):

>>> cd [_your_installation_dir_]\skinematics\tests
>>> python -m unittest

Modules

Indices and tables

Note

Author: Thomas Haslwanter
Version: 0.9.3
Date: July 2024
Copyright (c): 2024, Thomas Haslwanter. All rights reserved.
Licence: This work is licensed under the BSD 2-Clause License