Library implementation choices

KieranWynn/pyquaternion vs moble/quaternion

Project initially started with moble/quaternion but then moved to KieranWynn/pyquaternion because of the following reason:

• moble/quaternion doesn't work on windows, as stated in the readme
• pyquaternion has a better documentation
• pyquaternion has more high-level methods

On the downside pyquaternion has performance disadvantages, as example the following code with numpy-quaternion

quaternions = np.array(
[np.exp(numpy_quaternion.quaternion(*np.asarray(delta_theta)) / 2) for delta_theta in delta_thetas]
)

run in 0.6654262542724609 milliseconds while the following code with pyquaternion

quaternions = np.array(
[Quaternion.exp(Quaternion(vector=delta_theta)/2) for delta_theta in delta_thetas]
)

run in 24.69182014465332 milliseconds both with an array of 100 records

numpy_quaternion has a method "integrate_angular_velocity" but use a Runge-Kutta method that is very slow and a bit obscure