A differentiable quaternion implementation in tensorflow.

## Project description

# Tensorflow Quaternion An implementation of quaternions for tensorflow. Fully differentiable.

The tfquaternion module provides an implementation of quaternions as a tensorflow graph. tfquaternion offers module functions for the basic quaternion arithmetic operations as well as a Quaternion class which supports the relevant magic methods. This is similar to the tensorflow API, e.g. tfq.quaternion_multiply vs. tf.multiply and tfq.Quaternion vs tf.Tensor. Note that all functions starting with tf.quaternion_… assume that it’s arguments are tf.Tensor`s (or `tfq.Quaternion`s) that can be casted to `tfq.Quaternion, i.e. the shape must be (…, 4).

This implementation is mostly compatible with a small subset of [moble’s quaternion implementation](https://github.com/moble/quaternion/) (ensured by using slightly adapted versions of his tests). One major difference is that it is type specific as is tensorflow.

### Installation

To install the git version as development package run:
``
git clone https://github.com/PhilJd/tf-quaternion.git
cd tf-quaternion
pip install -e .
``
The -e option only links the working copy to the python site-packages,
so to upgrade, you only need to run git pull.

### Usage

Before getting started, an important note on the division: This library resembles the division behaviour of [moble’s quaternion](https://github.com/moble/quaternion/). While in general the division operator is not defined (from the notation q1/q2 one can not conclude if q1/q2 = q1 * q2^-1 or q1/q2 = q2^-1 * q1), we follow moble’s implementation, i.e. tfq.quaternion_divide and Quaternion.__truediv__ compute q1/q2 = q1 * 1/q2.

#### Example
A simple rotation by a quaternion can look like this:
``
>>> import tfquaternion as tfq
>>> import tensorflow as tf
>>> s = tf.Session()
>>> points = tf.constant([[1, 0, 0], [0, 1, 0], [0, 0, 1]], dtype=tf.float32)
>>> quat = tfq.Quaternion([0, 1, 0, 0]) rotate by 180 degrees around x axis
>>> s.run(tf.matmul(quat.as_rotation_matrix(), points))
array([[ 1., 0., 0.], [ 0., -1., 0.], [ 0., 0., -1.]], dtype=float32)
``

#### API

##### class Quaternion
The usage of the *-Operator depends on the multiplier. If the multiplier is a
Quaternion, quaternion multiplication is performed while multiplication with
a tf.Tensor uses tf.multiply. The behaviour of division is similar, except if
the dividend is a scalar, then the inverse of the quaternion is computed.
``
tfq.Quaternion([1, 0, 0, 0]) * tfq.Quaternion([0, 4, 0, 0])
>>> tfq.Quaternion([0, 4, 0, 0)
tfq.Quaternion([1, 0, 0, 0]) * tf.Tensor([0, 4, 0, 0])
>>> tf.Quaternion([0, 0, 0, 0)
``

## Project details

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Filename, size & hash SHA256 hash help | File type | Python version | Upload date |
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tfquaternion-0.1.2-py2.py3-none-any.whl (14.3 kB) Copy SHA256 hash SHA256 | Wheel | py2.py3 | Jan 2, 2018 |

tfquaternion-0.1.2.tar.gz (10.6 kB) Copy SHA256 hash SHA256 | Source | None | Jan 2, 2018 |