Clifford and Geometric Algebra with TensorFlow

## Project description

# TFGA - TensorFlow Geometric Algebra

Python package for Geometric / Clifford Algebra with TensorFlow 2.

This project is a work in progress. Its API may change and the examples aren't polished yet. Pull requests and suggestions either by opening an issue or by sending me an email are welcome.

## Installation

Install using pip: `pip install tfga`

Requirements:

- Python 3
- tensorflow 2
- numpy

## Basic usage

```
from tfga import GeometricAlgebra
# Create an algebra with 3 basis vectors given their metric.
# Used to create MultiVector instances.
ga = GeometricAlgebra(metric=[1, 1, 1])
# 1 e_0 + 1 e_1 + 1 e_2
ordinary_vector = ga.ones(batch_shape=[], kind="vector")
# 5 + 5 e_01 + 5 e_02 + 5 e_12
quaternion = ga.fill(batch_shape=[], fill_value=5.0, kind="even")
# 5 + 1 e_0 + 1 e_1 + 1 e_2 + 5 e_01 + 5 e_02 + 5 e_12
multivector = ordinary_vector + quaternion
# Inner product e_0 | 1 e_0 + 1 e_1 + 1 e_2 = 1
print(ga.basis_mvs[0] | ordinary_vector)
# Exterior product e_0 ^ e_1 = e_01
print(ga.basis_mvs[0] ^ ga.basis_mvs[1])
# Grade reversal ~(5 + 5 e_01 + 5 e_02 + 5 e_12)
# = 5 + 5 e_10 + 5 e_20 + 5 e_21
# = 5 - 5 e_01 - 5 e_02 - 5 e_12
print(~quaternion)
# tf.Tensor 5
print(quaternion.scalar)
# tf.Tensor -5 (ie. reversed sign of e_01 component)
print(quaternion.tensor("10"))
# MultiVector with only e_01: 5 e_01
print(quaternion["10"])
```

## Notebooks

## 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 Distribution

tfga-0.1.8.tar.gz
(13.7 kB
view hashes)

### Built Distribution

tfga-0.1.8-py3-none-any.whl
(15.0 kB
view hashes)