https://github.com/hafaio/hilbert-bytes

A python library for converting between d-dimensional points and indices on a hilbert curve
https://github.com/hafaio/hilbert-bytes

hilbert-curve numba numpy python

Last synced: 6 months ago
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A python library for converting between d-dimensional points and indices on a hilbert curve

• Host: GitHub
• URL: https://github.com/hafaio/hilbert-bytes
• Owner: hafaio
• License: mit
• Created: 2025-01-18T02:32:06.000Z (about 1 year ago)
• Default Branch: main
• Last Pushed: 2025-04-06T16:42:53.000Z (10 months ago)
• Last Synced: 2025-07-16T22:56:41.721Z (7 months ago)
• Topics: hilbert-curve, numba, numpy, python
• Language: Python
• Homepage: https://erikbrinkman.github.io/hilbert-bytes/
• Size: 134 KB
• Stars: 0
• Watchers: 1
• Forks: 0
• Open Issues: 0
• Metadata Files:
  • Readme: README.md
  • License: LICENSE

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README

          
# Hilbert Bytes

[![build](https://github.com/erikbrinkman/hilbert-bytes/actions/workflows/python-package.yml/badge.svg)](https://github.com/erikbrinkman/hilbert-bytes/actions/workflows/python-package.yml)

[![pypi](https://img.shields.io/pypi/v/hilbert-bytes)](https://pypi.org/project/hilbert-bytes/)

[![docs](https://img.shields.io/badge/api-docs-blue)](https://erikbrinkman.github.io/hilbert-bytes)

Hilbert Bytes is a python library for converting to and from points in

d-dimensions and their corresponding index on a hilbert curve. It's similar to

[hilbertcurve](https://pypi.org/project/hilbertcurve/) and

[numpy-hilbert-curve](https://pypi.org/project/numpy-hilbert-curve/) but is

faster and more space efficient than either by keeping manipulations at the byte

level, and using numba to compile the results. It also uses arbitrary precision

integers, allowing you to make the grid arbitrarily fine

## Installation

```sh

pip install hilbert-bytes

```

## Usage

```py

import hilbert_bytes

import numpy as np

points = ... # arbitrary d-dimensional points

num, dim = points.shape

# convert to big-endian bytes

points_bytes = points[..., None].astype(">u8").view("u1")

index_bytes = hilbert_bytes.encode(points_bytes)  # indies as big-endian ints

new_points_bytes = hilbert_bytes.decode(index_bytes)

```

If you want the indices as multi-byte ints, you can can do a similar trick in reverse:

```py

index_bytes = ... # an array of big-endian ints

indices = index_bytes.view(">u8").astype("u8")[..., 0]

```

But note that this will only work if your index fits in 8 bytes

## Publishing

```sh

rm -rf dist

uv build

uv publish --username __token__

```