Universal Hyperbolic Geometry library using pure projective operations
Project description
Universal Hyperbolic Geometry (UHG)
A PyTorch library for hyperbolic deep learning using pure UHG principles.
Features
- Pure projective geometry implementation
- No differential geometry or manifold concepts
- Cross-ratio preservation
- Projective transformations
- Graph neural networks
- Optimizers and samplers
Quick Start
import torch
import uhg
# Create points in projective space
x = torch.randn(10, 3)
y = torch.randn(10, 3)
# Initialize UHG
uhg_proj = uhg.ProjectiveUHG()
# Transform points
x_proj = uhg_proj.transform(x)
y_proj = uhg_proj.transform(y)
# Compute projective distance
dist = uhg_proj.proj_dist(x_proj, y_proj)
# Compute cross-ratio
cr = uhg_proj.cross_ratio(x_proj[0], x_proj[1], x_proj[2], x_proj[3])
Installation
pip install uhg
Documentation
For detailed documentation, visit uhg.readthedocs.io.
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
uhg-0.1.18.tar.gz
(33.7 kB
view details)
Built Distribution
Filter files by name, interpreter, ABI, and platform.
If you're not sure about the file name format, learn more about wheel file names.
Copy a direct link to the current filters
uhg-0.1.18-py3-none-any.whl
(34.5 kB
view details)
File details
Details for the file uhg-0.1.18.tar.gz.
File metadata
- Download URL: uhg-0.1.18.tar.gz
- Upload date:
- Size: 33.7 kB
- Tags: Source
- Uploaded using Trusted Publishing? No
- Uploaded via: twine/6.0.1 CPython/3.12.7
File hashes
| Algorithm | Hash digest | |
|---|---|---|
| SHA256 |
95fad3eb9e96bd6c8467128eea31702303d0d31dbc26520ff1125c7f28838769
|
|
| MD5 |
251b73503a2ac5005bf33d82ecdeb435
|
|
| BLAKE2b-256 |
89efd61d965ac7a42e054f7019b391e191f42c2f431ef4a9fa0e556b4de8b318
|
File details
Details for the file uhg-0.1.18-py3-none-any.whl.
File metadata
- Download URL: uhg-0.1.18-py3-none-any.whl
- Upload date:
- Size: 34.5 kB
- Tags: Python 3
- Uploaded using Trusted Publishing? No
- Uploaded via: twine/6.0.1 CPython/3.12.7
File hashes
| Algorithm | Hash digest | |
|---|---|---|
| SHA256 |
3c4b02926c38cb0493afd071ee85d957209c2aa87cdc9d50db84387d23b59987
|
|
| MD5 |
14f90dbc2e46aed2552ba16ce7b5d03a
|
|
| BLAKE2b-256 |
e964f28348f5c9d28f1e9bdc3b3b5c9482939f29003e026948f0727f5c9960de
|