Duck - a package for the duck (operator learning) renormalization group
This package is a Python implementation of the duck (operator learning) renormalization group in JAX.
[!NOTE] There was an older implementation of the duck RG in teal, which was used for the first 2 versions of the duck RG theory paper.
[!IMPORTANT] This package is still under development in alpha stage, and the API may change in the future.
Installation
This package is available on PyPI, thus can be installed via pip:
pip install rogerluo-duck
However, we highly recommend using uv to install the package, run the following in your Python project.
uv add rogerluo-duck
Features
- a simple symbolic system for defining operators
- a set of differentiable local solvers defined on top of the above symbolic system
- implementation of the duck RG loss function
- a set of utilities for training and evaluating the machine learning model in the duck RG
Documentation
The documentation is available at https://rogerluo.dev/duck/.
License
This package is licensed under the Apache License 2.0.
Release files for rogerluo-duck 0.3.2
For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.
Source distribution (sdist)
| File | Size | Uploaded | |
|---|---|---|---|
| rogerluo_duck-0.3.2.tar.gz | 123.2 kB | Details |
Built distribution (wheel)
| File | Interpreter | ABI | Platform | Reset |
|---|---|---|---|---|
| rogerluo_duck-0.3.2-py3-none-any.whl | Python 3 | none | any | Details |
Total release size: 179.3 kB
Release files / rogerluo_duck-0.3.2.tar.gz
| Download URL | rogerluo_duck-0.3.2.tar.gz |
|---|---|
| Size | 123.2 kB |
| Tags | Source |
|
SHA-256 checksum How to use checksums |
f7bbdc9875896be696d7633536900aa7595fb76aa1c8d77db997bfee70c247a1
|
|
BLAKE2b-256 checksum How to use checksums |
0c784d64fff1afea767915978fcbecea499cbb99e8e5ba9f48bc1ec7476b2d38
|
| Upload date | |
|
Uploaded using Trusted Publishing? What is trusted publishing? |
Yes |
| Uploaded via |
twine/5.1.1 CPython/3.12.7
|
Provenance
Provenance describes where a file came from. On PyPI, provenance is shared via attestations, which provide a verifiable record of the build or publishing details. View details, limitations and caveats.
PyPI Publish Attestation
PyPI verified that this artifact, at this checksum, originated from the publisher listed below.
Signed by GitHub Actions, verified by PyPI on Dec 4, 2024.
Transparency logRelease files / rogerluo_duck-0.3.2-py3-none-any.whl
| Download URL | rogerluo_duck-0.3.2-py3-none-any.whl |
|---|---|
| Size | 56.1 kB |
| Tags | Python 3 |
|
SHA-256 checksum How to use checksums |
c656e8b31a0d6b2692273479a9d67207be3e051b523adcca260b7de67874ec05
|
|
BLAKE2b-256 checksum How to use checksums |
2eae8a75cf66aada65c6b9df06627ab7bf7d9363ef0c8b5ac076f95c6f27a2e2
|
| Upload date | |
|
Uploaded using Trusted Publishing? What is trusted publishing? |
Yes |
| Uploaded via |
twine/5.1.1 CPython/3.12.7
|
Provenance
Provenance describes where a file came from. On PyPI, provenance is shared via attestations, which provide a verifiable record of the build or publishing details. View details, limitations and caveats.
PyPI Publish Attestation
PyPI verified that this artifact, at this checksum, originated from the publisher listed below.
Signed by GitHub Actions, verified by PyPI on Dec 4, 2024.
Transparency log