Metadata-Version: 2.4
Name: localuf
Version: 3.4.3
Summary: A Python package to simulate and visualise Union-Find-related decoders for CSS codes.
Project-URL: Homepage, https://github.com/timchan0/localuf
Project-URL: Documentation, https://github.com/timchan0/localuf
Project-URL: Repository, https://github.com/timchan0/localuf.git
Project-URL: Issues, https://github.com/timchan0/localuf/issues
Author-email: Tim Chan <timwlc@icloud.com>
License: MIT
License-File: LICENSE
Keywords: css-codes,decoders,quantum-error-correction,union-find
Classifier: Development Status :: 4 - Beta
Classifier: Intended Audience :: Science/Research
Classifier: License :: OSI Approved :: MIT License
Classifier: Natural Language :: English
Classifier: Operating System :: OS Independent
Classifier: Programming Language :: Python :: 3
Classifier: Programming Language :: Python :: 3.10
Classifier: Programming Language :: Python :: 3.11
Classifier: Programming Language :: Python :: 3.12
Classifier: Topic :: Scientific/Engineering :: Physics
Requires-Python: >=3.10
Requires-Dist: ipykernel
Requires-Dist: ipywidgets
Requires-Dist: matplotlib
Requires-Dist: networkx
Requires-Dist: pandas
Requires-Dist: pymatching
Requires-Dist: scipy
Requires-Dist: statsmodels
Requires-Dist: stim
Description-Content-Type: text/markdown

# localuf (Local Union-Find)

A Python package to simulate and visualise
Union-Find-related decoders for CSS codes.
All UML class diagrams can be found in `uml_class_diagrams.md`.

## Local Installation Instructions

### Using Conda

Create environment called `localuf`:

```bash
conda env create -f environment.yml
```

Activate the environment:

```bash
conda activate localuf
```

Install the `localuf` package in editable mode (and its dependencies from pip):

```bash
python -m pip install -e . --no-build-isolation --no-deps
```

### Using Pip (Untested)

Install the package in editable mode and its dependencies using pip:

```bash
pip install -e .
```

## Usage

See `demo_notebooks/intro.ipynb`.
The first section is a demo of the Macar and Actis decoders.
The second section is a demo of the Snowflake decoder.