Metadata-Version: 2.4
Name: drpangloss
Version: 0.1.0
Summary: Python package to fit interferometric data, accelerated using Jax.
Author-email: Benjamin Pope <benjamin.pope@mq.edu.au>, Dori Blakely <blakelyd@uvic.ca>
License: MIT License
        
        Copyright (c) 2022 Benjamin Pope
        
        Permission is hereby granted, free of charge, to any person obtaining a copy
        of this software and associated documentation files (the "Software"), to deal
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        The above copyright notice and this permission notice shall be included in all
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        THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
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Project-URL: repository, https://github.com/benjaminpope/drpangloss
Keywords: python,optics,machine-learning,jax,autodiff,differentiable,diffraction,simulation,telescope,drpangloss
Classifier: Programming Language :: Python :: 3
Classifier: Operating System :: OS Independent
Requires-Python: >=3.11
Description-Content-Type: text/markdown
License-File: LICENSE
Requires-Dist: jax
Requires-Dist: jaxlib
Requires-Dist: zodiax
Requires-Dist: numpy
Requires-Dist: matplotlib
Requires-Dist: numpyro
Requires-Dist: tensorflow-probability
Requires-Dist: astropy
Requires-Dist: tqdm
Requires-Dist: ipywidgets
Requires-Dist: optimistix
Requires-Dist: scipy
Requires-Dist: astroquery
Requires-Dist: pyoifits
Requires-Dist: termcolor
Requires-Dist: chainconsumer
Provides-Extra: dev
Requires-Dist: ruff==0.11.0; extra == "dev"
Requires-Dist: pre-commit; extra == "dev"
Requires-Dist: pytest; extra == "dev"
Requires-Dist: mkdocs; extra == "dev"
Requires-Dist: mkdocs-material; extra == "dev"
Requires-Dist: mkdocs-jupyter; extra == "dev"
Requires-Dist: mkdocstrings[python]; extra == "dev"
Requires-Dist: zensical; extra == "dev"
Dynamic: license-file

# drpangloss
[![PyPI version](https://badge.fury.io/py/drpangloss.svg)](https://badge.fury.io/py/drpangloss)
[![License: MIT](https://img.shields.io/badge/License-MIT-yellow.svg)](https://opensource.org/licenses/MIT)
[![integration](https://github.com/benjaminpope/drpangloss/actions/workflows/tests.yml/badge.svg)](https://github.com/benjaminpope/drpangloss/actions/workflows/tests.yml)
[![Documentation](https://github.com/benjaminpope/drpangloss/actions/workflows/documentation.yml/badge.svg)](https://benjaminpope.github.io/drpangloss/)

The best of all possible interferometry models.

Contributors: [Dori Blakely](https://github.com/blakelyd), [Benjamin Pope](https://github.com/benjaminpope)

## What is drpangloss?

drpangloss is a package for modelling optical interferometry data in JAX.

## Installation

drpangloss is hosted on PyPI; the easiest way to install it is:

```
pip install drpangloss
```

You can also build from source. To do so, clone the git repo, enter the directory, and run

```
pip install .
```

We recommend using a virtual environment to avoid dependency conflicts.

Using `uv` (recommended):

```bash
uv python install 3.11
uv venv --python 3.11 .venv
uv pip install --python .venv/bin/python -e . pytest
uv run --python .venv/bin/python pytest -q
```


## Use & Documentation

Documentation is published at [benjaminpope.github.io/drpangloss](https://benjaminpope.github.io/drpangloss/).

Documentation tooling is currently migrating from MkDocs to Zensical. During this transition, both builders are supported from the same configuration file.

Local docs checks:

```bash
uv run --python .venv/bin/python mkdocs build --strict
uv run --python .venv/bin/python zensical build --clean
```

## Collaboration & Development

We welcome collaboration and development contributions. See [CONTRIBUTING.md](CONTRIBUTING.md) for development setup, testing, and pull request workflow.

Current modernization priorities are tracked in [REVIEW_NOTES.md](REVIEW_NOTES.md) and [docs/review_2026-03-03.md](docs/review_2026-03-03.md).

## Name

Why is it called drpangloss?

The leading optical interferometry model fitting code is [CANDID](https://github.com/amerand/CANDID). In Voltaire's *Candide*, Dr Pangloss' belief that we live in the best of all possible worlds is a satire of Leibniz' theodicy. But we *do* live in a world with Jax, so that if we can't optimize the world, at least we can optimize our fits to VLTI data.  
