Metadata-Version: 2.4
Name: pymedm
Version: 2.2.6
Summary: Penalized Maximum-Entropy Dasymetric Modeling (P-MEDM) in Python.
Author-email: "Joe V. Tuccillo" <tuccillojv@ornl.gov>, "James D. Gaboardi" <gaboardijd@ornl.gov>
Maintainer: Joe V. Tuccillo, James D. Gaboardi
Project-URL: Home, https://github.com/likeness-pop
Project-URL: Repository, https://github.com/likeness-pop/pymedm
Classifier: Development Status :: 1 - Planning
Classifier: Intended Audience :: Science/Research
Classifier: Intended Audience :: Developers
Classifier: Intended Audience :: Education
Classifier: Topic :: Scientific/Engineering
Classifier: Topic :: Scientific/Engineering :: GIS
Classifier: Programming Language :: Python
Classifier: Programming Language :: Python :: 3
Requires-Python: >=3.11
Description-Content-Type: text/markdown
License-File: LICENSE
License-File: NOTICE
Requires-Dist: jax>=0.4.31
Requires-Dist: jaxlib>=0.4.31
Requires-Dist: jaxopt>=0.8.3
Requires-Dist: multiprocess>=0.70.15
Requires-Dist: packaging
Requires-Dist: numpy>=1.26
Requires-Dist: pandas>=2.2
Requires-Dist: scipy>=1.12
Provides-Extra: tests
Requires-Dist: pre-commit; extra == "tests"
Requires-Dist: pytest; extra == "tests"
Requires-Dist: pytest-cov; extra == "tests"
Requires-Dist: pytest-xdist; extra == "tests"
Requires-Dist: ruff; extra == "tests"
Requires-Dist: setuptools_scm; extra == "tests"
Requires-Dist: watermark; extra == "tests"
Provides-Extra: notebooks
Requires-Dist: ipywidgets; extra == "notebooks"
Requires-Dist: jupyterlab; extra == "notebooks"
Provides-Extra: jax-gpu
Requires-Dist: jax[cuda12]<=0.4.31; extra == "jax-gpu"
Requires-Dist: jaxlib[cuda12]<=0.4.31; extra == "jax-gpu"
Requires-Dist: cuda-nvcc; extra == "jax-gpu"
Requires-Dist: cudatoolkit; extra == "jax-gpu"
Provides-Extra: all
Requires-Dist: pymedm[notebooks,tests]; extra == "all"
Provides-Extra: cuda-gpu
Requires-Dist: pymedm[jax_gpu,notebooks,tests]; extra == "cuda-gpu"
Dynamic: license-file

# PyMEDM: Penalized Maximum-Entropy Dasymetric Modeling (P-MEDM) in Python

![tag](https://img.shields.io/github/v/release/likeness-pop/pymedm?include_prereleases&sort=semver)
[![Continuous Integration](https://github.com/likeness-pop/pymedm/actions/workflows/continuous_integration.yml/badge.svg)](https://github.com/likeness-pop/pymedm/actions/workflows/continuous_integration.yml)
[![codecov](https://codecov.io/gh/likeness-pop/pymedm/branch/develop/graph/badge.svg)](https://codecov.io/gh/likeness-pop/pymedm)
[![Ruff](https://img.shields.io/endpoint?url=https://raw.githubusercontent.com/astral-sh/ruff/main/assets/badge/v2.json)](https://github.com/astral-sh/ruff)

This is a GPU-ready Python port of [PMEDMrcpp](https://bitbucket.org/jovtc/pmedmrcpp/src/master) via `jax` and `jaxopt`. 

## References

1. **Leyk, S., Nagle, N. N., & Buttenfield, B. P.** (2013). Maximum entropy dasymetric modeling for demographic small area estimation. Geographical Analysis, 45(3), 285-306.
2. **Nagle, N. N., Buttenfield, B. P., Leyk, S., & Spielman, S.** (2014). Dasymetric modeling and uncertainty. Annals of the Association of American Geographers, 104(1), 80-95.
