Metadata-Version: 2.5
Name: nestsar
Version: 0.1.0
Summary: Nested species-area relationship datasets from point observations
Project-URL: Homepage, https://github.com/jmcmeen/nestsar
Project-URL: Source, https://github.com/jmcmeen/nestsar
Project-URL: Changelog, https://github.com/jmcmeen/nestsar/blob/main/CHANGELOG.md
Project-URL: Bug Tracker, https://github.com/jmcmeen/nestsar/issues
Author-email: John McMeen <johnmcmeen@gmail.com>
License-Expression: MIT
License-File: LICENSE
Classifier: Development Status :: 3 - Alpha
Classifier: Intended Audience :: Developers
Classifier: Intended Audience :: Science/Research
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: Programming Language :: Python :: 3.13
Requires-Python: >=3.10
Requires-Dist: numpy>=1.22
Requires-Dist: pandas>=1.4
Requires-Dist: sars>=0.7.10
Requires-Dist: shapely>=2.0
Provides-Extra: dev
Requires-Dist: pytest-cov; extra == 'dev'
Requires-Dist: pytest>=7.0; extra == 'dev'
Requires-Dist: ruff<0.18,>=0.17; extra == 'dev'
Description-Content-Type: text/markdown

# nestsar

Nested species-area relationship datasets from point observations. Build a
sequence of nested sub-samples from georeferenced species records and hand
the resulting area and richness table to [sars](https://pypi.org/project/sars/)
for curve fitting.

```python
import nestsar, sars

sample = nestsar.Sample.from_csv("observations.csv")   # species, lon, lat
nest = nestsar.random_nest(sample, seed=0)
fit = sars.sar_power(nest.sar_data())
```

## Development

```sh
make install   # create .venv with dev tooling
make check     # lint, format check, tests
```
