Metadata-Version: 2.5
Name: sobig
Version: 0.1.9
Summary: Simulation of observations of biodiversity across gradients.
Project-URL: Homepage, https://github.com/erthward/sobig
Project-URL: Repository, https://github.com/erthward/sobig
Project-URL: Issues, https://github.com/erthward/sobig/issues
Author-email: Drew Terasaki Hart <drew.terasaki.hart@gmail.com>
License: MIT License
        
        Copyright (c) 2026, Drew Ellison Terasaki Hart, Geonomics Development Team
        
        Permission is hereby granted, free of charge, to any person obtaining a copy
        of this software and associated documentation files (the "Software"), to deal
        in the Software without restriction, including without limitation the rights
        to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
        copies of the Software, and to permit persons to whom the Software is
        furnished to do so, subject to the following conditions:
        
        The above copyright notice and this permission notice shall be included in all
        copies or substantial portions of the Software.
        
        THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
        IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
        FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
        AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
        LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
        OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
        SOFTWARE.
License-File: LICENSE
Requires-Python: >=3.9
Requires-Dist: dill
Requires-Dist: dms-variants
Requires-Dist: matplotlib
Requires-Dist: nlmpy
Requires-Dist: numba
Requires-Dist: numpy
Requires-Dist: pandas
Requires-Dist: rasterio
Requires-Dist: rioxarray
Requires-Dist: scikit-learn>=1.2
Requires-Dist: scipy
Requires-Dist: xarray
Provides-Extra: dev
Requires-Dist: build>=1.2; extra == 'dev'
Requires-Dist: pytest>=8; extra == 'dev'
Requires-Dist: ruff>=0.6; extra == 'dev'
Requires-Dist: twine>=5; extra == 'dev'
Description-Content-Type: text/markdown

# SOBiG!

### **S**imulation of **O**bservations of **Bi**odiversity across **G**radients

A Python package for 'reverse-engineering' generalised dissimilarity modelling (GDM)
to simulate communities distributed across variable landscapes,
and then using a 'virtual ecologist' to simulate various observation processes on those communities.

![overview](img/sim_comm_comp_design.png)

## Overview

This package is designed for methods development in community ecology and biodiversity
modelling. It 'reverse-engineers' generalised dissimilarity modelling (GDM), allowing
the user to define environmental landscapes, monotonic environmental
turnover functions (e.g. I-splines) that relate ecological community turnover to those landscapes' variables, the size of the regional species pool (i.e., gamma diversity), and the set of sampling locations. Then it simulates communities at all sampling locations and 
uses a 'virtual ecologist' approach to simulate various observation processes on those communities
(ranging from full-communtiy censuses, to abudance-absence, presence-absence, or presence-only (i.e., 'opportunistic') records.

Workflows can be built from the following steps:

1. Define a landscape and environmental turnover functions.
2. Simulate the latent communities.
3. Simulate one or more observation/survey processes.
4. Fit/visualize GDM or other biodiversity models to the simulated data.
5. Modify environmental layers to represent environmental change.
6. Re-simulate communities and observations.

See the documentation for the full API and examples.

## Installation

```bash
pip install sobig
```

## License

See `LICENSE`.
