Metadata-Version: 2.1
Name: mccn-engine
Version: 0.1.15
Summary: mccn engine
Author-Email: Joseph <joseph.sclauzero@adelaide.edu.au>
License: MIT
Requires-Python: >=3.11
Requires-Dist: odc-stac>=0.3.10
Requires-Dist: pystac-generator>=0.4.0
Requires-Dist: matplotlib>=3.10.1
Requires-Dist: pystac-client>=0.8.6
Requires-Dist: dask==2024.10.0
Requires-Dist: scipy>=1.15.2
Description-Content-Type: text/markdown

# MCCN-Engine

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| Project |     | Status|
|---------|:----|-------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|
| CI/CD   |     | [![CI](https://github.com/aus-plant-phenomics-network/mccn-engine/actions/workflows/github-actions.yml/badge.svg)](https://github.com/aus-plant-phenomics-network/mccn-engine/actions/workflows/github-actions.yml) [![documentation](https://github.com/aus-plant-phenomics-network/mccn-engine/actions/workflows/pages/pages-build-deployment/badge.svg)](https://github.com/aus-plant-phenomics-network/mccn-engine/actions/workflows/pages/pages-build-deployment) |

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<hr>

Check out the [documentation 📚](https://aus-plant-phenomics-network.github.io/mccn-engine/)

Also check out the [case studies](https://github.com/aus-plant-phenomics-network/mccn-case-studies) notebooks.

## About


MCCN-Engine is a python library for loading and combining STAC described asset, generated using the [stac_generator](https://aus-plant-phenomics-network.github.io/stac-generator/), into an [xarray](https://docs.xarray.dev/en/stable/) datacube.

## Installation

Install from PyPi:

```bash
pip install mccn-engine
```

## For developers:

The MCCN-Engine repository uses `pdm` for dependency management. Please [install](https://pdm-project.org/en/latest/#installation) pdm before running the comands below.

Installing dependencies:

```bash
pdm install
```

Run tests:

```bash
make test
```

Lint:

```bash
make lint
```
