Metadata-Version: 2.4
Name: laserfarm
Version: 0.3.1
Summary: Laserchicken Framework for Applications in Research in Macro-ecology
Author-email: Netherlands eScience Center <team-atlas@esciencecenter.nl>
License-Expression: Apache-2.0
Project-URL: repository, https://github.com/eEcoLiDAR/Laserfarm
Project-URL: documentation, https://laserfarm.readthedocs.io
Project-URL: changelog, https://github.com/eEcoLiDAR/Laserfarm/blob/master/CHANGELOG.md
Project-URL: doi, https://doi.org/10.5281/zenodo.3842780
Keywords: Python,Point cloud
Classifier: Development Status :: 2 - Pre-Alpha
Classifier: Intended Audience :: Developers
Classifier: Natural Language :: English
Classifier: Programming Language :: Python :: 3
Classifier: Programming Language :: Python :: 3.10
Classifier: Programming Language :: Python :: 3.11
Classifier: Programming Language :: Python :: 3.12
Description-Content-Type: text/markdown
License-File: LICENSE
Requires-Dist: asyncssh
Requires-Dist: dask[complete]
Requires-Dist: fire
Requires-Dist: numpy
Requires-Dist: laspy[lazrs]
Requires-Dist: laserchicken>=0.6.0
Requires-Dist: plyfile
Requires-Dist: webdavclient3
Requires-Dist: PyShp
Requires-Dist: shapely
Provides-Extra: dev
Requires-Dist: pytest>=6.0; extra == "dev"
Requires-Dist: pytest-cov; extra == "dev"
Requires-Dist: pycodestyle; extra == "dev"
Requires-Dist: pyproj; extra == "dev"
Provides-Extra: docs
Requires-Dist: sphinx; extra == "docs"
Requires-Dist: m2r2; extra == "docs"
Dynamic: license-file

# Laserfarm

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Laserfarm (Laserchicken Framework for Applications in Research in Macro-ecology) provides a FOSS wrapper to
[Laserchicken](https://github.com/eEcoLiDAR/laserchicken) supporting the use of massive LiDAR point cloud data sets for
macro-ecology, from data preparation to scheduling and execution of distributed processing across a cluster of compute
nodes.

## Installation

Laserfarm requires the [PDAL](https://pdal.io) and [GDAL](https://gdal.org) libraries and the PDAL Python
bindings. These packages are most easily installed through `conda` from the `conda-forge` channel:
```shell
conda install pdal python-pdal gdal -c conda-forge
```
Laserfarm can then be downloaded and installed using `pip`:
```shell
pip install laserfarm
```
or using `git` + `pip`:
```shell
git clone git@github.com:eEcoLiDAR/Laserfarm.git
cd Laserfarm
pip install .
```
In order to setup a new conda environment with Laserfarm and all its dependencies, the YAML file provided can be
employed:
```shell
conda env create -f environment.yml
```

## Documentation

The project's full documentation can be found [here](https://laserfarm.readthedocs.io/en/latest/).

## Applications and Current Limitations

This package has been tested on data provided in a metric-based 2D-projected Cartesian coordinate system, i.e. the
[Actueel Hoogtebestand Nederland](https://www.pdok.nl/introductie/-/article/actueel-hoogtebestand-nederland-ahn3-).
While some of the tools of Laserfarm could be applied to data in an ellipsoidal latitude/longitude coordinate system
as well, this has not been tested and it is generally expected to fail.

## Contributing

If you want to contribute to the development of Laserfarm,
have a look at the  [contribution guidelines](CONTRIBUTING.md).

## License

Copyright (c) 2025, Netherlands eScience Center

Licensed under the Apache License, Version 2.0 (the "License");
you may not use this file except in compliance with the License.
You may obtain a copy of the License at

http://www.apache.org/licenses/LICENSE-2.0

Unless required by applicable law or agreed to in writing, software
distributed under the License is distributed on an "AS IS" BASIS,
WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
See the License for the specific language governing permissions and
limitations under the License.
