Skip to main content

Laserchicken Framework for Applications in Research in Macro-ecology

Project description

Laserfarm

Actions Status codecov Documentation Status DOI PyPI CII Best Practices

Laserfarm (Laserchicken Framework for Applications in Research in Macro-ecology) provides a FOSS wrapper to 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 and GDAL libraries and the PDAL Python bindings. These packages are most easily installed through conda from the conda-forge channel:

conda install pdal python-pdal gdal -c conda-forge

Laserfarm can then be downloaded and installed using pip:

pip install laserfarm

or using git + pip:

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:

conda env create -f environment.yml

Documentation

The project's full documentation can be found here.

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. 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.

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.

Project details


Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

laserfarm-0.3.1.tar.gz (40.6 kB view details)

Uploaded Source

Built Distribution

If you're not sure about the file name format, learn more about wheel file names.

laserfarm-0.3.1-py3-none-any.whl (32.1 kB view details)

Uploaded Python 3

File details

Details for the file laserfarm-0.3.1.tar.gz.

File metadata

  • Download URL: laserfarm-0.3.1.tar.gz
  • Upload date:
  • Size: 40.6 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/6.1.0 CPython/3.13.7

File hashes

Hashes for laserfarm-0.3.1.tar.gz
Algorithm Hash digest
SHA256 bc5356e939173f526e7b9eb208d3331751e5d22a244be9499ff3dcd598ab1699
MD5 d566135e13647893a32f63a502f17382
BLAKE2b-256 4f1db8a072a95c9d718a84be7db19e8a86c9f135e5b4802ec4fe7253ce891632

See more details on using hashes here.

File details

Details for the file laserfarm-0.3.1-py3-none-any.whl.

File metadata

  • Download URL: laserfarm-0.3.1-py3-none-any.whl
  • Upload date:
  • Size: 32.1 kB
  • Tags: Python 3
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/6.1.0 CPython/3.13.7

File hashes

Hashes for laserfarm-0.3.1-py3-none-any.whl
Algorithm Hash digest
SHA256 4d9715fe4ed77e53601eb12e420e4f8bee735505ad23201c2008ac829e1db78c
MD5 456f59fbe6991af3b2015702628402c6
BLAKE2b-256 984e564f665302a2e50be485f31ba21f39c53a9010d60caf7db0da2df313c335

See more details on using hashes here.

Supported by

AWS Cloud computing and Security Sponsor Datadog Monitoring Depot Continuous Integration Fastly CDN Google Download Analytics Pingdom Monitoring Sentry Error logging StatusPage Status page