Skip to main content

A python package to analyse LSM and DGVM outputs

Project description

Python Versions pipeline status PyPI Latest Release PyPI Downloads Docs Status gallery website

Canopy Logo

canopy is an open source python project designed to support research in the field of vegetation dynamics and climate modelling by providing tools for analysing and visualising Dynamic Global Vegetation Model (DGVM) outputs.

Installation

# Create a conda environment (optionnal)
conda create --name canopy python=3.12
conda activate canopy

# Use conda-forge to install canopy
conda install canopy-tools --channel conda-forge

# ... or pip
pip install canopy-tools

Documentation

You can find the canopy documentation on canopy-tools.readthedocs.io

How to use

You can use canopy in two modes:

  • Interactive mode, an intuitive and flexible mode, to analyse data and generate figures using python functions.

  • JSON mode, a easy-to-use and fast mode, to generate figures using a structured JSON configuration file.

Technical documentation

Gallery website

https://canopy.imk-ifu.kit.edu/

What is it? An interactive website showcasing figures created with canopy, where each image links to the code that generated it. Users can also submit their own canopy code (Python or JSON) and figure to be featured, helping build a collection of examples that make learning canopy easy and inspiring.

Issue, questions or suggestions

If you find any bug, please report it on our github issues.

If you have any questions or suggestions, you can also reach the canopy community through our mattermost.

Authors

This project is being developed by David M. Belda & Adrien Damseaux from the Global Land Ecosystem Modelling Group at the Karlsruhe Institute of Technology.

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

canopy_tools-0.7.0.tar.gz (6.3 MB view details)

Uploaded Source

Built Distribution

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

canopy_tools-0.7.0-py3-none-any.whl (408.6 kB view details)

Uploaded Python 3

File details

Details for the file canopy_tools-0.7.0.tar.gz.

File metadata

  • Download URL: canopy_tools-0.7.0.tar.gz
  • Upload date:
  • Size: 6.3 MB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/6.2.0 CPython/3.12.12

File hashes

Hashes for canopy_tools-0.7.0.tar.gz
Algorithm Hash digest
SHA256 ed87da829eed19eea8bfeccfc8462a0a41af825252a4d28c75d99ca5a451ea7c
MD5 af28286fae8845fc669b20952a1479f8
BLAKE2b-256 34a3562abdbe7acf1b33d4308b504366475346e929bc3064f9bac92080f0870c

See more details on using hashes here.

File details

Details for the file canopy_tools-0.7.0-py3-none-any.whl.

File metadata

  • Download URL: canopy_tools-0.7.0-py3-none-any.whl
  • Upload date:
  • Size: 408.6 kB
  • Tags: Python 3
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/6.2.0 CPython/3.12.12

File hashes

Hashes for canopy_tools-0.7.0-py3-none-any.whl
Algorithm Hash digest
SHA256 a1b0877c62ee2e22d71191b6323066012eb6bc370ed25f6c4a7f3c6fe9908753
MD5 9640133165c8927203f0f0199c232693
BLAKE2b-256 14699db635648f5cf5ea9e8f4c428013d79be8d7e4089452fa95e18c0d343e6f

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