Skip to main content

A python package to analyse LSM and DGVM outputs

Project description

DOI

Canopy Logo

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

Python Versions PyPI Latest Release Conda Version

pipeline status documentation website gallery website notebooks gitlab

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

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 and/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 gitlab issues

If you have any questions or suggestions, you can also reach the canopy community through our mattermost help-desk channel

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-0.11.0.tar.gz (8.3 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-0.11.0-py3-none-any.whl (578.6 kB view details)

Uploaded Python 3

File details

Details for the file canopy_tools-0.11.0.tar.gz.

File metadata

  • Download URL: canopy_tools-0.11.0.tar.gz
  • Upload date:
  • Size: 8.3 MB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/6.2.0 CPython/3.12.13

File hashes

Hashes for canopy_tools-0.11.0.tar.gz
Algorithm Hash digest
SHA256 27c523f04ea457061ec41ffafa087e39051809d6ff1ebed510199e32ce57f663
MD5 33fadcdb5a8c50d93b30a5f285dafdf1
BLAKE2b-256 26f2a7c3c07dfcf6db63cf3e3c018af2ba3aff9b0565783bd973500bf615205c

See more details on using hashes here.

File details

Details for the file canopy_tools-0.11.0-py3-none-any.whl.

File metadata

  • Download URL: canopy_tools-0.11.0-py3-none-any.whl
  • Upload date:
  • Size: 578.6 kB
  • Tags: Python 3
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/6.2.0 CPython/3.12.13

File hashes

Hashes for canopy_tools-0.11.0-py3-none-any.whl
Algorithm Hash digest
SHA256 e53e53152c9c85562d3ce864dd60a6d42870bb5163fc17a0f499864ea26fb89f
MD5 14611863ae2258d60b238c3d052fc32b
BLAKE2b-256 32323ec61f883dd0e5e3ee9427f8d6a1049b562abdcf90e41039868426f55971

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