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-0.10.1.tar.gz (8.2 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-0.10.1-py3-none-any.whl (433.0 kB view details)

Uploaded Python 3

File details

Details for the file canopy_tools-0.10.1.tar.gz.

File metadata

  • Download URL: canopy_tools-0.10.1.tar.gz
  • Upload date:
  • Size: 8.2 MB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/6.2.0 CPython/3.12.12

File hashes

Hashes for canopy_tools-0.10.1.tar.gz
Algorithm Hash digest
SHA256 ca87b3d4ece609af29dee502c096c0007203a53583ca733a636d1c3d42fb98c3
MD5 96aff01ca13c8f3d04e8681b52bcf6d3
BLAKE2b-256 812fc4f7fd04765c6007da980cdf65863f1ca46fdbd1386a9205a88897a91bae

See more details on using hashes here.

File details

Details for the file canopy_tools-0.10.1-py3-none-any.whl.

File metadata

  • Download URL: canopy_tools-0.10.1-py3-none-any.whl
  • Upload date:
  • Size: 433.0 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-0.10.1-py3-none-any.whl
Algorithm Hash digest
SHA256 2875d1b06a4893744a517f1e600f8ca74f7df669f6718058ef1be4a7e5d451b3
MD5 cfad10f14068348208fd0a2b6b1ba108
BLAKE2b-256 e9e845632cd2eae1aa386d83fe4d4854b8bb13b7cf298378d5c1ca01e77c66f6

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