foodwebviz

foodwebviz is a Python package for the visualization of food webs (trophic networks).

• Source: https://github.com/ibs-pan/foodwebviz
• Bug reports: https://github.com/ibs-pan/foodwebviz/issues

Gallery

Installation

Make sure you have Python installed (we recommend Anaconda which comes with a wide range of handy default packages, along with Jupyter Notebooks and convenient Spyder IDE: https://www.anaconda.com/). If you would like to check this package out without full installation - see section "Tutorial".

1. Install npm: https://docs.npmjs.com/cli/v7/configuring-npm/install

2. Install orca: npm install -g electron@6.1.4 orca

3. To create animations, install ImageMagick: https://docs.wand-py.org/en/0.3.5/guide/install.html (on Linux: 'sudo apt-get install libmagickwand-dev')

4. Manually download foodwebviz package from GitHub and run the following terminal command from the top-level source directory (on Windows use e.g. Anaconda Prompt):

   $ pip install .

Tutorial

• examples/sample_output contains examples of visualisations (screenshots of interactive heatmap and graph visualisations)
• examples/interactive_food_web_graph.html is an example of an interactive graph in HTML that can be viewed also without installing everything
• examples/foodwebviz_tutorial.ipynb is an interactive Jupyter Notebook with code examples and functionality overview.

To get information on a specific function/method "function_name" please execute "help(function_name)" in a Jupyter Notebook or Python console. You can also play with the tutorial notebook without installing the package locally: https://mybinder.org/v2/gh/ibs-pan/foodwebviz/master?filepath=examples%2Ffoodwebviz_tutorial.ipynb

Testing

To execute the tests run: $ pytest

foodwebviz uses the Python pytest testing package. You can learn more about pytest on their homepage.

Bugs \ Questions

In case of questions / problems / bugs please report them here.

Citation

When using foodwebviz package please cite:

Łukasz Pawluczuk, Mateusz Iskrzyński (2022) Food web visualisation: heatmap, interactive graph, animated flow network. Methods in Ecology and Evolution, 00, 1– 8. https://doi.org/10.1111/2041-210X.13839, https://github.com/ibs-pan/foodwebviz

A BibTeX entry for LaTeX users:

@article{foodwebviz, author={Łukasz Pawluczuk and Mateusz Iskrzyński}, title={Food web visualisation: heatmap, interactive graph, animated flow network}, year={2022}, journal={Methods in Ecology and Evolution}, doi={10.1111/2041-210X.13839} url={https://github.com/ibs-pan/foodwebviz } }