Welcome to the documentation for napari-stress! This ressource provides information, links and examples to navigate and use the functionality of napari-stress, which provides the code for Gross et al. (2021): STRESS, an automated geometrical characterization of deformable particles for in vivo measurements of cell and tissue mechanical stresses.


  • Usage from code: Overview about modular functions in napari-stress and how to use them from code or interactively from the napari viewer. Among others, you’ll find examples for how to use toolbox functions, which bundle up many functionalities of the STRESS workflow in few lines of code.

  • Interactive usage: If you want to do the analysis in an interactive fashion, you can do so directly in the napari viewer. Again, the provided toolboxes.


In order to make napari-stress on your machine, you can follow these tutorials:

  • Getting started with Python and Anaconda: If you have not yet installed Python or Anaconda on your computer, this explains how to set it up and create an environment that contain the most basic functionality (napari & Jupyterlab)

  • Devbio-napari: Not strictly necessary but strongly recommended - this package brings many handy functionalities to an otherwise quite plain napari-viewer.

After both of these are installed, install napari-stress into the environment you created by typing

pip install napari-stress

Other useful packages#

Some packages can be very helpful in conjunction with napari-STRESS, e.g., for better 3D interactivity, visualization of the results and/or data export. Here are some suggestions:

  • Napari-threedee: Enhance rendering options in napari with a set of interesting tools for mesh lighting, plane rendering, etc.install type pip install napari-threedee.

  • Napari-matplotlib: Visualize results obtained with napari-STRESS directly inside the napari viewer with matplotlib. To install, type pip install napari-matplotlib.

  • napari-aicsimageio: Importer library to directly load common file formats into the napari viewer via drag & drop. Note: Depending on the fileformat, you may have to install additional packages (see the documentation for hints on what exactly you need.) To install, type pip install napari-aicsimageio.

If you encounter problems during installations, please have a look at the FAQ page.


If you use napari-stress in your research, please check the acknowledgements and citation section on further information.


If you encounter any issues during installation, please