nViz

This project focuses on ingesting a set of TIFF images as OME-Zarr or OME-TIFF. Each input image set¹ are organized by channel and z-slices which form four dimensional (4D) microscopy data. These 4D microscopy data contain information for biological objects (such as organoids).

We read the output with Napari, which provides a way to analyze and understand the 3D image data.

1. Image set is loosely defined and changes depending on the context of the data. Here it represents a set of images in multiple dimensions that contain information regarding the same sample. Each image in an imageset is paired data and must be related as such.

Installation

Install nViz from PyPI or from source:

# install from pypi
pip install nviz

# install directly from source
pip install git+https://github.com/WayScience/nViz.git

Installation notes for Linux

nViz leverages Napari to help render visuals. Napari leverages PyQT to help build graphical components. PyQT has specific requirements based on the operating system which sometimes can cause errors within Napari, and as a result, also nViz.

Below are some steps to try if you find that nViz visualizations through Napari are resulting in QT-related errors.

• Attempt to install python3-pyqt5 through your system package manager (e.g. apt install python3-pyqt5).
• When using nViz within GitHub Actions Linux environments, consider using pyvista/setup-headless-display-action with qt: true in order to run without general exceptions.

Contributing, Development, and Testing

Please see our contributing documentation for more details on contributions, development, and testing.