The spatialdata-plot package extends spatialdata with a declarative plotting API that enables to quickly visualize spatialdata objects and their respective elements (i.e. images, labels, points and shapes).

SpatialData’s plotting capabilities allow to quickly visualise all contained modalities. The user can specify which elements should be rendered (images, labels, points, shapes) and specify certain parameters for each layer, such as for example the intent to color shapes by a gene’s expression profile or which color to use for which image channel. When the plot is then eventually displayed, all transformations, alignments and coordinate systems are internally processed to form the final visualisation. In concordance with the general SpatialData philosophy, all modalities of the major spatial technologies are supported out of the box.

For more information on the spatialdata-plot library, please refer to the documentation. In particular, the

• API documentation.
• Example notebooks (section "Visiualizations")

You need to have Python 3.9 or newer installed on your system. If you don't have Python installed, we recommend installing Mambaforge.

There are several alternative options to install spatialdata-plot:

1. Install the latest development version:

pip install git+https://github.com/scverse/spatialdata-plot.git@main

For questions and help requests, you can reach out in the scverse discourse. If you found a bug, please use the issue tracker.

If you use spatialdata in your work, please cite the spatialdata publication as follows:

SpatialData: an open and universal data framework for spatial omics

Luca Marconato, Giovanni Palla, Kevin A. Yamauchi, Isaac Virshup, Elyas Heidari, Tim Treis, Marcella Toth, Rahul Shrestha, Harald Vöhringer, Wolfgang Huber, Moritz Gerstung, Josh Moore, Fabian J. Theis, Oliver Stegle

bioRxiv 2023.05.05.539647; doi: https://doi.org/10.1101/2023.05.05.539647