The image viewing and analysis software napari has filled a gap in the programming language’s scientific ecosystem.
Josh Dorrington has become adept at viewing the jet streams. He plots fast-moving rivers of air at different atmospheric altitudes and positions the charts side by side. “You get pretty good at looking at all these cross-sections and working out what it implies,” says Dorrington, an atmospheric physicist at the University of Oxford, UK. But compared with computerized visualizations, this ‘manual’ method is slower and “it’s not as interactive”.
The team created the software in 2018 to fill a gap in the Python scientific ecosystem. Although Python is the lingua franca of scientific computing, it had no visualization tools that could handle-dimensional data sets. As a result, data analysis usually required a tedious back and forth between Python and other tools as researchers alternately manipulated their data and then visualized them to see what had happened.
Users can also extend napari using plug-ins: more than 100 are available on the napari hub . These include plug-ins for reading and writing files, microscope control and cell segmentation. Carsen Stringer, a computational neuroscientist at the Howard Hughes Medical Institute’s Janelia Research Campus near Ashburn, Virginia, created a cell-segmentation plug-in called CellPose, which makes the power of Python deep-learning algorithms available through a simple graphical interface.
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