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NanoPyx is a library specialised in the analysis of light microscopy and super-resolution data. It is a successor to NanoJ, which is a Java library for the analysis of super-resolution microscopy data.
NanoPyx focuses on performance, by being built on top of an adaptive performance system - the Liquid Engine - that picks the fastest way of running any image analysis task for each user's computer. It implements methods for the bioimage analysis field, with a special emphasis on those developed by the Henriques Laboratory. It will be distributed as a Python Library and also as Codeless Jupyter Notebooks, that can be run locally or on Google Colab, and as a napari plugin.
Check the methods section of the wiki to learn about currently implemented methods.
Check out our YouTube playlist of NanoPyx video tutorials here!
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