This repository contains Jupyter Notebooks to demo and learn how to process multi-dimensional data with HyperSpy. For learning purposes, we recommend to use them alongside the HyperSpy User Guide.
The root folder contains notebooks concerning general HyperSpy features while the subfolders contain notebooks for specific signals and other more specialized analyses.
Follow this link or click the "launch binder" banner above to run the the demos on mybinder.org. The demos will run remotely, and one can experiment with HyperSpy in a Jupyter notebook with no need to install or configure any software locally.
Note: depending on the remote server load, the interactive binder demo may take up to several minutes to load. For a quicker (but non-interactive) visualization, see below.
Follow this link or click on the "render nbviewer" banner above to display the demos with the Jupyter Notebook viewer. nbviewer will allow you to view the notebooks online, but you will not be able to change them or evaluate any code, like is possible with the binder.
To run the demo notebooks locally, clone or download the demos repository to your local machine, install HyperSpy and Jupyter Lab or Jupyter Notebook and use either of Jupyter tools to run the notebooks.
To test the demos, install nbval and py.test and run
$ py.testTo help visualize differences/errors, install nbdime as well, and run the test with
$ py.test --nbdimeTo contribute new demos or improvements to the current ones fork the demos repository and send us a pull request. See the HyperSpy Developer Guide for more details on how to contribute to HyperSpy.
For issues and discussions fill a new issue in the demos github repository or discuss it in HyperSpy's gitter chat.