Overview

You can install Nx5d either from PyPI, from its Git repository, or use our pre-packaged Jupyter Server container image.

To get an impression, you can review quick in-memory examples to find out how Nx5d "feels like". These will work with purely artificial data, no files required. They're intended only as a low-effort way to get acquaninted.

To actually work with real-life data that your experimental endstation has produced, understanding Nx5d's API elements is crucial.

Working with spice is one of the central discipline in Nx5d -- and therefore deserves its own section in the User's Guide.

Yes, we are eating our own dog food: we're using Nx5d in our beamlines and labs. We have prepared some smoothed-out, but otherwise full-sized exmples for you to check out.

Nx5d supports a small number of beamlines out-of-the-box. These are typically the facilities that we're dealing with on a regular basis -- our own, but also 3rd-party facilities we frequent often.

Finally, you're eventually going to want to access your own data and do your own processing. This section will help you navigate the necessary steps and API subclassing.