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Table of Contents

Speakers:


Carter Francis (University of Wisconsin-Madison)
Jacob Madsen (University of Vienna)
Kate MacArthur (Oxford Instruments)
Magnus Nord (NTNU, Norway)
Francisco de la Peña (University of Lille)
Eric Prestat (UKAEA)
Stephanie Ribet (LBL)
Thomas Slater (Cardiff University)

Joining also as panellists:

Colin Ophus (LBL)
Tara Mishra (LBL)
Steven Zeltmann (Cornell University)
Ben Savitzky (LBL - hbar instruments)

Diamond Light Source (ePSIC) organising team:

Mohsen Danaie - mohsen.danaie@diamond.ac.uk

David Hopkinson and Chris Allen

Agenda

View file
nameePSIC_hyperspy_workshop_2024.pdf



PDF
nameePSIC_hyperspy_workshop_2024.pdf

BYOD Session Organiser

If you would like to have a more focussed discussion with one of the Speakers about your own data please express interest via this link:

BYOD_Session.docx

Add to the table your name, a brief description of the type of data analysis and relevant packages, plus links to any existing code / example datasets, if possible. These will then be assigned to Speakers and we will have break-out rooms on Friday’s BYOD session.

Workshop Software Platform

We will be running the workshop on your local python installations [Instructions below]. It is crucial that you check your installation ahead of the week of workshop and if you have any issues to get in touch with us.

Installation guide- Using the bundle (Preferred route!)

You can use this bundle installer to get all the packages needed for the workshop all at once:

https://hyperspy.org/hyperspy-bundle/

For testing the installation, write click on a location on your machine and select Jupyter lab here and open a Python 3 notebook and try importing the packages as below in testing section.

Google Colab

For some of the demos - and as a back up in case your local installation develops an issue - we may run notebooks on Google Colab during the workshop.
Please make sure you have an active Google account for this.
We will share the link to those notebooks during the workshop.

Installation guide- Using Miniforge / Mamba (Potentially not as stable as above)

These instructions are provided to enable you to have your personalised hyperspy (and other packages covered in this workshop) installed on you local machine. Having the installation done through this route allows you to have these packages updated independent of each other, in case there is a new release in future.

Please follow the steps below for the installation:

  • Install Python from Mambaforge

  • Open a Miniforge terminal. This should look like a regular terminal but with the prompt set to (base)

  • Create a new environment by running:

    Code Block
    conda create --name hyperspy_env python=3.10
  • Activate the above environment by:

    Code Block
    WINDOWS: activate hyperspy_env
    LINUX, macOS: source activate hyperspy_env

    Now your prompt should read: (hyperspy_env)

  • Install the packages by running the following commands:

    Code Block
    mamba install hyperspy
    mamba install abtem nglview
    mamba install pyxem
    mamba install atomap
    mamba install particlespy
    mamba install jupyterlab notebook ipympl
    mamba install py4dstem pymatgen
Info

Please note that you need to ensure your local installation works ahead of the workshop! Please attend the troubleshooting session on Friday 19th if in doubt!

Testing your installation

To test your installation, from the same prompt, run:

Code Block
jupyter lab

This would open a Jupyter lab launcher in your web browser (You can choose the default browser here). If you have installed using the Bundle you can right click and select Jupyter Lab here! Under Notebook select Python 3 (ipykernel) button to open a new notebook. Copy this code to the first cell and run (press shift + enter). If the installation is correct you should not get any error messages (Note that you may get a Warning about pyOpenCl that can be ignored.).

Code Block
languagepy
%matplotlib qt5
import hyperspy.api as hs
import pyxem as pxm
import atomap.api as am
import particlespy.api as ps
import py4DSTEM

Workshop Notebooks and Presentations

We will gradually make the Jupyter notebooks, example datasets and presentations available here to download. In the meantime, we will be updating this github repository:

https://github.com/ePSIC-DLS/Hyperspy_Workshop_2024

Link to the ZIP file

Slides shared from Speakers