Virtual Infrastructure for Scientific Analysis (VISA) Workshop
We invite you to view our workshop – hosted jointly by ExPaNDS and PaNOSC!
VISA provides remote data analysis services giving access to experimental data, analysis software, compute infrastructure and expert-user support (IT and Scientific). The online half-day Workshop is open to all external...
Keywords: VISA, expands, PaNOSC, remote data analysis services
Resource type: slides
Virtual Infrastructure for Scientific Analysis (VISA) Workshop
https://expands.eu/presentations/#VISAWorkshop
https://pan-training.eu/materials/virtual-infrastructure-for-scientific-analysis-visa-workshop
We invite you to view our workshop – hosted jointly by ExPaNDS and PaNOSC!
VISA provides remote data analysis services giving access to experimental data, analysis software, compute infrastructure and expert-user support (IT and Scientific). The online half-day Workshop is open to all external stakeholders (especially scientists and IT staff but not limited to). We aim to demonstrate to beamline scientists the possibilities offered by VISA for data analysis and gathering IT staff around the table to discuss about the development and further deployment of the platform.
VISA has been developed at a critical time (during the COVID-19 crisis) to answer data analysis needs and allowing remote instrument control. It provides simplified access for scientists to data analysis tools, offers remote support to users from experts and allows them to remotely control their experiments with the assistance of on-site instrument scientists. VISA allows a user to use the Remote Desktop as if they were sitting in front a data treatment workstation at the host institute and embeds JupyterLab directly accessible from the same platform interface. Initially developed at the Institut Laue-Langevin (ILL) in Grenoble, France and further deployed in the context of PaNOSC, VISA enables the PaN research infrastructures (PaN RIs) to work together on further scientific collaborations to solve 21st century challenges.
The first session of the workshop showcases the implementation of VISA at the PaN RIs through ExPaNDS and PaNOSC partner’ demos and illustrate its use for scientific users and others.
The second session in the afternoon focuses on presentations on VISA development and deployment (on OpenStack and other infrastructures), paving the way for a roundtable discussion on the future of VISA: sustainability and future collaborations.
Video recording (direct link to vimeo) will be available soon.
VISA, expands, PaNOSC, remote data analysis services
JupyLabBook
A Jupyter Notebook used as an interactive lab book on the beamline SIRIUS (SOLEIL Synchrotron).
Keywords: labbook, jupyter notebook, SIRIUS beamline
Resource type: git, jupyter notebook
JupyLabBook
https://gitlab.com/soleil-data-treatment/soleil-beamlines/soleil-beamline-sirius/JupyLabBook
https://pan-training.eu/materials/jupylabbook
A Jupyter Notebook used as an interactive lab book on the beamline SIRIUS (SOLEIL Synchrotron).
labbook, jupyter notebook, SIRIUS beamline
JupyFluo
JupyFluo is a Jupyter Notebook to analyze X-Ray Fluorescence (XRF) experiments on the beamline SIRIUS at the synchrotron SOLEIL.
The notebook should be first set up by an Expert following the instructions in the "Expert" section. User can then follow the guidelines in the "User" section to start...
Scientific topics: x-ray fluorescence
Keywords: X-ray fluorescence, jupyter notebook, SIRIUS beamline
Resource type: git, jupyter notebook
JupyFluo
https://gitlab.com/soleil-data-treatment/soleil-beamlines/soleil-beamline-sirius/JupyFluo
https://pan-training.eu/materials/jupyfluo
JupyFluo is a Jupyter Notebook to analyze X-Ray Fluorescence (XRF) experiments on the beamline SIRIUS at the synchrotron SOLEIL.
The notebook should be first set up by an Expert following the instructions in the "Expert" section. User can then follow the guidelines in the "User" section to start using the notebook. Please note that the notebook is currently in development. As such, be skeptical about any unexpected results. Any feedback on the notebook or the code is welcome.
x-ray fluorescence
X-ray fluorescence, jupyter notebook, SIRIUS beamline
How to read/edit a nexus file using h5py
A tutorial notebook on how to read and edit a nexus file using h5py.
Keywords: NeXus
Resource type: git, jupyter notebook
How to read/edit a nexus file using h5py
https://gitlab.com/soleil-data-treatment/soleil-beamlines/soleil-beamline-sirius/tutorials/tutorial_edit_nexus/-/blob/main/howto_edit_nexus.ipynb
https://pan-training.eu/materials/how-to-read-edit-a-nexus-file-using-h5py
A tutorial notebook on how to read and edit a nexus file using h5py.
NeXus
PyMca tutorial
A manual and a tutorial notebook on how to use PyMca to fit XRF data obtained on the beamline SIRIUS.
To use the notebook first uncompress files.zip and save.zip
Scientific topics: x-ray fluorescence
Keywords: PyMca, XRF
Resource type: pdf, git
PyMca tutorial
https://gitlab.com/soleil-data-treatment/soleil-beamlines/soleil-beamline-sirius/tutorials/tutorial_pymca/-/blob/main/PyMca_User_Manual.pdf
https://pan-training.eu/materials/pymca-tutorial
A manual and a tutorial notebook on how to use PyMca to fit XRF data obtained on the beamline SIRIUS.
To use the notebook first uncompress files.zip and save.zip
x-ray fluorescence
PyMca, XRF
GenX tutorial
howto_batch
The notebook batch_genx.ipynb details the different steps on how to use GenX with command lines.
The aim is to batch fits for XRR without the GUI. To do so we edit the .hgx files, which are just hdf5 files.
The script batch_genx.py is a condensed script without all the details...
Scientific topics: x-ray reflectivity
Keywords: GenX, jupyter notebook, XRR
Resource type: git, jupyter notebook
GenX tutorial
https://gitlab.com/soleil-data-treatment/soleil-beamlines/soleil-beamline-sirius/tutorials/tutorial_genx
https://pan-training.eu/materials/genx-tutorial
howto_batch
The notebook batch_genx.ipynb details the different steps on how to use GenX with command lines.
The aim is to batch fits for XRR without the GUI. To do so we edit the .hgx files, which are just hdf5 files.
The script batch_genx.py is a condensed script without all the details from the notebook.
howto_parameters
Explains what are the different parameters in the GUI.
x-ray reflectivity
GenX, jupyter notebook, XRR