William Rigaut1, 2
1 Institut Néel, Centre National de la Recherche Scientifique, 38000 Grenoble, France
2 Université Grenoble Alpes, 38000 Grenoble, France
Extract ESRF Data is coded in Python code with a Jupyter Notebook provided by Institut Néel. Package used to vizualise and extract data from .h5 high-throughtput XRD data at BM02 (ESRF). You can contact me for any issues at [email protected]
Available on Windows, MacOS, and Linux. Requires Python 3.8+.
You will need a recent version of python (3.8 or higher) in order to run the python code Installing Jupyter Notebook is also highly recommanded since a detail tutorial is provided.
Then you will need to create a new python environnement to import the required libraries,
you can do that with the following command in a terminal:
python3 -m venv .venv
and then:
source .venv/bin/activate
Finally to import all the libraries:
pip install -r requirements.txt
Once the installation is done, you can open the Notebook Extract_ESRF-Data.ipynb
Since datafile sizes are huge for ESRF (bm02), no example dataset is provided, contact me if you need an example.
If you require support, have questions, want to report a bug, or want to suggest an improvement, please contact me at [email protected]
MIT License
This work was financed by the French National Research Agency through the « Datamag » project (ANR-22-CE91-0008) and the European Union through the MaMMoS project (Grant number 101135546, HORIZON-CL4-2023-DIGITAL-EMERGING-01)