leem-analysis
Quantitative Data Analysis for spectroscopic LEEM
Science Score: 67.0%
This score indicates how likely this project is to be science-related based on various indicators:
-
✓CITATION.cff file
Found CITATION.cff file -
✓codemeta.json file
Found codemeta.json file -
✓.zenodo.json file
Found .zenodo.json file -
✓DOI references
Found 8 DOI reference(s) in README -
✓Academic publication links
Links to: zenodo.org -
○Academic email domains
-
○Institutional organization owner
-
○JOSS paper metadata
-
○Scientific vocabulary similarity
Low similarity (14.2%) to scientific vocabulary
Keywords
Repository
Quantitative Data Analysis for spectroscopic LEEM
Basic Info
- Host: GitHub
- Owner: TAdeJong
- License: mit
- Language: Jupyter Notebook
- Default Branch: master
- Size: 37.9 MB
Statistics
- Stars: 17
- Watchers: 2
- Forks: 3
- Open Issues: 1
- Releases: 3
Topics
Metadata Files
README.md
Quantitative Data Analysis for spectroscopic LEEM.
This repository contains the code to showcase the methods and algorithms presented in the paper T.A. de Jong et al., Quantitative analysis of spectroscopic Low Energy Electron Microscopy data: High-dynamic range imaging, drift correction and cluster analysis, Ultramicroscopy, Volume 213, 2020, DOI: 10.1016/j.ultramic.2019.112913.
In addition it contains the code to stitch LEEM images using a similar algorithm.
It is organized as a set of notebooks, reproducing the different techniques and algorithms as presented in the paper, as well as the Figures. The notebooks are in some cases supported by a separate Python file with library functions. For human readable diffs, each notebook is shadowed by a Python file using jupytext.
Implementation
The code makes extensive use of dask for lazy and parallel computation, the N-D labeled arrays and datasets library xarray, as well as the usual components of the scipy stack such as numpy, matplotlib and skimage.
Getting started
- Git clone or download this repository.
pip install .Consider the-eflag for an editable install.- (Alternatively) Create a Python environment with the necessary packages, either from requirements.txt or (for
condausers) from environment.yml. - Activate the environment and start a Jupyter notebook and have a look at the notebooks
Data
The data is available separately at http://doi.org/10.4121/uuid:7f672638-66f6-4ec3-a16c-34181cc45202 (via https://researchdata.4tu.nl/). The zeroth notebook facilitates easy download of all (or parts of) related data.
The data of 6 - Stitching is not yet available.
Acknowledgements
This work was financially supported by the Netherlands Organisation for Scientific Research (NWO/OCW) as part of the Frontiers of Nanoscience (NanoFront) program.
Owner
- Name: Tobias de Jong
- Login: TAdeJong
- Kind: user
- Location: Netherlands
- Company: SRON Netherlands Institute for Space Research
- Twitter: TobiasAdeJong
- Repositories: 17
- Profile: https://github.com/TAdeJong
Citation (CITATION.cff)
cff-version: 1.2.0
message: "If you find this software useful and use it in scientific work, please cite it as below."
authors:
- family-names: "de Jong"
affiliation: "Leiden Institute of Physics"
given-names: "Tobias A."
orcid: "https://orcid.org/0000-0002-5211-8081"
title: "TAdeJong/LEEM-analysis"
version: 0.2.0
doi: 10.5281/zenodo.3539538
license: MIT
date-released: 2021-08-19
repository-code: "https://github.com/TAdeJong/LEEM-analysis"
preferred-citation:
type: article
authors:
- family-names: "de Jong"
given-names: "Tobias A."
orcid: "https://orcid.org/0000-0002-5211-8081"
- family-names: "Kok"
given-names: "David N.L."
orcid: "https://orcid.org/0000-0002-5227-6880"
- family-names: "van der Torren"
given-names: "A.J.H."
- family-names: "Schopmans"
given-names: "H."
- family-names: "Tromp"
given-names: "R.M."
- family-names: "van der Molen"
given-names: "Sense Jan"
orcid: "https://orcid.org/0000-0003-3181-2055"
- family-names: "Jobst"
given-names: "Johannes"
orcid: "https://orcid.org/0000-0002-2422-1209"
doi: "10.1016/j.ultramic.2019.112913"
journal: "Ultramicroscopy"
month: 6
start: 112913 # First page number
title: "Quantitative analysis of spectroscopic low energy electron microscopy data: High-dynamic range imaging, drift correction and cluster analysis"
issue: 1
volume: 213
year: 2020
GitHub Events
Total
- Watch event: 1
Last Year
- Watch event: 1
Dependencies
- dask
- dask-ml
- distributed
- ipywidgets
- jupytext
- matplotlib
- netcdf4
- numba
- numpy
- scikit-image
- scikit-learn
- scipy
- xarray
- zarr
- dask *
- dask-ml *
- distributed *
- ipywidgets *
- jupytext *
- matplotlib *
- netcdf4 *
- numba *
- numpy *
- scikit-image *
- scikit-learn *
- scipy >=1.2
- xarray *
- zarr *