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mpes

Distributed data processing routines for multidimensional photoemission spectroscopy (MPES)

https://github.com/mpes-kit/mpes

Science Score: 33.0%

This score indicates how likely this project is to be science-related based on various indicators:

  • ○
    CITATION.cff file
  • ○
    codemeta.json file
  • ○
    .zenodo.json file
  • ✓
    DOI references
    Found 6 DOI reference(s) in README
  • ✓
    Academic publication links
    Links to: nature.com
  • ✓
    Committers with academic emails
    3 of 9 committers (33.3%) from academic institutions
  • ○
    Institutional organization owner
  • ○
    JOSS paper metadata
  • ○
    Scientific vocabulary similarity
    Low similarity (13.6%) to scientific vocabulary

Keywords

arpes condensed-matter-physics dask distortion-correction distributed-processing electron-spectroscopy fitting instrument-calibration lineshape materials-science mpes pes photoemission physics python spectroscopy visualization
Last synced: 6 months ago · JSON representation

Repository

Distributed data processing routines for multidimensional photoemission spectroscopy (MPES)

Basic Info
Statistics
  • Stars: 31
  • Watchers: 11
  • Forks: 6
  • Open Issues: 0
  • Releases: 0
Topics
arpes condensed-matter-physics dask distortion-correction distributed-processing electron-spectroscopy fitting instrument-calibration lineshape materials-science mpes pes photoemission physics python spectroscopy visualization
Created almost 9 years ago · Last pushed about 3 years ago
Metadata Files
Readme License

README.md

mpes

Build Status License Downloads

Distributed data processing routines for multidimensional photoemission spectroscopy (MPES), an upgrade of the angle-resolved photoemission spectroscopy (ARPES) to achieve parallel data acquisition on multiple parameters by the use of a time-of-flight tube and a multichannel delay-line detector.

Banner

In a photoemission process, an extreme UV or X-ray photon liberates an electron from the confines of the electronic potential within the material. ARPES directly measures the electronic energy and momentum parallel to the surface of the sample under study to infer the electronic states of the material. For a tutorial review on ARPES and its applications in physics and material science, see here. The data structure of ARPES is a stack of 2D images measured at different sample geometries, which are used to reconstruct the full static 3D band structure of the material.

The MPES instrument enables sampling of the multidimensional parameter space associated with the electronic band structure at an elevated speed. At the minimum, it measures the two parallel momenta and the energy of photoelectrons simultaneously. The measurement procedure can be extended with recording of varying external parameters such as the temperature, photon polarization, dynamical time delay as in a time-resolved ARPES (trARPES) experiments using a ultrafast laser system (~ fs resolution), etc. These different flavors of momentum-resolved photoemission experiment together yield a complete understanding of the electronic properties of materials under equilibrium and nonequilibrium conditions for realistic design and simulation of electronic devices.

Installation

  1. Install from scratch

     pip install git+https://github.com/mpes-kit/mpes.git

  2. Upgrade or overwrite an existing installation

     pip install --upgrade git+https://github.com/mpes-kit/mpes.git

  3. PyPI installation

     pip install mpes

  4. Install a specific version

     # version 1.0.9 from PyPI
pip install mpes==1.0.9

# version 0.9.8 from GitHub
pip install --upgrade git+https://github.com/mpes-kit/mpes.git@0.9.8

Documentation and tutorials

Documentation on the usage is posted here and examples are provided in Jupyter notebooks.

List of current tutorials are viewable using nbviewer via the links

The size of the single-event datasets used in the tutorial notebooks are in the GB to TB range each, which reflect the actual examperimental setting and the light source configuration (see here for technical details). Example datasets are made available publicly in a Zenodo repository. Please always use the latest version of the datasets.

Reference

If you want to refer the software in your work, please cite the following paper.

R. P. Xian, Y. Acremann, S. Y. Agustsson, M. Dendzik, K. Bühlmann, D. Curcio, D. Kutnyakhov, F. Pressacco, M. Heber, S. Dong, T. Pincelli, J. Demsar, W. Wurth, P. Hofmann, M.Wolf, M. Scheidgen, L. Rettig, R. Ernstorfer, An open-source, end-to-end workflow for multidimensional photoemission spectroscopy, Sci. Data 7, 442 (2020).

Specifically, for the symmetry distortion correction, please cite

R. P. Xian, L. Rettig, R. Ernstorfer, Symmetry-guided nonrigid registration: The case for distortion correction in multidimensional photoemission spectroscopy, Ultramicroscopy 202, 133 (2019).

Owner

  • Name: mpes-kit
  • Login: mpes-kit
  • Kind: organization
  • Location: Germany

Codebase for materials informatics in multidimensional) photoemission spectroscopy (https://gitter.im/mpes_tools/community)

GitHub Events

Total
  • Watch event: 2
Last Year
  • Watch event: 2

Committers

Last synced: about 2 years ago

All Time
  • Total Commits: 513
  • Total Committers: 9
  • Avg Commits per committer: 57.0
  • Development Distribution Score (DDS): 0.179
Past Year
  • Commits: 15
  • Committers: 2
  • Avg Commits per committer: 7.5
  • Development Distribution Score (DDS): 0.467
Top Committers
Name Email Commits
RealPolitiX x****k@g****m 421
Laurenz Rettig l****g@w****e 32
Arora0 a****3@g****m 23
Laurenz Rettig r****g@f****e 19
Rui Patrick Xian x****n@f****e 12
JMaklar j****r@w****e 2
Laurenz Rettig 5****l 2
VincentStimper v****r@g****m 1
Laurenz Rettig r****g@p****e 1
Committer Domains (Top 20 + Academic)
fhi-berlin.mpg.de: 2 pcr840.gnz.mpg.de: 1

Issues and Pull Requests

Last synced: 7 months ago

All Time
  • Total issues: 0
  • Total pull requests: 6
  • Average time to close issues: N/A
  • Average time to close pull requests: about 1 month
  • Total issue authors: 0
  • Total pull request authors: 2
  • Average comments per issue: 0
  • Average comments per pull request: 0.0
  • Merged pull requests: 5
  • Bot issues: 0
  • Bot pull requests: 0
Past Year
  • Issues: 0
  • Pull requests: 0
  • Average time to close issues: N/A
  • Average time to close pull requests: N/A
  • Issue authors: 0
  • Pull request authors: 0
  • Average comments per issue: 0
  • Average comments per pull request: 0
  • Merged pull requests: 0
  • Bot issues: 0
  • Bot pull requests: 0
View more stats
Top Authors
Issue Authors
Pull Request Authors
  • rettigl (5)
  • Arora0 (1)
Top Labels
Issue Labels
Pull Request Labels

Packages

  • Total packages: 1
  • Total downloads:
    • pypi 17 last-month
  • Total dependent packages: 0
  • Total dependent repositories: 1
  • Total versions: 4
  • Total maintainers: 2
pypi.org: mpes

Distributed data processing routines for multidimensional photoemission spectroscopy (MPES)

  • Versions: 4
  • Dependent Packages: 0
  • Dependent Repositories: 1
  • Downloads: 17 Last month
Rankings
Dependent packages count: 10.1%
Stargazers count: 12.1%
Forks count: 13.3%
Average: 15.7%
Downloads: 21.3%
Dependent repos count: 21.6%
Maintainers (2)
realpolitix rettigl
Last synced: 6 months ago

Dependencies

requirements.txt pypi
  • astropy *
  • bokeh *
  • coverage *
  • dask *
  • deepdish *
  • fastdtw *
  • fastparquet *
  • funcy *
  • h5py >=2.9.0
  • igor *
  • imageio *
  • lmfit *
  • matplotlib *
  • natsort *
  • nose *
  • numba *
  • numpy *
  • opencv-python *
  • pandas *
  • photutils *
  • scikit-image *
  • scipy *
  • silx *
  • sphinx *
  • symmetrize *
  • threadpoolctl *
  • tqdm *
  • xarray *
setup.py pypi
  • x.strip *