Code supporting Unsupervised machine learning applied to scanning precession electron diffraction data
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Authors
Martineau, B
Publication Date
2022-01-18Type
Software
Metadata
Show full item recordCitation
Martineau, B. (2022). Code supporting Unsupervised machine learning applied to scanning precession electron diffraction data [Software]. https://doi.org/10.17863/CAM.26444
Description
The python code supplied here enables the reproduction of the figures presented in the publication as as set of executable python files. Also supplied is a complete static copy of the software used for data clustering, which was written for the publication.
Format
A README is included detailing dependencies. The most important include numpy (http://www.numpy.org/), matplotlib (https://matplotlib.org/), scikit-image (https://scikit-image.org/), HyperSpy (http://hyperspy.org/), and pyXem (http://pyxem.github.io/pyxem/),
Keywords
python, linear decomposition, multivariate analysis, clustering
Relationships
Related Item: https://doi.org/10.17863/CAM.26432
Publication Reference: https://doi.org/10.1186/s40679-019-0063-3
Sponsorship
The Royal Society (uf130286)
European Research Council (291522)
Identifiers
This record's DOI: https://doi.org/10.17863/CAM.26444
Rights
GNU General Public License version 3 (GPLv3)
Licence URL: https://www.gnu.org/licenses/gpl-3.0.html
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