Convert 4D-STEM data to a single powder diffraction pattern.
Project description
STEMDIFF :: Simple processing of 4D-STEM data
- The STEMDIFF package converts...
... a 4D-STEM dataset from a SEM microscope (huge and complex)
... to a single powder diffraction pattern (simple and easy to work with). - The STEMDIFF package is a key part of our 4D-STEM/PNBD method,
which was described (together with the package) in open-access publications:- Nanomaterials 11 (2021) 962. https://doi.org/10.3390/nano11040962
- Materials 14 (2021) 7550. https://doi.org/10.3390/ma14247550
- If you use STEMDIFF package, please cite the 2nd publication (or both :-).
Principle
Quick start
- Install stemdiff:
pip install stemdiff
- Download a demo dataset and follow the instructions in readme file.
- Basically, you just run the master script in Spyder like in this printscreen.
Documentation, help and examples
More detailed help, demo and source code including documentation are in GitHub.
Versions of STEMDIFF
- Version 1.0 = Matlab: just simple summation of 4D-dataset
- Version 2.0 = like v1.0 + post-processing in Jupyter
- Version 3.0 = Python scripts: summation + S-filtering
- Version 4.0 = Python package: summation + S-filtering + deconvolution
- summation = summation of all 2D-diffractograms
- S-filtering = sum only diffractograms with strong diffractions = high S
- deconvolution = reduce the effect of primary beam spread ⇒ better resolution
- Version 4.2 = like v4.0 + a few important improvements, such as:
- sum just the central region with the strongest diffractions ⇒ higher speed
- 3 centering types: (0) geometry, (1) weight of 1st, (2) individual weights
- better definition of summation and centering parameters
- better documentation strings + demo data + improved master script
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