Metadata-Version: 2.1
Name: stemdiff
Version: 4.2.10
Summary: Convert 4D-STEM data to a single powder diffraction pattern.
Home-page: https://github.com/mirekslouf/stemdiff/
Author: Mirek Slouf
Author-email: mirek.slouf@gmail.com
License: MIT
Project-URL: Documentation, https://mirekslouf.github.io/stemdiff/
Platform: UNKNOWN
Classifier: Programming Language :: Python :: 3
Classifier: License :: OSI Approved :: MIT License
Classifier: Operating System :: OS Independent
Requires-Python: >=3.6
Description-Content-Type: text/markdown
License-File: LICENCE

STEMDIFF :: Simple processing of 4D-STEM data
---------------------------------------------

* The **STEMDIFF package** converts... <br>
  ... a 4D-STEM dataset from a SEM microscope (huge and complex) <br>
  ... 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, <br>
  which was described (together with the package) in open-access publications:
	1. *Nanomaterials* 11 (2021) 962.
	   [https://doi.org/10.3390/nano11040962](https://doi.org/10.3390/nano11040962)
	2. *Materials* 14 (2021) 7550.
       [https://doi.org/10.3390/ma14247550](https://doi.org/10.3390/ma14247550)
* If you use STEMDIFF in your research, **please cite** the 2nd publication.

Principle
---------

<img src="https://raw.githubusercontent.com/mirekslouf/stemdiff/main/docs/images/principle2.png" alt="STEMDIFF principle" width="500"/>

Documentation, help and examples
--------------------------------

More detailed help, demo and source code including documentation are in
[GitHub](https://mirekslouf.github.io/stemdiff).

## 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
	  &rArr; better resolution 
* Version 4.2 = like v4.0 + a few important improvements, such as:
	* sum just the central region with the strongest diffractions
	  &rArr; 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*

