What?#

• The pyTEMlib package:

  • is a part of the pycroscopy ecosystem based on python

  • enables quantitative analysis through model based approach

  • provides routines for the analysis of diffraction, image and spectroscopic datasets

  • handles one, two, three, and four dimensional datasets

  • works in jupyter notebooks and in python programs.

  • provides dialog windows for metadata and analysis input in jupyter notebooks and in python programs.

• The pyTEMlib covers:

  • Diffraction: Single and poly crystalline diffraction data and analysis in parallel and convergent illumination

  • Imaging: Image analysis, atom detection and image stack registration.

  • EELS: It provides a framework for quantification of EELS spectra and spectrum images.

• Just as scipy uses numpy underneath, scientific packages like pyTEMlib use

  • sidpy format for dataset representation and

  • pyNSID for all file-handling.

• Dialogs are based on ipython widgets

• The packages sidpy and pyNSID use popular packages such as numpy, h5py, dask, matplotlib, etc. for most of the storage, computation, and visualization.

Why?#

pyTEMlib originates in the need for teaching and the development of new techniques for TEM/STEM data analysis. Please, see my lecture note(-books) for information on the background of analysis.

1. Growing data sizes

• Cannot use desktop computers for analysis

• Need: High performance computing, storage resources and compatible, scalable file structures

2. Increasing data complexity

• Sophisticated imaging and spectroscopy modes resulting in 5,6,7… dimensional data

• Need: Robust software and generalized data formatting

3. Multiple file formats

• Different formats from each instrument. Proprietary in most cases

• Incompatible for correlation

• Need: Open, instrument-independent data format

4. Expensive analysis software

• Software supplied with instruments often insufficient / incapable of custom analysis routines

• Commercial software (Eg: Matlab, Origin..) are often prohibitively expensive.

• Need: Free, powerful, open source, user-friendly software

5. Closed science

• Analysis software and data not shared

• No guarantees of reproducibility or traceability

• Need: open source data structures, file formats, centralized code and data repositories

Who?#

• We envision pyTEMlib to be a convenient package that facilitates all scientists to analyse data and develop new methods of anlysis, without being burdened with basic code functionality.

• This project is being led by staff members at Oak Ridge National Laboratory (ORNL), and professors at University of Tennessee, Knoxville

• We invite anyone interested to join our team to build better, free software for the scientific community

• Please visit our credits and acknowledgements_ page for more information.

• If you are interested in integrating our in your existing package, please get in touch with us.

Content#