DScribe

DScribe is a Python package for transforming atomic structures into fixed-size numerical fingerprints. These fingerprints are often called “descriptors” and they can be used in various tasks, including machine learning, visualization, similarity analysis, etc. To get started you can check the basic tutorial.

Capabilities at a Glance

DScribe currently includes the following descriptors:

Descriptor name	Features	Derivatives
Coulomb matrix	✓	✓
Sine matrix	✓	✓
Ewald sum matrix	✓	✓
Atom-centered Symmetry Functions (ACSF)	✓	✓
Smooth Overlap of Atomic Positions (SOAP)	✓	✓
Many-body Tensor Representation (MBTR)	✓	✓
Local Many-body Tensor Representation (LMBTR)	✓	✓
Valle-Oganov descriptor	✓	✓

Check the tutorials for more information.

Go Deeper

You can find more details in the following articles:

• DScribe: Library of descriptors for machine learning in materials science

• Updates to the DScribe Library: New Descriptors and Derivatives

Documentation for the source code can be found here. The full source code with examples and tests can be explored at github.