DScribe is a Python package (current version 2.1.2) designed for generating fixed-size numerical fingerprints, known as descriptors, from atomic structures. These descriptors are crucial for various applications in materials science, including machine learning, visualization, and similarity analysis. The library maintains an active development status with regular updates, including new descriptors and derivative functionalities. [1, 2, 5]
pip install dscribeVerified import paths — ran on the pinned version, not inferred.
This quickstart demonstrates how to initialize and use CoulombMatrix and SOAP descriptors for single and multiple atomic structures (represented by ASE Atoms objects). It also shows how to compute derivatives for a descriptor. Note the use of modern parameter names like `r_cut`, `n_max`, `l_max`, and the `compression` parameter for SOAP. [2, 3, 6]
Replace `positions` with `centers` when calling `.create()` or `.derivatives()` methods for local descriptors.
Adjust code expecting specific output shapes. Outputs are consistently flattened by default.
Update descriptor initialization to use the new parameter names (e.g., `r_cut` instead of `rcut`).
Replace `crossover=True` with `compression="crossover"` in SOAP descriptor initialization. If `crossover=False` was used, either omit `compression` (defaults to 'off') or explicitly set `compression='off'`.
Convert your atomic structures to `ase.Atoms` objects before passing them to DScribe descriptors.
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