The Simmate Toolkit¶
Many classes in this module are highly experimental. We strongly recommend using pymatgen and ase for toolkit functionality until Simmate hits v1.0.0. For developers, this means many of the classes are undocumented and untested. This accelerates our testing without spending time on reformating tests and rewriting guides. We include this experimental code on our main branch because higher-level functions (e.g. workflows) rely on some of these features. Higher-level functions are well tested and documented, however, to account for ongoing low-level changes.
The toolkit module is meant to be an extension of pymatgen and ase. It includes low-level classes and functions, such as the
Structure class and its associated methods. The toolkit module is written entirely in python and does not use third-party DFT programs. See the
simmate.apps module for those.
The most commonly used classes from this toolkit are the
Composition classes. These classes can be imported with...
from simmate.toolkit import Structure, Composition
Outline of submodules¶
base_data_types= defines fundamental classes for materials science, including
Compositionclasses. For convenience, these classes can be imported directly from
simmate.toolkit, as noted above.
creators= creates structures, lattices, and periodic sites
featurizers= converts properties into numerical descriptors for machine-learning
structure_prediction= predicts crystal structures using an evolutionary algorithm
symmetry= contains tools and metadata for symmetry analyses, such as spacegroups and wyckoff sites
transformations= methods to transform or "mutate"
validators= methods to check if a structure meets specific criteria