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Package: python3-amp (0.6.1-1build6)

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python3-amp

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Atomistic Machine-learning Package (python 3)

Amp is an open-source package designed to easily bring machine-learning to atomistic calculations. This project is being developed at Brown University in the School of Engineering, primarily by Andrew Peterson and Alireza Khorshidi, and is released under the GNU General Public License. Amp allows for the modular representation of the potential energy surface, allowing the user to specify or create descriptor and regression methods.

Amp is designed to integrate closely with the Atomic Simulation Environment (ASE). As such, the interface is in pure python, although several compute-heavy parts of the underlying code also have fortran versions to accelerate the calculations. The close integration with ASE means that any calculator that works with ASE ─ including EMT, GPAW, DACAPO, VASP, NWChem, and Gaussian ─ can easily be used as the parent method.

This package provides the python 3 modules.

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Download python3-amp

Download for all available architectures
Architecture Package Size Installed Size Files
amd64 258.9 kB1498 kB [list of files]
arm64 257.0 kB1324 kB [list of files]
armhf 216.6 kB1146 kB [list of files]
ppc64el 284.1 kB1448 kB [list of files]