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Releases: SSAGESLabs/PySAGES

v0.4.0

22 Sep 04:23
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What's Changed

  • Enable custom bias classes for umbrella integration (#177)
  • Add a take_snapshot method to backend Samplers (#190)
  • Allow multi component CVs (#192
  • Flexibility in choosing which orientation the acyclindricity is calcualted (#194)
  • Add support for HOOMD 3 (#200)
  • Support jax-md as backend (#199)
  • Add restraints in metad.py for grids (#217)
  • Phase angle CV (#227)
  • Add GeM CV (#242)
  • Interface for restarts (#254)
  • LAMMPS backend (#274)
  • Revamp documentation (#281)

And many more bug fixes and improvements!

Full Changelog: v0.3.0...v0.4.0

v0.3.0

12 Aug 13:57
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This new release includes usability enhancements, bugfixes and improvements over these previously existing methods:

  • ABF
  • ANN
  • FUNN
  • Harmonic biasing
  • Umbrella integration
  • Metadynamics
  • Forward Flux Sampling

And these new sampling methods:

  • CFF
  • SpectralABF
  • Well-tempered Metadynamics

ASE is now a supported backend which brings integration with many MD and QM/MM code bases including LAMMPS, CP2K, Quantum Espresso, VASP, among many others.

Other important key additions, include:

  • A new interface to allow running enhanced sampling simulations on multiple GPUs. For instance, different windows in UmbrellaIntegration can be sampled in parallel on different GPUs, the same is the case for multiple replicas for most sampling methods in PySAGES.
  • Many example scripts and Google Colab notebooks have been added as introductory resources to PySAGES.
  • A user interface to easily analyze the results of a sampling run, enabling users to easily obtain Free Energy profiles.

v0.2.0

03 May 22:25
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This new release includes usability enhancements, bugfixes and improvements over these previously existing methods:

  • ABF
  • ANN
  • FUNN

And these new sampling methods:

  • Harmonic biasing
  • Umbrella integration
  • Metadynamics
  • Forward Flux Sampling

In addition, many example scripts and Google Colab notebooks have been added as introductory resources to PySAGES.

v0.1.0

24 May 10:25
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First public release