Metadata-Version: 2.4
Name: runnerase-workflows
Version: 0.3.1
Summary: Collection of routines for applying the Ruhr University Neural Network energy representation (RuNNer).
Author: Jasper Krähe, Moritz R. Schäfer, Alexander L. M. Knoll
Author-email: Moritz R. Schäfer <moritz.schaefer-f91@rub.de>, Alexander L. M. Knoll <alexander.knoll@rub.de>
License-Expression: GPL-3.0-or-later
License-File: LICENSE
Classifier: Topic :: Scientific/Engineering :: Chemistry
Classifier: Intended Audience :: Science/Research
Classifier: Development Status :: 4 - Beta
Classifier: Operating System :: POSIX
Classifier: Operating System :: MacOS
Classifier: Programming Language :: Python :: 3
Requires-Dist: runnerase-core>=0.11.1
Requires-Dist: runnerase-prediction
Requires-Dist: ase>=3.29.0
Requires-Dist: ovito>=3.14.1 ; extra == 'ovito'
Requires-Python: >=3.10
Project-URL: Bugs, https://gitlab.com/runner-suite/runnerase-2.0/issues
Project-URL: Documentation, https://runner.theochem2.rub.de/runnerase-docs/latest/
Project-URL: Source, https://gitlab.com/runner-suite/runnerase-2.0
Provides-Extra: ovito
Description-Content-Type: text/markdown

# runnerase-workflows

High-level workflows and command-line entry points built on top of the other
`runnerase` packages — for users who want a ready-made procedure rather than
assembling one from `runnerase-core`/`runnerase-prediction`/`runnerase-training`
primitives.

## Provides

- `ActiveLearning`, `DisagreementFunctions`, `Settings`: active-learning loop
  for iteratively improving a potential based on prediction disagreement.
- RuNNer-LAMMPS interface helpers (`setup_runner_context`, `run_md`,
  `execute_runner_simulation`, `format_cmd_pair_style`, ...) for running MD
  simulations with RuNNer potentials in LAMMPS.
- `prepare_prediction_from_trained_potential`: set up a prediction run from an
  already-trained potential.
- `open_ovito`: visualize structures and trajectories with
  [OVITO](https://www.ovito.org/) (requires the optional `ovito` extra).

## Command-line tools

This package also installs several CLI entry points:

- `active-learning`
- `dataset-reduction`
- `prepare_prediction_from_trained_potential`
- `enforce-total-charge`
- `open_ovito`
- `prune_feature_maps`

## Installation

```bash
uv pip install runnerase-workflows
# with OVITO visualization support:
uv pip install "runnerase-workflows[ovito]"
```

## Documentation

Tutorials on active learning, structure visualization, and LAMMPS-based
simulations: https://runner.theochem2.rub.de/runnerase-docs/latest/

## License

GPL-3.0-or-later. Part of the [runnerase](https://gitlab.com/runner-suite/runnerase-2.0) project.
