zndraw 0.4.0a1

Display and Edit Molecular Structures and Trajectories in the Browser.

ZnDraw

Install via pip install zndraw. If you have pip install pywebview installed, ZnDraw will open in a dedicated window instead of your default browser.

CLI

You can use ZnDraw to view a file using the CLI zndraw traj.xyz. Supported file formats include everything that ase.io can read and additionally h5 files in the H5MD standard.

If you want to view the frames while they are added to the scene you can use zndraw -mp traj.xyz. See zndraw --help for more CLI options.

Python

ZnDraw provides a Python interface. The zndraw.ZnDraw object offers append, extend as well as assignment operations. More information is available in the example notebook.

from zndraw import ZnDraw
import ase

vis = ZnDraw()

vis.socket.sleep(2) # give it some time to fully connect
vis[0] = ase.Atoms(
  "H2O", positions=[[0.75, -0.75, 0], [0.75, 0.75, 0], [0, 0, 0]]
  )

ZnDraw also provides an interface to the Python logging library, including support for formatters and different logging levels.

import logging

log = logging.getLogger(__name__)
log.addHandler(vis.get_logging_handler())
log.critical("Critical Message")

Modifier

You can register modifier to change the scene via the interactions menu.

import typing as t

from zndraw import ZnDraw, Extension
import ase

vis = ZnDraw()

class MyModifier(UpdateScene):
  name: str = "H2O"

  def run(self, vis: ZnDraw, **kwargs) -> None:
    vis.append(molecule(self.name))

vis.register_modifier(
  MyModifier, public=True, run_kwargs={}
)

User Interface

Development

ZnDraw is developed using https://python-poetry.org/. Furthermore, the javascript packages have to be installed using https://www.npmjs.com/.

cd zndraw/static/
npm install

Docker

This package is available as a docker container and can be used via

docker run -pythonf/zndraw

References

If you use ZnDraw in your research and find it helpful please cite us.

@misc{elijosiusZeroShotMolecular2024,
  title = {Zero {{Shot Molecular Generation}} via {{Similarity Kernels}}},
  author = {Elijo{\v s}ius, Rokas and Zills, Fabian and Batatia, Ilyes and Norwood, Sam Walton and Kov{\'a}cs, D{\'a}vid P{\'e}ter and Holm, Christian and Cs{\'a}nyi, G{\'a}bor},
  year = {2024},
  eprint = {2402.08708},
  archiveprefix = {arxiv},
}

Acknowledgements

The creation of ZnDraw was supported by the Deutsche Forschungsgemeinschaft (DFG, German Research Foundation) in the framework of the priority program SPP 2363, “Utilization and Development of Machine Learning for Molecular Applications - Molecular Machine Learning” Project No. 497249646. Further funding though the DFG under Germany's Excellence Strategy - EXC 2075 - 390740016 and the Stuttgart Center for Simulation Science (SimTech) was provided.