Trajectory plotting

This example demonstrates the visualization of trajectory data. It also includes visualization of atomic forces.

The same parameters can be used with chemiscope.show to visualize an interactive widget in a Jupyter notebook.

import ase.io
import numpy as np

import chemiscope

Load structures and properties

frames = ase.io.read("data/trajectory.xyz", ":")

properties = {
    # concise definition of a property, with just an array and the type
    # inferred by the size
    "index": np.arange(len(frames)),
    # an example of the verbose definition
    "energy": {
        "target": "structure",
        "values": [frame.info["energy"] for frame in frames],
        "units": "eV",
        "description": "potential energy, computed with DFTB+",
    },
}

Create a visualization and save it as a file that can be viewed at chemiscope.org

chemiscope.write_input(
    "trajectory-md.json.gz",
    # dataset metadata can also be included, to provide a self-contained description
    # of the data, authors and references
    meta={
        "name": "Allyl alcohol MD trajectory.",
        "description": (
            "This dataset contains data from a DFTB+ trajectory of allyl alcohol."
        ),
        "authors": ["The chemiscope developers"],
        "references": [
            (
                "G. Fraux, R. Cersonsky, and M. Ceriotti, "
                '"Chemiscope: interactive structure-property explorer for materials '
                'and molecules," JOSS 5(51), 2117 (2020).'
            )
        ],
    },
    frames=frames,
    properties=properties,
    # visualize forces as vectors
    shapes={
        "forces": chemiscope.ase_vectors_to_arrows(
            frames, "forces", scale=1, radius=0.15
        )
    },
    settings={  # these are reasonable settings for trajectory visualization
        "structure": [
            {
                "keepOrientation": True,
                "playbackDelay": 100,
                "shape": "forces",  # visualize force vectors
            }
        ],
        "map": {
            "joinPoints": True,
        },
    },
)

The file can also be viewed in a notebook. Use chemiscope.show above to bypass the creation of a JSON file and directly create a viewer.

chemiscope.show_input("trajectory-md.json.gz")

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