Creating chemiscope input files

When using the default chemiscope interface, all the structures and properties in a dataset are loaded from a single JSON file. This sections describe how to generate such JSON file, either using a pre-existing python script that does most of the work for you, or by writing the JSON file directly. Since the resulting JSON file can be quite large and thus harder to share with collaborators, the default chemiscope interface also allows to load JSON files compressed with gzip.

tl;dr if you would like to generate a simple chemiscope for your dataset, we have a Google Colab notebook that can help!

Tools able to create chemiscope input

chemiscope Python module

The easiest way to create a JSON input file is to use the chemiscope Python module. Install the package with pip install chemiscope, and use chemiscope.write_input() or chemiscope.create_input() in your own script to generate the JSON file.

If all the properties you want to include into chemiscope are already stored in a file ase can read, the chemiscope python package also install a chemiscope-input command line script.

Note that chemiscope does not compute structural representations or dimensionality reduction, and you need to do this yourself or use another package such as ASAP.

ASAP

The ASAP structural analysis package is another tool that can directly generate an output in chemiscope format.

chemiscope functions reference

chemiscope.write_input(path, frames, meta=None, properties=None, environments=None, settings=None)

Create the input JSON file used by the default chemiscope visualizer, and save it to the given path.

Parameters:
  • path (str) – name of the file to use to save the json data. If it ends with ‘.gz’, a gzip compressed file will be written

  • frames (list) – list of atomic structures. For now, only ase.Atoms objects are supported

  • meta (dict) – optional metadata of the dataset

  • properties (dict) – optional dictionary of additional properties

  • environments (list) – optional list of (structure id, atom id, cutoff) specifying which atoms have properties attached and how far out atom-centered environments should be drawn by default.

  • settings (dict) – optional dictionary of settings to use when displaying the data. Possible entries for the settings dictionary are documented in the chemiscope input file reference.

This function uses create_input() to generate the input data, see the documentation of this function for more information.

Here is a quick example of generating a chemiscope input reading the structures from a file that ase can read, and performing PCA using sklearn on a descriptor computed with another package.

import ase
from ase import io
import numpy as np
import sklearn
from sklearn import decomposition
import chemiscope

frames = ase.io.read('trajectory.xyz', ':')

# example property 1: list containing the energy of each structure,
# from calculations performed beforehand
energies = np.loadtxt('energies.txt')

# example property 2: PCA projection computed using sklearn.
# X contains a multi-dimensional descriptor of the structure
X = np.array( ... )
pca = sklearn.decomposition.PCA(n_components=3).fit_transform(X)

properties = {
    "PCA": {
        "target": "atom",
        "values": pca,
        "description": "PCA of per-atom representation of the structures",
    },
    "energies": {
        "target": "structure",
        "values": energies,
        "units": "kcal/mol",
    },
}

# additional properties coming from the trajectory
frame_properties = chemiscope.extract_properties(
    frames,
    only=["temperature", "classification"]
)

# merge all properties together
properties.extend(frame_properties)

chemiscope.write_input(
    path="chemiscope.json.gz",
    frames=frames,
    properties=properties,
    # This is required to display properties with `target: "atom"`
    environments=chemiscope.all_atomic_environments(frames),
)
chemiscope.create_input(frames=None, meta=None, properties=None, environments=None, settings=None)

Create a dictionary that can be saved to JSON using the format used by the default chemiscope visualizer.

Parameters:
  • frames (list) – list of atomic structures. For now, only ase.Atoms objects are supported

  • meta (dict) – optional metadata of the dataset, see below

  • properties (dict) – optional dictionary of properties, see below

  • environments (list) – optional list of (structure id, atom id, cutoff) specifying which atoms have properties attached and how far out atom-centered environments should be drawn by default. Functions like all_atomic_environments() or librascal_atomic_environments() can be used to generate the list of environments in simple cases.

  • settings (dict) – optional dictionary of settings to use when displaying the data. Possible entries for the settings dictionary are documented in the chemiscope input file reference.

The dataset metadata should be given in the meta dictionary, the possible keys are:

meta = {
    'name': '...',         # str, dataset name
    'description': '...',  # str, dataset description
    'authors': [           # list of str, dataset authors, OPTIONAL
        '...',
    ],
    'references': [        # list of str, references for this dataset,
        '...',             # OPTIONAL
    ],
}

Properties can be added with the properties parameter. This parameter should be a dictionary containing one entry for each property. Properties can be extracted from structures with extract_properties() or composition_properties(), or manually defined by the user.

Each entry in the properties dictionary contains a target attribute ('atom' or 'structure') and a set of values. values can be a Python list of float or string; a 1D numpy array of numeric values; or a 2D numpy array of numeric values. In the later case, multiple properties will be generated along the second axis. For example, passing

properties = {
    'cheese': {
        'target': 'atom',
        'values': np.zeros((300, 4)),
        # optional: property unit
        'unit': 'random / fs',
        # optional: property description
        'description': 'a random property for example',
    }
}

will generate four properties named cheese[1], cheese[2], cheese[3], and cheese[4], each containing 300 values.

It is also possible to pass shortened representation of the properties, for instance:

properties = {
    'cheese':  np.zeros((300, 4)),
    }
}

In this case, the type of property (structure or atom) would be deduced by comparing the numbers atoms and structures in the dataset to the length of provided list/np.ndarray.

chemiscope.extract_properties(frames, only=None, environments=None)

Extract properties defined in the frames in a chemiscope-compatible format.

Parameters:
  • frames – iterable over structures (typically a list of frames)

  • only – optional, list of strings. If not None, only properties with a name from this list are included in the output.

  • environments – optional, list of environments (described as (structure id, center id, cutoff)) to include when extracting the atomic properties.

chemiscope.composition_properties(frames, environments=None)

Generate properties containing the chemical composition of the given frames.

This create two atomic properties: symbol (string) and number (int); and multiple structure properties: composition and n_{element} for each elements in the dataset. The properties are then returned in chemiscope format.

Parameters:
  • frames – iterable over structures (typically a list of frames)

  • environments – optional, list of environments (described as (structure id, center id, cutoff)) to include when generating the atomic properties.

chemiscope.all_atomic_environments(frames, cutoff=3.5)

Generate a list of environments containing all the atoms in the given frames. The optional spherical cutoff radius is used to display the environments in chemiscope.

Parameters:
  • frames – iterable over structures (typically a list of frames)

  • cutoff (float) – spherical cutoff radius used when displaying the environments

chemiscope.librascal_atomic_environments(frames, cutoff=3.5)

Generate the list of environments for the given frames, matching the behavior used by librascal when computing descriptors for only a subset of the atomic centers. The optional spherical cutoff radius is used to display the environments in chemiscope.

Only ase.Atoms are supported for the frames since that’s what librascal uses.

Parameters:
  • frames – iterable over ase.Atoms

  • cutoff (float) – spherical cutoff radius used when displaying the environments

chemiscope-input command line interface

Command-line utility to generate an input for chemiscope — the interactive structure-property explorer. Parses an input file containing atomic structures using the ASE I/O module, and converts it into a JSON file that can be loaded in chemiscope. Frame and environment properties must be written in the same file containing atomic structures: we recommend the extended xyz format, which is flexible and simple. In all cases, this utility will simply write to the JSON file anything that is readable by ASE.

chemiscope-input [-h] [-o OUTPUT] [--properties PROPERTIES]
                 [--only-atoms | --only-structures] [--cutoff CUTOFF] [--name NAME]
                 [--description DESCRIPTION] [--authors [AUTHORS ...]]
                 [--references [REFERENCES ...]] [--settings SETTINGS]
                 input

positional arguments

  • input - input file containing the structures and properties (default: None)

options

  • -h, --help - show this help message and exit

  • -o OUTPUT, --output OUTPUT - chemiscope output file in JSON format (default: None)

  • --properties PROPERTIES - comma-separated list of properties that should be extracted. defaults to all

  • --only-atoms - only use per-atom properties from the input file

  • --only-structures - only use per-structure properties from the input file (default)

  • --cutoff CUTOFF - spherical cutoff radius that should be visualized around environments (default: 3.5)

  • --name NAME - name of the dataset (default: )

  • --description DESCRIPTION - description of the dataset (default: )

  • --authors AUTHORS - list of dataset authors (default: [])

  • --references REFERENCES - list of references for the dataset (default: [])

  • --settings SETTINGS - visualization settings, as a JSON string, following the chemiscope format (default: )