Jupyter notebooks

chemiscope.show(frames=None, properties=None, meta=None, cutoff=None, mode='default')

Show the dataset defined by the given frames and properties (optionally meta and cutoff as well) using a embedded chemiscope visualizer inside a Jupyter notebook. These parameters have the same meaning as in the chemiscope.create_input() function.

The mode keyword also allows overriding the default two-panels visualization to show only a structure panel (mode = "structure") or the map panel (mode = "map"). These modes also make it possible to view a dataset for which properties (or frames) are not available.

When inside a jupyter notebook, the returned object will create a new chemiscope visualizer displaying the dataset. The returned object also have a save function that can be used to save the dataset to a .json or .json.gz file to load it in the main website later.

import chemiscope
from sklearn.decomposition import PCA
import ase.io

pca = PCA(n_components = 3)

frames = ase.io.read(...)
properties = {
    "PCA": pca.fit_transform(some_data)
}

widget = chemiscope.show(frames, properties)
# display the dataset in a chemiscope visualizer inside the notebook
widget
# ...


# Save the file for later use
widget.save("dataset.json")