VisualizationΒΆ

We also offer a ml4chem.visualization module to plot interesting graphics about your model, features, or even monitor the progress of the loss function and error minimization.

Two backends are supported to plot in ML4Chem: Seaborn and Plotly.

An example is shown below:

from ml4chem.visualization import plot_atomic_features
fig = plot_atomic_features("latent_space.db",
                           method="pca",
                           dimensions=3,
                           backend="plotly")
fig.write_html("latent_example.html")

This will produce an interactive plot with plotly where dimensionality was reduced using PCA, and an html with the name latent_example.html is created.