How to use the atoml.preprocess.clean_data.clean_infinite function in atoml

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github SUNCAT-Center / CatKit / docs / tutorials / 9_adsorbate_fingerprints.py View on Github external
# This list is passed on to the following setup functions,
#    along with a list of atoms.

# Get and print the names of features.
features_labels = fingerprinter.return_names(functions)
for l in range(len(features_labels)):
    print(l, features_labels[l])

# Get a matrix containing the fingerprints.
unlabeled_data_matrix = fingerprinter.return_vec(AtoML_atoms, functions)
print(np.shape(unlabeled_data_matrix), 'data matrix created.')

# Cleanup in case some of the functions are returning NaNs or Infs
print("Cleaning data.")
clean_data_matrix = clean_infinite(unlabeled_data_matrix)['train']

# Ready for Machine learning.
print(np.shape(clean_data_matrix), 'data matrix returned.')

atoml

Yet another style preserving TOML library

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Latest version published 3 years ago

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