Fingerprint

gtrick.ogb2fp(name, root='dataset', fp_type=['morgan', 'maccs'])

Generate fingerprint features for OGB datasets.

Molecular fingerprints are a way to represent molecules as mathematical objects.

Note

To use this trick, you should install rdkit at first:

pip install rdkit

Example

Fingerprint (DGL), Fingerprint (PyG)

Parameters:

Name	Type	Description	Default
name	str	Name of the dataset.	required
root	str	Root directory to store the dataset folder.	'dataset'
fp_type	list of str	The types of generated fingerprint. Can be the following values: morgan: Morgan fingerprint. maccs: MACCS keys. rdkit: RDKit topological fingerprint.	['morgan', 'maccs']

Returns:

Type	Description
torch.Tensor	The generated fingerprint features.
torch.Tensor	The ground truth label.

gtrick.smiles2fp(smiles, fp_type)

Convert smile strings to fingerprint.

Molecular fingerprints are a way to represent molecules as mathematical objects.

Note

To use this trick, you should install rdkit at first:

pip install rdkit

Parameters:

Name	Type	Description	Default
smiles	list of str	The smile strings to convert.	required
fp_type	list of str	The types of generated fingerprint. Can be the following values: morgan: Morgan fingerprint. maccs: MACCS keys. rdkit: RDKit topological fingerprint.	required

Returns:

Type	Description
np.array	The generated fingerprint features.