alinemol.preprocessing

alinemol.preprocessing

standardize_smiles

standardize_smiles(
    x: DataFrame, taut_canonicalization: bool = True
) -> pd.DataFrame

Standardization of a SMILES string.

Uses the Standardizer to perform sequence of cleaning operations on a SMILES string.

Parameters:

Name	Type	Description	Default
x	DataFrame	pd.DataFrame with smiles column	required
taut_canonicalization	bool	whether or not to use tautomer canonicalization	True

Returns:

Type	Description
DataFrame	pd.DataFrame with 'canonical_smiles', 'molecular_weight', and 'num_atoms' additional columns

drop_duplicates

drop_duplicates(x: DataFrame) -> pd.DataFrame

Remove conflicting duplicates from a DataFrame.

This function processes the DataFrame to

• Drop rows where the 'canonical_smiles' values are the same but the labels differ (conflicting rows).
• Retain only one row for each set of identical 'canonical_smiles' values with the same label.

Parameters:

Name	Type	Description	Default
x	DataFrame	The input DataFrame containing a 'canonical_smiles' column.	required

Returns:

Type	Description
DataFrame	pd.DataFrame: A DataFrame with conflicting duplicates removed, ensuring unique rows.

standardization_pipeline

standardization_pipeline(
    x: DataFrame, taut_canonicalization: bool = True
) -> pd.DataFrame

Standardization pipeline for a DataFrame.

This function performs the following operations on the input DataFrame

• Standardize the 'smiles' column using the standardize_smiles function.
• Drop conflicting duplicates using the drop_duplicates function.
• Return a DataFrame with 'smiles' and 'label' columns.

Parameters:

Name	Type	Description	Default
x	DataFrame	The input DataFrame containing a 'smiles' column.	required
taut_canonicalization	bool	Whether or not to use tautomer canonicalization.	True

Returns:

Type	Description
DataFrame	pd.DataFrame: A DataFrame with standardized 'canonical_smiles' values and conflicting duplicates removed.

Note

The input DataFrame must contain a 'smiles' and label column. Output DataFrame will contain 'smiles' and label columns.