pyproteonet.imputation.sklearn.generic_matrix_imputation

pyproteonet.imputation.sklearn.generic_matrix_imputation(dataset: Dataset, molecule: str, column: str, imputation_function: Callable[[ndarray], ndarray], transpose: bool = False, result_column: str | None = None, **kwargs) → Series

Apply a scikit-learn matrix imputer to a dataset.

Parameters:

  • dataset (Dataset) – Dataset to impute.

  • molecule (str) – Molecule type to impute (e.g. protein, peptide etc.).

  • column (str) – Name of the value column to impute.

  • imputation_function (Callable[[np.ndarray], np.ndarray]) – Impute function working on a 2d numpy array.

  • transpose (bool, optional) – Whether to transpose the matrix before imputation. Defaults to False.

  • result_column (Optional[str], optional) – If given, name of the value column to store the imputed values in. Defaults to None.

Returns:

The imputed values.

Return type:

pd.Series