@classmethod
def __load_biom(cls, filepath: str, **kwargs: Any) -> Tuple[(pd.DataFrame, dict)]:
    'Actual private method to process :mod:`biom` file.\n\n        Parameters\n        ----------\n        filepath\n            :mod:`biom` file path.\n        kwargs\n            Compatibility\n        '
    biom_file = biom.load_table(filepath)
    if (biom_file.metadata(axis='observation') is not None):
        obs_data = biom_file.metadata_to_dataframe('observation')
        col_names = list(obs_data.columns.values)
        col_names_low = [col.lower() for col in col_names]
        avail_col_names = [colname for tax_name in BIOM_TAXONOMY_NAMES for colname in col_names_low if ((colname[::(- 1)].find(tax_name[::(- 1)]) < 3) and (colname[::(- 1)].find(tax_name[::(- 1)]) > (- 1)))]
        metadata_cols = [col for col in col_names if (col.lower() not in avail_col_names)]
        if (len(avail_col_names) == 1):
            tmp_col_index = col_names_low.index(avail_col_names[0])
            taxonomy_frame = obs_data[col_names[tmp_col_index]]
        else:
            taxonomy_frame = obs_data
        tmp_metadata = obs_data.loc[:, metadata_cols].to_dict()
        return (taxonomy_frame, tmp_metadata)
    else:
        raise ValueError('Biom file does not contain observation metadata.')
Actual private method to process :mod:`biom` file.

Parameters
----------
filepath
    :mod:`biom` file path.
kwargs
    Compatibility
@classmethod
def __load_biom(cls, filepath: str, **kwargs: Any) -> Tuple[(pd.DataFrame, dict)]:
    'Actual private method to process :mod:`biom` file.\n\n        Parameters\n        ----------\n        filepath\n            :mod:`biom` file path.\n        kwargs\n            Compatibility\n        '
    biom_file = biom.load_table(filepath)
    if (biom_file.metadata(axis='observation') is not None):
        obs_data = biom_file.metadata_to_dataframe('observation')
        col_names = list(obs_data.columns.values)
        col_names_low = [col.lower() for col in col_names]
        avail_col_names = [colname for tax_name in BIOM_TAXONOMY_NAMES for colname in col_names_low if ((colname[::(- 1)].find(tax_name[::(- 1)]) < 3) and (colname[::(- 1)].find(tax_name[::(- 1)]) > (- 1)))]
        metadata_cols = [col for col in col_names if (col.lower() not in avail_col_names)]
        if (len(avail_col_names) == 1):
            tmp_col_index = col_names_low.index(avail_col_names[0])
            taxonomy_frame = obs_data[col_names[tmp_col_index]]
        else:
            taxonomy_frame = obs_data
        tmp_metadata = obs_data.loc[:, metadata_cols].to_dict()
        return (taxonomy_frame, tmp_metadata)
    else:
        raise ValueError('Biom file does not contain observation metadata.')