def get_dataframe_row(self, dataset_cases, predicted_data, pdb_data, record_id, additional_prediction_data_columns):
        '''Create a dataframe row for a prediction.'''
        record = dataset_cases[record_id]
        for m in record['PDBMutations']:
            assert('DSSPSimpleSSType' not in m)
            m['DSSPSimpleSSType'] = dssp_elision.get(m['ComplexDSSP']) or dssp_elision.get(m['MonomericDSSP'])
            m['DSSPType'] = m.get('ComplexDSSP') or m.get('MonomericDSSP')
            m['DSSPExposure'] = m.get('ComplexExposure') or m.get('MonomericExposure')

        dataframe_record = super(DBBenchmarkRun, self).get_dataframe_row(dataset_cases, predicted_data, pdb_data, record_id, additional_prediction_data_columns)
        # add columns
        return dataframe_record
def get_dataframe_row ( self , dataset_cases , predicted_data , pdb_data , record_id , additional_prediction_data_columns ) : record = dataset_cases [ record_id ] for m in record [ 'PDBMutations' ] : assert ( 'DSSPSimpleSSType' not in m ) m [ 'DSSPSimpleSSType' ] = dssp_elision . get ( m [ 'ComplexDSSP' ] ) or dssp_elision . get ( m [ 'MonomericDSSP' ] ) m [ 'DSSPType' ] = m . get ( 'ComplexDSSP' ) or m . get ( 'MonomericDSSP' ) m [ 'DSSPExposure' ] = m . get ( 'ComplexExposure' ) or m . get ( 'MonomericExposure' ) dataframe_record = super ( DBBenchmarkRun , self ) . get_dataframe_row ( dataset_cases , predicted_data , pdb_data , record_id , additional_prediction_data_columns ) return dataframe_record
Create a dataframe row for a prediction.