def add_features(self, features, append=True, merge='<STR_LIT>',<EOL>duplicates='<STR_LIT:ignore>', min_studies=<NUM_LIT:0.0>, threshold=<NUM_LIT>):
if (not append) or not hasattr(self, '<STR_LIT>'):<EOL><INDENT>self.feature_table = FeatureTable(self)<EOL><DEDENT>self.feature_table.add_features(features, merge=merge,<EOL>duplicates=duplicates,<EOL>min_studies=min_studies,<EOL>threshold=threshold)<EOL>
Construct a new FeatureTable from file.

        Args:
            features: Feature data to add. Can be:
                (a) A text file containing the feature data, where each row is
                a study in the database, with features in columns. The first
                column must contain the IDs of the studies to match up with the
                image data.
                (b) A pandas DataFrame, where studies are in rows, features are
                in columns, and the index provides the study IDs.
            append (bool): If True, adds new features to existing ones
                incrementally. If False, replaces old features.
            merge, duplicates, min_studies, threshold: Additional arguments
                passed to FeatureTable.add_features().