Added utility func for EncoderHelper to automatically encode labels f…

…or datasets

immuneML/encodings/deeprc/DeepRCEncoder.py

@@ -7,6 +7,7 @@
 from immuneML.data_model.encoded_data.EncodedData import EncodedData
 from immuneML.encodings.DatasetEncoder import DatasetEncoder
 from immuneML.encodings.EncoderParams import EncoderParams
+from immuneML.util.EncoderHelper import EncoderHelper
 from immuneML.util.PathBuilder import PathBuilder
 
 
@@ -88,11 +89,12 @@ def encode(self, dataset, params: EncoderParams) -> RepertoireDataset:
 
         self.export_repertoire_tsv_files(result_path)
 
-        labels = params.label_config.get_labels_by_name()
-        metadata_filepath = self.export_metadata_file(dataset, labels, result_path)
+
+        metadata_filepath = self.export_metadata_file(dataset, params.label_config.get_labels_by_name(), result_path)
 
         encoded_dataset = dataset.clone()
-        encoded_dataset.encoded_data = EncodedData(examples=None, labels=dataset.get_metadata(labels) if params.encode_labels else None,
+        encoded_dataset.encoded_data = EncodedData(examples=None,
+                                                   labels=EncoderHelper.encode_dataset_labels(dataset, params.label_config, params.encode_labels),
                                                    example_ids=dataset.get_repertoire_ids(),
                                                    example_weights=dataset.get_example_weights(),
                                                    encoding=DeepRCEncoder.__name__,

immuneML/util/EncoderHelper.py

@@ -71,10 +71,7 @@ def check_dataset_type_available_in_mapping(dataset, class_name):
 
     @staticmethod
     def encode_element_dataset_labels(dataset: ElementDataset, label_config: LabelConfiguration):
-        '''
-        Automatically generates the encoded labels for an ElementDataset (= SequenceDataset or ReceptorDataset)
-        '''
-
+        '''Automatically generates the encoded labels for an ElementDataset (= SequenceDataset or ReceptorDataset)'''
         labels = {name: [] for name in label_config.get_labels_by_name()}
 
         for sequence in dataset.get_data():
@@ -84,6 +81,25 @@ def encode_element_dataset_labels(dataset: ElementDataset, label_config: LabelCo
 
         return labels
 
+    @staticmethod
+    def encode_repertoire_dataset_labels(dataset: RepertoireDataset, label_config: LabelConfiguration):
+        '''Automatically generates the encoded labels for a RepertoireDataset'''
+        label_names = label_config.get_labels_by_name()
+        return dataset.get_metadata(label_names)
+
+    @staticmethod
+    def encode_dataset_labels(dataset: Dataset, label_config: LabelConfiguration, encode_labels: bool = True):
+        '''Automatically generates the encoded labels for a Dataset.
+        This contains labels in the following format: {'label_name': ['label_class1', 'label_class2', 'label_class2']}
+        where the inner list(s) contain the class label for each example in the dataset'''
+        if not encode_labels:
+            return None
+
+        if isinstance(dataset, RepertoireDataset):
+            return EncoderHelper.encode_repertoire_dataset_labels(dataset, label_config)
+        else:
+            return EncoderHelper.encode_element_dataset_labels(dataset, label_config)
+
     @staticmethod
     def check_positive_class_labels(label_config: LabelConfiguration, location: str):
         '''