Deep Learning Workshop

@@ -86,15 +86,16 @@ if __name__ == "__main__":
     print("Max exon length: {}".format(max_exon_length))
     print("Max utr length: {}".format(max_utr_length))
 
+    if max_exon_length > max_utr_length:
+        max_length = max_exon_length
+    else:
+        max_length = max_utr_length
+
     # Fill sequence with X char to get max length
     # One-hot-encoding of sequences
     for sequence, label in zip(sequences, labels):
-        if label == "exon":
-            if len(sequence) < max_exon_length:
-                sequence_adjust = sequence.ljust(max_exon_length + len(sequence), 'X')
-        elif label == "utr":
-            if len(sequence) < max_utr_length:
-                sequence_adjust = sequence.ljust(max_utr_length + len(sequence), 'X')
+        if len(sequence) < max_length:
+            sequence_adjust = sequence.ljust(max_length + len(sequence), 'X')
         print("Length sequence_adjust: {}".format(len(sequence_adjust)))
         integer_encoded = integer_encoder.fit_transform(list(sequence_adjust))
         integer_encoded = np.array(integer_encoded).reshape(-1, 1)