code: def predict(self, sequences):
          
          with tempfile.NamedTemporaryFile(suffix=".fsa", mode="w") as input_fd:
              for (i, sequence) in enumerate(sequences):
                  input_fd.write("> %d\n" % i)
                  input_fd.write(sequence)
                  input_fd.write("\n")
              input_fd.flush()
              try:
                  output = subprocess.check_output(["netChop", input_fd.name])
              except subprocess.CalledProcessError as e:
                  logging.error("Error calling netChop: %s:\n%s" % (e, e.output))
                  raise
  
          parsed = self.parse_netchop(output)
          assert len(parsed) == len(sequences), \
              "Expected %d results but got %d" % (
                  len(sequences), len(parsed))
          assert [len(x) for x in parsed] == [len(x) for x in sequences]
          return parsed
docs: Return netChop predictions for each position in each sequence.
  
          Parameters
          -----------
          sequences : list of string
              Amino acid sequences to predict cleavage for
  
          Returns
          -----------
          list of list of float
  
          The i'th list corresponds to the i'th sequence. Each list gives
          the cleavage probability for each position in the sequence.