def predict(self, sequences):
        """
        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.
        """
        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
def predict(self, sequences):
        """
        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.
        """
        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
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
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.
Return netChop predictions for each position in each sequence .