def convert_midi_to_tensor()

in ar-cnn/inference.py [0:0]

• 20 lines of code
• 4 McCabe index (conditional complexity)

    def convert_midi_to_tensor(self, input_midi_path):
        """
        Converts a midi to pianoroll tensor

        Parameters
        ----------
        input_midi_path : string
            Full file path to the input midi

        Returns
        -------
        2d numpy array
            2d tensor that is a pianoroll
        """

        multi_track = pypianoroll.Multitrack(
            beat_resolution=Constants.beat_resolution)
        try:
            multi_track.parse_midi(input_midi_path,
                                   algorithm='custom',
                                   first_beat_time=0)
        except Exception as e:
            logger.error("Failed to parse the MIDI file.")

        if len(multi_track.tracks) > 1:
            logger.error("Input MIDI file has more than 1 track.")

        multi_track.pad_to_multiple(self.number_of_timesteps)
        multi_track.binarize()
        pianoroll = multi_track.tracks[0].pianoroll

        if pianoroll.shape[0] > self.number_of_timesteps:
            logger.error("Input MIDI file is longer than 8 bars.")

        # truncate
        tensor = pianoroll[0:self.number_of_timesteps, ]
        tensor = np.expand_dims(tensor, axis=0)
        tensor = np.expand_dims(tensor, axis=3)

        return tensor