def __init__(self, log=None):
    """Create a new sppasFillIPUs instance.

    Log is used for a better communication of the annotation process and its
    results. If None, logs are redirected to the default logging system.

    :param log: (sppasLog) Human-readable logs.

    """
    super(sppasFillIPUs, self).__init__('fillipus.json', log)
    self.__audio_filename = None

def fix_options(self, options):
    """Fix all options.

        Available options are:

            - threshold: volume threshold to decide a window is silence or not
            - win_length: length of window for a estimation or volume values
            - min_sil: minimum duration of a silence
            - min_ipu: minimum duration of an ipu
            - shift_start: start boundary shift value.
            - shift_end: end boundary shift value.

        :param options: (sppasOption)

        """
    for opt in options:
        key = opt.get_key()
        if 'min_sil' == key:
            self.set_min_sil(opt.get_value())
        elif 'min_ipu' == key:
            self.set_min_ipu(opt.get_value())
        elif 'shift_start' == key:
            self.set_shift_start(opt.get_value())
        elif 'shift_end' == key:
            self.set_shift_end(opt.get_value())
        elif 'pattern' in key:
            self._options[key] = opt.get_value()
        else:
            raise AnnotationOptionError(key)

def get_min_sil(self):
    return self._options['min_sil']

def get_min_ipu(self):
    return self._options['min_ipu']

def get_shift_start(self):
    return self._options['shift_start']

def get_shift_end(self):
    return self._options['shift_end']

def set_min_sil(self, value):
    """Fix the initial minimum duration of a silence.

        :param value: (float) Duration in seconds.

        """
    self._options['min_sil'] = value

def set_min_ipu(self, value):
    """Fix the initial minimum duration of an IPU.

        :param value: (float) Duration in seconds.

        """
    self._options['min_ipu'] = value

def set_shift_start(self, value):
    """Fix the start boundary shift value.

        :param value: (float) Duration in seconds.

        """
    self._options['shift_start'] = value

def set_shift_end(self, value):
    """Fix the end boundary shift value.

        :param value: (float) Duration in seconds.

        """
    self._options['shift_end'] = value

def convert(self, channel, text_tier):
    """Return a tier with transcription aligned to the audio.

        :param channel: (Channel) Input audio channel
        :param text_tier: (sppasTier) Input transcription text in a PointTier
        :return: (sppasTier | None) Tier with transcription aligned to the audio

        """
    units = list()
    for a in text_tier:
        units.append(serialize_labels(a.get_labels()))
    ipus = [unit for unit in units if unit != SIL_ORTHO]
    filler = FillIPUs(channel, units)
    filler.set_min_ipu(self._options['min_ipu'])
    filler.set_min_sil(self._options['min_sil'])
    filler.set_shift_start(self._options['shift_start'])
    filler.set_shift_end(self._options['shift_end'])
    n = filler.fix_threshold_durations()
    if n != len(ipus):
        return None
    tracks = filler.get_tracks(time_domain=True)
    tier = sppasSearchIPUs.tracks_to_tier(tracks, channel.get_duration(), filler.get_vagueness())
    tier.set_name('Transcription')
    self._set_meta(filler, tier)
    i = 0
    for a in tier:
        if a.get_best_tag().is_silence() is False:
            a.set_labels([sppasLabel(sppasTag(ipus[i]))])
            i += 1
    return tier

def get_inputs(self, input_files):
    """Return the channel and the tier with ipus.

        :param input_files: (list)
        :raise: NoTierInputError
        :return: (Channel, sppasTier)

        """
    ext = self.get_input_extensions()
    audio_ext = ext[0]
    annot_ext = ext[1]
    tier = None
    channel = None
    audio_filename = ''
    for filename in input_files:
        fn, fe = os.path.splitext(filename)
        if channel is None and fe in audio_ext:
            audio_speech = audioopy.aio.open(filename)
            n = audio_speech.get_nchannels()
            if n != 1:
                audio_speech.close()
                raise AudioChannelError(n)
            idx = audio_speech.extract_channel()
            channel = audio_speech.get_channel(idx)
            audio_filename = filename
            audio_speech.close()
        elif tier is None and fe in annot_ext:
            parser = sppasTrsRW(filename)
            trs_input = parser.read()
            tier = sppasFindTier.transcription(trs_input)
            if 'raw' not in tier.get_name().lower():
                tier = None
    if tier is None:
        logging.error('A tier with the raw transcription was not found.')
        raise NoTierInputError
    if tier.is_point() is False:
        logging.error('The tier with the raw transcription should be of type: Point.')
        raise AnnDataTypeError(tier.get_name(), 'PointTier')
    if tier.is_empty() is True:
        raise EmptyInputError(tier.get_name())
    if channel is None:
        logging.error('No audio file found or invalid one. An audio file with only one channel was expected.')
        raise NoChannelInputError
    extm = os.path.splitext(audio_filename)[1].lower()[1:]
    media = sppasMedia(os.path.abspath(audio_filename), mime_type='audio/' + extm)
    tier.set_media(media)
    return (channel, tier)

def run(self, input_files, output=None):
    """Run the automatic annotation process on an input.

        input_filename is a tuple (audio, raw transcription)

        :param input_files: (list of str) (audio, ortho)
        :param output: (str) the output file name
        :returns: (sppasTranscription)

        """
    input_channel, input_tier = self.get_inputs(input_files)
    framerate = input_channel.get_framerate()
    tier = self.convert(input_channel, input_tier)
    if tier is None:
        self.logfile.print_message(_info(1296), indent=2, status=-1)
        return []
    trs_output = sppasTranscription(self.name)
    trs_output.set_meta('media_sample_rate', str(framerate))
    trs_output.set_meta('annotation_result_of', input_files[0])
    trs_output.append(tier)
    tier.set_media(input_tier.get_media())
    if output is not None:
        output_file = self.fix_out_file_ext(output)
        parser = sppasTrsRW(output_file)
        parser.write(trs_output)
        return [output_file]
    return trs_output

def run_for_batch_processing(self, input_files):
    """Perform the annotation on a file.

        This method is called by 'batch_processing'. It fixes the name of the
        output file, and call the run method.

        Override to NOT ANNOTATE if an annotation is already existing.

        :param input_files: (list of str) the required inputs for a run
        :returns: output file name or None

        """
    root_pattern = self.get_out_name(input_files[0])
    ext = []
    for e in sppasTrsRW.annot_extensions():
        if e not in ('.txt',):
            ext.append(e)
    exists_out_name = sppasBaseAnnotation._get_filename(root_pattern, ext)
    new_files = list()
    if exists_out_name is not None:
        out_name = self.fix_out_file_ext(root_pattern)
        if exists_out_name.lower() == out_name.lower():
            return list()
        else:
            try:
                parser = sppasTrsRW(exists_out_name)
                t = parser.read()
                parser.set_filename(out_name)
                parser.write(t)
                self.logfile.print_message(_info(1302).format(out_name), indent=2, status=annots.info)
                return [out_name]
            except:
                pass
    else:
        try:
            new_files = self.run(input_files, root_pattern)
        except Exception as e:
            self.logfile.print_message('{:s}\n'.format(str(e)), indent=1, status=-1)
    return new_files

def get_output_pattern(self):
    """Pattern this annotation uses in an output filename."""
    return self._options.get('outputpattern', '')

def get_input_patterns(self):
    """Pattern this annotation expects for its input filename."""
    return [self._options.get('inputpattern1', ''), self._options.get('inputpattern2', '')]

@staticmethod
def get_input_extensions():
    """Extensions that the annotation expects for its input filename."""
    return [sppasFiles.get_informat_extensions('AUDIO'), ['.txt']]

def _set_meta(self, filler, tier):
    """Set meta values to the tier."""
    tier.set_meta('threshold_volume', str(filler.get_vol_threshold()))
    tier.set_meta('minimum_silence_duration', str(filler.get_min_sil_dur()))
    tier.set_meta('minimum_ipus_duration', str(filler.get_min_ipu_dur()))
    tier.set_meta('shift_ipus_start', str(filler.get_shift_start()))
    tier.set_meta('shift_ipus_end', str(filler.get_shift_end()))
    self.logfile.print_message(_info(1058), indent=1)
    m1 = _info(1290).format(int(filler.get_vol_threshold()))
    m2 = _info(1292).format(filler.get_min_sil_dur())
    m3 = _info(1294).format(filler.get_min_ipu_dur())
    for m in (m1, m2, m3):
        self.logfile.print_message(m, indent=2)