How to use the nptdms.common.ObjectPath.from_string function in npTDMS

tdms_reader.read_metadata()

        # Use object metadata to build group and channel objects
        group_properties = OrderedDict()
        group_channels = OrderedDict()
        object_properties = {
            path_string: self._convert_properties(obj.properties)
            for path_string, obj in tdms_reader.object_metadata.items()}
        try:
            self._properties = object_properties['/']
        except KeyError:
            pass

        for (path_string, obj) in tdms_reader.object_metadata.items():
            properties = object_properties[path_string]
            path = ObjectPath.from_string(path_string)
            if path.is_root:
                pass
            elif path.is_group:
                group_properties[path.group] = properties
            else:
                # Object is a channel
                try:
                    channel_group_properties = object_properties[path.group_path()]
                except KeyError:
                    channel_group_properties = OrderedDict()
                channel = TdmsChannel(
                    path, obj.data_type, obj.scaler_data_types, obj.num_values,
                    properties, channel_group_properties, self._properties,
                    tdms_reader, self._raw_timestamps, self._memmap_dir)
                if path.group in group_channels:
                    group_channels[path.group].append(channel)

def _build_index(self):
        """ Builds an index into the segment data for faster lookup of values

            _segment_channel_offsets provides data offset at the end of each segment per channel
            _segment_chunk_sizes provides chunk sizes in each segment per channel
        """
        data_objects = [
            path
            for (path, obj) in self.object_metadata.items()
            if ObjectPath.from_string(path).is_channel]
        num_segments = len(self._segments)

        segment_num_values = {
            path: np.zeros(num_segments, dtype=np.int64) for path in data_objects}
        segment_chunk_sizes = {
            path: np.zeros(num_segments, dtype=np.int64) for path in data_objects}

        for i, segment in enumerate(self._segments):
            for obj in segment.ordered_objects:
                if not obj.has_data:
                    continue
                segment_chunk_sizes[obj.path][i] = obj.number_values if obj.has_data else 0
                segment_num_values[obj.path][i] = _number_of_segment_values(obj, segment)

        self._segment_chunk_sizes = segment_chunk_sizes
        self._segment_channel_offsets = {