How to use the nptdms.channel_data.get_data_receiver function in npTDMS

def _read_channel_data(self, offset=0, length=None):
        if offset < 0:
            raise ValueError("offset must be non-negative")
        if length is not None and length < 0:
            raise ValueError("length must be non-negative")

        with Timer(log, "Allocate space for channel"):
            # Allocate space for data
            if length is None:
                num_values = len(self) - offset
            else:
                num_values = min(length, len(self) - offset)
            num_values = max(0, num_values)
            channel_data = get_data_receiver(self, num_values, self._raw_timestamps, self._memmap_dir)

        with Timer(log, "Read data for channel"):
            # Now actually read all the data
            for chunk in self._reader.read_raw_data_for_channel(self.path, offset, length):
                if chunk.data is not None:
                    channel_data.append_data(chunk.data)
                if chunk.scaler_data is not None:
                    for scaler_id, scaler_data in chunk.scaler_data.items():
                        channel_data.append_scaler_data(scaler_id, scaler_data)

        return channel_data

def _read_data(self, tdms_reader):
        with Timer(log, "Allocate space"):
            # Allocate space for data
            for group in self.groups():
                for channel in group.channels():
                    self._channel_data[channel.path] = get_data_receiver(
                        channel, len(channel), self._raw_timestamps, self._memmap_dir)

        with Timer(log, "Read data"):
            # Now actually read all the data
            for chunk in tdms_reader.read_raw_data():
                for (path, data) in chunk.channel_data.items():
                    channel_data = self._channel_data[path]
                    if data.data is not None:
                        channel_data.append_data(data.data)
                    elif data.scaler_data is not None:
                        for scaler_id, scaler_data in data.scaler_data.items():
                            channel_data.append_scaler_data(scaler_id, scaler_data)

            for group in self.groups():
                for channel in group.channels():
                    channel_data = self._channel_data[channel.path]