code: def default_chunksize(self):
          
          if self._default_chunksize is None:
              try:
                  # TODO: if dimension is not yet fixed (eg tica var cutoff, use dim of data_producer.
                  self.dimension()
                  self.output_type()
              except:
                  self._default_chunksize = Iterable._FALLBACK_CHUNKSIZE
              else:
                  self._default_chunksize = Iterable._compute_default_cs(self.dimension(),
                                                                         self.output_type().itemsize, self.logger)
          return self._default_chunksize
docs: How much data will be processed at once, in case no chunksize has been provided.
  
          Notes
          -----
          This variable respects your setting for maximum memory in pyemma.config.default_chunksize