class_docstr: A segmentation of a space into labeled objects
  
  Supports overlapping objects and cacheing. Retrieval can be as a
  single plane (legacy), as multiple planes and as sparse ijv.
class_docstr_tok: ["A","segmentation","of","a","space","into","labeled","objects","Supports","overlapping","objects","and","cacheing",".","Retrieval","can","be","as","a","single","plane","(","legacy",")",",","as","multiple","planes","and","as","sparse","ijv","."]
docstr: Get the dense representation of the segmentation
  
  return the segmentation as a 6-D array and a sequence of arrays of the
  object numbers in each 5-D hyperplane of the segmentation. The first
  axis of the segmentation allows us to assign multiple labels to
  individual pixels. Given a 5-D algorithm, the code typically iterates
  over the first axis:
  
  for labels in self.get_dense():
      # do something
  
  The remaining axes are in the order, c, t, z, y and x
docstr_tok: ["Get","the","dense","representation","of","the","segmentation","return","the","segmentation","as","a","6-D","array","and","a","sequence","of","arrays","of","the","object","numbers","in","each","5-D","hyperplane","of","the","segmentation",".","The","first","axis","of","the","segmentation","allows","us","to","assign","multiple","labels","to","individual","pixels",".","Given","a","5-D","algorithm",",","the","code","typically","iterates","over","the","first","axis",":","for","labels","in","self.get_dense","(",")",":","#","do","something","The","remaining","axes","are","in","the","order",",","c",",","t",",","z",",","y","and","x"]
code: def get_dense(self):
      """Get the dense representation of the segmentation
  
      return the segmentation as a 6-D array and a sequence of arrays of the
      object numbers in each 5-D hyperplane of the segmentation. The first
      axis of the segmentation allows us to assign multiple labels to
      individual pixels. Given a 5-D algorithm, the code typically iterates
      over the first axis:
  
      for labels in self.get_dense():
          # do something
  
      The remaining axes are in the order, c, t, z, y and x
      """
      if self.__dense is not None:
          return self.__dense, self.__indices
  
      if not self.has_sparse():
          raise ValueError("Can't find object sparse segmentation.")
  
      return self.__convert_sparse_to_dense()
  
file_path: CellProfiler/src/subpackages/core/cellprofiler_core/object/_segmentation.py
imports: from cellprofiler_library.functions.segmentation import convert_dense_to_sparse
  from cellprofiler_library.functions.segmentation import convert_sparse_to_dense
  from cellprofiler_library.functions.segmentation import indices_from_dense
  from cellprofiler_library.functions.segmentation import dense_shape_from_sparse
  from cellprofiler_library.functions.segmentation import _validate_dense
  from cellprofiler_library.functions.segmentation import _validate_sparse
  from cellprofiler_library.functions.segmentation import _validate_dense_shape
label_desc: Use image node_id 8 for calling the Segmentation obj's underlying member method code with example usage: obj.get_dense() and returns: self, self,  self