class_docstr: Class to wrap MINC1 format opened netcdf object
  
  Although it has some of the same methods as a ``Header``, we use
  this only when reading a MINC file, to pull out useful header
  information, and for the method of reading the data out
docstr: Return scaled data for slice definition `sliceobj`
  
  Parameters
  ----------
  sliceobj : tuple, optional
      slice definition. If not specified, return whole array
  
  Returns
  -------
  scaled_arr : array
      array from minc file with scaling applied
docstr_tok: ["Return","scaled","data","for","slice","definition","`","sliceobj","`","Parameters","--","--","--","--","--","sliceobj",":","tuple",",","optional","slice","definition",".","If","not","specified",",","return","whole","array","Returns","--","--","--","-","scaled_arr",":","array","array","from","minc","file","with","scaling","applied"]
code: def get_scaled_data(self, sliceobj=()):
      """Return scaled data for slice definition `sliceobj`
  
      Parameters
      ----------
      sliceobj : tuple, optional
          slice definition. If not specified, return whole array
  
      Returns
      -------
      scaled_arr : array
          array from minc file with scaling applied
      """
      if sliceobj == ():
          raw_data = self._image.data
      else:
          raw_data = self._image.data[sliceobj]
      dtype = self.get_data_dtype()
      data = np.asarray(raw_data).view(dtype)
      return self._normalize(data, sliceobj)
  
imports: from __future__ import annotations
  from numbers import Integral
  import numpy
  from .externals.netcdf import netcdf_file
  from .fileslice import canonical_slicers
  from .spatialimages import SpatialHeader, SpatialImage
label_desc: Use image node_id 11 for calling the Minc1File obj's underlying member method code with example usage: obj.get_scaled_data(sliceobj) and returns: self