class_docstr: MINC implementation of array proxy protocol
  
  The array proxy allows us to freeze the passed fileobj and
  header such that it returns the expected data array.
docstr: Read data from file and apply scaling, casting to ``dtype``
  
  If ``dtype`` is unspecified, the dtype is automatically determined.
  
  Parameters
  ----------
  dtype : numpy dtype specifier, optional
      A numpy dtype specifier specifying the type of the returned array.
  
  Returns
  -------
  array
      Scaled image data with type `dtype`.
docstr_tok: ["Read","data","from","file","and","apply","scaling",",","casting","to","``","dtype","``","If","``","dtype","``","is","unspecified",",","the","dtype","is","automatically","determined",".","Parameters","--","--","--","--","--","dtype",":","numpy","dtype","specifier",",","optional","A","numpy","dtype","specifier","specifying","the","type","of","the","returned","array",".","Returns","--","--","--","-","array","Scaled","image","data","with","type","`","dtype","`","."]
code: def __array__(self, dtype=None):
      """Read data from file and apply scaling, casting to ``dtype``
  
      If ``dtype`` is unspecified, the dtype is automatically determined.
  
      Parameters
      ----------
      dtype : numpy dtype specifier, optional
          A numpy dtype specifier specifying the type of the returned array.
  
      Returns
      -------
      array
          Scaled image data with type `dtype`.
      """
      arr = self.minc_file.get_scaled_data(sliceobj=())
      if dtype is not None:
          arr = arr.astype(dtype, copy=False)
      return arr
  
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 5 for calling the MincImageArrayProxy obj's underlying member method code with example usage: obj.__array__(dtype) and returns: arr