class_docstr: The `Image` class provides the core object type used in nipy.
  
  An `Image` represents a volumetric brain image and provides means
  for manipulating the image data.  Most functions in the image module
  operate on `Image` objects.
  
  Notes
  -----
  Images can be created through the module functions.  See nipy.io for
  image IO such as ``load`` and ``save``
  
  Examples
  --------
  Load an image from disk
  
  >>> from nipy.testing import anatfile
  >>> from nipy.io.api import load_image
  >>> img = load_image(anatfile)
  
  Make an image from an array.  We need to make a meaningful coordinate map
  for the image.
  
  >>> arr = np.zeros((21,64,64), dtype=np.int16)
  >>> cmap = AffineTransform('kji', 'zxy', np.eye(4))
  >>> img = Image(arr, cmap)
docstr: Return new image with renamed output (range) coordinates
  
  Coordinates renamed according to the dictionary
  
  Parameters
  ----------
  \*\*names_dict : dict
      with keys being old names, and values being new names
  
  Returns
  -------
  newimg : Image
      An Image with the same data, having its output coordinates renamed.
  
  Examples
  --------
  >>> data = np.random.standard_normal((11,9,4))
  >>> im = Image(data, AffineTransform.from_params('ijk', 'xyz', np.identity(4), 'domain', 'range'))
  >>> im_renamed_reference = im.renamed_reference(x='newx', y='newy')
  >>> print(im_renamed_reference.reference)
  CoordinateSystem(coord_names=('newx', 'newy', 'z'), name='range', coord_dtype=float64)
code: def renamed_reference(self, **names_dict):
      r"""Return new image with renamed output (range) coordinates
  
      Coordinates renamed according to the dictionary
  
      Parameters
      ----------
      \*\*names_dict : dict
          with keys being old names, and values being new names
  
      Returns
      -------
      newimg : Image
          An Image with the same data, having its output coordinates renamed.
  
      Examples
      --------
      >>> data = np.random.standard_normal((11,9,4))
      >>> im = Image(data, AffineTransform.from_params('ijk', 'xyz', np.identity(4), 'domain', 'range'))
      >>> im_renamed_reference = im.renamed_reference(x='newx', y='newy')
      >>> print(im_renamed_reference.reference)
      CoordinateSystem(coord_names=('newx', 'newy', 'z'), name='range', coord_dtype=float64)
      """
      new_cmap = self.coordmap.renamed_range(names_dict)
      return self.__class__.from_image(self, coordmap=new_cmap)
  
imports: import warnings
  from copy import copy
  from itertools import chain
  import numpy
  from nibabel.onetime import auto_attr
  from ..reference.array_coords import ArrayCoordMap
  from ..reference.coordinate_map import AffineTransform, CoordinateSystem, input_axis_index
label_desc: Use image node_id 12 for calling the Image obj's underlying member method code with example usage: obj.renamed_reference() and returns: self