class_docstr: Class combining coordinate map and array shape
  
  When the function_domain of a CoordinateMap can be thought of as
  'array' coordinates, i.e. an 'input_shape' makes sense. We can
  than evaluate the CoordinateMap at np.indices(input_shape)
docstr: If the coordmap has a shape (so that it can be thought of as a
  map from voxels to some output space), return the range of the
  coordmap, i.e. the value at all the voxels.
  
  Parameters
  ----------
  coordmap : `CoordinateMap`
  transpose : bool, optional
     If False (the default), the result is a 2-dimensional
     ndarray with shape[1] == coordmap.ndims[1]. That is, the
     result is a list of output values.  Otherwise, the shape is
     (coordmap.ndims[1],) + coordmap.shape.
  
  Returns
  -------
  values : array
     Values of self.coordmap evaluated at np.indices(self.shape).
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code: def _evaluate(self, transpose=False):
      """
      If the coordmap has a shape (so that it can be thought of as a
      map from voxels to some output space), return the range of the
      coordmap, i.e. the value at all the voxels.
  
      Parameters
      ----------
      coordmap : `CoordinateMap`
      transpose : bool, optional
         If False (the default), the result is a 2-dimensional
         ndarray with shape[1] == coordmap.ndims[1]. That is, the
         result is a list of output values.  Otherwise, the shape is
         (coordmap.ndims[1],) + coordmap.shape.
  
      Returns
      -------
      values : array
         Values of self.coordmap evaluated at np.indices(self.shape).
      """
      indices = np.indices(self.shape).astype(
          self.coordmap.function_domain.coord_dtype
      )
      tmp_shape = indices.shape
      # reshape indices to be a sequence of coordinates
      indices.shape = (self.coordmap.ndims[0], np.prod(self.shape))
      # evaluate using coordinate map mapping
      _range = self.coordmap(indices.T)
      if transpose:
          # reconstruct np.indices format for output
          _range = _range.T
          _range.shape = (_range.shape[0],) + tmp_shape[1:]
      return _range
  
file_path: nipy/nipy/core/reference/array_coords.py
imports: import numpy
  from .coordinate_map import AffineTransform, CoordinateMap, compose, shifted_range_origin
  from .coordinate_map import product
  from .coordinate_system import CoordinateSystem
label_desc: Use image node_id 2 for calling the ArrayCoordMap obj's underlying member method code with example usage: obj._evaluate(transpose) and returns: _range