class_docstr: Domain class describing a rectangular domain
  
  Attributes:
      size (Tuple[int]): The size of the domain in absolute units.
      dx (Tuple(float)): The unit of measure
class_docstr_tok: ["Domain","class","describing","a","rectangular","domain","Attributes",":","size","(","Tuple","[","int","]",")",":","The","size","of","the","domain","in","absolute","units",".","dx","(","Tuple","(","float",")",")",":","The","unit","of","measure"]
docstr: The spatial axis of the domain
  
  Returns:
      Tuple[jnp.array]: The spatial axis of the domain
docstr_tok: ["The","spatial","axis","of","the","domain","Returns",":","Tuple","[","jnp.array","]",":","The","spatial","axis","of","the","domain"]
code: def spatial_axis(self):
      r"""The spatial axis of the domain
  
      Returns:
          Tuple[jnp.array]: The spatial axis of the domain
  
      """
  
      def _make_axis(n, delta):
          if n % 2 == 0:
              return jnp.arange(0, n) * delta - delta * n / 2
          else:
              return jnp.arange(0, n) * delta - delta * (n - 1) / 2
  
      axis = [_make_axis(n, delta) for n, delta in zip(self.N, self.dx)]
      axis = [ax - jnp.mean(ax) for ax in axis]
      return axis
  
file_path: jaxdf/jaxdf/geometry.py
imports: from functools import reduce
  from typing import Iterable
  import equinox
  import jax
  from jax import numpy
  from jax import random
  from .mods import Module
label_desc: Use image node_id 4 for calling the Domain obj's underlying member method code with example usage: obj.spatial_axis() and returns: axis, unknown, unknown