class_docstr: Array(array, meta=None)
  
  A subclass of np.ndarray that has a meta attribute. Get the dictionary
  that contains the meta data using ``im.meta``. Convert to a plain numpy
  array using ``np.asarray(im)``.
class_docstr_tok: ["Array","(","array",",","meta=None",")","A","subclass","of","np.ndarray","that","has","a","meta","attribute",".","Get","the","dictionary","that","contains","the","meta","data","using","``","im.meta","``",".","Convert","to","a","plain","numpy","array","using","``","np.asarray","(","im",")","``","."]
docstr: Make a 2-level deep copy of the meta dictionary.
docstr_tok: ["Make","a","2-level","deep","copy","of","the","meta","dictionary","."]
code: def _copy_meta(self, meta):
      """Make a 2-level deep copy of the meta dictionary."""
      self._meta = Dict()
      for key, val in meta.items():
          if isinstance(val, dict):
              val = Dict(val)  # Copy this level
          self._meta[key] = val
  
imports: from collections import OrderedDict
  import numpy
  import os
  import re
  import struct
  import sys
  import time
  import logging
label_desc: Use image node_id 2 for calling the Array obj's underlying member method code with example usage: obj._copy_meta(meta) without return types