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",")","``","."]
code: def __new__(cls, array, meta=None):
      # Check
      if not isinstance(array, np.ndarray):
          raise ValueError("Array expects a numpy array.")
      if not (meta is None or isinstance(meta, dict)):
          raise ValueError("Array expects meta data to be a dict.")
      # Convert and return
      meta = meta if meta is not None else getattr(array, "meta", {})
      try:
          ob = array.view(cls)
      except AttributeError:  # pragma: no cover
          # Just return the original; no metadata on the array in Pypy!
          return array
      ob._copy_meta(meta)
      return ob
  
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 1 for calling the Array obj's underlying member method code with example usage: obj.__new__(cls, array, meta) and returns: ob, array