class_docstr: Attributes
  ----------
  _data : recarray
      Underlying data, as a record array.
  _mask : boolean array
      Mask of the records. A record is masked when all its fields are
      masked.
  _fieldmask : boolean recarray
      Record array of booleans, setting the mask of each individual field
      of each record.
  _fill_value : record
      Filling values for each field.
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docstr: Returns all the fields sharing the same fieldname base.
  
  The fieldname base is either `_data` or `_mask`.
docstr_tok: ["Returns","all","the","fields","sharing","the","same","fieldname","base",".","The","fieldname","base","is","either","`","_data","`","or","`","_mask","`","."]
code: def __getitem__(self, indx):
      """
      Returns all the fields sharing the same fieldname base.
  
      The fieldname base is either `_data` or `_mask`.
  
      """
      _localdict = self.__dict__
      _mask = ndarray.__getattribute__(self, "_mask")
      _data = ndarray.view(self, _localdict["_baseclass"])
      # We want a field
      if isinstance(indx, basestring):
          # Make sure _sharedmask is True to propagate back to _fieldmask
          # Don't use _set_mask, there are some copies being made that
          # break propagation Don't force the mask to nomask, that wreaks
          # easy masking
          obj = _data[indx].view(MaskedArray)
          obj._mask = _mask[indx]
          obj._sharedmask = True
          fval = _localdict["_fill_value"]
          if fval is not None:
              obj._fill_value = fval[indx]
          # Force to masked if the mask is True
          if not obj.ndim and obj._mask:
              return masked
          return obj
      # We want some elements.
      # First, the data.
      obj = np.array(_data[indx], copy=False).view(mrecarray)
      obj._mask = np.array(_mask[indx], copy=False).view(recarray)
      return obj
  
imports: from __future__ import division, absolute_import, print_function
  import sys
  import warnings
  import numpy
  import numpy.core.numerictypes
  from numpy.compat import basestring
  from numpy import bool_, dtype, ndarray, recarray, array
  from numpy.core.records import fromarrays, fromrecords
  import numpy.ma
  from numpy.ma import MAError, MaskedArray, masked, nomask, masked_array, getdata, getmaskarray, filled
label_desc: Use image node_id 8 for calling the MaskedRecords obj's underlying member method code with example usage: obj.__getitem__(indx) and returns: obj, obj, masked