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.
class_docstr_tok: ["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","."]
docstr: Returns a view of the mrecarray.
docstr_tok: ["Returns","a","view","of","the","mrecarray","."]
code: def view(self, dtype=None, type=None):
      """
      Returns a view of the mrecarray.
  
      """
      # OK, basic copy-paste from MaskedArray.view.
      if dtype is None:
          if type is None:
              output = ndarray.view(self)
          else:
              output = ndarray.view(self, type)
      # Here again.
      elif type is None:
          try:
              if issubclass(dtype, ndarray):
                  output = ndarray.view(self, dtype)
              else:
                  output = ndarray.view(self, dtype)
          # OK, there's the change
          except TypeError:
              dtype = np.dtype(dtype)
              # we need to revert to MaskedArray, but keeping the possibility
              # of subclasses (eg, TimeSeriesRecords), so we'll force a type
              # set to the first parent
              if dtype.fields is None:
                  basetype = self.__class__.__bases__[0]
                  output = self.__array__().view(dtype, basetype)
                  output._update_from(self)
              else:
                  output = ndarray.view(self, dtype)
              output._fill_value = None
      else:
          output = ndarray.view(self, dtype, type)
      # Update the mask, just like in MaskedArray.view
      if getattr(output, "_mask", nomask) is not nomask:
          mdtype = ma.make_mask_descr(output.dtype)
          output._mask = self._mask.view(mdtype, ndarray)
          output._mask.shape = output.shape
      return output
  
imports: from numpy.ma import MAError, MaskedArray, masked, nomask, masked_array, getdata, getmaskarray, filled
  import numpy.ma
  import warnings
  import numpy
  from numpy import bool_, dtype, ndarray, recarray, array
  from numpy.core.records import fromarrays, fromrecords
label_desc: Use image node_id 12 for calling the MaskedRecords obj's underlying member method code with example usage: obj.view(dtype, type) and returns: output