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# numpy.ma.resize

`numpy.ma.``resize`(x, new_shape)

  Return a new masked array with the specified size and shape.

  This is the masked equivalent of the `numpy.resize` function. The new array is filled with repeated copies of x (in the order that the data are stored in memory). If x is masked, the new array will be masked, and the new mask will be a repetition of the old one.

  See also

  `numpy.resize`
    Equivalent function in the top level NumPy module.

  Examples

      >>> import numpy.ma as ma
      >>> a = ma.array([[1, 2] ,[3, 4]])
      >>> a[0, 1] = ma.masked
      >>> a
      masked_array(data =
       [[1 --]
       [3 4]],
                   mask =
       [[False  True]
       [False False]],
             fill_value = 999999)
      >>> np.resize(a, (3, 3))
      array([[1, 2, 3],
             [4, 1, 2],
             [3, 4, 1]])
      >>> ma.resize(a, (3, 3))
      masked_array(data =
       [[1 -- 3]
       [4 1 --]
       [3 4 1]],
                   mask =
       [[False  True False]
       [False False  True]
       [False False False]],
             fill_value = 999999)

  A MaskedArray is always returned, regardless of the input type.

      >>> a = np.array([[1, 2] ,[3, 4]])
      >>> ma.resize(a, (3, 3))
      masked_array(data =
       [[1 2 3]
       [4 1 2]
       [3 4 1]],
                   mask =
       False,
             fill_value = 999999)

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