def masked_all(shape, dtype=float):
a = masked_array(np.empty(shape, dtype),<EOL>mask=np.ones(shape, make_mask_descr(dtype)))<EOL>return a<EOL>
Empty masked array with all elements masked.

Return an empty masked array of the given shape and dtype, where all the
data are masked.

Parameters
----------
shape : tuple
    Shape of the required MaskedArray.
dtype : dtype, optional
    Data type of the output.

Returns
-------
a : MaskedArray
    A masked array with all data masked.

See Also
--------
masked_all_like : Empty masked array modelled on an existing array.

Examples
--------
>>> import numpy.ma as ma
>>> ma.masked_all((3, 3))
masked_array(data =
 [[-- -- --]
 [-- -- --]
 [-- -- --]],
      mask =
 [[ True  True  True]
 [ True  True  True]
 [ True  True  True]],
      fill_value=1e+20)

The `dtype` parameter defines the underlying data type.

>>> a = ma.masked_all((3, 3))
>>> a.dtype
dtype('float64')
>>> a = ma.masked_all((3, 3), dtype=np.int32)
>>> a.dtype
dtype('int32')