def make_mask_none(newshape, dtype=None):
if dtype is None:<EOL><INDENT>result = np.zeros(newshape, dtype=MaskType)<EOL><DEDENT>else:<EOL><INDENT>result = np.zeros(newshape, dtype=make_mask_descr(dtype))<EOL><DEDENT>return result<EOL>
Return a boolean mask of the given shape, filled with False.

This function returns a boolean ndarray with all entries False, that can
be used in common mask manipulations. If a complex dtype is specified, the
type of each field is converted to a boolean type.

Parameters
----------
newshape : tuple
    A tuple indicating the shape of the mask.
dtype : {None, dtype}, optional
    If None, use a MaskType instance. Otherwise, use a new datatype with
    the same fields as `dtype`, converted to boolean types.

Returns
-------
result : ndarray
    An ndarray of appropriate shape and dtype, filled with False.

See Also
--------
make_mask : Create a boolean mask from an array.
make_mask_descr : Construct a dtype description list from a given dtype.

Examples
--------
>>> import numpy.ma as ma
>>> ma.make_mask_none((3,))
array([False, False, False], dtype=bool)

Defining a more complex dtype.

>>> dtype = np.dtype({'names':['foo', 'bar'],
                      'formats':[np.float32, np.int]})
>>> dtype
dtype([('foo', '<f4'), ('bar', '<i4')])
>>> ma.make_mask_none((3,), dtype=dtype)
array([(False, False), (False, False), (False, False)],
      dtype=[('foo', '|b1'), ('bar', '|b1')])