numpy.ma.soften_mask(self) = Force the mask to soft. Whether the mask of a masked array is hard or soft is determined

numpy.ma.cumprod(self, axis=None, dtype=None, out=None) = Return the cumulative product of the elements along the given axis

numpy.ma.frombuffer(buffer, dtype=float, count=-1, offset=0) = Interpret a buffer as a 1-dimensional array.

MaskedArray.unshare_mask()

MaskedArray.std(axis=None, dtype=None, out=None, ddof=0)

MaskedArray.sort(axis=-1, kind='quicksort', order=None, endwith=True, fill_value=None)

MaskedArray.filled(fill_value=None)

numpy.ma.transpose(a, axes=None)

MaskedArray.all(axis=None, out=None)

numpy.ma.power(a, b, third=None)