numpy.ma.std(self, axis=None, dtype=None, out=None, ddof=0) = Compute the standard deviation along the specified axis. Returns

numpy.ma.getdata(a, subok=True)

MaskedArray.cumprod(axis=None, dtype=None, out=None)

MaskedArray.cumsum(axis=None, dtype=None, out=None)

MaskedArray.prod(axis=None, dtype=None, out=None)

numpy.ma.expand_dims(x, axis)

MaskedArray.sum(axis=None, dtype=None, out=None)

MaskedArray.transpose(*axes)

numpy.ma.zeros(shape, dtype=float, order='C') = Return a new array of given shape and type, filled with zeros.

numpy.ma.atleast_3d(*arys) = View inputs as arrays with at least three dimensions.