core.py 文件源码

def sum(self, axis=None, dtype=None, out=None, keepdims=np._NoValue):
        """
        Return the sum of the array elements over the given axis.

        Masked elements are set to 0 internally.

        Refer to `numpy.sum` for full documentation.

        See Also
        --------
        ndarray.sum : corresponding function for ndarrays
        numpy.sum : equivalent function

        Examples
        --------
        >>> x = np.ma.array([[1,2,3],[4,5,6],[7,8,9]], mask=[0] + [1,0]*4)
        >>> print(x)
        [[1 -- 3]
         [-- 5 --]
         [7 -- 9]]
        >>> print(x.sum())
        25
        >>> print(x.sum(axis=1))
        [4 5 16]
        >>> print(x.sum(axis=0))
        [8 5 12]
        >>> print(type(x.sum(axis=0, dtype=np.int64)[0]))
        <type 'numpy.int64'>

        """
        kwargs = {} if keepdims is np._NoValue else {'keepdims': keepdims}

        _mask = self._mask
        newmask = _check_mask_axis(_mask, axis, **kwargs)
        # No explicit output
        if out is None:
            result = self.filled(0).sum(axis, dtype=dtype, **kwargs)
            rndim = getattr(result, 'ndim', 0)
            if rndim:
                result = result.view(type(self))
                result.__setmask__(newmask)
            elif newmask:
                result = masked
            return result
        # Explicit output
        result = self.filled(0).sum(axis, dtype=dtype, out=out, **kwargs)
        if isinstance(out, MaskedArray):
            outmask = getattr(out, '_mask', nomask)
            if (outmask is nomask):
                outmask = out._mask = make_mask_none(out.shape)
            outmask.flat = newmask
        return out