numpy.ma.masked_array.sum¶
- masked_array.sum(axis=None, dtype=None, out=None)[source]¶
Return the sum of the array elements over the given axis. Masked elements are set to 0 internally.
Parameters: axis : {None, -1, int}, optional
Axis along which the sum is computed. The default (axis = None) is to compute over the flattened array.
dtype : {None, dtype}, optional
Determines the type of the returned array and of the accumulator where the elements are summed. If dtype has the value None and the type of a is an integer type of precision less than the default platform integer, then the default platform integer precision is used. Otherwise, the dtype is the same as that of a.
out : {None, ndarray}, optional
Alternative output array in which to place the result. It must have the same shape and buffer length as the expected output but the type will be cast if necessary.
Returns: sum_along_axis : MaskedArray or scalar
An array with the same shape as self, with the specified axis removed. If self is a 0-d array, or if axis is None, a scalar is returned. If an output array is specified, a reference to out is returned.
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'>