SciPy

numpy.ma.sum

numpy.ma.sum(self, axis=None, dtype=None, out=None) = <numpy.ma.core._frommethod instance at 0x7f63b51e2f80>

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'>

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