sum(self, axis=None, dtype=None, out=None, keepdims=<no value>)

Masked elements are set to 0 internally.

Refer to numpy.sum for full documentation.

Return the sum of the array elements over the given axis.

See Also

numpy.ndarray.sum

corresponding function for ndarrays

numpy.sum

equivalent function

Examples

This example is valid syntax, but we were not able to check execution

>>> x = np.ma.array([[1,2,3],[4,5,6],[7,8,9]], mask=[0] + [1,0]*4)
... x
masked_array(
  data=[[1, --, 3],
        [--, 5, --],
        [7, --, 9]],
  mask=[[False,  True, False],
        [ True, False,  True],
        [False,  True, False]],
  fill_value=999999)

This example is valid syntax, but we were not able to check execution

>>> x.sum()
25

This example is valid syntax, but we were not able to check execution

>>> x.sum(axis=1)
masked_array(data=[4, 5, 16],
             mask=[False, False, False],
       fill_value=999999)

This example is valid syntax, but we were not able to check execution

>>> x.sum(axis=0)
masked_array(data=[8, 5, 12],
             mask=[False, False, False],
       fill_value=999999)

This example is valid syntax, but we were not able to check execution

>>> print(type(x.sum(axis=0, dtype=np.int64)[0]))
<class 'numpy.int64'>

See :

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GitHub : /numpy/ma/core.py#None
type: <class 'numpy.ma.core._frommethod'>
Commit: