numpy.ma.cumsum#

ma.cumsum(self, axis=None, dtype=None, out=None)[source]#

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

Masked values are set to 0 internally during the computation. However, their position is saved, and the result will be masked at the same locations.

Refer to numpy.cumsum for full documentation.

See also

numpy.ndarray.cumsum

corresponding function for ndarrays

numpy.cumsum

equivalent function

Notes

The mask is lost if out is not a valid ma.MaskedArray !

Arithmetic is modular when using integer types, and no error is raised on overflow.

Examples

Try it in your browser!

>>> import numpy as np
>>> marr = np.ma.array(np.arange(10), mask=[0,0,0,1,1,1,0,0,0,0])
>>> marr.cumsum()
masked_array(data=[0, 1, 3, --, --, --, 9, 16, 24, 33],
             mask=[False, False, False,  True,  True,  True, False, False,
                   False, False],
       fill_value=999999)

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