numpy.ma.cumsum(self, axis=None, dtype=None, out=None) =
Return the cumulative sum of the elements along the given axis. The cumulative sum is calculated over the flattened array by default, otherwise over the specified 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.
Parameters: |
axis : {None, -1, int}, optional Axis along which the sum is computed. The default ( dtype : {None, dtype}, optional Type of the returned array and of the accumulator in which the elements are summed. If out : 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. |
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Returns: |
cumsum : ndarray. A new array holding the result is returned unless |
The mask is lost if out
is not a valid MaskedArray
!
Arithmetic is modular when using integer types, and no error is raised on overflow.
>>> marr = np.ma.array(np.arange(10), mask=[0,0,0,1,1,1,0,0,0,0]) >>> print(marr.cumsum()) [0 1 3 -- -- -- 9 16 24 33]
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https://docs.scipy.org/doc/numpy-1.11.0/reference/generated/numpy.ma.cumsum.html