numpy.cumsum(a, axis=None, dtype=None, out=None)
[source]
Return the cumulative sum of the elements along a given axis.
Parameters: |
a : array_like Input array. axis : int, optional Axis along which the cumulative sum is computed. The default (None) is to compute the cumsum over the flattened array. dtype : 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. See |
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Returns: |
cumsum_along_axis : ndarray. A new array holding the result is returned unless |
See also
Arithmetic is modular when using integer types, and no error is raised on overflow.
>>> a = np.array([[1,2,3], [4,5,6]]) >>> a array([[1, 2, 3], [4, 5, 6]]) >>> np.cumsum(a) array([ 1, 3, 6, 10, 15, 21]) >>> np.cumsum(a, dtype=float) # specifies type of output value(s) array([ 1., 3., 6., 10., 15., 21.])
>>> np.cumsum(a,axis=0) # sum over rows for each of the 3 columns array([[1, 2, 3], [5, 7, 9]]) >>> np.cumsum(a,axis=1) # sum over columns for each of the 2 rows array([[ 1, 3, 6], [ 4, 9, 15]])
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https://docs.scipy.org/doc/numpy-1.12.0/reference/generated/numpy.cumsum.html