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numpy.cumsum(a, axis=None, dtype=None, out=None)
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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
dtype
is not specified, it defaults to the dtype ofa
, unlessa
has an integer dtype with a precision less than that of the default platform integer. In that case, the default platform integer is used.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
doc.ufuncs
(Section ?Output arguments?) for more details.Returns: cumsum_along_axis : ndarray.
A new array holding the result is returned unless
out
is specified, in which case a reference toout
is returned. The result has the same size asa
, and the same shape asa
ifaxis
is not None ora
is a 1-d array.See also
Notes
Arithmetic is modular when using integer types, and no error is raised on overflow.
Examples
>>> 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]])
numpy.cumsum()
2017-01-10 18:13:35
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