python numpy sun() 的axis用法
python 数学计算模块
numpy.sum()的axis参数， 英文解释
None or int or tuple of ints, optional
Axis or axes along which a sum is performed. The default, axis=None, will sum all of the elements of the input array. If axis is negative it counts from the last to the first axis.
New in version 1.7.0.
If axis is a tuple of ints, a sum is performed on all of the axes specified in the tuple instead of a single axis or all the axes as before.
不过怎么感觉怎么看都不太明白这里的axis和axes是啥意思， 不是学数学的，真实太吃亏了。后悔当初线性代数没有好好学
自己好好总结一些，自己来理解吧。
axis参数可以传一个整数，也可以传一个矩阵。传整数是对应维度内所有元素相加， 比如：axis=0， 既0维里面所有元素相加， 这个可借鉴numpy.shape()方法中给出的结果
例子：
>>> z
array([[[[ 1, 2, 3, 4]],
[[ 1, 2, 3, 4]],
[[ 1, 2, 3, 4]]],
[[[ 7, 8, 9, 10]],
[[ 7, 8, 9, 10]],
[[ 7, 8, 9, 10]]],
[[[13, 14, 15, 16]],
[[13, 14, 15, 16]],
[[13, 14, 15, 16]]],
[[[19, 20, 21, 22]],
[[19, 20, 21, 22]],
[[19, 20, 21, 22]]],
[[[25, 26, 27, 28]],
[[25, 26, 27, 28]],
[[25, 26, 27, 28]]],
[[[31, 32, 33, 34]],
[[31, 32, 33, 34]],
[[31, 32, 33, 34]]],
[[[ 1, 2, 3, 4]],
[[ 1, 2, 3, 4]],
[[ 1, 2, 3, 4]]],
[[[ 7, 8, 9, 10]],
[[ 7, 8, 9, 10]],
[[ 7, 8, 9, 10]]],
[[[13, 14, 15, 16]],
[[13, 14, 15, 16]],
[[13, 14, 15, 16]]],
[[[19, 20, 21, 22]],
[[19, 20, 21, 22]],
[[19, 20, 21, 22]]],
[[[25, 26, 27, 28]],
[[25, 26, 27, 28]],
[[25, 26, 27, 28]]],
[[[31, 32, 33, 34]],
[[31, 32, 33, 34]],
[[31, 32, 33, 34]]]])
>>> np.sum(z, axis=0)
array([[[192, 204, 216, 228]],
[[192, 204, 216, 228]],
[[192, 204, 216, 228]]])
>>> np.sum(z, axis=1)
array([[[ 3, 6, 9, 12]],
[[ 21, 24, 27, 30]],
[[ 39, 42, 45, 48]],
[[ 57, 60, 63, 66]],
[[ 75, 78, 81, 84]],
[[ 93, 96, 99, 102]],
[[ 3, 6, 9, 12]],
[[ 21, 24, 27, 30]],
[[ 39, 42, 45, 48]],
[[ 57, 60, 63, 66]],
[[ 75, 78, 81, 84]],
[[ 93, 96, 99, 102]]])
>>> np.sum(z, axis=2)
array([[[ 1, 2, 3, 4],
[ 1, 2, 3, 4],
[ 1, 2, 3, 4]],
[[ 7, 8, 9, 10],
[ 7, 8, 9, 10],
[ 7, 8, 9, 10]],
[[13, 14, 15, 16],
[13, 14, 15, 16],
[13, 14, 15, 16]],
[[19, 20, 21, 22],
[19, 20, 21, 22],
[19, 20, 21, 22]],
[[25, 26, 27, 28],
[25, 26, 27, 28],
[25, 26, 27, 28]],
[[31, 32, 33, 34],
[31, 32, 33, 34],
[31, 32, 33, 34]],
[[ 1, 2, 3, 4],
[ 1, 2, 3, 4],
[ 1, 2, 3, 4]],
[[ 7, 8, 9, 10],
[ 7, 8, 9, 10],
[ 7, 8, 9, 10]],
[[13, 14, 15, 16],
[13, 14, 15, 16],
[13, 14, 15, 16]],
[[19, 20, 21, 22],
[19, 20, 21, 22],
[19, 20, 21, 22]],
[[25, 26, 27, 28],
[25, 26, 27, 28],
[25, 26, 27, 28]],
[[31, 32, 33, 34],
[31, 32, 33, 34],
[31, 32, 33, 34]]])
>>> np.sum(z, axis=3)
array([[[ 10],
[ 10],
[ 10]],
[[ 34],
[ 34],
[ 34]],