NumPy:对矩阵的每n列求和 [英] NumPy: sum every n columns of matrix
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问题描述
我想对矩阵的每n列求和.如何在不使用for循环的情况下以简单的方式做到这一点?这就是我现在拥有的:
I'd like to sum every n columns of a matrix. How can I do that in a simple way without using a for loop? This is what I have now:
n = 3 #size of a block we need to sum over
total = 4 #total required sums
ncols = n*total
nrows = 10
x = np.array([np.arange(ncols)]*nrows)
result = np.empty((total,nrows))
for i in range(total):
result[:,i] = np.sum(x[:,n*i:n*(i+1)],axis=1)
结果将是
array([[ 3., 12., 21., 30.],
[ 3., 12., 21., 30.],
...
[ 3., 12., 21., 30.]])
如何矢量化此操作?
推荐答案
这是一种方法;首先将x
整形为3D数组,然后在最后一个轴上求和:
Here's one way; first reshape x
to a 3D array and then sum over the last axis:
>>> x.reshape(-1, 4, 3).sum(axis=2)
array([[ 3, 12, 21, 30],
[ 3, 12, 21, 30],
[ 3, 12, 21, 30],
[ 3, 12, 21, 30],
[ 3, 12, 21, 30],
[ 3, 12, 21, 30],
[ 3, 12, 21, 30],
[ 3, 12, 21, 30],
[ 3, 12, 21, 30],
[ 3, 12, 21, 30]])
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