问题
I have an m x n numpy array arr, and for each column of arr, I have a given range of rows that I want to access.
I have an n x 1 array vec that describes when this range starts.
The range has some constant duration d.
How can I extract this d x n array of interest efficiently?
Can this be done by clever slicing?
My initial thought was to try something like:
arr = np.tile(np.arange(10),(4,1)).T
vec = np.array([3,4,5,4])
d = 3
vec_2 = vec+d
out = arr[vec:vec2,np.arange(n)]
But this gives the following error:
TypeError: only integer scalar arrays can be converted to a scalar index
The desired output would be the following array:
array([[3, 4, 5, 4],
[4, 5, 6, 5],
[5, 6, 7, 6],
[6, 7, 8, 7])
I could loop over d, but performance is important for this piece of code so I would prefer to vectorize it.
回答1:
In [489]: arr=np.arange(24).reshape(6,4)
In [490]: vec=np.array([0,2,1,3])
Taking advantage of the recent expansion of linspace to generate several arrays:
In [493]: x = np.linspace(vec,vec+2,3).astype(int)
In [494]: x
Out[494]:
array([[0, 2, 1, 3],
[1, 3, 2, 4],
[2, 4, 3, 5]])
In [495]: arr[x, np.arange(4)]
Out[495]:
array([[ 0, 9, 6, 15],
[ 4, 13, 10, 19],
[ 8, 17, 14, 23]])
the column iteration approach:
In [498]: np.stack([arr[i:j,k] for k,(i,j) in enumerate(zip(vec,vec+3))],1)
Out[498]:
array([[ 0, 9, 6, 15],
[ 4, 13, 10, 19],
[ 8, 17, 14, 23]])
来源：https://stackoverflow.com/questions/59914256/slicing-a-different-range-at-each-index-of-a-multidimensional-numpy-array