Magical index
To select a subset that meet certain sequence, simply by passing a specified list or array contains the desired sequence is accomplished:
import numpy as np
arr = np.empty((8,4))
for i in range(8):
arr[i] = i
print(arr)
print(arr[[4,3,0,6]])Print Results:
[[0. 0. 0. 0.]
[1. 1. 1. 1.]
[2. 2. 2. 2.]
[3. 3. 3. 3.]
[4. 4. 4. 4.]
[5. 5. 5. 5.]
[6. 6. 6. 6.]
[7. 7. 7. 7.]]
[[4. 4. 4. 4.]
[3. 3. 3. 3.]
[0. 0. 0. 0.]
[6. 6. 6. 6.]]
You can also be negative by the index. Do not write on a chestnut.
When transmitting a plurality of array index, the situation is somewhat different, this will be selected according to a one-dimensional array element corresponding to each index tuple
arr1 = np.arange(32).reshape((8,4))#重塑数组
print(arr1)
print('---------------|')
arr2 = arr1[[1,5,7,2], [0,3,1,2]]
print(arr2)Print Results:
[[ 0 1 2 3]
[ 4 5 6 7]
[ 8 9 10 11]
[12 13 14 15]
[16 17 18 19]
[20 21 22 23]
[24 25 26 27]
[28 29 30 31]]
---------------|
[ 4 23 29 10]In the above chestnuts, the elements (1,0), (5,3), (7,1), (2,2) is selected, if you do not consider the dimension, the index of the array of magical result is always one-dimensional .
Among imagine his results should not be this way, but by a subset of the rectangular area in the ranks of the matrix formed, but can also be achieved in the following way:
print(arr1[[1,5,7,2]])
print('---------------|')
print(arr1[[1,5,7,2]][:,[0,3,1,2]])Print Results:
[[ 4 5 6 7]
[20 21 22 23]
[28 29 30 31]
[ 8 9 10 11]]
---------------|
[[ 4 7 5 6]
[20 23 21 22]
[28 31 29 30]
[ 8 11 9 10]]This is the imagination of the way.
Keep in mind that different slice index magical, magical index always assign data to a new array, which means you change the new array produced no effect on the original array, and will slice his views are It is the original array