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I have a numpy array like this:
import numpy as np
arr = np.array([9, 6, 3, 8, 2, 3, 3, 4, 4, 9, 5, 6, 6, 6, 6, 7, 8, 9])
And I want to get a list of indexes of the found values by groups
index_list_2 = [4 ] # index list of the element with the value 2
index_list_3 = [2, 5, 6 ]
index_list_4 = [7, 8 ]
index_list_9 = [0, 9, 17]
# [...]
The first approach that comes to my mind (thats not very pythonic):
i = 0
for x in arr:
if x == 2:
index_list_2 += [i]
if x == 3:
index_list_3 += [i]
if x == 4:
index_list_4 += [i]
if x == 9:
index_list_9 += [i]
i += 1
Which is the most efficient way to achieve this with numpy arrays?
解决方案
This should not be too slow. The array is iterated only once.
The result (ind) is a dictionary value -> list of indexes.
import numpy as np
arr = np.array([2, 3, 3, 4, 4, 9, 5, 6, 6, 6, 6, 7, 8, 9])
ind = dict()
for i, val in enumerate(arr):
ind.setdefault(val, []).append(i)
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