I'm new to numpy, so I might be missing something obviuous here.
The following small argsort() test script gives strange results. Any directions ?
import numpy as np
a = np.array([[3, 5, 6, 4, 1] , [2, 7 ,4 ,1 , 2] , [8, 6, 7, 2, 1]])
print a
print a.argsort(axis=0)
print a.argsort(axis=1)
output:
[[3 5 6 4 1]
[2 7 4 1 2]
[8 6 7 2 1]]
[[1 0 1 1 0] # bad 4th & 5th columns ?
[0 2 0 2 2]
[2 1 2 0 1]]
[[4 0 3 1 2] # what's going on here ?
[3 0 4 2 1]
[4 3 1 2 0]]
As others have indicated this method is working correctly, so in order to provide an answer here is an explanation of how .argsort() works. a.argsort returns the indices (not values) in order that would sort the array along the specified axis.
In your example
a = np.array([[3, 5, 6, 4, 1] , [2, 7 ,4 ,1 , 2] , [8, 6, 7, 2, 1]])
print a
print a.argsort(axis=0)
returns
[[3 5 6 4 1]
[2 7 4 1 2]
[8 6 7 2 1]]
[[1 0 1 1 0]
[0 2 0 2 2]
[2 1 2 0 1]]
because along
[[3 ...
[2 ...
[8 ...
2 is the smallest value. Therefore the current index of 2 (which is 0) takes the first position along this axis in the matrix returned by argsort(). The second smallest value is 3 at index 0, therefore the second position along this axis in the returned matrix will be 0. Finally, the largest element is 2 which occurs at index 2 along the 0 axis, so the final element of the returned matrix will be 2. Thus:
[[1 ...
[0 ...
[2 ...
the same process is repeated along other 4 sequences along axis 0:
[[...5 ...] [[...0 ...]
[...7 ...] becomes ----> [... 2 ...]
[...6 ...]] [... 1 ...]]
[[...6 ...] [[...1 ...]
[...4 ...] becomes ----> [... 0 ...]
[...7 ...]] [... 2 ...]]
[[...4 ...] [[...1 ...]
[...1 ...] becomes ----> [... 2 ...]
[...2 ...]] [... 0 ...]]
[[...1] [[...0]
[...2] becomes ----> [... 2]
[...1]] [... 1]]
changing the axis to from 0 to 1, results in this same process being applied along sequences in the 1st axis:
[[3 5 6 4 1 becomes ----> [[4 0 3 1 2
again because the smallest element is 1 which is at index 4, then 3 at index 0, then 4 at index 3, 5 at index 1 and finally 6 is the largest at index 2.
As before this process is repeated across each of
[2 7 4 1 2] ----> [3 0 4 2 1]
[8 6 7 2 1] ----> [4 3 1 2 0]
giving
[[4 0 3 1 2]
[3 0 4 2 1]
[4 3 1 2 0]]
This actually returns a sorted array, whose elements, rather than the element of the array we want to sort, are the index of that element.
This says the first element in our sorted array would be the element whose index is '1', which in turn is '0'.
"bad 4th & 5th columns"?np.argsortstate :"Returns the indices that would sort an array.". So,argsortgives us the indices which when indexed into the input would give us the sorted version.