Efficiently sorting a numpy array in descending order

Question

I am surprised this specific question hasn t been asked before  but I really didn t find it on SO nor on the documentation of np sort   Say I have a random numpy array holding integers  e g    gt  temp   np random randint 1 10  10       gt  temp array  2  4  7  4  2  2  7  6  4  4     If I sort it  I get ascending order by default    gt  np sort temp  array  2  2  2  4  4  4  4  6  7  7     but I want the solution to be sorted in descending order   Now  I know I can always do   reverse order   np sort temp    -1    but is this last statement efficient  Doesn t it create a copy in ascending order  and then reverses this copy to get the result in reversed order  If this is indeed the case  is there an efficient alternative  It doesn t look like np sort accepts parameters to change the sign of the comparisons in the sort operation to get things in reverse order

User · Answer

Hello I was searching for a solution to reverse sorting a two dimensional numpy array, and I couldn't find anything that worked, but I think I have stumbled on a solution which I am uploading just in case anyone is in the same boat.

x=np.sort(array)
y=np.fliplr(x)

np.sort sorts ascending which is not what you want, but the command fliplr flips the rows left to right! Seems to work!

Hope it helps you out!

I guess it's similar to the suggest about -np.sort(-a) above but I was put off going for that by comment that it doesn't always work. Perhaps my solution won't always work either however I have tested it with a few arrays and seems to be OK.

User · Answer

Unfortunately when you have a complex array  only np sort temp    -1  works properly  The two other methods mentioned here are not effective

User · Answer

You could sort the array first  Ascending by default  and then apply np flip    https   docs scipy org doc numpy reference generated numpy flip html   FYI It works with datetime objects as well   Example       x   np array  2 3 1 0        x sort asc np sort x       print x sort asc        gt  gt  gt  array  0  1  2  3        x sort desc np flip x sort asc       print x sort desc        gt  gt  gt  array  3 2 1 0

User · Answer

gt  gt  gt  a np array  5  2  7  4  4  2  8  6  4  4     gt  gt  gt  np sort a  array  2  2  4  4  4  4  5  6  7  8     gt  gt  gt  -np sort -a  array  8  7  6  5  4  4  4  4  2  2

User · Answer

Here is a quick trick  In 3   import numpy as np In 4   temp   np random randint 1 10  10  In 5   temp Out 5   array  5  4  2  9  2  3  4  7  5  8    In 6   sorted   np sort temp  In 7   rsorted   list reversed sorted   In 8   sorted Out 8   array  2  2  3  4  4  5  5  7  8  9    In 9   rsorted Out 9    9  8  7  5  5  4  4  3  2  2

User · Answer

Be careful with dimensions  Let x    initial numpy array I   np argsort x  or I   x argsort    y   np sort x     or y   x sort   z    reverse sorted array  Full Reverse z   x I   -1   z   -np sort -x  z   np flip y    flip changed in 1 15  previous versions 1 14 required axis   Solution  pip install --upgrade numpy   First Dimension Reversed z   y   -1  z   np flipud y  z   np flip y  axis 0   Second Dimension Reversed z   y   -1     z   np fliplr y  z   np flip y  axis 1   Testing Testing on a 100  10  10 array 1000 times  Method         Time  ms  ------------- ---------- y   -1         0 126659    only in first dimension -np sort -x    0 133152 np flip y      0 121711 x I   -1       4 611778  x sort         0 024961 x argsort      0 041830 np flip x      0 002026  This is mainly due to reindexing rather than argsort    Timing code import time import numpy as np   def timeit fun  xs       t   time time       for i in range len xs       inline and map gave much worse results for x -I   5 t         fun xs i       t   time time   - t     print np round t 6    I  N   1000   100  10  10  xs   np random rand I  N  timeit lambda x  np sort x    -1   xs  timeit lambda x  -np sort -x   xs  timeit lambda x  np flip x sort     xs  timeit lambda x  x x argsort     -1    xs  timeit lambda x  x sort    xs  timeit lambda x  x argsort    xs  timeit lambda x  np flip x   xs

User · Answer

temp   -1  sort   sorts the array in place  whereas np sort temp    -1  creates a new array   In  25   temp   np random randint 1 10  10   In  26   temp Out 26   array  5  2  7  4  4  2  8  6  4  4    In  27   id temp  Out 27   139962713524944  In  28   temp   -1  sort    In  29   temp Out 29   array  8  7  6  5  4  4  4  4  2  2    In  30   id temp  Out 30   139962713524944

User · Answer

i suggest using this      np arange start index  end index  intervals    -1    for example    np arange 10  20  0 5  np arange 10  20  0 5    -1    Then your resault     19 5   19     18 5   18     17 5   17     16 5   16     15 5      15     14 5   14     13 5   13     12 5   12     11 5   11        10 5   10

User · Answer

For short arrays I suggest using np argsort   by finding the indices of the sorted negatived array  which is slightly faster than reversing the sorted array   In  37   temp   np random randint 1 10  10   In  38    timeit np sort temp    -1  100000 loops  best of 3  4 65   s per loop  In  39    timeit temp np argsort -temp   100000 loops  best of 3  3 91   s per loop

[python] Efficiently sorting a numpy array in descending order?

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