Menu
▾
▴
Re: [Numpy-discussion] array sort questions
|
From: CL WU <ane...@ho...> - 2003-09-18 21:00:52
|
Thanks again, Tim. It a wonderful example to show how efficient python can run if it is well written. Best, Chunlei Tim Hochberg wrote: > Hi Chunlei, > > I just realized one other thing that you should probably be aware of. > You could write a much faster version of sortrank in pure python by > doing your sorts differently. Python's built in sort is very fast, but > as soon as you start passing in comparison functions it slows down > dramatically. The trick is to arange the data you need to sort so that > you don't need an auxilliary function (know > asDecorate-Sort-Undecorate or the Schwartzian transform). Thus, the > following is almost certainly a lot faster than your original > sortrank, although probably still slower than the argsort solution. > > def sortrank(list): > index = range(len(list)) > li_a = zip(list, index) > li_a.sort() > li_b = [(li_a[i][1], i) for i in index] > li_b.sort() > return [x[1] for x in li_b] > > Regards, > > -tim > > > > > > > CL WU wrote: > >>>> I hope there is an efficient function in array level to do the same >>>> work. >>>> >>> from Numeric import * >>>> >>> a=array([5,2,3]) >>>> >>> argsort(a) >>>> array([1, 2, 0]) >>>> >>> def sortrank(list): >>>> ... n=len(list) >>>> ... li_a=[(i,list[i]) for i in range(n)] >>>> ... li_a.sort(lambda a,b:cmp(a[1],b[1])) >>>> ... li_b=[(i,li_a[i]) for i in range(n)] >>>> ... li_b.sort(lambda a,b:cmp(a[1][0],b[1][0])) >>>> ... return [x[0] for x in li_b] >>>> ... >>> sortrank(a) >>>> [2, 0, 1] >>>> >>> def sortrank2(li): >>>> ... li_sorted=li[:] >>>> ... li_sorted.sort() >>>> ... return [li_sorted.index(x) for x in li] >>>> >>> sortrank1(list(a)) >>>> [2, 0, 1] >>>> >>>> >>>> Thanks again. >>>> >>>> Chunlei >>>> >>>> Tim Hochberg wrote: >>>> >>>>> CL WU wrote: >>>>> >>>>>> Hi, group, >>>>>> I am new to numpy. I have 2 questions for array sort. >>>>>> >>>>>> 1. How to sort an array by its one column or one row? >>>>>> I know python build-in sort() can do it for list by passing >>>>>> own cmp function. but array function sort() will sort each column >>>>>> or row seperately,as I know. I don't want to convert array to >>>>>> list to sort and then convert back to array. >>>>> >>>>> >>>>> >>>>> >>>>> >>>>> >>>>> I think you want argsort plus take. For example, the following >>>>> sorts on the second column of a: >>>>> >>>>> a = array([[4,5,6], [1,2,3], [7,8,9]]) >>>>> arg = argsort(a[:,1]) >>>>> take(a, arg, 0) >>>>> >>>>>> 2. How to get the rank of a rank-0 array? The first "rank" means >>>>>> the order of each element after sorting, instead of the >>>>>> "dimension" meaning in numpy. Just like "rank()" function in >>>>>> splus. >>>>> >>>>> >>>>> >>>>> >>>>> >>>>> >>>>> If I understand you correctly, you want argsort as mentioned above. >>>>> >>>>> Regards, >>>>> >>>>> -tim >>>>> >>>>> >>>>>> >>>>>> Thank you >>>>>> >>>>>> Chunlei >>>>>> >>>>>> >>>>>> >>>>>> >>>>>> ------------------------------------------------------- >>>>>> This sf.net email is sponsored by:ThinkGeek >>>>>> Welcome to geek heaven. >>>>>> http://thinkgeek.com/sf >>>>>> _______________________________________________ >>>>>> Numpy-discussion mailing list >>>>>> Num...@li... >>>>>> https://lists.sourceforge.net/lists/listinfo/numpy-discussion >>>>>> >>>>> >>>>> >>>>> >>>>> >>>>> >>>>> ------------------------------------------------------- >>>>> This sf.net email is sponsored by:ThinkGeek >>>>> Welcome to geek heaven. >>>>> http://thinkgeek.com/sf >>>>> _______________________________________________ >>>>> Numpy-discussion mailing list >>>>> Num...@li... >>>>> https://lists.sourceforge.net/lists/listinfo/numpy-discussion >>>>> >>>> >>>> >>>> >>>> >>>> ------------------------------------------------------- >>>> This sf.net email is sponsored by:ThinkGeek >>>> Welcome to geek heaven. >>>> http://thinkgeek.com/sf >>>> _______________________________________________ >>>> Numpy-discussion mailing list >>>> Num...@li... >>>> https://lists.sourceforge.net/lists/listinfo/numpy-discussion >>>> >>> >>> >>> >>> >> >> >> > > > > |
