[Numpy-discussion] array sort questions

CL WU anewgene at hotpop.com
Thu Sep 18 14:04:44 CDT 2003


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
>>>>>> Numpy-discussion at lists.sourceforge.net
>>>>>> 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
>>>>> Numpy-discussion at lists.sourceforge.net
>>>>> 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
>>>> Numpy-discussion at lists.sourceforge.net
>>>> https://lists.sourceforge.net/lists/listinfo/numpy-discussion
>>>>
>>>
>>>
>>>
>>>
>>
>>
>>
>
>
>
>






More information about the Numpy-discussion mailing list