Tim Hochberg wrote:
> Norbert Nemec wrote:
>
>> unique1d is based on ediff1d, so it really calculates many differences
>> and compares those to 0.0
>>
>> This is inefficient, even though this is hidden by the general
>> inefficiency of Python (It might be the reason for the two milliseconds,
>> though)
>>
>> What is more: subtraction works only for numbers, while the various
>> proposed versions use only comparison which works for any data type (as
>> long as it can be sorted)
>>
>>
> My first question is: why? What's the attraction in returning a sorted
> answer here? Returning an unsorted array is potentially faster,
> depending on the algorithm chosen, and sorting after the fact is
> trivial. If one was going to spend extra complexity on something, I'd
> think it would be better spent on preserving the input order.
>
> Second, some objects can be compared for equality and hashed, but not
> sorted (Python's complex number's come to mind). If one is going to
> worry about subtraction so as to keep things general, it makes sense to
> also avoid sorting as well Sasha's slick algorithm not withstanding.
>
> Third, I propose that whatever the outcome of the sorting issue, I would
> propose that unique have the same interface as the other structural
> array operations. That is:
>
> unique(anarray, axis=0):
> ...
>
> The default axis=0 is for compatibility with the other, somewhat similar
> functions. Axis=None would return the flattened, uniquified data,
> axis=# would uniquify the result along that axis.
>
Hmmm. Of course that precludes it returning an actual array for
axis!=None. That might be considered suboptimal...
-tim
> Regards,
>
> -tim
>
>
>> My own version tried to capture all possible cases that the current
>> unique captures.
>>
>> Sasha's version only works for numpy arrays and has a problem for arrays
>> with all identical entries.
>>
>> David's version only works for numpy arrays of types that can be
>> converted to float.
>>
>> I would once more propose to use my own version as given before:
>>
>> def unique(arr,sort=True):
>> if hasattr(arr,'flatten'):
>> tmp = arr.flatten()
>> tmp.sort()
>> idx = concatenate([True],tmp[1:]!=tmp[:-1])
>> return tmp[idx]
>> else: # for compatibility:
>> set = {}
>> for item in inseq:
>> set[item] = None
>> if sort:
>> return asarray(sorted(set.keys()))
>> else:
>> return asarray(set.keys())
>>
>>
>> Greetings,
>> Norbert
>>
>>
>>
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>>
>>
>
>
>
>
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