Using unique.m function on NaNs

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Can someone please clarify if the result of unique([1 nan; 1 nan],'rows') should be
a) [1 nan; 1 nan] OR b) [1 nan]
Basically, in my version of matlab (2008b), I get a) as the answer and I think it's a bug as the answer should be b). Can someone please confirm if this is a feature or an issue. My mathworks support is limited because of $$ :(

Accepted Answer

Sean de Wolski
Sean de Wolski on 17 May 2011
No. It's supposed to be a.
By definition nans are not equal to themselves so they're not equal in rows either.
isequal(nan,nan)
or
nan==nan

More Answers (3)

Jan
Jan on 17 May 2011
NaNs compared to anything replies FALSE, even NaN==NaN. This is defined by the IEEE754 conventions.
Therefore [1, NaN] compared to [1, NaN] is FALSE also. In consequence UNIQUE([[1, NaN; 1, NaN], 'rows') must reply two rows.

Matt Fig
Matt Fig on 17 May 2011
In addition to what others have said, note this horribly named function:
A = [1 nan; 1 nan];
isequalwithequalnans(A(1,:),A(2,:))
  5 Comments
Sean de Wolski
Sean de Wolski on 17 May 2011
nanisequal does too and sticks in line with: nanmean, nanmedian, nancumsum etc.
Matt Fig
Matt Fig on 17 May 2011
@Andrew, I think you would agree that there is more to a great function name that it being descriptive! How often do you name your functions, for instance:
performstatisticsonmydatathenplottheresults(A)
I just think it is a monstrosity (IMO) to have a 20 character function name, that's all. Why not, for example, use:
isequal(A,B,'nansequal') % Or similar
or a name like Sean de recommends?

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Andy
Andy on 17 May 2011
If you have some application for which you need to ignore NaNs rather than take them into account, you could replace them with some other value which is easily identifiable as non-data. For example:
A; % your data
A(isnan(A)) = Inf; % replace NaN with Inf
A = unique(A,'rows'); % unique rows, where [1,Inf] == [1,Inf]
A(isinf(A)) = NaN; % convert back to NaN
It's a little hackish. I know there are various toolbox functions, like nanmean and nanstd, which calculate other statistics of a dataset while ignoring NaNs. But there is no nanunique or nansort. Also, the work in unique is done by calling sortrows which calls a MEX file, so you can't just edit it to take NaNs into account. So the above code seems like the cleanest quick solution.
  4 Comments
Rahul Chander
Rahul Chander on 17 May 2011
I think i would need to precondition the data to deal with NaNs basically by either removing them or replacing them or interpolating. Thank you all.
Andy
Andy on 17 May 2011
@Sean de, Matt Fig is correct. I intended him to replace Inf with any "value which is easily identifiable as non-data". I was just using Inf as an example, since, for my purposes, Inf never comes up data. But Rahul should choose whatever flag value is appropriate for the application.

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