combine two double cells into 1
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i have two Double[] cells with size of 1*n; every element is has some numbers in it . like :
C1{1} = [1 2 3 4]
C2{1} = [5 2 3 7]
.
.
.
C1{n} = [1 2]
C2{n} = [4 5]
how can i have a cell like this :
C{1} = [1 2 3 4 5 7]
.
.
.
C{n} = [1 2 4 5]
i`m totally new to matlab and sorry if its already been answered , but i search a lot and couldn`t find the answer .
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Plus de réponses (3)
If you are in doubt, start with a loop:
C1 = {[1 2 3 4], [1 2]};
C2 = {[5 2 3 7], [4 5]};
C = cell(size(C1));
for iC = 1:numel(C)
C{iC} = unique([C1{iC}, C2{iC}]);
end
3 commentaires
+1 Note that the example has only the unique values (so is not just the concatenation):
C{iC} = unique([C1{iC}, C2{iC}]);
Jan
le 6 Août 2017
Thanks, Stephen. I hit the Submit button too early.
Hamid Salari
le 6 Août 2017
Star Strider
le 6 Août 2017
Modifié(e) : Star Strider
le 6 Août 2017
This works, and should work with your entire ‘C1’ and ‘C2’:
C1{1} = [1 2 3 4];
C1{2} = [1 2];
C2{1} = [5 2 3 7];
C2{2} = [4 5];
C3 = cellfun(@union, C1, C2, 'Uni',0);
C3{1} % Display Result
C3{2} % Display Result
ans =
1 2 3 4 5 7
ans =
1 2 4 5
EDIT — Added output (the ‘ans’ variables).
1 commentaire
dpb
le 6 Août 2017
Good use for UNION, SS... +1
dpb
le 6 Août 2017
That's a little towards the advanced-beginner side... :)
>> C=cellfun(@(c1,c2) unique([c1 c2]),C1,C2,'uniform',0);
>> C{:}
C =
1 2 3 4 5 7
C =
1 2 4 5
>>
The @ symbol is defining an "anonymous function", with two arguments; cellfun passes the content of its two cell array arguments to the defined function cell-by-cell and unique does what it sounds like which is to return the unique values in its argument; the [] simply concatenate the two vectors.
3 commentaires
Hamid Salari
le 6 Août 2017
Jan
le 7 Août 2017
Anonymous functions are very handy, but tend to be slow e.g. in cellfun.
dpb
le 7 Août 2017
Note Star S's use of UNION over UNIQUE, though...saves a step of the concatenation.
I've never done specific timing; where the syntax is easy I'll write the CELLFUN solution as above and only if it turns out to be a bottleneck worry about what generally would be small differences in run time. Then again, I'm not actively consulting any longer so don't in general ever have large datasets where it would ever be an issue so "caveat emptor" reigneth, methinks. Keep Jan's note in mind if you're still waiting next week for the prompt to come back... :)
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