# How to avoid omitting empty items while extracting part of a structure as an array?

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zhehao.nkd 2023 年 1 月 6 日
コメント済み: zhehao.nkd 2023 年 1 月 8 日
For example, I have a structure
s = struct;
s(1).x = 1;
s(1).name = 'John';
s(2).name = 'Sarah'; % Sarah has no x values because of some unnoticed bug
s(3).x = 3;
s(3).name = 'Robert';
I would like know who is corresponding to "x = 3", so I tried:
disp([s.x].')
1 3
answer = s([s.x].' == 3 ).name % The correct answer should be Robert
The reason is that s(2).x was omitted when converting field x into an array.
Is there any way to avoid this dangerous situation?
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Askic V 2023 年 1 月 6 日

It is because you don't compare the elements in a consistent way. For example,
s = struct;
s(1).x = 1;
s(1).name = 'John';
s(2).name = 'Sarah'; % Sarah has no x values because of some unnoticed bug
s(3).x = 3;
s(3).name = 'Robert';
[s.x].'
ans = 2×1
1 3
so you compare two element vector to a scalar (3).
The best way to avoid these, as you called it dangerous situations, is to make sure you don't have empty elements.
So correct way to implement this would be (one of many ways):
s = struct;
s(1).x = 1;
s(1).name = 'John';
s(2).name = 'Sarah'; % Sarah has no x values because of some unnoticed bug
s(3).x = 3;
s(3).name = 'Robert';
% Find empty elements and replace them with Nan
ind = cellfun(@isempty,{s(:).x});
s(ind).x = NaN;
answer = s([s.x].' == 3 ).name % The correct answer should be Robert
zhehao.nkd 2023 年 1 月 8 日
Thank you very much! Converting empty values into NaN is the key to the solution of this problem.

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### 採用された回答

Cameron 2023 年 1 月 6 日
Here's one way to do it. The problem is that it will be very hard to get Sarah out of this.
for cc = 1:length(s)
if isempty(s(cc).x)
s(cc).x = NaN;
end
end
s([s.x].' == 3 ).name
another similar way is
cc = cellfun(@isempty,{s.x});
s(cc).x = NaN;
s([s.x].' == 3 ).name

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