Finding unique rows using "uniquetol" from top

9 次查看（过去 30 天）

J AI 2020-7-27

0
链接

此问题的直接链接

https://ww2.mathworks.cn/matlabcentral/answers/570970-finding-unique-rows-using-uniquetol-from-top

编辑： Bruno Luong 2020-7-27

It seems like there is no option for finding unique rows from top using uniquetol unlike unique where there is option for the argument "first". Is there a way to do this

[~,idx] = uniquetol(Q2(:,1:ns),'ByRows',true,'first') % the argument "first" picks unique rows from the top

some other way, since the "first" option is not supported by uniquetol?

Thanks!

9 个评论
显示 7更早的评论隐藏 7更早的评论

Bruno Luong 2020-7-27

编辑：Bruno Luong 2020-7-27

在 MATLAB Online 中打开

Even smaller (smallest example)

>> A = 1 + [1;0]*2^-40
A =
    1.0000
    1.0000
>> [Au,matlabidx] = uniquetol(A,1e-6,'byrows',true)
Au =
     1
matlabidx =
     2

J AI 2020-7-27

The data I was trying to work on is not random at all, rather it is from a well-known experiment in machine learning called the "Tiger example" often found in POMDP literature. Since several examples already have been provided by Bruno already, I am going to pass.

请先登录，再进行评论。

请先登录，再回答此问题。

采纳的回答

Bruno Luong 2020-7-27

0
链接

此回答的直接链接

https://ww2.mathworks.cn/matlabcentral/answers/570970-finding-unique-rows-using-uniquetol-from-top#answer_471262

编辑：Bruno Luong 2020-7-27

在 MATLAB Online 中打开

I suppose you can do something like this. I'm affraid the way UNIQUETOL and ISMEMBERTOL consider the TOL internally, and in some cases the result is not coherently match when the frontier is fuzzy. You might set 'DataScale' to 1 and control TOL to have more robust match.

Fake data

A = ceil(3*rand(1000,2));
A = A + rand(size(A))*1e-10;

Engine

[Au,idx] = uniquetol(A,1e-6,'DataScale',1,'byrows',true);
[tf,I] = ismembertol(A,Au,1e-6,'DataScale',1,'byrows',true);
if ~all(tf)
    error('incompatible tolerance');
end
firstidx = accumarray(I,(1:size(A,1))',[],@min)
if ~all(firstidx) || size(firstidx,1)~=size(Au,1)
    error('incompatible tolerance');
end

Check

A(idx,:)
A(firstidx,:)

If those matching error checking bother you, here is a way to ignore with the risk that the result might be different than UNIQUETOL alone

Au = uniquetol(A,1e-6,'DataScale',1,'byrows',true);
[tf,I] = ismembertol(A,Au,1e-6,'DataScale',1,'byrows',true);
firstidx = accumarray(I(tf),find(tf),[],@min)
Au = A(firstidx,:);

2 个评论
显示无隐藏无

J AI 2020-7-27

Thanks a lot!

Bruno Luong 2020-7-27

编辑：Bruno Luong 2020-7-27

在 MATLAB Online 中打开

Actually I was stupid; you can use the third output of UNIQUETOL, no need fot ISMEMBERTOL

[Au,matlabidx,I] = uniquetol(A, 1e-6, 'byrows', true);
firstidx = accumarray(I, (1:size(A,1))', [], @min)
% Check
norm(A(matlabidx,:)-A(firstidx,:),Inf)

请先登录，再进行评论。