Compacting a For Loop

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Benedict Comerford 2020-10-7

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此问题的直接链接

https://ww2.mathworks.cn/matlabcentral/answers/606716-compacting-a-for-loop

评论： Sindar 2020-10-7

For_loop.mlx

Hi all

I would love some help with compacting a for loop, i'm using it to find the smallest error in a matrix is there a way of finding the smallest value of the matrix as well as the name of the variable associated with the smallest value other then printing out a masive for loop.

Thanks Ben.

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Sindar 2020-10-7

在 MATLAB Online 中打开

post code in blocks, don't attach unless it's really long:

norm_er = 1.301;
exp_er = 9.126;
log_er = 1.301;
ray_er = 2.606;
Errors = [norm_er,exp_er,log_er,ray_er]
if norm_er<exp_er && norm_er<log_er && norm_er<ray_er
    disp('Normal distribution is best')
elseif exp_er<norm_er && exp_er<log_er && exp_er<ray_er
    disp('Exponential distribution is best')
elseif log_er<norm_er && log_er<exp_er && log_er<ray_er
    disp('Log distribution is best')
elseif ray_er<norm_er && ray_er<exp_er && ray_er<log_er
    disp('Rayleigh distribution is best')
elseif norm_er==exp_er
    disp('Normal and Exponential distributions are best')
elseif norm_er==log_er
    disp('Normal and Log distributions are best')
elseif norm_er==ray_er
    disp('Normal and Rayleigh distributions are best')
elseif exp_er==log_er
    disp('Exponential and Log distributions are best')
elseif exp_er==ray_er
    disp('Exponential and Rayleigh distributions are best')
elseif log_er==ray_er
    disp('Log and Rayleigh distributions are best')
end 

that's not a for loop
is there an actual appreciable chance that two methods will give the same error?

Benedict Comerford 2020-10-7

Hi Sindar

Sorry yeah should have said an if statement

Yes there is a strong possibility that 2 will have the same error

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Answer 1

Sindar 2020-10-7

0
链接

此回答的直接链接

https://ww2.mathworks.cn/matlabcentral/answers/606716-compacting-a-for-loop#answer_506871

编辑：Sindar 2020-10-7

在 MATLAB Online 中打开

norm_er = 1.301;
exp_er = 9.126;
log_er = 1.301;
ray_er = 2.606;
Errors = [norm_er,exp_er,log_er,ray_er];
% set a tolerance to define equal error
tol = 1e-3;
% find minimum error
min_error = min(Errors);
% find all methods with this error value
idxs = find((Errors-min_error) < tol);
error_str = ["Normal";"Exponential";"Log";"Rayleigh"];
% print based on how many errors are equal (extends to any number of distributions)
% none? that's not good
if length(idxs)==0
    error('something went wrong')
% e.g., Rayleigh distribution is best
elseif length(idxs)=1
    fprintf('%s Distribution is best\n',error_str(idxs))
elseif length(idxs)=length(Errors)
    fprintf('All Distributions are equally good\n')
% e.g., Log and Rayleigh distributions are best    
elseif length(idxs)=2
    fprintf('%s and %s Distributions are best\n',error_str(idxs))
% e.g., Log, Exponential, and Rayleigh distributions are best
else
    tmp = strjoin(error_str(idxs(1:end-1)),", ") + ", and " + error_str(idxs(end);
    fprintf('%s Distributions are best',tmp)
end