Calibrating Sensors: Hi does anyone know how to create a loop that will run through all of this code for multiple column vectors? I am having trouble creating a script to carry this out while taking out outliers, then running those vectors through

%Tau method 
for i=1:18
    B=variable(ampboil5,amphand14,amphand5, ampice14, ampice5, amproom14, amproom5, ampwarm14, ampwarm5,
    roseboil5, rosehand14, rosehand5, roseice14, roseice5, roseroom14, roseroom5, rosewarm14, rosewarm5);  %file, this file, this_file, data?
N=length(B);
nu=N-1;
Mx=mean(B);
Sx=std(B);
P=0.95;
tnup = sqrt(nu/betaincinv(1-P,nu/2,1/2)-nu);
xL=Mx-tnup(length(filename))*Sx;
xU=Mx+tnup(length(filename))*Sx;
%<xL and >xU outliers 
 
 
%precision uncertainty                    
al=(V*Q')/(V*V');
e=al*V-Q;
N=length(Q);
Sxy=sqrt(e*e'/(N-2));
nu=N-1;
P=0.95;
tnup=sqrt(nu/betaincinv(1-p,nu/2,1/2)-nu);
Dp=tnup*Sxy/sqrt(N);
 
%zero error
Sa0=Sxy*sqrt(V*V'/(N*(V*V')-sum(V)^2))
Dz=tnup*Sa0/sqrt(N);
 
%Sensitivity error
Sal=Sxy*sqrt(N/(N*(V/V')-sum(V)^2));
ro=max(Q);
rx=ro/al;
Ds=tnup*Sal*rx/sqrt(N);
 
%accuracy error
Da=sqrt((Dz^2)+(Ds^2))
 
%Total Calibration error
Dc=sqrt((Da^2)+(Dp^2))
 

Answer 1

[Zuber Khan]

Hi,

In order to create a loop that processes multiple column vectors, you can encapsulate your existing code within a function and then iterate over each vector you want to process.

Firstly, you need to define the column vectors outside the code block.

% Define column vectors and store in a variable.
vectors = {ampboil5, amphand14, amphand5, ampice14, ampice5, ...
               amproom14, amproom5, ampwarm14, ampwarm5, ...
               roseboil5, rosehand14, rosehand5, roseice14, ...
               roseice5, roseroom14, roseroom5, rosewarm14, rosewarm5};

Then, you can pass these vectors to a main function, for instance, calibrate_sensors as follows:

% Pass these vectors to calibrate_sensors() function to get the desired
% output
calibrate_sensors(vectors);

Lastly, you need to define the main and helper functions where you can substitute your code implementation.

% Define main and helper functions
function calibrate_sensors(vectors)    
    % Loop through each vector
    for i = 1:length(vectors)
        B = vectors{i};
        B = remove_outliers(B);
        calculate_uncertainties(B);
    end
end

function B = remove_outliers(B)
    N = length(B);
    nu = N - 1;
    Mx = mean(B);
    Sx = std(B);
    P = 0.95;
    tnup = sqrt(nu / betaincinv(1 - P, nu / 2, 1 / 2) - nu);
    xL = Mx - tnup * Sx;
    xU = Mx + tnup * Sx;
    
    % Remove outliers since <xL and >xU outliers 
    B = B(B >= xL & B <= xU);
end

function calculate_uncertainties(B)
    N = length(B);
    V = 1:N; % Example V, replace with actual values if different
    Q = B; % Assuming Q is the same as B, replace if needed
    
    al = (V * Q') / (V * V');
    e = al * V - Q;
    Sxy = sqrt(e * e' / (N - 2));
    nu = N - 1;
    P = 0.95;
    tnup = sqrt(nu / betaincinv(1 - P, nu / 2, 1 / 2) - nu);
    Dp = tnup * Sxy / sqrt(N);

    % Zero error
    Sa0 = Sxy * sqrt(V * V' / (N * (V * V') - sum(V)^2));
    Dz = tnup * Sa0 / sqrt(N);

    % Sensitivity error
    Sal = Sxy * sqrt(N / (N * (V / V') - sum(V)^2));
    ro = max(Q);
    rx = ro / al;
    Ds = tnup * Sal * rx / sqrt(N);

    % Accuracy error
    Da = sqrt((Dz^2) + (Ds^2));

    % Total Calibration error
    Dc = sqrt((Da^2) + (Dp^2));
   
end

I hope it will address your query.

Regards,

Zuber