Looping elseif conditions to process .csv data

Question: I have bulk of data for nodes 4-12. I would like to allocate lines from a .csv file to specific arrays 4-12 based on the node# which appears in column 1 of the .csv. The .csv file has 8 columns in all. Looking at my code below, I must type out each elseif condition manually for the conditions M(i,1)==3 all the way until M(i,1)==12. Is there a way to loop the elseif for values from M(i,1)==3, M(i,1)==4,...,M(i,1)==12 without causing a ruckus? I believe I need another layer of loops to do so.

Prospective Code :

M = csvread(fileName,1,0);
counter = [zeros(1,16)];    % [zeros(2,17)] = [0,0,0,0,0,0,0,0,0,0,0,0,0,0] == 1x16 matrice of zeros
Node = zeros(1,16);         % initializes node variables... Node(1)=0, Node(2)=0,...,Node(16)=0.

for i = 1 : size(M,1)
    if M(i,1)==2                                % if element in matrix M at row i, col 1 = 2
        counter(M(i,1)) = counter(M(i,1))+1;    % M(i,1)=2, so counter(2)=counter(2)+1
        Node{M(i,1)}(counter(M(i,1)),i:8) = M(i,1:8);
    elseif M(i,1)==3
        counter(M(i,1)) = counter(M(i,1))+1;
        Node{M(i,1)}(counter(M(i,1)),i:8) = M(i,1:8);
    elseif M(i,1)==4
        counter(M(i,1)) = counter(M(i,1))+1;
        Node{M(i,1)}(counter(M(i,1)),i:8) = M(i,1:8);
    elseif M(i,1)==5
        counter(M(i,1)) = counter(M(i,1))+1;
        Node{M(i,1)}(counter(M(i,1)),i:8) = M(i,1:8);
    elseif M(i,1)==6
        counter(M(i,1)) = counter(M(i,1))+1;
        Node{M(i,1)}(counter(M(i,1)),i:8) = M(i,1:8);
    elseif M(i,1)==7
        counter(M(i,1)) = counter(M(i,1))+1;
        Node{M(i,1)}(counter(M(i,1)),i:8) = M(i,1:8);
    elseif M(i,1)==8
        counter(M(i,1)) = counter(M(i,1))+1;
        Node{M(i,1)}(counter(M(i,1)),i:8) = M(i,1:8);
    elseif M(i,1)==9
        counter(M(i,1)) = counter(M(i,1))+1;
        Node{M(i,1)}(counter(M(i,1)),i:8) = M(i,1:8);
    elseif M(i,1)==10
        counter(M(i,1)) = counter(M(i,1))+1;
        Node{M(i,1)}(counter(M(i,1)),i:8) = M(i,1:8);
    elseif M(i,1)==11
        counter(M(i,1)) = counter(M(i,1))+1;
        Node{M(i,1)}(counter(M(i,1)),i:8) = M(i,1:8);
    elseif M(i,1)==12
        counter(M(i,1)) = counter(M(i,1))+1;
        Node{M(i,1)}(counter(M(i,1)),i:8) = M(i,1:8);
    end
end

[dpb]

That breaks my head to try to decipher what you're actually trying to do here, sorry...

Show a section of the input file and describe how you wish to arrange it; a small example of expected output never hurts in that regard.

More than likely it's just some logical addressing, but have to figure out what is the end result wanted first.

[Andy]

The code under each condition of the if / elseif statement is the same, so why do you need the if/else check at all?

[Guillaume]

@Mathieu, as you suspect there's a much better way of doing whatever you're trying to do. Whenever something is repetitive, the computer should be doing that task for you.

Like dpb, my eyes glaze over when I see so many elseif. Typically, elseif can be replaced by array lookup. But as Andy pointed out, there's actually no difference between any of the conditions so I suspect that what you've written is not even what you want to do.

So, please explain (with examples preferably) what you want to do.

[Bobby Huxford]

I think the above comments are right in that the if/elseif statements may not be needed at all. The code below shows a simple enough way to nest an if statement, if that helps at all. I couldn't really understand your problem fully but this might help.

for i = 1 : size(M,1) 
    for j = 2 : 12
        if M(i,1)==j                                % if element in matrix M at row i, col 1 = 2
            counter(M(i,1)) = counter(M(i,1))+1;     % M(i,1)=2, so counter(2)=counter(2)+1 
            Node{M(i,1)}(counter(M(i,1)),i:8) = M(i,1:8);
        end
    end
end

[Guillaume]

Well, as I said, I suspect there's an issue with the original code and it meant to do something different in each branch. It's unclear what though.

Note that looping to find if something is member of a set is also not the way to go. You can use set membership functions such as ismember instead. As for building histograms, there's already functions for that: histcounts and co.

[Mathieu Enger]

Firstly, thank you all for the assistance. I am just going to show you all of my cards. Here is my real full (Old) code. It is bulky but it works. I am trying to limit my repetition throughout using loops and/or array lookup. What it does is organize the data from 12 sensors into a arrays according each sensor's #. Then it plots the CO2 ppm over time and then calculates line of best fit/R^2. Then the CO2 flux is found in mg/m^2.hour. Finally all the data is reshown in tables according to node #. The .m file is connected and example of csv file that it processes is also attatched...

function [Node4,Node5,Node6,Node7,Node8,Node9,Node10,Node11,Node12] = prodataAllCorrectUnits(filename)
%Takes all data recorded by sensor and tables it

%-----------------------------------------------------------------------------------------
M = csvread(filename,1,0);
%-----------------------------------------------------------------------------------------

counter = [0,0,0,0,0,0,0,0,0];
Node4= 0;
Node5= 0;
Node6= 0;
Node7= 0;
Node8= 0;
Node9= 0;
Node10= 0;
Node11= 0;
Node12= 0;
%--------------------------------------------------------------------------
for i = 1:size(M,1)
    if M(i,3)<=0
       M(i,3) = NaN;
    end
end 

for i = size(M,1):-1:1
    if isnan(M(i,3))
       M(i,:) = [];    
    end
end 
%--------------------------------------------------------------------------
for i = 1 : size(M,1)
    % NODE 4------counter 1---------------------------------
    if M(i,1)==4  % column 1 is Node #
        counter(1) = counter(1)+1;
        Node4(counter(1),1) = 4;        % extract element in row counter(1), column 1
        Node4(counter(1),2) = M(i,2);       % column 2 is time (secs)
        Node4(counter(1),3) = M(i,3);       % column 3 is volume (in^3)
        Node4(counter(1),4) = M(i,4);       % column 4 is CO2 (ppm)
        Node4(counter(1),5) = M(i,5);       % column 5 is Temp 1 (C)
        Node4(counter(1),6) = M(i,6);       % column 6 is Humidity (%)
        Node4(counter(1),7) = M(i,7);       % column 7 is Temp 2 (C)    
        Node4(counter(1),8) = M(i,8);       % column 8 is pressure (kPa)      
   % NODE 5---counter 2------------------------------------
    elseif M(i,1)==5
        counter(2) = counter(2)+1;
        Node5(counter(2),1) = 5;
        Node5(counter(2),2) = M(i,2);
        Node5(counter(2),3) = M(i,3);
        Node5(counter(2),4) = M(i,4);
        Node5(counter(2),5) = M(i,5);
        Node5(counter(2),6) = M(i,6);       % column 6 is Humidity (%)
        Node5(counter(2),7) = M(i,7);       % column 7 is Temp 2 (C)    
        Node5(counter(2),8) = M(i,8);       % column 8 is pressure (kPa)    
    % NODE 6---counter 3-----------------------------------    
    elseif M(i,1)==6
    
        counter(3) = counter(3) +1;
        Node6(counter(3),1) = 6;
        Node6(counter(3),2) = M(i,2);
        Node6(counter(3),3) = M(i,3);
        Node6(counter(3),4) = M(i,4);
        Node6(counter(3),5) = M(i,5);
        Node6(counter(3),6) = M(i,6);       % column 6 is Humidity (%)
        Node6(counter(3),7) = M(i,7);       % column 7 is Temp 2 (C)    
        Node6(counter(3),8) = M(i,8);       % column 8 is pressure (kPa)    
     % NODE 7---counter 4------------------------------------    
    elseif M(i,1)==7
        counter(4) = counter(4) +1;
        Node7(counter(4),1) = 7;
        Node7(counter(4),2) = M(i,2);
        Node7(counter(4),3) = M(i,3);
        Node7(counter(4),4) = M(i,4);
        Node7(counter(4),5) = M(i,5);
        Node7(counter(4),6) = M(i,6);       % column 6 is Humidity (%)
        Node7(counter(4),7) = M(i,7);       % column 7 is Temp 2 (C)    
        Node7(counter(4),8) = M(i,8);       % column 8 is pressure (kPa)    
       % NODE 8---counter 5------------------------------------  
    elseif M(i,1)==8
    %----------CONTINUE REDOING COUNTER
    %HERE--------------------------------
        counter(5) = counter(5) +1;
        Node8(counter(5),1) = 8;
        Node8(counter(5),2) = M(i,2);
        Node8(counter(5),3) = M(i,3);
        Node8(counter(5),4) = M(i,4);
        Node8(counter(5),5) = M(i,5);
        Node8(counter(5),6) = M(i,6);       % column 6 is Humidity (%)
        Node8(counter(5),7) = M(i,7);       % column 7 is Temp 2 (C)    
        Node8(counter(5),8) = M(i,8);       % column 8 is pressure (kPa)    
     % NODE 9-----counter 6----------------------------------  
    elseif M(i,1)==9
    
        counter(6) = counter(6) +1;
        Node9(counter(6),1) = 9;
        Node9(counter(6),2) = M(i,2);
        Node9(counter(6),3) = M(i,3);
        Node9(counter(6),4) = M(i,4);
        Node9(counter(6),5) = M(i,5);
        Node9(counter(6),6) = M(i,6);       % column 6 is Humidity (%)
        Node9(counter(6),7) = M(i,7);       % column 7 is Temp 2 (C)    
        Node9(counter(6),8) = M(i,8);       % column 8 is pressure (kPa)    
    % NODE 10-------counter 7--------------------------------    
    elseif M(i,1)==10
        counter(7) = counter(7) +1;
        Node10(counter(7),1) = 10;
        Node10(counter(7),2) = M(i,2);
        Node10(counter(7),3) = M(i,3);
        Node10(counter(7),4) = M(i,4);
        Node10(counter(7),5) = M(i,5);
        Node10(counter(7),6) = M(i,6);       % column 6 is Humidity (%)
        Node10(counter(7),7) = M(i,7);       % column 7 is Temp 2 (C)    
        Node10(counter(7),8) = M(i,8);       % column 8 is pressure (kPa)    
    % NODE 11-------counter 8--------------------------------    
    elseif M(i,1)==11 
        counter(8) = counter(8) +1;
        Node11(counter(8),1) = 11;
        Node11(counter(8),2) = M(i,2);
        Node11(counter(8),3) = M(i,3);
        Node11(counter(8),4) = M(i,4);
        Node11(counter(8),5) = M(i,5);
        Node11(counter(8),6) = M(i,6);       % column 6 is Humidity (%)
        Node11(counter(8),7) = M(i,7);       % column 7 is Temp 2 (C)    
        Node11(counter(8),8) = M(i,8);       % column 8 is pressure (kPa)
     % NODE 12------counter 9---------------------------------   
    elseif M(i,1)==12
        counter(9) = counter(9) +1;
        Node12(counter(9),1) = 12;
        Node12(counter(9),2) = M(i,2);
        Node12(counter(9),3) = M(i,3);
        Node12(counter(9),4) = M(i,4);
        Node12(counter(9),5) = M(i,5);
        Node12(counter(9),6) = M(i,6);       % column 6 is Humidity (%)
        Node12(counter(9),7) = M(i,7);       % column 7 is Temp 2 (C)    
        Node12(counter(9),8) = M(i,8);       % column 8 is pressure (kPa)        
    end    
end
%--------------------------------------------------------------------------

        
        A = table(Node4);
        Node4 = unique(A);
        Node4 = table2array(Node4); 
        CO2Conversion4 = 0.0409*44.01*Node4(:,[4]);
        VolumeColumn4 = Node4(:,[3]);
        VolColMean4 = mean(VolumeColumn4);                  % Find mean volume of each node in in^3
      
        
         A = table(Node5);
        Node5 = unique(A);
        Node5 = table2array(Node5);
        CO2Conversion5 = 0.0409*44.01*Node5(:,[4]);
        VolumeColumn5 = Node5(:,[3]);
        VolColMean5 = mean(VolumeColumn5);
      
        
        
        A = table(Node6);
        Node6 = unique(A);
        Node6 = table2array(Node6);
        CO2Conversion6 = 0.0409*44.01*Node6(:,[4]);
        VolumeColumn6 = Node6(:,[3]);
        VolColMean6 = mean(VolumeColumn6);
        
        
        A = table(Node7);
        Node7=unique(A);
        Node7 = table2array(Node7);
        CO2Conversion7 = 0.0409*44.01*Node7(:,[4]);
        VolumeColumn7 = Node7(:,[3]);
        VolColMean7 = mean(VolumeColumn7);
        
        A = table(Node8);
        Node8=unique(A);
        Node8 = table2array(Node8);
        CO2Conversion8 = 0.0409*44.01*Node8(:,[4]);
        VolumeColumn8 = Node8(:,[3]);
        VolColMean8 = mean(VolumeColumn8);
        
        
         A = table(Node9);
        Node9 = unique(A);
        Node9 = table2array(Node9);
        CO2Conversion9 = 0.0409*44.01*Node9(:,[4]);
        VolumeColumn9 = Node9(:,[3]);
        VolColMean9 = mean(VolumeColumn9);
        
        
        A = table(Node10);
        Node10 = unique(A);
        Node10 = table2array(Node10);
        CO2Conversion10 = 0.0409*44.01*Node10(:,[4]);
        VolumeColumn10 = Node10(:,[3]);
        VolColMean10 = mean(VolumeColumn10);
       
        
        A = table(Node11);
        Node11 = unique(A);
        Node11 = table2array(Node11);
        CO2Conversion11 = 0.0409*44.01*Node11(:,[4]);
        VolumeColumn11 = Node11(:,[3]);
        VolColMean11 = mean(VolumeColumn11);
        
        A = table(Node12);
        Node12 = unique(A);
        Node12 = table2array(Node12);
        CO2Conversion12 = 0.0409*44.01*Node12(:,[4]);       
        VolumeColumn12 = Node12(:,[3]);
        VolColMean12 = mean(VolumeColumn12);
        
      
        Permin4 = (Node4(:,[2]))/60;
        Perhour4 = (Permin4)/60;
          Permin5 = (Node5(:,[2]))/60;
          Perhour5 = (Permin5)/60;
        Permin6 = (Node6(:,[2]))/60;
        Perhour6= (Permin6)/60; 
          Permin7 = (Node7(:,[2]))/60;
          Perhour7 = (Permin7)/60;
        Permin8 = (Node8(:,[2]))/60;
        Perhour8 = (Permin8)/60;
          Permin9 = (Node9(:,[2]))/60;
          Perhour9 = (Permin9)/60;
        Permin10 = (Node10(:,[2]))/60;
        Perhour10 = (Permin10)/60;
          Permin11 = (Node11(:,[2]))/60;
          Perhour11 = (Permin11)/60;
        Permin12 = (Node12(:,[2]))/60;
        Perhour12 = (Permin12)/60;
        
        
      Height4 = VolumeColumn4/(pi*4);             
      Height5 = VolumeColumn5/(pi*4);
      Height6 = VolumeColumn6/(pi*4);
      Height7 = VolumeColumn7/(pi*4);
      Height8 = VolumeColumn8/(pi*4);
      Height9 = VolumeColumn9/(pi*4);
      Height10 = VolumeColumn10/(pi*4);
      Height11= VolumeColumn11/(pi*4);
      Height12 = VolumeColumn12/(pi*4);
        
        HeightMean4 = (VolColMean4/(pi*4))*0.0254;  % volcolmean=in^3. pi*r^2 where r=2in.  
        HeightMean5= (VolColMean5/(pi*4))*0.0254;    %converting in to m = in*0.0254
        HeightMean6 = (VolColMean6/(pi*4))*0.0254;
        HeightMean7 = (VolColMean7/(pi*4))*0.0254;
        HeightMean8 = (VolColMean8/(pi*4))*0.0254;
        HeightMean9 = (VolColMean9/(pi*4))*0.0254;
        HeightMean10 = (VolColMean10/(pi*4))*0.0254;
        HeightMean11 = (VolColMean11/(pi*4))*0.0254;
        HeightMean12 = (VolColMean12/(pi*4))*0.0254;
        
        
   %Tables---------------------------------------     
    
   
   

   %-------R values--------------------
% R4 = corrcoef(Perhour4,CO2Conversion4) ;
% R4squared=R4*(2)^2 ;
% R5= corrcoef(Perhour5,CO2Conversion5) ;
% R5squared=R5*(2)^2 ;
% R6 = corrcoef(Perhour6,CO2Conversion6) ;
% R6squared=R6*(2)^2 ;
% R7 = corrcoef(Perhour7,CO2Conversion7) ;
% R7squared=R7*(2)^2;
% R8 = corrcoef(Perhour8,CO2Conversion8) ;
% R8squared=R8*(2)^2 ;
% R9 = corrcoef(Perhour9,CO2Conversion9) ;
% R9squared=R9*(2)^2 ;
% R10 = corrcoef(Perhour10,CO2Conversion10) ;
% R10squared=R10*(2)^2 ;
% R11 = corrcoef(Perhour11,CO2Conversion11) ;
% R11squared=R11*(2)^2 ;
% R12 = corrcoef(Perhour12,CO2Conversion12) ;
% R12squared=R12*(2)^2         ;
 %Graphing----------------------------------------------------------------------------------------------------------

figure(1)
set(gcf, 'Position', get(0,'Screensize'));
subplot(1,3,1)
scatter(Perhour4,CO2Conversion4)
md4 = fitlm(Perhour4,CO2Conversion4);  % fit linear regression model   
md4.Rsquared.Ordinary  ;
P4 = polyfit(Perhour4,CO2Conversion4,1);
    slope4 = P4(1);
    intercept4 = P4(2);
    yfit4 = P4(1)*Perhour4+P4(2);   % P4(1) is the slope and P(2) is the intercept.
    hold on;
    plot (Perhour4, yfit4, 'r-.')
    legend(sprintf('R^2=%.3f',md4.Rsquared.Ordinary),sprintf('y=%.2f*x+%.2f', slope4, intercept4));


title('Location A, Node 4 CO2 Emissions')
xlabel('Time hours')
ylabel('CO2 Concentration mgm3')

subplot (1,3,2)
scatter(Perhour5,CO2Conversion5)
md5 = fitlm(Perhour5,CO2Conversion5);  % fit linear regression model   
md5.Rsquared.Ordinary;
P5 = polyfit(Perhour5,CO2Conversion5,1);
    slope5 = P5(1);
    intercept5 = P5(2);
    yfit5 = P5(1)*Perhour5+P5(2);  
    hold on;
    plot (Perhour5, yfit5, 'r-.')
    legend(sprintf('R^2=%.3f',md5.Rsquared.Ordinary),sprintf('y=%.2f*x+%.2f', slope5, intercept5));
  
title('Location B, Node 5 CO2 Emissions')
xlabel('Time hours')
ylabel('CO2 Concentration mgm3')

subplot (1,3,3)
scatter(Perhour6,CO2Conversion6)
md6 = fitlm(Perhour6,CO2Conversion6);  % fit linear regression model   
md6.Rsquared.Ordinary  ;
P6 = polyfit(Perhour6,CO2Conversion6,1);
    slope6 = P6(1);
    intercept6 = P6(2);
    yfit6 = P6(1)*Perhour6+P6(2);  
    hold on;
    plot (Perhour6, yfit6, 'r-.')
    legend(sprintf('R^2=%.3f',md6.Rsquared.Ordinary),sprintf('y=%.2f*x+%.2f', slope6, intercept6));

title('Location C, Node 6 CO2 Emissions')
xlabel('Time hours')
ylabel('CO2 Concentration mgm3')

figure(2)
set(gcf, 'Position', get(0,'Screensize'));
subplot(1,3,1)
scatter(Perhour7,CO2Conversion7)
md7 = fitlm(Perhour7,CO2Conversion7);  % fit linear regression model   
md7.Rsquared.Ordinary  ;
P7 = polyfit(Perhour7,CO2Conversion7,1);
    slope7 = P7(1);
    intercept7 = P7(2);
    yfit7 = P7(1)*Perhour7+P7(2);  
    hold on;
    plot (Perhour7, yfit7, 'r-.')
    legend(sprintf('R^2=%.3f',md7.Rsquared.Ordinary),sprintf('y=%.2f*x+%.2f', slope7, intercept7));
title('Location D, Node 7 CO2 Emissions')
xlabel('Time hours')
ylabel('CO2 Concentration mgm3')

subplot (1,3,2)
scatter(Perhour8,CO2Conversion8)
md8 = fitlm(Perhour8,CO2Conversion8);  % fit linear regression model   
md8.Rsquared.Ordinary  ;
P8 = polyfit(Perhour8,CO2Conversion8,1);
    slope8 = P8(1);
    intercept8 = P8(2);
    yfit8 = P8(1)*Perhour8+P8(2);  
    hold on;
    plot (Perhour8, yfit8, 'r-.')
    legend(sprintf('R^2=%.3f',md8.Rsquared.Ordinary),sprintf('y=%.2f*x+%.2f', slope8, intercept8));

title('Location E, Node 8 CO2 Emissions')
xlabel('Time hours')
ylabel('CO2 Concentration mgm3')

subplot (1,3,3)
scatter(Perhour9,CO2Conversion9)
md9 = fitlm(Perhour9,CO2Conversion9);  % fit linear regression model   
md9.Rsquared.Ordinary ;
P9 = polyfit(Perhour9,CO2Conversion9,1);
    slope9 = P9(1);
    intercept9 = P9(2);
    yfit9 = P9(1)*Perhour9+P9(2);  
    hold on;
    plot (Perhour9, yfit9, 'r-.')
    legend(sprintf('R^2=%.3f',md9.Rsquared.Ordinary),sprintf('y=%.2f*x+%.2f', slope9, intercept9));
 
title('Location F, Node 9 CO2 Emissions')
xlabel('Time hours')
ylabel('CO2 Concentration mgm3')


figure(3)
set(gcf, 'Position', get(0,'Screensize'));
subplot(1,3,1)
scatter(Perhour10,CO2Conversion10)
md10 = fitlm(Perhour10,CO2Conversion10);  % fit linear regression model   
md10.Rsquared.Ordinary ;
P10 = polyfit(Perhour10,CO2Conversion10,1);
    slope10 = P10(1);
    intercept10 = P10(2);
    yfit10 = P10(1)*Perhour10+P10(2);  
    hold on;
    plot (Perhour10, yfit10, 'r-.')
    legend(sprintf('R^2=%.3f',md10.Rsquared.Ordinary),sprintf('y=%.2f*x+%.2f', slope10, intercept10));
 
    title('Location G, Node 10 CO2 Emissions')
xlabel('Time hours')
ylabel('CO2 Concentration mgm3')

subplot (1,3,2)
scatter(Perhour11,CO2Conversion11)
md11 = fitlm(Perhour11,CO2Conversion11);  % fit linear regression model   
md11.Rsquared.Ordinary  ;
P11 = polyfit(Perhour11,CO2Conversion11,1);
    slope11 = P11(1);
    intercept11 = P11(2);
    yfit11 = P11(1)*Perhour11+P11(2);  
    hold on;
    plot (Perhour11, yfit11, 'r-.')
    legend(sprintf('R^2=%.3f',md11.Rsquared.Ordinary),sprintf('y=%.2f*x+%.2f', slope11, intercept11));

title('Location H, Node 11 CO2 Emissions')
xlabel('Time hours')
ylabel('CO2 Concentration mgm3')


subplot (1,3,3)
scatter(Perhour12,CO2Conversion12)
md12 = fitlm(Perhour12,CO2Conversion12);  % fit linear regression model   
md12.Rsquared.Ordinary  ;
P12 = polyfit(Perhour12,CO2Conversion12,1);
    slope12 = P12(1);
    intercept12 = P12(2);
    yfit12 = P12(1)*Perhour12+P12(2);  
    hold on;
    plot (Perhour12, yfit12, 'r-.')
    legend(sprintf('R^2=%.3f',md12.Rsquared.Ordinary),sprintf('y=%.2f*x+%.2f', slope12, intercept12));

title('Location I, Node 12 CO2 Emissions')
xlabel('Time hours')
ylabel('CO2 Concentration mgm3')



%------------Fluxes--------------------

flux4 = slope4*HeightMean4;
flux5 = slope5*HeightMean5;
flux6 = slope6*HeightMean6;
flux7 = slope7*HeightMean7;
flux8 = slope8*HeightMean8;
flux9 = slope9*HeightMean9;
flux10 = slope10*HeightMean10;
flux11 = slope11*HeightMean11;
flux12 = slope12*HeightMean12;


fluxarray = [flux4; flux5; flux6; flux7; flux8; flux9; flux10; flux11; flux12];

fprintf('--------------------------------------------------------------------------------------------------------------\n')
fprintf('-------------------------SUMMARY OF CO2 FLUXES AND REGRESSION TRENDS -----------------------------------------\n')
fprintf('--------------------------------------------------------------------------------------------------------------\n')
fprintf('-----------LOCATION A.-------------------------------\nCO2 Flux = %.3f mg/m^3.hr.\nTrendline: y = %.2f x + %.2f.\nR^2 = %.3f.\n',flux4,slope4,intercept4, md4.Rsquared.Ordinary) 
fprintf('-----------LOCATION B.-------------------------------\nCO2 Flux = %.3f mg/m^3.hr.\nTrendline: y = %.2f x + %.2f.\nR^2 = %.3f.\n',flux5,slope5,intercept5, md5.Rsquared.Ordinary) 
fprintf('-----------LOCATION C.-------------------------------\nCO2 Flux = %.3f mg/m^3.hr.\nTrendline: y = %.2f x + %.2f.\nR^2 = %.3f.\n',flux6,slope6,intercept6, md6.Rsquared.Ordinary) 
fprintf('-----------LOCATION D.-------------------------------\nCO2 Flux = %.3f mg/m^3.hr.\nTrendline: y = %.2f x + %.2f.\nR^2 = %.3f.\n',flux7,slope7,intercept7, md7.Rsquared.Ordinary) 
fprintf('-----------LOCATION E.-------------------------------\nCO2 Flux = %.3f mg/m^3.hr.\nTrendline: y = %.2f x + %.2f.\nR^2 = %.3f.\n',flux8,slope8,intercept8, md8.Rsquared.Ordinary) 
fprintf('-----------LOCATION F.-------------------------------\nCO2 Flux = %.3f mg/m^3.hr.\nTrendline: y = %.2f x + %.2f.\nR^2 = %.3f.\n',flux9,slope9,intercept9, md9.Rsquared.Ordinary) 
fprintf('-----------LOCATION G.-------------------------------\nCO2 Flux = %.3f mg/m^3.hr.\nTrendline: y = %.2f x + %.2f.\nR^2 = %.3f.\n',flux10,slope10,intercept10, md10.Rsquared.Ordinary) 
fprintf('-----------LOCATION H.-------------------------------\nCO2 Flux = %.3f mg/m^3.hr.\nTrendline: y = %.2f x + %.2f.\nR^2 = %.3f.\n',flux11,slope11,intercept11, md11.Rsquared.Ordinary) 
fprintf('-----------LOCATION I.-------------------------------\nCO2 Flux = %.3f mg/m^3.hr.\nTrendline: y = %.2f x + %.2f.\nR^2 = %.3f.\n',flux12,slope12,intercept12, md12.Rsquared.Ordinary) 
fprintf('--------------------------------------------------------------------------------------------------------------\n')
fprintf('--------------------------------------------------------------------------------------------------------------\n\n')

fprintf('--------------------------------------------------------------------------------------------------------------\n')
fprintf('-----------------------------FULL RAW DATA SETS FOR EACH LOCATION/NODE ---------------------------------------\n')
fprintf('--------------------------------------------------------------------------------------------------------------\n')

    fprintf('\n---------LOCATION A OVERVIEW-----------------------------------------------------------------------------------------------------\n')
varNamesT4= {'A4','TIMEhr','TIMEmin','TIMEsec','VOLUMEin3','HEIGHTin','CO2ppm','CO2mgm3','TEMP1C', 'HUMIDITYpercent', 'TEMP2C','PRESSUREkPa'};
T4 = table(Node4(:,[1]),Perhour4,Permin4,Node4(:,[2]),Node4(:,[3]),Height4,Node4(:,[4]),CO2Conversion4,Node4(:,[5]),Node4(:,[6]),Node4(:,[7]),Node4(:,[8]), 'VariableNames',varNamesT4)     
    fprintf('\n---------LOCATION B OVERVIEW-----------------------------------------------------------------------------------------------------\n')    
varNamesT5= {'B5','TIMEhr','TIMEmin','TIMEsec','VOLUMEin3','HEIGHTin','CO2ppm','CO2mgm3','TEMP1C', 'HUMIDITYpercent', 'TEMP2C','PRESSUREkPa'};
T5 = table(Node5(:,[1]),Perhour5,Permin5,Node5(:,[2]),Node5(:,[3]),Height5,Node5(:,[4]),CO2Conversion5,Node5(:,[5]),Node5(:,[6]),Node5(:,[7]),Node5(:,[8]), 'VariableNames',varNamesT5)     
    fprintf('\n---------LOCATION C OVERVIEW-----------------------------------------------------------------------------------------------------\n')
varNamesT6= {'C6','TIMEhr','TIMEmin','TIMEsec','VOLUMEin3','HEIGHTin','CO2ppm','CO2mgm3','TEMP1C', 'HUMIDITYpercent', 'TEMP2C','PRESSUREkPa'};
T6 = table(Node6(:,[1]),Perhour6,Permin6,Node6(:,[2]),Node6(:,[3]),Height6,Node6(:,[4]),CO2Conversion6,Node6(:,[5]),Node6(:,[6]),Node6(:,[7]),Node6(:,[8]), 'VariableNames',varNamesT6)     
    fprintf('\n---------LOCATION D OVERVIEW-----------------------------------------------------------------------------------------------------\n')
varNamesT7= {'D7','TIMEhr','TIMEmin','TIMEsec','VOLUMEin3','HEIGHTin','CO2ppm','CO2mgm3','TEMP1C', 'HUMIDITYpercent', 'TEMP2C','PRESSUREkPa'};
T7 = table(Node7(:,[1]),Perhour7,Permin7,Node7(:,[2]),Node7(:,[3]),Height7,Node7(:,[4]),CO2Conversion7,Node7(:,[5]),Node7(:,[6]),Node7(:,[7]),Node7(:,[8]), 'VariableNames',varNamesT7)    
    fprintf('\n---------LOCATION E OVERVIEW-----------------------------------------------------------------------------------------------------\n')
varNamesT8= {'E8','TIMEhr','TIMEmin','TIMEsec','VOLUMEin3','HEIGHTin','CO2ppm8','CO2mgm3','TEMP1C','HUMIDITYpercent','TEMP2C','PRESSUREkPa'};
T8 = table(Node8(:,[1]),Perhour8,Permin8,Node8(:,[2]),Node8(:,[3]),Height8,Node8(:,[4]),CO2Conversion8,Node8(:,[5]),Node8(:,[6]),Node8(:,[7]),Node8(:,[8]), 'VariableNames',varNamesT8)    
    fprintf('\n---------LOCATION F OVERVIEW-----------------------------------------------------------------------------------------------------\n')
varNamesT9= {'F9','TIMEhr','TIMEmin','TIMEsec','VOLUMEin3','HEIGHTin','CO2ppm','CO2mgm3','TEMP1C', 'HUMIDITYpercent', 'TEMP2C','PRESSUREkPa'};
T9 = table(Node9(:,[1]),Perhour9,Permin9,Node9(:,[2]),Node9(:,[3]),Height9,Node9(:,[4]),CO2Conversion9,Node9(:,[5]),Node9(:,[6]),Node9(:,[7]),Node9(:,[8]), 'VariableNames',varNamesT9)    
    fprintf('\n---------LOCATION G OVERVIEW-----------------------------------------------------------------------------------------------------\n')
varNamesT10= {'G10','TIMEhr','TIMEmin','TIMEsec','VOLUMEin3','HEIGHTin','CO2ppm','CO2mgm3','TEMP1C', 'HUMIDITYpercent', 'TEMP2C','PRESSUREkPa'};
T10 = table(Node10(:,[1]),Perhour10,Permin10,Node10(:,[2]),Node10(:,[3]),Height10,Node10(:,[4]),CO2Conversion10,Node10(:,[5]),Node10(:,[6]),Node10(:,[7]),Node10(:,[8]), 'VariableNames',varNamesT10)    
    fprintf('\n---------LOCATION H OVERVIEW-----------------------------------------------------------------------------------------------------\n')
varNamesT11= {'H11','TIMEhr','TIMEmin','TIMEsec','VOLUMEin3','HEIGHTin','CO2ppm','CO2mgm3','TEMP1C', 'HUMIDITYpercent', 'TEMP2C','PRESSUREkPa'};
T11 = table(Node11(:,[1]),Perhour11,Permin11,Node11(:,[2]),Node11(:,[3]),Height11,Node11(:,[4]),CO2Conversion11,Node11(:,[5]),Node11(:,[6]),Node11(:,[7]),Node11(:,[8]), 'VariableNames',varNamesT11)   
    fprintf('\n---------LOCATION I OVERVIEW-----------------------------------------------------------------------------------------------------\n')   
varNamesT12= {'I12','TIMEhr','TIMEmin','TIMEsec','VOLUMEin3','HEIGHTin','CO2ppm','CO2mgm3','TEMP1C', 'HUMIDITYpercent', 'TEMP2C','PRESSUREkPa'};
T12 = table(Node12(:,[1]),Perhour12,Permin12,Node12(:,[2]),Node12(:,[3]),Height12,Node12(:,[4]),CO2Conversion12,Node12(:,[5]),Node12(:,[6]),Node12(:,[7]),Node12(:,[8]), 'VariableNames',varNamesT12)      
fprintf('\n\n---------------------------------------------------------------------------------------------------------------------------\n')
fprintf('\n-------------------------------T-H-A-T---I-S---A-L-L-----------------------------------------------------------------------\n')
fprintf('\n---------------------------------------H-A-V-E---A-------------------------------------------------------------------------\n')
fprintf('\n-------------------------------------------N-I-C-E---D-A-Y-----------------------------------------------------------------\n')
fprintf('\n---------------------------------------------------------------------------------------------------------------------------\n')

end 
  

[Guillaume]

Well, yes, I'm sorry to say that code is awful.

Numbered variables are always a mistake. The correct way is to index the variables. I think that's what you're trying to remediate with your new code.

Again, if you end up writing the same lines several time with only minor variations, you're doing it wrong. The computer should be doing the repetition for you. That's what they're good at.

As there's too much code for us to try to understand what it's doing (the lack of comments explaining what it's meant to do doesn't help), it would probably be a better use of our time if we ignored it and you explained in details what you want to do with the input data.

And also, what version of matlab are you using?

[dpb]

Can't emphasize Guillaume's comments enough (and others to same effect earlier).

Just explain what the data are in the file (no headers there doesn't help) and what it is you want to do with it. Give the basic definitions of the conversion explaining which variable is which and what units apply and then what is to be plotted against what. The starting point will be something like

t=readtable('Lods June13.2019 AB.csv');
t.Properties.VariableNames={'Sensor', ???   };
[g,id]=findgroups(t.Sensor);

then to apply the various operations to the groups as identified...see the doc for splitapply as one way to apply a specific function; simply a loop over the number of groups calling a function may be the ticket here with the plotting and all...