How to loop through the columns of a Matlab table by using the headings? - matlab

I am trying to make a for-loop for the Matlab code below. I have named each column with JAN90, FEB90, etc. all the way up to AUG19, which can be found in a matrix named "data". At this point I need to change the month and year manually to obtain the result I want. Is there a way to iterate over the columns by the column name? Would it be easier to name the columns Var1, Var2 etc.?
clear;
clc;
data = readtable('Data.xlsx','ReadVariableNames',false);
data(1,:) = [];
data.Var2 = str2double(data.Var2);
data.Var3 = str2double(data.Var3);
data.Var4 = str2double(data.Var4);
data.Var5 = str2double(data.Var5);
data.Var6 = str2double(data.Var6);
data.Var7 = str2double(data.Var7);
data.Var8 = str2double(data.Var8);
data.Var9 = str2double(data.Var9);
data.Var10 = str2double(data.Var10);
data.Var11 = str2double(data.Var11);
data.Var12 = str2double(data.Var12);
data.Var13 = str2double(data.Var13);
data(:,1) = [];
data = table2array(data);
data = array2table(data.');
data = table2cell(data)
data = cell2table(data, 'VariableNames',{'JAN90','FEB90','MAR90','APR90','MAY90','JUN90','JUL90','AUG90'...
,'SEP90','OCT90','NOV90','DEC90','JAN91','FEB91','MAR91','APR91','MAY91','JUN91','JUL91','AUG91'...
,'SEP91','OCT91','NOV91','DEC91','JAN92','FEB92','MAR92','APR92','MAY92','JUN92','JUL92','AUG92'...
,'SEP92','OCT92','NOV92','DEC92','JAN93','FEB93','MAR93','APR93','MAY93','JUN93','JUL93','AUG93'...
,'SEP93','OCT93','NOV93','DEC93','JAN94','FEB94','MAR94','APR94','MAY94','JUN94','JUL94','AUG94'...
,'SEP94','OCT94','NOV94','DEC94','JAN95','FEB95','MAR95','APR95','MAY95','JUN95','JUL95','AUG95'...
,'SEP95','OCT95','NOV95','DEC95','JAN96','FEB96','MAR96','APR96','MAY96','JUN96','JUL96','AUG96'...
,'SEP96','OCT96','NOV96','DEC96','JAN97','FEB97','MAR97','APR97','MAY97','JUN97','JUL97','AUG97'...
,'SEP97','OCT97','NOV97','DEC97','JAN98','FEB98','MAR98','APR98','MAY98','JUN98','JUL98','AUG98'...
,'SEP98','OCT98','NOV98','DEC98','JAN99','FEB99','MAR99','APR99','MAY99','JUN99','JUL99','AUG99'...
,'SEP99','OCT99','NOV99','DEC99','JAN00','FEB00','MAR00','APR00','MAY00','JUN00','JUL00','AUG00'...
,'SEP00','OCT00','NOV00','DEC00','JAN01','FEB01','MAR01','APR01','MAY01','JUN01','JUL01','AUG01'...
,'SEP01','OCT01','NOV01','DEC01','JAN02','FEB02','MAR02','APR02','MAY02','JUN02','JUL02','AUG02'...
,'SEP02','OCT02','NOV02','DEC02','JAN03','FEB03','MAR03','APR03','MAY03','JUN03','JUL03','AUG03'...
,'SEP03','OCT03','NOV03','DEC03','JAN04','FEB04','MAR04','APR04','MAY04','JUN04','JUL04','AUG04'...
,'SEP04','OCT04','NOV04','DEC04','JAN05','FEB05','MAR05','APR05','MAY05','JUN05','JUL05','AUG05'...
,'SEP05','OCT05','NOV05','DEC05','JAN06','FEB06','MAR06','APR06','MAY06','JUN06','JUL06','AUG06'...
,'SEP06','OCT06','NOV06','DEC06','JAN07','FEB07','MAR07','APR07','MAY07','JUN07','JUL07','AUG07'...
,'SEP07','OCT07','NOV07','DEC07','JAN08','FEB08','MAR08','APR08','MAY08','JUN08','JUL08','AUG08'...
,'SEP08','OCT08','NOV08','DEC08','JAN09','FEB09','MAR09','APR09','MAY09','JUN09','JUL09','AUG09'...
,'SEP09','OCT09','NOV09','DEC09','JAN10','FEB10','MAR10','APR10','MAY10','JUN10','JUL10','AUG10'...
,'SEP10','OCT10','NOV10','DEC10','JAN11','FEB11','MAR11','APR11','MAY11','JUN11','JUL11','AUG11'...
,'SEP11','OCT11','NOV11','DEC11','JAN12','FEB12','MAR12','APR12','MAY12','JUN12','JUL12','AUG12'...
,'SEP12','OCT12','NOV12','DEC12','JAN13','FEB13','MAR13','APR13','MAY13','JUN13','JUL13','AUG13'...
,'SEP13','OCT13','NOV13','DEC13','JAN14','FEB14','MAR14','APR14','MAY14','JUN14','JUL14','AUG14'...
,'SEP14','OCT14','NOV14','DEC14','JAN15','FEB15','MAR15','APR15','MAY15','JUN15','JUL15','AUG15'...
,'SEP15','OCT15','NOV15','DEC15','JAN16','FEB16','MAR16','APR16','MAY16','JUN16','JUL16','AUG16'...
,'SEP16','OCT16','NOV16','DEC16','JAN17','FEB17','MAR17','APR17','MAY17','JUN17','JUL17','AUG17'...
,'SEP17','OCT17','NOV17','DEC17','JAN18','FEB18','MAR18','APR18','MAY18','JUN18','JUL18','AUG18'...
,'SEP18','OCT18','NOV18','DEC18','JAN19','FEB19','MAR19','APR19','MAY19','JUN19','JUL19','AUG19'});
m = [1 2 3 6 12 24 36 60 84 120 240 360]';
for i=1:100
t = i;
data.X_1 = (1-exp(-m./t))./(m./t);
data.X_2 = ((1-exp(-m./t))./(m./t))-exp(-m./t);
model_1 = fitlm(data, 'FEB95 ~ X_1 + X_2');
RSS(100,:) = zeros ;
res = model_1.Residuals.Raw;
res(any(isnan(res), 2), :) = [];
RSS(i) = sum(res.^2);
end
RSS(:,2) = [1:1:100];
min = min(RSS(:,1));
t = find(RSS(:,1) == min)
data.X_1 = (1-exp(-m./t))./(m./t);
data.X_2 = ((1-exp(-m./t))./(m./t))-exp(-m./t);
model_1 = fitlm(data, 'FEB95 ~ X_1 + X_2')
res = model_1.Residuals.Raw;
res(any(isnan(res), 2), :) = [];
RSS = sum(res.^2)
intercept = model_1.Coefficients.Estimate(1,1);
beta_1 = model_1.Coefficients.Estimate(2,1);
beta_2 = model_1.Coefficients.Estimate(3,1);
Yhat = intercept + beta_1.*data.X_1 + beta_2.*data.X_2;
plot(m, Yhat)
hold on
scatter(m, data.FEB95)
I.e "FEB95" should be dynamic? Any suggestions?


Her is how I would approach your problem. First realize that VarNames=data.Properties.VariableNames will get a list of all column names in the table. You could then loop over this list. For example
for v=VarNames
current_column = v{1};
% ....
% Define the model spec for the current column
model_spec = [current_column ' ~ X_1 + X_2'];
% and create the model
model_1 = fitlm(data, model_spec);
% ... Continue computation ... and collect results in a table or array
end

Related

Creating a table from a variable inside a for loop

I am writing a for loop to calculate the value of four different variables. The first variable is M. M increases from 10^2 to 10^5,
M = [10^2,10^3,10^4,10^5];
The other three variables needed for the table are shown in the code below.
confmc
confcv
confmcSize/confcvSize
I first create a for loop to iterate through the four different values of M. I then create the table outside of the for loop.
How could I adjust the implementation so that the table displays all four values of M?
randn('state',100)
%%%%%% Problem and method parameters %%%%%%%%%
S = 5; E = 6; sigma = 0.3; r = 0.05; T = 1;
Dt = 1e-2; N = T/Dt; M = [10^2,10^3,10^4,10^5];
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
for k=1:numel(M)
%%%%%%%%% Geom Asian exact mean %%%%%%%%%%%%
sigsqT= sigma^2*T*(N+1)*(2*N+1)/(6*N*N);
muT = 0.5*sigsqT + (r - 0.5*sigma^2)*T*(N+1)/(2*N);
d1 = (log(S/E) + (muT + 0.5*sigsqT))/(sqrt(sigsqT));
d2 = d1 - sqrt(sigsqT);
N1 = 0.5*(1+erf(d1/sqrt(2)));
N2 = 0.5*(1+erf(d2/sqrt(2)));
geo = exp(-r*T)*( S*exp(muT)*N1 - E*N2 );
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
Spath = S*cumprod(exp((r-0.5*sigma^2)*Dt+sigma*sqrt(Dt)*randn(M(k),N)),2);
% Standard Monte Carlo
arithave = mean(Spath,2);
Parith = exp(-r*T)*max(arithave-E,0); % payoffs
Pmean = mean(Parith);
Pstd = std(Parith);
confmc = [Pmean-1.96*Pstd/sqrt(M(k)), Pmean+1.96*Pstd/sqrt(M(k))];
confmcSize = [(Pmean+1.96*Pstd/sqrt(M(k)))-(Pmean-1.96*Pstd/sqrt(M(k)))];
% Control Variate
geoave = exp((1/N)*sum(log(Spath),2));
Pgeo = exp(-r*T)*max(geoave-E,0); % geo payoffs
Z = Parith + geo - Pgeo; % control variate version
Zmean = mean(Z);
Zstd = std(Z);
confcv = [Zmean-1.96*Zstd/sqrt(M(k)), Zmean+1.96*Zstd/sqrt(M(k))];
confcvSize = [(Zmean+1.96*Zstd/sqrt(M(k)))-(Zmean-1.96*Zstd/sqrt(M(k)))];
end
T = table(M,confmc,confcv,confmcSize/confcvSize)
The current code returns
T =
1×4 table
M confmc confcv Var4
_____ ____________________ ____________________ ______
1e+05 0.096756 0.1007 0.097306 0.097789 8.1622
How could I change my implementation so that all four values of M are computed?

I just modified few things.Take a look at the following code.
randn('state',100)
%%%%%% Problem and method parameters %%%%%%%%%
S = 5; E = 6; sigma = 0.3; r = 0.05; T = 1;
Dt = 1e-2; N = T/Dt; M = [10^2,10^3,10^4,10^5];
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
confmc = zeros(numel(M), 2);
confcv = zeros(numel(M), 2);
confmcSize = zeros(numel(M), 1);
confcvSize = zeros(numel(M), 1);
for k=1:numel(M)
%%%%%%%%% Geom Asian exact mean %%%%%%%%%%%%
sigsqT= sigma^2*T*(N+1)*(2*N+1)/(6*N*N);
muT = 0.5*sigsqT + (r - 0.5*sigma^2)*T*(N+1)/(2*N);
d1 = (log(S/E) + (muT + 0.5*sigsqT))/(sqrt(sigsqT));
d2 = d1 - sqrt(sigsqT);
N1 = 0.5*(1+erf(d1/sqrt(2)));
N2 = 0.5*(1+erf(d2/sqrt(2)));
geo = exp(-r*T)*( S*exp(muT)*N1 - E*N2 );
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
Spath = S*cumprod(exp((r-0.5*sigma^2)*Dt+sigma*sqrt(Dt)*randn(M(k),N)),2);
% Standard Monte Carlo
arithave = mean(Spath,2);
Parith = exp(-r*T)*max(arithave-E,0); % payoffs
Pmean = mean(Parith);
Pstd = std(Parith);
confmc(k,:) = [Pmean-1.96*Pstd/sqrt(M(k)), Pmean+1.96*Pstd/sqrt(M(k))];
confmcSize(k,1) = [(Pmean+1.96*Pstd/sqrt(M(k)))-(Pmean-1.96*Pstd/sqrt(M(k)))];
% Control Variate
geoave = exp((1/N)*sum(log(Spath),2));
Pgeo = exp(-r*T)*max(geoave-E,0); % geo payoffs
Z = Parith + geo - Pgeo; % control variate version
Zmean = mean(Z);
Zstd = std(Z);
confcv(k,:) = [Zmean-1.96*Zstd/sqrt(M(k)), Zmean+1.96*Zstd/sqrt(M(k))];
confcvSize(k,1) = [(Zmean+1.96*Zstd/sqrt(M(k)))-(Zmean-1.96*Zstd/sqrt(M(k)))];
end
T = table(M',confmc,confcv,confmcSize./confcvSize)
In short, I just used a matrix instead of a vector or scalar as the members of the table. In your code, the variables (confmc, confcv, confmcSize, confcvSize) were getting overwritten.

how to save data that is generated via for loop in matlab?

i need a way to save data that is generated via for loops.To simply explain,first I generate a matrix 5*10-in the second iteration the process repeat and another matrix 5*10 is generated(** note that maybe some rows need to be empty)(i mean in second iteration row3 is empty) and the second matrix should concat the first one and make 5*20 matrix.It is possible in excel.but i need the faster way to save data? which of table/dataset/... can be used????
[data,header] = xlsread('E:\TEST\chozen_font_data.xlsx','font');
font_data = data(:,1);
a = 'C:\Users\S.R.P\Desktop\ouput';
A = dir(fullfile(a));
isub = [A(:).isdir];
nameFolds = {A(isub).name}';
nameFolds(ismember(nameFolds,{'.','..'})) = [];
for n_fol = 1:numel(nameFolds)
name_sub_fold = dir(fullfile(a,nameFolds{n_fol},'*.png'));
for n_sub = 1: numel( name_sub_fold )
[~,~,image] =
imread(fullfile(a,nameFolds{n_fol},name_sub_fold(n_sub).name));
image=im2bw(image);
[ image ] = Crop_AroundAllComponent( image );
name_font = regexprep(name_sub_fold(n_sub).name,'[^0-9]','');
co = find( font_data == str2num( name_font));
area = area_calculation( image );
md = matrix_density_calculation( image );
[ num ] = DisconnectedComponent_calc( image );
d={area,md,num};
[s,m] = xlswrite('E:\TEST\chozen_font_data.xlsx', d, 'font',
strcat('GB',num2str(co)));
end
end

To concatenate 2 matrices in matlab, you can just use square bracket concatenation notation. Like so:
row1 = zeros(10, 5); % 10 by 5 row
row2 = ones(10, 5); % another 10 by 5 row
total = [row1; row2]; % 20 by 5 combination
If you wanted to do this with for loops, you could add a new row with each iteration. For example:
start = 0;
end = 5;
result = [];
for i = start:end
row = ... % get the new row here
result = [result; row];
end

Repeating the same statement using loop

This is the same statement for 3 times. how to do this with loop. Here, the matrix G1 dimension is 3*10. so in each part i am taking different column.
G2 = f_range_m(1:8:length(timeline_ms),:); %%%% measured range
G1 = OrgiRange(1:8:end,:);
M1 = G1(:,1);
dist11 = abs(bsxfun( #minus,G2,M1));
[~,col1] = min(dist11,[],2);
Result_1 = diag(G2(:,col1));
M2 = G1(:, 2);
dist22 = abs(bsxfun(#minus,G2, M2));
[~,col2] = min(dist22,[],2);
Result_2 = diag(G2(:,col2));
M3 = G1(:, 3);
dist33 = abs(bsxfun(#minus,G2, M3));
[~,col3] = min(dist33,[],2);
Result_3 = diag(G2(:,col3));
I am trying this way. However not getting desired output. Result dimension should be 13*3.
obj = 3;
for ix = 1:obj
M = G1(:,ix);
dist = abs(bsxfun(#minus,G2,M));
[~,col] = min (dist,[],2);
Result = diag(G2(:,col));
end

With your updated code you nearly solved it. Everything which remains is writing to the columns of Result instead of overwriting it in each iteration.
obj = 3;
Result=nan(size(G1,1),obj);
for ix = 1:obj
M = G1(:,ix);
dist = abs(bsxfun(#minus,G2,M));
[~,col] = min (dist,[],2);
Result(:,ix) = diag(G2(:,col));
end

How can I display different types of output in a matix in matlab?

please consider that I have different types of output in each iteration , how I can show all of them in a matrix?or in a table ? I need to have label for each column and to be accessible when I need it for calling or comparing or etc ...
for example outputs of iterations:
myfilename =
file35.txt
a_Count =
3
PPS_Count =
16
PPP_Count =
8
emo =
'trust'
x =
1
for example outputs of iteration 2:
myfilename =
file36.txt
a_Count =
5
PPS_Count =
10
PPP_Count =
8
emo =
'anger'
x =
0
for example outputs of iteration 3:
myfilename =
file37.txt
a_Count =
6
PPS_Count =
32
PPP_Count =
8
emo =
'trust'
x =
0
thanks in advance.

Here is a tutorial on creating a struct array and documentation for struct.
In your case what I would do is first create the empty struct and then loop through the files:
data_struct = struct('a_Count',{},'PPS_Count',{},'PPP_Count',{},'emo',{},'x',{});
numfiles = 1; % just for testing purposes
for findex = 1:numfiles
% Code to read in file data goes here. Replace from here to next comment.
new_a_Count = 3;
new_PPS_Count = 16;
new_PPP_Count = 8;
new_emo = 'trust';
new_x = 1;
% Replace down to here populating variables:
% new_a_Count, new_PPS_Count, new_PPP_Count, new_emo, new_x
data_struct(findex).a_Count = new_a_Count;
data_struct(findex).PPS_Count = new_PPS_Count;
data_struct(findex).PPP_Count = new_PPP_Count;
data_struct(findex).emo = new_emo;
data_struct(findex).x = new_x;
end;
% display all values in data_struct(1):
disp("data_struct(1) = ");
disp(data_struct(1));
disp("\n");
% display just the first field "a_Count"
disp("data_struct(1).a_Count = ");
disp(data_struct(1).a_Count);
Note that you can call those new variables anything, including the same names as the struct fields. Here's the output you should get when you run this:
data_struct (1) =
{
PPP_Count = 8
PPS_Count = 16
a_Count = 3
emo = trust
x = 1
}
data_struct(1).a_Count =
3

Binary file - Matrix Manipulation

I have several binary files with a known structure (8,12000,real*4). 8 is the number of variables, and 12000 represent the time steps. From these binaries I need to get a final 16x9 matrix defined as followed:
the first column contains a filename identification.
on the diagonal are located the extreme values (maxima and minima) of the corresponding variable.
the simultaneous values of the other variables shall be given in the rows.
At the moment I'm using this code
for i = 1:num_files
for j = 1:num_ext
fid = fopen([fullfile(BEGINPATH{1},FILELIST{i}) '.$' VAREXTENSION{j}],'r');
A = fread(fid,[DLC_dimens{i}{3}(1) DLC_dimens{i}{3}(2)],'real*4');
for k = 1:size(A,1)
[max_val(k,i) max_idx(k,i)] = max(A(k,:));
[min_val(k,i) min_idx(k,i)] = min(A(k,:));
end
fclose(fid);
end
end
% Pre-allocate ULS matrices
uloads = cell(2*size(A,1),size(A,1)+1);
uloads_temp = cell(2*size(A,1),size(A,1)+1);
% Generate ULS matrix for the first file
for i = 1:size(uloads,1)
uloads{i,end} = DLC_dimens{1}(1);
end
fid = fopen([fullfile(BEGINPATH{1},FILELIST{1}) '.$' VAREXTENSION{1}],'r');
A = fread(fid,[DLC_dimens{i}{3}(1) DLC_dimens{i}{3}(2)],'real*4');
for j = 1:size(uloads,2)-1
uloads{1,j} = A(j,max_idx(1,1))*DLC_dimens{1}{4};
uloads{2,j} = A(j,min_idx(1,1))*DLC_dimens{1}{4};
uloads{3,j} = A(j,max_idx(2,1))*DLC_dimens{1}{4};
uloads{4,j} = A(j,min_idx(2,1))*DLC_dimens{1}{4};
uloads{5,j} = A(j,max_idx(3,1))*DLC_dimens{1}{4};
uloads{6,j} = A(j,min_idx(3,1))*DLC_dimens{1}{4};
uloads{7,j} = A(j,max_idx(4,1))*DLC_dimens{1}{4};
uloads{8,j} = A(j,min_idx(4,1))*DLC_dimens{1}{4};
uloads{9,j} = A(j,max_idx(5,1))*DLC_dimens{1}{4};
uloads{10,j} = A(j,min_idx(5,1))*DLC_dimens{1}{4};
uloads{11,j} = A(j,max_idx(6,1))*DLC_dimens{1}{4};
uloads{12,j} = A(j,min_idx(6,1))*DLC_dimens{1}{4};
uloads{13,j} = A(j,max_idx(7,1))*DLC_dimens{1}{4};
uloads{14,j} = A(j,min_idx(7,1))*DLC_dimens{1}{4};
uloads{15,j} = A(j,max_idx(8,1))*DLC_dimens{1}{4};
uloads{16,j} = A(j,min_idx(8,1))*DLC_dimens{1}{4};
end
fclose(fid);
% ULS temporary matrix generation
uls = uloads;
for i = 2:num_files
fid = fopen([fullfile(BEGINPATH{1},FILELIST{i}) '.$' VAREXTENSION{1}],'r');
A = fread(fid,[8 12000],'float32');
for j = 1:size(uloads,1)
uloads_temp{j,9} = DLC_dimens{i}(1);
end
for k = 1:size(uloads,2)-1
uloads_temp{1,k} = A(k,max_idx(1,i))*DLC_dimens{i}{4};
uloads_temp{2,k} = A(k,min_idx(1,i))*DLC_dimens{i}{4};
uloads_temp{3,k} = A(k,max_idx(2,i))*DLC_dimens{i}{4};
uloads_temp{4,k} = A(k,min_idx(2,i))*DLC_dimens{i}{4};
uloads_temp{5,k} = A(k,max_idx(3,i))*DLC_dimens{i}{4};
uloads_temp{6,k} = A(k,min_idx(3,i))*DLC_dimens{i}{4};
uloads_temp{7,k} = A(k,max_idx(4,i))*DLC_dimens{i}{4};
uloads_temp{8,k} = A(k,min_idx(4,i))*DLC_dimens{i}{4};
uloads_temp{9,k} = A(k,max_idx(5,i))*DLC_dimens{i}{4};
uloads_temp{10,k} = A(k,min_idx(5,i))*DLC_dimens{i}{4};
uloads_temp{11,k} = A(k,max_idx(6,i))*DLC_dimens{i}{4};
uloads_temp{12,k} = A(k,min_idx(6,i))*DLC_dimens{i}{4};
uloads_temp{13,k} = A(k,max_idx(7,i))*DLC_dimens{i}{4};
uloads_temp{14,k} = A(k,min_idx(7,i))*DLC_dimens{i}{4};
uloads_temp{15,k} = A(k,max_idx(8,i))*DLC_dimens{i}{4};
uloads_temp{16,k} = A(k,min_idx(8,i))*DLC_dimens{i}{4};
end
if uloads_temp{1,1}(:) > uls{1,1}(:)
uls(1,:) = uloads_temp(1,:);
end
if uloads_temp{2,1}(:) < uls{2,1}(:)
uls(2,:) = uloads_temp(2,:);
end
if uloads_temp{3,2}(:) > uls{3,2}(:)
uls(3,:) = uloads_temp(3,:);
end
if uloads_temp{4,2}(:) < uls{4,2}(:)
uls(4,:) = uloads_temp(4,:);
end
if uloads_temp{5,3}(:) > uls{5,3}(:)
uls(5,:) = uloads_temp(5,:);
end
if uloads_temp{6,3}(:) < uls{6,3}(:)
uls(6,:) = uloads_temp(6,:);
end
if uloads_temp{7,4}(:) > uls{7,4}(:)
uls(7,:) = uloads_temp(7,:);
end
if uloads_temp{8,4}(:) < uls{8,4}(:)
uls(8,:) = uloads_temp(8,:);
end
if uloads_temp{9,5}(:) > uls{9,5}(:)
uls(9,:) = uloads_temp(9,:);
end
if uloads_temp{10,5}(:) < uls{10,5}(:)
uls(10,:) = uloads_temp(10,:);
end
if uloads_temp{11,6}(:) > uls{11,6}(:)
uls(11,:) = uloads_temp(11,:);
end
if uloads_temp{12,6}(:) < uls{12,6}(:)
uls(12,:) = uloads_temp(12,:);
end
if uloads_temp{13,7}(:) > uls{13,7}(:)
uls(13,:) = uloads_temp(3,:);
end
if uloads_temp{14,7}(:) < uls{14,7}(:)
uls(14,:) = uloads_temp(14,:);
end
if uloads_temp{15,8}(:) > uls{15,8}(:)
uls(15,:) = uloads_temp(15,:);
end
if uloads_temp{16,8}(:) < uls{16,8}(:)
uls(16,:) = uloads_temp(16,:);
end
fclose(fid);
end
Now comes the question: I was thinking of a procedure where
I generate a temporary uloads_temp matrix just with the first file;
Calculate the uloads matrix for the i-th file (i = 2:num_files)
Compare the terms on the diagonal between i-th uloads matrix and temporary uloads_temp:
a) if the elements of the i-th ulaods are major (minor) than the respective uloads_temp values
b) update uloads_temp rows the condition a) occurs.
I hope I explained everything properly. Could you please give me a hint on how to perform the described loops?
I thank you all in advance.
WKR,
Francesco
P.S. : everything could be reproduced by means fo matrices filled of random numbers; I just copied and pasted my code with reference to a file list.