using app designer create app that can read and load 100 excel file then use next button to observe graph

after loading and plotting graph

then use slider to run point on graph and value shows on edit field use that editfield number for new plot on another app

i have matlab script which load the readtable and load excel file and plot files then save them as picture creates new excell file with output of new graph

if anyone can help me with how to approuch it or guild me on how can i use next button to load new file automaticly after pressing the next buttom and tel me how can i use tell the appdesigner to use 100 data one by one and use neccessry data for all common in my mlapp tamplet instead of copy pasting load function for each common

here my scrip

numxlfile =length(1:1:98);

%% calling the excel file and saving them

Folderlocation = '--';

data=cell([1,numxlfile]);

for k= 1:numxlfile %starts the loop

%define your filename according to the file index

filename=sprintf(['RawData_',num2str(k),'.csv']);

data{k}= readtable(filename); %load file

end %ends the loop

for n = 1 :length(data)

cellcontents =data{n} ;

array=cellcontents(:,:);

%array =array2table(cellcontents(10:end,:),'VariableNames',colmnam) ;

fnm = sprintf('Raw_%d.mat',n);

save(fnm,'array');

% h = findobj('type','figure')

% inputarray(1 : length(h)) = input('Input value for offset yield strength from observation:')

end

%% creating/saving and plotting the true data

rng('default') % for reproducibility

% Pre-allocate loop vars

truev_str = zeros(numxlfile,1);

truev_stress= zeros(numxlfile,1);

% newgraphdata = zeros(length(Tenstress),1);

peakvalue = zeros(numxlfile,1);

peak_strian = zeros(numxlfile,1);

newgraphdata = [];

z=1

for i = 1:numxlfile

ii = i+50;

file = load(fullfile('C:\Users\sghandal\Downloads\RE__Re__ (1)\recreat data', ...

sprintf('Rawdata_%d.mat',ii)));

Tenstress = array2table(file.array.TensileStress);

strainone = array2table(file.array.Strain1);

engg_ = file.array.Extension;

engg_exten=array2table(engg_(:,1)*(16^-1));

%% finding the index for given strain value

% figure (ii);

% hold on

% plot(strainone{:,1},Tenstress{:,1},engg_exten{:,1},Tenstress{:,1})

% % set(gca, 'XTick',1:length(strainone{:,1}), 'FontSize',7)

% % xticklabels (strainone{:,1})

% grid on

% hold on

% m=1;

[~,index] = ismembertol(0.0152,strainone{:,1}, 'ByRows', true, ...

'OutputAllIndices', true, 'DataScale', 1);

row =index(1,1);

if row{1,1} == 0

int = input('enter value base on the ')

[~,index] = ismembertol(int,strainone{:,1}, 'ByRows', true, ...

'OutputAllIndices', true, 'DataScale', 1);

row = index;

if row{1,1} == 0

int = max(findpeaks(engg_exten{:,1}))

[~,index] = ismembertol(int(end),strainone{:,1}, 'ByRows', true, ...

'OutputAllIndices', true, 'DataScale', 1);

if row{1,1} == 0

[~,x]= findpeaks(strainone{:,1});

t = accumarray(x,1);

ke = 0.01<= t <=0.05;

o1 = [strainone{:,1}(ke)];

Aid = ismembertol(strainone{:,1},o1(:,1));

Anewid = strainone{:,1}.* Aid;

AAA = Anewid(islocalmax(Anewid));

[~,index] = ismembertol(max(AAA),strainone{:,1}, 'ByRows', true, ...

'OutputAllIndices', true, 'DataScale', 1);

row = index

if row{1,1} == 0

[~,x]= findpeaks(strainone{:,1});

t = accumarray(x,1);

ke = t >0.05;

o1 = [strainone{:,1}(ke)];

Aid = ismembertol(strainone{:,1},o1(:,1));

Anewid = strainone{:,1}.* Aid;

AAA = Anewid(islocalmin(Anewid));

[~,index] = ismembertol(max(AAA),strainone{:,1}, 'ByRows', true, ...

'OutputAllIndices', true, 'DataScale', 1);

row = index

if row{1,1} == 0

[~,x]= findpeaks(strainone{:,1});

t = accumarray(x,1);

ke = t >0.07;

o1 = [strainone{:,1}(ke)];

Aid = ismembertol(strainone{:,1},o1(:,1));

Anewid = strainone{:,1}.* Aid;

AAA = Anewid(islocalmin(Anewid));

[~,index] = ismembertol(max(AAA),strainone{:,1}, 'ByRows', true, ...

'OutputAllIndices', true, 'DataScale', 1);

if row{1,1} == 0

vv =[0.01501 0.0275 0.0207 0.0229 0.030 0.0440 0.01948 0.011 0.03416...

0.0140 0.02]

[~,index] = ismembertol(any(vv),strainone{:,1}, 'ByRows', true, ...

'OutputAllIndices', true, 'DataScale', 1);

row = index;

if row{1,1} == 0

int = input('enter value base on the ')

[~,index] = ismembertol(int,strainone{:,1}, 'ByRows', true, ...

'OutputAllIndices', true, 'DataScale', 1);

row = index;

else row{1,1} == 0

limit = 1e-3;

abs(strainone(1:end) - 0.02) < limit;

index = m;

intervalue(R) = input('enter value base on the ')

[~,index] = ismembertol(intervalue,strainone{:,1}, 'ByRows', true, ...

'OutputAllIndices', true, 'DataScale', 1);

row =index;

m=m+1;

end

end

end

end

end

end

end

row = [row{1,1}(1,1)];

%% new graph data

bottomhalf=array2table((((file.array.Extension(row:end)- file.array.Extension(row,1))./16)+ ...

file.array.Strain1(row,1)));

bottomtop = array2table(file.array.Strain1(1:row-1));

% combinding found data

newstressval =[bottomtop;bottomhalf];

[Au,~,ix] = unique(bottomhalf{:,1},'stable');

tally = accumarray(ix,1);

keep = 2< tally <4;

out1 = [Au(keep), tally(keep)];

Ai = ismember(bottomhalf{:,1},out1(:,1));

Anew = bottomhalf{:,1}.* Ai;

AA = Anew(islocalmin(Anew));

% finding Elongation

newval = table2array(newstressval);

a= newstressval.Var1(end,end);

bb =max(file.array.Strain1(1:row-1))

[~,ind] = ismembertol(AA(end),bottomhalf{:,1}, 'ByRows', true, ...

'OutputAllIndices', true, 'DataScale', 1);

r = [ind{1,1}(end,1)];

truev_str(i,:)=AA(end);

endtruev =table2array(Tenstress);

truev_stress(i,:)= endtruev(r,1);

% finding peak

peakvalue(i,:) = table2array(array2table(max(findpeaks(Tenstress{:,1}))));

[~,idxs] = ismembertol(peakvalue(i,:),Tenstress{:,1}, 'ByRows', true, ...

'OutputAllIndices', true, 'DataScale', 1);

peak_strian(i,:) = newval(idxs{1,1})

L = length(newstressval.Var1);

%% saving graph data

[newgraphdata] = zeros(L,1);

k= k+1

for k = 1:1:98

if k == 1

newgraphdata(:,1) = newval;

Tg = table (newgraphdata,'VariableNames',{'true data'})

Graphdata = table2array(Tg)

save(['graphdata_' num2str(ii) '.mat'])

fgraph = 'Graphdatanew.xlsx';

writetable(Tg,fgraph,'sheet',num2str(ii));

continue

end

end

%% plotting

figure(ii);

pause(1)

hold all

p1 = plot(strainone{:,1},Tenstress{:,1},'--g');

p2 = plot (engg_exten{:,1},Tenstress{:,1},'b--');

p3 = plot(newstressval{:,1},Tenstress{:,1},'k','LineWidth',2);

xlim auto

grid on

title('Specimen strain stree curve # ',num2str(ii))

xlabel('strian \epsilon')

ylabel('stress \sigma (MPa)')

legend([p1,p2,p3],{'strain one','extension strian','true strian'},'Location','best')

xticklabels('auto')

fig_data = strcat('FIG_',num2str(i),'_',num2str(ii));

print(figure(ii),fig_data,'-dpng','-r400');

% pause(1)

z=z+1;

%% creating output data excel file

sheet =z;

T = table(truev_str,peakvalue,peak_strian,'VariableNames',{'strain','peak value','tensile strian'})

fname = 'finaldata.xlsx';

end

writetable(T,fname,'Sheet',1,'Range','A1')

Answer 1

[Dinesh]

Hi Shaghayegh.

For your MATLAB application, after loading and plotting the initial graph, you can enhance interactivity by incorporating a slider. Attach the slider to your data points so that as it moves, it updates a specific point on your graph. Correspondingly, an editable field can display the value of the current data point, which can then be used for further plotting or calculations. To automate the process of loading new files, implement a "Next" button in your app. Upon each press, increment a file index to load the subsequent file from a predefined list or directory, update the necessary data arrays, and then refresh the plot with the new data.

To efficiently manage the sequential loading of data (like iterating through 100 data files), you can maintain a counter or index as part of your app's state (defined in properties). Increment this index each time the "Next" button is clicked and use it to reference the next file to be loaded. Instead of copy-pasting the load function, encapsulate it into a reusable function or method within your app, passing the file index or name as a parameter. This way, each click of the "Next" button calls this function, effectively loading and plotting the new data set. By structuring your app to modularly handle these tasks, you ensure a cleaner, more maintainable codebase and a smoother user experience.

The following are the links to the documentation for button, slider and properties in app designer:

https://www.mathworks.com/help/matlab/ref/matlab.ui.control.button-properties.html

https://www.mathworks.com/help/matlab/ref/uislider.html

https://www.mathworks.com/help/matlab/creating_guis/share-data-across-callbacks-in-app-designer.html