Assign values of .mat files into matrix

Question

Tessa Kol 2020-10-19

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https://ww2.mathworks.cn/matlabcentral/answers/619078-assign-values-of-mat-files-into-matrix

编辑： Tessa Kol 2020-10-21

Dear all,

I have multiple .mat files (see attachment). I want to organize the MFR_mod variables within the those .mat files into one matrix. I feel like there is a smarter way then what I tried below. This will take me forever, since MFR_mod goes from 1 until 81.

for ii = 1:20
    load(['silomodresults',num2str(ii),'.mat'])
end
MFR_tot = [MFR_mod1; MFR_mod2; MFR_mod3; MFR_mod4; MFR_mod5; MFR_mod6; MFR_mod7; MFR_mod8; MFR_mod9; MFR_mod10; MFR_mod11; MFR_mod12; MFR_mod13; MFR_mod14; MFR_mod15; MFR_mod16; MFR_mod17; MFR_mod18; MFR_mod19; MFR_mod20];

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Answer 1

Stephen23 2020-10-19

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https://ww2.mathworks.cn/matlabcentral/answers/619078-assign-values-of-mat-files-into-matrix#answer_518408

编辑：Stephen23 2020-10-19

在 MATLAB Online 中打开

silomodresults.zip

D = 'path to the folder where the files are saved';
S = dir(fullfile(D,'silomodresults*.mat'));
C = {};
for k = 1:numel(S)
    F = fullfile(D,S(k).name);
    T = load(F,'-regexp','^MFR_mod\d+$');
    N = fieldnames(T);
    V = str2double(regexp(N,'\d+','once','match'));
    C(V) = struct2cell(T); %#ok<SAGROW>
end
M = vertcat(C{:}); % optional

Giving:

>> size(M)
ans =
    81     1
>> plot(M)

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Tessa Kol 2020-10-19

在 MATLAB Online 中打开

I tried using a for/while loop as you suggested. I used the silomoddata1.mat, silomoddata2.mat, silomoddata3.mat, silomoddata4.mat and silomoddata5.mat. But something is wrong. Running the code below is taking a very long time and I stopped the simulation eventually. Changing idx manually each time doesn't bother me that much.

TimeStepstable = [3.04, 6.5];
for ii = 1:5
    load(['silomoddata',num2str(ii),'.mat']);
    N_run = numel(runData_struc);
% Pre-allocate one cell for each loop variable
particlesInSilo = cell(max(cellfun(@numel,runData_struc)), N_run);
siloMass = particlesInSilo;
time = particlesInSilo;
k =1;
for i = 1:N_run
    for j = 1:numel(runData_struc{i})
        %Count the number of particles in the silo (silo outlet is located at z = 0.3 m)
        particlesInSilo{j,i} = find(expData_struc{1,i}{1,j}(:,3)>=0.3);
        % Multiply the number of particles with the volume of the particle
        siloMass{j,i} = sum(expData_struc{1,i}{1,j}(cell2mat(particlesInSilo(j,i)),6));
        % Corresponding time step
        time{j,i} = runData_struc{1,i}{1,j}(:,2);
        k = k + 1;
    end
end
% Index the time step values closest to the desired time step where the mass flow is stable
for i = 1:N_run
    for t = 1:numel(TimeStepstable)
        [~, idxtime(t,i)] = min(abs(cell2mat(time(:,i))-TimeStepstable(t)));
    end
end
% Calculate the mass flow rate (MFR) for the stable region
for i = 1:N_run
    siloMass_stable{i} = cell2mat(siloMass(idxtime(1,i):idxtime(2,i),i));
    time_stable{i} = cell2mat(time(idxtime(1,i):idxtime(2,i),i));
    opts = fitoptions('Method', 'LinearLeastSquares', 'Robust', 'off');
    [MFR_fit{i}, GoodnessOfFit] = fit(time_stable{i}(:,1),siloMass_stable{i}(:,1),'poly1',opts);
    MFR_mod(i) = abs(MFR_fit{i}.p1);
end
while ii == 1
    idx = [   1];
save(['silomodresultsv2',num2str(ii),'.mat'],'MFR_mod','idx')
end
while ii == 2
    idx = [   2];
save(['silomodresultsv2',num2str(ii),'.mat'],'MFR_mod','idx')
end
while ii == 3
    idx = [   3];
save(['silomodresultsv2',num2str(ii),'.mat'],'MFR_mod','idx')
end
while ii == 4
    idx = [   4];
save(['silomodresultsv2',num2str(ii),'.mat'],'MFR_mod','idx')
end
while ii == 5
    idx = [   5,   11,   20,   38,  81];
save(['silomodresultsv2',num2str(ii),'.mat'],'MFR_mod','idx')
end
end

Tessa Kol 2020-10-19

在 MATLAB Online 中打开

I changed it to a if/else loop and it seems to work. I will let you know tomorrow if everything went well from here and if the intended goal is reached.

TimeStepstable = [3.04, 6.5];
for ii = 1:5
    load(['silomoddata',num2str(ii),'.mat']);
    N_run = numel(runData_struc);
% Pre-allocate one cell for each loop variable
particlesInSilo = cell(max(cellfun(@numel,runData_struc)), N_run);
siloMass = particlesInSilo;
time = particlesInSilo;
k =1;
for i = 1:N_run
    for j = 1:numel(runData_struc{i})
        %Count the number of particles in the silo (silo outlet is located at z = 0.3 m)
        particlesInSilo{j,i} = find(expData_struc{1,i}{1,j}(:,3)>=0.3);
        % Multiply the number of particles with the volume of the particle
        siloMass{j,i} = sum(expData_struc{1,i}{1,j}(cell2mat(particlesInSilo(j,i)),6));
        % Corresponding time step
        time{j,i} = runData_struc{1,i}{1,j}(:,2);
        k = k + 1;
    end
end
% Index the time step values closest to the desired time step where the mass flow is stable
for i = 1:N_run
    for t = 1:numel(TimeStepstable)
        [~, idxtime(t,i)] = min(abs(cell2mat(time(:,i))-TimeStepstable(t)));
    end
end
% Calculate the mass flow rate (MFR) for the stable region
for i = 1:N_run
    siloMass_stable{i} = cell2mat(siloMass(idxtime(1,i):idxtime(2,i),i));
    time_stable{i} = cell2mat(time(idxtime(1,i):idxtime(2,i),i));
    opts = fitoptions('Method', 'LinearLeastSquares', 'Robust', 'off');
    [MFR_fit{i}, GoodnessOfFit] = fit(time_stable{i}(:,1),siloMass_stable{i}(:,1),'poly1',opts);
    MFR_mod(i) = abs(MFR_fit{i}.p1);
end
if ii == 1
    idx = [   1];
save(['silomodresultsv2',num2str(ii),'.mat'],'MFR_mod','idx')
elseif ii == 2
    idx = [   2];
save(['silomodresultsv2',num2str(ii),'.mat'],'MFR_mod','idx')
elseif ii == 3
    idx = [   3];
save(['silomodresultsv2',num2str(ii),'.mat'],'MFR_mod','idx')
elseif ii == 4
    idx = [   4];
save(['silomodresultsv2',num2str(ii),'.mat'],'MFR_mod','idx')
elseif ii == 5
    idx = [   5,   11,   20,   38,  81];
save(['silomodresultsv2',num2str(ii),'.mat'],'MFR_mod','idx')
end
end

Tessa Kol 2020-10-20

在 MATLAB Online 中打开

Based upon your code and hints I managed to organize the data into a single matrix (see code below). Maybe it can be even shorter/nicer, but for now this works perfectly.

TimeStepstable = [3.04, 6.5];
TimeStepsettle = [1.56];
V_silo = 0.66*0.60*0.053-0.25*0.053*(0.25*tand(45));
%% Objective function input data
for ii = 19:20
    load(['silomoddata',num2str(ii),'.mat']);
    N_run(ii) = numel(runData_struc);
    
    
    % Pre-allocate one cell for each loop variable
    particlesInSilo = cell(max(cellfun(@numel,runData_struc)), N_run(ii));
    siloMass = particlesInSilo;
    time = particlesInSilo;
    k =1;
    for i = 1:N_run(ii)
        for j = 1:numel(runData_struc{i})
            %Count the number of particles in the silo (silo outlet is located at z = 0.3 m)
            particlesInSilo{j,i} = find(expData_struc{1,i}{1,j}(:,3)>=0.3);
            % Multiply the number of particles with the volume of the particle
            siloMass{j,i} = sum(expData_struc{1,i}{1,j}(cell2mat(particlesInSilo(j,i)),6));
            % Corresponding time step
            time{j,i} = runData_struc{1,i}{1,j}(:,2);
            k = k + 1;
        end
    end
    % Index the time step values closest to the desired time step where the mass flow is stable
    for i = 1:N_run(ii)
        for t = 1:numel(TimeStepstable)
            [~, idxtime(t,i)] = min(abs(cell2mat(time(:,i))-TimeStepstable(t)));
        end
    end
    % Calculate the mass flow rate (MFR) for the stable region
    for i = 1:N_run(ii)
        siloMass_stable{i} = cell2mat(siloMass(idxtime(1,i):idxtime(2,i),i));
        time_stable{i} = cell2mat(time(idxtime(1,i):idxtime(2,i),i));
        opts = fitoptions('Method', 'LinearLeastSquares', 'Robust', 'off');
        [MFR_fit{i}, GoodnessOfFit] = fit(time_stable{i}(:,1),siloMass_stable{i}(:,1),'poly1',opts);
        MFR_mod(i) = abs(MFR_fit{i}.p1);
    end
    
    % Bulk density
    for i = 1:N_run(ii)
        for s = 1:numel(TimeStepsettle)
            [~, idxtimesettle(s,i)] = min(abs(cell2mat(time(:,i))-TimeStepsettle(s)));
        end
    end
    for i = 1:N_run(ii)
        siloMass_settle(i) = cell2mat(siloMass(idxtimesettle(1,i),i));
        rho_bmod(i) = siloMass_settle(i)/V_silo;
    end
    
    if ii == 1
        idx = [1];
        save(['silomodresults',num2str(ii),'.mat'],'MFR_mod','rho_bmod','idx')
    elseif ii == 2
        idx = [2];
        save(['silomodresults',num2str(ii),'.mat'],'MFR_mod','rho_bmod','idx')
    elseif ii == 3
        idx = [3];
        save(['silomodresults',num2str(ii),'.mat'],'MFR_mod','rho_bmod','idx')
    elseif ii == 4
        idx = [4];
        save(['silomodresults',num2str(ii),'.mat'],'MFR_mod','rho_bmod','idx')
    elseif ii == 5
        idx = [5,11,20,38,81];
        save(['silomodresults',num2str(ii),'.mat'],'MFR_mod','rho_bmod','idx')
    elseif ii == 6
        idx = [12,15,31,55,65];
        save(['silomodresults',num2str(ii),'.mat'],'MFR_mod','rho_bmod','idx')
    elseif ii == 7
        idx = [21,22,23,24,25];
        save(['silomodresults',num2str(ii),'.mat'],'MFR_mod','rho_bmod','idx')
    elseif ii == 8
        idx = [30,32,33,34,35];
        save(['silomodresults',num2str(ii),'.mat'],'MFR_mod','rho_bmod','idx')
    elseif ii == 9
        idx = [40,41,42,43,44];
        save(['silomodresults',num2str(ii),'.mat'],'MFR_mod','rho_bmod','idx')
    elseif ii == 10
        idx = [13,14,16,17,18];
        save(['silomodresults',num2str(ii),'.mat'],'MFR_mod','rho_bmod','idx')
    elseif ii == 11
        idx = [50,51,52,53,54];
        save(['silomodresults',num2str(ii),'.mat'],'MFR_mod','rho_bmod','idx')
    elseif ii == 12
        idx = [60,61,62,63,64];
        save(['silomodresults',num2str(ii),'.mat'],'MFR_mod','rho_bmod','idx')
    elseif ii == 13
        idx = [70,71,72,73,74];
        save(['silomodresults',num2str(ii),'.mat'],'MFR_mod','rho_bmod','idx')
    elseif ii == 14
        idx = [19,26,27,28,29];
        save(['silomodresults',num2str(ii),'.mat'],'MFR_mod','rho_bmod','idx')
    elseif ii == 15
        idx = [6,7,8,9,10];
        save(['silomodresults',num2str(ii),'.mat'],'MFR_mod','rho_bmod','idx')
    elseif ii == 16
        idx = [36,37,38,39,45];
        save(['silomodresults',num2str(ii),'.mat'],'MFR_mod','rho_bmod','idx')
    elseif ii == 17
        idx = [46,47,48,49,56];
        save(['silomodresults',num2str(ii),'.mat'],'MFR_mod','rho_bmod','idx')
    elseif ii == 18
        idx = [57,58,59,66,67];
        save(['silomodresults',num2str(ii),'.mat'],'MFR_mod','rho_bmod','idx')
    elseif ii == 19
        idx = [68,69,75,76];
        save(['silomodresults',num2str(ii),'.mat'],'MFR_mod','rho_bmod','idx')
    elseif ii == 20
        idx = [77,78,79,80];
        save(['silomodresults',num2str(ii),'.mat'],'MFR_mod','rho_bmod','idx')
    end
end
%% Combining input data
MFR_modtot = zeros(1,81);
rho_bmodtot = zeros(1,81);
for ii = 1:20
    S(ii) = load(['silomodresults',num2str(ii),'.mat']);
    MFR_modtot(S(ii).idx) = S(ii).MFR_mod;
    rho_bmodtot(S(ii).idx)= S(ii).rho_bmod;
end

Stephen23 2020-10-20

在 MATLAB Online 中打开

You could define all of the indices before the loop:

idc = {1,2,3,4,[5,11,20,38,81],[12,15,31,55,65],...};

and then inside the loop you can replace that entire huge lbock of code

if i== ..
    ..
elseif i== ..
    ..
    ..
end

with just this:

idx = idc{ii};
fnm = sprintf('silomodresults%d.mat',ii);
save(fnm,'MFR_mod','rho_bmod','idx')

It is still a mystery to me, how those indices are defined.

Tessa Kol 2020-10-21

编辑：Tessa Kol 2020-10-21

Thank you for the tip!

The indices are based on poor folder structure management from my side.

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Answer 2

Ameer Hamza 2020-10-19

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此回答的直接链接

https://ww2.mathworks.cn/matlabcentral/answers/619078-assign-values-of-mat-files-into-matrix#answer_518273

编辑：Ameer Hamza 2020-10-19

在 MATLAB Online 中打开

One of the major problem is naming the variables like this x1, x2, ...: https://www.mathworks.com/matlabcentral/answers/304528-tutorial-why-variables-should-not-be-named-dynamically-eval. You can try something like this

MFR_tot = zeros(1, 20);
for ii = 1:20
    data = load(['silomodresults',num2str(ii),'.mat']);
    MFR_tot(ii) = data.(sprintf('MFR_mod%d', ii))
end

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Tessa Kol 2020-10-19

编辑：Tessa Kol 2020-10-19

在 MATLAB Online 中打开

I came across the issue with eval many times in different posts. You solution didn't work unfortunatly, because the .mat files have unorganized MFR_mod. Maybe if I start from the beginning there is a better solution to this.

So first I have created 20 .mat files. Each .mat file is about 1.5 GB. So it is not possible to send it in this post.

For each .mat file I run the same code manually. The below code is an example of running the code for only the silomoddata20.mat file.

%% Loading the Data
load([pwd,'\silomoddata20.mat'])
%% Parameters
% Number of simulation runs
N_run = numel(runData_struc);
TimeStepstable = [3.04, 6.5];
TimeStepsettle = [1.56];
%% Mass flow Rate
% Pre-allocate one cell for each loop variable
particlesInSilo = cell(max(cellfun(@numel,runData_struc)), N_run);
siloMass = particlesInSilo;
time = particlesInSilo;
k =1;
for i = 1:N_run
    for j = 1:numel(runData_struc{i})
        %Count the number of particles in the silo (silo outlet is located at z = 0.3 m)
        particlesInSilo{j,i} = find(expData_struc{1,i}{1,j}(:,3)>=0.3);
        % Multiply the number of particles with the volume of the particle
        siloMass{j,i} = sum(expData_struc{1,i}{1,j}(cell2mat(particlesInSilo(j,i)),6));
        % Corresponding time step
        time{j,i} = runData_struc{1,i}{1,j}(:,2);
        k = k + 1;
    end
end
% Index the time step values closest to the desired time step where the mass flow is stable
for i = 1:N_run
    for t = 1:numel(TimeStepstable)
        [~, idxtime(t,i)] = min(abs(cell2mat(time(:,i))-TimeStepstable(t)));
    end
end
% Calculate the mass flow rate (MFR) for the stable region
for i = 1:N_run
    siloMass_stable{i} = cell2mat(siloMass(idxtime(1,i):idxtime(2,i),i));
    time_stable{i} = cell2mat(time(idxtime(1,i):idxtime(2,i),i));
    opts = fitoptions('Method', 'LinearLeastSquares', 'Robust', 'off');
    [MFR_fit{i}, GoodnessOfFit] = fit(time_stable{i}(:,1),siloMass_stable{i}(:,1),'poly1',opts);
    MFR_mod(i) = abs(MFR_fit{i}.p1);
end
%% save results
save silomodresults20.mat MFR_mod rho_bmod

I run the above code manually for every silomoddata*.mat file. Because I didn't know how to put this in a for loop.

If the whole code is in for loop I hope to get a 1x81 matrix of MFR_mod. The problem with that is the order.

silomoddata1.mat contains simulationrun 1

silomoddata2.mat contains simulationrun 2

silomoddata3.mat contains simulationrun 3

silomoddata4.mat contains simulationrun 4

silomoddata5.mat contains simulationrun 5, simulationrun 11, simulationrun 20, simulationrun 38 and simulationrun 81

silomoddata6.mat contains simulationrun 12, simulationrun 15, simulationrun 31, simulationrun 55 and simulationrun 65

silomoddata20.mat contains simulationrun 77, simulationrun 78, simulationrun 79, simulationrun 80

... etc.

When I calculated the MFR_mod of every silomoddata.mat file I can't just simply combine them into a matrix. The orde isn't right. That was what I am trying to achieve here, a matrix of MFR_mod in the correct order of 1 until 81.

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Answer 3

Mathieu NOE 2020-10-19

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在 MATLAB Online 中打开

hello

seems all your mat file contains the same size of data

so the modification of you r code is fairly simple - if I understand what you want :

MFR_tot = [];
for ii = 1:20
    data = load(['silomodresults',num2str(ii),'.mat']);
    MFR_tot = [MFR_tot; data];  % concatenation
end
    

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Mathieu NOE 2020-10-19

ok , now I understand

is there any possibility for you to generate dummy mat files , but much smaller. I'd like to try to solve it

I think the key thing is to extract the field (variables) names and then re order the whole thing based on the numeric content of the variable name

That shoudn't be too difficult for someone fluent in string / structure processing (I don't mean me only !)

I'll give it a try tomorrow if you can send me some dummy mat files in between

Tessa Kol 2020-10-19

Dear Mathieu,

I compressed silomoddata5.mat silomoddata6.mat and silomoddata20.mat into a zip file. You can download this using the link below (about 4 GB).

https://sendgb.com/xPkYbUa902H

Is this oke?

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