Save array values separetly in cells during a for loop

Hello,

I have a for loop that returns in each iteration a 6x1 array. I want to save the value of the 6 elements in a different cell so in the end I have a 6x1 cell with 2500 (for loop iteration) elements.

function [qdd,qds,qs]= qsiguiente(EM,torque,E2,zvel,deltaT,zpos,n,i)
            %qdd is a 6x1 array
            qdd= EM\(torque-E2);
           
            
            %speed
            for indx=1:6
                %%%%%%
                 % MY APROACH (not working) convert this 6x1 array to a 6x1
                 % cell with 2500 iterations
                qdd{indx,1}=qdd(indx,1);
                %%%%%%
                
                
                qdd{indx,1}=qdd(indx,1);
                qds(indx,1)=zvel{indx}(1,i)+deltaT*qdd(indx,1);
    
                % position
                qs(indx,1)=zpos{indx}(1,i)+deltaT*qds(indx,1);
                
            end
end

Answer 1

[Voss]

You cannot convert a numeric matrix to a cell array in-place like that, but you can make a new cell array variable and do it:

qdd = rand(6,1);
qdd_cell = cell(size(qdd));
for indx = 1:numel(qdd)
    qdd_cell{indx,1} = qdd(indx,1);
end
disp(qdd); disp(qdd_cell);

    0.1979
    0.8719
    0.6815
    0.9625
    0.4098
    0.6827

    {[0.1979]}
    {[0.8719]}
    {[0.6815]}
    {[0.9625]}
    {[0.4098]}
    {[0.6827]}

Or, simpler:

qdd_cell = num2cell(qdd);
disp(qdd); disp(qdd_cell);

    0.1979
    0.8719
    0.6815
    0.9625
    0.4098
    0.6827

    {[0.1979]}
    {[0.8719]}
    {[0.6815]}
    {[0.9625]}
    {[0.4098]}
    {[0.6827]}

However, I'm not sure a cell array is the best choice for what you want to do. If the idea is that each iteration adds a new element to each cell of qdd_cell, why not just use a 2D numeric matrix?

That is, instead of doing this:

qdd_cell = num2cell(qdd);
N_iterations = 100;
for jj = 1:N_iterations
    for indx = 1:numel(qdd)
        qdd_cell{indx}(end+1) = randn();
    end
end
disp(qdd_cell);

    {[0.1979 1.3184 -0.4066 0.2984 0.4895 0.5974 -0.0229 -1.1849 -0.4800 -1.0499 -0.4783 1.2495 -0.3460 2.1856 -0.3872 0.4493 0.3742 -0.9162 2.1993 0.7583 -0.3564 0.3000 1.0370 -0.3882 1.1593 1.1833 -0.4546 0.5094 -0.0470 … ]}
    {[    0.8719 -1.1574 2.6773 -0.4751 0.0783 0.0431 -0.0412 -1.0519 -0.3133 -1.6014 -2.7592 -0.4468 -0.4487 0.3383 1.3248 1.3718 -0.1225 -0.9849 -0.1420 -2.1463 0.1925 0.8244 0.7885 -0.2629 -0.2415 -0.2744 0.7501 0.6819 … ]}
    {[      0.6815 1.3340 -0.1197 2.2514 0.0535 0.4672 -0.4069 -0.3475 -1.4043 0.9099 0.8901 1.2388 -1.7230 -1.0479 0.0235 -0.2098 0.7027 -0.2710 -1.8637 0.4115 -0.3248 -0.7923 -0.6348 -0.5695 0.2774 0.7003 0.4823 -0.3350 … ]}
    {[     0.9625 0.8388 -0.4657 -3.1278 -0.5768 0.6173 1.5956 0.8062 -0.7343 -0.5167 -0.5327 0.9215 -1.1369 -2.6464 0.4665 -0.5237 -0.2613 -0.1988 -0.5226 -0.6931 1.2769 -1.4648 0.4755 0.7316 2.7159 0.0724 1.6769 -0.7795 … ]}
    {[   0.4098 -0.7810 -0.5091 0.2972 0.5440 -0.1566 -1.0752 -1.2345 1.2092 -1.0769 -0.1973 2.1954 2.9317 0.1247 0.5735 -1.5319 -0.8353 -0.4097 -1.3167 1.7274 -0.3101 -0.4680 0.0488 0.5104 -0.5825 -0.3463 -1.4754 -1.3549 … ]}
    {[     0.6827 -0.3138 -0.7544 -2.0646 0.8569 -0.4641 -0.0817 -0.2468 0.0918 0.2039 1.7584 0.4713 -0.0365 0.0734 1.0328 0.0663 -0.3027 -0.1675 -1.0524 -0.0111 0.7884 -1.6948 -1.2475 -1.2604 -1.8228 1.0890 0.3902 0.0135 … ]}

You can do this:

qdd_matrix = NaN(numel(qdd),N_iterations);
for jj = 1:N_iterations
    for indx = 1:numel(qdd)
        qdd_matrix(indx,jj) = randn();
    end
end
disp(qdd_matrix);

  Columns 1 through 22

   -2.1150   -1.2348    0.9292   -1.0466    0.0433    0.6537   -0.5743    1.5840    0.5644   -1.0570    0.3420   -1.5404   -0.1146    1.2409    1.0188    1.1134    0.1178   -1.4640   -0.8415   -0.7508    0.1603    0.6251
    0.2291   -0.4691   -0.6938   -0.9004   -0.1304   -1.6158    0.3462    0.0924    0.5912   -0.5214   -0.8440   -0.7224    1.4801    0.1292   -0.5733    0.1301   -0.0957    2.2561    1.1594    1.3208   -0.7286    1.6529
    0.9144    0.0766   -1.4980    0.4476    1.0194   -1.0746   -0.1578   -1.9101    0.4913   -0.7782    0.4552   -1.4068   -0.3081   -1.5103   -0.4787   -0.2321    1.4489   -0.7285    0.0333    0.7718    0.6036    0.6451
    0.1516   -0.8545   -1.7877    1.8617    1.2383   -0.5886   -0.6822    0.7587    0.9764    0.2486   -0.8648   -0.6014    0.1770   -0.8365    0.1741    1.3796    0.7802   -0.5137    0.7908    0.4076    0.2563   -0.6937
    0.6228    0.7938   -0.0501   -1.6762   -0.1991   -0.4979   -2.0716   -0.3895    0.4143    0.0009    1.2718   -0.5522   -0.6777    0.1095    0.2123    1.1560    0.8160   -1.4190   -0.6498   -1.7572   -1.5819   -0.4839
   -1.5969    1.6190   -1.1820    0.8032    0.1683   -0.5896   -0.8892   -1.8902   -2.8493   -1.7496    0.1985   -2.3295    0.9767   -1.4918   -0.3436   -0.4942    0.5727    0.7649    0.5417   -0.5040   -0.9051    1.9272

  Columns 23 through 44

    1.1653   -1.5050    0.1995    1.5419    0.9729   -0.1748   -0.1478   -0.2871   -0.5201   -1.9360    0.0029   -0.0855    0.6906    0.5626   -0.0357    0.1421   -0.7448    0.9392    0.3399   -0.8960   -1.0805    1.0545
    1.2576   -0.3041    1.1289   -0.7453    0.9692   -0.2980    0.9635    0.8867   -0.3714    0.2878    0.8496   -0.9332    0.2838   -0.8079    0.0897    1.8997    0.9894   -0.6837   -0.5924   -0.3025    0.1638    0.8526
   -1.0075   -1.3231   -1.4752    0.9485   -0.2493    0.3257   -0.2919    0.4093    0.0534   -0.0797    0.1167    2.0805    0.1490   -1.5117   -0.4243   -0.1472    0.0891    0.7442    0.1935   -1.0764   -0.0834    0.6888
    0.2471   -0.5945   -1.5464    1.2730    0.5871   -1.8472   -0.0759    0.8716    0.2530    0.4055   -0.3894    1.2459   -0.5138   -0.1815   -0.7127    1.0157   -1.3347    0.0343   -0.4816   -0.9803   -1.5198   -0.7442
   -1.2696   -0.4877    1.0498   -1.6611   -2.1780   -0.7519   -0.0573    1.8737   -0.5333    0.6133    0.0551   -0.1731    0.9421    0.5260    0.4575   -1.6644   -0.2699   -0.3135   -0.4243    2.5099   -0.7946   -0.7059
   -1.3087    0.9230   -0.5398   -1.0544    0.4877    1.8475   -0.0171    1.5016    0.6639   -2.0277    0.9118   -1.6037    0.1726   -0.2693   -1.6754    0.3091   -0.4914    0.4172    0.1470    1.5454   -0.9659   -0.3808

  Columns 45 through 66

   -0.2427    0.6006    0.7881    0.1452   -0.2661    0.8255    0.7855    0.2592    0.1963    0.0686    0.6204   -0.0825   -2.7009    0.5087   -0.7471    0.6285    0.8582    0.3182    0.4012    0.5414   -0.4635   -0.8297
   -0.8376   -0.6327   -1.7207    0.2507   -2.2007    0.2470   -1.4210    0.9207   -0.9699   -0.1680    0.3564   -0.2788   -0.0111    0.4384    1.1022   -0.9073   -1.5230   -0.4111    0.9419   -0.8387   -1.1460    1.2086
    2.0568   -0.2750    0.0769    0.0925   -0.0499    0.5940   -0.1154   -1.2031   -1.8675   -0.7579   -0.0921   -0.0010    0.6037    0.1765    0.0018    0.5480   -0.0300    1.3002   -0.3101    0.6420   -0.0104   -0.5437
    1.0293    0.5553    0.2856    0.7490    0.7516    0.8262    1.4713   -0.3601    0.4403    0.8954   -0.6730    0.6993   -0.8034    0.7322    0.1828    0.6300    0.8411    0.8548   -0.5231    1.9126   -0.1628    1.8854
   -1.4363    0.3748   -0.4122    0.0668    0.4038    3.2295    1.8983   -0.4170   -1.7229   -1.3898   -1.4574   -0.5795   -1.0599   -0.6753    0.7388    0.5745    0.4388   -0.2170   -0.0276   -1.1328    1.3301   -0.4120
    1.1222    1.6037   -0.9076   -2.0337   -0.0425    0.9924    0.5339   -0.9943    0.4461    0.0593    0.4277    1.6696   -1.1686   -0.9353   -1.0913    0.4382   -0.5750   -0.1822   -1.5486   -1.3129   -0.7827   -0.4636

  Columns 67 through 88

    1.5375   -0.6172    0.7630    1.4582    0.4960    1.0441    0.1139    0.8479    0.8904   -0.0655    0.5224    0.3396    0.4863    0.4904    0.4259   -1.1700    0.9905    0.7595    0.4921   -0.0377   -0.7438    0.2945
   -1.7675    0.0912   -0.7481   -1.8178    2.2909   -0.9219   -0.3296    1.4905   -0.5049    0.3704   -1.0991    0.0010   -0.5068    0.2767    0.0557    1.7974   -0.4277   -0.4161   -1.5677    0.3072    0.4226    1.2113
    1.8291    0.4297   -0.0395    0.7116   -0.3161    0.2870   -1.6942    0.2283   -0.6939    1.9671    0.9813    1.2012    0.8428   -1.2425    0.2013   -0.9363   -0.5069   -1.0491    2.1922   -0.9870    1.2962    0.1695
    0.6201   -2.1203    0.9199   -0.4952    0.5098   -0.3206    1.0467    0.4606   -1.3862    1.7105   -0.4254   -0.3584   -0.4277    0.2223    0.7250    0.5416    0.5245   -0.7529    1.0604    0.0063   -1.1043   -0.3598
    0.3082   -1.2486   -0.6466    0.5877    0.8581   -1.6631    1.4379    0.2711   -0.9368    0.2604   -1.0279   -0.6419    1.3876   -0.7034    0.4954   -1.3502   -1.2316    0.3003    0.4692    0.0975   -0.8908    0.3189
    0.8925   -1.0722   -0.4349    1.5501   -0.3177    0.9701   -0.7283   -0.0149    1.7196   -1.2338   -0.1987    0.3414    0.4321    0.4417    0.0913   -1.4343    0.2452   -1.1739   -1.5984   -1.4487    1.5659   -0.4672

  Columns 89 through 100

   -2.2876    0.8133   -1.3842    0.8663   -0.2993    0.5435   -0.5635   -0.8349   -1.1232    0.0470    0.6798   -0.5021
   -1.8427   -1.1277   -0.4006   -0.6520   -1.3521    0.0526   -0.6934    0.7613    0.9519   -0.9534   -1.3110   -0.4334
    0.1553    0.1519    1.0008   -0.0929   -1.4677    1.8407   -0.7559    0.2547   -0.5550    2.5657   -0.8447   -0.5390
   -0.8529    0.1275   -0.2916   -0.5304   -0.4930    2.2017   -1.4175    0.2243   -1.2064    0.0160    1.1907   -0.2501
    0.7980   -0.2192    0.0178   -1.2111    1.0719   -0.5097    1.7664    0.8944   -0.5343   -0.3339   -0.7654   -0.6763
   -0.6831   -0.8456    0.1670   -0.5257    0.7193   -0.9483   -0.3974    0.0385   -2.3019    0.4462   -0.2525   -1.1134

[mikel lasa]

thanks!