How can write and store my data in function file to excel file ?

3 Ansichten (letzte 30 Tage)
Furat Alobaidy
Furat Alobaidy am 13 Aug. 2020
Kommentiert: Furat Alobaidy am 13 Aug. 2020
Hi , i have function contain on data as below ( different columns) , how can store each column( inside data function ) to excel file ? or save them into individual matrix?
for example :
A= avg_delay ;
B= throughput ;
...
on [max_pir, max_throughput, min_delay] = routingfullyadaptiveselthermaltopology3x3x3Route4()
data = [
% pir avg_delay throughput max_delay total_energy cores_energy routers_energy avg_power avg_cores_power avg_routers_power power_per_router static_per_router dynamic_per_router rpackets rflits
0.001 25.6335 0.0049682 192 0.000728556 0.000118972 0.000609584 7.28556e-08 1.18972e-08 6.09584e-08 2.25772e-09 1.589e-09 6.6872e-10 221 1328
0.011 25.9113 0.00552189 476 0.000792492 0.000119341 0.000673151 7.92492e-08 1.19341e-08 6.73151e-08 2.49315e-09 1.58903e-09 9.04119e-10 251 1476
0.021 24.9548 0.00396932 129 0.000730386 0.000118895 0.00061149 7.30386e-08 1.18895e-08 6.1149e-08 2.26478e-09 1.58899e-09 6.75785e-10 178 1061
0.031 28.9934 0.00347175 115 0.00073316 0.000118856 0.000614303 7.3316e-08 1.18856e-08 6.14303e-08 2.2752e-09 1.589e-09 6.86203e-10 158 928
0.041 27.7404 0.00253691 83 0.000730482 0.000118544 0.000611938 7.30482e-08 1.18544e-08 6.11938e-08 2.26644e-09 1.589e-09 6.77435e-10 108 653
0.051 29.0826 0.00255518 106 0.000733119 0.000118572 0.000614547 7.33119e-08 1.18572e-08 6.14547e-08 2.2761e-09 1.589e-09 6.87107e-10 116 683
0.061 31.6022 0.00213992 134 0.000765916 0.000118518 0.000647398 7.65916e-08 1.18518e-08 6.47398e-08 2.39777e-09 1.58902e-09 8.08751e-10 103 572
0.071 23.2826 0.00130832 89 0.000762364 0.000118063 0.000644302 7.62364e-08 1.18063e-08 6.44302e-08 2.3863e-09 1.58902e-09 7.97283e-10 51 272
0.081 29.807 0.00166667 127 0.000758546 0.000118257 0.000640289 7.58546e-08 1.18257e-08 6.40289e-08 2.37144e-09 1.58901e-09 7.82427e-10 66 363
0.091 32.2459 0.00162782 95 0.000756582 0.000118342 0.00063824 7.56582e-08 1.18342e-08 6.3824e-08 2.36385e-09 1.58901e-09 7.74841e-10 75 419
0.101 37.8125 0.00135101 110 0.000730201 0.00011841 0.00061179 7.30201e-08 1.1841e-08 6.1179e-08 2.26589e-09 1.589e-09 6.76887e-10 62 321
0.111 32.7727 0.000976431 104 0.000748178 0.000118043 0.000630135 7.48178e-08 1.18043e-08 6.30135e-08 2.33383e-09 1.58901e-09 7.44825e-10 31 174
0.121 41.8 0.00101928 94 0.000809844 0.000117999 0.000691844 8.09844e-08 1.17999e-08 6.91844e-08 2.56239e-09 1.58902e-09 9.73364e-10 21 111
0.131 41.2273 0.00139657 103 0.000731131 0.000118433 0.000612698 7.31131e-08 1.18433e-08 6.12698e-08 2.26925e-09 1.58901e-09 6.80245e-10 55 318
0.141 50.7692 0.000846931 108 0.000793249 0.000118082 0.000675168 7.93249e-08 1.18082e-08 6.75168e-08 2.50062e-09 1.58903e-09 9.11592e-10 21 109
0.151 46.0303 0.00120707 115 0.000763975 0.000118328 0.000645646 7.63975e-08 1.18328e-08 6.45646e-08 2.39128e-09 1.589e-09 8.0228e-10 43 239
0.161 62.5714 0.00105402 150 0.000757508 0.000118293 0.000639215 7.57508e-08 1.18293e-08 6.39215e-08 2.36746e-09 1.58902e-09 7.78448e-10 45 240
0.171 52.1818 0.000631313 82 0.000730147 0.000117878 0.000612269 7.30147e-08 1.17878e-08 6.12269e-08 2.26766e-09 1.589e-09 6.7866e-10 14 75
0.181 60 0.00047619 95 0.000767215 0.000117782 0.000649432 7.67215e-08 1.17782e-08 6.49432e-08 2.4053e-09 1.58902e-09 8.16287e-10 8 33
0.191 73.8421 0.000814394 139 0.00080778 0.000118052 0.000689729 8.0778e-08 1.18052e-08 6.89729e-08 2.55455e-09 1.58903e-09 9.65524e-10 27 129
0.201 62.5 0.000767677 95 0.000762804 0.000118017 0.000644787 7.62804e-08 1.18017e-08 6.44787e-08 2.3881e-09 1.58902e-09 7.9908e-10 8 38
0.211 69 0.000828283 90 0.000756177 0.000117816 0.000638361 7.56177e-08 1.17816e-08 6.38361e-08 2.3643e-09 1.58901e-09 7.75291e-10 9 41
0.221 67.5 0.000565657 114 0.000730236 0.000117939 0.000612297 7.30236e-08 1.17939e-08 6.12297e-08 2.26777e-09 1.589e-09 6.78767e-10 5 28
0.231 59.5 0.000555556 97 0.00073664 0.000117998 0.000618642 7.3664e-08 1.17998e-08 6.18642e-08 2.29127e-09 1.58901e-09 7.02258e-10 9 44
0.241 83.9474 0.000865801 140 0.000729821 0.000117985 0.000611837 7.29821e-08 1.17985e-08 6.11837e-08 2.26606e-09 1.589e-09 6.77059e-10 23 120
0.251 80.1154 0.000939394 109 0.000725549 0.000118231 0.000607318 7.25549e-08 1.18231e-08 6.07318e-08 2.24933e-09 1.589e-09 6.60325e-10 37 186
0.261 65 0.000633609 93 0.000787905 0.000118017 0.000669888 7.87905e-08 1.18017e-08 6.69888e-08 2.48107e-09 1.58903e-09 8.92038e-10 13 69
0.271 83.2308 0.00079798 122 0.000729951 0.000118065 0.000611886 7.29951e-08 1.18065e-08 6.11886e-08 2.26624e-09 1.589e-09 6.77244e-10 16 79
0.281 77.5 0.000871212 117 0.00073354 0.000118018 0.000615522 7.3354e-08 1.18018e-08 6.15522e-08 2.27971e-09 1.589e-09 6.90707e-10 14 69
0.291 72.9286 0.000761461 112 0.000736384 0.000118164 0.00061822 7.36384e-08 1.18164e-08 6.1822e-08 2.2897e-09 1.58901e-09 7.00692e-10 21 98
0.301 64.3333 0.000636364 88 0.000728682 0.000117963 0.000610719 7.28682e-08 1.17963e-08 6.10719e-08 2.26192e-09 1.589e-09 6.72922e-10 12 63
0.311 81.125 0.000846931 118 0.00073114 0.000118133 0.000613008 7.3114e-08 1.18133e-08 6.13008e-08 2.2704e-09 1.589e-09 6.81401e-10 22 109
0.321 91.75 0.000894661 115 0.000729737 0.000117962 0.000611776 7.29737e-08 1.17962e-08 6.11776e-08 2.26584e-09 1.589e-09 6.76841e-10 11 62
0.331 82.8 0.000636364 96 0.000734294 0.000117823 0.000616472 7.34294e-08 1.17823e-08 6.16472e-08 2.28323e-09 1.589e-09 6.94225e-10 13 63
0.341 76.3333 0.000631313 95 0.000728938 0.000118118 0.00061082 7.28938e-08 1.18118e-08 6.1082e-08 2.2623e-09 1.589e-09 6.73294e-10 12 50
0.351 97.2857 0.000769231 127 0.000731767 0.000117921 0.000613845 7.31767e-08 1.17921e-08 6.13845e-08 2.2735e-09 1.589e-09 6.84499e-10 18 99
0.361 86.8 0.000656566 100 0.00073546 0.00011787 0.00061759 7.3546e-08 1.1787e-08 6.1759e-08 2.28737e-09 1.58901e-09 6.98361e-10 8 39
0.371 91.4 0.000656566 96 0.000725904 0.000117865 0.000608039 7.25904e-08 1.17865e-08 6.08039e-08 2.252e-09 1.589e-09 6.62992e-10 10 52
0.381 85.5 0.000525253 102 0.000759293 0.000117855 0.000641438 7.59293e-08 1.17855e-08 6.41438e-08 2.37569e-09 1.58902e-09 7.8668e-10 5 26
0.391 95.2632 0.00118916 146 0.000783203 0.000118355 0.000664848 7.83203e-08 1.18355e-08 6.64848e-08 2.4624e-09 1.58901e-09 8.73394e-10 49 259
0.401 89.4286 0.000628507 101 0.000761524 0.000117838 0.000643687 7.61524e-08 1.17838e-08 6.43687e-08 2.38402e-09 1.58902e-09 7.95005e-10 10 56
0.411 64.5 0.000707071 70 0.00076015 0.000117694 0.000642456 7.6015e-08 1.17694e-08 6.42456e-08 2.37947e-09 1.58901e-09 7.90455e-10 2 14
0.421 100.647 0.000750361 139 0.000730178 0.000117888 0.00061229 7.30178e-08 1.17888e-08 6.1229e-08 2.26774e-09 1.589e-09 6.78741e-10 19 104
0.431 94.3333 0.000545455 100 0.000730798 0.000117935 0.000612863 7.30798e-08 1.17935e-08 6.12863e-08 2.26986e-09 1.58901e-09 6.80849e-10 5 27
0.441 80.4286 0.000568182 88 0.000730796 0.000118002 0.000612794 7.30796e-08 1.18002e-08 6.12794e-08 2.26961e-09 1.58901e-09 6.80599e-10 8 45
0.451 94.2667 0.000801347 114 0.000758086 0.000117983 0.000640102 7.58086e-08 1.17983e-08 6.40102e-08 2.37075e-09 1.58902e-09 7.81727e-10 26 119
0.461 83.5 0.00046176 107 0.000769577 0.000117946 0.000651631 7.69577e-08 1.17946e-08 6.51631e-08 2.41345e-09 1.58901e-09 8.24435e-10 9 32
0.471 98.3871 0.00126263 131 0.000758338 0.000118187 0.000640152 7.58338e-08 1.18187e-08 6.40152e-08 2.37093e-09 1.58901e-09 7.81925e-10 33 200
0.481 90.6667 0.000707071 115 0.000731416 0.000118026 0.00061339 7.31416e-08 1.18026e-08 6.1339e-08 2.27181e-09 1.58901e-09 6.82808e-10 10 49
0.491 92.2 0.000686869 98 0.000732851 0.000117944 0.000614906 7.32851e-08 1.17944e-08 6.14906e-08 2.27743e-09 1.58901e-09 6.88424e-10 8 34
];
rows = size(data, 1);
cols = size(data, 2);
data_delay = [];
for i = 1:rows/1,
ifirst = (i - 1) * 1 + 1;
ilast = ifirst + 1 - 1;
tmp = data(ifirst:ilast, cols-14+1);
avg = mean(tmp);
[h sig ci] = ttest(tmp, 0.1);
ci = (ci(2)-ci(1))/2;
data_delay = [data_delay; data(ifirst, 1:cols-14), avg ci]
end
figure(1);title('\color{red} datadelay');
hold on;
plot(data_delay(:,1), data_delay(:,2));
data_throughput = [];
for i = 1:rows/1,
ifirst = (i - 1) * 1 + 1;
ilast = ifirst + 1 - 1;
tmp = data(ifirst:ilast, cols-14+2);
avg = mean(tmp);
[h sig ci] = ttest(tmp, 0.1);
ci = (ci(2)-ci(1))/2;
data_throughput = [data_throughput; data(ifirst, 1:cols-14), avg ci]
end
figure(2);title('\color{red} data throughput');
hold on;
plot(data_throughput(:,1), data_throughput(:,2));
data_maxdelay = [];
for i = 1:rows/1,
ifirst = (i - 1) * 1 + 1;
ilast = ifirst + 1 - 1;
tmp = data(ifirst:ilast, cols-14+3);
avg = mean(tmp);
[h sig ci] = ttest(tmp, 0.1);
ci = (ci(2)-ci(1))/2;
data_maxdelay = [data_maxdelay; data(ifirst, 1:cols-14), avg ci];
end
figure(3);title('\color{red} data_maxdelay');
hold on;
plot(data_maxdelay(:,1), data_maxdelay(:,2));
data_totalenergy = [];
for i = 1:rows/1,
ifirst = (i - 1) * 1 + 1;
ilast = ifirst + 1 - 1;
tmp = data(ifirst:ilast, cols-14+4);
avg = mean(tmp);
[h sig ci] = ttest(tmp, 0.1);
ci = (ci(2)-ci(1))/2;
data_totalenergy = [data_totalenergy; data(ifirst, 1:cols-14), avg ci];
end
figure(4);;title('\color{red} datatotalenergy');
hold on;
plot(data_totalenergy(:,1), data_totalenergy(:,2));
%-------- Saturation Analysis -----------
slope=[];
for i=2:size(data_throughput,1),
slope(i-1) = (data_throughput(i,2)-data_throughput(i-1,2))/(data_throughput(i,1)-data_throughput(i-1,1));
end
for i=2:size(slope,2),
if slope(i) < (0.95*mean(slope(1:i)))
max_pir = data_throughput(i, 1);
max_throughput = data_throughput(i, 2);
min_delay = data_delay(i, 2);
break;
end
end
  2 Kommentare
dpb
dpb am 13 Aug. 2020
slope=[];
for i=2:size(data_throughput,1),
slope(i-1) = (data_throughput(i,2)-data_throughput(i-1,2))/(data_throughput(i,1)-data_throughput(i-1,1));
end
is simply
slope=diff(data_throughput(:,2))./diff(data_throughput(:,1));
Use the vectoriized opererators/functions in MATLAB as intended...
As for the Q? re: writing data; use writetable or writematrix

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