hi i have this matrix :
Loudness=[2.79;3.16;3.71;2.29;2.49;2.64;2.9;2.79;2.91;3.35];
FlucStr=[0.0256;0.0277;0.0311;0.0246;0.021;0.0199;0.0194;0.0256;0.0213;0.0208];
Roughness=[0.491;0.6;0.728;0.34;0.425;0.515;0.617;0.491;0.389;0.438];
Sharpness=[1.03;1.11;1.21;0.887;0.934;0.954;0.985;1.03;1.04;1.12];
Leq=[39.7;40.9;42.6;38.1;38.9;39.5;40.6;39.7;40.3;41.7];
SIL=[29.4;30.9;32.9;26.9;28;28.8;30.1;29.4;28.8;30];
Tonality=[0.133;0.128;0.113;0.153;0.14;0.131;0.118;0.133;0.203;0.18];
Kurtosis=[2.2;2.2;2.2;2.44;2.49;2.48;2.45;2.2;2.39;2.38];
subjective=[7.5;7.02;6.94;7.91;7.96;7.91;7.78;7.42;7.86;7.47];
metriche=[Loudness FlucStr Roughness Sharpness Leq SIL Tonality Kurtosis];
and i need to select with the command for loop 2 every combination of column vectors like:
Loudness FlucStr, Loudness FlucStr , Loudness Roughness, Loudness Sharpness, Loudness Leq, Loudness SIL , Loudness Tonality, Loudness Kurtosis,
FlucStr Roughness, FlucStr Sharpness, FlucStr Leq, FlucStr SIL, FlucStr Tonality, FlucStr Kurtosis, ......................ecc

 Accepted Answer

use nchoosek to get all the pairs:
Loudness=[2.79;3.16;3.71;2.29;2.49;2.64;2.9;2.79;2.91;3.35];
FlucStr=[0.0256;0.0277;0.0311;0.0246;0.021;0.0199;0.0194;0.0256;0.0213;0.0208];
Roughness=[0.491;0.6;0.728;0.34;0.425;0.515;0.617;0.491;0.389;0.438];
Sharpness=[1.03;1.11;1.21;0.887;0.934;0.954;0.985;1.03;1.04;1.12];
Leq=[39.7;40.9;42.6;38.1;38.9;39.5;40.6;39.7;40.3;41.7];
SIL=[29.4;30.9;32.9;26.9;28;28.8;30.1;29.4;28.8;30];
Tonality=[0.133;0.128;0.113;0.153;0.14;0.131;0.118;0.133;0.203;0.18];
Kurtosis=[2.2;2.2;2.2;2.44;2.49;2.48;2.45;2.2;2.39;2.38];
subjective=[7.5;7.02;6.94;7.91;7.96;7.91;7.78;7.42;7.86;7.47];
metriche=[Loudness FlucStr Roughness Sharpness Leq SIL Tonality Kurtosis];
pairList = nchoosek(1:8,2);
for ii = 1:size(pairList,1)
thisMatrix = metriche(:,pairList(11,:)) % dispaly to screen
end

2 Comments

can i do this with 3 or 4 or all vector column?
to get all combinations of 3 columns, use nchoosek(1:8,3)
to get all combinations of 4 columns, use nchoosek(1:8,4)

Sign in to comment.

More Answers (0)

Categories

Find more on Statistics and Machine Learning Toolbox in Help Center and File Exchange

Community Treasure Hunt

Find the treasures in MATLAB Central and discover how the community can help you!

Start Hunting!