Loop through every nth row in a data frame in a function

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Reuben Addison
Reuben Addison 2023-3-22
回答： Sulaymon Eshkabilov 2023-3-22
I want to loop through specific rows to pick up data for some program I wrote and wondering if there is an efficient way of doing that. I have my coordinates in a matrix and each row represents a subject and the colums are the different orientation coordinates for a subject (see below)
In my loop I want to go through each row (each row and pick e.g "nose" for for each subject)
%% Define coil position
S.poslist{1}.pos(1).matsimnibs = [-m0n0 m1n0 -m2n0 x; -m0n1 m1n1 -m2n1 y; -m0n2 m1n2 -m2n2 z; 0 0 0 1]
I want to achieve something like this below but selecting every 4th row
S.poslist{1}.pos(1).matsimnibs = [-TargetInfo.data(4) TargetInfo.data(7) -TargetInfo.data(10) TargetInfo.data(1); -TargetInfo.data(5) TargetInfo.data(8) -TargetInfo.data(11) TargetInfo.data(2); -TargetInfo.data(6) TargetInfo.data(9) -TargetInfo.data(12) TargetInfo.data(3); 0 0 0 1]

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采纳的回答

Sulaymon Eshkabilov
Ran in:
The simpler and more efficient way would be using a logical indexing option or just use necessary indices, e.g.:
% DATA input/generation as a table array
TS = categorical({'Boy'; 'Boy';'Boy';'Boy'; 'Girl';'Girl';'Girl';'Girl';});
TN = categorical({'A'; 'B'; 'C'; 'D';'A'; 'B'; 'C'; 'D'});
DATA=table(TS);
DATA.TName=TN;
M1 = randn(numel(TN),1);
M2 = randn(numel(TN),1);
M3 = randn(numel(TN),1);
M4 = randn(numel(TN),1);
M5 = randn(numel(TN),1);
M6 = randn(numel(TN),1);
M7 = randn(numel(TN),1);
M8 = randn(numel(TN),1);
M9 = randn(numel(TN),1);
M10 = randn(numel(TN),1);
M11 = randn(numel(TN),1);
M12 = randn(numel(TN),1);
DATA.M1 = M1;
DATA.M2 = M2;
DATA.M3 = M3;
DATA.x = M4;
DATA.M5 = M5;
DATA.M6 = M6;
DATA.M7 = M7;
DATA.y = M8;
DATA.M9 = M9;
DATA.M10 = M10;
DATA.M11 = M11;
DATA.z = M12
DATA = 8×14 table
TS TName M1 M2 M3 x M5 M6 M7 y M9 M10 M11 z ____ _____ __________ _________ ________ ________ ________ ________ ________ _________ ________ ________ ________ ________ Boy A 0.94176 0.96592 0.83127 -0.96469 -1.1138 0.95343 0.29157 -0.2933 0.13869 -1.1075 0.59653 -0.1007 Boy B -0.0085146 1.4973 0.85337 -1.7562 -2.1965 1.9926 -0.10816 1.2715 -0.21628 0.23034 0.75606 0.085673 Boy C -0.13105 -0.19626 0.75003 -0.97582 0.022491 -0.1896 0.80425 -0.17841 0.11202 0.77753 0.32635 -0.64259 Boy D -0.18264 -2.2729 -0.39656 1.9849 0.1503 0.26151 -0.87482 1.0075 0.60166 0.43676 0.64651 0.12189 Girl A 0.56582 -2.5636 -0.88507 -0.95755 -1.2312 0.42936 -0.39495 -1.0043 2.1618 -0.14574 -0.8057 2.0259 Girl B 0.46113 0.4177 0.37114 0.12721 -0.42584 -0.19921 0.94893 1.3251 0.080742 -0.98153 0.052248 0.34372 Girl C -0.78052 -0.029752 -1.2213 -0.91497 -0.18431 0.12213 0.52505 -0.22272 -1.0057 -2.6867 -1.2729 -1.9098 Girl D 1.0694 -1.6838 -0.2042 0.36261 -0.22849 -0.15683 -0.49298 -0.038873 -0.88004 0.76735 0.16935 1.6251
% Logical indexing is used to take only 'A' or in your exercise: 'Nose'
% Note TName is a categorical data
CA=table2array(DATA(DATA.TName=='A', 3:end));
% Take out the necessary data and make some negative and leave some
% unchanged
Nose = [reshape(CA, 6, 4); 0 0 0 1].*[-1 1 -1 1]
Nose = 7×4
-0.9418 -0.9647 -0.2916 -1.1075 -0.5658 -0.9576 0.3949 -0.1457 -0.9659 -1.1138 0.2933 0.5965 2.5636 -1.2312 1.0043 -0.8057 -0.8313 0.9534 -0.1387 -0.1007 0.8851 0.4294 -2.1618 2.0259 0 0 0 1.0000
% Alternative way:
CA2=table2array(DATA(1:4:end, 3:end));
Nose2 = [reshape(CA2, 6, 4); 0 0 0 1].*[-1 1 -1 1]
Nose2 = 7×4
-0.9418 -0.9647 -0.2916 -1.1075 -0.5658 -0.9576 0.3949 -0.1457 -0.9659 -1.1138 0.2933 0.5965 2.5636 -1.2312 1.0043 -0.8057 -0.8313 0.9534 -0.1387 -0.1007 0.8851 0.4294 -2.1618 2.0259 0 0 0 1.0000

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