is there a way for a creation of variables for machine learning inside a loop from a dataset of waves

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i have this dataset of wavelengths, problem is they are flipped and as such whenever i load the data i run a secondary part to rotate and flip, though so far i only have a way to read it and not really make use of it inside an ai machine learning thing
clc; clear; close all;
load('-mat','sub-036_task-eyesclosed_eeg.set','data','group','subject')
data_plot=flip(rot90(data,1));
N=width(data_plot);
B=height(data_plot);
figure
%----------------------- all of this is just for plotting and seeing it in stackedplot
T = array2table(data_plot, 'VariableNames',"CH: "+(1:N));
s = stackedplot(T);
s.AxesProperties(1);
ax = findobj(s.NodeChildren, 'Type','Axes');
set(ax, 'YTick', []);
%--------------------------
xlim([-500 B+500])
grid on
set (zoom(gcf), 'Motion', 'horizontal', 'Enable', 'on');
%--------------------------
i was wondering if there is a way to make like a for loop so in each loop i get data_1 then data_2 data_3 etc etc etc or how could i use a machine learning or signal labeler app or ai or artificial neural network and deal with the issue that i need to rotateflip the data?
  2 Comments
Stephen23
Stephen23 on 8 Dec 2024
Edited: Stephen23 on 8 Dec 2024
"i was wondering if there is a way to make like a for loop so in each loop i get data_1 then data_2 data_3 etc etc etc "
The most important change is to always LOAD into an output variable:
S = load(..);
which you can then trivially loop over the fieldnames:
F = fieldnames(S);
for k = 1:numel(F)
A = S.(F{k});
.. do whatever with A
end
See also:

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Answers (1)

Walter Roberson
Walter Roberson on 28 Nov 2024
data_names = who('-file', 'sub-036_task-eyesclosed_eeg.set', '-regexp', '^data_\d+$');
for DNI = 1:length(data_names)
thisvar = data_names{DNI};
DS = load('-mat','sub-036_task-eyesclosed_eeg.set', thisvar);
data = DS.(thisvar);
%stuff
end
  6 Comments
Walter Roberson
Walter Roberson on 7 Dec 2024
x = [1 2 3 4];
y = [100 200 300 400];
data = [x; y];
data
data = 2×4
1 2 3 4 100 200 300 400
<mw-icon class=""></mw-icon>
<mw-icon class=""></mw-icon>
flip(data)
ans = 2×4
100 200 300 400 1 2 3 4
<mw-icon class=""></mw-icon>
<mw-icon class=""></mw-icon>
data.'
ans = 4×2
1 100 2 200 3 300 4 400
<mw-icon class=""></mw-icon>
<mw-icon class=""></mw-icon>
flip(data.')
ans = 4×2
4 400 3 300 2 200 1 100
<mw-icon class=""></mw-icon>
<mw-icon class=""></mw-icon>
rot90(data,1)
ans = 4×2
4 400 3 300 2 200 1 100
<mw-icon class=""></mw-icon>
<mw-icon class=""></mw-icon>
flip(rot90(data,1))
ans = 4×2
1 100 2 200 3 300 4 400
<mw-icon class=""></mw-icon>
<mw-icon class=""></mw-icon>
so data.' gives the same result as flip(rot90(data,1)).

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