How to approach iterative data reading?

I'm working with a dataset that has 3 different arrays I'm interested in plotting: time, accel, and gcamp. They are all of equal size.

I'm using the accel variable as a threshold detector, where I define an arbitrary threshold under which any data I ignore. Anything above that threshold I use the index of that data point to grab the equivalent data points from time and gcamp.

How can I store this data in one structure so that I can iterate through it and generate statistics/plots about only the thresholded data points?

Something like:

time = [rand(1, 5000)];
accel = [rand(1,5000)];
gcamp = [rand(1,5000)];

sd = std(accel);
threshold = sd;

dumb = [];
for i = 1:length(accel);
    if accel(i) > threshold;
        dumber = [time(i), gcamp(i)];
        dumb = [dumb, dumber];
    end
end

Answer 1

[Paul]

Hi Eric,

Use logical indexing.

time = [rand(1, 5000)];
accel = [rand(1,5000)];
gcamp = [rand(1,5000)];
sd = std(accel);
threshold = sd;
dumb = [];
for i = 1:length(accel);
    if accel(i) > threshold;
        dumber = [time(i), gcamp(i)];
%        dumb = [dumb, dumber];  
        dumb = [dumb; dumber];  
    end
end

index = accel > threshold;
foo = [time(index);gcamp(index)].';  % transpose to match dumb

isequal(foo,dumb)

ans = logical
   1