How can I calculate the standard deviation for a part of "all data"?

Hello,

I have a two different matrices:

time=[0,0.5,2,4,6]
time =
         0    0.5000    2.0000    4.0000    6.0000
data=[1,3,5,3,6]
data =
     1     3     5     3     6
         

Now I would like to do a specific operation only if time>=0 & =< 4. So in this case only for the first four values of data.

For example these kind of operations:

sqrt(mean((diff(data).*diff(data))))

std(a)

How can I do the calculation only for a specific period of time?

Thanks for your help!

Answer 1

[Image Analyst]

I have no idea what "a" is. But is this something like you were looking for?

timeVec = [0,0.5,2,4,6] % Don't use "time" since it's a built-in function.
data=[1,3,5,3,6]
indexes = timeVec >= 0 & timeVec <= 4
dataToUse = data(indexes)
% Now do your operation:
result = sqrt(mean((diff(dataToUse) .* diff(dataToUse))))
result2 = std(result) % No idea what a is.  Is it the result of the sqrt() operation?

[Max Behr]

Thank you for your help!

Sorry, it was a mistake. It should be data.

The time markers are in a matrix too.

time_markers=[0,4,6;0,5,8]

time_markers =

     0     4     6
     0     5     8

So if I have mutiple data matrices (data_0, data_1, etc.), can I do something like this. For example for data_0:

     data_0=[1,3,5,3,6]
     data_1=[...]
     time_Vec=[0,0.5,2,4,6]
     time_Vec1=[...]
         
     indexes=timeVec>=time_markers(1,1)&timeVec<=time_markers(1,2);
     dataToUse=data_0(indexes)
     results_1(1,1)=sqrt(mean((diff(dataToUse) .* diff(dataToUse))))
     results_2(1,1)=std(dataToUse)
     
     indexes=timeVec>=time_markers(1,3);
     dataToUse=data_0(indexes)
     results(1,2)=sqrt(mean((diff(dataToUse) .* diff(dataToUse))))
     results_2(1,2)=std(dataToUse)

So could I do the same for data_1 and time_Vec1 etc.?

I really appreciate your help :) !!!

[Image Analyst]

Sure, why not?

[Max Behr]

Thanks, wasn't sure if it works :)