Contain large&hetergeneous datasets : Cell vs Table vs Others
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Hyeong Seok Lee
le 11 Août 2020
Réponse apportée : Gouri Chennuru
le 14 Août 2020
load dryer2;
z = iddata(y2,u2,0.08,'Tstart',0);
na = 2:4;
nc = 1:2;
nk = 0:2;
models = cell(18,5);
ct = 1;
for i = 1:3
na_ = na(i);
nb_ = na_;
for j = 1:2
nc_ = nc(j);
for k = 1:3
nk_ = nk(k);
[models{ct, :}] = deal(armax(z,[na_ nb_ nc_ nk_]), na_, nb_, nc_, nk_);
ct = ct+1;
end
end
end
Above codes are from documentation of ARMAX. https://kr.mathworks.com/help/ident/ref/armax.html
I made some modifications to variable 'models'
In my problem, the number of parameters is much larger(e.g. na, nb, ..., nz), and their range is much broader.
I want to save all parameters(na, nb,..) and their output(like output of armax functin in above codes), which are heterogeneous.
Which data types are the most fit to contain these datasets? Cell? Table? other else?
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Réponse acceptée
Gouri Chennuru
le 14 Août 2020
Hi,
In order to work with large data sets, MATLAB has number of tools for accessing and processing large data in many ways,
- You can use datastore function that creates a datastore, which is a repository for collections of data that are too large to fit in memory.
- You can use Large MAT files access and change variables without loading into memory.
- You can create tall numeric arrays, cell arrays, categoricals, strings, datetimes, durations, or calendar durations, and you can use any of these tall types as variables in a tall table or tall timetable.
You can refer to these links for more information,
Hope this Helps!
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