Avoiding load and/or for loop - speed up
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Hi everyone!
I have a directory containing mat-files. they all contain vectors A and B.
I would like to find the maximum value A.*B out of all the mat files. However loading all the .mat files and checking if the maximum value from all the last files is crossed is very timeconsuming:
for i = first:last
load(filename{i})
U = lowpass(A,wpass)*U_scale; % [V] Lowpass-filtered & scaled voltage data
I = lowpass(B,wpass)*I_scale; % [A] Lowpass-filtered & scaled current data
E = abs(U.*I)*t_S;
E_quant = quantile(E,0.9);
if E_max < max(E_quant)
E_max = max(E_quant);
end
end
How do I do this efficiently?
Thanks a lot!
Ann
8 comentarios
Rik
el 19 de Oct. de 2020
You should load the variables to a struct:
S=load(filename{i});A=S.A;B=S.B;
Otherwise I'm not sure there is a lot you can do. Disks (even SSDs) are relatively slow. I'm not sure using parfor would help, I doubt it but it may be worth a try.
Ann Gerber
el 19 de Oct. de 2020
Rik
el 19 de Oct. de 2020
Do not use numbered variables. You can load to a struct array (or save your loaded variable into such an array). Then you can use indexing to reach all variable, instead of having to use more complex methods.
Ann Gerber
el 19 de Oct. de 2020
Rik
el 19 de Oct. de 2020
If it fills up your RAM, then it is probably faster to load it later on. Your disk will either be busy reading the files, or moving data between the swap on the disk and the actual RAM. This depends on the size of your data, the amount of RAM used by Matlab and other programs, and your total installed system memory.
Mathieu NOE
el 19 de Oct. de 2020
Hi
just my 2 cents
maybe you could reduce the size of data in your mat files
I see your doing low pass filtering, so why not make that (and decimate) in first place when mat files are being generated ?
Ann Gerber
el 19 de Oct. de 2020
Mathieu NOE
el 20 de Oct. de 2020
maybe you could decimate the data inside the loop before doing the low pass filtering
depends what is the original sampling rate and what bandwith must be kept for U and I ( for your computation E = abs(U.*I)*t_S;)
as decimation applies also low pass filtering , you have your lowpass effect plus you reduce the size of U and I.
=> help decimate
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