How can I speed up importing large .d files?

8 Ansichten (letzte 30 Tage)
Felix Lauwaert
Felix Lauwaert am 1 Aug. 2015
Bearbeitet: Cedric am 1 Aug. 2015
Hi,
soon I'll have large files, about 50000x6 (more than one of them) and I'll have to work on them several times to plot different stuff. I've realised that "importdata" command is very slow and I've been recommended to use GNUPlot, but I would prefer to stick to MATLAB if possible. So, is there any command to load data to workspace in a faster way? Maybe using .xls instead of .d?
Thanks.
  2 Kommentare
Cedric
Cedric am 1 Aug. 2015
Could you provide a sample file?
Felix Lauwaert
Felix Lauwaert am 1 Aug. 2015
I had to upload it as .txt because of website requirements. I tic-tocked the importdata and it was arround 12s, but I'll have to deal with way larger files soon.

Melden Sie sich an, um zu kommentieren.

Akzeptierte Antwort

Cedric
Cedric am 1 Aug. 2015
Bearbeitet: Cedric am 1 Aug. 2015
I would do something along the following line:
buffer = fileread( 'test.txt' ) ;
data = sscanf( buffer(76:end), '%f' ) ;
data = reshape( data, 6, [] )' ;
I built a file with more than 50k rows to test, and it takes half the time of IMPORTDATA. We can easily improve it so it doesn't rely on a fixed header size. You could also do something like:
fName = 'test.txt' ;
fId = fopen( fName, 'r' ) ;
header = strsplit( strtrim( fgetl( fId ) ), ' ' ) ;
data = fscanf( fId, '%f' ) ;
data = reshape( data, 6, [] )' ;
fclose( fId ) ;
but this is slower.
PS: I don't understand why your IMPORTDATA is that slow. On my test file with >50k lines, here is the timing:
IMPORTDATA: Elapsed time is 0.312664 seconds.
FSCANF : Elapsed time is 0.457961 seconds.
FILEREAD : Elapsed time is 0.171987 seconds.
  5 Kommentare
per isakson
per isakson am 1 Aug. 2015
Bearbeitet: per isakson am 1 Aug. 2015
I created a test file with
cssm0(50000)
where
function cssm0( N )
h = sprintf( 'H%06d ', 1:N );
d = sprintf( '%f ' , 1:N );
fid = fopen('test_long_rows.txt','w');
fprintf( fid, '%s\n', h,d,d,d,d,d,d );
fclose(fid);
end
and used profile. Maybe, I misread the original question. Anyhow, whether the rows or the columns are long and short, respectively, makes a huge difference with importdata
Cedric
Cedric am 1 Aug. 2015
Bearbeitet: Cedric am 1 Aug. 2015
It's interesting, 6x5e4 -> 2s and 5e4x6 -> 0.3s.
In any case, I've always been avoiding IMPORTDATA like plague (especially after looking at its source code), because its behavior is size-dependent and difficult to predict. This leads to situations like the one reported recently on the forum, where it works with a files that contains thousands of rows of data, but fails when there are only 30 lines (for the same data structure).

Melden Sie sich an, um zu kommentieren.

Weitere Antworten (1)

per isakson
per isakson am 1 Aug. 2015
Bearbeitet: per isakson am 1 Aug. 2015
Does the file consist of header rows followed by data rows, which contains only numerical data? (No string data such as date time data.)
Try txt2mat, by Andres "txt2mat basically is a wrapper for sscanf, it quickly converts ascii files containing m-by-n numeric data, allowing for header lines"
  3 Kommentare
per isakson
per isakson am 1 Aug. 2015
Yes, please upload the six row file.
Felix Lauwaert
Felix Lauwaert am 1 Aug. 2015
I tried txt2mat out and it's great, timing 0.157s! Awesome, I hope one day I'll be ready to answer questions and make such functions :)

Melden Sie sich an, um zu kommentieren.

Kategorien

Mehr zu Large Files and Big Data finden Sie in Help Center und File Exchange

Community Treasure Hunt

Find the treasures in MATLAB Central and discover how the community can help you!

Start Hunting!

Translated by