Read csv-File fast / convert csv to mat
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Hello everybody,
From a datalogger i have a csv-file which looks like this:
"s";"m";"";"";"deg";"";"m/s≤";"m/s≤";"m/s≤";"bar";"bar";"";"";"";"";"%";"1/s";"";"km/h";"";"V";"bar";"bar";"∞C";"∞C";"";"∞";"∞";"m";"∞";"Km/h";"km/h";"m/s≤";"deg/s";"m/s≤";"∞";"sec";"m"
"0,000";"0";"2,00";"10,48";"193,01";"11,08";"0,99";"0,21";"5,49";"0,85";"0,86";"50,00";"54,00";"53,00";"71,00";"5,5";"0,00";"1,0";"0,00";"0";"12,46";"0,00";"3,85";"-40,0";"-40,0";"0,00";"9,272901";"48,995935";"800,40";"1,00";"0,07";"0,1";"-0,01";"0,00";"0,00";"0,00";"0,00";"0,00"
What i've done yet is i created a little GUI tool to plot the data in different graphs, that works fine. To read the data, i've used the import tool from matlab itself, but the csv file is more than 200MB big, to import this takes realy long. And the csv will is becoming bigger in the next version because there will be more channels added.
So my question is the following: first, i want to load the csv-file faster and second it would be nice if the script imports automatically all columms, so it doesn't mater if the csv has 3 or 30 columms.
It would be nice if someone could help me with this problem :)
댓글 수: 1
dpb
2014년 4월 9일
Well, you can try importdata and see how it goes for speed but probably best you'll do will be with textread or textscan
The other delimited-file routines such as csvread aren't able to deal with the header row. If you could do without it, keeping it separately it might help.
Of course, if speed and file size is the issue, not writing a text file to begin with would be the way around the problem. If at all possible, use a stream file instead.
If you must stay formatted, I'd seriously recommend ditching the embedded headerline for a separate info file and then I'm very partial to the (deprecated) textread for the job as it returns a "regular" array instead of cell array by default.
답변 (6개)
per isakson
2014년 4월 9일
편집: per isakson
2014년 4월 10일
Warning: These functions change your data files. Operate on a copies!
Here are two functions to test regarding speed. I believe the first function will do the job in less time. This approach with a separate step, c2p, works well when there is enough memory for the entire file to fit in the system cache.
Both functions return
>> whos M
Name Size Bytes Class Attributes
M 3x38 912 double
Run
M = cssm_q( 'cssm.txt' );
where (in one m-file)
function num = cssm_q( filespec )
c2p( filespec );
fid = fopen( filespec, 'r' );
str = fgetl( fid );
ncl = length( strfind( str, ';' ) ) + 1;
frm = repmat( '%f', [1,ncl] );
cac = textscan( fid, frm, 'Delimiter',';', 'CollectOutput',true );
num = cac{1};
fclose( fid );
end
function c2p( filespec )
file = memmapfile( filespec, 'writable', true );
comma = uint8(',');
point = uint8('.');
file.Data(( file.Data==comma)' ) = point;
quote = uint8('"');
space = uint8(' ');
file.Data(( file.Data==quote)' ) = space;
end
and where cssm.txt contains your header row together with a few copies of your data row.
.
Second function is
function num = cssm( filespec )
c2p( filespec );
fid = fopen( filespec, 'r' );
str = fgetl( fid );
ncl = length( strfind( str, ';' ) ) + 1;
frm = repmat( '%q', [1,ncl] );
cac = textscan( fid, frm, 'Delimiter',';' );
num = nan( length(cac{1}), length(cac) );
for jj = 1 : length(cac)
num( :, jj ) = str2num( char( cac{jj} ) );
end
end
function c2p( filespec )
file = memmapfile( filespec, 'writable', true );
comma = uint8(',');
point = uint8('.');
file.Data(( file.Data==comma)' ) = point;
end
This is a few columns of the data file after running cssm_q
s ; m ; ; ; deg ; ; m/s? ; m/s? ; m/s? ; bar ;
0.000 ; 0 ; 2.00 ; 10.48 ; 193.01 ; 11.08 ; 0.99 ;
0.000 ; 0 ; 2.00 ; 10.48 ; 193.01 ; 11.08 ; 0.99 ;
0.000 ; 0 ; 2.00 ; 10.48 ; 193.01 ; 11.08 ; 0.99 ;
The "?" in the header shows that I have made a mistake regarding the text encoding.
.
"but i can also export the data without the double quotes, so the data is just seperated by commas"
And I assume "." as decimal separator. That's more Matlab-friendly. Try dlmread, which actually calls textscan, and cssm_c, which I believe to be somewhat faster. To be fair dlmread has better error handling.
function num = cssm_c( filespec )
fid = fopen( filespec, 'r' );
str = fgetl( fid );
ncl = length( strfind( str, ',' ) ) + 1;
frm = repmat( '%f', [1,ncl] );
cac = textscan( fid, frm, 'Delimiter',',', 'CollectOutput',true );
num = cac{1};
fclose( fid );
end
댓글 수: 3
Joseph Cheng
2014년 4월 10일
Oopse, it's late in the day and thought i should stop playing and get back to work. Didn't notice i just kind of left it vague. The test was for cssm_q. cssm took longer than my trip to and from the vending machine so... i killed the process.
Image Analyst
2014년 4월 9일
편집: Image Analyst
2014년 4월 9일
Doesn't look like a csv file to me, which should be numbers separated by commas. You have double quotes and semicolons in between the commas in addition to the numbers. It is supposed to be only numbers. You might be able to use dlmread, if your delimeters are actually semicolons and not commas. You might also try readtable(), which is what you use for reading in tables that have mixed data types such as character strings along with numbers on the same row.
댓글 수: 1
per isakson
2014년 4월 9일
편집: per isakson
2014년 4월 9일
In some parts of the world "," is used as decimal delimiter and ";" as list delimiter. Despite these delimiter characters we often call the file "csv". It certainly causes some confusion and extra work.
David
2014년 4월 9일
댓글 수: 2
Image Analyst
2014년 4월 9일
What about the semicolons? It almost looks like some European way of doing it where everything is different, like decimals are commas, and commas are semicolons.
David
2014년 4월 10일
댓글 수: 1
per isakson
2014년 4월 10일
편집: per isakson
2014년 4월 10일
One option is to replace
str = fgetl( fid );
by
st1 = fgetl( fid );
st2 = fgetl( fid );
If you do not need to keep the header line you may use the option, Headerlines, of textscan, i.e
cac = textscan( fid, ....., 'Headerlines', 2 );
Mistake: I forgot that the header line is needed to find the number of columns
ncl = length( strfind( str, ';' ) ) + 1;
frm = repmat( '%f', [1,ncl] );
However, those two solutions will break when you get a file with a different number of header lines. A more flexible solution will include something like
str = 'dummy'; n = -1;
while isempty( regexp( str, '^[0-9\+\-\.\,;" ]{100,}$', 'match' ) )
str = fgetl( fid );
n = n + 1;
end
....
frewind( fid )
cac = textscan( fid, frm, ....., 'Headerlines', n );
not tested
David
2014년 4월 11일
댓글 수: 3
per isakson
2014년 4월 13일
I never use GUIDE and I'm not able to quickly find an answer. Please post this comment as a new question with "GUIDE" as one of the tags.
Dahai Xue
2015년 1월 28일
for system with Excel installed, this simply works
[~,~,myTable] = xlsread('myFile.csv');
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