I find it safer to process the data without returning to a disk file. As
mentioned I actually prefer to start with mgeti() and read the file as
binary, as then all byte values are accepted.
But anyway with the data separated in lines, it is relatively simple to
split up with the wanted separators and decimal sign :
clear dataset;
headerlines=3:
footerlines=2:
for k=1:size(in_text,1)
if k>headerlines && k<n-footerlines then
datatemp=strtod(strsplit(in_text(k),[ascii(9),";"]),",");
dataset(k-headerlines,1:length(datatemp))=datatemp;
end
end
disp(in_text(1:headerlines));
disp(dataset);
disp(in_text(($-footerlines+1):$));
JÅ
On 2020-04-28 10:14 AM, Rafael Guerra wrote:
Antoine,
One workflow that works fast for me, for large data files, is to load
first the whole file with mgetl, then remove all empty lines using
isempty in a loop (as shown below), process the header block, isolate
the data block and save it to a temporary backup file to disk using
mputl, then load very efficiently from disk that backup file using
fscanfMat.
tlines=mgetl(fid,-1); /// reads lines until end of file into 1 column
text vector/
bool=~cellfun(isempty,tlines);
tlines=tlines(bool); /// removes empty lines/
function*out_text*=_cellfun_(*fun*, *in_text*)
/// Applies function to input text (column strings vector), line by line/
n=size(*in_text*,1);
for i=1:n;
*out_text*(i)=*fun*(*in_text*(i));
end
endfunction
Regards,
Rafael
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