Andres

In some cases, there's a problem with a curve end:

xTest = sqrt([0:0.1:0.5,0.4:-0.1:0]);
yTest = 5:-0.5:0;
ptTest = interparc(linspace(0,1,15),xTest,yTest,'linear');
figure
plot(xTest,yTest,'b.-')
hold on
plot(ptTest(:,1),ptTest(:,2),'r.-')

Perhaps this affects the 'linear' method only. Adding
tbins(end) = n-1;
at line 233 helped me out, but this is more or less a quick shot in the dark, I hope John will care for it. Thanks again,
Andres

Seems perfect in every respect. I used it to reduce the number of points of a curve which was given with unevenly distributed data. Thanks.

I haven't looked at the code yet, but I have used this submission to read in 1 GB of data. It just worked beautifully, very fast, and allowed me to filter out bogus lines. Very useful submission.

Thanks for your feedback. Indeed it would be nice to have a handy column selection input argument instead of using 'ConvString' with something like '%f %*f %f %*f %f'.
Regarding your memory issue, so far I can only refer to the 'NumericType' param and especially to example 6, but you probably found that in the doc already. txt2mat reads in the whole part of the file that is to be imported and initializes the output array. In an extreme case, a double array holding the data may consume about four times more memory than the file, unless some rows have missing values. I am thinking about making txt2mat more memory efficent - e.g. avoid slurping large files - without noticeably loosing speed (but tbh I have hardly any spare time now).

It would be most simple if you could uniquely identify every line of text by some string (or some few strings), as with 'tex' (or just 'x') in your example:

txt2mat('example.txt','BadLineString',{'tex'})

If that is not possible, you could read in all lines and then remove all NaN-only rows:

A = txt2mat('example.txt',0,'ReadMode','line')
A = A(any(isfinite(A),2),:)

If things are more complex, you may also contact me via the 'Contact Author' link. Good luck!