Findin asymptotes of data curve

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Hello everyone !
I'm trying to make a code finding the 2 asymptotes (zero and + infinity) of curve made of data points (so I don't know the theoretical function, and even if I can guess it, this is not the point). Basically, there is a linear asymptote in zero and a constant one in the other side (see pictures).
As you can see, the shape isn't exactly the same, and I would like to find the slope of the first linear part, and the constant at the infinity. Basically, if I can find the point where these two asymptotes are crossing, it's fine. I could use a derivative method but since the slope is very small, the noise in the raw datas is too strong (see next picture).
Any ideas ? I have a lot of these curves so I can't find these 2 asymptotes myself for all.
Thank you !
GADAL Cyril

Accepted Answer

Image Analyst
Image Analyst on 7 Jun 2016
How about if you find out when the data first exceeds the last point, and then fit from then on (basically the flat, right portion of the data) to a line?
firstIndex = find(y > y(end), 1, 'first');
coefficients = polyfit(x(firstIndex:end), y(firstIndex:end), 1);
  3 Comments
Image Analyst
Image Analyst on 7 Jun 2016
One or two data points won't significantly change the slope of the fitted line. However if you want, you can take only indexes within +/- std dev of the line
firstIndex = find(y > y(end), 1, 'first');
theMean = mean(y(firstIndex:end));
theSD = std(y(firstIndex:end));
someFactor = 1.5; % Whatever you want.
indexesToUse = abs(y-theMean) > someFactor * theSD;
coefficients = polyfit(x(indexesToUse), y(indexesToUse), 1);
% Fit the line
fittedY = polyval(coefficients, x);
hold on
plot(x, fittedY, 'r-', 'LineWidth', 3);
grid on;
Cyril GADAL
Cyril GADAL on 8 Jun 2016
Edited: Cyril GADAL on 8 Jun 2016
You're right, it doesn't change a lot, but using the standard deviation allow me indeed ton control a bit more the process.
Can you explain me a bit more this syntax I've never seen in matlab :
indexesToUse = abs(y-theMean) > someFactor * theSD;
Where there is by the way a small mistake and should be :
indexesToUse = abs(y-theMean) < someFactor * theSD;
Thanks a lot !

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