I have a labview programm, that continously (every ~0.1sec) reads in data (x=temperature, y1=voltage1, y2=voltage2) and saves it in a spreadsheet (example see attachment).
From these pretty messy raw data, I want to interpolate sets of function points (x,y1,y2) at certain x-values = (0.1, 0.2, 0.3,...300 ).
Do you have an idea, how this could be done?
(beginner knowledge of labview)
There is e.g. no x=0.1, so you would need to extrapolate. Do you have a mathematical model for the behavior? In that case, nonlinear fitting would be a good solution. Is that first point of y2=2314000.0000 real?
the attached data was just an example. I don`t want to extrapolate and will limit the taken data to a reasonable range. Also the first point of y2=2314000.0000 is a wrong value and would be excluded from evaluation.
I guess there is some exponential behaviour in the data, but unfortunately it is overlayed with other effects. That`s why I would prefer low-range interpolation to get a good fit with the actual data.
Since there seem to be noise, interpolation is not a good solution. How about a polynomial, or an exponential and polynomial?
How about applying a smoothing function before interpolation? How about a low order polynomial of nearby points?
Can you attach some more realistic data? What is the typical x spacing?