Interpolating the y values of a dataset A to correspond to the x values of dataset B.
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Hi,
I have 2 datasets containing the numerical (x1,y1) and experimental (x2,y2) results of a problem that lie within the same limits. I have to obtain the root-mean-square error to show the deviation of the numerical results from the experimental data, but the numerical data points (y1) are recorded on different locations (x1) from those of the experimental data points (x2) due to which the error calculation is not possible.
I'd like to know if there is a precise method to interpolate the y1 values for the locations prescribed in x2.
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Torsten
on 6 Jun 2024
Edited: Torsten
on 6 Jun 2024
The easiest way I can think of is
y1_at_x2 = interp1(x1,y1,x2)
If it's precise ? Define precise. At least you have the choice between different methods of interpolation. Read the documentation of "interp1" for more details.
If the (x1,y1) were obtained by a numerical method, you usually have the choice to define the output points x. Why didn't you choose x2 instead of x1 ?
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Torsten
on 6 Jun 2024
You need one command
y1_at_x2 = interp1(x1,y1,x2,method)
in which you should test for different interpolation methods available.
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