There are three functions in SMath for spline interpolation:

linterp('X-vector','Y-vector','x') - Returns a linearly interpolated value at x for data vectors X-vector and Y-vector of the same size.

cinterp('X-vector','Y-vector','x') - Returns a cubic spline interpolated value at x for data vectors X-vector and Y-vector of the same size.

ainterp('X-vector','Y-vector','x') - Returns Akima-spline interpolated value at x for data vectors X-vector and Y-vector of the same size.

Here is the example of presenting these functions:

splines

Notice how misleading all of these functions are outside the limits of the original datapoints, ie below x=1 and above x=5. Try and make sure that you only use these for interpolation, not extrapolation.

You can have the X-vector sorted in ascending order:

X-vector ascending

And also X-vector not sorted . As the main usage of the interpolation is to estimate y-value for the x-value not given in the table, this is not advisable:

X-vector not sorted

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