cubic-spline

I have two lists to describe the function y(x): x = [0,1,2,3,4,5] y = [12,14,22,39,58,77] I would like to perform cubic spline interpolation so that given some value u in the domain of x, e.g. u = 1.25 I can find y(u). I found this in SciPy but I am not sure how to use it. youngmit Short answer: from scipy import interpolate def f(x): x_points = [ 0, 1, 2, 3, 4, 5] y_points = [12,14,22,39,58,77] tck = interpolate.splrep(x_points, y_points) return interpolate.splev(x, tck) print(f(1.25)) Long answer: scipy separates the steps involved in spline interpolation into two operations, most likely for

I'm trying to calculate a Bezier-like spline curve that passes through a sequence of x-y coordinates. An example would be like the following output from the cscvn function in Matlab ( example link ): I believe the (no longer maintained) grid package used to do this ( grid.xspline function?), but I haven't been able to install an archived version of the package, and don't find any examples exactly along the lines of what I would like. The bezier package also looks promising, but it is very slow and I also can't get it quite right: library(bezier) set.seed(1) n <- 10 x <- runif(n) y <- runif(n)

I am asked to investigate the different types of interpolation using Matlab for the following points: x = [32 34 35 36 37 38] y = [26 28 31 30 29 25] and find the values for f(33) , f(33.5) and f(35) . When plotting x and y, I can see that f(33) should be around 27, which is also what I get using interp1(x,y,33) . I am not sure if this is the correct way of using the Cubic spline interpolation function but I used spline(x,y,33) and got ans = 24.3906 . Shouldn't I still get the same value for f(33) no matter what type of interpolation I use? Interpolation makes sure the values of the