interpolation_function {cinterpolate}  R Documentation 
Create an interpolation function, using the same implementation as
would be available from C code. This will give very similar
answers to R's splinefun
function. This is not the
primary intended use of the package, which is mostly designed for
use from C/C++. This function primarily exists for testing this
package, and for exploring the interface without writing C code.
interpolation_function(x, y, type, scalar = FALSE, fail_on_extrapolate = FALSE)
x 
Independent variable 
y 
Dependent variable 
type 
Character string indicating the interpolation type ("constant", "linear" or "spline"). 
scalar 
Return a function that will compute only a single

fail_on_extrapolate 
Logical, indicating if extrapolation should cause an failure (rather than an NA value) 
A function that can be used to interpolate the function(s)
defined by x
and y
to new values of x.
# Some data to interpolate x < seq(0, 8, length.out = 20) y < sin(x) xx < seq(min(x), max(x), length.out = 500) # Spline interpolation f < cinterpolate::interpolation_function(x, y, "spline") plot(f(xx) ~ xx, type = "l") lines(sin(xx) ~ xx, col = "grey", lty = 2) points(y ~ x, col = "red", pch = 19, cex = 0.5) # Linear interpolation f < cinterpolate::interpolation_function(x, y, "linear") plot(f(xx) ~ xx, type = "l") lines(sin(xx) ~ xx, col = "grey", lty = 2) points(y ~ x, col = "red", pch = 19, cex = 0.5) # Piecewise constant interpolation f < cinterpolate::interpolation_function(x, y, "constant") plot(f(xx) ~ xx, type = "s") lines(sin(xx) ~ xx, col = "grey", lty = 2) points(y ~ x, col = "red", pch = 19, cex = 0.5) # Multiple series can be interpolated at once by providing a # matrix for 'y'. Each series is interpolated independently but # simultaneously. y < cbind(sin(x), cos(x)) f < cinterpolate::interpolation_function(x, y, "spline") matplot(xx, f(xx), type = "l", lty = 1)