Description Usage Arguments Value Examples
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.
1 2  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.
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29  # 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)

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