ipol {latentcor}

Create an interpolating function from given values. Several interpolation methods are supported.

Description

Create an interpolating function from given values. Several interpolation methods are supported.

Usage

ipol(val, grid = NULL, ...)

Arguments

val

array or function. Function values on a grid.

grid

list. Each element is a vector of ordered grid-points for a dimension.

...

Further arguments to the function, if is.function(val). And some extra arguments for interpolant creation described in section Details.

Value

A function(x, threads=getOption('chebpol.threads')) defined on a hypercube, an interpolant for the given function. The argument x can be a matrix of column vectors which are evaluated in parallel in a number of threads. The function yields values for arguments outside the hypercube as well, though it will typically be a poor approximation. threads is an integer specifying the number of parallel threads which should be used when evaluating a matrix of column vectors.

Author(s)

Simen Gaure

Examples

## evenly spaced grid-points
su <- seq(0,1,length.out=10)
## irregularly spaced grid-points
s <- su^3
## create approximation on the irregularly spaced grid
ml1 <- ipol(exp(s), grid=list(s))
## test it, since exp is convex, the linear approximation lies above
## the exp between the grid points
ml1(su) - exp(su)

## multi dimensional approximation
f <- function(x) 10/(1+25*mean(x^2))
# a 3-dimensional 10x10x10 grid, first and third coordinate are non-uniform
grid <- list(s, su, sort(1-s))

# make multilinear spline.
ml2 <- ipol(array(apply(expand.grid(grid), 1, f), c(10, 10, 10)), grid=grid)
# make 7 points in R3 to test them on
m <- matrix(runif(3*7),3)
rbind(true=apply(m,2,f), ml=ml2(m))