I am trying to perform 2d interpolation on a table named vol_coarse.
install.packages("install.load")
install.load::load_package("pracma", "data.table")
vol_coarse <- data.table(V1 = c(3 / 8, 1 / 2, 3 / 4, 1, 1 + 1 / 2, 2, 3, 6),
V2 = c(0.50, 0.59, 0.66, 0.71, 0.75, 0.78, 0.82, 0.87),
V3 = c(0.48, 0.57, 0.64, 0.69, 0.73, 0.76, 0.80, 0.85),
V4 = c(0.44, 0.53, 0.60, 0.65, 0.69, 0.72, 0.76, 0.81))
setnames(vol_coarse, c("Maximum size of aggregate (in)", "2.40", "2.60", "2.80"))
x <- vol_coarse[, 2][[1]]
y <- as.numeric(colnames(vol_coarse[, 2:ncol(vol_coarse)]))
z <- meshgrid(x, y)
xp <- 3 / 4
yp <- 2.70
interp2(x = x, y = y, Z = z, xp = xp, yp = yp, method = "linear")
This is the error message that is returned:
Error: is.numeric(Z) is not TRUE
I read in ?interp2 that:
length(x) = nrow(Z) = 8 and length(y) = ncol(Z) = 3 must be satisfied.
How can I create a matrix that is 8 by 3 so that I can use interp2?
Or is there a better way to perform this type of interpolation?
Thank you.
If I don't get you wrong, you want:
x <- c(3 / 8, 1 / 2, 3 / 4, 1, 1 + 1 / 2, 2, 3, 6) ## V1
y <- c(2.4, 2.6, 2.8) ## column names
Z <- cbind(c(0.50, 0.59, 0.66, 0.71, 0.75, 0.78, 0.82, 0.87), ## V2
c(0.48, 0.57, 0.64, 0.69, 0.73, 0.76, 0.80, 0.85), ## V3
c(0.44, 0.53, 0.60, 0.65, 0.69, 0.72, 0.76, 0.81)) ## V4
xp <- 3 / 4
yp <- 2.70
You already has a well defined matrix on a grid. For example, you can investigate your 3D data by:
persp(x, y, Z)
image(x, y, Z)
contour(x, y, Z)
I don't recommend pracma, as the interp2 function has a bug. I suggest interp.surface function from fields package for interpolation on a grid.
library(fields)
## the list MUST has name `x`, `y`, `x`!
## i.e., unnamed list `list(x, y, Z)` does not work!
interp.surface(list(x = x, y = y, z = Z), cbind(xp, yp))
# [1] 0.62
interp2 from pracma is inconsistent. The manual says Z matrix is length(x) by length(y), but the function really checks that Z must be length(y) by length(x).
## from manual
Z: numeric ‘length(x)’-by-‘length(y)’ matrix.
## from source code of `interp2`
lx <- length(x)
ly <- length(y)
if (ncol(Z) != lx || nrow(Z) != ly)
stop("Required: 'length(x) = ncol(Z)' and 'length(y) = nrow(Z)'.")
So, in order to make interp2 works, you have to pass in the transpose of Z:
interp2(x, y, t(Z), xp, yp)
# [1] 0.62
or reverse x and y (and xp, yp, too!!):
interp2(y, x, Z, yp, xp)
# [1] 0.62
This is really inconsistent with the way that we work with image, contour and persp.