Uses fields::interp.surface to interpolate values defined in a bidimensional grid with bilinear interpolation.

Interpolate(formula, x.out, y.out, data = NULL, grid = TRUE, path = FALSE)

Arguments

formula

a formula indicating dependent and independent variables (see Details)

x.out, y.out

x and y values where to interpolate (see Details)

data

optional data.frame with the data

grid

logical indicating if x.out and y.out define a regular grid.

path

a logical or character indicating if the x.out and y.out define a path. If character, it will be the name of the column returning the order of said path.

Value

A data.frame with interpolated values and locations

Details

formula must be of the form VAR1 | VAR2 ~ X + Y where VAR1, VAR2, etc... are the names of the variables to interpolate and X and Y the names of the x and y values, respectively. It is also possible to pass only values of x, in which case, regular linear interpolation is performed and y.out, if exists, is ignored with a warning.

If grid = TRUE, x.out and y.out must define the values of a regular grid. If grid = FALSE, they define the locations where to interpolate. Both grid and path cannot be set to TRUE and the value of path takes precedence.

x.out can be a list, in which case, the first two elements will be interpreted as the x and y values where to interpolate and it can also have a path element that will be used in place of the path argument. This helps when creating a path with as.path (see Examples)

Examples

library(data.table) data(geopotential) geopotential <- geopotential[date == date[1]] # new grid x.out <- seq(0, 360, by = 10) y.out <- seq(-90, 0, by = 10) # Interpolate values to a new grid interpolated <- geopotential[, Interpolate(gh ~ lon + lat, x.out, y.out)] # Add values to an existing grid geopotential[, gh.new := Interpolate(gh ~ lon + lat, lon, lat, data = interpolated, grid = FALSE)$gh]
#> lon lat lev gh date gh.new #> 1: 0.0 -22.5 700 3163.839 1990-01-01 NA #> 2: 2.5 -22.5 700 3162.516 1990-01-01 NA #> 3: 5.0 -22.5 700 3162.226 1990-01-01 NA #> 4: 7.5 -22.5 700 3162.323 1990-01-01 NA #> 5: 10.0 -22.5 700 3163.097 1990-01-01 NA #> --- #> 4028: 347.5 -90.0 700 2715.936 1990-01-01 2715.936 #> 4029: 350.0 -90.0 700 2715.936 1990-01-01 NA #> 4030: 352.5 -90.0 700 2715.936 1990-01-01 NA #> 4031: 355.0 -90.0 700 2715.936 1990-01-01 NA #> 4032: 357.5 -90.0 700 2715.936 1990-01-01 NA
# Interpolate multiple values geopotential[, c("u", "v") := GeostrophicWind(gh, lon, lat)]
#> lon lat lev gh date gh.new u v #> 1: 0.0 -22.5 700 3163.839 1990-01-01 NA NA 1.08181190 #> 2: 2.5 -22.5 700 3162.516 1990-01-01 NA NA 0.55189199 #> 3: 5.0 -22.5 700 3162.226 1990-01-01 NA NA 0.06625043 #> 4: 7.5 -22.5 700 3162.323 1990-01-01 NA NA -0.29800162 #> 5: 10.0 -22.5 700 3163.097 1990-01-01 NA NA -0.75064329 #> --- #> 4028: 347.5 -90.0 700 2715.936 1990-01-01 2715.936 NA 0.00000000 #> 4029: 350.0 -90.0 700 2715.936 1990-01-01 NA NA 0.00000000 #> 4030: 352.5 -90.0 700 2715.936 1990-01-01 NA NA 0.00000000 #> 4031: 355.0 -90.0 700 2715.936 1990-01-01 NA NA 0.00000000 #> 4032: 357.5 -90.0 700 2715.936 1990-01-01 NA NA 0.00000000
interpolated <- geopotential[, Interpolate(u | v ~ lon + lat, x.out, y.out)] # Interpolate values following a path lats <- c(-34, -54, -30) # start and end latitudes lons <- c(302, 290, 180) # start and end longituded path <- geopotential[, Interpolate(gh ~ lon + lat, as.path(lons, lats))]