Interpolates values using 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))]