如何使用R语言从薄板样条（TPS）图中导出数据？

Question

I'm a beginner to R and I am trying to extract data in a gridded format from a Thin Plate Spline plot in the R language. Basically I have a data-set of points from across the UK containing the longitude, latitude and amount of rainfall for a particular day. Using the following code I can plot this data onto a UK map:

dat <- read.table("~jan1.csv", header=T, sep=",")
names(dat) <- c("gauge", "date", "station", "mm", "lat", "lon", "location", "county", "days")
library(fields)
quilt.plot(cbind(dat$lon,dat$lat),dat$mm)
world(add=TRUE)

So far so good. I can also perform a thin plate spline interpolation (TPS) using:

fit <- Tps(cbind(dat$lon, dat$lat), dat$mm, scale.type="unscaled")

and then I can do a surface plot at a grid scale of my choice eg:

surface (fit, nx=100, ny=100)

This effectively gives me a gridded data plot at the resolution of 100*100. So here are my questions:

1. How do I extract the data from this gridded data set (ie actual values) to put in a file such as excel or .txt?

2. How could I change the grid size so the grid starts at a particular x value (and y value) in steps of my choice?

Answer 1

With a predict function available, a typical strategy would be to use something like:

 rnglat <- range(dat$lat)
 rnglon <- range(dat$lon)
 xvals <- seq(rnglon[1], rnglon[2], len=100)
 yvals <- seq(rnglat[1], rnglat[2], len=100)
 griddf <- expand.grid(xvals, yvals)
 griddf$pred <- predict(fit, x=as.matrix(griddf) )

(Since Tps doesn't use a formula interface and predict.Krig doesn't appear to use a newdata argument, I'm not making this in a form that would work for most regression problems.) If you want to narrow the range to something less than the full range or change the number of "grid lines", then modify the seq arguments. (Tested with the fit0 -object constructed in the last example on the fields::predict.Krig help page.)