Question

我有一些电台的风数据。数据包括csv文件中每个站的站点纬度，经度，风速和风向。该数据不是规则间隔的数据。我需要在R语言中为这些数据绘制流线。

我通过互联网搜索了rasterVis STREAMPLOT()的几个包TeachingDemos My.Symbols，但是我没有成功。

这是我正在谈论的一个示例情节。 http://wx.gmu.edu/dev/clim301/850stream.png

此外，还有来自csv文件的一些示例数据，我试图绘制流线型。

longitude,latitude,windspeed,winddirection  
84.01,20,1.843478261,126.6521739  
77.13,28.48,3.752380952,138.952381  
77.2,28.68,2.413333333,140.2666667  
78.16,31.32,1.994444444,185.0555556  
77.112,31.531,2.492,149.96  
77,28.11,7.6,103  
77.09,31.5,1.752631579,214.8947368  
76.57,31.43,1.28,193.6  
77.02,32.34,3.881818182,264.4545455  
77.15,28.7,2.444,146.12  
77.35,30.55,3.663157895,131.3684211  
75.5,29.52,4.175,169.75  
72.43,24.17,2.095,279.3  
76.19,25.1,1.816666667,170  
76.517,30.975,1.284210526,125.6315789  
76.13,28.8,4.995,126.7  
75.04,29.54,4.09,151.85  
72.3,24.32,0,359  
72.13,23.86,1.961111111,284.7777778  
74.95,30.19,3.032,137.32  
73.16,22.36,1.37,251.8  
75.84,30.78,3.604347826,125.8695652  
73.52,21.86,1.816666667,228.9166667  
70.44,21.5,2.076,274.08  
69.75,21.36,3.81875,230  
78.05,30.32,0.85625,138.5625

有人可以帮助我绘制不规则风数据的流线型吗？

Answer 1

和你一样，我希望将与streamlnes相同类型的数据可视化，但我找不到能够解决这个问题的函数......所以我编写了自己的原始函数：

streamlines <- function(x, y, u, v, step.dist=NULL, 
                        max.dist=NULL, col.ramp=c("white","black"), 
                        fade.col=NULL, length=0.05, ...) {

  ## Function for adding smoothed vector lines to a plot. 
  ## Interpolation powered by akima package

  ## step.distance - distance between interpolated locations (user coords)
  ## max.dist - maximum length of interpolated line (user coords)
  ## col.ramp - colours to be passed to colorRampPalette
  ## fade.col - NULL or colour to add fade effect to interpolated line
  ## ... - further arguments to pass to arrows

  ## build smoothed lines using interp function
  maxiter <- max.dist/step.dist
  l <- replicate(5, matrix(NA, length(x), maxiter), simplify=FALSE)
  names(l) <- c("x","y","u","v","col")
  l$x[,1] <- x
  l$y[,1] <- y
  l$u[,1] <- u
  l$v[,1] <- v
  for(i in seq(maxiter)[-1]) {
    l$x[,i] <- l$x[,i-1]+(l$u[,i-1]*step.dist)
    l$y[,i] <- l$y[,i-1]+(l$v[,i-1]*step.dist)
    r <- which(l$x[,i]==l$x[,i-1] & l$y[,i]==l$y[,i-1])
    l$x[r,i] <- NA
    l$y[r,i] <- NA
    for(j in seq(length(x))) {
      if(!is.na(l$x[j,i])) {
        l$u[j,i] <- c(interp(x, y, u, xo=l$x[j,i], yo=l$y[j,i])$z)
        l$v[j,i] <- c(interp(x, y, v, xo=l$x[j,i], yo=l$y[j,i])$z) 
      } 
    }
  }

  ## make colour a function of speed and fade line
  spd <- sqrt(l$u^2 + l$v^2) # speed
  spd <- apply(spd, 1, mean, na.rm=TRUE) # mean speed for each line
  spd.int <- seq(min(spd, na.rm=TRUE), max(spd, na.rm=TRUE), length.out=maxiter)
  cr <- colorRampPalette(col.ramp)
  cols <- as.numeric(cut(spd, spd.int))
  ncols <- max(cols, na.rm=TRUE)
  cols <- cr(ncols)[cols]
  if(is.null(fade.col)) {
    l$col <- replicate(maxiter, cols)
  } else {
    nfade <- apply(!is.na(l$x), 1, sum)
    for(j in seq(length(x))) {
      l$col[j,seq(nfade[j])] <- colorRampPalette(c(fade.col, cols[j]))(nfade[j])
    } 
  }

  ## draw arrows
  for(j in seq(length(x))) {
    arrows(l$x[j,], l$y[j,], c(l$x[j,-1], NA), c(l$y[j,-1], NA), 
           col=l$col[j,], length=0, ...)
    i <- which.max(which(!is.na(l$x[j,]))) # draw arrow at end of line
    if(i>1) {
      arrows(l$x[j,i-1], l$y[j,i-1], l$x[j,i], l$y[j,i], 
             col=l$col[j,i-1], length=length, ...) 
    }
  }

}

该函数由akima包中的interp函数提供支持，并且通过一些摆弄，它可以产生一些不错的视觉效果：

＆＃13;

dat <- "longitude,latitude,windspeed,winddirection  
84.01,20,1.843478261,126.6521739  
77.13,28.48,3.752380952,138.952381  
77.2,28.68,2.413333333,140.2666667  
78.16,31.32,1.994444444,185.0555556  
77.112,31.531,2.492,149.96  
77,28.11,7.6,103  
77.09,31.5,1.752631579,214.8947368  
76.57,31.43,1.28,193.6  
77.02,32.34,3.881818182,264.4545455  
77.15,28.7,2.444,146.12  
77.35,30.55,3.663157895,131.3684211  
75.5,29.52,4.175,169.75  
72.43,24.17,2.095,279.3  
76.19,25.1,1.816666667,170  
76.517,30.975,1.284210526,125.6315789  
76.13,28.8,4.995,126.7  
75.04,29.54,4.09,151.85  
72.3,24.32,0,359  
72.13,23.86,1.961111111,284.7777778  
74.95,30.19,3.032,137.32  
73.16,22.36,1.37,251.8  
75.84,30.78,3.604347826,125.8695652  
73.52,21.86,1.816666667,228.9166667  
70.44,21.5,2.076,274.08  
69.75,21.36,3.81875,230  
78.05,30.32,0.85625,138.5625"

tf <- tempfile()
writeLines(dat, tf)
dat <- read.csv(tf)

library(rgdal) # for projecting locations to utm coords
library(akima) # for interpolation

## add utm coords
xy <- as.data.frame(project(cbind(dat$longitude, dat$latitude), "+proj=utm +zone=43 +datum=NAD83"))
names(xy) <- c("easting","northing")
dat <- cbind(dat, xy)

## add u and v coords
dat$u <- -dat$windspeed*sin(dat$winddirection*pi/180)
dat$v <- -dat$windspeed*cos(dat$winddirection*pi/180)


#par(bg="black", fg="white", col.lab="white", col.axis="white")
plot(northing~easting, data=dat, type="n", xlab="Easting (m)", ylab="Northing (m)")
streamlines(dat$easting, dat$northing, dat$u, dat$v, 
            step.dist=1000, max.dist=50000, col.ramp=c("blue","green","yellow","red"), 
            fade.col="white", length=0, lwd=5)

＆＃13;

Answer 2

我认为这不足以满足您的要求：

 require(plotrix)
 require(maps)
 map("world",xlim=c(69,85),ylim= c(20,35))
 with(dat, 
     vectorField(windspeed, winddirection, longitude, latitude , vecspec="deg") )

稍微盯着输出后，我认为我可能在使用该功能或使用功能本身时遇到问题。箭头的方向似乎是错误的。同样地，我认为TeachingDemos矢量字段做得不好，但这是我得到的：

require(TeachingDemos)
 map("world",xlim=c(69,85),ylim= c(20,35))
 with(dat, my.symbols(x=longitude, y=latitude, 
       symb= ms.arrows, length=windspeed/10, angle=2*pi*winddirection/360))

这个情节似乎在方向上有足够的变化，但箭头的大小似乎变化不大。无论如何，这些图都没有表明这些数据可用于构建流线。就相邻位置的wid方向而言，数据太稀疏且内部矛盾。

enter image description here

R中不规则间隔风数据的流线型？

2 个答案: