R：使用条件颜色绘制多边形

我想给曲线下的区域上色。y>0的区域应为红色，y<0的区域应为绿色

x <- c(1:4)
y <- c(0,1,-1,2,rep(0,4))
plot(y[1:4],type="l")
abline(h=0)

到目前为止，我取得的成就如下：

polygon(c(x,rev(x)),y,col="green")
polygon(c(x,rev(x)),ifelse(y>0,y,0),col="red")

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但是红色区域太大了。你知道如何得到想要的结果吗？

如果你想要两种不同的颜色，你需要两个不同的多边形。您可以多次调用多边形，也可以在

x

和

y

向量中添加

NA

值以指示新的多边形。R不会自动为您计算交叉点。你必须自己做。这是你如何用不同的颜色画出来的

x <- c(1,2,2.5,NA,2.5,3,4)
y <- c(0,1,0,NA,0,-1,0)

#calculate color based on most extreme y value
g <- cumsum(is.na(x))
gc <- ifelse(tapply(y, g, 
    function(x) x[which.max(abs(x))])>0, 
    "red","green")

plot(c(1, 4),c(-1,1), type = "n")
polygon(x, y, col = gc)
abline(h=0)

这应该适用于简单的凹多边形以及斜线。这是另一个例子

x <- c(1,2,3,4,5,4,3,2)
y <- c(-2,2,1,2,-2,.5,-.5,.5)

sl<-getSplitLine(.5,-1.25)

plot(range(x, na.rm=T),range(y, na.rm=T), type = "n")
p <- splitPolygon(x,y,sl)
g <- cumsum(c(F, is.na(head(p$y,-1))))
gc <- ifelse(attr(p,"side")[is.na(p$y)],  
    "red","green")
polygon(p, col=gc)
sl$plot(lty=2, col="grey")

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x一个更快但不太准确的解决方案是根据分组变量（例如，上面=红色，下面=蓝色）将数据框拆分为列表。对于相当大（我想说>100个元素）的数据集来说，这是一个非常好的解决方案。对于较小的块体，可能会出现一些不连续：

x <- 1:100
y1 <- sin(1:100/10)*0.8
y2 <- sin(1:100/10)*1.2
plot(x, y2, type='l')
lines(x, y1, col='red')

df <- data.frame(x=x, y1=y1, y2=y2)

df$pos_neg <- ifelse(df$y2-df$y1>0,1,-1) # above (1) or below (-1) average

# create the number for chunks to be split into lists:
df$chunk <- c(1,cumsum(abs(diff(df$pos_neg)))/2+1) # first element needs to be added`
df$colors <- ifelse(df$pos_neg>0, "red","blue") # colors to be used for filling the polygons
# create lists to be plotted:
l <- split(df, df$chunk) # we should get 4 sub-lists
lapply(l, function(x) polygon(c(x$x,rev(x$x)),c(x$y2,rev(x$y1)),col=x$colors))

x啊，我刚刚意识到我用了一个坏例子。由于y中的0，多边形的一侧已经在分割线上。不带0的数据呢，例如
y实际上所有的凸多边形都是凸多边形吗？或者它们也是凹面的。我几乎有了一个更通用的解决方案，但有一些恼人的边缘情况。我想我只会有凸多边形。通常，我必须划分打印数据，这些数据将只包含凸多边形。
splitPolygon <- function(x, y, splitter) {
    addnullrow <- function(x) if (!all(is.na(x[nrow(x),]))) rbind(x, NA) else x
    rollup <- function(x,i=1) rbind(x[(i+1):nrow(x),], x[1:i,])
    idx <- cumsum(is.na(x) | is.na(y))
    polys <- split(data.frame(x=x,y=y)[!is.na(x),], idx[!is.na(x)])
    r <- lapply(polys, function(P) {
        x <- P$x; y<-P$y
        side <- splitter$classify(x, y)
        if(side[1] != side[length(side)]) {
            ints <- splitter$intercepts(c(x,x[1]), c(y, y[1]), c(side, side[1]))
        } else {
            ints <- splitter$intercepts(x, y, side)
        }
        sideps <- lapply(unique(side), function(ss) {
            pts <- data.frame(x=x[side==ss], y=y[side==ss], 
                idx=seq_along(x)[side==ss], dir=0)
            mm <- rbind(pts, ints)
            mm <- mm[order(mm$idx), ]
            br <- cumsum(mm$dir!=0 & c(0,head(mm$dir,-1))!=0 & 
                c(0,diff(mm$idx))>1)
            if (length(unique(br))>1) {
                mm<-rollup(mm, sum(br==br[1]))
            }
            br <- cumsum(c(FALSE,abs(diff(mm$dir*mm$dir))==3))
            do.call(rbind, lapply(split(mm, br), addnullrow))
        })
        pss<-rep(unique(side), sapply(sideps, nrow))
        ps<-do.call(rbind, lapply(sideps, addnullrow))[,c("x","y")]
        attr(ps, "side")<-pss
        ps
   })
   pss<-unname(unlist(lapply(r, attr, "side")))
   src <- rep(seq_along(r), sapply(r, nrow))
   r <- do.call(rbind, r)
   attr(r, "source")<-src
   attr(r, "side")<-pss
   r
}

x <- c(1,2,2.5,NA,2.5,3,4)
y <- c(1,-2,2,NA,-1,2,-2)

sl<-getSplitLine(0,0)

plot(range(x, na.rm=T),range(y, na.rm=T), type = "n")
p <- splitPolygon(x,y,sl)
g <- cumsum(c(F, is.na(head(p$y,-1))))
gc <- ifelse(attr(p,"side")[is.na(p$y)],  
    "red","green")
polygon(p, col=gc)
sl$plot(lty=2, col="grey")

x <- c(1,2,3,4,5,4,3,2)
y <- c(-2,2,1,2,-2,.5,-.5,.5)

sl<-getSplitLine(.5,-1.25)

plot(range(x, na.rm=T),range(y, na.rm=T), type = "n")
p <- splitPolygon(x,y,sl)
g <- cumsum(c(F, is.na(head(p$y,-1))))
gc <- ifelse(attr(p,"side")[is.na(p$y)],  
    "red","green")
polygon(p, col=gc)
sl$plot(lty=2, col="grey")

x <- 1:100
y1 <- sin(1:100/10)*0.8
y2 <- sin(1:100/10)*1.2
plot(x, y2, type='l')
lines(x, y1, col='red')

df <- data.frame(x=x, y1=y1, y2=y2)

df$pos_neg <- ifelse(df$y2-df$y1>0,1,-1) # above (1) or below (-1) average

# create the number for chunks to be split into lists:
df$chunk <- c(1,cumsum(abs(diff(df$pos_neg)))/2+1) # first element needs to be added`
df$colors <- ifelse(df$pos_neg>0, "red","blue") # colors to be used for filling the polygons
# create lists to be plotted:
l <- split(df, df$chunk) # we should get 4 sub-lists
lapply(l, function(x) polygon(c(x$x,rev(x$x)),c(x$y2,rev(x$y1)),col=x$colors))