我希望使用ggplot获得多边形类型的空间图。其中,绘制多边形并且多边形的颜色由其重量决定。
示例数据框看起来像 - (这里是数据文件CompleteDataFile)
polyNr x y centroidX centroidY weight
1 4459425.25 5328202.595264193 4459675.25 5328202.595264193 -13.055709633886783
1 4459550.25 5328419.101615138 4459675.25 5328202.595264193 -13.055709633886783
1 4459800.25 5328419.101615138 4459675.25 5328202.595264193 -13.055709633886783
1 4459925.25 5328202.595264193 4459675.25 5328202.595264193 -13.055709633886783
1 4459800.25 5327986.088913247 4459675.25 5328202.595264193 -13.055709633886783
1 4459550.25 5327986.088913247 4459675.25 5328202.595264193 -13.055709633886783
2 4457550.25 5337512.3683548765 4457800.25 5337512.3683548765 -118.36760699572329
2 4457675.25 5337728.874705822 4457800.25 5337512.3683548765 -118.36760699572329
2 4457925.25 5337728.874705822 4457800.25 5337512.3683548765 -118.36760699572329
2 4458050.25 5337512.3683548765 4457800.25 5337512.3683548765 -118.36760699572329
2 4457925.25 5337295.862003931 4457800.25 5337512.3683548765 -118.36760699572329
2 4457675.25 5337295.862003931 4457800.25 5337512.3683548765 -118.36760699572329
3 4475175.25 5336862.849302039 4475425.25 5336862.849302039 -3.397375074455629
3 4475300.25 5337079.355652984 4475425.25 5336862.849302039 -3.397375074455629
3 4475550.25 5337079.355652984 4475425.25 5336862.849302039 -3.397375074455629
3 4475675.25 5336862.849302039 4475425.25 5336862.849302039 -3.397375074455629
3 4475550.25 5336646.342951093 4475425.25 5336862.849302039 -3.397375074455629
3 4475300.25 5336646.342951093 4475425.25 5336862.849302039 -3.397375074455629
4 4464675.25 5343358.039830423 4464925.25 5343358.039830423 -51.57522722796112
4 4464800.25 5343574.546181369 4464925.25 5343358.039830423 -51.57522722796112
4 4465050.25 5343574.546181369 4464925.25 5343358.039830423 -51.57522722796112
4 4465175.25 5343358.039830423 4464925.25 5343358.039830423 -51.57522722796112
4 4465050.25 5343141.533479477 4464925.25 5343358.039830423 -51.57522722796112
4 4464800.25 5343141.533479477 4464925.25 5343358.039830423 -51.57522722796112
3438 4459050.25 5338378.393758661 4459300.25 5338378.393758661 1.066256760712294
3438 4459175.25 5338594.900109607 4459300.25 5338378.393758661 1.066256760712294
3438 4459425.25 5338594.900109607 4459300.25 5338378.393758661 1.066256760712294
3438 4459550.25 5338378.393758661 4459300.25 5338378.393758661 1.066256760712294
3438 4459425.25 5338161.887407715 4459300.25 5338378.393758661 1.066256760712294
3438 4459175.25 5338161.887407715 4459300.25 5338378.393758661 1.066256760712294
我的步骤是 -
将整个数据集划分为十分位数
breaks=unique(quantile(df$weight,probs=seq(0,1,by=0.1)))
df$deciles = cut(df$weight,breaks=breaks,include.lowest=TRUE)
色标(我希望正数为红色,负数为绿色)
library(RColorBrewer)
colours=brewer.pal(name="RdYlGn", n=nlevels(df$deciles))
names(colours)=rev(levels(df$deciles))
积
library(ggplot2)
ggplot(df,aes(x=x,y=y)) + geom_polygon(aes(group=polyNr,fill=factor(deciles))) + scale_fill_manual(values=colours)
这给了我一个情节 - 看起来像 -
但是,我的另一个要求是 - 我希望零为白色。一般来说,我可以使用
来做到这一点scale_fill_gradient2(low = muted("green"), mid = "white", high = muted("red"), midpoint = 0,)
但是,我不能用我的离散量表来使用它。
首先,这可能吗?如果是,我怎样才能获得低中高颜色和十分位数。如果这是重复的问题,请找到我错过的原始问题。
P.S。 - 我对不同的数据集使用相同的代码,因此,设置手动色标是不可取的。
编辑 -
对于颜色设置(红色,白色,绿色)我也试过了colorRampPalette。 (感谢@ Pewi指出)
colours = colorRampPalette(c("red", "white", "green"))(11)
这给我以下情节。
设置白色为零重量是一个主要问题。我在基础包中遇到了同样的问题。
答案 0 :(得分:2)
我将您的问题解释为“如何创建从x到y穿过白色的n种颜色”。该问题的一个答案是使用包colorRampPalette
grDevices
library(grDevices)
colours <- colorRampPalette(c("red", "white", "green"))(n = 21)
plot(1:21, col=colours,pch=18,cex=4)
如果用类似的东西替换你的第2部分,你可能会得到所需的输出。
编辑:
我担心这不会很优雅,但请耐心等待。
#sim data
dat = data.frame(x =-3:9)
#cut into deciles
dat$y = cut(dat$x,breaks=quantile(dat$x,seq(0,1,0.1)),include.lowest = T)
#Find in wich decile the value closest to zero is
dat$part = as.numeric(dat$y) <= as.numeric(dat$y[which(abs(0-dat$x)==min(abs(dat$x-0)))])
#split color range into two parts
highcolours <- colorRampPalette(c("red","white"))(n = sum(dat$part==TRUE))
lowcolours <- colorRampPalette(c("white","green"))(n = sum(dat$part==FALSE)+1)
#combine colors
cols = c(highcolours,lowcolours)
#both high and low contain midpoint (white) remove one of them
cols = cols[!duplicated(cols)]
#Example
plot(1:nrow(dat), col=cols ,pch=18,cex=4)
答案 1 :(得分:0)
最后我做了什么。
df = read.table("sampleData.txt",header=T)
breaks=unique(quantile(df$weight,probs=seq(0,1,by=0.1)))
df$deciles = cut(df$weight,breaks=breaks,include.lowest=TRUE)
df$part = as.numeric(df$deciles) <= as.numeric(df$deciles[which(abs(0-df$weight)==min(abs(df$weight-0)))])
在这一步之后,我不能只拥有与数据点一样多的颜色。因此,我将df $ part
的比例分为色标highCols = round (sum(df$part==FALSE)*10/(sum(df$part==FALSE)+sum(df$part==TRUE)))
lowCols = 10 - highCols
highColours = colorRampPalette(c("red","darkred"))(n = highCols)
lowColours = colorRampPalette(c("darkgreen","green","white"))(n=lowCols)
cols = c(lowColours,highColours)
cols = cols[!duplicated(cols)]
ggplot(df,aes(x=x,y=y)) + geom_polygon(aes(group=polyNr,fill=factor(deciles))) + scale_fill_manual(values=cols)
这给了我情节 -
虽然情节仍然很好,但从长远来看,如果可能的话,我更愿意采用更直接的方法。感谢。