我想绘制一堆栅格,我创建了一个代码来调整每个栅格的断点并通过for循环绘制它们。但是我得到了一个有问题的色标栏,而我的努力并没有有效解决这个问题。例如:
我的降水范围从0到11.000 ......但大部分数据介于0到5.000之间,而非常少介于11.000之间。因此,我需要更改中断以捕获此变化...更多中断我有更多数据。
然后我为此创建了一个休息对象 但是当我绘制光栅时,刻度颜色条变得非常糟糕,非常混乱......
#get predictors (These are a way lighter version of mine)
predictors_full<-getData('worldclim', var='bio', res=10)
predic_legends<-c(
"Annual Mean Temperature [°C*10]",
"Mean Diurnal Range [°C]",
"Isothermality",
"Temperature Seasonality [standard deviation]",
"Max Temperature of Warmest Month [°C*10]",
"Min Temperature of Coldest Month [°C*10]",
"Temperature Annual Range [°C*10]",
"Mean Temperature of Wettest Quarter [°C*10]",
"Mean Temperature of Driest Quarter [°C*10]",
"Mean Temperature of Warmest Quarter [°C*10]",
"Mean Temperature of Coldest Quarter [°C*10]",
"Annual Precipitation [mm/year]",
"Precipitation of Wettest Month [mm/month]",
"Precipitation of Driest Month [mm/month]",
"Precipitation Seasonality [coefficient of variation]",
"Precipitation of Wettest Quarter [mm/quarter]",
"Precipitation of Driest Quarter [mm/quarter]",
"Precipitation of Warmest Quarter [mm/quarter]",
"Precipitation of Coldest Quarter [mm/quarter]",
)
# Crop rasters and rename
xmin=-120; xmax=-35; ymin=-60; ymax=35
limits <- c(xmin, xmax, ymin, ymax)
predictors <- crop(predictors_full,limits)
predictor_names<-c("mT_annual","mT_dayn_rg","Isotherm","T_season",
"maxT_warm_M","minT_cold_M","rT_annual","mT_wet_Q","mT_dry_Q",
"mT_warm_Q","mT_cold_Q","P_annual","P_wet_M","P_dry_M","P_season",
"P_wet_Q","P_dry_Q","P_warm_Q","P_cold_Q")
names(predictors)<-predictor_names
#Set a palette
Blues_up<-c('#fff7fb','#ece7f2','#d0d1e6','#a6bddb','#74a9cf','#3690c0','#0570b0','#045a8d','#023858','#233159')
colfunc_blues<-colorRampPalette(Blues_up)
#Create a loop to plot all my Predictor rasters
for (i in 1:19) {
#save a figure
png(file=paste0(predictor_names[[i]],".png"),units="in", width=12, height=8.5, res=300)
#Define a plot area
par(mar = c(2,2, 3, 3), mfrow = c(1,1))
#extract values from rasters
vmax<- maxValue(predictors[[i]])
vmin<-minValue(predictors[[i]])
vmedn=(maxValue(predictors[[i]])-minValue(predictors[[i]]))/2
#breaks
break1<-c((seq(from=vmin,to= vmedn, length.out = 40)),(seq(from=(vmedn+(vmedn/5)),to=vmax,length.out = 5)))
#plot without the legend because the legend would come out with really messy, with too many marks and uneven spaces
plot(predictors[[i]], col =colfunc_blues(45) , breaks=break1, margin=FALSE,
main =predic_legends[i],legend.shrink=1)
dev.off()
}
然后我写了一个不同的代码来为颜色栏设置不同的中断
#Plot the raster with no color scale bar
plot(predictors[[i]], col =colfunc_blues(45) , breaks=break1, margin=FALSE,
main =predic_legends[i],legend=FALSE)
#breaks for the color scale
def_breaks = seq(vmax,vmin,length.out=(10))
#plot only the legend
image.plot(predictors_full[[i]], zlim = c(vmin,vmax),
legend.only = TRUE, col = colfunc_greys(30),
axis.args = list(at = def_breaks, labels =def_breaks,cex.axis=0.5))
但这不起作用,因为颜色与地图中的数字并不完全匹配...在每张地图中查看6.000的颜色......它是不同的。
有关如何继续进行的任何提示? 我是R的新手所以我为实现目标而奋斗很多... 另外,我在数字中得到了很多小数位...如何改变2位小数?
编辑:@jbaums教我使用日志...我喜欢但它还不是我想要的东西levelplot(predictors[[12]]+1, col.regions=colorRampPalette(brewer.pal(9, 'Blues')), zscaleLog=TRUE, at=seq(1, 4, len=100), margin=FALSE)
答案 0 :(得分:4)
您可以使用classIntervals()
包中的classInt
函数来避免日志缩放(正如某些用户所说)。
使用levelplot()
(在我看来,结果优于raster::plot()
函数):
# Normal breaks
break1 <- classIntervals(predictors[[12]][!is.na(predictors[[12]])], n = 50, style = "equal")
levelplot(predictors[[12]], col.regions=colorRampPalette(brewer.pal(9, 'Blues')), at=break1$brks, margin=FALSE,main =predic_legends[12])
# Using quantiles
break1 <- classIntervals(predictors[[12]][!is.na(predictors[[12]])], n = 50, style = "quantile")
levelplot(predictors[[12]], col.regions=colorRampPalette(brewer.pal(9, 'Blues')), at=break1$brks, margin=FALSE,main =predic_legends[12])
此外,您还可以选择更多选项,例如sd
,pretty
,kmeans
,hclust
等。
首先,我将上面的图表保存到p
,这个例子的行太长了:
p <- levelplot(predictors[[12]], col.regions=colorRampPalette(brewer.pal(9, 'Blues')), at=break1$brks, margin=FALSE,main =predic_legends[12])
我将使用与您的wrld_simpl
数据相同的数据作为多边形添加到绘图中,我还会创建要添加到绘图中的点。
library(maptools)
library(rgeos)
data(wrld_simpl)
pts <- gCentroid(wrld_simpl, byid = T)
要添加线条,多边形,点数甚至文字,您可以使用layer()
函数和panel.spplot
对象:
p + layer(sp.polygons(wrld_simpl)) + layer(sp.points(pts))
最后,您还可以更改颜色,填充,符号系统等:
p + layer(sp.polygons(wrld_simpl,col='firebrick')) + layer(sp.points(pts,pch = 12,col='red'))
查看?panel.spplot
了解详情。