绘图问题 - 图例条形比例,中断,图例,小数

Question

我想绘制一堆栅格,我创建了一个代码来调整每个栅格的中断并通过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:

我的降水范围从0到11.000 ......但是大部分数据都在0到5.000之间......而非常少到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()
}

这个数字是循环中所有栅格的i = 12

然后我写了一个不同的代码来为颜色条设置不同的中断

#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......这是不同的.

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...而且,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,但它还不是我寻求的

levelplot(predictors[[12]]+1, col.regions=colorRampPalette(brewer.pal(9, 'Blues')), zscaleLog=TRUE, at=seq(1, 4, len=100), margin=FALSE)

Answer 1

classIntervals()您可以使用包中的函数来避免对数缩放（正如一些用户所说）classInt。

使用levelplot()（在我看来结果比raster::plot()函数更好）：

# 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，您还有更多选项可供选择，例如sd、pretty、kmeans、hclust等。

将多边形和点添加到绘图中

首先，我将上面的图保存到p，该行对于本示例来说太长：

p <- levelplot(predictors[[12]], col.regions=colorRampPalette(brewer.pal(9, 'Blues')), at=break1$brks, margin=FALSE,main =predic_legends[12])

我将使用与您的数据相同的数据wrld_simpl作为多边形添加到绘图中，并且我还将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、多边形、点甚至文本，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更多信息。