Question

代码

    #
    # This is code for mapping of CGE_Morocco results
    #

    # rm(list = ls(all = TRUE)) # don't use this in code that others will copy/paste

    ## Loading packages
    library(rgdal)
    library(plyr)
    library(maps)
    library(maptools)
    library(mapdata)
    library(ggplot2)
    library(RColorBrewer)

    ## Loading shape files administrative coordinates for Morocco maps
    #Morocco <- readOGR(dsn=".", layer="Morocco_adm0")
    MoroccoReg <- readOGR(dsn=".", layer="Morocco_adm1")

    ## Reorder the data in the shapefile based on the regional order
    MoroccoReg <- MoroccoReg[order(MoroccoReg$ID_1), ] 

    ## Add the yield impacts column to shapefile
    MoroccoReg@data$SRESB2_CO2 <- c(0.003,0.100,0.116,-0.105,-0.010,0.048,0.006,-0.004,0.061,0.032,0.003,-0.016,-0.018,0.095)

    ## Check the structure and contents of shapefile
    summary(MoroccoReg)
    attributes(MoroccoReg)

    ## Plotting 
    MoroccoRegMap <- ggplot(data = MoroccoReg, aes(long, lat, group = group)) 
    MoroccoRegMap <- MoroccoRegMap + geom_polygon()
    MoroccoRegMap <- MoroccoRegMap + geom_path(colour = 'gray', linestyle = 2)
    MoroccoRegMap <- MoroccoRegMap + scale_fill_brewer('ID_1')
    MoroccoRegMap <- MoroccoRegMap + coord_equal() + theme_bw()
    MoroccoRegMap

情节

Morocco_Regs

该问题有两个方面：首先，我希望能够分别为每个区域着色。其次，我希望根据数据中变量“SRESB2_CO2”捕获的每个区域的预计产量影响来做到这一点。

提前感谢您的帮助。

Answer 1

以下是.csv格式，代码和结果的附加产量数据。

产量数据： Data

代码：

    ## Loading packages
    library(rgdal)
    library(plyr)
    library(maps)
    library(maptools)
    library(mapdata)
    library(ggplot2)
    library(RColorBrewer)
    library(foreign)  
    library(sp)

    ## get.centroids: function to extract polygon ID and centroid from shapefile
    get.centroids = function(x){
    poly = MoroccoReg@polygons[[x]]
    ID   = poly@ID
    centroid = as.numeric(poly@labpt)
    return(c(id=ID, long=centroid[1], lat=centroid[2]))
    }

    ## Loading shapefiles and .csv files
    #Morocco <- readOGR(dsn=".", layer="Morocco_adm0")
    MoroccoReg <- readOGR(dsn=".", layer="Morocco_adm1")
    MoroccoYield <- read.csv(file = "F:/Purdue University/RA_Position/PhD_ResearchandDissert/PhD_Draft/Country-CGE/RMaps_Morocco/Morocco_Yield.csv", header=TRUE, sep=",", na.string="NA", dec=".", strip.white=TRUE)
    MoroccoYield$ID_1 <- substr(MoroccoYield$ID_1,3,10) # Eliminate the ID_1 column

    ## Reorder the data in the shapefile
    MoroccoReg    <- MoroccoReg[order(MoroccoReg$ID_1), ]
    MoroccoYield  <- cbind(id=rownames(MoroccoReg@data),MoroccoYield) # Add the column "id" for correct merging with the spatial data 

    ## Build table of labels for annotation (legend).
    labs <- do.call(rbind,lapply(1:14,get.centroids))
    labs <- merge(labs,MoroccoYield[,c("id","ID_1","Label")],by="id")
    labs[,2:3] <- sapply(labs[,2:3],function(x){as.numeric(as.character(x))})
    labs$sort <- as.numeric(as.character(labs$ID_1))
    labs <- labs[order(labs$sort),]

    MoroccoReg.df <- fortify(MoroccoReg) # transform shapefile into dataframe
    MoroccoReg.df <- merge(MoroccoReg.df,MoroccoYield, by="id") # merge the spatial data and the yield data
    str(MoroccoReg.df)

    ## Define new theme for map
    ## I have found this function on the website
    theme_map <- function (base_size = 12, base_family = "") {
    theme_gray(base_size = base_size, base_family = base_family) %+replace% 
    theme(
    axis.line=element_blank(),
    axis.text.x=element_blank(),
    axis.text.y=element_blank(),
    axis.ticks=element_blank(),
    axis.ticks.length=unit(0.3, "lines"),
    axis.ticks.margin=unit(0.5, "lines"),
    axis.title.x=element_blank(),
    axis.title.y=element_blank(),
    legend.background=element_rect(fill="white", colour=NA),
    legend.key=element_rect(colour="white"),
    legend.key.size=unit(1.2, "lines"),
    legend.position="right",
    legend.text=element_text(size=rel(0.8)),
    legend.title=element_text(size=rel(0.8), face="bold", hjust=0),
    panel.background=element_blank(),
    panel.border=element_blank(),
    panel.grid.major=element_blank(),
    panel.grid.minor=element_blank(),
    panel.margin=unit(0, "lines"),
    plot.background=element_blank(),
    plot.margin=unit(c(1, 1, 0.5, 0.5), "lines"),
    plot.title=element_text(size=rel(1.2)),
    strip.background=element_rect(fill="grey90", colour="grey50"),
    strip.text.x=element_text(size=rel(0.8)),
    strip.text.y=element_text(size=rel(0.8), angle=-90) 
    )   
    }

    MoroccoRegMap1 <- ggplot(data = MoroccoReg.df, aes(long, lat, group = group)) 
    MoroccoRegMap1 <- MoroccoRegMap1 + geom_polygon(aes(fill = A2Med_noCO2))
    MoroccoRegMap1 <- MoroccoRegMap1 + geom_path(colour = 'gray', linestyle = 2)
    #MoroccoRegMap <- MoroccoRegMap + scale_fill_gradient(low = "#CC0000",high = "#006600")
    MoroccoRegMap1 <- MoroccoRegMap1 + scale_fill_gradient2(name = "%Change in yield",low = "#CC0000",mid = "#FFFFFF",high = "#006600")
    MoroccoRegMap1 <- MoroccoRegMap1 + labs(title="SRES_A2, noCO2 Effect")
    MoroccoRegMap1 <- MoroccoRegMap1 + coord_equal() + theme_map()
    MoroccoRegMap1 <- MoroccoRegMap1 + geom_text(data=labs, aes(x=long, y=lat, label=ID_1, group=ID_1), size=6)
    MoroccoRegMap1 <- MoroccoRegMap1 + annotate("text", x=max(labs$long)-5, y=min(labs$lat)+3-0.5*(1:14),
                                        label=paste(labs$ID_1,": ",labs$Label,sep=""),
                                        size=5, hjust=0)
    MoroccoRegMap1

结果： Map

如何按地区添加颜色？

1 个答案: