如何为地区添加颜色？ [英] How to add color to map by region?

问题描述

代码：

  ##加载软件包
 library（rgdal） 
库（plyr）
库（地图）
库（maptools）
库（mapdata）
库（ggplot2）
库（RColorBrewer）
库（外部）
库（sp）
 
 ## get.centroids：从shapefile中提取多边形ID和质心的函数
 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]））
} 
 
 ##加载shapefile和.csv文件
 #Morocco<  -  readOGR（dsn =。 ，layer =Morocco_adm0）
 M oroccoReg<  -  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）＃消除ID_1列
 
 ##重新排序shapefile中的数据
 MoroccoReg<  -  MoroccoReg [order（MoroccoReg $ ID_1），] 
 MoroccoYield <  -  cbind（id = rownames（MoroccoReg @ data），MoroccoYield）＃为空间数据
 
 ##构建正确合并列添加id列。构建注释（图例）标签表。 
 labs < -  do.call（rbind，lapply（1：14，get.centroids））
 labs<  -  merge（labs，MoroccoYield [，c（id，ID_1， 标签）]，by =id）
 labs [，2：3]<  -  sapply（labs [，2：3]，function（x）{as.numeric（as.character ））}）
 labs $ sort<  -  as.numeric（as.character（labs $ ID_1））
 labs<  -  labs [order（labs $ sort），] 
 
 MoroccoReg.df < -  fortify（MoroccoReg）＃将shapefile转换为dataframe 
 MoroccoReg.df<  -  merge（MoroccoReg.df，MoroccoYield，by =id）＃合并空间数据和收益率数据
 str（MoroccoReg.df）
 
 ##为map 
 ##定义新主题我在网站上找到了这个函数
 theme_map<  -  function（ base_size = 12，base_family =）{
 theme_gray（base_size = base_size，base_family = base_family）％+替换％
主题（
 axis.line = element_blank（），
 axis.text.x = element_blank（），
 axis.text.y = element_blank（），
 axis.ticks = element_blank（），
 axis.tick s.length = unit（0.3，lines），
 axis.ticks.margin =单位（0.5，lines），
 axis.title.x = element_blank（），
 axis.title.y = element_blank（），
 legend.background = element_rect（fill =white，color = NA），
 legend.key = element_rect（color =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 =单位（0，lines），
图。 background = element_blank（），
 plot.margin =单位（c（1,1,0.5,0.5），lines），
 plot.title = element_text（size = rel（1.2））， 
 strip.background = element_rect（fill =grey90，color =grey50），
 strip.text.x = element_text（size = rel（0.8）），
 strip.text .y = element_text（size = rel（0.8），a （数据= MoroccoReg.df，aes（long，lat，group = group））
（
）
} 
 
 MoroccoRegMap1 < -  ggplot MoroccoRegMap1<  -  MoroccoRegMap1 + geom_polygon（aes（fill = A2Med_noCO2））
 MoroccoRegMap1 < -  MoroccoRegMap1 + geom_path（color ='gray'，linestyle = 2）
 #MoroccoRegMap<  -  MoroccoRegMap + scale_fill_gradient低=＃CC0000，高=＃006600）
 MoroccoRegMap1 < -  MoroccoRegMap1 + scale_fill_gradient2（name =％Change of yield，low =＃CC0000，mid =#FFFFFF =＃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 = pa ste（实验室$ ID_1，：，实验室$标签，sep =），
 size = 5，hjust = 0）
 MoroccoRegMap1 
  pre> 
 
 
结果： 
 
The Data

The code
    #
    # 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
The plot



The Question is two fold:
First, I am looking to be able to color each region separately.
Second, I want to do that based on each region's projected yield impact as captured by the variable "SRESB2_CO2" in the data.

Thanks in advance for the help. 
解决方案
Here is the additional yield data in .csv format, code and results.

Yield data:
Data

Code:
    ## 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
Results: 

                        
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