ggplot2で複数のプロットの幅を制御する方法は？

マップデータ：InputSpatialData

収量データ：InputYieldData

Results_using viewport（）：

編集：@rawrによって提案された「multiplot」関数を使用した結果（以下のコメントを参照）。私は新しい結果が大好きです。特に、マップが大きくなっていることが気に入っています。それにもかかわらず、箱ひげ図はまだマッププロットとずれているようです。センタリングと配置を制御するためのより体系的な方法はありますか？

私の質問：箱ひげ図のサイズを制御して、サイズを近づけ、その上のマッププロットの中央に配置する方法はありますか？

FullCode：

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

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

    ## read input files (shapefile and .csv file)
    wmap <- readOGR(dsn=".", layer="ne_110m_admin_0_countries")
    wyield <- read.csv(file = "F:/Purdue University/RA_Position/PhD_ResearchandDissert/PhD_Draft/GTAP-CGE/GTAP_Sims&Rests/NewFiles/RMaps_GTAP/AllWorldCountries_CCShocksGTAP.csv", header=TRUE, sep=",", na.string="NA", dec=".", strip.white=TRUE)
    wyield$ID_1 <- substr(wyield$ID_1,3,10) # Eliminate the ID_1 column

    ## re-order the shapefile
    wyield <- cbind(id=rownames(wmap@data),wyield)

    ## Build table of labels for annotation (legend).
    labs <- do.call(rbind,lapply(1:17,get.centroids)) # Call the polygon ID and centroid from shapefile
    labs <- merge(labs,wyield[,c("id","ID_1","name_long")],by="id") # merging the "labs" data with the spatial data
    labs[,2:3] <- sapply(labs[,2:3],function(x){as.numeric(as.character(x))})
    labs$sort <- as.numeric(as.character(labs$ID_1))
    labs <- cbind(labs, name_code = paste(as.character(labs[,4]), as.character(labs[,5])))
    labs <- labs[order(labs$sort),]

    ## Dataframe for boxplot plot
    boxplot.df <- wyield[c("ID_1","name_long","A1B","A1BLow","A1F","A1T","A2","B1","B1Low","B2")]
    boxplot.df[1] <- sapply(boxplot.df[1], as.numeric)
    boxplot.df <- boxplot.df[order(boxplot.df$ID_1),]
    boxplot.df <- cbind(boxplot.df, name_code = paste(as.character(boxplot.df[,1]), as.character(boxplot.df[,2])))
    boxplot.df <- melt(boxplot.df, id=c("ID_1","name_long","name_code"))
    boxplot.df <- transform(boxplot.df,name_code=factor(name_code,levels=unique(name_code)))

    ## Define new theme for map
    ## I have found this function on the website
    theme_map <- function (base_size = 14, base_family = "serif") {
    # Select a predefined theme for tweaking features
    theme_bw(base_size = base_size, base_family = base_family) %+replace% 
    theme(
    axis.line=element_blank(),
    axis.text.x=element_text(size=rel(1.2), color="grey"),
    axis.text.y=element_text(size=rel(1.2), color="grey"),
    axis.ticks=element_blank(),
    axis.ticks.length=unit(0.3, "lines"),
    axis.ticks.margin=unit(0.5, "lines"),
    axis.title.x=element_text(size=rel(1.2), color="grey"),
    axis.title.y=element_text(size=rel(1.2), color="grey"),
    legend.background=element_rect(fill="white", colour=NA),
    legend.key=element_rect(colour="white"),
    legend.key.size=unit(1.3, "lines"),
    legend.position="right",
    legend.text=element_text(size=rel(1.3)),
    legend.title=element_text(size=rel(1.4), face="bold", hjust=0),
    panel.border=element_blank(),
    panel.grid.minor=element_blank(),
    plot.title=element_text(size=rel(1.8), face="bold", hjust=0.5, vjust=2),
    plot.margin=unit(c(0.5,0.5,0.5,0.5), "lines")
    )}

    ## Transform shapefile to dataframe and merge with yield data
    wmap_df <- fortify(wmap)
    wmap_df <- merge(wmap_df,wyield, by="id") # merge the spatial data and the yield data

    ## Plot map
    mapy <- ggplot(wmap_df, aes(long,lat, group=group)) 
    mapy <- mapy + geom_polygon(aes(fill=AVG))
    mapy <- mapy + geom_path(data=wmap_df, aes(long,lat, group=group, fill=A1BLow), color="white", size=0.4) 
    mapy <- mapy + labs(title="Average yield impacts (in %) across SRES scenarios ") + scale_fill_gradient2(name = "%Change in yield",low = "red3",mid = "snow2",high = "darkgreen") 
    mapy <- mapy + coord_equal() + theme_map()
    mapy <- mapy + geom_text(data=labs, aes(x=long, y=lat, label=ID_1, group=ID_1), size=6, family="serif") 
    mapy

    ## Plot boxplot
    boxploty <- ggplot(data=boxplot.df, aes(factor(name_code),value)) + 
    geom_boxplot(stat="boxplot", 
           position="dodge", 
           fill="grey",
           outlier.colour = "blue", 
           outlier.shape = 16, 
           outlier.size = 4) +
    labs(title="Distribution of yield impacts (in %) by GTAP region", y="Yield (% Change)") + theme_bw() + coord_flip() +
    stat_summary(fun.y = "mean", geom = "point", shape=21, size= 4, color= "red") +
    theme(plot.title = element_text(size = 26,
                              hjust = 0.5,
                              vjust = 1,
                              face = 'bold',
                              family="serif")) +
    theme(axis.text.x = element_text(colour = 'black',
                               size = 18,
                               hjust = 0.5, 
                               vjust = 1,
                               family="serif"),
    axis.title.x = element_text(size = 14, 
                               hjust = 0.5,
                               vjust = 0, 
                               face = 'bold',
                               family="serif")) +  
    theme(axis.text.y = element_text(colour = 'black', 
                               size = 18, 
                               hjust = 0, 
                               vjust = 0.5,
                               family="serif"), 
    axis.title.y = element_blank())
    boxploty

    ## I found this code on the website, and tried to tweak it to achieve my desired
    result, but failed
    # Plot objects using widths and height and respect to fix aspect ratios
    grid.newpage()
    pushViewport( viewport( layout = grid.layout( 2 , 1 , widths = unit( c( 1 ) , "npc" ) ,
                                                  heights = unit( c( 0.45 ) , "npc" ) , 
                                                  respect = matrix(rep(2,1),2) ) ) ) 
    print( mapy, vp = viewport( layout.pos.row = 1, layout.pos.col = 1 ) )
    print( boxploty, vp = viewport( layout.pos.row = 2, layout.pos.col = 1 ) )
    upViewport(0)
    vp3 <- viewport( width = unit(0.5,"npc") , x = 0.9 , y = 0.5)
    pushViewport(vp3)
    #grid.draw( legend )
    popViewport()