Map Data: InputSpatialData
Yield Data: InputYieldData
Results_using viewport(): 
EDIT: Results using "multiplot" function as suggested by @rawr (see comment below). I do love the new results, especially that the map is bigger. Nonetheless, the boxplot seems misaligned with the map plot still. Is there a more systematic way to control for centering and placement?
My Question: Is there a way to control for the size of the boxplot plot to make it close in size and centered with the map plot above it?
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()