I am having some trouble with getting a certain plot layout when using the maps package. Here is what I am attempting:
library(maps)
library(mapdata)
aa <- rep(1,5); ab <- c(2,3,1,1,1)
mat <- rbind(aa,aa,aa,ab)
layout(mat)
map('state', mar=c(0,0,0,0))
map('worldHires', region='USA:Alaska', xlim=c(-175,-120))
map('worldHires', region='Hawaii', xlim=c(-161,-154.5))
Here is the error I receive:
Error in plot.new() : plot region too large
Usually I mess with the margins to resolve this error, but that doesn't seem to be working. Any ideas?
You can resolve this by setting the margins before plotting each new map:
layout(mat)
map('state')
par(mar=c(0,0,0,0))
map('worldHires', region='USA:Alaska', xlim=c(-175,-120), col="blue")
par(mar=c(0,0,0,0))
map('worldHires', region='Hawaii', xlim=c(-161,-154.5), col="blue")
via https://stat.ethz.ch/pipermail/r-help/2006-September/113030.html
Related
I'm trying to plot a world map on R but I don't have the version updated for ggplot2. Is there a way of doing it without?
You can get an extremely simple world map with:
library(maps)
map('world', fill = TRUE, col = 2:8, wrap=c(-180,180) )
And a somewhat better map from the mapdata package
library(mapdata)
map('worldHires', fill=TRUE, col=2:8)
And just for fun, here is a version with prettier colors, a blue ocean and cutting out Antarctica.
RegHR <- map("worldHires", namesonly=TRUE, plot=FALSE)
map('worldHires', fill=TRUE, col=terrain.colors(6), bg="#CCEEFF",
region=RegHR[-grep("Antarctica", RegHR)])
I am unsuccessfully trying to plot lines on a world map with Mollweide projection. I also plotted points on that same map, and it worked out fine. For the lines, I tried to adapt this example to my needs: http://flowingdata.com/2011/05/11/how-to-map-connections-with-great-circles/.
I failed with the pre-test (Step 4 in the ex.) already. In the following code, the line is supposed to connect Kenya and Australia. It runs without errors, but there's no line in the output. (I also tested the example without mapproj and the line is there.)
library("maps")
library("mapproj")
library("geosphere")
map("world",proj="mollweide", orientation= c(90,0,0), fill=TRUE, col="white", bg="lightblue")
lon_ke <- 38
lat_ke <- 1
lon_aus <- 133
lat_aus <- -27
inter <- gcIntermediate(c(mapproject(lon_ke,lat_ke), proj="mollweide", orientation= c(90,0,0)),
c(mapproject(lon_aus,lat_aus), proj="mollweide", orientation= c(90,0,0)),
n=50, addStartEnd=TRUE)
lines(inter)
I found a solution to my problem, based on Thomas Rahlf's book (see comment). Here's my script (it helps visualizing where authors publish articles).
library(maps)
library(geosphere)
library(mapproj)
#load data
locations <- read.csv("articles-authors-locations.csv", header=TRUE, check.names = FALSE)
#plot map with Mollweide projection
myProj.type<-"mollweide"
myProj.orient<-c(90,0,0)
x<-map(proj=myProj.type,orient=myProj.orient,wrap=T,fill=TRUE, col="white", bg="lightblue",xlim=range(locations$ArticleLong),ylim=range(locations$ArticleLat)
)
#plot jittered points for authors' locations
myStartP<-mapproject(jitter(locations$AuthorLong,amount=3),jitter(locations$AuthorLat, amount=1),proj=myProj.type,orient=myProj.orient)
points(myStartP,col="darkblue",pch=20,cex=1)
#set transparent colors
myTColour<-rgb(0,0,0,50,maxColorValue=255)
red_transp <- adjustcolor("red", alpha.f = 0.4)
#plot lines and jittered points, connecting authors' and articles locations
for (i in 1:nrow(locations))
{
myGC1<-gcIntermediate(c(locations$AuthorLong[i],locations$AuthorLat[i]),c(locations$ArticleLong[i],locations$ArticleLat[i]),addStartEnd=T, n=50)
moll<-mapproject(myGC1[,1],myGC1[,2],projection=myProj.type,orientation=myProj.orient)
lines(moll$x,moll$y,lwd=2.5,col=myTColour)
myDestP<-mapproject(
jitter(locations$ArticleLong[i], amount=3),
jitter(locations$ArticleLat[i], amount=1),
proj=myProj.type,orient=myProj.orient)
points(myDestP,col=red_transp,pch=20,cex=1)
}
I want to plot a shapefile over a raster file in R but I can't make them overlap perfectly: the raster appears to be rotated of few degrees counter-clockwise. Is it a problem with the projection?
Please consider the following MWE
library(raster)
library(rgdal)
# Download from http://biogeo.ucdavis.edu/data/gadm2/shp/ITA_adm.zip
shape_file = "ITA_adm1.shp"
# Download from http://sedac.ciesin.columbia.edu/data/set/gpw-v3-population-density/data-download
# Setting Geography: Country, Italy; Data Attributes: Grid
pop_density_file ="w001001.adf"
italy_map <- readOGR(dsn = shape_file, layer = "ITA_adm1")
italy_map_dens <- raster(pop_density_file)
colPal <- colorRampPalette(c("white", "red"))( 500 )
par(mar=c(0,0,0,0))
plot(italy_map_dens, xlim = c(6.70, 18.32), ylim = c(35.2, 47.6), axes=FALSE, box=FALSE, legend=FALSE, col=colPal)
plot(italy_map, xlim = c(6.70, 18.32), ylim = c(35.2, 47.6), border="grey", add=TRUE)
Apparently there was a bug in the rgdal package. My problem was solved after I updated it to version 0.8-12.
It does appear to be a problem with the projection. You need to find out the exact projection of both datasets, and convert one of the datasets to the projection of the other dataset.
I want to create a contour of variable z with the x,y,z data. However, it seems like we need to provide the data in increasing order.
I tried to use some code but it gave me the error.
I tried the following code: Trial 1:
age2100 <- read.table("temp.csv",header=TRUE,sep=",")
x <- age2100$x
y <- age2100$y
z <- age2100$z
contour(x,y,z,add=TRUE,col="black")
I got the following error
Error in contour.default(x, y, z, add = TRUE, col = "black") : increasing 'x' and 'y' values expected
I then tried to use ggplot2 to create the contour. I used the following code:
library("ggplot2")
library("MASS")
library("rgdal")
library("gpclib")
library("maptools")
age2100 <- read.table("temp.csv",header=TRUE,sep=",")
v <- ggplot(age2100, aes(age2100$x, age2100$y,z=age2100$z))+geom_contour()
v
I got the following error:
Warning message:
Not possible to generate contour data
Please find the data on the following location https://www.dropbox.com/s/mg2bo4rcr6n3dks/temp.csv
Can anybody tell me how to create the contour data from the third variable (z) from the temp.csv ? I need to do these many times so I am trying to do on R instead of Arcgis.
Here is an example of how one interpolates using interp from the akimapackage:
age2100 <- read.table("temp.csv",header=TRUE,sep=",")
x <- age2100$x
y <- age2100$y
z <- age2100$z
require(akima)
fld <- interp(x,y,z)
par(mar=c(5,5,1,1))
filled.contour(fld)
Here is an alternate plot using the imagefunction (this allows some flexibility to adding lower level plotting functions (requires the image.scale function, found here):
source("image.scale.R") # http://menugget.blogspot.de/2011/08/adding-scale-to-image-plot.html
x11(width=5, height=6)
layout(matrix(c(1,2), nrow=1, ncol=2), widths=c(4,1), height=6, respect=TRUE)
layout.show(2)
par(mar=c(4,4,1,1))
image(fld)
contour(fld, add=TRUE)
points(age2100$x,age2100$y, pch=".", cex=2)
par(mar=c(4,0,1,4))
image.scale(fld$z, xlab="", ylab="", xaxt="n", yaxt="n", horiz=FALSE)
box()
axis(4)
mtext("text", side=4, line=2.5)
I have been trying for a few days to create the contour and then plot the shapefile and contour on the same file. Now, that I am able to create the contour and shapefile on the same plot. I want to clip the contour with the shapefile an only show the shapefile.
The data temp.csv can be found on this link https://www.dropbox.com/s/mg2bo4rcr6n3dks/temp.csv
Shapefile can be found on the following location: https://www.dropbox.com/sh/ztvmibsslr9ocmc/YOtiwB8p9p
The script file image.scale.R can be found on the following location "https://www.dropbox.com/s/2f5s7cc02fpozk7/image.scale.R "
The code that I have used so far is as follows:
## Required packages
library(maptools)
library(rgdal)
library(sp)
library(maptools)
library(sm)
require(akima)
require(spplot)
library(raster)
library(rgeos)
## Set Working Directory
setwd("C:\\Users\\jdbaba\\Documents\\R working folder\\shape")
## Read Data from a file
age2100 <- read.table("temp.csv",header=TRUE,sep=",")
x <- age2100$x
y <- age2100$y
z <- age2100$z
####################################
##Load the shape file
#####################################
shapefile <- readShapePoly("Export_Output_4.shp")
fld <- interp(x,y,z)
par(mar=c(5,5,1,1)) filled.contour(fld)
###Import the image.scale
source source("image.scale.R")
# http://menugget.blogspot.de/2011/08/adding-scale-to-image-plot.html
x11(width=8, height=7)
layout(matrix(c(1,2), nrow=1, ncol=2), widths=c(6,1), height=6, respect=TRUE)
layout.show(2)
par(mar=c(4,4,1,2))
image(fld,axes=T)
contour(fld, add=TRUE)
#points(age2100$x,age2100$y, pch=".", cex=2,legend=F)
plot(shapefile,add=T,lwd=2)
box()
par(mar=c(4,0,1,4))
image.scale(fld, xlab="Eastings", ylab="Northings", xaxt="n", yaxt="n", horiz=FALSE)
axis(4)
mtext("Salinity", side=4, line=2.5)
The output of the above code is as follows:
Now, I want to get rid of the colored gradients and the contours from the polygon shapefile and only leave the intersection part.
Any help is highly appreciated.
Research: I found this link https://gis.stackexchange.com/questions/25112/clip-depth-contour-with-spatial-polygon on Stack exchange Gis and I tried to follow this method I always get error while creating the contour.
I found another similar thread on https://stat.ethz.ch/pipermail/r-sig-geo/2009-May/005793.html . But I couldn't make it work on my dataset.
I would like to acknowledge Marc in the box for helping me in getting to this point.
Thanks.
Indeed, #baptiste gave you a strong hint for the solution, the recent paper by Paul Murrell. Paul was generous to provide us with the code for his entire paper manuscript, which you can get from his personal website. On the side topic, Paul shows beautiful example of reproducible research with this paper. Generally, I took the following approach:
extract latitude and longitude coordinates from the shapefile (a function to do this is here, by Paul Hiemstra),
plot everything with your code,
and use polypath to remove everything outside the boundaries defined by shapefile, using extracted coordinates as a baseline.
#function to extract coordinates from shapefile (by Paul Hiemstra)
allcoordinates_lapply = function(x) {
polys = x#polygons
return(do.call("rbind", lapply(polys, function(pp) {
do.call("rbind", lapply(pp#Polygons, coordinates))
})))
}
q = allcoordinates_lapply(shapefile)
#extract subset of coordinates, otherwise strange line connections occur...
lat = q[110:600,1]
long = q[110:600,2]
#define ranges for polypath
xrange <- range(lat, na.rm=TRUE)
yrange <- range(long, na.rm=TRUE)
xbox <- xrange + c(-20000, 20000)
ybox <- yrange + c(-20000, 20000)
#plot your stuff
plot(shapefile, lwd=2)
image(fld, axes=F, add=T)
contour(fld, add=T)
#and here is the magic
polypath(c(lat, NA, c(xbox, rev(xbox))),
c(long, NA, rep(ybox, each=2)),
col="white", rule="evenodd")