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I'm trying to use tm_facets to display data (in this case on maize yields) in 2005, 2050, and 2080. The test.RDS file is available here.
library(tmap)
map.temp <- readRDS("test.RDS")
title <- "Maize rainfed yield <br> (mt/ha)"
legend_title <- "(mt/ha)"
breaks <- c(1.0, 2139.2, 4277.5, 6415.8, 8554)
tm_shape(map.temp) +
tm_polygons(col = "value", title = legend_title) +
tm_facets(by = "year") +
tm_layout(main.title = title) +
tm_view(view.legend.position = c("left", "bottom"))
The code above does this, but displays the data in the wrong polygon and wrong years. To see this, run the script and click the dark red area in northeast Canada. The popup in all three maps says AMR_RUS with value of 5,634, but the colors are different. View the map.temp file (I'm using Rstudio to do all of this). Filter on FPU with AMR_RUS. The 2005 value is 6,047, 2050 is 5634 and 2080 is 4406 (climate change will reduce yields in this area). Next look at the first couple of entries in the geometry column. The lat long coordinates are for a region along the Chinese-Russian border. The Amur River makes up that border and AMR_RUS FPU (food production unit) is to the north of the Amur River in Russia.
Is the problem with my code or data or the tm_facet function in tmap?
Unfortunately, I can't figure out a solution with tmap, and not sure why is doing that misplacing of polygon names and values in the popup. UPDATE: seems that this was a tmap bug, which was immediately fixed - see tmap issue 268.
I know you asked for tmap solution, but, alternatively, could be worth exploring a solution with mapview - check this out and see if it works for you:
library(mapview)
breaks <- c(1.0, 2139.2, 4277.5, 6415.8, 8554)
m_2005 <- mapview(map.temp[map.temp$year == 2005, ],
zcol = "value",
at = breaks,
layer.name = "2005 - mt/ha")
m_2050 <- mapview(map.temp[map.temp$year == 2050, ],
zcol = "value",
at = breaks,
layer.name = "2050 - mt/ha")
m_2080 <- mapview(map.temp[map.temp$year == 2080, ],
zcol = "value",
at = breaks,
layer.name = "2080 - mt/ha")
sync(m_2005, m_2050, m_2080) # add ncol = 1, if you wish 1 column representation
I am trying to plot GIS coordinates, specifically UK national Grid Coordinates which eastings and northings ressemble:
194630000 562220000
I can plot these using clusplot in the Cluster library:
clusplot (df2,k.means.fit$cluster,main=i,color=TRUE,shade=FALSE,labels=0,lines=0,bty="7")
where df2 is my data frame and k.means.fit is the result of the K means analysis on df2.
Note that the coordinates of the centers after the k means analysis have not been normalised:
k.means.fit$centers
# Grid.Ref.Northing Grid.Ref.Easting
#1 206228234 581240726
But when I plot the clusters, all the points are translated such that they are centered around the origin.
I am wanting to show a map in the backround for context of the plots, but unless I am able to stop the translation, or at least know the values the function used, I cannot allign these properly.
I understand clusplots is designed to do a lot of feature automatically, which limits customisation, but I am not able to find a package that creates similar cluster plots.
Intended plot
(this was done at a random placement and is innaccurate)
Actual cluster diagram
Here is a way to produce something close what you are asking for.
Because of the need to translate between (lat, lon) and the graphics
coordinates (x,y) I did not use clusplot. Instead, I am using RgoogleMaps to get the background map and do the coordinate translations. I use car to plot the ellipses.
library(RgoogleMaps)
library(car)
## Some setup to get the map of the Chelmsford area.
lat <- c(51.7,51.8)
lon <- c(0.4, 0.5)
center = c(mean(lat), mean(lon))
zoom <- 10
Chelmsford <- GetMap(center=center, zoom=zoom, maptype= "roadmap",
destfile = "Chelsford.png")
You did not provide any points to test on, so I made up a few. I realize that my points are more separable than yours, but that only affects the clustering algorithm, not the mapping.
## Some Test Data
MC = structure(c(51.7965309028563, 51.794104389723, 51.7908688357699,
51.7787334409852, 51.7633572542762, 51.7674041270742, 51.7479758289189,
51.7649760469292, 51.7447369665147, 51.7576910228736, 51.7487855082363,
51.7601194948316, 51.754452857092, 51.7309692105151, 51.7107148897781,
51.6977473627376, 51.7139561908073, 51.7366387945275, 51.7325891642372,
51.7050420540348, 51.7050420540348, 51.7285391710661, 51.6677457194661,
51.6571998818184, 51.6466515895592, 51.6377241941241, 51.6377241941241,
51.645028557487, 51.6636899185361, 51.6580111872422, 51.6385358481586,
51.63528914486, 51.8789546795942, 51.8571513038925, 51.8531124817854,
51.8514968514399, 51.8676505449041, 51.8805693240155, 51.862805045846,
51.8506890145161, 51.8345292307446, 51.8337210892835, 51.8256388769982,
51.812704320496, 51.8232139304917, 51.8312965778826, 51.8240222604979,
51.8135128390641, 51.8094701011681, 51.807044284361, 51.7973397115523,
51.7803516822409, 51.7803516822409, 51.7949132419417, 51.7949132419417,
51.7811607811046, 51.7763059702794, 51.7787334409852, 51.9007474867743,
51.8781473356377, 51.8910630993239, 51.8757252167833, 51.8821839104485,
51.8821839104485, 51.8595744231562, 51.8821839104485, 51.8741103983922,
51.8660354365472, 51.8797620090535, 51.8765326042323, 51.8652278606205,
51.8934843918728, 51.8829911819196, 0.0895846775599907, 0.109172466823018,
0.153571455819268, 0.144430487496514, 0.140512929643877, 0.115701729910693,
0.109172466823018, 0.0882788249424316, 0.124842698233447, 0.171853392464776,
0.423882947649248, 0.447388294764912, 0.477422904968252, 0.45130585261751,
0.442164884294756, 0.468281936645498, 0.502234104701436, 0.504845809936514,
0.487869725908525, 0.430412210736963, 0.399071747916064, 0.395154190063467,
0.520516041346943, 0.527045304434619, 0.523127746582022, 0.511375073024189,
0.517904336111865, 0.54010383061001, 0.550550651550283, 0.55577406202044,
0.572750146048389, 0.508763367789111, 0.513986778259268, 0.504845809936514,
0.515292630876787, 0.537492125374932, 0.549244798932764, 0.588420377458818,
0.587114524841299, 0.550550651550283, 0.508763367789111, 0.493093136378682,
0.515292630876787, 0.485258020673487, 0.508763367789111, 0.504845809936514,
0.652407155718095, 0.669383239746084, 0.668077387128565, 0.644572040012901,
0.640654482160303, 0.640654482160303, 0.643266187395342, 0.606702314104326,
0.608008166721885, 0.619760840279717, 0.626290103367393, 0.594949640546534,
0.162712424142022, 0.156183161054346, 0.194052886962881, 0.182300213405049,
0.212334823608389, 0.217558234078545, 0.220169939313624, 0.238451875959131,
0.25542795998708, 0.259345517839678, 0.27109819139751, 0.28546257019042,
0.284156717572901, 0.295909391130693, 0.30113280160085), .Dim = c(73L,
2L), .Dimnames = list(NULL, c("lat", "lon")))
Plot the map and points just to get oriented.
PlotOnStaticMap(Chelmsford)
P1 = LatLon2XY.centered(Chelmsford, MC[,1], MC[,2], 10)
names(P1) = c("x", "y")
points(P1, pch=16)
Now we need to find and plot the clusters.
set.seed(42) ## For reproducibility
Clust = kmeans(MC, 7)
## Convert to graphics coordinates
Points = LatLon2XY.centered(Chelmsford, MC[,1], MC[,2], 10)
names(Points) = c("x", "y")
Points = data.frame(Points)
## Replot noting clusters
PlotOnStaticMap(Chelmsford)
points(Points, pch=21, bg=Clust$cluster)
## Add ellipses
for(i in 1:length(unique(Clust$cluster))) {
dataEllipse(Points[Clust$cluster == i,1], Points[Clust$cluster == i,2],
center.pch=10, levels=0.90, fill=TRUE, fill.alpha=0.1,
plot.points=FALSE, col=i, lwd=1,)
}
Et voila!
Hallo everyone can anybody help me to upgrade my code with possibility of insering additional data into my map. This is the code that draw me a map with intensity of migration, and I am trying to add ehtnic information of every region (many small pie charts).
to draw a map
con <- url("http://biogeo.ucdavis.edu/data/gadm2/R/UKR_adm1.RData")
print(load(con))
close(con)
name<-gadm$VARNAME_1
value<-c(4,2,5,2,1,2,4,2,2,4,1,1,1,4,3,3,1,1,3,1,2,4,5,3,4,2,1)
gadm$VARNAME_1<-as.factor(value)
col<- colorRampPalette(c('cadetblue4','cadetblue1','mediumseagreen','tan2','tomato3'))(260)
spplot(gadm, "VARNAME_1", main="Ukraine", scales = list(draw = TRUE), col.regions=col)
sp.label <- function(x, label) {
list("sp.text", coordinates(x), label)
}
NAME.sp.label <- function(x) {
sp.label(x, x$NAME_1)
}
draw.sp.label <- function(x) {
do.call("list", NAME.sp.label(x))
}
spplot(gadm, 'VARNAME_1', sp.layout = draw.sp.label(gadm), col.regions=col,
colorkey = list(labels = list( labels = c("Very low","Low", "Average",
"High","Very high"),
width = 1, cex = 1)))
and this is a part of df, that I am trying to add to that map as pie charts or bar charts, with every latitude (lat) and longitude (long) to locate mu bar or pie charts.
df<-data.frame(region=c('Kiev oblast', 'Donezk oblast'),
rus=c(45,35), ukr=c(65,76), mold=c(11,44),long=c(50.43,48),
lat=c(30.52, 37.82))
i found one example and another but... can't figure out how to use it in ma case.
Hope for your help, thank you.
only that solution i have discovered by now, but it doesn't upgrade my code(((
mapPies( df,nameX="lat", nameY="long", nameZs=c('rus','ukr','mold'),
xlim=c(30,33), ylim=c(44,53), symbolSize = 2)
perhaps this will help:
pieSP The function provide SpatialPolygonsDataFrame depending on few attributes, ready to use for plotGoogleMaps or spplot.
library(plotGoogleMaps)
data(meuse)
coordinates(meuse)<-~x+y
proj4string(meuse) <- CRS('+init=epsg:28992')
pies <- pieSP(meuse,zcol=c('zinc','lead','copper'), max.radius=120)
pies$pie <- rep(c('zinc','lead','copper'),155)
pies$pie2 <- rep(1:3,155)
spplot(pies, 'pie2')
I have a map of the USA and a list of long, lat that I want to plot. Once I get this working, I also want to switch over to the "world" map. The map is generated, but no points appear on the map. The first line of the TSV file contains this header: LONG{tab}LAT R appears to be reading in the 'traffic' table OK. What am I doing wrong?
library("maps")
traffic = read.table("C:/temp/traffic_10.40.tsv", header=T, sep="\t")
png(filename="C:/temp/usa.png", width=850, height=600, bg="white")
map('state', plot = TRUE, fill = FALSE, col = palette())
title("Destinations")
points(x=traffic$LONG,y=traffic$LAT,col='red',cex=0.75)
dev.off()
EDIT
> dput(traffic)
structure(list(LONG = c(47.6218, 32.7942, 34.1121, 40.0068, 47.6218,
33.9553, 33.7629, 40.0068, 39.05, 38.1075, 33.7629, 32.769, 37.3857,
29.4576, 34.1674, 38.8147, 32.7942, 31.1429, 40.3254, 30.3059,
38.2248, 47.6218, 33.9553, 38.1075, 27.1943, 29.4576, 30.5175,
38.5668, 42.6657, 40.2982, 32.7539, 40.6698, 47.6742, 32.7942,
47.6218, 35.8219), LAT = c(-122.35, -96.7653, -118.411, -75.1347,
-122.35, -83.3937, -84.4226, -75.1347, -77.4833, -122.264, -84.4226,
-96.5998, -122.026, -98.5054, -84.8014, -77.0647, -96.7653, -81.471,
-78.9195, -97.7505, -85.7412, -122.35, -83.3937, -122.264, -80.2432,
-98.5054, -97.6721, -121.467, -73.799, -111.698, -97.3363, -73.9438,
-122.115, -96.7653, -122.35, -78.6588)), .Names = c("LONG", "LAT"
), class = "data.frame", row.names = c(NA, -36L))
Also, I am a R newbie and have tried finding this on google with limited success because I am not sure what to search for exactly.
The problem is in your data set rather than your later code.
The first point has one co-ordinate 47.6218 and the other -122.35. Latitudes cannot be outside the range [-90,90] degrees so the longitude must be -122.35 and latitude 47.6218, the opposite of your data set. This is slightly north of the Seattle Space needle
x (horizontal) is traditionally longitude or easting; y (vertical) is traditionally latitude or northing
One option would be to use googleVis for this. You could plot out your points Google-Maps style.
Fixed. I swapped $LAT and $LONG. Now it works perfectly.
points(x=traffic$LAT,y=traffic$LONG,col='red',cex=0.75)
Good day everyone,
Using the code below I can successfully retrieve a raster from Google using ggmap, plot an annotation_raster using ggplot2, and plot site localities as red dots on top of the raster layer. On the plot the positions don't quite match (they should follow the coastline). I know my sites' positions are correct because they plot where they should be when I upload the data onto Google Earth as a KML file.
Suggestions will be appreciated.
This code will run as is... Note that you need a development version of ggplot2, which is available on github. To install:
# install.packages("devtools")
library(devtools)
install_github("ggplot2")
and for the code:
library(ggplot2)
library(ggmap)
library(grDevices)
theme_set(theme_bw())
# Some coordinates of points to plot:
siteLat = c(-22.94414, -22.67119, -29.25241, -30.31181, -32.80670, -33.01054, -32.75833, - 33.36068, -31.81708, -32.09185, -32.31667, -34.13667, -34.05016, -33.91847, -34.13525, -34.12811, -34.10399, -34.16342, -34.41459, -34.58786, -34.83353, -34.37150, -34.40278, -34.17091, -34.08565, -34.04896, -33.98066, -34.02448, -34.20667, -34.05889, -33.97362, -33.99125, -33.28611, -33.02407, -33.01798, -32.99316, -31.09704, -31.05000, -30.91622, -30.70735, -30.28722, -30.27389, -29.86476, -29.54501, -29.49660, -29.28056, -28.80467, -27.42472)
siteLon = c(14.50175, 14.52134, 16.86710, 17.26951, 17.88522, 17.95063, 18.02778, 18.15731, 18.23065, 18.30262, 18.32222, 18.32674, 18.34971, 18.38217, 18.43592, 18.45077, 18.48364, 18.85908, 19.25493, 19.33971, 20.00439, 21.43518, 21.73972, 22.12749, 23.05532, 23.37925, 23.64567, 23.89933, 24.77944, 25.58889, 25.64724, 25.67788, 27.48889, 27.91626, 27.92182, 27.95036, 30.18395, 30.21666, 30.32982, 30.48474, 30.76026, 30.83556, 31.04479, 31.21662, 31.24665, 31.44403, 32.07567, 32.73333)
siteName = c(seq(1:length(siteLon)))
sites <- as.data.frame(cbind(siteLat, siteLon, siteName))
# specify raster's approximate coordinates:
lats = c(-35, -20)
lons = c(10, 35)
SAMap <- GetMap.bbox(lons, lats, maptype = "satellite")
# extract "real" coords of raster:
lonr <- c(SAMap$BBOX$ll[2], SAMap$BBOX$ur[2])
latr <- c(SAMap$BBOX$ll[1], SAMap$BBOX$ur[1])
# extract raster fill data:
h_raster <- as.raster(SAMap$myTile)
# plot using annotation_raster:
g <- ggplot(sites, aes(siteLon, siteLat))
g + annotation_raster(h_raster, lonr[1], lonr[2], latr[1], latr[2]) +
geom_point(aes(x = siteLon, y = siteLat), colour = "red", data = sites) +
scale_x_continuous(limits = lonr) +
scale_y_continuous(limits = latr)
(Sorry, I cannot post an image as I am new here).
Okay, the problem has been resolved thanks to David Kahle. See this post:
https://groups.google.com/forum/?hl=en&fromgroups#!topic/ggplot2/ABffHL3WTpY
AJ