I am trying to print an R map with the following function (see at bottom)
The input is a data frame that contain Longitude, Latitudes in decimal format and the errors that would be depicted as color bullet points.
This works quite okay but I want to add a new extra point, apart of what the data frame includes, that would have a different type (instead of dot, perhaps a cross or a square) and with a fixed red color, instead of following the color ramp I have for the rest of the points.
Can you please help me sort this out?
Regard
Alex
dfE<-data.frame(c(-0.1456250,-0.1442639),c(51.51476,51.51492),c(0.018878676,0.111847050))
names(dfE) <- c("Longitude", "Latitude", "Error")
stationaryPoint<-data.frame(0.1422361,51.51516)
names(stationaryPoint) <- c("Longitude", "Latitude")
data<-dfE
jet.colors <- colorRampPalette(c("#00007F", "red", "#007FFF", "yellow", "#7FFF7F", "cyan", "#FF7F00", "blue", "#7F0000"))
bbox <- c(min(data[, 1])-0.001, min(data[, 2])-0.001, max(data[, 1])+0.001, max(data[, 2])+0.001)
mp <- get_stamenmap(bbox, maptype = "toner", zoom = zoom)
ggmap(mp, darken = 0) + geom_point(aes(Longitude, Latitude, colour =Error), data = dfE, size = 3)
I tried adding the below line to add the extra point with different color and shape to the ggmap line before but I always get an error
geom_point(aes(Longitude, Latitude), data = stationaryPoint, size = 3,shape=4,color="red")
Since you didn't provide any data it is difficult to help you.
The solution to your problem could be to add another layer with geom_point:
# create new data.frame with location of point you want to plot
newdata <- data.frame(Longitude = c(40.7143528), Latitude = c(-74.0059731)) # New York
ggmap(mp, darken = 0) +
geom_point(aes(Longitude, Latitude, colour =Error), data = dfE, size = 3) +
geom_point(data = newdata, shape = 15) +
RestofyourCode
Related
I am trying to make a map with hotels in las vegas. I have all the coordinates. I also made a map with a dot at the 'hotel points'. But these dots are all black. I need every hotel (dot) to be another color.
As you can see, all the dots (hotels) are black..
This is my code:
df_hotels <- df_joinall %>%
group_by(hotel_name)
df <- st_as_sf(df_hotels, coords = c("Longitude","Latitude"))
tmap_mode("view")+
tm_basemap("OpenStreetMap") +
tm_shape(df) +
tm_dots(popup.format = list(text.align = "center"), size = 0.5, alpha = 0.7)
Does anyone has suggestions on how to give every point (hotel) another color
To have the points colored you need to map the col aesthetic to a column of your data frame. Note that {tmap} requires column names enclosed in quotation marks.
Your example is not exactly reproducible, but I expect this to work:
df_hotels <- df_joinall %>%
group_by(hotel_name)
df <- st_as_sf(df_hotels, coords = c("Longitude","Latitude"))
tmap_mode("view")+
tm_basemap("OpenStreetMap") +
tm_shape(df) + tm_dots(col = "hotel_name", size = 0.5, alpha = 0.7)
I have a fairly simple and probably common task, plotting a raster dataset with countour lines and adding country borders together in one plot, however I did not find a solution anywhere. There are a a few hints available (such as this one), but no raster dataset is used there and I can't get it to work.
The dataset I am using is actually in netcdf format and available here (15mb in size) and contains about 40 years of gridded precipitation data.
Here is my line of code:
setwd("...netcdf Data/GPCP")
library("raster")
library("maps")
nc_brick79_17 <- brick("precip.mon.mean.nc") # load in the ncdf data as a
raster brick
newextent <- c(85, 125, -20, 20) # specify region of interest
SEA_brick <- crop(nc_brick79_17, newextent) # crop the region
day1 <- SEA_brick[[1]] # select very first day as example
colfunc<-colorRampPalette(c("white","lightblue","yellow","red","purple")) # colorscale for plotting
So it works of course when I just plot the raster data together with a map overlaid:
plot(day1, col=(colfunc(100)), interpolate=F, main="day1",legend.args=list(text='mm/hr', side=4,font=1, line=2.5, cex=1.1))
map("world", add=TRUE, lwd=0.5, interior = FALSE, col = "black")
We get this plot (Raster Plot with country borders added)
Now the code I use to generate the contour plot is the following:
filledContour(day1,zlim=c(0,20),color=colorRampPalette(c("white","lightblue","yellow","red","purple")),
xlab = "Longitude (°)", ylab = "Latitude (°)")
map("world", add=TRUE, lwd=0.5, interior = FALSE, col = "black") # add map overlay
I end up with a plot where obviously the country borders do not align and are even covering the colorbar.
Contour plot with map overlay shifted
In this last part I am trying to add the country boundaries to the contour plot, but it does not work, even though it should I assume. The map is simply not there, no error though:
filledContour(day1, zlim=c(0,20),
color.palette = colorRampPalette(c("white","lightblue","yellow","red","purple")),
xlab = "Longitude (°)", ylab = "Latitude (°)",
xlim = c(90, 120), ylim = c(-20, 20), nlevels = 25,
plot.axes = {axis(1); axis(2);
map('world', xlim = c(90, 120), ylim = c(-20, 20), add = TRUE, lwd=0.5, col = "black")})
From that line of code I get this plot.
Contour plot but no country borders added
What could I improve or is there any mistake somewhere? Thank you!
I chose to use ggplot here. I leave two maps for you. The first one is the one you created. This is a replication with ggplot. The second one is the one you could not produce. There are many things to explain. But I am afraid I do not have enough time to write all. But I left some comments in my code below. Please check this question to learn more about the second graphic. Finally, I'd like to give credit to hrbrmstr who wrote a great answer in the linked question.
library(maptools)
library(akima)
library(raster)
library(ggplot2)
# This is a data set from the maptools package
data(wrld_simpl)
# Create a data.frame object for ggplot. ggplot requires a data frame.
mymap <- fortify(wrld_simpl)
# This part is your code.
nc_brick79_17 <- brick("precip.mon.mean.nc")
newextent <- c(85, 125, -20, 20)
SEA_brick <- crop(nc_brick79_17, newextent)
day1 <- SEA_brick[[1]]
# Create a data frame with a raster object. This is a spatial class
# data frame, not a regular data frame. Then, convert it to a data frame.
spdf <- as(day1, "SpatialPixelsDataFrame")
mydf <- as.data.frame(spdf)
colnames(mydf) <- c("value", "x", "y")
# This part creates the first graphic that you drew. You draw a map.
# Then, you add tiles on it. Then, you add colors as you wish.
# Since we have a world map data set, we trim it at the end.
ggplot() +
geom_map(data = mymap, map = mymap, aes(x = long, y = lat, map_id = id), fill = "white", color = "black") +
geom_tile(data = mydf, aes(x = x, y = y, fill = value), alpha = 0.4) +
scale_fill_gradientn(colors = c("white", "lightblue", "yellow", "red", "purple")) +
scale_x_continuous(limits = c(85, 125), expand = c(0, 0)) +
scale_y_continuous(limits = c( -20, 20), expand = c(0, 0)) +
coord_equal()
ggplot version of filled.contour()
# As I mentioned above, you want to study the linked question for this part.
mydf2 <- with(mydf, interp(x = x,
y = y,
z = value,
xo = seq(min(x), max(x), length = 400),
duplicate = "mean"))
gdat <- interp2xyz(mydf2, data.frame = TRUE)
# You need to draw countries as lines here. You gotta do that after you draw
# the contours. Otherwise, you will not see the map.
ggplot(data = gdat, aes(x = x, y = y, z = z)) +
geom_tile(aes(fill = z)) +
stat_contour(aes(fill = ..level..), geom = "polygon", binwidth = 0.007) +
geom_contour(color = "white") +
geom_path(data = mymap, aes(x = long, y = lat, group = group), inherit.aes = FALSE) +
scale_x_continuous(limits = c(85, 125), expand = c(0, 0)) +
scale_y_continuous(limits = c(-20, 20), expand = c(0, 0)) +
scale_fill_gradientn(colors = c("white", "lightblue", "yellow", "red", "purple")) +
coord_equal() +
theme_bw()
I am generating a map very similar to this
(source: dominodatalab.com)
] to visualize the frequency in which cities occur. How can I create a legend or key for this map so I can see what the size of the circles represent numerically?
Here is my code:
myLocation <- c(-124, 32, -66, 42)
myMap <- get_map(location = myLocation, source = "stamen",
maptype = "toner", crop = FALSE, zoom = 4)
ggmap(myMap) +
geom_point(aes(x = lon, y = lat), data = csr.Ax1,
col = "orange", alpha = 0.4, size = csr.Ax1$freq*.25) +
scale_size_continuous(range = range(csr.Ax1$freq), guide = "legend") +
ggtitle("CSR Active Candidates") +
legend()
EDIT: SOLVED!
The solution was placing the size=csr.Ax1$freq from the geom_point argument into the aes() argument.
The solution was placing the size=csr.Ax1$freq from the geom_point argument into the aes() argument.
I have been trying to create a map of membership locations from postcodes across the UK as a project in learning R. I have achieved nearly the result I wanted, but it's proving very frustrating getting the glitches sorted. This image is my current best effort:
I still want to change:
get rid of the extraneous legend (the "0.16", "0.5" squares), which are coming from the size arg to geom_point. If I remove the size=0.16 arg the guide/legend disappears, but the geom size returns to the default too. This also happens for the "black" guide -- coming from a colour obviously -- but why?
properly clip the stat_density2d polygons, which are exhibiting undesireable behaviour when clipped (see bottom-right plot near the top)
have control over the line-width of the geom_path that includes the county boundaries: it's currently too thick (would like about 1/2 thickness shown) but all I can achieve by including 'size' values is to make the lines stupidly thick - so thick that they obscure the whole map.
The R code uses revgeocode() to find the placename closest to the centre point but I don't know how to include the annotation on the map. I would like to include it in a text-box over the North Sea (top right of UK maps), maybe with a line/arrow to the point itself. A simpler option could just be some text beneath the UK map, below the x-axis ... but I don't know how to do that. geom_rect/geom_text seem fraught in this context.
Finally, I wanted to export the map to a high-res image, but when I do that everything changes again, see:
which shows the high-res (~1700x1800px) image on the left and the Rstudio version (~660x720px) on the right. The proportions of the maps have changed and the geom_text and geom_point for the centre point are now tiny. I would be happy if the gap between the two map rows was always fairly small, too (rather than just small at high res).
Code
The basics: read list of members postcodes, join with mySociety table of postcode<>OSGB locations, convert locations to Lat/long with spTransform, calculate binhex and density layers, plot with ggmap.
The code for all this is somewhat lengthy so I have uploaded it as a Gist:
https://gist.github.com/rivimey/ee4ab39a6940c0092c35
but for reference the 'guts' of the mapping code is here:
# Get a stylised base map for the whole-of-uk maps.
map.bbox = c(left = -6.5, bottom = 49.5, right = 2, top = 58)
basemap.uk <- get_stamenmap(bb = map.bbox, zoom=calc_zoom(map.bbox), maptype="watercolor")
# Calculate the density plot - a continuous approximation.
smap.den <- stat_density2d(aes(x = lat, y = lon, fill = ..level.., alpha = ..level..),
data = membs.wgs84.df, geom = "polygon",
breaks=2/(1.5^seq(0,12,by=1)), na.rm = TRUE)
# Create a point on the map representing the centroid, and label it.
cmap.p <- geom_point(aes(x = clat, y = clon), show_guide = FALSE, data = centroid.df, alpha = 1)
cmap.t1 <- geom_text(aes(x = clat, y = clon+0.22, label = "Centre", size=0.16), data = centroid.df)
cmap.t2 <- geom_text(aes(x = clat, y = clon+0.1, label = "Centre", size=0.25), data = centroid.df)
# Create an alternative presentation, as binned hexagons, which is more true to the data.
smap.bin <- geom_hex(aes(x = lat, y = lon),
data = membs.wgs84.df, binwidth = c(0.15, 0.1), alpha = 0.7, na.rm = TRUE)
# Create a path for the county and country boundaries, to help identify map regions.
bounds <- geom_path(aes(x = long, y = lat, group = group, colour = "black"), show_guide = FALSE,
data = boundaries.subset, na.rm = TRUE)
# Create the first two actual maps: a whole-uk binned map, and a whole-uk density map.
map.bin <- ggmap(basemap.uk) + smap.bin + grad + cmap.p + cmap.t1
map.den <- ggmap(basemap.uk) + smap.den + alpha + cmap.p + cmap.t1
# Create a zoomed-in map for the south-east, to show greater detail. I would like to use this
# bbox but google maps don't respect it :(
map.lon.bbox = c(left = -1, bottom = 51, right = 1, top = 52)
# Get a google terrain map for the south-east, bbox roughly (-1.7,1.7, 50.1, 53)
basemap.lon <- get_map(location = c(0,51.8), zoom = 8, maptype="terrain", color = "bw")
# Create a new hexbin with more detail than earlier.
smap.lon.bin <- geom_hex(aes(x = lat, y = lon),
data = membs.wgs84.df, bins=26, alpha = 0.7, na.rm = TRUE)
# Noe create the last two maps: binned and density maps for London and the SE.
lonmap.bin <- ggmap(basemap.lon) + bounds + smap.lon.bin + grad + cmap.p + cmap.t2
lonmap.den <- ggmap(basemap.lon) + bounds + smap.den + alpha + cmap.p + cmap.t2
# Arrange the maps in 2x2 grid, and tell the grid code to let the first row be taller than the second.
multiplot(map.bin, lonmap.bin, map.den, lonmap.den, heights = unit( c(10,7), "null"), cols=2 )
I have been playing around with ggplot2 a bunch and found Adding table within the plotting region of a ggplot in r
I was wondering is there any method for this for plotting using non cartesian coordinates, eg if map coordinates were used for the positioning of the table. I had some maps and thought it would be cool if they could have their corresponding data in a table for points to show more detail.
If anyone knows a work around for annotation_custom for non cartesian coordinates it would be greatly appreciated.
EDIT:Here is a image of what my map looks like, I was just thinking is there another way to plot the table on the left side of this.
EDIT: here is what Im attempting to do
EDIT: Here is the basic code structure for the plot
library(ggplot2)
library(ggmap)
plotdata <- read.csv("WellSummary_All_SE_NRM.csv", header = T)
plotdata <- na.omit(plotdata)
plotdata <- plotdata[1:20, c("Unit_No","neg_decimal_lat", "decimal_long", "max_drill_depth", "max_drill_date")]
map.plot<- get_map(location = c(min(plotdata$decimal_long),
min(plotdata$neg_decimal_lat),
max(plotdata$decimal_long),
max(plotdata$neg_decimal_lat)),
maptype ="hybrid",source = "google", zoom=8)
theme_set(theme_bw(base_size = 8))
colormap <- c("darkblue","blue","lightblue", "green", "yellow", "orange","darkorange", "red", "darkred")
myBreaks <- c(0,2, 10, 50, 250, 1250, 2000, 2500)
static.map <- ggmap(map.plot) %+% plotdata +
aes(x = decimal_long,
y = neg_decimal_lat,
z= max_drill_depth)+
stat_summary2d(fun = median, binwidth = c(.03, .03),alpha = 0.7) +
scale_fill_gradientn(name = "depth", colours= colormap, breaks=myBreaks,labels = format(myBreaks),
limits= c(0,2600), space = "Lab") +
labs(x = "Longitude",y = "Latitude")+
geom_text(aes(label=Unit_No),hjust=0, vjust=0,size=2,
position = position_dodge(width=0.9), angle = 45)+
coord_map()
#Creates image of the plot in file to Working Directory
filename=paste("2dmap",".png", sep="")
cat("\t",filename,"file created, saving...\n")
print(static.map)
cat("\tpassed mapping, file now being made\n")
ggsave(filename=filename,
plot = static.map,
scale = 1,
width = 6, height = 4,
dpi = 300)
I will try to upload the data today, cheers for some of the pointers already!
I have uploaded the data, dont worry about the positioning of the gradient values and text tags as I can fix them later I will also link the current ggmap code but I am using a very large loop for the data to be sorted.
https://drive.google.com/file/d/0B8qOIJ-nPp9rM1U1dkEzMUM0Znc/edit?usp=sharing
try this,
library(gridExtra)
grid.arrange(tableGrob(head(iris)), qplot(1,1), ncol=2)
annotation_custom wouldn't help, it's meant for adding things inside the plot panel, not to the side.