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Update/Edit/Reprex: Rendering the same spatial data with the same graphics device takes 1 second with tmap versus 80 seconds with ggplot2, even though the tmap plot's R object is 80x larger in size. Difference in internals and/or implementation btw. packages & graphics device?

library(ggplot2); library(sf); 
library(tmap); library(tidyverse)
library(here) # project directory

data(World) # sf object from tmap; Provides Africa polygon

# 'd' data pulled from acleddata.com/data, restricted to Aug 18 2017  - Aug 18 2018, Region: N/S/E/W/Middle Africa only
d <- read.csv(here('2017-08-18-2018-08-18-Eastern_Africa-Middle_Africa-Northern_Africa-Southern_Africa-Western_Africa.csv'))
dsf <- st_as_sf(d, coords = c('longitude', 'latitude'), crs = 4326)

Data used: 1 -- 'World' shapefile data from the tmap package itself, and

2 -- acleddata.com/data, ACLED conflict events restricted to Africa between August 18 2017 and August 18 2018 (7.8 MB .csv; these filters:)

enter image description here

Plot rendering:

# ggplot2; build plot, assign to object
dev.cur()   # RStudioGD on macOS: quartz
system.time(p <- ggplot(World %>% filter(continent == 'Africa')) + 
  geom_sf() + 
  geom_sf(data = dsf, aes(fill = event_type, 
              color = event_type)) + 
  ggthemes::theme_tufte() + 
  theme(legend.key.size = unit(.1, 'cm'),
        legend.title = element_blank()))
   # user  system elapsed 
   # 0.016   0.001   0.017 

object.size(p)
# 175312 bytes

# render
system.time(print(p))
# user  system elapsed 
# 84.755   0.432  85.418  # Note over 80 seconds

ggplot2 png

# tmap; build plot, assign to object
tmap_mode('plot')
system.time(tm <- tm_shape(World, filter = 
                        (World$continent == 'Africa')) + 
               tm_polygons(group = 'Countries') +
               tm_shape(dsf) + 
               tm_dots(col = 'event_type', group = 'event_type'))
    # user  system elapsed 
    # 0.000   0.000   0.001 

object.size(tm)
# 14331968 bytes   # This is 80x ggplot2 plot's object size
                   # 14331968/175312 = 81.75121
# render
dev.cur()    # RStudioGD on macOS: quartz
system.time(print(tm))
# user  system elapsed 
# 1.438   0.038   1.484   # Note 1 second

tmap png


[Previous inquiry into geom_sf() & graphics devices, without the tmap comparison:]

TL;DR:

I am trying to speed up my plotting speed by switching graphics devices to X11, since my default Quartz graphics device is slow. After downloading XQuartz (to connect to the X11 graphics device) and calling grDevices::X11(), I don't understand the errors I'm getting.

X11(type = "cairo")
# Error in .External2(C_X11, d$display, d$width, d$height, d$pointsize,  : 
                    #   unable to start device X11
                    # In addition: Warning message:
                    #   In X11() : unable to open connection to X11 display 'cairo'
#> Warning in X11(type = "cairo"): unable to open connection to X11 display ''

And when I call R from a XQuartz.app terminal on macOS instead, the error message is slightly different:

X11(type = "cairo")
#> Error in .External2(C_X11, d$display, d$width, d$height, d$pointsize, : unable to start device X11cairo

End TL;DR

~~~~~~~

Broader Context:

Plotting large shapefiles with ggplot2::geom_sf(), the quartz graphics device used in macOS plots considerably slower than other devices, and while this larger performance issue is being resolved, I want to change my device from Quartz to X11.

I downloaded XQuartz, following advice from the RStudio forums, but my code doesn't successfully call X11, even when I launch R from XQuartz.

Proof, using the same data as the RStudio forum poster:

library(sf)
#> Linking to GEOS 3.6.1, GDAL 2.1.3, proj.4 4.9.3
library(ggplot2)
tmpzip <- tempfile(fileext = ".zip")
download.file("https://github.com/bcgov/bcmaps.rdata/blob/master/data-raw/ecoregions/ecoregions.zip?raw=true", destfile = tmpzip)
gdb_path <- unzip(tmpzip, exdir = tempdir())
ecoregions <- sf::read_sf(dirname(gdb_path[1]))

## Create ggplot2 object
ecoregions_gg <- ggplot() + geom_sf(data = ecoregions)

# Running quartz device - default macOS
system.time(print(ecoregions_gg))
#>    user  system elapsed 
#> 128.980   0.774 130.375

### ^ Note two full minutes!

Shapefile

This default device runs for an unusually long 129 seconds given the size. X11 should run faster according to the RStudio forum. A test on a (granted, faster) Windows 7 machine (32 GB RAM, 3.60 GHz) using its default graphics device (not Quartz), yielded:

#>    user  system elapsed 
#>    2.16    2.24    4.46

###  ^Only two seconds

While people are troubleshooting the general geom_sf / Quartz performance problems (Github Issue 1, Github Issue 2), how can I use my XQuartz install to run X11 and speed up my shapefile plotting?

5
  • I don't get the error you're getting with X11(type = "cairo"). Are you sure you have x11 /XQuartz installed?
    – SymbolixAU
    Jul 6, 2018 at 0:31
  • As far as I know yes. Perhaps there's some trouble linking it to R, but I do have XQuartz installed, and I've reinstalled as well. As I mention above I get this error from inside RStudio, but also when I launch a terminal within XQuartz.app, run R, and then call base::capabilities(), which recognizes X11.
    – dad
    Jul 6, 2018 at 15:49
  • Could you modify the example so it uses a data file that is publicly available? We don't have ggplot2vstmap/2017-08-18-2018-08-18-Eastern_Africa-Middle_Africa-Northern_Africa-Southern_Africa-Western_Africa.csv. Aug 18, 2018 at 21:55
  • Thanks, it was in my code block but I should have pulled it out to be clearer. I've fixed that and also added a screenshot of how the page looks when you pull the .csv, which should be 7.8 MB with those filters
    – dad
    Aug 18, 2018 at 22:27
  • Another way of plotting shape files is to use polygon from base and looping through the shape-sturcture manually. On a Mac it is still not blazingly fast, but acceptable (e.g. under a minute for all US counties in high resolution). Dec 22, 2020 at 16:32

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