[R-sig-Geo] Dramatically slow plotting

[Rolando Valdez]

Hi Ben,

I tried with X11(type=“Xlib”) and I had no changes in time. Then I tried with X11(type=“cairo”) and it reduced considerably the time, however, I got a low quality map.

I think, the Quartz gives a high quality plots, that’s why it takes a lot of time. 

Regards, 

Rolando Valdez

El 18/03/2014, a las 09:26, Ben <galuardi at MIT.EDU> escribió:

> Hi Rolando,
> 
> I don't use Macs but I do use Linux and have similar issues. I found it that the plotting device type called by default is inordinately slow at plotting spatial objects. Try opening a different type of device and run the example
> 
> X11(type='Xlib')
> X11(type='cairo')
> 
> also, try
> 
> quartz()
> 
> which is mac specific (and possibly called by default)
> 
> help on X11 here:
> https://stat.ethz.ch/R-manual/R-devel/library/grDevices/html/x11.html
> 
> Cheers,
> Ben
> 
> 
> ------ Original Message ------
> From: "Rolando Valdez" <rvaldezr at gmail.com>
> To: r-sig-geo at r-project.org
> Sent: 3/17/2014 6:23:51 PM
> Subject: [R-sig-Geo] Dramatically slow plotting
> 
>> Hello,
>> 
>> Recently, I acquired a MacBook Pro, Core i7, 8 GB ram. I Installed the newest R version, 3.0.3 from the web page. The problem is when I’m plotting maps, because is going very, very slow, about 3 or 4 minutes just for a single map, while I’ve done this in a few seconds in Windows with Core i5 and 4 GB ram.
>> 
>> This is what I have:
>> 
>> R version 3.0.3 (2014-03-06) -- "Warm Puppy"
>> Copyright (C) 2014 The R Foundation for Statistical Computing
>> Platform: x86_64-apple-darwin10.8.0 (64-bit)
>> 
>> [R.app GUI 1.63 (6660) x86_64-apple-darwin10.8.0]
>> 
>> I found a reproducible example in web and I took time with proc.time()
>> 
>> ptm <- proc.time()
>> library(sp)
>> library(lattice) # required for trellis.par.set():
>> trellis.par.set(sp.theme()) # sets color ramp to bpy.colors()
>> 
>> # prepare nc sids data set:
>> library(maptools)
>> nc <- readShapePoly(system.file("shapes/sids.shp", package="maptools")[1], proj4string=CRS("+proj=longlat +datum=NAD27"))
>> arrow = list("SpatialPolygonsRescale", layout.north.arrow(),
>>    offset = c(-76,34), scale = 0.5, which = 2)
>> #scale = list("SpatialPolygonsRescale", layout.scale.bar(),
>> # offset = c(-77.5,34), scale = 1, fill=c("transparent","black"), which = 2)
>> #text1 = list("sp.text", c(-77.5,34.15), "0", which = 2)
>> #text2 = list("sp.text", c(-76.5,34.15), "1 degree", which = 2)
>> ## multi-panel plot with filled polygons: North Carolina SIDS
>> spplot(nc, c("SID74", "SID79"), names.attr = c("1974","1979"),
>>    colorkey=list(space="bottom"), scales = list(draw = TRUE),
>>    main = "SIDS (sudden infant death syndrome) in North Carolina",
>>    sp.layout = list(arrow), as.table = TRUE)
>> 
>> # sp.layout = list(arrow, scale, text1, text2), as.table = TRUE)
>> proc.time() - ptm
>> 
>> user system elapsed
>>  2.408 0.064 2.616
>> 
>> It was quick.
>> 
>> Then I did a single plot with my shape:
>> 
>> mapa <- readShapePoly(“Entidades_2013.shp”)
>> ptm <- proc.time()
>> spplot(mapa[1]); proc.time() - ptm
>> 
>> user system elapsed
>> 87.575 0.786 88.068
>> 
>> Why it take a lot of time? I worked with same shapes in Windows and never took that time.
>> 
>> Hope you can help me,
>> 
>> Regards,
>> 
>> Rolando Valdez
>> 
>> _______________________________________________
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> 

Rolando Valdez