[R-sig-Geo] Merging regions in a map & plotting values

[Joshua Onyango]

Hi Bob,
Still getting the memory error to do with memory after merging the data to plot points as per your suggestions.
What could I be doing wrong is is there a way out to fix this?
Thanks
dat_merge =merge(regions,orf_data,by="Region",duplicateGeoms=TRUE)
eng_map <- fortify(regions, region="Region")
names(eng_map)[names(eng_map)=="id"]<-"Region" 
big_eng = merge(dat_merge, eng_map,by = "Region",duplicateGeoms=TRUE)

Error: cannot allocatevector of size 903.8 Mb
 

    On Wednesday, 20 January 2016, 19:14, boB Rudis <bob at rudis.net> wrote:
 

 That's actually why I did the second `geom_map` the way I did. Add
another column to that data frame and use it for the fill color
(preferably using `cut` to bin values  ahead of time as it's unlikey
you really want to use a continuous color palette.

On Wed, Jan 20, 2016 at 1:55 PM, Joshua Onyango <jaonyango at yahoo.com> wrote:
> Hi Bob
>
> Thanks for the help, merging region appear to work now.  However still stuck
> on the other bit on merging data with spatial object, ("regions") in this
> case to be able to plot the data points. I mainly want to plot information
> such as % disease prevalence in every region, temperature, flock size etc
>
> Thanks advance
>
> Josh
>
>
> On Wednesday, 20 January 2016, 1:49, boB Rudis <bob at rudis.net> wrote:
>
>
> I think this might help you out a bit (it's probably worth taking the
> time to look it over as it removes much of the redundant code you
> had).
>
> library(sp)
> library(maptools)
> library(rgeos)
> library(rgdal)
> library(dplyr)
> library(ggplot2)
> library(ggthemes)
> library(ggalt)
>
> URL <-
> "http://census.edina.ac.uk/ukborders/easy_download/prebuilt/shape/England_gor_2011.zip"
> fil <- basename(URL)
> if (!file.exists(fil)) download.file(URL, fil)
>
> fils <- unzip(fil)
> shp <- grep("shp$", fils, value=TRUE)
>
> region <- readOGR(shp, ogrListLayers(shp)[1], stringsAsFactors=FALSE)
>
> # define new regions
> region at data$Region <- c("East", "South &S.E", "North", "North", "Midlands",
>                        "North", "SouthWest", "Midlands", "South & S.E")
> colnames(region at data) <- c("code", "name","Region")
>
> # dissolve polygons and simplify the shapes
> regions <- unionSpatialPolygons(region, region at data$Region)
> regions <- gSimplify(regions, 100, topologyPreserve=TRUE)
> regions <- gBuffer(regions, byid=TRUE, width=0)
>
> # coord_map and coord_proj will eventually work but this transformation
> # will absolutely speed up the calculations
>
> regions <- SpatialPolygonsDataFrame(spTransform(regions,
>                                                CRS("+proj=longlat
> +ellps=sphere +no_defs")),
>                                    data.frame(Region=names(regions),
>                                              row.names=names(regions),
>                                              stringsAsFactors=FALSE))
>
> eng_map <- fortify(regions, region="Region")
>
> # new projection (good for the UK)
> eng_proj <- "+proj=aea +lat_0=54.55635146083455 +lon_0=-3.076171875"
>
> ggplot() +
>  # base map
>  geom_map(data=eng_map, map=eng_map,
>          aes(x=long, y=lat, map_id=id),
>          color=NA, fill=NA, size=0.5) +
>  # sample fill of the regions
>  geom_map(data=data.frame(id=unique(eng_map$id)), map=eng_map,
>          aes(map_id=id, fill=id),
>          color="white", size=0.15) +
>  scale_fill_brewer(palette="Set2") +
>  coord_proj(eng_proj) +
>  theme_map()
>
> NOTE: this requires the new ggplot2 (2.0)
>
> On Tue, Jan 19, 2016 at 3:04 PM, Joshua Onyango via R-sig-Geo
> <r-sig-geo at r-project.org> wrote:
>> HelloI'm new into creating maps in R so any help would be great.I have
>> read a few articles on the internet - mainly blogs on mapping in R which I
>> have tried to follow with no much success. Basically I want to merge merge
>> some English regions from 8 to 5 then show information that relates to
>> disease prevalence, temperature etc
>> Here is what I have tried but sound like this cant run due to computer
>> memory or must be doing following a wrong approach.
>>
>>
>>> #Getting theshapefile into working directory
>>
>>>
>>> download.file("http://census.edina.ac.uk/ukborders/easy_download/prebuilt/shape/England_gor_2011.zip",
>>
>>                destfile ="lad-region-lookup.zip")> #inzipping theshapefile
>> folder
>>
>>>unzip("lad-region-lookup.zip", exdir = ".")
>>
>>> #reading theshapefile in r
>>
>>> region <-readOGR(".", "England_gor_2011")
>>
>> OGR data source withdriver: ESRI Shapefile
>>
>> Source:".", layer: "England_gor_2011"
>>
>> with 9 features
>>
>> It has 2 fields
>>
>>> # Check theshapefile has loaded correctly
>>
>>> plot(region)
>>
>>>
>>
>>> lu <-data.frame()
>>
>>> lu <-rbind(lu, region at data)
>>
>>> lu$CODE <-as.character(lu$CODE)
>>
>>> lu$NAME <-as.character(lu$NAME)
>>
>>> lu$Region <-NA
>>
>>> name=c("East", "South
>>> &S.E","North","North","Midlands","North","SouthWest","Midlands","South &
>>> S.E")
>>
>>> lu$Region <-name
>>
>>> # Merge lu(LookUp) into polygons,
>>
>>> region at data$CODE<- as.character(region at data$CODE)
>>
>>> region at data<- full_join(region at data, lu, by = "CODE")
>>
>>> # Tidy mergeddata
>>
>>> region at data<- select(region at data, -NAME.x)
>>
>>>colnames(region at data) <- c("code", "name","Region")
>>
>>>
>>
>>> # Ensureshapefile row.names and polygon IDs are sensible
>>
>>>row.names(region) <- row.names(region at data)
>>
>>> region <-spChFIDs(region, row.names(region))
>>
>>>
>>
>>> # Now thedissolve
>>
>>> region <-gUnaryUnion(region, id = region at data$Region)
>>
>>>
>>
>>> # If you want torecreate an object with a data frame
>>
>>> # make sure row namesmatch
>>
>>>row.names(region) <- as.character(1:length(region))
>>
>>>
>>
>>> # Extract thedata you want (the larger geography)
>>
>>> lu <-unique(lu$Region)
>>
>>> lu <-as.data.frame(lu)
>>
>>> colnames(lu)<- "Region"  # your datawill probably have more than 1 row!
>>
>>>
>>
>>> # And add thedata back in
>>
>>> region <-SpatialPolygonsDataFrame(region, lu)
>>
>>> region2 <-merge(region at data, data, by="Region")
>>
>>> dat2=fortify(region,region="Region")
>>
>>>names(dat2)[names(dat2)=="id"]<-"Region"
>>
>>> dat <-merge(dat2, region2, by="Region")
>>
>> Error: cannotallocate vector of size 904.9 Mb
>>
>> In addition:Warning messages:
>>
>> 1: In`[.data.frame`(x, c(m$xi, if (all.x) m$x.alone),
>> c(by.x,seq_len(ncx)[-by.x]),  :
>>
>>  Reached total allocation of 4016Mb: seehelp(memory.size)
>>
>>
>>
>>
>> Any simpler approach will be highly appreciated.
>> Thanks
>> Josh
>>        [[alternative HTML version deleted]]
>>
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>> R-sig-Geo at r-project.org
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>
>


  
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