[R-sig-Geo] Impoting multiple asci grids into R?

[Tomislav Hengl]

Carsten,

I highly recommend using the Robert Hijmans' raster package 
[http://CRAN.R-project.org/package=raster] to run such operation on a 
stack of grids (raster package is really a brilliant implementation of 
raster processing as your final code looks fairly short, and it does not 
uses so much RAM; for more info see 
[http://cran.r-project.org/web/packages/raster/vignettes/Raster.pdf]).

This is an example of how to run your stats on grid nodes in 4 lines:

 > library(raster); library(rgdal)
# list all files of interest:
 > asc_files <- list.files(pattern = glob2rx('EVAPTR_dem30m_*01.sum'))
# Read to R:
 > EtRR <- brick(lapply(asc_files, raster))
# derive a sum:
 > EtRR.sum <- aggregate(EtRR, fun=mean)
 > image(EtRR.sum)
# write back to ASCII format:
 > writeRaster(EtRR.sum, "EtRR_sum.asc")


Otherwise, SAGA GIS is also efficient in processing large grids:

 > library(RSAGA)
 > rsaga.get.usage("geostatistics_grid", 4)
library path:   C:/PROGRA~1/R/R-212~1.2/library/RSAGA/saga_vc/modules
library name:   geostatistics_grid
module name :   Statistics for Grids
Usage: 4 -GRIDS <str> [-MEAN <str>] [-MIN <str>] [-MAX <str>] [-VAR 
<str>] [-STDDEV <str>] [-STDDEVLO <str>] [-STDDEVHI <str>]
   -GRIDS:<str>          Grids
         Grid list (input)
   -MEAN:<str>           Arithmetic Mean
         Grid (optional output)
   -MIN:<str>            Minimum
         Grid (optional output)
   -MAX:<str>            Maximum
         Grid (optional output)
   -VAR:<str>            Variance
         Grid (optional output)
   -STDDEV:<str>         Standard Deviation
         Grid (optional output)
   -STDDEVLO:<str>       Mean less Standard Deviation
         Grid (optional output)
   -STDDEVHI:<str>       Mean plus Standard Deviation
         Grid (optional output)


see also: 
http://spatial-analyst.net/wiki/index.php?title=List_of_SAGA_modules

cheers,

T. Hengl
http://www.wewur.wur.nl/popups/vcard.aspx?id=HENGL001


On 28-10-2011 14:49, Carsten Neumann wrote:
>    Am 27.10.2011 17:12, schrieb Swen Meyer:
>> Dear All,
>> I like to import a series of asci grids into R. It is a time series of
>> 30 years and I like to calculate the mean monthly sum value for each
>> grid node for every month of the year. This is way I´m doing this at the
>> moment.
>>
>> #read asci files
>> ####Month01
>> EtRR.asci01<-  read.asciigrid("EVAPTR_dem30m_7101.sum", as.image=FALSE,
>> plot.image=TRUE)
>> EtRR.asci01 at data$EVAPTR7101<- EtRR.asci01 at data$EVAPTR_dem30m_7101.sum
>> #1
>> EVAPTR7201<- read.asciigrid("EVAPTR_dem30m_7201.sum", as.image=FALSE,
>> plot.image=TRUE)
>> EtRR.asci01 at data$EVAPTR7201<- EVAPTR7201 at data$EVAPTR_dem30m_7201.sum
>> #2
>> EVAPTR7301<- read.asciigrid("EVAPTR_dem30m_7301.sum", as.image=FALSE,
>> plot.image=TRUE)
>> EtRR.asci01 at data$EVAPTR7301<- EVAPTR7301 at data$EVAPTR_dem30m_7301.sum
>> #3
>> .
>> .
>> .
>> #29
>> EVAPTR0001<- read.asciigrid("EVAPTR_dem30m_0001.sum", as.image=FALSE,
>> plot.image=TRUE)
>> EtRR.asci01 at data$EVAPTR0001<- EVAPTR0001 at data$EVAPTR_dem30m_0001.sum
>> #30
>>
>> # claculating the mean sum ofer 30 years
>> EtRR.asci01 at data$sum<- ((EtRR.asci01[[1]] + EtRR.asci01[[2]] +......+
>> EtRR.asci01[[30]]) /30)
>>
>> My script is working well, but it is pretty time and workspace
>> consuming. I tried to use wildcards like this:
>>
>> txt_files = list.files(pattern = 'EVAPTR_dem30m_*01.sum')
>>
>> But the result is then:
>>
>> character(0)
>>
>> Does anyone maybe have an idea how to import multiple asci-grids in a
>> faster a more elegant way?
>>
>> Thank you in advance,
>>
>> Swen
>>
>>
>> 	[[alternative HTML version deleted]]
>>
>>
>>
>> _______________________________________________
>> R-sig-Geo mailing list
>> R-sig-Geo at r-project.org
>> https://stat.ethz.ch/mailman/listinfo/r-sig-geo
> Dear Sven,
>
> First: wildcards with * do not work. Just use pattern = 'EVAPTR_dem30m'
> to get all files in a folder within a list.
> Second: use raster package and then function stack() to read all ascii
> grids without accessing memory.
>
> So you can simply do a layer stack with your list within two r command
> lines and without memory handling problems ;-)
>
> With Best regards
>
> Carsten
>
>
>
>
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