[R] iterative read - write

[Thierry Onkelinx]

Dear Bruce,

I'd write a function that take filenames as arguments. It should read
the file, do the calculations and write that output to another file
which can be calculated from the input. You can get all input files in
a directory with e.g. list.files(). Then you can simply loop over the
inputs. Here is some pseudo code.

my_summary <- function(input) {
   raw <- read.table(input)
   summarised <- summary(raw)
   output <- calculate_output(input)
   write.csv(summarised, output)
}
inputs <- list.files("raw/data/path")
sapply(inputs, my_summary)

Best regards,

ir. Thierry Onkelinx
Statisticus / Statistician

Vlaamse Overheid / Government of Flanders
INSTITUUT VOOR NATUUR- EN BOSONDERZOEK / RESEARCH INSTITUTE FOR NATURE
AND FOREST
Team Biometrie & Kwaliteitszorg / Team Biometrics & Quality Assurance
thierry.onkelinx using inbo.be
Havenlaan 88 bus 73, 1000 Brussel
www.inbo.be

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2018-04-17 13:20 GMT+02:00 Neotropical bat risk assessments
<neotropical.bats using gmail.com>:
> Hi all,
>
> I would like to set up an iterative read & write sequence to avoid
> reading and writing each file one at a time.
> Hundreds of data sets to re-calculate.  The code I have works well
> individually, but would like to set up an iterative read, calculate and
> write changing the input and output file names each iteration.
>
> I  think I have read that there is an R  feature using "Pipes" and %
> that may help but have not figured out how to do this.
> What I am seeking is a way to read a list of TXT files, calculate the
> values and write the results in an iterative manner to avoid manually
> reading each file individually
>
> Suggestions?
>
> Tnx,
> Bruce*
> *
>
> *# This works*
>
> *#read in a data file
> *
>
> *>Corbre_2 <- read.table("E:/Acoustic Parameters/~Emballonuridae/Data by
> genus/~Corbre/Corbre_2.txt",header=T,sep="\t",quote="")*
>
> *# create and calculate a new variable for time between call pusles
> *
>
> *Corbre_2 [c("TBC")] <- recode.variables(Corbre_2[c("TBC")] , "0 -> NA;")*
>
> *# Create new BW variable for band width then change data file name*
>
> *BW<-within(Corbre_2,BW<-Fmax-Fmin)*
>
> *# Create 2 new variables for fundamental H1 and third harmonic H3
> frequencies
> *
>
> *#based on Fc that is generally loudest at the 2^nd harmonic.*
>
> *BW<-within(BW,FcH1<-Fc*.5)*
>
> *BW<-within(BW,FcH3<-FcH1*3)*
>
> *#rename to a DF to calculate the stats
> *
>
> *BatStats<-BW*
>
> *BatStats<-Deducer::descriptive.table (vars = d
> (Dur,TBC,Fmin,Fmax,BW,Fmean,Fk,FcH1,Fc,FcH3,Sc,Pmc),data=
> BatStats,func.names =c("Valid N","Minimum","Maximum","Mean","St.
> Deviation"),func.additional= list(p10=function(x) quantile(x, c(0.10),
> na.rm=TRUE),p25=function(x) quantile(x, c(0.25),
> na.rm=TRUE),p75=function(x) quantile(x,
> c(0.75),na.rm=TRUE),p90=function(x) quantile(x, c(0.90),na.rm=TRUE)))*
>
> *## Write the results and change output name and directory for the
> calculated stats.*
>
> *write.csv(BatStats,file="C:\\=Bat data working\\Acoustic
> Parameters\\Corbre_Stats.csv")*
>
>
>
> --
> Bruce W. Miller, PhD.
> Neotropical bat risk assessments
> Conservation Fellow - Wildlife Conservation Society
>
> If we lose the bats, we may lose much of the tropical vegetation and the lungs of the planet
>
> Using acoustic sampling to identify and map species distributions for >25 years.
>
> Providing free Interactive identification keys and call fact sheets for the vocal signatures of New World Bats
>
>
>         [[alternative HTML version deleted]]
>
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