old_C_code/wrapper.R

   1 #Exemple :
   2 #
   3 #dans old_C_code/build :
   4 #cmake ../stage1/src
   5 #make
   6 #
   7 #dans data/, lancer R puis :
   8 #source("../old_C_code/wrapper.R")
   9 #serialize("../old_C_code/build", "2009.csv","2009.bin",1)
  10 #library(parallel)
  11 #np = detectCores()
  12 #nbSeriesPerChunk = 3000
  13 #nbClusters = 20
  14 #ppam_exe("../old_C_code/build",np,"2009.bin",nbSeriesPerChunk,nbClusters)
  15 #C = getMedoids("../old_C_code/build", "ppamResult.xml", "ppamFinalSeries.bin")
  16 #first100series = deserialize("../old_C_code/build", "2009.bin", "2009.csv.part", "1-100")
  17 #distor = getDistor("../old_C_code/build", "ppamResult.xml", "2009.bin")
  18
  19 ppam_exe = function(path=".", np=parallel::detectCores(), data=NULL,
  20     nbSeriesPerChunk, nbClusters, randomize=1, p_dissims=2)
  21 {
  22     args = paste(nbSeriesPerChunk," ",nbClusters," ",randomize," ",p_dissims,sep="")
  23
  24     command_line = paste("mpirun -np ",np," ",path,"/ppam.exe cluster",sep="")
  25
  26     #if data provided (as data.frame or matrix...): binarize it, and add it as first argument
  27     if (!is.null(data))
  28     {
  29         if (!is.character(data))
  30         {
  31             #assuming matrix or data.frame, WITH row names
  32             #( identifiers; could be line number... e.g. data <- cbind(1:nrow(data),data) )
  33             write.table(data, "/tmp/data_csv", sep=",", row.names=FALSE, col.names=FALSE)
  34             system(paste(path,"/ppam.exe serialize /tmp/data_csv /tmp/data_bin 0 0",sep=""))
  35         } else
  36         {
  37             system(paste(path,"/ppam.exe serialize ",data," /tmp/data_bin 0 0",sep=""))
  38         }
  39         command_line = paste(command_line," /tmp/data_bin",sep="")
  40     }
  41
  42     command_line = paste(command_line," ",args,sep="")
  43     system(command_line)
  44 }
  45
  46 #NOTE: identifiers in first column
  47 getMedoids = function(path=".", xmlResult = "ppamResult.xml",
  48     finalSeries = "ppamFinalSeries.bin")
  49 {
  50     system(paste(path,"/ppam.exe deserialize ",finalSeries," ppamFinalSeries.csv -1",sep=""))
  51     curves = read.table("ppamFinalSeries.csv", sep=",")
  52     library(XML)
  53     ranks = as.integer( xmlToList( xmlParse(xmlResult) )$ranks )
  54     return ( curves[ranks,] ) # == medoids
  55 }
  56
  57 getDistor = function(path=".", xmlResult = "ppamResult.xml",
  58     finalSeries = "ppamFinalSeries.bin")
  59 {
  60     system(paste(path,"/ppam.exe classif ",finalSeries," ",xmlResult,sep=""))
  61 }
  62
  63 serialize = function(path=".", csvSeries, binSeries, byCols=0, nbSeries=0)
  64 {
  65     system(paste(path,"/ppam.exe serialize ",csvSeries," ",binSeries," ",byCols," ",nbSeries,
  66         sep=""))
  67 }
  68
  69 deserialize = function(path=".", binSeries, csvSeries, ranks="-1", return=TRUE)
  70 {
  71     system(paste(path,"/ppam.exe deserialize ",binSeries," ",csvSeries," ",ranks,sep=""))
  72     if (return)
  73         return ( read.table(csvSeries, sep=",") )
  74 }