| 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 | } |