throw away old code, prepare tests

[epclust.git] / old_C_code / stage2_UNFINISHED / src / unused / 03_compute-sums-of-classesRANDOM_2009.r

diff --git a/old_C_code/stage2_UNFINISHED/src/unused/03_compute-sums-of-classesRANDOM_2009.r b/old_C_code/stage2_UNFINISHED/src/unused/03_compute-sums-of-classesRANDOM_2009.r
deleted file mode 100644 (file)
index 016b6de..0000000
--- a/old_C_code/stage2_UNFINISHED/src/unused/03_compute-sums-of-classesRANDOM_2009.r
+++ /dev/null
@@ -1,82 +0,0 @@
-## File : 03_compute-sum-of-classes_2009.r
-## Description : Calculer les synchrones pour chaque groupe obtenu par le
-##               clustering. 
-
-rm(list = ls())
-
-setwd("~/Documents/projects/2014_EDF-Orsay-Lyon2/codes/")
-
-## 1. Read auxiliar data files ####
-
-identifiants <- read.table("identifs.txt")[ ,1]
-dates0       <- read.table("datesall.txt")[, 1]
-dates        <- dates0[grep("2009", dates0)]
-rm(dates0)
-
-n <- length(identifiants)-
-p <- length(dates)
-
-blocks <- c(rep(6500, 3), 5511)  
-
-# Fit of the clustering : clfit 
-#load('~/Documents/projects/2014_EDF-Orsay-Lyon2/res/clfit500.Rdata')
-load('~/Documents/projects/2014_EDF-Orsay-Lyon2/res/clfit200.Rdata')
-#load('~/Documents/projects/2014_EDF-Orsay-Lyon2/res/clfit200RC.Rdata')
-#  table(clfit$clustering)
-
-dfclust <- data.frame(cluster = clfit$clustering) # real clustering 
-K       <- nrow(clfit$clusinfo)
-
-#dfclust2 <- dfclust
-dfclust$cluster <- sample(unlist(Map(rep, 1:200, table(dfclust)))) # random clust
-
-
-
-#dfclust <- head(dfclust, 50)           # just for testing purpouses
-synchros <- matrix(0, ncol = p, nrow = K)
-rm(clfit)
-                   
-## 2. Process the large file ####
-
-close(con)
-con <- file("~/tmp/2009_full.txt")  # Establish a connection to the file
-open(con, "r")                      # Open the connection
-
-for(b in seq_along(blocks)){        # Reading loop
-  nb <- blocks[b]
-  actual <- readLines(con = con, n = nb )
-  auxmat <- matrix(unlist(strsplit(actual, " ")), ncol = p + 1, byrow = TRUE)
-  rm(actual)
-
-  datamat <- t(apply(auxmat[, -1], 1, as.numeric))
-  rownames(datamat) <- substr(auxmat[, 1], 2, 7)
-  rm(auxmat)
-
-  # obtain for each line of datamat the cluster membership (if any)
-  clustfactor <- dfclust$cluster[match(rownames(datamat), rownames(dfclust))] 
-  
-#  if(length(which(rownames(datamat) == "218095"))>0) print(b);
-  
-  for(k in 1:K){ 
-    clustk <- which(clustfactor == k)
-    if(length(clustk) > 0) {
-    
-    if(length(clustk) > 1) {
-      synchrosk <- colSums(datamat[which(clustfactor == k), ])
-    } else {
-      synchrosk <- datamat[which(clustfactor == k), ]
-    }
-    synchros[k, ] <- synchros[k, ] + synchrosk
-    rm(synchrosk)
-    }
-  }
-}
-
-close(con)                # close connection to the file
-
-synchros <- data.frame(t(synchros), total = colSums(synchros))
-
-write.table(synchros, file = "~/tmp/2009_synchros200RANDOM.txt")
-write.table(dfclust,  file = "../res/dfclust200RANDOM.txt")
-#write.table(synchros, file = "~/tmp/2009_synchros200RC.txt")
-