throw away old code, prepare tests

[epclust.git] / old_C_code / stage2_UNFINISHED / src / unused / 01_extract-features2_2009.r

diff --git a/old_C_code/stage2_UNFINISHED/src/unused/01_extract-features2_2009.r b/old_C_code/stage2_UNFINISHED/src/unused/01_extract-features2_2009.r
deleted file mode 100644 (file)
index 85a2b5b..0000000
--- a/old_C_code/stage2_UNFINISHED/src/unused/01_extract-features2_2009.r
+++ /dev/null
@@ -1,67 +0,0 @@
-## File : 01_extract-features_2009.r
-## Description : Using the full data matrix, we extract handy features to
-##               cluster.
-
-rm(list = ls())
-
-#source('http://eric.univ-lyon2.fr/~jcugliari/codes/functional-clustering.r')
-setwd("~/Documents/projects/2014_EDF-Orsay-Lyon2/codes/")
-source('aux2.r')
-
-## 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)  
-
-# table( substr(dates, 11, 15) ) # Sunlight time saving produces an 
-                                 # unbalanced number of time points
-                                 # per time stepa across the year
-
-
-## 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)
-
-  nas <- which(is.na(datamat)[, 1]) # some 1/1/2009 are missing
-  if(length(nas)>0) datamat[nas, 1] <- rowMeans(datamat[nas, 2:4])
-  
-  imput   <- datamat[, 4180:4181] %*% matrix(c(2/3, 1/3, 1/3, 2/3), 2)
-  datamat <- cbind(datamat[, 1:4180], imput, datamat[, 4181:17518])
-  
-  dayimp   <- t(apply(datamat, 1, dayimpact))
-  nightimp <- t(apply(datamat, 1, nightimpact))
-  lunchimp <- t(apply(datamat, 1, lunchimpact))
-  
-  auxfeat  <- cbind(dayimp, nightimp, lunchimp)
-  
-  if(b == 1) {
-    matfeat <- auxfeat 
-  } else {
-    matfeat <- rbind(matfeat, auxfeat)
-  }
-  
-}
-
-close(con)                      # close connection to the file
-
-write.table(matfeat, file = "~/tmp/2009_impacts.txt")
-