| 1 | ## File : 01_extract-features_2010.r |
| 2 | ## Description : Using the full data matrix, we extract handy features to |
| 3 | ## cluster. |
| 4 | |
| 5 | rm(list = ls()) |
| 6 | |
| 7 | source('http://eric.univ-lyon2.fr/~jcugliari/codes/functional-clustering.r') |
| 8 | setwd("~/ownCloud/projects/2014_EDF-Orsay-Lyon2/codes/") |
| 9 | |
| 10 | ## 1. Read auxiliar data files #### |
| 11 | |
| 12 | identifiants <- read.table("identifs.txt")[ ,1] |
| 13 | dates0 <- read.table("datesall.txt")[, 1] |
| 14 | dates <- dates0[grep("2010", dates0)] |
| 15 | rm(dates0) |
| 16 | |
| 17 | n <- length(identifiants) |
| 18 | p <- length(dates) |
| 19 | |
| 20 | blocks <- c(rep(6500, 3), 5511) |
| 21 | |
| 22 | |
| 23 | ## 2. Process the large file #### |
| 24 | |
| 25 | close(con) |
| 26 | con <- file("~/tmp/2010_full.txt") # Establish a connection to the file |
| 27 | open(con, "r") # Open the connection |
| 28 | |
| 29 | for(b in seq_along(blocks)){ # Reading loop |
| 30 | nb <- blocks[b] |
| 31 | actual <- readLines(con = con, n = nb ) |
| 32 | auxmat <- matrix(unlist(strsplit(actual, " ")), ncol = p + 1, byrow = TRUE) |
| 33 | rm(actual) |
| 34 | |
| 35 | datamat <- t(apply(auxmat[, -1], 1, as.numeric)) |
| 36 | rownames(datamat) <- substr(auxmat[, 1], 2, 7) |
| 37 | rm(auxmat) |
| 38 | |
| 39 | auxDWT <- t(apply(datamat, 1, toDWT)) |
| 40 | auxcontrib <- t(apply(auxDWT, 1, contrib)) |
| 41 | rm(auxDWT) |
| 42 | |
| 43 | if(b == 1) { |
| 44 | matcontrib <- auxcontrib |
| 45 | } else { |
| 46 | matcontrib <- rbind(matcontrib, auxcontrib) |
| 47 | } |
| 48 | |
| 49 | } |
| 50 | |
| 51 | close(con) # close connection to the file |
| 52 | |
| 53 | write.table(matcontrib, file = "~/tmp/2010_contrib.txt") |
| 54 | |