out
}
-
-##from textometrieR
-##http://txm.sourceforge.net/doc/R/textometrieR-package.html
-##Sylvain Loiseau
-#specificites.probabilities <- function (lexicaltable, types = NULL, parts = NULL)
-#{
-# rowMargin <- rowSums(lexicaltable)
-# colMargin <- colSums(lexicaltable)
-# F <- sum(lexicaltable)
-# if (!is.null(types)) {
-# if (is.character(types)) {
-# if (is.null(rownames(lexicaltable)))
-# stop("The lexical table has no row names and the \"types\" argument is a character vector.")
-# if (!all(types %in% rownames(lexicaltable)))
-# stop(paste("Some requested types are not known in the lexical table: ",
-# paste(types[!(types %in% rownames(lexicaltable))],
-# collapse = " ")))
-# }
-# else {
-# if (any(types < 1))
-# stop("The row index must be greater than 0.")
-# if (max(types) > nrow(lexicaltable))
-# stop("Row index must be smaller than the number of rows.")
-# }
-# lexicaltable <- lexicaltable[types, , drop = FALSE]
-# rowMargin <- rowMargin[types]
-# }
-# if (!is.null(parts)) {
-# if (is.character(parts)) {
-# if (is.null(colnames(lexicaltable)))
-# stop("The lexical table has no col names and the \"parts\" argument is a character vector.")
-# if (!all(parts %in% colnames(lexicaltable)))
-# stop(paste("Some requested parts are not known in the lexical table: ",
-# paste(parts[!(parts %in% colnames(lexicaltable))],
-# collapse = " ")))
-# }
-# else {
-# if (max(parts) > ncol(lexicaltable))
-# stop("Column index must be smaller than the number of cols.")
-# if (any(parts < 1))
-# stop("The col index must be greater than 0.")
-# }
-# lexicaltable <- lexicaltable[, parts, drop = FALSE]
-# colMargin <- colMargin[parts]
-# }
-# if (nrow(lexicaltable) == 0 | ncol(lexicaltable) == 0) {
-# stop("The lexical table must contains at least one row and one column.")
-# }
-# specif <- matrix(0, nrow = nrow(lexicaltable), ncol = ncol(lexicaltable))
-# for (i in 1:ncol(lexicaltable)) {
-# whiteDrawn <- lexicaltable[, i]
-# white <- rowMargin
-# black <- F - white
-# drawn <- colMargin[i]
-# independance <- (white * drawn)/F
-# specif_negative <- whiteDrawn < independance
-# specif_positive <- whiteDrawn >= independance
-# specif[specif_negative, i] <- phyper(whiteDrawn[specif_negative],
-# white[specif_negative], black[specif_negative], drawn)
-# specif[specif_positive, i] <- phyper(whiteDrawn[specif_positive] -
-# 1, white[specif_positive], black[specif_positive],
-# drawn)
-# }
-# dimnames(specif) <- dimnames(lexicaltable)
-# return(specif)
-#}
-#
-##from textometrieR
-##http://txm.sourceforge.net/doc/R/textometrieR-package.html
-##Sylvain Loiseau
-#specificites <- function (lexicaltable, types = NULL, parts = NULL)
-#{
-# spe <- specificites.probabilities(lexicaltable, types, parts)
-# spelog <- matrix(0, nrow = nrow(spe), ncol = ncol(spe))
-# spelog[spe < 0.5] <- log10(spe[spe < 0.5])
-# spelog[spe > 0.5] <- abs(log10(1 - spe[spe > 0.5]))
-# spelog[spe == 0.5] <- 0
-# spelog[is.infinite(spe)] <- 0
-# spelog <- round(spelog, digits = 4)
-# rownames(spelog) <- rownames(spe)
-# colnames(spelog) <- colnames(spe)
-# return(spelog)
-#}
-
make.spec.hypergeo <- function(mat) {
- library(textometrieR)
- spec <- specificites(mat)
+ library(textometry)
+ spec <- specificities(mat)
sumcol<-colSums(mat)
eff_relatif<-round(t(apply(mat,1,function(x) {(x/t(as.matrix(sumcol))*1000)})),2)
+ colnames(eff_relatif) <- colnames(mat)
out <-list()
out[[1]]<-spec
out[[3]]<-eff_relatif
mat
}
+build.prof.tgen <- function(x) {
+ nbst <- sum(x[nrow(x),])
+ totcl <- x[nrow(x),]
+ tottgen <- rowSums(x)
+ nbtgen <- nrow(x) - 1
+ chi2 <- x[1:(nrow(x)-1),]
+ pchi2 <- chi2
+ for (classe in 1:ncol(x)) {
+ for (tg in 1:nbtgen) {
+ cont <- c(x[tg, classe], tottgen[tg] - x[tg, classe], totcl[classe] - x[tg, classe], (nbst - totcl[classe]) - (tottgen[tg] - x[tg, classe]))
+ cont <- matrix(unlist(cont), nrow=2)
+ chiresult<-chisq.test(cont,correct=FALSE)
+ if (is.na(chiresult$p.value)) {
+ chiresult$p.value<-1
+ chiresult$statistic<-0
+ }
+ if (chiresult$expected[1,1] > cont[1,1]) {
+ chiresult$statistic <- chiresult$statistic * -1
+ }
+ chi2[tg,classe] <- chiresult$statistic
+ pchi2[tg,classe] <- chiresult$p.value
+ }
+ }
+ res <- list(chi2 = chi2, pchi2 = pchi2)
+}
+
BuildProf<- function(x,dataclasse,clusternb,lim=2) {
####
#r.names<-rownames(x)