--- /dev/null
+#* Textometrie
+#* ANR project ANR-06-CORP-029
+#* http://textometrie.ens-lsh.fr/
+#*
+#* 2008 (C) Textometrie project
+#* BSD New and Simplified BSD licenses
+#* http://www.opensource.org/licenses/bsd-license.php
+
+## Sylvain Loiseau <sloiseau@u-paris10.fr>
+
+`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);
+ #class(spelog) <- "specificites";
+ #attr(spelog, "l.t") <- spe;
+ return(spelog);
+}
+
+`specificites.probabilities` <-
+function(lexicaltable, types=NULL, parts=NULL) {
+
+ # if (!is.numeric(lexicaltable)) stop("The lexical table must contain numeric values.");
+
+ rowMargin <- rowSums(lexicaltable); # or "F" (the total frequency of all the types).
+ colMargin <- colSums(lexicaltable); # or "T" (the size of the parts).
+ F <- sum(lexicaltable); # The grand total (number of tokens in the corpus).
+
+ if (! is.null(types)) { # Filter on tokens to be considered.
+ if(is.character(types)) { # convert the name of types given with "types" into row index numbers.
+ 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)) { # Filter on parts to be considered.
+ if(is.character(parts)) { # convert the name of parts given with "parts" into col index numbers.
+ 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(0.0, nrow=nrow(lexicaltable), ncol=ncol(lexicaltable));
+
+ for(i in 1:ncol(lexicaltable)) { # We proceed the whole lexical table by column (i.e. by part).
+
+ whiteDrawn <- lexicaltable[,i]; # The frequencies observed in this part for each type.
+ white <- rowMargin; # The total frequencies in the corpus for each type.
+ black <- F-white; # The total complement frequency in the corpus for each type.
+ drawn <- colMargin[i]; # The number of tokens in the part.
+
+ independance <- (white * drawn) / F; # The theoretic frequency of each type.
+ specif_negative <- whiteDrawn < independance; # index of observed frequencies below the theoretic frequencies.
+ specif_positive <- whiteDrawn >= independance; # index of observed frequencies above the theoretic frequencies.
+
+ 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);
+}
+
+`specificites.lexicon` <-
+function(lexicon, sublexicon) {
+ spe <- specificites.lexicon.probabilities(lexicon, sublexicon);
+ 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);
+ #class(spelog) <- "specificites";
+ #attr(spelog, "l.t") <- spe;
+ return(spelog);
+}
+
+`specificites.lexicon.new` <-
+function(lexicon, sublexicon) {
+
+ if (! all(names(sublexicon) %in% names(lexicon))) stop(
+ paste(
+ sum(! (names(sublexicon) %in% names(lexicon))),
+ "types of the sublexicon not found in the lexicon: ",
+ )
+ );
+
+sub <- numeric(length(lexicon));
+names(sub) <- names(lexicon);
+sub[names(sublexicon)] <- sublexicon;
+
+ complementary.lexicon <- c(lexicon- sub);
+ if (any(complementary.lexicon < 0)) stop("type cannot be more frequent in the sublexicon than in the lexicon");
+
+ lexicaltable <- matrix(c(sub, complementary.lexicon), ncol=2);
+ rownames(lexicaltable) <- names(lexicon);
+ colnames(lexicaltable) <- c("sublexicon", "complementary");
+ #stop(colnames(lexicaltable));
+ return(specificites(lexicaltable,NULL,NULL));
+}
+
+`specificites.lexicon.probabilities` <-
+function(lexicon, sublexicon) {
+
+ if (!is.numeric(lexicon)) stop("The lexicon must contain numeric values.");
+ if (!is.numeric(sublexicon)) stop("The sublexicon must contain numeric values.");
+ if (is.null(names(lexicon))) stop("The lexicon must contain names.");
+ if (is.null(names(sublexicon))) stop("The sub lexicon must contain names.");
+
+ if (! all(names(sublexicon) %in% names(lexicon)))
+ stop(
+ paste(
+ "Some requested types of the sublexicon are not known in the lexicon: ",
+ paste(names(sublexicon)[! (names(sublexicon) %in% names(lexicon))], collapse=" ")
+ )
+ );
+
+ F <- sum(lexicon);
+ f <- sum(sublexicon);
+
+ # complementary.lexicon <- c(lexicon[names(sublexicon)] - sublexicon, lexicon[!names(lexicon) %in% names(sublexicon)]);
+
+ if (F < f) {
+ stop("The lexicon cannot be smaller than the sublexicon");
+ }
+
+ whiteDrawn <- numeric(length(lexicon)); # The frequencies observed in this part for each type.
+ names(whiteDrawn) <- names(lexicon);
+ whiteDrawn[names(sublexicon)] <- sublexicon;
+ white <- lexicon; # The total frequencies in the corpus for each type.
+ black <- F-white; # The total complement frequency in the corpus for each type.
+ drawn <- f; # The number of tokens in the part.
+
+ # print(whiteDrawn);
+ # print(white);
+ # print(black);
+ # print(drawn);
+
+ independance <- (white * drawn) / F; # The theoretic frequency of each type.
+
+ specif_negative <- whiteDrawn < independance; # index of observed frequencies below the theoretic frequencies.
+ specif_positive <- whiteDrawn >= independance; # index of observed frequencies above the theoretic frequencies.
+
+ specif <- double(length(lexicon));
+
+ specif[specif_negative] <- phyper (
+ whiteDrawn[specif_negative], white[specif_negative], black[specif_negative], drawn
+ );
+
+ specif[specif_positive] <- phyper (
+ whiteDrawn[specif_positive] - 1, white[specif_positive], black[specif_positive], drawn
+ );
+
+ names(specif) <- names(lexicon);
+
+ return(specif);
+}
+
+#print.specificites(x, line=20, part=1, form=NULL, ...) {
+# if (all(is.null(line, part))) {
+# stop("either a line or a part must be specified");
+# }
+# if (all(!is.null(line, part))) {
+# stop("only a line or a part must be specified");
+# }
+#}
projects / iramuteq / blobdiff