Merge branch 'master' of ssh://git@github.com/CompNet/NaNet.git

Author: vlabatut

src/dynamic/narr_smooth.R

@@ -346,7 +346,7 @@ ns.read.graph <- function(filtered, remove.isolates=TRUE, pub.order=TRUE)
 		ord.fold <- "order_story"
 
 	base.file <- get.path.data.graph(mode="scenes", net.type="narr_smooth", order=ord.fold, filtered=filtered, pref="ns")
-	gs <- read.dynamic.graph(base.path=base.file, remove.isolates=remove.isolates)
+	gs <- read.dynamic.graph(base.file=base.file, remove.isolates=remove.isolates)
 
 	return(gs)
 }

src/graphs/read_write.R

@@ -68,13 +68,13 @@ write.dynamic.graph <- function(gs, base.path)
 #
 # returns: list of igraph objects representing a dynamic graph.
 ###############################################################################
-read.dynamic.graph <- function(base.path, remove.isolates=TRUE)
+read.dynamic.graph <- function(base.file, remove.isolates=TRUE)
 {	tlog(2,"Reading files of the form \"",base.file,"\"")
 	gs <- list()
 
 	# get folder path 
-	folder <- dirname(base.path)
-	file <- basename(base.path)
+	folder <- dirname(base.file)
+	file <- basename(base.file)
 	ll <- list.files(path=folder, pattern=paste0(file,".+"), full.names=TRUE)
 
 	# number of digits in the file names
@@ -85,7 +85,7 @@ read.dynamic.graph <- function(base.path, remove.isolates=TRUE)
 	go.on <- TRUE
 	s <- 1
 	while(go.on)
-	{	graph.file <- paste0(base.file,"_",s,".graphml")
+	{	graph.file <- paste0(base.file,"_",sprintf(paste0("%0",digits,"d"),s),".graphml")
 		if(file.exists(graph.file))
 		{	if(s==1 || s %% 500 == 0 || s==length(gs))
 				tlog(4, "Reading file ",graph.file)

src/post/description/char_sim.R

@@ -18,7 +18,7 @@ start.rec.log(text="CharSim")
 ################################################################################
 # main parameters
 wide <- TRUE				# wide plots showing volumes as rectangles
-narr.smooth <- TRUE			# whether to use narrative smoothing
+narr.smooth <- TRUE			# whether to use narrative smoothing or cumulative scene-based networks
 weighted <- TRUE			# whether to use the graph weights
 sc.lim <- NA				# limit on the considered scenes (NA for no limit)
 pub.order <- TRUE			# whether to use the volume publication vs. story order
@@ -99,26 +99,26 @@ tlog(0,"Evolution of similarity between pairs of characters")
 
 # similarity measures
 sim.meas <- list()
-#sim.meas[["cosine"]] <- list(
-#	bounds=c(0,1),
-#	cname="Cosine Similarity",
-#	foo=function(a,idx) {sapply(1:nrow(idx), function(r) sum(a[idx[r,1],]*a[idx[r,2],])/sqrt(sum(a[idx[r,1],]^2)*sum(a[idx[r,2],]^2)))}
-#)
-#sim.meas[["pearson"]] <- list(
-#	bounds=c(-1,1),
-#	cname="Pearson Coefficient",
-#	foo=function(a,idx) {sapply(1:nrow(idx), function(r) cor(x=a[idx[r,1],], y=a[idx[r,2],]))}
-#)
-#sim.meas[["euclidean"]] <- list(
-#	bounds=c(0,NA),
-#	cname="Euclidean Distance",
-#	foo=function(a,idx) {sapply(1:nrow(idx), function(r) sqrt(sum((a[idx[r,1],]-a[idx[r,2],])^2)))}
-#)
-sim.meas[["regequiv"]] <- list(
+sim.meas[["cosine"]] <- list(
+	bounds=c(0,1),
+	cname="Cosine Similarity",
+	foo=function(a,idx) {sapply(1:nrow(idx), function(r) sum(a[idx[r,1],]*a[idx[r,2],])/sqrt(sum(a[idx[r,1],]^2)*sum(a[idx[r,2],]^2)))}
+)
+sim.meas[["pearson"]] <- list(
+	bounds=c(-1,1),
+	cname="Pearson Coefficient",
+	foo=function(a,idx) {sapply(1:nrow(idx), function(r) cor(x=a[idx[r,1],], y=a[idx[r,2],]))}
+)
+sim.meas[["euclidean"]] <- list(
 	bounds=c(0,NA),
-	cname="Regular Equivalence",
-	foo=function(a,idx) {tmp <- REGE.for(M=a,E=0)$E; sapply(1:nrow(idx), function(r) tmp[idx[r,1],idx[r,2]])}
+	cname="Euclidean Distance",
+	foo=function(a,idx) {sapply(1:nrow(idx), function(r) sqrt(sum((a[idx[r,1],]-a[idx[r,2],])^2)))}
 )
+#sim.meas[["regequiv"]] <- list(
+#	bounds=c(0,NA),
+#	cname="Regular Equivalence",
+#	foo=function(a,idx) {tmp <- REGE.for(M=a,E=0)$E; sapply(1:nrow(idx), function(r) tmp[idx[r,1],idx[r,2]])}
+#)
 
 # plot parameters
 pal <- ATT_COLORS_FILT