R/visualization/identifier_for_relation.R

In amirms/GeLaToLab: GELATOLAB

# getters <-  c(
#     "getBooleanProperty",
#     
#     "getIntegerProperty",
#     
#     "getSelectedIndex",
#     "getMaximum" ,
#     
#     "getPaper",
#     "getValue",
#     "getShowHiddenFiles" ,
#     
# 
#     "getDefault",
#     "getStructureHighlightColor",
#     "getIgnoreCase",
#     "getSearchString",
#     "getListener",
#     "getFontHandler",
#     "getScope"
#     
#   );
# 
# setters <-  c(
#   "setBooleanProperty",
#   
#   "setIntegerProperty",
#   
#   "setSelectedIndex",
#   "setMaximum" ,
#   
#   "setPaper",
#   "setValue",
#   "setShowHiddenFiles" ,
#   "setDefault",
#   "setStructureHighlightColor",
#   "setIgnoreCase",
#   "setSearchString",
#   "setListener",
#   "setFontHandler",
#   "setScope"
#   
#   
# )
# 
# identifiers_for_relations <- c(
#   getters,setters
# )
# 
# 
# identifiersPerClass <- list(
#   list("getMaximum", "setMaximum"),
#   list("getBorder", "setBorder"),
#   list("getVisibleRowCount", "setVisibleRowCount"),
#   #list("getDefaultRenderer", "setDefaultRenderer"),
#   list("getKeyEventInterceptor", "setKeyEventInterceptor"),
#   list("getReshowDelay", "setReshowDelay"),
#   list("getFirstLine", "setFirstLine"),
#   #list("getMethod", "setMethod"),
#   list("getSelectedItem", "setSelectedItem"),
#   #list("getStyles", "setStyles"),
#   list("getMultipleSelectionColor", "setMultipleSelectionColor"),
#   list("getSelectionColor", "setSelectionColor"),
#   list("getSelectionPath", "setSelectionPath"),
#   #list("getTerminateChar", "setTerminateChar"),
#   list("getAutoWrapAround", "setAutoWrapAround"),
#   list("getDefault", "setDefault"),
#   list("getDefaultMax", "setDefaultMax"),
#   list("getDTDHandler", "setDTDHandler"),
#   list("getAutoReload", "setAutoReload"),
#   #list("getCurrentLineForeground", "setCurrentLineForeground"),
#   #list("getColumnWidth", "setColumnWidth"),
#   list("getRepeatCount", "setRepeatCount"),
#   #list("getFeature", "setFeature"),
#   #list("getIntegerProperty", "setIntegerProperty"),
#   #list("getMaximumSize", "setMaximumSize"),
#   list("getIgnoreCase", "setIgnoreCase")
#   
# )




#abbreviated, domain-specific vocabulary and encrypted forms.

finGettersAndSetters <- function(names){
  
  others <- c("#V#", "#P#" )
  
getters = names[grepl("get",names)]

getters <- getters[!grepl(others[1], getters)]
getters <- getters[!grepl(others[2], getters)]


setters = names[grepl("set",names)]
setters <- setters[!grepl(others[1], setters)]
setters <- setters[!grepl(others[2], setters)]

# 
# getterRoot = unique(unlist(strsplit(getters, 'get')))
# getterRoot = getterRoot[-1]
# 
# results = c()
# for(i in 1:length(getterRoot)){
#   if (paste("set", getterRoot[i],sep="") %in% setters){
#     results <- c(results, paste("get", getterRoot[i],sep=""), paste("set", getterRoot[i],sep=""))
#   }
# }

return(list(getters=getters, setters=setters))

}


plot = function(){
  library(Rtsne)
  
  # identifiers = results[101:120]
  # identifiers = unlist(identifiersPerClass)
  
  ## calling the installed package
  train <- read.csv("C:\\workspace\\org.graph.cnn\\res\\jedit-5.1.0\\identifier2vec.transr.ee.bern", sep=";", header = F);
  train <- data.matrix(train[,-101])
  
  identifier2id <- read.csv("C:\\workspace\\org.graph.cnn\\data\\jedit-5.1.0\\identifier2id.txt", sep=";", header = F);
  
  names <- as.vector(identifier2id$V1)
  # names <- apply(names,1, function(n) strsplit(n, ";")[[1]][1])
  
  

  
  rownames(train) <- names

  # classes = getClasses(identifiersPerClass, names)
  
  r <- finGettersAndSetters(names)
  
  result <- group_getters_setters(r$getters, r$setters)
  allNames <- c(result$getters, result$setters)
  
  
  data = train[allNames,]
  
  ## Curating the database for analysis with both t-SNE and PCA
  # train$label = unlist(lapply(seq(1:dim(train)[1]), function(x) paste("id", x, sep="_")))
  # Labels<-train$label
  # train$label<-as.factor(train$label)
  # ## for plotting
  # colors = rainbow(length(unique(train$label)))
  # names(colors) = unique(train$label)
  
  # colors = rainbow(max(classes))
  # names(colors) = unique(classes)
  

    # x <- prcomp(train[,-dim(train)[2]], center = T, scale. = T)
    x <- prcomp(train, center = F, scale. = F)$x
    
    x <- x[allNames,]
    # tsne <- list(Y=x$x[identifiers,1:2])

  ## Plotting
  # plot(tsne$Y, t='n', main="tsne")
  # text(tsne$Y, labels=rownames(tsne$Y))
  # text(tsne$Y, labels=train$label, col=colors[classes])
  
  
  ## Plotting using ggplot2
  library(ggplot2)
  
  # data = as.data.frame(tsne$Y)
  data = as.data.frame(x)
  # color = Topics)
  pc1 <- ggplot(data, aes(x=PC1, y=PC2)) + theme_bw() + theme(#axis.title.x=element_text("PC1"), axis.title.y=element_text("PC2"),
                                                                      # axis.text.x=element_blank(),
                                                                      # axis.ticks.x=element_blank(),
                                                                      panel.grid.major = element_blank(),
                                                                      panel.grid.minor = element_blank(), 
                                                                      axis.line = element_line(colour = "black"))
  
  # pc1 + geom_point()
  # pc1 + geom_point(shape = 1, size = 4)
  
  # pc2 <- pc1 + geom_point(aes(group=g), size = 3, color="blue")#, stroke = 2.5)
  pc2 <- pc1 + geom_point( size = 3, color="blue")#, stroke = 2.5)
  
  library("ggrepel")
  
  # x <- list(c(3,4), c(1,5), c(2,15), c(6,17), c(7,13), c(8,20), c(9,16), c(10,26), c(11,19), c(12,21), c(14, 24), c(18,23 ), c(22,25));
  
  
  # g <- c("G1", "G1", "G2", "G2", "G3", "G3", "G4", "G4", "G5", "G5",
  #        "G6", "G6", "G7", "G7", "G8","G8", "G9", "G9", "G10", "G10",
  #        "G11", "G11", "G12", "G12", "G13", "G13", "G14", "G14", "G15", "G15",
  #        "G16", "G16", "G17", "G17") 
  
  g <- result$classes
  
  
  pc3 <- pc2 + geom_line(aes(group=g), linetype = 2, color="red", size = 1)
  
  
  labels <- rownames(data)
  labels <- unlist(lapply(labels, function(cur) substring(cur, gregexpr("#M#", cur)[[1]]+3)))
  
  pc4 <- pc3 +     geom_text_repel(aes(label = labels),
                                    color = "gray20", force=1)
}


group_getters_setters = function(getters, setters, sample_size=50) {
  if (sample_size > 0){
    
  # take a random sample 
    # ss = sample(1:length(setters), sample_size, replace=F)
    # 
    # setters <- setters[300:350]
    

    setter_choices <- c("setInitialDelay", "setScope", "setItem", "setLabel",  "setSelectedText", "setSelectedIndex", "setIntegerProperty", "setMessage", "setElementAt", "setNameSpace",
               "setShortcut", "setAbbrev", "setLineContext", "setKeywords", "setDigitRegexp")

    setters <- unlist(lapply(setter_choices, function(ss) setters[endsWith(tolower(setters), tolower(ss))][1]))
  }
  
  # names(setters) <- setters
  # names(getters) <- getters
  
  
  cooresponding_setters <- gsub("#M#get", "#M#set", getters);
  setters <- setters[which(setters %in% cooresponding_setters)]
  
  cooresponding_getters <- gsub("#M#set", "#M#get", setters);
  getters <- getters[which(getters%in%cooresponding_getters)]
  
  
  classes <- rep(0, 2 * length(getters))
  
  no_of_getters <- length(getters)
  
  for (i in 1:length(getters)) {
    current_getter = getters[i]
    
    #replace #M#get with #M#set
    current_setter <- gsub("#M#get", "#M#set", current_getter)
    print(current_setter)
    
    index <- which(setters == current_setter)
    
    print(index)
    
    classes[c(i, index+no_of_getters)] <- i
  }
  
  return(list(classes=classes, getters=getters, setters=setters))
}