plotPowerLaw-iSearch.r

# set the working directory
# setwd('D:/evaldata/evaltools/')
setwd('/Users/schaer/Desktop/evaldata/evaltools')

# Configure the root directory and the correct CSV file
#rootDir <- 'C:/Users/sc/Dropbox/Dissertation/results/girt/facets_topicQuery'
rootDir <- '/Users/schaer/Dropbox/Dissertation/results/iSearch/facets-topicQuery'
csvFile <- 'powerlawForPlot.csv'

# read in the csv file with all PL exponents
powerLawExponents <- read.csv2(paste(rootDir,csvFile,sep='/'), 
                               sep=';',
                               header=TRUE,
                               blank.lines.skip=TRUE,
)[,-8] # delete last empty column

# draw the power law plots for a given directory, a year and a data type
# drawPlot <- function(folder,file){      

folder <- rootDir
#file <- 'facets-source.txt'
file <- 'facets-author.txt'

#init the PDF export  
outputFile <- paste(folder,'/../pdf.merged/',file,'.pdf',sep='')
pdf(outputFile, pointsize=8)

# arrange the layout
par(mfrow=c(5,5),mar=c(1.5,2,1.5,1.5),lwd=0.5,pty='s')

# extract the entity filename
entity <- sub('.txt','',sub('facets-','',file))

# read in the facet file
facets <- read.csv2(paste(folder,file,sep='/'), 
                    sep=';',
                    header=FALSE,
                    col.names=c('topic','name','count'))

# explicitly convert to numeric (001 -> 1)
#facets$topic <- as.numeric(facets$topic)

topics <- unique(as.numeric(facets$topic))

for(topic in topics){
  #print status line
  print(paste('plotting',topic,'for entity',entity))
  
  freqs <- as.numeric(facets[facets$topic==topic,]$count)
  #freqs <- freqs[-1] # how to deal with empty facets? -> delete them in the plot for source only
  ranks <- 1:length(freqs)
  
  # plot with on a log-log scale
  plot(ranks,freqs,xlab='rank',ylab='frequency',log='xy')        
  
  # extract the power law exponent
  tempValues <- powerLawExponents[powerLawExponents$topic==topic,]
  resultValues <- tempValues[grep(entity,tempValues$run),]
  
  # when more than one result, take the first one
  resultValue <- resultValues[1,]
  
  alpha <- resultValue$alpha
  D <- resultValue$D
  xmin <- resultValue$xmin
  pval <- resultValue$pval      
  
  # draw a dotted line to mark xmin
  abline(v=xmin,lty=3)
  
  # check is we really observed a PL 
  # See Clauset et al (2009) - section 4.2        
  # print(pval)
  if(pval >= 0.1){      
    
    # calulate the intersection with y-axis (y_0) and set this
    # as the (a) intersect=y_0 and (b) slope=-alpha      
    # y_xmin <- freqs[xmin] 
    # y_0 <- y_xmin + (xmin * alpha)      
    # abline(a=log10(y_0), b=-log10(alpha),lty=2, col='yellow', lwd=2)            
    # print(paste('intersection method: ', xmin, y_xmin, -alpha, y_0))
    # --> this just does not work out!      
    
    # very skewed plot... but seems right
    # WARNING: NOT WORKING WITH LOG-LOG-PLOT      
    # x0 <- xmin
    # y0 <- freqs[xmin]      
    # x1 <- max(ranks)
    # y1 <- x1^(-log10(alpha))
    # segments(c(x0), c(y0), c(x1), c(y1), lty=2, col='red', lwd=2)
    # print(paste('segment method: ',x0,y0,x1,y1))      
    
    # draw an approximated (wrong!) linear regression model
    # abline(lm(log10(freqs)~log10(ranks)),lty=2)      
    # we only use the data in respect to xmin
    filteredRanks <- log10(ranks[xmin:length(ranks)])
    filteredFreqs <- log10(freqs[xmin:length(freqs)])
    logmodel <- lm(filteredFreqs~filteredRanks)            
    # print(summary(logmodel))
    # print(logmodel$df.residual)
    if(logmodel$df.residual > 0){
      abline(logmodel, lty=1, col='gray', lwd=1.5)  
    }                        
  }
  
  # add some decorating text
  alpha <- format(alpha,digits=3) # only 3 digits
  text(max(ranks), max(freqs), 
       labels=(paste('top:',topic,'a: -',alpha,'xmin:',xmin)),
       adj=1)    
    
} 

dev.off() #close file

  #compress the pdf file with pdftk  
  # commandLine <- paste('C:/cygwin/bin/pdftk.exe',
  #                      filename,
  #                      'output',
  #                      sub('merged','compressed',filename),                       
  #                      'compress')  
  # system(commandLine)  
  # }
  
  # drawPlot(rootDir,'facets-source.txt')      
  # drawPlot(rootDir,'facets-author.txt')