In sysbiomed/ransac: RANSAC

knitr::opts_chunk$set(echo = TRUE)

library(reshape2)
library(ggplot2)
library(futile.logger)

print.sensitivy <- function(cache.file, data.org){
  load(cache.file)
  for (data.type in sort(unique(overall.df$data))) {
    for (data.family in sort(unique(subset(overall.df, data == data.type)$family))) {
      data.type.df <- subset(overall.df, data == data.type & family == data.family)
      flog.info('Unique for %s / %s (%d observations)', data.type, data.family, nrow(data.type.df))
      flog.info('              n (%d): %s', length(unique(data.type.df$n)), paste(sort(unique(data.type.df$n)), collapse = ', '))
      flog.info('      threshold (%d): %s', length(unique(data.type.df$threshold)), paste(sort(unique(data.type.df$threshold)), collapse = ', '))
      flog.info('  good.fit.perc (%d): %s', length(unique(data.type.df$good.fit.perc)), paste(sort(unique(data.type.df$good.fit.perc)), collapse = ', '))
      flog.info('----------------------')
      ##
      overall.n <- 30
      overall.good.fit.perc <- .4
      data.type.df.melt <- melt(data.type.df, c(1,2,3,4,5,6,7), c(8,11,14,17,20,23), value.name = 'Outliers', variable.name = 'Criteria')
      g <- ggplot(data = data.type.df.melt, aes(x = threshold, y = Outliers, color = Criteria)) + theme_minimal() +
        ggtitle(sprintf('%s -- data: %s -- family: %s', data.org, data.type, data.family))
      print(g + geom_line(linetype = 'dotted') + geom_point())
    }
  }
}

Print Parameter Sensitivity

cache.files <- list(original  = file.path('cache', 'overall.RData'), 
                    perturbed = file.path('cache', 'overall.pert.RData'))

Original Data

print.sensitivy(cache.files$original, data.org = 'original')

Perturbed Data

print.sensitivy(cache.files$perturbed, data.org = 'perturbed')

sysbiomed/ransac documentation built on May 14, 2019, 12:55 a.m.