Plotting function R

rcode/distributedDelay_densities.R

+# ----
+
+
+library("ggplot2")
+if (Sys.info()['sysname'] == 'Darwin'){
+  setwd('/Users/toni/Dropbox/NPCMaturation/results/emdata/delay')
+} else {
+  setwd('C:\\Users\\toni\\Dropbox\\NPCMaturation\\results\\emdata\\delay')
+}
+
+inData = list()
+fname <- 'delayedMaturation_v0.015_ts10_den.txt'
+tmpCsv = read.csv(fname, skip=0, sep='\t')
+tmpCsv['dtauM'] = 0
+tmpCsv['idx'] = 6
+inData = rbind(inData, tmpCsv)
+
+delay = c(5,10,15, 20, 30)
+for (idx in seq(1,length(delay),1)) {
+  fname <- paste(c('delayedMaturationDistrubutedDelay_ts10_v0.015_dtau',  as.character(delay[idx]), '_den.txt'), collapse = '')
+  tmpCsv = read.csv(fname, skip=0, sep='\t')
+  tmpCsv['dtauM'] = delay[idx]
+  tmpCsv['idx'] = length(delay)-idx
+  inData = rbind(inData, tmpCsv)
+}
+
+
+# -----
+
+
+
+addOpt <- function(p) {
+  p <- p + xlab(' Time after AO (min)') + ylab(expression(paste("Density (pores/", mu, m^2, ")"))) +
+    scale_x_continuous(expand = c(0, 0), limits = c(0,120), breaks=seq(0,120,20)) + 
+    scale_y_continuous(expand = c(0, 0), limits = c(0, 13), breaks=seq(0,13,4)) + 
+    theme_classic(base_size = 8) + 
+    theme(legend.position = 'none', axis.line.x = element_line(color="black", size = 0.5),
+          axis.line.y = element_line(color="black", size = 0.5)) + 
+    theme(axis.text.x = element_text(size=8), 
+          axis.text.y = element_text(size=8), 
+          plot.margin = unit(c(5,5,0,0), "mm"))
+  return(p)
+}
+
+# ---- 
+pint <- ggplot(data = inData) +  geom_line(data = inData, aes(time, inter_i, group = idx,  colour = -idx)) + 
+  geom_line(data = inData, aes(time, mature_i, group = idx, colour = idx))
+#pmat <- ggplot(data = inData) +   
+#  geom_line(aes(time, mature_i, group = N+200,  colour = N+200))
+
+pint <- addOpt(pint) + scale_color_gradient2(midpoint = 0, low="red", mid = "gray", high="blue")
+
+#pint <- addOpt(pint) + scale_color_gradient2(midpoint = 0,space='Lab', low="black", mid = "gray", high="black")
+
+
+pint
+
+if (Sys.info()['sysname'] == 'Darwin'){
+  setwd('/Users/toni/Dropbox/NPCMaturation/results/emdata/figures')
+} else {
+  setwd('C:\\Users\\toni\\Dropbox\\NPCMaturation\\results\\emdata\\figures')
+}
+
+ggsave(filename="inner_distributedDelay.pdf", plot=pint, width = 71, height = 44, units = 'mm')
+
+
+gp <- ggplot_build(pint)
+cp <- unique(gp$data[[1]]["colour"])
+
+
+# -----
+cols = c("#BEBEBE", "#9B9B9B", "#7A7A7A", "#5B5B5B", "#3D3D3D", "#000000")
+dtauM_distr = c(0.1, 5, 10, 15, 20, 30)
+times = seq(20, 60, 0.1)
+distr = list()
+for (dtau in dtauM_distr){
+  distrloc = data.frame(time = seq(20,60,0.1), dis =0 , dtauM=0)
+  
+  distrloc$dis = 1/dtau*(distrloc$time>40-dtau/2)*(distrloc$time<40+dtau/2)
+  distrloc$dtauM = dtau
+  distr = rbind(distr, distrloc)
+}
+
+distr$dtauM = factor(distr$dtauM,  c(0.1, 5, 10, 15, 20, 30))
+pdtauM <- ggplot() + geom_line(data = distr, aes(x=time, y = dis, group = dtauM, colour = dtauM)) + 
+  theme_classic(base_size = 8) + xlab('Maturtion time (min)')  +   scale_colour_manual(values = cols[seq(6,1,-1)]) + ylab('Probability')  + 
+  coord_cartesian(ylim= c(0,0.3)) + 
+  theme(legend.position = 'none', axis.line.x = element_line(color="black", size = 0.5),
+        axis.line.y = element_line(color="black", size = 0.5)) + 
+  theme(axis.text.x = element_text(size=8), 
+        axis.text.y = element_text(size=8), 
+        plot.margin = unit(c(5,5,0,0), "mm"))
+pdtauM 
+ggsave(filename="distributedDelay_dtauM.pdf", plot=pdtauM, width = 72, height = 22, units = 'mm')
+

rcode/distributedDelayvsdelayequation.R

+library("ggplot2")
+# ---- 
+
+if (Sys.info()['sysname'] == 'Darwin'){
+  indatadir <-'/Users/toni/Dropbox/NPCMaturation/expdata/emdata'
+  indir <- '/Users/toni/Dropbox/NPCMaturation/results/emdata/delay'
+  outdir <- '/Users/toni/Dropbox/NPCMaturation/results/emdata/figures'
+} else {
+  indatadir <- 'C:\\Users\\toni\\Dropbox\\NPCMaturation\\expdata\\emdata'
+  indir <- 'C:\\Users\\toni\\Dropbox\\NPCMaturation\\results\\emdata\\delay'
+  outdir <- 'C:\\Users\\toni\\Dropbox\\NPCMaturation\\results\\emdata\\figures'
+}
+
+setwd(indir)
+inData = list()
+fname <- 'delayedMaturation_v0.015_ts10.txt'
+tmpCsv = read.csv(fname, skip=6, sep='\t')
+idx = which.min(tmpCsv$norm)
+concatDF = tmpCsv[idx,]
+concatDF['dtauM'] = 0
+concatDF['idx'] = 0
+inData = rbind(inData,  concatDF[,c('idx', 'norm',  'tauM', 'dtauM')])
+
+
+
+
+delay = c(5,10,15,20, 30)
+for (idx in seq(1,length(delay),1)) {
+  fname <- paste(c('delayedMaturationDistrubutedDelay_ts10_v0.015_dtau',  as.character(delay[idx]), '.txt'), collapse = '')
+  tmpCsv = read.csv(fname, skip=6, sep='\t')
+  idxC = which.min(tmpCsv$norm)
+  concatDF = tmpCsv[idxC,]
+  concatDF['idx'] = idx
+  concatDF['dtauM'] = concatDF['dtauM']/2
+  inData = rbind(inData, concatDF[,c('idx','norm',  'tauM', 'dtauM')])
+}
+
+
+inData$dtauM = factor(inData$dtauM,levels = c(0, 5, 10,15,20,30)/2)
+inData$idx = factor(inData$idx,levels = c(0,1,2,3,4,5))
+
+# ----
+cols = c("#BEBEBE", "#9B9B9B", "#7A7A7A", "#5B5B5B", "#3D3D3D", "#000000")
+pChi2<- ggplot(inData, aes(x = dtauM, y = norm, fill = idx))+ 
+  geom_bar(stat = "identity", position = 'dodge') + coord_cartesian(ylim= c(20,40)) +
+  theme_classic(base_size = 8) + xlab('Half-width distribution (min)') + ylab('Sum of squared \n residuals')   + 
+  theme(legend.position = 'none', axis.line.x = element_line(color="black", size = 0.5),
+      axis.line.y = element_line(color="black", size = 0.5)) + 
+  theme(axis.text.x = element_blank(), 
+        axis.text.y = element_text(size=8),
+        plot.margin = unit(c(5,5,0,0), "mm"))  + scale_fill_manual(values = cols[seq(6,1,-1)])
+pChi2
+
+setwd(outdir)
+
+
+ggsave(filename="distributedDelay_chi2.pdf", plot=pChi2, width = 71, height = 30, units = 'mm')
+
+# ---- 
+
+ptaum<- ggplot(inData, aes(x = dtauM, y = tauM, fill = idx)) + geom_bar(stat = "identity", position = 'dodge')  +
+  theme_classic(base_size = 8) + xlab('Half-width distribution (min)')  +   scale_fill_manual(values = cols[seq(6,1,-1)]) + ylab('Avg. Mat. time (min)\n')  + 
+  coord_cartesian(ylim= c(0,50), xlim = c(0.4,6.6), expand = c(0)) + 
+  theme(legend.position = 'none', axis.line.x = element_line(color="black", size = 0.5),
+        axis.line.y = element_line(color="black", size = 0.5)) + 
+  theme(axis.text.x = element_text(size=8), 
+        axis.text.y = element_text(size=8), 
+        plot.margin = unit(c(5,5,0,0), "mm"))
+ptaum
+ggsave(filename="distributedDelay_tauM.pdf", plot=ptaum, width = 71, height = 35, units = 'mm')
+
+#----
+
+

rcode/linearChainvsdelayequation.R

+library("ggplot2")
+# ---- 
+
+
+if (Sys.info()['sysname'] == 'Darwin'){
+  setwd('/Users/toni/Dropbox/NPCMaturation/results/emdata/linearChain')
+} else {
+  setwd('C:\\Users\\toni\\Dropbox\\NPCMaturation\\results\\emdata\\linearChain')
+}
+
+inData = list()
+
+for (N in c(5, 10, 20, 40, 100)) {
+  tmpCsv = read.csv(paste(c('linearChainApproximation_N',  as.character(N), '_v0.015.txt'), collapse = '')
+               , skip=6, sep='\t')
+  tmpCsv['N'] = N
+  tmpCsv['model'] = 'multi step'
+  colnames(tmpCsv)[1] <- 'ts'
+  idx = which.min(tmpCsv$norm)
+  concatDF = tmpCsv[idx,]
+  concatDF['tauM'] = (N-1)/concatDF$k
+  inData = rbind(inData, concatDF[,  c('norm', 'N', 'model', 'tauM')])
+}
+
+
+
+
+
+if (Sys.info()['sysname'] == 'Darwin'){
+  setwd('/Users/toni/Dropbox/NPCMaturation/results/emdata/delay')
+} else {
+  setwd('C:\\Users\\toni\\Dropbox\\NPCMaturation\\results\\emdata\\delay')
+}
+fname <- 'delayedMaturation_v0.015_ts10.txt'
+tmpCsv = read.csv(fname, skip=6, sep='\t')
+colnames(tmpCsv)[1] <- 'ts'
+colnames(tmpCsv)[3] <- 'k'
+
+idx = which.min(tmpCsv$norm)
+concatDF = tmpCsv[idx,]
+concatDF['model'] = 'delay'
+concatDF['N'] = 'delay'
+inData = rbind(inData, concatDF[, c('norm', 'N', 'model', 'tauM')])
+
+inData$N = factor(inData$N,levels = c(5, 10,20,40,100, 'delay'))
+# ----
+if (Sys.info()['sysname'] == 'Darwin'){
+  setwd('/Users/toni/Dropbox/NPCMaturation/results/emdata/figures')
+} else {
+  setwd('C:\\Users\\toni\\Dropbox\\NPCMaturation\\results\\emdata\\figures')
+}
+cols = c("#BEBEBE", "#9B9B9B", "#7A7A7A", "#5B5B5B", "#3D3D3D", "#000000")
+pChi2<- ggplot(inData, aes(x = N, y = norm, fill = N)) + 
+  geom_bar(stat = "identity", position = 'dodge') + coord_cartesian(ylim= c(20,40)) +
+  theme_classic(base_size = 8) + xlab('') + ylab('Sum of squared \n residuals')   + 
+  theme(legend.position = 'none', axis.line.x = element_line(color="black", size = 0.5),
+      axis.line.y = element_line(color="black", size = 0.5)) + 
+  theme(axis.text.x = element_blank(), 
+        axis.text.y = element_text(size=8), 
+        plot.margin = unit(c(5,5,0,0), "mm"))  + scale_fill_manual(values = cols)
+pChi2
+ggsave(filename="linearChain_delay_chi2.pdf", plot=pChi2, width = 71, height = 30, units = 'mm')
+
+# ---- 
+ptaum<- ggplot(inData, aes(x = N, y = tauM, fill = N)) + geom_bar(stat = "identity", position = 'dodge')  +
+  theme_classic(base_size = 8) + xlab('Number of steps (N)')  +   scale_fill_manual(values = cols) + ylab('Maturation time (min)\n')  + 
+  coord_cartesian(ylim= c(0,50), xlim = c(0.4,6.6), expand = c(0)) + 
+  theme(legend.position = 'none', axis.line.x = element_line(color="black", size = 0.5),
+        axis.line.y = element_line(color="black", size = 0.5)) + 
+  theme(axis.text.x = element_text(size=8), 
+        axis.text.y = element_text(size=8), 
+        plot.margin = unit(c(5,5,0,0), "mm"))
+ptaum
+
+ggsave(filename="linearChain_delay_tauM.pdf", plot=ptaum, width = 71, height = 35, units = 'mm')
+
+

rcode/linearChainvsdelayequation_densities.R

+# ----
+
+
+library("ggplot2")
+if (Sys.info()['sysname'] == 'Darwin'){
+  setwd('/Users/toni/Dropbox/NPCMaturation/results/emdata/linearChain')
+} else {
+  setwd('C:\\Users\\toni\\Dropbox\\NPCMaturation\\results\\emdata\\linearChain')
+}
+
+
+inData = list()
+Nval = c(5,10,20,40,100)
+for (idx in c(1,2,3,4,5)) {
+  fname <- paste(c('linearChainApproximation_N',  as.character(Nval[idx]), '_v0.015_den.txt'), collapse = '')
+  tmpCsv = read.csv(fname, skip=0, sep='\t')
+  tmpCsv['N'] = Nval[idx]
+  tmpCsv['id'] = idx-1
+  inData = rbind(inData, tmpCsv)
+}
+if (Sys.info()['sysname'] == 'Darwin'){
+  setwd('/Users/toni/Dropbox/NPCMaturation/results/emdata/delay')
+} else {
+  setwd('C:\\Users\\toni\\Dropbox\\NPCMaturation\\results\\emdata\\delay')
+}
+
+fname <- 'delayedMaturation_v0.015_ts10_den.txt'
+tmpCsv = read.csv(fname, skip=0, sep='\t')
+tmpCsv['N'] = 1000
+tmpCsv['id'] = 5
+
+inData = rbind(inData, tmpCsv)
+
+
+addOpt <- function(p) {
+  p <- p + xlab(' Time after AO (min)') +ylab(expression(paste("Density (pores/", mu, m^2, ")"))) +
+    scale_x_continuous(expand = c(0, 0), limits = c(0,120), breaks=seq(0,120,20)) + 
+    scale_y_continuous(expand = c(0, 0), limits = c(0, 13), breaks=seq(0,13,4)) + 
+    theme_classic(base_size = 8) + 
+    theme(legend.position = 'none', axis.line.x = element_line(color="black", size = 0.5),
+          axis.line.y = element_line(color="black", size = 0.5)) + 
+    theme(axis.text.x = element_text(size=8), 
+          axis.text.y = element_text(size=8), 
+          plot.margin = unit(c(5,5,0,0), "mm"))
+  return(p)
+}
+
+# ---- 
+if (Sys.info()['sysname'] == 'Darwin'){
+  setwd('/Users/toni/Dropbox/NPCMaturation/results/emdata/figures')
+} else {
+  setwd('C:\\Users\\toni\\Dropbox\\NPCMaturation\\results\\emdata\\figures')
+}
+pint <- ggplot(data = inData) +  geom_line(data = inData, aes(time, inter_i, group = id,  colour = -id)) + 
+  geom_line(data = inData, aes(time, mature_i, group = id, colour = id))
+#pmat <- ggplot(data = inData) +   
+#  geom_line(aes(time, mature_i, group = N+200,  colour = N+200))
+
+pint <- addOpt(pint) + scale_color_gradient2( midpoint = 0, low="red", mid = "gray", high="blue")
+
+
+pint
+
+
+ggsave(filename="inner_linearChain_delay.pdf", plot=pint, width = 71, height = 44, units = 'mm')
+
+
+gp <- ggplot_build(pint)
+cp <- unique(gp$data[[1]]["colour"])

rcode/prodVariants.R

+# ----
+
+
+library("ggplot2")
+
+
+# ------
+if (Sys.info()['sysname'] == 'Darwin'){
+  setwd('/Users/toni/Dropbox/NPCMaturation/results/emdata/delay')
+} else {
+  setwd('C:\\Users\\toni\\Dropbox\\NPCMaturation\\results\\emdata\\delay')
+}
+
+fnames = c('delayedMaturation_v0_ts10.txt',
+           'delayedMaturation_noPrecursor_ts10.txt', 
+           'delayedMaturationExponentialV_noPrecursor_ts10_v0.015.txt',
+           'delayedMaturation_v0.015_ts10.txt',
+           'delayedMaturationExponentialV_ts10_v0.015.txt')
+
+#vbasal is kept constant 
+#nrpar = c(6, 5, 6, 6, 8)
+nrpar = c(6, 5, 7, 7, 8)
+# fnames = c('delayedMaturation_v0_ts10.txt',
+#            'delayedMaturation_noPrecursor_ts10.txt', 
+#            'delayedMaturationExponentialV_noPrecursor_ts10.txt',
+#            'delayedMaturationSteadyRho_noPrecursor_ts10.txt',
+#            'delayedMaturation_ts10.txt',
+#            'delayedMaturationExponentialV_ts10.txt',
+#            'delayedMaturationSteadyRho_ts10.txt')
+#
+#nrpar = c(6, 5, 7, 6, 7, 9, 8)
+varNames = c('Var 1',  'Var 2', 'Var 3', 'Var 1+2', 'Var 1+3')
+inData = list()
+seq_plot = c(1, 2, 3, 4, 5)
+for (i in seq_along(fnames) ) {
+  
+  tmpCsv = read.csv(fnames[i], skip=6, sep='\t')
+  tmpCsv['model'] = varNames[i]
+  tmpCsv['nrpar']= nrpar[i]
+  idx = which.min(tmpCsv$norm)
+  inData = rbind(inData, tmpCsv[idx, c('tauM', 'norm', 'model', 'nrpar')])
+}
+
+inData$model = factor(inData$model, levels = varNames[seq_plot])
+
+#----- 
+if (Sys.info()['sysname'] == 'Darwin'){
+  setwd('/Users/toni/Dropbox/NPCMaturation/results/emdata/figures')
+} else {
+  setwd('C:\\Users\\toni\\Dropbox\\NPCMaturation\\results\\emdata\\figures')
+}
+pChi2<- ggplot(inData, aes(x = model, y = norm, fill = model)) + geom_bar(stat = "identity") + coord_cartesian(ylim= c(20,55)) +
+  theme_classic(base_size = 8)  + xlab('') + ylab('Sum of squared \n residuals') + 
+  theme(legend.position = 'none', axis.line.x = element_line(color="black", size = 0.5),
+        axis.line.y = element_line(color="black", size = 0.5)) + 
+  theme(axis.text.x = element_blank(), 
+        axis.text.y = element_text(size=8), 
+        plot.margin = unit(c(5,5,0,0), "mm")) 
+pChi2
+gp <- ggplot_build(pChi2)
+cp <- unique(gp$data[[1]]["fill"])
+
+ggsave(filename="production_rates_Chi2.pdf", plot=pChi2,  width = 71, height = 30, units = 'mm')
+
+
+# -----
+ptaum<- ggplot(inData, aes(x = model, y = tauM, fill = model)) + geom_bar(stat = "identity") + 
+  coord_cartesian(ylim= c(0,50), expand = c(0),  xlim = c(0.4,5.6)) +
+  theme_classic(base_size = 8)  + xlab('') + ylab('Maturation time (min)\n') + 
+  theme(legend.position = 'none', axis.line.x = element_line(color="black", size = 0.5),
+        axis.line.y = element_line(color="black", size = 0.5)) + 
+  theme(axis.text.x = element_text(size=8, angle = 45, vjust = 0.5), 
+        axis.text.y = element_text(size=8), 
+        plot.margin = unit(c(5,5,0,0), "mm")) 
+ptaum
+
+ggsave(filename="production_rates_tauM.pdf", plot=ptaum, width = 71, height = 43, units = 'mm')
+
+
+
+# ----
+testPairs = rbind(c(1,2), c(1,3),c(1,4), c(1,5), c(2,3), c(2,4), c(2,5), c(3,5))
+for(i in seq(1,8,1)) {
+  print(1 - pchisq(abs(inData$norm[testPairs[i,1]]-inData$norm[testPairs[i,2]]),abs(inData$nrpar[testPairs[i,2]]-inData$nrpar[testPairs[i,1]])))
+}
+#----
+
+#----
+if (Sys.info()['sysname'] == 'Darwin'){
+  setwd('/Users/toni/Dropbox/NPCMaturation/results/emdata/delay')
+} else {
+  setwd('C:\\Users\\toni\\Dropbox\\NPCMaturation\\results\\emdata\\delay')
+}
+
+fnames = c('delayedMaturation_v0_ts10_prodrate.txt', 
+           'delayedMaturation_noPrecursor_ts10_prodrate.txt', 
+           'delayedMaturationExponentialV_noPrecursor_ts10_v0.015_prodrate.txt',
+           'delayedMaturation_v0.015_ts10_prodrate.txt',
+           'delayedMaturationExponentialV_ts10_v0.015_prodrate.txt')
+
+inData = list()
+seq_plot = c(1, 4, 2, 5, 3)
+for (i in seq_along(fnames) ) {
+
+  tmpCsv = read.csv(fnames[i], skip=0, sep='\t')
+  tmpCsv['model'] = varNames[i]
+  if (i== 2 || i == 3 || i==5) {
+  tmpCsv['ProdDensity_inner'] = tmpCsv['ProdDensity_inner']*0.25
+  }
+  inData = rbind(inData, tmpCsv)
+}
+
+inData$model = factor(inData$model, levels = varNames[seq_plot])
+
+p <- ggplot(inData, aes(time, ProdDensity_inner, colour = model)) + geom_line(size = 1)  + theme_classic(base_size = 8) + 
+  coord_cartesian(ylim = c(0, 0.1), xlim = c(0, 50)) + facet_wrap(~ model, ncol = 2) + xlab('Time after AO (min)') +
+  ylab('Production density (pores/um2/min)') + 
+  theme(legend.position = 'none', 
+        strip.background = element_blank(), axis.line.y = element_blank(), #element_line(color="black", size = 0.5),
+        axis.line.x = element_blank(),
+        strip.text.x = element_text(size = 8, angle = 0),
+        legend.key = element_blank(),
+        #axis.text.x = element_blank(), 
+        #axis.text.y = element_blank(),
+        #axis.ticks.x=element_blank(),
+        #axis.ticks.y=element_blank(),
+        plot.margin = unit(c(5,5,0,0), "mm")) + scale_colour_manual(values=cp$fill[seq_plot])
+p
+
+if (Sys.info()['sysname'] == 'Darwin'){
+  setwd('/Users/toni/Dropbox/NPCMaturation/results/emdata/figures')
+} else {
+  setwd('C:\\Users\\toni\\Dropbox\\NPCMaturation\\results\\emdata\\figures')
+}
+
+ggsave(filename="production_rates.pdf", plot=p, width = 100, height = 60, units = 'mm') 
+
+
+
+
+
+# ----
+
+# -----
+
+
+
+addOpt <- function(p) {
+  p <- p + xlab(' Time after AO (min)')  +
+    scale_x_continuous(expand = c(0, 0), limits = c(0,120), breaks=seq(0,120,20)) + 
+    scale_y_continuous(expand = c(0, 0), limits = c(0, 13), breaks=seq(0,13,4)) + 
+    theme_classic(base_size = 8) + 
+    theme(legend.position = 'none', axis.line.x = element_line(color="black", size = 0.5),
+          axis.line.y = element_line(color="black", size = 0.5)) + 
+    theme(axis.text.x = element_text(size=8), 
+          axis.text.y = element_text(size=8), 
+          plot.margin = unit(c(5,5,0,0), "mm"))
+  return(p)
+}
+
+if (Sys.info()['sysname'] == 'Darwin'){
+  setwd('/Users/toni/Dropbox/NPCMaturation/expdata/emdata')
+} else {
+  setwd('C:\\Users\\toni\\Dropbox\\NPCMaturation\\expdata\\emdata')
+}
+
+denData = read.csv('density_innercore.txt', skip=0, sep='\t')
+
+if (Sys.info()['sysname'] == 'Darwin'){
+  setwd('/Users/toni/Dropbox/NPCMaturation/results/emdata/delay')
+} else {
+  setwd('C:\\Users\\toni\\Dropbox\\NPCMaturation\\results\\emdata\\delay')
+}
+fnames = c('delayedMaturation_v0_ts10_den.txt',
+           'delayedMaturation_noPrecursor_ts10_den.txt', 
+           'delayedMaturationExponentialV_noPrecursor_ts10_v0.015_den.txt',
+           'delayedMaturation_v0.015_ts10_den.txt',
+           'delayedMaturationExponentialV_ts10_v0.015_den.txt')
+varNames = c('Var 1',  'Var 2', 'Var 3', 'Var 1+2', 'Var 1+3')
+inData = list()
+seq_plot = c(1, 2, 3, 4, 5)
+for (i in seq_along(fnames) ) {
+  
+  tmpCsv = read.csv(fnames[i], skip=0, sep='\t')
+  tmpCsv['model'] = varNames[i]
+  tmpCsv['nrpar']= nrpar[i]
+  inData = rbind(inData, tmpCsv)
+}
+
+inData$model = factor(inData$model, levels = varNames[seq_plot])
+
+
+# ----
+
+pint_inter <- ggplot() + geom_bar(data=denData, stat = 'identity', width = 1.5, aes(time, int_avg, fill = 'red')) + 
+  geom_line(data = inData, size = 0.8, aes(time, inter_i, group = model,  colour = model)) + ylab(expression(paste("Intermediate density (pores/", mu, m^2, ")")))
+
+pint_mature <- ggplot() + geom_bar(data=denData, stat = 'identity', width = 2, aes(time, mat_avg, fill = '#1E477E')) + 
+  geom_line(data = inData, size = 0.8, aes(time, mature_i, group = model, colour = model))+ ylab(expression(paste("Mature density (pores/", mu, m^2, ")")))
+pint_inter <- addOpt(pint_inter) + scale_fill_manual(values = c('red'))
+pint_mature <- addOpt(pint_mature) + scale_fill_manual(values = c('#1E477E'))
+
+pint_inter
+pint_mature
+
+
+if (Sys.info()['sysname'] == 'Darwin'){
+  setwd('/Users/toni/Dropbox/NPCMaturation/results/emdata/figures')
+} else {
+  setwd('C:\\Users\\toni\\Dropbox\\NPCMaturation\\results\\emdata\\figures')
+}
+ggsave(filename="prodVariants_inter_inner_den.pdf", plot=pint_inter, width = 71, height = 44, units = 'mm')
+ggsave(filename="prodVariants_mature_inner_den.pdf", plot=pint_mature, width = 71, height = 44, units = 'mm')
+

rcode/prodVariants_den.R

+library("ggplot2")
+# ---- 
+
+if (Sys.info()['sysname'] == 'Darwin'){
+setwd('/Users/toni/Dropbox/NPCMaturation/results/emdata/delay')
+} else {
+  setwd('C:\\Users\\toni\\Dropbox\\NPCMaturation\\results\\emdata\\delay')
+}
+
+fnames = c('delayedMaturation_v0_ts10_den.txt',
+           'delayedMaturation_noPrecursor_ts10_den.txt', 
+           'delayedMaturationExponentialV_noPrecursor_ts10_v0.015_den.txt',
+           'delayedMaturation_v0.015_ts10_den.txt',
+           'delayedMaturationExponentialV_ts10_v0.015_den.txt')
+

rcode/prodVariants_reduced.R

+# ----
+
+
+library("ggplot2")
+
+if (Sys.info()['sysname'] == 'Darwin'){
+  indatadir <-'/Users/toni/Dropbox/NPCMaturation/expdata/emdata'
+  indir <- '/Users/toni/Dropbox/NPCMaturation/results/emdata/delay'
+  outdir <- '/Users/toni/Dropbox/NPCMaturation/results/emdata/figures'
+} else {
+  indatadir <- 'C:\\Users\\toni\\Dropbox\\NPCMaturation\\expdata\\emdata'
+  indir <- 'C:\\Users\\toni\\Dropbox\\NPCMaturation\\results\\emdata\\delay'
+  outdir <- 'C:\\Users\\toni\\Dropbox\\NPCMaturation\\results\\emdata\\figures'
+}
+
+
+setwd(indir)
+
+fnames = c('delayedMaturation_noPrecursor_ts10.txt', 
+           'delayedMaturationExponentialV_noPrecursor_ts10_v0.015.txt',            
+           'delayedMaturation_v0.015_ts10.txt')
+
+varNames = c('Var 1',  'Var 2', 'Var 3')
+inData = list()
+seq_plot = c(1, 2, 3)
+for (i in seq_along(fnames) ) {
+  
+  tmpCsv = read.csv(fnames[i], skip=6, sep='\t')
+  tmpCsv['model'] = varNames[i]
+  idx = which.min(tmpCsv$norm)
+  inData = rbind(inData, tmpCsv[idx, c('tauM', 'kM', 'norm', 'model', 'nrpara')])
+}
+
+inData$model = factor(inData$model, levels = varNames[seq_plot])
+