library(ggplot2)

library(cowplot)
library(plyr)
library(scales)
library(gridExtra)
library(grid)
library(ggplotify)

palette <- c('end-to-end' = '#00e600', 'absent' = '#666666', 'partial' = '#ff0066')
dat <- read.table('output/statsFiles/all.tmerge.min2reads.vs.SIRVs.detection.stats.tsv', header=T, as.is=T, sep='\t')

dat <- subset(dat, seqTech=='ONT')



dat <- subset(dat, sizeFrac=='0+')

dat <- subset(dat, sampleRep=='BrainRep1')


dat$seqTech <- gsub('-', '\n', dat$seqTech)

dat$sampleRep <- gsub('byCapDesign_', '', dat$sampleRep)



horizCats <- length(unique(dat$capDesign)) * length(unique(dat$sampleRep))
vertCats <- length(unique(dat$seqTech))

wXyPlot = (horizCats * 0.9) +1.7
hXyPlot = (vertCats * 0.6) + 1.7

geom_textSize=1.4 
themeSize = (14/5) * geom_textSize
# https://stackoverflow.com/questions/25061822/ggplot-geom-text-font-size-control/25062509
lineSize=geom_textSize/8
minorLineSize=lineSize/2




plotBase <- "p <- ggplot(dat, aes(x=concentration, y=length, color=detectionStatus)) + geom_point(alpha=0.8, shape=18) +
coord_trans(x='log2') +
scale_color_manual(values=palette) +
xlab('SIRV molarity (fmol/uL)') +
ylab('SIRV length (nt)') +
theme(axis.text= element_text(size=themeSize*1.8), axis.ticks = element_line(size=lineSize), axis.line = element_line(colour = '#595959', size=lineSize), axis.title=element_text(size = themeSize*2), panel.grid.major = element_line(colour='#d9d9d9', size=lineSize),panel.grid.minor = element_line(colour='#e6e6e6', size=minorLineSize),panel.border = element_blank(),panel.background = element_blank(), strip.background = element_rect(colour='#737373',fill='white'), legend.key.size=unit(0.5,'line'), legend.title=element_text(size=themeSize*1.2), legend.text=element_text(size=themeSize), strip.text = element_text(size = themeSize)) + "


plotFacetXy <- parse(text =paste(plotBase, "facet_grid( seqTech ~ capDesign + sampleRep, scales='free_y')"))
plotFacetYx <- parse(text=paste(plotBase, "facet_grid( capDesign + sampleRep ~ seqTech, scales='free_y')"))

pXy <- eval(plotFacetXy)
pYx <- eval(plotFacetYx)

legend <- get_legend(pXy)

pXyNoLegend <- pXy + theme(legend.position='none')
pYxNoLegend <- pYx + theme(legend.position='none')

legendOnly <- grid.arrange(legend)
pXyGrob <- as.grob(pXy)
pYxGrob <- as.grob(pYx)
pXyNoLegendGrob <- as.grob(pXyNoLegend)
pYxNoLegendGrob <- as.grob(pYxNoLegend)


hLegendOnly <- convertUnit(sum(legend$heights), 'in', valueOnly=TRUE)
wLegendOnly <- convertUnit(sum(legend$widths), 'in', valueOnly=TRUE)


hYxPlot <- wXyPlot
wYxPlot <- hXyPlot 

hXyNoLegendPlot<- hXyPlot 
wXyNoLegendPlot<- wXyPlot - wLegendOnly

hYxNoLegendPlot<- hYxPlot
wYxNoLegendPlot<- wYxPlot - wLegendOnly


save_plot('output/plots/tmerge.vs.SIRVs.detection.stats/ONT/byCapDesign/ONT_byCapDesign_0+_BrainRep1.tmerge.min2reads.vs.SIRVs.detection.stats.legendOnly.png', legendOnly, base_width=wLegendOnly, base_height=hLegendOnly)
save_plot('output/plots/tmerge.vs.SIRVs.detection.stats/ONT/byCapDesign/ONT_byCapDesign_0+_BrainRep1.tmerge.min2reads.vs.SIRVs.detection.stats.xy.wLegend.png', pXy, base_width=wXyPlot, base_height=hXyPlot)

save_plot('output/plots/tmerge.vs.SIRVs.detection.stats/ONT/byCapDesign/ONT_byCapDesign_0+_BrainRep1.tmerge.min2reads.vs.SIRVs.detection.stats.xy.woLegend.png', pXyNoLegend, base_width=wXyNoLegendPlot, base_height=hXyNoLegendPlot)
save_plot('output/plots/tmerge.vs.SIRVs.detection.stats/ONT/byCapDesign/ONT_byCapDesign_0+_BrainRep1.tmerge.min2reads.vs.SIRVs.detection.stats.yx.wLegend.png', pYx, base_width=wYxPlot, base_height=hYxPlot)

save_plot('output/plots/tmerge.vs.SIRVs.detection.stats/ONT/byCapDesign/ONT_byCapDesign_0+_BrainRep1.tmerge.min2reads.vs.SIRVs.detection.stats.yx.woLegend.png', pYxNoLegend, base_width=wYxNoLegendPlot, base_height=hYxNoLegendPlot)