[R] Create a colour scale for different data sets

BARLAS Marios 247554 Marios.BARLAS at cea.fr
Sun Jul 24 23:11:45 CEST 2016


Hello Every1, 

I'm working on analysing some data and I want to make some cartography maps. 

Since I treat data in batch, I need to have a common reference colour scale for all the datasets I need to plot. This is important otherwise it becomes hard to quickly assert visually changes from one experiment to another if the colour scale resets all the time. 

So I though of finding the min and max value of my data values and create a colour scale versus that. 

Nonetheless the code does not work as intended, 
I realised my code was not easily reproducible so I send some with initialized values to help :)

Here is a part of the code (reproducible):

meas.data <- c( 2.38762e+02, 2.54709e+02, 2.45204e+02, 2.32134e+02, 2.28587e+02, 2.31493e+02, 2.34867e+02, 2.41127e+02, 2.76113e+02, 2.57450e+02, 2.23804e+02, 2.39064e+02, 2.28636e+02, 2.37417e+02, 2.53686e+02, 2.45593e+02, 2.29043e+02, 9.25698e+10, 2.31001e+02, 2.36022e+02, 2.67654e+02, 2.50275e+02, 2.72641e+02, 2.24342e+02, 9.36361e+10, 2.28610e+02, 2.20854e+02, 2.37955e+02, 2.58944e+02, 2.68088e+02, 2.36356e+02, 2.52802e+02, 2.32976e+02, 2.39819e+02, 2.48820e+02, 2.80206e+02, 2.63318e+02, 2.43431e+02, 2.83426e+02, 2.48557e+02, 2.45493e+02, 2.53264e+02, 2.51834e+02, 2.34187e+02, 2.56326e+02, 2.96419e+02, 2.52473e+02, 2.68144e+02, 2.40842e+02)

die.codes <- c("X5_Y4"  , "X5_Y6" ,  "X5_Y8" ,  "X5_Y9", "X5_Y10", "X5_Y11", "X5_Y12", "X7_Y4", "X7_Y6", "X7_Y8", "X7_Y9", "X7_Y10", "X7_Y11", "X7_Y12", "X9_Y4", "X9_Y6", "X9_Y8", "X9_Y9", "X9_Y10", "X9_Y11", "X9_Y12", "X11_Y4", "X11_Y6", "X11_Y8", "X11_Y9", "X11_Y10", "X11_Y11", "X11_Y12", "X13_Y4", "X13_Y6", "X13_Y8", "X13_Y9",  "X13_Y10", "X13_Y11", "X13_Y12", "X15_Y4",  "X15_Y6",  "X15_Y8",  "X15_Y9",  "X15_Y10", "X15_Y11", "X15_Y12", "X17_Y4",  "X17_Y6", "X17_Y8" ,"X17_Y9",  "X17_Y10", "X17_Y11", "X17_Y12")
dies.x.total <- 17
dies.y.total <- 15
r.max <- 1e13



    dies.in.wafer <- expand.grid(X=as.numeric(1:dies.x.total), Y=as.numeric(1:dies.y.total))
      # This procedure can be used to generate the patterns for the test labels as well. To be Tested and verified.
      # Catch all numerical values in the string
      # 4 Is the column for which the names of the die coordinates are stored
      dies.tested <-strsplit(die.codes, "[^[:digit:]]")
      # Convert to Numeric
      dies.tested<- lapply(dies.tested,as.numeric )

      dies.tested<- data.frame((matrix(unlist(dies.tested), ncol = dim.data.frame(dies.tested[[1]])[2], byrow = TRUE)))
      # Drop all Columns containing NAs
      dies.tested <- dies.tested[colSums(!is.na(dies.tested)) > 0]
      dies.tested$test.order <- as.factor(1:dim.data.frame(dies.tested)[1])
      colnames(dies.tested)  <- c("X","Y","Order")

      dies.in.wafer.x <- dies.in.wafer$X
      dies.in.wafer.y <- dies.in.wafer$Y
      dies.in.wafer.tested <- rep(F, length = dim.data.frame(dies.in.wafer)[1])
      dies.in.wafer.Order = rep(NA, length = dim.data.frame(dies.in.wafer)[1])
      dies.in.wafer.r     = rep(NA, length = dim.data.frame(dies.in.wafer)[1])
      dies.in.wafer.op    = rep(NA, length = dim.data.frame(dies.in.wafer)[1])

      dies.tested.x <- dies.tested$X
      dies.tested.y <- dies.tested$Y
      dies.tested.order<- dies.tested$Order

      dim.dies.in.wafer <- dim(dies.in.wafer)[1]
      for(ixx in seq(1, dim(dies.tested)[1], by=1) ){
        for (inn in seq(1, dim.dies.in.wafer, by=1) ){
          if (dies.in.wafer.tested[inn]==F) {
            dies.in.wafer.tested[inn] <- dies.tested.x[ixx] == dies.in.wafer.x[inn] & dies.tested.y[ixx] == dies.in.wafer.y[inn]
            if (dies.in.wafer.tested[inn]==T) {
              dies.in.wafer.Order[inn]  <- dies.tested$Order[ixx]
              dies.in.wafer.r[inn]      <- meas.data
              dies.in.wafer.op[inn]     <- op.type 
            }
          }
        }
      }
      dies.in.wafer$tested  <- dies.in.wafer.tested
      dies.in.wafer$Order   <- dies.in.wafer.Order
      dies.in.wafer$op.type <- as.factor(dies.in.wafer.op)
      dies.in.wafer$R       <- dies.in.wafer.r


      r.colour.map <- c("lightgreen", "darkgreen", "yellow","red" )
      r.range.breaks <- c(0, 1.5e4, 1e5, r.max )/r.max  
      r.breaks.guide <- c(0, 1.5e4, 1e5, r.max ) 
      g.map <- ggplot(dies.in.wafer, aes(X, Y)) +
        geom_raster(aes(fill = R))+
        scale_fill_gradientn(name="R", na.value = "grey50", colours = r.colour.map, values = r.range.breaks, breaks=r.breaks.guide, limits=c(0,r.max) )
      g.map


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