gistfile1.r

#Fix libraries
need<-c("jpeg","tcltk2","zoo") #needed libraries
ins<-installed.packages()[,1] #find out which libs are installed
(Get<-need[which(is.na(match(need,ins)))])
if(length(Get)>0){install.packages(Get)} #install needed libs
eval(parse(text=paste("library(",need,")")))#load libraries


#load imagefile
jpegfile<-tk_choose.files(caption="JPEG FILE")
(outfile<-paste(unlist(strsplit(jpegfile,"\\."))[1],".txt",sep=""))

#digitize functions
ReadAndCal = function(fname)
{
  ReadImg(fname)
  calpoints <- locator(n=4,type='p',pch=4,col='blue',lwd=2)
  return(calpoints)
}

ReadImg = function(fname)
{
  img <- readJPEG(fname)
  op <- par(mar=c(0,0,0,0))
  on.exit(par(op))
  plot.new()
  rasterImage(img,0,0,1,1)
}

DigitData = function(col='red',type='p',...)
{
  type <- ifelse(type=='b','o',type)
  type <- ifelse(type%in%c('l','o','p'),type,'p')
  locator(type=type,col=col,...)
}

Calibrate = function(data,calpoints,x1,x2,y1,y2)
{
  x 		<- calpoints$x[c(1,2)]
  y 		<- calpoints$y[c(3,4)]
  
  cx <- lm(formula = c(x1,x2) ~ c(x))$coeff
  cy <- lm(formula = c(y1,y2) ~ c(y))$coeff
  
  data$x <- data$x*cx[2]+cx[1]
  data$y <- data$y*cy[2]+cy[1]
  
  return(as.data.frame(data))
}

#digitize a graph
(cal = ReadAndCal(jpegfile))#This opens the jpeg in a plotting window and lets you define points on the x and y axes. You must start by clicking on the left-most x-axis point, then the right-most axis point, followed by the lower y-axis point and finally the upper y-axis point. You don’t need to choose the end points of the axis, only two points on the axis that you know the x or y value for. As you click on each of the 4 points, the coordinates are saved in the object cal.
(data.points = DigitData(col = 'red'))#You return to the figure window, and now you can click on each of the data points you’re interested in retrieving values for. The function will place a dot (colored red in this case) over each point you click on, and the raw x,y coordinates of that point will be saved to the data.points list. When you’re finished clicking points, you need to hit stop/Finish or right-click to stop the data point collection.
df = Calibrate(data.points, cal, 37257, 37287, 268, 276)#Finally, you need to convert those raw x,y coordinates into the same scale as the original graph. You do this by calling the Calibrate function and feeding it your data.point list, the cal list that contains your 4 control points from the first step, and then 4 numeric values that represent the 4 original points you clicked on the x and y axes. These values should be in the original scale of the figure (i.e. read the values off the graph’s tick marks).

#some manual editing of values at end/known points
df<-df[order(df$x),]
df[1,1]<-37257
df[nrow(df),1]<-37287
plot(df$x,df$y,type="l")

#Optiona
#interpolate at user defined points
fxn<-approxfun(df)
xnew<-seq(37257,37287,1/24)
ynew<-fxn(xnew)
dato<-as.POSIXct(xnew * (60*60*24), origin="1899-12-30", tz="GMT") #my known x-points are dates
newdf<-data.frame(dato,y=ynew)
plot(newdf,las=2,type="l")
write.table(newdf,file=outfile,sep=",",quote=FALSE)