library(rpart)

target.lrn <- read.table("../lrn/num/472.dat",header=T,colClasses="numeric")
target.val <- read.table("../val/num/472.dat",header=T,colClasses="numeric")
target.tst <- read.table("../tst/num/472.dat",header=T,colClasses="numeric")

 
y.lrn <- target.lrn[,1]
y.val <- target.val[,1]
y.tst <- target.tst[,1]
y     <- c(y.lrn,y.val,y.tst)

target.lrn <- read.table("../lrn/num/471.dat",header=T,colClasses="numeric")
target.val <- read.table("../val/num/471.dat",header=T,colClasses="numeric")
target.tst <- read.table("../tst/num/471.dat",header=T,colClasses="numeric")
 
b.lrn <- target.lrn[,1]
b.val <- target.val[,1]
b.tst <- target.tst[,1]
b     <- c(b.lrn,b.val,b.tst)

n.lrn <- length(y.lrn)
n.val <- length(y.val)
n.tst <- length(y.tst)
n     <- length(y)

rm(target.lrn,target.val,target.tst)

wts <- mat.or.vec(n,1) ; for (i in 1:n.lrn) wts[i]=1
idx.lrn <- 1:n.lrn
idx.val <- (n.lrn+1):(n.lrn+n.val)
idx.tst <- (n.lrn+n.val+1):n

mod <- read.table("../cty_mod.txt",
         header=F,colClasses="character",col.names=c("file","feature","type"))

n.mod <- length(mod$file)

first.time <- TRUE

for (i in 1:n.mod) {

  fn.lrn <- paste("../lrn/",mod$type[i],"/",mod$file[i],".dat",sep="")
  fn.val <- paste("../val/",mod$type[i],"/",mod$file[i],".dat",sep="")
  fn.tst <- paste("../tst/",mod$type[i],"/",mod$file[i],".dat",sep="")
  print(mod$feature[i])

  if (mod$type[i]=="chr") {

    f.lrn <- read.table(fn.lrn,
               header=T,colClasses="character",blank.lines.skip=F)
    f.val <- read.table(fn.val,
               header=T,colClasses="character",blank.lines.skip=F)
    f.tst <- read.table(fn.tst,
               header=T,colClasses="character",blank.lines.skip=F)

    f <- c(f.lrn[,1],f.val[,1],f.tst[,1])

    if (mod$feature[i]=="STATE") {
      f[f=="AS"|f=="DC"|f=="DE"|f=="MA"|f=="ME"|f=="NH"] <- "S1"
      f[f=="OH"|f=="RI"|f=="VI"|f=="WV"]                 <- "S1"
      f[f=="AA"|f=="AE"|f=="AP"|f=="CT"|f=="GU"|f=="MD"] <- "S2"
      f[f=="NJ"|f=="NY"|f=="PA"|f=="VA"|f=="VT"|f=="WY"] <- "S2"
      f[f=="AK"|f=="UT"|f=="MS"]                         <- "S3"
      f[f=="NE"|f=="ND"]                                 <- "S4"
      f[f=="SD"|f=="SC"]                                 <- "S5"
    } 
    
    f <- as.factor(f)

    n.lev <- nlevels(f)
    f.name <- levels(f) 
    if(n.lev==2) f.name <- c(mod$feature[i],mod$feature[i])
    print(paste("  nlevels = ",n.lev))

    yave <- mat.or.vec(n.lev,1)
    bave <- mat.or.vec(n.lev,1)
    xave <- 1:n.lev
    fc.lrn <- codes(f[idx.lrn])
    for (j in (1:n.lev)) {
      yave[j] <- mean(y.lrn[fc.lrn==j])
      bave[j] <- mean(b.lrn[fc.lrn==j])
    }

    feature <- mod$feature[i]
    filename <- paste("cty_target_",feature,".eps",sep="")
    postscript(file=filename) 

    plot(x=c(xave,xave),y=c(yave,bave),ylab="target",xlab=feature,type="n")
      points(x=xave,y=bave,col="black")
      points(x=xave,y=yave,col="red")
      lines(x=xave,y=bave,col="black")
      lines(x=xave,y=yave,col="red")

    dev.off()

    rm(yave, bave, f.lrn)

    f <- model.matrix(y ~ f - 1)      # Note: Intercept removed.
    f <- f[,2:n.lev]                  # Note: First dummy deleted.
    f.name <- f.name[2:n.lev]         # Note: First name deleted.

  } else {
    
    f.lrn<-read.table(fn.lrn,
             header=T,colClasses="numeric",blank.lines.skip=F)
    f.val<-read.table(fn.val,
             header=T,colClasses="numeric",blank.lines.skip=F)
    f.tst<-read.table(fn.tst,
             header=T,colClasses="numeric",blank.lines.skip=F)

    f <- c(f.lrn[,1],f.val[,1],f.tst[,1])

    f[is.na(f)] <- 0

    f.name <- mod$feature[i]

    if (mod$feature[i]=="DOB") { 
      d <- f ; d[d>0] <- 1         # Note: Dummy for missing DOB 
      f <- cbind(d,f,f^2)          # Note: Quadratic term added to DOB.
      rm(d)
      f.name <- c("DOB.0","DOB.1","DOB.2")
    }
  }

  if (first.time) {
    X <- f
    X.names <- f.name
    first.time <- FALSE
  } else {
    X <- cbind(prev.X,f)
    X.names <- c(prev.X.names,f.name)
  }

  prev.X <- X
  prev.X.names <- X.names

}

LAST.by.PEP <- X[,1]*X[,2]
print("LAST.by.PEP")

X <- cbind(prev.X,LAST.by.PEP)
X.names <- c(prev.X.names,"LAST.by.PEP")

rm(prev.X,prev.X.names)
rm(f.lrn,f.val,f)

dimnames(X) <- list(NULL,X.names)

y.fit <- lm(y~X,weights=wts)       # Note: Validation sample not in fit.

yhat <- y.fit$fitted.values

ehat <- y - mean(y)
mse.nul <- mean(ehat[idx.lrn]^2) 

ehat <- y.fit$residuals
mse.lrn <- mean(ehat[idx.lrn]^2)
mse.val <- mean(ehat[idx.val]^2)
mse.tst <- mean(ehat[idx.tst]^2)

print(paste("  mse.nul = ",mse.nul))
print(paste("  mse.lrn = ",mse.lrn))
print(paste("  mse.val = ",mse.val))
print(paste("  mse.tst = ",mse.tst))

y    <- y[idx.lrn]
X    <- X[idx.lrn,]
yhat <- yhat[idx.lrn]
ehat <- ehat[idx.lrn]

y0    <- y[y<=0] 
X0    <- X[y<=0,]
yhat0 <- yhat[y<=0] 
ehat0 <- ehat[y<=0] 

idx <- seq(1,length(yhat0),length=sum(b[idx.lrn]))

y0    <- y0[idx]
X0    <- X0[idx,]
yhat0 <- yhat0[idx]
ehat0 <- ehat0[idx]

y1    <- y[y>0] 
X1    <- X[y>0,]
yhat1 <- yhat[y>0] 
ehat1 <- ehat[y>0] 

source("psopts.r")
postscript(file="cty_ehat_yhat.eps")

plot(x=c(yhat0,yhat1),y=c(ehat0,ehat1),ylab="ehat=y-yhat",xlab="yhat",type="n")
  points(x=yhat0,y=ehat0,col="black")
  points(x=yhat1,y=ehat1,col="red")

dev.off()

numeric <- c(1,37,40,41,42,43)

for (i in numeric) {
  feature <- dimnames(X)[[2]][i]
  filename <- paste("cty_target_",feature,".eps",sep="")
  postscript(file=filename) 

  plot(x=c(X0[,i],X1[,i]),y=c(y0,y1),ylab="target",xlab=feature,type="n")
#   points(x=X0[,i],y=y0,col="black")
    points(x=X1[,i],y=y1,col="red")

  dev.off()
}