PreMean <- matrix(ncol=3, nrow=2, byrow=TRUE)
PreMean[1, ] <- c(1, -1, 0)
PreMean[2, ] <- c(-0.8, 0, 0.8)
PreZeta <- c(0.4, 1.8, 1)

GenExpression <- function(x, cancertype, sdv) {
    rnorm(1, PreMean[x,cancertype], sdv)
}

GenSurvival <- function(funtype, cancertype, x1, x2, cancerprob) {
#    rm(.Random.seed)
	 S <- runif(1, 0, 1)
	 
    if(cancertype==1) {  h <- 0.3*x1 + 0.4*x2 - 0.1  }
    if(cancertype==2) {  h <- 0.5*(x1-x2)^2 + 1      }
	 if(cancertype==3) {  h <- 0.006*x1^3 - 0.2*x2    }
	 
	 if(funtype=="1") {  -(log(S)/exp(-h))  }
	 
	 #survival function is Weibull
	 exp((-log(S)/exp(-h))^(1/PreZeta[cancertype]))
}

patientProfile <- matrix(nrow=50, ncol=3000, byrow=TRUE);
patientCancertype <- sample(c(1, 2, 3), 50, TRUE, c(0.3, 0.4, 0.3));
patientT <- c();
patientZ <- c();
for(i in 1:50) {

	                 patientProfile[i,1] <- GenExpression(1, patientCancertype[i], sqrt(0.3));

					     patientProfile[i,2] <- GenExpression(2, patientCancertype[i], sqrt(0.3));

  					     patientProfile[i,3:3000] <- rnorm(3000-2, 0, 1);

						  failureTime <- GenSurvival(1, patientCancertype[i], patientProfile[i,1],patientProfile[i, 2], c(0.3, 0.4, 0.3));

						  censorTime <- runif(1, 20, 50);

						  if(failureTime > censorTime) { patientT[i] <- failureTime; z <- 0;}

						  else { patientT[i] <- censorTime; z <- 1; }

						  write.table(patientProfile[i,], file="./temp/ec1afd6712a87a6b9880f15259c0b608.R.profile", quote=FALSE, col.names=FALSE, row.names=FALSE, sep="\t");

					 }