#regular mode
chassis.p <- 0.0833
neuro.p <- 0.0769
system.p <- 0.0564
bp.p <- 0.0564


n <- 10000
runs <- rep(NA,n)
for (i in 1:n){
	parts <- rep(NA,4)
	t <- 1
	while (sum(is.na(parts))>0) {
		x1 <- replicate(2,sample(2,1,prob=c(chassis.p,(1-chassis.p))))
		if (sum(x1==1)>0) parts[1] = 1
		x2 <- sample(2,1,prob=c(neuro.p,(1-neuro.p)))
		if (x2==1) parts[2] =1

		x3 <- sample(3,1,prob=c(system.p,bp.p,(1-system.p-bp.p)))

		if (x3==1){
			parts[3] <- 1
		} else if (x3== 2)
			parts[4] <- 1
		t <- t+1
	}
	runs[i] <- t
}

#elite mode
#rotation A
#khora chassis, lato receiver
rot.A.prob <- c(0.0316, 0.0201, 1- (0.0316+0.0201))

#Khora Neurop, Braton Barrel, Braton Receiver, Lato BP
rot.B.prob <- c(0.0369, 0.0369, 0.0369, 0.0201, 1- (0.0369+ 0.0369+ 0.0369+ 0.0201))

#khora system,khora bp, braton stock, braton bp, lato barrel,
rot.C.prob<-c(0.0316,0.0316,0.0316,0.0201,0.0316)
rot.C.prob <- c(rot.C.prob, 1-sum(rot.C.prob))


n <- 10000
runs.khora <- runs.braton <- runs.lato <- rep(NA,n)
for (i in 1:n){
	khora <- braton <- rep(NA,4)
	lato <- rep(NA,3)
	t <- 1
	condition = rep(0,3)
	while ( prod(condition) ==0 ) {
		x1 <- replicate(2,sample(length(rot.a.prob),1,prob=rot.A.prob))
		if (sum(x1==1)>0) {
			khora[1] <- 1
		} else if (sum(x1==2) >0) {
			lato[1] <- 1
		}

		x2 <- sample(length(rot.b.prob),1,prob=rot.B.prob)
		if (x2==1) {
			khora[2] <- 1
		} else if (x2==2){
			braton[1] <- 1
		} else if (x2==3){
			braton[2] <- 1
		} else if (x2==4){
			lato[2] <- 1
		}

		x3 <- sample(length(rot.C.prob),1,prob=rot.C.prob)

		if (x3==1) {
			khora[3] <- 1
		} else if (x3==2){
			khora[4] <- 1
		} else if (x3==3){
			braton[3] <- 1
		} else if (x3==4){
			braton[4] <- 1
		} else if (x3==5) {
			lato[3] <- 1
		}


		if (condition[1] ==0 & sum(is.na(khora))==0) {
			condition[1]=1
			runs.khora[i] <- t
		}

		if (condition[2] ==0 & sum(is.na(braton)) == 0) {
			condition[2]=1
			runs.braton[i] <- t
		}

		if (condition[3] ==0 & sum(is.na(lato)) == 0) {
			condition[3]=1
			runs.lato[i] <- t
		}

		t <- t+1
	}
}


#nidus
p <- 0.1429

prob <- c(p,p,p,1-3*p)

N <- 10000
run.nidus <- rep(NA,N)
for (i in 1:N) {
	condition <- 0
	full.set <- 1:3
	t <- 1
	while (condition == 0){
		new <- sample(4,1,prob=prob)
		if (new %in% full.set) {
			full.set <- setdiff(full.set, new)
		}

		if (length(full.set)==0)
			condition <- 1
		t <- t +1
	}
	run.nidus[i]<- t-1
}