selecting from a dataset using set probabilities in r - r

Question

I am running some simulations for a selection experiment I am doing.
As part of this, I want to select from a dataset I've already made using probabilities to simulate selection.
I start by making an initial population using starting frequencies where the probability of getting a 1 is 0.25, a 2 is 0.5 and a 3 is 0.25. 1,2 and 3 represent the 3 different genotypes.
N <- 400
my_prob = c(0.25,0.5,0.25)
N1=sample(c(1:3), N, replace= TRUE, prob=my_prob)
P1 <-data.frame(N1)
I now want to simulate selection in my population where one homozygote is selected against and there is partial selection against heterozygotes so probabilities of ((1-s)^2, (1-s), 1) where s=0.2 in this example.
Initially I was sampling each group individually using the sample_frac() function and then recombing the datasets.
s <- 0.2
S1homo<- filter(P1, N1==1) %>%
sample_frac((1-s)^2, replace= FALSE)
S1hetero <-filter(P1, N1==2) %>%
sample_frac((1-s), replace= FALSE)
S1others <-filter(P1, N1==3)
S1 <- rbind(S1homo, S1hetero, S1others)
The problem with this is there isn't any variability in the numbers it returns which is unrealisitic, for example S1homo will always return exactly 64% of the 1 values when I set s=0.2 whereas in my initial populations there is some variability in the numbers you get for each value.
So I was wondering if there is a way to select from my P1 population using the set probabilities of ((1-s)^2,(1-s), 1) for the different genotypes so that I don't always get the exact same numbers being returned for each group being selected against.
I tried doing this using the sample() function I used before but I couldn't get it to work.
# sel is done to give the total number of values there will be in the new population when times by N
sel <-((1-s)^2 + 2*(1-s)+1)/4
S1 <-sample(P1, N*sel, replace=FALSE, prob=c((1-s)^2,(1-s),1))
Error in sample.int(length(x), size, replace, prob) :
cannot take a sample larger than the population when 'replace = FALSE'

Answer 1

I am not 100% sure what you are trying to do, but if you want (1-s)^2 to be the probability that a randomly chosen element is included in the sample, rather than the exact percentage chosen, you can use sample_n rather than sample_frac, with an n which is randomly chosen to reflect that rate:
S1homo<- filter(P1, N1==1) %>%
sample_n(rbinom(1,sum(N1==1),(1-s)^2))
Using rbinom like that is perhaps a bit indirect, but I don't see another way to easily do it with %>%.