Models with different parameters are run using the same seed

[GForb]

Thanks for developing this package - I really like the way it structures simulations.

I've been running some simulations and have noticed some unexpected correlations in my results. I've traced this to the following issue:

Expected behavior: Data generated from a model with different parameter values will be independent

Observed behaviour: Some data generated from models with different parameters is perfectly correlated

Example

library(simulator)

make_data <- function(n_covariates) {
  new_model(name = "test",
            label = paste0("n_covariates = ", n_covariates),
            params = list(n_covariates = n_covariates),
            simulate = function(n_covariates, nsim) {
            data <- vector(mode = "list", length = nsim)
              for(i in 1:nsim){
              x <- vector(mode = "list", length = n_covariates)
              for(j in 1:n_covariates){
                x[[j]]<-  rnorm(1000)
              }
            data[[i]] <- x
            }
            return(data)
            })
}

sim <- new_simulation(name = "correlated_draws",
               label = "data from different models is the same") %>%
  generate_model(make_data, seed = 1234,
               n_covariates = list(1,2,3,4,5,6,7,8,9,10),
               vary_along = c("n_covariates")) %>% 
  simulate_from_model(nsim = 2) 
  
x1_model1.1 <- draws(sim)[[1]]@draws$r1.1[[1]]
x1_model2.1 <- draws(sim)[[2]]@draws$r1.1[[1]]

cor(x1_model1.1, x1_model2.1) # This is 1, I'd expect this to be zero as different draws should be independent

I believe this issue is caused by generate_model passing the same seed to generate_model_single for each different value of the parameters being varied along. This even happens if no seed is set as the default is for a seed of 123 to be used. A work around is to use seed = NULL in generate model.