Mutpars <- matrix(c(mutpars.locus1, mutpars.locus2, mutpars. Points(1L:fit$pars$G, fit$expected_pop_sizes, type = 'l', col = 'red')įit_fixed <- fwsim_fixed(G = 100L, H0 = H0, N0 = 10000L, mutmodel = mutmodel) Ylim = range(range(fit$pop_sizes), range(fit$expected_pop_sizes))) Plot(1L:fit$pars$G, fit$pop_sizes, type = 'l', Xtabs(N ~ DYS19 + DYS389I, fit$population) Mutmodel <- init_mutmodel(modeltype = 1L, Whether to print trace of the evolution (more verbose than progress).Įnsures that every generation has at least one child implemented by getting Poisson(α*M) + 1 children.Ī number specifying the plot (currently only 1: the actual population sizes vs the expected sizes).įit <- fwsim(G = 100L, H0 = c(0L, 0L, 0L), N0 = 10000L, Whether to print progress of the evolution. Else, a vector of the generation numbers to save. NULL means that no intermediate population will be saved. To make alleles modulus 2 to immitate SNPs. If length 1, the value is reused in creating a vector of length G. Vector of length 1 or G of growth factors (1 correspond to expected constant population size). Alternatively, a numeric vector of length r of mutation probabilities (this will create a stepwise mutation model with r loci divide the mutation probabilities evenly between upwards and downwards mutation). sum(N0) is the size of initial population.Ī mutmodel object created with init_mutmodel. The i'th element is the count of the haplotype H0. to make alleles modulus 2 to immitate SNPs. The number of loci is the length or number of columns of H0.Ĭount of the H0 haplotypes. fwsim(G, H0, N0, mutmodel, alpha 1.0, SNP FALSE, savegenerations NULL, progress TRUE, trace FALSE. Must be a vector or matrix (if more than one initial haplotype). Number of generations to evolve (integer, remember postfix L).

Let it go fwsim