sim.metapopgen.dioecious.multilocus <- function(init.par,
sigma_F, sigma_M,
phi_F, phi_M,
fec.distr_F = "poisson", fec.distr_M = "poisson",
migration = "forward", migr,
delta.prop = NULL, delta.ad = NULL,
recr.dd="settlers",
T_max,
save.res = F, save.res.T = seq(1:T_max),
output.var = "N",
verbose = F) {
# Reading basic variables
m <- init.par$m # Number of genotypes
meiosis_matrix <- init.par$meiosis_matrix # Meiosis matrix
mat_geno_to_index_mapping <- init.par$mat_geno_to_index_mapping # Mapping of combinations of gametotypes to genotypes
if (is.null(mat_geno_to_index_mapping)) mat_geno_to_index_mapping <- init.par$index_matr # This is for gamete-based representation
l <- dim(meiosis_matrix)[1] # Number of multilocus gametotypes
n <- init.par$n # Number of demes
z <- init.par$z # Number of age-classes
kappa0 <- init.par$kappa0 # Carrying capacity
N1_F <- init.par$N1_F # Initial composition
N1_M <- init.par$N1_M # Initial composition
# If only one age-class and recr.dd=="adults", gives an error
if (z == 1 & recr.dd == "adults") {
stop("Detected only one age class (z=1) and recruitment probability dependent on adult density (recr.dd == 'adults'). This combination is not supported. Use recr.dd == 'settlers' instead.")
}
# Check fec.distr_F and fec.distr_M
if(!fec.distr_F %in% c("fixed","poisson")) stop(paste("Unknown parameter value for fec.distr_F:",fec.distr_F))
if(!fec.distr_M %in% c("fixed","poisson")) stop(paste("Unknown parameter value for fec.distr_M:",fec.distr_M))
# Check output.var
for (i.var in 1 : length(output.var)) {
if(!output.var[i.var] %in% c("N","Nprime","Nprimeprime","L","S")) stop(paste0("Unknown variable in output.var:",output.var[i.var]))
}
# Read output.var
output.N <- FALSE
output.Nprime <- FALSE
output.Nprimeprime <- FALSE
output.L <- FALSE
output.S <- FALSE
if("N" %in% output.var) output.N <- TRUE
if("Nprime" %in% output.var) output.Nprime <- TRUE
if("Nprimeprime" %in% output.var) output.Nprimeprime <- TRUE
if("L" %in% output.var) output.L <- TRUE
if("S" %in% output.var) output.S <- TRUE
if (migration == "backward" & output.L == TRUE) stop("Variable \"L\" is not calculated with backward migration. Correct argument \"output.var\"")
if (migration == "backward" & output.S == TRUE) stop("Variable \"S\" is not calculated with backward migration. Correct argument \"output.var\"")
# .............................Check the existence of dispersal matrices
if (is.null(delta.prop)) {
print("Setting propagule dispersal probability (delta.prop)")
delta.prop <- diag(1,n)
delta.prop <- array(delta.prop,c(n,n,T_max))
}
if (is.null(delta.ad)) {
print("Setting adult dispersal probability (delta.ad)")
delta.ad <- diag(1,n)
delta.ad <- array(delta.ad,c(n,n,z,T_max))
}
##########################################################################
# Check if input data are time-dependent or not; in case, augment them
##########################################################################
# Female Survival
if (is.na(dim(sigma_F)[4])) {
print("Augmenting sigma_F for time dimension")
sigma_F <- array(rep(sigma_F,T_max),c(m,n,z,T_max))
}
# Male Survival
if (is.na(dim(sigma_M)[4])) {
print("Augmenting sigma_M for time dimension")
sigma_M <- array(rep(sigma_M,T_max),c(m,n,z,T_max))
}
# Adult dispersal
if (is.na(dim(delta.ad)[3])) {
print("Augmenting delta.ad for age dimension")
delta.ad <- array(rep(delta.ad,z),c(n,n,z))
}
if (is.na(dim(delta.ad)[4])) {
print("Augmenting delta.ad for time dimension")
delta.ad <- array(rep(delta.ad,T_max),c(n,n,z,T_max))
}
# Female fecundity
if (is.na(dim(phi_F)[4])) {
print("Augmenting phi_F for time dimension")
phi_F <- array(rep(phi_F,T_max),c(m,n,z,T_max))
}
# Male fecundity
if (is.na(dim(phi_M)[4])) {
print("Augmenting phi_M for time dimension")
phi_M <- array(rep(phi_M,T_max),c(m,n,z,T_max))
}
# Propagule dispersal
if (migration == "forward") {
if (is.na(dim(delta.prop)[3])) {
print("Augmenting delta.prop for time dimension")
delta.prop <- array(rep(delta.prop,T_max),c(n,n,T_max))
}
}
# Carrying capacity
if (is.vector(kappa0)) {
print("Augmenting kappa0 for time dimension")
kappa0 <- array(rep(kappa0,T_max),c(n,T_max))
}
##########################################################################
# Initialize state variables
##########################################################################
print("Initializing variables...")
if (save.res){
N_F <- N1_F
N_M <- N1_M
dimnamesN1 <- dimnames(N1_F)
dimnamesN1noage <- dimnames(N1_F)[c(1,2)]
dimnames(N_F) <- dimnamesN1
dimnames(N_M) <- dimnamesN1
rm(N1_M, N1_F)
} else {
N_F <- array(NA, dim=c(m,n,z,T_max))
N_F[,,,1] <- N1_F
N_M <- array(NA, dim=c(m,n,z,T_max))
N_M[,,,1] <- N1_M
Nprime_F <- array(NA, dim=c(m,n,z,T_max))
Nprime_M <- array(NA, dim=c(m,n,z,T_max))
Nprimeprime_F <- array(0, dim=c(m,n,z,T_max))
Nprimeprime_M <- array(0, dim=c(m,n,z,T_max))
L_F <- array(NA, dim=c(m,n,T_max))
L_M <- array(NA, dim=c(m,n,T_max))
S_F <- array(0, dim=c(m,n,T_max))
S_M <- array(0, dim=c(m,n,T_max))
dimnamesN1 <- dimnames(N1_M)
dimnamesN1$time <- c(1:T_max)
dimnames(N_F) <- dimnamesN1
dimnames(N_M) <- dimnamesN1
dimnames(Nprime_F) <- dimnamesN1
dimnames(Nprime_M) <- dimnamesN1
dimnames(Nprimeprime_F) <- dimnamesN1
dimnames(Nprimeprime_M) <- dimnamesN1
dimnamesN1$age <- NULL
dimnames(L_F) <- dimnamesN1
dimnames(L_M) <- dimnamesN1
dimnames(S_F) <- dimnamesN1
dimnames(S_M) <- dimnamesN1
rm(N1_M, N1_F, dimnamesN1)
}
# Create output folder
if (save.res){
dir.res.name <- paste(getwd(),format(Sys.time(), "%Y-%b-%d-%H.%M.%S"),sep="/")
dir.create(dir.res.name)
}
##########################################################################
# Simulate metapopulation genetics
##########################################################################
print("Running simulation...")
for (t in 1 : T_max) {
if (t %% 10 == 0) print(t)
# If save.res, redefine variables
if (save.res) {
Nprime_F <- array(NA,dim=c(m,n,z))
Nprime_M <- array(NA,dim=c(m,n,z))
Nprimeprime_F <- array(0,dim=c(m,n,z))
Nprimeprime_M <- array(0,dim=c(m,n,z))
L_F <- array(NA,dim=c(m,n))
L_M <- array(NA,dim=c(m,n))
S_F <- array(0,dim=c(m,n))
S_M <- array(0,dim=c(m,n))
dimnames(Nprime_F) <- dimnamesN1
dimnames(Nprime_M) <- dimnamesN1
dimnames(Nprimeprime_F) <- dimnamesN1
dimnames(Nprimeprime_M) <- dimnamesN1
dimnames(L_F) <- dimnamesN1noage
dimnames(L_M) <- dimnamesN1noage
dimnames(S_F) <- dimnamesN1noage
dimnames(S_M) <- dimnamesN1noage
}
# Survival
if (verbose) cat("t =",t,"Apply survival function \n")
# If there is only one age-class, we must force the third dimension. What if only one year?
if (length(dim(sigma_M))==2) dim(sigma_M)[3] <- 1
if (length(dim(sigma_F))==2) dim(sigma_F)[3] <- 1
for (i in 1 : n) {
for (x in 1 : z) {
for (k in 1 : m) {
if (save.res){
Nprime_M[k,i,x] = surv(sigma_M[k,i,x,t], N_M[k,i,x])
Nprime_F[k,i,x] = surv(sigma_F[k,i,x,t], N_F[k,i,x])
} else {
Nprime_M[k,i,x,t] = surv(sigma_M[k,i,x,t], N_M[k,i,x,t])
Nprime_F[k,i,x,t] = surv(sigma_F[k,i,x,t], N_F[k,i,x,t])
}
}
}
}
# Adult dispersal
if (verbose) cat("t =",t,"Apply adult dispersal function \n")
for (i in 1 : n) {
for (x in 1 : z) {
for (k in 1 : m) {
if (save.res){
y = disp.ad(Nprime_F[k,i,x], delta.ad[,i,x,t])
Nprimeprime_F[k,,x] <- Nprimeprime_F[k,,x] + y[1:n]
y = disp.ad(Nprime_M[k,i,x], delta.ad[,i,x,t])
Nprimeprime_M[k,,x] <- Nprimeprime_M[k,,x] + y[1:n]
} else {
y = disp.ad(Nprime_F[k,i,x,t], delta.ad[,i,x,t])
Nprimeprime_F[k,,x,t] <- Nprimeprime_F[k,,x,t] + y[1:n]
y = disp.ad(Nprime_M[k,i,x,t], delta.ad[,i,x,t])
Nprimeprime_M[k,,x,t] <- Nprimeprime_M[k,,x,t] + y[1:n]
}
}
}
}
# Reproduction
if (migration == "forward") {
if (verbose) cat("t =",t,"Apply reproduction function \n")
# If there is only one age-class, we must force the third dimension
if (length(dim(phi_F))==2) dim(phi_F)[3] <- 1
if (length(dim(phi_M))==2) dim(phi_M)[3] <- 1
for (i in 1 : n) {
if (save.res) {
if (sum(Nprimeprime_F[,i,], Nprimeprime_M[,i,])==0) { # To save computing time. In the older version it was: if (sum(Nprime_M[,i,])==0 | sum(Nprime_F[,i,])==0)
L_M[,i] = 0
L_F[,i] = 0
next
} else {
LL <- repr(Nprimeprime_F[,i,], Nprimeprime_M[,i,], phi_F[,i,,t], phi_M[,i,,t], l, m, z,
meiosis_matrix, mat_geno_to_index_mapping, fec.distr_F, fec.distr_M, migration)
L_M[,i] <- LL[,1]
L_F[,i] <- LL[,2]
rm(LL)
}
} else {
if (sum(Nprimeprime_F[,i,,t], Nprimeprime_M[,i,,t])==0) { # To save computing time. In the older version it was: if (sum(Nprime_M[,i,])==0 | sum(Nprime_F[,i,])==0)
L_M[,i,t] = 0
L_F[,i,t] = 0
next
} else {
LL <- repr(Nprimeprime_F[,i,,t], Nprimeprime_M[,i,,t], phi_F[,i,,t], phi_M[,i,,t], l, m, z,
meiosis_matrix, mat_geno_to_index_mapping, fec.distr_F, fec.distr_M, migration)
L_M[,i,t] <- LL[,1]
L_F[,i,t] <- LL[,2]
}
}
}
}
# Propagule dispersal
if (migration == "forward") {
if (verbose) cat("t =",t,"Apply propagule dispersal function \n")
for (i in 1 : n) {
for (k in 1 : m) {
if (save.res) {
y = disp(L_M[k,i],delta.prop[,i,t])
S_M[k,] <- S_M[k,] + y[1:n]
y = disp(L_F[k,i],delta.prop[,i,t])
S_F[k,] <- S_F[k,] + y[1:n]
} else {
y = disp(L_M[k,i,t], delta.prop[,i,t])
S_M[k,,t] <- S_M[k,,t] + y[1:n]
y = disp(L_F[k,i,t], delta.prop[,i,t])
S_F[k,,t] <- S_F[k,,t] + y[1:n]
}
}
}
}
# Save results if save.res=T
if (save.res){
if (output.N) {
file.name <- paste0("N",t,".RData")
save(N_F, N_M, file=paste(dir.res.name,file.name,sep="/"))
}
if (output.Nprime) {
file.name <- paste0("Nprime",t,".RData")
save(Nprime_F, Nprime_M, file=paste(dir.res.name,file.name,sep="/"))
}
if (output.Nprimeprime) {
file.name <- paste0("Nprimeprime",t,".RData")
save(Nprimeprime_F, Nprimeprime_M, file=paste(dir.res.name,file.name,sep="/"))
}
if (output.L) {
file.name <- paste0("L",t,".RData")
save(L_F, L_M, file=paste(dir.res.name,file.name,sep="/"))
}
if (output.S) {
file.name <- paste0("S",t,".RData")
save(S_F, S_M, file=paste(dir.res.name,file.name,sep="/"))
}
}
# Recruitment
if (t == T_max) break # otherwise attempts to write on T_max + 1
# Recruitment with backward migration
if (migration == "backward") {
# Not implemented yet. See the corresponding section of sim.metapopgen.monoecious.multilocus
next
}
if (verbose) cat("t =",t,"Apply recruitment function \n")
for (i in 1 : n) {
if (save.res) {
Naged <- recr(N_F = array(Nprimeprime_F[,i,], dim=c(m,z)),
N_M = array(Nprimeprime_M[,i,], dim=c(m,z)),
S_F = array(S_F[,i], dim=c(m,1)),
S_M = array(S_M[,i], dim=c(m,1)),
m = m,
z = z,
kappa0 = kappa0[i,t+1],
recr.dd = recr.dd,
sexuality = "dioecious")
N_F[,i,] <- Naged[,,1]
N_M[,i,] <- Naged[,,2]
} else {
Naged <- recr(N_F = array(Nprimeprime_F[,i,,t], dim=c(m,z)),
N_M = array(Nprimeprime_M[,i,,t], dim=c(m,z)),
S_F = array(S_F[,i,t], dim=c(m,1)),
S_M = array(S_M[,i,t], dim=c(m,1)),
m = m,
z = z,
kappa0 = kappa0[i,t+1],
recr.dd = recr.dd,
sexuality = "dioecious")
N_F[,i,,t+1] <- Naged[,,1]
N_M[,i,,t+1] <- Naged[,,2]
}
}
}
print("...done")
if (save.res==F) {
output.res <- list()
if (output.N) {
output.res$N_F <- N_F
output.res$N_M <- N_M
}
if (output.Nprime) {
output.res$Nprime_F <- Nprime_F
output.res$Nprime_M <- Nprime_M
}
if (output.Nprimeprime) {
output.res$Nprimeprime_F <- Nprimeprime_F
output.res$Nprimeprime_M <- Nprimeprime_M
}
if (output.L) {
output.res$L_F <- L_F
output.res$L_M <- L_M
}
if (output.S) {
output.res$S_F <- S_F
output.res$S_M <- S_M
}
return(output.res)
}
}
Add the following code to your website.
For more information on customizing the embed code, read Embedding Snippets.