R/DAISIE_format_CS_sampled_stt.R

In xieshu95/DAISIE_new: Dynamical Assembly of Islands by Speciation, Immigration and Extinction

#' Formats clade-specific simulation output into standard
#' DAISIE list output
#'
#' @inheritParams default_params_doc
#'
#' @return List with CS DAISIE simulation output
DAISIE_format_CS_sampled_stt <- function(island_replicates,
                                         time,
                                         M,
                                         sample_freq,
                                         verbose = TRUE,
                                         trait_pars = NULL) {
  
  if (!is.null(trait_pars)) {
    return(
      DAISIE_format_CS_trait(
        island_replicates = island_replicates,
        time = time,
        M = M,
        sample_freq = sample_freq,
        verbose = verbose,
        trait_pars = trait_pars
      )
    )
  }
  totaltime <- time
  several_islands <- list()
  for (rep in seq_along(island_replicates)) {
    full_list <- island_replicates[[rep]]
    stac_vec <- unlist(full_list)[which(names(unlist(full_list)) == "stac")]
    number_not_present <- length(which(stac_vec == 0))
    present <- which(stac_vec != 0)
    number_present <- length(present)
    type_vec <- unlist(full_list)[which(names(unlist(full_list)) == "type1or2")]
    prop_type2_pool <- length(which(type_vec == 2)) / M
    number_type2_cols <- length(which(match(which(stac_vec != 0),
                                            which(type_vec == 2)) > 0))
    number_type1_cols <- number_present - number_type2_cols
    island_list <- list()
    for (i in 1:(number_present + 1)) {
      island_list[[i]] <- list()
    }
    ### all species
    stt_list <- list()
    for (i in 1:M) {
      stt_list[[i]] <- full_list[[i]]$stt_table
    }
    stt_all <- matrix(ncol = 5, nrow = sample_freq + 1)
    colnames(stt_all) <- c("Time", "nI", "nA", "nC", "present")
    stt_all[, "Time"] <- rev(seq(from = 0,
                                 to = totaltime,
                                 length.out = sample_freq + 1))

      immig_spec <- c()
      ana_spec <- c()
      for (i in 1:M) {
        immig_spec[i] <- sum(full_list[[i]]$stt_table[1, 2])
        ana_spec[i] <- sum(full_list[[i]]$stt_table[1, 3])
      }
      immig_spec <- sum(immig_spec)
      ana_spec <- sum(ana_spec)
      init_present <- immig_spec + ana_spec
      stt_all[1, 2:5] <- c(immig_spec, ana_spec, 0, init_present)

    for (i in 2:nrow(stt_all)) {
      the_age <- stt_all[i, "Time"]
      store_richness_time_slice <- matrix(nrow = M, ncol = 3)
      colnames(store_richness_time_slice) <- c("I", "A", "C")
      for (x in 1:M) {
        row_index <- max(which(stt_list[[x]][, "Time"] >= the_age))
        store_richness_time_slice[x, ] <- stt_list[[x]][row_index, 2:4]
      }
      count_time_slice <- store_richness_time_slice[, 1] +
        store_richness_time_slice[, 2] +
        store_richness_time_slice[, 3]
      present_time_slice <- rep(0, M)
      present_time_slice[which(count_time_slice > 0)] <- 1
      store_richness_time_slice <- cbind(store_richness_time_slice,
                                         present_time_slice)
      stt_all[i, c(2:5)] <- apply(store_richness_time_slice, 2, sum)
    }
    if (number_type2_cols > 0) {
      ######################################################### list type1
      stt_list_type1 <- list()
      for (i in 1:max(which(type_vec == 1))) {
        stt_list_type1[[i]] <- full_list[[i]]$stt_table
      }
      stt_type1 <- matrix(ncol = 5, nrow = sample_freq + 1)
      colnames(stt_type1) <- c("Time", "nI", "nA", "nC", "present")
      stt_type1[, "Time"] <- rev(seq(from = 0,
                                     to = totaltime,
                                     length.out = sample_freq + 1))
      stt_type1[1, 2:5] <- c(0, 0, 0, 0)
      for (i in 2:nrow(stt_type1)) {
        the_age <- stt_type1[i, "Time"]
        store_richness_time_slice <- matrix(nrow = max(which(type_vec == 1)),
                                            ncol = 3)
        colnames(store_richness_time_slice) <- c("I", "A", "C")
        for (x in 1:max(which(type_vec == 1))) {
          store_richness_time_slice[x, ] <- stt_list_type1[[x]][max(
            which(stt_list_type1[[x]][, "Time"] >= the_age)), 2:4]
        }
        count_time_slice <- store_richness_time_slice[, 1] +
          store_richness_time_slice[, 2] +
          store_richness_time_slice[, 3]
        present_time_slice <- rep(0, max(which(type_vec == 1)))
        present_time_slice[which(count_time_slice > 0)] <- 1
        store_richness_time_slice <- cbind(store_richness_time_slice,
                                           present_time_slice)
        stt_type1[i, c(2:5)] <- apply(store_richness_time_slice, 2, sum)
      }
      ######################################################### list type2
      type2len <- length(which(type_vec == 2))
      stt_list_type2 <- list()
      for (i in 1:type2len) {
        stt_list_type2[[i]] <- full_list[[which(type_vec == 2)[i]]]$stt_table
      }
      stt_type2 <- matrix(ncol = 5, nrow = sample_freq + 1)
      colnames(stt_type2) <- c("Time", "nI", "nA", "nC", "present")
      stt_type2[, "Time"] <- rev(seq(from = 0,
                                     to = totaltime,
                                     length.out = sample_freq + 1))
      stt_type2[1, 2:5] <- c(0, 0, 0, 0)
      for (i in 2:nrow(stt_type2)) {
        the_age <- stt_type2[i, "Time"]
        store_richness_time_slice <- matrix(nrow = type2len, ncol = 3)
        colnames(store_richness_time_slice) <- c("I", "A", "C")
        for (x in 1:type2len) {
          store_richness_time_slice[x, ] <- stt_list_type2[[x]][max(
            which(stt_list_type2[[x]][, "Time"] >= the_age)), 2:4]
        }
        count_time_slice <- store_richness_time_slice[, 1] +
          store_richness_time_slice[, 2] +
          store_richness_time_slice[, 3]
        present_time_slice <- rep(0, prop_type2_pool * M)
        present_time_slice[which(count_time_slice > 0)] <- 1
        store_richness_time_slice <- cbind(store_richness_time_slice,
                                           present_time_slice)
        stt_type2[i, c(2:5)] <- apply(store_richness_time_slice, 2, sum)
      }
      island_list[[1]] <- list(island_age = totaltime,
                               not_present_type1 = DDD::roundn(
                                 M * (1 - prop_type2_pool)) -
                                 (number_type1_cols),
                               not_present_type2 = DDD::roundn(
                                 M * prop_type2_pool) - number_type2_cols,
                               stt_all = stt_all,
                               stt_type1 = stt_type1,
                               stt_type2 = stt_type2)
    } else {
      island_list[[1]] <- list(island_age = totaltime,
                               not_present = number_not_present,
                               stt_all = stt_all)
    }
    if (number_present > 0) {
      for (i in 1:number_present) {
        island_list[[1 + i]] <- full_list[[present[i]]]
        island_list[[1 + i]]$stt_table <- NULL
      }
    }
    if (number_present == 0) {
      island_list <- list()
      island_list[[1]] <- list(island_age = totaltime,
                               not_present = M,
                               stt_all = stt_all)
      island_list[[2]] <- list(
        branching_times = totaltime,
        stac = 0,
        missing_species = 0
      )
    }
    several_islands[[rep]] <- island_list
    if (verbose == TRUE) {
      print(paste("Island being formatted: ",
                  rep,
                  "/",
                  length(island_replicates),
                  sep = ""))
    }
  }
  return(several_islands)
}

DAISIE_format_CS_trait <- function(island_replicates,
                                   time,
                                   M,
                                   sample_freq,
                                   verbose = TRUE,
                                   trait_pars = NULL)
{
  totaltime <- time
  several_islands <- list()
  
  for(rep in 1:length(island_replicates))
  {
    full_list <- island_replicates[[rep]]
    stac_vec <- unlist(full_list)[which(names(unlist(full_list)) == "stac")]
    number_not_present <- length(which(stac_vec == 0))
    present <- which(stac_vec!=0)
    number_present <- length(present)
    type_vec <- unlist(full_list)[which(names(unlist(full_list)) == "type1or2")]
    prop_type2_pool <- length(which(type_vec == 2)) / M
    
    number_type2_cols <- length(which(match(which(stac_vec != 0),which(type_vec == 2)) > 0))
    number_type1_cols <- number_present-number_type2_cols
    
    island_list <- list()
    for(i in 1:(number_present + 1))
    {
      island_list[[i]] = list()
    }
    
    ### all species
    stt_list = list()
    for(i in 1:(M + trait_pars$M2))
    {
      stt_list[[i]] = full_list[[i]]$stt_table
    }
    stt_all = matrix(ncol = 8,nrow = sample_freq + 1)
    
    colnames(stt_all) = c("Time","nI","nA","nC","nI2","nA2","nC2","present")
    stt_all[,"Time"] = rev(seq(from = 0,to = totaltime,length.out = sample_freq + 1))
  
    ####
    immig_spec <- c()
    ana_spec <- c()
    immig_spec2 <- c()
    ana_spec2 <- c()
    for (i in 1:(M + trait_pars$M2)) {
      immig_spec[i] <- sum(full_list[[i]]$stt_table[1, 2])
      ana_spec[i] <- sum(full_list[[i]]$stt_table[1, 3])
      immig_spec2[i] <- sum(full_list[[i]]$stt_table[1, 5])
      ana_spec2[i] <- sum(full_list[[i]]$stt_table[1, 6])
    }
    immig_spec <- sum(immig_spec)
    ana_spec <- sum(ana_spec)
    immig_spec2 <- sum(immig_spec2)
    ana_spec2 <- sum(ana_spec2)
    init_present <- immig_spec + ana_spec + immig_spec2 + ana_spec2
    stt_all[1, 2:8] <- c(immig_spec, ana_spec, 0, immig_spec2, ana_spec2, 0, init_present)
    
    ####
    for(i in 2:nrow(stt_all))
    {
      the_age = stt_all[i,"Time"]
      store_richness_time_slice = matrix(nrow = M + trait_pars$M2,ncol = 6)
      colnames(store_richness_time_slice) = c("I","A","C","I2","A2","C2")
      for(x in 1:(M + trait_pars$M2))
      {
        testit::assert(x >= 1)
        testit::assert(x <= length(stt_list))
        testit::assert(class(stt_list[[x]]) == "matrix")
        testit::assert("Time" %in% colnames(stt_list[[x]]))
        store_richness_time_slice[x,] = stt_list[[x]][max(which(stt_list[[x]][,"Time"] >= the_age)),2:7] # HERE 2
      }
      count_time_slice = store_richness_time_slice[,1] +
        store_richness_time_slice[,2] +
        store_richness_time_slice[,3] +
        store_richness_time_slice[,4] +
        store_richness_time_slice[,5] +
        store_richness_time_slice[,6]
      present_time_slice = rep(0,M + trait_pars$M2)
      present_time_slice[which(count_time_slice>0)] = 1
      store_richness_time_slice = cbind(store_richness_time_slice,present_time_slice)
      stt_all[i,c(2:8)] = apply(store_richness_time_slice,2,sum)
    }
    if(number_type2_cols > 0){
      stop("Two species types and two trait states not considered simutanously.")
    }
    
    island_list[[1]] = list(island_age = totaltime,not_present = number_not_present, stt_all = stt_all)
    
    
    if(number_present > 0)
    {
      for(i in 1:number_present)
      {
        island_list[[1 + i]] = full_list[[present[i]]]
        island_list[[1 + i]]$stt_table = NULL
      }
    }
    
    if(number_present == 0)
    {
      island_list = list()
      island_list[[1]] = list(island_age = totaltime,not_present = M, stt_all = stt_all)
      island_list[[2]] = list(branching_times= totaltime, stac = 0, missing_species = 0)
      
    }
    
    several_islands[[rep]] = island_list
    if (verbose == TRUE) {
      print(paste("Island being formatted: ",rep,"/",length(island_replicates),sep = ""))
    }
  }
  
  return(several_islands)
}