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[QUOTE="karton, post: 596054, member: 5060"]
Voici le dernier script obtenu:

# Nettoyage initial
rm(list = ls())
graphics.off()

# Chargement des packages
if (!require("fields")) install.packages("fields")
library(fields)

### PARAMÈTRES ###
sizeenvironment <- 50      # Taille de la grille
r <- 0.25                 # Taux de croissance
K <- 500                  # Capacité porteuse
dt <- 0.1                 # Pas de temps
dureesimulation <- 50     # Durée totale
tauxdispersion <- 0.2     # Probabilité de dispersion

### INITIALISATION ###
create_matrix <- function(size, val) {
  m <- matrix(val, nrow = size + 2, ncol = size + 2)
  m[c(1, size + 2), ] <- m[, c(1, size + 2)] <- 0  # Bordures à 0
  return(m)
}

# Populations - Densité visible dès le départ
pop1 <- create_matrix(sizeenvironment, K * 0.6)  # B.subtilis (60% de remplissage)
pop2 <- create_matrix(sizeenvironment, 0)        # E.coli
pop2[(sizeenvironment/2-1):(sizeenvironment/2+1), 
     (sizeenvironment/2-1):(sizeenvironment/2+1)] <- K/4  # Tache centrale 3x3

### COULEURS AMÉLIORÉES ###
setup_display <- function() {
  par(mar = c(3, 3, 3, 5))
  list(
    colorRampPalette(c("#FFCCCC", "#FF0000", "#990000"))(100),  # B.sub (rouge)
    colorRampPalette(c("#CCE5FF", "#0066FF", "#003399"))(100),  # E.coli (bleu)
    rgb(0.2, 0.7, 1, alpha = seq(0.1, 0.8, length.out = 50))   # Inhibiteur
  )
}

### FONCTIONS ###
safe_growth <- function(Ni, Nj, r, K, dt, aji) {
  Ni <- max(0, Ni, na.rm = TRUE)
  Nj <- max(0, Nj, na.rm = TRUE)
  growth <- Ni * r * dt * (1 - (Ni + aji * Nj)/K)
  return(max(0, Ni + growth))
}

### BOUCLE PRINCIPALE ###
colors <- setup_display()

for (t in seq(0, dureesimulation, dt)) {
  # Copie des populations
  old_pop1 <- pop1
  old_pop2 <- pop2
  
  # Croissance
  for (i in 2:(sizeenvironment + 1)) {
    for (j in 2:(sizeenvironment + 1)) {
      pop1[i,j] <- rpois(1, lambda = safe_growth(old_pop1[i,j], old_pop2[i,j], r, K, dt, 1.5))
      pop2[i,j] <- rpois(1, lambda = safe_growth(old_pop2[i,j], old_pop1[i,j], r, K, dt, 0.8))
    }
  }
  
  # Dispersion simplifiée
  disperse <- function(pop) {
    new_pop <- pop
    for (i in 2:(sizeenvironment + 1)) {
      for (j in 2:(sizeenvironment + 1)) {
        if (pop[i,j] > 0) {
          n_disp <- rbinom(1, size = min(pop[i,j], 20), prob = tauxdispersion * dt)
          if (n_disp > 0) {
            for (k in 1:n_disp) {
              di <- sample(-1:1, 1)
              dj <- sample(-1:1, 1)
              new_pop[i + di, j + dj] <- new_pop[i + di, j + dj] + 1
            }
            new_pop[i,j] <- new_pop[i,j] - n_disp
          }
        }
      }
    }
    return(new_pop)
  }
  
  pop1 <- disperse(pop1)
  pop2 <- disperse(pop2)
  
  # Affichage (tous les 2 pas de temps)
  if (t %% 2 == 0) {
    # Préparation des données
    display_pop1 <- sqrt(pop1[2:(sizeenvironment+1), 2:(sizeenvironment+1)] / K)  # Normalisation + sqrt
    display_pop2 <- sqrt(pop2[2:(sizeenvironment+1), 2:(sizeenvironment+1)] / K)
    
    # Plot principal
    image(display_pop1, col = colors[[1]], zlim = c(0, 1), 
          main = paste("Simulation - Temps =", round(t, 1)),
          xlab = "", ylab = "", axes = FALSE)
    image(display_pop2, col = colors[[2]], add = TRUE)
    
    # Légende
    legend("topright", 
           legend = c("B.subtilis", "E.coli"),
           fill = c("#FF0000", "#0066FF"),
           bg = "white", cex = 0.9)
    
    # Échelle de couleur
    image.plot(zlim = c(0, 1), legend.only = TRUE,
               col = colors[[1]], 
               smallplot = c(0.88, 0.9, 0.3, 0.7),
               legend.args = list(text = "Densité (√)", side = 4, cex = 0.8))
    
    Sys.sleep(0.1)  # Pause pour visualisation
  }
}
[/QUOTE]

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