# Step 1: Generate random number of external walls
num_external_walls <- sample(1:10, 1)

# Step 2: If only one external wall, assign all area to that external wall
if (num_external_walls == 1) {
  area_assigned <- total_area <- 1000
} else {
  # Step 3-5: Assign random area to each external wall
  total_area <- 1000
  area_assigned <- vector(mode = "integer", length = num_external_walls)
  
  for (i in 1:(num_external_walls - 1)) {
    max_area <- min(floor((total_area - sum(area_assigned)) / (num_external_walls - i)), total_area - sum(area_assigned))
    area_assigned[i] <- sample(0:max_area, 1)
  }
  
  # Assign remaining area to the last external wall
  area_assigned[num_external_walls] <- total_area - sum(area_assigned)
}

# Step 6: Generate random type for each external wall (WINDOW or WALL)
wall_types <- sample(c("WINDOW", "WALL"), num_external_walls, replace = TRUE)

# Create dataframe
external_walls_df <- data.frame(External_Surface = paste("External Surface", 1:num_external_walls),
                                Area_Assigned = area_assigned,
                                Wall_Type = wall_types)

# Print the dataframe
print("External Surfaces and their Area Assigned:")
print(external_walls_df)

# Print the total area
total_area_sum <- sum(area_assigned)
print(paste("Total area assigned:", total_area_sum))