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wa_tor.py
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wa_tor.py
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from grid import Grid
import random
class Wator:
def __init__(self, width, height, cell_size):
self.grid = Grid(width, height, cell_size)
self.energy_grid = Grid(width, height, cell_size)
self.reproduce_grid = Grid(width, height, cell_size)
self.rows = height // cell_size
self.columns = width // cell_size
self.run = False
self.rule_list = ['standard']
self.rule_index = 0
self.fish_reproduce = 5
self.shark_reproduce = 50
self.energy_per_fish = 2
self.shark_energy = 10
for row in range(self.rows):
for column in range(self.columns):
self.reproduce_grid.cells[row][column] = -1
self.energy_grid.cells[row][column] = -1
def draw(self, window):
self.grid.draw(window)
def update(self):
if self.is_running():
for row in range(self.rows):
for column in range(self.columns):
# determine free adjacent cells
free_cells = []
neighbor_offsets = [(-1, 0), (0, -1), (0, 1), (1, 0)]
for offset in neighbor_offsets:
new_row = (row + offset[0]) % self.rows
new_column = (column + offset[1]) % self.columns
if self.grid.cells[new_row][new_column] == 0:
free_cells.append([new_row, new_column])
# if there is a free adjacent cell
if len(free_cells) > 0:
destination = random.choice(free_cells)
else:
destination = (row, column)
# if cell is a fish
if self.grid.cells[row][column] == 3:
# if fish cant reproduce
if self.reproduce_grid.cells[row][column] > 0:
self.grid.cells[row][column] = 0
reproduce_timer = self.reproduce_grid.cells[row][column] - 1
self.reproduce_grid.cells[row][column] = -1
# if fish can reproduce
else:
reproduce_timer = self.fish_reproduce
self.reproduce_grid.cells[row][column] = self.fish_reproduce
# movement
self.grid.cells[destination[0]][destination[1]] = 3
self.reproduce_grid.cells[destination[0]][destination[1]] = reproduce_timer
# if cell is a shark
if self.grid.cells[row][column] == 1:
# determine adjacent fish
fish_cells = []
neighbor_offsets = [(-1, 0), (0, -1), (0, 1), (1, 0)]
for offset in neighbor_offsets:
new_row = (row + offset[0]) % self.rows
new_column = (column + offset[1]) % self.columns
if self.grid.cells[new_row][new_column] == 3:
fish_cells.append([new_row, new_column])
energy = self.energy_grid.cells[row][column]
# if there is an adjacent fish
if len(fish_cells) > 0:
destination = random.choice(fish_cells)
energy += self.energy_per_fish
if energy > self.shark_energy:
energy = self.shark_energy
# if shark runs out of energy
if energy <= 0:
self.grid.cells[row][column] = 0
self.energy_grid.cells[row][column] = -1
self.reproduce_grid.cells[row][column] = -1
else:
# if shark cant reproduce
if self.reproduce_grid.cells[row][column] > 0:
self.grid.cells[row][column] = 0
reproduce_timer = self.reproduce_grid.cells[row][column] - 1
self.reproduce_grid.cells[row][column] = -1
self.energy_grid.cells[row][column] = -1
# if shark can reproduce
else:
reproduce_timer = self.shark_reproduce
self.reproduce_grid.cells[row][column] = self.shark_reproduce
# movement
self.grid.cells[destination[0]][destination[1]] = 1
self.reproduce_grid.cells[destination[0]][destination[1]] = reproduce_timer
self.energy_grid.cells[destination[0]][destination[1]] = energy - 1
def is_running(self):
return self.run
def start(self):
self.run = True
def stop(self):
self.run = False
def clear(self):
if self.is_running() == False:
self.grid.clear()
def create_random_state(self):
if self.is_running() == False:
self.grid.fill_random()
def toggle_cell(self, row, column):
if self.is_running() == False:
if self.grid.cells[row][column] == 0:
self.grid.cells[row][column] = 3
self.reproduce_grid.cells[row][column] = self.fish_reproduce
elif self.grid.cells[row][column] == 3:
self.grid.cells[row][column] = 1
self.reproduce_grid.cells[row][column] = self.shark_reproduce
self.energy_grid.cells[row][column] = self.shark_energy
else:
self.grid.cells[row][column] = 0
self.reproduce_grid.cells[row][column] = 0
def rule_down(self):
if self.is_running() == False:
if self.rule_index < len(self.rule_list) - 1:
self.rule_index += 1
else:
self.rule_index = 0
def rule_up(self):
if self.is_running() == False:
if self.rule_index > 0:
self.rule_index -= 1
else:
self.rule_index = len(self.rule_list) - 1