added multi processing, extremly slow though

scripts/main_ui.py

@@ -2,7 +2,7 @@
 
 import random
 
-from cellular_automaton.cellular_automaton import CellularAutomaton, CellularAutomatonEvolver
+from cellular_automaton.cellular_automaton import CellularAutomaton, CellularAutomatonProcessor
 from cellular_automaton.ca_rule import Rule
 from cellular_automaton.ca_neighborhood import MooreNeighborhood, EdgeRule
 from cellular_automaton.ca_display import PyGameFor2D
@@ -12,22 +12,32 @@ from cellular_automaton.ca_grid import Grid
 
 class TestRule(Rule):
     def evolve_cell(self, cell, iteration_index):
-        active = False
-        neighbors = cell.neighbours
         if cell.state is None:
-            rand = random.randrange(0, 101, 1)
+            return self._init_state(cell)
-            if rand <= 99:
+        else:
-                cell.state = MyStatus(0)
+            return self._evolve_state(cell, iteration_index)
-            else:
+
-                cell.state = MyStatus(1)
+    @staticmethod
-                cell.is_set_for_redraw = True
+    def _evolve_state(cell, iteration_index):
-                active = True
+        try:
-        elif len(neighbors) == 8:
+            left_neighbour_state = cell.neighbours[0].state.get_status_of_iteration(iteration_index - 1)
-            left_neighbour_state = neighbors[0].state.get_status_of_iteration(iteration_index - 1)
             active = cell.state.set_status_of_iteration(left_neighbour_state, iteration_index)
             if active:
                 cell.is_set_for_redraw = True
-        return active
+            return active
+        except IndexError:
+            return False
+
+    @staticmethod
+    def _init_state(cell):
+        rand = random.randrange(0, 101, 1)
+        if rand <= 99:
+            cell.state = MyStatus(0)
+            return False
+        else:
+            cell.state = MyStatus(1)
+            cell.is_set_for_redraw = True
+            return True
 
 
 class MyStatus(CellState):
@@ -44,8 +54,10 @@ class MyStatus(CellState):
 if __name__ == "__main__":
     random.seed(1000)
     rule = TestRule()
-    ca = CellularAutomaton(Grid([400, 400], MooreNeighborhood(EdgeRule.FIRST_AND_LAST_CELL_OF_DIMENSION_ARE_NEIGHBORS)),
+    grid = Grid(dimension=[400, 400],
-                           rule)
+                neighborhood=MooreNeighborhood(EdgeRule.FIRST_AND_LAST_CELL_OF_DIMENSION_ARE_NEIGHBORS))
-    ca_evolver = CellularAutomatonEvolver(2)
+    ca = CellularAutomaton(grid, rule)
-    ca_window = PyGameFor2D([1000, 800], ca, ca_evolver, 5)
+    ca_window = PyGameFor2D(window_size=[1000, 800], cellular_automaton=ca)
-    ca_window.main_loop()
+    ca_processor = CellularAutomatonProcessor(process_count=8)
+    ca_window.main_loop(cellular_automaton_processor=ca_processor,
+                        ca_iterations_per_draw=5)

src/cellular_automaton/ca_cell_state.py

@@ -30,3 +30,6 @@ class CellState:
 
     def get_state_draw_color(self, iteration):
         raise NotImplementedError
+
+    def __str__(self):
+        return str(self._state_slots)

src/cellular_automaton/ca_display.py

@@ -2,7 +2,7 @@ import pygame
 import time
 import operator
 
-from cellular_automaton.cellular_automaton import CellularAutomaton, CellularAutomatonEvolver
+from cellular_automaton.cellular_automaton import CellularAutomaton, CellularAutomatonProcessor
 
 
 class _DisplayInfo:
@@ -33,22 +33,16 @@ class DisplayFor2D:
 
 
 class PyGameFor2D:
-    def __init__(self,
+    def __init__(self, window_size: list, cellular_automaton: CellularAutomaton):
-                 windows_size: list,
+        self._window_size = window_size
-                 cellular_automaton: CellularAutomaton,
-                 cellular_automaton_evolver: CellularAutomatonEvolver,
-                 ca_iterations_per_draw):
-        self._window_size = windows_size
         self._cellular_automaton = cellular_automaton
-        self._cellular_automaton_evolver = cellular_automaton_evolver
-        self._ca_steps_per_draw = ca_iterations_per_draw
 
         pygame.init()
         pygame.display.set_caption("Cellular Automaton")
         self._screen = pygame.display.set_mode(self._window_size)
         self._font = pygame.font.SysFont("monospace", 15)
 
-        self.ca_display = DisplayFor2D([0, 30, windows_size[0], windows_size[1]-30], cellular_automaton, self._screen)
+        self.ca_display = DisplayFor2D([0, 30, window_size[0], window_size[1] - 30], cellular_automaton, self._screen)
 
     def _print_process_duration(self, time_ca_end, time_ca_start, time_ds_end):
         self._screen.fill([0, 0, 0], ((0, 0), (self._window_size[0], 30)))
@@ -60,12 +54,12 @@ class PyGameFor2D:
         update_rect = self._screen.blit(label, pos)
         pygame.display.update(update_rect)
 
-    def main_loop(self):
+    def main_loop(self, cellular_automaton_processor: CellularAutomatonProcessor, ca_iterations_per_draw):
         running = True
 
         while running:
             time_ca_start = time.time()
-            self._cellular_automaton_evolver.evolve_x_times(self._cellular_automaton, self._ca_steps_per_draw)
+            cellular_automaton_processor.evolve_x_times(self._cellular_automaton, ca_iterations_per_draw)
             time_ca_end = time.time()
             self.ca_display._redraw_cellular_automaton()
             time_ds_end = time.time()

src/cellular_automaton/cellular_automaton.py

@@ -1,5 +1,9 @@
 from cellular_automaton.ca_grid import Grid
 from cellular_automaton.ca_rule import Rule
+from cellular_automaton.ca_cell_state import CellState
+
+from multiprocessing import Process, Pipe,  Array, Value
+import multiprocessing
 
 
 class CellularAutomaton:
@@ -9,14 +13,22 @@ class CellularAutomaton:
         self.evolution_iteration_index = 0
 
 
-class CellularAutomatonEvolver:
+class _EvolutionProcess:
+    def __init__(self, process: Process, pipe: Pipe):
+        self.process = process
+        self.pipe = pipe
+        self.cell = None
+
+
+class CellularAutomatonProcessor:
     def __init__(self, process_count: int = 1):
-        self.__processes = process_count
+        self._processes = list(_create_processes(process_count))
         self.__cellular_automaton = None
 
     def evolve_x_times(self, cellular_automaton: CellularAutomaton, evolution_steps: int):
         """ Evolve all cells for x time steps.
-        :param evolution_steps: the count of evolutions done.
+        :param cellular_automaton: The cellular automaton to evolve.
+        :param evolution_steps: The count of evolutions done.
         :return: True if all cells are inactive
         """
         for evo in range(evolution_steps):
@@ -27,10 +39,12 @@ class CellularAutomatonEvolver:
 
     def evolve(self, cellular_automaton: CellularAutomaton):
         """ Evolves all active cells for one time step.
+        :param cellular_automaton: The cellular automaton to evolve.
         :return: True if all cells are inactive.
         """
         self.__cellular_automaton = cellular_automaton
         if self._is_evolution_finished():
+            print("finished")
             return True
         else:
             cellular_automaton.evolution_iteration_index += 1
@@ -44,11 +58,115 @@ class CellularAutomatonEvolver:
         active_cells = self.__cellular_automaton.grid.get_active_cells()
         self.__cellular_automaton.grid.clear_active_cells()
         self._evolve_cells(active_cells.values())
+        print(len(self.__cellular_automaton.grid.get_active_cells()))
 
-    def _evolve_cells(self, cells: list):
+    def _evolve_cells(self, cells):
         cellular_automaton = self.__cellular_automaton
-        for cell in cells:
+        processes = self._processes
-            active = cellular_automaton.evolution_rule.evolve_cell(cell, cellular_automaton.evolution_iteration_index)
+        process_count = len(processes)
+        for i, cell in enumerate(cells):
+            evolution_process = processes[i % process_count]
+            if evolution_process.cell:
+                response = evolution_process.pipe.recv()
+                evolved_cell = evolution_process.cell
+                evolved_cell.state = response[0]
+                evolved_cell.is_set_for_redraw |= response[1]
+                if evolved_cell.is_set_for_redraw:
+                    cellular_automaton.grid.set_cells_active([evolved_cell] + evolved_cell.neighbours)
+                evolution_process.cell = None
 
-            if active:
+            cell_info = self.read_cell_info(cell, cellular_automaton.evolution_iteration_index)
+            evolution_process.pipe.send(cell_info)
+            evolution_process.cell = cell
+
+        for evolution_process in processes:
+            response = evolution_process.pipe.recv()
+            cell = evolution_process.cell
+            cell.state = response[0]
+            cell.is_set_for_redraw |= response[1]
+            if cell.is_set_for_redraw:
                 cellular_automaton.grid.set_cells_active([cell] + cell.neighbours)
+            evolution_process.cell = None
+
+            # if cellular_automaton.evolution_rule.evolve_cell(cell.state, cellular_automaton.evolution_iteration_index):
+            #     cellular_automaton.grid.set_cells_active([cell] + cell.neighbours)
+
+    @staticmethod
+    def read_cell_info(cell, iteration):
+        coordinate = cell.coordinate
+        return [coordinate, cell.state, [n.state for n in cell.neighbours], iteration]
+
+        # if cell.state is not None:
+        #     cell_state = cell.state.get_status_of_iteration(iteration - 1)
+        # else:
+        #     cell_state = None
+        #
+        # neighbor_states = []
+        # for neighbor in cell.neighbours:
+        #     if neighbor.state is not None:
+        #         neighbor_state = neighbor.state.get_status_of_iteration(iteration - 1)
+        #     else:
+        #         neighbor_state = None
+        #     neighbor_states.append(neighbor_state)
+        #
+        # return [coordinate,  cell_state, neighbor_states]
+
+
+def _create_processes(count):
+    for i in range(count):
+        parent_pipe_connection, child_pipe_connection = Pipe()
+        p = Process(target=process_routine, args=(child_pipe_connection, ))
+        p.start()
+        yield _EvolutionProcess(p, parent_pipe_connection)
+
+
+def process_routine(pipe_conn: Pipe):
+    while True:
+        info = pipe_conn.recv()
+        pipe_conn.send(evolve_cell(*info))
+
+
+def evolve_cell(coordinate, cell_state, neighbor_states, index):
+    if cell_state is None:
+        return _init_state()
+    else:
+        new_state = _evolve_state(cell_state, neighbor_states, index)
+        if new_state is None:
+            print(",".join([str(x) for x in neighbor_states]))
+            return [cell_state, False]
+        else:
+            changed = cell_state.set_status_of_iteration(new_state, index)
+            return [cell_state, changed]
+
+
+def _evolve_state(cell_state, neighbor_states, index):
+    try:
+        left_neighbour_state = neighbor_states[0].get_status_of_iteration(index - 1)
+        return left_neighbour_state
+    except (IndexError, AttributeError):
+        return None
+
+
+import random
+
+
+def _init_state():
+    rand = random.randrange(0, 101, 1)
+    if rand <= 99:
+        return [MyStatus(0), False]
+    else:
+        return [MyStatus(1), True]
+
+
+class MyStatus(CellState):
+    def __init__(self, initial_state):
+        super().__init__(initial_state)
+
+    def get_state_draw_color(self, iteration):
+        red = 0
+        if self._state_slots[iteration % 2][0]:
+            red = 255
+        return [red, 0, 0]
+
+    def __str__(self):
+        return super().__str__()