Substitute count_alive_neighbors function by sum

neuropercolation/__init__.py

@@ -18,4 +18,4 @@ limitations under the License.
 from .neighborhood import Neighborhood, MooreNeighborhood, RadialNeighborhood, VonNeumannNeighborhood, \
                           HexagonalNeighborhood, EdgeRule
 from .automaton import Neuropercolation, NeuropercolationCoupled
-from .display import Simulate2Layers
+from .display import Simulate2Layers, Simulate4Layers

neuropercolation/automaton.py

@@ -123,7 +123,7 @@ class Neuropercolation(CellularAutomatonCreator, abc.ABC):
         for coord, old, new in zip(this_state.keys(), this_state.values(), next_state.values()):
             coord_c = tuple([*coord[:2],int(1-coord[2])])
             old_c = this_state[coord_c]
-            new_state = evolution_rule(old.state.copy(), old_c.state.copy(), [n.state for n in old.neighbors], coord[2], coord_c[2]) #inverse the inhibitory layer's action
+            new_state = evolution_rule(old.state.copy(), old_c.state.copy(), [n.state[0] for n in old.neighbors], coord[2], coord_c[2]) #inverse the inhibitory layer's action
             
             evolve_cell(old, new, new_state)
 
@@ -136,9 +136,9 @@ class Neuropercolation(CellularAutomatonCreator, abc.ABC):
     def evolve_rule(self, last_cell_state, link_last_state, neighbors_last_states, cell_lay, link_cell_lay):
         new_cell_state = last_cell_state
         if link_cell_lay==0:
-            alive_neighbours = self.__count_alive_neighbours(neighbors_last_states)+link_last_state[0] # adjust for excitatory link cells
+            alive_neighbours = sum(neighbors_last_states)+link_last_state[0] # adjust for excitatory link cells
         else:
-            alive_neighbours = self.__count_alive_neighbours(neighbors_last_states)+(1-link_last_state[0]) # adjust for inhibitory link cells
+            alive_neighbours = sum(neighbors_last_states)+(1-link_last_state[0]) # adjust for inhibitory link cells
         
         CASE = (random.random()>=self.epsilon)
         if alive_neighbours > 2:
@@ -153,14 +153,6 @@ class Neuropercolation(CellularAutomatonCreator, abc.ABC):
                 new_cell_state = ALIVE
         return new_cell_state
     
-    @staticmethod
-    def __count_alive_neighbours(neighbours):
-        alive_neighbors = []
-        for n in neighbours:
-            if n == ALIVE:
-                alive_neighbors.append(1)
-        return len(alive_neighbors)
-    
 class NeuropercolationCoupled(CellularAutomatonCreator, abc.ABC):
     
     def __init__(self, dim, eps, coupling=[], *args, **kwargs):
@@ -206,11 +198,11 @@ class NeuropercolationCoupled(CellularAutomatonCreator, abc.ABC):
             if coord[:2] in self.coupling:
                 coord_c = tuple([*coord[:2],coord[2],int(1-coord[3])])
                 old_c = this_state[coord_c]
-                new_state = evolution_rule(old.state.copy(), old_c.state.copy(), [n.state for n in old.neighbors], 0)
+                new_state = evolution_rule(old.state.copy(), old_c.state.copy(), [n.state[0] for n in old.neighbors], 0)
             else:
                 coord_c = tuple([*coord[:2],int(1-coord[2]),coord[3]])
                 old_c = this_state[coord_c]
-                new_state = evolution_rule(old.state.copy(), old_c.state.copy(), [n.state for n in old.neighbors], coord_c[2]) #inverse the inhibitory layer's action
+                new_state = evolution_rule(old.state.copy(), old_c.state.copy(), [n.state[0] for n in old.neighbors], coord_c[2]) #inverse the inhibitory layer's action
                 
             evolve_cell(old, new, new_state)
 
@@ -223,9 +215,9 @@ class NeuropercolationCoupled(CellularAutomatonCreator, abc.ABC):
     def evolve_rule(self, last_cell_state, link_last_state, neighbors_last_states, other_layer):
         new_cell_state = last_cell_state
         if other_layer==0:
-            alive_neighbours = self.__count_alive_neighbours(neighbors_last_states)+link_last_state[0] # adjust for excitatory link cells
+            alive_neighbours = sum(neighbors_last_states)+link_last_state[0] # adjust for excitatory link cells
         else:
-            alive_neighbours = self.__count_alive_neighbours(neighbors_last_states)+(1-link_last_state[0]) # adjust for inhibitory link cells
+            alive_neighbours = sum(neighbors_last_states)+(1-link_last_state[0]) # adjust for inhibitory link cells
         
         CASE = (random.random()>=self.epsilon)
         if alive_neighbours > 2:

neuropercolation/display.py

@@ -113,6 +113,7 @@ class Simulate2Layers:
                 self.__draw_engine._pygame.quit()
             except:
                 print('Failed to quit pygame')
+                
     def _sleep_to_keep_rate(self, time_taken, evolutions_per_second):  # pragma: no cover
         if evolutions_per_second > 0:
             rest_time = 1.0 / evolutions_per_second - time_taken
@@ -173,3 +174,116 @@ class Simulate2Layers:
 
     def _is_not_user_terminated(self):
         return self.__draw_engine.is_active()
+
+class Simulate4Layers:
+    def __init__(self,
+                 cellular_automaton: NeuropercolationCoupled,
+                 window_size=(1000, 800),
+                 stretch_cells=False,
+                 draw_engine=None,
+                 state_to_color_cb=None,
+                 *args, **kwargs):
+        """
+        Creates a window to render a 2D CellularAutomaton.
+        :param cellular_automaton:  The automaton to display and evolve
+        :param window_size:         The Window size (default: 1000 x 800)
+        :param stretch_cells:       Stretches cells to fit into window size. (default: false)
+                                    Activating it can result in black lines throughout the automaton.
+        :param draw_engine:         The draw_engine (default: pygame)
+        :param state_to_color_cb:   A callback to define the draw color of CA states (default: red for states != 0)
+        """
+        super().__init__(*args, **kwargs)
+        self._cellular_automaton = cellular_automaton
+        self.__rect = _Rect(left=0, top=30, width=window_size[0], height=window_size[1])
+        self.__calculate_cell_display_size(stretch_cells)
+        self.__draw_engine = PygameEngine(window_size, self.__rect.top) if draw_engine is None else draw_engine
+        self.__state_to_color = self._get_cell_color if state_to_color_cb is None else state_to_color_cb
+
+    def run(self,
+            evolutions_per_second=0,
+            evolutions_per_draw=1,
+            last_evolution_step=0,):
+        """
+        Evolves and draws the CellularAutomaton
+        :param evolutions_per_second:   0 = as fast as possible | > 0 to slow down the CellularAutomaton
+        :param evolutions_per_draw:     Amount of evolutions done before screen gets redrawn.
+        :param last_evolution_step:     0 = infinite | > 0 evolution step at which this method will stop
+        Warning: is blocking until finished
+        """
+        with contextlib.suppress(KeyboardInterrupt):
+            while self._is_not_user_terminated() and self._not_at_the_end(last_evolution_step):
+                time_ca_start = time.time()
+                self._cellular_automaton.evolve(evolutions_per_draw)
+                time_ca_end = time.time()
+                self._redraw_dirty_cells()
+                time_ds_end = time.time()
+                self.print_process_info(evolve_duration=(time_ca_end - time_ca_start),
+                                        draw_duration=(time_ds_end - time_ca_end),
+                                        evolution_step=self._cellular_automaton.evolution_step)
+                self._sleep_to_keep_rate(time.time() - time_ca_start, evolutions_per_second)
+            try:
+                self.__draw_engine._pygame.quit()
+            except:
+                print('Failed to quit pygame')
+                
+    def _sleep_to_keep_rate(self, time_taken, evolutions_per_second):  # pragma: no cover
+        if evolutions_per_second > 0:
+            rest_time = 1.0 / evolutions_per_second - time_taken
+            if rest_time > 0:
+                time.sleep(rest_time)
+
+    def _not_at_the_end(self, last_evolution_step):
+        return (self._cellular_automaton.evolution_step < last_evolution_step or last_evolution_step <= 0)
+
+    def __calculate_cell_display_size(self, stretch_cells):  # pragma: no cover
+        grid_dimension = self._cellular_automaton.dimension
+        if stretch_cells:
+            self.__cell_size = [(self.__rect.width) / (grid_dimension[0]*2),
+                                (self.__rect.height) / (grid_dimension[1]*2)]
+        else:
+            self.__cell_size = [int((self.__rect.width) / (grid_dimension[0]*2)),
+                                int((self.__rect.height) / (grid_dimension[1]*2))]
+
+    def _redraw_dirty_cells(self):
+        self.__draw_engine.update_rectangles(list(self.__redraw_dirty_cells()))
+
+    def __redraw_dirty_cells(self):
+        for coordinate, cell in self._cellular_automaton.cells.items():
+            if cell.is_dirty:
+                yield self.__redraw_cell(cell, coordinate)
+
+    def __redraw_cell(self, cell, coordinate):
+        cell_color = self.__state_to_color(cell.state)
+        if coordinate[2]==1:
+            cell_color = cell_color[::-1]
+        cell_pos = self.__calculate_cell_position_in_the_grid(coordinate)
+        surface_pos = self.__calculate_cell_position_on_screen(cell_pos)
+        cell.is_dirty = False
+        return self.__draw_cell_surface(surface_pos, cell_color)
+    
+    def _get_cell_color(self, current_state: Sequence) -> Sequence:
+        """ Returns the color of the cell depending on its current state """
+        return 255 if current_state[0] else 0, 0, 0
+
+    def __calculate_cell_position_in_the_grid(self, coord):
+        return list(map(operator.add,
+                        map(operator.mul,
+                            self.__cell_size,
+                            coord[:2]),
+                        [(self.__rect.width/2)*(coord[3]),
+                         (self.__rect.height/2)*(coord[2])]))
+
+    def __calculate_cell_position_on_screen(self, cell_pos):
+        return [self.__rect.left + cell_pos[0], self.__rect.top + cell_pos[1]]
+    
+    def __draw_cell_surface(self, surface_pos, cell_color):
+        return self.__draw_engine.fill_surface_with_color((surface_pos, self.__cell_size), cell_color)
+
+    def print_process_info(self, evolve_duration, draw_duration, evolution_step):
+        self.__draw_engine.fill_surface_with_color(((0, 0), (self.__rect.width, 30)))
+        self.__draw_engine.write_text((10, 5), "CA: " + "{0:.4f}".format(evolve_duration) + "s")
+        self.__draw_engine.write_text((310, 5), "Display: " + "{0:.4f}".format(draw_duration) + "s")
+        self.__draw_engine.write_text((660, 5), "Step: " + str(evolution_step))
+
+    def _is_not_user_terminated(self):
+        return self.__draw_engine.is_active()