some more tests and improvements

performance.txt

@@ -9,3 +9,9 @@ SIZE: 21.7525MB			# process size 51,4 / main(75,9)
 
 TOTAL TIME: 0.1161s
 SIZE: 20.3338MB         # removed grid
+
+TOTAL TIME: 0.1792s 	# probably wrong calculated (asizeof was in there)
+SIZE: 20.2575MB			# Factory instead of grid
+
+TOTAL TIME: 0.1152s		# dict instead of list for cells
+SIZE: 20.2575MB			# process size 53 / 75,8

scripts/main_ui.py

@@ -4,7 +4,7 @@ from cellular_automaton.ca_cell_state import CellState
 from cellular_automaton.ca_rule import Rule
 
 from cellular_automaton.cellular_automaton import CellularAutomaton, CellularAutomatonProcessor
-from cellular_automaton.ca_factory import Factory
+from cellular_automaton.ca_factory import CAFactory
 
 
 class TestRule(Rule):
@@ -35,8 +35,7 @@ class MyState(CellState):
 
 
 def make_cellular_automaton(dimension, neighborhood, rule, state_class):
-    ca_factory = Factory()
-    cells = ca_factory.make_cellular_automaton(dimension=dimension, neighborhood=neighborhood, state_class=state_class)
+    cells = CAFactory.make_cellular_automaton(dimension=dimension, neighborhood=neighborhood, state_class=state_class)
     return CellularAutomaton(cells, dimension, rule)
 
 

src/cellular_automaton/__init__.py

@@ -0,0 +1,7 @@
+from .ca_cell import *
+from .ca_cell_state import *
+from .ca_display import *
+from .ca_factory import *
+from .ca_neighborhood import *
+from .ca_rule import *
+from .cellular_automaton import *

src/cellular_automaton/ca_cell.py

@@ -3,34 +3,34 @@ from typing import Type
 
 
 class Cell:
-    def __init__(self, state_class: Type[CellState], coordinate: list):
+    def __init__(self, state_class: Type[CellState], coordinate):
         self._coordinate = coordinate
-        self._state = state_class()
-        self._neighbours = []
+        self.state = state_class()
+        self.neighbours = []
 
     def set_neighbours(self, neighbours):
-        self._neighbours = neighbours
+        self.neighbours = neighbours
 
     def get_state(self):
-        return self._state
+        return self.state
 
     def get_coordinate(self):
         return self._coordinate
 
     def evolve_if_ready(self, rule, iteration):
-        if self._state.is_active(iteration):
-            new_state = rule(self._state.get_state_of_last_iteration(iteration), self.get_neighbour_states(iteration))
+        if self.state.is_active(iteration):
+            new_state = rule(self.state.get_state_of_last_iteration(iteration), self.get_neighbour_states(iteration))
             self.set_new_state_and_activate(new_state, iteration)
 
     def get_neighbour_states(self, index):
-        return [n.get_state_of_last_iteration(index) for n in self._neighbours]
+        return [n.get_state_of_last_iteration(index) for n in self.neighbours]
 
     def set_new_state_and_activate(self, new_state: CellState, iteration):
-        changed = self._state.set_state_of_iteration(new_state, iteration)
+        changed = self.state.set_state_of_iteration(new_state, iteration)
         if changed:
             self._set_active_for_next_iteration(iteration)
 
     def _set_active_for_next_iteration(self, iteration):
-        self._state.set_active_for_next_iteration(iteration)
-        for n in self._neighbours:
+        self.state.set_active_for_next_iteration(iteration)
+        for n in self.neighbours:
             n.set_active_for_next_iteration(iteration)

src/cellular_automaton/ca_display.py

@@ -60,11 +60,12 @@ class PyGameFor2D:
         running = True
         cellular_automaton_processor.evolve()
         first = True
+
         while running:
             pygame.event.get()
             time_ca_start = time.time()
             if first:
-                self._evolve_with_performance(cellular_automaton_processor, time_ca_start)
+                self._evolve_with_performance(cellular_automaton_processor)
                 first = False
             else:
                 cellular_automaton_processor.evolve()
@@ -73,9 +74,11 @@ class PyGameFor2D:
             time_ds_end = time.time()
             self._print_process_duration(time_ca_end, time_ca_start, time_ds_end)
 
-    def _evolve_with_performance(self, cap, time_ca_start):
+    def _evolve_with_performance(self, cap):
         size = asizeof.asizeof(self._cellular_automaton)
+        time_ca_start = time.time()
         cProfile.runctx("cap.evolve_x_times(10)", None, locals(), "performance_test")
+        time_ca_end = time.time()
         print("PERFORMANCE")
         p = pstats.Stats('performance_test')
         p.strip_dirs()
@@ -83,7 +86,6 @@ class PyGameFor2D:
         p.sort_stats('cumulative').print_stats(10)
         # sort by time spent in a function
         p.sort_stats('time').print_stats(10)
-        time_ca_end = time.time()
         print("TOTAL TIME: " + "{0:.4f}".format(time_ca_end - time_ca_start) + "s")
         print("SIZE: " + "{0:.4f}".format(size / (1024 * 1024)) + "MB")
 

src/cellular_automaton/ca_factory.py

@@ -1,61 +1,35 @@
 from cellular_automaton.ca_cell import Cell, CellState
 from cellular_automaton.ca_neighborhood import Neighborhood
 from typing import Type
+import itertools
 
 
-class Factory:
-    def __init__(self):
-        self._dimension = None
-        self._state_class = None
-        self._cells = {}
-
-    def make_cellular_automaton(self,
-                                dimension,
+class CAFactory:
+    @staticmethod
+    def make_cellular_automaton(dimension,
                                 neighborhood: Type[Neighborhood],
                                 state_class: Type[CellState]):
-        self._dimension = dimension
-        self._state_class = state_class
 
-        self.__create_cells()
-        self.__set_cell_neighbours(self._cells, neighborhood)
-        return tuple(self._cells.values())
+        cells = CAFactory._make_cells(dimension, state_class)
+        CAFactory._apply_neighbourhood_to_cells(cells, neighborhood, dimension)
+        return tuple(cells.values())
 
-    def __create_cells(self, dimension_index=0, coordinate=None):
-        """ Recursively steps down the dimensions to create cells in n dimensions and adds them to a dict.
-        :param dimension_index:     The index indicating which dimension is currently traversed.
-        :param coordinate:          The coordinate generated so far.
-                                    (each recursion adds one dimension to the coordinate.
-        """
-        coordinate = _instantiate_coordinate_if_necessary(coordinate)
+    @staticmethod
+    def _make_cells(dimension, state_class):
+        cells = {}
+        for c in itertools.product(*[range(d) for d in dimension]):
+            coordinate_string = _join_coordinate(c)
+            cells[coordinate_string] = Cell(state_class, c)
+        return cells
 
-        try:
-            self.__recursive_step_down_dimensions(coordinate, dimension_index)
-        except IndexError:
-            coordinate_string = _join_coordinate(coordinate)
-            self._cells[coordinate_string] = Cell(self._state_class, coordinate)
-
-    def __recursive_step_down_dimensions(self, coordinate, dimension_index):
-        """ For the range of the current dimension, recalls the recursion method.
-        :param coordinate:          The coordinate so far.
-        :param dimension_index:     The current dimension lvl.
-        """
-        for cell_index in range(self._dimension[dimension_index]):
-            new_cod = coordinate + [cell_index]
-            self.__create_cells(dimension_index + 1, new_cod)
-
-    def __set_cell_neighbours(self, cells, neighborhood):
+    @staticmethod
+    def _apply_neighbourhood_to_cells(cells, neighborhood, dimension):
         for cell in cells.values():
             n_coordinates = neighborhood.calculate_cell_neighbor_coordinates(cell.get_coordinate(),
-                                                                             self._dimension)
+                                                                             dimension)
             cell.set_neighbours([cells[_join_coordinate(coordinate)].get_state() for coordinate in n_coordinates])
 
 
-def _instantiate_coordinate_if_necessary(coordinate):
-    if coordinate is None:
-        coordinate = []
-    return coordinate
-
-
 def _join_coordinate(coordinate):
     return '-'.join(str(x) for x in coordinate)
 

src/cellular_automaton/cellular_automaton.py

@@ -14,10 +14,11 @@ class CellularAutomaton:
 class CellularAutomatonProcessor:
     def __init__(self, cellular_automaton, process_count: int = 1):
         self.ca = cellular_automaton
+        cells = {i: self.ca.cells[i] for i in range(len(self.ca.cells))}
         self.evolve_range = range(len(self.ca.cells))
         self.pool = multiprocessing.Pool(processes=process_count,
                                          initializer=_init_process,
-                                         initargs=(self.ca.cells,
+                                         initargs=(cells,
                                                    self.ca.evolution_rule,
                                                    self.ca.evolution_iteration_index))
         for cell in self.ca.cells:

test/test_factory.py

@@ -0,0 +1,50 @@
+import sys
+sys.path.append('../src')
+
+from cellular_automaton import *
+import unittest
+import mock
+
+
+class TestFac(CAFactory):
+    @staticmethod
+    def make_cells(dimension, state_class):
+        return CAFactory._make_cells(dimension, state_class)
+
+    @staticmethod
+    def apply_neighbourhood(cells, neighborhood, dimension):
+        return CAFactory._apply_neighbourhood_to_cells(cells, neighborhood, dimension)
+
+
+class TestCAFactory(unittest.TestCase):
+    def test_make_ca_calls_correct_methods(self):
+        with mock.patch.object(CAFactory, '_make_cells', return_value={1: True}) as m1:
+            with mock.patch.object(CAFactory, '_apply_neighbourhood_to_cells') as m2:
+                CAFactory.make_cellular_automaton([10], Neighborhood, CellState)
+                m1.assert_called_once_with([10], CellState)
+                m2.assert_called_once_with({1: True}, Neighborhood, [10])
+
+    def test_make_ca_returns_correct_values(self):
+        with mock.patch.object(CAFactory, '_make_cells', return_value={1: True}):
+            with mock.patch.object(CAFactory, '_apply_neighbourhood_to_cells'):
+                cells = CAFactory.make_cellular_automaton([10], Neighborhood, CellState)
+                self.assertEqual(cells, (True, ))
+
+    def test_1dimension_coordinates(self):
+        fac = TestFac()
+        c = fac.make_cells([3], CellState)
+        self.assertEqual(list(c.keys()), ['0', '1', '2'])
+
+    def test_2dimension_coordinates(self):
+        fac = TestFac()
+        c = fac.make_cells([2, 2], CellState)
+        self.assertEqual(list(c.keys()), ['0-0', '0-1', '1-0', '1-1'])
+
+    def test_3dimension_coordinates(self):
+        fac = TestFac()
+        c = fac.make_cells([2, 2, 2], CellState)
+        self.assertEqual(list(c.keys()), ['0-0-0', '0-0-1', '0-1-0', '0-1-1', '1-0-0', '1-0-1', '1-1-0', '1-1-1'])
+
+
+if __name__ == '__main__':
+    unittest.main()

test/test_neighborhood.py

@@ -5,8 +5,9 @@ import cellular_automaton.ca_neighborhood as csn
 import unittest
 
 
-class TestCellState(unittest.TestCase):
-    def check_neighbors(self, neighborhood, neighborhood_sets):
+class TestNeighborhood(unittest.TestCase):
+    @staticmethod
+    def check_neighbors(neighborhood, neighborhood_sets):
         for neighborhood_set in neighborhood_sets:
             neighbors = neighborhood.calculate_cell_neighbor_coordinates(neighborhood_set[0], [3, 3])
             if neighborhood_set[1] != neighbors: