Beispiel #1
0
    def test_methods(self):
        self.node1 = NavNode(Point(x=0, y=0), 2, 4)
        self.node1.calculate_f()
        self.node2 = NavNode(Point(x=1, y=0), 2, 3)
        self.node2.calculate_f()
        self.node3 = NavNode(Point(x=2, y=0), 2, 2)
        self.node3.calculate_f()
        self.node4 = NavNode(Point(x=2, y=1), 2, 1)
        self.node4.calculate_f()
        self.node5 = NavNode(Point(x=2, y=0), 3, 2)  # like node3

        my_collection = NodePrioritySet()
        my_collection.add(self.node2, self.node2.f)
        my_collection.add(self.node1, self.node1.f)
        my_collection.add(self.node3, self.node3.f)

        self.assertFalse(my_collection.is_empty())

        self.assertTrue(self.node1 in my_collection)
        self.assertTrue(self.node2 in my_collection)
        self.assertTrue(self.node3 in my_collection)
        self.assertFalse(self.node4 in my_collection)
        self.assertTrue(self.node5
                        in my_collection)  # node5 has same position as node3

        self.assertEquals(my_collection[self.node1], self.node1)
        self.assertEquals(my_collection[self.node5], self.node3)

        self.assertEquals(my_collection.pop(), self.node3)
        self.assertEquals(my_collection.pop(), self.node2)
        self.assertEquals(my_collection.pop(), self.node1)

        self.assertTrue(my_collection.is_empty())
        self.assertFalse(self.node1 in my_collection)
Beispiel #2
0
    def test_methods(self):
        self.node1 = NavNode(Point(x=0, y=0), 2, 4)
        self.node1.calculate_f()
        self.node2 = NavNode(Point(x=1, y=0), 2, 3)
        self.node2.calculate_f()
        self.node3 = NavNode(Point(x=2, y=0), 2, 2)
        self.node3.calculate_f()
        self.node4 = NavNode(Point(x=2, y=1), 2, 1)
        self.node4.calculate_f()
        self.node5 = NavNode(Point(x=2, y=0), 3, 2)  # like node3

        my_collection = NodePrioritySet()
        my_collection.add(self.node2, self.node2.f)
        my_collection.add(self.node1, self.node1.f)
        my_collection.add(self.node3, self.node3.f)

        self.assertFalse(my_collection.is_empty())

        self.assertTrue(self.node1 in my_collection)
        self.assertTrue(self.node2 in my_collection)
        self.assertTrue(self.node3 in my_collection)
        self.assertFalse(self.node4 in my_collection)
        self.assertTrue(self.node5 in my_collection)  # node5 has same position as node3

        self.assertEquals(my_collection[self.node1], self.node1)
        self.assertEquals(my_collection[self.node5], self.node3)

        self.assertEquals(my_collection.pop(), self.node3)
        self.assertEquals(my_collection.pop(), self.node2)
        self.assertEquals(my_collection.pop(), self.node1)

        self.assertTrue(my_collection.is_empty())
        self.assertFalse(self.node1 in my_collection)
Beispiel #3
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    def test_first_in_first_out(self):
        self.node1 = NavNode(Point(x=0, y=2), 2, 2)
        self.node2 = NavNode(Point(x=1, y=1), 2, 2)
        self.node3 = NavNode(Point(x=2, y=0), 2, 2)

        my_collection = NodePrioritySet()
        my_collection.add(self.node1, 4)
        my_collection.add(self.node2, 4)
        my_collection.add(self.node3, 4)

        self.assertEquals(my_collection.pop(), self.node3)
        self.assertEquals(my_collection.pop(), self.node2)
        self.assertEquals(my_collection.pop(), self.node1)
Beispiel #4
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    def test_first_in_first_out(self):
        self.node1 = NavNode(Point(x=0, y=2), 2, 2)
        self.node2 = NavNode(Point(x=1, y=1), 2, 2)
        self.node3 = NavNode(Point(x=2, y=0), 2, 2)

        my_collection = NodePrioritySet()
        my_collection.add(self.node1, 4)
        my_collection.add(self.node2, 4)
        my_collection.add(self.node3, 4)

        self.assertEquals(my_collection.pop(), self.node3)
        self.assertEquals(my_collection.pop(), self.node2)
        self.assertEquals(my_collection.pop(), self.node1)
Beispiel #5
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    def run(self, start_node):
        """
        Run the A* algorithm
        start_node: must be an instance of a subclass of BaseNode
        """
        open_list = NodePrioritySet()
        closed_list = {}
        start_node.calculate_h()
        start_node.calculate_f()
        open_list.add(start_node, start_node.f)

        def attach_and_eval(parent_node, child_node):
            child_node.set_g(parent_node.g + parent_node.get_arc_cost(child_node))
            child_node.calculate_h()
            child_node.calculate_f()
            child_node.set_parent(parent_node)

        def print_stats(_current_node, _closed_list, _open_list, _num_nodes_popped, _print_path):
            print "number of nodes created:", len(_closed_list) + len(_open_list.dict)
            print "number of nodes popped:", _num_nodes_popped
            print "path length:", len(_current_node.get_ancestors())
            if _print_path:
                print "backtracked nodes that led to the solution:"
                print current_node
                for ancestor in ancestors:
                    print ancestor

        # If the algorithm still hasn't found a solution after the max number of iterations,
        # then the algorithm will stop
        max_num_iterations = 50000000
        current_node = None
        num_nodes_popped = 0
        for num_iterations in xrange(max_num_iterations):
            if open_list.is_empty():
                print 'Failed to find a solution'
                print_stats(current_node, closed_list, open_list, num_nodes_popped, self.print_path)
                return False, current_node
            current_node = open_list.pop()
            num_nodes_popped += 1
            closed_list[current_node] = current_node
            if not self.disable_gfx and num_iterations % self.draw_every == 0:
                ancestors = current_node.get_ancestors()
                self.draw(current_node, ancestors, closed_list, open_list)  # draw current state
            if current_node.is_solution():
                print_stats(current_node, closed_list, open_list, num_nodes_popped, self.print_path)
                return True, current_node
            children = current_node.generate_children()
            for child in children:
                previously_generated = False
                if child in open_list:
                    child = open_list[child]  # re-use previously generated node
                    previously_generated = True
                elif child in closed_list:
                    child = closed_list[child]  # re-use previously generated node
                    previously_generated = True

                if not previously_generated:
                    attach_and_eval(current_node, child)
                    open_list.add(child, child.f)
                elif current_node.g + current_node.get_arc_cost(child) < child.g:
                    attach_and_eval(current_node, child)

        print 'Failed to find a solution within the max number of iterations,', max_num_iterations
        print_stats(current_node, closed_list, open_list, num_nodes_popped, self.print_path)
        return False, current_node
Beispiel #6
0
    def run(self, start_node):
        """
        Run the A* algorithm
        start_node: must be an instance of a subclass of BaseNode
        """
        open_list = NodePrioritySet()
        closed_list = {}
        start_node.calculate_h()
        start_node.calculate_f()
        open_list.add(start_node, start_node.f)

        def attach_and_eval(parent_node, child_node):
            child_node.set_g(parent_node.g +
                             parent_node.get_arc_cost(child_node))
            child_node.calculate_h()
            child_node.calculate_f()
            child_node.set_parent(parent_node)

        def print_stats(_current_node, _closed_list, _open_list,
                        _num_nodes_popped, _print_path):
            print "number of nodes created:", len(_closed_list) + len(
                _open_list.dict)
            print "number of nodes popped:", _num_nodes_popped
            print "path length:", len(_current_node.get_ancestors())
            if _print_path:
                print "backtracked nodes that led to the solution:"
                print current_node
                for ancestor in ancestors:
                    print ancestor

        # If the algorithm still hasn't found a solution after the max number of iterations,
        # then the algorithm will stop
        max_num_iterations = 50000000
        current_node = None
        num_nodes_popped = 0
        for num_iterations in xrange(max_num_iterations):
            if open_list.is_empty():
                print 'Failed to find a solution'
                print_stats(current_node, closed_list, open_list,
                            num_nodes_popped, self.print_path)
                return False, current_node
            current_node = open_list.pop()
            num_nodes_popped += 1
            closed_list[current_node] = current_node
            if not self.disable_gfx and num_iterations % self.draw_every == 0:
                ancestors = current_node.get_ancestors()
                self.draw(current_node, ancestors, closed_list,
                          open_list)  # draw current state
            if current_node.is_solution():
                print_stats(current_node, closed_list, open_list,
                            num_nodes_popped, self.print_path)
                return True, current_node
            children = current_node.generate_children()
            for child in children:
                previously_generated = False
                if child in open_list:
                    child = open_list[
                        child]  # re-use previously generated node
                    previously_generated = True
                elif child in closed_list:
                    child = closed_list[
                        child]  # re-use previously generated node
                    previously_generated = True

                if not previously_generated:
                    attach_and_eval(current_node, child)
                    open_list.add(child, child.f)
                elif current_node.g + current_node.get_arc_cost(
                        child) < child.g:
                    attach_and_eval(current_node, child)

        print 'Failed to find a solution within the max number of iterations,', max_num_iterations
        print_stats(current_node, closed_list, open_list, num_nodes_popped,
                    self.print_path)
        return False, current_node