diff --git a/Search_Algorithms/Heuristics.py b/Search_Algorithms/Heuristics.py
index cf5fa56e4ecf28ebb02ed4b1b7cbdab6de3b6d7a..069822967d37b2b015a5c8934b009fab4dd1abd4 100644
--- a/Search_Algorithms/Heuristics.py
+++ b/Search_Algorithms/Heuristics.py
@@ -1,4 +1,5 @@
import is_goal
+import Sucessors
@@ -16,21 +17,9 @@ def puzzle_opt(path):
def sudoku_opt(path):
- # state = path[-1]
- # box_value, row_value, col_value = 0, 0, 0
- # # check each box to see the least empty
- # for down in range(0, 9, 3):
- # for across in range(0, 9, 3):
- # box_value += 9 - ()
- # box_value = 0
- #
- # # check each row for the one with the least zeros
- # row_value = 0
- #
- # # check each column for the one with the least zeros
- # col_value = 0
-
- pass
+ starting_point = [Sucessors.choose_best_subsquare(path[-1]), Sucessors.choose_best_rows(path[-1]),
+ Sucessors.choose_best_column(path[-1])]
+ return max(starting_point, key=lambda w: w[2])[-1]
def queens_opt(path):
diff --git a/Search_Algorithms/Search_Algorithms.py b/Search_Algorithms/Search_Algorithms.py
index 6558e36bc21821219080d2e28ef2e19f9af02bee..242844794e9e912521abe6ecebd62712c4509f81 100644
--- a/Search_Algorithms/Search_Algorithms.py
+++ b/Search_Algorithms/Search_Algorithms.py
@@ -34,7 +34,6 @@ def DepthFirstSearch(state, successor, isgoal):
if next_state not in explored:
explored.add(next_state)
path2 = path + [next_state]
- print(path2)
toDo.append(path2)
return "Error Path not found"
diff --git a/Search_Algorithms/Sucessors.py b/Search_Algorithms/Sucessors.py
index 0de1748da760bb55db475c1c3638c8c07ff0795f..1baefd29db00388c8318db08115f39e8c272ebc6 100644
--- a/Search_Algorithms/Sucessors.py
+++ b/Search_Algorithms/Sucessors.py
@@ -9,11 +9,8 @@ def maze_successor(state):
def sudoku_successor(state):
new_state = list(map(list, state)) # Convert state to a list of lists
- y, x = -1, -1
- for i, s in enumerate(state):
- if 0 in s:
- (y, x) = (i, s.index(0))
- break
+ starting_point = [choose_best_subsquare(new_state), choose_best_rows(new_state), choose_best_column(new_state)]
+ x, y, dummy = max(starting_point, key=lambda w: w[2])
next_states = []
for j in range(1, len(new_state) + 1):
new_state[y][x] = j
@@ -22,45 +19,6 @@ def sudoku_successor(state):
return next_states
-def maze_allowed(state):
- maze = [[' ', 'W', ' ', ' ', 'G'],
- [' ', 'W', ' ', 'W', ' '],
- [' ', 'W', ' ', ' ', ' '],
- [' ', ' ', 'W', 'W', ' '],
- [' ', ' ', ' ', ' ', ' ']]
- if state[0] >= len(maze[0]) or state[0] < 0:
- return False
- if state[1] >= len(maze) or state[1] < 0:
- return False
- return maze[state[0]][state[1]] == ' ' or maze[state[0]][state[1]] == 'G'
-
-
-def sudoku_allowed(state):
- (y, x, grid) = state
- """I'm making the state a triple on this one"""
- # (y, x, z): x,y is the coordinate and z is the value in the square
-
- # check if still inside the box
- if y < 0 or y >= len(grid[0]):
- return False
- if x < 0 or x >= len(grid):
- return False
-
- # inspect columns and rows
- if ([row[x] for row in grid].count(grid[y][x]) > 1) or (grid[y].count(grid[y][x]) > 1):
- return False
-
- # inspect minor square in teh sudoku
- inner_x = ((x - (x % 3)), (x - (x % 3) + 3))
- inner_y = (y - (y % 3))
- inner_square = grid[inner_y][inner_x[0]:inner_x[1]] + grid[inner_y + 1][inner_x[0]:inner_x[1]] + \
- grid[inner_y + 2][inner_x[0]:inner_x[1]]
- if inner_square.count(grid[y][x]) > 1:
- return False
-
- return True
-
-
def puzzle_successor(state):
y, x = -1, -1
for i in range(len(state)):
@@ -103,10 +61,52 @@ def queens_successor(state):
return next_states
+# Allowed moves Functions
def puzzle_allowed(state):
return True
+
+def maze_allowed(state):
+ maze = [[' ', 'W', ' ', ' ', 'G'],
+ [' ', 'W', ' ', 'W', ' '],
+ [' ', 'W', ' ', ' ', ' '],
+ [' ', ' ', 'W', 'W', ' '],
+ [' ', ' ', ' ', ' ', ' ']]
+ if state[0] >= len(maze[0]) or state[0] < 0:
+ return False
+ if state[1] >= len(maze) or state[1] < 0:
+ return False
+ return maze[state[0]][state[1]] == ' ' or maze[state[0]][state[1]] == 'G'
+
+
+def sudoku_allowed(state):
+ (y, x, grid) = state
+ """I'm making the state a triple on this one"""
+ # (y, x, z): x,y is the coordinate and z is the value in the square
+
+ # check if still inside the box
+ if y < 0 or y >= len(grid[0]):
+ return False
+ if x < 0 or x >= len(grid):
+ return False
+
+ # inspect columns and rows
+ if ([row[x] for row in grid].count(grid[y][x]) > 1) or (grid[y].count(grid[y][x]) > 1):
+ return False
+
+ # inspect minor square in teh sudoku
+ inner_x = ((x - (x % 3)), (x - (x % 3) + 3))
+ inner_y = (y - (y % 3))
+ inner_square = grid[inner_y][inner_x[0]:inner_x[1]] + grid[inner_y + 1][inner_x[0]:inner_x[1]] + \
+ grid[inner_y + 2][inner_x[0]:inner_x[1]]
+ if inner_square.count(grid[y][x]) > 1:
+ return False
+
+ return True
+
+
+
def queens_allowed(state):
"""in this case the state is also y, x, grid"""
y, x, grid = state
@@ -137,3 +137,49 @@ def queens_allowed(state):
return False
return True
+
+
+# Helper Functions
+def choose_best_rows(grid):
+ best_row = -1
+ x = -1
+ min_empty = len(grid)
+ for i in range(len(grid)):
+ empty_cells = grid[i].count(0)
+ if 0 < empty_cells < min_empty:
+ best_row = i
+ min_empty = empty_cells
+ x = grid[i].index(0)
+ return x, best_row, min_empty
+
+
+def choose_best_column(grid):
+ best_col = -1
+ y = -1
+ min_empty = len(grid)
+ for i in range(len(grid)):
+ col = [row[i] for row in grid]
+ empty_cells = col.count(0)
+ if 0 < empty_cells < min_empty:
+ best_col = i
+ min_empty = empty_cells
+ y = col.index(0)
+ return best_col, y, min_empty
+
+
+def choose_best_subsquare(grid):
+ x = -1
+ y = -1
+ best_val = len(grid)
+ for down in range(0, 9, 3):
+ for across in range(0, 9, 3):
+ subsquare = [grid[i][across: across + 3] for i in range(down, down + 3)]
+ zeros = sum([subsquare[i].count(0) for i in range(len(subsquare))])
+ if 0 < zeros < best_val:
+ best_val = zeros
+ for j in range(len(subsquare)):
+ if 0 in subsquare[j]:
+ x = across + subsquare[j].index(0)
+ y = down + j
+ break
+ return (x, y, best_val)
diff --git a/Search_Algorithms/solution testing.py b/Search_Algorithms/solution testing.py
index d34c13505f48ef42031e591b23861a05497c1c51..6a537e262497f2d05956953e95819e3a2f8807e1 100644
--- a/Search_Algorithms/solution testing.py
+++ b/Search_Algorithms/solution testing.py
@@ -5,26 +5,29 @@ import Heuristics
# Maze Problem, note, the maze is fixed in the allowed state.
-# print(Search_Algorithms.BreadthFirstSearch((4, 0), Sucessors.maze_successor, is_goal.is_goal_maze))
+print(Search_Algorithms.BreadthFirstSearch((4, 0), Sucessors.maze_successor, is_goal.is_goal_maze))
# Sudoku
-grid = ((1, 0, 0, 0, 0, 0, 0, 0, 0),
- (0, 0, 0, 0, 0, 0, 0, 0, 0),
- (0, 0, 0, 0, 0, 0, 0, 0, 0),
- (0, 0, 0, 0, 0, 0, 0, 0, 0),
- (0, 0, 0, 0, 0, 0, 0, 0, 0),
- (0, 0, 0, 0, 0, 0, 0, 0, 0),
- (0, 0, 0, 0, 0, 0, 0, 0, 0),
- (0, 0, 0, 0, 0, 0, 0, 0, 0),
+grid = ((5, 3, 0, 0, 7, 0, 0, 0, 0),
+ (6, 0, 0, 1, 9, 5, 0, 0, 0),
+ (0, 9, 8, 0, 0, 0, 0, 6, 0),
+ (8, 0, 0, 0, 6, 0, 0, 0, 3),
+ (4, 0, 0, 8, 0, 3, 0, 0, 1),
+ (7, 0, 0, 0, 2, 0, 0, 0, 6),
+ (0, 6, 0, 0, 0, 0, 2, 8, 0),
+ (0, 0, 0, 4, 1, 9, 0, 0, 5),
(0, 0, 0, 0, 8, 0, 0, 0, 0))
-# sln = (Search_Algorithms.BreadthFirstSearch(grid, Sucessors.sudoku_successor, is_goal.is_goal_sudoku)[-1])
+sln = (Search_Algorithms.BreadthFirstSearch(grid, Sucessors.sudoku_successor, is_goal.is_goal_sudoku)[-1])
-# sln = (Search_Algorithms.DepthFirstSearch(
-# grid, Sucessors.sudoku_successor, is_goal.is_goal_sudoku)[-1])
+for rows in sln:
+ print(rows)
+print("--------------------------------")
+sln = (Search_Algorithms.DepthFirstSearch(
+ grid, Sucessors.sudoku_successor, is_goal.is_goal_sudoku)[-1])
#
-# for rows in sln:
-# print(rows)
+for rows in sln:
+ print(rows)
# N Queens
board = ((False, False, False, False, False, False, False, False, False),
@@ -38,15 +41,15 @@ board = ((False, False, False, False, False, False, False, False, False),
(False, False, False, False, False, False, False, False, False))
-# sln = (Search_Algorithms.BreadthFirstSearch(board, Sucessors.queens_successor, is_goal.is_goal_queens)[-1])
-#
+sln = (Search_Algorithms.BreadthFirstSearch(board, Sucessors.queens_successor, is_goal.is_goal_queens)[-1])
+
# sln = (Search_Algorithms.DepthFirstSearch(
# board, Sucessors.queens_successor, is_goal.is_goal_queens)[-1])
-#
-# output_tuple = tuple(tuple("Q" if value else "." for value in sln)
-# for sln in sln)
-# for rows in output_tuple:
-# print(rows)
+
+output_tuple = tuple(tuple("Q" if value else "." for value in sln)
+ for sln in sln)
+for rows in output_tuple:
+ print(rows)
# Sliding Puzzle
@@ -55,14 +58,14 @@ initial_puzzle = (
(5, 0, 6),
(8, 3, 1)
)
-#
-# sln = (Search_Algorithms.BreadthFirstSearch(initial_puzzle, Sucessors.puzzle_successor, is_goal.is_goal_puzzle)[-1])
-#
-# if sln:
-# for rows in sln:
-# print(rows)
-# else:
-# print("No solution found")
+
+sln = (Search_Algorithms.BreadthFirstSearch(initial_puzzle, Sucessors.puzzle_successor, is_goal.is_goal_puzzle)[-1])
+
+if sln:
+ for rows in sln:
+ print(rows)
+else:
+ print("No solution found")
#
# sln = (Search_Algorithms.DepthFirstSearch(initial_puzzle, Sucessors.puzzle_successor, is_goal.is_goal_puzzle)[-1])
@@ -73,7 +76,13 @@ initial_puzzle = (
# else:
# print("No solution found")
-print(Search_Algorithms.A_StarSearch((4, 0), Sucessors.maze_successor, is_goal.is_goal_maze, Heuristics.maze_opt))
+# print(Search_Algorithms.A_StarSearch((4, 0), Sucessors.maze_successor, is_goal.is_goal_maze, Heuristics.maze_opt))
+
+sln = (Search_Algorithms.A_StarSearch(grid, Sucessors.sudoku_successor,
+ is_goal.is_goal_sudoku, Heuristics.sudoku_opt))[-1]
+
+for rows in sln:
+ print(rows)