init commit

CS3243_P2_Sudoku_XX.py

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+# CS3243 Introduction to Artificial Intelligence
+# Project 2, Part 1: Sudoku
+
+import sys
+import copy
+from collections import deque
+
+# Running script: given code can be run with the command:
+# python file.py, ./path/to/init_state.txt ./output/output.txt
+
+class Sudoku(object):
+    def __init__(self, puzzle):
+        # you may add more attributes if you need
+        self.puzzle = puzzle # self.puzzle is a list of lists
+        self.ans = copy.deepcopy(puzzle) # self.ans is a list of lists
+        self.csp = CSP(puzzle)
+
+    def solve(self):
+        self.AC3(self.csp)
+        assignment = self.backtrackingSearch(self.csp)
+        if not assignment:
+            return False
+        for (i, j) in assignment:
+            self.ans[i][j] = assignment[(i, j)]
+        # self.ans is a list of lists
+        return self.ans
+
+    # you may add more classes/functions if you think is useful
+    # However, ensure all the classes/functions are in this file ONLY
+    # Note that our evaluation scripts only call the solve method.
+    # Any other methods that you write should be used within the solve() method.
+
+
+    def AC3(self, csp):
+        arc_q = deque()
+        for cons in csp.constraints:
+            arc_q.append(cons)
+
+        while arc_q:
+            (xi, xj) = arc_q.popleft()
+            if self.revise(csp, xi, xj):
+                if not xi.domain:
+                    return False
+                for xk in xi.neighbour:
+                    if xk != xj:
+                        arc_q.append((xk, xi))
+        return True
+
+    def revise(self, csp, xi, xj):
+        revised = False
+        for x in xi.domain:
+            if all(map(lambda y : csp.constraints[(xi, xj)](x, y), xj.domain)):
+                xi.domain.remove(x)
+        return revised
+
+    def backtrackingSearch(self, csp):
+        return self.backtrack(csp)
+
+    def backtrack(self, csp, assignment = dict()):
+        if self.complete(assignment):
+            return assignment
+        var = self.selectUnassignedVariable(csp, assignment)
+        for value in self.orderDomainValue(var, assignment, csp):
+            if self.isConsistent(value, assignment, csp):
+                assignment[var] = value
+                # self.printAssignment(assignment)
+                var.value = value
+                # inferences = self.inference(csp, var, value)
+                # if not inferences:
+                    # add inferences to assignment
+                result = self.backtrack(csp, assignment)
+                if not result:
+                    return result
+        del assignment[var]
+        var.value = 0
+        # del inferences from assignment
+        return False
+
+    def isConsistent(self, value, assignment, csp):
+        return not any(map(lambda key : csp.constraints[key](key), csp.constraints))
+
+    def complete(self, assignment):
+        return len(assignment) == 81
+
+    def selectUnassignedVariable(self, csp, assignment):
+        ''' using minimum remaining values '''
+        # Maintain a PQ in csp might be more efficient
+        lst = sorted(list(filter(lambda var: var not in assignment, csp.variables)), key = lambda var : len(var.domain))
+        return lst[0]
+
+    def orderDomainValue(self, var, assignment, csp):
+        ''' using least constraining values '''
+        # lst = sorted(list(var.domain), key = csp.variables.numConstrainingValues)
+        lst = list(var.domain)
+        return lst
+
+    def inference(self, csp, var, value):
+        return 0
+
+    def printAssignment(self, assignment):
+        for key, value in assignment.items():
+            print(key, value)
+
+class CSP(object):
+    def __init__(self, puzzle):
+        self.variables = list()  # set of var (tuple representing indexes)
+
+        # self.domains = dict()   # key = var, value = var_domain (set)
+        # self.neighbour = dict() # key = var, value = var_neighbour (set)
+        # TODO change AC3 and backtrack
+
+        # set of binary constraints (constraint function involving two var) represented by pair(scope, relation)
+        # scope = (x, y), relation = f(x, y), where x, y are vars
+        self.constraints = dict()
+        self.initialiseCSP(puzzle)
+        for var in self.variables:
+            print(var.coordinate, var.value)
+        # self.currDomains = None
+        return
+
+    # def allowsPruning(self):
+    #     ''' Create a copy of domains as currDomains '''
+    #     self.currDomains = dict()
+    #     for var in self.domains:
+    #         self.currDomains[var] = self.domains[var]
+    #     return
+
+    def initialiseCSP(self, puzzle):
+        # going through 2d list
+        for i in range(9):
+            for j in range(9):
+                self.variables.append(Variable((i,j), puzzle[i][j]))
+
+        # going through var set
+        for var1 in self.variables:
+            # self.domains[var1] = {1, 2, 3, 4, 5, 6, 7, 8, 9} if not var1.value else {var1.value}
+            # self.neighbour[var1] = set()
+            for var2 in self.variables:
+                if var1 != var2 and var1.isSameUnit(var2):
+                    # self.constraints[(var1, var2)] = self.conflict
+                    # self.neighbour[var1].add(var2)
+                    var1.neighbour.add(var2)
+        return
+
+    def conflict(self, var1, var2):
+        ''' var1 and var2 are in conflict when they having same value,
+        only comparing vars in same unit (represent by arc) '''
+        return var1 == var2
+
+class Variable(object):
+    def __init__(self, coordinate, value):
+        self.coordinate = coordinate    # (x, y)
+        self.value = value
+        self.domain = {1, 2, 3, 4, 5, 6, 7, 8, 9} if not value else {value}
+        self.neighbour = set()
+        self.degree = len(self.neighbour)
+        return
+
+    def __hash__(self):
+        return hash(self.coordinate)
+
+    def __eq__(self, var):
+        return self.coordinate == var.coordinate
+
+    def __str__(self):
+        return str(self.coordinate)
+
+    def isSameUnit(self, var):
+        return self.isSameRow(var) or self.isSameCol(var) or self.isSameSquare(var) 
+
+    def isSameRow(self, var):
+        return self.coordinate[0] == var.coordinate[0]
+
+    def isSameCol(self, var):
+        return self.coordinate[1] == var.coordinate[1]
+
+    def isSameSquare(self, var):
+        ''' square refers to 3*3 square '''
+        return (self.coordinate[0]//3, self.coordinate[1]//3) == (var.coordinate[0]//3, var.coordinate[1]//3)
+
+if __name__ == "__main__":
+    # STRICTLY do NOT modify the code in the main function here
+    if len(sys.argv) != 3:
+        print ("\nUsage: python CS3243_P2_Sudoku_XX.py input.txt output.txt\n")
+        raise ValueError("Wrong number of arguments!")
+
+    try:
+        f = open(sys.argv[1], 'r')
+    except IOError:
+        print ("\nUsage: python CS3243_P2_Sudoku_XX.py input.txt output.txt\n")
+        raise IOError("Input file not found!")
+
+    puzzle = [[0 for i in range(9)] for j in range(9)]
+    lines = f.readlines()
+
+    i, j = 0, 0
+    for line in lines:
+        for number in line:
+            if '0' <= number <= '9':
+                puzzle[i][j] = int(number)
+                j += 1
+                if j == 9:
+                    i += 1
+                    j = 0
+
+    sudoku = Sudoku(puzzle)
+    ans = sudoku.solve()
+    print(ans)
+    with open(sys.argv[2], 'a') as f:
+        for i in range(9):
+            for j in range(9):
+                f.write(str(ans[i][j]) + " ")
+            f.write("\n")