def check_model_2_constraints_FC(stu_model):
score = 0
print("---starting check_model_2_constraints_FC---")
try:
board = [[3, '.', 0, '.', 0, '<', 0], [0, '.', 0, '.', 0, '.', 0],
[0, '.', 0, '<', 0, '.', 0], [0, '.', 0, '>', 0, '.', 1]]
answer = [[3], [1, 2, 3, 4], [1, 2, 3, 4], [1, 2, 3, 4], [1, 2, 3, 4],
[1, 2, 3, 4], [1, 2, 3, 4], [1, 2, 3, 4], [1, 2, 3, 4],
[1, 2, 3, 4], [1, 2, 3, 4], [1, 2, 3, 4], [1, 2, 3, 4],
[1, 2, 3, 4], [1, 2, 3, 4], [1]]
csp, var_array = stu_model.futoshiki_csp_model_2(board)
lister = []
soln_propagators.prop_FC(csp)
for i in range(4):
for j in range(4):
lister.append(var_array[i][j].cur_domain())
if lister != answer:
print("FAILED\nExpected Output: %r\nOutput Received: %r" %
(answer, lister))
else:
print("PASS")
score = 2
except Exception:
print("Error occurred: %r" % traceback.print_exc())
print("---finished check_model_2_constraints_FC---\n")
return score
def three_queen_FC():
score = 0
try:
queens = nQueens(8)
curr_vars = queens.get_all_vars()
curr_vars[0].assign(4)
curr_vars[2].assign(1)
curr_vars[7].assign(5)
prop_FC(queens)
answer = [[4], [6, 7, 8], [1], [3, 6, 8], [6, 7], [2, 6, 8],
[2, 3, 7, 8], [5]]
var_vals = [x.cur_domain() for x in curr_vars]
if var_vals != answer:
details = "Failed three queens FC test: variable domains don't match expected results"
else:
score = 1
details = ""
except Exception:
details = "One or more runtime errors occurred while testing FC with three queens: %r" % traceback.format_exc(
)
return score, details
def check_model_1_constraints_FC(stu_model):
score = 0
print("---starting check_model_1_constraints_FC---")
try:
board = [[3,'.',0,'.',0,'<',0],
[0,'.',0,'.',0,'.',0],
[0,'.',0,'<',0,'.',0],
[0,'.',0,'>',0,'.',1]];
answer = [[3], [1, 2, 3, 4], [1, 2, 3, 4], [1, 2, 3, 4], [1, 2, 3, 4], [1, 2, 3, 4], [1, 2, 3, 4], [1, 2, 3, 4], [1, 2, 3, 4], [1, 2, 3, 4], [1, 2, 3, 4], [1, 2, 3, 4], [1, 2, 3, 4], [1, 2, 3, 4], [1, 2, 3, 4], [1]]
csp, var_array = stu_model.futoshiki_csp_model_1(board)
lister = []
soln_propagators.prop_FC(csp)
for i in range(4):
for j in range(4):
lister.append(var_array[i][j].cur_domain())
if lister != answer:
print("FAILED\nExpected Output: %r\nOutput Received: %r" % (answer,lister))
else:
print("PASS")
score = 2
except Exception:
print("Error occurred: %r" % traceback.print_exc())
print("---finished check_model_1_constraints_FC---\n")
return score
def test_simple_FC():
did_fail = False
score = 0
try:
queens = nQueens(8)
curr_vars = queens.get_all_vars()
curr_vars[0].assign(1)
prop_FC(queens, newVar=curr_vars[0])
answer = [[1], [3, 4, 5, 6, 7, 8], [2, 4, 5, 6, 7, 8],
[2, 3, 5, 6, 7, 8], [2, 3, 4, 6, 7, 8], [2, 3, 4, 5, 7, 8],
[2, 3, 4, 5, 6, 8], [2, 3, 4, 5, 6, 7]]
var_domain = [x.cur_domain() for x in curr_vars]
for i in range(len(curr_vars)):
if var_domain[i] != answer[i]:
details = "Failed simple FC test: variable domains don't match expected results"
did_fail = True
break
if not did_fail:
score = 1
details = ""
except Exception:
details = "One or more runtime errors occurred while testing simple FC: %r" % traceback.format_exc(
)
return score, details
def test_simple_FC(self):
queens = nQueens(8)
curr_vars = queens.get_all_vars()
curr_vars[0].assign(1)
propagators.prop_FC(queens,newVar=curr_vars[0])
answer = [[1],[3, 4, 5, 6, 7, 8],[2, 4, 5, 6, 7, 8],[2, 3, 5, 6, 7, 8],[2, 3, 4, 6, 7, 8],[2, 3, 4, 5, 7, 8],[2, 3, 4, 5, 6, 8],[2, 3, 4, 5, 6, 7]]
var_domain = [x.cur_domain() for x in curr_vars]
for i in range(len(curr_vars)):
self.assertEqual(var_domain[i], answer[i], "Failed simple FC test: variable domains don't match expected results")
def test_PMOK2_FC(
self): #tests the incorrect solution of a 4 queens problem
queens = nQueens(4)
cur_var = queens.get_all_vars()
cur_var[0].assign(4)
pruned = propagators.prop_FC(queens, newVar=cur_var[0])
self.assertTrue(pruned[0],
"Failed a FC test: returned DWO too early.1")
cur_var[1].assign(2)
pruned = propagators.prop_FC(queens, newVar=cur_var[1])
self.assertFalse(pruned[0], "Failed a FC test: did not return DWO.2")
def test_DWO_FC(self):
queens = nQueens(6)
cur_var = queens.get_all_vars()
cur_var[0].assign(2)
pruned = propagators.prop_FC(queens,newVar=cur_var[0])
self.assertTrue(pruned[0], "Failed a FC test: returned DWO too early.")
cur_var[1].assign(5)
pruned = propagators.prop_FC(queens,newVar=cur_var[1])
self.assertTrue(pruned[0], "Failed a FC test: returned DWO too early.")
cur_var[4].assign(1)
pruned = propagators.prop_FC(queens,newVar=cur_var[4])
self.assertFalse(pruned[0], "Failed a FC test: should have resulted in a DWO")
def test_PMOK_FC(self): #tests the correct solution of a 4 queens problem
queens = nQueens(4)
cur_var = queens.get_all_vars()
cur_var[0].assign(2)
pruned = propagators.prop_FC(queens, newVar=cur_var[0])
self.assertTrue(pruned[0], "Failed a FC test: returned DWO too early.")
cur_var[1].assign(4)
pruned = propagators.prop_FC(queens, newVar=cur_var[1])
self.assertTrue(pruned[0], "Failed a FC test: returned DWO too early.")
cur_var[2].assign(1)
pruned = propagators.prop_FC(queens, newVar=cur_var[2])
self.assertTrue(pruned[0], "Failed a FC test: returned DWO too early.")
cur_var[3].assign(3)
pruned = propagators.prop_FC(queens, newVar=cur_var[3])
self.assertTrue(pruned[0], "Failed a FC test: returned DWO too early.")
def val_lcv(csp, var):
'''
Assign a value (from the variable's domain) to the given variable
then leverage FC propagation to determine how many values are being pruned
due to the assignment. Return a sorted (according to the number of pruned values)
list of values.
'''
domain = var.cur_domain()
returnList = []
dictionary = {}
for value in domain:
var.assign(value)
garbage, prunedList = propagators.prop_FC(csp, var)
dictionary[value] = len(prunedList)
#reset
for variable, val in prunedList:
variable.unprune_value(val)
var.unassign()
#sort the dictionary according to the number of the pruned values
dictionarySorted = sorted(dictionary.items(), key=lambda x: x[1])
for key in dictionarySorted:
returnList.append(int(key[0]))
return returnList
def val_lcv(csp, var):
val_lcv = []
for val in var.cur_domain():
var.assign(val)
status, pruned = prop_FC(csp, var)
var.unassign()
for var_p, val_p in pruned:
var_p.unprune_value(val_p)
if status:
val_lcv.append((val, len(pruned)))
val_lcv.sort(key=lambda v: v[1])
return [v[0] for v in val_lcv]
