def run(self):
print('K VALUE: ', self.k)
domain = [x for x in range(1, self.k + 1)]
function = make_function(['x, y'], 'x != y')
gac = GAC()
nodes = {}
constraints = {}
for node in sorted(self.board.graph.nodes()):
id = str(node)
var = Variable(id)
nodes[id] = var
var.domain = domain
# gac.variables.append(var)
for key in nodes.keys():
constraints[key] = self.board.graph.neighbors(key)
constraint = Constraint()
constraint.function = function
state = CSPState()
state.constraints = constraints
state.constraint = constraint
state.variables = nodes
state.gac = gac
gac.state = state
astar_csp = AstarCSP()
astar_csp.csp_state = state
astar_csp.initialize()
for r in astar_csp.run():
if r[0]:
s = r[0][-1]
self.redraw_nodes_with_color(s)
#self.color_node(s.colored_node)
unsatisfied = [(len(x.domain) - 1)
for x in gac.state.variables.values()]
without_assignments = [
1 for x in gac.state.variables.values()
if len(x.domain) > 1
]
print('UNSATISFIED CONSTRAINTS: {}'.format(sum(unsatisfied)))
print('Vertices without assignments: {}'.format(
sum(without_assignments)))
print('Nodes in seachtree: {}'.format(len(r[1])))
print('Number of expanded: {}'.format(len(r[2])))
def run(self):
print('K VALUE: ', self.k)
domain = [x for x in range(1, self.k + 1)]
function = make_function(['x, y'], 'x != y')
gac = GAC()
nodes = {}
constraints = {}
for node in sorted(self.board.graph.nodes()):
id = str(node)
var = Variable(id)
nodes[id] = var
var.domain = domain
# gac.variables.append(var)
for key in nodes.keys():
constraints[key] = self.board.graph.neighbors(key)
constraint = Constraint()
constraint.function = function
state = CSPState()
state.constraints = constraints
state.constraint = constraint
state.variables = nodes
state.gac = gac
gac.state = state
astar_csp = AstarCSP()
astar_csp.csp_state = state
astar_csp.initialize()
for r in astar_csp.run():
if r[0]:
s = r[0][-1]
self.redraw_nodes_with_color(s)
#self.color_node(s.colored_node)
unsatisfied = [(len(x.domain)-1) for x in gac.state.variables.values()]
without_assignments = [1 for x in gac.state.variables.values() if len(x.domain) > 1]
print('UNSATISFIED CONSTRAINTS: {}'.format(sum(unsatisfied)))
print('Vertices without assignments: {}'.format(sum(without_assignments)))
print('Nodes in seachtree: {}'.format(len(r[1])))
print('Number of expanded: {}'.format(len(r[2])))
def run(self):
gac = NonogramGAC()
nodes = {}
function = make_function(['x', 'y'], 'x == y') #x[1][x[0]]
constraints = {}
for row in range(len(self.board.rows)):
constraints[(0, row)] = [(1, x) for x in range(len(self.board.cols))]
node = Variable((0, row))
node.domain = generate_permutations(self.board.rows[row], len(self.board.cols))
print("xxxxx", self.board.rows[row])
print(node.domain)
nodes[(0, row)] = node
for col in range(len(self.board.cols)):
constraints[(1, col)] = [(0, x) for x in range(len(self.board.rows))]
node = Variable((1, col))
node.domain = generate_permutations(self.board.cols[col], len(self.board.rows))
nodes[(1, col)] = node
constraint = Constraint()
constraint.function = function
state = CSPState()
state.constraints = constraints
state.constraint = constraint
state.variables = nodes
state.gac = gac
gac.state = state
astar_csp = AstarCSP()
astar_csp.csp_state = state
astar_csp.initialize()
pprint(state.constraints)
for r in astar_csp.run():
if r[0]:
s = r[0][-1]
self.generate_matrix(s)
self.draw_map()
#self.update_map()
print("This is s: ", s)
def run(self):
gac = NonogramGAC()
nodes = {}
function = make_function(["x", "y"], "x == y") # x[1][x[0]]
constraints = {}
for row in range(len(self.board.rows)):
constraints[(0, row)] = [(1, x) for x in range(len(self.board.cols))]
node = Variable((0, row))
node.domain = generate_permutations(self.board.rows[row], len(self.board.cols))
print("xxxxx", self.board.rows[row])
print(node.domain)
nodes[(0, row)] = node
for col in range(len(self.board.cols)):
constraints[(1, col)] = [(0, x) for x in range(len(self.board.rows))]
node = Variable((1, col))
node.domain = generate_permutations(self.board.cols[col], len(self.board.rows))
nodes[(1, col)] = node
constraint = Constraint()
constraint.function = function
state = CSPState()
state.constraints = constraints
state.constraint = constraint
state.variables = nodes
state.gac = gac
gac.state = state
astar_csp = AstarCSP()
astar_csp.csp_state = state
astar_csp.initialize()
pprint(state.constraints)
for r in astar_csp.run():
if r[0]:
s = r[0][-1]
self.generate_matrix(s)
self.draw_map()
# self.update_map()
print("This is s: ", s)