class NRooks:
def __init__(self, N = 1):
def rowConstraint(state, values, size = N):
pairs = values.items()
validStates = list(range(state.state//size*size, state.state//size*size+size))
validPairs = list(filter(lambda pair: pair[1] and pair[0].state in validStates, pairs))
statesToConsider = list(map(lambda x: x[1], validPairs))
return sum(statesToConsider) <= 1
def columnConstraint(state, values, size = N):
pairs = values.items()
validStates = list(range(state.state % size, size**2,size))
validPairs = list(filter(lambda pair: pair[1] and pair[0].state in validStates, pairs))
statesToConsider = map(lambda x: x[1], validPairs)
return sum(statesToConsider) <= 1
self._number = N
goal = lambda values, size=N: sum(map(lambda v: v[1], values.items())) == size
self._CSP = CSP(goal, ChessState(0, set([True,False]),N))
for i in range(N*N):
self._CSP.addVariable(ChessState(i, set([True,False]),N))
self._CSP.addConstraint(rowConstraint)
self._CSP.addConstraint(columnConstraint)
def solve(self):
return self._CSP.solve()
def toCSP(self) -> CSP:
"""
Transforms the map into a CSP
:return: the CSP
"""
csp = CSP()
for p in self._region:
v = Variable(
'region ' + str('%.3f' % p.x()) + '-' + str('%.3f' % p.y()),
self._color)
csp.addVariable(v)
for l in self._borders:
csp.addBinaryConstraint(
csp.getVariable('region ' + str('%.3f' % l[0].x()) + '-' +
str('%.3f' % l[0].y())), Constraint(different),
csp.getVariable('region ' + str('%.3f' % l[1].x()) + '-' +
str('%.3f' % l[1].y())))
return csp
class NBishops:
def __init__(self, N=1):
def leftDiagonalConstraint(state, values, size=N):
pairs = values.items()
validStates = list(
range(
state.state -
min(state.state // size, state.state % size) * (size + 1),
size**2, size + 1))
validPairs = list(
filter(lambda pair: pair[1] and pair[0].state in validStates,
pairs))
statesToConsider = map(lambda x: x[1], validPairs)
return sum(statesToConsider) <= 1
def rightDiagonalConstraint(state, values, size=N):
pairs = values.items()
validStates = list(
range(
state.state - min(state.state // size,
(N - 1) - state.state % size) *
(size - 1), size**2, (size - 1)))
validPairs = list(
filter(lambda pair: pair[1] and pair[0].state in validStates,
pairs))
statesToConsider = map(lambda x: x[1], validPairs)
return sum(statesToConsider) <= 1
self._number = N
goal = lambda values, size=N: sum(map(lambda v: v[1], values.items())
) == size
self._CSP = CSP(goal, ChessState(0, set([True, False]), N))
for i in range(N * N):
self._CSP.addVariable(ChessState(i, set([True, False]), N))
self._CSP.addConstraint(leftDiagonalConstraint)
self._CSP.addConstraint(rightDiagonalConstraint)
def solve(self):
return self._CSP.solve()
