def _strategy(self):
max = 0
maxvalue = []
base = self.base.copy()
for line in open(os.path.join(define.APP_TMP, "route.txt")):
result = np.array(eval(line.rstrip()))
tmp = base.copy()
for r in result:
tmp[r[0]][r[1]] = "V"
res = [self.delete(tmp.copy(), flag=True), result, calc(self.get_result())]
if not max > res[2]:
maxvalue = [res[2], res[1]]
max = res[2]
return maxvalue[0], maxvalue[1]
def setup( self, define_dict = None, funmod = None, filename = None,
required = None, other = None ):
define_dict = get_default( define_dict, self.__dict__ )
self._filename = filename
other_missing = self.validate( required = required, other = other )
self.transform_input_trivial()
self._raw = {}
for key, val in define_dict.iteritems():
if isinstance( val, dict ):
self._raw[key] = copy( val )
self.transform_input()
self.funmod = funmod
def __strategy(self, base, bresult, bpredict, bnode):
if len(bresult) > 3:
return
else:
for p in bpredict:
tmp = base.copy()
tmp[p[0]][p[1]] = "V"
parr = np.array([[p[0],p[1]]])
result = np.append(bresult.copy(), parr, axis=0)
if self.equal(result.copy()):
pass
else:
res = [self.delete(tmp.copy(), flag=True), result.copy(), self.get_result()]
node = Node(result, parr, res[0] - len(res[1]), res[2])
self.node.append(node)
bnode.add(node)
predict = self._predict(result)
self.__strategy(tmp, result, predict, node)
def _strategy(self):
max = 0
maxvalue = []
base = self.base.copy()
for i in range(1, 7):
for j in range(0, 8):
result = np.array([[i,j]])
tmp = base.copy()
tmp[i][j] = "V"
res = [self.delete(tmp.copy(), flag=True), result, self.get_result()]
node = Node(res[1], res[1], res[0] - len(res[1]), res[2])
self.node.append(node)
self.root.add(node)
predict = self._predict(result)
self.__strategy(tmp, result, predict, node)
for n in self.node:
if not max > n._score:
maxvalue = [n._score, n._result]
max = n._score
return maxvalue[0], maxvalue[1]
def get_standard_keywords():
return copy( _required ), copy( _other )
