def find_unbalanced(self):
node = self
while True:
grouped_children = node.grouped('children')
unbalanced = cc.pipe(grouped_children,
cc.valfilter(lambda x: len(x) == 1),
lambda x: cc.first(x.values())[0])
if unbalanced.children_are_balanced:
return unbalanced
node = unbalanced
def indice2Arr(indice: Indice) -> Union[np.ndarray, float]:
whichIn = insDispatcher(indice)[0]
doFuncs: Dict[str, bool] = valmap(lambda v: bool(v(indice)[0]), funcsIndex)
whichFunc = list(valfilter(identity, doFuncs).keys())
if not whichFunc:
func = lambda x: x
else:
if whichFunc[0] not in f2:
raise ValueError("No function called {}.".format(whichFunc[0]))
func = f2[whichFunc[0]]
return func(
self.getInputElement(inArrs[whichIn], tuple(indexConverters2[whichIn](indice)))
)
def getIndexConverters(
self, indexMap: Dict[Indice, LabelInIndice]
) -> List[IndexConverter]:
return [
self.getIndexConverter(
i,
compose(
valmap(lambda v: v[1]),
valfilter(lambda v, i=i: v[0] == i),
)(indexMap),
)
for i in range(len(self.inAsts))
]
x[1], lambda x: x.split(','), cc.map(str.strip), list))), list)
tree_val_dict = cc.pipe(
data_input, cc.map(cc.first),
cc.map(lambda x: [tree_val_re.match(x).group(y) for y in (1, 2)]), dict,
cc.valmap(int))
tree_mapping_dict = cc.pipe(
data_input, cc.map(lambda x: (tree_val_re.match(x[0]).group(1), x[1])),
dict)
root = cc.pipe(
tree_mapping_dict.keys(),
cc.filter(lambda x: x not in cc.concat(tree_mapping_dict.values())),
cc.first)
tree = Tree(root, tree_mapping_dict, tree_val_dict)
unbalanced = tree.find_unbalanced()
unbalanced_self_weight = unbalanced.weight - sum(x.weight
for x in unbalanced.children)
unbalanced_grouped_siblings = unbalanced.grouped('siblings')
balanced_weight = cc.first(
cc.valfilter(lambda x: len(x) > 1, unbalanced_grouped_siblings).keys())
unbalanced_weight = cc.first(
cc.valfilter(lambda x: len(x) == 1, unbalanced_grouped_siblings).keys())
weight_offset = balanced_weight - unbalanced_weight
pp(unbalanced_self_weight + weight_offset)
max_seen_index = None
for i, value in enumerate(seq):
if max_seen is None or value > max_seen:
max_seen = value
max_seen_index = i
return max_seen_index
data_input = cc.pipe(sys.stdin.readline(), str.split, cc.map(int), list)
selected_bin = 0
dist = data_input
seen_dists_dict = {}
cycle_len_dict = {}
while not cc.valfilter(lambda x: x >= 2, seen_dists_dict):
dist_tuple = tuple(dist)
if dist_tuple not in seen_dists_dict:
seen_dists_dict[dist_tuple] = 1
else:
seen_dists_dict[dist_tuple] += 1
if dist_tuple not in cycle_len_dict:
cycle_len_dict[dist_tuple] = 0
cycle_len_dict = cc.valmap(lambda x: x + 1, cycle_len_dict)
selected_bin = argmax(dist)
selected_bin_val = dist[selected_bin]
dist[selected_bin] = 0
while selected_bin_val > 0: