def _dfs_visit(
cube: Tuple[int, int],
grid: List[List[str]],
word_list: pygtrie.Trie,
word: str,
cubes_visited: Set[Tuple[int, int]],
) -> Set[str]:
"""
Visit the next state in a depth-first search for words in the letter grid.
:param Tuple[int, int] cube: grid indices of a letter cube
:param List[List[str]] grid: a grid of letter cubes to search
:param pygtrie.Trie word_list: a Trie containing all valid words
:param str word: a string of letters representing the current search path
:param Set[Tuple[int, int]] cubes_visited: set of cube indices already visited
:return: set of valid words found from the current search state
:rtype: Set[str]
"""
i, j = cube
# Capitalize all words
word += grid[i][j].upper()
if not word_list.has_node(word):
return set()
words_found = {word} if word_list.has_key(word) and len(word) > 2 else set()
neighbors = _get_neighboring_cubes(cube, grid, cubes_visited)
neighboring_words = [
_dfs_visit(n, grid, word_list, word, cubes_visited.union({cube}))
for n in neighbors
]
return reduce(lambda x, y: x.union(y), neighboring_words, words_found)
def filter_legal_actions_for_vw_node(legal_actions: Tuple[int],
is_recursive: bool,
current_trie: pygtrie.Trie):
if is_recursive:
# We need to check that only pieces which can be extended are valid.
legal_actions = [
action for action in legal_actions
if current_trie.has_subtrie((action, ))
]
else:
# We need to check that only pieces which yield a valid word are
# valid.
legal_actions = [
action for action in legal_actions
if current_trie.has_key((action, ))
]
return legal_actions
