您将如何在对角线列表中找到单词?注意:要表明已找到一个单词,可以将其替换为任何字符,例如'-'
grid = ["HXXWXXXXXD",
"XOXXOXXXOX",
"XXRXXCXGXX",
"XXXSXXXXXT",
"XXXXEXXXEX"]
我认为网格中对角线的所有可能性是:
在这种情况下要查找的单词是:
words = ["HORSE","COW","DOG","ET"] # don't ask
对角查找单词似乎比水平或垂直困难得多。在水平查找单词时,我可以遍历row
中的每个grid
和word
中的每个words
。然后,我可以将word
中的row
替换为符号* len(word)
,以说明已找到它。在垂直方向上,我将网格顺时针旋转90°,然后执行了在列表中水平循环的相同过程。然后,我将列表旋转回原始状态。
对角查找单词有哪些不同的解决方案?
答案 0 :(得分:3)
您可以通过以下方式转换列表:将列表中的每个字符串都比上一个移位1-用填充符填充创建的空间(在这种情况下,使用'0'
)
mearray = np.array([[e for e in g] for g in grid])
words = ["HORSE","COW","DOG","ET"] # don't ask
我使用numpy
是因为我比较习惯它,并且在这里显示起来更容易,但是可以肯定地通过常规列表理解来完成。之后,您的数组现在是一个numpy数组:
[['H' 'X' 'X' 'W' 'X' 'X' 'X' 'X' 'X' 'D']
['X' 'O' 'X' 'X' 'O' 'X' 'X' 'X' 'O' 'X']
['X' 'X' 'R' 'X' 'X' 'C' 'X' 'G' 'X' 'X']
['X' 'X' 'X' 'S' 'X' 'X' 'X' 'X' 'X' 'T']
['X' 'X' 'X' 'X' 'E' 'X' 'X' 'X' 'E' 'X']]
通过添加移位填充符来对其进行转换:
leng = len(mearray)
def pad_with(vector, pad_width, iaxis, kwargs):
pad_value = kwargs.get('padder', '0')
vector[:pad_width[0]] = pad_value
vector[-pad_width[1]:] = pad_value
return vector
np.array([np.pad(mearray[i], (leng-i, i+1), pad_with) for i in range(leng)])
您的数组现在为:
[['0' '0' '0' '0' '0' 'H' 'X' 'X' 'W' 'X' 'X' 'X' 'X' 'X' 'D' '0']
['0' '0' '0' '0' 'X' 'O' 'X' 'X' 'O' 'X' 'X' 'X' 'O' 'X' '0' '0']
['0' '0' '0' 'X' 'X' 'R' 'X' 'X' 'C' 'X' 'G' 'X' 'X' '0' '0' '0']
['0' '0' 'X' 'X' 'X' 'S' 'X' 'X' 'X' 'X' 'X' 'T' '0' '0' '0' '0']
['0' 'X' 'X' 'X' 'X' 'E' 'X' 'X' 'X' 'E' 'X' '0' '0' '0' '0' '0']]
您可以清楚地看到HORSE
和COW
被规范化。您需要通过切换填充方向来再次执行此操作,以便拥有GOD
和ET
:
反方向:np.array([np.pad(mearray[i], (i+1, leng-i), pad_with) for i in range(leng)])
[['0' 'H' 'X' 'X' 'W' 'X' 'X' 'X' 'X' 'X' 'D' '0' '0' '0' '0' '0']
['0' '0' 'X' 'O' 'X' 'X' 'O' 'X' 'X' 'X' 'O' 'X' '0' '0' '0' '0']
['0' '0' '0' 'X' 'X' 'R' 'X' 'X' 'C' 'X' 'G' 'X' 'X' '0' '0' '0']
['0' '0' '0' '0' 'X' 'X' 'X' 'S' 'X' 'X' 'X' 'X' 'X' 'T' '0' '0']
['0' '0' '0' '0' '0' 'X' 'X' 'X' 'X' 'E' 'X' 'X' 'X' 'E' 'X' '0']]
现在,您可以在矩阵中看到GOD
和ET
(上下)。您应该可以使用原始功能来检索它们。
答案 1 :(得分:3)
如果您不太在乎所有对角线的遍历顺序,那么纯Python中的此生成器函数就可以使用,这是利用了右上向左下的事实:
def rotate(row, n):
return row[n:] + row[:n]
def diags(grid, rev=False):
n = len(grid)
_grid = [list(row) + [None]*(n-1) for row in grid] # pad for rotation
for diag in zip(*(rotate(_grid[i], (i, -i)[rev]) for i in range(n))):
d = ''.join(filter(None, diag))
yield from (d, d[::-1])
if not rev:
yield from diags(grid, rev=True)
>>> list(diags(grid))
['H',
'H',
'XX',
'XX',
'XOX',
'XOX',
'WXXX',
'XXXW',
'XXRXX',
'XXRXX',
'XOXXX',
'XXXOX',
'XXXSX',
'XSXXX',
'XXCXX',
'XXCXX',
'XXXXE',
'EXXXX',
'DOGXX',
'XXGOD',
'XXXX',
'XXXX',
'XXX',
'XXX',
'TE',
'ET',
'X',
'X',
'HORSE',
'ESROH',
'XXXXX',
'XXXXX',
'XXXXX',
'XXXXX',
'WOCXX',
'XXCOW',
'XXXXE',
'EXXXX',
'XXGXX',
'XXGXX',
'XXXT',
'TXXX',
'XOX',
'XOX',
'XX',
'XX',
'D',
'D',
'X',
'X',
'XX',
'XX',
'XXX',
'XXX',
'XXXX',
'XXXX']
答案 2 :(得分:1)
要遍历所有可能的对角线,可以使用numpy diagonal。还可以使用numpy fliplr
,flipud
,flip
来获取各个方向的对角线:
import numpy as np
grid = [
"HXXWXXXXXD",
"XOXXOXXXOX",
"XXRXXCXGXX",
"XXXSXXXXXT",
"XXXXEXXXEX"]
data_orig = np.array(list(map(list, grid)))
transformations = {
'Downwards and Right': np.array,
'Downwards and left': np.fliplr,
'Upwards and Right': np.flipud,
'Upwards and left': np.flip,
}
for descr, trans in transformations.items():
data = trans(data_orig)
print(descr)
print(data)
offset_row = 1 - data.shape[0]
offset_column = data.shape[1]
for offset in range(offset_row, offset_column):
print(data.diagonal(offset=offset))
输出:
Downwards and Right
[['H' 'X' 'X' 'W' 'X' 'X' 'X' 'X' 'X' 'D']
['X' 'O' 'X' 'X' 'O' 'X' 'X' 'X' 'O' 'X']
['X' 'X' 'R' 'X' 'X' 'C' 'X' 'G' 'X' 'X']
['X' 'X' 'X' 'S' 'X' 'X' 'X' 'X' 'X' 'T']
['X' 'X' 'X' 'X' 'E' 'X' 'X' 'X' 'E' 'X']]
['X']
['X' 'X']
['X' 'X' 'X']
['X' 'X' 'X' 'X']
['H' 'O' 'R' 'S' 'E']
['X' 'X' 'X' 'X' 'X']
['X' 'X' 'X' 'X' 'X']
['W' 'O' 'C' 'X' 'X']
['X' 'X' 'X' 'X' 'E']
['X' 'X' 'G' 'X' 'X']
['X' 'X' 'X' 'T']
['X' 'O' 'X']
['X' 'X']
['D']
Downwards and left
[['D' 'X' 'X' 'X' 'X' 'X' 'W' 'X' 'X' 'H']
['X' 'O' 'X' 'X' 'X' 'O' 'X' 'X' 'O' 'X']
['X' 'X' 'G' 'X' 'C' 'X' 'X' 'R' 'X' 'X']
['T' 'X' 'X' 'X' 'X' 'X' 'S' 'X' 'X' 'X']
['X' 'E' 'X' 'X' 'X' 'E' 'X' 'X' 'X' 'X']]
['X']
['T' 'E']
['X' 'X' 'X']
['X' 'X' 'X' 'X']
['D' 'O' 'G' 'X' 'X']
['X' 'X' 'X' 'X' 'E']
['X' 'X' 'C' 'X' 'X']
['X' 'X' 'X' 'S' 'X']
['X' 'O' 'X' 'X' 'X']
['X' 'X' 'R' 'X' 'X']
['W' 'X' 'X' 'X']
['X' 'O' 'X']
['X' 'X']
['H']
Upwards and Right
[['X' 'X' 'X' 'X' 'E' 'X' 'X' 'X' 'E' 'X']
['X' 'X' 'X' 'S' 'X' 'X' 'X' 'X' 'X' 'T']
['X' 'X' 'R' 'X' 'X' 'C' 'X' 'G' 'X' 'X']
['X' 'O' 'X' 'X' 'O' 'X' 'X' 'X' 'O' 'X']
['H' 'X' 'X' 'W' 'X' 'X' 'X' 'X' 'X' 'D']]
['H']
['X' 'X']
['X' 'O' 'X']
['X' 'X' 'X' 'W']
['X' 'X' 'R' 'X' 'X']
['X' 'X' 'X' 'O' 'X']
['X' 'S' 'X' 'X' 'X']
['X' 'X' 'C' 'X' 'X']
['E' 'X' 'X' 'X' 'X']
['X' 'X' 'G' 'O' 'D']
['X' 'X' 'X' 'X']
['X' 'X' 'X']
['E' 'T']
['X']
Upwards and left
[['X' 'E' 'X' 'X' 'X' 'E' 'X' 'X' 'X' 'X']
['T' 'X' 'X' 'X' 'X' 'X' 'S' 'X' 'X' 'X']
['X' 'X' 'G' 'X' 'C' 'X' 'X' 'R' 'X' 'X']
['X' 'O' 'X' 'X' 'X' 'O' 'X' 'X' 'O' 'X']
['D' 'X' 'X' 'X' 'X' 'X' 'W' 'X' 'X' 'H']]
['D']
['X' 'X']
['X' 'O' 'X']
['T' 'X' 'X' 'X']
['X' 'X' 'G' 'X' 'X']
['E' 'X' 'X' 'X' 'X']
['X' 'X' 'C' 'O' 'W']
['X' 'X' 'X' 'X' 'X']
['X' 'X' 'X' 'X' 'X']
['E' 'S' 'R' 'O' 'H']
['X' 'X' 'X' 'X']
['X' 'X' 'X']
['X' 'X']
['X']
答案 3 :(得分:0)
您可以遍历每个字符,如果该字符是单词的一部分,则可以检查每种可能性(垂直,水平,右诊断,左诊断):
from collections import namedtuple
d = ['HXXWXXXXXD', 'XOXXOXXXOX', 'XXRXXCXGXX', 'XXXSXXXXXT', 'XXXXEXXXEX']
node = namedtuple('node', ['val', 'ischar'])
_d = [[node(i, i != 'X') for i in b] for b in d]
def traverse(_func, _start, _board):
while True:
try:
_a, _b = _func(*_start)
if not _board[_a][_b].ischar:
break
_start = [_a, _b]
yield _board[_a][_b].val
except:
break
def get_words(board, *args):
funcs = [[lambda x, y:(x-1, y), lambda x, y:(x+1, y)], [lambda x, y:(x, y+1), lambda x, y:(x, y-1)], [lambda x:(x-1, y-1), lambda x, y:(x+1, y+1)], [lambda x, y:(x-1, y+1), lambda x, y:(x+1, y-1)]]
for _s1, _s2 in funcs:
yield ''.join(traverse(_s1, args, board))+board[args[0]][args[1]].val+''.join(traverse(_s2, args, board))
def words(board, to_find):
for i in range(len(board)):
for b in range(len(board[0])):
if board[i][b].ischar:
for word in get_words(board, i, b):
if word in to_find:
yield word
if word[::-1] in to_find:
yield word[::-1]
print(list(set(words(_d, ["HORSE","COW","DOG","ET"]))))
输出:
['DOG', 'ET', 'HORSE', 'COW']