我试图构造一个python类型int的矩阵,一个64位有符号整数。
cdef matrix33():
return np.zeros((3,3),dtype=int)
cdef do_stuf(np.ndarray[int, ndim=2] matrix):
...
return some_value
def start():
print do_stuf(matrix33())
它编译得很好,但是当我运行它时,我仍然会得到这个错误:
ValueError: Buffer dtype mismatch, expected 'int' but got 'long'
我不能使用python long,但我不知道如何正确地转换为64 int
更新
好的。我很确定我正确地使用了Cython。我写的代码是为了在capture go/atari go游戏中进行minmax搜索。
到目前为止,调用最多的函数是:
cdef isThere_greedy_move(np.ndarray[np.int64_t, ndim=2]board, int player):
cdef int i, j
for i in xrange(len(board)):
for j in xrange(len(board)):
if board[i,j] == 0:
board[i,j] = player
if player in score(board):
board[i,j] = 0
return True
board[i,j] = 0
return False
# main function of the scoring system.
# returns list of players that eat a stone
cdef score(np.ndarray[np.int64_t, ndim=2] board):
scores = []
cdef int i,j
cdef np.ndarray[np.int64_t, ndim = 2] checked
checked = np.zeros((board.shape[0], board.shape[1]), dtype = int)
for i in xrange(len(board)):
for j in xrange(len(board)):
if checked[i,j] == 0 and board[i,j] !=0:
life, newly_checked = check_life(i,j,board,[])
if not life:
if -board[i,j] not in scores:
scores.append(-board[i,j])
if len(scores) == 2:
return scores
checked = update_checked(checked, newly_checked)
return scores
# helper functions of score/1
cdef check_life(int i, int j, np.ndarray[np.int64_t, ndim=2] board, checked):
checked.append((i,j))
if liberty(i,j,board):
return True, checked
for pos in [[1,0],[0,1],[-1,0],[0,-1]]:
pos = np.array([i,j]) + np.array(pos)
if check_index(pos[0],pos[1],len(board)) and board[pos[0],pos[1]] == board[i,j] and (pos[0],pos[1]) not in checked:
life, newly_checked = check_life(pos[0],pos[1],board,checked)
if life:
checked = checked + newly_checked
return life, checked
return False, [] # [] is a dummy.
cdef liberty(int i,int j, np.ndarray[np.int64_t, ndim=2] board):
for pos in [np.array([1,0]),np.array([0,1]),np.array([-1,0]),np.array([0,-1])]:
pos = np.array([i,j]) - pos
if check_index(pos[0],pos[1],len(board)) and board[pos[0],pos[1]] == 0:
return True
return False
我真的以为这会是一个让赛顿大放异彩的机会。 要解决3x3捕获,请执行以下操作:
Python2.7的2.28秒是一致的,而cython的2.03秒是一致的 两者都是在python时间模块和低于60C°的i7处理器上测试的
现在我的问题是,如果我要切换到Haskell或C++的这个项目…
Cython的
int
类型与Cint
类型相同,即通常(但不一定)32位。您应该将matrix33
中的dtype
声明为np.int64
,并将do_stuf
中的np.int64_t
声明为其C对应项:相关问题 更多 >
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