如何将numpy字符串类型的数组传递给Cython中的函数 [英] How to pass a numpy array of string types to a function in Cython

问题描述

传递一个dtype np.float64_t的numpy数组可以正常工作(如下)，但是我不能传递字符串数组.

Passing a numpy array of dtype np.float64_t works fine ( below), but I can't pass string arrays.

这是可行的方法:

# cython_testing.pyx
import numpy as np
cimport numpy as np

ctypedef np.float64_t dtype_t 

cdef func1 (np.ndarray[dtype_t, ndim=2] A):
    print A 

def testing():
    chunk = np.array ( [[94.,3.],[44.,4.]], dtype=np.float64)

    func1 (chunk)

但是我无法完成这项工作: 我找不到numpy字符串dtypes的匹配类型标识符".

But I can't make this work: I can't find the matching 'type identifiers' for numpy string dtypes.

# cython_testing.pyx
import numpy as np
cimport numpy as np

ctypedef np.string_t dtype_str_t 

cdef func1 (np.ndarray[dtype_str_t, ndim=2] A):
    print A 

def testing():
    chunk = np.array ( [['huh','yea'],['swell','ray']], dtype=np.string_)

    func1 (chunk)

编译错误为:

Error compiling Cython file:
------------------------------------------------------------
ctypedef np.string_t dtype_str_t 
    ^
------------------------------------------------------------

cython_testing.pyx:9:9: 'string_t' is not a type identifier

更新

通过numpy.pxd查看，我看到以下ctypedef语句.也许这足以说明我可以使用uint8_t并假装一切正常，只要我可以进行强制转换?

Per looking through numpy.pxd, I see the following ctypedef statements. Maybe that's enough to say I can use uint8_t and pretend everything is normal, as long as I can do some casting?

ctypedef unsigned char      npy_uint8
ctypedef npy_uint8      uint8_t

只需要看一下铸件的昂贵程度即可.

Just have to see how expensive that casting will be.

推荐答案

看起来您不走运.

http://cython.readthedocs.org/en/latest /src/tutorial/numpy.html

尚不支持某些数据类型，例如布尔数组和字符串数组.

Some data types are not yet supported, like boolean arrays and string arrays.

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此答案不再有效，如Saullo Castro的答案所示，但出于历史目的，我将其保留.

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This answer is no longer valid as shown by Saullo Castro's answer, but I'll leave it for historical purposes.

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