如何在C++中爲Cython中的兩種類型使用模板化函數？

Question

我有一個模板化的C++函數，我希望能夠使用這兩種類型。由於Python不支持重載，我有點卡住如何解決這個問題。我有一個.pyx如下所示。我如何在float和double中使用C++函數？

import cython 
import numpy as np 
cimport numpy as np 

# declare the interface to the C code 
cdef extern from "diff_cpp.cpp" namespace "diff": 
    cdef void diff_cpp[float] (float* at, const float* a, const float visc, 
           const float dxidxi, const float dyidyi, const float dzidzi, 
           const int itot, const int jtot, const int ktot) 

cdef extern from "diff_cpp.cpp" namespace "diff": 
    cdef void diff_cpp[double] (double* at, const double* a, const double visc, 
           const double dxidxi, const double dyidyi, const double dzidzi, 
           const int itot, const int jtot, const int ktot) 

@cython.boundscheck(False) 
@cython.wraparound(False) 
def diff(np.ndarray[double, ndim=3, mode="c"] at not None, 
     np.ndarray[double, ndim=3, mode="c"] a not None, 
     double visc, double dxidxi, double dyidyi, double dzidzi): 
    cdef int ktot, jtot, itot 
    ktot, jtot, itot = at.shape[0], at.shape[1], at.shape[2] 
    diff_cpp[double](&at[0,0,0], &a[0,0,0], visc, dxidxi, dyidyi, dzidzi, itot, jtot, ktot) 
    return None 

@cython.boundscheck(False) 
@cython.wraparound(False) 
def diff_f(np.ndarray[float, ndim=3, mode="c"] at not None, 
      np.ndarray[float, ndim=3, mode="c"] a not None, 
      float visc, float dxidxi, float dyidyi, float dzidzi): 
    cdef int ktot, jtot, itot 
    ktot, jtot, itot = at.shape[0], at.shape[1], at.shape[2] 
    diff_cpp[float](&at[0,0,0], &a[0,0,0], visc, dxidxi, dyidyi, dzidzi, itot, jtot, ktot) 
    return None 

---

用解決

UPDATE @ OZ1的答案提供了這樣做的正確方法。這個代碼適用於那些對解決這個特定問題感興趣的人。

import cython 
import numpy as np 
cimport numpy as np 

# declare the interface to the C code 
cdef extern from "diff_cpp.cpp" namespace "diff": 
    cdef void diff_cpp[T](T* at, const T* a, const T visc, 
          const T dxidxi, const T dyidyi, const T dzidzi, 
          const int itot, const int jtot, const int ktot) 

ctypedef fused float_t: 
    cython.float 
    cython.double 

@cython.boundscheck(False) 
@cython.wraparound(False) 
def diff(np.ndarray[float_t, ndim=3, mode="c"] at not None, 
     np.ndarray[float_t, ndim=3, mode="c"] a not None, 
     float_t visc, float_t dxidxi, float_t dyidyi, float_t dzidzi): 
    cdef int ktot, jtot, itot 
    ktot, jtot, itot = at.shape[0], at.shape[1], at.shape[2] 
    diff_cpp(&at[0,0,0], &a[0,0,0], visc, dxidxi, dyidyi, dzidzi, itot, jtot, ktot) 
    return None 

Answer 1

兩個附註：

1. 用Cython支持C++模板（http://docs.cython.org/en/latest/src/userguide/wrapping_CPlusPlus.html）
2. 用Cython已熔融的類型（http://docs.cython.org/en/latest/src/userguide/fusedtypes.html）

一個例子：

// lib.cpp 
template<typename T> 
T arr_sum(T *arr, size_t size) 
{ 
    T temp=0; 
    for (size_t i=0; i != size; ++i){ 
     temp += arr[i]; 
    } 
    return temp; 
} 

---

# lib_wrapper.pyx 
cimport cython 

ctypedef fused float_t: 
    cython.float 
    cython.double 

cdef extern from "lib.cpp" nogil: 
    T arr_sum[T](T *arr, size_t size) 

def py_arr_sum(float_t[:] arr not None): 
    print(sizeof(arr[0])) # check the element size 
    return arr_sum(&arr[0], arr.shape[0]) 

---

# use.py 
import numpy as np 
from lib_wrapper import py_arr_sum 

print(py_arr_sum(np.array([1,2,3], dtype=np.float32))) 
print(py_arr_sum(np.array([1,2,3], dtype=np.float64))) 
print(py_arr_sum(np.array([1,2,3], dtype=np.int32))) # oops