cpdef myf():
# pd has to be a c array.
# Because it will then be consumed by some c function.
cdef double pd[8000]
# Do something with pd
...
# Get a memoryview.
cdef double[:] pd_view = pd
# Coercion the memoryview to numpy array. Not working.
ret = np.asarray(pd)
return ret
我希望它返回一个numpy数组。我该怎么办?
我必须做的那一刻
pd_np = np.zeros(8000, dtype=np.double)
cdef int i
for i in range(8000):
pd_np[i] = pd[i]
答案 0 :(得分:6)
如果你只是在你的函数中声明你的数组,为什么不把它作为一个numpy数组开始,那么当你需要c数组时,你可以抓住数据指针。
cimport numpy as np
import numpy as np
def myf():
cdef np.ndarray[double, ndim=1, mode="c"] pd_numpy = np.empty(8000)
cdef double *pd = &pd_numpy[0]
# Do something to fill pd with values
for i in range(8000):
pd[i] = i
return pd_numpy
答案 1 :(得分:1)
在此memview
示例中http://docs.cython.org/src/userguide/memoryviews.html
# Memoryview on a C array
cdef int carr[3][3][3]
cdef int [:, :, :] carr_view = carr
carr_view[...] = narr_view # np.arange(27, dtype=np.dtype("i")).reshape((3, 3, 3))
carr_view[0, 0, 0] = 100
我可以从carr_view
创建一个numpy数组,carr
上的内存视图,一个C数组。
# print np.array(carr) # cython error
print 'numpy array on carr_view'
print np.array(carr_view)
print np.array(carr_view).sum() # match sum3d(carr)
# or np.asarray(carr_view)
print 'numpy copy from carr_view'
carr_copy = np.empty((3,3,3))
carr_copy[...] = carr_view[...] # don't need indexed copy
print carr_copy
print carr_copy.sum() # match sum3d(carr)
答案 2 :(得分:1)
ret = np.asarray(pd_view)
有效