Reputation: 21707
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
I would like it to return a numpy array. How can I do it?
For the moment I have to do
pd_np = np.zeros(8000, dtype=np.double)
cdef int i
for i in range(8000):
pd_np[i] = pd[i]
Upvotes: 5
Views: 3677
Reputation: 7184
If you are just declaring your array in your function why not make it a numpy array to begin with, then when you need the c array you can just grab the data pointer.
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
Upvotes: 6
Reputation: 231335
In the memview
example here 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
I can create a numpy array from carr_view
, the memory view on carr
, a C array.
# 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)
Upvotes: 1