Passing numpy arrays in Cython to a C function that requires dynamically allocated arrays

Question

I have some C code that has the following declaration:

int myfunc(int m, int n, const double **a, double **b, double *c);

So a

Answer 1

Reply 1: You can pass NumPy array via Cython to C using the location of the start of the array (see code below).

Reply 2: Your declarations seem correct but I don't use this approach of explicit memory management. You can use NumPy to declare cdef-ed arrays.

Use

cdef double[:,::1] a = np.random.random([p, q])
cdef double[:,::1] b = np.empty([p, q])
cdef double[::1] b = np.empty(q)

Then pass &a[0], the location of the start of the array, to your C function. The ::1 is to ensure contiguousness.

A good reference for this is Jake Vanderplas' blog: https://jakevdp.github.io/blog/2012/08/08/memoryview-benchmarks/

Finally, typically one creates functions in Cython and calls them in Python, so your Python code would be:

import pyximport; pyximport.install()
import mytest
mytest.mywrappedfunc()

where mywrappedfunc is a Python (def and not cdef) function defined in the module that can do the array declaration show above.

Answer 2

Create a helper array in cython

To get a double** from a numpy array, you can create a helper-array of pointers in your *.pyx file. Further more, you have to make sure that the numpy array has the correct memory layout. (It might involve creating a copy)

Fortran order

If your C-function expects fortran order (all x-coordinates in one list, all y coordinates in another list, all z-coordinates in a third list, if your array a corresponds to a list of points in 3D space)

N,M = a.shape
# Make sure the array a has the correct memory layout (here F-order)
cdef np.ndarray[double, ndim=2, mode="fortran"] a_cython =
                         np.asarray(a, dtype = float, order="F")
#Create our helper array
cdef double** point_to_a = <double **>malloc(M * sizeof(double*))
if not point_to_a: raise MemoryError
try:
    #Fillup the array with pointers
    for i in range(M): 
        point_to_a[i] = &a_cython[0, i]
    # Call the C function that expects a double**
    myfunc(... &point_to_a[0], ...)
finally:
    free(point_to_a)

C-order

If your C-function expects C-order ([x1,y1,z1] is the first list, [x2,y2,z2] the second list for a list of 3D points):

N,M = a.shape
# Make sure the array a has the correct memory layout (here C-order)
cdef np.ndarray[double, ndim=2, mode="c"] a_cython =
                         np.asarray(a, dtype = float, order="C")
#Create our helper array
cdef double** point_to_a = <double **>malloc(N * sizeof(double*))
if not point_to_a: raise MemoryError
try:
    for i in range(N): 
        point_to_a[i] = &a_cython[i, 0]
    # Call the C function that expects a double**
    myfunc(... &point_to_a[0], ...)
finally:
    free(point_to_a)