What is the correct way to pass a numpy 2d - array to a c function using ctypes ? My current approach so far (leads to a segfault):
C code :
void te
#include <stdio.h>
void test(double (*in_array)[3], int N){
int i, j;
for(i = 0; i < N; i++){
for(j = 0; j < N; j++){
printf("%e \t", in_array[i][j]);
}
printf("\n");
}
}
int main(void)
{
double a[][3] = {
{1., 2., 3.},
{4., 5., 6.},
{7., 8., 9.},
};
test(a, 3);
return 0;
}
if you want to use a double **
in your function, you must pass an array of pointer to double (not a 2d array):
#include <stdio.h>
void test(double **in_array, int N){
int i, j;
for(i = 0; i < N; i++){
for(j = 0; j< N; j++){
printf("%e \t", in_array[i][j]);
}
printf("\n");
}
}
int main(void)
{
double a[][3] = {
{1., 2., 3.},
{4., 5., 6.},
{7., 8., 9.},
};
double *p[] = {a[0], a[1], a[2]};
test(p, 3);
return 0;
}
Another (as suggested by @eryksun): pass a single pointer and do some arithmetic to get the index:
#include <stdio.h>
void test(double *in_array, int N){
int i, j;
for(i = 0; i < N; i++){
for(j = 0; j< N; j++){
printf("%e \t", in_array[i * N + j]);
}
printf("\n");
}
}
int main(void)
{
double a[][3] = {
{1., 2., 3.},
{4., 5., 6.},
{7., 8., 9.},
};
test(a[0], 3);
return 0;
}
While the reply might be rather late, I hope it could help other people with the same problem.
As numpy arrays are internally saved as 1d arrays, one can simply rebuild 2d shape in C. Here is a small MWE:
// libtest2d.c
#include <stdlib.h> // for malloc and free
#include <stdio.h> // for printf
// create a 2d array from the 1d one
double ** convert2d(unsigned long len1, unsigned long len2, double * arr) {
double ** ret_arr;
// allocate the additional memory for the additional pointers
ret_arr = (double **)malloc(sizeof(double*)*len1);
// set the pointers to the correct address within the array
for (int i = 0; i < len1; i++) {
ret_arr[i] = &arr[i*len2];
}
// return the 2d-array
return ret_arr;
}
// print the 2d array
void print_2d_list(unsigned long len1,
unsigned long len2,
double * list) {
// call the 1d-to-2d-conversion function
double ** list2d = convert2d(len1, len2, list);
// print the array just to show it works
for (unsigned long index1 = 0; index1 < len1; index1++) {
for (unsigned long index2 = 0; index2 < len2; index2++) {
printf("%1.1f ", list2d[index1][index2]);
}
printf("\n");
}
// free the pointers (only)
free(list2d);
}
and
# test2d.py
import ctypes as ct
import numpy as np
libtest2d = ct.cdll.LoadLibrary("./libtest2d.so")
libtest2d.print_2d_list.argtypes = (ct.c_ulong, ct.c_ulong,
np.ctypeslib.ndpointer(dtype=np.float64,
ndim=2,
flags='C_CONTIGUOUS'
)
)
libtest2d.print_2d_list.restype = None
arr2d = np.meshgrid(np.linspace(0, 1, 6), np.linspace(0, 1, 11))[0]
libtest2d.print_2d_list(arr2d.shape[0], arr2d.shape[1], arr2d)
If you compile the code with gcc -shared -fPIC libtest2d.c -o libtest2d.so
and then run python test2d.py
it should print the array.
I hope the example is more or less self-explaining. The idea is, that the shape is also given to the C-Code which then creates a double **
pointer for which the space for the additional pointers is reserved. And these then are then set to point to the correct part of the original array.
PS: I am rather a beginner in C so please comment if there are reasons not to do this.
This is probably a late answer, but I finally got it working. All credit goes to Sturla Molden at this link.
The key is, note that double**
is an array of type np.uintp
. Therefore, we have
xpp = (x.ctypes.data + np.arange(x.shape[0]) * x.strides[0]).astype(np.uintp)
doublepp = np.ctypeslib.ndpointer(dtype=np.uintp)
And then use doublepp
as the type, pass xpp
in. See full code attached.
The C code:
// dummy.c
#include <stdlib.h>
__declspec(dllexport) void foobar(const int m, const int n, const
double **x, double **y)
{
size_t i, j;
for(i=0; i<m; i++)
for(j=0; j<n; j++)
y[i][j] = x[i][j];
}
The Python code:
# test.py
import numpy as np
from numpy.ctypeslib import ndpointer
import ctypes
_doublepp = ndpointer(dtype=np.uintp, ndim=1, flags='C')
_dll = ctypes.CDLL('dummy.dll')
_foobar = _dll.foobar
_foobar.argtypes = [ctypes.c_int, ctypes.c_int, _doublepp, _doublepp]
_foobar.restype = None
def foobar(x):
y = np.zeros_like(x)
xpp = (x.__array_interface__['data'][0]
+ np.arange(x.shape[0])*x.strides[0]).astype(np.uintp)
ypp = (y.__array_interface__['data'][0]
+ np.arange(y.shape[0])*y.strides[0]).astype(np.uintp)
m = ctypes.c_int(x.shape[0])
n = ctypes.c_int(x.shape[1])
_foobar(m, n, xpp, ypp)
return y
if __name__ == '__main__':
x = np.arange(9.).reshape((3, 3))
y = foobar(x)
Hope it helps,
Shawn