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pythoncctypesnumpy-ndarray
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Reputation: 1735

Segmentation fault (core dumped) when a 2d numpy array is passed using ctypes

I want to pass a 2d numpy array to a function written in C using ctypes. When I try to access the data in the C function I get: Segmentation fault (core dumped). The code is:

code in C

#include <stdio.h>

void np_array_complex_shape(double ** data, int * shape){
  printf("%d\n", shape[0]);
  printf("%d\n", shape[1]);  // These print ok.
  printf("%f", data[0][0]);  // This one throws: Segmentation fault (core dumped)
}

code in python:

import os
import ctypes
import numpy as np
import numpy.ctypeslib as npct

test_library_file_location = "library.so"

array_2d_double = npct.ndpointer(dtype=np.double, ndim=2, flags='CONTIGUOUS')
array_1d_int = npct.ndpointer(dtype=np.int32, ndim=1, flags='CONTIGUOUS')

LIBC = ctypes.CDLL(test_library_file_location)
LIBC.np_array_complex_shape.restype = None
LIBC.np_array_complex_shape.argtypes = [array_2d_double, array_1d_int]

x = np.array([[1,2,3],[4,5,6],[7,8,9]], dtype=np.float64)
s = np.array(x.shape, dtype=np.int32)

c = LIBC.np_array_complex_shape(x, s)

I've tried different solutions I found on line, but non work. Could someone help me?

I am using linux and gcc compilers.

Upvotes: 2

Views: 813

Answers (1)

Joseph Sible-Reinstate Monica
Joseph Sible-Reinstate Monica

Reputation: 48592

While you can often get away with mixing up arrays with pointers to some extent, mixing up 2D arrays with pointers to pointers will never work right. If you know that the second dimension will always be 3, then you can change double ** data to double (*data)[3] in your C code, and then everything will work. If it's not always a constant, but Python will always know what it is and you're okay with using VLAs, then you can redeclare your function as void np_array_complex_shape(int cols, double (*data)[cols], int *shape) and pass the appropriate value for cols. Otherwise, you need to change it to double *data, and then manually calculate indices as if it were flattened into a 1D array (which is just changing data[0][0] to data[0] in your simple example).

Upvotes: 1

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