passing c++ double pointer to python

Question

I could pass one-dimension array to python like below. and I wonder if I can pass c++ double pointer array to python by using ctypes, numpy.

test.cpp:

#include <stdio.h>
extern "C" void cfun(const void * indatav, int rowcount, int colcount, void * outdatav);

void cfun(const void * indatav, int rowcount, int colcount, void * outdatav) {
    //void cfun(const double * indata, int rowcount, int colcount, double * outdata) {
    const double * indata = (double *) indatav;
    double * outdata = (double *) outdatav;
    int i;
    puts("Here we go!");
    for (i = 0; i < rowcount * colcount; ++i) {
        outdata[i] = indata[i] * 4;
    }
    puts("Done!");
}

test.py:

import numpy
import ctypes

indata = numpy.ones((5,6), dtype=numpy.double)
outdata = numpy.zeros((5,6), dtype=numpy.double)
lib = ctypes.cdll.LoadLibrary('./ctest.so')
fun = lib.cfun
# Here comes the fool part.
#fun(ctypes.c_void_p(indata.ctypes.data), ctypes.c_void_p(outdata.ctypes.data))

fun(ctypes.c_void_p(indata.ctypes.data), ctypes.c_int(5), ctypes.c_int(6),
    ctypes.c_void_p(outdata.ctypes.data))


print 'indata: %s' % indata
print 'outdata: %s' % outdata

This is a hack I have been taught, but why not just pass the pointers as long integers ? — Pavan Yalamanchili
– Pavan Yalamanchili, Commented Jan 9, 2012 at 3:58
The pointers can always be represented as long integers. and then cast back to whatever type you want. — Pavan Yalamanchili
– Pavan Yalamanchili, Commented Jan 16, 2012 at 15:30

Mark Tolonen · Accepted Answer · 2012-01-09 04:21:58Z

8

Here's a way. I didn't see a nice way to use numpy with double**.

test.cpp (Windows)

#include <stdio.h>

extern "C" __declspec(dllexport) void cfun(const double ** indata, int rowcount, int colcount, double ** outdata) {
    for (int i = 0; i < rowcount; ++i) {
        for (int j = 0; j < colcount; ++j) {
            outdata[i][j] = indata[i][j] * 4;
        }
    }
}

test.py

import numpy
import ctypes

# Allocate array of double*
indata = (ctypes.POINTER(ctypes.c_double) * 5)()
for i in range(5):
    # Allocate arrays of double
    indata[i] = (ctypes.c_double * 6)()
    for j in range(6):
        indata[i][j] = 1.0

outdata = (ctypes.POINTER(ctypes.c_double) * 5)()
for i in range(5):
    outdata[i] = (ctypes.c_double * 6)()
    for j in range(6):
        outdata[i][j] = 1.0

lib = ctypes.cdll.LoadLibrary('test')
fun = lib.cfun

def dump(a,rows,cols):
    for i in range(rows):
        for j in range(cols):
            print a[i][j],
        print

dump(indata,5,6)
fun(ctypes.byref(indata),5,6,ctypes.byref(outdata))
dump(outdata,5,6)

Output

1.0 1.0 1.0 1.0 1.0 1.0
1.0 1.0 1.0 1.0 1.0 1.0
1.0 1.0 1.0 1.0 1.0 1.0
1.0 1.0 1.0 1.0 1.0 1.0
1.0 1.0 1.0 1.0 1.0 1.0
4.0 4.0 4.0 4.0 4.0 4.0
4.0 4.0 4.0 4.0 4.0 4.0
4.0 4.0 4.0 4.0 4.0 4.0
4.0 4.0 4.0 4.0 4.0 4.0
4.0 4.0 4.0 4.0 4.0 4.0

edited Jan 9, 2012 at 4:21

answered Jan 9, 2012 at 3:55

Mark Tolonen

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6 Comments

wonjun Over a year ago

I got an error while creating ".so" file test.cpp:4:1: error: expected constructor, destructor, or type conversion before ‘(’ token

wonjun Over a year ago

it works fine without "__declspec(dllexport)". thanks and in fortran, multi-dimensional array can be passed directly with numpy right? fwrap.. actually I am looking for passing array among python <-> c,c++ <-> fortran.

Mark Tolonen Over a year ago

Yes, __declspec(dllexport) is Windows-specific to export a function from a dynamic library. The code you posted works as is (with minor mods for Windows, for me) with a double pointer and multi-dimensional array. You don't need all that casting, though. What exactly is your question?

Mark Tolonen Over a year ago

I haven't touched Fortran for years so can't help there. I'll note that if you write your original C++ function with double* instead of void* you can pass _____.ctypes.data directly without the ctypes.c_void_p wrappers. You also can pass 5,6 instead of ctypes.c_int(5),ctypes.c_int(6).

wonjun Over a year ago

Is there a way to pass this array by using numpy? I want to use numpy not only using ctypes.

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