numpy - 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

Answer 1

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