Short Answer
The NameError was cause by the fact that Python couldn't find the module, the working directory isn't automatically added to your PYTHONPATH. Using setenv with setenv("PYTHONPATH", ".", 1); in your C/C++ code fixes this.
Longer Answer
There's an easy way to do this, apparently. With a python module pythonmodule.py containing an already created array:
import numpy as np
result = np.arange(20, dtype=np.float).reshape((2, 10))
You can structure your pymodule.pyx to export that array by using the public keyword. By adding some auxiliary functions, you'll generally won't need to touch neither the Python, nor the Numpy C-API:
from pythonmodule import result
from libc.stdlib cimport malloc
import numpy as np
cimport numpy as np
cdef public np.ndarray getNPArray():
""" Return array from pythonmodule. """
return <np.ndarray>result
cdef public int getShape(np.ndarray arr, int shape):
""" Return Shape of the Array based on shape par value. """
return <int>arr.shape[1] if shape else <int>arr.shape[0]
cdef public void copyData(float *** dst, np.ndarray src):
""" Copy data from src numpy array to dst. """
cdef float **tmp
cdef int i, j, m = src.shape[0], n=src.shape[1];
# Allocate initial pointer
tmp = <float **>malloc(m * sizeof(float *))
if not tmp:
raise MemoryError()
# Allocate rows
for j in range(m):
tmp[j] = <float *>malloc(n * sizeof(float))
if not tmp[j]:
raise MemoryError()
# Copy numpy Array
for i in range(m):
for j in range(n):
tmp[i][j] = src[i, j]
# Assign pointer to dst
dst[0] = tmp
Function getNPArray and getShape return the array and its shape, respectively. copyData was added in order to just extract the ndarray.data and copy it so you can then finalize Python and work without having the interpreter initialized.
A sample program (in C, C++ should look identical) would look like this:
#include <Python.h>
#include "numpy/arrayobject.h"
#include "pyxmod.h"
#include <stdio.h>
void printArray(float **arr, int m, int n);
void getArray(float ***arr, int * m, int * n);
int main(int argc, char **argv){
// Holds data and shapes.
float **data = NULL;
int m, n;
// Gets array and then prints it.
getArray(&data, &m, &n);
printArray(data, m, n);
return 0;
}
void getArray(float ***data, int * m, int * n){
// setenv is important, makes python find
// modules in working directory
setenv("PYTHONPATH", ".", 1);
// Initialize interpreter and module
Py_Initialize();
initpyxmod();
// Use Cython functions.
PyArrayObject *arr = getNPArray();
*m = getShape(arr, 0);
*n = getShape(arr, 1);
copyData(data, arr);
if (data == NULL){ //really redundant.
fprintf(stderr, "Data is NULL\n");
return ;
}
Py_DECREF(arr);
Py_Finalize();
}
void printArray(float **arr, int m, int n){
int i, j;
for(i=0; i < m; i++){
for(j=0; j < n; j++)
printf("%f ", arr[i][j]);
printf("\n");
}
}
Always remember to set:
setenv("PYTHONPATH", ".", 1);
before you call Py_Initialize so Python can find modules in the working directory.
The rest is pretty straight-forward. It might need some additional error-checking and definitely needs a function to free the allocated memmory.
Alternate Way w/o Cython:
Doing it the way you are attempting is way hassle than it's worth, you would probably be better off using numpy.save to save your array in a npy binary file and then use some C++ library that reads that file for you.
