I am trying to use python 3 (with numpy) in my C++ application.
This entails sending a C++ array to python, performing calculations and then retrieving the result in C++.
To do this I based myself on the code that was discussed here:
https://codereview.stackexchange.com/questions/92266/sending-a-c-array-to-python-numpy-and-back/92353#92353
and also here:
Sending a C++ array to Python and back (Extending C++ with Numpy).
While the example from the code review post basically works I am having troubles with the return values when I modified the python and C++ script: when I am trying to return a variable that was created in python the result is a vector of nan instead of the intended computations.
My guess is that the object somehow goes out of scope but I can't fix this problem.
I use the following python script in a file called mymodule.py:
import numpy
def array_tutorial(a):
print("array_tutorial - python")
print(a)
print("")
firstRow = a[0,:]
#beta = numpy.array([[10,20,30],[10,20,30],[10,20,30]])
#firstRow = beta[0,:]
return firstRow
def myfunction():
beta = numpy.array([[1,2,3],[1,2,3],[1,2,3]])
print("myfunction - python")
print(beta)
print("")
firstRow = beta[0,:]
return firstRow
#define NPY_NO_DEPRECATED_API NPY_1_7_API_VERSION
#include <stdio.h>
#include <iostream>
#include <stdlib.h>
#include <Python.h>
#include "numpy/arrayobject.h"
int main(int argc, char* argv[])
{
setenv("PYTHONPATH", ".", 0);
Py_Initialize();
import_array();
// Build the 2D array in C++
const int SIZE = 3;
npy_intp dims[2]{SIZE, SIZE};
const int ND = 2;
long double(*c_arr)[SIZE]{ new long double[SIZE][SIZE] };
for (int i = 0; i < SIZE; i++){
for (int j = 0; j < SIZE; j++){
c_arr[i][j] = i + j;}
}
// Convert it to a NumPy array.
PyObject *pArray = PyArray_SimpleNewFromData(ND, dims, NPY_LONGDOUBLE, reinterpret_cast<void*>(c_arr));
// import mymodule
const char *module_name = "mymodule";
PyObject *pName = PyUnicode_FromString(module_name);
PyObject *pModule = PyImport_Import(pName);
Py_DECREF(pName);
// import function
const char *func_name = "array_tutorial";
PyObject *pFunc = PyObject_GetAttrString(pModule, func_name);
PyObject *pReturn = PyObject_CallFunctionObjArgs(pFunc, pArray, NULL);
PyArrayObject *np_ret = reinterpret_cast<PyArrayObject*>(pReturn);
// Convert back to C++ array and print.
int len = PyArray_SHAPE(np_ret)[0];
long double* c_out;
c_out = reinterpret_cast<long double*>(PyArray_DATA(np_ret));
std::cout << "Printing output array - C++" << std::endl;
for (int i = 0; i < len; i++){
std::cout << c_out[i] << ' ';
}
std::cout << std::endl << std::endl;
// import function without arguments
const char *func_name2 = "myfunction";
PyObject *pFunc2 = PyObject_GetAttrString(pModule, func_name2);
PyObject *pReturn2 = PyObject_CallFunctionObjArgs(pFunc2, NULL);
PyArrayObject *np_ret2 = reinterpret_cast<PyArrayObject*>(pReturn2);
// convert back to C++ array and print
int len2 = PyArray_SHAPE(np_ret2)[0];
long double* c_out2;
c_out2 = reinterpret_cast<long double*>(PyArray_DATA(np_ret2));
std::cout << "Printing output array 2 - C++" << std::endl;
for (int i = 0; i < len2; i++){
std::cout << c_out2[i] << ' ';
}
std::cout << std::endl << std::endl;
Py_Finalize();
return 0;
}
setenv("PYTHONPATH", ".", 0);
g++ -Wall numpy_cpp.cpp -I/usr/include/python3.5m/ -lpython3.5m
array_tutorial - python
[[ 0.0 1.0 2.0]
[ 1.0 2.0 3.0]
[ 2.0 3.0 4.0]]
Printing output array - C++
0 1 2
myfunction - python
[[1 2 3]
[1 2 3]
[1 2 3]]
Printing output array 2 - C++
nan nan nan
import numpy
def array_tutorial(a):
print("array_tutorial - python")
print(a)
print(numpy.dtype(a[0,0]))
print("")
firstRow = a[0,:]
#beta = numpy.array([[10,20,30],[10,20,30],[10,20,30]],dtype=numpy.float128)
#firstRow = beta[0,:]
return firstRow
def myfunction():
beta = numpy.array([[1,2,3],[1,2,3],[1,2,3]],dtype=numpy.float128)
print("myfunction - python")
print(beta)
print("")
firstRow = beta[0,:]
return firstRow
You should specify dtype when you create the array in Python code. You are casting to long double in C++ code while the dtype is deduced to be int64 (on 64-bit platforms)