Sending a C++ array to Python and back (Extending C++ with Numpy)

Question

I am going to send a c++ array to a python function as numpy array and get back another numpy array. After consulting with numpy

Answer 1

Try out xtensor and the xtensor-python python bindings.

xtensor is a C++ library meant for numerical analysis with multi-dimensional array expressions.

xtensor provides

• an extensible expression system enabling numpy-style broadcasting (see the numpy to xtensor cheat sheet).
• an API following the idioms of the C++ standard library.
• tools to manipulate array expressions and build upon xtensor.
• bindings for Python, but also R and Julia.

Example of usage

Initialize a 2-D array and compute the sum of one of its rows and a 1-D array.

#include 
#include "xtensor/xarray.hpp"
#include "xtensor/xio.hpp"

xt::xarray arr1
  {{1.0, 2.0, 3.0},
   {2.0, 5.0, 7.0},
   {2.0, 5.0, 7.0}};

xt::xarray arr2
  {5.0, 6.0, 7.0};

xt::xarray res = xt::view(arr1, 1) + arr2;

std::cout << res;

Outputs

{7, 11, 14}

Creating a Numpy-style universal function in C++.

#include "pybind11/pybind11.h"
#include "xtensor-python/pyvectorize.hpp"
#include 
#include 

namespace py = pybind11;

double scalar_func(double i, double j)
{
    return std::sin(i) - std::cos(j);
}

PYBIND11_PLUGIN(xtensor_python_test)
{
    py::module m("xtensor_python_test", "Test module for xtensor python bindings");

    m.def("vectorized_func", xt::pyvectorize(scalar_func), "");

    return m.ptr();
}

Python code:

import numpy as np
import xtensor_python_test as xt

x = np.arange(15).reshape(3, 5)
y = [1, 2, 3, 4, 5]
z = xt.vectorized_func(x, y)
z

Outputs

[[-0.540302,  1.257618,  1.89929 ,  0.794764, -1.040465],
 [-1.499227,  0.136731,  1.646979,  1.643002,  0.128456],
 [-1.084323, -0.583843,  0.45342 ,  1.073811,  0.706945]]