How to access data using raw pointers - Boost.Python NumPy extension 1.0 documentation

###  | # (NumPy) |

# How to access data using raw pointers

One of the advantages of the ndarray wrapper is that the same data can be used in both Python and C++ and changes can be made to reflect at both ends. The from_data method makes this possible.

Like before, first get the necessary headers, setup the namespaces and initialize the Python runtime and numpy module:

    #include <boost/python/numpy.hpp>
    #include <iostream>

    namespace p = boost::python;
    namespace np = boost::python::numpy;

    int main(int argc, char **argv)
    {
      Py_Initialize();
      np::initialize();

Create an array in C++ , and pass the pointer to it to the from_data method to create an ndarray:

    int arr[] = {1,2,3,4,5};
    np::ndarray py_array = np::from_data(arr, np::dtype::get_builtin<int>(),
                                         p::make_tuple(5),
                                         p::make_tuple(sizeof(int)),
                                         p::object());

Print the source C++ array, as well as the ndarray, to check if they are the same:

    std::cout << "C++ array :" << std::endl;
    for (int j=0;j<4;j++)
    {
      std::cout << arr[j] << ' ';
    }
    std::cout << std::endl
              << "Python ndarray :" << p::extract<char const *>(p::str(py_array)) << std::endl;

Now, change an element in the Python ndarray, and check if the value changed correspondingly in the source C++ array:

    py_array[1] = 5 ;
    std::cout << "Is the change reflected in the C++ array used to create the ndarray ? " << std::endl;
    for (int j = 0; j < 5; j++)
    {
      std::cout << arr[j] << ' ';
    }

Next, change an element of the source C++ array and see if it is reflected in the Python ndarray:

      arr[2] = 8;
      std::cout << std::endl
                << "Is the change reflected in the Python ndarray ?" << std::endl
                << p::extract<char const *>(p::str(py_array)) << std::endl;
    }

As we can see, the changes are reflected across the ends. This happens because the from_data method passes the C++ array by reference to create the ndarray, and thus uses the same locations for storing data.