52 lines
1.9 KiB
ReStructuredText
52 lines
1.9 KiB
ReStructuredText
|
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/numpy.hpp>
|
||
|
|
#include <iostream>
|
||
|
|
|
||
|
|
namespace p = boost::python;
|
||
|
|
namespace np = boost::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} ;
|
||
|
|
np::ndarray py_array = np::from_data(arr, np::dtype::get_builtin<int>() , p::make_tuple(4), p::make_tuple(4), 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<4 ; 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.
|
||
|
|
|