ceph/src/boost/libs/python/doc/numpy/tutorial/fromdata.rst

   1 How to access data using raw pointers
   2 =====================================
   3
   4 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.
   5 The from_data method makes this possible.
   6
   7 Like before, first get the necessary headers, setup the namespaces and initialize the Python runtime and numpy module::
   8
   9   #include <boost/python/numpy.hpp>
  10   #include <iostream>
  11
  12   namespace p = boost::python;
  13   namespace np = boost::python::numpy;
  14
  15   int main(int argc, char **argv)
  16   {
  17     Py_Initialize();
  18     np::initialize();
  19
  20 Create an array in C++ , and pass the pointer to it to the from_data method to create an ndarray::
  21
  22     int arr[] = {1,2,3,4,5};
  23     np::ndarray py_array = np::from_data(arr, np::dtype::get_builtin<int>(),
  24                                          p::make_tuple(5),
  25                                          p::make_tuple(sizeof(int)),
  26                                          p::object());
  27
  28 Print the source C++ array, as well as the ndarray, to check if they are the same::
  29
  30     std::cout << "C++ array :" << std::endl;
  31     for (int j=0;j<4;j++)
  32     {
  33       std::cout << arr[j] << ' ';
  34     }
  35     std::cout << std::endl
  36               << "Python ndarray :" << p::extract<char const *>(p::str(py_array)) << std::endl;
  37
  38 Now, change an element in the Python ndarray, and check if the value changed correspondingly in the source C++ array::
  39
  40     py_array[1] = 5 ;
  41     std::cout << "Is the change reflected in the C++ array used to create the ndarray ? " << std::endl;
  42     for (int j = 0; j < 5; j++)
  43     {
  44       std::cout << arr[j] << ' ';
  45     }
  46
  47 Next, change an element of the source C++ array and see if it is reflected in the Python ndarray::
  48
  49     arr[2] = 8;
  50     std::cout << std::endl
  51               << "Is the change reflected in the Python ndarray ?" << std::endl
  52               << p::extract<char const *>(p::str(py_array)) << std::endl;
  53   }
  54
  55 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.
  56