text: // Copyright Ankit Daftery 2011-2012.
  // Distributed under the Boost Software License, Version 1.0.
  //    (See accompanying file LICENSE_1_0.txt or copy at
  //          http://www.boost.org/LICENSE_1_0.txt)
  
  /**
   *  @brief An example to show how to create ndarrays with built-in python data types, and extract
   *         the types and values of member variables
   *
   *  @todo Add an example to show type conversion.
   *        Add an example to show use of user-defined types
   *        
   */
  
  #include <boost/python/numpy.hpp>
  #include <iostream>
  
  namespace p = boost::python;
  namespace np = boost::python::numpy;
  
  int main(int argc, char **argv)
  {
    // Initialize the Python runtime.
    Py_Initialize();
    // Initialize NumPy
    np::initialize();
    // Create a 3x3 shape...
    p::tuple shape = p::make_tuple(3, 3);
    // ...as well as a type for C++ double
    np::dtype dtype = np::dtype::get_builtin<double>();
    // Construct an array with the above shape and type
    np::ndarray a = np::zeros(shape, dtype);
    // Print the array
    std::cout << "Original array:\n" << p::extract<char const *>(p::str(a)) << std::endl;
    // Print the datatype of the elements
    std::cout << "Datatype is:\n" << p::extract<char const *>(p::str(a.get_dtype())) << std::endl ;
    // Using user defined dtypes to create dtype and an array of the custom dtype
    // First create a tuple with a variable name and its dtype, double, to create a custom dtype
    p::tuple for_custom_dtype = p::make_tuple("ha",dtype) ;
    // The list needs to be created, because the constructor to create the custom dtype
    // takes a list of (variable,variable_type) as an argument
    p::list list_for_dtype ;
    list_for_dtype.append(for_custom_dtype) ;
    // Create the custom dtype
    np::dtype custom_dtype = np::dtype(list_for_dtype) ;
    // Create an ndarray with the custom dtype
    np::ndarray new_array = np::zeros(shape,custom_dtype);
  
  }
  