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// 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);
}
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