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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);

}