// 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 demonstrate use of universal functions or ufuncs

*

*

* @todo Calling the overloaded () operator is in a roundabout manner, find a simpler way

* None of the methods like np::add, np::multiply etc are supported as yet

*/

#include <boost/python/numpy.hpp>

#include <iostream>

namespace p = boost::python;

namespace np = boost::python::numpy;

// Create the structs necessary to implement the ufuncs

// The typedefs *must* be made

struct UnarySquare

{

typedef double argument_type;

typedef double result_type;

double operator()(double r) const { return r * r;}

};

struct BinarySquare

{

typedef double first_argument_type;

typedef double second_argument_type;

typedef double result_type;

double operator()(double a,double b) const { return (a*a + b*b) ; }

};

int main(int argc, char **argv)

{

// Initialize the Python runtime.

Py_Initialize();

// Initialize NumPy

np::initialize();

// Expose the struct UnarySquare to Python as a class, and let ud be the class object

p::object ud = p::class_<UnarySquare, boost::shared_ptr<UnarySquare> >("UnarySquare")

.def("__call__", np::unary_ufunc<UnarySquare>::make());

// Let inst be an instance of the class ud

p::object inst = ud();

// Use the "__call__" method to call the overloaded () operator and print the value

std::cout << "Square of unary scalar 1.0 is " << p::extract <char const * > (p::str(inst.attr("__call__")(1.0))) << std::endl ;

// Create an array in C++

int arr[] = {1,2,3,4} ;

// ..and use it to create the ndarray in Python

np::ndarray demo_array = np::from_data(arr, np::dtype::get_builtin<int>() , p::make_tuple(4), p::make_tuple(4), p::object());

// Print out the demo array

std::cout << "Demo array is " << p::extract <char const * > (p::str(demo_array)) << std::endl ;

// Call the "__call__" method to perform the operation and assign the value to result_array

p::object result_array = inst.attr("__call__")(demo_array) ;

// Print the resultant array

std::cout << "Square of demo array is " << p::extract <char const * > (p::str(result_array)) << std::endl ;

// Lets try the same with a list

p::list li ;

li.append(3);

li.append(7);

// Print out the demo list

std::cout << "Demo list is " << p::extract <char const * > (p::str(li)) << std::endl ;

// Call the ufunc for the list

result_array = inst.attr("__call__")(li) ;

// And print the list out

std::cout << "Square of demo list is " << p::extract <char const * > (p::str(result_array)) << std::endl ;

// Now lets try Binary ufuncs

// Expose the struct BinarySquare to Python as a class, and let ud be the class object

ud = p::class_<BinarySquare, boost::shared_ptr<BinarySquare> >("BinarySquare")

.def("__call__", np::binary_ufunc<BinarySquare>::make());

// Again initialise inst as an instance of the class ud

inst = ud();

// Print the two input listsPrint the two input lists

std::cout << "The two input list for binary ufunc are " << std::endl << p::extract <char const * > (p::str(demo_array)) << std::endl << p::extract <char const * > (p::str(demo_array)) << std::endl ;

// Call the binary ufunc taking demo_array as both inputs

result_array = inst.attr("__call__")(demo_array,demo_array) ;

std::cout << "Square of list with binary ufunc is " << p::extract <char const * > (p::str(result_array)) << std::endl ;

}