87 lines
3.5 KiB
C++
87 lines
3.5 KiB
C++
// Copyright Ankit Daftery 2011-2012.
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// Distributed under the Boost Software License, Version 1.0.
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// (See accompanying file LICENSE_1_0.txt or copy at
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// http://www.boost.org/LICENSE_1_0.txt)
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/**
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* @brief An example to demonstrate use of universal functions or ufuncs
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*
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*
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* @todo Calling the overloaded () operator is in a roundabout manner, find a simpler way
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* None of the methods like np::add, np::multiply etc are supported as yet
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*/
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#include <boost/python/numpy.hpp>
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#include <iostream>
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namespace p = boost::python;
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namespace np = boost::python::numpy;
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// Create the structs necessary to implement the ufuncs
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// The typedefs *must* be made
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struct UnarySquare
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{
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typedef double argument_type;
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typedef double result_type;
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double operator()(double r) const { return r * r;}
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};
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struct BinarySquare
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{
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typedef double first_argument_type;
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typedef double second_argument_type;
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typedef double result_type;
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double operator()(double a,double b) const { return (a*a + b*b) ; }
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};
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int main(int argc, char **argv)
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{
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// Initialize the Python runtime.
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Py_Initialize();
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// Initialize NumPy
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np::initialize();
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// Expose the struct UnarySquare to Python as a class, and let ud be the class object
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p::object ud = p::class_<UnarySquare, boost::shared_ptr<UnarySquare> >("UnarySquare")
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.def("__call__", np::unary_ufunc<UnarySquare>::make());
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// Let inst be an instance of the class ud
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p::object inst = ud();
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// Use the "__call__" method to call the overloaded () operator and print the value
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std::cout << "Square of unary scalar 1.0 is " << p::extract <char const * > (p::str(inst.attr("__call__")(1.0))) << std::endl ;
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// Create an array in C++
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int arr[] = {1,2,3,4} ;
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// ..and use it to create the ndarray in Python
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np::ndarray demo_array = np::from_data(arr, np::dtype::get_builtin<int>() , p::make_tuple(4), p::make_tuple(4), p::object());
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// Print out the demo array
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std::cout << "Demo array is " << p::extract <char const * > (p::str(demo_array)) << std::endl ;
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// Call the "__call__" method to perform the operation and assign the value to result_array
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p::object result_array = inst.attr("__call__")(demo_array) ;
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// Print the resultant array
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std::cout << "Square of demo array is " << p::extract <char const * > (p::str(result_array)) << std::endl ;
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// Lets try the same with a list
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p::list li ;
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li.append(3);
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li.append(7);
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// Print out the demo list
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std::cout << "Demo list is " << p::extract <char const * > (p::str(li)) << std::endl ;
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// Call the ufunc for the list
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result_array = inst.attr("__call__")(li) ;
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// And print the list out
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std::cout << "Square of demo list is " << p::extract <char const * > (p::str(result_array)) << std::endl ;
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// Now lets try Binary ufuncs
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// Expose the struct BinarySquare to Python as a class, and let ud be the class object
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ud = p::class_<BinarySquare, boost::shared_ptr<BinarySquare> >("BinarySquare")
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.def("__call__", np::binary_ufunc<BinarySquare>::make());
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// Again initialise inst as an instance of the class ud
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inst = ud();
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// Print the two input listsPrint the two input lists
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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 ;
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// Call the binary ufunc taking demo_array as both inputs
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result_array = inst.attr("__call__")(demo_array,demo_array) ;
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std::cout << "Square of list with binary ufunc is " << p::extract <char const * > (p::str(result_array)) << std::endl ;
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}
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