libs/python/example/numpy/dtype.cpp
// 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); }