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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 using arbitrary Python sequences. * * The Python sequence could be any object whose __array__ method returns an array, or any * (nested) sequence. This example also shows how to create arrays using both unit and * non-unit strides. */ #include #include namespace p = boost::python; namespace np = boost::python::numpy; #if _MSC_VER using boost::uint8_t; #endif int main(int argc, char **argv) { // Initialize the Python runtime. Py_Initialize(); // Initialize NumPy np::initialize(); // Create an ndarray from a simple tuple p::object tu = p::make_tuple('a','b','c') ; np::ndarray example_tuple = np::array (tu) ; // and from a list p::list l ; np::ndarray example_list = np::array (l) ; // Optionally, you can also specify a dtype np::dtype dt = np::dtype::get_builtin(); np::ndarray example_list1 = np::array (l,dt); // You can also create an array by supplying data.First,create an integer array int data[] = {1,2,3,4} ; // Create a shape, and strides, needed by the function p::tuple shape = p::make_tuple(4) ; p::tuple stride = p::make_tuple(4) ; // The function also needs an owner, to keep track of the data array passed. Passing none is dangerous p::object own ; // The from_data function takes the data array, datatype,shape,stride and owner as arguments // and returns an ndarray np::ndarray data_ex = np::from_data(data,dt,shape,stride,own); // Print the ndarray we created std::cout