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50 lines
1.8 KiB
C++
50 lines
1.8 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 show how to create ndarrays with built-in python data types, and extract
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* the types and values of member variables
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*
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* @todo Add an example to show type conversion.
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* Add an example to show use of user-defined types
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*
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*/
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#include <boost/numpy.hpp>
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#include <iostream>
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namespace p = boost::python;
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namespace np = boost::numpy;
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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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// Create a 3x3 shape...
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p::tuple shape = p::make_tuple(3, 3);
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// ...as well as a type for C++ double
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np::dtype dtype = np::dtype::get_builtin<double>();
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// Construct an array with the above shape and type
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np::ndarray a = np::zeros(shape, dtype);
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// Print the array
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std::cout << "Original array:\n" << p::extract<char const *>(p::str(a)) << std::endl;
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// Print the datatype of the elements
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std::cout << "Datatype is:\n" << p::extract<char const *>(p::str(a.get_dtype())) << std::endl ;
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// Using user defined dtypes to create dtype and an array of the custom dtype
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// First create a tuple with a variable name and its dtype, double, to create a custom dtype
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p::tuple for_custom_dtype = p::make_tuple("ha",dtype) ;
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// The list needs to be created, because the constructor to create the custom dtype
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// takes a list of (variable,variable_type) as an argument
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p::list list_for_dtype ;
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list_for_dtype.append(for_custom_dtype) ;
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// Create the custom dtype
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np::dtype custom_dtype = np::dtype(list_for_dtype) ;
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// Create an ndarray with the custom dtype
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np::ndarray new_array = np::zeros(shape,custom_dtype);
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}
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