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NumPy C++ extension for boost::python
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martwo/BoostNumpy
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BoostNumpy ========== BoostNumpy is an extension of boost::python to handle numpy arrays in C++ code. It introduces the boost::numpy::ndarray class derived from boost::python::object to manage PyArrayType objects, i.e. numpy arrays. This project is based on an implemenation by Jim Bosch & co [1]. The major development of BoostNumpy is the dstream, a.k.a. data stream, sub-library for vectorizing (scalar) C++ functions. It implements the Generalized Universal Functions approach described by the numpy community [2]. BoostNumpy uses meta-programming (MPL) to achieve the vectorization of a C++ function with only one line of code. Example:: #include <boost/python.hpp> #include <boost/numpy/dstream.hpp> namespace bp = boost::python; namespace bn = boost::numpy; double square(double v) { return v*v; } BOOST_PYTHON_MODULE(my_py_module) { bn::initialize(); bn::dstream::def("square", &square, bp::arg("v"), "Calculates the square of v."); } The square function in Python will accept a numpy array as input and will return a numpy array as output:: import numpy as np import my_py_module arr = np.array([1, 2, 3]) out = my_py_module.square(arr) The C++ function will be called for every entry in the given input numpy array. Furthermore, the Python function will have an addition optional argument named "out=None" in order to pass an already existing output numpy array to the function. Of course, this works also for C++ class member functions using bp::class_<...>(...).def(bn::dstream::method(...)); An addition feature is multi-threading. By adding the bn::dstream::allow_threads() option to the bn::dstream::def function, an addition optional argument named "nthreads=1" is available to the Python function. So calculations can be distributed over several CPU cores. [1] https://github.com/ndarray/Boost.NumPy [2] http://docs.scipy.org/doc/numpy/reference/c-api.generalized-ufuncs.html Dependencies ------------ BoostNumpy depends on the following libraries: - cmake (>= 2.8.3) - boost (including boost::python) (>= 1.38) - python (>= 2.6) - numpy (>= 1.6) Installation ------------ An automated compilation and installation procedure is provided via cmake. In order to create a build directory with the neccessary cmake and make files, execute the ``configure`` script within the BoostNumpy source root directory:: ./configure --prefix </path/to/the/installation/location> The location of the final installation can be specified via the ``--prefix`` option. If this option is not specified, it will be installed inside the ./build directory. By default the g++ C++ compiler is chosen for compiling BoostNumpy. The compiler can be selected via the --c-compiler and --cxx-compiler option. Type ``./configure --help`` for a list of possible options. After success, change to the build directory:: cd build Start the compilation process:: make Run all the tests:: make test Build the documentation (if Sphinx is installed):: make html After that, install BoostNumpy (and the documentation) by typing:: make install Known Limitations ----------------- 1. Functions exposed using the dstream library cannot use references and/or const qualifiers in their arguments.
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