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Diffstat (limited to 'src/boost/libs/python/example')
19 files changed, 1169 insertions, 0 deletions
diff --git a/src/boost/libs/python/example/Jamroot b/src/boost/libs/python/example/Jamroot new file mode 100644 index 000000000..fe9d69ecc --- /dev/null +++ b/src/boost/libs/python/example/Jamroot @@ -0,0 +1,35 @@ +# Copyright Stefan Seefeld 2016. +# 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) + +import python ; + +if ! [ python.configured ] +{ + ECHO "warning: no Python configured in user-config.jam" ; + ECHO "warning: will use default configuration" ; + using python ; +} + +# Adjust the following if Boost.Python isn't installed in a default location +lib boost_python ; + +project + : requirements +# <include>/path/to/boost/python + <library>boost_python +; + +rule run-test ( test-name : sources + ) +{ + import testing ; + testing.make-test run-pyd : $(sources) : : $(test-name) ; +} + +build-project quickstart ; +build-project tutorial ; +if [ python.numpy ] +{ + build-project numpy ; +} diff --git a/src/boost/libs/python/example/README.md b/src/boost/libs/python/example/README.md new file mode 100644 index 000000000..b090cbe1e --- /dev/null +++ b/src/boost/libs/python/example/README.md @@ -0,0 +1,11 @@ + + +# Examples + +This directory contains various examples using Boost.Python. +You may compile these using the `bjam` command either in this directory +or in any of the subdirectories. +You may need to adjust the paths in the Jamroot file if Boost.Python +is not installed in a default location. +See http://boostorg.github.io/python/doc/html/building/no_install_quickstart.html +for details. diff --git a/src/boost/libs/python/example/numpy/Jamfile b/src/boost/libs/python/example/numpy/Jamfile new file mode 100644 index 000000000..ac70a6ff0 --- /dev/null +++ b/src/boost/libs/python/example/numpy/Jamfile @@ -0,0 +1,29 @@ +# Copyright Stefan Seefeld 2016. +# 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) + +import python ; + +# Adjust the following if Boost.Python isn't installed in a default location +lib boost_numpy + : + : <search>/usr/local/Boost/lib + <include>/usr/local/Boost/include + ; + +project numpy + : requirements + <include>/usr/local/Boost/include + <library>boost_numpy + <location>. + ; + +exe simple : simple.cpp boost_numpy /python//python ; +exe dtype : dtype.cpp boost_numpy /python//python ; +exe ndarray : ndarray.cpp /python//python ; +exe fromdata : fromdata.cpp /python//python ; +exe ufunc : ufunc.cpp /python//python ; +exe wrap : wrap.cpp /python//python ; + +python-extension gaussian : gaussian.cpp ; diff --git a/src/boost/libs/python/example/numpy/demo_gaussian.py b/src/boost/libs/python/example/numpy/demo_gaussian.py new file mode 100644 index 000000000..0b1c78995 --- /dev/null +++ b/src/boost/libs/python/example/numpy/demo_gaussian.py @@ -0,0 +1,37 @@ +# Copyright Jim Bosch 2010-2012. +# 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) + +import numpy +import gaussian + +mu = numpy.zeros(2, dtype=float) +sigma = numpy.identity(2, dtype=float) +sigma[0, 1] = 0.15 +sigma[1, 0] = 0.15 + +g = gaussian.bivariate_gaussian(mu, sigma) + +r = numpy.linspace(-40, 40, 1001) +x, y = numpy.meshgrid(r, r) + +z = g(x, y) + +s = z.sum() * (r[1] - r[0])**2 +print "sum (should be ~ 1):", s + +xc = (z * x).sum() / z.sum() +print "x centroid (should be ~ %f): %f" % (mu[0], xc) + +yc = (z * y).sum() / z.sum() +print "y centroid (should be ~ %f): %f" % (mu[1], yc) + +xx = (z * (x - xc)**2).sum() / z.sum() +print "xx moment (should be ~ %f): %f" % (sigma[0,0], xx) + +yy = (z * (y - yc)**2).sum() / z.sum() +print "yy moment (should be ~ %f): %f" % (sigma[1,1], yy) + +xy = 0.5 * (z * (x - xc) * (y - yc)).sum() / z.sum() +print "xy moment (should be ~ %f): %f" % (sigma[0,1], xy) diff --git a/src/boost/libs/python/example/numpy/dtype.cpp b/src/boost/libs/python/example/numpy/dtype.cpp new file mode 100644 index 000000000..749a36b5e --- /dev/null +++ b/src/boost/libs/python/example/numpy/dtype.cpp @@ -0,0 +1,49 @@ +// 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); + +} diff --git a/src/boost/libs/python/example/numpy/fromdata.cpp b/src/boost/libs/python/example/numpy/fromdata.cpp new file mode 100644 index 000000000..bd073cc69 --- /dev/null +++ b/src/boost/libs/python/example/numpy/fromdata.cpp @@ -0,0 +1,48 @@ +// 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 access data using raw pointers. This shows that you can use and + * manipulate data in either Python or C++ and have the changes reflected in both. + */ + +#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 an array in C++ + int arr[] = {1,2,3,4} ; + // Create the ndarray in Python + np::ndarray py_array = np::from_data(arr, np::dtype::get_builtin<int>() , p::make_tuple(4), p::make_tuple(4), p::object()); + // Print the ndarray that we just created, and the source C++ array + std::cout << "C++ array :" << std::endl ; + for (int j=0;j<4;j++) + { + std::cout << arr[j] << ' ' ; + } + std::cout << std::endl << "Python ndarray :" << p::extract<char const *>(p::str(py_array)) << std::endl; + // Change an element in the python ndarray + py_array[1] = 5 ; + // And see if the C++ container is changed or not + std::cout << "Is the change reflected in the C++ array used to create the ndarray ? " << std::endl ; + for (int j = 0;j<4 ; j++) + { + std::cout << arr[j] << ' ' ; + } + // Conversely, change it in C++ + arr[2] = 8 ; + // And see if the changes are reflected in the Python ndarray + std::cout << std::endl << "Is the change reflected in the Python ndarray ?" << std::endl << p::extract<char const *>(p::str(py_array)) << std::endl; + +} diff --git a/src/boost/libs/python/example/numpy/gaussian.cpp b/src/boost/libs/python/example/numpy/gaussian.cpp new file mode 100644 index 000000000..5f138b397 --- /dev/null +++ b/src/boost/libs/python/example/numpy/gaussian.cpp @@ -0,0 +1,315 @@ +// Copyright Jim Bosch 2010-2012. +// 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) + +#include <boost/python/numpy.hpp> + +#include <cmath> +#include <memory> + +#ifndef M_PI +#include <boost/math/constants/constants.hpp> +const double M_PI = boost::math::constants::pi<double>(); +#endif + +namespace bp = boost::python; +namespace bn = boost::python::numpy; + +/** + * A 2x2 matrix class, purely for demonstration purposes. + * + * Instead of wrapping this class with Boost.Python, we'll convert it to/from numpy.ndarray. + */ +class matrix2 { +public: + + double & operator()(int i, int j) { + return _data[i*2 + j]; + } + + double const & operator()(int i, int j) const { + return _data[i*2 + j]; + } + + double const * data() const { return _data; } + +private: + double _data[4]; +}; + +/** + * A 2-element vector class, purely for demonstration purposes. + * + * Instead of wrapping this class with Boost.Python, we'll convert it to/from numpy.ndarray. + */ +class vector2 { +public: + + double & operator[](int i) { + return _data[i]; + } + + double const & operator[](int i) const { + return _data[i]; + } + + double const * data() const { return _data; } + + vector2 operator+(vector2 const & other) const { + vector2 r; + r[0] = _data[0] + other[0]; + r[1] = _data[1] + other[1]; + return r; + } + + vector2 operator-(vector2 const & other) const { + vector2 r; + r[0] = _data[0] - other[0]; + r[1] = _data[1] - other[1]; + return r; + } + +private: + double _data[2]; +}; + +/** + * Matrix-vector multiplication. + */ +vector2 operator*(matrix2 const & m, vector2 const & v) { + vector2 r; + r[0] = m(0, 0) * v[0] + m(0, 1) * v[1]; + r[1] = m(1, 0) * v[0] + m(1, 1) * v[1]; + return r; +} + +/** + * Vector inner product. + */ +double dot(vector2 const & v1, vector2 const & v2) { + return v1[0] * v2[0] + v1[1] * v2[1]; +} + +/** + * This class represents a simple 2-d Gaussian (Normal) distribution, defined by a + * mean vector 'mu' and a covariance matrix 'sigma'. + */ +class bivariate_gaussian { +public: + + vector2 const & get_mu() const { return _mu; } + + matrix2 const & get_sigma() const { return _sigma; } + + /** + * Evaluate the density of the distribution at a point defined by a two-element vector. + */ + double operator()(vector2 const & p) const { + vector2 u = _cholesky * (p - _mu); + return 0.5 * _cholesky(0, 0) * _cholesky(1, 1) * std::exp(-0.5 * dot(u, u)) / M_PI; + } + + /** + * Evaluate the density of the distribution at an (x, y) point. + */ + double operator()(double x, double y) const { + vector2 p; + p[0] = x; + p[1] = y; + return operator()(p); + } + + /** + * Construct from a mean vector and covariance matrix. + */ + bivariate_gaussian(vector2 const & mu, matrix2 const & sigma) + : _mu(mu), _sigma(sigma), _cholesky(compute_inverse_cholesky(sigma)) + {} + +private: + + /** + * This evaluates the inverse of the Cholesky factorization of a 2x2 matrix; + * it's just a shortcut in evaluating the density. + */ + static matrix2 compute_inverse_cholesky(matrix2 const & m) { + matrix2 l; + // First do cholesky factorization: l l^t = m + l(0, 0) = std::sqrt(m(0, 0)); + l(0, 1) = m(0, 1) / l(0, 0); + l(1, 1) = std::sqrt(m(1, 1) - l(0,1) * l(0,1)); + // Now do forward-substitution (in-place) to invert: + l(0, 0) = 1.0 / l(0, 0); + l(1, 0) = l(0, 1) = -l(0, 1) / l(1, 1); + l(1, 1) = 1.0 / l(1, 1); + return l; + } + + vector2 _mu; + matrix2 _sigma; + matrix2 _cholesky; + +}; + +/* + * We have a two options for wrapping get_mu and get_sigma into NumPy-returning Python methods: + * - we could deep-copy the data, making totally new NumPy arrays; + * - we could make NumPy arrays that point into the existing memory. + * The latter is often preferable, especially if the arrays are large, but it's dangerous unless + * the reference counting is correct: the returned NumPy array needs to hold a reference that + * keeps the memory it points to from being deallocated as long as it is alive. This is what the + * "owner" argument to from_data does - the NumPy array holds a reference to the owner, keeping it + * from being destroyed. + * + * Note that this mechanism isn't completely safe for data members that can have their internal + * storage reallocated. A std::vector, for instance, can be invalidated when it is resized, + * so holding a Python reference to a C++ class that holds a std::vector may not be a guarantee + * that the memory in the std::vector will remain valid. + */ + +/** + * These two functions are custom wrappers for get_mu and get_sigma, providing the shallow-copy + * conversion with reference counting described above. + * + * It's also worth noting that these return NumPy arrays that cannot be modified in Python; + * the const overloads of vector::data() and matrix::data() return const references, + * and passing a const pointer to from_data causes NumPy's 'writeable' flag to be set to false. + */ +static bn::ndarray py_get_mu(bp::object const & self) { + vector2 const & mu = bp::extract<bivariate_gaussian const &>(self)().get_mu(); + return bn::from_data( + mu.data(), + bn::dtype::get_builtin<double>(), + bp::make_tuple(2), + bp::make_tuple(sizeof(double)), + self + ); +} +static bn::ndarray py_get_sigma(bp::object const & self) { + matrix2 const & sigma = bp::extract<bivariate_gaussian const &>(self)().get_sigma(); + return bn::from_data( + sigma.data(), + bn::dtype::get_builtin<double>(), + bp::make_tuple(2, 2), + bp::make_tuple(2 * sizeof(double), sizeof(double)), + self + ); +} + +/** + * To allow the constructor to work, we need to define some from-Python converters from NumPy arrays + * to the matrix/vector types. The rvalue-from-python functionality is not well-documented in Boost.Python + * itself; you can learn more from boost/python/converter/rvalue_from_python_data.hpp. + */ + +/** + * We start with two functions that just copy a NumPy array into matrix/vector objects. These will be used + * in the templated converted below. The first just uses the operator[] overloads provided by + * bp::object. + */ +static void copy_ndarray_to_mv2(bn::ndarray const & array, vector2 & vec) { + vec[0] = bp::extract<double>(array[0]); + vec[1] = bp::extract<double>(array[1]); +} + +/** + * Here, we'll take the alternate approach of using the strides to access the array's memory directly. + * This can be much faster for large arrays. + */ +static void copy_ndarray_to_mv2(bn::ndarray const & array, matrix2 & mat) { + // Unfortunately, get_strides() can't be inlined, so it's best to call it once up-front. + Py_intptr_t const * strides = array.get_strides(); + for (int i = 0; i < 2; ++i) { + for (int j = 0; j < 2; ++j) { + mat(i, j) = *reinterpret_cast<double const *>(array.get_data() + i * strides[0] + j * strides[1]); + } + } +} + +/** + * Here's the actual converter. Because we've separated the differences into the above functions, + * we can write a single template class that works for both matrix2 and vector2. + */ +template <typename T, int N> +struct mv2_from_python { + + /** + * Register the converter. + */ + mv2_from_python() { + bp::converter::registry::push_back( + &convertible, + &construct, + bp::type_id< T >() + ); + } + + /** + * Test to see if we can convert this to the desired type; if not return zero. + * If we can convert, returned pointer can be used by construct(). + */ + static void * convertible(PyObject * p) { + try { + bp::object obj(bp::handle<>(bp::borrowed(p))); + std::auto_ptr<bn::ndarray> array( + new bn::ndarray( + bn::from_object(obj, bn::dtype::get_builtin<double>(), N, N, bn::ndarray::V_CONTIGUOUS) + ) + ); + if (array->shape(0) != 2) return 0; + if (N == 2 && array->shape(1) != 2) return 0; + return array.release(); + } catch (bp::error_already_set & err) { + bp::handle_exception(); + return 0; + } + } + + /** + * Finish the conversion by initializing the C++ object into memory prepared by Boost.Python. + */ + static void construct(PyObject * obj, bp::converter::rvalue_from_python_stage1_data * data) { + // Extract the array we passed out of the convertible() member function. + std::auto_ptr<bn::ndarray> array(reinterpret_cast<bn::ndarray*>(data->convertible)); + // Find the memory block Boost.Python has prepared for the result. + typedef bp::converter::rvalue_from_python_storage<T> storage_t; + storage_t * storage = reinterpret_cast<storage_t*>(data); + // Use placement new to initialize the result. + T * m_or_v = new (storage->storage.bytes) T(); + // Fill the result with the values from the NumPy array. + copy_ndarray_to_mv2(*array, *m_or_v); + // Finish up. + data->convertible = storage->storage.bytes; + } + +}; + + +BOOST_PYTHON_MODULE(gaussian) { + bn::initialize(); + + // Register the from-python converters + mv2_from_python< vector2, 1 >(); + mv2_from_python< matrix2, 2 >(); + + typedef double (bivariate_gaussian::*call_vector)(vector2 const &) const; + + bp::class_<bivariate_gaussian>("bivariate_gaussian", bp::init<bivariate_gaussian const &>()) + + // Declare the constructor (wouldn't work without the from-python converters). + .def(bp::init< vector2 const &, matrix2 const & >()) + + // Use our custom reference-counting getters + .add_property("mu", &py_get_mu) + .add_property("sigma", &py_get_sigma) + + // First overload accepts a two-element array argument + .def("__call__", (call_vector)&bivariate_gaussian::operator()) + + // This overload works like a binary NumPy universal function: you can pass + // in scalars or arrays, and the C++ function will automatically be called + // on each element of an array argument. + .def("__call__", bn::binary_ufunc<bivariate_gaussian,double,double,double>::make()) + ; +} diff --git a/src/boost/libs/python/example/numpy/ndarray.cpp b/src/boost/libs/python/example/numpy/ndarray.cpp new file mode 100644 index 000000000..d7b57aa73 --- /dev/null +++ b/src/boost/libs/python/example/numpy/ndarray.cpp @@ -0,0 +1,71 @@ +// 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 <boost/python/numpy.hpp> +#include <iostream> + +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<int>(); + 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 << "Single dimensional array ::" << std::endl << p::extract < char const * > (p::str(data_ex)) << std::endl ; + // Now lets make an 3x2 ndarray from a multi-dimensional array using non-unit strides + // First lets create a 3x4 array of 8-bit integers + uint8_t mul_data[][4] = {{1,2,3,4},{5,6,7,8},{1,3,5,7}}; + // Now let's create an array of 3x2 elements, picking the first and third elements from each row + // For that, the shape will be 3x2 + shape = p::make_tuple(3,2) ; + // The strides will be 4x2 i.e. 4 bytes to go to the next desired row, and 2 bytes to go to the next desired column + stride = p::make_tuple(4,2) ; + // Get the numpy dtype for the built-in 8-bit integer data type + np::dtype dt1 = np::dtype::get_builtin<uint8_t>(); + // First lets create and print out the ndarray as is + np::ndarray mul_data_ex = np::from_data(mul_data,dt1, p::make_tuple(3,4),p::make_tuple(4,1),p::object()); + std::cout << "Original multi dimensional array :: " << std::endl << p::extract < char const * > (p::str(mul_data_ex)) << std::endl ; + // Now create the new ndarray using the shape and strides + mul_data_ex = np::from_data(mul_data,dt1, shape,stride,p::object()); + // Print out the array we created using non-unit strides + std::cout << "Selective multidimensional array :: "<<std::endl << p::extract < char const * > (p::str(mul_data_ex)) << std::endl ; + +} + + diff --git a/src/boost/libs/python/example/numpy/simple.cpp b/src/boost/libs/python/example/numpy/simple.cpp new file mode 100644 index 000000000..ad598bde4 --- /dev/null +++ b/src/boost/libs/python/example/numpy/simple.cpp @@ -0,0 +1,32 @@ +// Copyright 2011 Stefan Seefeld. +// 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) + +#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++ float + np::dtype dtype = np::dtype::get_builtin<float>(); + // Construct an array with the above shape and type + np::ndarray a = np::zeros(shape, dtype); + // Construct an empty array with the above shape and dtype as well + np::ndarray b = np::empty(shape,dtype); + // Print the array + std::cout << "Original array:\n" << p::extract<char const *>(p::str(a)) << std::endl; + // Reshape the array into a 1D array + a = a.reshape(p::make_tuple(9)); + // Print it again. + std::cout << "Reshaped array:\n" << p::extract<char const *>(p::str(a)) << std::endl; +} diff --git a/src/boost/libs/python/example/numpy/ufunc.cpp b/src/boost/libs/python/example/numpy/ufunc.cpp new file mode 100644 index 000000000..5fb692045 --- /dev/null +++ b/src/boost/libs/python/example/numpy/ufunc.cpp @@ -0,0 +1,86 @@ +// 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 demonstrate use of universal functions or ufuncs + * + * + * @todo Calling the overloaded () operator is in a roundabout manner, find a simpler way + * None of the methods like np::add, np::multiply etc are supported as yet + */ + +#include <boost/python/numpy.hpp> +#include <iostream> + +namespace p = boost::python; +namespace np = boost::python::numpy; + + +// Create the structs necessary to implement the ufuncs +// The typedefs *must* be made + +struct UnarySquare +{ + typedef double argument_type; + typedef double result_type; + + double operator()(double r) const { return r * r;} +}; + +struct BinarySquare +{ + typedef double first_argument_type; + typedef double second_argument_type; + typedef double result_type; + + double operator()(double a,double b) const { return (a*a + b*b) ; } +}; + +int main(int argc, char **argv) +{ + // Initialize the Python runtime. + Py_Initialize(); + // Initialize NumPy + np::initialize(); + // Expose the struct UnarySquare to Python as a class, and let ud be the class object + p::object ud = p::class_<UnarySquare, boost::shared_ptr<UnarySquare> >("UnarySquare") + .def("__call__", np::unary_ufunc<UnarySquare>::make()); + // Let inst be an instance of the class ud + p::object inst = ud(); + // Use the "__call__" method to call the overloaded () operator and print the value + std::cout << "Square of unary scalar 1.0 is " << p::extract <char const * > (p::str(inst.attr("__call__")(1.0))) << std::endl ; + // Create an array in C++ + int arr[] = {1,2,3,4} ; + // ..and use it to create the ndarray in Python + np::ndarray demo_array = np::from_data(arr, np::dtype::get_builtin<int>() , p::make_tuple(4), p::make_tuple(4), p::object()); + // Print out the demo array + std::cout << "Demo array is " << p::extract <char const * > (p::str(demo_array)) << std::endl ; + // Call the "__call__" method to perform the operation and assign the value to result_array + p::object result_array = inst.attr("__call__")(demo_array) ; + // Print the resultant array + std::cout << "Square of demo array is " << p::extract <char const * > (p::str(result_array)) << std::endl ; + // Lets try the same with a list + p::list li ; + li.append(3); + li.append(7); + // Print out the demo list + std::cout << "Demo list is " << p::extract <char const * > (p::str(li)) << std::endl ; + // Call the ufunc for the list + result_array = inst.attr("__call__")(li) ; + // And print the list out + std::cout << "Square of demo list is " << p::extract <char const * > (p::str(result_array)) << std::endl ; + // Now lets try Binary ufuncs + // Expose the struct BinarySquare to Python as a class, and let ud be the class object + ud = p::class_<BinarySquare, boost::shared_ptr<BinarySquare> >("BinarySquare") + .def("__call__", np::binary_ufunc<BinarySquare>::make()); + // Again initialise inst as an instance of the class ud + inst = ud(); + // Print the two input listsPrint the two input lists + 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 ; + // Call the binary ufunc taking demo_array as both inputs + result_array = inst.attr("__call__")(demo_array,demo_array) ; + std::cout << "Square of list with binary ufunc is " << p::extract <char const * > (p::str(result_array)) << std::endl ; +} + diff --git a/src/boost/libs/python/example/numpy/wrap.cpp b/src/boost/libs/python/example/numpy/wrap.cpp new file mode 100644 index 000000000..33f71c85a --- /dev/null +++ b/src/boost/libs/python/example/numpy/wrap.cpp @@ -0,0 +1,135 @@ +// Copyright Jim Bosch 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) + +/** + * A simple example showing how to wrap a couple of C++ functions that + * operate on 2-d arrays into Python functions that take NumPy arrays + * as arguments. + * + * If you find have a lot of such functions to wrap, you may want to + * create a C++ array type (or use one of the many existing C++ array + * libraries) that maps well to NumPy arrays and create Boost.Python + * converters. There's more work up front than the approach here, + * but much less boilerplate per function. See the "Gaussian" example + * included with Boost.NumPy for an example of custom converters, or + * take a look at the "ndarray" project on GitHub for a more complete, + * high-level solution. + * + * Note that we're using embedded Python here only to make a convenient + * self-contained example; you could just as easily put the wrappers + * in a regular C++-compiled module and imported them in regular + * Python. Again, see the Gaussian demo for an example. + */ + +#include <boost/python/numpy.hpp> +#include <boost/scoped_array.hpp> +#include <iostream> + +namespace p = boost::python; +namespace np = boost::python::numpy; + +// This is roughly the most efficient way to write a C/C++ function that operates +// on a 2-d NumPy array - operate directly on the array by incrementing a pointer +// with the strides. +void fill1(double * array, int rows, int cols, int row_stride, int col_stride) { + double * row_iter = array; + double n = 0.0; // just a counter we'll fill the array with. + for (int i = 0; i < rows; ++i, row_iter += row_stride) { + double * col_iter = row_iter; + for (int j = 0; j < cols; ++j, col_iter += col_stride) { + *col_iter = ++n; + } + } +} + +// Here's a simple wrapper function for fill1. It requires that the passed +// NumPy array be exactly what we're looking for - no conversion from nested +// sequences or arrays with other data types, because we want to modify it +// in-place. +void wrap_fill1(np::ndarray const & array) { + if (array.get_dtype() != np::dtype::get_builtin<double>()) { + PyErr_SetString(PyExc_TypeError, "Incorrect array data type"); + p::throw_error_already_set(); + } + if (array.get_nd() != 2) { + PyErr_SetString(PyExc_TypeError, "Incorrect number of dimensions"); + p::throw_error_already_set(); + } + fill1(reinterpret_cast<double*>(array.get_data()), + array.shape(0), array.shape(1), + array.strides(0) / sizeof(double), array.strides(1) / sizeof(double)); +} + +// Another fill function that takes a double**. This is less efficient, because +// it's not the native NumPy data layout, but it's common enough in C/C++ that +// it's worth its own example. This time we don't pass the strides, and instead +// in wrap_fill2 we'll require the C_CONTIGUOUS bitflag, which guarantees that +// the column stride is 1 and the row stride is the number of columns. That +// restricts the arrays that can be passed to fill2 (it won't work on most +// subarray views or transposes, for instance). +void fill2(double ** array, int rows, int cols) { + double n = 0.0; // just a counter we'll fill the array with. + for (int i = 0; i < rows; ++i) { + for (int j = 0; j < cols; ++j) { + array[i][j] = ++n; + } + } +} +// Here's the wrapper for fill2; it's a little more complicated because we need +// to check the flags and create the array of pointers. +void wrap_fill2(np::ndarray const & array) { + if (array.get_dtype() != np::dtype::get_builtin<double>()) { + PyErr_SetString(PyExc_TypeError, "Incorrect array data type"); + p::throw_error_already_set(); + } + if (array.get_nd() != 2) { + PyErr_SetString(PyExc_TypeError, "Incorrect number of dimensions"); + p::throw_error_already_set(); + } + if (!(array.get_flags() & np::ndarray::C_CONTIGUOUS)) { + PyErr_SetString(PyExc_TypeError, "Array must be row-major contiguous"); + p::throw_error_already_set(); + } + double * iter = reinterpret_cast<double*>(array.get_data()); + int rows = array.shape(0); + int cols = array.shape(1); + boost::scoped_array<double*> ptrs(new double*[rows]); + for (int i = 0; i < rows; ++i, iter += cols) { + ptrs[i] = iter; + } + fill2(ptrs.get(), array.shape(0), array.shape(1)); +} + +BOOST_PYTHON_MODULE(example) { + np::initialize(); // have to put this in any module that uses Boost.NumPy + p::def("fill1", wrap_fill1); + p::def("fill2", wrap_fill2); +} + +int main(int argc, char **argv) +{ + // This line makes our module available to the embedded Python intepreter. +# if PY_VERSION_HEX >= 0x03000000 + PyImport_AppendInittab("example", &PyInit_example); +# else + PyImport_AppendInittab("example", &initexample); +# endif + // Initialize the Python runtime. + Py_Initialize(); + + PyRun_SimpleString( + "import example\n" + "import numpy\n" + "z1 = numpy.zeros((5,6), dtype=float)\n" + "z2 = numpy.zeros((4,3), dtype=float)\n" + "example.fill1(z1)\n" + "example.fill2(z2)\n" + "print z1\n" + "print z2\n" + ); + Py_Finalize(); +} + + diff --git a/src/boost/libs/python/example/quickstart/Jamfile b/src/boost/libs/python/example/quickstart/Jamfile new file mode 100644 index 000000000..6dd351301 --- /dev/null +++ b/src/boost/libs/python/example/quickstart/Jamfile @@ -0,0 +1,35 @@ +# Copyright Stefan Seefeld 2016. +# 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) + +import python ; +import testing ; + +project quickstart + : requirements + <location>. + ; + +# Declare a Python extension called hello. +python-extension extending : extending.cpp ; + +# Declare an executable called embedding that embeds Python +exe embedding : embedding.cpp /python//python ; + +# Declare a test of the extension module +testing.make-test run-pyd : extending test_extending.py : : test_ext ; + +# Declare a test of the embedding application +testing.run embedding embedding.cpp + : # any ordinary arguments + : script.py # any arguments that should be treated as relative paths + : # requirements + : test_embed ; # name of test + +# Create a "test" target that runs all the tests +alias test : test_ext test_embed ; + +# make sure the tests don't run by default +explicit test_ext test_embed test ; + diff --git a/src/boost/libs/python/example/quickstart/embedding.cpp b/src/boost/libs/python/example/quickstart/embedding.cpp new file mode 100644 index 000000000..65bcd16a0 --- /dev/null +++ b/src/boost/libs/python/example/quickstart/embedding.cpp @@ -0,0 +1,154 @@ +// Copyright Stefan Seefeld 2005. +// 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) + +#include <boost/python.hpp> + +#include <boost/detail/lightweight_test.hpp> +#include <iostream> + +namespace python = boost::python; + +// An abstract base class +class Base : public boost::noncopyable +{ +public: + virtual ~Base() {}; + virtual std::string hello() = 0; +}; + +// C++ derived class +class CppDerived : public Base +{ +public: + virtual ~CppDerived() {} + virtual std::string hello() { return "Hello from C++!";} +}; + +// Familiar Boost.Python wrapper class for Base +struct BaseWrap : Base, python::wrapper<Base> +{ + virtual std::string hello() + { +#if BOOST_WORKAROUND(BOOST_MSVC, <= 1300) + // workaround for VC++ 6.x or 7.0, see + // http://boost.org/libs/python/doc/tutorial/doc/html/python/exposing.html#python.class_virtual_functions + return python::call<std::string>(this->get_override("hello").ptr()); +#else + return this->get_override("hello")(); +#endif + } +}; + +// Pack the Base class wrapper into a module +BOOST_PYTHON_MODULE(embedded_hello) +{ + python::class_<BaseWrap, boost::noncopyable> base("Base"); +} + + +void exec_test() +{ + std::cout << "registering extension module embedded_hello..." << std::endl; + + // Register the module with the interpreter + if (PyImport_AppendInittab("embedded_hello", initembedded_hello) == -1) + throw std::runtime_error("Failed to add embedded_hello to the interpreter's " + "builtin modules"); + + std::cout << "defining Python class derived from Base..." << std::endl; + + // Retrieve the main module + python::object main = python::import("__main__"); + + // Retrieve the main module's namespace + python::object global(main.attr("__dict__")); + + // Define the derived class in Python. + python::object result = python::exec( + "from embedded_hello import * \n" + "class PythonDerived(Base): \n" + " def hello(self): \n" + " return 'Hello from Python!' \n", + global, global); + + python::object PythonDerived = global["PythonDerived"]; + + // Creating and using instances of the C++ class is as easy as always. + CppDerived cpp; + BOOST_TEST(cpp.hello() == "Hello from C++!"); + + std::cout << "testing derived class from C++..." << std::endl; + + // But now creating and using instances of the Python class is almost + // as easy! + python::object py_base = PythonDerived(); + Base& py = python::extract<Base&>(py_base) BOOST_EXTRACT_WORKAROUND; + + // Make sure the right 'hello' method is called. + BOOST_TEST(py.hello() == "Hello from Python!"); + + std::cout << "success!" << std::endl; +} + +void exec_file_test(std::string const &script) +{ + std::cout << "running file " << script << "..." << std::endl; + + // Run a python script in an empty environment. + python::dict global; + python::object result = python::exec_file(script.c_str(), global, global); + + // Extract an object the script stored in the global dictionary. + BOOST_TEST(python::extract<int>(global["number"]) == 42); + + std::cout << "success!" << std::endl; +} + +void exec_test_error() +{ + std::cout << "intentionally causing a python exception..." << std::endl; + + // Execute a statement that raises a python exception. + python::dict global; + python::object result = python::exec("print unknown \n", global, global); + + std::cout << "Oops! This statement should be skipped due to an exception" << std::endl; +} + +int main(int argc, char **argv) +{ + BOOST_TEST(argc == 2); + std::string script = argv[1]; + // Initialize the interpreter + Py_Initialize(); + + bool error_expected = false; + + if ( + python::handle_exception(exec_test) + || python::handle_exception(boost::bind(exec_file_test, script)) + || ( + (error_expected = true) + && python::handle_exception(exec_test_error) + ) + + ) + { + if (PyErr_Occurred()) + { + if (!error_expected) + BOOST_ERROR("Python Error detected"); + PyErr_Print(); + } + else + { + BOOST_ERROR("A C++ exception was thrown for which " + "there was no exception translator registered."); + } + } + + // Boost.Python doesn't support Py_Finalize yet, so don't call it! + return boost::report_errors(); +} diff --git a/src/boost/libs/python/example/quickstart/extending.cpp b/src/boost/libs/python/example/quickstart/extending.cpp new file mode 100644 index 000000000..a539d3b4b --- /dev/null +++ b/src/boost/libs/python/example/quickstart/extending.cpp @@ -0,0 +1,41 @@ +// Copyright Ralf W. Grosse-Kunstleve 2002-2004. 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) + +#include <boost/python/class.hpp> +#include <boost/python/module.hpp> +#include <boost/python/def.hpp> +#include <iostream> +#include <string> + +namespace { // Avoid cluttering the global namespace. + + // A friendly class. + class hello + { + public: + hello(const std::string& country) { this->country = country; } + std::string greet() const { return "Hello from " + country; } + private: + std::string country; + }; + + // A function taking a hello object as an argument. + std::string invite(const hello& w) { + return w.greet() + "! Please come soon!"; + } +} + +BOOST_PYTHON_MODULE(extending) +{ + using namespace boost::python; + class_<hello>("hello", init<std::string>()) + // Add a regular member function. + .def("greet", &hello::greet) + // Add invite() as a member of hello! + .def("invite", invite) + ; + + // Also add invite() as a regular function to the module. + def("invite", invite); +} diff --git a/src/boost/libs/python/example/quickstart/script.py b/src/boost/libs/python/example/quickstart/script.py new file mode 100644 index 000000000..c3e034ba8 --- /dev/null +++ b/src/boost/libs/python/example/quickstart/script.py @@ -0,0 +1,7 @@ +#! /usr/bin/env python +# Copyright Stefan Seefeld 2006. 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) + +print('Hello World !') +number = 42 diff --git a/src/boost/libs/python/example/quickstart/test_extending.py b/src/boost/libs/python/example/quickstart/test_extending.py new file mode 100644 index 000000000..938c7b904 --- /dev/null +++ b/src/boost/libs/python/example/quickstart/test_extending.py @@ -0,0 +1,37 @@ +#! /usr/bin/env python +# Copyright Ralf W. Grosse-Kunstleve 2006. 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) + +# Using the doctest module here to ensure that the results are as expected. +r'''>>> from extending import * + >>> hi = hello('California') + >>> hi.greet() + 'Hello from California' + >>> invite(hi) + 'Hello from California! Please come soon!' + >>> hi.invite() + 'Hello from California! Please come soon!' + + >>> class wordy(hello): + ... def greet(self): + ... return hello.greet(self) + ', where the weather is fine' + ... + >>> hi2 = wordy('Florida') + >>> hi2.greet() + 'Hello from Florida, where the weather is fine' + >>> invite(hi2) + 'Hello from Florida! Please come soon!' +''' + +def run(args = None): + if args is not None: + import sys + sys.argv = args + import doctest, test_extending + return doctest.testmod(test_extending, verbose=True) + +if __name__ == '__main__': + import sys + sys.exit(run()[0]) + diff --git a/src/boost/libs/python/example/tutorial/Jamfile b/src/boost/libs/python/example/tutorial/Jamfile new file mode 100644 index 000000000..a32272e7f --- /dev/null +++ b/src/boost/libs/python/example/tutorial/Jamfile @@ -0,0 +1,19 @@ +# Copyright Stefan Seefeld 2016. +# 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) + +import python ; + +project tutorial + : requirements + <location>. + ; + +python-extension hello_ext : hello.cpp ; + +run-test hello : hello_ext hello.py ; + +alias test : hello ; +explicit test ; + diff --git a/src/boost/libs/python/example/tutorial/hello.cpp b/src/boost/libs/python/example/tutorial/hello.cpp new file mode 100644 index 000000000..d5114312b --- /dev/null +++ b/src/boost/libs/python/example/tutorial/hello.cpp @@ -0,0 +1,20 @@ +// Copyright Joel de Guzman 2002-2004. 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) +// Hello World Example from the tutorial +// [Joel de Guzman 10/9/2002] + +#include <boost/python/module.hpp> +#include <boost/python/def.hpp> + +char const* greet() +{ + return "hello, world"; +} + +BOOST_PYTHON_MODULE(hello_ext) +{ + using namespace boost::python; + def("greet", greet); +} + diff --git a/src/boost/libs/python/example/tutorial/hello.py b/src/boost/libs/python/example/tutorial/hello.py new file mode 100755 index 000000000..31f75565d --- /dev/null +++ b/src/boost/libs/python/example/tutorial/hello.py @@ -0,0 +1,8 @@ +#! /usr/bin/env python +# Copyright Joel de Guzman 2002-2007. 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) +# Hello World Example from the tutorial + +import hello_ext +print(hello_ext.greet()) |