// // Copyright 2017-2018 Ettus Research, a National Instruments Company // // SPDX-License-Identifier: GPL-3.0-or-later // #ifndef INCLUDED_UHD_STREAM_PYTHON_HPP #define INCLUDED_UHD_STREAM_PYTHON_HPP #include "utils/gil_release_python.hpp" #include #include #include static size_t wrap_recv(uhd::rx_streamer *rx_stream, bp::object &np_array, bp::object &metadata, const double timeout = 0.1) { // Release the GIL scoped_gil_release gil_release; // Extract the metadata bp::extract get_metadata(metadata); if (not get_metadata.check()) { return 0; } // Get a numpy array object from given python object // No sanity checking possible! PyObject* array_obj = PyArray_FROM_OF(np_array.ptr(), NPY_ARRAY_CARRAY); PyArrayObject* array_type_obj = reinterpret_cast(array_obj); // Get dimensions of the numpy array const size_t dims = PyArray_NDIM(array_type_obj); const npy_intp* shape = PyArray_SHAPE(array_type_obj); // How many bytes to jump to get to the next element of this stride // (next row) const npy_intp* strides = PyArray_STRIDES(array_type_obj); const size_t channels = rx_stream->get_num_channels(); // Check if numpy array sizes are okay if (((channels > 1) && (dims != 2)) or ((size_t) shape[0] < channels)) { // Manually decrement the ref count Py_DECREF(array_obj); // If we don't have a 2D NumPy array, assume we have a 1D array size_t input_channels = (dims != 2) ? 1 : shape[0]; throw uhd::runtime_error(str(boost::format( "Number of RX channels (%d) does not match the dimensions of the data array (%d)") % channels % input_channels)); } // Get a pointer to the storage std::vector channel_storage; char* data = PyArray_BYTES(array_type_obj); for (size_t i = 0; i < channels; ++i) { channel_storage.push_back((void*)(data + i * strides[0])); } // Get data buffer and size of the array size_t nsamps_per_buff; if (dims > 1) { nsamps_per_buff = (size_t) shape[1]; } else { nsamps_per_buff = PyArray_SIZE(array_type_obj); } // Call the real recv() const size_t result = rx_stream->recv( channel_storage, nsamps_per_buff, get_metadata(), timeout ); // Manually decrement the ref count Py_DECREF(array_obj); return result; } BOOST_PYTHON_FUNCTION_OVERLOADS(overload_wrap_recv, wrap_recv, 3, 4); static size_t wrap_send(uhd::tx_streamer *tx_stream, bp::object &np_array, bp::object &metadata, const double timeout = 0.1) { // Release the GIL scoped_gil_release gil_release; // Extract the metadata bp::extract get_metadata(metadata); // TODO: throw an error here? if (not get_metadata.check()) { return 0; } // Get a numpy array object from given python object // No sanity checking possible! // Note: this increases the ref count, which we'll need to manually decrease at the end PyObject* array_obj = PyArray_FROM_OF(np_array.ptr(),NPY_ARRAY_CARRAY); PyArrayObject* array_type_obj = reinterpret_cast(array_obj); // Get dimensions of the numpy array const size_t dims = PyArray_NDIM(array_type_obj); const npy_intp* shape = PyArray_SHAPE(array_type_obj); // How many bytes to jump to get to the next element of the stride // (next row) const npy_intp* strides = PyArray_STRIDES(array_type_obj); const size_t channels = tx_stream->get_num_channels(); // Check if numpy array sizes are ok if (((channels > 1) && (dims != 2)) or ((size_t) shape[0] < channels)) { // Manually decrement the ref count Py_DECREF(array_obj); // If we don't have a 2D NumPy array, assume we have a 1D array size_t input_channels = (dims != 2) ? 1 : shape[0]; throw uhd::runtime_error(str(boost::format( "Number of TX channels (%d) does not match the dimensions of the data array (%d)") % channels % input_channels)); } // Get a pointer to the storage std::vector channel_storage; char* data = PyArray_BYTES(array_type_obj); for (size_t i = 0; i < channels; ++i) { channel_storage.push_back((void*)(data + i * strides[0])); } // Get data buffer and size of the array size_t nsamps_per_buff = (dims > 1) ? (size_t) shape[1] : PyArray_SIZE(array_type_obj); // Call the real recv() const size_t result = tx_stream->send( channel_storage, nsamps_per_buff, get_metadata(), timeout ); // Manually decrement the ref count Py_DECREF(array_obj); return result; } BOOST_PYTHON_FUNCTION_OVERLOADS(overload_wrap_send, wrap_send, 3, 4); static bool wrap_recv_async_msg(uhd::tx_streamer *tx_stream, uhd::async_metadata_t &async_metadata, double timeout = 0.1) { // Release the GIL scoped_gil_release gil_release; return tx_stream->recv_async_msg(async_metadata, timeout); } BOOST_PYTHON_FUNCTION_OVERLOADS(overload_wrap_recv_async_msg, wrap_recv_async_msg, 2, 3); void export_stream() { using stream_args_t = uhd::stream_args_t; using rx_streamer = uhd::rx_streamer; using tx_streamer = uhd::tx_streamer; bp::class_ ("stream_args", bp::init()) // Properties .def_readwrite("cpu_format", &stream_args_t::cpu_format) .def_readwrite("otw_format", &stream_args_t::otw_format) .def_readwrite("args" , &stream_args_t::args ) .def_readwrite("channels" , &stream_args_t::channels ) ; bp::class_< rx_streamer, boost::shared_ptr, boost::noncopyable>("rx_streamer", "See: uhd::rx_streamer", bp::no_init) // Methods .def("recv" , &wrap_recv, overload_wrap_recv() ) .def("get_num_channels" , &uhd::rx_streamer::get_num_channels ) .def("get_max_num_samps", &uhd::rx_streamer::get_max_num_samps) .def("issue_stream_cmd" , &uhd::rx_streamer::issue_stream_cmd ) ; bp::class_< tx_streamer, boost::shared_ptr, boost::noncopyable>("tx_streamer", "See: uhd::tx_streamer", bp::no_init) // Methods .def("send" , &wrap_send, overload_wrap_send()) .def("get_num_channels" , &tx_streamer::get_num_channels ) .def("get_max_num_samps", &tx_streamer::get_max_num_samps ) .def("recv_async_msg" , &wrap_recv_async_msg, overload_wrap_recv_async_msg() ) ; } #endif /* INCLUDED_UHD_STREAM_PYTHON_HPP */