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@lamyj
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I'm trying to wrap a custom type using pybind11 and xtensor-python. Although I can create a numpy array of my wrapped type from Python, I cannot pass this numpy array to C++ functions or pass xt::xarray to Python.
The C++ part is
#include <pybind11/numpy.h> #include <pybind11/pybind11.h> #include <xtensor/xarray.hpp> #define FORCE_IMPORT_ARRAY #include <xtensor-python/pyarray.hpp> struct Quantity { double q; Quantity(double q=0) : q(q) { } }; PYBIND11_MODULE(test_array, test_array) { xt::import_numpy(); pybind11::class_<Quantity>(test_array, "Quantity") .def(pybind11::init<double>()) .def_readwrite("q", &Quantity::q); test_array.def("create", []() { return xt::xarray<Quantity>{1.1, 2.2}; }); test_array.def( "consume", [](xt::xarray<Quantity> const & array) { for(auto && item: array) { std::cout << item.q << "\n"; } }); }
And the Python code
import numpy import test_array q1 = test_array.Quantity(42) q2 = test_array.Quantity(3.14) a = numpy.array([q1, q2]) print([x.q for x in a]) try: test_array.create() except Exception as e: print(e) try: test_array.consume(a) except Exception as e: print(e)
Both try/except blocks in Python yield a RuntimeError saying "NumPy type info missing for 8Quantity"
Is this use case supported by xtensor-python? If so, what am I missing? If not, what alternative would you suggest?
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