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Support for custom types? #285
Description
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?
Activity
tdegeus commentedon Mar 10, 2023
I don't think that this is supported. You are welcome to figure out if this could be done ;) I have no use case for this, so I won't be able to push this