1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
|
#ifndef PYBIND11_HPP
#define PYBIND11_HPP
// We must load pybind11 consistently through this header to ensure that our type_caster
// specialization is used in every translation unit. Otherwise we get ODR violations.
#include <pybind11/numpy.h>
#include <pybind11/operators.h>
#include <pybind11/pybind11.h>
#include <pybind11/pytypes.h>
#include <pybind11/stl.h>
#include <vector>
namespace pybind11 {
namespace detail {
// This specialization for vector<double> acts as an override from the more generic
// template in pybind11/stl.h. We use it to cast the C++ vector into a numpy array
// instead of a Python list.
template <>
struct type_caster<std::vector<double>> {
using vec_t = std::vector<double>;
using value_conv = make_caster<double>;
using size_conv = make_caster<std::size_t>;
bool load(handle src, bool convert) {
value.clear();
// TODO optimize for python objects that support buffer protocol
if (isinstance<iterable>(src)) {
auto seq = reinterpret_borrow<iterable>(src);
if (hasattr(seq, "__len__")) value.reserve(static_cast<std::size_t>(len(seq)));
for (auto it : seq) {
value_conv conv;
if (!conv.load(it, convert)) return false;
value.push_back(cast_op<double&&>(std::move(conv)));
}
return true;
}
return false;
}
template <typename T>
static handle cast(T&& src, return_value_policy, handle) {
array_t<double> arr(static_cast<ssize_t>(src.size()));
std::copy(src.begin(), src.end(), arr.mutable_data());
return arr.release();
}
PYBIND11_TYPE_CASTER(vec_t, _("List[") + value_conv::name + _("]"));
};
} // namespace detail
} // namespace pybind11
#endif // PYBIND11_HPP
|