[英]How to convert NumPy ndarray to C++ vector with Boost.Python and back?
I am working on a project where I need to convert an ndarray
in Python to a vector
in C++ and then return a processed vector
from C++ back to Python in an ndarray
. 我正在开发一个项目,我需要将Python中的
ndarray
转换为C ++中的vector
,然后在ndarray
处理后的vector
从C ++返回到Python。 I am using Boost.Python with its NumPy extension . 我正在使用Boost.Python及其NumPy扩展 。 My problem specifically lies in converting from
ndarray
to vector
, as I am using an extended class of vector: 我的问题特别在于从
ndarray
转换为vector
,因为我正在使用扩展的vector类:
class Vector
{
public:
Vector();
Vector(double x, double y, double z);
/* ... */
double GetLength(); // Return this objects length.
/* ... */
double x, y, z;
};
The ndarray
I receive is n
x 2
and filled with x,y data. 我收到的
ndarray
是n
x 2
并填充x,y数据。 Then I process the data in C++ with a function, which returns an std::vector<Vector>
. 然后我用一个函数处理C ++中的数据,该函数返回一个
std::vector<Vector>
。 This vector then should be returned to Python as an ndarray
, BUT only with the x and y values. 然后应该将此向量作为
ndarray
返回到Python,但仅限于x和y值。
I have written the following piece of code, with inspiration from " how to return numpy.array from boost::python? " and the gaussian.cpp from the Boost NumPy examples. 我编写了下面这段代码,灵感来自“ 如何从boost :: python返回numpy.array? ”和Boost NumPy示例中的gaussian.cpp 。
#include <vector>
#include "Vector.h"
#include "ClothoidSpline.h"
#include <boost/python/numpy.hpp>
namespace py = boost::python;
namespace np = boost::python::numpy;
std::vector<Vector> getFineSamples(std::vector<Vector> data)
{
/* ... */
}
np::ndarray wrapper(np::ndarray const & input)
{
std::vector<Vector> data;
/* Python ndarray --> C++ Vector */
Py_intptr_t const* size = input.get_shape();
Py_intptr_t const* strides = input.get_strides();
double x;
double y;
double z = 0.0;
for (int i = 0; i < size[0]; i++)
{
x = *reinterpret_cast<double const *>(input.get_data() + i * strides[0] + 0 * strides[1]);
y = *reinterpret_cast<double const *>(input.get_data() + i * strides[0] + 1 * strides[1]);
data.push_back(Vector::Vector(x,y,z));
}
/* Run Algorithm */
std::vector<Vector> v = getFineSamples(data);
/* C++ Vector --> Python ndarray */
Py_intptr_t shape[1] = { v.size() };
np::ndarray result = np::zeros(2, shape, np::dtype::get_builtin<std::vector<Vector>>());
std::copy(v.begin(), v.end(), reinterpret_cast<double*>(result.get_data()));
return result;
}
EDIT: I am aware that this is a (possibly) failed attempt, and I am more interested in a better method to solve this problem, than edits to my code. 编辑:我知道这是一个(可能)失败的尝试,我更感兴趣的是一个更好的方法来解决这个问题,而不是编辑我的代码。
So to sum up : 总结一下 :
boost::python::numpy::ndarray
to a std::vector<Vector>
? boost::python::numpy::ndarray
转换为std::vector<Vector>
? std::vector<Vector>
to an boost::python::numpy::ndarray
, returning only x and y? std::vector<Vector>
转换为boost::python::numpy::ndarray
,仅返回x和y? As a last note : I know almost nothing about Python, and I am beginner/moderate in C++. 作为最后一点 :我对Python几乎一无所知,而且我在C ++中是初学/中等。
I will consider the title of your question to give a more generalized answer to whoever finds this post. 我将考虑你的问题的标题,以便对发现这篇文章的人给出更广泛的答案。
You have a boost::python::numpy::ndarray
called input
that contains doubles
and you want to convert it a std::vector<double>
called v
: 你有一个
boost::python::numpy::ndarray
叫做input
,它包含doubles
,你想把它转换成一个名为v
的std::vector<double>
:
int input_size = input.shape(0);
double* input_ptr = reinterpret_cast<double*>(input.get_data());
std::vector<double> v(input_size);
for (int i = 0; i < input_size; ++i)
v[i] = *(input_ptr + i);
Now, you have a std::vector<double>
called v
and you want to convert it back to boost::python::numpy::ndarray
of doubles
called output
: 现在,你有一个名为
v
的std::vector<double>
,你想将它转换回boost::python::numpy::ndarray
of doubles
名为output
:
int v_size = v.size();
py::tuple shape = py::make_tuple(v_size);
py::tuple stride = py::make_tuple(sizeof(double));
np::dtype dt = np::dtype::get_builtin<double>();
np::ndarray output = np::from_data(&v[0], dt, shape, stride, py::object());
Supposing you are wrapping this function, don't forget that you need to create a new reference to this array before returning it to python: 假设您正在包装此函数,请不要忘记在将其返回到python之前需要创建对此数组的新引用:
np::ndarray output_array = output.copy();
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