Pybind Numpy访问2D / ND阵列

[英]Pybind Numpy access 2D / ND arrays

New to pybind - read the documentation but I do not grasp how to apply it to 2D arrays.

pybind新手 - 阅读文档,但我不知道如何将其应用于2D数组。

I have two arrays storing 3d coordinates shape = (10,3)


a = np.zeros(shape=(10,3))
b = np.ones(shape=(10,3)) * 3
c = a + b

Now, using pybind, how do I perform this operation in C++ working on the numpy arrays?

现在,使用pybind,如何在numpy数组上使用C ++执行此操作?

In some documentations I read to access the elements with the [] operator, in others with (). How do assign the 3D vector? How would I get the pointer to the array element to use strides for assignment - or does it have an operator?

在一些文档中,我读取使用[]运算符访问元素,而在其他文档中使用()。如何分配3D矢量?我如何获得指向数组元素的指针以使用步幅进行赋值 - 或者它是否有运算符?

2 个解决方案



PyBind is awesome, shout out to the authors/maintainers! You have an almost working example here.


Adapted to your problem it would give something like (edited answer after El Dude's comment):

适应你的问题它会给出类似的东西(在El Dude评论之后编辑的答案):

#include <iostream>
#include <pybind11/pybind11.h>
#include <pybind11/numpy.h>

namespace py = pybind11;

py::array_t<double> add_arrays(py::array_t<double> input1, py::array_t<double> input2) {
auto buf1 = input1.request(), buf2 = input2.request();

if (buf1.size != buf2.size)
throw std::runtime_error("Input shapes must match");

/*  allocate the buffer */
py::array_t<double> result = py::array_t<double>(buf1.size);

auto buf3 = result.request();

double *ptr1 = (double *) buf1.ptr,
        *ptr2 = (double *) buf2.ptr,
        *ptr3 = (double *) buf3.ptr;
int X = buf1.shape[0];
int Y = buf1.shape[1];

for (size_t idx = 0; idx < X; idx++)
    for (size_t idy = 0; idy < Y; idy++)
        ptr3[idx*Y + idy] = ptr1[idx*Y+ idy] + ptr2[idx*Y+ idy];

// reshape array to match input shape

return result;

PYBIND11_MODULE(example, m) {
        m.doc() = "Add two vectors using pybind11"; // optional module docstring

        m.def("add_arrays", &add_arrays, "Add two NumPy arrays");

That I built on linux with python2.7 and gcc v5.4 using (I had to use a slightly different command than provided in the doc, because Python.h wasn't found, hence I added the link to python 2.7)

我使用python2.7和gcc v5.4在linux上构建(我必须使用与doc中提供的稍微不同的命令,因为找不到Python.h,因此我添加了到python 2.7的链接)

c++ -O3 -Wall -shared -std=c++11 -fPIC -I/usr/include/python2.7 -lpython2.7 `python -m pybind11 --includes` example.cpp -o example`python-config --extension-suffix

And you'd call it from python with


import numpy as np
import example # [bad] name I chose for my compiled module

a = np.zeros((10,3))
b = np.ones((10,3)) * 3 
c = example.add_arrays(a, b)

print c

Hope it helps.




The trick is to use the buffer class. It's well hidden / convoluted into the documentation and examples, but it's mentioned (@Christian 's post).


Buffers contain a pointer to the data as well as strides and others array parameters. Essentially the numpy header accessed through request method. Easy to use from there on, but finding it is bit of a pain since the example uses beautiful C11 auto type to explain this usage.





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