在Python中调用C++的Eigen库函数

Question

我在用C++做一些计算，使用了Eigen库，函数是这样的：

MatrixXd Cov(MatrixXd Data)
{

  VectorXd meanVector;
  ...
  return Covariance;
}

..在包装的Python函数里：

static PyObject *Wrap_Cov(PyObject *self,PyObject *args)
{   
      Pyobject *Objectdata;

      if(!PyArg_ParseTuple(args,"O", &ObjectData))
        return NULL;

      Cov(ObjectData);

      return Py_BuildValue("O",&covariance_answer);

  }

显然，Python不知道我定义的“对象”，它无法把“MatrixXd”翻译成“对象”，我觉得这是一种“数组”，而不是“对象”。

我该怎么做才能不使用boost呢？

Answer 1

如果你要让不同编程语言写的数字模块互相交流，保持数据的简单扁平化是个好主意。

在libeigen库中，最简单的实数矩阵表示方式是一个C语言的实数数组（可以是float或double类型）。

下面是一个C++的示例：

---

#include <stdexcept>
#include <iostream>
#include <string>
#include <sstream>
#include <python2.7/Python.h>
#include <eigen3/Eigen/Dense>


using std::size_t;
typedef double real_t;

typedef Eigen::Matrix<real_t, Eigen::Dynamic, Eigen::Dynamic> 
        Matrix;

static PyObject* p_eigen_python_error(NULL);

static PyObject *
randomDxDMatrix(PyObject *self, PyObject *args) {
    PyObject* p(NULL);
    PyObject* item(NULL);    

    try{
        size_t d(0);

        PyArg_ParseTuple(args, "L", &d);
        Matrix M = Matrix::Random(d,d);

        size_t length = d * d;

        p = PyList_New(length);

        if (p == NULL) {
            std::stringstream msg;
            msg << "Could not allocate a Pylist of "
                << d << "x" << d << " = " << d*d 
                << " size for the return Object";
            throw std::runtime_error(msg.str().c_str());
        } else {
            for (size_t i = 0; i < length; ++i) {
                item = PyFloat_FromDouble(M.data()[i]);
                PyList_SET_ITEM(p, i, item);
            }   
        }

    } catch (const std::exception& e) {
        delete p; p = NULL;
        delete item; item = NULL;

        std::string msg = ("randomDxDMatrix failed: ");
        msg += e.what();
        PyErr_SetString(p_eigen_python_error, msg.c_str());
    }

    return p;
}

static PyMethodDef EigenMethods[] = {
    {"randomDxDMatrix",  randomDxDMatrix, METH_VARARGS, 
    "Gets a random DxD matrix column-major as a list of (python) floats"},
    {NULL, NULL, 0, NULL}        /* Sentinel */
};

PyMODINIT_FUNC
initeigen_python(void) {

    PyObject* p;

    p = Py_InitModule("eigen_python", EigenMethods);
    if (p == NULL)
        return;

    p_eigen_python_error = PyErr_NewException(
                                const_cast<char*>("eigen_python.error"), 
                                NULL, NULL
                            );
    Py_INCREF(p_eigen_python_error);
    PyModule_AddObject(p, "error", p_eigen_python_error);
}

---

接下来是setup_eigen_python.py：

---

from distutils.core import setup, Extension

cpp_args = ['-Wall', '-pedantic']
cxx_args = ['-std=c++11'].extend(cpp_args)

module_eigen_python = Extension('eigen_python',
                          define_macros = [('MAJOR_VERSION', '0'),
                                            ('MINOR_VERSION', '1')],
                          include_dirs = ['/usr/local/include'],
                          sources = ['eigen_python.cpp'],
                          extra_compile_args = cpp_args
#                          sources = ['eigen_python.cxx'],
#                          extra_compile_args = cxx_args
                      )

setup (name = 'eigen_python',
       version = '0.1',
       description = 'This is just a demo',
       author = 'Solkar',
       url = 'http://stackoverflow.com/questions' 
         + '/15573557/call-c-using-eigen-library-function-in-python',
       long_description = 'just a toy',
       ext_modules = [module_eigen_python])

---

可以像这样使用：

python2.7 setup_eigen_python.py install --user

还有一个小测试程序：

---

import eigen_python as ep
import numpy as np

DIM = 4

M = np.array(ep.randomDxDMatrix(DIM), order="F")
M.shape= DIM,DIM

print(M) 

---

¹特别是因为如果不使用boost库的话，我更希望能用C++ 2011标准的一些特性，比如auto和std::unique_ptr，但我不确定QO是否支持这些特性。