call C++ using Eigen Library function in python

Question

I'm doing some calculations in C++ with help of Eigen Library, the function is like this:

MatrixXd Cov(MatrixXd Data)
{

  VectorXd meanVector;
  ...
  return Covariance;
}

..in the wrap python function:

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);

  }

Obviously, Python doesn't know the ''object'' I defined, it can't translate ''MatrixXd'' to ''Object'', I think it's some kinds of ''array'', not ''object''

How can I do this without using boost?

Answer 1

If interfacing numerical modules written in different languages, it's a good practice to keep the data exchanged as flat as possible.

The flattest representation of a libeigen real Matrix is a c array of real type (float or double)

Here's a C++¹ sample

---

#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);
}

---

Here's 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])

---

to be used like

python2.7 setup_eigen_python.py install --user

and here's a little test driver

---

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) 

---

¹Especially, but by far not restricted to, because having to get along without boost, would have preferred using features of the C++ 2011 standard like auto and std::unique_ptr but I did not know if the QO has sufficient support for this.