Question

I want to write a Boost-Python program to take a symbolic python function from user and evaluate its derivative in my program.

For example the User provide a python file (Function.py) which defines a function like
F = sin(x)*cos(x).

Then I want to have access to F'(x) (derivative of F(x)) using symbolic differentiation ability of Sympy. I don’t want to use numerical differentiation.

Is there a way to make such a function F'(x) accessible in the C++ using Boost-Python.

Answer 1

I am not a SymPy expert but maybe this can help you:

You can define a Python method like:

def f(x):
  return sin(x)*cos(x)

You can create an evaluable function f1 as the derivative of f using:

from sympy import *
x = symbols('x')
f1 = lambdify(x, diff(f(x)))

This function f1 can be called from C++ using boost::python. You may create an object to function f1, call the function using the () operator and convert the result to double using extract<>.

Here is an example:

  namespace py = boost::python;

  Py_Initialize();

  py::object main_module = py::import("__main__");
  py::object main_dict   = main_module.attr("__dict__");

  py::exec(
    "def f(x):\n"
    "  return  sin(x)*cos(x)\n",
    main_dict
  );

  py::exec(
    "from sympy import *\n"
    "x = symbols('x')\n"
    "f1 = lambdify(x, diff(f(x)))\n",
     main_dict
  );

  py::object f1 = main_dict["f1"];
  std::cout << py::extract<double>(f1(0.0)) << std::endl;
  std::cout << py::extract<double>(f1(1.0)) << std::endl;

  return 0;