{"id":1221,"date":"2009-05-13T19:29:05","date_gmt":"2009-05-13T18:29:05","guid":{"rendered":"http:\/\/www.walkingrandomly.com\/?p=1221"},"modified":"2011-08-22T15:48:29","modified_gmt":"2011-08-22T14:48:29","slug":"pynag-a-python-package-for-interfacing-with-the-nag-c-library","status":"publish","type":"post","link":"https:\/\/walkingrandomly.com\/?p=1221","title":{"rendered":"PyNAG – A Python package for interfacing with the NAG C Library"},"content":{"rendered":"

Update (5th November 2009): <\/strong>PyNAG has been updated several times since this post was written. The latest version will always be available from https:\/\/www.walkingrandomly.com\/?page_id=1662<\/a><\/p>\n

This is part 6 of a series of articles devoted to demonstrating how to call the Numerical Algorithms Group (NAG) C library<\/a> from Python.\u00a0 Click here for the index<\/a> to this series.<\/p>\n

Over the last few articles I have demonstrated that it is relatively straightforward to interface Python to the NAG C library.\u00a0 The resulting code, however, looks a bit ugly and overly verbose since you have to include a lot of boiler plate code<\/a> such as telling Python where the C library is, defining pythonic versions of C structures, defining various constants and so on.\u00a0 I found myself doing a lot of copying and pasting in the early stages of working all this stuff out.<\/p>\n

Just recently I made a small step forward by moving all of this boilerplate into a Python package which I have called PyNAG.\u00a0\u00a0 It’s a relatively simple package since all it does is define Pythonic versions of various C-structures, link to the NAG library, perform restypes on the function names, define a few often used NAG variables such as NAGERR_DEFAULT and so on.<\/p>\n

The practical upshot is that you need to write a lot less code when interfacing with the C library.\u00a0 For example here is the Python code to minimise a 2D function via the simplex method using e04ccc<\/a> of the NAG library.<\/p>\n

#!\/usr\/bin\/env python\r\n#Mike Croucher - April 2008\r\n#A minimisation problem solved using e04ccc\r\nfrom PyNAG import e04ccc,NAGERR_DEFAULT,E04_DEFAULT,Nag_Comm\r\nfrom ctypes import *\r\nfrom math import *\r\n\r\n#Create the communication structure\r\ncomm = Nag_Comm() \r\n\r\n#set up the objective function\r\ndef py_obj_func(n,xc,objf,comm):\r\n\tobjf[0] = exp(xc[0]) * (xc[0] * 4.0 * ( xc[0]+xc[1] ) + xc[1] * 2.0 * (xc[1] +1.0) +1.0 )\r\nC_FUNC = CFUNCTYPE(None,c_int,POINTER(c_double),POINTER(c_double),POINTER(Nag_Comm) )\r\nc_obj_func = C_FUNC(py_obj_func)\r\n\r\n#Set up the starting point\r\nn=2\r\nx=(c_double*2)()\r\nx[0]=c_double(0.4)\r\nx[1]=c_double(-0.8)\r\n\r\n#Set up other variables\r\nobjf = c_double()\r\n\r\ne04ccc(n, c_obj_func, byref(x), byref(objf),E04_DEFAULT,comm,NAGERR_DEFAULT)<\/pre>\n
It’s still not as pretty as it would it if it were written in pure python but it’s a (small) step in the right direction I think.<\/p>\n
The good<\/h3>\n