Francesco Biscani added the comment:
Hi Mark,
the original code is C++, and the inf + nanj result can be reproduced by the
following snippet:
"""
#include <complex>
#include <iostream>
int main(int argc, char * argv[]) {
std::cout << std::complex<double>(3,0) / 0. << '\n';
return 0;
}
"""
Here is the C99 version:
"""
#include <complex.h>
#include <math.h>
#include <stdio.h>
int main(int argc, char * argv[]) {
double complex a = 3.0 + 0.0*I;
printf("%f + i%f\n", creal(a/0.), cimag(a/0.));
return 0;
}
"""
This is on Linux x86_64 with GCC 4.9. Clang gives the same result. Adding the
"-ffast-math" compilation flag changes the result for the C version but
apparently not for the C++ one.
The original code came from an implementation of a special function f(z) which
has a pole near the origin. When computing f(0), the C++ code returns
inf+nan*j, which is fine (in the sense that it is a complex infinity of some
kind). I then need to use this result in a larger piece of code which at one
point needs to compute 1/f(0), with the expected result being 0 mathematically.
This works if I implement the calculation all within C/C++, but if I switch to
Python when computing 1/f(0) I get nan + nan*j as a result.
Of course I could do all sorts of stuff to improve this specific calculation
and avoid the problems (possibly improving the numerical behaviour near the
pole via a Taylor expansion, etc. etc. etc.).
Beware that implementing C99 behaviour will result in a noticeable overhead for
complex operations. In compiled C/C++ code one usually has the option to switch
on/off the -ffast-math flag to improve performance at the expense of
standard-conformance, but I imagine this is not feasible in Python.
----------
_______________________________________
Python tracker <rep...@bugs.python.org>
<http://bugs.python.org/issue25453>
_______________________________________
_______________________________________________
Python-bugs-list mailing list
Unsubscribe:
https://mail.python.org/mailman/options/python-bugs-list/archive%40mail-archive.com
