Dear all, My advice would be to boostify the code, write the documentation including
as much performances tests as you consider could help to consider this library a should have.
I have modified the code to match the quality criterions, added a comprehensive (doxygen) documentation and modified all the directories to mimic the main trunk. You can also find in the sources a test file which tests all operators and functions for accuracy. It uses boost::test and shows that all functions are accurate within 10e-12 (four doubles) when compared to the same computation done with std::complex<>. When the result is not completely identical, the imaginary<> class version is always closer to the analytical result than the std::complex<> one. The only exception is the tanh() function which differs from the std::complex<> one by 1e-9 for numbers close to 0. I have also added another example (computing the Julia fractal set in mathematics) showing a ~5% gain in performance. The speed-up in this case is much less impressive but the algorithm does not only use imaginary numbers. I could also provide an example which brutally compares the speed of some functions and operators but I prefer presenting real applications rather than artificially improved codes. Is there something that could obviously be improved ? Is there some interest in pushing this further ? Regards, Matthieu Schaller