[General] SU(2) equation set
Dr Nicholas J Bailey
nicholas.bailey at glasgow.ac.uk
Fri Nov 13 03:21:32 PST 2015
Do you want it to be /fast/?
Python is fast (and fun!) to write but slow to run. Although actually, not
that slow. Artifastring[1], a modal physical model written by my ex-postgrad
in C++ as the engine behind Vivi[2], the virtual violinist, actually ran faster
when bound to Python than when linked to a larger C++ program! I didn't
look into why. Curious.
Anyway, if you want fast, I'd write in C++ with as much built-in operator
overloading as you can so that you can read your own code. You can test
that to hell, then pull it in to Python using swig[3] or sip[4].
Alternatively, I suppose one could think of starting with Python and
extending the functionality of a numeric module such as numpy[5].
The other advantage of having at least the possibility of running C++
instead of Python is that Python doesn't support threads (because of the
Global Intepreter Lock[6] problem) and if you want to do real heavy duty
number crunching on multiple cores, you'd best use C++ with boost[7] or
something like that. Boost is proposed to be included in the standard
library in C++17 anyway.
Nick/.
On Thursday 12 November 2015 13:37:03 John Williamson wrote:
Firstly need to implement a system with primitive operations which parallel
the workings of the space-time algebra. Multiplications, divisions and
differentiations in particular. It would be nice if such a framework existed
already, but I do not think so. Stephen has written a suite in PYTHON to
deal with the multiplications, which may be a start. Not sure what is best
here: C++?, Python?, Something else?
--------
[1] http://percival-music.ca/artifastring/
[2] http://percival-music.ca/vivi.html
[3] http://www.swig.org/
[4] https://riverbankcomputing.com/software/sip/intro
[5] http://www.numpy.org/
[6] https://www.jeffknupp.com/blog/2012/03/31/pythons-hardest-problem/
[7] http://www.boost.org/
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